A novel hybridized metaheuristic technique in enhancing the diagnosis of cross-sectional dent damaged offshore platform members

Offshore jacket platforms are widely used for oil and gas extraction as well as transportation in shallow to moderate water depth. Tubular cross-sectional elements are used to construct offshore platforms. Tubular cross sections impart higher resistance against hydrodynamic forces and have high torsional rigidity. During operation, the members can be partially or fully damaged due to lateral impacts. The lateral impacts can be due to ship collisions or through the impact of falling objects. The impact forces can weaken some members that influence the overall performance of the platform. This demonstrates an urgent need to develop a framework that can accurately forecast dent depth as well as dent angle of the affected members. This study investigates the use of an adaptive metaheuristics algorithm to provide automatic detection of denting damage in an offshore structure. The damage information includes dent depth and the dent angle. A model is developed in combination with the percentage of the dent depth of the damaged member and is used to assess the performance of the method. It demonstrates that small changes in stiffness of individual damaged bracing members are detectable from measurements of global structural motion.     

以 提高实践能力为目标的数据结构课程教学改革探索

This paper analyzes the problems existing in the teaching of data structure course, and puts forward the reform from the as- pects of strengthening basic programming, visualized explanation of abstract theory, combination of C++, Java programming, ratio- nal use of online platform, and stratification of exercises, aiming at improving students' practical ability, learning interest and self- confidence.     

A Practical Method for Animating Anisotropic Elastoplastic Materials

This paper introduces a simple method for simulating highly anisotropic elastoplastic material behaviors like the dissolution of fibrous phenomena (splintering wood, shredding bales of hay) and materials composed of large numbers of irregularly-shaped bodies (piles of twigs, pencils, or cards). We introduce a simple transformation of the anisotropic problem into an equivalent isotropic one, and we solve this new “fictitious” isotropic problem using an existing simulator based on the material point method. Our approach results in minimal changes to existing simulators, and it allows us to re-use popular isotropic plasticity models like the Drucker-Prager yield criterion instead of inventing new anisotropic plasticity models for every phenomenon we wish to simulate.     

Simulation of media behaviour in vibration assisted abrasive flow machining

Abrasive flow machining (AFM) is an abrasive-based precision finishing process used for achieving surface finish in micro and nano-level. The AFM polishes surfaces by extruding a visco-elastic media in contact with the workpiece. The media, also called a ‘flexible tool’, plays a key role in the performance of the process. Ultrasonic assisted abrasive flow machining (UAAFM) is a new variant of the AFM process in which the workpiece is subjected to mechanical vibration orthogonal to the media flow direction. In this process a high frequency, in the range of about 5–20 kHz, is given to the workpiece with the help of a piezo actuator and a specially designed fixture. The present work highlights on the possible behaviour of the tool (media) during UAAFM and its effect on the machining process through a computation based approach. Commercially available simulation tool was used to study the effect of the media in response to different set of machining conditions. The responses were evaluated in terms of changes in the fluid pressure, velocity profile of the fluid, temperature distribution in the working fluid and the possible wall shear on the work surface. A three-dimensional model was constructed for simulating the UAAFM process. The simulation shows that the abrasive particles tend to hit the target surface at an angle ‘θ’ which significantly affects the basic mechanisms involved and enhances the effectiveness of the process. The computed wall shear explains that the process will have higher finishing rate and hence the performance. The enhanced interaction of abrasive media in UAAFM while compared to simple AFM could be explained by the resultant pressure–velocity phenomena. Results show that while changes in the amplitude of applied vibration (10 μm and 50 μm) significantly affect the wall shear, the media velocity and pressure profiles are only marginally sensitive to this parameter. The simulation results also confirm that the rise in temperature during the process will not affect the media stability. Results have been discussed vis-a-vis the basic mechanism of the process through suitable illustrations.     

基于matlab的电磁场仿真与分析

电磁场问题往往较为抽象，并且计算也相对比较复杂。为此，借助计算机软件对复杂问题进行求解的重要性也得到凸显。本文通过两个例子，着重介绍了matlab在电磁场仿真与数值分析中的应用。结果表明这一方法具有计算效率高，能使抽象的场的问题具体化的优点。     

共网数字集群系统应用问题的研究

现今国内的数字集群网络发展存在局限性、差异性，还远没有达到“网”状分布的程度，因此，共网数字集群发展空间巨大、前景广阔。通过列举共网数字集群系统在龙嘉国际机场和长春雷锋车队的成功应用案例，探讨了我国共网数字集群系统应用的可行性和必要性。     

Using a Discrete-Event System Specifications (DEVS) for designing a Modelica compiler

We introduce a new architecture for the design of a tool for modeling and simulation of continuous and hybrid systems. The environment includes a compiler based on Modelica, a modular and a causal standard specification language for physical systems modeling (the tool supports models composed using certain component classes defined in the Modelica Standard Library, and the instantiation, parameterization and connection of these MSL components are described using a subset of Modelica). Models are defined in Modelica and are translated into DEVS models. DEVS theory (originally defined for modeling and simulation of discrete event systems) was extended in order to permit defining these of models. The different steps in the compiling process are show, including how to model these dynamic systems under the discrete event abstraction, including examples of model simulation with their execution results.     

Lean production system design for fishing net manufacturing using lean principles and simulation optimization

Value stream mapping (VSM) is a useful tool for describing the manufacturing state, especially for distinguishing between those activities that add value and those that do not. It can help in eliminating non-value activities and reducing the work in process (WIP) and thereby increase the service level. This research follows the guidelines for designing future state VSM. These guidelines consist of five factors which can be changed simply, without any investment. These five factors are (1) production unit; (2) pacemaker process; (3) number of batches; (4) production sequence; and (5) supermarket size. The five factors are applied to a fishing net manufacturing system. Using experimental design and a simulation optimizing tool, the five factors are optimized. The results show that the future state maps can increase service level and reduce WIP by at least 29.41% and 33.92% respectively. For the present study, the lean principles are innovatively adopted in solving a fishing net manufacturing system which is not a well-addressed problem in literature. In light of the promising empirical results, the proposed methodologies are also readily applicable to similar industries.     

A household dishwasher heated by a heat pump system using an energy storage unit with water as the heat source

Electricity usage by a household dishwasher can be reduced by using a heat pump system to heat the dishwasher cabinet, dishware and washing water. The evaporator obtains the energy from an energy storage unit which consists of a container filled with water which freezes to ice. The majority of the heat transfer from the energy storage to the evaporator occurs when ice is created in the energy storage unit. A transient simulation model of a dishwasher with a heat pump system was developed and compared to an experimental setup with good agreement. A simulation study of the compressor cylinder volume and the compressor operating time was performed. The results showed a 24% reduction in total electricity use compared to a dishwasher cycle using a traditional electric element.     

Simulation optimization approach for hybrid flow shop scheduling problem in semiconductor back-end manufacturing

This study presents a simulation optimization approach for a hybrid flow shop scheduling problem in a real-world semiconductor back-end assembly facility. The complexity of the problem is determined based on demand and supply characteristics. Demand varies with orders characterized by different quantities, product types, and release times. Supply varies with the number of flexible manufacturing routes but is constrained in a multi-line/multi-stage production system that contains certain types and numbers of identical and unrelated parallel machines. An order is typically split into separate jobs for parallel processing and subsequently merged for completion to reduce flow time. Split jobs that apply the same qualified machine type per order are compiled for quality and traceability. The objective is to achieve the feasible minimal flow time by determining the optimal assignment of the production line and machine type at each stage for each order. A simulation optimization approach is adopted due to the complex and stochastic nature of the problem. The approach includes a simulation model for performance evaluation, an optimization strategy with application of a genetic algorithm, and an acceleration technique via an optimal computing budget allocation. Furthermore, scenario analyses of the different levels of demand, product mix, and lot sizing are performed to reveal the advantage of simulation. This study demonstrates the value of the simulation optimization approach for practical applications and provides directions for future research on the stochastic hybrid flow shop scheduling problem.