AI / Machine Learning
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[L-AU-226] Fully Leveraging the Power of JMAG via AI Using the JMAG Script Library
JMAG Script can automate almost every function in JMAG. The JMAG Script Library makes sample scripts for the various operational procedures to use for AI training or reference.
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[L-AU-225] Accelerating Data-Driven Design to the Limit with AI
We are transitioning from an era of "humans operating tools" to a new paradigm where "AI agents operate JMAG to deliver autonomous design." Through synergy with AI, JMAG is accele…
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[JFT213] Offline Optimization Using Response Value Surrogate Model and Geometry Check Surrogate Model
This tutorial describes the procedures to export a geometry check surrogate model from an optimization run with a response value surrogate model to execute an optimization that re…
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[JAC319] Design Exploration of an IPM Motor Using an Offline Optimization
This document introduces a process for an offline optimization run using a surrogate model to explore design solutions that satisfy the requirements in less time while also reduci…
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Machine learning in traction motor design – fragile hype or real revolution? An experience report.
Louis Jäkel, IAV Japan Co., Ltd.
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Data-Driven Optimization of E-Machines Considering the Powertrain of Electric Vehicles
Maximilian Clauer, Dr. Ing. h.c. F. Porsche AG
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[JFT188] Creation and Use of Surrogate Models Using Multiple Analysis Case Results
This document describes the procedures to create a surrogate model using results from an analysis with multiple cases to review response value maps by calling that surrogate model…
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[JFT198] Rapid Design Exploration Using Surrogate Models
This document provides a sample file of a book with Excel macros that explore designs using surrogate models. This document describes how to use this book with Excel macros to obt…
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[JFT152] Output of Response Values Using Surrogate Models
In this document, a macro is provided for quickly evaluating the results obtained by design parameter combinations using surrogate models. This document, as a workflow for paramet…
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[JFT146] Optimization Calculation Using Surrogate Models
This document describes as the workflow for optimization calculations using surrogate models creating training data, creating the sample case, and using a surrogate model in runni…
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The Future of R&D and Design: What Can Electromagnetic Field Analysis and Artificial Intelligence Do for You?
Hajime Igarashi, Hokkaido University
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Smart Motor Control Technology Evolving with AI – Virtual Sensors and Fault Detection –
Atsushi Katagiri, MathWorks Japan
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1 : JMAG-Ansys-Optimus Electromagnetic Field-Structure Analysis 2 : AI and PIDO Integration -Fast non-parametric shape optimisation-
Mio Hashiba, CYBERNET SYSTEMS CO., LTD.
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Electrical, Electronics and Information Engineering, Engineering, Nagaoka University of Technology
Value the challenges in developing new technologies, and taking the initiative in motor structure innovations
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Automatic Design System for Permanent Magnet Synchronous Motors Using Deep Generative Model
Yuki Shimizu, Ritsumeikan University
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Calculation Cost Reduction Method in Multi-Objective Optimization Using Machine Learning: Case Study on Actuator Development
Tomohiro Kuroda, AISIN CORPORATION
