Fast Stiff ODE/DAE Solvers via Symbolic-Numeric Compiler Tricks | Rackauckas | JuliaHub What if ODE solvers weren’t just numerical black boxes? In this talk, Dr. Chris Rackauckas breaks convention with Julia by integrating symbolic-numeric techniques into stiff ODE/DAE solvers. Discover ...

What if ODE solvers weren’t just numerical?
Dr. Chris Rackauckas shows how Julia’s symbolic-numeric tricks supercharge stiff ODE/DAE solvers—making them faster & more robust than ever.
Watch here: www.linkedin.com/feed/update/...
#JuliaLang #ModelingToolkit #ScientificComputing

Mitsubishi Electric – Building High-Fidelity HVAC Models with Dyad and Scientific Machine Learning - Event - JuliaHub Learn how Mitsubishi Electric used Dyad and SciML to build a high-fidelity HVAC model that predicts refrigerant mass with less than 2% error.

Accurate refrigerant mass estimation is key to #HVAC efficiency and compliance. Join Mitsubishi Electric + JuliaHub to see how #ModelingToolkit and #SciML enable a #digitaltwin estimator with <2% error using only pressure & temperature data.
juliahub.com/events/mitsu...
#JuliaLang #Simulation #Dyad

Mitsubishi Electric – Building High-Fidelity HVAC Models with Dyad and Scientific Machine Learning - Event - JuliaHub Learn how Mitsubishi Electric used Dyad and SciML to build a high-fidelity HVAC model that predicts refrigerant mass with less than 2% error.

Refrigerant mass estimation in #HVAC just got easier. Join experts from Mitsubishi Electric & JuliaHub for a #webinar on using #SciML + #ModelingToolkit to build a high-accuracy, non-invasive model using just pressure & temp data. juliahub.com/events/mitsu...
#julialang #DigitalTwin #Dyad

Power, Precision, and Performance: Recent Updates to JuliaHub Copy - Blog - JuliaHub Discover the latest JuliaHub updates: reproducible jobs, static code analysis, large file handling, flexible environments, and enhanced admin controls.

A massive new JuliaHub update is here! Focus on reproducibility, flexibility, and control. Introducing #TimeCapsule (immutable job reproduction), #StaticCode Analysis, and automatic Git LFS for large files. Log in to explore the full update! juliahub.com/blog/power-p...
#JuliaLang #ModelingToolkit

Advancing the Goals of the ARPA-E’s DIFFERENTIATE Program with Julia - Case Study - JuliaHub Explore how JuliaHub empowered ARPA-E's DIFFERENTIATE program to optimize HVAC systems, boosting energy efficiency, reducing simulation times, and integrating machine learning for real-time results.

We partnered with ARPA-E to unlock 30% energy savings. See how JuliaHub drove massive efficiency by taking complex HVAC simulations from weeks to real-time.
juliahub.com/case-studies...
#JuliaLang #JuliaHub #ModelingToolkit #SciML #DigitalTwins #MachineLearning #HVAC #SystemModeling #Simulation

What's New With ModelingToolkit - Blog - JuliaHub This is a short preview of Aayush Sabharwal's JuliaCon 2025 talk that explored the growth of ModelingToolkit over the past couple of years.

The package now includes MTKParameters for optimization, improved initialization, dynamic optimization, and new polynomial solvers. It's a major boost for modeling and simulation.
juliahub.com/blog/what-s-...
#JuliaLang #SciML #ModelingToolkit #Engineering #NumericalMethods #ScientificComputing

Julia for Engineers: Modeling Steady-State and Dynamic Systems with Dyad Learn how to model and simulate hydraulic actuators in Julia using ModelingToolkit.jl—covering steady-state and dynamic system behavior in one session.

Struggling to model steady-state & dynamic systems? Our new video shows how engineers use Julia and ModelingToolkit to build a hydraulic actuator model.
Learn a unified workflow to capture both behaviors efficiently.
juliahub.com/company/reso...
#JuliaLang #ModelingToolkit #OpenSource #SciML

Julia for Engineers Part 1 Intro to Julia and ModelingToolkit YouTube video by JuliaHub

See how Julia + ModelingToolkit.jl streamline engineering workflows. Build, analyze & simulate complex systems faster with symbolic + component-based modeling. Watch here: youtu.be/jkHponz0Jok?...

#JuliaLang #ModelingToolkit #Simulation #Engineering

Julia for Engineers: Modeling Steady-State and Dynamic Systems with Dyad Learn how to model and simulate hydraulic actuators in Julia using ModelingToolkit.jl—covering steady-state and dynamic system behavior in one session.

Aug 27, 1 PM ET — free JuliaHub webinar: Julia for Engineers. See how Julia + ModelingToolkit.jl streamline modeling from steady-state to dynamics. Register now: juliahub.com/company/reso...
#JuliaLang #simulation #Engineering #SystemModeling #ModelingToolkit #Webinar

From Equations to Simulation: Modeling Actuators in Julia Learn how to model and simulate hydraulic actuators in Julia using ModelingToolkit.jl—covering steady-state and dynamic system behavior in one session.

Live webinar Aug 27, 1 PM ET — See how Julia + ModelingToolkit.jl make steady-state & dynamic system modeling faster, easier, smarter.

Register here - juliahub.com/company/reso...

#JuliaLang #ModelingToolkit #Simulation #Engineering

Julia for Engineers Part 1: Intro to Julia and ModelingToolkit.jl Join us for the first session of the Julia for Engineers series, where we introduce Julia, a high-performance programming language designed for technical computing.

Unlock faster, more accurate engineering workflows. See how Julia & ModelingToolkit.jl enable symbolic, component-based modeling to build, analyze & simulate complex systems. juliahub.com/company/reso...
#JuliaLang #ModelingToolkit #ModelBasedDesign #Simulation #DigitalEngineering

Julia for Engineers Part 1: Intro to Julia and ModelingToolkit.jl Join us for the first session of the Julia for Engineers series, where we introduce Julia, a high-performance programming language designed for technical computing.

Only 2 days left!
Join us for Part 1 of Julia for Engineers—a live session on #modeling & #simulation with Julia + ModelingToolkit.jl.
📅 July 30 | 1PM ET
🔗 Register now: juliahub.com/company/reso...
#JuliaLang #ModelingToolkit #Engineering #Simulation #Webinar

Julia for Engineers Part 1: Intro to Julia and ModelingToolkit.jl Join us for the first session of the Julia for Engineers series, where we introduce Julia, a high-performance programming language designed for technical computing.

Engineers and researchers: Join our live workshop on July 30 to explore symbolic + component-based #modeling with Julia and ModelingToolkit.jl. Learn to build, #simulate & analyze complex systems.
Register now → juliahub.com/company/reso...
#JuliaLang #ModelingToolkit #Simulation #EngineeringTools

JuliaHub at JuliaCon 2025 JuliaCon 2025 is set to be the biggest yet, and JuliaHub is excited to take part. Join us July 22–26 in Pittsburgh, Pennsylvania.

JuliaCon 2025 is almost here—JuliaHub is ready! We're a Diamond Sponsor with 50+ attendees, 40 speakers, and 50+ sessions covering Dyad, #SciML, and more. See you in Pittsburgh! juliahub.com/blog/juliahu...
#JuliaLang #JuliaCon2025 #OpenSource #ModelBasedDesign #Simulation #Dyad #ModelingToolkit

Power Subsystem Design for Small Satellites in Julia Explore a unified approach to satellite power system design using Julia's open-source tools—fast, reproducible, and ideal for small satellite missions.

Designing #satellite power systems just got simpler. Watch our recorded webinar to see how Julia’s open-source tools enable integrated, high-performance analysis—from orbit #modeling to solar system #simulation —all in one framework juliahub.com/company/reso... #JuliaLang #Aerospace #ModelingToolkit

Open Source Component-Based Modeling with ModelingToolkit - Stochastic Lifestyle Component-based modeling systems such as Simulink and Dymola allow for building scientific models in a way that can be composed. For example, Bob can build a model of an engine, and Alice can build a ...

Component-based modeling isn't just for proprietary tools anymore. #ModelingToolkit brings open source, composable #modeling to scientific computing. Learn how it powers scalable, high-fidelity digital twins from domain-specific components. www.stochasticlifestyle.com/open-source-... #JuliaLang

Machine learning with hard constraints: Neural Differential-Algebraic Equations (DAEs) as a general formalism - Stochastic Lifestyle We recently released a new manuscript Semi-Explicit Neural DAEs: Learning Long-Horizon Dynamical Systems with Algebraic Constraints where we showed a way to develop neural networks where any arbitrary...

New blog post: Machine learning with hard constraints: Neural Differential-Algebraic Equations (DAEs) as a general formalism.

www.stochasticlifestyle.com/machine-lear...

#sciml #ai4science #hardconstraints #neuralnetworks #dae #acausal #modelingtoolkit #julialang #modelica

Hierarchical Component-Based Modeling with ModelingToolkit.jl | Rackauckas, Tiller | JuliaCon 2024 YouTube video by The Julia Programming Language

Explore hierarchical, component-based modeling with ModelingToolkit.jl! Dive into reusable, high-fidelity models & simplify complex systems for efficient #simulation and #optimization. Learn more: youtu.be/OMn9FeVM8NA #JuliaLang #SciML #Numerical #Modeling #ModelingToolkit #juliacon

System identification with Julia: 13 Sensor fusion YouTube video by JuliaHub

Discover the art of System Identification in Julia! Learn how to model a pendulum, fuse #Sensor #Data, and estimate states without bias. Dive into our introductory video series here: youtu.be/BLsJrW5XXcg #JuliaLang #SensorFusion #ModelingToolkit #Modeling

System identification with Julia: 13 Sensor fusion YouTube video by JuliaHub

Explore sensor fusion with Julia! In this tutorial by Fredrik Bagge Carlson, learn how to integrate measurements from sensors with varying sample rates for accurate, bias-free system estimates. See how #ModelingToolkit and #JuliaSim power this process. youtu.be/BLsJrW5XXcg?... #JuliaLang

Improved HVAC Diagnostics - JuliaSim Case Study Learn how JuliaSim's first principles HVAC modeling & scientific machine learning techniques enhanced diagnostic capabilities for vapor-compression cycles.

Improved #HVAC #diagnostics with JuliaSim! Discover how MERL uses #ModelingToolkit and JuliaSim to estimate refrigerant mass with <2% error, boosting efficiency & sustainability. juliahub.com/case-studies...
#julialang #JuliaSim #ScientificComputing #Innovation #simulation #Modeling