Tutorial

Generating a Coffee Cup Thermal Model from a Schematic with Dyad's Agentic AI

Tutorial

Generating a Coffee Cup Thermal Model from a Schematic with Dyad's Agentic AI

Date Published

Nov 6, 2025

Nov 6, 2025

Speakers

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Date Published

Nov 6, 2025

Speakers

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Watch how Dyad's AI agent builds a complete thermal model from just an image! In this video, we demonstrate Dyad's agentic workflow by recreating a coffee cup cooling model originally developed by Dr. Clément Coïc—starting only from a schematic image and simulation plots. The AI agent:

  • Analyzes the thermal model schematic and identifies all components

  • Generates parameter calculation scripts with physical correlations

  • Implements the complete model in Dyad with documentation

  • Calibrates the model using Dyad Model Optimizer to match reference results

  • Creates custom visualizations and animations

This video showcases how Dyad transforms model development workflows, from understanding physical systems through images to generating production-ready code. Whether you're working with hand-drawn schematics, PowerPoint diagrams, or standard system drawings, Dyad's AI agent can help translate visual representations into validated physical models. *Key Highlights:*

  • Image-to-model generation with automatic component identification

  • Automated parameter calculations with physical insights

  • Model optimization and calibration workflows

  • Custom visualization and animation generation

  • Complete Julia code generation with documentation

Speakers

Dr. Chris Rackauckas is the VP of Modeling and Simulation at JuliaHub, the Director of Scientific Research at Pumas-AI, Co-PI of the Julia Lab at MIT, and the lead developer of the SciML Open Source Software Organization. He is the lead developer of the Pumas project and has received a top presentation award at every ACoP in the last 3 years for improving methods for uncertainty quantification, automated GPU acceleration of nonlinear mixed effects modeling (NLME), and machine learning assisted construction of NLME models with DeepNLME. For these achievements, Chris received the Emerging Scientist award from ISoP.

Speakers

Dr. Chris Rackauckas is the VP of Modeling and Simulation at JuliaHub, the Director of Scientific Research at Pumas-AI, Co-PI of the Julia Lab at MIT, and the lead developer of the SciML Open Source Software Organization. He is the lead developer of the Pumas project and has received a top presentation award at every ACoP in the last 3 years for improving methods for uncertainty quantification, automated GPU acceleration of nonlinear mixed effects modeling (NLME), and machine learning assisted construction of NLME models with DeepNLME. For these achievements, Chris received the Emerging Scientist award from ISoP.

Speakers

Dr. Chris Rackauckas is the VP of Modeling and Simulation at JuliaHub, the Director of Scientific Research at Pumas-AI, Co-PI of the Julia Lab at MIT, and the lead developer of the SciML Open Source Software Organization. He is the lead developer of the Pumas project and has received a top presentation award at every ACoP in the last 3 years for improving methods for uncertainty quantification, automated GPU acceleration of nonlinear mixed effects modeling (NLME), and machine learning assisted construction of NLME models with DeepNLME. For these achievements, Chris received the Emerging Scientist award from ISoP.

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Want to get enterprise support, schedule a demo, or learn about how we can help build a custom solution? We are here to help.

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Generating a Coffee Cup Thermal Model from a Schematic with Dyad's Agentic AI

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Generating a Coffee Cup Thermal Model from a Schematic with Dyad's Agentic AI