IES has signed a strategic partnership with French software company Octopus Lab to bring better indoor air quality simulation to a wider international audience. Octopus Lab’s Indalo software uses Inca-Indoor, which is claimed to be the world’s only validated indoor air chemistry calculation engine.

IES’ Virtual Environment (VE) software, which is used for building performance analysis, currently simulates the ventilation and impact in terms of internal CO2 concentration, allowing VE users to set external concentration levels, test ventilation strategies and simulate occupants CO2 release to calculate indoor CO2 levels. However, CO2 is not the only chemical that impacts human health and comfort, and occupants are not the only source of chemicals.

The integration of Indalo into IESVE will allow VE users to simulate the concentration of over a thousand pollutants, taking into account various parameters such as emissions from materials and furniture, ventilation strategy, outdoor pollution, occupancy and planned activities.

Indoor Air Quality has become a major global health concern. New or recently renovated buildings are becoming increasingly airtight in response to today’s need for energy efficiency. While better insulation helps to reduce heat loss, it is often forgotten that it also prevents the proper renewal of indoor air.

Poor air quality can be the cause of many health problems, ranging from simple temporary tiredness to serious respiratory diseases.

Indalo is designed to enable building designers to make the best possible ventilation and material choices in order to meet indoor air quality objectives (regulatory or certification) in future new or renovated buildings. The solution also makes it possible to predict the risks of mould and viral infections and identify the most appropriate ways to limit them.

The Indalo plugin exports all relevant information from the VE model to Indalo, with all necessary data provided in the VE via IES’s Navigator technology. Geometry, ventilation flow rates, and occupancy is already simulated by the VE and the results can then be exported. Additional information such as materials’ emissions, filtration and external pollutants’ concentration, can be input via the VE Navigator to complete the required data for the Indalo calculation.

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While BIM adoption has primarily been driven by the need for coordinated documentation output, the AEC industry has always hoped to derive other model-centric benefits from this approach. In particular, the analysis, simulation and optimisation of designs has been seen as a significant potential source of competitive advantage.

With this in mind, more advanced 3D practitioners with considerable in-house programming resources have created their own suites of analysis applications. These firms include Foster + Partners, for example, as well as ARD, which presented on this subject at AEC Magazine’s NXT BLD conference last year. Those companies that have taken this route insist that the insights they derive from such tools are especially useful in the early stages of a design.

For other firms, many new conceptual tools now come with built-in analysis capabilities that focus on environmental conditions such as daylight, solar energy and wind. These tools, which include Autodesk Forma, provide quick feedback. The insights they provide may not be definitive, or offer specialist indemnity, but they are giving more firms access to early-stage, performance-based design.

Acoustic analysis, however, is an area where available tools are either highly specialist, developed in-house by very large firms, or both.

Treble aims to change that tune. Last year, the Reykjavik-based company came to market with a more accessible acoustic simulation suite that can generate, from BIM data, interactive, real-time, immersive audio-visual ‘auralisations’.

The Treble platform is cloud-based and uses a proprietary wave-based simulation technology, which offers new levels of accuracy, according to company executives. Geometry can be imported from SketchUp Pro, Rhino and Revit, via plug-ins. The application identifies problems like reverberation, assesses speech intelligibility, privacy, privacy distance and distraction distance.

Recently, AEC Magazine got the opportunity to chat with Treble co-founder Dr Finnur Pind, and hear more about how this self-confessed ‘sound nerd’ turned his attention to the AEC industry.

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Sound city

Reykjavik is an exceptionally musical city. It boasts lots of local bands and plenty of places to hear live music, not least at its annual Airwaves musical festival. Every November, live performances take over seemingly every square inch of the city, even its shop windows.

Dr Pind started his acoustic journey within the city’s lively music scene and studied engineering because he wanted to know how guitar amplifiers and other audio equipment work. This drew him further into the field of acoustics engineering, culminating in a doctorate in sound simulation technology. As part of his PhD research, he developed new algorithms capable of simulating sound faster and more precisely than previous approaches. And that, in turn, led to the founding of Treble.

“Our research was always kind of very Icelandic developer Treble has created a suite of tools designed to analyse and optimise designs for acoustic performance, based on the founder’s own research into wave-based sound simulation analysis Treble: sound advice Software practically oriented. We wanted to solve real-world problems, especially for the building industry, where people are always struggling with dealing with acoustics,” says Pind.

“As my PhD was concluding, me and my friend Jasper [Pedersen], who’s also an acoustic simulation guy, thought we could do something with this. We decided to apply for a grant, which we got, so we thought we had better start a company!”

Treble is currently fundraising for a Series A investment round, having already gone through a pre-seed and seed round and raised $10 million so far ($3 million in grants and $7 million in equity). Investors include the European Innovation Council and NOVA, the venture arm of building materials giant Saint-Gobain.

As Dr Pind explains, the Treble application takes a 3D model of an environment, into which the user can place sound sources, such as a human talking, or a loudspeaker. The tool takes into consideration the materials used in the model and then simulates how the source will sound in real life. It might be used for designing and optimising that space, or designing and optimising a sound system, from the small (a speaker phone, say) to the vast (a concert hall system). In fact, he adds, many audio tech companies use Treble to train or improve adaptive audio technologies that adjust to the spaces in which they are placed.

There are two core markets for Treble, as Pind sees it: users that want to build acoustic analysis for a particular sound system for a building, and tech customers who require simulation technology to synthesise a million different environments, in order to create data to improve their audio algorithms. “While these two applications seem quite disconnected, from our technology perspective, it’s all very related,” he says.

Treble deliver results as listening experiences, giving designers and clients the ability to hear the sounds associated with a proposed design. Hearing is believing, after all

At the start of its development, Treble concentrated on serving the sound specialist community, but as the company grows, it is developing tools for architects working on spaces that might include a typical meeting room, an office layout, a call centre, or a classroom.

A key aim for the application development was to make Treble simple to use and able to work seamlessly with other design tools. Going from BIM to Treble, performing an analysis and then getting the feedback can be done in almost one click. Treble extracts the 3D model and its materials, and then simulates how this will sound. Results are delivered as either coefficients, graphs or colour maps. Users can venture into the real-life space and listen to the predicted sound on headphones. They can flip between different design variations and materials and hear how this impacts sound quality.

“We are most proud of this simulation engine that we built, which is very precise. We’ve benchmarked it against many, many real-world scenarios and it’s so precise that it’s not just useful for building design, but also for product development and data generation, where you really need real-world fidelity. Our technology doesn’t use the typical ray casting approach. Instead, we solve the maths equations that describe sound propagation, capturing the wave nature of sound.”

Technology choices

So why did Pind choose to support SketchUp, Rhino and Revit? He explained, “SketchUp is used a lot by acoustic engineers, acoustic specialists. That seems to be a common tool for them to prepare models for simulation. And then Rhino too, is so powerful, and used in early designs, which is a good place to think about acoustic performance. For generative design, we have an SDK/API, perfect for Rhino/Grasshopper to work with for analytical loops. We have done some internal tests with that kind of process, but the API is still relatively new. Some of our customers are testing this out. Revit for BIM modelling, of course, because it’s just so widely used.”

From the onset, he decided Treble should be browser-based and deliver its experience within the browser. This way, it’s possible to create virtual listening experiences, and then send them over the web. The person on the receiving end just opens it in their browser and can listen to the simulated acoustics from a set position within the model. This capability is powered by gaming engine technology.

Because these experiences can be shared via the web and delivered to headphones, you can have as many people as you want listening. Alternatively, the experience could be delivered to a speaker. While for now, these are screen-based experiences, virtual reality options are on the roadmap, leveraging Unity and Unreal.

The company has already been working with companies that are fiercely protective when it comes to data security, such as automotive manufacturers, and Treble complies with the highest cloud security certifications. It’s considered safe enough to persuade some of the biggest tech firms to upload some of their most sensitive designs – but if a big client wanted to deploy locally on its own server farm, for example, Pind says that could be considered.

Until now, Treble has supported the analysis of just one space at a time, with users having to pick representative spaces out of the building they wish to analyse. But that’s about to change with the imminent launch of what Pind calls ‘multi-space import’, where they can input a whole building and get a quick analysis of basically every space inside it. If problematic areas are found, users might zoom in and iterate the design to solve the acoustic issue.

The software doesn’t yet offer advice on rectifying a design, but it clearly indicates where problems lie. It’s then the job of the designer to adjust the materials, the space, or the furnishings to then explore the impact on sound of these changes.

The core analysis isn’t AI-driven, either – but the company is looking to utilise some kind of machine learning to improve processes and efficiency. Outside of the AEC world, Treble is already active in the world of ‘synthetic data generation’, where simulation is used to generate data, which is then used to train machine learning models. For Treble, this means providing analysed spaces for all kinds of modern audio equipment manufacturers. The resulting data sets feed machine learning algorithms that look to detect speech, remove extraneous noise, or improve acoustics in that space. For manufacturers, getting their hands on these training datasets can be a headache. Treble, by contrast, can easily generate 10,000 meeting rooms, containing all sorts of surface materials, furnishing and occupants. According to Pind, this is becoming one of Treble’s biggest use cases.

Hearing is believing

Treble is typical of the way that many new software companies now come to market. Their solutions are written as services in the cloud, with plug-in and API access to relevant third-party tools.

But where it differs from other analysis tools that focus on early-stage design is that while many of these use nice colour maps to deliver indicative results, these may still mean little to a non-specialist. Treble’s answer is to deliver results as listening experiences, giving designers and clients the ability to hear the sounds associated with a proposed design. Hearing is believing, after all, and Treble looks like a useful tool to have in the BIM analysis armoury.

It’s available for a 30-day free trial that offers access to all features. From there, one seat for small and occasional users is priced at €149/month, with a token system deployed to pay for processing. A one-seat unlimited use bundle is €299/ month. For five or more seats, you’ll need an Enterprise bundle, which requires a call with the company to discuss needs. Discounts are available for yearly payment and special pricing is available for academics. Access to the Treble SDK is currently subject to a waiting list.

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TwinUp is a new AI-driven architectural software tool for creating, managing, optimising, and presenting 3D design models and project images.

The platform is powered by ‘Arch-e’, an AI-driven personal assistant that processes ‘vast amounts’ of data in real-time to transform the design process from beginning to end.’

The software suite is currently in beta and includes three integrated apps: TwinUp Community, TwinUp Building, and TwinUp World.

TwinUp Community is a free virtual design portfolio and social media platform just for architects. Users upload, enhance, organize, and share images and videos of their design work with private groups and the larger architectural community at their choosing.

TwinUp Building is a 3D digital twin maker app that helps architects convert their 3D models (BIM, et. al.) into what TwinUp describes as digital twin models. TwinUp Building’s visualisation features and simulation capabilities allow users to render, analyse, optimize, present, and share their models with peers and clients.

TwinUp World is a 3D virtual digital twin model of the earth whereupon users can place their 3D project models for analysis, enhancement, rendering, and presentation in their proper local site context. Features include advanced navigation tools, data layers, rendering tools, multi-party collaboration interfaces, and simulation features. An App Store of plug-in modules adds a selection of ML-based design simulation capabilities, from simple daylight studies to more complex carbon emissions simulations for single and multiple buildings.

TwinUp Community is slated to launch early this summer (2023), and TwinUp World is expected to launch later this Autumn (2023). The TwinUp Beta Program is currently accepting applications from practicing architects.

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Geological modelling specialist, Seequent, has released Slope3D, a slope stability analysis tool for geotechnical engineers and engineering geologists.

According to Seequent, Slop3D offers a practical approach for capturing slope failure mechanisms for simple to complex geotechnical models.

Building on the capabilities of Seequent’s GeoStudio 2D Slope/W product, Slope3D is billed as an intuitive limit equilibrium solution for analysing rock and soil slopes in mining and civil projects – for example, hillslopes, open pit mines, and engineered structures such as dams and levees.

“Ensuring the safety and reliability of engineered projects is at the heart of geotechnical engineering,” said Chris Kelln, director, technical solutions for GeoStudio.

“We specifically designed Slope3D to empower geotechnical and geological engineers to make confident decisions, improve safety, reduce project risks and costs, and ultimately design better infrastructure.”

Slope3D is part of Seequent’s GeoStudio 2023 release. It connects directly with Seequent’s geological modelling software, Leapfrog, via Seequent Central, and integrates with GeoStudio’s Seep3D. According to Seequent, this creates a seamless workflow with smooth data exchange and simpler data management to improve project accuracy and outcomes.

Seequent was acquired by Bentley Systems in 2021 for $1.05 billion.

Seequent’s products include Geosoft for 3D earth modelling and geoscience data management, GeoStudio for geotechnical slope stability and de-formation modelling, and Leapfrog for 3D geological modelling and visualisation.

Leapfrog appears to have particular relevance to infrastructure projects. The software is designed to replace traditional 2D subsurface modelling and simulation processes. According to Bentley, the usage of the software, often in conjunction with Bentley’s software offerings, has been growing consistently in civil infrastructure sectors.

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We all know BIM models have a tendency to get big, fast. The more detail that gets added, the slower manipulating the model becomes. There’s an argument that, for certain analyses and deeper insight into the performance of a building design, using something simultaneously more lightweight and more intelligent might be a better way to proceed.

Enter Topologic, a free, open-source tool that breaks down buildings into an external envelope and subdivisions of the enclosed space. Creating separate spaces and zones by using zero-thickness internal surfaces produces a model that is optimised for better understanding of building performance.

Topologic’s story starts with Dr Robert Aish, the ‘father’ of Bentley Systems Generative Components (GC) and Autodesk DesignScript. He was writing a paper on the application of non-manifold topology as a lightweight form for architectural modelling as far back as 2013.

Meanwhile, Dr Wassim Jabi of Cardiff University, who was researching parametric design thinking and its role in building performance simulation, took Aish’s research on board. Jabi applied the concept of non-manifold topology to his own design and energy performance simulation research, publishing papers on his findings in 2014 and 2015.

In 2015, Dr Jabi and Dr Aish (who at this time was visiting professor at the Bartlett School of Architecture at University College London) decided to collaborate. The goal of their research project was to investigate non-manifold topology further, by building a platform independent software library to be used with Grasshopper, Dynamo and Blender.

Their proposal was funded by a threeyear grant of over £300,000, awarded in 2016 by the Leverhulme Trust. In 2019, the first alpha version of Topologic was released. Once the project was complete, Aish left. Today, the code’s use in AEC practice is being championed and developed by Jabi.

Topologic is now an open-source software development kit and plug-in for visual data flow applications. Jabi claims it will assist architects in understanding their buildings from a holistic perspective — both as a physical assembly of components and as a logical, spatial and hierarchical system.

Topologic enables connections with analysis and simulation engines, such as EnergyPlus and OpenStudio and can be used to analyse the thermal performance of a building without the need for a huge and detailed BIM model. It can also be used to plot paths such as mapping fire egress routes, identifying the least disruptive route for a new service pipe, or computing the most congested location in a city layout.

Pretty much all BIM models are produced using walls, doors and windows – or in other words, building components. The reality is that, in analysis, models do not need this level of detail. What they do need is more knowledge of connections and interfaces. And while you will find plenty of adjacencies of spaces in a typical BIM model, the way they are modelled tends to create lapping co-linear lines between spaces and edges that don’t meet. The result can create issues for confused analysis tools. Topologic tries to close those loops.

“Topologic is used to basically model spaces, rather than actual elements,” Jabi explains. “We are replacing detailed geometry with smart topology and information, thus reducing a very heavy geometric model into lightweight geometry. We add smart, rigorous topology to designs, such as how things are connected, and then imbue it with a lot of additional information.”

That information is not just attributes, he continues. It can also travel with geometric operations or topological information. This makes a Topologic model extremely lightweight and extremely powerful.

“Topologic is based on the idea of nonmanifold topology, which allows you to model spaces and create internal subdivisions, like cells. If you can imagine a cube and if every point on the surface of that cube were sentient, they would see the world divided into two sets – the outside and the inside of the cube,” he says.

“Now imagine that condition being violated, where a point on the cube can actually see more than two sets. The outside can see other sets of points inside the cube. That situation is called non-manifold. So basically, when you have a geometric engine that supports non-manifold topology, you can have extremely powerful representations.”

A building, for example, can be seen as an outside envelope with interior cells. These interior cells can encompass other interior cells. Hierarchical embedding is possible, too. “Then you can start to think of your building, your design, as a set of interconnected entities, usually defined as space,” says Jabi.

Topologic can be used to analyse the thermal performance of a building without the need for a huge and detailed BIM model. It can also be used to plot paths such as mapping fire egress routes, identifying the least disruptive route for a new service pipe, or computing the most congested location in a city layout

Explaining the fundamental database underpinning Topologic, Jabi says: “Behind all of this is the idea of a ‘graph’. This is unlike BIM systems, as we don’t have to use ad hoc methods to add topological connections. As an example, a door in Revit should know what two rooms it separates, but that only happens in Revit if you checkmark it at a certain point. If you don’t do that checkmark, that door doesn’t know what rooms it separates. In Topologic, that is built into the DNA of the software — everything knows what it is connected to, and it’s automatic and part of the data structure.”

Obviously one of the key times in a project to do analysis and to make important decisions is at the concept phase. Here, the industry has seen many exciting applications come to market. Most of these tools are based on the concept of spaces that lie adjacent to one another, which is Topologic’s core starting point, too.

Jabi explained that synergies between products have already kickstarted some collaborative development work. Topologic, for example, has worked with Testfit, because there are compatibilities between the models that the two products create.

“Testfit creates these simple, blocky models, where everything is interconnected. Once we understood how their file format was organised, we created a reader for it, and we imported Testfit models into Topologic,” says Jabi.

“This meant we could analyse the heck out of them, as we understood exactly the walls that are between two units, the walls between the unit and the corridor, the walls between the unit, and the elevator shaft etcetera,” he says.

The Topologic team has also created rules for generating graphic models, producing Revit models via Dynamo, ready for design development. “We could identify external walls, internal walls etcetera, so we were able to apply the right thickness and materials. So Topologic can be used as a driver to ‘thicken’ into a BIM model.”

While products like Testfit can generate hundreds of models very quickly, the software has no understanding of whether designs are energy efficient or if they constitute ‘good’ architecture. Even though Topologic can help to enable analysis and drive them into Revit, we wondered if the process might go in the opposite direction, from Revit into Topologic for analysis?

“We have started with a BIM model, rather than create one from Topologic,” says Jabi. “We took a model of a building that was filled with rooms, but they were not connected into apartments. So it was impossible to get an idea of the rentable area and have data for analysis.”

By running the model through Topologic, a graph was created where all the ‘graph islands’ (apartments) could be identified. The graph immediately went back to Revit, with apartments correctly assigned and colour coded, and schedules needed for analysis were created.

“So we can import an unstructured BIM model, run it through Topologic’s intelligence and make it a little bit more structured,” says Jabi. “But, you know, bad modelling is not something we can magically solve in Topologic. What we are advocating is to start modelling in Topologic first, and then move to BIM. Don’t model in BIM and move back to Topologic — if anything, that is the worst case scenario. While we have to deal with it, obviously, that’s not what we recommend. Start building even in SketchUp, or Blender, or wherever you have lightweight things, and then imbue them with intelligence, imbue them with information, and do lots of analysis on those lightweight models. Once you’re done, and you know what you’re doing, it’s just a click away to go to Revit models, so that it becomes an output not an input for us.”

With the rise of open source, Topologic plays well with popular tools such as Blender BIM. Bruno Postle, a colleague of Jabi and a member of the OSArch community, has used Blender, Topologic and Blender BIM to create BIM models, for example.

The process starts in standard Blender, where the user makes a simple cube structure and adds in slice planes of zero thickness to form spaces. Then, with one click, this is sent to Topologic, which behind the scenes starts to create a building with all the topology and information needed. Based on Topologic’s output, the data can be thickened with IFC information for building an energy and structural model. These full IFC files can be imported into Blender BIM. If the model needs changing, you can go back to the simple model, drag edges and so on, and convert it one more time.

Conclusion

In many ways, Topologic reminds me of the finite element analysis (FEA) packages used in the mechanical CAD world. While product designers are modelling every component and part in an engine assembly, the analysis teams are not using these explicit 3D models, because FEA tools need simplified geometry and lots of data about forces, materials and temperatures. The core output is performance information, to find design flaws and limits to the performance envelope.

Topologic is a spatial representation, a framework where questions can be asked before detailed modelling continues. And, as is the case with all these rapid conceptual tools, which predominantly report back financial information, Topologic can quickly identify any financial downsides of rapid design suggestions. The fact it’s free also makes it excellent value! Sometimes, it pays to think in levels of abstraction.

The source code can be downloaded here.

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Nvidia has expanded the reach of its 3D design, collaboration and simulation platform, Nvidia Omniverse, by introducing several new connectors that link standard applications through the Universal Scene Description (USD) framework.

 These include Blender, Cesium, Unity and Vectorworks. Omniverse Connectors for Azure Digital Twin, Blackshark.ai, and NavVis are coming soon, adding to the hundreds that are already available, such as Revit, SketchUp, Archicad, and 3ds Max.

Nvidia is also adding new features to the platform through the forthcoming Omniverse Kit 105 release. This includes the ‘first real time ray traced subsurface scattering shader’, as Richard Kerris, VP Omniverse platform development, Nvidia explains, “When light hits an object, depending on what that object is, a light can be refracted or split or shattered through the different types of surfaces.

“So when light hits marble or it hits something like skin, it doesn’t just bounce off of it, there’s actually parts where the light goes in, and it scatters around, but it’s very computationally hard to do.

“We were the first ones a few years ago to do real time photorealistic ray tracing and now adding to that the first real time ray trace subsurface scattering.”

Other forthcoming new features include performance improvements thanks to new runtime data transfer and scene optimisers for large ‘worlds’ and more ‘sim ready’ assets, now in the hundreds.

Nvidia has also been working closely with Microsoft to bring Omniverse Cloud to Microsoft Azure. The next stage is to bring this to Microsoft 365 to make Omniverse viewers available inside application such as Teams. From a Teams call, for example, participants will be able to teleport into a 3D environment to work and better understand what’s taking place. “Each of them will have their own experience in that 3D environment, collaboratively,” says Kerris.

“Integrating this [Omniverse] into Teams is just a natural progression of how we communicate. It’s the manipulation of the 3D world in much the same way you can do today in the 2D paradigm of the web,” he adds.

Users won’t need local processing for this. “You’ll be streaming out, in much the same way that you access the cloud through a browser,” says Kerris.

Omniverse will also be connected to the Azure IoT ecosystem, delivering real world sensor inputs from Azure Digital Twin to Omniverse models.

Everyone can be a developer

Nvidia is working to harness the power of ChatGPT for Omniverse. Kerris explains that end users will be able to use ChatGPT and instruct it to write code which they can then drop into Omniverse.

“You’ll have an idea for something, and you’ll just be able to tell it to create something and a platform like Omniverse will allow you to realise it and see your vision come to life,” he says.

Developers can also use AI-generated inputs to provide data to Omniverse extensions like Camera Studio, which generates and customises cameras in Omniverse using data created in ChatGPT. See video below

Nvidia has also announced Nvidia Picasso, a cloud service for AI powered image, video and 3D applications, designed for software developers, not for end users. “Imagine just typing in what you need, and it creates a USD-based model that you can put into Omniverse and continue on,” explained Kerris.

Finally, Nvidia has introduced its third generation of OVX, a computing system for large-scale digital twins running within Nvidia Omniverse Enterprise, powered by Nvidia L40 GPUs and Bluefield-3 DPUs.

Find this article plus many more in the March / April 2023 Edition of AEC Magazine

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Netherlands-based Viktor.ai is an innovative cloud-based development platform for architects, engineers and designers, enabling them to build and share their own powerful work tools.

This cloud-based platform offers all sorts of software connectors for quick Python code creation and programme management. In the two years since AEC Magazine first looked at the company’s offering, it has gone from being mainly Dutch-focused to attracting international clients, having raised over $2 million in seed funding and a Series A round worth some $5 million.

Currently many firms lack the skills to effectively manage code developed inhouse, or they rely heavily on expertise that subsequently leaves the company. Viktor offers a service where the creation of applications is simplified, from code generation through to GUIs (graphical user interfaces), as well as providing automated API hooks into the vast majority of commercial applications. These include SCIA, Revit, Plaxis, Grasshopper, AutoCAD, Ansys and Excel to name but a few.

With Vikro.ai it’s possible to create tools by simply entering input parameters, creating the flow logic and then specifying the visualisation of the results in dashboards, interactive graphs, data drive maps and 3D models.

These applications can be placed in a common cloud environment, with Viktor taking care of hosting, security, handling roles and permissions, and version control. This means that custom code need never get lost and can be shared with as many people as you want. If staff leave, you have the functioning code, plus the logic and the version history needed to maintain that investment. Viktor has won over clients in the fields of geotechnics, structural, energy, architectural and GIS.

Viktor.ai has also benefited from its use in some big projects. One of these is the 18km-long Fehmarnbelt Tunnel, which will link Germany with Denmark and will be the longest combined road and rail tunnel anywhere in the world. Made up from 89 massive concrete sections, it will cost $7.1 billion and should be completed in 2029. The tunnel was designed with the help of a Viktor application, which has been a great demonstrator to other firms that serious applications could be designed this way.

AEC Magazine spoke with Anande Bergman, Viktor.ai’s chief growth officer (CGO), about the industry changes driving more in-house development.

AEC Magazine (AEC): There appears to have been a shift towards in-house development of design automation applications. Why do you think that is?

Anande Bergman (AB): We see this in existing clients and in new clients. Making tools has become a profession in itself. Engineers working on big projects used to make small tools to help their designs, but now they are developing bigger, more professional tools. Some have dedicated groups of people, even divisions with their own management to create digital tools for their own organisations.

We used to have software that was able to do one thing well, like finite element analysis, or routing software. Then engineers started realising that they wanted to have more tailored software, and so started building apps for those things. This then exploded as people got handier and connected different applications. At the end of the day, if you want to design a tunnel, you cannot be from the IT department, you just don’t have domain knowledge. So that’s the big shift: We’re seeing that the real domain experts are the ones writing custom software now. And Viktor’s trying to facilitate that as much as we can.

AEC: You recently announced a free version and an app store. What’s the thinking behind these moves?

AB: Yes, we have made a free version of the product. So everyone in the world who is willing to test Victor can just go to the website, download it and they can make apps. And people will also be able to publish those apps for free. We really want to stimulate firms to start creating apps and sharing knowledge. We want to be the place where engineers come and share their knowledge and their code with people. Customers can choose to keep their apps in-house, or to share them with everyone. In the Apps Gallery on our website, you can find multiple templates of readyto-use Viktor apps, such as a solar panel configurator and CPT-interpreter, including the source code.

AEC: So what are the limitations of the free service?

AB: The limitation is basically around the type of app that you’re able to publish. For instance, as a free version user, you could publish apps that are public. By public, I mean apps can be shared from our website with just a link. Click on the link, and you will be able to use this app. You don’t even need a Viktor account, or need to donate anything. You can share it with anyone. Free users will be able to publish any app they want, but only to publish as public. The reason we’re making it free is because we want people to share knowledge. If you want to have a more private experience, where you only work with colleagues, where your apps are not seen by anyone outside your firm, and are password protected and require a login, then that’s the paid version of the product. In the future, we would like to offer the ability for clients to distribute and charge for others to use their applications too.

It seems that Viktor has managed to capture the zeitgeist of the engineering industry at just the right time

AEC: What kinds of functionality are your customers currently asking for?

AB: It’s very client specific. Customers ask for specific support for software X, or improvement to an integration. Sometimes it’s very generic, in the sense that they want to know which are the most used apps, so we produced a dashboard to show this. We’re working on different topics like sharing and tagging, extending input fields, mapping, search functions. Then we have business-side requests, enhancing tools for managers, providing more insight into tool use and which projects are using which apps, and their frequency of use, because maybe they want to do internal billing. Other developments we are working on are things we believe are important, like making it easier to produce better documentation for free, publishing rights, and so on.

AEC: With Autodesk introducing Forge, it seems like the industry realises that customers want to build and integrate their own applications, but the reality is that companies are using applications from multiple vendors, so they need tool sets that span all applications, to have broad connectivity.

AB: I totally agree, this is what we see. The reason to write an app and to invest more time in developing automation, is especially to connect all these different data islands. Some people use an Excel sheet to do this! Engineers want to combine the output of programmes because teams work in different applications. Someone uses geotechnical, someone else does structural engineering, and they need to talk with each other, because design is an iterative process. They need to connect all the information and be 100% sure that the right information was used for those calculations, and that no errors were made because they used the wrong cell sheet or email. There are deserts of integration that need connecting and we have clients who are now able to automate 80% of their work.

Conclusion

It seems that Viktor has managed to capture the zeitgeist of the engineering industry at just the right time. An increased focus on in-house development, the need to manage code, share it, measure its use and retain knowledge is a heady mix of capabilities for one firm to offer. The new app store, combined with offering free use and distribution certainly whets the appetite for open source, while keeping a keen eye on possible monetisation in the future. Viktor is a development platform, a distribution and management tool, as well as an open resource. Hopefully many developers will take up the offer to add free apps and that Viktor can police these, in order to retain quality. Certainly, this is a company to watch.

Main image: Warehouse configurator app, demonstrating how a user could design a warehouse with an adjacent office in a simplified parameterized manner

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Treble Technologies has launched a sound simulation platform that allows architects and engineers to visualize the acoustics of building designs and simultaneously hear exactly how the environment will sound in real life.

The cloud-based platform uses a proprietary wave-based simulation technology, which according to the Icelandic startup, offers a level of accuracy and reliability that was previously unobtainable in the architectural and engineering fields. It can accept geometry from SketchUp Pro, Rhino and Revit via a plug-in.

The Treble platform has been in an open beta testing phase leading up to the launch, where architectural firms such as BIG Architects, Henning Larsen, engineering consultancies like COWI and material manufacturers like Saint-Gobain have been using the platform to improve their design processes.

Henning Larsen worked with Treble on Uppsala Town & City Hall in Sweden to help ensure the renovated and expanded building was fit for purpose from a sound perspective. For instance, the expansive glass façade, although visually stunning, sparked a lot of uncertainty about the way it would impact the building’s soundscape.

By using Treble’s technology, Henning Larsen was able to experiment with potential solutions, such as the use of different materials. Ultimately, this testing led the firm to the realisation that the façade needed perforated wooden frames to turn the wall into a giant sound absorber, improving the building’s overall acoustics.

In Norway, engineering consultancy firm COWI utilized Treble to great effect to investigate and shape the acoustical performance of an open plan office in their office in Stavanger. See VR demo below.

“Sound has a major impact on people’s health, well-being, productivity and ability to communicate, and yet the world today is plagued with noise and low-quality sound experiences,” said Finnur Pind, CEO and co-founder of Treble.

“For too long, engineers and designers have lacked the necessary tools to harness the power of sound, and design great sound experiences. With Treble, users can now visualise how their designs will look, as well as listen to how the acoustics will manifest, and do so in an efficient manner.”

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Nvidia has launched the Nvidia RTX 6000, a high-end workstation GPU built on the company’s new Ada Lovelace architecture, named after the English Mathematician credited with being the first computer programmer.

The Nvidia RTX 6000 GPU is said to deliver up to two to four times the performance of the previous generation ‘Ampere’ Nvidia RTX A6000 and promises to deliver big advances in real-time rendering, graphics, AI and compute, including engineering simulation. It is not to be confused with 2018’s Turing-based Nvidia Quadro RTX 6000.

The Nvidia RTX 6000 is a dual slot graphics card with 48 GB of GDDR6 memory (with error-correcting code (ECC)), a max power consumption of 300 W and support for PCIe Gen 4, giving it full compatibility with workstations featuring the latest Intel and AMD CPUs. It supports Nvidia virtual GPU (vGPU) software for multiple high-performance virtual workstation instances and boasts 3x the video encoding performance of the Nvidia RTX A6000, for streaming multiple simultaneous XR sessions using Nvidia CloudXR.

The Nvidia RTX 6000 offers all the generational improvements you’d expect from a new GPU architecture – third-gen RT Cores for ray tracing, fourth-gen Tensor Cores for AI compute, and next-gen CUDA cores for graphics and simulation – but there are also significant changes in the way the ‘Ada Lovelace’ GPU carries out calculations to increase performance in viz-centric workflows.

Deep Learning Super Sampling 3 (DLSS) and Shader Execution Reordering (SER) are the two technologies that stand out.

Deep Learning Super Sampling 3 (DLSS)

Nvidia DLSS has been around for several years and with the new ‘Ada Lovelace’ Nvidia RTX 6000, is now on its third generation. DLSS uses deep learning-based upscaling techniques where frames are rendered at a lower resolution and the GPU’s ‘AI’ Tensor cores are then used to predict what a high-res frame would look like.

With Nvidia’s previous generation ‘Ampere’ GPUs, DLSS 2 took a low-resolution current frame and the high-resolution previous frame to predict, on a pixel-by-pixel basis, what a high-resolution current frame would look like.

With DLSS 3, the AI generates entirely new frames rather than just pixels. It processes the new frame, and the prior frame, to discover how the scene is changing, then generates entirely new frames without having to process the graphics pipeline. According to Nvidia CEO Jensen Huang, this approach means DLSS 3 will benefit both GPU and CPU limited games.

Huang made no reference to how DLSS 3 might benefit professional 3D applications. However, while DLSS 2 was used mainly in GPU limited viz applications such as Enscape and Autodesk VRED, we wonder if DLSS 3 could deliver big performance improvements for 3D CAD, which tends to be CPU limited.

Shader Execution Reordering (SER)

Nvidia explains that GPUs are most efficient when processing similar work at the same time. However, with ray tracing, rays bounce in different directions and intersect surfaces of various types. According to Huang, this can lead to different threads processing different shaders or accessing memory that is hard to coalesce or cache.

With Shader Execution Reordering (SER), the Nvidia RTX 6000 dynamically reorganises its workload, so similar shaders are processed together. According to Nvidia, SER can give a two to three times speed up for ray tracing and a frame rate increase of up to 25%. Nvidia did not announce which software applications will take advantage of this technology.

Engineering simulation

For the launch of Nvidia RTX 6000, the focus was mainly on graphics-centric workflows. However, Nvidia also dedicated some time to engineering simulation, specifically the use of Ansys software, including Ansys Discovery and Ansys Fluent for Computational Fluid Dynamics (CFD).

“The new Nvidia Ada Lovelace architecture will enable designers and engineers to continue pushing the boundaries of engineering simulations,” said Dipankar Choudhury, Ansys fellow and HPC Centre of Excellence lead. “The RTX 6000 GPU’s larger L2 cache, significant increase in number and performance of next-gen cores and increased memory bandwidth will result in impressive performance gains for the broad Ansys application portfolio.”

Nvidia showed a car model set up for a wind tunnel analysis in Ansys Discovery to perform external aerodynamics simulation with flow inlets, pressure outlets, and wall boundary conditions. It showed how the Nvidia RTX 6000 can allow multiple design alternatives to be explored in real time, demonstrating that when the flow inlet velocity is changed, the results can be viewed instantly.

Nvidia also highlighted the benefits of having 48 GB of memory, explaining that with the Nvidia RTX 6000 users can increase the fidelity of the solver to perform more accurate simulations and still obtain the results in near real time.

The Nvidia RTX 6000 workstation GPU will be available from global distribution partners and manufacturers starting in December.

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KPF’s Environmental Performance team (KPFep) has developed a wind modelling tool for early-stage design studies. The ‘Wind Flow’ app, which utilises the API of cloud-based simulation platform Simscale, is designed to make wind and microclimate studies accessible to architects across KPF.

The Wind Flow app can be used to maximize comfortable spaces with respect to pedestrian wind comfort. It also integrates with outdoor thermal comfort and UTCI calculations, which are critical to KPF’s projects, particularly in hot-humid climates.

Now in beta development, the software is currently used by a handful of architects in KPF’s New York and London offices for competitions and bids, but its integration with Rhino means it will eventually extend its reach to the whole firm.

“Our plan is to deploy this to over 100 architects globally, giving them access to fast and accurate microclimate analysis as and when needed,” said Elias Anka, sustainable design lead in KPF’s London office.

“The aim is to equip our designers with the right toolset and knowledge to tackle climate change and be proactive in designing carbon neutral buildings and cities that prioritize the comfort and wellbeing of occupants.”

With the Wind Flow app, Pedestrian wind comfort (PWC) and building aerodynamics studies take just a few minutes to simulate. From within Rhino, users can quickly select the climate data/location and the number of wind speeds.

A series of dialog boxes appear in turn for architects to configure a wind study. The simulation is then sent to SimScale in the cloud to run, delivering simulation data such as probe point coordinates, result planes, and wind speeds. The results are imported back into Rhino for visualisation.

Simscale uses the Lattice Boltzmann Method (LBM) solver Pacefish which, acording to Simscale, makes it robust when importing complex CAD models. The geometry does not need to be ‘water-tight’, and what used to be classified as ‘imperfect geometry’ for simulation purposes can be worked with directly in SimScale.

The KPF Rhino app has an active development roadmap. Future plans include different types of analysis and new powerful plugins for designers, such as outdoor thermal comfort, natural ventilation studies, and possibly moving to more indoor environmental analysis.

Caption: A new build project in London. The coloured streamlines show an incident wind from the right. The building has been simulated in a virtual wind tunnel using SimScale. Courtesy of KPF and SimScale.

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