Posts Tagged "simulation data management"

Any complete FEA solution has at-least three mandatory components: Pre-Processor, solver and post-processor. If you compare it with an automobile, solver is the engine that has all the steps/solution sequences to solve the discretized model. It can be regarded as the main power source of a CAE system. The pre-processor is a graphical user interface that allows user to define all the inputs into the model such as geometry, material, loads and boundary scenarios etc. In our automobile analogy, pre-processor can be regarded as the ignition key without which it is not possible to utilize the engine (solver) efficiently. The post-processor is a visualization tool to make certain conclusion from requested output: either text or binary. A good CAE workflow is regarded as one that offers closed loop CAD to CAD data transfer.

The above workflow is not closed so there is no scope of model update. Any changes in design requires all the rework. This has been the traditional workflow in organizations that have completely disconnected design and analysis departments. Designers send the CAD data to analysts who perform FEA in specialized tools and submit the product virtual performance report back to designers. If a change is mandatory, FEA is performed manually all over again. Let’s look at a better workflow.

In this workflow, if the initial design does not meet the design requirements, it is updated and sent to the solver, not to the pre-processor. It means that all the pre-processing steps are mapped from old design to new design without any manual intervention. This is an effort to bridge the gap between design and analysis departments that has been embraced by the industry so far. The extent to which the GAP can be bridged depends on the chosen workflow but to some extent, almost every CAE company has taken an initiative to introduce products that bridge this GAP. Let’s discuss in context of Dassault Systemes and Siemens.

Dassault Systemes: After acquiring Abaqus Inc in 2005, Dassault Systemes rebranded it as SIMULIA with the objective of giving users access to simulation capabilities without requiring the steep learning curve of disparate, traditional simulation tools. They have been introducing new tools to meet this objective.

  • The first one in series was Associative interfaces for CATIA, Pro-E and Solidworks which is a plug-in to Abaqus CAE. With this plug-in it is possible to automatically transfer the updated data from above mentioned CAD platforms to Abaqus CAE with a single click. All the CAE parameters in Abaqus CAE are mapped from old design to updated design. It’s a nice way to reduce re-work but design and simulation teams are still separate in this workflow.
  • Next initiative was SIMULIA V5 in which Abaqus was introduced in CATIA V5 as a separate workbench. This workbench includes additional toolbars to define Abaqus model and generate Abaqus input file from within CATIA. Introduce Knowledge ware, and user has all the nice features to perform DOE’s and parametric studies. This approach brings designers and analysts with CATIA experience under one roof.
  • Next Dassault Systemes introduced SIMULIA on 3D Experience platform allowing analysts to utilize data management, process management and collaboration tools with Abaqus in the form of simulation apps and roles. The solution is now in a mature stage with incorporation of process optimization, light weight optimization, durability and advanced CFD tools. By merging SIMULIA with BIOVIA we are also talking about multi scale simulation from system to molecular level. It is further possible to perform the simulation and store the data on public or private cloud.

Siemens PLM solutions: Siemens traditional CAE tools include FEMAP user interface and NX Nastran solver. Both have been specialized tools primarily meant for analysts with little or no connectivity to CAD. More specialized and domain specific tools were added with the acquisition of LMS and Mentor Graphics.

  • In 2016 Siemens introduced its new Simulation solutions portfolio called as Simcenter that includes all Siemens simulation capabilities that can be integrated with NX environment. The popular pre-processor in Simcenter series is NX CAE that has bi-directional associativity with NX CAD. Though meant for specialists, NX CAE offers a closed loop workflow between NX CAD and NX Nastran thus making easier to evaluate re-designs and perform DOE’s.
  • Siemens also offers NX CAE add-on environments for Abaqus and Ansys thereby allowing analysis to efficiently incorporate these solvers in their NX design environment.
  • It is further possible to use Simcenter solutions with Siemens well known PLM solution Teamcenter for enterprise wide deployment of Siemens simulation tools.

This shift in approach is not limited to Dassault Systemes and Siemens. Every organization in this space be it Ansys, Autodesk or Altair are introducing such closed form solutions. One reason may be the recent acquisition of many CAE companies by bigger organizations such as Dassault, Siemens and Autodesk. Nevertheless, the change has been triggered and it will continue.

 

 

I mentioned the process automation concept of ISight in a previous simulation automation blog. ISight is an open source code simulation automation and parametric optimization tool to create workflows that automate the repetitive process of model update and job submission with certain objectives associated with it. The objective could be achievement of an optimal design through any of the available techniques in ISight: Design of experiments, optimization, Monte Carlo simulation or Six Sigma. In this blog post, I will be discussing various value added algorithms in DOE technique; I will discuss other techniques in future blogs.

Why design of experiments

Real life engineering models are associated with multiple design variables and with multiple responses. There are two ways to evaluate the effect of change in design variable on response: Vary one at a time (VOAT) approach or Design of experiments (DOE) approach. The VOAT approach is not viable because:

  • This approach ignores interactions among design variables, averaged and non-linear effects.
  • In models associated with large FE entities, each iteration is very expensive. VOAT does not offer the option of creating high fidelity models with a manageable number of iterations.

With the DOE approach, user can study the design space efficiently, can manage multi dimension design space and can select design points intelligently vs. manual guessing. The objective of any DOE technique is to generate an experimental matrix using formal proven methods. The matrix explores design space and each technique creates a design matrix differently. There are multiple techniques which will be discussed shortly and they are classified into two broad configurations:

  • Configuration 1: User defines the number of levels and their values for each design variable. The chosen technique and number of variables determines number of experiments.
  • Configuration 2: User defines the number of experiments and design variables range.

Box-Behnken Technique

This is a three level factorial design consisting of orthogonal blocks that excludes extreme points. Box-Behnken designs are typically used to estimate the coefficients of a second-degree polynomial. The designs either meet, or approximately meet, the criterion of rotatability. Since Box-Behnken designs do not include any extreme (corner) point, these designs are particularly useful in cases where the corner points are either numerically unstable or infeasible. Box-Behnken designs are available only for three to twenty-one factors.untitled

Central Composite Design Technique […]

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