Fraunhofer Institute for Algorithms and Scientific Computing SCAI

Fraunhofer SCAI

Fraunhofer SCAI develops innovative methods in Computational Science and actively supports their take-up in industrial practice. The institute combines mathematical and computational knowledge with a focus on algorithms – bringing benefits to customers and partners.

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Machine Learning

Applications of machine learning are a topic in several business areas of Fraunhofer SCAI.

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EVOLOPRO

Evolutionary self-adaptation of complex production processes and products.

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Closer to Reality

Wind turbines, airplanes and artificial heart valves are examples for structures, whose development requires the solution of coupled fluid dynamics and structural mechanics problems, or – more generally – multidisciplinary problems. The MpCCI CouplingEnvironment provides a framework for the solution of multidisciplinary applications.

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The VMAP project

aims to gain a common understanding of and interoperable definitions for virtual material models in CAE. Using industrial use cases from major material domains and with representative manufacturing processes, new concepts will be created for a universal material exchange interface for virtual engineering workflows.

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Software AutoBarSizer

Generate optimized layouts for the cutting of stock items, namely steel profiles (metal beams) and other bars and rods.

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Software Bioinformatics

Professional software solutions for information management in the pharmaceutical research process.

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RoKoRa

Secure human-robot collaboration using high-resolution radars

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Creating New Materials

TREMOLO-X is a powerful software package used for the numerical simulation of interactions between atoms and molecules, the molecular dynamics. It provides the environment to design new innovative materials. TREMOLO-X is successfully applied in many projects in nanotechnology, material science, biochemistry and biophysics.

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Virtual product development

In virtual product development, machine learning is increasingly used to support the development engineer in the research and development process.

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Software AutoPanelSizer

AutoPanelSizer provides an answer to the question of how to place rectangular parts on rectangular plates as efficiently as possible.

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Digital Twins

SCAI develops new methods for context-dependent model generation and coupling.

 

Machine Learning

 

Research Center for Machine Learning

The direct transfer of ML research to industry is the aim of the Fraunhofer Research Center for Machine Learning within the research cluster »Cognitive Internet Technologies«.

 

Software and Services for the Automotive Industry

Fraunhofer SCAI cooperates with manufacturers and suppliers from the automotive industry in many areas.

Press - 24/05/2019

New Annual Report 2018/2019 published

Fraunhofer SCAI has published its Annual Report 2018/2019. It describes the research in the ten business areas of the institute. It also provides an overview of the institute's numerous software solutions that are used in industrial practice.

Press - 18/01/2019

New analysis methods facilitate the evaluation of complex engineering data

A further increase in the performance of supercomputers is expected over the next few years. So-called exascale computers will be able to deliver more precise simulations. This leads to considerably more data. Fraunhofer SCAI develops efficient data analysis methods for this purpose, which provide the engineer with detailed insights into the complex technical contexts.

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