分布式环境下并行有限元分析策略的研究

为提高结构优化设计的效率，研究了结构静动态性能的快速分析方法。提出了一种分布式环境下并行有限元分析策略，并从参数化有限元分析、有限元分析过程自动化和有限元分析任务动态分配三个方面阐述了其实现方法。提出的策略成功地应用于液压挖掘机工作装置的结构静动态协同优化设计中。     

水压轴向柱塞泵配流盘最小水膜厚度的理论分析——结构参数的影响

最小水膜厚度是保证配流盘静压支承工作的基本条件，本文提出了最小水膜厚度应满足的基本要求，在两种不同的运动副表面粗糙度下，分别讨论了配流盘静压支承的主要结构参数对最小水膜厚度的影响，另一方面，分析结果又为结构参数的设计提供了参考依据。     

周期式冷轧管机的发展

叙述了周期式冷轧管机国内外开发、研制的历史和现状。介绍了典型型号的周期式冷轧管机的技术参数,结构特点及目前应用情况。     

Mooring system diagnosis and structural reliability control for position moored vessels

Early diagnosis and fault-tolerant control are essential for safe operation of floating platforms where mooring systems maintain vessel position and must withstand environmental loads. This paper considers two critical faults, line breakage and loss of a buoyancy element and employs vector statistical change detection for timely diagnosis of faults. Diagnosis design is scrutinised and a procedure is proposed based on specified false alarm probability and estimation of the distribution of the test statistics on which change detection is based. A structural reliability index is applied for monitoring the safety level of each mooring line and a set-point chasing algorithm accommodates the effects of line failure, as an integral part of the reliability-based set-point chasing control algorithm. The feasibility of the diagnosis and of the fault-tolerant control strategy is verified in model basin tests.     

Detection of delamination in laminated composites with limited measurements combining PCA and dynamic QPSO

This paper presents an output only damage diagnostic algorithm based on frequency response functions and the principal components for health monitoring of laminated composite structures. The principal components evaluated from frequency response data, are employed as dynamical invariants to handle the effects of operational/environmental variability on the dynamic response of the structure. Finite element models of a laminated composite beam and plate are used to generate vibration data for healthy and damaged structures. Three numerical examples include a laminated composite beam, cantilever plate made of carbon–epoxy and a laminated composite simply supported plate. Varied levels of delamination of laminated composite plies and matrix cracking at varied locations in the plies are simulated at different spatial locations of the structure. Numerical investigations have been carried out to identify the spatial location of damage using the proposed principal component analysis (PCA) based algorithm. In order to limit the number of sensors on the structure, an optimal sensor placement algorithm based on PCA is employed in the present work and the effectiveness of the proposed algorithm with a limited number of sensors is also investigated. Finally, the inverse problem associated with the detection of delamination and matrix cracking is formulated as an optimization problem and is solved using the newly developed dynamic quantum particle swarm optimization (DQPSO) algorithm. Studies carried out and presented in this paper clearly indicate that the proposed SHM scheme can robustly identify the instant of damage, spatial location, the extent of delamination and matrix cracking even with limited sensor measurements and also with noisy data.     

Students Weigh In: Usability Test of Online Library Tutorials

Librarians can improve their online tutorials by borrowing usability testing techniques from the computer science field to improve the human-computer interface. This study involved a multimethod usability test of librarian-created tutorials to determine what students learned, how they felt on several affective questions, and what they suggested for improving the tutorials. Results of pre- and post-tests showed that student knowledge increased, and surveys and focus group findings lean to several suggestions for improving engagement and placing tutorials where they will be most effective. This case study demonstrates the value of user input to improve the effectiveness of online instruction for information literacy.     

Comparing interpolation techniques for monthly rainfall mapping using multiple evaluation criteria and auxiliary data sources: A case study of Sri Lanka

Interpolating climatic variables such as rainfall is challenging due to the highly variable nature of meteorological processes, the effects of terrain and geography, and the difficulty in establishing a representative network of stations. While interpolation models are being adapted to include these effects, often the rainfall data contain significant gaps in coverage. In this paper, we evaluated rainfall data from an agro-ecological monitoring network for producing maps of total monthly rainfall in Sri Lanka. We compared four spatial interpolation techniques: inverse distance weighting, thin-plate splines, ordinary kriging, and Bayesian kriging. Error metrics were used to validate interpolations against independent data. Satellite data were used to assess the spatial pattern of rainfall. Results indicated that Bayesian kriging and splines performed best in low and high rainfall, respectively. Rainfall maps generated from the agro-ecological network were found to have accuracies consistent with previous studies in Sri Lanka.     

Limit load and shakedown analysis of plastic structures under stochastic uncertainty

Problems from plastic analysis are based on the convex, linear or linearised yield/strength condition and the linear equilibrium equation for the stress (state) vector. In practice one has to take into account stochastic variations of several model parameters. Hence, in order to get robust maximum load factors, the structural analysis problem with random parameters must be replaced by an appropriate deterministic substitute problem. A direct approach is proposed based on the primary costs for missing carrying capacity and the recourse costs (e.g. costs for repair, compensation for weakness within the structure, damage, failure, etc.). Based on the mechanical survival conditions of plasticity theory, a quadratic error/loss criterion is developed. The minimum recourse costs can be determined then by solving an optimisation problem having a quadratic objective function and linear constraints. For each vector a(·) of model parameters and each design vector x, one obtains then an explicit representation of the “best” internal load distribution F^∗. Moreover, also the expected recourse costs can be determined explicitly. Consequently, an explicit stochastic nonlinear program results for finding a robust maximal load factor μ^∗. The analytical properties and possible solution procedures are discussed.     

Conceptual equivalence for contrast mining in classification learning

Learning often occurs through comparing. In classification learning, in order to compare data groups, most existing methods compare either raw instances or learned classification rules against each other. This paper takes a different approach, namely conceptual equivalence, that is, groups are equivalent if their underlying concepts are equivalent while their instance spaces do not necessarily overlap and their rule sets do not necessarily present the same appearance. A new methodology of comparing is proposed that learns a representation of each group’s underlying concept and respectively cross-exams one group’s instances by the other group’s concept representation. The innovation is fivefold. First, it is able to quantify the degree of conceptual equivalence between two groups. Second, it is able to retrace the source of discrepancy at two levels: an abstract level of underlying concepts and a specific level of instances. Third, it applies to numeric data as well as categorical data. Fourth, it circumvents direct comparisons between (possibly a large number of) rules that demand substantial effort. Fifth, it reduces dependency on the accuracy of employed classification algorithms. Empirical evidence suggests that this new methodology is effective and yet simple to use in scenarios such as noise cleansing and concept-change learning.     

Explaining IS continuance in environments where usage is mandatory

Several research efforts over the last decade have attempted to explain user acceptance in mandated environments. This research is an attempt in the same direction. It addresses users’ satisfaction in mandated environments to further contribute to our understanding of how we can manage mandated use of information systems (IS) effectively beyond initial adoption. To better explain users’ IS continuance a revised post-acceptance model is proposed and empirically tested using the structural equation modelling technique. The results demonstrate the reliability and validity of the proposed measurement model and further demonstrate that confirmed expectations and ease of use perceptions explain 61% of the users’ satisfaction in this setting. Our findings have important implications for the management of users in mandated environments as well as for further research in the area of mandated use. To that end, we offer directions for future research.