Dataset for Evaluating Accuracy and Runtime Trade-Offs of Simulation-Based Virtual Sensors

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Authors: Andreas Kormann
Cited by: 0

Abstract

This dataset provides benchmark data for the evaluation of simulation-based virtual sensors in mechanical engineering. It supports the analysis of accuracy, runtime behavior, and deployment trade-offs for physics-based virtual sensing workflows. The dataset includes processed and derived results from two representative case studies: (A) a nonlinear tension-bar benchmark and (B) a steady-state thermal model of a multi-core CPU. The data cover live finite element virtual sensors (SVS-LFE) as well as lookup-database virtual sensors (SVS-LDB) constructed using different design-of-experiments strategies and database sizes. For both case studies, the dataset contains accuracy metrics, runtime measurements, mesh convergence results, lookup-database design data, and aggregated comparison tables. The data enable verification of the quantitative results reported in the accompanying publication and provide a reference for future method development and benchmarking. The repository contains processed numerical data only. Full finite element models, meshes, solver input files, and proprietary software outputs are not included.

Fields of Study & Subjects

Model Reduction and Neural Networks Simulation Techniques and Applications Modeling and Simulation Systems

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
27 January 2026
Language
EN
Document type
Dataset