Analysis of polymorphic data uncertainties in engineering applications

Analysis of polymorphic data uncertainties in engineering applications
复制标题

工程应用中的多态数据不确定性分析

DOI:
10.1002/gamm.201900010
复制
发表时间:
2019
期刊:
GAMM‐Mitteilungen
影响因子:
--
通讯作者:
K. Weinberg
K. Weinberg
中科院分区:
--
文献类型:
--
作者:
M. Drieschner;H. G. Matthies;T.-V. Hoang;B. V. Rosic;T. Ricken;C. Henning;G.-P. Ostermeyer;M. Müller;S. Brumme;T. Srisupattarawanit;T. F. Korzeniowski;K. Weinberg

文献摘要

参考文献

被引文献

相似文献

在这方面的贡献,几个案例研究与数据的不确定性已在个别项目的一部分DFG(德国研究基金会)优先计划SPP 1886年“多态不确定性建模的数值设计的结构”。在所有的案例研究中,不确定性的数值模型来自工程问题,描述了处理和纳入测量数据的概念,无论是模型输入参数还是系统响应。第一个案例研究涉及多态性的不确定数据的基础上,计算机断层扫描的空气空隙的采集,简化和集成的数值模型的粘合剂债券。在第二个案例研究中,变化敏感性分析,提供合适的先验知识的数值土壤分析,例如,为了减少所需的输入数据。摩擦过程中的不确定性在案例研究3中进行了处理,其中测量数据用于数据驱动方法以改进数值预测。在案例研究4中,通过马尔可夫链方法研究了受不确定初始孔隙分布影响的压铸窗铰链的失效行为。在最后两个案例研究中,统计推断和更新算法的不确定性模型的数学方法。由于异构频谱的问题,数据建模,采集和同化的一般化策略的开发和应用在每个案例研究。
In this contribution, several case studies with data uncertainties are presented which have been performed in individual projects as part of the DFG (German Research Foundation) Priority Programme SPP 1886 “Polymorphic uncertainty modelling for the numerical design of structures.” In all case studies numerical models with uncertainties are derived from engineering problems describing concepts for handling and incorporating measurement data, either of model input parameters or of the system response. The first case study deals with polymorphic uncertain data based on computer tomographic scans with respect to air voids which are acquired, simplified and integrated in numerical models of adhesive bonds. In the second case study, the variation sensitivity analysis is presented to provide suitable prior knowledge for numerical soil analyses, for example, in order to reduce required input data. The uncertainty in friction processes is treated in case study 3 whereby measurement data are used in data driven methods to improve the numerical predictions. In case study 4, the failure behavior of die‐cast window hinges, which is affected by an uncertain initial pore distribution, is investigated by means of a Markov chain approach. In the last two case studies, mathematical methods of statistical inference and updating algorithms for uncertainty models are shown. Due to the heterogeneous spectrum of problems, a generalized strategy for data modeling, acquisition, and assimilation is developed and applied on each case study.
DOI: 10.1016/j.csda.2006.02.009
发表时间: 2006-11-01
影响因子: 1.8
作者:
Baudrit, C.;Dubois, D.
通讯作者: Dubois, D.
《可能性理论:不确定性的计算机化处理方法》,Didier Dubois 和 Henri Prade,Plenum Press,纽约,1988 年。 xvi 263 页。
DOI: --
发表时间: 1989
期刊:
影响因子: --
作者:
A. Ramer
通讯作者: A. Ramer
DOI: 10.1007/978-3-662-04999-0_2
发表时间: 2002
期刊: Nature
影响因子: 64.8
作者:
J. Bluhm
通讯作者: J. Bluhm
DOI: 10.1016/j.engstruct.2012.12.029
发表时间: 2012-01
期刊: ArXiv
影响因子: --
作者:
B. Rosic;A. Kucerová;J. Sýkora;O. Pajonk;A. Litvinenko;H. Matthies
通讯作者: B. Rosic;A. Kucerová;J. Sýkora;O. Pajonk;A. Litvinenko;H. Matthies
DOI: --
发表时间: 2017
期刊:
影响因子: --
作者:
C. Henning;T. Ricken
通讯作者: T. Ricken