Simulation of abrasive flow machining process for 2D and 3D mixture models

Improvement of surface finish and material removal has been quite a challenge in a finishing operation such as abrasive flow machining (AFM). Factors that affect the surface finish and material removal are media viscosity, extrusion pressure, piston velocity, and particle size in abrasive flow machining process. Performing experiments for all the parameters and accurately obtaining an optimized parameter in a short time are difficult to accomplish because the operation requires a precise finish. Computational fluid dynamics (CFD) simulation was employed to accurately determine optimum parameters. In the current work, a 2D model was designed, and the flow analysis, force calculation, and material removal prediction were performed and compared with the available experimental data. Another 3D model for a swaging die finishing using AFM was simulated at different viscosities of the media to study the effects on the controlling parameters. A CFD simulation was performed by using commercially available ANSYS FLUENT. Two phases were considered for the flow analysis, and multiphase mixture model was taken into account. The fluid was considered to be a Newtonian fluid and the flow laminar with no wall slip.     

Optimization of fused deposition modeling process parameters:a review of current research and future prospects

Fused deposition modeling(FDM) is one of the most popular additive manufacturing technologies for various engineering applications.FDM process has been introduced commercially in early 1990 s by Stratasys Inc.,USA.The quality of FDM processed parts mainly depends on careful selection of process variables.Thus,identification of the FDM process parameters that significantly affect the quality of FDM processed parts is important.In recent years,researchers have explored a number of ways to improve the mechanical properties and part quality using various experimental design techniques and concepts.This article aims to review the research carried out so far in determining and optimizing the process parameters of the FDM process.Several statistical designs of experiments and optimization techniques used for the determination of optimum process parameters have been examined.The trends for future FDM research in this area are described.     

层次聚类法在逆向工程中的应用研究

针对层次聚类法和逆向工程的点云采样问题,在深入分析层次聚类法特 征的基础上对其进行了分类定义,包括曲面变分、BSP 构建等关键技术,构建了算法实现的 流程图。应用该算法结合Geomagic Qualify 软件对某汽轮机厂的水轮机叶片进行了采样和逆 向建模研究,证明了层次聚类法在逆向工程方面应用的可行性。     

本体驱动的机械设备诊断维护知识建模

为了提高机械故障诊断的准确性与可靠性,引入了诊断维护知识的语义表示方法。通过对设备结构信息、维护经验知识以及诊断行为过程进行建模,建立了本体驱动的故障诊断推理模型。提出了设备运行状态与故障征兆之间的本体映射算法,并根据征兆空间到故障案例空间的映射关系进行实例匹配,完成了静态维护知识与动态诊断过程的统一,从而实现自动化、智能化的故障诊断与维护决策。将所建立的本体驱动的故障诊断推理模型应用于某转子故障诊断,得到了准确、实时的诊断结果。     

Interactive design computation—a case study on quantum design paradigm

The ever-increasing complexity of design processes fosters novel design computation models to be employed in architectural research and design in order to facilitate accurate data processing and refined decision making. These computation models have enabled designers to work with complex geometry and numeric design constraints to explore a whole new design field that is impossible to explore without computation techniques. However, most current design computation models follow an automation-oriented paradigm that only deal with strictly defined problem solving and optimization, but fail in establishing an intuitive and interactive communication with designers. This lack of interaction leads to an unconscious rejection ofnon-parameterizable design factors, which, reduces design computation models to specific design problem solving tools instead of operating as active design partners. This paper presents a non-deterministic design computation modeling approach derived from a discussion on quantum design paradigm, which employs real-time user interaction as the co-driver to evolve user+computation driven informed design outputs. A case study of such a design computation model; QPC Toolset, developed and applied in a QuantumPointCloud workshop, will be illustrated in this paper. Expanded discussions on fabrication optimization and constructiontechniques from the QPC workshop will be addressed to conclude a comprehensive report.     

Multi-objective optimization of process parameters in Electro-Discharge Diamond Face Grinding based on ANN-NSGA-II hybrid technique

The effective study of hybrid machining processes (HMPs), in terms of modeling and optimization has always been a challenge to the researchers. The combined approach of Artificial Neural Network (ANN) and Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) has attracted attention of researchers for modeling and optimization of the complex machining processes. In this paper, a hybrid machining process of Electrical Discharge Face Grinding (EDFG) and Diamond Face Grinding (DFG) named as Electrical Discharge Diamond face Grinding (EDDFG) have been studied using a hybrid methodology of ANN-NSGA-II. In this study, ANN has been used for modeling while NSGA-II is used to optimize the control parameters of the EDDFG process. For observations of input-output relations, the experiments were conducted on a self developed face grinding setup, which is attached with the ram of EDM machine. During experimentation, the wheel speed, pulse current, pulse on-time and duty factor are taken as input parameters while output parameters are material removal rate (MRR) and average surface roughness (R_a). The results have shown that the developed ANN model is capable to predict the output responses within the acceptable limit for a given set of input parameters. It has also been found that hybrid approach of ANN-NSGA-II gives a set of optimal solutions for getting appropriate value of outputs with multiple objectives.     

A Higher Order Synergistic Damage Model for Prediction of Stiffness Changes due to Ply Cracking in Composite Laminates

A non-linear damage model is developed for the prediction of stiffness degradation in composite laminates due to transverse matrix cracking. The model follows the framework of a recently developed synergistic damage mechanics (SDM) approach which combines the strengths of micro-damage mechanics and continuum damage mechanics (CDM) through the so-called constraint parameters. A common limitation of the current CDM and SDM models has been the tendency to over-predict stiffness changes at high crack densities due to linearity inherent in their stiffness-damage relationships. The present paper extends this SDM approach by including higher order damage terms in the characterization of ply cracking damage inside the material. Following the SDM procedure, predictions are aided by suitable micromechanical computations of crack opening displacements. A nonlinear SDM model is developed and applied for multiple classes of composite laminate layups. Stiffness predictions for damaged laminates using the developed model are compared with the experimental data for cross-ply ([0m/90n]s), angle-ply ([±θm/90n]s), off-axis ([0/±θ4/01/2]s) and quasi-isotropic ([0/90/±45]s) laminates. A comparison with current linear damage models showcases the usefulness of the proposed nonlinear SDM approach.     

一种基于像素抽样建模的车辆目标提取方法

针对传统背景建模算法初始化时间长、存在Ghost区等缺点,本文根据样本一致性原理,提出一种基于像素抽样的背景建模方法。初始化阶段利用历史像素序列多次采样构建背景模型;模型更新采用改进的ViBe算法,同时更新历史像素模型和ViBe背景模型;前景检测时,利用样本一致性原理,将源像素同时与两个模型作比较,获得目标。对比实验表明,与Vibe原算法及传统目标提取算法相比,本文算法在有运动目标存在的情况下,初始化效率较高,并且有效抑制Ghost区,低速目标检测效果良好。     

基于RFID技术的跟踪与追溯系统研究

针对游客游览过程中游客游迹跟踪和追溯的需求,给出了游客游迹可追溯单元的语义描述,提出了使用事件处理机制处理游客身份标签数据并完成相应信息的转换,建立了基于射频识别语义事件的游迹跟踪模型和追溯方法,通过并发射频识别事件优先级处理策略机制,设计了游客游迹跟踪与追溯系统的功能架构、网络结构和查询。