Author Archives: Jasmine Chokshi

A Next-Gen Approach to Modeling: What Makes ModelingToolkit.jl Stand Out?

By: Jasmine Chokshi

Re-posted from: https://info.juliahub.com/blog/a-next-gen-approach-to-modeling

ModelingToolkit.jl: Advanced modeling & simulation in Julia

ModelingToolkit.jl is a high-performance modeling framework in Julia that integrates symbolic and numeric computations, to meet the needs of scientific computing and scientific machine learning. It combines elements from symbolic computational algebra systems with both causal and acausal equation-based modeling paradigms, offering an extensible and parallelizable environment for complex system modeling.  

Julia’s Alternative to C-Code Generation for Model-Based Engineering

By: Jasmine Chokshi

Re-posted from: https://info.juliahub.com/blog/c-code-generation-julia

Julia enables direct compilation for model-based engineering without C-code generation

For years, a sort of dogma has prevailed in the world of embedded systems and real-time control: if you’re using a high-level language like Python or R for modeling and simulation, you must rewrite your code in C for deployment. But what if there was a better way? What if you could leverage the productivity of high-level languages without sacrificing performance?

A Fresh Approach to Lithium-Ion Battery Simulation: Insights from JuliaCon 2024

By: Jasmine Chokshi

Re-posted from: https://info.juliahub.com/blog/lithium-ion-battery-simulation

JuliaSimBatteries.jl for advanced lithium-ion battery simulation.

Lithium-ion battery models are highly non-linear systems of stiff, partial differential-algebraic equations (PDAEs). One of the key challenges of working with these models is to solve the system of equations over a range of inputs and parameters. Many commercial and open-source battery modeling tools are prone to sporadic failure stemming from issues in setting up, initializing, and solving these systems.