Overview
Electromagnetic devices are everywhere in our daily lives, from consumer electronics and home appliances to electric vehicles and electric aircraft.
Traditional simulations of electromagnetic components rely heavily on numerical methods, such as the finite element and boundary element methods. With scientific machine learning (ML) advancements, mainly geometric deep learning and physics-informed ML, solving the governing equations of electromagnetic phenomena is more efficient by combining numerical solutions and artificial intelligence (AI) and ML techniques.
This presentation will showcase the workflow of using Ansys Maxwell and HFSS, our gold-standard electromagnetic simulation tools, and Ansys SimAI for electromagnetic field training and prediction. This combination transforms the design and analysis of electromagnetic components by reducing the field prediction time by tens to hundreds of times.
Several application scenarios, such as predicting the distributed magnetic force on PCB traces, characterizing the performance of electric traction motors, and detecting magnetic interference caused by permanent magnets in consumer electronics devices, highlight the advantages of Ansys Electronics Desktop tools and Ansys SimAI. We'll also discuss workflow automation using Python APIs and integrating SimAI into Ansys Electronics Desktop.
What you will learn
- How to create your first ML model with little coding experience by SimAI
- How to make 3D field predictions with SimAI and explore the design space of electromagnetic components
- When should SimAI be used for solving electromagnetic problems
- Benefits of using SimAI with a variety of tools available in Ansys Electronics Desktop
Who should attend
Electromagnetic Simulation Engineers & Analysts in all industries and Academia.
Speaker
Peng Han