Digital transformation

In this blog post, we will talk about:

- The digital transformation in engineering and construction, specifically geotechnics
- The effects of automation, integration, and collaboration within the industry
- The solution to digitally tranformating geotechnical engineering: GeoTools
- The benefits of GeoTools
- How you can help imrove GeoTools
- How you can use GeoTools within your organization


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## 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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Autonomous cars, algorithms that are trading stocks, people having conversations with robots and digital services from the valley make our lives easier. It is already part of many different industries and drives extreme productivity. Considering these benefits of digitalization, there is huge potential in introducing this in the engineering and construction sector.

However, the engineering and construction industry spends way less on digital transformation than other sectors or automotive. So when the benefits are obvious, why have the engineering and construction industry not yet fully embraced new digital technologies? The reasons of lacking behind are understandable and have to do with the characteristics of the industry. But we have come to a time where there are increasing opportunities at hand for 
the sector to speed up digital transformation.

What are these trends in digital transformation and how will it effect the engineering and construction industry? You can read the answers to these questions and more in the white paper.



Learn about the trends on digital transformation and how to take the next step.

Download the White Paper and get INSPIRED

What are the trends in digital transformation and how will it effect the engineering and construction industry? You can read the answers to these questions and more in the white paper.

Digital Transformation Engineering and Construction Industry

Boost your organization's digital transformation with digital building blocks that help geotechnical engineers build apps to save time and reduce costs.

Digital building blocks for geo-engineering | VIKTOR.ai

Geotechnical engineering isn’t just another sector that is ripe for a digital transformation. It now just so happens that building is done in and on the ground, and geotechnics is the starting point. Because the soil is never the same in the Netherlands, every building requires a unique solution. Every project starts with a blank sheet on which the substrate must first be properly mapped. That sounds easy. Nevertheless, it is difficult to analyse the entire subsurface on a construction project on the basis of a number of drillings and CPTs (Cone Penetration Tests) and to make a responsible prediction of the foundation. This requires a lot of expertise and complex calculations. Partly because of this, the geotechnical aspects in projects are often a risk. The fact that more information about the subsurface often only becomes available later in the project further increases this risk.

### Automating processes

A toolbox with Python digital building blocks that offers usable solutions is already providing geotechnical engineering with the answer to many digital challenges.  Although the data that geotechnical consultants work with is always different, the process is the same every time. That is why the activities in this field of expertise lend themselves well to the automation and digitisation of process steps. Of course, a frequently heard counter-argument is that geotechnical consultancy is work that can only really be done by a person with a lot of knowledge and experience. Yet a mindshift is visible. And there is a reason for that.

### Combining forces

Consultants do a lot of repetitive work, while a computer with an algorithm performs complex calculations quickly and more reliably. During the construction of a tunnel, the base can vary every 100 meters and mapping it adequately requires a chain of new calculations. These analyses are complicated and very labour-intensive. Because of this distance between the measurements on a construction site, its tedious, and sometimes impossible to get a good insight. Even if the analyses and soil map are correct, design changes, optimisations or unexpected influences often surface during a project that require new calculations. There is often no time for these changes later in the design or construction process. If it is possible to map out this new situation quickly and integrate it with the existing data, the quality of the advice will improve considerably and the risks will decrease.

![Digital building blocks for geotechnical engineering.png](/uploads/Digital_building_blocks_for_geotechnical_engineering_05b2a92caf.png)

Digital tranformation in geotechnics

1. Why the Engineering and Construction industry is falling behind
2. Key components for a successful digital transformation
3. Stages of starting a digital transformation
4. Implementing your first digital transformation
5. What digital transformation means for you

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By 2021, the Engineering and Construction industry is one of the fastest growing sectors. Even though the sector is growing rapidly, it is still amongst the least digitized industries around the world. This is not due to the lack of supply of digital solutions, but rather due to the fact that the adoption of new technologies is not forthcoming within the industry. Finding ways to boost this adoption is both a big challenge and opportunity. Therefore, it is important we start at the right place.

There are three aspects to digital transformation: first people, then process, and after that technology. Adopting new digital solutions in your organization is impossible when your people are not on board with it. That is why convincing your people about the benefits is the first priority in digitally transforming your organization. Instead of looking at the digital solution from a technology perspective, you have to look at it from a people perspective. Your digital solution should never be implemented for digital’s sake. It is there to help the people in your organization do their job easier, quicker, better, and with more pleasure. After they are convinced that it will do just that, digital transformation can start!

In this white paper, it is explained how you can start digitally transforming your organization whilst keeping people at the centre of your digital solution. 



See how you can boost digital transformation in your company in the E&C industry by putting people first and technology second!

Read all about how you can boost digital transformation for your company in the Engineering and Construction industry by centralizing digital solutions around people, instead of around technology. 

People First, Tech Second: The Way to Boost Digital Transformation in the E&C Industry

By automating the geotechnical process on the basis of existing domain knowledge, humans and computers can reinforce one another. By integrating previously disconnected disciplines and jointly developing applications for digitization of processes, an increase in speed and efficiency and decrease error margins and failure cost in the sector can be achieved. 

### Automating processes

Automating process steps offers the opportunity to process and analyse more data in a shorter time. This contributes to better interpretations of data and decision-making for the individual process steps, and for the whole. In practice, insights and advice are obtained by combining different partial solutions within a multidisciplinary team. 

A change in one domain in turn triggers a chain of changes in other disciplines. The challenge is therefore not only to automate these (digital) islands, but also to connect and integrate them. 

> "The work of engineers is heading towards cloud computing, [machine learning](https://www.viktor.ai/blog/40/artificial-intelligence-machine-learning-engineering-construction) and [artificial intelligence](https://www.viktor.ai/blog/40/artificial-intelligence-machine-learning-engineering-construction). There is no doubt about that and it would be foolish to ignore this. The VIKTOR platform is an indicator of what our computing tools will look like in the near future.”

### Integrating disciplines

Digitisation is less effective if all partners in this chain of disciplines pick up and implement this process independently. This applies to consultants, designers and construction companies. Although construction companies compete, the process steps for projects are largely generic. By jointly developing applications for the digitisation of the design and construction process, speed and efficiency in the sector will increase. At the same time, the error margins and failure costs decrease.

### Joint development

This realisation has now reached the construction world. BAM Infra Nederland, Ballast Nedam and Heijmans already jointly developed an application for automating the design process of soil bodies. The application, which is based on the VIKTOR platform, links various data sources and software packages together. In addition, they use it to generate more design solutions at a quicker pace. 

Although the construction companies are competitors, they nevertheless work together because the distinctive character of the developed application is limited in itself. It is about how the individual companies integrate this application in their own process. They are therefore not afraid of competition, but see the added value of combining knowledge and investments.

Rob van Putten, from Waternet, thinks government agencies should adopt this model too: 

> “Water boards – that have the task of testing all flood defences geotechnically – could develop modules in collaborative ventures and make them accessible via VIKTOR. In this way we can prevent the wheel from being re-invented over and over, and we can work much more efficiently."

Automation, integration, and collaboration

VIKTOR believes in the power of digitisation together. That is why we invests in the development of a toolbox for geotechnical engineering: GeoTools. GeoTools uses building blocks to facilitate work-efficiency, for example by enabling automatic interpretation of CPTs and drilling.

### Geotechnical engineering 

If you are a geotechnical engineer or working with geotechnicians, you will recognise how slow and tedious it can be to interpret CPTs, create a 2D soil layout and set up your model with all soil properties. This is especially the case for larger projects with 10 or more CPTs. When working on large infrastructure projects, such as dikes, highways, or tunnels, creating these models can become your daily job. In [this article](https://www.viktor.ai/blog/14/web-application-python-geotechnics) you can read more about how this can be done more easily with GeoTools but first, let us show and explain what the GeoTools are.

<div style="padding:50.36% 0 0 0;position:relative;"><iframe src="https://player.vimeo.com/video/475043701?h=005feea02b&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="GeoTools Demo"></iframe></div><script src="https://player.vimeo.com/api/player.js"></script>

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### Digital building blocks

The GeoTools toolbox consists of Python building blocks that individually or in combination provide full functionality to allow the geo-technician to work more efficiently. These blocks, together with all multidisciplinary building blocks, form the puzzle pieces of the total design of, for example, an infrastructural project.

#### Quality-guarantee

In order to guarantee a toolbox with building blocks of the highest value, the platform for the development of the blocks works together with geotechnical consultancy CRUX Engineering and knowledge institute Deltares, amongst others. Within this initiative, CRUX’s sister company CEMS (CRUX Engineering MicroServices) realises so-called microservices for specific geotechnical calculations. 

"With such standard building blocks, complex projects can be efficiently converted to a good end product." - Ritchie Vink, co-founder at CEMS

CEMS was founded to further develop the skills for software development and [artificial intelligence](https://www.viktor.ai/blog/40/artificial-intelligence-machine-learning-engineering-construction). This sister company develops and supplies microservices or Cloud-based tools that can be part of a design process via an API. Ritchie Vink, co-founder of CEMS: “People are not scalable, so it is easier to automate repetitive calculations. Then people can focus on control and advice. We have specialist knowledge of and software for geotechnical engineering and use it to automate our own processes more efficiently. But we can also help others in the construction chain with that. For example, if we consider an algorithm for a pile calculation that we offer in a subscription form. With such standard building blocks, complex projects can be efficiently converted to a good end product.”

#### Collaboration

The focus of CEMS is on microservices and data analytics, and the company does not want to be bothered with the user experience or front-end. Vink: “That’s where VIKTOR comes in. They make our microservices accessible to others via GeoTools. We use this toolbox to supply standard Python code building blocks with which companies can build their own applications. If other specialists also develop building blocks, they enrich the toolbox and together we build proven standards. We are still at the beginning of this development, but by investing together, we are taking the most important first step.”

#### Model integrations

For Deltares, which develops calculation models, it is important to be able to link these models more easily and integrate them with other tools. VIKTOR then offers these building blocks integrated and on a pay-per-use basis via the platform. In this way, geotechnical consultants, construction companies or other parties can use or build professional applications more quickly.

## Soil layout digitisation

GeoTools is the first geotechnical standard application for automated interpretation of CPTs and drilling. GeoTools helps geo-engineers centralize, interpret, inspect, modify, and use their project’s CPT collection. Whatever a project is about, there are some aspects of working with CPT’s that reccur each time. CPT’s form the basis for many different calculations. They have to be interpreted, that is to say translated into a soil profile. The soil profile can then form the basis for various calculations, e.g. pile foundations calculations, dyke stability calculations, sheet piling calculations and much more.

> “A construction project starts with mapping the ground. If you consider a geotechnical consultant’s work process, he receives the data from CPTs and drillings in separate files that sometimes also differ in format. These are often printed for comparison. It requires a lot of manual work to get from the CPT to a soil structure.” - Stijn Jansen, head of application development at VIKTOR

![Example of a Soil Layout Table in VIKTOR's GeoTools application](/uploads/Example_of_Soil_Layout_Table_in_Geo_Tools_1e1918f9d9.png)
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*A Soil Layout Table in GeoTools*

The toolbox speeds up this process and makes it more accurate and standardised. Stijn Jansen: “The data files of a CPT are loaded into a web application and the soil structure is immediately available visually. The calculations and analyses are automated with algorithms. Subsequently, the consultant quickly has a good idea of ​​the soil structure. And if additional drilling or CPTs follow, this data is integrated and processed in the soil structure. This forms the basis for further calculations, such as, for example, of the pile foundation. This can then be done with other building blocks, such as the microservices from CRUX or the D-series from Deltares.”

GeoTools explained

There are several benefits to using GeoTools on within your organization, such as the acceleration of repetitive and manual processes to safe time (and money), the development of intellectual property, the channeling and refining of domain knowledge, and the possibility to easily integrate different processes and work from one central database. 

## Acceleration

Jacco Haasnoot, director at CRUX, explains why his company is participating in this initiative. “VIKTOR is a driver of digitisation in the construction sector. We too must and want to participate in this. We still use (VBA) Excel a lot for our consultancy, but there is clearly a need for further automation of the design process. Our people also spend a lot of time processing data. With an algorithm we can calculate more variants more quickly and monitor the quality better. Process steps are then more transparent and the number of errors decreases due to less manual work.”

> “VIKTOR is a driver of digitisation in the construction sector. We must and want to participate in this. - Jacco Haasnoot, director at CRUX

Ready to save time? Learn how GeoTools can speed up your geotechnical design process and make your data insightful [here](https://www.viktor.ai/geotools/?utm_source=LinkedIn&utm_medium=Post&utm_campaign=Articles_M2001&utm_content=M2001-3%20-%20Digital-building-blocks-geotechnical-engineers). 

## Intellectual property

Using GeoTools results a shift in the business model of consultancy and engineering firms. Haasnoot: “Presently we mainly sell the hours we spent to conclude our consultancy to our clients. Our knowledge and experience is recorded in good Excel sheets. These are our crown jewels, which we do not want to give away just like that. By developing microservices, we translate our knowledge into software that others can also use. They enter data and receive output that is paid, which gives them a new revenue model. The intelligence required for this remains our property. We currently have around 30 to 40 Excel sheets that we can potentially offer as a microservice.”

### Domain knowledge

Van Putten identifies that digitalisation is creating new business opportunities for small businesses or freelance specialists too. “As a small entrepreneur, VIKTOR offers me a platform to unlock specific domain knowledge via apps to an audience that is difficult to reach without this platform. The development of such a platform would normally take years of development time and is now being taken care of”

## Quick integration

The advantage of GeoTools is not only the availability of a wide and complete range of building blocks and solutions. The toolbox also facilitates the integration of different process steps based on the same data, which is shared along the way. All VIKTOR building blocks are web-based and use one database. This gives all disciplines access to the same data. There is always one version of what is considered the truth. Vink: “A microservice for a pile foundation can be built up from our algorithm in combination with structural design software. This however still needs considerable work. We can facilitate this faster with our microservice. And if multiple pile types are required, we can quickly calculate all variations as a basis for multiple scenarios. This directly contributes to a better end result.”

Why GeoTools

GeoTools is currently up and running. You can now use GeoTools through the [VIKTOR demo environment](https://www.viktor.ai/blog/56/try-free-apps-in-demo-environment). Some code is already openly available through [VIKTOR GitHub repositories](https://github.com/viktor-platform), enabling engineers to build on and improve GeoTools together.

## Improving GeoTools

Currently, the first versions of GeoTools have been developed and tested. The feedback from geotechnical consultants is continuously collected and used to further improve and expand the functionality of the building blocks. 

Peter Madlener, CCO and co-founder of VIKTOR concludes: “It is important to involve the end users as early as possible in the development process. We are indeed the initiator, but of course benefit from a wide and complete range of building blocks.”

## Building together

According to him, the challenge is to build the GeoTools building blocks together with the market. “The ultimate goal is an app store that engineers can easily use and adapt so that the tools are even better suited to the specific wishes of organisations in the chain. That is why we also call on other parties to join. By making domain knowledge accessible and cleverly combining it with digital technology, we achieve better results faster. Together we can also fulfill the promise of digitisation in the Construction and Infrastructure sector.”

Van Putten agrees, “I can imagine nothing better than an app store for geotechnical modules and applications. It is the only logical step to keep up with the rapidly changing world of cloud and artificial intelligence.”

## GeoTools for your organization

A first version of this App Store that offers GeoTools is now accessible through the [VIKTOR demo environment](https://demo.viktor.ai/login?to=/workspaces). Apply for a demo account to try GeoTools or read more about the demo environment and other available applications [here](https://www.viktor.ai/blog/56/try-free-apps-in-demo-environment). 


**[Learn more about the GeoTools.](https://www.viktor.ai/appstore/geotechnics-automation-python-digital-transformation)**

Using and improving GeoTools

Digital building blocks for geotechnical engineering

Creating Apps & Python

## Cone penetration testing
In many construction projects a cone penetration test (CPT) is converted to a soil layout. The data of such a CPT is often filtered based on the layer thickness, because very small layers (e.g. 4 cm) are not realistic. A CPT is a soil measurement, obtained by inserting a probe into the ground which measures the resistance. 

## Algortihm for classification
This resistance varies between different types of soil, allowing identification of the soils that are present. Roeland: “The difficult part is that the slightest measurement deviation can already result in a different type of soil, when the classification consists of many soil types.” In the picture here you can see an example of an unfiltered soil layout on the left. The thin layers are not realistic and have to be filtered. In the old algorithm, the user could specify the minimum soil thickness (e.g. 10 cm) which have to be removed from the soil layout. These layers are replaced by the soil which is present on top, such that there are no gaps in the overall layout. “This method works well, but is rather coarse.”, says Roeland.

![Soil layouts: unfiltered, with old filter, with new filter ](/uploads/Filtering_of_soil_layouts_according_to_the_old_algorithm_134f56efad.jpg)

*Example of filtering of soil layouts respectively without a filter, with the old filter, and with the new filter* 

## Continuous improvement
VIKTOR is continuously improving, so when the request came in to improve this filter algorithm, Roeland accepted the challenge. He explains: “Now we do not simply remove the thin layers, but we mark which layers are smaller than for example 10 cm. These layers are clustered to form individual layers with a maximum thickness equal to the specified filter thickness.”

## Why an algorithm?
The way a cluster is replaced depends on the thickness. If the total thickness of the individual layers is still thinner than the filter thickness, the old algorithm is used. The layers are removed and replaced by the soil present on top. If the cluster thickness is larger than the filter thickness, a new layer is formed. “A soil type has to be assigned to this newly created layer. The soil which is the most occurent within the cluster is automatically selected.” This logic is visualised in this schematic:

![placement of cluster and layers.png](/uploads/placement_of_cluster_and_layers_300649ad2b.png)

## The difference between now and then
Roeland: “With the improved filter, the soil layout is classified less coarse.” The difference between the old and new Python algorithms seems large in the first example, however Roeland states that this is not always the case. “In many cases it is not very likely to see such a large amount of different soil layers.” The old filter will not become obsolete, as many projects do not require the level of detail the improved filter offers.

## Soil layout interpretation
Many projects make use of the soil layout classification, which may become more accurate with the improved filter. However, in the end the technical advisor will always be the one making the decision of how the soil layout should be interpreted. Roeland: “When it comes to classification of a soil layout, a lot of expertise is required. Based on geological knowledge, experience from previous projects, location data, etc. the advisor will determine the soil layout.”

This improved filter will soon be available in the VIKTOR platform. Roeland: “We are trying to continuously improve our product and I think this is a great example of such an improvement.”



Soil layouts: unfiltered, with old filter, with new filter 

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An improved algorithm for soil layout classification

Parametric design

Five years ago, I first came into contact with Geotechnics for a project to automate the design process of high-voltage pylon foundations (Wintrack). With a background in Aerospace, these are disciplines that are (literally) far apart. To be honest, I was also quite arrogant about it: "How complicated can it be to design a concrete foundation? Flying an airplane, that is really complex." Over the past five years I have learned a lot about Geotechnics, being involved in numerous projects from a [parametric design](https://www.viktor.ai/blog/46/parametric-design-cloud-engineering-construction) perspective. As a result, that opinion has changed considerably and my love for Geotechnics has grown.

What is it that makes Geotechnical Engineering so interesting and challenging?

- Everything is unique, the soil structure is nowhere exactly the same.
- The behavior of soil is non-linear and heterogeneous: it is therefore labor-intensive to model properly.
- Unpredictability: you never know exactly what is underground and what its' properties are. You often only really find out how the soil behaves during the construction process.

Due to these circumstances, the greatest risks in construction projects often have to do with Geotechnics. Because everything is so different for each circumstance, Geotechnics does not seem to have the ideal conditions for automated/parametric design methods. Or does it? 

## Contents
In this article, I will explain why I believe that it is precisely because of the specific properties of Geotechnics that a lot can be achieved with the help of digitization. For this, the following will be discussed:

- The problem: Changes
- [What is parametric design?](https://www.viktor.ai/blog/46/parametric-design-cloud-engineering-construction)
- How do you apply this in Geotechnics?
- What is the impact of these types of tools?
- Is there still room for human interpretation?
- How do you ensure that you can use this on projects?
- What is your contribution?

## The problem: Changes
One of the major challenges during projects is that (many) changes occur along the way. The bigger the project, the greater its impact. The change can be caused by external factors, for example from changes in the desires of the customer or by new information from additional soil investigation. Often changes also simply occur because a design process does not run linearly but in parallel. During design processes, all kinds of different disciplines gather more information. This can lead to new insights and results in that the intended solution no longer works or that an opportunity is found for a better solution.

In order to mitigate this risk, the strategy is often chosen to record as much as possible as early as possible. We try very hard to ensure that no changes occur. “First time right” is a popular saying. But is this really possible? Isn’t progressive insight inherent in a complex design process? And don’t we miss a lot of opportunities for optimization if we record a lot too early on in a process?

I believe that you should turn it around: Make sure you organize your processes so that you can deal with changes correctly. Assume that the customer will come up with a change 20 times, the soil investigation will turn out differently, or that ideas will gradually arise to arrive at a more optimal design. This is where [parametric design](https://www.viktor.ai/blog/46/parametric-design-cloud-engineering-construction) comes into play.

## What is parametric design?

With [parametric design](https://www.viktor.ai/blog/46/parametric-design-cloud-engineering-construction), one quickly thinks of the parametric creation of a geometric model. For example, you can define a beam based on three parameters: length, width and height. For more complex constructions you can do this with more parameters. Besides geometric parameters, there are a lot of other parameters involved in a design as well. Think of soil parameters, loads, requirements, and preconditions.

By setting up a [model parametrically](https://www.viktor.ai/blog/46/parametric-design-cloud-engineering-construction), you ensure that when changing a parameter, the impact of this is immediately visible and transparent. This can be achieved by automating steps of the process.

![parametric model by.jpg](https://cms.viktor.ai/uploads/parametric_model_by_d42889033b.jpg)

*An upside down force model of the Sagrada Família by Gaudí. The strings are weighted down and by changing the position of the weights or the length of the strings, the shape of each arch can be altered and the impact of this on the rest of the structure can be seen.* 

## How do you apply this in Geotechnics?

Example: During a project, a geotechnical consultant made a large number of models to do settlement calculations for different cuts for a soil body. Gradually, additional soil research shows that the soil parameters are different than assumed. The geotechnical consultant now has to manually adjust all models and redetermine the required increase to meet the residual settlement requirement.

![The traditional design process](/uploads/Traditional_design_process_06326fe5b8.png)
*The traditional design process* 

How can this be improved through [parametric design](https://www.viktor.ai/blog/46/parametric-design-cloud-engineering-construction), you may ask? Well, with parametric design methods you create one central place where the soil parameters are recorded. The geotechnical consultant now only has to adjust the parameter underwent a change, after which the models can be updated at just the push of a button. Subsequently, the required increment can be determined automatically, using a Python algorithm that iteratively makes several sums.

![The parametric design process](/uploads/parametric_desing_process_511f670ac9.png)
*The parametric design process*

The principle of [parametric design methods](https://www.viktor.ai/blog/46/parametric-design-cloud-engineering-construction) is quite simple: Centralize the input, link the various calculations and present the results clearly.

## What is the impact of these types of tools?

With VIKTOR we have already developed many applications according to this principle, for example [dikes](https://www.viktor.ai/customer-cases/15/digital-transformation-parametric-design-dikes), [pile foundations](https://www.viktor.ai/customer-cases/32/parametric-design-automation-python-pile-core), [soil bodies](https://www.viktor.ai/blog/15/digital-transformation-automation-Excel-python-geotechnics), and [sheet piling](https://www.viktor.ai/customer-cases/20/parametric-design-automation-python-BIM3Dmodel-tunnel). These applications have now proven their value on [all kinds of projects](https://www.viktor.ai/customer-cases/). Often links are made for this purpose with geotechnical software, such as the [D-series](https://www.viktor.ai/customer-cases/24/parametric-design-tool-python-D-series-Plaxis-SCIA-Excel-BIM) or [Plaxis](https://www.viktor.ai/blog/34/integration-plaxis-python-parametricdesign).

The main results of the tools are:

- Time savings on “boring” work, which leaves more time to deploy expertise
- Flexibility with changes
- Risk reduction through more calculations, sensitivity analyzes, and less chance of errors
- Optimal design, because more iterations or cuts can be calculated

## Is there still room for human interpretation?

I often notice that geotechnical consultants (like all engineers, by the way, apparently this is in our blood) are skeptical about automation. This is a very healthy and understandable response. Geotechnics is a field in which human interpretation and experience is essential: You do not put this knowledge into a computer or an algorithm. For example, the automatic interpretation of CPTs to a soil structure is very difficult to get right in 100% of the cases. It will not be possible to automate a geotechnical design process from A to Z in the foreseeable future.

### Don't give up too quickly

I often notice that an idea for automation is being thrown off this. Because a few steps in the process cannot be automated, nothing is automated ultimately. That is a shame: You don’t go all the way from Rotterdam to Arnhem on foot because you have to change trains in Utrecht, right? Despite the time it takes to change trains, you are still 15 times fast in Arnhem compared to when you have to walk the whole distance.

### Find the perfect balance

You can also look at a design process in this way. Where is the repetitive (“boring”) work essential? And where is human interpretation and expertise essential? The repetitive steps in the process often lend themselves very well to automation. A computer is very good at doing "stupid" (read: repetitive) work very quickly. Despite the fact that certain steps are still carried out by humans, you can speed up the process drastically.

When these types of tools are properly developed, it gives the consultant more insight, instead of becoming a black box. Consider, for example, the ability to perform sensitivity analyzes or to calculate many more cuts. Then the combination of people and computer ensures the strongest team in this situation as well.

## How do you ensure that you can use this on projects?

Developing these types of applications of course takes time and money. Development time is often limited because a project has to be planned and follow a schedule. This makes developign an application for this challenging. The development initially requires an investment. Not only from developers, but also from a specialist who (in a Product Owner role) must give direction to the development. So, compared to the traditional design process, extra effort is required in the beginning. The role of the geotechnical consultant is also changing: They will develop part of their time, or work together with a developer to achieve a good application. The planning will have to be adapted to this process change. The involvement of the specialist in the development is also crucial to remove the black box feeling: The specialist understands what has been programmed and is able to explain it to others.

Of course, it also helps to ensure that you don’t start developing an application from scratch when a project starts. You can do this by developing more generic applications outside of projects that can then be used on different projects later. Also, by developing building blocks that you can quickly assemble or expand on a project.

### Sharing applications

We have noticed that different parties require the same kind of applications for their projects. From this point of view, the initiative arose to develop tools together with various parties: [The first application that was jointly developed for soil bodies](https://www.viktor.ai/posts/bam-ballast-nedam-en-heijmans-behalen-grensverleggend-succes-bij-collectieve-automatisering/). In this way, the investment is divided among different parties and the business case for automation is stronger!

### Tools from VIKTOR

In addition, VIKTOR has taken the initiative to develop a number of basic tools for geotechnical consultants, under the name GeoTools. The first version of this was created based on input from various geotechnical consultants. With this application you can:

- Interpret CPTs to a soil structure with different methods
- Visualize these CPTs on a map and in 3D
- Define the soil parameters in a central place
- Create transverse and longitudinal profiles based on the CPTs
- Generate D-Series models based on the profiles and soil parameters

### Other Geotechnical content

There is of course much more to be said about [parametric design](https://www.viktor.ai/blog/46/parametric-design-cloud-engineering-construction) within geotechnical engineering. That is why we would like to take you further into the topic:

- Our colleague Roeland Weigand has written a blog about [an improved filter algorithm](https://www.viktor.ai/blog/16/web-application-python-CPT) that he has developed which enables geotechnical consultants to gain a better insight into the actual soil structure
- Together with Jacco Haasnoot (CRUX), Ritchie Vink (CEMS, sister of CRUX) and Rob van Putten (Waternet), I contributed to an article about [digital building blocks in geotechnical engineering](https://www.viktor.ai/blog/15/digital-transformation-automation-Excel-python-geotechnics). By making domain knowledge accessible and [smartly](https://www.viktor.ai/blog/40/artificial-intelligence-machine-learning-engineering-construction) combining it with digital technology, we achieve better results faster!
- Kevin van Giessen has written a blog about the development and operation of the [GeoTools application](https://www.viktor.ai/blog/14/web-application-python-geotechnics) that was mentioned in this article. 

## We are looking for input!

We strive to be able to provide a valuable tool with the GeoTools, which makes the work of every geotechnical consultant easier and more fun. For this, we need input from specialists. So, if you are interested in the application, you can contact me directly via a personal message. I am also very curious about the experiences you have with [parametric design and automation](https://www.viktor.ai/blog/46/parametric-design-cloud-engineering-construction) within geotechnics. If you have feedback, experiences or ideas, please send me an email: sjansen@viktor.ai.

See how you can [create parametric design applications](https://www.viktor.ai/parametric-design-software) as well.

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The impact of Parametric Design on Geotechnics

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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The adoption of parametric design grows exponentially thanks to friendly programming languages like Python or visual programming packages like Dynamo or Grasshopper.
 
Our perception is changing. We no longer see parametric design as a model to solve specific technical problems, but rather as a new way of working, in which stakeholders collaborate to find the best solution for a project.

Learn about the latest trends and the future of parametric design in this white paper

Collaborative parametric design models allow you to work together for better solutions

Download the white paper and get INSPIRED

Did you know parametric design models are no longer just used to solve specific technical problems, but rather as a new way of working? Read here how stakeholders use parametric design to collaborate and find the best solutions for their projects!

The Future of Parametric Design is COLLABORATION

This article was written in collaboration with Peter Konijnenbelt (Arcadis), Johan Tuls (BAM), Kelvin Roovers (BESIX), Tjeerd Hermsen (Sweco), Nynke ter Heide (Vidabo) and Kevin van Giessen (VIKTOR). We have something in common: we create software tools that have a big impact in our organisations and are used by many people. However, none of us have a background in software engineering. We are trained engineers in our different disciplines. We believe you can do this too. You just need to choose the right tools and follow a good method. Here we share our experience. 

## The start of a series
This is the part of a series of articles about [engineering and Python](https://www.viktor.ai/blog/19/digital-transformation-parametric-design-python). Each time we will go deeper into engineering content and talk about solving specific problems. 

### In this article we will talk about:

- The digital transformation and why engineers are programming
- The four components of professional engineering tool: Automation, integration, optimisation, and distribution… and why you should consider all of them when creating your tools.
- Why we recommend using Python for making your own tools and our experience with other languages or software.
- Creating digital building blocks and their impact on the future of engineering
- How to make your code accessible for everyone, even to people that cannot code!
- Why and how engineers are using VIKTOR to create software tools that are accelerating the digital transformation of their companies. 
- Tips & tricks you can apply to your own projects

## The digital transformation
Digitization is growing exponentially thanks to the increasing accessibility to user-friendly software development tools. Gartner defines this movement as the Democratization of Technology. This means providing people with easy access to technical expertise without extensive (and expensive) training. This is often referred to as “citizen access”.

This changes the way software is developed. In construction and engineering companies, for example, there is a transformation. Software is no longer something for the IT department. Engineers are empowered to make their own software applications. Management sees the value of such powerful tools and creating them has become a company policy. Like this example from BAM, to design subway crossing under roads or railways. 

![VIKTOR application for designing subways under roads and railways (BAM)](/uploads/VIKTOR_application_for_designing_subways_under_roads_and_railways_BAM_a72f04e442.png)

## Why are engineers programming?
In engineering, every project is unique, at least that is what most engineers will say. This means you cannot copy one design directly to another project; however, the design techniques will be applied in the same way in each project. For example, a bridge must always comply with same design code, and its beams, foundation and paving are calculated in the same way. In addition, finding the optimal solution requires many calculations. A time-consuming process when done manually and, perhaps worst of all, no fun at all.

Automating these types of repetitive processes can help to quickly find the best solution and make engineering work more fun. This is why most engineers start programming. After all, we did not study engineering to spend our days updating models and copying/pasting results into reports. We want to engineer awesome things.

> “If you don’t learn to automate the repetitive part of your work, someone else will do it for you. You must learn this to stay relevant.” - Kevin van Giessen, VIKTOR

## The four components of a professional engineering tool
I notice that each professional engineering tool created to solve a specific problem, for instance designing a bridge, has four distinguishable components: integrate, automate, optimise, and distribute.

![The four components of a professional engineering tool](/uploads/the_four_components_of_a_professional_engineering_tool_5c1e9e54bf.png)

### Automation
By automation I mean that the program can perform a task automatically, such as generating a report or copying data from one place to another. 

### Integration
Integration is the automatic combining of different sources of information, which could be models, databases, Excel sheets or external software packages. 

### Optimisation
Optimisation is when the software tool calculates different designs or scenarios and helps you find the best solution. 

### Distribution
Distribution makes the software tools available to other. It transforms the tools you use into something anyone can use. As some of us have learned the hard way, processes, software packages and programming languages that seems perfectly suitable for one part become the bottleneck for the other. Distribution is the most underestimated part. For some reason, people often think this is something we can solve later, and that integration and optimisation are much more complex. This is not true; I have seen so many great projects end up in the drawer because they did not think of distribution and usability beforehand. That is why it is important that you consider all components and from the start choose the right tools.

## Which programming language should I use?
Having the computer help you solve engineering problems is not a new concept. Many engineers have their own Excel or Mathcad sheets and VBA or Matlab codes. But there are some drawbacks to those programs, such as the difficulty to do version control, the lack of a user-friendly interface and codes that are hard to understand if you have not written them. Fortunately, a new language is rising in the engineering world that is overcoming these problems, namely Python.

> “Python is very scalable. Each piece of code can be used countless times as it just needs an input and it will create an output. In this way you could solve a large problem by connecting smaller pieces of code; it is like having digital building blocks”. - Johan Tuls, BAM

### Excel, Matchcad, and Python
Peter Konijnenbelt: “Until now we at Arcadis made Excel and Mathcad sheets available with the reason to ensure that all engineers had the same working method to do calculations. But with the introduction of Python we went up to a whole new level: now we calculate a cloud of possible outcomes to find the best one. It also allows us to make a user interface for the tools, where results are presented visually for everyone to use.” This way of working gives more opportunities to find optimal solutions.

Tjeerd Hermsen likes Python because you can command other software and automate tasks, he explains ”we extract cone penetration test (CPT) data stored in Excels sheets and automatically make D-Foundations (geotechnical software) model from it”

## Digital Building Blocks
I observed that the common approach to building scalable software and cooperating with other specialists is to think in digital building blocks that can be interconnected. This make the process versatile and scalable. Some of the benefits of using the building block approach are:

- You can quickly build code by utilizing someone else’s work.
- It enables people to share knowledge in the form of code.
- It makes it easier to replace parts of your code.
- It makes growing the code manageable, as each block has a specific function.

“I like it when you can use the work of others. With fewer people you can make more applications if you have a collection of digital building blocks that you can connect” says Johan Tuls. That is also a good reason why people are using Python, explains Van Giessen: “Python is based on digital building blocks, and there are many available for free, such as libraries for numerical calculus or data science”.

### Creating new building blocks
Companies are also investing in making their own blocks. “Large software products try to provide a total solution; however, they are not always flexible enough to work efficiently. That is why we are transferring the expertise we have into our own software tools, that add to the existing software and which we can make available to further valorise knowledge”, tells Kelvin Roovers.

> “Parametric design will cover a much larger part of the work. In the future you will have modular systems with an application for each part of the construction. The engineer will create, connect,  and validate these apps instead of doing the calculations” - Nynke ter Heide, Vidabo

According to Johan Tuls, software development will have a big impact on construction companies. “Construction companies grow linearly, but programming will make it exponential. Companies will accumulate digital building blocks over time, which will be an important asset of the company. With these blocks you can make better applications faster and faster. This will lead to a new business model that has yet to be developed”.

## How to make your code accessible for everyone
I have observed that many talented people create models and analysis tools that have a big impact in their organization. As the adoption of their tools grow in the organisation, they fall victim to their own success. These tools are often too complex to be used by other people, and the creator does not have enough time to process all the requests from the organisation, which therefore becomes the bottleneck. Worse, what happens with that knowledge if they leave the organisation?

### Controlled distribution
What you want is to distribute the code in a controlled manner. This, however, can be quite challenging when choosing the wrong tools. “Excel does not have a version control. You can download the sheets from the company’s server, but how do you make sure everyone is using the latest version and that upgraded sheets are compatible for each application?”, says Nynke ter Heide. Kelvin Roovers shares a similar experience: “you don’t want to share code in Excel sheets. Everyone starts making their own modifications and it is impossible to keep track of the changes. It is better to keep you code externally, for example using Python”. “There are good solutions for code distribution among programmers when using Python, like GitLab”, says Kevin van Giessen.

### User interface required
The reality is that most people who can benefit from using these codes lack the programming skills necessary to understand them. Part of the solution is “a good user interface with visualisations of results. This makes the application accessible to everyone”, says Johan Tuls. It is useful to have a web-based application because version control is guaranteed, explains Kelvin Roovers. “When improving an application, all you have to do is put it online to make sure everyone works with the latest version right away.”

Web-based applications also have tremendous benefits for the end-users. “This allows different users to access a central point from anywhere, at any time, so they work with the same design or version of the information and make decisions together”, explains Kevin van Giessen. He adds, “It makes distribution of your code also very controlled; the administrator can give users permission to access different parts of it and remove it if desired”.

![Distribution of interface code](/uploads/distribution_of_interface_code_4839e53a6c.png)

Personally, I think technical people can be very critical about their work and think that it is not ready to be used by others; that there is still too much to improve. This is probably true. However, the solution is not to improve the code by yourself, but to make it available to others with a good user interface. You want people to use your software and give you feedback. This is the best way to truly understand what needs to be improved so that people can use it. It could be anything from technical features to greater managerial awareness. The shorter the feedback loop, the more organically your software grows in the organization, and the more likely people will use it.

## Why are engineers using VIKTOR?

### Toolbox
Kevin van Giessen explains: “VIKTOR is an application development platform to build professional web-based applications with Python. It’s easy to use; it’s like having a digital building block toolbox to create your own engineering applications. You can integrate with other engineering software, make user interfaces, create 3D models, use map views, perform optimisations and visualize results. This gives engineers the opportunity to become a professional software developer: the engineer developer. Kevin continues, “By enabling the engineer to build user-friendly software applications, knowledge is turned into an asset that can be distributed within and outside the organisation.”

> “Distribution is one of the biggest advantages of VIKTOR applications: you put it online and everyone can use it.” - Kelvin Roovers, BESIX

### Sharable application
Nynke ter Heide adds “Having Python code is different from an application that you can share with your colleagues”. She continues: “Making a Python script is nice for a proof of concept, but with the VIKTOR platform your code shifts to another level. It’s a way to create applications that everyone can use.”

### Unity
Tjeerd Hermsen: “Colleagues started sharing Python scripts while not all using the same version of the required packages, which made the scripts unusable. A lot of time is wasted trying to find and fix such problems. “The solution was to create a VIKTOR application. He explains:” The VIKTOR application ensures that all users are working with the same version of the external Python package. In addition, the Excel files that are used as input for the calculation are used, centralised in the database and they do not have to go back and forth between colleagues.

> “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, Sweco

### User-friendly
Kelvin Roovers comments: “What I like is that you can program complex applications with a user-friendly interface and easily present results through different visualisations”. “VIKTOR is also interesting for simple applications. There are many Excel files in a company that can be easily converted into a professional application with version control, user management system and visualizations. It is more user-friendly than a multi-sheet Excel file, and you can perform different calculations to find the best solution, ”says Nynke ter Heide. “As a freelancer, I like to be at the beginning of developments. I regularly see that my customers are enthusiastic about my proof of concepts, but that it is challenging to put them into production in the organization. VIKTOR can help meet this challenge and turn concepts into applications, ” she adds.

### Web-based and automated
Johan Tuls notes that he wanted to “create and host a web-based application; In the perception of management, however, this differs from the main field of work of the engineer and the company. A partnership with VIKTOR has reduced or overcome this risk ”. Peter Konijnenbelt says: “The management and engineers are very positive about VIKTOR and the results we have achieved in a short period of time”. He adds: “Their team has helped us a lot, you notice that they are much more involved with automation and have a different mindset. They help set up a better [parametric model](https://www.viktor.ai/parametric-design-software) and visualize the results so that we can compare different solutions." 

![VIKTOR application for designing subways under roads and railways (BAM)](/uploads/VIKTOR_application_for_designing_subways_under_roads_and_railways_BAM_2_79badeffb2.png)
*VIKTOR application for designing subways under roads and railways (BAM)*

## Want to know more?
This is the first of a series of articles about engineering and Python. The next articles will be published soon. We will talk about how you can make [parametric design tools](https://www.viktor.ai/parametric-design-software) using Python and common engineering software like Grasshopper, Dynamo, SCIA, RFEM and IDEA. To write these articles we interviewed engineers that make these kinds of tools on a daily base. Real pros!

Maybe you wonder why we are writing this. At VIKTOR we are on a mission to unleash the world’s real engineering potential. We are developing a platform where engineers can build their own web-based applications using Python. We work closely together with engineering, construction and manufacturing companies and help them boost their digital transformation. We would love to hear your feedback on our ideas, try out the platform, and help us create the perfect tools for you.

Creation of diverse professional software tools

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How are engineers creating professional software tools?

)In this article I will also share the thoughts of a handful experts, who were willing to be interviewed by Lisa de Kluijver and me and contributed with their experience. 

A special thanks to:

- Lieke Melsen – Assistant Professor Computation Hydrology at Wageningen University
- Thijs Damsma – Data Engineer at Van Oord
- Jacco Hoekstra – Professor CNS/ATM (Communication, Surveillance, Navigation / Air Traffic Management), and former Dean of the faculty of Aerospace Engineering, at Technical University Delft
- Johan Tuls – Structural Engineer at BAM Infraconsult
- Philip Vollet – Senior Data Engineer at KPMG and [Machine Learning](https://www.viktor.ai/blog/40/artificial-intelligence-machine-learning-engineering-construction) and Natural Language Processing (NLP) Specialist
- Maaike van Putten – IT trainer and developer at Bright Boost

This is part of a series of articles about engineering and Python. Each time we will go deeper into engineering content and talk about solving specific problems. Other articles on this subject are:

- [How are engineerings creating professional software tools?](https://www.viktor.ai/blog/18/digital-transformation-python-BIM-data-analysis--artificial-intelligence)
- [Parametric design in the cloud with Grasshopper](https://www.viktor.ai/blog/13/parametric-design-python-grasshopper-excel)
- [Automating RFEM model generation with Python in a web application](https://www.viktor.ai/blog/9/web-application-automation-python-RFEM)
- [How to make an IDEA StatiCa Concrete model with Python](https://www.viktor.ai/blog/8/web-application-python-IDEA-StatiCa-Concrete)
- [Combine the power of Dynamo and Python in the cloud for easy sharing and accessibility](https://www.viktor.ai/blog/32/parametric-design-web-application-python-dynamo-real-estate)
- [How to integrate a PLAXIS model into a cloud-based parametric engineering tool with a few lines of Python code](https://www.viktor.ai/blog/34/integration-plaxis-python-parametricdesign) 
- [Automated Pile Driveability analysis with GRLWEAP and Python](https://www.viktor.ai/blog/22/parametric-design-python-GRLWEAP-pile-driveability)
- [Using Python to create parametric SCIA models in the cloud](https://www.viktor.ai/blog/10/parametric-design-python-SCIA)
- [An application with custom Python scripts to save time and reduce errors](https://www.viktor.ai/blog/27/web-application-python-D-foundations-Excel)

## Boosting your digital transformation

### The frustration of the iteration
Eight years ago, I graduated from Aerospace Engineering at the University of Technology Delft. During my study I used all kinds of parametric design models, advanced analysis, and optimization techniques. When I started working as a Structural Engineer, I was disappointed: there was never time, budget, and willingness to create professional software tools that could make a big difference in the long term.

Frustrated by the large amount of boring and repetitive tasks of a typical engineering project, I went on making software tools myself, using project hours. This was a little risk-taking and it felt a bit clandestine. I was supposed to just update the models and reports, but it seemed that no one cared as long I was meeting the deadlines. I never regret this decision, as those tools enabled me to react more quickly to the many design changes in a project every time.

### My Python toolbox

It took me a while before I discovered the best programming language to do this. At university, I learned to use Matlab; however, not every engineering company I worked for could afford those expensive licenses. Frustrated by the limitation of my Excel sheets I decided to give it a boost by learning Visual Basic (VBA). What a bad choice. I wish that someone had told me: use Python!

With time, I had a small library with codes. It was like having a box with digital building blocks that I could connect and combine to solve a specific problem, making it easier and quicker to make those programs each time. The advantages of having a software library were obvious, but the question remaind: Why were the companies for whom I was working not building their own libraries?

### Going beyond the project system

It took me some time to understand. Many companies work project-based, and that was exactly the problem. Everything needs to be done between the scope, budget, and limitations of a project. This project-based model does not stimulate creating software as a company, that can later be used in several other projects as well. Due the lack of good software, design changes need to be done individually by each discipline, models are updated manually, and there is a lot of (slow) communication. Therefore, each change has a significant impact on the progress. I call this the sawtooth effect (see figure).

![Graph of the sawtooth effect](/uploads/The_sawtooth_effect_92f0e4b302.png)

### Building digital assets

Starting to build custom software tools as a company requires a change in mentality. It is investing upfront and benefiting later, which may seem risky. Making a proper software tool from scratch is risky as well and can require a huge effort at the beginning of the project. However, when done properly, progress can go exponentially and calculating and reporting a design change can become a matter of minutes (see figure).

At the beginning, progress is hard to track, which makes people nervous. I think this is a big reason why many companies are not taking the first step to creating custom software for their projects. The solution is therefore investing in digital building blocks. Once you have a few of those in your possesion,  you can reutilize and connect them to quickly make software applications and benefit immediately. It is clear: Digital building blocks are assets for the company, that everyone can use, and provide a long-term benefit.

> "Construction companies grow linearly, but programming their own building blocks makes it exponential. Programming building blocks is like building up capital. Each time you can make more, better, quicker and cheaper software applications, allowing you to make a big step forward." - Johan Tuls, BAM


## Some background info about Python

Python was created by Guido van Rossum and first released in the beginning of the nineties. The aim was to help programmers write clear, logical code for both small and large-scale projects. That is exactly the reason Python has grown as big as it is now.

> "Python is the future because it is a lingua franca. It transcends all platforms and domains. You can 
use it for infinitely different software applications. This makes Python unique." - Jacco Hoekstra, Technical University Delft

![Graph_Popularity of Programming Language.svg](https://cms.viktor.ai/uploads/Graph_Popularity_of_Programming_Language_af37efc9c6.svg)


To sum it up, these are the most important reasons for why Python has become so popular:

- **It is free and easy to learn!** Out of all programming languages it is probably the one that resembles English most, meaning you can go from thought to code very fast and intuitive.
- **It is not only about the language.** It is also an amazing open and accessible world of knowledge and available resources.
- **You can do anything with Python**, from simple maths to scientific calculations on a supercomputer, including Data Science, Machine Learning, creating web-based applications, and much more.
- **It is very scalable** and suitable for working together with other people, even from different disciplines. 

With Python, you can start small and slowly build up a digital empire. Do you not believe me? Google, Facebook, Instagram, Spotify, and Netflix; they all use Python as well! Just Google it ;).

## Digital Building Blocks
I noticed that the common approach to build scalable software and cooperate with other specialists is literally thinking in digital building blocks that can be connected to each other. This make the process versatile and scalable. 

Some benefits of using this building block approach are:

- You can build code fast by utilizing someone else's work! No starting from scratch.
- It enables people to share knowledge in the form of code!
- It makes it easier to replace parts of your code!
- It makes growing the code more controllable, as each block has a specific function!

This approach started in the software development community, with object-oriented programming and packages you could use to make your own software tools. Nowadays, it is becoming more popular in Engineering, Data Science, Architecture, and the Scientific Community as well.

Anything you can connect and command can be seen as a building block. It could be from a simple script, from one of the many free Python packages, or from FEM software.

## Objects: The building blocks of Python

Python is object-oriented. This allows you to break down your software into small problems (we call them objects) that you an then solve seperately, one object at a time. It is like building something large out of smaller components. This is a good match since it is very similar to how I, as an engineer, look at physical objects that have to be designed, built and maintained.

### Object creation

To create an object, you need to define a class. A class is a template for creating objects on which you are able to define its' behaviour and properties. A class can be used to make as many objects as you need. The great thing is that you can use properties of different objects for other calculations or for creating a ‘larger’ object as well. For example, you can create many beam objects, and then use their mass and stiffness properties to calculate the deflection in the bridge object.

### Free information flow

Information between objects can flow very freely. This is totally different from scripts typically made when using Visual Basic, Matlab or FEM packages. Here, the code runs top-down, meaning that changing something in the code will affect everything beneath it. This is like playing Jenga. The more complex it gets, the greater the chances become that it will collapse. With Python however, this problem does not exist.

In general, you can see objects as digital building blocks for making a larger software program. Allowing different specialists to build, maintain and improve their objects, and share it with the rest of the world to make something even more awesome!

## Free building blocks
The Python Package Index (PyPI) has 243,692 packages you can use for free! Most are not self-standing software, but building blocks for creating larger software tools. There are packages for visualizations, Machine Learning, Data Science, numerical calculus, and much more. Their quality is very high, so use them well and build your code fast! 

For example: 
- Numpy can be used to do all kind of matrix operations. Its functionalities are comparable to MATLAB. 
- Pandas helps you manipulate and analyse large sets of data without having to learn a specialized data-processing language. 
- PyTorch enables you to use machine learning without being a specialist. 

Which ones do you use the most?

> "There is a democratization of knowledge. It has become easier to use people’s tools and get insight into other disciplines thanks to the many available software packages." - Thijs Damsma, Van Oord

## External software is just another block

Quite often I hear that engineers are facing the limits of the standard software packages they use and this is leading to cause a change in mentality. Nowadays, standard software packages are not considered to be the total solution anymore. These software packages are just part of a greater process and engineers are now searching for connectivity.

These days, a large number of external software packages can also be commanded with Python. This is very powerful, as it enables you to use them like any other digital building block in your code. For example, you can combine a cost model made in Excel with a structural calculation to find the cheapest solution that satisfies the structural requirements. This can also be done with other tools, such as Grasshopper, Dynamo, SCIA, Plaxis, Diana, Excel, ANSYS and Deltares D-Series.

![External software packages that can be commanded with Python](/uploads/External_software_packages_that_can_be_commanded_with_Python_f270df6020.png)

## What’s next?

### Knowledge distribution
As an engineering community we still have a great challenge: the distribution of knowledge. What do you think is the best way of distributing digital building blocks and making knowledge available to others? I would like to hear your opinion about this topic, so don't hesitate to contact me!

Personally, I think there are two groups: the programmer, who can read, understand, and use a code; and the end-user who cannot program, but is going to use the tool. 

For the first group, good distribution channels are still missing. As a result, many of these specialists are programming the same theories or creating programs for solving the same problems over and over again.

> "We lose enormous amounts of time by programming the same models. If there was a central place where these models where available, we could invest that time in going forward."  - Lieke Melsen, Wageningen University

### Marketplaces for software applications

I believe soon there will be marketplaces where specialist can offer the software applications they made, so they can be used as digital building blocks for solving larger or more specific problems. There should be a financial compensation, such that companies and freelancers see this as an investment, and the creation of specific engineering tools is stimulated. If you are interested in this marketplace, let me know as well!

### Additional challenges

For the second group, the ones that cannot read or write code, another solution must be found. I am a strong believer in user interfaces and online software applications. 

> “A big benefit of web-based applications is that the different disciplines have access to a common environment and always can make decisions based on the latest version of the information.” - Philip Vollet, KPMG

## Want to know more?

This is the first of a series of articles about engineering and Python. We will talk about how you can make professional engineering applications that everyone can use, as well as on how you can make [parametric design tools](https://www.viktor.ai/blog/46/parametric-design-cloud-engineering-construction) using Python and common engineering software like Grasshopper, Dynamo, SCIA, RFEM and IDEA. To write these articles we interviewed engineers that make these kinds of tools on a daily base. Real pros!

**Stay tuned! Follow us on LinkedIn, so you don't miss anything.**

Maybe you wonder why we are writing this. VIKTOR is on a mission to unleash the world’s real engineering potential. We are developing a platform where engineers can build their own web-based applications using Python. We work closely together with engineering, construction and manufacturing companies and help them boost their digital transformation. We would love to hear your feedback on our ideas, try out the platform, and help us create the perfect tools that enables you to:

AUTOMATE THE BORING. ENGINEER THE AWESOME!

If you are interested in [developing your own parametric design tools](https://www.viktor.ai/parametric-design-software), make sure to [check out our solutions page](https://www.viktor.ai/parametric-design-software).


Accelerate your digital transformation using Python

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## Confusing structural models

A structural model may vary between its' different subsections. Implementing these variations makes the design process very tedious and time consuming. Besides this, the following problems and questions arise:

- How can the results of a batch calculation of for example 100 tunnel sections be visualised effectively?
- How can the results obtained from different software programmes, in this case SCIA Engineer and IDEA StatiCa, be combined in one clear visualisation?
- What is the amount of effort required to update all individual models whenever a global change in geometry occurs (e.g. a wider tunnel)?

## Parametric design methods

### Automatic generation of structural models

On the VIKTOR platform, an application has been developed that enables the automatic design of a tunnel. Within this application, global parameters can easily be varied, such as the height of the tunnel, thickness of the walls, applied load, and more. Due to the variation in depth along the tunnel, the design is split into subsections (tunnel slices), enabling local overruling of deviations. An integration between the online application and SCIA has been established such that the user can start a (batch) analysis with a single button. The result of this analysis is sent back to VIKTOR and shown in an insightful visualisation. Moreover, the results are stored automatically within the application, making it possible to retrieve and visualise earlier obtained results as well. With this visualisation, the critical locations within the structure can quickly be determined.

![Automatic modelling and analysis of a tunnel consisting of hundreds of subsections.png](/uploads/Automatic_modelling_and_analysis_of_a_tunnel_consisting_of_hundreds_of_subsections_dc3bc918f7.png)

*Automatic modelling and analysis of a tunnel with parametric design methods through an integration with SCIA on the VIKTOR platform*

### Automatic testing of reinforcements

Now that the critical internal forces are known, they can be compared to the capacity of the reinforcement to see whether this reinforcement suffices. The design of the reinforcement is done in a similar way as the tunnel geometry, using [parametric inputs](https://www.viktor.ai/blog/46/parametric-design-cloud-engineering-construction). Each unique reinforced cross-section is tested through an integration with IDEA StatiCa. Similar to the SCIA (batch) analysis, the user is able to start a (batch) analysis in IDEA after which the results are returned and stored on the VIKTOR platform. At this point, all data is centralised in the application and can be combined and visualised in almost any desired way. In the example below, the internal forces (in red and blue) of a tunnel cross-section are shown, along with the reinforcement capacity (in dark and light green).

![The internal forces of a tunnel cross-section and the reinforcement capacity.png](/uploads/The_internal_forces_of_a_tunnel_cross_section_and_the_reinforcement_capacity_f8dc155163.png)

*The internal forces (red/blue) of a tunnel cross-section with the reinforcement capacity (dark green/light green)*

## The benefits of parametric design

### Cost reduction

The development of this application ran parallel to the design process of the tunnel. Initially, the focus was placed on delivering a minimum viable product of which the preliminary design could be simplified and sped up. Now, the amount of tedious and time consuming tasks an engineer would have to perform for each tunnel slice design has significantly been reduced. Also the chance of manual (human) errors has almost completely been mitigated. The time reduction enables faster iteration of designs with more detail, resulting in a tremendous reduction of material cost. All of that for only 500 hours of development time!

### Batch analysis

After making the necessary changes to the preliminary model, the changes have been incorporated in the application code such that it is ready for the detail design phase. This phase cost another 500 hours of development time and with the expansion it was also made possible to do the batch analyses of multiple tunnel slices. Thanks to this, with just a single button click, a large part of the tunnel could be analysed during the night.

### Time-savings

Last but not least, thanks to the [parametric](https://www.viktor.ai/blog/46/parametric-design-cloud-engineering-construction) setup, last-minute design changes were easily applied and the complete tunnel was re-analysed in no time. This results in huge time savings for the engineer.

## Potential and future

We can hear you thinking, “What use does the application have when the tunnel is designed completely? Can the code-base now just be flushed down the toilet?” Definitely not! During the development process of an application, features are built with reusability in mind. They are created as “generic” as possible, which means that they may be used in another application as 'digital builiding blocks, in a plug-and-play way.

Besides the integrations with SCIA Engineer and IDEA StatiCa, the application has potential to incorporate an analysis of the foundation piles using an integration with, for example, D-Foundations. Such an integration is quite standard and can be created as a generic feature as described above, making it easy to reuse. In fact, this feature readily exists in other applications and can therefore fairly easy be implemented in this application (meaning no 500 hours development time needed)!

See how you can [create your own parametric design tools for automation and optimization](https://www.viktor.ai/parametric-design-software) here.



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Parametric design for automated tunnel modelling and analysis

## Why a hackathon?

Knowledge development is one reason for the IB decided to organize a hackathon. Addiotionally, besides getting acquainted with programming hands-on, they also wanted to experience what it is like working with VIKTOR. 

As some structural engineers, such as Lester Neijzing, are currenlty part of a pilot project by the Gemeente Amsterdam in which VIKTOR is also being used, some are already a bit familiar with the platform. Now, the hackathon offers a great opportunity for the other structural engineers to get introduced to VIKTOR as well, and for those who are already acquainted to improve their programming skills. 

> "Participating in the hackathon is a fun way to get to know VIKTOR and learn more about programming with Python." - Lester Neijzing

![blog_hackathon_amsterdam](https://cms.viktor.ai/uploads/blog_hackathon_amsterdam_ae737a634c.jpg)

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## Quay wall applications

During the two-day hackathon, three teams used Python to develop applications on the VIKTOR platform. All of the apps are to some extend related to the parametric design application that Amsterdam is currenlty developing for the renovation of their quay walls. 

The stakes were high during the event: In total, three apps were developed, but only one could be the winner and would thus be further developed eventually. Next, each app will be described in more detail.

![kademuur renoveren.jpg](https://cms.viktor.ai/uploads/kademuur_renoveren_7f4840c190.jpg)

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### Application 1

Currently, structural engineers at the IB gather data about the state of quay walls in Excel sheets. Even though this process works well for the people who work with these sheets on a daily basis, it is difficult for other to interpret the data. For that reason, team 1 developed an application to make this data more transparent and easily adjustable. 

Of course, the IB could ask their GIS-department to visualize their data for them, but even then it would still remain a static process. With this application, engineers can visualize and adjust project data using different colors on a graphical map themselves. This also helps make it easier to explain to others why the work of the structural engineers is important and how they, for example, estimate workload and project duration.

### Application 2

Justl ike team 1, team 2 also worked on an application for the visualization of project data. With their app, it becomes easier and faster to project geometries on a map view and translate these to the calculation program SCIA, and after that to Word to generate downloadable reports.

Because this app includes a rather far-reaching integration, it was not unfortunately yet at a usable level at the end of the hackathon. On the flip side, this does mean that there is still a lot of room to improve and expand the tool. 

### Application 3

Opposing team 1 and 2, team 3 developed an application not aimed at the visualization of project data, but for the automated design and modelling of foundation piles, channels, and the surrounding soil. For this, the team integrated an Excel calculation sheet with an export to the calculation program SCIA to their VIKTOR application.

Just like with team 2's application, there was still some work to be done before team 3's app was ready to be used on real projects. However, the results were promising so far and made for an interesting concept for further developments.

## Choosing a winner

Based on the judge's critiques, a winner was chosen at the end of the second hackathon day: Application 1. Where the other apps mainly focused on integrating with pre-existing calculation software, application 1 stood out due to its unique use of data-processing and visualization - a nice use of VIKTOR that had not been done that often yet. 

> "I think it was this tool that won the hackathon because the rough outlines were already finished - the application worked in such a way that it produced the results that we were looking for. According to the jury, it was a unique tool, especially thanks to the maps and the visualizations." - Lester Neijzing

## Putting the pieces together

According to team 1 participants Rick and Lester, even though they were part of the same team, they were constantly programming completely different parts of the application. Only within the last few hours of the hackathon, when they began putting all the parts together, it felt like "it magically turned into a working product".

The application consists of several different parts, For example, it shows a graphical map and Excel sheet with risk drilling and assessments of quay walls, using different colors to indicate wether a wall is still sufficient or needs reinforcement. Team 1: "The map view really makes the data come to life". Within the application, it is also possible to adjust source data, link it immediately back to Excel (or the other way around), and export overview reports.

> "We knew what our vision was but did not yet realize how incredible it would be until we put everything together and it actually started working the way we envisioned." - Rick Voortman

![hackathon artikel 2.jpg](https://cms.viktor.ai/uploads/hackathon_artikel_2_b764fb081e.jpg)


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## What's next?

Following the hackathon, two things are certain:

1. The further development of team 1's winning application
2. A second edition of the hackathon

**Are you also interested in organizing a hackathon with your organization? Don't hesitate to contact us at contact@viktor.ai!**



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Structural engineers at the engineering firm of the municipality of Amsterdam organized a hackathon to boost their programming skills and learn about building apps with VIKTOR.

VIKTOR Blog

Hackathon stimulates knowledge development