CDFAM Computational Design Symposium

Duann Scott

Recordings of presentations from the CDFAM Computational Design Symposium held worldwide. Leading experts in computational design, AI and machine learning for industrial design, engineering and architecture from industry, academia and software development. www.designforam.com

  1. 2d ago

    The Era of Living Machines: How Biology Will Build the Next Generation of Building Materials

    CDFAM Computational Design Symposium — DC 2026 Giorgia Cannici · Virginia Tech What if material fabrication could shift from assembly to growth—and be directed with precision through external fields? This work introduces magnetotropic plants: genetically engineered organisms in which gravity-sensing organelles (statoliths) are rendered magnetically responsive. By replacing gravitational cues with externally applied magnetic fields, plant growth direction can be actively controlled in real time. This enables programmable morphogenesis, where biological growth becomes a steerable process rather than a fixed outcome of genetics and environment. The presentation will outline the biological mechanism, the experimental framework, and the implications of this approach for material production. Magnetic fields act as an invisible, non-contact control layer, allowing spatial and temporal guidance of growth without mechanical intervention. Beyond applications in microgravity environments such as space, this work suggests a broader shift in how we produce materials—moving from extractive, energy-intensive processes toward growth-driven fabrication, where form emerges from the interaction between engineered biology and designed environmental conditions. Links Talk page with full transcript Watch the talk on YouTube Search this talk's transcript Cite this talk This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.designforam.com

  2. 4d ago

    From Horns to Armor: Biomimicry, Computational Design, and the Future of Impact Protection

    CDFAM Computational Design Symposium — DC 2026 Matthew Shomper · Not a Robot Engineering Nature has been solving the problem of impact protection for millennia, in order to arrive at solutions far more elegant than anything on the market today. The microstructure of a bighorn sheep’s horn is one of the most striking examples : a geometry that is brutally efficient at scattering and absorbing energy, such that the animal can sustain repeated high-speed collisions without lasting damage. The challenge has always been translating that geometry into something we can actually manufacture. Additive manufacturing allows us to build internal geometries that were previously impossible to fabricate : graded densities, interlocking fiber patterns, and layered structures that mirror what nature spent millions of years optimizing. By digitally modeling the ram’s horn at the microstructural level and translating those patterns directly into printable designs, we can produce armor components that outperform conventional materials in energy absorption while perfectly conforming to the body. This work represents a broader shift in protective equipment design: away from material selection alone, and toward architecture as the primary engineering tool. Links Talk page with full transcript Watch the talk on YouTube Search this talk's transcript Cite this talk This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.designforam.com

  3. 5d ago

    Before the Model: Aurora as AI-Grounded Climate Intelligence for Early-Stage Design

    CDFAM Computational Design Symposium — DC 2026 Damola Michael; Elliot Glassman · CannonDesign The environmental design conversation typically begins too late, after massing is committed and geometry is locked. Aurora repositions that conversation to day one, giving architects and engineers an immediate, evidence-based picture of any site before a design tool is opened. The platform synthesises EPW weather files, CMIP6 climate projections, ASHRAE design conditions, NOAA historical records for US sites, and seismic hazard data into a unified analysis environment, covering temperature and humidity distributions, wind roses, solar radiation by facade orientation, thermal comfort (UTCI, PET, SET), rainfall, carbon intensity, and future projections to 2050. Every analysis is immediately exportable as a formatted PDF or PowerPoint report, ready to present to a client or design team without additional preparation. Two integrated AI layers surface this data as design insight. A streaming conversational assistant powered by Google Gemini is grounded in the actual EPW and CMIP6 data for the active location. It explains what site climate means for design decisions, renders specific charts inside the conversation, and adjusts application settings through natural language. A second layer generates AI-written summary cards for ASHRAE design conditions and 2050 climate outlooks, automatically scoped to the site. Aurora does not generate or evaluate geometry. This is intentional: it is a pre-design climate intelligence layer, not a replacement for tools like Autodesk Forma. It provides the environmental literacy that should inform every decision made in those tools, a shared language between architect, engineer, and client before a single wall is drawn. Links Talk page with full transcript Watch the talk on YouTube Search this talk's transcript Cite this talk This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.designforam.com

  4. 6d ago

    AI-Native, Simulation-Driven Insight with End-to-End Traceability

    CDFAM Computational Design Symposium — DC 2026 Mike Park · Flexcompute Computational design enables wider configuration exploration and reduces time to market, but turning innovation into validated, manufacturable designs is hampered by human-in-the-loop simulation. Manual geometry cleanup, meshing, and data management pace every workflow, while the feedback loops between simulation and the rest of the design organization stay broken by data silos. This talk presents an end-to-end, AI-native approach to closing those loops. GeometryAI applies a novel, topology-aware geometry representation that takes raw CAD to analysis-ready models automatically with mathematical guarantees that facilitate meshing and analysis. Physics-agnostic output feeds CFD, structural, and thermal tools with direct connections to surrogate training and inference. The GPU-native solver Flow360 delivers high-fidelity physics at speeds that tighten feedback loops. Thread ties it together with automatic data lineage, so every run is reproducible, every result is traceable, and institutional knowledge becomes the starting point rather than the bottleneck. Standard web interfaces and Python APIs enable humans and their agents equally. Real-world results are validated with industry-standard AIAA High-Lift Prediction Workshop submissions. Full-aircraft hover analysis is possible in hours. We show how geometry-aware automation, GPU-native simulation, and complete traceability make simulation-driven design genuinely agent-ready, at the scale and speed modern programs demand. Links Talk page with full transcript Watch the talk on YouTube Search this talk's transcript Cite this talk This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.designforam.com

  5. Sep 29

    Optimal Lattice Selection for PCM Thermal Management

    CDFAM Computational Design Symposium — DC 2026 Andreas Vlahinos · Advanced Engineering Solutions PCMs provide cooling without requiring an extra power source, unlike fans or active liquid cooling systems. They absorb peak energy loads during operation and release that heat when the ambient temperature drops, acting as a buffer against rapid temperature changes. This allows for more compact thermal management systems. Because most PCMs have inherently low thermal conductivity, they often fail to absorb or release heat quickly enough for high-demand applications. Designers can significantly improve the thermal performance of Phase Change Materials (PCM) by embedding lattice structures. Embedding a highly conductive lattice, such as aluminum or copper, forms a “thermal skeleton” that functions as a heat highway, dissipating heat more quickly and evenly through the PCM. Adding a 3D-printed metal lattice can increase the effective thermal conductivity of a PCM system by an order of magnitude compared to pure PCM. The internal structure provides a continuous path for heat conduction, which can double the melting speed. Beyond thermal benefits, the lattice provides mechanical support to the PCM, preventing leakage and helping it maintain its shape during the liquid phase. Simulating PCMs’ thermal behavior is difficult due to the highly nonlinear nature of latent heat release, the shifting phase-change boundaries, and the significant differences in physical properties between the solid and liquid states. This presentation demonstrates simulation techniques and showcases the process of optimal lattice selection. Links Talk page with full transcript Watch the talk on YouTube Search this talk's transcript Cite this talk This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.designforam.com

  6. Sep 29

    Git for Hardware: Version Control as the Foundation for Agile Systems Engineering

    CDFAM Computational Design Symposium — DC 2026 Steve Massey · SysGit Software development was transformed when version control became infrastructure rather than afterthought. Hardware engineering has not had an equivalent transition. Requirements live in documents. System models are stored in vendor-locked platforms. Design reviews happen in meetings rather than pull requests. The result is programs that cannot iterate at the speed the environment demands. SysGit applies the tools and workflows that scaled software development — branching, merging, diffing, CI/CD pipelines — directly to systems engineering artifacts, built on SysMLv2 and backed by existing Git infrastructure. Requirements, system models, and verification activities are captured in a single machine-readable format, traceable across the full program lifecycle and accessible to every stakeholder from specialist engineers to contracting officers. This presentation covers the technical architecture behind that approach, the role of agentic AI in automating requirements generation and model validation, and what continuous acquisition looks like when the digital thread is built on open standards rather than walled gardens. Links Watch the talk on YouTube Search this talk's transcript Cite this talk This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.designforam.com

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Recordings of presentations from the CDFAM Computational Design Symposium held worldwide. Leading experts in computational design, AI and machine learning for industrial design, engineering and architecture from industry, academia and software development. www.designforam.com

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