A CAD-based design parameterization for shape optimization of elastic solids

In this paper a CAD-based design sensitivity analysis (DSA) and optimization method using Pro/ENGINEER for shape design of structural components is presented. The CAD-based design model is critically important for multidisciplinary shape design optimization. Only when each discipline can compute the design sensitivity coefficients of the CAD-based design model, can a true multidisciplinary what-if study, trade-off analysis, and design optimization be carried out. The proposed method will allow the design engineer to compute design sensitivity coefficients of structural performance measures such. as stress and displacement, evaluated using existing finite element analysis (FEA) tools, both h- and p-versions, with respect to design variables defined in the parameterized CAD model. The proposed method consists of (i) a CAD-based design parameterization technique that ties the structural DSA and optimization to a CAD tool; (ii) a design velocity field computation that defines material point movement due to design change in CAD geometry, satisfies linearity and regularity requirements, and supports both hand p-version FEA meshed using existing mesh generators; and (iii) a design optimization method that supports structural geometric and finite element model updates in Pro/ENGINEER during the optimization process.     

An Optimization-Based Scheme for Efficient Virtual Machine Placement

According to the important methodology of convex optimization theory, the energy-efficient and scalability problems of modern data centers are studied. Then a novel virtual machine (VM) placement scheme is proposed for solving these problems in large scale. Firstly, by referring the definition of VM placement fairness and utility function, the basic algorithm of VM placement which fulfills server constraints of physical machines is discussed. Then, we abstract the VM placement as an optimization problem which considers the inherent dependencies and traffic between VMs. By given the structural differences of recently proposed data center architectures, we further investigate a comparative analysis on the impact of the network architectures, server constraints and application dependencies on the potential performance gain of optimization-based VM placement. Comparing with the existing schemes, the performance improvements are illustrated from multiple perspectives, such as reducing the number of physical machines deployment, decreasing communication cost between VMs, improving energy-efficient and scalability of data centers.     

Integration of design and manufacturing for structural shape optimization

This paper presents an integrated design and manufacturing approach that supports shape optimization of structural components. The approach starts from a primitive concept stage, where boundary and loading conditions of the structural component are given to the designer. Topology optimization is conducted for an initial structural layout. The discretized structural layout is smoothed using parametric B-Spline surfaces. The B-Spline surfaces are imported into a CAD system to construct parametric solid models for shape optimization. Virtual manufacturing (VM) techniques are employed to ensure that the optimized shape can be manufactured at a reasonable cost. The solid freeform fabrication (SFF) system fabricates physical prototypes of the structure for design verification. Finally, a computer numerical control (CNC) machine is employed to fabricate functional parts as well as mold or die for mass production of the structural component. The main contribution of the paper is incorporating manufacturing into the design process, where manufacturing cost is considered for design. In addition, the overall design process starts from a primitive stage and ends with functional parts. A 3D tracked vehicle roadarm is employed throughout this paper to illustrate the overall design process and various techniques involved.     

Integration of topology and shape optimization for design of structural components

This paper presents an integrated approach that supports the topology optimization and CAD-based shape optimization. The main contribution of the paper is using the geometric reconstruction technique that is mathematically sound and error bounded for creating solid models of the topologically optimized structures with smooth geometric boundary. This geometric reconstruction method extends the integration to 3-D applications. In addition, commercial Computer-Aided Design (CAD), finite element analysis (FEA), optimization, and application software tools are incorporated to support the integrated optimization process. The integration is carried out by first converting the geometry of the topologically optimized structure into smooth and parametric B-spline curves and surfaces. The B-spline curves and surfaces are then imported into a parametric CAD environment to build solid models of the structure. The control point movements of the B-spline curves or surfaces are defined as design variables for shape optimization, in which CAD-based design velocity field computations, design sensitivity analysis (DSA), and nonlinear programming are performed. Both 2-D plane stress and 3-D solid examples are presented to demonstrate the proposed approach. Received January 27, 2000 Communicated by J. Sobieski     

A hierarchical design concept for shape optimization based on the interaction of CAGD and FEM

The numerical treatment of shape optimization problems requires sophisticated software tools such as Computer Aided Design (CAD), the Finite Element Method (FEM) and a suitable Mathematical Programming (MP) algorithm. Efficiency of the overall procedure is guaranteed if these tools interact optimally. The theoretical and numerical effort for sensitivity analysis reflect the complexity of this engineering problem.In this paper we outline a general modelling concept for shape optimization problems. Hierarchical design models within Computer Aided Geometrical Design (CAGD) and the interaction of geometry and FEM lead to an efficient overall optimization procedure. Our concept has been derived, implemented and tested for shell structures but it is seen to be generally applicable.After a short introduction containing the state of the art we give an overview of the numerical tools used and outline the interaction of CAGD and FEM within the overall optimization procedure.The paper is mainly devoted to the hierarchical design space based on a hierarchical geometrical modelling. The major part of computational effort is consumed by sensitivity analysis related to the number of design variables. Therefore, this number should be limited and only few powerful design variables corresponding to the special interests of the considered problem should be defined. This procedure may lead to a considerable limitation of the design space. Based on a hierarchy in the geometrical model different types of design variables are introduced: design variables with global, regional and local influence. The new method is based on successive activation of these types of design variables. This procedure leads to a considerable reduction of computational time for the sensitivity analysis without loss of geometrical flexibility.A new method of geometrical refinement and a successive adaptively driven expansion and reduction of the design space is described. It is based on the degree elevation or degree reduction of parametric curves and surfaces, respectively.A numerical example illustrates the new method and the efficiency of the overall optimization procedure.     

Bat inspired algorithm for discrete size optimization of steel frames

Bat inspired (BI) algorithm is a recently developed metaheuristic optimization technique inspired by echolocation behavior of bats. In this study, the BI algorithm is examined in the context of discrete size optimization of steel frames designed for minimum weight. In the optimum design problem frame members are selected from available set of steel sections for producing practically acceptable designs subject to strength and displacement provisions of American Institute of Steel Construction-Allowable Stress Design (AISC-ASD) specification. The performance of the technique is quantified using three real-size large steel frames under actual load and design considerations. The results obtained provide a sufficient evidence for successful performance of the BI algorithm in comparison to other metaheuristics employed in structural optimization.     

虚拟制造环境下VE型分配泵的研发

介绍了虚拟制造技术及其分类，探讨了以设计为中心的虚拟制造技术在汽车零部件研发中的实践．利用该技术，以柴油发动机VE型分配泵为研究对象，重点分析了传动部件易断裂问题，研究内容涉及产品全生命周期的各个阶段，包括虚拟样机设计、虚拟样机运动学动力学仿真、虚拟装配、有限元分析和零件虚拟加工仿真等，并对研究结果进行了实验验证．结合企业实际，给出了解决方案．     

A virtual punching method for shape optimization of openings on curved panels using CAD-based Boolean operations

This paper aims at developing new methodologies for shape optimization of openings on three-dimensional curved panels that are used widely in aeronautical and aerospace engineering. To circumvent the difficulties associated with the hole boundary shape parameterization, a virtual punching method that exploits Boolean operations of the CAD modeler is proposed for the definition of shape design variables. Compared with the parametric mapping method developed previously, the virtual punching method is shown to be an implicit boundary representation for this specific kind of structure. Instead, the parametric mapping method is based on the explicit boundary representation.A zero-order genetic algorithm (GA) is correspondingly implemented into the design procedure of the virtual punching method to execute the optimization process for two reasons. First, it makes it possible to avoid sensitivity analysis that is relatively difficult due to the implicit boundary representation formulation and the use of an unstructured mesh. Second, the computing cost of the GA is practically affordable in shape optimization because often only a small number of design variables are involved. Numerical tests are carried out for typical examples of the stress concentration minimization around openings on the curved panels.     

Structural optimization strategies to design green products

This paper addresses the need for a structured approach to environmental assessment and improvement. We propose a computer-aided methodology, named Eco-OptiCAD, based on the integration of Structural Optimization and Life Cycle Assessment (LCA) tools. Eco-OptiCAD supports the designer during product development, highlighting when and where the core of the environmental impact lies. Furthermore, it provides effective tools to address such impacts, improving the original product, while ensuring structural and functional requirements. It foresees the synergic use of (1) virtual prototyping tools, such as 3D CAD, Finite Element Analysis (FEA) and Structural optimization, (2) function modeling methodology and (3) Life Cycle Assessment (LCA) tools. The kernel of the methodology is constituted by a set of optimization strategies and a module, named Life Cycle Mapping (LCM). In particular, we have conceived ten optimization strategies converting environmental objectives and constraints into structural and geometrical parameters. They enable the designer to generate alternative green scenarios according to the triad shape–material–production. The LCM tool has been specifically developed to easily trace the growth of environmental impacts throughout the product's life cycle and allow the user to focus his effort on the most relevant aspects. Thanks to the integration of the structural optimizer with an LCA map, the designer becomes aware of the consequences that each change in the geometry, the material or the manufacturing process will produce on the environmental impact of the product throughout its life cycle. With a complete view of the product life cycle, the designer can improve a single phase, while retaining a global perspective; thus avoiding the possibility of gaining a local green improvement at the cost of a global increase in environmental impacts.     

Structural optimization with CADO method for a three-dimensional sheet-metal vehicle body

The aim of this study is to increase power/weight ratio of a steel-alloyed vehicle body without any structural weakness and to use an integrated engineering solution of “computer-aided design, engineering and optimization (CADO)”. In this optimization study, primarily the body's “computer-aided design (CAD)” parametric model has been prepared for some static analyses are essential for the design study. In the following step, some critical dimensions of the structure's parts have been defined as design parameters. The goal of the optimization study is a minimization of critical equivalent stress value is under the yield limit. In addition, a sensitivity study has been made on the body model with stress measures for an in-depth analysis. In various steps, Pro/Engineer CAD and Pro/MECHANICA computer-aided engineering (CAE) software has been used. Finally, the obtained results have been presented as both visually and in diagrams or tables. In other words, this study can be defined as a computer-aided design and optimization application of a sophisticated three-dimensional (3D) sheet-metal structural model. Consequently, for the solution of a sophisticated structural design problem, it has been seen that integrated CAD/CAE programs supported optimization techniques are vital much more proper to provide the time, error and cost reduction compared to classical design processes, can be given as contributes of this study to previous literature.     

Shape design sensitivity analysis and optimization of spatially rotating objects

Shape design sensitivity analysis (DSA) and optimization of spatially rotating objects is presented in this paper. Design sensitivity expressions are derived using a continuum DSA method for spatial objects rotating with angular velocity and angular acceleration, based on three definitions of the finite element mass matrix: consistent, lumped, and diagonalized. The design sensitivity expression derived using a diagonalized element mass matrix, which is consistent with the finite element analysis (FEA) method used in ANSYS, is implemented, although the method can work with other FEA codes, such as MSC/NASTRAN or ABAQUS. Since the continuum DSA method is used, sensitivity information can be computed outside the FEA codes by postprocessing finite element data. Rotating block and turbine blade examples are presented to validate the proposed DSA method. The turbine blade example is optimized using an integrated optimization module of the Design Sensitivity Analysis and Optimization (DSO) tool developed at the University of Iowa. The integrated module consists of ANSYS, MSC/NASTRAN, or ABAQUS for FEA; Design Optimization Tool (DOT) for nonlinear programming; and DSA and design model update programs developed in DSO.     

Adaptive Markov-based approach for dynamic virtual machine consolidation in cloud data centers with quality-of-service constraints

Dynamic virtual machine (VM) consolidation is one of the emerging technologies that has been considered for low-cost computing in cloud data centers. Quality-of-service (QoS) assurance is one of the challenging issues in the VM consolidation problem since it is directly affected by the increase of resource utilization due to the consolidations. In this paper, we take advantage of Markov chain models to propose a novel approach for VM consolidation that can be used to explicitly set a desired level of QoS constraint in a data center to ensure the QoS goals while improving system utilization. For this purpose, an energy-efficient and QoS-aware best fit decreasing algorithm for VM placement is proposed, which considers QoS objective when determining the location of a migrating VM. This algorithm employs an online transition matrix estimator method to deal with the nonstationary nature of real workload data. We also propose new policies for detecting overloaded and underloaded hosts. The performance of our proposed algorithms is evaluated through simulations. The results show that the proposed VM consolidation algorithms in this paper outperforms the benchmark algorithms in terms of energy consumption, service-level agreement violations, and other cost factors.     

基于优化的COW虚拟块设备的虚拟机按需部署机制

基于COW(Copy-on-Write)读写模式的虚拟块设备有利于实现大规模虚拟机环境下虚拟机的快速部署.文中为虚拟机管理器中的COW虚拟块设备设计了一种优化方法,能够提高COW磁盘的访问性能以及生成多个小尺寸的COW磁盘映像文件,以降低通过网络部署虚拟机的开销.基于优化的COW虚拟块设备,文中提出了虚拟机环境下的虚拟机按需部署机制及关键技术问题的解决方案.基于Linux平台和QEMU虚拟机,实现了基于优化COW虚拟块设备的虚拟机按需部署原型系统.实验表明,优化的COW虚拟块设备、基于COW磁盘有效工作集的优化部署以及COW磁盘回收等方法能够有效地支持虚拟机环境下低开销的、按需的虚拟机部署.     

Cuckoo search based resource optimization of datacenters

With advancements in virtualization technology, datacenters are often faced with the challenge of managing large numbers of virtual machine (VM) requests. Due to this large amount of VM requests, it has become practically impossible to search all possible VM placements in order to find a solution that best optimizes certain design objectives. As a result, managers of datacenters have resorted to the employment of heuristic optimization algorithms for VM placement. In this paper, we employ the cuckoo search optimization (CSO) algorithm to solve the VM placement problem of datacenters. Firstly, we use the CSO to optimize the datacenter for the minimization of the number of physical machines used for placement. Secondly, we implement a multiobjective CSO algorithm to simultaneously optimize the power consumption and resource wastage of the datacenter. Simulation results show that both CSO algorithms outperform the reordered grouping genetic algorithm (RGGA), the grouping genetic algorithm (GGA), improved least-loaded (ILL) and improved FFD (IFFD) methods of VM placement.     

A cost-effective power-aware approach for scheduling cloudlets in cloud computing environments

On a cloud platform, the user requests are managed through workload units called cloudlets which are assigned to virtual machines through cloudlet scheduling mechanism that mainly aims at minimizing the request processing time by producing effective small length schedules. The efficient request processing, however, requires excessive utilization of high-performance resources which incurs large overhead in terms of monetary cost and energy consumed by physical machines, thereby rendering cloud platforms inadequate for cost-effective green computing environments. This paper proposes a power-aware cloudlet scheduling (PACS) algorithm for mapping cloudlets to virtual machines. The algorithm aims at reducing the request processing time through small length schedules while minimizing energy consumption and the cost incurred. For allocation of virtual machines to cloudlets, the algorithm iteratively arranges virtual machines (VMs) in groups using weights computed through optimization and rescaling of parameters including VM resources, cost of utilization of resources, and power consumption. The experiments performed with a diverse set of configurations of cloudlets and virtual machines show that the PACS algorithm achieves a significant overall performance improvement factor ranging from 3.80 to 23.82 over other well-known cloudlet scheduling algorithms..

     

Design parameterization and tool integration for CAD-based mechanism optimization

This paper presents an open and integrated tool environment that enables engineers to effectively search, in a CAD solid model form, for a mechanism design with optimal kinematic and dynamic performance. In order to demonstrate the feasibility of such an environment, design parameterization that supports capturing design intents in product solid models must be available, and advanced modeling, simulation, and optimization technologies implemented in engineering software tools must be incorporated. In this paper, the design parameterization capabilities developed previously have been applied to support design optimization of engineering products, including a High Mobility Multi-purpose Wheeled Vehicle (HMMWV). In the proposed environment, Pro/ENGINEER and SolidWorks are supported for product model representation, DADS (Dynamic Analysis and Design System) is employed for dynamic simulation of mechanical systems including ground vehicles, and DOT (Design Optimization Tool) is included for a batch mode design optimization. In addition to the commercial tools, a number of software modules have been implemented to support the integration; e.g., interface modules for data retrieval, and model update modules for updating CAD and simulation models in accordance with design changes. Note that in this research, the overall finite difference method has been adopted to support design sensitivity analysis.     

云数据中心网络中的先应式碎片整理算法

在云数据中心网络内,虚拟机（Virtual machine, VM）被动态创建和下线,这就导致资源碎片不被后续VM请求所利用。为解决上述问题,以最小化使用服务器数 量为目标的服务器整合技术被提出。虽然这种方法可以在某一时间段内减少资源碎片,但却付出了较大的VM迁移代价。因此本文提出了一种基于预测的先应式碎片 整理算法,在减少无效VM迁移的同时,将资源碎片重新整合为可用的连续资源,从而最大化VM收益。文中对此问题进行了数学定义,随后设计了启发式方法获取近似最优解。仿真结果表明,所提算法能够获取最大收益,并能够大幅度降低VM迁移成本。