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Parameter Identification of a Rate Dependent Constitutive Model for Rock Salt

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8962))

Abstract

The tendency to shift from fossil and nuclear energy sources to renewable energy carriers in Germany leads to the necessity to develop effective energy storage systems. Nowadays, caverns excavated in rock salt formations are recognized as the appropriate places for underground storage of energy in the form of compressed air, hydrogen and natural gas. Accurate design of these underground cavities requires suitable numerical simulations employing proper constitutive models to describe the material behavior of rock salt under various geological conditions. In this paper, a rate dependent model is selected to describe the mechanical response of the rock salt around the cavern. This model is implemented in the finite element code CODE-BRIGHT, then its application in numerical modeling of salt caverns is illustrated. Finally, inverse analysis of the synthetic data is performed to identify the material parameters of the selected model. The applied inverse analysis algorithm employs metamodeling technique in order to reduce the computation time of the parameter identification procedure.

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Acknowledgement

This work was performed in the frame of the project ANGUS+ funded by the Federal Ministry of Education and Research (BMBF) under grant no. 03EK3022C. The authors are grateful for their support.

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Correspondence to Maria Datcheva .

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© 2015 Springer International Publishing Switzerland

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Khaledi, K., Mahmoudi, E., Datcheva, M., Schanz, T. (2015). Parameter Identification of a Rate Dependent Constitutive Model for Rock Salt. In: Dimov, I., Fidanova, S., Lirkov, I. (eds) Numerical Methods and Applications. NMA 2014. Lecture Notes in Computer Science(), vol 8962. Springer, Cham. https://doi.org/10.1007/978-3-319-15585-2_23

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  • DOI: https://doi.org/10.1007/978-3-319-15585-2_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-15584-5

  • Online ISBN: 978-3-319-15585-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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