0:00 Such a great event. So yeah, I’m I’m Matthew Voda. I’m a director at Arab and I’m an Arab fellow in computational design. To my my surprise actually they they promoted me in in that sense and I’m going to give you engineers perspective of where we are as a company. So to keep it a little bit interactive by show of hands who does who knows Arab as a company?

0:21 Okay. So okay I I’ll skip to all that then I’ll tell you only some stuff that u that you might not know. So so we are international firm about 19,000 employees but what separates us from what the competition is that we are employee owned. So in 1970 our partners said okay we put the shares in a in a foundation and the benefactors of the foundations are employees that’s me and all the other ones and a number of good good causes that we believe in and what we’ve learned over the years is that if you’re an employee owned firm then what keeps you together right what keeps unity and that’s branding.

1:04 So we tend not to buy other firms. We tend to grow organically. But particularly what binds us is to drive for quality in each and every project that we do. Right. And well that’s been successful. We’ve been growing and and growth is not a a particular objective of us but we’ve been growing organically for the last 75 years and now we’ve we’re at 19,000 people across the globe and and we’re a multi-disiplinary firm.

1:30 So we like the we like to be outcome focused, right? Right? So, we’re not structural engineers that design a structural beam, but we want to think about, okay, what’s the structural engineer? What’s the beam for? How does the man mechanical services go through it? What’s the objective? Which people are occupying it? And that’s that’s our field of play. The first project we used computational design was probably our signature project was a Sydney Opera House, right?

25:36 So we were a big fan of you know simple calculations hand calculations but then we we helped Judson to win the competition for the opera house and we just couldn’t fathom to do this by hand. And we use computer times. Now we spent 200 computational hours on this project and 400,000 manual hours to design this project. I don’t think if we did it now that would be the same equation.

Yeah, probably the other way around. And now with AI the 400,000 we wouldn’t we wouldn’t get there. So I’m an Arab fellow and I’ve been working in the industry now for for 20 plus years and I have two parts of my career. So I’m a structure engineer by training and I like to do scripting when I was when I graduated and that’s the reason why I came to Arab because they did buildings that I couldn’t do by hand anymore and it needed scripting.

And that was the first part of my career why I as a structure engineer I like big numbers like big structures and but I call them now the iconic or landmark buildings right and I moved to the east Asia Australia worked a lot there this is a Singapore sports hub which is my biggest project it’s largest span structure in the world and we needed computers to actually design all that stuff similar to the opera house really right because to do all these calculations by hand we just didn’t have the time then 10 years ago I I got a little girl.

I wanted to give her grandparents. So I moved back to the Netherlands and that was also a bit of a career shift. So I started more being involved in the lighthouse projects. So each project I take on or like to take on I want to up the benchmark what we can do on integrated sustainable design. And I think computational design and I saw it in most presentations actually can help with that.

You know how to shape a better world which is actually our our our mission statement right so I’m not going to talk today I’m not going to talk about FAM for additive or advanced manufacturing I’m going to talk about computational design right and first I’m going to talk about computational and how we see it in Arab and I’ll when when I when we drive for innovation in the computational techniques and you know I’ve saw all these really cool presentations I’m totally inspired at the moment but it’s all about efficiency accuracy and particularly also validation right so when I look at the the recent years how we are moving through these stages right first we had simulation based driven design that’s what we did in the opera house and what I did on sportsub right so in sportsub it was finite element analysis and we you know and and and that’s nice when you talk about design it’s it’s you you kind of look at okay what does the client want what are the ambitions what are the constraints, right?

And when you know it, you actually make a design hypothesis in the traditional way. So you say, okay, this is this is an idea, an option. I work with architects a lot. Often those options come by the architects, right? They give them to us, right? And then you make a model and you run your CFD and you find your conclusions and then you if you’re happy, you’re in paradise and move to the next stage.

If you’re unhappy, you well, you might think about, okay, does it work at all? Are the ambitions too high or can we can we do it? If that’s okay, then you do another and you run cyclically and it’s iterative and it’s a lot of pain before you get to paradise. Okay. Then then you know then this was around the time when the architects they learned how to do 3D modeling right and they hit these engineers me with a lot of these 3D models.

Can we do this? Can we do that? Can we do that? And basically we couldn’t keep up, right? So what’s I started doing was connecting these geometrical models through parametric design and Grasshopper is a great tool. So we totally use it and love it. But there were other tools before that. To keep up with it, right? So we built parametric models. So not so we didn’t look at one solution anymore, but we could look at a solution space.

You know, within these constraints, this is the optimal result. This is the minimum steel tonnage or this is the one you could do or you could build, right? And and by doing that we could keep up with these these the these assumptions but really the design process itself didn’t change. Yeah, there was still an assumption right a a and and it wasn’t a design but an algorithmic assumption right and within the algorithms we could look at the solution space and keep up with it to get to paradise.

33:33 The thing is if you create a solution space not all if you have one single model running in an F fea analysis you know it’s the result is validated right because you have an engineer looked at it and it checked it off if you create thousand or 100 or thousand and you come to an optimal result you still need to validate it right but what I what we’ve learned through the parametric process we’re kind of certain it works right and we’re kind of certain to be happy so we move we we we present the optim more sell to a client and then if we sell it then we validate it right so that’s the process but you know times moves on we have to be quicker and we have to be cheaper and more lean and stuff and now we have the machine learning right and in a way that this this changes quite quite a bit so now we take the data right I’ve seen examples where data was taken from external sources so that’s this is this is the process now we take the data we train a model we predict an outcome but when I have that outcome I’m not quite sure that I can present it to an external client.

Right? So now what I do is I validate it the outcome. I I validate my my my prediction before I go to the client and if if it’s it’s if it’s happy I and the client likes it as well, we get to paradise again, right? But the the validation part actually takes longer almost than the using of the machine learning itself. And that’s a bit of a problem, right?

So what what we started to doing is actually to merge merge those those processes itself right and in a multi-disiplinary environment where you look at you know environmental analysis wind daylight comfort energy embodied carbon all these kind of constraints. There’s a lot of different processes we we’re running simultaneously. But we what we what we said is if we okay if we now use our parametric process to generate synthetic data, we can trust that database and we kind of can trust that machine machine learn model as well.

And then at the same time if we use a parametric model as input in the machine learning train model we can again train get a big solution space and we can understand the whole the whole system at large which will give us the confidence to go to our client then validate it if it’s been sold and then get to paradise very quickly. Yeah. So that’s about computational and this is what we’re doing for a lot of workflows.

Right. So one of the things that we are very comfortable in in in in the Dutch environment is we train the machine learning on wind comfort, right? See if the analysis takes a long time for our per model, right? So if if if if I’m at the stage where I want to influence an architect to maybe change a tower shape or you know or maybe build two towers instead of one, my potential solution space is very very large.

I’m talking about thousands of options. If I run the CFD on all those thousands of options, cannot do it. With machine learning, I can and I can keep up with it. And then I can mix the wind comfort with structural analysis or settlement analysis. And suddenly there’s a different ballgame happening. And we’re starting doing that for you know for wind comfort. From wind comfort we’re now doing thermal comfort blast analysis takes us even longer to come up to have one calculation on in in a traditional way.

One one column with one blast load takes us about you know in computation cost about €6,000. Yeah. Now we can do it in seconds totally unlocking that that that solution space to our clients early stage. Yeah. And that that computational power now leads us to design for more outcome based solutions. So we’re starting doing behavioral simulations. So can we design for happiness, right? Instead of anything else and that’s the direction we’re we’re taking when it comes to computation.

Now we park that for a minute. If you’re up for it, I want to talk about design. And that’s probably what sets us the AEC industry apart maybe from the aerospace industry a little bit and for sure from the the very specialized prosthetics industry is that in in our case we have many different stakeholders. There’s not one client actually making the decisions, right? So design as we see it is probably a little bit different than some of the other industries are seeing it.

So I would just want to test with you. I’m showing you some images and maybe somebody wants to give us one word what they see when they look at this image. Tenzaggity. Good word. Somebody else. Sorry. Balance. Balance. Very nice. Yeah. Well, for me it’s simplicity, right? When when you do a design, you try to find the most simple answer to a certain problem. And I cannot make this within you know for a transgity structure keeping balance I cannot simplify this any further.

So in my view this is a really good design to a particular constraint and as a as a computational designer particularly I like it because it’s also algorithmic. Yeah I can code this quite easily right and I can optimize it and you know there’s stuff to do with it. This is Teo Jonce. He’s a Dutch artist and he devoted well big part of his career making beach animals and he he made them always using PVC and a certain connection mechanics and his animals became more and more complex over the years and he he let them running over the on the beach.

One word fun. Fun. Good word. Good word. Yeah, for me it’s complexity. Yeah. And as a computational designer, I like algorithmic complexity because anything that’s not codable and this animal is almost totally codable, right? It’s a lot of code to actually do the the one exemption unless the exemption is actually the rule, but then it’s algorithmic again, right? And I like looking for these ones in in my designs and it will help it will help our database, it will help our solutions, etc.

And this one word very good for me and this this is important. It’s about choice. So when you live when you work in a multi- stakeholder environment with a lot of different perspectives, we have to realize that design is also always about choice. Right? This is our stand at the Provvada trade fair. 26,000 people came there. We talked about stuff that we were doing and the last year we outsourced the design of the stand and I was totally unhappy because this the stand smelled after a while the heat curved all the panels and we look pretty awful.

So this year I said okay we’re going to design it because but we we designed it and the our market marketing people they said okay you have to stick within the corporate colors and I said okay what are the corporate colors? Well they’re red and they’re white. And I asked Simona Colon, one of one of our best designers, and she she made one little sketch and she said, “Okay, I choose red.” And we totally took it, right?

Red chairs, red coffee. We had red biscuits, red sweets, strawberries, etc., etc. And even our, people who were serving the coffee were made red as well. Loved it. But it’s a choice. We could should have could have chosen white or any other thing. Yeah. And because it’s about choice and that’s also you know as computational designers we try to find the optimum right and as a structure engineer we saw an example and you know you if it’s a single criteria optimization maybe two criteria optimization you can find a optimum but in a world where you have a contractor and architect and the owner and the end user who’s not even at the table and the government there’s a lot of different perspectives so the optimum doesn’t exist.

It’s always trying to find the best fit compromise solution, right? The platform where everybody’s happy. And when thinking about it in a computational design world, and this is something we don’t do yet enough, I think in the AEC industry, why don’t we organize ourselves on these particular perspectives and say, okay, this pet fit compromise, you know, and this do we who knows the eeky guy model? Okay, not really well known.

So, I really love this model, right? So this is a Japanese model where they say well if you find something you love right scripting the world needs the outcomes of computational design what you be paid for well if you have good outcomes you’ll be paid for it and we need a million engineers and what you’re good at then you are at the eeky guy that’s that’s the job you really need right and that’s also what I like in in a in a you know a good project is always In my view, a good buildings project is also when you have an a a a a setup where the different perspectives can live mutually to each other and at the end of the project, everybody can write their own story and they’re all proud of it from their perspective because they found the icky guy, right?

If the architects gets too powerful, right, you get art. Yeah. If the engineers gets too powerful, well, you might get Moscow. Yeah. If the contractor gets too powerful, well, you get leaking. I don’t know. Yeah. So, but in the middle is where the the sweet stuff lies and finding that is something that we can do. And in in the A industry, in my view, finding that middle ground is is the objective.

So, when we use computational design, it’s not to find the optimum. It’s, you know, have a black box because nobody will trust the blackbox optimal solution. It’s actually finding a a method, a system, a platform, visualizations to bring all these different perspectives together into one well best fit compromise. Eeky guy design because if best fit compromise, if you tell your client, I’m going to give you the best fit compromise, they don’t like it.

So, I need another we need another word. And maybe the word is eeky guy, right? And we have to acknowledge and this has been said by many other presenters as well, right? We we’re living in interesting times, right? So in the building industry we have accelerated urbanization. In the Netherlands we need a million homes we think. Yeah. In the next 30 years and we cannot build them.

We don’t have have the space. We don’t have the materials. We don’t have the nitrogen capacity to do it right. And it leads to dense and complex environments. But if you add density right you lose daylight. Yeah. And you might you get more noise. So that’s that’s a trade-off. But at the same time we say well we want our buildings to be more healthy, more comfortable, less noisy, right?

So it’s actually it’s an exponentially complex problem that we need to solve. And then there’s sustainability, right? We want to use less materials or materials and we want to increase the energy performance of our buildings at the same time. Now, how can you navigate that increased complexity and find these different outcomes and at the same time because that’s another problem manage the risk for the client that they spend a lot of engineering money and don’t end up with a solution they can build you know and and that’s something I try to to to to to fix so I got two project examples one of them is is is seammens where we where we tried to do this so so this was a densification scheme where the AA architect made a reference design and that was a starting point for us and you know this this these are three existing buildings in the H in a quite complex location because here this is this is a residential area and the residents are quite vocal about anything that changes in the neighborhood and in the Netherlands they’re very when they’re very particularly when they’re very vocal they can stop any development happening yeah this is a train track a lot of noise problems very busy road tram line.

So it’s and there’s existing buildings, right? And the client timeless wanted to explore if if they could densify a particular site, adding a commercial area and adding residential area in a different tower block. And traditionally, I think, you know, it was it was a really good design if you look at it from a from a master planning perspective, right? You put a building block here. There’s this area.

This is the residential tower. It’s at the street and this we’re going to take and we build up it and then we put a commercial tower on. That reference design was done and then we were asked to put in different perspectives right environmental perspectives structural perspectives to that particular mix and we closely worked together with Timeless and Neo as a as a client in that guy model.

We took care of the engineering and ZDP was the architect. And then we said together, okay, what are then the different perspectives that we need to bring in, right? Gross floor area, sunlight, the sun on the park, particular sunlight on the neighboring free. Basically, we said they’re so focal, we don’t want to put them in the shade at all, right? So, it was a pretty important KPI to to move forward with.

Also, we were, you know, we were going to be constructing on a live site where people had to work at the same time. So constructibility was important, daylight for the residential equality, commercial as well, solar potential because you know we might want to do a energy neutral building because a lot of commercial clients they are promising that that they will going to occupy energy neutral buildings. We had to look at the noise from two roads and this is actually a train station.

So a lot of people actually passing our site as well. So wind comfort was also a very important KPI. Now these are nine different sets of KPIs all with totally different solution spaces right and good thing that we had we built this preact. So we actually used this and this was the first time we used it in a commercial environment. We said okay the wind comfort we can now predict.

So all the different options we can predict the wind and we’re quite comfortable that we’re going to be right and we tested it. We also because of the because of the the the train track metro track here if we would move the tower out the metro track would start to settle. Now in the Netherlands if you have a settling metro then you have a lot of conversations with the people that own the metro line and that can take years.

So we said okay that’s that’s another KPI we put into into the analysis as well. And then basically we started to explore the solution space. You know the client called this a lawn mower. You know, we made the different heights, different locations of both the office building and the residential building and then we built a parallel coordinate system to test all of them. So all the solutions for the office, all the solutions for the residential and then then they said to the architect okay now we start restart the design and we take all these different perspectives and see if we can find the best fit compromise and not only looking at master planning but also looking at all these other ones including settlement wind comfort daylight etc.

I won’t dwell on this a little bit and the outcome was totally different, right? So we one thing for the for the residential was was we we we found well we learned through this analysis that if we would put the residential building back, we didn’t need any deaf facads. So deaf facade is when you can’t open your can’t open your windows in your residential apartment. So pretty important KPI for the for the end user of the building.

And if we had to put it on the road, this this facade had to be deaf. If we put it on the rail, that facade had to be deaf. In the middle, it was fine. So it became a very important design decision that eventually led the architect to say, “Okay, you know, we’ll do it differently. We’ll make a nice square here and create a different different environment.

Same goes with the with the commercial tower which we moved in the back.” Actually, by moving this one back, the whole wind comfort at the back side improves significantly. Right. Creating a safe space and a happy space for the people to move daily from their from the station into the into the zone which made the government very happy. All right. So that’s one so that’s actually you know using computational design technique in a collaborative environment to decrease the risk and come up with a best fit compromise solution.

The other one and we’ve seen it as well computational design can sometimes surprise as well and that’s that’s another project I would like to share with you. It’s it’s the elements project. So this was a tender you know the government said okay I have a bit of land Mr. Developer if you come in miss developer actually if you come in in this case if you come in with with the best proposition right you’ll get the exclusive right to develop this piece this piece of land and 50 points were for sustainability and 40 points were for architecture 10 points were for the money they they bid for the particular property.

So it was a quality power tender where sustainability was as at par with the with the architecture. Now we set up this eeky guy model you know in a tender stage we had six weeks not a long time. So we said we keep it small we take a responsibility each for their own their their their own work and obviously designers make a lot of decisions. Some of them are implicit but here we said okay let before we start the design process itself let’s set up what we need to do because in the end you know a design is always a marriage between the boundary conditions the constraints and the ambitions right let’s do a parametric gener generative script we look at all the solutions do generate all the solutions we do the analysis and then look at it similar as we did to the seaman’s the seaman’s result but here We set very six six before we started this whole process.

We said okay we read the tender documents. We said okay how are we going to score this? How are we going to score the most points in the in the tender design? We said okay we’re going to set two KPIs for the building sustainability two for the neighborhood sustainability and two for the planet sustainability. Right? So, daylight, sunlight for the building, good wind conditions, green for the for the neighborhood, energy performance and material for the planet.

Now, this building was in the same neighborhood, the MSO crater, and the the tender before that was how project, which was a total timber tower, which we won as well. So, I thought this one we’re going to put on energy, and we kind of knew that we couldn’t afford a full timber tower on this particular location, right? So here we took 50%. Instead of 100% and we focused doing the first energy neutral timber residential energy neutral high-rise building in the Netherlands and then we and then we started looking okay what shapes could we do and that was nice about this particular tender any shape could any shape would be a we would be be able to do any shape according to the request of the of the government government.

That’s not always the case. So we were a lot of freedom of shape. We started to explore okay what shapes should we do and the government gave a reference design. So they said this is what we think what should be done. But looking at the KPIs we started looking at different options right in an algorithmic way. And what we found was if we want to do optimal daylight in the in the plint building we want to move and to the for the neighbors we want to move the building as as far to the tip as we could could get it.

Then if we want to be able to generate enough energy, it actually started to pull the pull the east and the west facade apart making a very well very fat building with a lot of facade on the east and west side where you have energy in the morning and in the evening when most residents are using the energy as well. Yeah. But what then what the algorithm found and these are just some some snapshots of the algorithm, right?

Well, then what the algorithm found, it started to actually shave it here and there because what it found was when you do a building like that, the wind hits it and you get very nasty wind conditions on the south southwest facade and start to shave it off. So the wind could actually find its way at this level instead of hitting this tip. We still hit it a little bit, but it’s this was actually the best fit compromise solution.

And this was a a last algorithm that we ran. So we so instead of taking the you know traditional hypothetical approach where we choose one design and then check it we developed a thousand and then looked at it and then and start started the choosing of the of the overall design as well. We talked about the wind. We tested it with a with a with a with a preact and later with a we validated it with a CFD.

We looked at the energy performance with a bespoke energy calculations and then and then we said okay you know okay we don’t put put timber anywhere let’s make these double height apartments and every second floor in the apartment itself we make in timber because then you don’t have the problems with acoustics or with fire which we thought was a very good solution at the time and meeting our carbon carbon requirements now these are literally the slides that I presented to the client now I who as an engineer I often do these type of competitions with architects.

This was the first time ever in 20 years that I got to present before the architect. Yeah. So I I presented exactly this and then the architect said, “Yeah, and we’re going to make a great building out of it.” and I I want to share this video with you to how the architect and the developer experienced this process where we didn’t do the you know we didn’t do the the traditional design process but we did the well I would say the computational design process.

Hopefully it works. It was quite difficult because it hadn’t been done before. We had the ingredients of sun, wind, water taking in consideration. Sustainability was the first thing to go by and afterwards architecture. But of course that brings up also discussions about what should a building be. It had to have had good daylight conditions, good energy performance. We wanted to make an energy neutral building, boost the biodiversity of the site itself.

We wanted to optimize the wind conditions. We wanted to prevent shadowing of the neighbors. And we wanted to have good materialization. This is how elements was born, but also how we tried to load it. And then the decision was being made to use parametric tools to define actually the process or the project. The biggest challenge we faced was to come up with an integrated design that provided a solution to all the sustainability requirements we set ourselves, provided aesthetically and pleasing building that was also functional and had a close business case.

What we did in the first phase, more of a classical approach into urbanism, looking at the context, shaping the volume within the building envelope, and we had a a stepping building that made the connection to the surroundings on one hand and then really established kind of a relationship with the tower to the surroundings. And the first results of kind of the parametric approach to me they were pretty amazing because it was the opposite than I expected.

The power of parametric design is that it involves all elements and maximize the experience people have in their own home and that contributes to more healthy living environments for people. In a traditional process, the architect takes a lead in coordination and comes up with a shape. Sustainability requirements are becoming much more important. So with the paradigm, our form follows sustainability. Also the design process itself changes where everybody is much more integrated involved with the overall shaping of the building.

You really have to look at it with an open mind and to see like what is the benefits of the solution being offered and there was a lot of good we saw in it but it’s also like humans against machine in a way something we learned from this unique process is that the role of the architect changes but he’s still very important for the process I think at the end of the day it’s a merging of of both of it.

It’s not the machine taking the control and like computer that is fed by parameters but it’s really kind of the interaction of urbanism typology and kind of learning from machines as well. You have to take a holistic approach to take a balanced view on what is the best overall solution for the building and exactly that is what we did on elements. It asked a lot from all parties involved Arab and Koshuk and also us because we had to make instead of one sketch design we had to make like thousands.

I’m actually thankful for two things. First thing is the open-mindedness of both the client and the architect in looking for a new way of exploring the best possible solution for this fantastic project. The other thing is the perseverance. It wasn’t easy and we clashed but particularly the client held on on the perceived quality that the building had to have and pushed us as far as we could go.

It was a small team but I think we came to know each other quite well. We made a lot of hours before coming to the final design. It became a friendship actually. It was a yeah a mind-blowing experience here because there was a obviously big role of Arab in the process. I really embraced it joining them as a team trying to make each other better and exploiting new ways.

So, I’m I’m super proud of obviously what we’re going to achieve and what we’re going to make energy neutral highrise in Amsterdam, which is unique. Yeah. So, we won the we won the tender and it we won it by by Yeah. You know, sometimes it’s close. This one wasn’t so close. Very happy with it and we’re now constructing it. The thing is which is important that we one of the learnings is, you know, we won the competition in the construction industry.

33:41 You win something and then it’s built a couple of years later and the world changes, right? So, we won this before the war. The the real estate market was at its peak. So with the decisions we made then we might not make him again because it you know it is from a materials point of view construction point of view a pretty complex building you know to do a cantal levered building a steel timber concrete hybrid structure.

34:03 So the and and we found that actually the double height the double height u spaces yeah they al also very very special right so but then again so I don’t think we would have made exactly the same decisions if we would have run the process itself now I do I do think this process looking at it taking into consideration all these different constraints powered by computational design because having them the the the trust and the valid valation to actually make these arguments up up front.

34:35 You know, early stage design has a lot of benefits. And then yeah, obviously we’re constructing it now and you know this was a six week weeks program and we’ve been working on this project two years after that. So all kudos to the engineer, one of the engineers that’s still working on it and making sure all the rebar gets into the right position and and make it done. So thank you for listening. For more information about CDFM events around the world, visit CDFAM.com. Thank you.