The datasheets provide detailed reports on the processing performance of JMAG software.
These reports can be used for decision-making when upgrading current JMAG version or additional licenses as the scale of analysis increases.
Large-Scale Processing
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[DD-001] Performance of Massive Parallel Processing Magnetic Field Analysis Solver for Medium and Large Models
This datasheet presents the computational speed-up performance of the MPP solver with respect to the number of parallels.
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[L-MA-185] Virtual Prototyping Enables Immediately to Validate the Machine Performance
By prototyping and testing motors, design problems can be identified and rework in the mass production stage can be reduced. However, prototyping is costly and time consuming. The…
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Improvement of Motor Design Process through Topology Optimization and Parametric Multi-Objective Optimization
Hisayoshi Takeuchi, DAIHATSU MOTOR CO.,LTD.
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Large-scale Loss Analysis of Large Capacity Synchronous Motors and Comparison with Actual Measurements.
Kohei Matsuura, TMEIC Corporation
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An Effect of Leakage Flux from the Traction Motor to the Resolver
Kan Akatsu, Yokohama National University
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Electromagnetic Vibration and Noise Analysis of Induction Motor Using JMAG and Actran for Realizing Virtual Prototyping
Hayato Naojima, Fuji Electric Co., Ltd.
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Large-scale Simulation and Optimization Using PSL
Kim Bergsro, Volvo Cars
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[JFT164] Searching for a Parameter Range that Reduces Geometry Collapse During Optimization Calculation (For Ver.22.0 or later)
This document explains how to use this useful function to search for parameter ranges that reduce geometry collapse during optimization calculations.
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[JFT001] Wire Modeling Using the Sweep Function
This tutorial describes the procedures to create three-dimensional geometry using the sweep function.
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[L-SE-59] Detailed Modeling for Harmonic Loss Analysis
In IPM motors driven by PWM inverters, eddy current losses occur due to carrier higher harmonics. For higher efficiency, it is important to evaluate higher harmonic loss at design…
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Best of Bosch – The Computational Concerto Orchestrating Finite Element Analysis, Network Methods, and Machine Learning
Stefan KURZ, Robert Bosch GmbH
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The Faster Analysis of the Axial Gap Motor using JMAG
Satoru Ota, MEIDENSHA CORPORATION
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Operating Characteristics of Adjustable-Field Permanent Magnet Motors with 3D Magnetic Paths and Asymmetric Magnet Arrangement
Yutaro Hiyoshi, Yamaha Motor Co., Ltd.
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Verification of Motor Component Losses using Large-Scale Analysis
Daisuke Misu, Toshiba Infrastructure Systems & Solutions Corporation
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Development of a Detailed 3D Eccentric eMotor Model for Electric Vehicle NVH Simulations
Jacob Krizan, Ford Motor Company
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Practical Robust Optimization Method using HPC
Takuya Yoshioka, DENSO CORPORATION
