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Discover how the Dyad Agent accelerates model-based engineering workflows through AI-assisted model construction, debugging, and validation for complex engineering systems.
Discover how to accelerate modeling and simulation with Dyad AI Agent by building RLC circuits, running analyses, creating animations, and generating models from images.
Discover how to build interactive dashboards connecting Dyad models with Makie.jl visualizations, using UI elements and 3D charts to enhance model exploration and communication.
Discover how to accelerate modeling workflows using Dyad's standard libraries to build high-fidelity DC motor models across multiple physical domains in Julia.
Master DC motor modeling with Dyad standard library components, PID control implementation, and automatic parameter tuning in Julia for electromechanical systems.
Discover how Julia's compiler advancements enable direct binary compilation for real-time model-based applications, eliminating C code dependencies while maintaining high performance across scientific computing and embedded systems.
Discover how to develop acausal models of suspension systems and automatically tune PID controllers using JuliaSim's cloud platform, combining graphical modeling with in-depth coding capabilities.
Dive into applied modeling with Julia using ModelingToolkit.jl and DifferentialEquations.jl to solve complex engineering problems through symbolic math programming, component-based modeling, and efficient ODE/DAE solutions.
Discover how to solve engineering problems using Julia's powerful modeling capabilities, from symbolic mathematics to component-based modeling and integrated analysis, demonstrated through an Active Suspension System model.
Master PID controller autotuning in JuliaSim, from system modeling and stability analysis to optimizing control performance while maintaining robustness and minimizing noise amplification.
Discover how Dyad leverages JuliaC to generate smaller, faster Functional Mockup Units with 55MB size and 2-minute compilation times using Julia's new workflow.
Discover how to use Dyad's SciML capabilities to automatically identify missing physics in engineering models through Universal Differential Equations and neural networks.
Explore control systems development in Julia, from plant modeling to PID controller design and deployment in this comprehensive 43-minute technical overview.
Discover JuliaC, a revolutionary toolchain for creating executables and shared libraries from Julia code, enabling seamless cross-language integration and deployment.
Master system identification techniques using Julia through hands-on experiments, model estimation, validation, and real-world applications like control systems and fault detection.
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