Why do we need simulations?

All right, I think we are live. So we're welcome to everyone, and especially to you, Emanuele. This is the inaugurate podcast slash live webinar Community Talk from Infrared City, and we are really, really excited to have you here. I'm gonna just share a couple of words from my side, and then we can just straight go to the conversation. I'm Angelos Cronis, I'm the CEO and co-founder of Infrared City, and this is essentially the first community talk we have. What we're trying to do with these talks is to bring together the people we think are most important in this field and discuss pressing issues of, you know, simulations, climate change, buildings, and all of these things that bother us every day, and also the reason why we're building Infrared City. So again, warm welcome to everyone who's watching us already live. We'll post this further on as a podcast. You'll also be able to see an overview of our chat on our website soon, and we'll do follow-ups for sure with questions and comments. So feel free to post your questions on the chat as we go, and comment on the social media channels as we said, and I'm gonna go straight to it. So, Emanuele, hi and welcome. Hi, Angelos, pleasure to meet you also in this format. Yeah, so I'll start with where we met, right? So I think we met, as we just discussed, in Łódź, in Poland, at EKD, right? Was that the first time we met? Yes, that was the first time, and then was fun enough we met in Chicago the week after, and since then I think we've met several times, and each time in a different country, so that's interesting. We'll try not to talk about the carbon footprint of, you know, going around the world talking about sustainability. I have said the joke enough times, it's actually not that funny. So, yeah, the first question I have for you, before we even start, is how do you drink your coffee? I mean, you're Italian, right? You definitely have preference. So how do you drink your coffee? Yes, I'm boiling most coffees in the area where I am. So I start with what is called, here where I am, right now in Dubai, Flat White, and they call me Two Finger Less, because I ask Flat White with less milk, Two Finger Less, so now they call me Two Finger Less. They call you Two Finger Less. That's awesome. So I also drink Flat White, but with oat milk, so I think they just call me vegan, even if I'm not. So that's that's out of the sort of like, way we can now dive deeper. So maybe you tell us a little bit about your background. I know you're like, you get more titles than I can, I can spell out. So like, maybe you tell us what it is that you're currently doing, and perhaps what like, you know, what you feel you should be like most proud of for for from your work? Sure, yes, yes. So first of all, I think our paths are very similar. We've been in different countries, and we try to learn from different contexts from different people. But it all began began for me in America, when I went for my PhD and later for my postdoc at the Lawrence Berkeley National Laboratories, where I was very lucky to be part of the energy plus development teams. And there I learned a little bit of coding, a little bit of thermodynamic, and we also had the chance to collaborate with major firms like Morophosis back in the days that were very popular, Renzo Piano for the New York Times, William McDonough with the Pasadena, NASA building, and so on. So that was my first exposure. And then I began to apply the learnings at different scale, getting much more architectural in some years with Skidmore and Merrill in San Francisco. And then getting back in Europe after seven, eight years, locating myself in Denmark at the Royal Danish Academy, beginning also extra collaboration with the Ingels and other firms throughout Europe. But in each of these sites, there has been some learning. For instance, in Denmark, I learned in the interaction with my previous mentor, Torben Dahl, the simplicity of sustainability and how tackling single analysis possible to achieve a major impact, but also went back to Berkeley and worked with Stefano Schiavone, where I learned the depth of human comfort up to the body thermal receptors. More recently, in the latest years, I learned a lot in EPFL, working with Scott Tazzini and Jerome Kampf, and helping a little bit in the testing or development of CT-SIM and understanding how each characterization should be synchronized also with regional models. So it's been a travel from scale to scale. And the last time I met Ingels was in Sydney. We didn't even know. We actually met randomly walking into the campus or something like that. That's funny. But both we spent time with Professor Matt Santamuris and I really envy and I try to grasp the way he explained to the large public, to the policymakers, what is the impact of certain choices, how we can talk in a very simple way about sustainability despite there is so much into the back. So this is part of the travel, I would say. Yeah, that's fantastic. I mean, it is true. Matt Santamuris is actually really influential in the way he talks about climate change. I remember my breakfast with him when I was in Sydney. It was actually just like a breakfast together and it was like a really like a mind blowing conversation for me. Not only in, as you say, the sort of like, you know, intuitive and simplicity sort of like oriented way of describing. So simple. It's actually probably sort of like very approachable, very sort of like accessible way to understand the impact of climate change. But also, you know, what he taught me was like, for me, like, it sounded devastating. We've accepted essentially the impact that this this crisis will have on like, you know, millions, if not billions of people. And and somehow we've we've agreed sort of collectively to accept that. That's I think it's scary. But anyway, I'm not going to go very, you know, very eerie yet. I love how you say you started from energy plus maybe I share my first sort of like interaction with with climate simulation and simulation tools in general was when I was in the University of Patras, I was still like an undergrad student. And I remember I was introduced to back then the DOE list of software. I don't know if you remember there was like this page in the Department of Energy of the US, I had a list of software, which was also part of like, you know, the energy plus group. And it was like, you know, tools that that were ranging from sort of like, simple standalone software that you could just like do, you know, window configuration, and you could just like understand the daylight impact of that to more complex sort of like, you know, energy plus integrations. And I remember like, you know, back then, like energy plus was still sort of like more a command line tool. And perhaps, you know, that led me very quickly to, as I was not able, I was not like sort of like proficient enough in coding back then to very quickly understand that, you know, this is, it is a problem that we don't have access to it. I remember like there were like more than 100 tools in that page that you could access, but like no one knew any way to use them or no one that I knew was using them. So perhaps that brings me to the next talking point, which is essentially, and this is sort of like, you know, people very often ask these questions, especially when they're not like directly related to our field, when they're not like, you know, they've not spent the last 15 years perhaps like working with simulations as you've done and I in some sort of like, sort of like range. What are simulations? What are environmental simulations? How do you, you know, define environmental simulations? And how do you explain to, you know, everyone what they are and how they're used and why they're like important and how they have impact on your research? How did they change really in actual reality, the buildings you've advised, you've sort of like worked on the sort of like urban environments that you've helped shape? Sure, that's a great question. And it's not, it doesn't come to surprise that the first depositories of tools were made in America. This is because the first tools, the first environmental tools were those analog, primarily developed by the broader all geeks. Probably most of you or some of you have read the book Design with Climate, which by the way suggests. And then there was this transition. I have it here. Oh, you have it? Yeah, somewhere here, yeah. Sure. If some of you is able to buy like an eBay, the original copy into the 60s, that will have an increased value in two times. So it's a good investment. Yes. And so we can define environmental tool in two ways. Scientifically, it's a code set of algorithm that help up to decipher what is the climate. This can be extended also to major interaction with human activity or anthropogenic activities. And the tools are different at different scales. So it's a way to decipher the thermodynamic happenings that move from the larger context to the local one. But if you think more philosophically, this soon lead to a deeper contemplation and to a certain stewardship that we can have with the context, with the climate. And also I have to say that it's a tool that can develop foresight, but also some sense of humility when we construct so we can understand how we can better relate with the climate and the larger ecosystem. So I think we can sort of keep this double face in the definition. But maybe expanding on that definition, how do they impact design? Like, how do you sort of like measure? Like, you know, you've worked in simulations for a very long time, and you've also sort of measured enough on regenerative design. Like when you're really on the nitty-gritty of a project, like how important are simulations for sort of essentially shaping a project? I have my own sort of like, you know, take on that having worked on maybe like more than 50 projects at Foster's. And I remember a lot of cases where like, you know, simulations were absolutely needed. And maybe like, you know, I'll hint on why, for example, like infrared was developed and what sort of like my research has always been. I was like, there's many, many cases for me that like simulations were actually very much needed in the project. You could see that the project was not informed enough on the impact that, you know, certain design decisions would have on the climate, but were not really accessible, even if we had like, you know, cutting edge tools, software tools, and we were developing cutting edge software tools to integrate simulations. The actual decision makers wouldn't have access to that simulation. They either would use them to sort of like prove a point, like, you know, to a client or like to say, hey, you know, like, here's an option. Here's the bad option. Here's how, you know, better this option works. Sometimes like it's also an artificial sort of dilemma. Or they literally didn't have time to do those simulations or to like really inform design decisions. So, but I want to hear from you, like, how do we, how much do we actually use simulations to inform design decisions? Let's have an honest discussion about this. Yes, you touch on the full scale of points. And I have to say that while you were in the imposter and the performative groups, I was very, very much interested on how you almost developed the first biomorphic approach to performance, where the use was far beyond just compliances. So, I have to say that, of course, the range of works we were exposed ranges from compliances to form a making. But in general, after many years of just doing this almost, what I can say is that surely we can understand how the way cities are built, districts are made, buildings are formed. It's pretty much a float. There is several weaknesses. Possibly, we can begin to inform better design, changing and reverting the action using simulation for generate better systems. Perhaps form is a limiting word. We better talk about system. One of the interesting things now that we work like you're doing at this stage, I believe, with infrared, working with cities and understand how the metabolism happens will be much more interesting and performative to design cities that are more like veins of a leaf almost, where systems are more integrated, where the anthropogenic system and the natural system are much more connected. So, the first weakness I found after using simulation, into the structure of the city. The second comes to the second level of analysis. We just ran a studio. It's about the form of district. How most cities, both if we take the historical cities or the most recent design, we can see how there is a certain grid that responds to other needs, but not to the one of ever clusters of competencies. By competency means biological system, farming system, production system, living system, amenity system. How do we interact them in order to have thermodynamic synergies and capitalize on that probably will lead to very different shapes that reminds much more of biological configuration. And finally, when it comes to building, what we're seeing, and this comes perhaps from consults in different countries, is that, and this is an absurd, but we all know, and most of us, our presentation is that for each climate, we really need to have very different building. In tropical climate, we may want to have aerial spirals with brief history type of skins. When we talk about desertic architecture, we need to increase as much as possible compact and about also shading and indoor microclimate. So clearly shapes needs to be more compact, less transparent than the one I'm seeing from my window now in Dubai, and capitalize into inner metabolism. And of course, when we reach far north, it's very interesting to see how certain species, certain form of in nature are already optimized. And when we approach with simulation, building simulation, we can see how this thermodynamic principle can be much more understood by digging into even just zoning, assembling or shaping. I guess traveling around the world does help experience a little bit those sort of like different climates and the different like building solutions. And now, you know, you're in Dubai, next, you know, you'll be in Poland, I don't know, I don't know where and, you know, the fact that we build the same sort of like, you know, the same sort of like construction methods and building methods like across the world right now, we sort of like globalized construction and typologies is actually probably a bad idea. I totally agree with you, the sort of like localization of building systems is probably key here. And in a way, perhaps this leads to the next point of like, you know, design as an experiment, right? So like, you know, sort of like design research, like, you need to actually try things to sort of like come to conclusions, you can't just say, you know, simulation is enough. But at the same time, you know, before we build, you know, like 10,000 buildings a day or 13,000 buildings a day, which is what we need to build by 2050 as I normally state, we need to also perhaps come up with some like, you know, some policy, policy sort of like regulatory sort of frameworks that doesn't like that don't allow us to really, you know, experiment on the expense of the climate. So maybe a couple of words very briefly on like, you know, experimental design and how much should we really sort of like compute before we build? And perhaps a hint on that on how, you know, the the current sort of like shift in simulation, I mean, it's not just infrared, it's there's a lot of other tools out there that like are on the same sort of like like quest to democratize simulation to make, you know, simulations accessible to everyone. And that will probably also have an impact on sort of like how we see design as an experiment, like perhaps before we actually, you know, build things and then go test them as we did Mazda, for example, you're very close to Mazda. I remember like when we had like a lot of assumptions about Mazda when I wasn't actually involved in the design phase when when Foster's built the built the sort of city area. And then there was a post occupancy study with Salman, Craig actually did like really, really great, great job there, looking at how much of these sort of like design ideas actually worked all this sort of like, you know, the wind towers and the and the DFE foils and like how they would reduce temperature, did they actually reduce temperature, how much, etc. How much of these assumptions were true. And perhaps also a hint on because what I often sort of like discuss about is like, you know, a simulation accuracy and accuracy of design, sort of like predictions versus the need to actually act. So let's say if I am now to design a new building in Abu Dhabi, like near the Mazda, and I come up with a strategy, I can have some sort of like, you know, bio sort of like inspired design or even like, you know, some sort of like form that cools down, you know, the environment, and then I can simulate that but maybe not accurately because I don't have enough time because or whatever like restrictions, I might have budget restrictions, or whatever other restrictions. And then I built that and then I test like how well that actually worked. And I mean, there's a question like how much time did I put into designing and simulating and like making sure that I'm absolutely certain that, you know, the material choices and everything that I had were the right ones versus to the reality of that, like when I actually build it, how much of that was actually implemented versus, you know, how much of that actually works in the end. And I want to hear your thoughts because I have my opinions on that, but I'm not going to state them yet. Do we need to shift more on like the design phase? Like actually, let's just simulate even not as accurately as that's what at least, you know, we're doing it like, you know, using AI tools, using sort of like other simulation tools, like to get an answer when it's needed, because the design phase will actually dictate the rest, right? So if your design is wrong, and you hadn't had any chance to simulate, you haven't had any chance to analyze, then the implementation and post occupancy study actually are less significant. So I want to hear your thoughts. I think I shared enough of my of my views on that. What do you think? No, that's great. Actually, you're right, we need to understand what weapon to use to fight who. And it's a war going there. Continue. Yes, it is indeed a war. I noticed by collaborating with a certain consultancy company, I will not name them, that there is almost a schematic approach to design where there are, for instance, employees that are trained in a certain way, and then repeat systematically a certain set of analysis, independently from the final goal of the design. On the other end, there is a certification system and regulation that makes the design oriented towards certain types of criteria. So both are, let's say, hindering from the most interesting and creative solution to a topic. So obviously, using tools like infrared to understand how wind stream or use radiation, radiation calculation offers already so much insights to just start from. And then it could be also interesting to use a very simple intuition, try to decode perhaps how certain system in nature works, and then try to translate these basic forms of material properties into what I call meta models so that it's possible to understand the principle of happenings. So what is more interesting, and I know Angelos agrees, is not because at the same time I'm lucky to attend to some review in his courses at YAC. It is not about being detailed about a certain performance, but it's about having a comprehensive and creative management of the set of data that are given by context. So this means understand what are the most important relationships that happen locally, being these, what are the changes given by climate change, how the ecological system works, and in what thermodynamic settings. How decarbonization can happen by choice of material, but primarily also by optimized shapes, and how we can contribute to health. So we don't need all this set of data. We can cherry pick here, and there are some meaningful relationships, and then try to understand how basic shaping and how material choice can be arrayed at the best. So this is very far from what is happening in practice. We have two threads. One is the intuition or artistic sketch from the architects that needs to become sustainable, or we have the performative guys in offices that try to follow what they learn in school or and what certification systems and policy is keeping suggesting them. In all this direction, oftentimes we never reach the best performance. What do you think about this? I absolutely love the answer because I think that that gap, that sort of like divide between the architect, the intuition. So like you go to architecture school, you're given certain sort of like guidelines of like, you know, the vernacular, the sort of like, you know, the sort of like standard bioclimatic sort of like advice and courses that you do. Then you go to design a building, and then of course that, you know, we all know the design process is very far from just like, you know, focusing on climate issues only. It's like it has a lot of issues, and like, you know, climate issues, unfortunately, are only like a part of it. I would say they should be like as important as structural issues. Like most people say, yeah, the building should stand and that's okay, but no, it shouldn't be the case. Like the building should stand and should also not destroy the environment around it. But like, that's a different discussion. But then you have the other sort of like side, as you very correctly said, which is essentially the experts and they say, I need 16 months of research to be able to answer a question of like, how exactly this facade will work. And you're like, in 16 months, the building will already be there. So there's no, there's no really time for that. And it's the divide, it's the gap. This is exactly, you know, for me, this is super interesting, aside from like, you know, building, which is exactly the, this is essentially the problem that we're trying to solve. Aside of that, this is a very important topic. So, you know, you have to reach a point where architects and planners and designers and everybody who's making a decision that actually influences the urban environment and the 40% carbon emissions that come with it, should have the ability to at least make an informed decision, to at least be able to be knowledgeable enough or like have the tools to understand, you know, whether the building will stand not only in terms of like its structural integrity, but will also stand in terms of its sort of like climate integrity. It won't really just create a horrible condition. And I mean, like, you know, the Scorchy Talkies and the Rays of Death, I'm not going to mention anyone in particular of these words, actually teach us that, you know, it's pretty incredible that, you know, the sort of like leading architecture, you know, offices in the world do not have the capacity to make these decisions, these informed decisions. And this is, this is, you know, slightly disappointing. So we need to close that gap. I totally agree with you. And so that probably also leads me to the next sort of topic, which I think like closes to like us sort of like reaching a sort of like more, you know, deeper side of the conversation. So urban cooling and cooling in general. So like, I remember like, I don't know, I don't have the right number. I don't have the sort of like the right start here of, you know, when we surpassed the need for heating to the need of cooling. So globally, meaning the energy we consume for heating is now less than the energy we need to consume for cooling. Or if it's not surpassed already, it's planned to be surpassed very, very soon, which means that we're shifting, right? So like, also all the education that we have, and this is a very interesting point, because we're talking about data, right? When we even talk about weather files and, you know, we're using weather files, we're using sort of like EPW. Let's say the climate, and you're wondering like, this is not right at all, right? Also, perhaps our education on our strategies are perhaps not as right. Perhaps Vienna doesn't have a strategy for cooling the buildings until now, but it has to develop one. And I say that because I live in Vienna and I've experienced the heat in the summer. So the question I have is like, you know, urban cooling and, you know, cooling as a topic, you're an expert on that. And perhaps what we want to hear, and I think this is talking on behalf of the viewers, I shouldn't, but we really want to hear perhaps, you know, your high level advice, your high level sort of like, you know, from your experience, for anyone who's going to watch this, who's going to hear this sort of podcast. What are the first few things we need to pay attention to? Do we need predictive sort of like weather files? We cannot use the weather files we currently have. Do we need, let's say, to just, you know, focus on cooling strategies more? Is it just about integrating nature or is it like a little bit more complex than that? What about all the sort of like, you know, facade cooling systems? What's your, you know, three most important pieces of advice for anyone who thinks about urban cooling? Yeah. Sure. I think this is an incredibly well articulated question. I say that because most of the teaching and also the debate we have are oftentimes yet linked to an eating dominated scenario. Most of the technology or the planning that happens in European cities, just to make an example, but that influence other contexts, it's still within mind the heating paradigm. I say this because I'm actually working in some project in Saudi Arabia, where I can see where the American European model of city is implemented, whereas cooling needs are very different. And that brings to major cooling loads for building. But coming to your sub question about how do we use data? What are the key issues? What are the key topics that we should tackle when we think of translation of data into design? There is a set of misassumptions that perhaps I can try to talk about. The first that surprised me all the time is when people talk about urban Thailand, whereas in all cities, actually the center, and this applies actually very well to Vienna, where the ring is way farther, way hotter than the center of the city. So I would talk more about the surrounding the Iceland heat more than urban Thailand. And that links to the need of use. We can call it the island, sorry, the heating, the heat shore, like sort of like the heat and the heat shore around the island. That will be the title of the next paper. And that will have a lot of citation if we are so provocative. I love the title. I will definitely acknowledge that, or perhaps we do it together. So this is with tools like infrared. We can already see some of this when we talk about ventilation or radiation study. We immediately see just by comparing these two variables how that is a fact. So another misconception is the one about greenery. Now every city is trying to green as much as possible everywhere. There is also no cutting tree policy to promote biodiversity. All interesting, but we need to have some coordinate to that. Primarily because vegetation, local vegetation nowadays with the threat of climate change, and this links to the topic of use future weather files rather than contemporary ones. What we can see is that actually the comfort zone of these plants is way rich. We are way out. Very interestingly, I will keep citing Vienna. If we look at green roof in Vienna, most are dry because actually grass and trees are not able to cope with so much radiation. So more than being worried on creating microclimate for people, I think we should be more worried about creating microclimate for plants and trees and vegetation, but then in turn is able to create a microclimate for us. But the most efficient way to create microclimate, it's beyond urban fabric is of course managing the living system. I have two more points. The one is about courtyards. We still keep thinking about courtyards because they come from the Greek and then from the Romans and then from the Arabs because in all of our story, we have some tradition of courtyards and there is also in Chinese culture and so on. But this is a less efficient way to cool the space, the courtyard. I know I'm touching the art of someone. I love that. Controversial. Yeah, go for it. Go for it. And also in all the first simulation we ran about this, we were like, how is possible? But actually courtyards are obstructing, especially the taller one, obstructing wind and wind up to 36, 37 degrees. It's something that anyway helps in the body equation to cool down. And during night, they don't cool down because the skyview factor is very little in most courtyards. So if we look, if we check on the 24-hour cycles and there are many other factors, and if we look with future climate each year that it pass, the least courtyards will be effective. We need to rethink them, having them much more open and several other parameters we can discuss in finer terms. Finally, this, we are in Europe, all obey to, you know, the regulation imparted from Berlin, very much influenced by German standard or Nordic standard. When we want to have insulation, there is a mantra that works in winter, we all know, and also at work in summer. In each climate, almost even in Scandinavia, actually all the requirements by insulation are actually not the most effective, which we need much less insulation. And each year that passes and climate changes, insulation becomes an issue, especially along the summer scenario. And the recent studies we have done, for instance, for the city of Gothenburg and other locations throughout Scandinavia and Germany, what we can see is that buildings that were built in the 60s, before the insulation mantra was passing through, are much more performing, especially in summer, because, and especially when there is a surrounding with the trees, vegetation, when there is a cool breeze, when there is a good ventilation, because the building is dispersed a lot during night or just because of the natural surroundings. So all this possibility of communicating with the outdoors, it's actually undermined. So it's very important to understand what's the very specific local climate. We cannot isolate every building independently from what's the context. So we need to understand to make almost a local EPW and understand what's the surrounding. And in several cases, a better design implies much less isolation or not at all in certain cases. These are four coordinates that I'm finding out. First of all, thanks a lot for sharing those, like really insightful. I actually think I am learning right now because in some of these... Oh, you're modest, yeah. In some of these, I didn't even think that in some of these suggestions, I didn't even think that those designs are like recommendations deep enough, I think. And yeah, I love specifically the point about localizing. The idea of EPWs is like something I remember I was trying to do maybe even almost 20 years ago when I was in Patras with probably the best professor I've ever had, Catherine Iliapi, who actually led my research project back then. And what I was trying to do is actually create my own EPW from essentially the data from the Department of Physics of the University of Patras where I was situated. And I remember I took all the data from like 15 years of recording of the weather station, tried to make my own EPW because the nearest airport, which is where you get the weather files, was like literally 100 kilometers away in a different city, in a completely different climate because Patras is essentially more dense, sort of like urban environment, not so dense, but denser than definitely the airport which was in the middle of nowhere next to a sort of like big, sort of like hilly spot. I mean, I've taken flight out of there once and I was like really scared. So the wind patterns, the sort of thermal patterns, this radiation, all of them were different, completely different to what the localized EPW. And that perhaps brings me to the ideas that we have also within our research in inference, like localizing climate data with the microclimate that you can actually get. There's a lot of research actually that focuses on how do you get the urban fabric, the massing, the vegetation, the water bodies and everything that's around, sort of like us, and using that to fine-tune because that weather file clearly doesn't tell the story off your site. So another approach is really using simulation, early stage simulation, to just really localizing the climate conditions before you actually put any mass on it. Before you actually start putting mass, you need to have a sort of like a simulation of that specific. So maybe now we're going to start sort of addressing now. I see the time. We need to close in about 10 minutes. We start perhaps addressing also with that questions from the audience. And yeah, naturally one of the first ones that comes in is how can we use data to improve the city design? This is a question from Nur. I think I'm trying to summarize it here. How can we use data and the different layers of data in the city to inform climate aware design? I think that's a very general question. Perhaps you want to sort of like narrow it down. Perhaps you want to address it in your way. So it's up to you. Sure, yes. I want to perhaps leverage this question and link also to your previous comments on the local data. Perhaps this will turn into a question for you because you are much more the expert than I am into the field. So for me, one of the biggest issues is not so much the environment, but it's about the localize with the data. In the sense that for me it's very interesting to be able to understand local patterns because especially for cooling, what's becoming more interesting, we sort of have an understanding on how to manage the radiant environment. But what I think is more unexplored, it's the, let's say, aerodynamic environment. So how can we, so at the level of data for me is very key to understand and to have much more education into that and more experiment also among us as simulationists or architects. How can we deflect wind? How can we accelerate wind with structure? How can we induce vortex in a public space? How can we use, I don't know, green corridors to create buffer zone? Or how do we create permable fabrics for distributed ventilation and so on? So this is actually the field that I found very interesting, both at urban level and then when it comes to the building, how to, you know, create terraces or how to curate canopies, funnels, wind walls. So this is the part that I wanted almost to interview you, Angelos, before getting to the question of the metal data because I'm very curious about your answer, if I may. How do we get local, hyperlocal in that? That's a very good question. I think that, you know, what I normally say around the topic is we actually have a lot more data than we think we have. I think that if we coordinated our efforts on utilizing open urban data as well as simulations that we've run thousands and billions, I would say, of simulations in the past and we have measured, like, you know, quintillions of like, you know, data points of like data, we have enough data to localize, I believe. What I believe we're suffering from is like we don't have any common, sort of like, any common formatting data, sort of like encoding of all of these data to actually access it. So, you know, weather files, we all know how to use them and we've been using them for years. But if I start looking at any sort of sensor and try to, you know, get that stream in, I think, you know, we've done several projects in IEC where we try to use sort of like, you know, anything from like local sensors or home sensors, you know, there's like the smart citizen project as well to just get that stream and like understand microclimate more locally. We also, very good study from Lu Yang, one of our interns in the CAL, was also a student of us in IEC, who looked at sort of like open access data from just sensors from a company. And, you know, you can actually use this data and already have a very much better sort of like view of what Vienna it looks like in individual sort of like spots. And that's like studies all available online. I can send it to whoever is interested. But then there's the, we start having problems, like they're not positioned in the same place. They're like, you know, you cannot essentially integrate them as easily. There's a lot, all sorts of like other things, like, you know, when we're talking about smart buildings and smart sensors and like all of that, we don't have a way to unify that data. I think that's one of the problems. And the other is that we really don't have, as in architecture and specifically in urban planning, any serious sort of like research work in unifying the climate data with the sort of like form generation that we do. Like, you know, we still lack that, I think, but maybe I'm just, you know, I'm just, this is a blanket comment. I think this is perhaps too much. I'm going to go into another question, which I think I found it very interesting, which is essentially specifically about water and the effects of water. So evaporative cooling, moisture, humidity in the microclimate simulation. So like, do we take, this is from Okan. And yeah, this is essentially the questions, like if we're planning to include the effects of water in microclimate simulations, I do think I've worked with evaporative cooling as a sort of like input before. And I think this is absolutely relevant. We definitely plan to have it as part of infrared sort of like simulation prediction modeling, but I'd like to have your question, your answer on that. Sure, sure, sure. Thank you so much. So water is definitely one of the variables. We'll use this question also to link to the previous one about metadata. For me, it's very important that we have sort of an approach to simulation, but it's with different arrows that touch upon different topics. And definitely water is one of the primary coordinates. So a couple of years ago, when I attended one of your review, I think it was the first time for me to see such an holistic approach. I don't say because you are here now, but it was very interesting how it was very interesting because with some degree of different degree of depth, but in your course, you are putting together simulated data with data vested from different sources. And to me, it's very important that nowadays we are not monodirectional. So we have in a city now water experts, we have heat experts, we have material flow experts into a city and all of them, they have some occasional meeting, but actually there is no city that has an integral model where all these parameters are interconnected. So with the parametric environment and possibility with machine learning are very strong. We can finally be able to understand the relationship from, for instance, urban heat mapping, water collection into the city or possibility for harvesting heat. We can map harvesting some data from environmental agency, biodiversity data. We all talk now about internet of nature. We have constant data, we can have speeches monitoring, as well as I remember in some of the students of Anglos, we have data from the energy catastrophe. I discovered in Spain, there is this energy catastrophe, but there isn't in other countries in Barcelona, quite interesting data. And then we have also the public health survey. So more and more with some resistance, but public health data are more or less available. Not always because there is always the hardest topic for city to release or from agency to release. So if we have this data and we can begin to simply overlay these layers graphically or just in Excel or both, we can see so much about how certain part of the city works and what are all these flow of information, including these of water. Because water, and this links to the question, it can be expressed like a millimeter per year, per month, liter, we can express it as collected water from ground, harvested water on surfaces. We can use it also in thermodynamic as an entity which evaporates and that changes humidity into the atmosphere, as well as a surface that has a different type of albedo and there's a thermal mass. But we need to think of water. And so for all the variables, very, in a very integrated way, has it influenced heat, has it influenced biodiversity, is a nutrient that stays in a place and that we can harvest. For energy consumption of building, we change the thermodynamic of the outdoor. So it means that we modify heating and cooling loads. It is something that can be like building can become a sponge. And then it's a material that is harvested by the skin mediating or the thermodynamic and the building itself becomes like a bioreceptor where life can thrive. In terms of public health, it has a quality water, but it's drinkable in most cases. It's something that modified the outdoor perception. So the important for each of these variables, and this is the challenge, is to create ways that allows to put these single variables, and we can name many, into a full systematic approach where we are able, through simulation, to highlight these parameters, describe them in very simple equations, even in Grasshopper, and machine learning will expand that. But we need to engage into this systemic type of thinking, I believe. Yes. Lovely. Well, thanks. This is a very detailed answer. Looking at the time, we need to start closing this, but I'd like to first of all add to the topic of water flooding, which for me seems to have been the key talking point in many, many cities that I've talked to different sort of like municipality related departments, etc. That everybody is worried, and I want to say my thoughts are with Brazil and the people who are now suffering, but we suffered in Greece. In the summer, I have the number is staggering. We had a city which had a maximum sort of like 750 millimeters per 24 hours, like received 1500 millimeters per 24 hours, like double the all-time record, which is incredible. So I'd like to do this last thing. I don't know if you have like one or two more minutes, Emmanuel, where we can actually do something very quick, which is, you know, sort of like speed answers to very quick questions. So like one sentence answers. So maybe I'd start with the scales question. I'm going to have it here. So like how do you identify optimal scales and boundaries in simulations that provide more effective results? Maybe one center answer on that from Sahar. Sure. The question is, it depends, but the boundary conditions are very important. Sometimes to study a very specific technology on a building, we need to have a regional model. Sometimes to study a large mesoscale strategy, we need to understand the chemistry of the chemistry of some processes. So it depends. Lovely. And this is also for me very interesting. So Hassan says, I understand why simulation is necessary, but from white to gray and black box modeling, which one can be suitable for the climate resilience strategies testing? I don't know if you can answer that. I have very little to say. What do you think? I think that, well, I think that it's not just black and gray and white boxes. I think, you know, modeling strategies, I mean, they vary on resilience strategies, but like I say, the black boxes become white boxes, the more you use them and educate people on the use of them. So like, you know, it's also part of our, as developers of the simulation tools, it's part of our job to actually make the black boxes gray or white by making them accessible. This is exactly what we're trying to do with infrared. You don't need to know how ray tracing works or mesh based CFD works to understand that the wind effect of your tall building is X or Y or your solar radiation sort of like effect is that. So I think the modeling and simulation component can be still black, but the result has to be more white to gray. But I don't know if you have any very quick answer to that. I couldn't do any better. Lovely. So I'm going to have to stop here. Thanks everyone for the questions. Really, really happy. This is the first time we do this. I'm really happy with the engagement. I think everyone will try to answer the rest of the questions on comments and posts. And I'd like to have a last sort of like words from you, Emanuele, about the future of climate aware design. It can be dark and it can be gray and it can also be white. It's up to you. Yes, I believe that the future could be of different colors, but we need to instill much more knowledge into the processes and we have to have a more expeditive methods so that I think tools like yours, Angelos, which can be shared across specialists and non-specialist or semi-specialist stakeholders is what we need to seek for. We need to have a more interactive and less scholarly approaches to the topics because variables are so hyper-specific that we always need to understand the hyper-specificity through some set of simulation. In general, there is a mind shift that we all know about this, but the competencies and the tooling are yet to evolve. Each year there is more awareness, yet there is a certain out-of-the-shelf so-called solution that is implemented, but reality is much more complex. Yes, I close with this bittersweet. Yes, bittersweet. It's just like making sure that we don't have an eerie conclusion. I mean, in what we see in the world today, it's very difficult to be very positive, but at the same time we need to act. I think my suggestion is let's all put more effort in making these climate design workflows and simulation processes.

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