Predicting the settlement of geosynthetic-reinforced soil foundations using evolutionary artificial intelligence technique

In order to ensure safe and sustainable design of geosynthetic-reinforced soil foundation (GRSF), settlement prediction is a challenging task for practising civil/geotechnical engineers. In this paper, a new hybrid technique for predicting the settlement of GRSF has been proposed based on the combination of evolutionary algorithm, that is, grey-wolf optimisation (GWO) and artificial neural network (ANN), abbreviated as ANN-GWO model. For this purpose, the reliable pertinent data were generated through numerical simulations conducted on validated large-scale 3-D finite element model. The predictive power of the model was assessed using various well-established statistical indices, and also validated against several independent scientific studies as reported in literature. Furthermore, the sensitivity analysis was conducted to examine the robustness and reliability of the model. The results as obtained have indicated that the developed hybrid ANN-GWO model can estimate the maximum settlement of GRSF under service loads in a reliable and intelligent way, and thus, can be deployed as a predictive tool for the preliminary design of GRSF. Finally, the model was translated into functional relationship which can be executed without the need of any expensive computer-based program.     

The concept of smartness in cyber–physical systems and connection to urban environment

The next-generation systems are expected to be largely cyber–physical systems (CPSs) that autonomously control physical processes, through sensors and actuators typically in real-time feedback and cooperative control loops distributed among physical and cyber environments. The rapid technological advancements enhance the smartness of these CPSs, pushing their boundaries of performance and efficiency by embedding new information and communication technologies. However, to what extent CPSs should be smarter so that they do not compromise safety and security of safety critical systems? is an open research question. Towards this goal, the purpose of this study is to establish a grounded theory to analyse what makes these systems smart? and eventually, how to find a balance between smartness and safety risks? In this precinct, this article aims to develop a conceptual framework, define the dimensions and derive the characteristics that make CPSs smart. The proposed approach combines an automated informetric and systematic analysis of literature pertinent to the topic of smartness across anthropology, science, engineering and technology. The analysis of a case study building and the discussions presented herein support the connection between the existing understanding of CPSs and smartness offered by the building design approach in urban environment.     

Interval analysis of mode shapes to identify damage in beam structures

Various damage detection methods have been proposed by several researchers in the past few decades. Amongst them, the efficiency of mode shapes in detecting damage has been demonstrated by many researchers when further processed. In most cases, the processing involves expansion or reduction of the mode shape data. However, vital information that are damage-prints are often lost during processing of the mode shape data. In addition, most of these processes involve long and complex computation, thus, leading to inaccurate damage identification. In this study, a simple and fast damage identification technique is proposed to identify damage in beam structures. Interval analysis is applied to the mode shapes of a beam structure in the damaged and undamaged states. The interval situations of each of the beam's segment via mode shape are derived to obtain the upper and lower bounds and the derived bounds are compared. To establish a relationship for identify the damaged point, a possibility of damage existence is defined for each segment of the beam structure. The mode shape increment is defined as the increase in the mode shape value. Furthermore, a damage measure index that provide enhance damage information is obtained as the product of the possibility of damage existence and mode shape increment. A numerical model of a simply supported steel beam is applied to demonstrate this method by imposing damage through thickness reduction of elements in segments. In addition, a parametric analysis is carried out to evaluate noise effect by considering varying damage severities and different noise levels. The results showed that this method is simple and provides considerable accurate results.     

A rapid method to quantify casein in fluid milk by front-face fluorescence spectroscopy combined with chemometrics

Casein in fluid milk determines cheese yield and affects cheese quality. Traditional methods of measuring casein in milk involve lengthy sample preparations with labor-intensive nitrogen-based protein quantifications. The objective of this study was to quantify casein in fluid milk with different casein-to-crude-protein ratios using front-face fluorescence spectroscopy (FFFS) and chemometrics. We constructed calibration samples by mixing microfiltration and ultrafiltration retentate and permeate in different ratios to obtain different casein concentrations and casein-to-crude-protein ratios. We developed partial least squares regression and elastic net regression models for casein prediction in fluid milk using FFFS tryptophan emission spectra and reference casein contents. We used a set of 20 validation samples (including raw, skim, and ultrafiltered milk) to optimize and validate model performance. We externally tested another independent set of 20 test samples (including raw, skim, and ultrafiltered milk) by root mean square error of prediction (RMSEP), residual prediction deviation (RPD), and relative prediction error (RPE). The RMSEP for casein content quantification in raw, skim, and ultrafiltered milk ranged from 0.12 to 0.13%, and the RPD ranged from 3.2 to 3.4. The externally validated error of prediction was comparable to the existing rapid method and showed practical model performance for quality-control purposes. This FFFS-based method can be implemented as a routine quality-control tool in the dairy industry, providing rapid quantification of casein content in fluid milk intended for cheese manufacturing.     

煤巷高效快速掘进技术优化浅析

煤巷掘进效率低容易造成采掘接替紧张,以柠条塔煤矿S12002工作面胶运顺槽和辅运顺槽为工程背景,采用理论分析和现场工程对比试验相结合的方法,分析了制约巷道快速掘进各环节的因素,提出了优化控制对策。在减少顶板锚杆的支护数量,改良锚固方式并增大锚固长度和排距后,支护效率提高了20%,支护密度降低了30%,极大降低了顶板支护环节的时间;对掘进工艺进行优化后,将日单进水平从35 m左右提升到50~60 m左右,月单进水平从900 m提升到1500 m以上,创出了单日掘进75 m新水平,实现了高效快速掘进。实践表明,该方式现场成巷效果良好,可以满足煤巷高效快速掘进的需要。     

《电机与拖动基础》课程教学改革研究

针对《电机与拖动基础》课程特点和传统教学方法弊端,提出了一系列改革措施。通过引入计算机仿真加深学生对基本概念和基本原理的认知；应用对比教学法有利于学生掌握各知识点的共性和差异；采用问题教学法使学生带着问题去学习,提高学习的针对性；通过规范实验流程、增加设计性和综合性实验,培养学生基本实验设计能力,提高学生理论实践结合能力和创新能力；采用多种考核方式,客观反映学生学习效果,督促学生重视实验过程。     

BRISOL钠同位素放射性核束的产生

北京放射性核束装置在线同位素分离器（BRISOL）采用100 MeV、200 μA回旋加速器提供的质子束打靶产生中、短寿命放射性核束，在线分析后供物理用户使用，其质量分辨率好于20 000。为开展²⁰Na核的奇异衰变特性研究，研制了氧化镁靶，并采用100 MeV质子束轰击氧化镁靶在线产生了^20～26Na⁺的钠同位素放射性核束。当质子束流强为8 μA时，²⁰Na⁺离子束的最大产额为2×10⁵ s^-1，²¹Na⁺离子束的最大产额为4×10⁸ s^-1。完成了北京放射性核束装置首个放射性核束物理实验，累计供束近200 h。     

“Lattice Strain Matching”-Enabled Nanocomposite Design to Harness the Exceptional Mechanical Properties of Nanomaterials in Bulk Forms

Nanosized materials are known to have the ability to withstand ultralarge elastic strains (4–10%) and to have ultrahigh strengths approaching their theoretical limits. However, it is a long-standing challenge to harnessing their exceptional intrinsic mechanical properties in bulk forms. This is commonly known as “the valley of death” in nanocomposite design. In 2013, a breakthrough was made to overcome this challenge by using a martensitic phase transforming matrix to create a composite in which ultralarge elastic lattice strains up to 6.7% are achieved in Nb nanoribbons embedded in it. This breakthrough was enabled by a novel concept of phase transformation assisted lattice strain matching between the uniform ultralarge elastic strains (4–10%) of nanomaterials and the uniform crystallographic lattice distortion strains (4–10%) of the martensitic phase transformation of the matrix. This novel concept has opened new opportunities for developing materials of exceptional mechanical properties or enhanced functional properties that are not possible before. The work in progress in this research over the past six years is reported.     

轿车后轿横梁焊缝纵向开裂的原因分析

针对某轿车后梁焊缝纵向开裂情况，采用宏观观察、金相检验和扫描电镜分析等方法，对材质为CP-800高强钢，厚度为2 mm焊缝开裂原因进行了分析。扫描电镜发现裂纹起源于Cr的氧化物，以及其与Al、Si、Ca和Mn的复合氧化物处，且有疲劳辉纹形成，说明开裂是疲劳裂纹扩展到临界尺寸时在外载荷作用下发生快速扩展造成的。     

Zr-Ti合金相稳定性与弹性性质的第一性原理研究

利用特殊准随机结构(specialquasi-randomstructure,SQS)超晶胞模型及第一性原理计算研究了Zr_(1-x)Tix合金中Ti含量及相结构(hcp与bcc结构,α相与β相)对合金相稳定性及弹性性质的影响。研究表明:从弹性性质上看,Ti含量增加会使Zr-Ti合金的结构更加稳定,Zr-Ti合金α相的结构稳定性普遍高于β相;Zr-Ti合金普遍具有延展性,Zr-Ti合金的α相具有更高的硬度并且其硬度和韧性都与Ti元素浓度成正比,Zr-Ti合金的β相具有更高的韧性;从电子结构上看,Ti不会显著改变hcp结构和bcc结构Zr-Ti合金系统的态密度(DOS),Zr-Ti合金系统的DOS分布中的费米能级与纯Zr系统的相似,Ti含量对Zr-Ti合金的相稳定性影响不大。