Probabilistic crack trajectory analysis by a dimension reduction method

This paper proposes a novel analysis method of stochastic crack trajectory based on a dimension reduction approach. The developed method allows efficiently estimating the statistical moments, probability density function and cumulative distribution function of the crack trajectory for cracked elastic structures considering the randomness of the loads, material properties and crack geometries. First, the traditional dimension reduction method is extended to calculate the first four moments of the crack trajectory, in which the responses are eigenvectors rather than scalars. Then the probability density function and cumulative distribution function of the crack trajectory can be obtained using the maximum entropy principle constrained by the calculated moments. Finally, the simulation of the crack propagation paths is realized by using the scaled boundary finite element method. The proposed method is well validated by four numerical examples performed on varied cracked structures. It is demonstrated that this method outperforms the Monte Carlo simulation in terms of computational efficiency, and in the meanwhile, it has an acceptable computational accuracy.     

Critical factors and paths influencing construction workers’ safety risk tolerances

While workers’ safety risk tolerances have been regarded as a main reason for their unsafe behaviors, little is known about why different people have different risk tolerances even when confronting the same situation. The aim of this research is to identify the critical factors and paths that influence workers’ safety risk tolerance and to explore how they contribute to accident causal model from a system thinking perceptive. A number of methods were carried out to analyze the data collected through interviews and questionnaire surveys. In the first and second steps of the research, factor identification, factor ranking and factor analysis were carried out, and the results show that workers’ safety risk tolerance can be influenced by four groups of factors, namely: (1) personal subjective perception; (2) work knowledge and experiences; (3) work characteristics; and (4) safety management. In the third step of the research, hypothetical influencing path model was developed and tested by using structural equation modeling (SEM). It is found that the effects of external factors (safety management and work characteristics) on risk tolerance are larger than that of internal factors (personal subjective perception and work knowledge & experiences). Specifically, safety management contributes the most to workers’ safety risk tolerance through its direct effect and indirect effect; while personal subjective perception comes the second and can act as an intermedia for work characteristics. This research provides an in-depth insight of workers’ unsafe behaviors by depicting the contributing factors as shown in the accident causal model developed in this research.     

SVC动态特性对风电场接入电网电压稳定性的影响

以多数风场配置的无源无功补偿装置为例,构建TCR/MCR型SVC仿真控制模型,研究它们在风场动稳和暂稳期间的响应特性,分析它们对风电运行电压稳定的改善作用仿真结果表明TCR/MCR型SVC对于提高风电场电压稳定性均具有明显的作用,但前者能更快地跟踪电压波动,快速调整无功输出,更好地抑制了电压波动.     

电脑鼠走迷宫算法仿真设计

主要研究电脑鼠走迷宫的算法,主要包括迷宫生成算法、原始全迷宫搜索算法和修正后的泛洪算法.改进后的算法可以搜索到从起点到终点的所有可行路径中的一条最佳路径,以实现快速、高效求解迷宫的目的.     

论独立学院应用型艺术设计人才培养模式研究

独立学院是近年来我国高等教育的新产物,也是素质教育新形势下的高等教育办学体制与模式的一项探索和创新.独立学院艺术设计专业在人才培养模式上应强调应用型人才的培养.本文根据独立学院的现状,分别从教学模式、专业课程及教学资源等方面,探讨了独立学院艺术设计专业人才培养的问题,以求探索出一条适合独立院校设计类专业发展的新路子,不断创新加强人才培养的抗风险能力,为今后独立学院艺术设计专业人才培养模式的构建提供一定的参考.     

北京王府井步行商业街景观环境设计探析

通过对北京王府井步行商业街景观环境现状进行研究分析,归纳总结出王府井步行商业街景观设计应遵循的原则,并且提出对王府井步行商业街景观环境设计的对策：突出历史文化的主题,构建绿色、和谐的街道形态,加强街道景观的维护管理,从而对王府井步行商业街景观环境进行更为良好的营造,提升王府井步行商业街景观环境的质量.     

Dynamic mechanical and thermal properties of MAPE treated jute/HDPE composites

The present paper summarizes an experimental study on the mechanical and viscoelastic behavior of jute fibre reinforced high density polyethylene (HDPE) composites. Variations in mechanical strength, storage modulus (E′), loss modulus (E″) and damping parameter (tan δ) with the addition of fibres and coupling agents were investigated. It was observed that the tensile, flexural and impact strengths increased with the increase in fibre loading upto 30%, above which there was a significant deterioration in the mechanical strength. Further, the composites treated with MAPE showed improved properties in comparison to the untreated composites. Dynamic mechanical analysis data showed an increase in the storage modulus of the treated composites The tan δ spectra presented a strong influence of fibre content and coupling agent on the α and γ relaxation process of HDPE. The thermal behavior of the composites was evaluated from TGA/DTG thermograms. The fibre–matrix morphology in the treated composites was confirmed by SEM analysis of the tensile fractured specimens. FTIR spectra of the treated and untreated jute fibres was also studied to ascertain the existence of type of interfacial bonds.     

Analysis of stiffened corrugated plates based on the FSDT via the mesh-free method

The elastic bending of unstiffened and stiffened corrugated plates is studied in this paper, and a mesh-free Galerkin method is presented for the analyses. A corrugated plate is treated as an orthotropic plate that has different flexure properties in two perpendicular directions. The equivalent flexure properties are estimated by applying constant curvature conditions to the corrugated sheet. The stiffened corrugated plate is considered as a composite structure of an orthotropic plate with beams. By superimposing the strain energy of the orthotropic plate and the beams, and imposing the displacement compatibility conditions between the plate and the beams, the stiffness matrix of the structure is obtained. Because no mesh is needed in the proposed method, there is no limitation to the position of the stiffeners (beams). Changes in the positions of the stiffeners do not require the re-meshing of the plate. Several numerical examples are employed to show the accuracy and convergence of the proposed method. The computation results demonstrate good agreement with the solutions given by ANSYS, and different profiles of corrugated plates are considered.     

Received signal strength based positioning for multiple nodes in wireless sensor networks

We address the problem of locating multiple nodes in a wireless sensor network with the use of received signal strength (RSS) measurements. In RSS based positioning, transmit power and path-loss factor are two environment dependent parameters which may be uncertain or unknown. For unknown transmit powers, we devise two-step weighted least squares (WLS) and maximum likelihood (ML) algorithms for node localization. The mean square error of the former is analyzed in the presence of zero-mean white Gaussian disturbances. When both transmit powers and path-loss factors are unavailable, two nonlinear least squares estimators, namely, the direct ML approach and combination of linear least squares and ML algorithm, are developed. Numerical examples are also included to evaluate the localization accuracy of the proposed estimators by comparing with two existing node positioning methods and the Cramér–Rao lower bound.     

Detecting outlier pairs in complex network based on link structure and semantic relationship

In this paper, we propose an outlier pair detection method, called LSOutPair, which discovers the vast differences between link structure and semantic relationship. LSOutPair addresses three important challenges: (1) how can we measure the target object's link similarity among multi-typed objects and multi-typed relations? (2) how can we measure the semantic similarity using the short texts? (3) how can we find the objects’ maximum differences between link structure and semantic relationship? To tackle these challenges, LSOutPair applies three main techniques: (1) two matrices are used to store link similarity and semantic similarity, (2) a k-step index algorithm, which calculates the term weighting for each object, (3) applying the linear transformation of Frobenius norm to matrices can obtain the top-K outlier pairs. LSOutPair considers link and semantics in complex network simultaneously, which is a new attempt in data mining. Substantial experiments show that LSOutPair is very effective for outlier pair detection.