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.

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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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Mott MacDonald Ventures, the strategic corporate venture arm of the global engineering, consultancy, has made an equity investment in Spanish software and engineering start-up SAALG Geomechanics.

SAALG’s Daarwin software provides an analytical capability for assessing ground behaviour during the construction stage of civil engineering and building projects. In the future the aim is to cover the entire lifecycle of civil projects, from planning and design to construction and maintenance.

Daarwin is designed to overcome the limitations of laboratory and in-situ testing by using ‘real time backanalysis’, a methodology that compares monitoring data (such as topography, inclinometers, sliding micrometers, piezometers etc.) to a digital twin (numerical models) to provide a more accurate representation of the real soil behaviour

According to Mott MacDonald, it supports the ‘Observational Method through Progressive Modification’ which its geotechnics practice has pioneered. The ambition is for SAALG’s platform to enable a shift in the industry towards performance-based design, using the observational method.

SAALG Geomechanics plans to offer its technology as Software as a Service (SaaS) integrated with Mott MacDonald’s Moata digital platform, providing Daarwin through a subscription-based model that includes a training plan to enable qualified teams to use the tool.

“This operation is a strategic move in the SAALG Geomechanics business model,” said Cristian de Santos and Ignasi Aliguer, SAALG Geomechanics founders. “We envision Daarwin to be a standard in construction, used by engineers all around the world. The aim is to become a global platform, for large volumes of geotechnical data at the service of the construction sector.”

The investment forms part of a Euro 0.5M funding round led by Mott MacDonald Ventures.

Others participating in the latest round are Scale Lab Andorra, the hyper-acceleration business program of Crèdit Andorrà and CEMEX Ventures.

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Bentley Systems has acquired Inro Software, a specialist in multimodal transportation planning, traffic simulation, and mobility visualisation software.

The company’s tools are used by metropolitan, regional, and national transport and transit operators and planning agencies. Customers include some of the world’s busiest transit systems and metros, such as Transport for London, Transport for New South Wales, the Washington State Department of Transportation, the Swedish Transport Administration Trafikverket, and the public transport system of São Paulo SPTrans.

Inro’s products include Emme, a multimodal transportation planning system for urban, regional, and national transportation forecasting; Dynameq, a vehicle-based traffic simulation platform for city-wide traffic planning; and CityPhi, a mobility visualisation solution providing data visualisation and visual analytics of large-scale mobility and geospatial datasets.

Bentley intends to combine Inro’s traffic and vehicle simulation capabilities with its passenger and pedestrian simulation and civil design software – including Cube, Streetlytics, Legion, and OpenRoads – to deliver ‘mobility digital twins’ of multimodal transportation systems at urban, metropolitan, regional, and national scale.

Mobility digital twins, which can be continuously updated with as-operated engineering conditions and with observed traffic data, will help infrastructure planning and simulations become continuously valuable throughout engineering, construction, and operations. According to Bentley, this is in contrast to traditional workflows where transportation modelling tools are used in isolation and only on occasion.

A key aim is to help urban planners better understand the ongoing impacts – on transportation system performance, reliability, and accessibility – of the new opportunities and challenges of private and shared mobility, the propensity for cycling or walking, connected autonomous vehicles, and potential congestion charging.

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