Multi-Objective Optimization of Tree Trunk Axes in Glulam Beam Design Considering Fuzzy Probability-Based Random Fields

F. N. Schietzold, W. Graf, M. Kaliske
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引用次数: 5

Abstract

Deterministic design and a priori parameters are used in traditional optimization approaches. The material characteristics of solid wood are not deterministic in reality. Hence, realistic optimization and simulation methods need to take the uncertainties of parameters into account. The uncertainty characteristics of wood are mainly originated in natural variation. In addition to this, incertitudes from lack of knowledge are inherent. Accordingly, the aleatoric approach of randomness can be expanded to a polymorphic uncertainty model. Fuzzy probability-based randomness is used in this work. Therefore, the epistemic approach of fuzziness is taken into account. The distribution functions of random variables are parametrized by fuzzy variables. So coupling of both, aleatoric and epistemic uncertainties, is involved. Interactions of fuzzy variables and crosscorrelations of random variables are considered among and within the parameters. Crosscorrelated random fields are used to represent spatial variation of material parameters. The autocovariance structures are modeled structurally dependent on the tree trunk axes. Finite element method is applied as deterministic basic solution of a loaded timber structure. A local orthotropic material formulation with respect to specifically located tree trunk axes is used. The optimal positions of the tree trunk axes for each wooden log are examined as design parameters. Polymorphic uncertainty is used to describe a priori parameters. The developed methods for uncertainty analysis are embedded in an automated and parallelized optimization processing. An analysis of a two-tier glulam beam, according to a purlin of a timber roof construction, is shown as numerical example for the optimization framework.
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基于模糊概率随机场的胶合木梁树干轴线多目标优化
传统的优化方法采用确定性设计和先验参数。实木的材料特性在现实中是不确定的。因此,现实的优化和仿真方法需要考虑参数的不确定性。木材的不确定性主要来源于自然变化。除此之外,由于缺乏知识而产生的不确定性是固有的。因此,随机的任意方法可以扩展为多态不确定性模型。本文采用了基于模糊概率的随机性。因此,本文考虑了模糊的认知方法。随机变量的分布函数用模糊变量参数化。因此,涉及到任意不确定性和认知不确定性两者的耦合。考虑了参数间和参数内模糊变量的相互作用和随机变量的相互关系。采用互相关随机场表示材料参数的空间变化。自协方差结构在结构上依赖于树干轴。采用有限元法作为木结构受载的确定性基本解。一个局部正交各向异性材料的公式相对于特定位置的树干轴被使用。每个原木的树干轴的最佳位置作为设计参数进行了检查。多态不确定性用于描述先验参数。所开发的不确定性分析方法嵌入在自动化和并行化的优化处理中。以某木结构屋面结构为例,对两层胶合梁进行了分析,并给出了优化框架的数值算例。
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CiteScore
5.20
自引率
13.60%
发文量
34
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