Structural optimization in engineering design with a focus on process automation.

The present work is concerned with the advancement of the knowledge of structural optimization in engineering design while focusing on efficient and easy to use ways of setting-up the required automated processes as well as the problems arising from it. Three industry examples are considered. In the first example a software tool that serves as a hands-on decision guidance for many occurring design situations for structured wall PE pipes is developed. In order to avoid licensing fees only public domain software or in-house code are used. It offers the efficient and automated simulation of the ringstiffness test as well as the most common pipe installation scenarios. In addition, an optimization feature is implemented for the design of optimum pipe profiles with regards to the ringstiffness test. In the second example a framework for the optimum design of carbon fibre mountain bike frames is developed. An extensively parameterized and automated simulation model is created that allows for varying tube shapes, paths and laminate ply thicknesses as well as joint locations. For improved efficiency a decomposition approach has been employed that decomposes the original optimization problem into a size optimization sub problem and a shape optimization top level problem. The former is solved by the built-in optimization tool in OptiStruct and the latter by means of surrogate based optimization where each experiment in the DoE is a full size optimization. The third example is concerned with the optimum design of a blade for a novel vertical axis wind turbine. A design approach similar to those with horizontal axes is chosen. The altered design requirements are accounted for by creating a parameterized simulation model and performing size optimization runs for 32 models with different material settings and shear web locations where the model creation process has been automated

Application of Permutation Genetic Algorithm for Sequential Model Building–Model Validation Design of Experiments

YesThe work presented in this paper is motivated by a complex multivariate engineering problem associated with engine mapping experiments, which require efficient Design of Experiment (DoE) strategies to minimise expensive testing. The paper describes the development and evaluation of a Permutation Genetic Algorithm (PermGA) to support an exploration-based sequential DoE strategy for complex real-life engineering problems. A known PermGA was implemented to generate uniform OLH DoEs, and substantially extended to support generation of Model Building–Model Validation (MB-MV) sequences, by generating optimal infill sets of test points as OLH DoEs, that preserve good space filling and projection properties for the merged MB + MV test plan. The algorithm was further extended to address issues with non-orthogonal design spaces, which is a common problem in engineering applications. The effectiveness of the PermGA algorithm for the MB-MV OLH DoE sequence was evaluated through a theoretical benchmark problem based on the Six-Hump-Camel-Back (SHCB) function, as well as the Gasoline Direct Injection (GDI) engine steady state engine mapping problem that motivated this research. The case studies show that the algorithm is effective at delivering quasi-orthogonal space-filling DoEs with good properties even after several MB-MV iterations, while the improvement in model adequacy and accuracy can be monitored by the engineering analyst. The practical importance of this work, demonstrated through the engine case study, also is that significant reduction in the effort and cost of testing can be achieved.The research work presented in this paper was funded by the UK Technology Strategy Board (TSB) through the Carbon Reduction through Engine Optimization (CREO) project

Continuous Optimization in Aerospace Structures

In structural design optimization, engineers and designers aim to obtain more efficient designs with regards to weight, stiffness and frequency measures, for a given set of design variables. These design variables can be of different type: material properties, geometric variables, etc. Hence, depending on the design variables that are chosen, different techniques such as topology, shape and sizing optimization have been introduced. This paper presents a brief introduction to the topic in their continuous and corresponding discrete formulation based on the Finite Element Method (FEM). Basic concepts of the advanced technologies that are involved in a typical structural design progress are also included, such as: modeling analysis using the FEM, mesh generation/adaptivity, and error estimation. Illustrative examples of numerical instabilities in the FE solution, shape and topology optimization, and fully integrate design optimization processes are also presented.Fil: Luege, Mariela. Swansea University; Reino Unido. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Instituto de Estructuras "Ing. Arturo M. Guzmán"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán; ArgentinaFil: Sienz, Johann. Swansea University; Reino UnidoFil: Fuerle, Fabián. Swansea University; Reino Unid

A Transparent Communication Layer for Heterogenous, Distributed Systems

In this paper we present a novel communication layer for distributed heterogenous environments typical found in the area of Grid computing. This communication layer is used as part of ViPIOS islands, an I/O module for storage and administration of large data sets

ViPIOS: The Vienna Parallel Input/Output System

. In this paper we present the Vienna Parallel Input Output System (ViPIOS), a novel approach to enhance the I/O performance of high performance applications. It is a client-server based tool combining capabilities found in parallel I/O runtime libraries and parallel file systems. 1 Introduction In the last few years the applications in high performance computing (Grand Challenges [1]) shifted from being CPU-bound to be I/O-bound. Performance can not be scaled up by increasing the number of CPUs any more, but by increasing the bandwidth of the I/O subsystem. This situation is commonly known as the I/O bottleneck in high performance computing ([5]) In reaction all leading hardware vendors of multiprocessor systems provided powerful concurrent I/O subsystems. In accordance researchers focused on the design of appropriate programming tools to take advantage of the available hardware resources. 1.1 The ViPIOS approach Conventionally two different directions in developing programming supp..