基于宽度学习的结构沉降预测

结构监测是确保工程结构建设在施工和运营阶段安全的关键因素,因此采用合理有效的预测模型对结构沉降监测数据进行科学准确的预测成为了当前结构沉降预测研究的重点。针对传统预测方法与深度学习方法用于结构沉降预测存在的预测精度不够高、模型结构复杂、训练耗时等问题,提出了一种基于宽度学习的结构沉降时间序列预测模型。通过实测地铁地下隧道沉降监测数据对宽度学习、人工神经网络、支持向量回归和深度置信网络-支持向量回归预测模型的预测结果进行对比分析。实验结果表明:宽度学习系统(broad learning system,BLS)应用于结构沉降预测具有良好的效果,其训练速度更快,预测精度更高。验证了所提出的宽度学习算法应用于结构沉降预测的可实施性和有效性。     

基于大数据的产品族本体造型意象挖掘方法研究

为提升产品造型意象成族的准确性,增强感性工学研究中意象词汇提取的规范性和知识重用性。 首先从同族、泛族、异族的概念切入,对目标产品族的造型意象本体进行了定义;再借助 word2vec 工具和主 成分分析法(PCA)分别完成了对产品族意象词汇的关联性联想和降维提取,从而构建了意象词汇挖掘机制,通 过此机制可以辅助设计师利用网络大数据资源更高效、准确地进行目标产品意象的挖掘,一定程度上解决了传 统感性工学在意象挖掘方法中模糊性。最后结合意象词汇与造型特征的映射关系,利用 Protege 工具构建了产 品族造型意象的本体模型,对目标产品的造型意象知识进行了逻辑化表征,为下一代产品继承并发展原产品族 造型意象提供参考。以马自达 MX-5 车系的造型意象为例构建了本体模型,并进行了子代产品前脸的概念设计。     

顶管施工引起地表塌陷及关键技术分析

长距离大断面顶管施工不可避免的引起土体扰动和土层损失,导致土体塌陷和地表拉裂等现象.以某长距离超大断面顶管工程为工程研究背景,对顶管施工引起土体变形的机理展开了分析,对顶进施工过程中土体产生塌陷、地表出现张拉裂缝的原因进行了阐释,探讨了地表变位对周边建筑（构筑）物的影响,以及分析了该工程中运用的进出洞、中继器、触变泥浆减阻、加强现场监测、以及其他应急措施这5种关键控制技术,得到了一些保证工程施工安全的有益的经验.     

泥页岩中有机质-黏土复合体的微观结构、变形作用及源-储意义

泥页岩中的有机质和黏土矿物在沉积演化过程中能够相互结合形成有机质-黏土复合体,成为重要的生烃母质。基于大量的场发射扫描电镜和透射电镜观察分析,以中国鄂尔多斯盆地三叠系延长组、黔北奥陶系-志留系五峰组-龙马溪组、黔中寒武系牛蹄塘组及南华北盆地二叠系山西组4套泥页岩储层为研究对象,详细查明了泥页岩中有机质-黏土复合体的微观结构及变形作用,并深入探讨了其源-储意义。泥页岩中有机质-黏土复合体成分复杂,形态多样,且易发生变形;驱动复合体发生变形的主要机制有构造应力作用、矿物颗粒作用、有机质赋存及黏土矿物转化。其中,由外部构造应力和复合体内部矿物颗粒对黏土层、有机质层挤压引起的变形能够改变复合体局部应力环境,所形成的拉张环境可使复合体发育大量纳米孔隙,且这些孔隙因黏土层的保护而不易发生烃类散失,可有效提升泥页岩的储集能力。相关结论有助于完善泥页岩的成岩理论,增进对页岩油气生成、运移和储集过程的认识,进而指导页岩油气的勘探开发。     

基于流固耦合的尼龙网流场特性及变形分析

考虑到柔性网衣在水流作用下易发生变形,会造成网箱有效体积减小并伴随网衣撕裂风险,因此研究网衣周围流场变化及网衣变形特性具有重要意义。基于剪应力SST k-ω湍流模型,结合ANSYS Workbench的单向流固耦合(Fluid-Solid Interaction, FSI)方法,将网衣所受压力作为输入载荷施加在平面网表面,研究在不同流速、网衣密实度和攻角情况下平面尼龙无结网衣的流场特性,对大变形非线性网衣结构的有限元模型进行分析。结果表明基于FSI的单向耦合数值模拟用于平面网衣变形及流场特性分析具有可行性,网衣造成的流速降低现象在不同攻角条件下的差异较明显。得到网衣水动力系数在不同流速、网衣密实度和攻角下的变化情况,以及平面网的等效应力分布特点和变形随攻角变化的特性,发现从网衣中心网线至边缘位置网线处的应力由大逐渐变小,最终在网线固定端附近发现应力最大位置。     

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 65钢热轧圆盘条广泛应用于拉拔高强度钢丝。在拉拔钢丝的过程中断裂现象时有发生。用金相手段分析断裂原因。分析结果认为：导致拉丝断裂的原因是拉丝工艺不当。     

Influencing factors on elastic-plastic deformation of multi-layered surfaces under sliding contact

Stress distribution in the gradient multi-layered surface under a sliding contact was investigated using finite element method(FEM). The main structure parameters of layered surface discussed are total layer thickness,layer number and elastic modulus ratio of layer to the substrate. A model of multi-layered surface contact with rough slider was studied. The effect of the surface structure parameters on the elastic-plastic deformation was analyzed.     

Influence of groove type on welding-induced residual stress,deformation and width of sensitization region in a SUS304 steel butt welded joint

To join a medium or thick plate weldment with a full penetration, a groove is usually prepared in the space between two sections of metal. Because weld metal needs to be deposited within the groove to form the joint, it is expected that different groove type will require different heat input, which may consequently have influence on welding residual stress and deformation. Generally, different groove corresponds to different bead layout, so it can be foreseen that the groove type has a significant effect on temperature history, shape and size of heat affected zone, and region of sensitization in certain alloys such as austenitic stainless steel. The influences of groove type on residual stress, angular distortion and width of sensitization region in a SUS304 butt-welded joint were investigated by means of numerical simulation and experiment. Based on ABAQUS code, a computational approach with considering thermo-mechanical coupling behaviors, moving heat source, strain hardening and annealing effect was developed to simulate temperature profile, stress field and deformation in multi-pass joint. Welding temperature cycles, residual stress distributions and deformations in V, K and X groove joints were calculated through using the proposed computational procedure. Meanwhile, experiments were carried out to obtain residual stress distributions and angular distortions. Through comparing the numerical results and the measured data, the effectiveness and accuracy of the developed computational approach were verified. The simulation results show that groove type has a significant influence on welding residual stress distribution, angular distortion and width of sensitization region.     

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.     

Automatic generation algorithm of expected results for testing of component-based software system

ContextA component-based software (CBS) system is a typical example of a composite component, which is composed of two or more atomic components. In the test of a CBS system, it is necessary to automatically generate expected results because they are compared with the actual results.ObjectiveThis paper proposes an automatic generation algorithm of expected results for the testing of a CBS system.MethodThe algorithm analyzes Input/Output (I/O) relationships of a CBS system to identify inputs that influence its outputs. Then, the algorithm uses test cases of atomic components for each input and automatically generates expected results. To evaluate the proposed approach, we compare the proposed approach with the other I/O relationship based approach via two case studies which are the CBS systems for guide robot. The comparison shows the effectiveness of our approach.ResultsTo verify effectiveness of the proposed approach, we measure the cost of manual generation of expected results for each case study. The costs are from 0.001 to 0.015 in the first case study, and are from 0.590 to 0.998 in the second case study.ConclusionThis proposed approach reduces the time-consuming and error-prone task which manually generates expected results for the testing of a CBS system.