全散射法测量颗粒粒径分布技术的进展

本文介绍了国内外光学全散射法测粒技术的发展过程、存在的主要问题,提出一改进后的新方法:用多波长全散射法测量颗粒粒径分布。该方法不仅可消除全散射法测量结果有多值性的缺陷,而且可以直接获得颗粒的粒径分布,测试粒径范围也有所扩充(0.03～8μm)。文章还给出了用独立及非独立模式的两种算法,求解粒径分布的数值模拟结果以及对聚苯乙烯标准颗粒的实测结果。计算和实测的结果令人满意。     

光全散射测粒方法的实验研究

如何快速准确地测量微米及亚微米级颗粒的尺寸分布是一个有待解决的问题。作者在对应用光全散射理论测量颗粒尺寸分布进行理论分析和数值模拟的基础上,行了实验研究。本文给出了作者应用该方法测量聚苯乙烯标准颗粒和二氧化钛的实验结果。结果表明,作者提出的用光全散射法测量颗粒尺寸分布的两种算法是正确的,从0.17～9.85μm共6种标准颗粒的测量结果均与其名义尺寸吻合得很好。实验结果还表明,测量时Ⅰ/Ⅰ_0值控制在0.4～0.9为宜。     

基于智能粒子群优化算法的人员疏散问题研究

针对建筑物内发生火灾时人员疏散的逃逸行为进行了研究,将智能粒子群优化算法应用在人员逃逸的过程中,提出了一种智能粒子群逃逸模型。将行人群比拟为粒子群,并将粒子赋予一定的维能力,此时的智能粒子将会具有类似行人的一些特征如行为特征和心理特征。智能粒子在受灾害模型与自身思维特征模型的影响下,确定其逃逸的速度包括速度的大小和方向,然后改变自己目前的位置。在建模的过程中,还考虑了智能粒子间的碰撞及建筑物内诱导信息的作用。最后通过应用智能粒子群优化算法对某一建筑物内发生火灾时人员逃逸行为的二维仿真实验来验证模型的有效性及算法的可行性。

Abstract：

The escape behavior of people’s evacuating in the fire disaster was researched.The Intelligent Particle Swarm Optimization （IPSO） was applied in the processing of escaping.A novel IPSO escape model was proposed.The pedestrians were assimilated as the particles.All particles were endowed with thoughts like human being.These intelligent particles will have some characteristic such as behavior and psychology characteristic at present.Their velocity included the direction and the magnitude under the influence of the disaster model and thinking characteristic model was determined.Then the particles positions were changed.The collision of particles and the effect of elicitation information in building were also considered.Most importantly,the simulated results demonstrate that method is feasible and efficient to simulate the escape behavior in fire disaster,especially to drilling.     

基于RBF和PSO的双喉道气动矢量喷管优化设计

本文探索了一种能多变量综合优化的方法,即对喷管进行参数化设计后,用均匀试验设计(UED)将试验样本均匀散布在设计区间内,求出各性能参数后,利用径向基神经网络(RBF)对试验样本进行拟合,再用粒子群算法(PSO)对训练好的神经网络进行寻优,找出了更好的双喉道气动矢量喷管设计参数组合。数值模拟结果显示,优化后的双喉道气动矢量喷管的矢量角有了明显提高。试验表明这种优化方法具有很好的优化能力,可以用来对喷管几何外形进行参数优化。      

Restoring particle phenomenology

No-go theorems are known in the literature to the effect that, in relativistic quantum field theory, particle localizability in the strict sense violates relativistic causality. In order to account for particle phenomenology without particle ontology, Halvorson and Clifton (2002) proposed an approximate localization scheme. In a recent paper, Arageorgis and Stergiou (2013) proved a no-go result that suggests that, even within such a scheme, there would arise act–outcome correlations over the entire spacetime, thereby violating relativistic causality. Here, we show that this conclusion is untenable. In particular, we argue that one can recover particle phenomenology without having to give up relativistic causality.     

Einstein׳s Equations for Spin 2 Mass 0 from Noether׳s Converse Hilbertian Assertion

An overlap between the general relativist and particle physicist views of Einstein gravity is uncovered. Noether׳s 1918 paper developed Hilbert׳s and Klein׳s reflections on the conservation laws. Energy-momentum is just a term proportional to the field equations and a ‘curl’ term with identically zero divergence. Noether proved a converse “Hilbertian assertion”: such “improper” conservation laws imply a generally covariant action.Later and independently, particle physicists derived the nonlinear Einstein equations assuming the absence of negative-energy degrees of freedom (“ghosts”) for stability, along with universal coupling: all energy-momentum including gravity׳s serves as a source for gravity. Those assumptions (all but) imply (for 0 graviton mass) that the energy-momentum is only a term proportional to the field equations and a symmetric “curl,” which implies the coalescence of the flat background geometry and the gravitational potential into an effective curved geometry. The flat metric, though useful in Rosenfeld׳s stress-energy definition, disappears from the field equations. Thus the particle physics derivation uses a reinvented Noetherian converse Hilbertian assertion in Rosenfeld-tinged form.The Rosenfeld stress-energy is identically the canonical stress-energy plus a Belinfante curl and terms proportional to the field equations, so the flat metric is only a convenient mathematical trick without ontological commitment. Neither generalized relativity of motion, nor the identity of gravity and inertia, nor substantive general covariance is assumed. The more compelling criterion of lacking ghosts yields substantive general covariance as an output. Hence the particle physics derivation, though logically impressive, is neither as novel nor as ontologically laden as it has seemed.     

Finite Element Simulation of the Polymeric Liquid Flow in Coat-hanger Die

A three - dimenslonal finite element model is developed to deal with the polymeric liquid flow in coat - hanger die. This model is used to predict the flow behavior of the 2％ CMC/watsr solution in the coat - hanger die with linearly taper manifolds and its validity is experimentally verified quantitatively and qualitatively by using Laser Doppler Velocimetry and Particle Image Velocimetry respectively.     

粒子运动轨迹法在喷雾干燥设备中的应用：Ⅰ设计方法

文中介绍了喷雾干燥设备设计的几种方法，并着重指出粒子运动轨迹法在喷雾干燥设备中的设计原理和方法。     

玻璃粉粒度分布对胶凝材料性能的影响

为了给玻璃粉水泥用玻璃粉的颗粒级配优化提供理论指导,研究了不同粒度分布的玻璃粉对胶凝材料的性能影响。首先将废玻璃破碎、球磨、干筛、湿筛和沉降,获得化学组分相同、粒度分布不同的超细废玻璃粉。分别测定不同粒度分布的废玻璃粉在复合胶凝材料中的强度,运用活性因子法分析玻璃粉对复合体系贡献度。试验结果表明:复合胶凝材料的强度随着废玻璃粉掺量的增加而减少;玻璃粉颗粒细化对复合体系的强度起着积极作用;玻璃粉水泥浆水化早期时,大多数情况下玻璃粉的活性因子为负,这表明玻璃粉对复合体系的早期强度不仅不能起到增强作用,反而对复合体系的早期强度起着负面影响。     

基于SPH方法与GPU并行计算的阶梯流数值模拟

为了更好地模拟分析地下空间阶梯流动力学规律和提升数值计算效率,本文利用光滑粒子流体动力学方法(SPH)并借助GPU并行计算技术对地下空间阶梯流进行数值建模和计算。基于GPU并行化加速的SPH地下空间阶梯流模型的数值计算结果表明：该模型不仅计算获得较好的阶梯流流态,而且计算效率大幅度提高,比串行SPH模型和移动粒子半隐方法(MPS)模型快数百倍,这为研究大尺度城市街区洪水提供了一个比较有前景的研究途径。