Computational Design Methods

Traditional surrogate-based design optimization (SBDO) is hitting a wall, especially with high-dimensional, complex designs. In this new paper, Dr. Namwoo Kang presents a next-gen framework using generative AI, integrating three key models: - Generative model (design synthesis) - Predictive model (performance estimation) - Optimization model (iterative or generative) Rather than optimizing directly in a high-dimensional design space (x), the workflow introduces a low-dimensional latent space (z) learned via generative models. ➡️ z → x → y z = latent variables x = CAD geometry y = performance (drag, stress, etc.) This means we’re no longer hand-coding design parameters or doing trial-and-error with simplified surrogate models. 🧠 Why this matters: - Parametric modeling is no longer a bottleneck - Complex shapes are learned directly from CAD - Dynamic and multimodal performance data (1D, 2D, 3D) can be used - Near real-time optimization is possible #AI #GenerativeDesign #CAE #DesignOptimization

Ever wondered why some park benches are always full… and others are always empty? We all have our favorite spots in the park - maybe it’s a sunny grassy patch for lunch, or a shady bench for reading. But there are also those dark, windy corners that everyone seems to avoid. Our Computational Design team has been exploring how microclimate analysis can help us design public spaces that people actually want to use - all year round. By understanding how temperature, wind, and sun interact in a specific location, we can place features like bike racks, cafés, and even loading docks exactly where they make the most sense, both for comfort and for function. Here’s how we do it: 1️⃣ Simulate the wind. We run CFD simulations in #OpenFOAM for the specific site, then collect data on temperature, humidity, wind speed, and sunlight. This is fed into Grasshopper for a Perceived Temperature Analysis, and into #ParaView to visualize the wind streamlines. 2️⃣ Assess comfort with #UTCI. The Universal Thermal Climate Index helps us evaluate which areas are best for relaxing, exercising, or other public uses. These results are integrated into our #Rhino model, with 3D assets showing activities, temperatures, and wind flows. 3️⃣ Bring it to life. Finally, we create a camera path in a rendering engine so clients can see and feel how different parts of the park, street, or plaza will be experienced throughout the year. In one recent project, this approach helped us design pocket parks that extend the outdoor comfort season by sheltering visitors from wind - turning those “empty spots” into vibrant, welcoming places. Great work by our 💚 Computational Design team 💚!

New publication from the Form Finding Lab, now available in Computer Methods in Applied Mechanics and Engineering. Our paper presents an accelerated simulation and design optimization framework for multi‑stable elastic rod networks (ERNs), with applications in adaptive structures, aerospace engineering, and soft robotics. ERNs exhibit rich nonlinear and multi‑stable behavior, but their proximity to unstable equilibria makes conventional simulation and optimization approaches computationally challenging. To address this, we introduce a spline‑based least‑squares formulation for solving the Kirchhoff rod boundary value problem, enabling robust and efficient simulations. The framework is applied to networks composed of bistable bigons assembled into articulated bigon arms. Benchmarks demonstrate significant improvements in computational efficiency and robustness compared to traditional boundary value problem solvers. Building on this, we introduce a physics‑based shape optimization method that allows ERNs to be optimized to approximate target curves and end‑plane constraints. The approach is validated through numerical experiments and physical prototypes. Article link: https://lnkd.in/egNEhktw Reference: Larsson, A., Hayashi, K., Adriaenssens, S. (2026). Accelerated simulation and design optimization of elastic rod networks with a spline‑based least‑squares formulation. Computer Methods in Applied Mechanics and Engineering, 456, 118925. https://lnkd.in/ezV3VWH6 Image credit: Axel Larsson

Sean McNamara Studios Presents: Computational Concrete - When Digital Fabrication Meets Material Tradition Exploring AI-Enhanced Geometry and Advanced Forming Techniques in Contemporary Concrete Architecture These architectural studies demonstrate how computational design and advanced fabrication are revolutionizing concrete construction, enabling organic sculptural forms that challenge assumptions about this traditionally rigid material's expressive possibilities. The flowing ribbon-like sculptural elements showcase concrete's emerging plasticity when liberated by digital design tools and precision forming systems. These sinuous forms—with smooth curves, twisted geometries, and impossible-seeming cantilevers—suggest advanced fabrication including CNC-milled formwork, robotic concrete deposition, or AI-optimized structural geometries balancing aesthetic ambition with engineering feasibility. The material contrast proves essential to the design language. The board-formed concrete walls display traditional construction's honest texture—horizontal formwork lines revealing the construction process and material authenticity. Against this deliberately rough backdrop, the smooth sculptural interventions read as technological achievement, creating dialogue between craft tradition and digital innovation. The transparency strategy maximizes the sculptural forms' visual impact. Large glass planes allow the concrete sculptures to be appreciated from multiple vantage points—visible from exterior as facade elements and from interior as spatial focal points. This transforms the sculptures from applied decoration into integrated architectural elements that organize spatial experience. The geometric variation across the three studies demonstrates computational design's flexibility. The first presents flowing textile-like draping, the second explores angular faceted geometry, while the third achieves ribbon-like twisting suggesting movement frozen in concrete. This formal diversity proves that advanced fabrication enables architects to explore multiple geometric languages within single material systems. The AI-enhancement potential lies in optimization algorithms calculating complex geometries that balance aesthetic intent, structural performance, material economy, and constructability—generating forms nearly impossible through traditional design methods while ensuring buildability within budget and timeline parameters. These sculptures demonstrate concrete's potential as expressive medium when digital tools unlock its plastic qualities, challenging brutalism's legacy while honoring concrete's essential material character through honest expression of its fluid origins. How do you see computational design and advanced fabrication transforming concrete architecture? #SeanMcNamaraStudios #ComputationalDesign #ConcreteArchitecture #DigitalFabrication #AIArchitecture #ContemporaryArchitecture #ArchitecturalInnovation

Presenting a parametric workflow developed for a complex architectural project. Built in #Grasshopper and integrated with #RhinoInsideRevit, this script generates the Building Envelope Mesh and automates the creation of underlying structure, and GFRC facade elements directly within Revit. Key highlights:   - Automated #BIM element generation with complete data and parameters.   - Seamless integration between computational design and BIM environments.   - Flexible, rapid iteration for precise control over structural and facade systems. Beyond the facade, the workflow also:   - Designs the structural framework for an organic dome.   - Positions windows to maximize natural lighting conditions.   - Optimizes site components, including paths, roads, and communication areas. This script consolidates multiple complex systems into a unified parametric process, enabling efficient coordination and accurate BIM documentation. Developed by Eltun A. VAMI P.S. Probably one of the biggest Grasshopper scripts in the world. #ParametricDesign #Grasshopper3D #RhinoInsideRevit #BIM #GFRC #FacadeDesign #ArchitecturalEngineering #ComputationalDesign

🚀 𝐓𝐨𝐩𝐨𝐥𝐨𝐠𝐲 𝐎𝐩𝐭𝐢𝐦𝐢𝐳𝐚𝐭𝐢𝐨𝐧: 𝐓𝐡𝐞 𝐅𝐮𝐭𝐮𝐫𝐞 𝐨𝐟 𝐒𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐚𝐥 𝐃𝐞𝐬𝐢𝐠𝐧 In today’s engineering world, the focus is shifting toward design efficiency, performance improvement, and sustainability. One of the most powerful methods driving this transformation is Topology Optimization. 🔹 𝑾𝒉𝒂𝒕 𝒊𝒔 𝒊𝒕? Topology optimization is a computational design approach that determines the most efficient way to distribute material within a defined design space—considering loads, constraints, and performance goals. 🔹 𝑾𝒉𝒚 𝒊𝒕 𝒎𝒂𝒕𝒕𝒆𝒓𝒔? ✅ Weight reduction ✅ Improved performance ✅ Cost savings ✅ Sustainability ✅ Design innovation ✅ Additive manufacturing compatibility ✅ Multiphysics integration 🔹 Industry Applications: Airbus – Wing rib for A380 optimized → ~40% lighter & 20% stiffer GE Aviation – Fuel nozzle redesigned via topology optimization & 3D printing → reduced part count, higher efficiency Volkswagen – Steering bracket optimized → ~50% lighter BMW – Engine mount redesign → 20% lighter, 15% cheaper ANSYS & Frustum – Medical & patient-specific implants optimized for strength and functionality Boeing – Structural aerospace systems via open-source FEM (Z88) From aerospace to automotive, medical to defense, topology optimization is revolutionizing the way we design and manufacture components. 🌍 The future of structural design lies not in adding more material, but in using material smartly. 🔧 As engineers and designers, embracing these methods will be key to building lighter, stronger, and more sustainable systems. 💡 What’s your take—Do you see topology optimization becoming a standard design practice across industries in the next decade? #Engineering #Design #TopologyOptimization #FiniteElementAnalysis #Innovation #Sustainability #AdditiveManufacturing #FiniteElementAnalysis #StructuralDesign #AdditiveManufacturing #DesignEngineering #GenerativeDesign #LightweightDesign #AerospaceEngineering #AutomotiveEngineering #MedicalDevices #SustainableDesign #FutureOfDesign #MechanicalEngineering #ProductDevelopment #EngineeringInnovation #AdvancedManufacturing #CADDesign #EngineeringExcellence #SmartDesign #3DPrintingInnovation #NextGenEngineering #EngineeringCommunity

🏦🗝️ Finite Element Method (FEM) — How Engineers Turn Reality Into Numbers Most people see FEM as a giant matrix problem. But once you understand the story behind it, it becomes beautifully simple. FEM is nothing more than: ➡️ Break a complex shape into small pieces ➡️ Explain how each piece deforms ➡️ Connect all pieces together ➡️ Let mathematics do the stitching That’s it. FEM is not magic — it’s organization. 🔒 The Entire FEM Workflow in One Intuitive Line: Define → Discretize → Stiffen → Assemble → Solve → Interpret Every FEM software LS-DYNA, Abaqus, ANSYS, SAP etc. follows this storyline. 🔹 STEP 1 — Define the Problem The structure, the material, the supports, the forces. You tell the computer what world you’re building. 🔹 STEP 2 — Discretize the Geometry You chop reality into tiny elements. Why? We discretize because a whole structure is too complex to model directly but a tiny element follows clean, well-defined mechanics. A mesh is simply the structure sliced into pieces that obey simple rules 🔹 STEP 3 — Stiffness of Each Element Each element says: “Here’s how I stretch, bend, or twist if you push me.” That’s the element stiffness matrix [k]. 🔹 STEP 4 — Assemble the Global System Now comes the magic. All elements join hands at their nodes. Their stiffness matrices merge into one giant master matrix [K]. This is where the structure becomes a single system. 🔹 STEP 5 — Write the Global Equation F=[K]U Three symbols that run the entire world of simulations: F → What you apply K → What the structure is U → How it reacts 🔹 STEP 6 — Solve With supports and loads applied, the solver finds the unknown nodal displacements U. Once U is known, the structure’s stresses and internal forces reveal themselves. This is the moment the structure comes alive. 🔹 STEP 7 — Extract Stresses & Strains Displacements are the key. Once each node’s movement is known, the solver computes ε from element deformation, σ from material laws, and then identifies cracking, plastic zones, and failure modes. The hidden mechanics become visible. You finally “see” what the structure has been hiding. 🧱 Why FEM Is Beautiful Because FEM doesn’t guess. It listens to the geometry, the material, the loads, the constraints and then it tells you the most honest version of how the structure will behave. 🗝️ Final Thought FEM is not hard. You just need to see the storyline behind the matrices. Once the story clicks, every simulation from a beam to a skyscraper becomes intuitive. 🔒 Save this post if you want FEM to finally make intuitive sense. 🗝️ And if you want a deeper dive, check the article in the first comment. pic credits: https://lnkd.in/dHZP94rH #StructuralEngineering #FEM #FiniteElementMethod #LSDYNA #Abaqus #EngineeringIntuition #StructuralVault

The Architecture Firm of 2027: One Person + One AI I just built something that should make traditional AEC firms very nervous. A parametric tower designer that generates a complete 3D structural model—columns, beams, slabs, cores, stairs, façades—in seconds. No installs. Runs entirely in your browser. Fully editable. Exports to IFC. But here’s the real revolution: It has a central AI brain. When I want a new façade algorithm, I describe it. “Organic fins with simplex noise.” The AI builds it, tests it, deploys it. Minutes—not months. This is what people miss: Traditional firms rely on: Modelers → replaced by AI generation Visualizers → replaced by real-time 3D + AI rendering Code teams → replaced by AI that reads building codes Cost estimators → replaced by instant BOQ analysis Coordinators → replaced by AI-managed data flow Project managers → replaced by AI orchestration One person with this system = an entire firm. You’re not just designing faster—you’re collapsing the whole organizational chart into a conversation with AI. Every discipline, every workflow, every iteration becomes a prompt. Architecture graduates of 2027 won’t be learning Revit. They’ll be learning how to orchestrate intelligent systems that design, analyze, visualize, and manage on command. If your process still looks like: Export from Revit → Send to render farm → Wait for consultant feedback → Manually coordinate you’re designing like it’s 2015. The divide between AI-native studios and traditional firms will soon be unbridgeable. 2026–2027 isn’t the future. It’s next year. The question isn’t whether AI will replace jobs. It’s who controls the AI—you or your replacement. Web-native. Real-time. Conversational. Infinitely extensible. This is computational design once you step outside the #walls of legacy software. #AIArchitecture #ComputationalDesign #ParametricDesign #AEC #GenerativeDesign #FutureOfWork #ArchitectureInnovation

They introduce a pioneering computational approach to enhance the morphological design of #robots. Their framework accepts a parameterized robot design and a motion plan, encompassing trajectories for end-effectors and, optionally, the body. The algorithm optimizes design parameters, including link lengths and actuator placements, while concurrently adjusting motion parameters like joint trajectories, actuator inputs, and contact forces. The key insight lies in establishing the intricate relationship between design and motion parameters through sensitivity analysis, assuming the robot's movements are modeled as spatiotemporal solutions to an optimal control problem. This connection between form and function enables automatic optimization of the robot design based on specifications expressed as a function of actuator forces or trajectories. The model undergoes evaluation by computationally optimizing four simulated robots utilizing various actuators. They further validate the framework by optimizing the design of two small quadruped robots and assessing their performances through hardware implementations. #authors: Sehoon Ha, Stelian Coros, Alex Alspach, James Bern, Joohyung Kim, Katsu Yamane #research #papers: https://lnkd.in/dde8udvV, https://lnkd.in/dgi8KNWE #robotics #projects #technology 

𝐅𝐫𝐨𝐦 𝐁𝐈𝐌 𝐭𝐨 𝐓𝐑𝐈𝐌 ... Here is The largest shopping mall in Beijing , China 𝔾𝔸𝕃𝔸𝕏𝕐𝕊𝕆ℍ𝕆 by Zaha Hadid Architects ... ✨ 𝐆𝐀𝐋𝐀𝐗𝐘 𝐒𝐎𝐇𝐎 has four domed volumes coalesce together via bridges and platforms, thus creating a fluid and 𝐝𝐲𝐧𝐚𝐦𝐢𝐜 world of continuous open spaces within the 𝐜𝐨𝐦𝐩𝐥𝐞𝐱 inspired from courtyards of the neighborhood and Rice Fields Contours . 𝐂𝐎𝐍𝐒𝐓𝐑𝐔𝐂𝐓𝐀𝐁𝐈𝐋𝐈𝐓𝐘 The 𝐝𝐢𝐠𝐢𝐭𝐚𝐥 free-form design processes arising from the use of tools such as subdivision surface modelling in 𝐌𝐚𝐲𝐚 and 𝐑𝐡𝐢𝐧𝐨. In this case, the interplay between a fluid, dynamic design language that is deliberately unconstrained by premature concerns of constructability, and the sensitive maxima, and, often, an understood range of 𝐜𝐨𝐬𝐭 implications . 𝐅𝐈𝐋𝐄 𝐓𝐎 𝐅𝐀𝐁𝐑𝐈𝐂𝐀𝐓𝐈𝐎𝐍 – 𝗆𝖺𝗒𝖺 + 𝖼𝖺𝗍𝗂𝖺  The more sophisticated parametric tools available today include decision-making nodes that allow the 𝐦𝐨𝐝𝐞𝐥 to have a certain degree of ‘intelligence’, in the sense that, depending on real-time modifications to the geometry, the 𝐩𝐚𝐫𝐚𝐦𝐞𝐭𝐫𝐢𝐜 construct of the model can react by modifying the detail assemblage according to different rules based on particular decision trees. For example, in the 𝐂𝐀𝐓𝐈𝐀 system these are referred to as ‘checks’, ‘rules’ and ‘reactions’, and constitute a form of user-defined 𝐚𝐫𝐭𝐢𝐟𝐢𝐜𝐢𝐚𝐥 𝐢𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞 (in the classic computer science definition of 𝐀𝐈) that can be used to govern the detailing of a design within a finite set of possible outcomes. Utilizing 𝐂𝐀𝐓𝐈𝐀 𝐕𝟓, the entire building and its assembly was fully developed and evaluated first in a virtual environment. Coupled with an extensive development on computational design, the entire building information modeling process was fully automated, enabling the successful project delivery on time and on budget. 𝐃𝐈𝐆𝐈𝐓𝐀𝐋 𝐌𝐀𝐍𝐔𝐅𝐀𝐂𝐓𝐔𝐑𝐈𝐍𝐆 The team shared their Building Information Modeling (𝐁𝐈𝐌) data with their selected construction manufacturer, providing accurate measurements to ensure a smooth construction process. 𝐒𝐔𝐒𝐓𝐀𝐈𝐍𝐀𝐁𝐈𝐋𝐈𝐓𝐘 the complex adopts water-efficient systems that recycle greywater. The implementation of the system results in a reduction in overall water usage by at least 𝟐𝟎%. The Beijing Galaxy SOHO building saves its energy consumption by 𝟏𝟒% by using highly efficient lighting fixtures, air ventilation systems, and a double-glazing exterior envelope. 𝐒𝐎𝐅𝐓𝐖𝐀𝐑𝐄𝐒 - Autodesk : 𝖬𝖠𝖸𝖠 – 𝖱𝖧𝖨𝖭𝖮 – 𝖦𝖱𝖠𝖲𝖲𝖧𝖮𝖯𝖯𝖤𝖱 – 𝖱𝖤𝖵𝖨𝖳 – 𝖢𝖠𝖣 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭 : Zaha Hadid Architects 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫 : Newtecnic 𝐁𝐈𝐌 : Cristiano Ceccato + Chikara Inamura #bim #autodesk #revit #cad #rhino #maya #architecture #engineering #construction #design