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Quantification of Uncertainty in the Mathematical Modelling of a Multivariable Suspension Strut Using Bayesian Interval Hypothesis-Based Approach

Mallapur, Shashidhar ; Platz, Roland (2022):
Quantification of Uncertainty in the Mathematical Modelling of a Multivariable Suspension Strut Using Bayesian Interval Hypothesis-Based Approach. (Publisher's Version)
In: Applied Mechanics and Materials, 885, pp. 3-17. Trans Tech Publications, ISSN 1660-9336, e-ISSN 1662-7482,
DOI: 10.26083/tuprints-00020445,
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Item Type: Article
Origin: Secondary publication service
Status: Publisher's Version
Title: Quantification of Uncertainty in the Mathematical Modelling of a Multivariable Suspension Strut Using Bayesian Interval Hypothesis-Based Approach
Language: English
Abstract:

Mathematical models of a suspension strut such as an aircraft landing gear are utilized by engineers in order to predict its dynamic response under different boundary conditions. The prediction of the dynamic response, for example the external loads, the stress and the strength as well as the maximum compression in the spring-damper component aids engineers in early decision making to ensure its structural reliability under various operational conditions. However, the prediction of the dynamic response is influenced by model uncertainty. As far as the model uncertainty is concerned, the prediction of the dynamic behavior via different mathematical models depends upon various factors such as the model's complexity in terms of the degrees of freedom, material and geometrical assumptions, their boundary conditions and the governing functional relations between the model input and output parameters. The latter can be linear or nonlinear, axiomatic or empiric, time variant or time-invariant. Hence, the uncertainty that arises in the prediction of the dynamic response of the resulting different mathematical models needs to be quantified with suitable validation metrics, especially when the system is under structural risk and failure assessment. In this contribution, the authors utilize the Bayesian interval hypothesis-based method to quantify the uncertainty in the mathematical models of the suspension strut.

Journal or Publication Title: Applied Mechanics and Materials
Volume of the journal: 885
Publisher: Trans Tech Publications
Classification DDC: 600 Technik, Medizin, angewandte Wissenschaften > 600 Technik
600 Technik, Medizin, angewandte Wissenschaften > 620 Ingenieurwissenschaften
Divisions: 16 Department of Mechanical Engineering > Research group System Reliability, Adaptive Structures, and Machine Acoustics (SAM)
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres > CRC 805: Control of Uncertainty in Load-Carrying Structures in Mechanical Engineering
Date Deposited: 10 Feb 2022 13:29
Last Modified: 10 Feb 2022 13:29
DOI: 10.26083/tuprints-00020445
Corresponding Links:
URN: urn:nbn:de:tuda-tuprints-204459
Additional Information:

Keywords: Bayesian Interval Hypothesis, Marginal Likelihood, Mathematical Model, Model Validation, Suspension Strut, Uncertainty

URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/20445
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