Creating Apps & Python

Parametric design

Due to this wide range of options, setting all parameters using PLAXIS’ Graphical User Interface (GUI) can be a cumbersome task. Especially if you do not need most parameters for your specific purpose. Also, if you need to set up a model in the same fashion multiple times, this must be done manually, even though a computer could easily do this for you.

This is where VIKTOR comes into play. In this article, we will explain how you can achieve the best results with PLAXIS, while discussing the following:

- PLAXIS in a web app
- Automating in- and output
- Centralizing data
- Easy material parametrization
- Open-source Python code for a PLAXIS web app


Blog_sample_app_PLAXIS

Automate PLAXIS in- and output, centralize data, and easily parametrize materials with this open-source Python code by VIKTOR. 

PLAXIS in a web-based application

VIKTOR offers the possibility to integrate PLAXIS’ Python API with a web-based application that engineers can easily use to:

- Parametrically generate, update, and edit their PLAXIS models, 
- export results from PLAXIS easily to the Cloud, 
- and integrate PLAXIS models with other third-party software, such as D-Series.

Here, you can see PLAXIS integrated with such a web app on the VIKTOR platform:

<div style="padding:56.25% 0 0 0;position:relative;"><iframe src="https://player.vimeo.com/video/715587375?h=9017847dd2&amp;badge=0&amp;autopause=0&amp;player_id=0&amp;app_id=58479" frameborder="0" allow="autoplay; fullscreen; picture-in-picture" allowfullscreen style="position:absolute;top:0;left:0;width:100%;height:100%;" title="Sample app PLAXIS"></iframe></div><script src="https://player.vimeo.com/api/player.js"></script>

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In this video you can see how the materials that are used for a project are defined, as well as the layout of the soil, embankment and drains. Then, a 2D model of the embankment is generated and automatically analysed with PLAXIS.


PLAXIS in a web app

As mentioned, setting up the appropriate geometry and models of a PLAXIS analysis can be a lengthy process, especially as projects continue to grow. Additionally, modifying your calculation input must be done using the wide range of options that PLAXIS’ GUI offers. By automating the generation of models and integrating the analysis and visualization of results within a single application, a significant increase in efficiency can be achieved. For example, by reducing the number of options to a few necessary input parameters that can easily be re-used in other projects as well. 

In this video, you can see how a 2D embankment is analysed in a VIKTOR web app. In the app, you can adjust the necessary input parameters for the embankment (width, height, material), soil, and drains. By simply clicking the ‘update’ button in the down-right corner of the application, the results of the analysis are calculated in PLAXIS and returned to the VIKTOR app. From here on, you can see if any adjustments are needed and if so, run the analysis again at the push of a button. 

<div style="padding:56.25% 0 0 0;position:relative;"><iframe src="https://player.vimeo.com/video/715587462?h=878e4de30f&amp;badge=0&amp;autopause=0&amp;player_id=0&amp;app_id=58479" frameborder="0" allow="autoplay; fullscreen; picture-in-picture" allowfullscreen style="position:absolute;top:0;left:0;width:100%;height:100%;" title="Sample app PLAXIS - automation"></iframe></div><script src="https://player.vimeo.com/api/player.js"></script>
</br> 

The video also shows all the calculations that are happening in the background while the application is running the analysis. As you may know, the output files can have a substantial size. Therefore, only the relevant information is being taken out and sent back to the VIKTOR app. A clever tip is to store the output files on the server so they can always be inspected by a geotechnical engineer later. 


Automating in- and output

The advantage of integrating PLAXIS’ Python API with a VIKTOR web app does not end at the ability to automate processes and visualize results. Often, in a team of people working with PLAXIS, everyone has their own Excel sheet to define materials. Because these sheets are isolated, this can get confusing in case someone changes something in their Excel sheet and someone else does not in theirs. With a VIKTOR web app, everyone in a company can access a central database to define materials.

In the video, you can see how in the left menu underneath ‘materials’ a database application can be found in which all material parameters can be defined and edited. Whenever something is changed within the application, this change is automatically processed for everyone who works with the app. 

<div style="padding:57.08% 0 0 0;position:relative;"><iframe src="https://player.vimeo.com/video/715587998?h=2297ac11d1&amp;badge=0&amp;autopause=0&amp;player_id=0&amp;app_id=58479" frameborder="0" allow="autoplay; fullscreen; picture-in-picture" allowfullscreen style="position:absolute;top:0;left:0;width:100%;height:100%;" title="Sample app PLAXIS - material database"></iframe></div><script src="https://player.vimeo.com/api/player.js"></script>

</br>

Because VIKTOR applications are hosted in the Cloud, all data is stored centrally and can be accessed through the internet with the right credentials. VIKTOR apps automatically include user management and version control, enabling you to collaborate on projects with everyone you want. It is possible to assign roles and permissions to determine who can view and change parts of a project.


Centralizing data

### Content: 

1. An introduction to developing successful applications
2. Designing and planning your application
3. How to start coding
4. Gathering and processing feedback
5. Increasing the adoption of your app



How to create successful application that ensure adoption

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How to create a succesful that people will adopt

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Do you want to build a successful application? This guide is here to help you make apps that provide real value to your work and that other people will definitely want to use too!

This guide will provide actionable insights that are useful for anyone involved in creating custom software tools, such as:

- **People developing the tools** (developers, engineers, data scientists, etc..)
- **End-users**, who will use the tools when they are released
- **Project managers** who are interested in workflow automation/optimization
- **Program managers,** who oversee and stimulate digital transformation initiatives
- **Domain experts**, who provide their expertise to people creating software tools
- And **anyone else i in the process of creating awesome software tools**

Over the past years, we, the application developers at VIKTOR, have built many apps for many different industries. We have learned a lot from that and now want to share our experiences with you. 

The principles and processes we explain in this guide are the same as we apply daily. They have helped us build anything from simple apps designed to save time to advanced engineering applications that are used to automatically calculate underground tunnels, dikes, and other large structures. 





Learn how you (developer, engineer, end-user, domain expert, project manager, etc.) can contribute to the creation of apps that provide real value to your work.

Build successful applications

This guide provides actionable insights for anyone involved in the creation of apps, such as engineers, developers, end-users, project managers, and domain experts. Learn how you can contribute to creating apps that provide real value to your work!

Building Successful Applications

Have you already automated your PLAXIS in- and output, but are you still looking for a way to easily define your materials? Look no further, as we have figured this out for you!

When you try to define materials yourself using the Python API, you may find that some inputs are not copied correctly. One way to copy properties is by placing the entire string from the PLAXIS command window into your Python application. However, because this string is very long and has no documented ending, it is difficult to properly parametrize your materials from within Python.

An alternative option is to instantiate the material and then select all the properties on the material. In this fashion, all the keywords will be updated correctly. However, you have to do this in a very specific order for it to work.

Defining this specific order is difficult and time-consuming. That is why we have done this for you instead! 

With the following function you can now properly set your materials:

```python
# Add soil materials. This must be done in a specific order to ensure the materials are set correctly
materials = {}  # Make a dict to be able to refer to the materials by name
for i, params_material in enumerate(params_materials):
    material_zip_list = []
    material_flattened_dict = get_deepest_dict(
        params_material
    )  # Get the deepest items from the material parameters dict
    for (
        material_key
    ) in ORDERED_MATERIAL_KEYS:  # Use a specific material key order such that the settings are set correctly
        if material_key in material_flattened_dict:
            material_zip_list.append((material_key, material_flattened_dict[material_key]))
    material = g_i.soilmat(material_zip_list[0])
    for material_zip in material_zip_list[1:]:
        material.setproperties(*material_zip)  # Set all the properties of the material in an iterative fashion
    materials.update({material_flattened_dict["MaterialName"]: material})
```

Throughout this article, we have shown multiple videos from a PLAXIS application on the VIKTOR platform. In our [GitHub repository](https://github.com/viktor-platform/sample-plaxis), you can find the entire open-source code of this app. Feel free to download the code and use it in your own Python code.

If you are still looking for a way to:

- Easily integrate software,
- automate and optimize processes,
- centrally store data,
- and quickly visualize results,
 
If you first want to see the PLAXIS sample application from this article in action, you can access the app (and many more) through the [demo environment] (https://www.viktor.ai/demo-environment). Continue reading for more information about the sample app.


Easy material parametrization

### Using the functionality

If you have been looking for a way to easily automate and optimize your PLAXIS analyses, we can help you with in two ways:

1. With VIKTOR, nearly-out-of-the-box. Here, the parametrization of materials, embankment, and drains, as well as an output of the visualization is taken care of for you. Do you want to try VIKTOR? Request a [free version](https://www.viktor.ai/start-building-apps).
2. Without VIKTOR, in that case you integrate with your own Python code and create a parametrization of materials, embankment, and drains yourself, as well as an output of the visualization. You can follow the instructions as described in the [readme](https://github.com/viktor-platform/sample-plaxis) in the VIKTOR GitHub repository, under the section: “Specific script use”. 

### Automating PLAXIS in 3 steps

In the video below, you can see how the functionality is being used in a VIKTOR application, just as with the videos shown before. 

<div style="padding:56.25% 0 0 0;position:relative;"><iframe src="https://player.vimeo.com/video/715587375?h=9017847dd2&amp;badge=0&amp;autopause=0&amp;player_id=0&amp;app_id=58479" frameborder="0" allow="autoplay; fullscreen; picture-in-picture" allowfullscreen style="position:absolute;top:0;left:0;width:100%;height:100%;" title="Sample app PLAXIS"></iframe></div><script src="https://player.vimeo.com/api/player.js"></script>

</br> 

As you can see, the process of defining a PLAXIS run and output extraction consists of 3 steps. 

1.	**Define your materials used**

![Blog_sample_app_PLAXIS_materials](https://cms.viktor.ai/uploads/Blog_sample_app_PLAXIS_materials_40f55fe121.png)

*Input in the material database*

</br>

2.	**Define the layout of the soil, embankment and the drains**

![soil, embankment, drains pLAXIS.png](https://cms.viktor.ai/uploads/soil_embankment_drains_p_LAXIS_acef92fbbe.png)

*Input (left) and corresponing output (right) of layout*

</br>

3.	**Click update in the PLAXIS analysis view and review your results!**

![results PLAXIS analysis.png](https://cms.viktor.ai/uploads/results_PLAXIS_analysis_b714fd4977.png)

*Results of the PLAXIS analysis in the application*

</br>

Use the [free version](https://www.viktor.ai/start-building-apps) or apply for a [demo account](https://www.viktor.ai/demo-environment) to try the functionality yourself!


Open-source Python code for a PLAXIS web app

Save time by automating PLAXIS in the Cloud

1. What is parametric design, and how is it evolving
2. Collaborative parametric design: working together for better results
3. How to make tools available to others
4. Active collaboration on parametric design tools
5. Parametric design in a billion-euro project
6. What collaborative parametric design means for you



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Parametric design is a design approach that uses flexible models that can be adjusted and solved quickly. The goal is to see the effect of specific choices on your design by just changing the input variables. 

The benefits are:

- **Flexibility:** Parametric design allows you to react quickly to changes at a low cost. Always generate the best solution for your project no matter the time pressure.

- **Better decisions:** Automatically calculate thousands of different solutions, get deep insight, and mitigate risks. Make better decisions and provide more added value to clients.

- **Digital Assets:** Create models and data that are reusable in new projects. Improve them over time, building up digital capital

This white paper is for engineers, architects, project leaders, and innovation and business managers. You will learn how collaborative parametric design in the cloud helps organizations get better results with real study cases such as a billion-euro infrastructure project.
 
Additionally, we talk about how you can transform Python, Dynamo and Grasshopper scripts into user-friendly web apps and significantly impact your organization performance. 

Learn how collaborative parametric design models allow you to work together for better solutions.

Download the white paper and get INSPIRED

This white paper is for engineers, project leaders, and innovation and business managers that want to learn more about what collaborative parametric design can mean for them. Discover more about this new way of working in which stakeholders collaborate to find the best solution for a project.

The Future of Parametric Design is COLLABORATION

## Pros and cons of Grasshopper

Grasshopper is a strong tool when it comes to 3D modelling and quickly developing scripts to manipulate geometries. Grasshopper seamlessly integrates with Rhino, which makes it possible to visualize changes in 3D models immediately, and is famous when it comes to architecture and BIM. Over the past years, different plug-ins have made it possible to integrate Grasshopper software with other software as well. 

However, sharing Grasshopper scripts internally is difficult, and externally impossible without revealing any of your source code. Additionally, managing and processing large amounts of data or performing numerical calculations and matrix operations for the optimization of designs can be difficult as well. 

## A Grasshopper web app 

That is why VIKTOR enables the development of web applications that you can use to link Grasshopper models to an interface and share these with internal and external users without requiring any downloads or knowledge about Grasshopper.

In this article, we give an example of such an application that is immediately available for trying out in the VIKTOR [demo environment](https://www.viktor.ai/demo-environment). You can also find the open-source Python code in our [GitHub repository](https://github.com/viktor-platform).

## Using the functionality 

You can use the code out-of-the-box with VIKTOR or try the app directly through the [demo environment](https://www.viktor.ai/demo-environment).

When using the sample app with VIKTOR, you should:

1. Make sure you have Rhino installed at ``C:\Program Files\Rhino 7\System\Rhino.exe``
2. Install a generic worker found on https://docs.viktor.ai/docs/worker. Make sure you select ``generic``.
3. Replace the config.yaml file in your worker folder with the file found at ``app/grasshopper/data/config.yaml``.
4. Copy the file found at ``app/grasshopper/data/run_grasshopper.bat`` in the same worker folder.

Below, you see a snippet of the Python code that shows how little lines of code are needed to run Grasshopper analysis and retrieve files. 

```python
# Run the analysis on grasshopper
generic_analysis = GenericAnalysis(files=files, executable_key="run_grasshopper,output_filenames=["output.txt", "output.obj", "output.mtl"])
generic_analysis.execute(timeout=300)

# Retrieve all files from the analysis
grass_hopper_data_bytes = generic_analysis.get_output_file("output.txt")
object_file = generic_analysis.get_output_file("output.obj")
material_file = generic_analysis.get_output_file("output.mtl")
```

In the video, you can see how a football stadium is [parametrically created](https://www.viktor.ai/blog/46/parametric-design-cloud-engineering-construction) through an integration with Grasshopper. On the left side of the application are all input parameters and a download button, in the middle you can see a 3D view of the mesh, and on the right side you can find all calculated information.

<div style="padding:48.75% 0 0 0;position:relative;"><iframe src="https://player.vimeo.com/video/706022495?h=9bdfe52a5e&autoplay=1&loop=1&autopause=0&amp;badge=0&amp;autopause=0&amp;player_id=0&amp;app_id=58479" frameborder="0" allow="autoplay; fullscreen; picture-in-picture" allowfullscreen style="position:absolute;top:0;left:0;width:100%;height:100%;" title="Sample app parametric football stadium with Grasshopper"></iframe></div><script src="https://player.vimeo.com/api/player.js"></script>

</br>
</br>

**Apply for a [demo account](https://www.viktor.ai/demo-environment) to get access to this and all other VIKTOR sample applications.**

</br>
</br>

## Parametric football stadium in 3 steps

Complete the following three steps to parametrically design a football stadium with Grasshopper using the sample application. 

1. **Define input parameters**, such as the shape, pitch width, offset from pitch, depth factor, asymmetrie along length and width, and height. 
2. **Create a 3D model**. Based on the input parameters, the field width, field length, and number of seats are calculated. 
3. **Download the 3D model**. Unfold 'downloads' to download a .glb (Graphic Language Bytes) file of the design. 

![Parametrically design football stadium grasshopper](https://cms.viktor.ai/uploads/Blog_sample_app_parametric_stadium_grasshopper_98ab0e1008.png)

</br>

Use the [free version](https://www.viktor.ai/try-for-free) or apply for a [demo account](https://www.viktor.ai/try-for-free) to try the functionality yourself! 




Blog_sample_app_grasshopper

Discover how you can make your Grasshopper scripts more accessible with this open-source web app. Read more on VIKTOR.ai.

Parametric design of football stadium with Grasshopper

Sample app parametric football stadium with Grasshopper

## Pros and cons of Dynamo 

Dynamo is a great tool for designers to create visual logic that you can use to easily calculate and visualize a parametric design of a structure. With Dynamo, designers can automate repetitive design tasks in order to use their productive time more wisely.  
 
However, the visual logic of Dynamo can be difficult to read for any other person than the one who created it. The logic quickly becomes ‘messy’, which reduces the usability. Especially for longer running projects this can become a problem when certain people leave or get assigned to a different project. Additionally, sharing Dynamo models is difficult, because an installation of Dynamo is required on each individual device to open the drawings.  
 
## A Dynamo web app  

With VIKTOR, you can develop user-friendly web applications that integrate with all kinds of software programs, such as Dynamo. VIKTOR apps have a clear and intuitive user interface in which users only see the adjustable parameters, which improves the usability of Dynamo software. VIKTOR also enables connecting Dynamo drawings to other computational programs through integrations, for example to calculate the strength of the structure. Additionally, everything runs in the Cloud, making your data always accessible to anyone with an internet connection! 

In this article, we give an example of such an application. Continue reading to learn more, or use our [free version](https://www.viktor.ai/try-for-free) to start using this app!

## Using the functionality 

You can use the code out-of-the-box with VIKTOR.

Here, you see a snippet of the Python code that shows how little lines of code are needed to edit, compute and visualize your Dynamo model within VIKTOR.   

```python
file = File.from_path(Path(__file__).parent.parent / "lib" / "files" / "dynamo_model_sample_app.dyn") 
input_file = DynamoFile(file) 
 
input_file.update("Height roof", params.step_2.height_roof) 
 
# Generate updated dynamo file and load into memory 
input_file = input_file.generate() 
files = [('input.dyn', BytesIO(input_file.getvalue_binary()))] 
 
# Run the analysis and obtain the output file 
generic_analysis = GenericAnalysis(files=files, executable_key="dynamo", 
                                   output_filenames=["output.xml", "geometry.json"]) 
generic_analysis.execute(timeout=60) 
 
# Generate output file and set up data for the DataViewer 
output_file = generic_analysis.get_output_file("output.xml", as_file=True) 
 
```

- In row 1 and 2 the dynamo model is loaded 
- In row 4 the dynamo model is updated  
- In row 7 and 8 the dynamo model is updated with your input parameter
- In row 11 to 13 the dynamo model is computed by the worker and sent back to the application 

And that’s it! Your model is now computed and visualized within the VIKTOR platform. 

The necessary modules are included in this sample app. All that needs to be done is import them, call them and let them do their work for you!

In the video you can see the functionality being used in an applicaton on the VIKTOR platform.

<div style="padding:56.25% 0 0 0;position:relative;"><iframe src="https://player.vimeo.com/video/698906446?h=5ff0ca5cc4&autoplay=1&loop=1&autopause=0&amp;badge=0&amp;autopause=0&amp;player_id=0&amp;app_id=58479" frameborder="0" allow="autoplay; fullscreen; picture-in-picture" allowfullscreen style="position:absolute;top:0;left:0;width:100%;height:100%;" title="Sample app Dynamo"></iframe></div><script src="https://player.vimeo.com/api/player.js"></script>

</br>

## Dynamo in 3 steps 

The process of using the Dynamo sample app consists of 3 steps.  

1. **Defining the location.** As a first step you can choose the location of you project on the map. In the example the construction of a residential block is used. By clicking on the map the necessary required space for the project is shown on the map. When the input parameters are adjusted, they are also adjusted on the map 

![Define location on the map](https://cms.viktor.ai/uploads/Blog_sample_Dynamo_1_5bf72b8656.png)
</br>

2. **3D dynamo model.** In this step the input parameters for your project are required. For this example the parameters are used such as the dimensions of the house and the number of houses. When the update button is pressed, the model is computed and vizualized. 

![Generate 3D model](https://cms.viktor.ai/uploads/Blog_sample_Dynamo_2_2bec3c873d.png)
</br>

3. **Report.** It is possible to compute additional information related to your project, such as the cost of construction or the impact on the environment. Using the Report functionality from VIKTOR a report is generated automatically, in which all this information is presented. It is of course possible to edit the template of this report to your taste. 

![Download report](https://cms.viktor.ai/uploads/Blog_sample_Dynamo_3_5d9bc8427f.png)

Use our [free version](https://www.viktor.ai/try-for-free) to start using this app!

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Use this open-source sample application to make your Dynamo models more accessible. Read more on VIKTOR.ai.

Make Dynamo models more accessible with open-source sample app

Sample app Dynamo

Digital transformation

*Read the original article on [heijmans.nl](https://www.heijmans.nl/nl/verhalen/digitaal-bouwen-en-ontwerpen-door-samenwerking/)*

A thick mist is hanging over the dark polder near Lage Zwaluwe when they arrive at Heijmans’ construction site. In the distance lie the foundations of six wind turbines, currently under construction, spread over several kilometers: Constructions of piles, reinforcements, and concrete in different stages of completion. Heijmans designed these foundations and is now constructing them.

![Heijmans_VIKTOR_wind_turbine_foundation_app_on_site](https://cms.viktor.ai/uploads/Heijmans_VIKTOR_wind_turbine_foundation_app_Wouter_Marcel_0b31531573.jpg)

*Wouter Riedijk, CEO of VIKTOR and Marcel Simons, manager Energy Design at Heijmans on the construction site of wind turbine park Klaverspoor near Lage Zwaluwe.*

## Calculation work

Noticeable is how the designs came to be: With the help of an application that Geotechnical Advisors and Constructors from Heijmans developed themselves on the low code application development platform VIKTOR. VIKTOR empowers engineers and domain experts at construction companies and engineering firms with basic Python knowledge to build their own technical design applications. Now, engineers at Heijmans used VIKTOR to create an application that takes over a lot of their manual calculation work. 

## Automation

“We have some unique knowledge within the industry”, says VIKTOR co-founder and CEO Wouter Riedijk. “Of the analysis, design, and of software development. In 2017, we decided to combine these into one platform, specifically aimed at the construction and infra sector. To enable engineers to build their own applications for the automated generation of designs. Within these applications, data is centrally stored, and processes are automatized to save time, generate smarter solutions, and turn knowledge into assets.”

![Blog_Heijmans_wind_turbine_foundation_app_interface](https://cms.viktor.ai/uploads/Heijmans_VIKTOR_wind_turbine_foundation_app_interface_3569f8c211.jpg)

## Together

A design consists of many variables that all influence each other. For example, with pile foundations: The width of the piles, the length, the soil, the load, the planning… When you turn one wheel, all the others start to turn as well. Multiple disciplines work on one design with each their own tooling and data sources. In an application, you can bring all of these together and simply press a button to come to one integral design. This is not only very efficient, but also gives them much more control over the process since all design calculations can be performed by Heijmans. 

## Better decisions

“This way, you can calculate many different scenarios much faster to generate different possible solutions”, explains Wouter Riedijk from VIKTOR. “Multiple people can work simultaneously on a design. You create several designs within less time, which leaves more time to judge each design based on costs and risks, which enables better decision-making and improves registration on tenders.”

![Blog_Heijmans_wind_turbine_foundation_app_agile](https://cms.viktor.ai/uploads/Heijmans_VIKTOR_wind_turbine_foundation_app_sprint_meeting_c8103d82a7.jpg)

## Digital Engineering Community

The application for the automated calculation for the design of wind turbine foundations is one example, but there are a lot more. De digitization of design processes is increasing within the engineering and construction world. Construction companies and engineering firms are even collaborating in this. That is also how the [Digital Engineering Community (DEC)](www.digitalengineeringcommunity.nl) came to be: A group of organizations collaborating in the development of design applications for infra objects. 

## Soil bodies

“Within the DEC, there are now four applications that are developed in collaboration on the VIKTOR platform”, tells Marcel Simons. “Geotechnicians at Heijmans, BAM, and Ballast Nedam were the first to build an application for the design of soil bodies. After that, five other constructors got on board as well. Within a year we (further) developed three more applications. Now, engineering firms are joining in as well!”

## Competitive

A collaboration like this is not very common. The engineering and construction world is competitive. Construction companies are heavy competitors whenever they register for a tender. So why would you collaborate in the (co-)development of applications in which you share data and that allow everyone the same chance to generate the optimal design?

## Journey

“It is true that you can see you are collaborating with your competitors. Everyone is in it for a strategic reason”, states Wouter with a fresh look at it from the outside. “We have been through quite a journey together, the trust really had to grow. But once it was there, it quickly accelerated. The set-up is accessible: When someone has a good idea for an application, the other companies can join in voluntarily by in it investing in some way.”

## Higher level

“And if you don’t do it like this, everyone starts building their own applications”, adds Marcel. “That also makes it more difficult for clients to judge designs. Now, the top of our geotechnicians is collaborating and all of this knowledge is put into one application. That takes the whole industry to a higher level.”

## Building blocks

Moreover, the DEC works according to the building blocks principle: Only standard processes are automated within an application. Everyone drives piles, everyone builds soil bodies, everyone pours tarmac. Not one constructor distinguishes themselves with that. “But these building blocks can be used to create your own, distinct application”, says Marcel. “The [wind turbine foundation application](https://www.viktor.ai/customer-cases/35/wind-turbine-foundation-parametric-design-python) is an example of that: It completely belongs to Heijmans.”

## Concrete

A short car ride away, the results of the application can be observed. The foundation of wind turbine number 6 currently consists of only a circle of 40 piles with a wickerwork construction on top. In a few days, they will start pouring concrete. The question arises: Can you also make a *better* foundation with such an application? 

## Optimal design

“You create an optimal design. That is always better”, says Wouter. “Less material, safer, cheaper, less nuisance for the surrounding environment.” “You also become more predictable, which means you are more likely to finish on time”, adds Marcel. Wouter: “And more flexible: Whenever something doesn’t work the way you planned, you simply generate a new design.” Marcel: “Within certain boundaries, of course. You cannot build a foundation using gingerbread.”

![Wind turbine foundation parametric design engineering](https://cms.viktor.ai/uploads/Blog_Heijmans_Wind_Turbine_Foundation_8bb28b6967.jpg)


The sun has come up by now, but the mist is still hanging around. Inside the polder near Lage Zwaluwe lie six wind turbine foundations, waiting to be completed. After that, the wind turbine can be anchored on top. Partly a product of digitization and collaboration; and partly of old-fashioned manual labour. 






Cloud-based design application wind turbine foundations on sight

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Discover how geotechnical engineers developed their own online parametric design application for wind turbine foundations on VIKTOR.ai.

Parametric design web app for Geotechnical engineering | VIKTOR.ai

All design knowledge within one Cloud-based application

## Get the white paper

**INDEX**

1. Construction companies and digital transformation
2. Technology trends for a different approach
3. Technology trends in the construction industry
4. A new technology trend for the construction industry
5. Low code for the construction industry
6. The VIKTOR platform
7. What does it cost?
8. How to start
9. What's next?

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What are the current trends in digital transformation and how do they affect the engineering and construction industry? 

This white paper is for every engineer, manager, director, or anyone else that wants to learn more about (new) technology trends that help boost digital transformation in engineering and construction, such as BIM, parametric or generative design, and low-code and no-code. 

Discover how web applications can help you find the best solution fast, get the best insights, capture knowledge into assets, and make work more joyful! 






Learn about trends in digital transformation and how they affect the engineering and construction industry.

Download the White Paper and get INSPIRED

This white paper is for every engineer, manager, director, or anyone else that wants to learn more about (new) technology trends that help boost digital transformation in engineering and construction, such as BIM, parametric or generative design, and low-code and no-code. 

Digital Transformation: Engineering and Construction Industry

## In this blog, we answer the following questions: 

- What is parametric design? 
- What is the difference between parametric and traditional design?
- What is generative design? 
- What is collaborative parametric design?
- What are the benefits of parametric design in the Cloud?
- How do I achieve collaborative parametric design?
- What software tools do I need for parametric design?
- What are some examples of parametric design applications?
- What is VIKTOR?

**Note**: You can use the navigation bar below to get directly to the topic of your choice!

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Unlock the real potential of parametric design by optimizing workflows through collaboration. Read all about Cloud-based parametric design on VIKTOR.ai.
 
 


Parametric design for Engineering & Construction | VIKTOR.ai

## What is parametric design?

Parametric design is a design approach that uses flexible models that can be adjusted and solved quickly to automatically generate a solution. A more formal definition can be found through Wikipedia: “The parametric design process is based on algorithmic thinking that enables the expression of parameters and rules that, together, define, encode, and clarify the relationship between design intend and design response.”

To make it simple, you can think of parametric models like an Excel sheet. You put a formula which links to a cell, change the number in the cell, and the sheet automatically calculates the right answer for you. 

The same goes for more complex parametric design models. By simply changing the input variables (read: parameters) within a parametric model, you can immediately see the effect this has on the design outcome. A good parametric model includes all key elements of a project and can dynamically be changed based on new knowledge, insights, or requirements (material, dimensions, go on) that come along during a project. 

## Parametric design versus traditional design

With traditional design, models are created, changed, and checked manually. As everyone in the business knows, it is very unlikely that you will find a good solution the first time trying. Usually, you must iterate several times until you find a solution that fulfils the requirements. On top of that, requirements and circumstances often change throughout a project, meaning even more iterations are needed before you get a good outcome. This process is time consuming and not fun at all.

### Automated & optimized designs 

That is why parametric design models are so popular. Here, all components of the design rely on parameters, meaning that if a parameter changes, everything else automatically changes as well. This means you spend less time updating and calculating models. This time you can invest in finding better and more optimized designs and exploring new solutions. Moreover, you are flexible and always ready in case requirements or circumstances change.

Thus: A traditional model provides one outcome for a structure at a time, while parametric design models can be used to automate designs for every possible outcome structure you can think of! 

![blog_long_read_Traditional vs Parametric](https://cms.viktor.ai/uploads/blog_long_read_Traditional_vs_Parametric_afdef98562.svg)

## Generative design versus parametric design

Both parametric design and generative design are often called the future of design, and that is for a good reason. Just like parametric design, generative design approaches are faster than traditional design approaches. With both, designers can make real-time changes to their models, which can be reused in future projects as well. 

### More automation

Even though a lot of people often use both terms to indicate the same thing, they do differ from each other to a certain extent. These differences lie in the degree of design automation. Generative design takes it a step further than parametric design, using an algorithm that generates thousands of design options. These are all analyzed and compared to each other to come up with the most optimal outcome (considering the requirements) or with solutions you have maybe never even thought of yet.

### Artificial intelligence

Lately, generative design is becoming even more powerful thanks to the inclusion of [artificial intelligence](https://www.viktor.ai/blog/40/artificial-intelligence-machine-learning-engineering-construction). Here, machine learning algorithms can be used at both sides of the equation: To generate different designs and to evaluate and rank these designs according to their performance.  

In short, this means that where with parametric design we still have to manually change the parameters and check the result by hand to find a solution. Generative design actually allows us to choose the design we prefer out of a set of designs that all fulfil the requirements. 
To avoid confusion: Throughout this article we will use the term parametric design to indicate both parametric and generative design.

![blog_long_read_parametric_generative](https://cms.viktor.ai/uploads/blog_long_read_parametric_generative_7cf5cba06d.svg)

## Collaborative parametric design

There are lots of people that use parametric design to automate parts of their workflow (e.g. repetitive calculation processes). This is already very beneficial, but to reap the most benefit from design automation, we must take parametric design to the next level by also enabling active collaboration.

### Collaboration between stakeholders

With collaborative parametric design we mean that different stakeholders work together on a single tool to find a solution for a problem. These models integrate data across different software packages and disciplines to include all key elements of the project, saving time and making the process less prone to communication errors.   

### Collaboration between disciplines

Additionally, we also mean active collaboration in creating parametric design tools. This means that, instead of reinventing the wheel, different people and organizations cooperate to create better and more powerful tools than they can create individually.   
The rise of web-based parametric design applications is helping to reach collaborative parametric design. These applications are hosted in the Cloud and can be accesses anywhere through internet and are user-friendly, which enables people with all kinds of different backgrounds to use them. Additionally, they serve as a single source of truth making sure everyone always works with the same version of the data and tools. 

![blog_long_read_traditional_vs_collaborative](https://cms.viktor.ai/uploads/blog_long_read_traditional_vs_collaborative_a13c791faa.svg)


## The benefits of parametric design in the Cloud

We have already mentioned several good reasons why you should use parametric design but to sum it up, here are the nine biggest benefits of creating and using parametric design applications in the Cloud: 

1.	**Design speed**: Calculate designs at the push of a button with the power of Cloud computing. 
2.	**Optimized designs**: Rapidly generate hundreds of designs to choose the best one from. 
3.	**Flexibility to change**: Adjust to new requirements without affecting your planning.
4.	**Automate**: Get deeper insights into the effects and risks of your choices.
5.	**Error reduction**: Mitigate risk for human mistakes and increase accuracy.
6.	**Digital assets**: Use your models for multiple projects and keep improving over time.
7.	**Better collaboration**: Work together and make sure everyone uses the same logic and data. 
8.	**User-friendliness**: Create tools that people with diverse backgrounds can use.
9.	**Intellectual property**: Provide access to your knowledge without sharing the logic. 

![blog_long_read_9_benefits](https://cms.viktor.ai/uploads/blog_long_read_9_benefits_cac8a514c9.svg)


Parametric design explained

It may be difficult to visualize how to reach true collaborative parametric design. That’s why we created a roadmap to help you evaluate how far you are in the journey and think about how to achieve the next step(s). Note: This is not a linear process – you can see it more as a guideline to evaluate what the foundation is for the next step. It is like building a pyramid; digitalization is the basis for building everything on top until you reach democratization. However, as the reach and power of your parametric design tools grows, it may be necessary to extend the basis and digitalize things that were not necessary to be digitalized before. 

### Circular process

We love it when people have big dreams. However, we always encourage you to start small. Even though the roadmap looks like a linear process, it is actually more of a circular one. We advise you to try and go through all the steps as quickly as possible, learn from your experiences, and start the cycle again. Don’t get stuck in automation and optimization, only to discover afterwards that you cannot properly distribute and democratize your tools.  

![blog_long_read_roadmap](https://cms.viktor.ai/uploads/blog_long_read_roadmap_b0d762909c.svg)

### 7 stages of collaborative parametric design

#### 1.	Digitalization

Digitalization is the first step. We assume that most organizations are not creating their designs using pen and paper anymore but depending on your ambitions it may be necessary to digitalize other parts of the workflow that are not digitalized yet. For example, data sharing between colleagues or registration of data at the construction site. 

#### 2.	Standardization

After digitalization follows the second step, which is the standardization of your processes. We don’t mean that you should provide just a limited number ‘standard’ solutions, designs, or products. It is about always following a clear and well-defined path to find the right solution. Even though each design is different, the process to create it is very similar each time if you think about!

So, how do you go about this? Try to sketch your process in a flowchart. At the top you will have all input that is relevant for your design (dimensions, materials, etc.). At the bottom you have a design that fulfils the requirements. You process is standardized if you can define all steps and choices needed to go from ‘input’ to ‘solution’ in such a way that you can simply follow a path without landing in a situation that requires improvisation. 

Standardization not only applies to designs but data as well. To standardize, make sure data is stored in an even and consistent way. Think also in input data obtained from the jobsite, time sheets, CPT measurements, or other things alike.

#### 3.	Integration

The third step is integration. If you want to avoid all the manual copy+pasting of information, you must find a way to break the boundaries between all the software packages and data sources you use to create your designs. That way, the various models and data sources you are using can communicate with each other, which is necessary if you want to automate processes. This can be done, for example, by using an API (Application Programming Interface) provided by the software vendor or using plug-ins in Grasshopper or Dynamo. 

For example, for your parametric design tool you may have to combine spreadsheets (e.g. Excel) with visual programming tools like Grasshopper or Dynamo, structural design software like SCIA, and/or a programming language like Python. 

#### 4.	Automation

Nice, copy+paste is gone now! But wait, are there still some actions that need to be performed manually within the different software packages you are using? Now it is time to eliminate those steps as well! 

Through automation, your parametric model can run all software packages and access all data sources automatically. You want to reach the point where you only have to provide the input variables, run the model at the push a button, and get the results. For this, all processes should be standardized, and all necessary software integrated.

#### 5.	Optimization

After automation follows optimization. Countless calculations need to be done before you end up with the optimal design. You don’t want to do all these iteration by hand but rather use an algorithm that helps you calculate hundreds of solutions in an instant to find out [what the optimal outcome is](https://www.viktor.ai/blog/30/digital-transformation-automation-python). 

At this point, it is important to have tools that not only allow you to run multiple calculations but also help you to find the best and most optimized design and make it possible to compare multiple solutions in an insightful way. We noticed that results are most insightful when they are presented in a graphical way, thus, instead of providing a bunch of data, try to use graph(ic)s, 3D models, and other visual representations. 

#### 6.	Distribution

Distribution is an important but often underestimated step. People often think that automation and optimization require much more attention, which is not true at all! With distribution we mean how tools are shared, which is very important. Not having a good system in place can affect your complete project or organization.

Let’s illustrate this with a simple example. Let’s think of any model that is placed on the company network drive, for example a Grasshopper script. With a bit of luck, people will be able to find, understand, and use it instead of having to start from scratch. So, they copy this model on their local drive and use it. But what happens if you discover a bug or make an improvement to your model after that? In that case, you update the script and publish it on the network drive again. However, the people who already downloaded your previous version are now using the ‘wrong’ one. So the question is: How can you be sure that everyone is using the latest version? Moreover, what happens if people have already modified a local copy of the model for their own specific situation? You may end up with all kinds of different versions of the model, with and without bugs, that all come up with numerous different results.

Thus, having good distribution means making sure that:

- People are aware that different models are available, and they are able to find the ones that are suited for their case easily.
- You have a user management system. Thus, you have control over who can access, use, and modify different models. And you can remove that right if necessary.
- You can manage how improvements to the models are made and how different people can help with creating a better tool. 
- People always use the right version of the model and data.

#### 7.	Democratization

Democratization is the last step of the roadmap to collaborative parametric design. After you have found a way to properly distribute your tools, you have to ask yourself the question:  Is anyone actually able to use them? That is the essence of democratization: Transforming the parametric design tools that only you or a handful of experts can use into something anyone can and <u>wants</u> to use. 
User-friendliness of your tools is key for adoption. If your tools are too difficult to understand, nobody will end up using them at all. Many users may not feel comfortable using Python, Grasshopper, Dynamo, and others. That is why you have to find a way to create applications with a user-friendly interface that are easy to understand and navigate for everyone and, most important, that provide real value for the end user. But how?

The answer: Make the end-user part of the process. Constantly ask them how they feel about the tools you are creating. This not only results in better tools but makes the end-users feel ownership. If you are interested in learning more about this topic, we wrote a complete guide addressing user-centric tool creation: [Building successful applications (that others want to use as well)](https://www.viktor.ai/white-papers/how-to-build-successful-apps).

[![CTA_mastering_app_creation_2](https://cms.viktor.ai/uploads/CTA_mastering_app_creation_2_d432d3bf35.png)](https://www.viktor.ai/white-papers/how-to-build-successful-apps)

### Application development platforms 

Over the past years, [application development platforms](https://www.viktor.ai/parametric-design-software) are becoming more popular. These platforms facilitate the democratization of parametric design methods by enabling people to create user-friendly web applications that, besides easy distribution, can easily be used for collaboration by all stakeholders (e.g. direct colleges but also other departments, organizations, or clients) to find the best solutions for a project. But more on that later. 




The roadmap to collaborative parametric design

## Commonly used tools

In the previous chapter, we explained which steps are involved in the creation of collaborative parametric design tools. Keeping the roadmap in mind, we will evaluate different aspects of commonly used parametric design tools. Starting off with an explanation of the various parts and an overview, which can be seen in the table below. We will go into more detail about this later but to sum it up and to keep things simple, we created three categories: 

1.	Spreadsheets, like Excels.
2.	Classic programming languages, like Python and C#. 
3.	Visual programming languages like Dynamo and Grasshopper. 


![long_read_parametric_design_overview](https://cms.viktor.ai/uploads/long_read_parametric_design_overview_054c548b53.svg)

### Explanation of the categories:

- **Easy to start**: Are the tools easy to learn when creating simple tools.
- **Easy to create tools**: It is easy to develop advanced tools that optimise a design, for example.
- **Build together with others**: How easy is it to work simultaneously to create tools with other people. 
- **Software integration**: how suitable are these tools to integrate or command other software packages, like a FEM or 3D modelling software.
- **User-management**: Can you give people controlled access to the tools and remove them if necessary?
- **Version control of the tools**: Are there good ways of controlling which version of the model people use. 
- **IP protection**: Can the parametric design models made with the software be used without exposing your intellectual property (IP)
- **User-friendly**: Are other people able to use the tools and understand the results. How error-sensitive is it?
- **Used to collaborate**: Can you work with several people on the same parametric design model
- **Version control of project data**: Do you know which data belong to which phase of the project and which input parameters were used. 
- **Scalable technology**: Can you make this tool available to many people or perform much larger calculations in a reasonable time.
- **Re-utilisable code**: Is code/logic used in your parametric model re-utilisable for creating or modifying tools?

### Parametric design with Excel

#### Learning curve

It is easy to learn the basics of Excel to make simple parametric tools that, for example, can be used to calculate a beam. Actually, the real power of Excel is that many people already know how to use it. This means that, as long as your tool is well-structured and not too complex, people will find it easy to use too. It is also nice that you can use Excel to create all kinds of graphs that help visualise data and short table data in different ways with little effort. 

#### Advanced tool creation 

It is only when you want to create more advanced tools that working with Excel starts to become a problem. For example, you have limited possibilities to process data, show another kind of visualisation (3D models, maps, etc.), do matrix operations, and command other software packages. You can solve some of these limitations by creating macros (VBA scripts), but not all of them. Although people are creating excellent tools in Excel, we think that – at the moment you start programming – it makes more sense to choose for a more powerful and friendly programming language, such as Python. 

#### Distribution & collaboration 

When it comes to distribution and collaboration, Excel is a weak tool as well. There are no good ways to work together with other people to create parametric design tools or use these together with other people. There is also no version control of the code and data. It is difficult to follow the logic of an advanced sheet and it is challenging to make sure that the changes you make to the logic will not break something else. You can distribute Excel tools only by sharing the files. After some has received a file, there is little control over what they do with it or who else they share it with. This makes it challenging to protect your intellectual property. It actually is possible to lock a sheet with a password. However, this still does not provide sufficient protection from someone with serious intentions. 

### Parametric design with programming languages (Python)

#### Learning curve

In this section, we will use Python as the representative of programming languages because we believe it is [the most used programming language in the engineering and construction industry](https://www.viktor.ai/blog/19/digital-transformation-parametric-design-python) and is easier to learn and use than other languages, like Matlab and C#. Out of all programming languages, Python probably resembles English most, meaning you can go from thought to code very fast and intuitive.

#### Advanced tool creation

Even though learning Python is harder than learning the basics of Excel, when you get through this initial learning phase, you will discover that making advanced tools is much easier. A significant advantage of Python is that there are so many libraries that you can use for free. You can find libraries for numerical calculus, machine learning, data processing, aerodynamics, creating interactive visualisations, geodesics, and so much more. Many software packages have a Python API that makes it possible to use FEM or 3D modelling software just as any other digital building block. 

The drawback of creating and using parametric design tools with Python – or any other programming language – is that they can be pretty intimidating to someone without programming experience. Additionally, Python scripts are distributed by file-sharing, meaning you have the same version control and user management problems as with Excel. On top of that, these files are also difficult to use together with other people. 

On the positive side, you can solve these problems as long as you are willing to invest enough time in getting more skilled at Python. You can use it to make almost anything you want. For example, you can create a Graphical User Interface (GUI, or connect your tools to a database to have a user management system and version control of your data. Additionally, you can build-in tests that automatically check if your code works appropriately after modifying it, and much more. There are also entire libraries that you can use for this, but that is a more advanced topic and that requires a high level of expertise.

#### Distribution & collaboration

Python is also very scalable. Large organisations like Google, Spotify, and Netflix use Python too. Many other tools facilitate the collaboration with several people on a single Python project and can be used to control how code and versions changes and how distribution takes place. An example of such a tool is [GitLab]( https://about.gitlab.com/). You can share Python scripts as files and also create an executable file (.exe) that enables availability of a tool without exposing its logic.

### Parametric design with visual programming tools

#### Learning curve

Visual programming tools are relatively easy to learn how to use. You don't even need to write a single line of code to create a parametric design model. These tools allow you to work with pre-made pieces of logic (nodes) that can be connected,. You can see how this works on the right side of the picture below.  

![blog_long_read_visual_programming](https://cms.viktor.ai/uploads/blog_long_read_visual_programming_fb54363aae.gif)
 
#### Advanced tool creation 

Software tools like Grasshopper and Dynamo are strong when it comes to 3D modelling and they seamlessly integrate with Rhino and Revit, respectively. This makes it possible to visualise changes in your 3D model immediately, as shown on the left side of the picture. Features like these are the ones that made this software's famous for architecture and BIM. Over the last years, different plug-ins also make it possible to integrate with structural engineering and other software.

However, Grasshopper and Dynamo are not as strong as Python when it comes to managing and processing large amounts of data or performing numerical calculus and matrix operations, which may be necessary to optimise your design or perform advanced analysis. Additionally – and in a similar way to Excel – there can come a point where you reach the limit of what can be done using just nodes, and it becomes inevitable to start writing actual code.

#### Distribution & collaboration

When it comes to distribution, Grasshopper and Dynamo are not really made to create or use parametric design tools with other people. However, there are still interesting [possibilities for collaboration](https://bimcorner.com/5-tips-to-better-collaboration-in-grasshopper/). For example, it is possible to create, share and import nodes. You can also ask to write or read data from a network drive so that you can share data with colleagues or clients. Nevertheless, this is not to the level that you are able work together with different people on the same script to create better solutions. Moreover, you still need to share Grasshopper or Dynamo files through Excel, making that version control of data and models and IP protection are also limited. 



Software for parametric modeling

 Looking at the overview of the pros and cons of different software packages, you may notice that there is no perfect solution for creating collaborative parametric design tools. In general, all of these tools are quite strong when it comes to integration, automation and optimisation, but lack the features required for distribution and democratisation. This leaves the question: How can you overcome the limitations of these packages without hiring a software engineer?

In this chapter, we will explain why hosting software in the Cloud the solution to this problem is. This will be followed by some concrete examples of how this can be done.  

## Application development platforms & collaborative parametric design

So, how can you overcome the limitations of software packages without hiring a software engineer? The answer: By using an [application development platform](https://www.viktor.ai/platform), such as VIKTOR. An application development platform enables people to create web-based applications that are user-friendly and easy to distribute. You can use it to transform your Excel, Python, Grasshopper or Dynamo scripts into a professional online application without requiring software development skills. It also includes ready-to-use integrations with engineering and design software so you can easily and quickly automate your workflow(s). 

Because everything is hosted in the Cloud, it is easy to share your apps with everyone you want to. The apps automatically include user management and version control of the design, enabling you to collaborate with all kinds of different people. You can assign roles and permissions to determine who works on and sees which parts of the project. People can simply use the app but don't actually get to see any of the logic behind it, meaning your intellectual property is safe at all times. Moreover, people are not required to install any software locally, as this runs in the Cloud.

[![CTA_Find_Out_More](https://cms.viktor.ai/uploads/solutions_page_banner_7_7bcffae017.svg)](https://www.viktor.ai/parametric-design-software)

## Software for parametric modeling in the Cloud

Here we have some examples for you of how software is hosted in Cloud-based VIKTOR applications to automate processes.

### 1.	Parametric design with Excel and SCIA

Many Excel sheets are used in construction to do calculations. Heijmans linked their Excel sheets with reinforcement calculations for concrete cross-sections to SCIA in a VIKTOR application for the reinforcement of slabs. Now, fewer numbers have to be copied and engineers can work more efficiently, have more time left for complex and challenging work, and the risk of error is reduced.

![Customer_case_automating_calculation_process_linking_excel_SCIA_2](https://cms.viktor.ai/uploads/Excel_and_SCIA_connected_c24d123297.png)

Read the full article here: [Automating concrete-cross section analysis by linking Excel sheets to SCIA](https://www.viktor.ai/blog/23/automation-Excel-SCIA-cross-sections)

### 2.	Parametric design with Python

To simplify and enhance the efficiency of their process, Sweco created custom Python scripts. They used VIKTOR to integrate in an application which functions as a user-friendly interface to centralize data and enable people to simultaneously use the scripts. All in one day!

> “It’s amazing that we are able to develop an application within 1 day, which ensures that everybody uses the same analyses and models. This saves time and reduces the chance of errors.” - Tjeerd Hermsen, BIM manager at Sweco

Read the full article here: [Custom Python scripts in VIKTOR to save time and reduce change of errors](https://www.viktor.ai/blog/27/web-application-python-D-foundations-Excel)

### 3.	Parametric design with Python and SCIA

Engineers often use SCIA Engineer in the design process of civil structures to assess whether the design(s) suffice the requirements. SCIA offers an API to create structural models without having to manually use the interface. VIKTOR created a Python library with specific SCIA objects that can be used to easily build up a (parametric) model that also can be exported to XML format, which can then be read in SCIA.

A VIKTOR worker takes care of a connection between the web application and the software, such that SCIA can be executed from within the browser. After the analysis, the results are returned and can be visualised on top of the model visualization. This means that the manual tasks of constructing a SCIA model in the interface, analysing the model and assessing the results can all be done with a simple click of a button from within the VIKTOR interface. See here, the associated visualization:

![blog_python_scia_example_associated_processing](https://cms.viktor.ai/uploads/blog_python_scia_example_associated_processing_c130288e81.png)

Read the full article to see how you can create the SCIA model with a few lines of Python: [Using Python and SCIA to create parametric models in the Cloud](https://www.viktor.ai/blog/10/parametric-design-python-SCIA)

### 4.	Parametric design with Dynamo and Python

Dynamo is loved by modelers for making automation accessible to non-programmers. However, Dynamo models tend to get quite complicated quite quickly, making them hard to use for those unfamiliar with their inner workings. At global design and consultancy firm Arcadis, engineering teams are ‘wrapping’ their Dynamo models in VIKTOR web apps, making cooperation easier and quicker.

VIKTOR provides an easy-to-use user interface that asks for input and shows the results. This allows you to use a model you don’t know, without being afraid to break it. You don't need to learn another new tool, or program, and you can use models from your colleagues easily, which can save enormous amounts of time and prevent mistakes from happening. As soon as you finish it, the app is instantly available online and providing access to colleagues is easy and fast.

In the video, you can see one of Arcadis’ two Dynamo models in a VIKTOR web-app:

<div style="padding:56.25% 0 0 0;position:relative;"><iframe src="https://player.vimeo.com/video/513789510?h=cef1da5778&amp;badge=0&amp;autopause=0&amp;player_id=0&amp;app_id=58479" frameborder="0" allow="autoplay; fullscreen; picture-in-picture" allowfullscreen style="position:absolute;top:0;left:0;width:100%;height:100%;" title="Arcadis Dynamo Dome Design"></iframe></div><script src="https://player.vimeo.com/api/player.js"></script>

Read the full article here: [Dynamo and Python in the Cloud for easy sharing and accessibility](https://www.viktor.ai/blog/32/parametric-design-Cloud-python-dynamo)

### 5.	Parametric design with Dynamo and Civil3D

The design and construction of objects in the civil engineering industry requires the collaboration of many disciplines, such as structural engineers, structural designers, and road designers. Often, each discipline in a multidisciplinary team uses its own specialised software, making design processes complex and data exchange difficult. Due to Dynamo’s steep learning curve only a specialist knows how it works often. This makes other disciplines dependent on the time and resources of these specialized individuals. That’s where VIKTOR comes into play.

By building an integration between Dynamo and VIKTOR, both expertise and distribution of data can be leveraged. That is why Dura Vermeer build a Dynamo-VIKTOR node package: Nodes where data can be fetched and pushed from Dynamo to VIKTOR. 
In the video, you can see the node package used in Revit and Civil3D. It shows how cross-sections are manipulated using the parameters in VIKTOR, resulting in a live connection between all disciplines – a single source of truth!

<div style="padding:56.25% 0 0 0;position:relative;"><iframe src="https://player.vimeo.com/video/574320490?h=c3842bf8bb&amp;badge=0&amp;autopause=0&amp;player_id=0&amp;app_id=58479" frameborder="0" allow="autoplay; fullscreen; picture-in-picture" allowfullscreen style="position:absolute;top:0;left:0;width:100%;height:100%;" title="Revit, Civil 3D, and Dynamo integration"></iframe></div><script src="https://player.vimeo.com/api/player.js"></script>

Read the full article here: [A single source of truth for Dynamo and Civil3D](https://www.viktor.ai/customer-cases/14/python-dynamo-civil3D-MXroad)

### 6.	Parametric design with Grasshopper

Grasshopper is a great tool for creating complex logic in a quick and visual manner, ideal for those who are not quite ready for coding yet. Grasshopper easily integrates with your VIKTOR web application, empowering Grasshopper users to contribute to applications or even take over most of the coding. Deploying the Grasshopper script is easily done by pushing it to our worker in the Cloud.
In other words, VIKTOR and Grasshopper is a powerful combination of visual programming and code, empowering a whole new group of people to contribute to online web application development.

Here, you can see what it looks like to parametrically design a façade structure with visual programming in Grasshopper on the VIKTOR platform:

<div style="padding:56.25% 0 0 0;position:relative;"><iframe src="https://player.vimeo.com/video/477572964?h=f73af7a4a2&amp;badge=0&amp;autopause=0&amp;player_id=0&amp;app_id=58479" frameborder="0" allow="autoplay; fullscreen; picture-in-picture" allowfullscreen style="position:absolute;top:0;left:0;width:100%;height:100%;" title="Grasshopper"></iframe></div><script src="https://player.vimeo.com/api/player.js"></script>

Read the full article here: [Parametric design in the Cloud with Grasshopper](https://www.viktor.ai/blog/13/parametric-design-python-grasshopper-excel-Cloud).


## Benefits of application development platforms 

From the examples you can see that there are several benefits to hosting software (for parametric design) in Cloud-based VIKTOR applications. To sum it up, here we have an overview of the 6 most important benefits of an application development platform:

- **Develop quickly**: Use digital building blocks to rapidly build applications without having to reinvent the wheel each time. 
- **Automate complex workflows**: Integrate industry-leading software and manage complex data structures inside one app. 
- **User-Friendly apps**: Create intuitive apps and visualise results in 3D models, interactive graphics, maps, and much more. 
- **Controlled distribution**: Anyone with the proper credentials can access your app in the Cloud, and you are sure everyone always uses the latest version of both data and tool. 
- **Facilitate collaboration**: Work together with different people on a single app and keep track of all changes. Your app serves as a single source of truth.
- **Focus on what matters**: Your apps automatically include user management and version control. The platform also takes care of the Cloud infrastructure, so you can focus on what matters.

![blog_long_read_6_benefits](https://cms.viktor.ai/uploads/blog_long_read_6_benefits_bd4b826f47.svg)




Parametric design software in the Cloud

## Successfull parametric design projects for engineering & construction

### 1.	Dike reinforcement

For this project, [The Graaf Weinaldalliantie](https://www.gralliantie.nl/), consisting of the [Water Board Rivierenland](https://rwbwater.com/project/water-board-rivierenland-sleeuwijk/), the contractor consortium ‘Waalensemble’ ([Heijmans](https://www.heijmans.nl/nl/nieuws/grote-stap-voor-dijkversterking-gorinchem-waardenburg/), [GMB](https://www.gmb.eu/actueel/63/gmb-ondertekent-alliantieovereenkomst-dijkversterking-gorinchem-waardenburg), de Vries & van de Wiel), and advisory party [Royal HaskoningDHV](https://global.royalhaskoningdhv.com/nederland/projecten/dijkversterking-gorinchem-waardenburg-samen-versterken), build an extensive parametric calculation tool for dike improvements, called [Wilma](https://www.viktor.ai/customer-cases/24/parametric-design-tool-python-D-series-Plaxis-SCIA-Excel-BIM). 

Traditionally, dike design methods are based on manual input of cross-sections and based on that a planning is made of how many cross-sections can be calculated. This normally is about one for every hundred meters of dike, which causes the design to be over-dimensioned. For people that built the dike from a safety point of view, this is okay. However, this does lead to strict and heavy measures that affect the environment and therefore this is not always desirable from a stakeholder point of view. With the Wilma tool, these calculations are automated, resulting in the optimal dike design, that also considers the requirements of stakeholders.

![Traditional vs Parametric vs Generative designwilma design process (1).svg](https://cms.viktor.ai/uploads/Traditional_vs_Parametric_vs_Generative_designwilma_design_process_1_dcdd3d64a0.svg)


### 2.	The world’s longest immersed tunnel

Another example is a parametric design application by COWI that automates the design of the Fehmarnbelt: [A road and rail tunnel from Germany to Denmark](https://www.viktor.ai/customer-cases/33/parametric-design-automation-python-tunnel). With the application, the [design of the tunne](https://www.cowi.com/solutions/infrastructure/northern-europe-largest-construction-project) will be optimized so it can enable lorries to take shorter routes and reduce overall traffic to contribute to  [a more sustainable future](https://femern.com/en/Benefits/A-greener-corridor)  by significantly decreasing CO2 emissions.

![blog_parametric_design_fehmarnbelt](https://cms.viktor.ai/uploads/blog_parametric_design_fehmarnbelt_e68b51669e.jpg)

### 3.	Offshore jack-ups

The online application for site-specific assessments [Calypso](https://www.viktor.ai/customer-cases/13/python-parametric-design-offshore-wind), enables both experts and non-experts to analyze offshore jack-up platforms quickly for a specific site. Because [Calypso](https://www.calypso.app/) can be used for all kinds of purposes, from quick communication to generation of clear images, to easy performance of in-depth calculations, it can be used to create the optimal design that also meets the wishes of all kinds of stakeholders (e.g. sales managers, engineers).

<div style="padding:56.25% 0 0 0;position:relative;"><iframe src="https://player.vimeo.com/video/584895866?h=b827e04b07&amp;badge=0&amp;autopause=0&amp;player_id=0&amp;app_id=58479" frameborder="0" allow="autoplay; fullscreen; picture-in-picture" allowfullscreen style="position:absolute;top:0;left:0;width:100%;height:100%;" title="Calypso-Tutorial-Jack-up-SSA"></iframe></div><script src="https://player.vimeo.com/api/player.js"></script>

### 4.	Truss construction anlyses

[FrameFlux](https://frameflux.nl/products.html) used the VIKTOR platform to quickly generate geometrically complex custom constructions (used at festivals) with in-house parametric design software. In their application, the [Antalyze One](https://www.viktor.ai/customer-cases/6/python-grasshopper-web-application-truss-construction), they integrated Grasshopper, Python, and SCAD Re-Event (a popular 3D CAD program) in a user-friendly interface. Now, clients can easily structurally 

![blog_long_read_truss_construction](https://cms.viktor.ai/uploads/blog_long_read_truss_construction_fc3b7ebe62.png)

*A visualization of a truss structure in Antalyze One on the VIKTOR platform (integrated with Grasshopper software)*

### 5.	Windturbines

Dura Vermeer has also been working on a parametric design application for wind turbines in which the geotechnical analysis (carrying capacity, D-foundations) is combined with the constructional analysis (AxisVM). The results of these analyses depend on each other and normally you must solve them iteratively. With this application, however, the analyses are linked and therefore this happens automatically. Additionally, the reinforcement of the concrete can be tested using another link with IDEA Statica. Besides that, it combines the results of all analyses and puts them in a downloadable design report. 

![GIf kleiner.gif](https://cms.viktor.ai/uploads/G_If_kleiner_a6b2e9c626.gif)

*The creation of a 3D parametric model with the Wind Turbine application on the VIKTOR platform*

### 6.	A16 tunnel

Together with joint venture [de Groene Boog](https://www.besix.com/en/projects/de-groene-boog), BESIX designed the 2.2 kilometer long A16 tunnel through Rotterdam. This tunnel consists of many similar tunnel sections, thousands of foundations and sheet piles, a detailed 3D BIM model, and numerous technical drawings. [The project](https://www.viktor.ai/customer-cases/20/parametric-design-automation-python-BIM3Dmodel-tunnel) focusses on the automation and improvement of repetitive work for the structural design of the tunnel  using parametric design methods. For the design of the reinforced concrete tunnel structure, BESIX developed a parametric design tool to drastically speed up the calculation process. Where one would traditionally calculate only a handful of representative tunnel sections, this tool allows calculating hundreds within the same time. The tool is hence beneficial to achieve higher precision results and improved insight, which enables fine-tuning the design and reducing material costs as well.

![Customer_case_a16_tunnel_rotterdam_5](https://cms.viktor.ai/uploads/Design_and_product_automation_for_the_A16_tunnel_in_Rotterdam_7252867b45.jpg)

### 7.	Theemsweg route

Due to the rapidly developing Rotterdam port area, train traffic has intensified. Because of that, the [Theemsweg route](https://www.portofrotterdam.com/en/news-and-press-releases/eu-backs-construction-theemsweg-route) was built as new railway viaduct. [Wagemaker](https://www.wagemaker.nl/en/) used VIKTOR to [parametrically design](https://www.viktor.ai/customer-cases/8/parametric-design-python-railway-viaduct) and calculate the substructure of the route. To do this, they integrated with geotechnical and structural calculation software such as the finite element program [SCIA](https://www.viktor.ai/blog/10/parametric-design-python-SCIA). Using the tool resulted in a more efficient design process and reporting enabled Wagemaker to demonstrate that they have been able to design and analyze all support points properly.

![blog_long_read_theemswegroute](https://cms.viktor.ai/uploads/blog_long_read_theemswegroute_be1d19cf16.png)

### 8.	Pile foundations

[Voorbij](https://www.voorbijfunderingstechniek.nl/) created [a web-based parametric design application](https://www.viktor.ai/customer-cases/34/automation-parametric-design-python-digitization) on the VIKTOR platform to optimize the (re)design process of pile foundations, which helped their clients save a lot of time and money. Before, Voorbij optimized pile foundations based on their experience, by grouping CPTs, and including soil variances in a smarter way. Now, they use their parametric design application to speed up this time-consuming manual process. The app allows for the automated grouping of CPTs based on a given set of rules and generates optimized pile plans according to aspects such as cost, soil structure, grouping, pile tip levels, and pile types, while also providing rich visualizations of results for quick interpretations.

![Blog_smart_application_contributes_sustainable_future_construction](https://cms.viktor.ai/uploads/Voorbij_areal_a17012b79f.jpg)


### 9. Your application as part of this list?

[![Discover the VIKTOR platform](https://cms.viktor.ai/uploads/CTA_discover_the_platform_fc4f5d42af.svg)](https://www.viktor.ai/platform)


Parametric design in engineering & construction

## Parametric design in the Cloud

VIKTOR is a platform for parametric design in the Cloud. It empowers engineers to create professional and multidisciplinary parametric design tools quickly. It allows you to profit from all the advantages of custom software in the cloud without software engineering skills in-house. VIKTOR is made for engineering: Invest time in standardizing and improving your process. We take care of the rest!

<div style="padding:56.25% 0 0 0;position:relative;"><iframe src="https://player.vimeo.com/video/545019231?h=360509f47a&amp;badge=0&amp;autopause=0&amp;player_id=0&amp;app_id=58479" frameborder="0" allow="autoplay; fullscreen; picture-in-picture" allowfullscreen style="position:absolute;top:0;left:0;width:100%;height:100%;" title="VIKTOR Explained under 2 minutes"></iframe></div><script src="https://player.vimeo.com/api/player.js"></script>

[![CTA_try_for_free](https://cms.viktor.ai/uploads/CTA_try_for_free_6af1b46cf2.svg)](https://m.viktor.ai/free_version)

## Engineering & construction

The past years, VIKTOR has been working on the development of many different applications that can be used to automate and optimize processes, centralize data, and allow people to work efficiently and collaborate on projects by implementing the principles of parametric design. Results from these projects all point to the same type of benefits of the implementation of parametric design methods in engineering: Because parametric design methods can be used to calculate all possible outcomes it reduces risks, saves times, leads to the most optimal design, and makes you more flexible in case of changes compared to when using traditional design methods.

## Application development

Our approach is implementing the right centralized system that facilitates collaboration and analysis and provides understandable insights to all key players. This system is easily set up with the desired tools and can be controlled by a team of domain experts and low-code developers. All the while, we focus on the following:

### Our 7 key drivers

1. Rapid and easy application development
2. Centralize and distribute data and tools
3. Integrate and automate 
4. Find the best solution. Fast!
5. Capture knowledge into assets.
6. Provide understandable insights.
7. Make work more joyful!

Curious about how you can use VIKTOR to improve your workflow? Check out our [parametric design solutions](https://www.viktor.ai/parametric-design-software)!






About VIKTOR

Parametric design in the Cloud for engineering & construction

## 1. Why should people start with parametric design now?

Even though it is a hot topic, [parametric design](https://www.viktor.ai/blog/46/parametric-design-cloud-engineering-construction) has been around for a while. Ever since programming exists, parametric models could be made. However, back then it required much skill of the individual doing this, both with programming and their specific profession (such as structural engineering or architecture). This made the threshold to start building parametric models very high and that is also why parametric modelling has only been achievable for a small group of people for a long time.

[![CTA_start_using_PD](https://cms.viktor.ai/uploads/solutions_page_banner_4_f474c9c318.svg)](https://www.viktor.ai/parametric-design-software)

### Democratization of knowledge 

The major difference between now and then, is that building a parametric model has become way easier. This is mainly due to the rise of visual programming tools, such as Grasshopper or Dynamo. Instead of hard-core scripting, pre-coded building blocks can be linked to form logic that shapes a parametric model, or anything else for that matter. This type of “simple” programming is known of its’ steep learning curve and enables users to quickly reach a level, where one can actually use it for their work-related activities. 

### Rise of the internet

Additionally, another factor contributing to the democratization of [parametric design](https://www.viktor.ai/blog/46/parametric-design-cloud-engineering-construction) is the fact that there is much more content available today. If you run into a problem, a quick Google-search will bring you to the right forum page, or even better, a YouTube tutorial explaining step-by-step what needs to be done.

### Gateway programming language

Lastly, visual programming can be seen as a gateway programming language. Because similar as with conventional programming, you do need to break down the desired process into a series of computational steps where input is processed into the desired output. This ability is what we refer to as computational thinking. In visual programming the ability for computational thinking is trained, which makes the step towards the more abstract conventional programming much easier.

## 2. How do you envision the development of a parametric model?

The development of a parametric model depends on several factors. Developing such a model costs time, which needs to be in balance with the projects’ budget as well. Generally, a parametric model grows during a project if it continues to add value. For example, in the beginning phase, one uses a parametric model to quickly investigate the impact, consequences, or characteristics of different designs. Based on that information, a well-informed decision can then be made. Only in case more details are required on a (or several) design(s), the model will be developed further to do so.

In some cases, this may instigate the start of an automation process in which the output is used for multiple projects instead of just one. In that case, the developments become process-based instead of project-based. This means that in every new project the same script is used and further developed, since for every new project, more resources are made available for additions or improvements. With large developments like this, it is more common to use conventional programming methods rather than visual programming methods since it is more suited to work on with multiple people, more memory-efficient, and easier to maintain overview. 

I think the scale of the development determines whether one can call it automation or [parametric design](https://www.viktor.ai/blog/46/parametric-design-cloud-engineering-construction). To me, parametric design is more applicable to visual programming workflows and small-scale developments whereas automation, to me, refers to large scale developments for which more conventional programming languages are often used.

## 3. What would you compare a parametric model to? 

In a parametric model, often one or multiple software packages are linked in which the data is centralized. This means that one data source is responsible for providing all linked software packages with the needed input. In contrast to a traditional process where software packages are used individually, individual input data has now been defined. This can be laborious when changes occur in the project because the input data of every single software package that is used needs to be changed as well. 

How centralised data in a parametric model is shared with different software often reminds me of the hub and spoke model in aviation. Centralised data is the hub, for example Schiphol that links to multiple small range city destinations, hence software packages. In the hub and spoke model, less flights (or less links) are needed compared to when creating a link between every destination (or every software package). This frees up resources and enables a more efficient throughput of people (or data).
 
![centralized data-sharing parametric design](https://cms.viktor.ai/uploads/blog_parametric_design_rayaan_ajouz_2666d63cbd.svg)

## 4. How will parametric models affect work as an engineer?

My guess is that large scale developments, hence automation, will become much more prevalent within the construction industry. Currently, most projects start from scratch, so creating an automated process around a certain type of building or a certain type of structure will definitely result in a more efficient way of working with a constant flow of qualitative output.

For engineers, this will change their way of working. Their work will shift from them repeatedly designing similar things by hand towards constructing the logic that is needed to generate models that do this for repetitive work for them. Moreover, monitoring and validating existing automated processes will become a major part of their job as well, since engineers will stay responsible for the output they send to others. To be able to monitor and validate automated processes, some programming competence is needed to for example identify bugs and solve these. Therefore, I think that the engineer of the future will become much more data-oriented, simply because they have to. 

## 5. Do you think all engineers have to become programmers in the future?

There is quickly a lot of expertise involved in programming. There are many different things you must keep in mind: Stability, version compatibility, speed, and go on. Especially for lesser experienced programmers, this can quickly become a dilemma because there are only so many hours in a working day to spend on specializing in a certain field. This makes it nearly impossible to specialize in two fields and reach the same results compared to someone that is fully committed to specializing in only one field.

However, thanks to visual programming, the bar to entry is getting lower since it makes programming easier to grasp. Additionally, there is an increasing amount of software packages that do a lot of the work for you, enabling you to fully focus on the task at hand, which is finding a solution to the engineering problem instead of focussing on software engineering. 

## 6. What was your personal experience with learning how to program?

For my graduation, I deliberately chose a topic for which I could develop my visual programming and conventional programming skills, even though I did not have much experience with it. Programming was something I always wanted to learn but did not find the time for while following courses at the university. 
 
During my graduation I built a script for steel trusses that integrated both the analyses of the main bearing structure and every structural connection into one workflow. To achieve this, I used a combination of the visual programming tool Grasshopper and conventional programming with C#, which I used to build my own Grasshopper components. I remember that when the first time the script did a full run analysing every connection, I was so amazed that I had actually managed to achieve this. It truly felt like magic. 

Deliberately choosing to develop my programming skills has also been advantageous for my career. Having basic competence in programming is beneficial because it is going to increase the likeliness of getting programming related tasks at work assigned and this will then again increase your programming skills. The beauty of having programming competence beside your expertise, is both skills can really amplify each other. As an engineer it enables you to tackle more complex projects, which let you automate the boring repetitive stuff so you can focus on what really matters.

For me it even opened the possibility to continue my graduation work at Bouwen met Staal in the form of the SMARTconnection research project, which is the main reason why I am currently in the unique position of having two employers.

## 7. Do you have a recommendation for the industry? 

I would recommend companies to have all of their employees learn basic programming concepts. Something simple like basic principles comparable with an A1 level for languages, but then for programming. For everyone, including team managers and people from higher level layers. They donot need to be able to build scripts themselves, but I think companies can add great value if the decision makers can identify when [parametric design])(https://www.viktor.ai/blog/46/parametric-design-cloud-engineering-construction) or automation can bring more efficiency and added value to the project. With such an awareness throughout multiple company layers, we as an industry can add more value to projects, the core business of our organizations, and fully utilize the potential that this digital era brings!


## Beneftis of parametric design (in the Cloud)

![benefits parametric design cloud](https://cms.viktor.ai/uploads/blog_long_read_9_benefits_cac8a514c9.svg)

See how you can [build your own parametric design application](https://www.viktor.ai/parametric-design-software) now!

Or find out more about the many applications of [collaborative parametric design in the Cloud](https://www.viktor.ai/blog/46/parametric-design-cloud-engineering-construction) with VIKTOR.

[![CTA_try_for_free](https://cms.viktor.ai/uploads/CTA_try_for_free_6af1b46cf2.svg)](https://m.viktor.ai/free_version)


medium_parametric design.jpg

small_parametric design.jpg

thumbnail_parametric design.jpg

Blog_future_parametric_design_7_questions_rayaan_ajouz

The future of parametric design: 7 questions with Rayaan Ajouz

## What is SkyCiv?

If you are a structural or civil engineer, you might know SkyCiv. SkyCiv is a powerful cloud-based structural design software focusing on efficiency and innovation for the modern engineer. On top of that, it also has a fantastic API, supporting many modern programming languages, including python. Today, professionals in more than 160 countries use SkyCiv structural analysis and design software, and API technology to solve their projects. 

Visit the [SkyCiv](https://skyciv.com/) website for more information.


### What we like most about SkyCiv

With the same level of functionality as traditional structural analysis software, or maybe more, SkyCiv has many things we are enthusiastic about. However, we want to highlight these functionalities in particular:

- All calculations are done in the cloud, making it super easy to integrate SkyCiv into your web application. You don't need software running on your computer or company's servers, making company-wide licensing and distribution issues a thing of the past. We really liked that! 
- Having a Python-enabled API is great! It enables you to use the complete Python ecosystem and powerful libraries such as NumPy, Plotly, and Pandas for your calculations.
- The model you make using the SkyCiv API is also a Python object and not just a text input file, meaning you can interact directly with it, read, and change its properties, and more!  
- You can ask SkyCiv to render your model and results in HTML, making it possible to embed the completely interactive 3D model in your website or VIKTOR app. Enabling you, for example, to adjust the view, get information about the materials or sections, and calculate the distance between nodes inside your app. 
- SkyCiv has a database with all kinds of section and material properties, and much cooler; you can also get the wind and snow load based on a GPS location. 


## SkyCiv and VIKTOR: A powerful combination

You hear us being quite positive about SkyCiv. So, why should you want to use it in combination with VIKTOR?

Like any FEM software, SkyCiv is powerful but requires specialist knowledge to make the most of it. Many processes can be automated, but that means working with an elaborate Python script using the SkyCiv API. Will all your colleagues be able to? Maybe, but probably not.

If you are looking for a way to make custom tools people can pick up and use quickly, you need a user-friendly interface on top of SkyCiv. Yes, we know you can make a product configurator directly with SkyCiv, but for this, you need to be quite handy with HTML and JavaScript. Here is where VIKTOR comes in handy.

With VIKTOR, you can quickly create a complete web-based user interface using nothing but Python, and it is easy too! On top of that, VIKTOR allows you to automate a larger part of your workflow by integrating your SkyCiv model with all kinds of other software packages. And what about the hosting? VIKTOR takes care of that too.     
     
<div style="padding:56.25% 0 0 0;position:relative;"><iframe src="https://player.vimeo.com/video/729982382?h=305d479fc4&autoplay=1&loop=1&autopause=0&amp;badge=0&amp;autopause=0&amp;player_id=0&amp;app_id=58479" frameborder="0" allow="autoplay; fullscreen; picture-in-picture" allowfullscreen style="position:absolute;top:0;left:0;width:100%;height:100%;" title="SkyCiv &amp;lt; &amp;gt; VIKTOR"></iframe></div><script src="https://player.vimeo.com/api/player.js"></script>

*Select fullscreen for a better view of the application*

</br>

### The benefits of SkyCiv and VIKTOR

Integrating SkyCiv with VIKTOR brings out the best features of both software. Below, we have listed why we think SkyCiv and VIKTOR complement each other perfectly: 

**Accessibility:** VIKTOR has an intuitive user interface, which makes it easy for other people to interact with your app. This makes building your SkyCiv model in an automated way much more accessible for people without (lots of) coding experience.

For example, this is a VIKTOR interface:

![MicrosoftTeams-image (11).png](https://cms.viktor.ai/uploads/Microsoft_Teams_image_11_9b22b4f850.png)

</br>

And this is the code you need to build a SkyCiv model:

```python
def _build_model_from_parameters(num_floors,
            grid_num_width, grid_num_length, 
            nodes_per_plain, corner_positions, 
            neighbours, grid_size_length, 
            grid_size_width, add_braces
        ) -> skyciv.Model:
    """Builds a SkyCiv model with the chosen parameters"""
    model = skyciv.Model("metric")  # Initialise an empty model

    # Member ids:
    # 1: Column
    # 2: Beams
    # 3: Braces

    current_y = 0  # Would be the current height
    for current_floor in range(num_floors + 1):
        current_z = 0  # Would be the current "width"
        for _ in range(grid_num_width):
            current_x = 0  # Would be the current "length"
            for _ in range(grid_num_length):
                uid = int(
                    model.nodes.add(current_x, current_y, current_z)
                )  # Add the node to the model and record the id tag
                # If the node ID is bigger then the nodes per plain
                #   then there is a node below it
                if uid > nodes_per_plain:  
                    # Connect the node to the node below
                    model.members.add(uid - nodes_per_plain, uid, 1)  
                    # If the column is not the first in its row
                    if (uid - 1) % grid_num_length > 0:
                        # Connect beam in x direction  
                        model.members.add(uid, uid - 1, 2)  
                    # The id on its own floor
                    floor_position = (uid - 1) % nodes_per_plain
                    # If the column is not in the in the first row
                    if floor_position >= grid_num_length:  
                        # Connect beam in z direction
                        model.members.add(uid, uid - grid_num_length, 2)  
                    if add_braces:  # Enable braces on the model
                        # Check for corners
                        for c, n in zip(corner_positions, neighbours): 
                            if floor_position == c:  # This is a corner
                                for sn in n: # Check every neighbour of corner
                                    # Get the id of the neighbour
                                    nid = sn+current_floor*nodes_per_plain+1  
                                    model.members.add(
                                        nid, uid - nodes_per_plain, 3
                                    )# Brace from neighbour to column of corner
                                    model.members.add(
                                        nid - nodes_per_plain, uid, 3
                                    )# Brace from column of neighbour to corner
                else:  # These nodes are on the floor
                    # Add support to the floor node
                    model.supports.add(uid, "FFFFFF")  
                current_x += grid_size_length  # Increment on the x-axis
            current_z += grid_size_width  # Increment on the z-axis
        current_y += FLOOR_HEIGHT  # Increment on the y-axis
    return model
```

</br>

**Speed:** VIKTOR is like a box of digital building blocks you can assemble to create your own apps. With Python, you can use the full functionality of SkyCiv and VIKTOR, making it easy to build powerful and user-friendly applications quickly.

<div style="padding:56.25% 0 0 0;position:relative;"><iframe src="https://player.vimeo.com/video/729945922?h=557e8fb532&autoplay=1&loop=1&autopause=0&amp;badge=0&amp;autopause=0&amp;player_id=0&amp;app_id=58479" frameborder="0" allow="autoplay; fullscreen; picture-in-picture" allowfullscreen style="position:absolute;top:0;left:0;width:100%;height:100%;" title="SkyCiv &amp;amp; VIKTOR - Adding parameter"></iframe></div><script src="https://player.vimeo.com/api/player.js"></script>

*Adding a parameter*

</br>

<div style="padding:56.25% 0 0 0;position:relative;"><iframe src="https://player.vimeo.com/video/729945794?h=811668fa56&autoplay=1&loop=1&autopause=0&amp;badge=0&amp;autopause=0&amp;player_id=0&amp;app_id=58479" frameborder="0" allow="autoplay; fullscreen; picture-in-picture" allowfullscreen style="position:absolute;top:0;left:0;width:100%;height:100%;" title="SkyCiv &amp;amp; VIKTOR - Adding control"></iframe></div><script src="https://player.vimeo.com/api/player.js"></script>

*Adding a control*


</br>


**Integrate with other software:** VIKTOR makes it easy to use SkyCiv in combination with (multiple) different ready-to-use integrations with industry-leading software, Like Excel sheets, Geotechnical Software, 3D modeling software, and much more. You can also generate custom reports based on your own templates.

**Interactive visualizations:** You can embed a completely interactive SkyCiv model into your VIKTOR app. Select, for example, which parts of the design you would like to show and which parts you would like to hide. You can also see information about the materials used for each member, forces, and calculate the distance between nodes. On top of that, you can use VIKTOR Views to enrich your app with maps, interactive graphs, other 3D models, and more. 

For example, this is the web view in your VIKTOR app:

<div style="padding:56.3% 0 0 0;position:relative;"><iframe src="https://player.vimeo.com/video/731261594?h=23f0446916& autoplay=1&loop=1&autopause=0&amp;badge=0&amp;autopause=0&amp;player_id=0&amp;app_id=58479" frameborder="0" allow="autoplay; fullscreen; picture-in-picture" allowfullscreen style="position:absolute;top:0;left:0;width:100%;height:100%;" title="SkyCiv results and interactive renderer"></iframe></div><script src="https://player.vimeo.com/api/player.js"></script>

</br>

And this is the code used to create an HTML page for your VIKTOR web view:

```python
def get_html_render(model, mode: str = "model", results: str = None):
        """The SkyCiv render is written in javascript. We can use the 
        webview to use it. However the webview only uses a single
        html file. We therefor use the jinja utility to build the html 
        file.
        """

        # Build the html file
        url = (
            "https://api.skyciv.com/dist/v3/javascript/skyciv-renderer-dist-2.0.0.js" 
        ) # The url to the skyciv renderer
        renderer = get_renderer(url)  # Request the renderer
        context = {
            "renderer": renderer,
            "model": model.get(),
            "mode": mode,
            "results": results,
        }  # Create the context to use with jinja
        path = Path(__file__).parent.parent / "lib" # Template location
        # Open the html file to be used as jinja template 
        with open(path / "renderer.html.jinja", "rb") as template:
            # Build the html file using the template and context  
            filedata = render_jinja_template(template, context)  

        # The return type of the jinja utility is already an 
        # viktor.core.File so it can be directly used in WebResult
        return filedata  
```

</br>

**Easy parametrization:** It is super easy to create parametric structures with SkyCiv in VIKTOR. Simply connect the InputField, Sliders, and other features to your SkyCiv model, and see it change at the click of a button.  

<div style="padding:56.3% 0 0 0;position:relative;"><iframe src="https://player.vimeo.com/video/731261579?h=88632d1b91&autoplay=1&loop=1&autopause=0&amp;badge=0&amp;autopause=0&amp;player_id=0&amp;app_id=58479" frameborder="0" allow="autoplay; fullscreen; picture-in-picture" allowfullscreen style="position:absolute;top:0;left:0;width:100%;height:100%;" title="SkyCiv model in VIKTOR"></iframe></div><script src="https://player.vimeo.com/api/player.js"></script>

</br>

**Total flexibility:** You can create a parametric model in VIKTOR, but what happens if you want to add some specific details for a project? No worries, The SkyCiv API lets you save the models you send in their own cloud environment. So, if you want to edit details after designing your model, you can continue inside the SkyCiv editor.

<div style="padding:56.25% 0 0 0;position:relative;"><iframe src="https://player.vimeo.com/video/729946100?h=665a8c0a89&autoplay=1&loop=1&autopause=0&amp;badge=0&amp;autopause=0&amp;player_id=0&amp;app_id=58479" frameborder="0" allow="autoplay; fullscreen; picture-in-picture" allowfullscreen style="position:absolute;top:0;left:0;width:100%;height:100%;" title="SkyCiv &amp;amp; VIKTOR - Dashboard"></iframe></div><script src="https://player.vimeo.com/api/player.js"></script>

*The dashboard*

</br>


## Try SkyCiv in VIKTOR

In this video, you can see the SkyCiv API integrated with a VIKTOR web application. With only a handful of input parameters, a structural model is created and analyzed in no time.

<div style="padding:56.25% 0 0 0;position:relative;"><iframe src="https://player.vimeo.com/video/729982382?h=305d479fc4&autoplay=1&loop=1&autopause=0&amp;badge=0&amp;autopause=0&amp;player_id=0&amp;app_id=58479" frameborder="0" allow="autoplay; fullscreen; picture-in-picture" allowfullscreen style="position:absolute;top:0;left:0;width:100%;height:100%;" title="SkyCiv &amp;lt; &amp;gt; VIKTOR"></iframe></div><script src="https://player.vimeo.com/api/player.js"></script>

</br>

There are three steps to using the application:

1. **Design the building:** First, insert the input parameters. The input parameters for materials are aligned with the materials in the SkyCiv database. 

2. **Map view:** Second, go to the map view to select a point on the map that you can later use to calculate the snow load through the SkyCiv API.

3. **Analyze:** For this third step, you can choose for yourself which loads you use. There are two things you can do with the API request here: 1) Generate an analysis report from the model that you created that shows typical FEA results like nodal displacements, support reactions, and member forces. 2) View the deformations on the model inside the SkyCiv renderer. These deformations are based on the parameters you have set. This model is then also saved to your SkyCiv dashboard (see: 'Recent files'). 


## What we can conclude

So, what we can conclude is that SkyCiv and VIKTOR together is a powerful combination. Linking SkyCiv's advanced FEM software - which often requires specialist knowledge to use to its full potential - to the user-friendly and intuitive interface of VIKTOR, enables not only specialists but also other (structural) engineers to automate and optimize their workflows! 

With easy accessibility, design and calculation speed, the ability to integrate with other software, interactive visualizations, easy parametrization, and total design flexibility, we invite you to build your own SkyCiV - VIKTOR apps. Download the full code from our [GitHub repository](https://github.com/viktor-platform) and sign up for a [free VIKTOR account](https://www.viktor.ai/start-building-apps) to start building awesome apps!

Blog_skyciv_VIKTOR

Combine SkyCiv and VIKTOR to create powerful and user-friendly parametric design tools. 

VIKTOR Blog

SkyCiv and VIKTOR to automate and optimize structural workflows