Structural optimization in steel structures, algorithms and applications

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Hybrid harmony search for sustainable design of post-tensioned concrete box-girder pedestrian bridges

This paper aims to find sustainable designs of post-tensioned concrete box-girder pedestrian bridges. A hybrid harmony search algorithm combining threshold optimization is used to find the geometry and the materials for which the sum of the costs or the emissions are the lowest, yet satisfying the requirements for structural safety and durability. An experimental design method was used to adjust the algorithm parameters. The parametric study was applied to three-span deck bridges ranging from 90 m to 130 m. The findings indicated that both objectives lead to similar cost results. However, the variables presented some differences. Such deviations suggested greater depths, more strands and a lower concrete strength for CO2 target functions. Carbonation captured less than 1% of the deck emissions over 100 years. This methodology leads to a precise analysis of the practical rules to achieve an environmental design approach.This research was financially supported by the Spanish Ministry of Science and Innovation (Research Project BIA2011-23602).García Segura, T.; Yepes Piqueras, V.; Alcalá González, J.; Pérez López, E. (2015). Hybrid harmony search for sustainable design of post-tensioned concrete box-girder pedestrian bridges. Engineering Structures. 92:112-122. https://doi.org/10.1016/j.engstruct.2015.03.015S1121229

Interactive Optimisation in Marine Propeller Design

Marine propeller design is a complex engineering problem that depends on the collaboration of several scientific disciplines. During the design process, the blade designers need to consider contradicting requirements and come up with one optimal propeller design as a solution to the specific problem. This solution is usually the trade-o between the stakeholders\u27 requirements and the objectives and constraints of the problem.The significant amount of design variables related to blade design problems requires a systematic search in a large design space. Automated optimisation has been utilised for a number of blade design applications, as it has the advantage of creating a large set of design alternatives in a short period of time. However, automated optimisation has failed to be used in industrial applications, due to its complex set-up and the fact that in more complex scenarios the majority of the non-dominated design alternatives are infeasible. This necessitates a way of enabling the blade designers to interact with the algorithm during the optimisation process.The purpose of this thesis is to develop a methodology that supports the blade designers during the design process and to enable them to interact with the design tools and assess design characteristics during the optimisation. The overall aim is to improve the design performance and speed. According to the proposed methodology, blade designers are called during intermediate stages of the optimisation to provide information about the designs, and then this information is input in the algorithm. The goal is to steer the optimisation to an area of the design space with feasible Pareto designs, based on the designer\u27s preference. Since there are objectives and constraints that cannot be quantified with the available computational tools, keeping the "human in the loop" is essential, as a means to obtain feasible designs and quickly eliminate designs that are impractical or unrealistic.The results of this research suggest that through the proposed methodology the designers have more control over the whole optimisation procedure and they obtain detailed Pareto frontiers that involve designs that are characterised by high performance and follow the user preference

Parametric design and optimization of arched trusses under vertical and horizontal multi-load cases

This dissertation faces the problem of the optimum design of steel truss arches subject to multiple load cases. Arches are one of the most ancient shape-resistant structures, widely used in both civil engineering and architecture. For instance, arches can be considered as purely compressed structures, provided that their “line of thrust” coincides with the centre line of the arch. The “line of thrust” is the locus of the points of application of the thrusts (internal forces or stress resultants) that must be contained within the cross-section of the arch in such a way that the arch transfers loads to the foundations through axial compressive stresses only. As a matter of fact, the more the “line of thrust” differs from the centre line of the arch, the larger the unfavourable bending moments that arise in the arch. This is the reason why it is fundamental to pay close attention to the choice of the shape for an arch in order to minimize (or avoid when it is possible) unfavourable bending effects. Several analytical, graphical and physical methods are provided to find the optimal shape of a monolithic (single rib) arch subjected to a certain load case (i.e. the “funicular curve” for that load). However, if multiple load cases must be considered, it is not possible to find a proper optimal shape for an arch with single rib. In this case, the choice of truss arches with at least two chords becomes indispensable. Indeed, it has been demonstrated that structural optimization of in-plane truss arches with two chords subjected to a single load case leads to optimal solutions in which upper and lower chords tend to coincide with each other and with the “funicular curve” (i.e. the “line of thrust”) for that load. In light of the above, simultaneous shape and size optimization of steel truss arches with two arched chords linked each other through a bracing system (with variable Pratt-type pattern) has been performed for multiple load cases and different structural boundary conditions. Truss arches are effectively used in arch bridges, especially when the arch span exceeds 200 meters (five out of the six steel arch bridges with a span over 500 m are truss arch bridges). For this purpose, a hybrid optimization routine integrating a parametric definition of the design problem, a metaheuristic optimization algorithm and a code for Finite Element Analysis (FEA) has been developed through a MATLAB program. The proposed optimization method allows to simultaneously optimize a larger set of design variables, notwithstanding their large number and various nature (topology, shape and size, as well as continuous and discrete variables, have been concurrently considered). Third-degree Rational Bézier Curves have been chosen to optimize the shape of the arch chords because they can represent a wide family of curves (including conic curves), depending on a small number of parameters. In so doing, in-plane truss arches with different span lengths and structural boundary conditions have been optimized for multiple load cases, only considering vertical loads (acting on the same plane as the arch), since in-plane arches are not suited to withstand out-of-plane loads. On the other hand, spatial arched trusses with two arched chords lying on different planes have been optimally designed for multiple loadings acting in different directions. In particular, a steel arched truss with a lower arched chord variably inclined in the 3D-space and a horizontal upper arched chord linked each other through a bracing system has been designed and optimized for three vertical load cases and a horizontal seismic action parallel to the upper chord plane. Thus, analysing the obtained results, useful suggestions for steel truss arch design have been deduced and presented in this dissertation

Behavior of concrete-filled pvc tube columns under axial load

A concrete-filled tube (CFT) column system offers numerous advantages due to its large axial stiffness and capacity. In the system, steel is a common type of material and has been widely used. However, the application of FRP and PVC came into the picture as the alternative to the steel application in the system. In this study, the concrete-filled PVC tube (CF-PVCT) columns subjected to axial load were considered in both experimental and numerical analysis. The PVC tube is a low-maintenance material and locally available in abundance. The investigation on such columns was carried out to study their potential and the success of such columns would be a milestone achievement in the local construction industry. The study involved parameters such as variable lengths, diameters, and thicknesses of the PVC tube as well as various concrete strengths for the concrete infill. A total of 110 columns which included CFPVCT, CF-PVCT confined with plain PVC socket, hollow PVC column and concrete columns were tested under axial load. From the experimental results, the CF-PVCT columns failed in shear, outward buckling, sudden explosive as well as PVC tube rupture and most of the columns experienced sudden failure. The CF-PVCT columns have a higher capacity of around 32% to 98% compared to the unconfined concrete columns; however, the CF-PVCT columns confined by plain PVC sockets achieved more capacity (23% to 54%) than the CF-PVCT columns. The increase of the thickness and diameter of PVC tube led to a good increase in ultimate strength and the corresponding strain of the CF-PVCT columns. The displacement at ultimate load decreased as the concrete strength increased while it increase as the thickness of tube and slenderness ratio increased. The increase of the slenderness ratio led to decrease the ultimate strengths and the axial strain of CF-PVCT columns. A simulation using finite element software ANSYS v14.5 was conducted to validate the experimental work. Three empirical equations to predict the ultimate strength for CF-PVCT columns by using three approaches were proposed according to ACI 318-08. Finite element analysis by ANSYS indicated similar behaviour in terms of axial displacement and mode of failure. The empirical equations proposed in this study showed good agreement with the experimental values. The approach using PSO could predict the ultimate load of CF-PVCT column with higher accuracy

Optimal seismic retrofitting of existing RC frames through soft-computing approaches

2016 - 2017Ph.D. Thesis proposes a Soft-Computing approach capable of supporting the engineer judgement in the selection and design of the cheapest solution for seismic retrofitting of existing RC framed structure. Chapter 1 points out the need for strengthening the existing buildings as one of the main way of decreasing economic and life losses as direct consequences of earthquake disasters. Moreover, it proposes a wide, but not-exhaustive, list of the most frequently observed deficiencies contributing to the vulnerability of concrete buildings. Chapter 2 collects the state of practice on seismic analysis methods for the assessment the safety of the existing buildings within the framework of a performancebased design. The most common approaches for modeling the material plasticity in the frame non-linear analysis are also reviewed. Chapter 3 presents a wide state of practice on the retrofitting strategies, intended as preventive measures aimed at mitigating the effect of a future earthquake by a) decreasing the seismic hazard demands; b) improving the dynamic characteristics supplied to the existing building. The chapter presents also a list of retrofitting systems, intended as technical interventions commonly classified into local intervention (also known “member-level” techniques) and global intervention (also called “structure-level” techniques) that might be used in synergistic combination to achieve the adopted strategy. In particular, the available approaches and the common criteria, respectively for selecting an optimum retrofit strategy and an optimal system are discussed. Chapter 4 highlights the usefulness of the Soft-Computing methods as efficient tools for providing “objective” answer in reasonable time for complex situation governed by approximation and imprecision. In particular, Chapter 4 collects the applications found in the scientific literature for Fuzzy Logic, Artificial Neural Network and Evolutionary Computing in the fields of structural and earthquake engineering with a taxonomic classification of the problems in modeling, simulation and optimization. Chapter 5 “translates” the search for the cheapest retrofitting system into a constrained optimization problem. To this end, the chapter includes a formulation of a novel procedure that assembles a numerical model for seismic assessment of framed structures within a Soft-Computing-driven optimization algorithm capable to minimize the objective function defined as the total initial cost of intervention. The main components required to assemble the procedure are described in the chapter: the optimization algorithm (Genetic Algorithm); the simulation framework (OpenSees); and the software environment (Matlab). Chapter 6 describes step-by-step the flow-chart of the proposed procedure and it focuses on the main implementation aspects and working details, ranging from a clever initialization of the population of candidate solutions up to a proposal of tuning procedure for the genetic parameters. Chapter 7 discusses numerical examples, where the Soft-Computing procedure is applied to the model of multi-storey RC frames obtained through simulated design. A total of fifteen “scenarios” are studied in order to assess its “robustness” to changes in input data. Finally, Chapter 8, on the base of the outcomes observed, summarizes the capabilities of the proposed procedure, yet highlighting its “limitations” at the current state of development. Some possible modifications are discussed to enhance its efficiency and completeness. [edited by author]XVI n.s

Graph-based reinforcement learning for discrete cross-section optimization of planar steel frames

A combined method of graph embedding (GE) and reinforcement learning (RL) is developed for discrete cross-section optimization of planar steel frames, in which the section size of each member is selected from a prescribed list of standard sections. The RL agent aims to minimize the total structural volume under various practical constraints. GE is a method for extracting features from data with irregular connectivity. While most of the existing GE methods aim at extracting node features, an improved GE formulation is developed for extracting features of edges associated with members in this study. Owing to the proposed GE operations, the agent is capable of grasping the structural property of columns and beams considering their connectivity in a frame with an arbitrary size as feature vectors of the same size. Using the feature vectors, the agent is trained to estimate the accurate return associated with each action and to take proper actions on which members to reduce or increase their size using an RL algorithm. The applicability of the proposed method is versatile because various frames different in the numbers of nodes and members can be used for both training and application phases. In the numerical examples, the trained agents outperform a particle swarm optimization method as a benchmark in terms of both computational cost and design quality for cross-sectional design changes; the agents successfully assign reasonable cross-sections considering the geometry, connectivity, and support and load conditions of the frames

Marine propeller optimisation tools for scenario-based design

The marine propulsion system is one of the most important components of a ship in order to cover the demanding operating needs of propulsion nowadays and to increase performance in a wide range of operating conditions. Marine propellers are designed with the purpose of matching the hull and machinery system, create the required thrust for the entire operational profile, and fulfil the techno-economical requirements that depend on the decision-making of several stakeholders. The final product must represent a unique propeller, designed for a specific vessel, and is a trade-off between all requirements. In an industrial framework, the marine propeller design process should therefore be straightforward and well-developed. The limited time under which the design process must be performed, plays a decisive role in the methods utilised to carry it out, as for example in the selection of the analysis tools, which must be fast and they usually involve semi-empirical evaluations. Since blade design is a multi-objective and multidisciplinary problem, automated optimisation has been used with the aim to search good solutions in the design space efficiently. However, automated optimisation has failed to be used in industrial applications due to obtaining solutions with high performance but with infeasible geometries, and as a method it proved to be inferior to the manual design process, something that shows the importance of the designer\u27s expertise. The main research question of this thesis is therefore related to incorporating optimisation in a systematic way in order to improve the propeller design process and assist the blade designers to obtain feasible and high-performing propellers in strict time constraints. A methodology is proposed that combines interactive optimisation with machine learning and in parallel new objectives are implemented for more complex scenarios. The designer is enabled to manually evaluate cavitation nuisance during the optimisation and guide the algorithm towards areas of the design space with satisfactory cavitation characteristics. Several scenario-based situations have been investigated by using the proposed methodology, that involve different propeller types, design and off-design conditions, several objectives and constraints, cavitation nuisance on the suction and the pressure side of the blade, and applications within conventional and wind propulsion. The results have shown that by involving the blade designer\u27s expertise in the design and optimisation process systematically, competitive propeller designs with feasible geometries can be obtained efficiently

Evolutionary Computation

This book presents several recent advances on Evolutionary Computation, specially evolution-based optimization methods and hybrid algorithms for several applications, from optimization and learning to pattern recognition and bioinformatics. This book also presents new algorithms based on several analogies and metafores, where one of them is based on philosophy, specifically on the philosophy of praxis and dialectics. In this book it is also presented interesting applications on bioinformatics, specially the use of particle swarms to discover gene expression patterns in DNA microarrays. Therefore, this book features representative work on the field of evolutionary computation and applied sciences. The intended audience is graduate, undergraduate, researchers, and anyone who wishes to become familiar with the latest research work on this field