Comparison of finite element reliability methods

The spectral stochastic finite element method (SSFEM) aims at constructing a probabilistic representation of the response of a mechanical system, whose material properties are random fields. The response quantities, e.g. the nodal displacements, are represented by a polynomial series expansion in terms of standard normal random variables. This expansion is usually post-processed to obtain the second-order statistical moments of the response quantities. However, in the literature, the SSFEM has also been suggested as a method for reliability analysis. No careful examination of this potential has been made yet. In this paper, the SSFEM is considered in conjunction with the first-order reliability method (FORM) and with importance sampling for finite element reliability analysis. This approach is compared with the direct coupling of a FORM reliability code and a finite element code. The two procedures are applied to the reliability analysis of the settlement of a foundation lying on a randomly heterogeneous soil layer. The results are used to make a comprehensive comparison of the two methods in terms of their relative accuracies and efficiencies.     

Data requirements for neutron activation: Part I: Cross sections

Existing neutron cross section libraries such as EAF-2003 contain a large number of reactions. Of these only a small proportion are significant in the production of the nuclides that dominate activation quantities such as activity or γ-dose rate at various decay times. These reactions were identified in a recent extensive set of calculations on all the elements and reported in the ‘Activation Handbook’. These 1340 reactions are considered here and the set of reactions with no differential or integral data are listed and prioritised. A set of 339 reactions with very limited possibility of measurement are given; these require further study by theoretical calculations. A set of 100 reactions with either discrepant or no data, that might be measurable are listed and are recommended to be the subject of future experimental work.     

浅析艺术设计专业设立工作室制教学模式的重要性

当今时代,随着文化与经济的不断发展,市场越来越需要能快速适应社会发展的全方位设计人才。就艺术设计专业而言,对设计人才的培养应是多层次、多元化的。目前国内艺术设计教育与市场还存在脱节的现象,传统的视觉传达设计教育模式受到考验。本文通过论述工作室制教学模式的优点,探讨了艺术设计专业设立工作室制的重要性。     

Importance Sampling Microfacet‐Based BSDFs using the Distribution of Visible Normals

We present a new approach to microfacet‐based BSDF importance sampling. Previously proposed sampling schemes for popular analytic BSDFs typically begin by choosing a microfacet normal at random in a way that is independent of direction of incident light. To sample the full BSDF using these normals requires arbitrarily large sample weights leading to possible fireflies. Additionally, at grazing angles nearly half of the sampled normals face away from the incident ray and must be rejected, making the sampling scheme inefficient. Instead, we show how to use the distribution of visible normals directly to generate samples, where normals are weighted by their projection factor toward the incident direction. In this way, no backfacing normals are sampled and the sample weights contain only the shadowing factor of outgoing rays (and additionally a Fresnel term for conductors). Arbitrarily large sample weights are avoided and variance is reduced. Since the BSDF depends on the microsurface model, we describe our sampling algorithm for two models: the V‐cavity and the Smith models. We demonstrate results for both isotropic and anisotropic rough conductors and dielectrics with Beckmann and GGX distributions.     

关于我国中小企业实施会计电算化制度的探讨

信息化时代对财务管理的科学化、高效率、全方位提出了新的要求,会计电算化越来越被企业所重视,特别是地位日益重要的中小企业。随着中小企业的规模不断壮大,贸易往来越来越频繁,如何从财务的角度,精细化、集约化的管理好企业,是中小企业面临的最大问题。为此,市场经济环境下,会计电算化成为势在必行的大趋势。     

给水管网抗震对策的重要度分析方法研究

针对城市给水管线不同管段在灾后对于管网整体可靠度影响的差异性,为了能够较好地评价不同管段对管网系统连接可靠度的贡献,引入失效概率重要度和关键重要度,建立了基于历史经验方法的管网可靠度及管线失效概率重要度、关键重要度计算模型。实例计算结果表明,该模型计算的管网连接可靠度结果与其他文献方法的计算结果基本一致,验证了模型的合理性、有效性。进而应用该模型计算出各段管线的失效概率重要度、关键重要度,对管线防灾等级划分,给出了管网分割方法与管网震后恢复策略。研究结果为编制给水管网抗震防灾规划、震后管网恢复计划及制定出相应的抗灾应急措施提供依据。     

Efficient conditional probability theorem and importance sampling-based methods for global reliability sensitivity analysis

Global reliability sensitivity (GRS) analysis can measure the effect of random inputs on failure probability (FP). To efficiently solve GRS, two conditional probability theorem (CPT)-based methods are proposed by combining adaptive Kriging (AK) with importance sampling (IS) (CPT-AK-IS) and combining AK with Meta-IS (CPT-AK-Meta-IS) respectively. Firstly, differentiation approximation and CPT are used to convert the estimation of conditional probability density function (PDF), which is required by the existing Bayes theorem-based methods, into that of a series of probabilities. Secondly, GRS can be directly estimated by the failure samples of IS, while the existing Bayes theorem methods based on IS need to transform the failure samples of IS into those of original PDF. Both the first and second strategies can reduce the computational complexity of solving GRS. Thirdly, by selecting a suitable differentiation interval with a proposed adaptive strategy, the estimation of a series of probabilities can be accurately completed as a byproduct of one IS based simulation for solving FP without additional computational cost. Finally, by introducing AK into IS and Meta-IS, it can reduce the number of evaluating performance function and the size of candidate sample pool simultaneously. These novelties are sufficiently verified by the presented examples.     

Importance sampling for volumetric illumination of flames

Physically based rendering of scenes with volumetric illumination of flames remains a challenging problem due to the complexity of their heterogeneous radiative properties. Current bidirectional importance sampling strategies have been focusing on emissive light sources without anisotropic extinction. In this paper, we present an efficient importance sampling method for volumetric light sources with anisotropic extinction. According to the radiative properties of flames, we separate the computation of anisotropic extinction from the evaluation of illumination inside flames and utilize cluster-based hierarchies to rapidly estimate them. To exploit the coherence of radiative voxels, we also propose a new similarity metric to aggregate voxels into clusters. For each pixel to be shaded, we use these clusters to rapidly approximate the importance function of voxels, and draw final illumination samples from clusters. Our results show that this approach substantially reduces the variance of images when rendering scenes with flames.     

Adaptive simulation for system reliability analysis of large structures

This article proposes an efficient simulation-based methodology to estimate the system reliability of large structures. The proposed method uses a hybrid approach: first, a probabilistic enumeration technique is used to identify a significant system failure sequence. This provides an initial sampling domain for an adaptive importance sampling procedure. As further simulations are performed, information about other significant sequences is incorporated to refine the sampling domain and to estimate the failure probability of the system. The adaptive sampling overcomes the restrictive assumptions of analytical techniques, yet achieves the robustness and accuracy of basic Monte Carlo simulation in an efficient manner. In this article, the proposed method is implemented using the ANSYS finite element software, and is applied to the system reliability estimation of two redundant structural systems, a six-story building frame and a transmission tower. Both ductile and brittle failure modes are considered. The method is structured in a modular form such that it can be easily applied to different types of problems and commercial software, thus facilitating practical application.