CDFAM Computational Design Symposium – Détails, épisodes et analyse

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.

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Bridging the CAD-to-Simulation Gap: Integrating Meshing-free Isogeometric Analysis into Industrial Workflows

Saison 7 · Épisode 21

jeudi 1 octobre 2026 • Durée 15:10

Matthew Sederberg · Coreform

The traditional “design-to-analysis” loop is often bottlenecked by the laborious process of mesh generation, which can consume up to 80% of total simulation time. This presentation introduces Coreform IGA for Abaqus, a solution that brings CAD-exact isogeometric analysis (IGA) directly into the Abaqus ecosystem. By utilizing Coreform’s Isogeometric Analysis approach, users can perform high-fidelity simulations directly on CAD geometry, effectively bypassing the need for traditional finite element meshing.

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

Saison 7 · Épisode 20

jeudi 1 octobre 2026 • Durée 16:32

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.

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Optimal Lattice Selection for PCM Thermal Management

Saison 7 · Épisode 19

mardi 29 septembre 2026 • Durée 20:19

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.

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

Saison 7 · Épisode 18

mardi 29 septembre 2026 • Durée 15:00

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.

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CDFAM Computational Design Symposium — Washington DC 2026

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Artificial Intuition: Building an AI Mind for Electromagnetic Design and Engineering

Saison 7 · Épisode 17

vendredi 25 septembre 2026 • Durée 21:54

Michael Frei · ARENA Physica

Most advances in computational design focus on mechanical structure — domains we can visualize and have evolved an intuition for. But as modern hardware becomes increasingly software defined, the unseen and unintuitive world of electromagnetism is taking center stage.

Conventional solvers can simulate fields, yet they cannot imagine new ones. Over the past year, our team has been building toward that capability. At CDFAM NYC and Barcelona, we shared early results from Atlas — an AI that learns electromagnetic behavior inductively from test data rather than deductively from first principles, enabling verification, optimization, and design postulation in domains where classical simulation reaches its limits.

This talk shares our vision for the future of AI-driven electromagnetic design.

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AI-Enabled Assembly Configuration Spaces: Encoding Mechanical Intuition at the Design-Manufacturing Interface

Saison 7 · Épisode 16

vendredi 25 septembre 2026 • Durée 20:34

CDFAM Computational Design Symposium — Washington DC 2026

Sai Nelaturi · C-Infinity

The gap between digital design and physical assembly is not primarily a geometry problem. It is a reasoning problem. Engineering teams spend thousands of hours communicating assembly intent through manual CAD workflows, managing configuration complexity across product variants, and catching fitment and feasibility issues that could have been identified before any metal was cut. The cost is measured in weeks of engineering time per product release cycle.

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Physics AI as a Strategic Advantage: How Physics-based AI Models Are Reshaping U.S. Defense Engineering

Saison 7 · Épisode 15

jeudi 24 septembre 2026 • Durée 20:07

CDFAM Computational Design Symposium — Washington DC 2026

Juan Alonso · Luminary

The next decade of great-power competition will be won or lost in the engineering loop. Adversaries have increased the speed of iteration in hypersonics, undersea platforms, and autonomous aircraft and the U.S. defense industrial base cannot keep up by relying on traditional engineering workflows. Closing that gap requires a step-change in how programs are developed with AI-accelerated engineering.

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Join leading experts in computational design at all scales for two days of knowledge sharing and networking at CDFAM in Tokyo, October 8-9, 2026

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From Text to Robotic Assembly: 3D Generative AI and Discrete Robotic Assembly for Making Physical Objects

Saison 7 · Épisode 11

mercredi 23 septembre 2026 • Durée 11:24

CDFAM Computational Design Symposium — Washington DC 2026

Alexander Htet Kyaw · MIT

Recent advances in 3D generative AI make it possible to create object geometries directly from natural language, but turning these digital forms into functional physical objects remains a major challenge. Most generated 3D models are meshes that do not contain the component level, structural, material, and assembly information required for robotic fabrication. This presentation introduces a research pipeline that combines 3D generative AI, vision language models, and robotic assembly to transform text prompts into multicomponent physical objects. Rather than only asking what an object should look like, the system reasons about how it should be physically composed, including where stronger, lighter, stiffer, or more flexible components are needed. The work points toward a future in which AI driven design systems can generate not only visual form, but also buildable, reusable, and materially informed assemblies for real world fabrication.

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CDFAM Computational Design Symposium — Washington DC 2026

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

Computational Design in Aerostructures: Topology Optimization for Conceptual Design and Trade Studies

Saison 7 · Épisode 9

mercredi 23 septembre 2026 • Durée 17:18

Brandon DeMille · General Atomics Aeronautical Systems

Computational design methodologies, including topology optimization, are transforming airframe structures development by enabling rapid exploration of design configurations during early conceptual phases. This presentation demonstrates a workflow that enables informed decision-making across disciplines and accelerates the path from initial concept to detailed design. A fuselage case study illustrates the simultaneous optimization of composite laminates for skins, substructure geometry, and overall shaping. This integrated approach facilitates quantitative trade-offs among competing priorities such as cost, structural performance, manufacturability, and production rate.

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