Modelling polymers with side chains: MEH-PPV and P3HT

Modelling polymers with side chains is always a challenge once the degrees of freedom are very high. In this study, we present a successful methodology to model poly[2-methoxy-5-(2′-ethyl-hexyloxy)-p-phenylenevinylene] (MEH-PPV) and poly[3-hexylthiophene] (P3HT) in solutions, taking into account the influence of side chains on the polymer conformation. Molecular dynamics and semi-empirical quantum mechanical methods were used for structure optimisation and evaluation of optical properties. The methodology allows to describe structural and optical characteristics of the polymers in a satisfactory way, as well as to evaluate some usual simplifications adopted for modelling these systems. Effective conjugation lengths of 8-14.6 and 21 monomers were obtained for MEH-PPV and P3HT, respectively, in accordance with experimental findings. In addition, anti/syn conformations of these polymers could be predicted based on intrinsic interactions of the lateral branches. © 2013 Copyright Taylor and Francis Group, LLC.

Optimizing feature selection through binary charged system search

Feature selection aims to find the most important information from a given set of features. As this task can be seen as an optimization problem, the combinatorial growth of the possible solutions may be inviable for a exhaustive search. In this paper we propose a new nature-inspired feature selection technique based on the Charged System Search (CSS), which has never been applied to this context so far. The wrapper approach combines the power of exploration of CSS together with the speed of the Optimum-Path Forest classifier to find the set of features that maximizes the accuracy in a validating set. Experiments conducted in four public datasets have demonstrated the validity of the proposed approach can outperform some well-known swarm-based techniques. © 2013 Springer-Verlag.

Otimização dinâmica de rotores com eixos em compósito

Pós-graduação em Engenharia Mecânica - FEG

Boundary condition identification of a bridge pier using experimental data and FEM modal updating

Over the past twenty years, new technologies have required an increasing use of mathematical models in order to understand better the structural behavior: finite element method is the one mostly used. However, the reliability of this method applied to different situations has to be tried each time. Since it is not possible to completely model the reality, different hypothesis must be done: these are the main problems of FE modeling. The following work deals with this problem and tries to figure out a way to identify some of the unknown main parameters of a structure. This main research focuses on a particular path of study and development, but the same concepts can be applied to other objects of research. The main purpose of this work is the identification of unknown boundary conditions of a bridge pier using the data acquired experimentally with field tests and a FEM modal updating process. This work doesn’t want to be new, neither innovative. A lot of work has been done during the past years on this main problem and many solutions have been shown and published. This thesis just want to rework some of the main aspects of the structural optimization process, using a real structure as fitting model.

Synthesis and characterization of GaAsSb-capped InAs-based QDIPs

Quantum dot infrared photodetectors (QDIPs) are very attractive for infrared imaging applications due to its promising features such as high temperature operation, normal incidence response and low dark current [1]. However, the key issue is to obtain a high quality active region which requires a structural optimization of the nanostructures. With using GaAsSb capping layer, the optical properties, such as the PL intensity and its full width at half maximum (FWHM), of InAs QDs have been improved in the range between 1.15 and 1.5 m, because of the reduction of the compressive strain in QDs and the increment of QD height [2]. In this work, we have demonstrated strong and narrow intraband photoresponse spectra from GaAsSb-capped InAs-based QDIPs

An integrated approach to conceptual design of arch bridges with curved deck

El concepto de funicularidad se puede extender a estructuras lineales espaciales como, por ejemplo, los puentes arco con tablero curvo. Estas estructuras, especialmente pasarelas peatonales, son consecuencia de la necesidad de encajar trazados exigentes y de dar respuesta a nuevas demandas arquitectónicas. En las estructuras curvas el diseño conceptual juega un papel absolutamente esencial. Siempre ha sido así, pero en el caso presente, cabe resaltar que una errónea elección de la geometría conlleva una serie de problemas que se irán acumulando a lo largo del proceso de proyecto, de la construcción y de la vida de la estructura. En este trabajo se presenta SOFIA (Shaping Optimal Form with an Interactive Approach), una herramienta capaz de, conocida la geometría del tablero, de buscar automáticamente la forma del arco antifunicular correspondiente. El planteamiento seguido es conceptualmente el mismo que el utilizado en la búsqueda de formas óptimas en estructuras en dos dimensiones: el arco antifunicular es el que representa, para unas cargas dadas, el lugar geométrico de los puntos con momento flector nulo. La herramienta ha sido desarrollada en un entorno integrado, interactivo y paramético. Su implementación está ilustrada y unos ejemplos de análisis paramétricos están desarrollados. La posición transversal relativa entre tablero y arco ha sido investigada para obtener la configuración del puente estructuralmente más eficiente. Las pasarelas curvas se han convertido en un problema de ingeniería más común de lo habitual en el contexto de los desarrollos urbanos cuando el cliente está buscando un fuerte componente estético: un diseño conceptual adecuado permite obtener una estructura eficiente y elegante. Spatial arch bridges represent an innovative answer to demands on functionality, structural optimization and aesthetics for curved decks, popular in urban contexts. This thesis presents SOFIA (Shaping Optimal Form with an Interactive Approach), a methodology for conceptual designing of antifunicular spatial arch bridges with curved deck in a parametric, interactive and integrated environment. The approach and its implementation are in-depth described and detailed examples of parametric analyses are illustrated. The optimal deck-arch relative transversal position has been investigated for obtaining the most cost-effective bridge. Curved footbridges have become a more common engineering problem in the context of urban developments when the client is looking for a strong aesthetics component: an appropriate conceptual design allows to obtain an efficient and elegant structure.

Management audit : Department of Central Management Services' administration of the state's space utilization program.

"This is our report of the Management Audit of the Department of Central Management Services' Administration of the State's Space Utilization Program. The audit was conducted pursuant to Legislative Audit Commission Resolution Number 126, which was adopted December 11, 2002. This audit was conducted in accordance with generally accepted government auditing standards and the audit standards promulgated by the Office of the Auditor General at 74 Ill. Adm. Code-420.310. The audit report is transmitted in conformance with Section 3-14 of the Illinois State Auditing Act."--Cover letter.

Model updating using genetic algorithms with sequential niche technique

The authors would like to express their gratitude to organizations and people that supported this research. Piotr Omenzetter’s work within the Lloyd’s Register Foundation Centre for Safety and Reliability Engineering at the University of Aberdeen is supported by Lloyd’s Register Foundation. The Foundation helps to protect life and property by supporting engineering-related education, public engagement and the application of research. Ben Ryder of Aurecon and Graeme Cummings of HEB Construction assisted in obtaining access to the bridge and information for modelling. Luke Williams and Graham Bougen, undergraduate research students, assisted with testing.

Algoritmos de otimização e o problema inverso aplicados à identificação de danos estruturais com o uso do MEF

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Civil e Ambiental, 2015.

Combining data mining and evolutionary computation for multi-criteria optimization of earthworks

Earthworks tasks aim at levelling the ground surface at a target construction area and precede any kind of structural construction (e.g., road and railway construction). It is comprised of sequential tasks, such as excavation, transportation, spreading and compaction, and it is strongly based on heavy mechanical equipment and repetitive processes. Under this context, it is essential to optimize the usage of all available resources under two key criteria: the costs and duration of earthwork projects. In this paper, we present an integrated system that uses two artificial intelligence based techniques: data mining and evolutionary multi-objective optimization. The former is used to build data-driven models capable of providing realistic estimates of resource productivity, while the latter is used to optimize resource allocation considering the two main earthwork objectives (duration and cost). Experiments held using real-world data, from a construction site, have shown that the proposed system is competitive when compared with current manual earthwork design.

Engineering knowledge-based variance-reduction simulation and G-dominance for structural frame robust optimization

[EN] This paper proposes the incorporation of engineering knowledge through both (a) advanced state-of-the-art preference handling decision-making tools integrated in multiobjective evolutionary algorithms and (b) engineering knowledge-based variance reduction simulation as enhancing tools for the robust optimum design of structural frames taking uncertainties into consideration in the design variables.The simultaneous minimization of the constrained weight (adding structuralweight and average distribution of constraint violations) on the one hand and the standard deviation of the distribution of constraint violation on the other are handled with multiobjective optimization-based evolutionary computation in two different multiobjective algorithms. The optimum design values of the deterministic structural problem in question are proposed as a reference point (the aspiration level) in reference-point-based evolutionary multiobjective algorithms (here g-dominance is used). Results including

A hybrid Particle Swarm Optimization - Simplex algorithm (PSOS) for structural damage identification

This study proposes a new PSOS-model based damage identification procedure using frequency domain data. The formulation of the objective function for the minimization problem is based on the Frequency Response Functions (FRFs) of the system. A novel strategy for the control of the Particle Swarm Optimization (PSO) parameters based on the Nelder-Mead algorithm (Simplex method) is presented; consequently, the convergence of the PSOS becomes independent of the heuristic constants and its stability and confidence are enhanced. The formulated hybrid method performs better in different benchmark functions than the Simulated Annealing (SA) and the basic PSO (PSO(b)). Two damage identification problems, taking into consideration the effects of noisy and incomplete data, were studied: first, a 10-bar truss and second, a cracked free-free beam, both modeled with finite elements. In these cases, the damage location and extent were successfully determined. Finally, a non-linear oscillator (Duffing oscillator) was identified by PSOS providing good results. (C) 2009 Elsevier Ltd. All rights reserved

Materials selection for a set of multiple parts considering manufacturing costs and weight reduction with structural isoperformance using direct multisearch optimization

Materials selection is a matter of great importance to engineering design and software tools are valuable to inform decisions in the early stages of product development. However, when a set of alternative materials is available for the different parts a product is made of, the question of what optimal material mix to choose for a group of parts is not trivial. The engineer/designer therefore goes about this in a part-by-part procedure. Optimizing each part per se can lead to a global sub-optimal solution from the product point of view. An optimization procedure to deal with products with multiple parts, each with discrete design variables, and able to determine the optimal solution assuming different objectives is therefore needed. To solve this multiobjective optimization problem, a new routine based on Direct MultiSearch (DMS) algorithm is created. Results from the Pareto front can help the designer to align his/hers materials selection for a complete set of materials with product attribute objectives, depending on the relative importance of each objective.

An evolutionary multi-objective optimization system for earthworks

Earthworks involve the levelling or shaping of a target area through the moving or processing of the ground surface. Most construction projects require earthworks, which are heavily dependent on mechanical equipment (e.g., excavators, trucks and compactors). Often, earthworks are the most costly and time-consuming component of infrastructure constructions (e.g., road, railway and airports) and current pressure for higher productivity and safety highlights the need to optimize earthworks, which is a nontrivial task. Most previous attempts at tackling this problem focus on single-objective optimization of partial processes or aspects of earthworks, overlooking the advantages of a multi-objective and global optimization. This work describes a novel optimization system based on an evolutionary multi-objective approach, capable of globally optimizing several objectives simultaneously and dynamically. The proposed system views an earthwork construction as a production line, where the goal is to optimize resources under two crucial criteria (costs and duration) and focus the evolutionary search (non-dominated sorting genetic algorithm-II) on compaction allocation, using linear programming to distribute the remaining equipment (e.g., excavators). Several experiments were held using real-world data from a Portuguese construction site, showing that the proposed system is quite competitive when compared with current manual earthwork equipment allocation.

An Analysis of black-box optimization problems in reinsurance: evolutionary-based approaches

Black-box optimization problems (BBOP) are de ned as those optimization problems in which the objective function does not have an algebraic expression, but it is the output of a system (usually a computer program). This paper is focussed on BBOPs that arise in the eld of insurance, and more speci cally in reinsurance problems. In this area, the complexity of the models and assumptions considered to de ne the reinsurance rules and conditions produces hard black-box optimization problems, that must be solved in order to obtain the optimal output of the reinsurance. The application of traditional optimization approaches is not possible in BBOP, so new computational paradigms must be applied to solve these problems. In this paper we show the performance of two evolutionary-based techniques (Evolutionary Programming and Particle Swarm Optimization). We provide an analysis in three BBOP in reinsurance, where the evolutionary-based approaches exhibit an excellent behaviour, nding the optimal solution within a fraction of the computational cost used by inspection or enumeration methods.