Multi-objective robust design optimization of a novel negative Poisson’s ratio bumper system

Negative Poisson’s ratio (NPR) structure has outstanding performances in lightweight and energy absorption, and it can be widely applied in automotive industries. By combining the front anti-collision beam, crash box and NPR structure, a novel NPR bumper system for improving the crashworthiness is first proposed in the work. The performances of the NPR bumper system are detailed studied by comparing to traditional bumper system and aluminum foam filled bumper system. To achieve the rapid design while considering perturbation induced by parameter uncertainties, a multi-objective robust design optimization method of the NPR bumper system is also proposed. The parametric model of the bumper system is constructed by combining the full parametric model of the traditional bumper system and the parametric model of the NPR structure. Optimal Latin hypercube sampling technique and dual response surface method are combined to construct the surrogate models. The multi-objective robust optimization results of the NPR bumper system are then obtained by applying the multi-objective particle swarm optimization algorithm and six sigma criteria. The results yielded from the optimizations indicate that the energy absorption capacity is improved significantly by the NPR bumper system and its performances are further optimized efficiently by the multi-objective robust design optimization method.     

Machine-learning-aided precise prediction of deletions with next-generation sequencing

When detecting deletions in complex human genomes,split-read approaches using short reads generated with next-generation sequencing still face the challenge that either false discovery rate is high,or sensitivity is low.To address the problem,an integrated strategy is proposed.It organically combines the fundamental theories of the three mainstream methods(read-pair approaches,split-read technologies and read-depth analysis) with modern machine learning algorithms,using the recipe of feature extraction as a bridge.Compared with the state-of-art split-read methods for deletion detection in both low and high sequence coverage,the machine-learning-aided strategy shows great ability in intelligently balancing sensitivity and false discovery rate and getting a both more sensitive and more precise call set at single-base-pair resolution.Thus,users do not need to rely on former experience to make an unnecessary trade-off beforehand and adjust parameters over and over again any more.It should be noted that modern machine learning models can play an important role in the field of structural variation prediction.     

基于Pushover方法的大跨度悬挑钢梁结构的弹塑性分析

本文以某实际工程为例,采用静力弹塑性分析方法,通过SAP2000进行Pushover分析,研究大跨度悬挑梁在地震作用下的结构抗震性能。通过在多遇和罕遇地震荷载作用下对结构的顶点位移、层间位移角以及塑性铰发展过程的研究,分析其抗震性能。同时研究不同悬挑长度对结构抗震性能的影响规律并提出相应的加固措施,可为今后类似结构的设计与抗震分析提供参考。     

Microstructure and properties of cement foams prepared by magnesium oxychloride cement

Microstructural features including pore size distribution, cell walls and phase compositions of magnesium oxychloride cement foams (MOCF) with various MgO powders and water mixture ratios were studied. Their influences on compressive strength, water absorption and resistance of MOCF were also discussed in detail. The experimental results indicated that moderate and slight excess MgO powders (MgO/MgCl₂ molar ratios from 5.1 to 7) were beneficial to the formation of excellent microstructure of MOCF, but increasing water contents (H₂O/MgO mass ratios from 0.9 to 1.29) might result in opposite conclusions. The microstructure of MOCF produced with moderate and slight excess MgO powders could enhance the compressive strength, while serious excess MgO powders addition (MgO/MgCl₂ molar ratios = 9) would destroy the cell wall structures, and therefore decrease the strength of the system. Although MOCF produced with excess MgO powders could decrease the water absorption, its softening coefficient was lower than that of the material produced with moderate MgO powders. This might be due to the instability of phase 5, the volume expansion and cracking of cell walls as immersed the sample into water.     

聚羧酸助磨剂合成及其性能

利用水泥粉磨过程中的机械力促使水解聚马来酸酐（HPMA）与聚乙二醇单甲醚（MPEG）进行酯化反应形成聚羧酸助磨剂。试验研究了HPMA、MPEG、HPMA与MPEG的混合物、HPMA与MPEG的反应合成物对水泥助磨效果以及对砂浆性能的影响。结果表明,HPMA与MPEG都有一定的助磨性,HPMA与MPEG的混合物和反应合成物具有更佳的助磨性能,且可以改善水泥砂浆的流动性能和显著提高水泥砂浆的早期强度。激光拉曼光谱测试表明HPMA与MPEG的混合物和反应合成物与水泥共同粉磨后吸附在水泥颗粒表面,具有相似的拉曼位移图谱。     

五种基流分割方法在长江螺山站的应用对比研究

基流是枯水期河川径流的主要来源,稳定可靠的基流分割方法对基流研究具有重要作用。基于螺山站1965-2012年逐日流量资料,采用基流指数法、HYSEP法(固定步长法、滑动步长法、局部最小值法)和数字滤波法3类(5种)基流分割方法进行基流分割。研究结果表明:5种方法所得年基流指数相差不大,但年内基流过程差别显著。BFI法和局部最小值法计算结果较为合理,对不同年份BFI值年际变化有较好的辨识度,是长江中游干流区较为适宜的基流分割手段。     

基于表面反应和扩散迁移控制的灰岩单裂隙渗流—溶解模型及其数值模拟

针对碳酸盐类可溶岩地区水电站坝址流场、化学场以及固相介质属性等随时间发生改变,从而对工程安全运行造成不利影响等问题,研究了灰岩地区地下水运移过程中各物理场间的相互作用,分析了影响灰岩溶解速率的两个因素,即表面反应控制和扩散迁移控制。在此基础上,建立了单裂隙中的渗流—溶解耦合模型,并进行数值求解。模拟结果表明,在垂直裂隙延伸方向,其溶蚀锋面为非齐整平面,而是呈似“虫洞”状非均一变化,而沿裂隙延伸方向即自上游侧向下游方向溶蚀程度逐渐减轻;而通过裂隙的流量呈现随时间逐渐增大的趋势,但变幅不大;根据流量求得的等效水力隙宽,其增幅和增长速率均小于实际平均隙宽;同时,化学场中Ca2+浓度的分布与裂隙开度变化具有相似性,不同时刻下上游侧反应速率R均大于下游侧。就反应机制而言,在初期均受表面反应控制,而随反应进行,位于上游补给区部位转为受扩散迁移控制,但在下游位置仍受表面反应控制。     

考虑爆裂影响的轴向约束高强混凝土柱耐火性能研究

应用有限元软件ABAQUS,基于一次爆裂模式,建立了轴向约束高强混凝土（HSC）柱的抗火分析模型.采用试验数据验证了模型的合理性.采用验证后的模型,分析了不同轴向约束刚度比下高强混凝土柱轴力及位移变化的规律,重点考虑了爆裂深度、爆裂长度、爆裂开始时间等爆裂参数对高强混凝土柱轴向位移、截面温度场和耐火极限的影响规律.研究表明：相同爆裂时间前提下,HSC柱轴向位移随爆裂深度、爆裂长度的增大而增大,耐火极限随之减小.爆裂深度、爆裂长度相同前提下,爆裂开始时间对HSC柱的耐火性能影响很小.当荷载比不变时,轴向约束刚度比对HSC柱膨胀阶段的最大轴向位移影响甚小,但是在越过初始平衡位置的收缩阶段对轴向位移影响很大.轴向约束刚度比对轴向约束HSC柱的耐火极限影响不大.     

微波加热法合成蜂窝状堇青石载体Al2O3涂层

采用微波加热法在堇青石蜂窝陶瓷基体表面涂覆多孔Al2O3涂层,研究了制备条件对堇青石蜂窝陶瓷表面Al2O3涂层中Al2O3的质量分数的影响。通过BET、SEM对涂层结构及形貌进行了表征,结果表明,采用微波加热法制备的Al2O3涂层均匀、稳定,具有较大的比表面积、孔容和较高的Al2O3质量分数。     

Valence-induced effects on the electrical properties of NiMn2O4 ceramics with different Ni sources

Spinel-structured NiMn₂O₄ ceramics, with different valence Ni sources, were originally prepared using Ni₂O₃ and NiO as raw materials, and the effects of different valence Ni sources on their electrical properties were first investigated. XRD patterns show that both Ni₂O₃-based and NiO-based NiMn₂O₄ ceramics are single cubic spinel structures. SEM/EDS images indicate that the NiMn₂O₄ ceramics exhibited high density at the experiment-determined sintering temperatures. XPS results and Raman drifts prove that the Ni valence-induced changes in Mn ions at B sites played a significant role in the electrical properties and thermal stability of NiMn₂O₄ ceramics. Compared with NiO-based NiMn₂O₄, the resistivity at 25°C (ρ_25°C) of Ni₂O₃-based NiMn₂O₄ increased dramatically from 3109 to 106958 Ω cm, the thermal constant (B_25/50) increased from 3264 to 4473 K, and the resistance shifts after annealing for 1000 h at 150°C decreased from 0.80% to 0.74%. The investigation of the relationship between the material properties and valence of Ni sources has provided a new and effective way for designing the spinel-structured negative temperature coefficient (NTC) materials by modulating the valence of ions at A sites in the raw materials.