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ProgSim German Online Magazine

ProgSim, the German-language Online Magazine

Relaunched - focusing on AI/ML, SPDM, and CAE


ISSN 2311-522X


The magazine "ProgSim" (Progressive Simulation) is the German-language online magazine for engineering simulation focusing on Artificial Intelligence (AI), Machine Learning (ML), Simulation Process and Data Management (SPDM), Computer Aided Engineering (CAE) / numerical simulation methods and related fields.

AI / ML
Today, a new generation of predictive models is emerging. These models go beyond integral values – they can predict high-dimensional outputs such as spatially and time-resolved quantities. While the potential impact on CAE-based workflows is significant, industry adoption is slow. Questions regarding robustness, data generation, generalization, validation, and integration into existing simulation environments remain.

SPDM
Information about best practice methodologies – and challenges – in SPDM deployment as well as strategic value of SPDM solutions are essentiall. Real-world examples of the business benefits and competitive advantages that can be gained from the adoption of SPDM solutions, including early AI deployments utilizing SPDM.

CAE
Standards for exchange, collaborative working, and long-term archival of simulation datasets are as vital as data and process integration tools. How best to achieve technical interoperability between CAE tools, PDM/PLM systems, and AI agents to ensure seamless data flow.

The first issue is soon available for download.

Please send requests, information, and article suggestions to magazin@nafems.de

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Download the latest issue here starting on 16 July

Contents

Aufbau einer Wissensdatenbank über das Crashverhalten mittels Modellreduktion und deren Anwendung zur Ausreißererkennung durch maschinelles Lernen
Nouran Abdelhady, Dominik Borsotto, Stefan Müller, Kirill Schreiner (Sidact)

Effizienter entwickeln mit KI-gestützten CAE-Workflows im Simulationsdatenmanagement
Marko Thiele (Scale); Harsh Sharma (Scalesdm India)

Benchmarking von Vision Language Modellen zur intelligenten Bauteilerkennung in industriellen CAE Workflows
Maria Bonner, Roberta Luca, Viorica Puscas (Siemens)

Integration von Systemsimulationen für einfache und aussagekräftige Betriebsfestigkeitserprobungen von Teilstrukturen
Volker Landersheim, Jan Hansmann, Marc Wallmichrath (Fraunhofer-Institut für Betriebsfestigkeit und Systemzuverlässigkeit LBF)

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