Simulation analysis and experimental verification of coal suction characteristics of the new railway tunnel fallen coal dust collection device北大核心CSCD

Due to air turbulence, large areas of coal will fall when the special coal-transportation trains pass the tunnel exits and entrances. Aiming at the problems of low efficiency and high cost of manual cleaning for long distance coal cleaning in the tunnel, a new railway tunnel fallen coal dust collection device which was composed of a main conveying coal feeding pipe and multiple branch pipes of coal suction was designed. It was used to clean the small particles and lightweight railway tunnel fallen coal. Firstly, the gas-solid two-phase flow model based on the Euler-Lagrange approach for the design of the main conveying coal feeding pipe was established in the coal conveying pipelines. Secondly, the effect of the coal particles' incident angle and multiple branch pipe spacing on the main coal conveying pipe flow field, which was based on Fluent finite element simulation software, was studied. What was more, the optimal angle of incidence and the optimal value of the number of branch coal suction pipe, which was installed on the main conveying pipe, were analyzed. Finally, the finite element simulation was verified by field test. Simulation and experimental results showed that it was more conducive to the railway tunnel fallen coal transportation when coal particles' incident angle was less than 45° and the branch pipe spacing was in the vicinity of 750 mm. For that when incident angle was less than 45°, the main conveying coal pipe pressure-drop became weaker and particle flow could obtain large horizontal transport velocity. And when the branch pipe spacing was in the vicinity of 750 mm, the horizontal transport velocity had a smaller fluctuation range and the transportation of coal was larger than that of the other groups. The research results are of great significance to improve the structure of the main conveying coal pipe, increase the efficiency of tunnel coal conveying and optimize the railway tunnel coal dust collection device.     

Using dynamic demand information and zoning for the storage of non-uniform density stock keeping units

The warehouse order-picking operation is one of the most labour-intense activities that has an important impact on responsiveness and efficiency of the supply chain. An understanding of the impact of the simultaneous effects of customer demand patterns and order clustering, considering physical restrictions in product storage, is critical for improving operational performance. Storage restrictions may include storing non-uniform density stock keeping units (SKUs) whose dimensions and weight constrain the order-picking operation given that a priority must be followed. In this paper, a heuristic optimisation based on a quadratic integer programming is employed to generate a layout solution that considers customer demand patterns and order clustering. A simulation model is used to investigate the effects of creating and implementing these layout solutions in conjunction with density zones to account for restrictions in non-uniform density SKUs. Results from combining layout optimisation heuristics and density zoning indicate statistical significant differences between assignments that ignore the aforementioned factors and those that recognise it.     

高能超声分散纳米晶须的数值和物理模拟

为研究高能超声处理制备纳米复合材料过程中纳米增强相在熔体中的分散过程,采用甘油为介质分别进行了数值模拟以及物理模拟。数值模拟结果表明,当超声作用于甘油中时,甘油中会形成中心-底面-壁面-中心的环形流动,变幅杆探头端面边缘附近甘油流体存在最大的流动速度,且随着超声功率的增大,流体运动速度增大。物理模拟实验结果显示,高能超声作用下甘油的实际运动行为与数值模拟结果相符合,存在环形流动;此外,高能超声作用下甘油中存在明显的空化效应;纳米晶须在超声作用下于甘油中分散良好,且随着超声功率的增大,达到充分分散所需时间变短。     

基于AEM法的爆破拆除倒塌过程的数值模拟

利用应用单元法(AEM法),以含填充墙的某多层框架结构定向爆破拆除为例,进行倒塌过程的数值模拟。结果表明:在框架结构爆破切口形成后,结构由于重力作用逐渐沿横向偏转,并在横向最外侧的一排柱上形成活动铰,产生翻转倒塌,模拟结果与实际倒塌结果基本相符。在倒塌的过程中,结构爆破切口的横向很快进入大变形倒塌,同时引起横向隔墙的平面失去稳定而倒塌。落地的倒塌碎块,在纵向产生150kN左右的峰值冲击力,在横向产生30~50kN的峰值冲击力。基于仿真结果,可以定量设置防护措施,避免安全隐患。     

Topological derivative-based technique for imaging thin inhomogeneities with few incident directions

Many non-iterative imaging algorithms require a large number of incident directions. Topological derivative-based imaging techniques can alleviate this problem, but lacks a theoretical background and a definite means of selecting the optimal incident directions. In this paper, we rigorously analyse the mathematical structure of a topological derivative imaging function, confirm why a small number of incident directions is sufficient, and explore the optimal configuration of these directions. To this end, we represent the topological derivative-based imaging function as an infinite series of Bessel functions of integer order of the first kind. Our analysis is supported by the results of numerical simulations.     

Reliability analysis on systems with self-healing and self-repairing under different environments and shock models

Inspired by the process of self-healing of biological damage, high technology materials with self-healing and self-repairing mechanisms have been developed for high reliability and long lifetime. Therefore, the reliability modeling on intelligent systems with healing performance has become a research hotspot. Based on the diversity of healing mechanisms, this paper proposes a two-phase reliability model method on self-healing and self-repairing systems. Impacts of environments, shock loads, self-healing, and self-repairing mechanisms are taken into account in this novel model. Besides, system lifetime and some reliability indexes under two shock models are derived, respectively. Moreover, Monte Carlo simulations are conducted to verify the accuracy of reliability under two models. Finally, an engineering case of metallized film capacitor is provided to illustrate the effectiveness and applicability of the proposed models by comparing numerical results and simulation results.     

电力有源滤波器控制器的研究与仿真分析

建立了包括有源电力滤波器（ＡＰＦ）在内的公共连接点（ＰＣＣ）的数学模型;针对实际控制器计算过程中的时间延迟,提出对负载电流值进行预测的两种算法,对逆变器的开关元件提出一种新型脉宽调制（ＰＷＭ）控制方案,并采用电力电子仿真软件包进行了仿真验证。     

ARPO-2: An expert system for legal advice on the breach of building contracts

Although Berman and Hafner [Berman 1989, pp. 928–938] presented the possibility to adapt the model of reasoning of development of an expert system for medical diagnosis to the reasoning of a judge when he/she sentences criminals does not resemble the reasoning found in the decisions of physicians, mathematicians or statisticians.When a lawyer reasons, he/she not only looks for the solution of a case; he/she simultaneously looks for the bases on which his/her reasoning can rest [Galindo 1992, pp. 363–367]. That is to say, he/she not only needs to find the solution but moreover he/she has to find the references (laws, jurisprudence and bibliography) that allow him/her to argue the solution.In many cases, computer solutions to these reasoning processes have been made in a separated way: the solution to the cases using expert systems, and the search of documentation using information retrieval systems.This paper presents the ARPO-2 prototype, a solution integrating the two aspects of legal reasoning: an expert system which is able to simultaneously find the solution to a problem and to give the necessary references so that the lawyer argues the solution. The subject on which the prototype solves problems is the breach of building contracts.In this paper, we describe the process of development of an expert system for solving, justification and documentation of breach of contracts, giving details on the way how the objects that intervene in the case were defined as well as on the reasoning followed.This paper was funded in part by DGICYT, Spanish Civil Law Computerization Project: PB870-632.     

LiveROMS: A virtual environment for ocean numerical simulations

LiveROMS is a bootable DVD that contains an Linux-based computer operating system which has a complete, functioning version of the ROMS ocean circulation model and an Octave version of ROMSTOOLS. It allows students and scientists to experiment with this ocean numerical model, with just a basic knowledge of Linux.     

ADAPTIVE RANKS CLONE AND k‐NEAREST NEIGHBOR LIST–BASED IMMUNE MULTI‐OBJECTIVE OPTIMIZATION

Artificial immune systems (AIS) are computational systems inspired by the principles and processes of the vertebrate immune system. The AIS‐based algorithms typically exploit the immune system's characteristics of learning and adaptability to solve some complicated problems. Although, several AIS‐based algorithms have proposed to solve multi‐objective optimization problems (MOPs), little focus have been placed on the issues that adaptively use the online discovered solutions. Here, we proposed an adaptive selection scheme and an adaptive ranks clone scheme by the online discovered solutions in different ranks. Accordingly, the dynamic information of the online antibody population is efficiently exploited, which is beneficial to the search process. Furthermore, it has been widely approved that one‐off deletion could not obtain excellent diversity in the final population; therefore, a k‐nearest neighbor list (where k is the number of objectives) is established and maintained to eliminate the solutions in the archive population. The k‐nearest neighbors of each antibody are founded and stored in a list memory. Once an antibody with minimal product of k‐nearest neighbors is deleted, the neighborhood relations of the remaining antibodies in the list memory are updated. Finally, the proposed algorithm is tested on 10 well‐known and frequently used multi‐objective problems and two many‐objective problems with 4, 6, and 8 objectives. Compared with five other state‐of‐the‐art multi‐objective algorithms, namely NSGA‐II, SPEA2, IBEA, HYPE, and NNIA, our method achieves comparable results in terms of convergence, diversity metrics, and computational time.