Uncertainty-based evaluation and coupling of mathematical and physical models

被引:1
作者
Scheiber, E. [1 ]
Motra, H. B. [2 ]
Legatiuk, D. [1 ]
Werner, F. [3 ]
机构
[1] Bauhaus Univ Weimar, Res Training Grp 1462, Berkaer Str 9, D-99425 Weimar, Germany
[2] Univ Kiel, Marine & Land Geomech & Geotech, Ludewig Meyn Str 10, D-24118 Kiel, Germany
[3] Bauhaus Univ Weimar, Chair Steel Struct, Marienstr 7, D-99423 Weimar, Germany
关键词
Model quality; Uncertainty; Mathematical model; Physical model; Weighting factors;
D O I
10.1016/j.probengmech.2016.02.001
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
A procedure for coupling of mathematical and physical models is proposed in this paper. This process is based on a quantification of uncertainties in both models. The procedure allows to determine the influences of uncertainties in mathematical models, as well as in physical models. Moreover, the influences of scattering input parameters in the models are quantified. To assess a global model, the approach for evaluation of models based on the graph theory is applied. By comparing the quantitative model outputs of mathematical and physical models, the coincidence of model responses is shown and assessed. The evaluation of model responses allows a model selection for the coupling process. This process of coupling is based on weighting factors, which are directly related to the model uncertainties. Hence, the model coupling approach gives possibilities to verify the accuracy of used models, and to adopt the coupled model, to be more precise in predicting physical reality. The process of coupling is illustrated by an academic example of the fourth order partial differential equation for a cantilever beam. To create a synthetic model data of a virtual physical model and to validate obtained results, the analytical solution which is based on the Fourier method is used. As an example with real measurements, the model of a torsional loaded steel beam is considered. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:52 / 60
页数:9
相关论文
共 50 条
  • [41] Redefining the impact assessment of buildings: an uncertainty-based approach to rating codes
    Caputo, Silvio
    Gaterell, Mark R.
    IMPACT ASSESSMENT AND PROJECT APPRAISAL, 2018, 36 (04) : 348 - 357
  • [42] Uncertainty-based comparison of conventional and surface topography-based methods for wear volume evaluation in pin-on-disc tribological test
    Maculotti, Giacomo
    Goti, Edoardo
    Genta, Gianfranco
    Mazza, Luigi
    Galetto, Maurizio
    TRIBOLOGY INTERNATIONAL, 2022, 165
  • [43] Toward an Uncertainty-Based Model Level Selection for the Simulation of Complex Power Systems
    Benigni, Andrea
    Ponci, Ferdinanda
    Monti, Antonello
    IEEE SYSTEMS JOURNAL, 2012, 6 (03): : 564 - 574
  • [44] Uncertainty-Based Test Planning Using Dempster-Shafer Theory of Evidence
    Kukulies, J.
    Schmitt, R. H.
    2017 2ND INTERNATIONAL CONFERENCE ON SYSTEM RELIABILITY AND SAFETY (ICSRS), 2017, : 243 - 249
  • [45] Future Uncertainty-Based Control for Relative Navigation in GPS-Denied Environments
    Bai, He
    Taylor, Clark N.
    IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 2020, 56 (05) : 3491 - 3501
  • [46] Quantitative Uncertainty-Based Incremental Localization and Anchor Selection in Wireless Sensor Networks
    Xie, Zhiheng
    Hong, Mingyi
    Liu, Hengchang
    Li, Jingyuan
    Zhu, Kangyuan
    Stankovic, John A.
    MSWIM 11: PROCEEDINGS OF THE 14TH ACM INTERNATIONAL CONFERENCE ON MODELING, ANALYSIS, AND SIMULATION OF WIRELESS AND MOBILE SYSTEMS, 2011, : 417 - 426
  • [47] DUEL: Dempster Uncertainty-Based Enhanced-Trust Level Scheme for VANET
    Bhargava, Arpita
    Verma, Shekhar
    IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 23 (09) : 15079 - 15090
  • [48] Towards an Uncertainty-based Model Level Selection for the Simulation of Complex Power Systems
    Benigni, A.
    Ponci, F.
    Monti, A.
    2010 COMPLEXITY IN ENGINEERING: COMPENG 2010, PROCEEDINGS, 2010, : 46 - 48
  • [49] Uncertainty-based prioritization of road safety projects: An application of data envelopment analysis
    Sadeghi, Aliasghar
    Moghaddam, Abolfazl Mohammadzadeh
    TRANSPORT POLICY, 2016, 52 : 28 - 36
  • [50] MATHEMATICAL MODELS OF UNCERTAINTY FOR SURFACE ANALYSES AND DECISION MAKING
    Caha, Jan
    Vondrakova, Alena
    Dvorsky, Jiri
    GEOCONFERENCE ON INFORMATICS, GEOINFORMATICS AND REMOTE SENSING - CONFERENCE PROCEEDINGS, VOL I, 2013, : 773 - 780