Flexural response of HSC girders strengthened with non- and prestressed CFRP laminates

An experimental programme was carried out to characterise the flexural response of prestressed highstrength concrete (HSC) girders strengthened with CFRP laminates. For that purpose, four beams with 20 m span were subjected to four-point bending loads and the effectiveness of two distinct strengthening strategies was analysed. The following testing situations have been considered: one girder was externally strengthened with CFRP laminates, whereas one was externally strengthened with prestressed CFRP laminates; the two remaining girders were left unstrengthened and were used as control. The monitoring system included the measurement of deflections at critical sections, strains in pre-selected points of the concrete girder and CFRP laminates and the applied loading, respectively using displacement transducers, strain gages and load cells. Herein, the tests are thoroughly described and the most relevant results and conclusions are presented

What are the Best Hierarchical Descriptors for Complex Networks?

This work reviews several hierarchical measurements of the topology of complex networks and then applies feature selection concepts and methods in order to quantify the relative importance of each measurement with respect to the discrimination between four representative theoretical network models, namely Erd\"{o}s-R\'enyi, Barab\'asi-Albert, Watts-Strogatz as well as a geographical type of network. The obtained results confirmed that the four models can be well-separated by using a combination of measurements. In addition, the relative contribution of each considered feature for the overall discrimination of the models was quantified in terms of the respective weights in the canonical projection into two dimensions, with the traditional clustering coefficient, hierarchical clustering coefficient and neighborhood clustering coefficient resulting particularly effective. Interestingly, the average shortest path length and hierarchical node degrees contributed little for the separation of the four network models.Comment: 9 pages, 4 figure

Comportamento à rotura de vigas de betão de alta resistência reforçadas com CFRP

O presente artigo encontra-se inserido num projeto que visa caracterizar o comportamento de vigas de Betão de Alta Resistência (HSC) reforçadas com laminados de CFRP (Carbon Fiber Reinforced Polymer). Para o efeito, foi definido um programa experimental que compreende o reforço de uma viga fabricada em HSC e o seu ensaio em flexão até à rotura. A realização de um estudo numérico prévio permitiu concluir que a aplicação de pré-esforço aos laminados de CFRP aumentaria de forma considerável a eficiência do reforço. Sendo assim a viga pré-esforçada de grande vão (20 m), fabricada com um betão de resistência à compressão de 120 MPa e de secção transversal em I (com altura de 0.5 m e largura de 0.30 m) foi reforçada com laminados de CFRP pré-esforçados. A operação de reforço das vigas foi precedida do carregamento das mesmas com uma carga correspondente a uma combinação quase permanente de ações, mantida constante durante a operação de reforço, de forma a simular o reforço de elementos estruturais em aplicações correntes de engenharia civil. Após reforço, a viga foi ensaiada até à rotura por flexão. Os resultados deste estudo foram comparados com os obtidos em ensaios à rotura de duas vigas de HSC não reforçadas com as mesmas dimensões e condições de ensaio, apresentando-se as principais conclusões

Multiple solutions of mixed variable optimization by multistart hooke and jeeves filter method

In this study, we propose a multistart method based on an extended version of the Hooke and Jeeves (HJ) algorithm for computing mul- tiple solutions of mixed variable optimization problems. The inequal- ity and equality constraints of the problem are handled by a filter set methodology. The basic ideas present in the HJ algorithm, namely the exploratory and pattern moves, are extended to consider two objective functions and to handle continuous and integer variables simultaneously. This proposal is integrated into a multistart method as a local search procedure that is repeatedly invoked to converge to different global and non-global optimal solutions starting from randomly generated points. To avoid repeated convergence to previously computed solutions, the concept of region of attraction of an optimizer is implemented. The performance of the new method is tested on benchmark problems. Its effectiveness is emphasized by a comparison with a well-known solver.Fundação para a Ciência e a Tecnologia (FCT

Improving efficiency of a multistart with interrupted Hooke-and-Jeeves filter search for solving MINLP problems

Publicado em: "Computational science and its applications – ICCSA 2016: 16th International Conference, Beijing, China, July 4-7, 2016, Proceedings, Part I". ISBN 978-3-319-42084-4This paper addresses the problem of solving mixed-integer nonlinear programming (MINLP) problems by a multistart strategy that invokes a derivative-free local search procedure based on a filter set methodology to handle nonlinear constraints. A new concept of componentwise normalized distance aiming to discard randomly generated points that are sufficiently close to other points already used to invoke the local search is analyzed. A variant of the Hooke-and-Jeeves filter algorithm for MINLP is proposed with the goal of interrupting the iterative process if the accepted iterate falls inside an -neighborhood of an already computed minimizer. Preliminary numerical results are included.FCT - Fundação para a Ciência e Tecnologia, within the projects UID/CEC/00319/2013 and UID/MAT/00013/2013.COMPETE: POCI-01- 0145-FEDER-00704

On optimizing a WWTP design using multi-objective approaches

In this paper, the multi-objective formulation of an optimization problem arising from an activated sludge (AS) system of a wastewater treatment plant (WWTP) design optimization is solved through a multi-objective genetic algorithm. Two multi-objective approaches are proposed. First, a solution to the WWTP design is provided, regardless of its location, date of construction or the involved unit operations. The variables that mostly influence the cost of the system define the objectives and are simultaneously optimized. Second, two crucial objectives for the correct operation of the AS system are simultaneously optimized: the investment and operation costs are minimized and the effluent quality is maximized. Since the objectives are conflicting, several trade-offs between objectives are obtained through the optimization process. The direct visualization of the trade-offs through Pareto curves assists the decision-maker in the selection of crucial design and operation variables. The numerical results show that the proposed methodology produces improved results with physical meaning when compared with previous work.Fundação para a Ciência e a Tecnologia (FCT

Multistart Hooke and Jeeves filter method for mixed variable optimization

AIP Conference Proceedings, vol. 1558In this study, we propose an extended version of the Hooke and Jeeves algorithm that uses a simple heuristic to handle integer and/or binary variables and a filter set methodology to handle constraints. This proposal is integrated into a multistart method as a local solver and it is repeatedly called in order to compute different optimal solutions. Then, the best of all stored optimal solutions is selected as the global optimum. The performance of the new method is tested on benchmark problems. Its effectiveness is emphasized by a comparison with other well-known stochastic solvers.Fundação para a Ciência e a Tecnologia (FCT

A hybrid genetic pattern search augmented Lagrangian method for constrained global optimization

Hybridization of genetic algorithms with local search approaches can enhance their performance in global optimization. Genetic algorithms, as most population based algorithms, require a considerable number of function evaluations. This may be an important drawback when the functions involved in the problem are computationally expensive as it occurs in most real world problems. Thus, in order to reduce the total number of function evaluations, local and global techniques may be combined. Moreover, the hybridization may provide a more effective trade-off between exploitation and exploration of the search space. In this study, we propose a new hybrid genetic algorithm based on a local pattern search that relies on an augmented Lagrangian function for constraint-handling. The local search strategy is used to improve the best approximation found by the genetic algorithm. Convergence to an $\varepsilon$-global minimizer is proved. Numerical results and comparisons with other stochastic algorithms using a set of benchmark constrained problems are provided.FEDER COMPETEFundação para a Ciência e a Tecnologia (FCT

An artificial fish swarm algorithm based hyperbolic augmented Lagrangian method

This paper aims to present a hyperbolic augmented Lagrangian (HAL) framework with guaranteed convergence to an ϵ-global minimizer of a constrained nonlinear optimization problem. The bound constrained subproblems that emerge at each iteration k of the framework are solved by an improved artificial fish swarm algorithm. Convergence to an ϵk-global minimizer of the HAL function is guaranteed with probability one, where ϵk→ϵ as k→∞. Preliminary numerical experiments show that the proposed paradigm compares favorably with other penalty-type methods.Fundação para a Ciência e a Tecnologia (FCT

On a hyperbolic augmented lagrangian artificial fish swarm based method: convergence issues

Fundação para a Ciência e a Tecnologia (FCT