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Dassault Systèmes acquired FE-DESIGN GmbH, developer of the respected TOSCA Fluid software for topology optimization of channel flow problems, and TOSCA Structure for topology, shape and bead optimization of structures. Signaling that design space exploration has the attention of DS’s top management, CEO Bernard Charlès said during the company’s quarterly earnings call on April 25, “In our opinion [FE-DESIGN] is the technology leader for non-parametric optimization,” as well as “complementary to our parametric optimization capabilities.”
We agree the TOSCA technology strongly complements and augments Isight, DS SIMULIA’s longstanding solution for design space exploration which provides size, parametric shape, geometric parameter, and multidisciplinary optimization, as well as design of experiments (DOE), approximations, design for Six Sigma (DFSS), interactive post-processing tools, and a framework that lets users integrate and automate simulation process flows. We expect the FE-DESIGN technologies will be integrated with the Isight environment and its companion SIMULIA Execution Engine (SEE), which lets users distribute and parallelize the execution of simulations and Isight simulation process flows across available compute resources, and share Isight simulation process flows and results.
In a separate earnings call for North American investors later the same day, Charlès playfully called on Thibault de Tersant, DS’s chief financial officer, to amplify on the technical rationale: “Now, a very techie acquisition. And because, believe it or not, Thibault was the one who convinced me we should acquire this very scientific acquisition, I will let him comment to you why we bought this company.”
de Tersant was more than game. “Okay, why not. So the interest of non-parametric optimization is the topic here. Optimization – design optimization – is about designing for a certain targeted robustness of the product such that you can optimize your design and remove material until you have removed all material necessary for the targeted robustness of the car with chassis or whatever part you are doing.
“You have two methods to do that. One is parametric optimization; the other one is non-parametric optimization. And, believe it or not, the words here are confusing because the one which is more automated is the non-parametric optimization method, and not the opposite. And so this is the interest of this acquisition: it’s frankly the best technology for non-parametric optimization, and this does drive a lot of savings in time in order to run this optimization process.”
What’s the difference? Parametric shape optimization “searches the space spanned by the design variables to minimize or maximize some externally defined objective function,” as summed up by researchers Jiaqin Chen, Vadim Shapiro, Krishnan Suresh and Igor Tsukanov of the Spatial Automation Laboratory at the University of Wisconsin-Madison (“Parametric and Topological Control in Shape Optimization”). “In other words, parametric shape optimization is essentially a sizing problem that is a natural extension of parametric computer-aided design.”
“The downside of parametric shapes,” the authors continue, “is that they do not provide any explicit information about the geometry or topology of the shape’s boundaries. This, in turn, leads to at least two widely acknowledged difficulties: boundary evaluation may fail, and topological changes in the boundaries may invalidate boundary conditions or the solution procedure.”
Non-parametric optimization, by comparison, works at the node/element level to derive an optimal structure. It can offer greater design freedom, and can make use of existing CAE models without the need for parameterization. “The main advantage of non-parametric shape optimization is the ease of setup, avoiding tedious parameterization that may be too restrictive with respect to design freedom,” Michael Böhm and Peter Clausen of FE-DESIGN wrote in a technical paper presented at PICOF ’12, the 6th Annual Conference on Inverse Problems, Control and Shape Optimization. “One of the major disadvantages, on the other hand,” they observe, “is that the CAD interpretation of the shape optimization result is not trivial.”
Charlès noted that FE-DESIGN is “a company we already have an OEM relationship with, as we embedded some of their technology in SIMULIA,” specifically ATOM (Abaqus Topology Optimization Module), based on a subset of TOSCA Structure. At the same time, TOSCA Structure is the basis for Siemens PLM’s Femap Topology Optimization and works with NX Nastran, ANSYS and MSC Nastran. DS pledged to keep TOSCA open to and compatible with these solutions from its CAE rivals.
FE-DESIGN founder and CEO Dr. Jürgen Sauter was quoted as saying, “We have been working closely with Dassault Systèmes for more than 10 years and recognize the business benefits our customers will immediately gain through their global support organization, and more over time with their enterprise collaboration environment and advanced technologies for 3D modeling and realistic simulation.”
FE-DESIGN is now part of SIMULIA, the DS brand for FEA, design optimization and simulation data management. The transaction was completed April 23, 2013. Terms were not disclosed. DS reports FE-DESIGN has 50 employees and more than 200 customers.
Disclosure: DS SIMULIA is a member of our Design Space Exploration Advanced Research Practice. No compensation was received for this blog post.
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