JMAG Newsletter January, 2016Product Report


Introduction of JMAG-Designer Ver.15.0

JMAG-Designer Ver.15.0 (hereafter called Ver.15.0) was released in December 2015.
The multi-objective optimization engine can be used for the global design exploration of complex design space. In addition to the framework that reduces operation steps in the Geometry Editor and post-processing, operability of case control has also been improved for higher success with parametric analyses. Additional improvements include the check function of BH curves and magnetic field analysis accounting for hysteresis characteristics, as well as enhancements in customization features. This report introduces you the new features in Ver.15.0.


About 42 features have been added / improved in Ver.15.0.
A multi-objective optimization engine using genetic algorithms has also been embedded, and has allowed optimization in the practical use. We have continually improved operation for mesh generation and have maintained the distributed processing environment to allow hundreds and thousands of cases that are required for optimization. In addition, case controls are easier to use, and cases are displayed in a list for parametric analyses, which allow design spaces to be even more fully understood.
The user interface for the Geometry Editor and post processing has also been improved to allow for more efficient analyses to be performed. Analysis functions and material modeling functions are also now better than ever. Not only have magnetic performance evaluations been improved, but so have other analysis technologies, such as for electric field, thermal and structural analyses, allowing the entire machine to be evaluated from a multitude of perspectives.
This product report only covers a few of the 42 new features available in the new version; for a comprehensive overview, please visit the following Ver.15.0 introduction page.

Performing More Efficient Analyses

Reducing overall time for simulation workflow is sought by optimizing essential operations such as creating models, setting conditions, and visualizing results.
Picking up from where Ver. 14.1 left off, the user interface has been further refined, and frequently performed operations have been made into functions to support a more efficient workflow. Manual explanations for script functions have also been improved. So it is easier than ever for users to automate operations.

Geometry Library

Typical 2D and 3D geometry (polygons, circles, ovals, rectangles, spheres, cones, prisms, tori, and spirals) can be created by simply specifying their dimensions and coordinates (Fig. 1). Steps of sketch creation and feature settings can now be omitted.

Fig.1 Example of creating a spiral part.
Fig.1 Example of creating a spiral part.
Create spiral geometry by simply entering its dimensions and coordinate values.

Region Boolean and Pattern Features

Region boolean function (Fig. 2) is added. Cutting shapes and holes can be easily created combined with line patterns or rotation patterns. Also, specifying features such as revolve, chamfer, and fillet with the pattern processing function allows these processes to be run simultaneously with pattern copy.

Fig.2 Region boolean function
Fig.2 Region boolean function
The boolean function runs automatically when duplicate regions are created. The overlapping region is removed (left) and a notch is created in the geometry (right).
Fig.3 Creating damper bar geometry
Fig.3 Creating damper bar geometry
Easily turn multiple notch geometry into a pattern by copying a region boolean feature

Outputting Circuits and Response Values to a csv File

Quickly access required information after completing a calculation with a csv file. In addition to outputting history graph items to a csv file in Ver. 14.1, circuits and response values can now be output as well (Fig. 4). Export only the needed results to the available physical computer when performing distributed processing.

Fig.4 Example of outputting circuit terminal voltage
Fig.4 Example of outputting circuit terminal voltage
Output voltage values of the electric potential probe
set in advance to a csv file all at once

Improved Mesher Capabilities

The flexibility for mesh generation is always being improved to allow generating the least amount of mesh required to capture phenomena precisely. The extrusion direction of thin solid mesh and extruded mesh can now be user-specified. Functions to specify the number of divisions and division ratio for manual mesh have also been added, allowing control over the mesh density.

Specifying the Extrusion Direction of Thin Solid Mesh

By freely specifying the extrusion direction of thin solid mesh, mesh necessary for capturing the desired phenomena can be efficiently created. For example, for an eddy current distribution analysis of core geometry as shown below, thin solid mesh is created only for the surface of the material where eddy currents are generated (Fig. 5). By roughly cutting out tetrahedral mesh, the phenomena in the core section can be grasped in detail while also efficiently reducing the mesh elements.

Fig.5 Eddy current loss analysis of a large transformer (left)
Fig.5 Eddy current loss analysis of a large transformer (right)
Fig.5 Eddy current loss analysis of a large transformer
Create thin solid mesh as a separate part for the core surface where eddy currents are being generated (left), and then accurately analyze the loss distribution (right).

Improved Analysis Functions

The all-new zooming analysis function, a technique for reducing calculation time while allowing phenomena to be captured in high detail, separates out a single, detailed section of the model and analyzes the section. When it comes to electromechanical design, comprehensive solutions are sought not only for magnetic performance, but everything from the intricate details of a machine to the machine as a whole, such as noise phenomena and dielectric breakdown. To achieve this with JMAG, we are focused on improving electric field, thermal and structural analysis functions. Electric field analyses using higher-order elements can now be performed.

Zooming Analysis

Performing an analysis by separating out just a single section of a large, detailed model is now possible. This allows copper loss analyses for wires and stray loss analyses for cases to be easily performed. When typically performing a copper loss analysis, an analysis model which simulates the wire geometry the size of several millimeters is required, and this increases the number of mesh elements, and in turn, creates longer calculation times. The newly implemented zooming analysis is an efficient analysis method which limits the model size to just one section separated out from the rest of the analysis model.
In a copper loss analysis for an IPM motor, the model size is minimized by calculating copper loss from two analyses: analysis of a master model simulating the wire in bulk, and analysis of a sub-model of only the slot wire section (Fig. 6). By using vector potential distribution obtained in the master model analysis as a boundary condition in the sub-model analysis, magnet positions not included in the sub-model and slot geometry effects can be accounted for, and copper loss distribution can be obtained (Fig. 7). A typical analysis for a case that requires one hour can be performed in under 10 minutes using a zooming analysis.

Fig.6 Copper loss analysis model using the zooming analysis method
Fig.6 Copper loss analysis model using the zooming analysis method [1]
A model expressing the wire as bulk (left) and a model with only the slot and wire section (right) are created and analyzed.
Fig.7 Obtained copper loss distribution
Fig.7 Obtained copper loss distribution
Increased copper losses due to slot higher harmonics components can be seen in the wire near the slot opening.

Higher-Order Element in Electric Field Analysis

To perform a detailed evaluation of dielectric breakdown in the air, which requires a quantitative evaluation of electric field intensity, locally occurring electric field concentrations must be analyzed with high accuracy. Analysis methods using higher-order elements were incorporated so suddenly changing electric fields can be captured. Evaluating with an increased resolution in areas where electric fields concentrate is possible (Fig. 8).

Fig.8 Electric field distribution analysis of a slot (a)Electric field distribution
(a) Electric field distribution
Fig.8 Electric field distribution analysis of a slot (b)
(b) Electric field distribution over the line
Fig.8 Electric field distribution analysis of a slot
Analyze the electric field distribution of a wire in a motor.
Express electric field concentrations using higher-order elements

Improved Coupling Functions with Abaqus

By directly linking a JMAG magnetic field analysis and an Abaqus thermal analysis or structural analysis, elasto-plastic deformations due to induction heating and formation issues using electromagnetic force can be solved with high accuracy. Electromagnetic force affecting magnetic material and Lorentz force affecting non-magnetic material can now be accounted for simultaneously to solve for deformations (Fig. 9). Appropriate time intervals can be set depending on the coupling issue. An option has been added to allow the time intervals for a JMAG transient response analysis to be synchronized with Abaqus Implicit time intervals.

Fig.9 Analysis example of electromagnetic forming
Analyze plate deformations accounting for electromagnetic force affecting carbon steel, which was obtained in JMAG, and Lorentz force affecting the coil

Material Modeling

Modeling technologies that can accurately acquire losses due to various factors are essential for evaluating the reduction of losses occurring in a machine. In addition to incorporating the various characteristics of electromagnetic steel sheets and magnets, modeling technologies have been developed which can account for the production effects such as deterioration from processing. There are over 700 products in the material database to make analyses even more reliable, and now hysteresis characteristics can be used directly in a magnetic field analysis

Magnetic Field Analysis Accounting For Hysteresis Characteristics

By directly accounting for minor loops in magnetic properties for a magnetic field analysis, (Fig. 10), loss evaluations can be performed accounting for the energy balance. Vector play models are used to express minor loops.

Fig.10 Example of a 2D transient analysis of a ring core
Fig.10 Example of a 2D transient analysis of a ring core
A 0.05A sinusoidal wave current is applied to the coil,
and alternating magnetic field generated in the ring core draws the symmetry loop

Check Function of BH Curves

Actual measurement environments can limit the preparation of sufficient reference points, and may become data where differential permeability (μdiff) is not simple reduction. Convergence of calculation can be improved by running smoothing for the BH curve if necessary (Fig.11).

Fig.11 Example of smoothing BH curve
Fig.11 Example of smoothing BH curve
Confirm state of the input data from differential permeability and magnetic field graph then convert to a smoother curve with smoothing

Addition of Material Data

Neodymium bonded magnet from Molycorp Magnequench, electromagnetic steel sheet from ThyssenKrupp, and soft magnetic composite from Höganäs has been added (Table 1). Approximately 240 types of core materials and 460 types of PM materials can be used.

Table.1 Added material list
Magnequench Corp.
Neodymium bonded magnet
ThyssenKrupp Corp.
Magnetic steel sheet
TKSE M 235-35 A
TKSE M 400-50 A
TKSE M 530-50 A
TKSE M 330-35 A
TKSE M 470-65 A
TKSE M 800-100 A
Soft magnetic composite
*1 Intensity of magnetization field varies in 6 patterns for each material: 7.5kOe,10kOe,12.5kOe, 15kOe,20kOe,40kOe
*2 Soft magnetic composites from Höganäs in Ver.14.1 has been replaced with 11 new materials


Analysis functions and material modeling have been enhanced so users can be further involved in electromechanical design. On the other hand, the customization function has been improved for flexible support in evaluation items specializing in machinery, control methods, and original complicated analyses. To be specific, the user subroutine has been enhanced, and setting items customizable by the user have also been increased. Subroutines supported in the settings of iron loss calculation, current source, and voltage source have also been added.

Customizing Iron Loss Algorithm

A new setting that can now be customized is the iron loss algorithm. There are several methods on how to categorize and cut apart losses depending on the approach. Subroutine of iron loss calculation has been added in response to demands for breaking up iron loss components using an original algorithm (Fig.12).

Fig.12 Example of customizing iron loss calculation
Fig.12 Example of customizing iron loss calculation
Directly calculate each loss (from the left: hysteresis loss, classical eddy current loss, excess eddy current loss) from magnetic flux density of the rotor core and stator core using subroutine

Exploration of Design Space

Design exploration may eventually become the key to electromechanical design. Multi-objective optimization engine using genetic algorithm expands the design space and allows exploration of optimization design proposals. The advantage of multi-objective optimization in JMAG is that it can be easily run, as with parametric analysis. Reviewing the procedure to specify the design variable and adding a design proposal to the design table has allowed Ver.15.0 for improvements in accuracy of operations. Functionality has also been improved such as support for point sequence data, as well as enhancements in analysis functions such as Pareto curve and correlation matrix.
In addition, the MATLAB engine is now available for use in multi-objective optimization, and an interface to register the user engine to the optimization panel has been embedded so complicated/various optimization processing can be run from JMAG.

Multi-Objective Optimization

Genetic algorithm embedded from Ver.14.1 now supports multi-objective optimization, and this has allowed optimization design for contrary design issues such as performance and cost.
For example, rotor design of IPM motors needs to maximize torque while controlling loss that occurs in the magnet. Multi-objective optimization can be run with magnet width, magnet thickness, position, and slit width as design variables for these application issues (Fig.13). Magnet torque can be increased by enlarging magnet width and magnet thickness, and there are hopes for improvements in average torque from the initial design proposal. On the other hand, reduction in magnet eddy current loss can be expected by effectively passing magnetic flux of the slot harmonic components that is the principal harmonic component inside the magnet through the slit part, but average torque drops simultaneously and control of the slot geometry becomes the key for optimization design. Using magnetic flux distribution and the correlation matrix allows examination of the obtained optimization design (Fig.14).

Fig.13 Pareto solution and optimized geometry (a)
(a) Acquired Pareto solution
Fig.13 Pareto solution and optimized geometry (b)
(b) Optimized geometry and slot harmonic components of magnetic flux line
Fig.13 Pareto solution and optimized geometry [2]
Magnet eddy current loss is reduced, average torque is increased. Pareto curve is structured in the bottom-right direction (a), design proposal is examined from flux line distribution (b)

Fig.14 Correlation matrix
Fig.14 Correlation matrix
Confirm correlation coefficient with each design variable

Improvements in Case Control

Parametric analysis can be run in three steps.

  Step1: Select a design variable in the [Select Parameters].
  Step2: Register a design proposal in the [Design Table].
  Step3: Run calculation.

Improvents in the user interface of case control allow movement from the selection of design variables directly to the input window of the case according to the execution step (Fig.15).

Fig.15 Operation method of parametric analysis
Fig.15 Operation method of parametric analysis
Open design table directly from the [Select Parametric Prameters] panel

Improved Geometry Parametric Operation

With improvements in the user interface, the operation procedures have also been made easier to understand in parametric analysis that uses dimensions as variables. When using only geometry dimensions as design variables, select a variable in [Select CAD Parameters], open the design table directly, then register a case. Furthermore, each variable can be previewed in the model, and design variables are now easier to select (Fig.16).

Fig.16 Geometry parametric operation method
Fig.16 Geometry parametric operation method
Confirm settings of the model, and open design table directly

Parametric Support for Point Sequence Data

The target range has been expanded so all settings can be used as design variables. Parametric analysis with time-dependent point sequence data of circuit components and material characteristics as design variables can be run (Fig.17). Point sequence data is specified for each case in case control.

Fig.17 Current voltage characteristics analysis of flyback converter (a)
(a) Switch settings
Fig.17 Current voltage characteristics analysis of flyback converter (b)
(b) Voltage characteristics
Fig.17 Current voltage characteristics analysis of flyback converter
Analyze current voltage characteristics when the duty ratio is changed (b) changing point sequence data of the switch (a)

Distributed Processing and Job Management

Affinity with general-purpose job management systems (such as LSF) is improved so existing systems can be used effectively by predicting users' involvement with hundereds and thousands of analyses with parametric analysis or optimization calculation.
In addition to function improvements in JMAG-Scheduler, the function to monitor job state when using the general-purpose job management system has also been improved.

Running a Project Batch from JMAG-Scheduler

Distributed processing of coupling analysis can be directly run from the JMAG-Scheduler. The specified analysis group can be selected when running batch processing (Fig.18).

Fig.18 Batch processing of magnetic  two-way coupled magnetic field and thermal analysis
Fig.18 Batch processing of magnetic two-way coupled magnetic field and thermal analysis
Specify analysis group included in the specified jproj file


We hope you will enjoy the latest version of JMAG. This product report introduced part of the new features in Ver.15.0.
Introduction videos of each function can be viewed at our company website (*3). In addition, tutorials and sample files of each function can be accessed from the download page of Ver.15.0 (*4). Please make use of these services.
We hope JMAG's newest features will prove useful for your business

*3 JMAG Function Videos URL:
*4 Sample data URL:
Accesible from the sample data of the Introducing JMAG-Designer Ver.15.0 page. A user account will be necessary.

(Mari Nakamura)

[1]  Katagiri, Sano, Semba, Mimura, Matsunaga, Tani, Yamada: "Loss Calculation of Rotating Machine using Zooming Analysis", The Papers of Joint Technical Meeting on Static Apparatus and Rotating Machinery, IEE Japan, SA-16-029, RM-16-029, pp.55-60(2016) (in Japanese)
[2]  Kida, Katagiri, Matsunaga, Semba, Sano, Suzuki, Tani, Yamada: "An Evaluation of Genetic Algorithm for Multi-Objective Design Optimization of Electromagnetic Device", The Papers of Joint Technical Meeting on Static Apparatus and Rotating Machinery, IEE Japan, SA-15-100, RM-15-138, pp.65-70(2015) (in Japanese)


1. Solutions   - Coupled Magnetic Field and Vibration Analysis for Power Transformer -
2. Product Report   - Introduction of JMAG-Designer Ver.15.0 -
3. Fully Mastering JMAG   - Common Questions for JMAG -
4. Event Information

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