Surrogatizing Dynamic Systems using JuliaSim: An introduction.

In this talk, we will discuss the use of surrogates in scientific simulations, and introduce JuliaSim, a commercial offering built on top of the SciML ecosystem, and introduce some of the surrogates available in JuliaSim.

In recent years, the use of surrogates in scientific simulations has become increasingly of interest. Surrogates, also known as digital-twins, are approximate models that are trained to mimic the output of a computationally expensive or complex simulation. They can be used to quickly explore the parameter space of a simulation, tune a controller, or optimize inputs and parameters.

The SciML ecosystem is an open-source project that aims to provide a suite of software tools for scientific modeling in the Julia programming language. It includes a wide range of modeling and simulation tools, including differential equations solvers, optimization algorithms, and surrogate models. The goal of SciML is to make it easy for scientists and engineers to use advanced modeling techniques in their work.

JuliaSim is a commercial offering built on top of the open-source SciML ecosystem. It provides a suite of tools for building and deploying surrogate models in Julia. JuliaSim makes it easy to interface with existing simulation codes and dynamic models and also to train, validate, and deploy surrogates using a wide range of algorithms.

In this talk, we will discuss the use of surrogates in scientific simulations, and introduce JuliaSim and discuss the variety of surrogates available in JuliaSim, including their individual specialties.