Application of a Hierarchical Chromosome Based Genetic Algorithm to the Problem of Finding Optimal Initial Meshes for the Self-Adaptive hp-FEM

The paper presents an algorithm for finding the optimal initial mesh for the self-adaptive hp Finite Element Method (hp-FEM) calculations. We propose the application of the hierarchical chromosome based genetic algorithm for optimal selection of the initial mesh. The selection of the optimal initial mesh will optimize the convergence rate of the numerical error of the solution over the sequence of meshes generated by the self-adaptive hp-FEM. This is especially true in the case when material data are selected as a result of some stochastic algorithm and it is not possible to design optimal initial mesh by hand. The algorithm has been tested on the non-stationary mass transport problem modeling phase transition phenomenon

Petri Nets Modeling of Dead-End Refinement Problems in a 3D Anisotropic hp-Adaptive Finite Element Method

We consider two graph grammar based Petri nets models for anisotropic refinements of three dimensional hexahedral grids. The first one detects possible dead-end problems during the graph grammar based anisotropic refinements of the mesh. The second one employs an enhanced graph grammar model that is actually dead-end free. We apply the resulting algorithm to the simulation of resistivity logging measurements for estimating the location of underground oil and/or gas formations. The graph grammar based Petri net models allow to fix the self-adaptive mesh refinement algorithm and finish the adaptive computations with the required accuracy needed by the numerical solution

Multiscale optimization of non-conventional composite structures for improved mechanical response

Nowadays, due to governmental requirements to control climate change, there is a great inter- est on the part of the automotive and aerospace industry to design structures as light as possible, without jeopardize their performance, thus increasing their efficiency. Multi-material design is a way to achieve this goal, as will be shown in this work In this work, multi-material design is considered with the goal of improving the structure’s stiffness, strength, and non-linear behaviour when it yields. Firstly, a microstructural topology optimization is carried out seeking for multi-material microstructures with increased stiffness and strength compared to equivalent single-material microstructures. Afterwards, this study is further extended to perform multi-scale topology optimization, where a concurrent optimization of ma- terial and structure is done. Ultimately, the non-linear behaviour of hybrid fibre reinforced com- posites is optimized in order to introduce a so-called “pseudo-ductility”. Two different optimization problems are formulated and solved here. One compliance mini- mization with mass constraint problem and another stress-based problem where the maximal von Mises stress is locally minimized in the unit-cell. The multi-material design is investigated here using two different approaches. On one hand, the two solids coexist being bonded together across sharp interfaces. On the other hand, a functionally graded material is obtained as an extensive smooth variation of material properties on account of varying composition’s volume fractions of both solids throughout the design domain. The compliance-based optimization results show that multi-material microstructures can be stiffer compared to single-material ones for the same mass requirement. Regarding the stress-based problem, lower stress peaks are obtained in bi-material design solutions and, specially, in the case of graded material solutions. As regards multi-scale topology optimization, the results show that a multi-material structure can be stiffer than its single-material counterpart, which is in accordance with the microstructural study performed earlier. Hybrid composites can achieve the so-called “pseudo-ductile” behaviour mimicking the well- known elastic-plastic behaviour. To understand under what circumstances such behaviour is ob- tained, optimization problems are formulated and solved here. Two different types of optimiza- tion problems are considered. Firstly, one finds out the optimal properties of fibres to hybridize and get the pseudo-ductile behaviour. Once an optimal hybridization is found, another optimiza- tion problem is solved in order to understand the influence of the fibre dispersion on the composite response. The optimal results obtained show hybrid composites having a considerable pseudo- ductile behaviour.Atualmente, devido às imposições governamentais para controlar as alterações climáticas, existe um grande interesse por parte da indústria automóvel e aeroespacial para o projeto de es- truturas o mais leves possíveis, sem se comprometer o seu desempenho, aumentando assim a sua eficiência. O projeto multimaterial de estruturas é um dos caminhos para se alcançar este objetivo, conforme será mostrado neste trabalho. Neste trabalho, considera-se o projeto multimaterial de estruturas com o objetivo de se melho- rar a rigidez, resistência, e comportamento não linear após cedência. Primeiro, é feita uma otimi- zação de topologia ao nível da microestrutura procurando-se microestruturas multimateriais com maior rigidez e resistência quando comparadas com microestruturas de material único equivalen- tes. Depois, este estudo é explorado também no contexto de otimização topológica multi-escala, onde é realizada uma otimização concorrente do material e estrutura. Por fim, o comportamento não linear de compósitos híbridos reforçados por fibra é otimizado com vista à introdução de um efeito de “pseudo-ductilidade”. São formulados e resolvidos aqui dois problemas diferentes de otimização. Um problema de minimização de compliance (flexibilidade) sujeito a um constrangimento de massa e outro pro- blema baseado na tensão, onde a tensão máxima de von Mises é localmente minimizada na célula unitária. O projeto multi-material é investigado aqui utilizando duas diferentes abordagens. Numa das abordagens, os dois sólidos coexistem na sua forma discreta originando-se interfaces com uma variação abrupta de propriedades. Na outra abordagem, obtém-se um material de gradiente funcional onde existe uma suave variação das propriedades obtida variando pontualmente a fração volúmica dos sólidos ao longo de todo o domínio de projeto. Os resultados da otimização baseada na compliance mostraram que microestruturas multimateriais podem ser mais rígidas quando comparadas com as de material único para o mesmo requisito de massa. Relativamente ao pro- blema baseado na tensão, são obtidos picos de tensão mais baixos nas soluções constituídas por duas fases discretas de material e, sobretudo, nas soluções de material de gradiente funcional. No que que diz respeito à otimização topológica multi-escala, os resultados mostraram que uma estrutura multimaterial pode ser mais rígida que uma estrutura de material único equivalente, o que está de acordo com o estudo realizado anteriormente ao nível da microestrutura. Os compósitos híbridos conseguem alcançar um comportamento designado de “pseudo-dúc- til”, imitando o conhecido comportamento elasto-plástico. Para melhor se compreender sob que circunstâncias tal comportamento é obtido, são formulados e resolvidos problemas de otimização. São assim considerados dois tipos diferentes de problemas de otimização. Primeiramente, desco- brem-se quais as propriedades ótimas das fibras a hibridizar, obtendo-se o comportamento pseudo-dúctil. Assim que hibridização ótima tenha sido descoberta, outro problema de otimização é resolvido de modo a perceber-se a influência da dispersão das fibras na resposta do compósito. Os resultados ótimos obtidos mostram compósitos híbridos tendo um comportamento pseudo- dúctil considerável

Computational methods and software for the design of inertial microfluidic flow sculpting devices

The ability to sculpt inertially flowing fluid via bluff body obstacles has enormous promise for applications in bioengineering, chemistry, and manufacturing within microfluidic devices. However, the computational difficulty inherent to full scale 3-dimensional fluid flow simulations makes designing and optimizing such systems tedious, costly, and generally tasked to computational experts with access to high performance resources. The goal of this work is to construct efficient models for the design of inertial microfluidic flow sculpting devices, and implement these models in freely available, user-friendly software for the broader microfluidics community. Two software packages were developed to accomplish this: uFlow and FlowSculpt . uFlow solves the forward problem in flow sculpting, that of predicting the net deformation from an arbitrary sequence of obstacles (pillars), and includes estimations of transverse mass diffusion and particles formed by optical lithography. FlowSculpt solves the more difficult inverse problem in flow sculpting, which is to design a flow sculpting device which produces a target flow shape. Each piece of software uses efficient, experimentally validated forward models developed within this work, which are applied to deep learning techniques to explore other routes to solving the inverse problem. The models are also highly modular, capable of incorporating new microfluidic components and flow physics to the design process. It is anticipated that the microfluidics community will integrate the tools developed here into their own research, and bring new designs, components, and applications to the inertial flow sculpting platform

7th International Meshing Roundtable '98

The goal of the 7th International Meshing Roundtable is to bring together researchers and developers from industry, academia, and government labs in a stimulating, open environment for the exchange of technical information related to the meshing process. In the past, the Roundtable has enjoyed significant participation from each of these groups from a wide variety of countries

Multi-objective Optimization of Tube Hydroforming Using Hybrid Global and Local Search

An investigation of non-linear multi-objective optimization is conducted in order to define a set of process parameters (i.e. load paths) for defect-free tube hydroforming. A generalized forming severity indicator that combines both the conventional forming limit diagram (FLD) and the forming limit stress diagram (FLSD) was adopted to detect excessive thinning, necking/splitting and wrinkling in the numerical simulation of formed parts. In order to rapidly explore and capture the Pareto frontier for multiple objectives, two optimization strategies were developed: normal boundary intersection (NBI) and multi-objective genetic algorithm (MOGA) based on the concept of dominated solutions . The NBI method produced a uniformly distributed set of solutions. For the MOGA method, a stochastic Kriging model was used as a surrogate model. Furthermore, the MOGA constraint-handling technique was improved, Kriging model updating was automated and a hybrid global-local search was implemented in order to rapidly explore the Pareto frontier. Both piece-wise linear and pulsating pressure paths were investigated for several case studies, including straight tube, pre-bent tube and industrial tube hydroforming. For straight tube hydroforming, the optimal load path was obtained using the NBI method and it showed a smaller corner radius compared to that predicted by the commercial program LS-OPT4.0. Moreover, the hybrid method coupling global search (MOGA) and local search (sequential quadratic programming: SQP) was applied for straight tube hydroforming, and the results showed a significant improvement in terms of the stress safety margin and reduced local thinning. For a commercial refrigerator door handle, the MOGA method was utilized to inversely analyze the loading path and the calculated path correlated well with the production path. For a hydroformed T-shaped tubular part, the amplitude and frequency of the pulsating pressure were optimized with MOGA. Thinning was reduced by 25% compared with experimental results. A multi-stage (prebent) tube hydroforming simulation was performed and it indicated that the reduction in formability due to bending can be largely compensated by end feeding the tube during hydroforming. The loading path optimized by MOGA showed that the expansion into the corner of the hydroforming die increased by 16.7% compared to the maximum expansion obtained during experimental trials

Virtual Reality Games for Motor Rehabilitation

This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion