Optimization of Stirling Engine Performance Based on Multipoint Approximation Technique

The ideal Stirling working cycle has the maximum obtainable efficiency defined by Carnot efficiency, and highly efficient Stirling engines can therefore be built, if designed properly. To analyse the power output and the efficiency of a Stirling engine, numerical simulation programs (NSP) have been developed, which solve the thermodynamic equations. In order to find optimum values of design variables, numerical optimization techniques can be used (Bartczak and Carlsen, 1991). To describe the engine realistically, it is necessary to consider several tens of design variables. As even a single call for NSP requires considerable computing time, it would be too time consuming to use conventional optimization techniques, which require a very large number of calls for NSP. Furthermore, objective and constraint functions of the optimization problem present some level of noise, i.e. can only be estimated with a finite accuracy. To cope with these problems, the multipoint explicit approximation technique is used.

Derivation of Multiple Assembly Sequences From Exploded Views

The original exploded view method of assembly planning (Mohammad and Kroll, 1993b) attempts to automatically generate the “simplest” assembly plan for a product. Criteria for optimal assembly sequences, however, are sometimes unclear and dependent on specific circumstances. It may therefore be advantageous to present the designer with more than one solution to the assembly planning problem, or allow him or her to select the appropriate criteria. This paper introduces an extension to the original method, where all possible assembly sequences are generated. This completely automatic capability is demonstrated by manually applying the method to a simple example and then comparing the results to those generated by the algorithmic procedure of the C. S. Draper Lab.

A Simulated Annealing-Based Approach to Three Dimensional Component Packing

This paper introduces a computational approach to three dimensional component layout that employs simulated annealing to generate optimal solutions. Simulated annealing has been used extensively for two dimensional layout of VLSI circuits; this research extends techniques developed for two dimensional layout optimization to three dimensional problems which are more representative of mechanical engineering applications. In many of these applications, miniaturization trends increase the need to achieve higher packing density and fit components into smaller containers. This research addresses the three dimensional packing problem, which is a subset of the general component layout problem, as a framework in which to solve general layout problems.

Composite Laminate Stiffnesses and Their Sensitivities

The great number of possible stacking orders to form laminates suggests to apply optimization, more frequently than usual, in the design of structures made of composite materials. One of the columns upon which optimization of structures is built is the mathematical search procedure for locating a minimum (or maximum) of a constrained function. Efficient algorithms will require the evaluation of derivatives of the object function as well as of the constraints. In that context the sensitivities of laminate stiffness matrices may be required. In order to meet such a requirement the derivatives with respect to both ply thicknesses and ply angles, of laminate stiffnesses, including transverse shear stiffness, will be presented in this report.

Variable-Topology Shape Optimization With a Control on Perimeter

This paper describes a new method for variable-topology shape optimization. The method addresses certain problems that arise in relaxed formulations (i.e., homogenization design methods). For example, a complete relaxation generates optimal designs containing material with perforated microstructures that may be difficult or expensive to manufacture. Formulations that penalize perforated material, either explicitly or through a partial relaxation, can generate manufacturable designs. However, the same illposedness that motivates relaxed formulations reappears as the penalty against perforated material is strengthened. The practical consequence is that numerical implementations of the penalized formulations fail to converge with grid refinement. The new approach uses a control on the design perimeter to effectively exclude chattering designs (which have an infinite perimeter) from the feasible solution space. This achieves a well-posed shape design problem without the introduction of microstructure. Numerical examples demonstrate that manufacturable designs can be obtained in a single, automatic operation. Grid refinement improves geometric resolution without altering the design topology. The new method also provides a means to control the number and the length scale of holes in the optimal design.

Application of Topological Optimization Techniques to Structural Crashworthiness

The topological optimization of components to maximize crash energy absorption for a given volume is considered. The crash analysis is performed using a DYNA3D finite element analysis. The original solid elements are replaced by ones with holes, the hole size being characterized by a so-called density (measure of the reduced volume). A homogenization method is used to find elastic moduli as a function of this density. Simpler approximations were developed to find plastic moduli and yield stress as functions of density. Optimality criteria were derived from an optimization statement using densities as the design variables. A resizing algorithm was constructed so that the optimality criteria are approximately satisfied. A novel feature is the introduction of an objective function based on strain energies weighted at specified times. Each different choice of weighting factors leads to a different structure, allowing a range of design possibilities to be explored. The method was applied to an automotive body rear rail. The original design and a new design of equal volume with holes were compared for energy absorption.

Recycling Oriented Fasteners: A Critical Evaluation of VDI 2243’s Selection Table

A growing concern about the environment, and especially about waste and landfill, has spurred research into the design of more environmentally benign products. A dramatic reduction in environmental impact can be made by recycling. A critical issue in recycling is the separation of joints in the disassembly process. In product recycling (also referred to as reuse) non-destructive disassembly is desired, whereas in material recycling destructive disassembly is allowed (e.g., shredding). This has an impact on the selection of fasteners. In this paper, we provide an overview of the issues involved and specifically we evaluate the selection of fasteners in the context of product recycling, material recycling, and technical aspects as documented in the new German standard VDI 2243, “Designing Technical Products for Ease of Recycling – Fundamentals and Rules for Design”. The results of this evaluation provide insight in future areas of research and fastener selection models for life cycle design.

Robust Design by Matching the Design With Manufacturing Variation Patterns

This paper deals with robust design problems in which variations on design variables have significant correlation. Manufacturing errors often affect design variables with characteristic patterns, that is, the variations are coupled. Robust optimization seeks designs with optimal and robust performance. Designers should match the design to the Manufacturing Variation Patterns (MVP) in the constrained robust optimization procedure. This study focuses on matching the variation patterns found in typical manufacturing processes. It uses quadrature experimental design to approximate the performance variation within the patterns. We redefine the robust constraint activity for designs using MVP and propose our procedure to search for the robust feasible designs. Theoretical development of manufacturing variation matching leads to our case study of heat treated shaft design with minimum dimensional distortion. The paper also outlines our future application in injection molding gear design and challenge in the identification of nonlinear correlated MVP.

A Hybrid Approach of Heuristic and Neural Network for Packing Problems

Artificial Neural Networks, particularly the Hopfield-Tank network, have been effectively applied to the solution of a variety of tasks formulated as large scale combinatorial optimization problems, such as Travelling Salesman Problem and N Queens Problem [1]. The problem of optimally packing a set of geometries into a space with finite dimensions arises frequently in many applications and is far difficult than general NP-complete problems listed in [2]. Until now within accepted time limit, it can only be solved with heuristic methods for very simple cases (e.g. 2D layout). In this paper we propose a heuristic-based Hopfield neural network designed to solve the rectangular packing problems in two dimensions, which is still NP-complete [3]. By comparing the adequacy and efficiency of the results with that obtained by several other exact and heuristic approaches, it has been concluded that the proposed method has great potential in solving 2D packing problems.

Multicriterion Optimization: A Tool in Advanced Materials Technology

This paper will demonstrate on two advanced materials — a fibre-reinforced composite laminate (FRC) and a transformation toughened ceramic (TTC) — the importance of multicriterion optimization in the production of useful advanced materials with enhanced mechanical properties. In a previous paper (Thomsen et al., 1994a), the authors have demonstrated the application of single-criterion optimization to these materials which are based on a brittle matrix and thus prone to cracking at very low applied stresses. The optimization process aims at altering their microstructure so that all their desirable mechanical properties are enhanced. Currently, the advanced materials technologists must take a heuristic approach to meeting the often competing requirements. The present paper will show how multicriterion optimization can come to the aid of the technologists and reduce their reliance on empirical approaches.