ANSYS Workbench Platform Applications

ANSYS Meshing

Meshing is an integral part of the computer-aided engineering (CAE) simulation process. The mesh influences the accuracy, convergence and speed of the solution. Furthermore, the time it takes to create a mesh model is often a significant portion of the time it takes to get results from a CAE solution. Therefore, the better and more automated the meshing tools, the better the solution.

From easy, automatic meshing to a highly crafted mesh, ANSYS, Inc. provides the ultimate solution. Powerful automation capabilities ease the initial meshing of a new geometry by keying off physics preferences and using smart defaults so that a mesh can be obtained upon first try.  Additionally, users are able to update immediately to a parameter change, making the handoff from CAD to CAE seamless and aiding in up-front design.

Click image for animation showing mesh updates to parameter changes.	click image for animation of automated meshing with flexible mesh controls

Once the best design is found, meshing technologies from ANSYS provide the flexibility to produce meshes that range in complexity from a pure hex mesh to highly detailed hybrid meshes; users can put the right mesh in the right place and ensure that a simulation will accurately validate the physical model.

Meshing Solutions Brochure (PDF)

ANSYS DesignXplorer

The ANSYS DesignXplorer solution works from within the ANSYS Workbench interface to perform Design of Experiments (DOE) analyses of any ANSYS Workbench simulation, including those with CAD parameters. Although it requires more analyses to be performed and is typically slower than Variational Technology, which is now also a part of ANSYS DesignXplorer, DOE is not limited in the types of analyses that can be used with it. In fact, ANSYS DesignXplorer software can be used with ANSYS® Parametric Design LanguageTM (APDL)-based files to perform DOE on existing or new ANSYS analyses. ANSYS DesignXplorer allows you to perform optimization and Design for Six Sigma with any application or sequence of applications, including in-house codes, by using the third-party plug-in.

Design of Experiments

ANSYS DesignXplorer has a powerful suite of DOE tools. Automatic Design Points can be generated two ways, Central Composite Design (CCD) or Optimal Space-Filling. CCD provides a traditional DOE sampling set, while Optimal Space-Filling’s objective is to gain the maximum insight with the fewest number of points. After sampling, ANSYS DesignXplorer provides four different meta-models to represent the simulations responses; Full Second-Order Polynomial, Kriging, Non-Parametric Regression and Neural Network. Kriging has two variants, pure Kriging and Radial Basis Function. These meta-models can accurately represent highly nonlinear responses. Once you have the simulation’s responses characterized, ANSYS DesignXplorer supplies three different types of optimization algorithms: Screening (shifted Hammersley), Multi-Objective Genetic Algorithm (MOGA) and Nonlinear Sequential Quadractic Programming (NLPQL). ANSYS DesignXplorer has a full suite of sampling, modeling and optimization routines to address a wide variety of applications.

DesignXplorer's powerful sampling techniques and meta-models can capture complicated responses such as the one shown above.

Variational Technology

Look beyond traditional aspects of response simulation by using the Variational Technology method within ANSYS DesignXplorer that gives users a broader view of design concepts providing complete FEA results for every design point. Depending on the analysis problem, the Variational Technology method can provide acceleration factors up to 100. With Variational Technology (VT), users can approach product design decisions much more efficiently.

Using the VT method to automatically calculate the entire design envelope within a single finite element solution, ANSYS DesignXplorer software allows users to perform quick and accurate what-if scenarios to periodically test design ideas. A traditional Design of Experiments approach requires many solutions to capture the behavioral changes due to parameter variations. For boolean parameters, the practical limit using traditional methods is about 10 boolean parameters, but the VT method handles up to 20 boolean parameters.

The Variational Technology method addresses many kinds of parameters:

• Geometric variations (CAD or ANSYS DesignModeler)
• Boolean variations (active or inactive status of spot welds, stiffening ribs, bolts, etc.)
• Element property variations (shell thickness, spring stiffness, point mass)
• Material variations (engineered plastics, composites, metals)
• Load variations (inertia and surface structural and thermal loads)

Design for Six Sigma (DFSS)

Design for Six Sigma (DFSS) is an analysis technique for assessing the effect of uncertain input parameters and assumptions on your model. A Design for Six Sigma analysis allows you to determine the extent to which uncertainties in the model affect the results of an analysis. Based on a probabilistic characterization, Design for Six Sigma enables you to quantify the quality of your product addressing issues such as minimizing warranty costs and quantifying the reliability and robustness of the product. DesignXplorer VT supports DFSS by allowing you to define Uncertainty Variables, which are used in a probabilistic analysis.

Histogram of the Maximum Equivalent Stress	Cumulative Distribution Function of the Maximum Equivalent Stress
Probability Table showing the value Maximum Equivalent stress at different Probability Values

The presentation format of results makes it easy to understand how design variation can effect system performance.

Design for Six Sigma Solution Brochure (PDF)