Dr. Hedda R. Schmidtke Profile

Dr. Hedda R. Schmidtke

at Univ. zu Lübeck

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Proceedings Article | 28 April 2023 Poster + Paper

Digitalized data access of DE material models and their parameters using an OBD(M)A approach

Jana Mertens, Mena Leemhuis, Özgür Özçep, Hedda Schmidtke, Jürgen Maas

Proceedings Volume 12482, 124820Z (2023) https://doi.org/10.1117/12.2661222

KEYWORDS: Data modeling, Databases, Elasticity, Deformation, Modeling, Transducers, Error analysis, Dielectrics, Data storage, Associative arrays

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Dielectric Elastomer (DE) transducers are characterized by their geometrical dimensions and in particular by the properties of the elastomer and electrode materials. Therefore, in addition to dimensions, it is advantageous to consider optimization of material properties to fulfill transducer requirements, such as blocking force, free stroke, or response time. A big challenge in describing the properties of DE materials deals with utilizing different but commonly used hyperelastic material models and their parameters, which differ in complexity and corresponding model errors. Thus, determined material parameters are not necessarily consistent. In addition, parameters are depending on the measurement method, its conditions and the samples themselves. All of this leads to heterogeneous datasets making data access more complicated and in certain cases impossible for users. To overcome this, OBDA (ontology-based data access) approaches have been proven to access these heterogeneous datasets individually and efficiently and to gain the relevant information with the help of an ontology. Within a research project funded by the Federal Ministry of Education and Research, an extended OBDA approach is developed: OBDMA (ontology-based data and model access) combines data access with model-based working steps. While the joint project considers four different smart material classes, this paper focuses on dielectric materials and their transducers, in particular the development of methods to handle hyperelastic material models and their parameters. The various possibilities of material models and parameter identification methods are discussed on the basis of a measurement curve. Finally, the working principle and the advantages of the OBDMA system are demonstrated by means of a representative DE use case.

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