Optimum design of reinforced concrete retaining walls with the flower pollination algorithm

The flower pollination algorithm (FPA) is anefficient metaheuristicoptimizationalgorithm mimickingthe pollinationprocessof flowering species. In this study, FPA is applied, for first time, to the optimum design of reinforced concrete (RC) cantilever retaining walls. It is foundthat FPA offers important savings with respect to conventional design approachesand that it outperformsgenetic algorithm (GA)andthe particle swarm optimization (PSO) algorithm in this designproblem.Furthermore, parameter tuning reveals that the best FPA performance is achieved for switch probability values ranging between 0.4 and 0.7, a population size of 20 individualsand aLévy flightstep sizescale factor of 0.5. Finally, parametric optimum designs show that theoptimumcost of RC retaining walls increases rapidly with the wallheight and smoothly with the magnitude of surcharge loadin

Projeto ótimo de amortecedores de massa usando evolução diferencial para reduzir a resposta dinâmica das estruturas sob cargas sísmicas

This paper introduces a methodology for the optimal design of passive Tuned Mass Dampers (TMDs) to control the dynamic response of buildings subjected to earthquake loads. The selection process of the optimal design parameters is carried out through a metaheuristic approach based on differential evolution (DE) which is a fast, efficient, and precise technique that does not require high computational efforts. The algorithm is aimed to reduce the maximum horizontal peak displacement of the structure and the root mean square (RMS) response of displacements as well. Furthermore, four more objective functions derived from multiple weighted linear combinations of the two previously mentioned parameters are also studied to obtain the most efficient TMD design configuration. A parallel process based on an exhaustive search (ES) with precision to 2 decimal positions is used to validate the optimization methodology based on DE. The proposed methodology is then applied to a 32-story case-study derived from an actual building structure and subjected to different ground acceleration registers. The best dynamic performance of the building is observed when the greatest weight is given to the RMS response of displacement in the optimization process. Finally, the numerical results reveal that the proposed methodology based on DE is effective in finding the optimal TMD design configuration by reducing the maximum floor displacement up to 4% and RMS values of displacement of up to 52% in the case-study building.Este artículo presenta una metodología para el diseño óptimo de Amortiguadores de Masa Sintonizada (AMS) para el control de la respuesta dinámica de edificios sometidos a cargas sísmicas. El proceso de selección de los parámetros óptimos de diseño se realiza mediante un enfoque metaheurístico basado en Evolución Diferencial (ED) la cual es una técnica rápida, eficiente y precisa que no requiere grandes esfuerzos computacionales. El algoritmo tiene como objetivo reducir el desplazamiento de pico horizontal máximo de la estructura y también la media cuadrática (Valor eficaz) de desplazamientos. Adicionalmente, se estudian otras cuatro funciones objetivo derivadas de múltiples combinaciones lineales ponderadas de los dos parámetros mencionados anteriormente para obtener la configuración de diseño del AMS más eficiente. De forma paralela, se utiliza un proceso basado en una búsqueda exhaustiva (ES) con precisión a 2 posiciones decimales para validar la metodología de optimización basada en DE. Posteriormente, la metodología propuesta se aplica a un caso de estudio derivado de un edificio real de 32 pisos sometido a diferentes registros sísmicos de aceleración del suelo. Se observa un mejor comportamiento dinámico del edificio cuando se le da el mayor peso a la respuesta RMS de desplazamiento en el proceso de optimización. Finalmente, los resultados numéricos revelan que la metodología propuesta basada en DE es efectiva para encontrar la configuración óptima de diseño de TMD al reducir el desplazamiento máximo del piso hasta en un 43% y los valores RMS de desplazamiento de hasta el 52% en el caso de estudio.Este artigo apresenta uma metodologia para a otimização de amortecedores de massa sintonizados (TMD) para o controle da resposta dinâmica de edifícios sujeitos a cargas sísmicas. O processo de seleção dos parâmetros ótimos é realizado mediante uma abordagem metaheurística baseada na Evolução Diferencial (DE) que é uma técnica rápida, eficiente e precisa que não requer de grandes esforços computacionais. O algoritmo visa reduzir o deslocamento máximo do pico horizontal da estrutura e também os deslocamentos da raiz quadrada média (RMS). Além disso, quatro outras funções objetivo derivadas de distintas combinações lineares ponderadas dos dois parâmetros de resposta já mencionados, são estudadas para obter a configuração de TMD mais eficiente. Em paralelo, um processo de busca exaustiva (ES) com precisão de 2 casas decimais é usado para validar a metodologia de otimização baseada na DE. Posteriormente, a metodologia proposta é aplicada a um caso de estudo derivado de um edifício real de 32 andares sujeito a diferentes registros de aceleração sísmica do solo. É observado um melhor comportamento dinâmico do edifício quando é dada uma maior ponderação no processo de otimização à resposta de deslocamento RMS. Finalmente, os resultados numéricos revelam que a metodologia proposta fundamentada na DE é eficaz para encontrar os parâmetros ótimos do TMD, reduzindo o pico de deslocamento máximo em até 43% e os valores de deslocamento RMS em até 52% no caso estudado

Flower pollination algorithm parameters tuning

The flower pollination algorithm (FPA) is a highly efficient metaheuristic optimization algorithm that is inspired by the pollination process of flowering species. FPA is characterised by simplicity in its formulation and high computational performance. Previous studies on FPA assume fixed parameter values based on empirical observations or experimental comparisons of limited scale and scope. In this study, a comprehensive effort is made to identify appropriate values of the FPA parameters that maximize its computational performance. To serve this goal, a simple non-iterative, single-stage sampling tuning method is employed, oriented towards practical applications of FPA. The tuning method is applied to the set of 28 functions specified in IEEE-CEC'13 for real-parameter single-objective optimization problems. It is found that the optimal FPA parameters depend significantly on the objective functions, the problem dimensions and affordable computational cost. Furthermore, it is found that the FPA parameters that minimize mean prediction errors do not always offer the most robust predictions. At the end of this study, recommendations are made for setting the optimal FPA parameters as a function of problem dimensions and affordable computational cost. [Abstract copyright: © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021.

Flower pollination algorithm with pollinator attraction

The Flower Pollination Algorithm (FPA) is a highly efficient optimization algorithm that is inspired by the evolution process of flowering plants. In the present study, a modified version of FPA is proposed accounting for an additional feature of flower pollination in nature that is the so-called pollinator attraction. Pollinator attraction represents the natural tendency of flower species to evolve in order to attract pollinators by using their colour, shape and scent as well as nutritious rewards. To reflect this evolution mechanism, the proposed FPA variant with Pollinator Attraction (FPAPA) provides fitter flowers of the population with higher probabilities of achieving pollen transfer via biotic pollination than other flowers. FPAPA is tested against a set of 28 benchmark mathematical functions, defined in IEEE-CEC’13 for real-parameter single-objective optimization problems, as well as structural optimization problems. Numerical experiments show that the modified FPA represents a statistically significant improvement upon the original FPA and that it can outperform other state-of-the-art optimization algorithms offering better and more robust optimal solutions. Additional research is suggested to combine FPAPA with other modified and hybridized versions of FPA to further increase its performance in challenging optimization problems

Surrogate-based optimum design of 3D reinforced concrete building frames to Eurocodes

The optimum structural design of real-world 3D concrete building frames to modern design standards is a complex and computationally expensive task. Hence, the use of surrogate-based optimization (SBO) methodologies must be investigated to reduce computational cost. The present study applies, for first time, a fully-fledged SBO algorithm to the optimum design of 3D concrete building frames. More particularly, the algorithm is applied to the minimum material cost design of a 4-storey and a 12-storey 3D RC building according to Eurocodes. It is found that the SBO algorithm can converge earlier than other well-established metaheuristic optimization algorithms reducing considerably the required computational effort. Nevertheless, it is likely to get trapped in local optima for large-scale RC frames. To overcome this drawback, a novel hybrid approach is also proposed herein that offers improved computational performance for large-scale concrete building frames

Passive, semi-active, active and hybrid mass dampers: A literature review with associated applications on building-like structures

In this paper, a state-of-the-art literature review is presented emphasising on the development of control variants for mass damper schemes on building-like structures. Additionally, a systematic literature review is conducted addressing three relevant questions: What type of mass damper is preferable by the associated industry? How are mass dampers distributed around the world? Is industry following research? Through the systematic literature review, updated lists of mass damper implementations and control algorithm applications in real-life structures were compiled. 208 case-studies are discussed in total. It is found that, 63% of them refer to passive tuned mass dampers, 31% to hybrid mass dampers, 4.0% to active mass dampers and only 2% to semi-active mass dampers. Regarding control algorithms, controllers of 24 structures driving semi-active, active or hybrid mass dampers are presented. It is concluded that the industry considerably lags behind latest structural control research both regarding implementations and overall management

Particle swarm optimization of friction tuned mass dampers subjected to ground motion records

Friction tuned mass dampers (FTMDs) are widely used to control the displacement of structures located in seismically active areas. Typically, the frequency and friction ratios of FTMDs are tuned up during design, but this task is complex if real ground motion records are considered. This article proposes a novel and accurate approach to calculate optimum parameters of FTMDs for controlling the displacements of both single degree of freedom (SDOF) systems and multi-story structural frames subjected to real ground motion records. In this study, the SDOF displacement and two FTMD parameters (frequency ratio and friction ratio) are first optimized simultaneously using a Particle Swarm Optimization (PSO) algorithm. A series of sensitivity analyses are then carried out to examine the effect of different structural features (damper movement, variations of optimized parameters and damping) on the optimized SDOF displacements and FTMD parameters given by the PSO. It is shown that, compared to a more established method available in the literature, the PSO algorithm reduces the SDOF displacements by an additional 21% on average. The PSO is then used to obtain optimum parameters of FTMDs and TMDs connected to four moment-resisting frames, and the results from the frames are compared to those from equivalent SDOF systems. This article contributes towards providing more suitable optimization tools for structures fitted with FTMDs, which in turn can lead to more efficient design methods for dampers

Amortiguadores de masa sintonizada: una revisión general

The loads generated by seismic events and strong winds are forces of nature that subject civil works to extreme situations, generally causing the failure of structures and in many cases, the loss of human lives. In order to face these forces of random character and difficult to predict, structural engineering proposes design and construction regulations that are mandatory in most countries of the world, which allow the structures to adequately resist the imposed forces. And as history has shown, sometimes a good design is not enough, so seismic-resistant engineering develops new methodologies and devices that help to further protect structures when they are subjected to actions such as earthquakes and winds. In order to face these challenges, mechanisms such as shock absorbers and controllers appear, grouped as passive, active, semi-active and hybrid devices, with innovative designs that greatly contribute to give greater safety and confidence to our civil works. This article presents a general overview of seismic dampers and controllers, their historical development, mechanical and analytical models, scopes, strengths and weaknessesLas cargas que generan los eventos sísmicos y los fuertes vientos son fuerzas de la naturaleza que someten a las obras civiles a situaciones extremas, lo que provoca eventualmente la falla de las estructuras y en muchas ocasiones, la pérdida de vidas humanas. Para enfrentar estas fuerzas de carácter aleatorio y de difícil predicción, la ingeniería estructural plantea normativas de diseño y construcción de obligatorio cumplimiento en la mayoría de los países del mundo, que permiten que las estructuras puedan resistir de manera adecuada las fuerzas impuestas. Y como la historia lo ha demostrado, algunas veces un buen diseño no es suficiente, por lo que la ingeniería sismoresistente desarrolla nuevas metodologías y dispositivos que ayuden a proteger aún más a las estructuras cuando se ven sometidas a acciones como los sismos y los vientos. Para afrontar estos retos, aparecen mecanismos como los amortiguadores y controladores, agrupados como dispositivos pasivos, activos, semiactivos e híbridos, con diseños innovadores que contribuyen en gran medida a dar mayor seguridad y confianza a nuestras obras civiles. En este artículo se presenta una visión general de los amortiguadores de masa sintonizada, su desarrollo histórico, modelos mecánicos y analíticos, alcances, fortalezas y debilidades. The loads generated by seismic events and strong winds are forces of nature that subject civil works to extreme situations, generally causing the failure of structures and in many cases, the loss of human lives. In order to face these forces of random character and difficult to predict, structural engineering proposes design and construction regulations that are mandatory in most countries of the world, which allow the structures to adequately resist the imposed forces. And as history has shown, sometimes a good design is not enough, so seismic-resistant engineering develops new methodologies and devices that help to further protect structures when they are subjected to actions such as earthquakes and winds. In order to face these challenges, mechanisms such as shock absorbers and controllers appear, grouped as passive, active, semi-active and hybrid devices, with innovative designs that greatly contribute to give greater safety and confidence to our civil works. This article presents a general overview of seismic dampers and controllers, their historical development, mechanical and analytical models, scopes, strengths and weaknesses

Applied Metaheuristic Computing

For decades, Applied Metaheuristic Computing (AMC) has been a prevailing optimization technique for tackling perplexing engineering and business problems, such as scheduling, routing, ordering, bin packing, assignment, facility layout planning, among others. This is partly because the classic exact methods are constrained with prior assumptions, and partly due to the heuristics being problem-dependent and lacking generalization. AMC, on the contrary, guides the course of low-level heuristics to search beyond the local optimality, which impairs the capability of traditional computation methods. This topic series has collected quality papers proposing cutting-edge methodology and innovative applications which drive the advances of AMC

Applied Methuerstic computing

For decades, Applied Metaheuristic Computing (AMC) has been a prevailing optimization technique for tackling perplexing engineering and business problems, such as scheduling, routing, ordering, bin packing, assignment, facility layout planning, among others. This is partly because the classic exact methods are constrained with prior assumptions, and partly due to the heuristics being problem-dependent and lacking generalization. AMC, on the contrary, guides the course of low-level heuristics to search beyond the local optimality, which impairs the capability of traditional computation methods. This topic series has collected quality papers proposing cutting-edge methodology and innovative applications which drive the advances of AMC