Effiziente Algorithmen

[no abstract available

Advances in Evolutionary Algorithms

With the recent trends towards massive data sets and significant computational power, combined with evolutionary algorithmic advances evolutionary computation is becoming much more relevant to practice. Aim of the book is to present recent improvements, innovative ideas and concepts in a part of a huge EA field

PHYSICS-BASED SHAPE MORPHING AND PACKING FOR LAYOUT DESIGN

The packing problem, also named layout design, has found wide applications in the mechanical engineering field. In most cases, the shapes of the objects do not change during the packing process. However, in some applications such as vehicle layout design, shape morphing may be required for some specific components (such as water and fuel reservoirs). The challenge is to fit a component of sufficient size in the available space in a crowded environment (such as the vehicle under-hood) while optimizing the overall performance objectives of the vehicle and improving design efficiency. This work is focused on incorporating component shape design into the layout design process, i.e. finding the optimal locations and orientations of all the components within a specified volume, as well as the suitable shapes of selected ones. The first major research issue is to identify how to efficiently and accurately morph the shapes of components respecting the functional constraints. Morphing methods depend on the geometrical representation of the components. The traditional parametric representation may lend itself easily to modification, but it relies on assumption that the final approximate shape of the object is known, and therefore, the morphing freedom is very limited. To morph objects whose shape can be changed arbitrarily in layout design, a mesh based morphing method based on a mass-spring physical model is developed. For this method, there is no need to explicitly specify the deformations and the shape morphing freedom is not confined. The second research issue is how to incorporate component shape design into a layout design process. Handling the complete problem at once may be beyond our reach,therefore decomposition and multilevel approaches are used. At the system level, a genetic algorithm (GA) is applied to find the positions and orientations of the objects, while at the sub-system or component level, morphing is accomplished for select components. Although different packing applications may have different objectives and constraints, they all share some common issues. These include CAD model preprocessing for packing purpose, data format translation during the packing process if performance evaluation and morphing use different representation methods, efficiency of collision detection methods, etc. These common issues are all brought together under the framework of a general methodology for layout design with shape morphing. Finally, practical examples of vehicle under-hood/underbody layout design with the mass-spring physical model based shape morphing are demonstrated to illustrate the proposed approach before concluding and proposing continuing work

Book of Abstracts of the Sixth SIAM Workshop on Combinatorial Scientific Computing

Book of Abstracts of CSC14 edited by Bora UçarInternational audienceThe Sixth SIAM Workshop on Combinatorial Scientific Computing, CSC14, was organized at the Ecole Normale Supérieure de Lyon, France on 21st to 23rd July, 2014. This two and a half day event marked the sixth in a series that started ten years ago in San Francisco, USA. The CSC14 Workshop's focus was on combinatorial mathematics and algorithms in high performance computing, broadly interpreted. The workshop featured three invited talks, 27 contributed talks and eight poster presentations. All three invited talks were focused on two interesting fields of research specifically: randomized algorithms for numerical linear algebra and network analysis. The contributed talks and the posters targeted modeling, analysis, bisection, clustering, and partitioning of graphs, applied in the context of networks, sparse matrix factorizations, iterative solvers, fast multi-pole methods, automatic differentiation, high-performance computing, and linear programming. The workshop was held at the premises of the LIP laboratory of ENS Lyon and was generously supported by the LABEX MILYON (ANR-10-LABX-0070, Université de Lyon, within the program ''Investissements d'Avenir'' ANR-11-IDEX-0007 operated by the French National Research Agency), and by SIAM

Study of the flow field through the wall of a Diesel particulate filter using Lattice Boltzmann Methods

Contamination is becoming an important problem in great metropolitan areas. A large portion of the contaminants is emitted by the vehicle fleet. At European level, as well as in other economical areas, the regulation is becoming more and more restrictive. Euro regulations are the best example of this tendency. Specially important are the emissions of nitrogen oxide (NOx) and Particle Matter (PM). Two different strategies exist to reduce the emission of pollutants. One of them is trying to avoid their creation. Modifying the combustion process by means of different fuel injection laws or controlling the air regeneration are the typical methods. The second set of strategies is focused on the contaminant elimination. The NOx are reduced by means of catalysis and/or reducing atmosphere, usually created by injection of urea. The particle matter is eliminated using filters. This thesis is focused in this matter. Most of the strategies to reduce the emission of contaminants penalise fuel consumption. The particle filter is not an exception. Its installation, located in the exhaust duct, restricts the pass of the air. It increases the pressure along the whole exhaust line before the filter reducing the performance. Optimising the filter is then an important task. The efficiency of the filter has to be good enough to obey the contaminant normative. At the same time the pressure drop has to be as low as possible to optimise fuel consumption and performance. The objective of the thesis is to find the relation between the micro-structure and the macroscopic properties. With this knowledge the optimisation of the micro-structure is possible. The micro-structure of the filter mimics acicular mullite. It is created by procedural generation using random parameters. The relation between micro-structure and the macroscopic properties such as porosity and permeability are studied in detail. The flow field is solved using LabMoTer, a software developed during this thesis. The formulation is based on Lattice Botlzmann Methods, a new approach to simulate fluid dynamics. In addition, Walberla framework is used to solve the flow field too. This tool has been developed by Friedrich Alexander University of Erlangen Nürnberg. The second part of the thesis is focused on the particles immersed into the fluid. The properties of the particles are given as a function of the aerodynamic diameter. This is enough for macroscopic approximations. However, the discretization of the porous media has the same order of magnitude than the particle size. Consequently realistic geometry is necessary. Diesel particles are aggregates of spheres. A simulation tool is developed to create these aggregated using ballistic collision. The results are analysed in detail. The second step is to characterise their aerodynamic properties. Due to the small size of the particles, with the same order of magnitude than the separation between molecules of air, the fluid can not be approximated as a continuous medium. A new approach is needed. Direct Simulation Monte Carlo is the appropriate tool. A solver based on this formulation is developed. Unfortunately complex geometries could not be implemented on time. The thesis has been fruitful in several aspects. A new model based on procedural generation has been developed to create a micro-structure which mimics acicular mullite. A new CFD solver based on Lattice Boltzmann Methods, LabMoTer, has been implemented and validated. At the same time it is proposed a technique to optimized setup. Ballistic agglomeration process is studied in detail thanks to a new simulator developed ad hoc for this task. The results are studied in detail to find correlation between properties and the evolution in time. Uncertainty Quantification is used to include the Uncertainty in the models. A new Direct Simulation Monte Carlo solver has been developed and validated to calculate rarefied flow.La contaminación se está volviendo un gran problema para las grandes áreas metropolitanas, en gran parte debido al tráfico. A nivel europeo, al igual que en otras áreas, la regulación es cada vez más restrictiva. Una buena prueba de ello es la normativa Euro de la Unión Europea. Especialmente importantes son las emisiones de óxidos de nitrógeno (NOx) y partículas (PM). La reducción de contaminantes se puede abordar desde dos estrategias distintas. La primera es la prevención. Modificar el proceso de combustión a través de las leyes de inyección o controlar la renovación de la carda son los métodos más comunes. La segunda estrategia es la eliminación. Se puede reducir los NOx mediante catálisis o atmósfera reductora y las partículas mediante la instalación de un filtro en el conducto de escape. La presente tesis se centra en el estudio de éste último. La mayoría de as estrategias para la reducción de emisiones penalizan el consumo. El filtro de partículas no es una excepción. Restringe el paso de aire. Como consecuencia la presión se incrementa a lo largo de toda la línea reduciendo las prestaciones del motor. La optimización del filtro es de vital importancia. Tiene que mantener su eficacia a la par que que se minimiza la caída de presión y con ella el consumo de combustible. El objetivo de la tesis es encontrar la relación entre la miscroestructura y las propiedades macroscópicas del filtro. Las conclusiones del estudio podrán utilizarse para optimizar la microestructura. La microestructura elegida imita los filtros de mulita acicular. Se genera por ordenador mediante generación procedimental utilizando parámetros aleatorios. Gracias a ello se puede estudiar la relación que existe entre la microestructura y las propiedades macroscópicas como la porosidad y la permeabilidad. El campo fluido se resuelve con LabMoTer, un software desarrollado en esta tesis. Está basado en Lattice Boltzmann, una nueva aproximación para simular fluidos. Además también se ha utilizado el framework Walberla desarrollado por la universidad Friedrich Alexander de Erlangen Nürnberg. La segunda parte de la tesis se centra en las partículas suspendidas en el fluido. Sus propiedades vienen dadas en función del diámetro aerodinámico. Es una buena aproximación desde un punto de vista macroscópico. Sin embargo éste no es el caso. El tamaño de la discretización requerida para calcular el medio poroso es similar al tamaño de las partículas. En consecuencia se necesita simular geometrías realistas. Las partículas Diesel son agregados de esferas. El proceso de aglomeración se ha simulado mediante colisión balística. Los resultados se han analizado con detalle. El segundo paso es la caracterización aerodinámica de los aglomerados. Debido a que el tamaño de las partículas precursoras es similar a la distancia entre moléculas el fluido no puede ser considerado un medio continuo. Se necesita una nueva aproximación. La herramienta apropiada es la Simulación Directa Monte Carlo (DSMC). Por ello se ha desarrollado un software basado en esta formulación. Desafortunadamente no ha habido tiempo suficiente como para implementar condiciones de contorno sobre geometrías complejas. La tesis ha sido fructífera en múltiples aspectos. Se ha desarrollado un modelo basado en generación procedimental capaz de crear una microestructura que aproxime mulita acicular. Se ha implementado y validado un nuevo solver CFD, LabMoTer. Además se ha planteado una técnica que optimiza la preparación del cálculo. El proceso de aglomeración se ha estudiado en detalle gracias a un nuevo simulador desarrollado ad hoc para esta tarea. Mediante el análisis estadístico de los resultados se han planteado modelos que reproducen la población de partículas y su evolución con el tiempo. Técnicas de Cuantificación de Incertidumbre se han empleado para modelar la dispersión de datos. Por último, un simulador basadoLa contaminació s'està tornant un gran problema per a les grans àrees metropolitanes, en gran part degut al tràfic. A nivell europeu, a l'igual que en atres àrees, la regulació és cada volta més restrictiva. Una bona prova d'això és la normativa Euro de l'Unió Europea. Especialment importants són les emissions d'òxits de nitrogen (NOX) i partícules (PM). La reducció de contaminants se pot abordar des de dos estratègies distintes. La primera és la prevenció. Modificar el procés de combustió a través de les lleis d'inyecció o controlar la renovació de la càrrega són els mètodos més comuns. La segona estratègia és l'eliminació. Se pot reduir els NOX mediant catàlisis o atmòsfera reductora i les partícules mediant l'instalació d'un filtre en el vas d'escap. La present tesis se centra en l'estudi d'este últim. La majoria de les estratègies per a la reducció d'emissions penalisen el consum. El filtre de partícules no és una excepció. Restringix el pas d'aire. Com a conseqüència la pressió s'incrementa a lo llarc de tota la llínea reduint les prestacions del motor. L'optimisació del filtre és de vital importància. Ha de mantindre la seua eficàcia a la par que que es minimisa la caiguda de pressió i en ella el consum de combustible. L'objectiu de la tesis és trobar la relació entre la microescritura i les propietats macroscòpiques del filtre. Les conclusions de l'estudi podran utilisar-se per a optimisar la microestructura. La microestructura elegida imita els filtres de mulita acicular. Se genera per ordenador mediant generació procedimental utilisant paràmetros aleatoris. Gràcies ad això es pot estudiar la relació que existix entre la microestructura i les propietats macroscòpiques com la porositat i la permeabilitat. El camp fluït se resol en LabMoTer, un software desenrollat en esta tesis. Està basat en Lattice Boltzmann, una nova aproximació per a simular fluïts. Ademés també s'ha utilisat el framework Walberla, desentollat per l'Universitat Friedrich Alexander d'Erlangen Nürnberg. La segona part de la tesis se centra en les partícules suspeses en el fluït. Les seues propietats venen donades en funció del diàmetro aerodinàmic. És una bona aproximació des d'un punt de vista macroscòpic. No obstant este no és el cas. El tamany de la discretisació requerida per a calcular el mig porós és similar al tamany de les partícules. En conseqüència es necessita simular geometries realistes. Les partícules diésel són agregats d'esferes. El procés d'aglomeració s'ha simulat mediant colisió balística. Els resultats s'han analisat en detall. El segon pas és la caracterisació aerodinàmica dels aglomerats. Degut a que el tamany de les partícules precursores és similar a la distància entre molècules el fluït no pot ser considerat un mig continu. Se necessita una nova aproximació. La ferramenta apropiada és la Simulació Directa Monte Carlo (DSMC). Per això s'ha desenrollat un software basat en esta formulació. Malafortunadament no ha hagut temps suficient com per a implementar condicions de contorn sobre geometries complexes. La tesis ha segut fructífera en múltiples aspectes. S'ha desenrollat un model basat en generació procedimental capaç de crear una microestructura que aproxime mulita acicular. S'ha implementat i validat un nou solver CFD, LabMoTer. Ademés s'ha plantejat una tècnica que optimisa la preparació del càlcul. El procés d'aglomeració s'ha estudiat en detall gràcies a un nou simulador desenrollat ad hoc per ad esta tasca. Mediant l'anàlisis estadístic dels resultats s'han plantejat models que reproduixen la població de partícules i la seua evolució en el temps. Tècniques de Quantificació d'Incertea s'han empleat per a modelar la dispersió de senyes. Per últim, un simulador basat en DSMC s'ha desenrollat per a calcular fluïts rarificats.García Galache, JP. (2017). Study of the flow field through the wall of a Diesel particulate filter using Lattice Boltzmann Methods [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/90413TESI

Measurements, Models, Systems and Design

531 s.

Natural Parameterization

The objective of this project has been to develop an approach for imitating physical objects with an underlying stochastic variation. The key assumption is that a set of “natural parameters” can be extracted by a new subdivision algorithm so they reflect what is called the object’s “geometric DNA”. A case study on one hundred wheat grain crosssections (Triticum aestivum) showed that it was possible to extract thirty-six such parameters and to reuse them for Monte Carlo simulation of “new” stochastic phantoms which possessthe same stochastic behavior as the “original” cross-sections

Optimal use of computing equipment in an automated industrial inspection context

This thesis deals with automatic defect detection. The objective was to develop the techniques required by a small manufacturing business to make cost-efficient use of inspection technology. In our work on inspection techniques we discuss image acquisition and the choice between custom and general-purpose processing hardware. We examine the classes of general-purpose computer available and study popular operating systems in detail. We highlight the advantages of a hybrid system interconnected via a local area network and develop a sophisticated suite of image-processing software based on it. We quantitatively study the performance of elements of the TCP/IP networking protocol suite and comment on appropriate protocol selection for parallel distributed applications. We implement our own distributed application based on these findings. In our work on inspection algorithms we investigate the potential uses of iterated function series and Fourier transform operators when preprocessing images of defects in aluminium plate acquired using a linescan camera. We employ a multi-layer perceptron neural network trained by backpropagation as a classifier. We examine the effect on the training process of the number of nodes in the hidden layer and the ability of the network to identify faults in images of aluminium plate. We investigate techniques for introducing positional independence into the network's behaviour. We analyse the pattern of weights induced in the network after training in order to gain insight into the logic of its internal representation. We conclude that the backpropagation training process is sufficiently computationally intensive so as to present a real barrier to further development in practical neural network techniques and seek ways to achieve a speed-up. Weconsider the training process as a search problem and arrive at a process involving multiple, parallel search "vectors" and aspects of genetic algorithms. We implement the system as the mentioned distributed application and comment on its performance

Metaheuristic design of feedforward neural networks: a review of two decades of research

Over the past two decades, the feedforward neural network (FNN) optimization has been a key interest among the researchers and practitioners of multiple disciplines. The FNN optimization is often viewed from the various perspectives: the optimization of weights, network architecture, activation nodes, learning parameters, learning environment, etc. Researchers adopted such different viewpoints mainly to improve the FNN's generalization ability. The gradient-descent algorithm such as backpropagation has been widely applied to optimize the FNNs. Its success is evident from the FNN's application to numerous real-world problems. However, due to the limitations of the gradient-based optimization methods, the metaheuristic algorithms including the evolutionary algorithms, swarm intelligence, etc., are still being widely explored by the researchers aiming to obtain generalized FNN for a given problem. This article attempts to summarize a broad spectrum of FNN optimization methodologies including conventional and metaheuristic approaches. This article also tries to connect various research directions emerged out of the FNN optimization practices, such as evolving neural network (NN), cooperative coevolution NN, complex-valued NN, deep learning, extreme learning machine, quantum NN, etc. Additionally, it provides interesting research challenges for future research to cope-up with the present information processing era