soft Product List and Ranking from 1826 Manufacturers, Suppliers and Companies | IPROS

Last Updated： Aggregation Period:Apr 15, 2026～May 12, 2026
This ranking is based on the number of page views on our site.

soft Manufacturer, Suppliers and Company Rankings

Last Updated： Aggregation Period:Apr 15, 2026～May 12, 2026
This ranking is based on the number of page views on our site.

  1. アークシステム 本社 Kanagawa//others
  2. シネマレイ 名古屋本社 Aichi//Information and Communications
  3. ユニオンシステム Osaka//Information and Communications
  4. 4 アドバン Nagano//others
  5. 5 JIPテクノサイエンス Tokyo//Information and Communications
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soft Product ranking

Last Updated： Aggregation Period:Apr 15, 2026～May 12, 2026
This ranking is based on the number of page views on our site.

  1. Safety Education and Technical Education VR シネマレイ 名古屋本社
  2. Quicker and more accurate construction cost estimation! Drawing extraction software Hiroi-kun III アークシステム 本社
  3. Super Build／SS7 Op.木造ラーメン ユニオンシステム
  4. 4 "AI-OCR" that digitizes handwritten invoices with high precision *customizable アドバン
  5. 5 Easy operation with just a click" - Drawing extraction software "Hiroi-kun III アークシステム 本社

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[Example] Topology optimization considering manufacturing requirements

[Example] Topology optimization considering manufacturing requirements

Initial design proposals and significant contributions to cost reduction! Introducing topology density variation limitation functions such as 'cross-section'!

Topology optimization is a method for determining the necessity or redundancy of materials (member layout) that contributes to lightweight and high-rigidity product design by seeking structures that maximize rigidity under a certain weight limit. While it allows for significant structural changes compared to the initial structure, it can also result in outcomes that are difficult to manufacture or lead to complex structures with high manufacturing costs. To avoid such situations, the topology optimization in 'OPTISHAPE-TS' utilizes a topology density variation limitation function, enabling optimization while satisfying manufacturing requirements. [Contents] ■ Overview ■ Topology Density Variation Limitation Function ■ Discussion *Detailed case information can be viewed through the related links. For more information, please feel free to contact us.

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[Example] Shape optimization using multiple reduced-order models.

[Example] Shape optimization using multiple reduced-order models.

Achieved approximately 27% weight reduction! Introducing a method for shape optimization that simultaneously considers multiple mechanical conditions.

In mechanical components with mechanisms like links, the arrangement of surrounding parts can change depending on their operational status, which may also alter the mechanical conditions experienced by the component. When designing such mechanical components, it is necessary to consider multiple mechanical conditions simultaneously. "OPTISHAPE-TS" provides various functions for optimization that take these multiple mechanical conditions into account at the same time. Here, we will introduce a method for shape optimization that considers multiple mechanical conditions simultaneously by using several reduced-order models and switching between them during analysis. [Contents (partial)] ■ Overview ■ Analysis Model ■ Model Reduction ■ Optimization Conditions *Detailed information about the case study can be viewed via the related links. For more information, please feel free to contact us.

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[Example] Shape optimization considering stress

[Example] Shape optimization considering stress

Using "OPTISHAPE-TS"! Introducing optimization cases with different stress constraints based on model parts.

In strength design, stress serves as an important guideline. When performing strength assessments based on stress, it is necessary to change the evaluation stress values according to different parts, not just relying on the maximum value. In such cases, by specifying constraint stress values for each region, it is possible to obtain an optimal shape that constrains stress at multiple evaluation points and all locations. This time, we will introduce an optimization case that applies different stress constraints based on the model's parts. [Contents] ■ Overview ■ Analysis Model ■ Optimization Conditions ■ Results ■ Discussion *Detailed information about the case can be viewed through the related links. For more information, please feel free to contact us.

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[Case Study] Accuracy Verification of Stress Using Finite Covering Method (FCM)

[Case Study] Accuracy Verification of Stress Using Finite Covering Method (FCM)

Compared to the finite element method (FEM)! Verified with models using three patterns of voxel sizes.

Finite element analysis using voxels has the advantage of being easy to operate, fast, and not incurring human costs; however, it also has the disadvantage of causing stress wave phenomena. To eliminate this disadvantage, we apply the Finite Covering Method (FCM) to improve analysis accuracy. Here, we will verify how the analysis accuracy is improved by using the Finite Covering Method (FCM) while changing the mesh size and comparing it with the Finite Element Method (FEM). [Contents] ■ Overview ■ Analysis Model ■ Analysis Results *Detailed information about the case study can be viewed through the related links. For more details, please feel free to contact us.

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[Case Study] Accuracy Verification of Displacement and Temperature Using Finite Covering Method (FCM)

[Case Study] Accuracy Verification of Displacement and Temperature Using Finite Covering Method (FCM)

I will introduce the issues with voxel analysis and a case study applying FCM as a solution!

The displacement solution of static stress analysis, or the temperature solution of steady-state heat conduction analysis, generally does not produce significant errors as long as the shape is accurately represented. However, there are cases where errors can become substantial. When the original shape does not match the voxel pitch, discrepancies in the shape occur. Therefore, to achieve better accuracy in the analysis, it is necessary to refine the mesh, which increases the model size. Here, we will introduce a case study applying FCM as a solution to this issue. 【Contents】 ■ Overview - Issues with voxel analysis ■ Analysis Model - Boundary conditions ■ Analysis Results - Static stress analysis / Steady-state heat conduction analysis *Detailed information about the case study can be viewed through the related links. For more information, please feel free to contact us.

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Example: Injection Molding - Reducing clamping force to downsize the molding machine.

Example: Injection Molding - Reducing clamping force to downsize the molding machine.

We will collaborate with 3D TIMON to explore gate positions that can be injected even with small molding machines, thereby reducing production costs.

Optimizing molding conditions parametrically in resin flow analysis can be relatively easily achieved, but automatically changing the shape of the cavity and the arrangement of the runner while optimizing is challenging. To facilitate these optimizations, we developed "AMDESS for 3D TIMON" in collaboration with Toray Engineering Co., Ltd. Here, we will introduce a case study of optimizing the gate position to minimize clamping force while automatically re-modeling the runner when changing the gate position. [Contents] ■ Overview ■ Analysis Model ■ Optimization Conditions ■ Results ■ Discussion *Detailed information about the case study can be viewed through the related links. For more information, please feel free to contact us.

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Case Study Collection 1 of Structural Optimization Design Software 'OPTISHAPE-TS'

Case Study Collection 1 of Structural Optimization Design Software 'OPTISHAPE-TS'

Detailed explanations of examples of shape optimization that aligns the natural frequency with experimental measurement results, and topology optimization cases that consider manufacturing requirements, using diagrams and tables!

In this case study collection, we introduce problem-solving examples using the structural optimization design software 'OPTISHAPE-TS'. We include examples of shape optimization that aligns natural frequencies with experimental measurement results, as well as topology optimization examples that consider manufacturing requirements. We provide a detailed explanation of the analysis models, optimization conditions, results, and discussions, using figures and tables. Please feel free to download and take a look. [Contents] ■ Shape optimization that aligns natural frequencies with experimental measurement results ■ Lightweight design of rotating parts considering rigidity and manufacturing requirements ■ Topology optimization considering manufacturing requirements ■ Shape optimization considering rigidity in the arrangement patterns of multiple parts *For more details, please refer to the PDF materials or feel free to contact us. *Those who are not members of Ipros can also download the materials from the related links below (within our company site).

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[Technical Column] The Theory of OPTISHAPE-TS: "Wave Phenomenon"

[Technical Column] The Theory of OPTISHAPE-TS: "Wave Phenomenon"

The Difficulty of Nonparametric Optimization! Introduction to a Technical Column

In the previous discussion, I explained that the checkerboard phenomenon is a challenging issue in topology optimization. I also discussed a technique called filtering as a workaround, but highlighted the difficulty in finding the right balance for its application. Additionally, a completely different approach has been proposed to avoid the checkerboard pattern without modifying the optimization problem. This idea involves using design variables at the nodes rather than at the elements, and interpolating within elements using a C^0 continuous function. Please feel free to download and take a look. [Contents] ■ Episode 5: The Difficulty of Nonparametric Optimization Part 4 "Wavy Phenomenon" *For more details, please refer to the PDF document or feel free to contact us.

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[Column] The Theory of OPTISHAPE-TS: Checkerboard Phenomenon

[Column] The Theory of OPTISHAPE-TS: Checkerboard Phenomenon

I will explain the difficulties of non-parametric optimization from another perspective!

In the previous sections, we explained that in non-parametric optimization, the number of design variables to be determined is large, meaning that the dimensionality of the search space is high, which is why optimization algorithms using sensitivity are employed. In this article, we will further explain the difficulties of non-parametric optimization from another perspective. Please feel free to download and take a look. [Contents] ■ Episode 4: The Difficulty of Non-Parametric Optimization Part 3 "Checkerboard Phenomenon" *For more details, please refer to the PDF document or feel free to contact us.

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[Column] The Theory of OPTISHAPE-TS: Norm Spaces and Inner Product Spaces

[Column] The Theory of OPTISHAPE-TS: Norm Spaces and Inner Product Spaces

Explanation of spaces where norms and inner products are defined! Introduction to a technical column.

In the previous article, we explained the concept of "space" in modern mathematics. The concept of a set exists as "a collection of specific things," and among those, we specifically call those that can determine some kind of relationship between the elements belonging to it "space." Additionally, we introduced "linear spaces" and "metric spaces" as concrete examples of spaces. In this article, we will further discuss spaces where norms and inner products are defined. Please feel free to download and take a look. [Contents] ■ Episode 10: What is the H1 Gradient Method? Part 3 "Norm Spaces and Inner Product Spaces" *For more details, please refer to the PDF document or feel free to contact us.

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[Technical Column] The Theory of OPTISHAPE-TS: "Time Complexity"

[Technical Column] The Theory of OPTISHAPE-TS: "Time Complexity"

A simple analysis example of using an optimization algorithm for the number of trials is also included!

In the previous discussions, I explained that non-parametric optimization, mathematically, is optimization focused on functions, and in practice, it becomes a problem of finding a number of design variables comparable to the scale of the finite element model (number of nodes, number of elements). In this article, I will explain the optimization algorithms for solving such problems. Please feel free to download and take a look. [Contents] ■ Episode 3: The Difficulty of Non-Parametric Optimization Part 2 "Time Complexity" *For more details, please refer to the PDF materials or feel free to contact us.

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[Technical Column] The Theory of OPTISHAPE-TS: "Optimization of Functions"

[Technical Column] The Theory of OPTISHAPE-TS: "Optimization of Functions"

What does "optimizing a function" mean? An explanation from the perspective of the difficulties it entails.

In the previous article, I briefly explained non-parametric optimization. In that context, I mentioned that non-parametric optimization is a method for optimizing functions. In this article, I will explain what "optimizing a function" means, to deepen your understanding of the challenges it presents. Please feel free to download and take a look. [Contents] ■ Episode 2: The Challenges of Non-Parametric Optimization Part 1 "Function Optimization" *For more details, please refer to the PDF document or feel free to contact us.

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[Technical Column] The Theory of OPTISHAPE-TS Topology Optimization

[Technical Column] The Theory of OPTISHAPE-TS Topology Optimization

The emergence of the H1 gradient method and its background! Introduction to a technical column on structural optimization design software.

In the previous article, I explained the calculation procedure of the force method, which is an H1 gradient method in shape optimization, including the previously proposed growth strain method. In this article, I will explain the H gradient method in topology optimization. Please feel free to download and take a look. 【Contents】 ■ Episode 7: The Emergence of the H1 Gradient Method and Its Background Part 2 "Topology Optimization" *For more details, please refer to the PDF document or feel free to contact us.

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[Technical Column] The Theory of OPTISHAPE-TS: "Shape Optimization"

[Technical Column] The Theory of OPTISHAPE-TS: "Shape Optimization"

An explanation of what the gradient method specifically entails! Introduction to a technical column.

In the previous four articles, we discussed the challenges of non-parametric optimization and the positioning of the H1 gradient method as a solution. From here, we will explain specifically what the H1 gradient method entails. Please feel free to download and take a look. [Contents] ■ Episode 6: The Emergence of the H1 Gradient Method and Its Background Part 1 "Shape Optimization" *For more details, please refer to the PDF document or feel free to contact us.

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[Technical Column] The Theory of OPTISHAPE-TS: "Completeness"

[Technical Column] The Theory of OPTISHAPE-TS: "Completeness"

An explanation of the important property of completeness among the characteristics of space! Introduction to a technical column.

In the previous article, we explained normed spaces and inner product spaces. A normed space is a space equipped with a norm that generalizes the concept of size, while an inner product space is a space equipped with an inner product. In this article, we will explain the important property of completeness among these spaces. Please feel free to download and take a look. [Contents] ■ Episode 11: What is the H1 Gradient Method? Part 4 "Completeness" *For more details, please refer to the PDF document or feel free to contact us.

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[Column] The Theory of OPTISHAPE-TS: "What is H1 in the first place?"

[Column] The Theory of OPTISHAPE-TS: "What is H1 in the first place?"

An explanation of the function space H1 from several perspectives! Introduction to a technical column.

In the previous two articles, I explained what the H1 gradient method is in shape optimization and topology optimization, along with its historical background. In this article, I will explain what "H1" in the H1 gradient method refers to. Please feel free to download and take a look. [Contents] ■ Episode 8: What is the H1 Gradient Method? Part 1 "What is H1 in the first place?" *For more details, please refer to the PDF document or feel free to contact us.

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[Technical Column] Optimization Algorithm Using the H1 Gradient Method

[Technical Column] Optimization Algorithm Using the H1 Gradient Method

An overview of the structural optimization algorithm used in OPTISHAPE-TS! Introduction to the technical column.

In the previous articles, we explained the theoretical background of the H1 gradient method. Since the discussion became mathematically complex, in this article, we will introduce a more approachable topic: an overview of the structural optimization algorithm used in OPTISHAPE-TS. Please feel free to download and take a look. 【Contents】 <Chapter 17: Optimization Algorithm Using the H1 Gradient Method> ■ Solve the state equations and calculate the value of the evaluation function ■ Solve the adjoint equations and calculate the sensitivity of the evaluation function ■ Calculate the variation of design variables using the H1 gradient method ■ Calculate the weighting coefficients for the variations ■ Update the design variables ■ Satisfy the unsatisfied constraint functions *For more details, please refer to the PDF document or feel free to contact us.

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The theory of OPTISHAPE-TS: Evaluating the maximum value of the KS function.

The theory of OPTISHAPE-TS: Evaluating the maximum value of the KS function.

Introduction to the evaluation method for maximum values using something called the KS function!

In OPTISHAPE-TS, it is possible to evaluate the maximum values of functions distributed over the model, such as "maximum Mises stress" and "maximum displacement." However, if we literally use the maximum value as the evaluation function, we will not be able to evaluate the derivatives, making it impossible to determine sensitivity. This time, I will introduce a method for evaluating maximum values using a function called the KS function, which is adopted in OPTISHAPE-TS. Please feel free to download and take a look. [Contents] ■ Episode 18 Evaluating the Maximum Value of Functions: KS Function *For more details, please refer to the PDF document or feel free to contact us.

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Theory of OPTISHAPE-TS Compliance Sensitivity Part 2

Theory of OPTISHAPE-TS Compliance Sensitivity Part 2

Compliance with design variables! An introduction to substitution method and direct differentiation method in a column.

We would like to introduce a technical column on our structural optimization design software "OPTISHAPE-TS." The discussion began in the previous article about deriving the sensitivity of compliance. This article is the second installment, where we will consider the derivative of compliance with respect to design variables. Please feel free to download and take a look. [Contents] ■ Episode 23: Sensitivity of Compliance Part 2 "Substitution Method and Direct Differentiation Method" *For more details, please refer to the PDF document or feel free to contact us.

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Theory of OPTISHAPE-TS Compliance Sensitivity Part 3

Theory of OPTISHAPE-TS Compliance Sensitivity Part 3

Sensitivity of compliance for a one-dimensional cantilever beam! Explanation of the derivation approach.

In the previous article, we introduced the Lagrange multiplier method as a condition that the solutions of optimization problems with equality constraints should satisfy. This time, we will apply that concept to derive the sensitivity of compliance. Please feel free to download and take a look. [Contents] ■ Episode 25 Sensitivity of Compliance Part 3 "Lagrange Multiplier Method" *For more details, please refer to the PDF document or feel free to contact us.

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Theory of OPTISHAPE-TS Compliance Sensitivity Part 4

Theory of OPTISHAPE-TS Compliance Sensitivity Part 4

Introduction to a technical column on problems involving design variables represented by functions!

In the previous articles, we explained the compliance and its sensitivity when introducing two-dimensional design variables for a one-dimensional cantilever beam. This time, we will finally replace the design variables from a finite-dimensional vector to an infinite-dimensional function and construct the problem. Please feel free to download and take a look. [Contents] ■ Episode 26 Sensitivity of Compliance Part 4 "Problems with Design Variables Represented by Functions" *For more details, please refer to the PDF document or feel free to contact us.

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[Technical Column] The Theory of OPTISHAPE-TS: Sigmoid Function

[Technical Column] The Theory of OPTISHAPE-TS: Sigmoid Function

A thorough explanation of linear spaces, also serving as a review! Introduction to our company's technical column.

This time, I will discuss the idea related to the optimization problem of a function that takes values within a certain specified range, specifically focusing on the sigmoid function. When solving non-parametric optimization problems using the H1 gradient method, we consider that an initial value of the function, which serves as the design variable, is given, and we update the design variable by adding an incrementing term to it. Therefore, this function must be an element of a linear space. I will carefully explain the concept of linear space as a review. Please feel free to download and take a look. [Contents] ■ Episode 29: Sigmoid Function *For more details, please refer to the PDF document or feel free to contact us.

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Case Study Collection 1 of CAD Model Generation Software 'S-Generator'

Case Study Collection 1 of CAD Model Generation Software 'S-Generator'

Examples of outputting CAD data from STL data! Explained clearly with illustrations!

This document is a collection of case studies on problem-solving using the CAD model generation software 'S-Generator', Volume 1. It includes examples such as "CAD model generation from engine block STL data," "CAD model generation from the topology optimization results of a chair," and "CAD model generation from the topology optimization results of a bracket." We provide detailed explanations of the overview, work content, and utilization of the generated surfaces, so please feel free to download and take a look. [Contents] ■ Case Study 1: CAD model generation from engine block STL data ■ Case Study 2: CAD model generation from the topology optimization results of a chair ■ Case Study 3: CAD model generation from the topology optimization results of a bracket *For more details, please refer to the PDF document or feel free to contact us!

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Structural optimization design software 'HiramekiWorks'

Structural optimization design software 'HiramekiWorks'

Responding to practical needs on the design site. Smoothly create prototype models of optimized result shapes with easy editing of STL data for 3D printing!

HiramekiWorks is an add-in structural optimization design software for 3D CAD SOLIDWORKS, boasting a proven track record in the manufacturing industry. Using the analysis conditions set in SOLIDWORKS, you can complete everything from running the analysis to importing the result model with just one click. Additionally, the optimized result shapes can be easily edited into STL data for 3D printing using the included "Geometry Editor," making it simple and smooth to create prototype models. Would you like to try designing something that has never been done before with our software, which incorporates unique know-how? 【Features】 ■ Easy optimization in a familiar environment ■ Addresses practical needs such as weight reduction and stress reduction under various conditions ■ Automatically generates solid models of the optimized result shapes ■ Easily generates STL data for 3D printing using the Geometry Editor *For more details, please refer to the related links or feel free to contact us. We are currently offering the "HiramekiWorks Product Catalog" and "STL Editing Case Studies" (S-Generator Case Studies) for PDF download!

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Case Studies of Structural Optimization Design Software 'OPTISHAPE-TS' Volume 3

Case Studies of Structural Optimization Design Software 'OPTISHAPE-TS' Volume 3

We will introduce case studies on the optimization of spot-welded parts and examples of shapes that equalize reaction forces ★ Detailed explanations of analysis models, optimization conditions, and discussions!

In this case study collection, we introduce problem-solving examples using the structural optimization design software 'OPTISHAPE-TS'. We present examples of optimizing spot-welded flat plate stiffeners, optimizing the optimal arrangement of spot welds themselves, and optimizing shapes to equalize reaction forces. We provide a detailed explanation of the analysis model, optimization conditions, results, and discussions using diagrams. Please feel free to download and take a look. [Featured Examples] ■ Shape optimization of spot-welded flat plate stiffeners ■ Topology optimization to reduce spot welding ■ Shape optimization to equalize reaction forces *For more details, please refer to the PDF materials or feel free to contact us! *Those who are not Ipros members can also download the materials from the related links below (within our company site).

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Web schedule sharing software "Hot Scheduler"

Web schedule sharing software "Hot Scheduler"

Now, it's clear at a glance who is doing what! Comprehensive security with cloud solutions for businesses.

"Hot Scheduler" is a web-based schedule sharing system that can be used for managing and sharing employee schedules, as well as reserving meeting rooms. It allows you to view the schedules of selected group members in a single screen, presented in a chronological graphical bar format, making it easy to see at a glance who is doing what at any given moment. [Features] ■ Smooth handling of inquiries since you can see members' schedules at your desk ■ Freedom to set up groups and register common schedules collectively ■ Schedule sharing possible with external parties and even overseas ■ Reservation and status checking for meeting rooms and shared equipment ■ Monthly view for a clear understanding of future plans *For more details, please refer to the PDF document or feel free to contact us.

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Easy Aluminum Cable System for Labor-saving and Improved Safety in Electrical Work

Easy Aluminum Cable System for Labor-saving and Improved Safety in Electrical Work

Adopting aluminum conductors achieves a weight reduction of 30-50%. It contributes to labor savings during installation and improved maneuverability.

The "Easy Aluminum Cable System" is a low-voltage aluminum conductor CV cable (Easy Aluminum Cable) composed of dedicated terminals, terminal blocks, connection materials, and tools. We provide a packaged set of necessary components to apply the Easy Aluminum Cable on-site. 【Features】 ■ Improved workability ■ Labor-saving ■ Significant reduction in line extension work time → Possible shortening of construction period ■ Reduction in labor for electrical work *Catalogs are also available. If you would like a catalog, please contact us using the inquiry button.

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3D Ion Beam Trajectory Analysis Software / μ-Beam

3D Ion Beam Trajectory Analysis Software / μ-Beam

Consider the ion trajectories in electrostatic fields and magnetic fields, dielectrics, electrodes, conductors, coils, magnets, magnetic materials, and space charge!

μ-Beam is a three-dimensional trajectory analysis module for charged particles that takes into account space charge. It can simulate ion beam control. μ-Beam is the trajectory analysis module within the electromagnetic field analysis system μ-MF by Mutech. 【Features】 - Trajectory analysis of charged particles in electric and magnetic fields - Input functions for initial position, initial velocity, and assigned current of charged particles - Function to read condition setting CSV files from Excel - Specification of calculation range and automatic calculation stop function - Trajectory analysis considering classical and relativistic effects - The trajectory calculation method employs Runge-Kutta *For more details, please request materials or view the PDF data available for download.

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3D Finite Element Method Electromagnetic Field Analysis Software / μ-MF

3D Finite Element Method Electromagnetic Field Analysis Software / μ-MF

After confirming the basic characteristics with μ-EXCEL, proceed to a more detailed three-dimensional analysis! Easy and fast calculations for electrostatic fields, static magnetic fields, alternating magnetic fields, and magnetic hysteresis analysis!

Three-dimensional electromagnetic field analysis is indeed difficult. Therefore, we have devised a way for simple problems to be easily set up and analyzed by beginners, while also allowing for more advanced analyses. μ-MF is an FEM electromagnetic field analysis system optimized for solving user-specific problems through the objectification of a subdivided module group. In μ-MF, a wizard-style GUI guides users in setting the problem type and conditions. Depending on the type of analysis, it combines subdivided solver modules to achieve the most efficient analysis. 【Features】 - Customizable object-oriented system - Capable of analyzing large-scale problems with over one million unknowns on a PC - High-speed computation using fast matrix solvers (ICCG, MRT) - Equipped with the latest technologies for coupled problems and material modeling - Comprehensive options for iron loss analysis and trajectory analysis - Modules starting from 900,000 yen - Rental: 450,000 yen per year, starting from 45,000 yen per month Additionally, - We offer professional consulting that delves into your specific problems - We provide contract analysis and custom development at affordable prices *For more details, please contact us or refer to the PDF data.

  • Scientific Calculation and Simulation Software
  • soft

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3D Microwave and Optical Wave Analysis Software / μ-WAVE

3D Microwave and Optical Wave Analysis Software / μ-WAVE

FDTD method (Finite-Difference Time-Domain), equipped with orthogonal grid pre-post processing, rapidly analyzes electromagnetic fields in the time domain!

The optical wave and microwave analysis software μ-WAVE is a highly practical electromagnetic wave simulation tool. μ-WAVE rapidly analyzes electromagnetic field distribution in the time domain. 【Features】 - Adopts FDTD and CIP methods for analysis - High-speed computation for problems with 10 million cells (when using FDTD) - Realizes infinite boundaries without PML (when using CIP) - Time steps determined by Courant condition do not need to be changed even if small cells are partially present (significant reduction in computation time) (CIP) - Evaluates wideband absorption and scattering characteristics in a single calculation - Comes standard with a dedicated GUI designed for ease of use - Priced from 3.15 million yen *For more details, please request documentation or view the PDF data available for download.

  • Scientific Calculation and Simulation Software
  • soft

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