Design Exploration / Optimization

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  1. [JFT058] Creating Efficiency Maps Using JMAG-Designer (Speed Priority Mode)

    This document describes how to create efficiency maps using a JMAG-Designer efficiency map study (prioritizing speed).

  2. [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…

  3. [JFT124] Searching for the Parameter Range Reducing Geometry Collapse During Optimization Calculations

    This document describes the method for using the functions useful in searching parameter ranges that reduce geometry collapse during optimization calculations.

  4. [JFT131] Evaluating Degrees of Similarity for Geometry Using NGnet Weight

    This document describes a method where after executing topology optimization using NGnet, degrees of similarity for geometry from NGnet weight are evaluated.

  5. [JFT125] Inheriting Operating Points Between Modes in Efficiency Map Studies

    This document describes the method for using operating point information obtained with speed priority mode in accuracy priority mode.

  6. [JFT122] Executing Optimization Calculations Using Reduced Order Models

    This document describes the method for executing simple analysis and optimization using a reduced order model.

  7. [JFT132] Simultaneous Parameter and Topology Optimization

    This document describes the method for optimizing parameters and topology simultaneously.

  8. [JFT136] Sending SSH Settings to Remote Machines

    This document describes the method for sending SSH settings configured on local machines to remote machines for executing other case calculations.

  9. [JFT112] Defining Response Values with Scripts in Topology Optimization Using NGnet

    In this document, response values are calculated using a Python script, and a method for performing topology optimization used as an objective function is described.

  10. [L-OP-25] Utilizing JMAG in Cloud Services

    More cloud services for CAE continue to be offered. This allows sufficient computational resources to be used when needed to perform analysis work. Refer to the table at the botto…

  11. [W-OP-96] Necessity of GA for Multi-Objective Optimization of Drive Motor

    In this paper, the multi-objective optimization calculation has 12 design variables (8 geometric variables, 4 circuit variables) with 6 objective functions (maximize torque, minim…

  12. [L-OP-34] Using MATLAB’s Optimization Engine in JMAG

    MATLAB is widely used in the engineering field, and the MATLAB Global Optimization Toolbox is often used for optimization calculations also.

  13. AI Technology with Aid of Data-driven Method Makes EM Simulation and Optimization More Effective

    Hajime Igarashi, Hokkaido University

  14. Reduction of Optimal Design Time for IPMSMs for Automotive Applications Using Machine Learning

    Yuki Shimizu, Osaka Prefecture University

  15. 3D Design of Magnetic Components by Gaussian Kernel Regression -Forward Design and Inverse Design-

    Yuki Sato, Texas Instruments Japan Limited

  16. Application of SIMP-based Topology Optimization in JMAG

    Sukhwa Jung, DENSO CORPORATION

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