Fraunhofer Institute for Algorithms and Scientific Computing SCAI

Fraunhofer SCAI
© Fraunhofer 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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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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© Fotolia – Nataliya Hora / Fraunhofer SCAI

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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© Adobe Stock – diuno

Quantum Computing

Quantum computers promise to solve certain problems orders of magnitude faster than conventional digital computers. However, this requires new algorithms and solution methods.

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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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© lassedesignen Fotolia / Fraunhofer SCAI


The goal of the project ViPrIA is the development of intelligent assistance systems based on artificial intelligence and machine learning approaches to support engineers in simulation-based, virtual product development.

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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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The "COVID-19 Knowledgespace" offers innovative tools and services. These include the Biomedical Knowledge Miner "BiK>Mi", the knowledge discovery software "SCAIView" and a cause-and-effect model for SARS-CoV-2.


Symposium on the “Human Brain Pharmacome”

The MAVO Symposium took place on June 9, 2021 as a digital event.


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VMAP enhances interoperability in virtual engineering workflows



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.