Performance-based global reliability assessment of a high-rise frame-core tube structure subjected to multi-dimensional stochastic earthquakes

When evaluating the seismic safety and reliability of complex engineering structures,it is a critical problem to reasonably consider the randomness and multi-dimensional nature of ground motions.To this end,a proposed modeling strategy of multi-dimensional stochastic earthquakes is addressed in this study.This improved seismic model has several merits that enable it to better provide seismic analyses of structures.Specifically,at first,the ground motion model is compatible with the design response spectrum.Secondly,the evolutionary power spectrum involved in the model and the design response spectrum are constructed accordingly with sufficient consideration of the correlation between different seismic components.Thirdly,the random function-based dimension-reduction representation is applied,by which seismic modeling is established,with three elementary random variables.Numerical simulations of multi-dimensional stochastic ground motions in a specific design scenario indicate the effectiveness of the proposed modeling strategy.Moreover,the multi-dimensional seismic response and the global reliability of a high-rise frame-core tube structure is discussed in detail to further illustrate the engineering applicability of the proposed method.The analytical investigations demonstrate that the suggested stochastic model of multi-dimensional ground motion is available for accurate seismic response analysis and dynamic reliability assessment of complex engineering structures for performance-based seismic resistance design.

A High-Performance and Flexible Chemical Structure&Data Search Engine Built on CouchDB&ElasticSearch

Computer-assisted chemical structure searching plays a critical role for efficient structure screening in cheminformatics. We designed a high-performance chemical structure & data search engine called DCAIKU, built on CouchDB and ElasticSearch engines. DCAIKU converts the chemical structure similarity search problem into a general text search problem to utilize off-the-shelf full-text search engines. DCAIKU also supports flexible document structures and heterogeneous datasets with the help of schema-less document database. Our evaluations show that DCAIKU can handle both keyword search and structural search against millions of records with both high accuracy and low latency. We expect that DCAIKU will lay the foundation towards large-scale and cost-effective structural search in materials science and chemistry research.

Development of hybrid optimization algorithm for structures furnished with seismic damper devices using the particle swarm optimization method and gravitational search algorithm

Previous studies about optimizing earthquake structural energy dissipation systems indicated that most existing techniques employ merely one or a few parameters as design variables in the optimization process,and thereby are only applicable only to simple,single,or multiple degree-of-freedom structures.The current approaches to optimization procedures take a specific damper with its properties and observe the effect of applying time history data to the building;however,there are many different dampers and isolators that can be used.Furthermore,there is a lack of studies regarding the optimum location for various viscous and wall dampers.The main aim of this study is hybridization of the particle swarm optimization(PSO) and gravitational search algorithm(GSA) to optimize the performance of earthquake energy dissipation systems(i.e.,damper devices) simultaneously with optimizing the characteristics of the structure.Four types of structural dampers device are considered in this study:(ⅰ) variable stiffness bracing(VSB) system,(ⅱ) rubber wall damper(RWD),(ⅲ) nonlinear conical spring bracing(NCSB) device,(iv) and multi-action stiffener(MAS) device.Since many parameters may affect the design of seismic resistant structures,this study proposes a hybrid of PSO and GSA to develop a hybrid,multi-objective optimization method to resolve the aforementioned problems.The characteristics of the above-mentioned damper devices as well as the section size for structural beams and columns are considered as variables for development of the PSO-GSA optimization algorithm to minimize structural seismic response in terms of nodal displacement(in three directions) as well as plastic hinge formation in structural members simultaneously with the weight of the structure.After that,the optimization algorithm is implemented to identify the best position of the damper device in the structural frame to have the maximum effect and minimize the seismic structure response.To examine the performance of the proposed PSO-GSA optimization method,it has been applied to a three-story reinforced structure equipped with a seismic damper device.The results revealed that the method successfully optimized the earthquake energy dissipation systems and reduced the effects of earthquakes on structures,which significantly increase the building’s stability and safety during seismic excitation.The analysis results showed a reduction in the seismic response of the structure regarding the formation of plastic hinges in structural members as well as the displacement of each story to approximately 99.63%,60.5%,79.13% and 57.42% for the VSB device,RWD,NCSB device,and MAS device,respectively.This shows that using the PSO-GSA optimization algorithm and optimized damper devices in the structure resulted in no structural damage due to earthquake vibration.

SEGMENTATION ALGORITHM BASED ON EDGE-SEARCHING FOR MULTI-LINEAR STRUCTURED LIGHT IMAGES

Aiming at the problem that the existence of disturbances on the edges of light-stripe makes the segmentation of the light-stripes images difficult, a new segmentation algorithm based on edge-searching is presented. It firstly calculates every edge pixel＇s horizontal coordinate grads to produce the corresponding grads-edge, then uses a designed length-variable l D template to scan the light-stripes＇ grads-edges. The template is able to find the disturbances with different width utilizing the distributing character of the edge disturbances. The found disturbances are eliminated finally. The algorithm not only can smoothly segment the light-stripes images, but also eliminate most disturbances on the light-stripes＇ edges without damaging the light-stripes images＇ 3D information. A practical example of using the proposed algorithm is given in the end. It is proved that the efficiency of the algorithm has been improved obviously by comparison.

Nearest neighbor search algorithm for GBD tree spatial data structure

This paper describes the nearest neighbor (NN) search algorithm on the GBD(generalized BD) tree. The GBD tree is a spatial data structure suitable for two-or three-dimensional data and has good performance characteristics with respect to the dynamic data environment. On GIS and CAD systems, the R-tree and its successors have been used. In addition, the NN search algorithm is also proposed in an attempt to obtain good performance from the R-tree. On the other hand, the GBD tree is superior to the R-tree with respect to exact match retrieval, because the GBD tree has auxiliary data that uniquely determines the position of the object in the structure. The proposed NN search algorithm depends on the property of the GBD tree described above. The NN search algorithm on the GBD tree was studied and the performance thereof was evaluated through experiments.

Web Structure Mining在电子商务网站中的应用

介绍web结构挖掘的概念，并分析基于链接结构的两种重要的Web结构挖掘算法，最后指出其在电子商务网站的应用以提高网站的价值。

Structure learning on Bayesian networks by finding the optimal ordering with and without priors

Ordering based search methods have advantages over graph based search methods for structure learning of Bayesian networks in terms on the efficiency. With the aim of further increasing the accuracy of ordering based search methods, we first propose to increase the search space, which can facilitate escaping from the local optima. We present our search operators with majorizations, which are easy to implement. Experiments show that the proposed algorithm can obtain significantly more accurate results. With regard to the problem of the decrease on efficiency due to the increase of the search space, we then propose to add path priors as constraints into the swap process. We analyze the coefficient which may influence the performance of the proposed algorithm, the experiments show that the constraints can enhance the efficiency greatly, while has little effect on the accuracy. The final experiments show that, compared to other competitive methods, the proposed algorithm can find better solutions while holding high efficiency at the same time on both synthetic and real data sets.

Structural reliability analysis using enhanced cuckoo search algorithm and artificial neural network

The present study proposed an enhanced cuckoo search(ECS) algorithm combined with artificial neural network(ANN) as the surrogate model to solve structural reliability problems. In order to enhance the accuracy and convergence rate of the original cuckoo search(CS) algorithm, the main parameters namely, abandon probability of worst nests paand search step sizeα0 are dynamically adjusted via nonlinear control equations. In addition, a global-best guided equation incorporating the information of global best nest is introduced to the ECS to enhance its exploitation. Then, the proposed ECS is linked to the well-trained ANN model for structural reliability analysis. The computational capability of the proposed algorithm is validated using five typical structural reliability problems and an engineering application. The comparison results show the efficiency and accuracy of the proposed algorithm.

A Rework Reduction Mechanism in Complex Projects Using Design Structure Matrix Clustering Methods

To reduce the uncertainty and reworks in complex projects,a novel mechanism is systematically developed in this paper based on two classical design structure matrix(DSM)clustering methods:Loop searching method(LSM)and function searching method(FSM).Specifically,the optimal working areas for the two clustering methods are first obtained quantitatively in terms of non-zero fraction(NZF)and singular value modularity index(SMI),in which the whole working area is divided into six sub-zones.Then,a judgement procedure is proposed for conveniently choosing the optimal DSM clustering method,which makes it easy to determine which DSM clustering method performs better for a given case.Subsequently,a conceptual model is constructed to assist project managers in effectively analyzing the network of projects and greatly reducing reworks in complex projects by defining preventive actions.Finally,the aircraft design process is presented to show how the proposed judgement mechanism can be utilized to reduce the reworks in actual projects.

Application of CS-PSO algorithm in Bayesian network structure learning

In view of the shortcomings of traditional Bayesian network(BN)structure learning algorithm,such as low efficiency,premature algorithm and poor learning effect,the intelligent algorithm of cuckoo search(CS)and particle swarm optimization(PSO)is selected.Combined with the characteristics of BN structure,a BN structure learning algorithm of CS-PSO is proposed.Firstly,the CS algorithm is improved from the following three aspects:the maximum spanning tree is used to guide the initialization direction of the CS algorithm,the fitness of the solution is used to adjust the optimization and abandoning process of the solution,and PSO algorithm is used to update the position of the CS algorithm.Secondly,according to the structure characteristics of BN,the CS-PSO algorithm is applied to the structure learning of BN.Finally,chest clinic,credit and car diagnosis classic network are utilized as the simulation model,and the modeling and simulation comparison of greedy algorithm,K2 algorithm,CS algorithm and CS-PSO algorithm are carried out.The results show that the CS-PSO algorithm has fast convergence speed,high convergence accuracy and good stability in the structure learning of BN,and it can get the accurate BN structure model faster and better.

Structure prediction, electronic, and mechanical properties of alkali metal MB_(12)(=Be, Mg, Ca, Sr) from first principles

Using the particle swarm optimization algorithm on structural search methods, we focus our crystal structures search on boron-rich alkali metal compounds of MB_(12)(M = Be, Mg, Ca, Sr) with simulation cell sizes of 1–2 formula units(f.u.)at 0 GPa. The structure, electronic, and mechanical properties of MB_(12) are obtained from the density functional theory using the plane-wave pseudopotential method within the generalized gradient approximations. The formation enthalpies of MB_(12) regarding to solid metal M and solid alpha-boron suggested the predicted structures can be synthesized except for BeB12. The calculated band structures show MB_(12)(M = Be, Mg, Ca, Sr) are all indirect semiconductors. All the calculated elastic constants of MB_(12) satisfy the the mechanical stable conditions. The mechanical parameters(i.e., bulk modulus,shear modulus, and Young’s modulus) are derived using the Voigt–Reuss–Hill method. The G/B ratios indicated that the MB_(12) should exhibit brittle behavior. In addition, the hardness, Debye temperature, universal anisotropic index, and the percentage of anisotropy in compression and shear are also discussed in detail. We hope our results can inspire further experimental study on these boron-rich alkali-metal compounds.

Analysis of the ore-controlling structure of the Shihu gold deposit, Hebei Province and deep-seated ore-prospecting prediction

Under the guidance of the theory of mantle-branch structure-associated metallogenesis and on the basis of the geological characteristics, analysis of the ore-forming and ore-controlling structures, the geochemical characteristics of metallogenesis, the source of ore-forming materials, changes in the physical and chemical conditions of metallogenesis, changes in the vertical width of ore veins, and changes in gold grade of the Shihu gold deposit, the mechanism of its metallogenesis was discussed and the rules of vertical variation of ore veins were summarized in this study. It is pointed out that the orebodies under exploitation at present time should be in the middle and upper portions of gold veins in the Shihu gold mining district. Particularly on the basis of the characteristics of mantle-branch structure-associated metallogenesis, it is indicated that metallogenesis is controlled mainly by such ore-forming conditions as temperature and pressure. Deep-seated ore-forming fluids are characterized mainly by injection and precipitation. So the vein bodies in the adjacent metallogenic structures are of obvious comparability, and there would be great prospects for ore search both at depth and in the periphery of the Shihu gold deposit. Therefore, ore prospecting should be strengthened both at depth and in the peripheries.

HiSC:A Hybrid XML Index Composing Structure-Encoded with Cluster

A new way of indexing and processing twig patterns in an XML documents is proposed in this paper. Every path in XML document can be transformed into a sequence of labels by Structure-Encoded that constructs a one-to-one correspondence between XML tree and sequence. Base on identifying characteristics of nodes in XML tree, the elements are classified and clustered. During query proceeding, the twig pattern is also transformed into its Structure-Encoded. By performing subsequence matching on the set of sequences in XML documents, all the occurrences of path in the XML documents are refined. Using the index, the numbers of elements retrieved are minimized. The search results with pertinent format provide more structure information without any false dismissals or false alarms. The index also supports keyword search Experiment results indicate the index has significantly efficiency with high precision.

Optimum structural design of full-scale steel buildings using drift-tribe-charged system search

In this paper,the potential of utilizing improved metaheuristic approaches in optimal design of building structures is concerned.In this regard,the drift-tribe-charged system search algorithm is proposed that the position and velocity updating processes of the charged system search is developed by implementing the mathematical presentation of the free-electron model utilized for metal conductors.In addition,the searching phase of the developed algorithm is also divided into three separate phases in order to improve the convergence capability of the algorithm.By means of these modifications,the exploitation and exploration rates of the standard algorithm are enhanced.In order to determine the ability of the proposed improved metaheuristic method considering some complex optimization problems,a 10-story steel building structure with 1026 structural members alongside a 60-story structure with 8272 members are utilized as numerical examples.The overall capability of the developed metaheuristic approach is compared with other metaheuristics.A total number of 30 independent runs have been conducted for each of the standard and proposed methods while a statistical analysis is also conducted for comparative purposes.The obtained optimum results demonstrated that the proposed metaheuristic approach is capable of preparing better outcomes than other metaheuristics.

Quality Analyses of Fine Structures Transfer in the Photorealistic Images

This work presents method of the quality analyses of the photorealistic images. Developed method utilizes proposed criteria of image definition quality for fine details. Presented method has the following significant property: the quality estimation is provided without test images or patterns. Algorithm for search and recognition of fine structures in the photorealistic images using the predefined criterion is considered.

Necessary and Sufficient Conditions for Feasible Neighbourhood Solutions in the Local Search of the Job-Shop Scheduling Problem

The meta-heuristic algorithm with local search is an excellent choice for the job-shop scheduling problem(JSP).However,due to the unique nature of the JSP,local search may generate infeasible neighbourhood solutions.In the existing literature,although some domain knowledge of the JSP can be used to avoid infeasible solutions,the constraint conditions in this domain knowledge are sufficient but not necessary.It may lose many feasible solutions and make the local search inadequate.By analysing the causes of infeasible neighbourhood solutions,this paper further explores the domain knowledge contained in the JSP and proposes the sufficient and necessary constraint conditions to find all feasible neighbourhood solutions,allowing the local search to be carried out thoroughly.With the proposed conditions,a new neighbourhood structure is designed in this paper.Then,a fast calculation method for all feasible neighbourhood solutions is provided,significantly reducing the calculation time compared with ordinary methods.A set of standard benchmark instances is used to evaluate the performance of the proposed neighbourhood structure and calculation method.The experimental results show that the calculation method is effective,and the new neighbourhood structure has more reliability and superiority than the other famous and influential neighbourhood structures,where 90%of the results are the best compared with three other well-known neighbourhood structures.Finally,the result from a tabu search algorithm with the new neighbourhood structure is compared with the current best results,demonstrating the superiority of the proposed neighbourhood structure.

水下人-机协同搜救作业人因可靠性分析研究

为分析水下人-机协同搜救作业人因可靠性并识别其关键影响因素,根据水下搜救训练实际和相关研究结论提取人因可靠性影响因素;建立人因可靠性影响因素体系,利用解释结构模型定性分析各影响因素间相关关系,将建立的各影响因素的解释结构模型转换为贝叶斯网络拓扑结构,分别构建潜水员作业、无人遥控潜水器(ROV)作业、人-机协同作业人因可靠性分析贝叶斯网络;通过对3类贝叶斯网络进行推理,揭示影响人因可靠性的关键因素及其依赖关系,并定量分析3种作业模式下的人因可靠性变化。结果表明:人-机协同搜救作业中“误解意图”“通信不畅”“信息不对称”“作业精度不足”“丧失救助能力”等影响因素起到关键作用;当上述因素得到较好控制时,人-机协同搜救作业的人因可靠性将会表现出优于单纯的ROV或潜水员独立施救的效能。研究结果可为水下搜救作业人因可靠性分析与提升提供参考。

基于天牛须算法的钢筋混凝土框架结构优化

为使天牛须算法适用于解决钢筋混凝土框架离散变量结构优化问题,将天牛须算法进行改进,对天牛位置更新进行离散化处理。通过对两个钢筋混凝土框架结构优化算例进行分析,其结果表明:改进后的天牛须算法相较于遗传算法具有更好的优化效率。因此改进后的天牛须算法是一种适用于钢筋混凝土框架结构优化的智能优化算法。

基于立方Farrow结构的插值细搜频偏估计算法

在高动态通信环境中,由相对运动引起的多普勒频移会在接收机下变频所得的基带信号中引入残留频偏,致使基带信号的相位发生偏离。对频偏进行精确估计是提升高动态环境通信质量的重要途径。传统方法通常通过对快速傅里叶变换(Fast Fourier Transform,FFT)后所得频谱进行一维搜索来估计载波频偏值,只能估计整数倍频点。为了进一步提高频偏估计的精度,本文提出了一种基于立方Farrow结构的插值细搜(Interpolation Detail Search, IDS)算法。仿真结果表明,此算法仅在16倍插值条件下就得到了逼近克拉美罗界(Cramer-Rao Bounds,CRB)的频偏估计性能,信噪比精度损失仅为1.2 dB,具有良好的估计性能。

基于改进麻雀搜索算法的变电构架优化方法

为了解决变电构架设计中的优化问题,采用改进麻雀搜索算法对其进行优化设计。在基本麻雀搜索算法中引入Circle混沌映射,以提高种群的多样性和算法的全局搜索能力;引入萤火虫算法对麻雀搜索算法进行扰动更新,使其易于跳出局部最优。建立尺寸优化的数学模型,采用罚函数法处理约束条件。先将改进后的算法用于典型桁架算例分析,证明其稳定性与有效性,再将其用于变电构架的优化设计,结果表明,采用改进后的麻雀搜索算法能够有效提升变电构架的优化效果。