Achieves efficient structural optimization of plate structures while the design constraints are multiple frequency constraints. Reduces the computational cost of optimization by…
Abstract
Achieves efficient structural optimization of plate structures while the design constraints are multiple frequency constraints. Reduces the computational cost of optimization by approximating the frequencies using the Rayleigh quotient. Uses an optimality criteria method to solve each of the approximate problems. The creation of a high quality approximation is the key to the efficiency of the method. Also, with the great number of design variables, the optimality criteria methods are robust approaches. Thus the combination of approximation concepts and optimality criteria methods forms the basis of an efficient tool for optimum design of plate structures with frequency constraints. Presents examples and compares the results with previous work.
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Nima Gerami Seresht, Rodolfo Lourenzutti, Ahmad Salah and Aminah Robinson Fayek
Due to the increasing size and complexity of construction projects, construction engineering and management involves the coordination of many complex and dynamic processes and…
Abstract
Due to the increasing size and complexity of construction projects, construction engineering and management involves the coordination of many complex and dynamic processes and relies on the analysis of uncertain, imprecise and incomplete information, including subjective and linguistically expressed information. Various modelling and computing techniques have been used by construction researchers and applied to practical construction problems in order to overcome these challenges, including fuzzy hybrid techniques. Fuzzy hybrid techniques combine the human-like reasoning capabilities of fuzzy logic with the capabilities of other techniques, such as optimization, machine learning, multi-criteria decision-making (MCDM) and simulation, to capitalise on their strengths and overcome their limitations. Based on a review of construction literature, this chapter identifies the most common types of fuzzy hybrid techniques applied to construction problems and reviews selected papers in each category of fuzzy hybrid technique to illustrate their capabilities for addressing construction challenges. Finally, this chapter discusses areas for future development of fuzzy hybrid techniques that will increase their capabilities for solving construction-related problems. The contributions of this chapter are threefold: (1) the limitations of some standard techniques for solving construction problems are discussed, as are the ways that fuzzy methods have been hybridized with these techniques in order to address their limitations; (2) a review of existing applications of fuzzy hybrid techniques in construction is provided in order to illustrate the capabilities of these techniques for solving a variety of construction problems and (3) potential improvements in each category of fuzzy hybrid technique in construction are provided, as areas for future research.
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Ting Zhou, Yingjie Wei, Jian Niu and Yuxin Jie
Metaheuristic algorithms based on biology, evolutionary theory and physical principles, have been widely developed for complex global optimization. This paper aims to present a…
Abstract
Purpose
Metaheuristic algorithms based on biology, evolutionary theory and physical principles, have been widely developed for complex global optimization. This paper aims to present a new hybrid optimization algorithm that combines the characteristics of biogeography-based optimization (BBO), invasive weed optimization (IWO) and genetic algorithms (GAs).
Design/methodology/approach
The significant difference between the new algorithm and original optimizers is a periodic selection scheme for offspring. The selection criterion is a function of cyclic discharge and the fitness of populations. It differs from traditional optimization methods where the elite always gains advantages. With this method, fitter populations may still be rejected, while poorer ones might be likely retained. The selection scheme is applied to help escape from local optima and maintain solution diversity.
Findings
The efficiency of the proposed method is tested on 13 high-dimensional, nonlinear benchmark functions and a homogenous slope stability problem. The results of the benchmark function show that the new method performs well in terms of accuracy and solution diversity. The algorithm converges with a magnitude of 10-4, compared to 102 in BBO and 10-2 in IWO. In the slope stability problem, the safety factor acquired by the analogy of slope erosion (ASE) is closer to the recommended value.
Originality/value
This paper introduces a periodic selection strategy and constructs a hybrid optimizer, which enhances the global exploration capacity of metaheuristic algorithms.
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Jamiu Adetayo Dauda, Suraj A. Rahmon, Ibrahim A. Tijani, Fouad Mohammad and Wakeel O. Okegbenro
The purpose of this study is to find the optimum design of Reinforced Concrete (RC) pile foundation to enable efficient use of structural concrete with greater consequences for…
Abstract
Purpose
The purpose of this study is to find the optimum design of Reinforced Concrete (RC) pile foundation to enable efficient use of structural concrete with greater consequences for global environment and economy.
Design/methodology/approach
A non-linear optimisation technique based on the Generalised Reduced Gradient (GRG) algorithm was implemented to find the minimum cost of RC pile foundation in frictional soil. This was achieved by obtaining the optimum pile satisfying the serviceability and ultimate limit state requirements of BS 8004 and EC 7. The formulated structural optimisation procedure was applied to a case study project to assess the efficiency of the proposed design formulation.
Findings
The results prove that the GRG method in Excel solver is an active, fast, accurate and efficient computer programme to obtain optimum pile design. The application of the optimisation for the case study project shows up to 26% cost reduction compared to the conventional design.
Research limitations/implications
The design and formulation of design constraints will be limited to provisions of BS 8004 and EC 7.
Practical implications
Since the minimum quantity of concrete was attained through optimisation, then minimum cement will be used and thus result in minimum CO2 emission. Therefore, the optimum design of concrete structures is a vital solution to limit the damage to the Earth's climate and the physical environment resulting from high carbon emissions.
Originality/value
The current study considers the incorporation of different soil ground parameters in the optimisation process rather than assuming any pile capacity value for the optimisation process.
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Abdalhakem Alkhadashi, Fouad Mohammad, Rasheedah Olamide Zubayr, Hynda Aoun Klalib and Piotr Balik
The optimality objectives are the structure weight and embodied energy as well as calculating the cost and embodied carbon of the resulting optimum options. Three optimality…
Abstract
Purpose
The optimality objectives are the structure weight and embodied energy as well as calculating the cost and embodied carbon of the resulting optimum options. Three optimality algorithms developed in MATLAB, namely, genetic algorithms (GA), particle swarm optimisation (PSO) and harmony search algorithm (HSA), were used for structural optimisation to compare the effectiveness of the algorithms. Two life-cycle stages were considered, production and construction stages, which include three boundaries: materials, transportation and erection. In the formulation of the optimum design problem, 107 universal steel beams (UKB) and 64 columns (UKC) sections were considered for the discrete design variables. The imposed behavioural constraints in the optimum design process were set according to the provision of Eurocode 3 (EC3). The study aims to find the optimum solution of 2D steel frames whilst considering weight and embodied energy, investigate the performance of the analysis integrated with MATLAB and provide three examples to which all these are applied to.
Design/methodology/approach
Undoubtedly, in structural engineering, the best design of any structure aims at the most economical and environmental option, without impairing the functional and its structural integrity. In the paper, multi-objective stochastic search methods are proposed for optimum design of three two-dimensional multi-story frames.
Findings
Results showed that the optimised designs obtained by HSA are better than those found by the GA and PSO with an average difference of 16% from GA and PSO, where this difference increases at larger frame structures. It was, therefore, concluded that the integration of the analysis, design and optimisation methods employed in MATLAB can be effective in obtaining prompt optimum results during the decision-making stage.
Research limitations/implications
There may be some possible limitations in the study. Due to the time constraints, only three meta-heuristic approaches were investigated, where more methods should be investigated to fully understand their effectiveness in multi-objective problems.
Originality/value
Investigating the performance of three optimisation methods in multi-objective problems developed in MATLAB. More importantly, developing optimisation models for evaluation of embodied energy, embodied carbon and cost for steel structures to assist designers, during the initial stages, to evaluate design decisions against their energy consumption and carbon impacts.
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C. Angulo, E. Garcia Vadillo and J. Canales
In this paper an application of structural optimization to the design ofstructures with constraints in frequency and mode shape is presented. Theobjective is to obtain an optimum…
Abstract
In this paper an application of structural optimization to the design of structures with constraints in frequency and mode shape is presented. The objective is to obtain an optimum design making adequate changes in the structure to modify its dynamic characteristics. The method is based on an iterative process of optimization that includes structural analysis by the Finite Element Method (FEM), sensitivity analysis, and optimization techniques. An efficient and accurate method is used to calculate the sensitivities of the dynamic behaviour of the structure. The sensitivity analysis is accomplished using a semi‐analytical procedure based on the Nelson method. A Sequential Linear Programming (SLP) algorithm is used to solve the optimization problem. In the minimization process the convergence is assured even in a short number of iterations. The validation of the method is also shown by means of two examples of application.
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A. Kaveh and M. Shahrouzi
The generality of the genetic search in the light of proper coding schemes, together with its non‐gradient‐based search, has made it popular for many discrete problems including…
Abstract
Purpose
The generality of the genetic search in the light of proper coding schemes, together with its non‐gradient‐based search, has made it popular for many discrete problems including structural optimization. However, the required computational effort increases as the cardinality of the search space and the number of design variables increase. Memetic algorithms are formal attempts to reduce such a drawback for real‐world problems incorporating some kind of problem‐specific information. This paper aims to address this issue.
Design/methodology/approach
In this paper both Lamarckian and Baldwinian approaches for meme evolution are implemented using the power of graph theory in topology assessment. For this purpose, the concept of load path connectivity in frame bracing layouts is introduced and utilized by the proposed graph theoretical algorithms. As an additional search refinement tool, a dynamic mutation band control is recommended. In each case, the results are studied via a set of ultimate design family rather than one pseudo optimum. The method is further tested using a number of steel frame examples and its efficiency is compared with conventional genetic search.
Findings
Here, the problem of bracing layout optimization in steel frames is studied utilizing a number of topological guidelines.
Originality/value
The method of this paper attempts to reduce the computational effort for optimal design of real‐world problems incorporating some kind of problem‐specific information.
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Faisal Mehraj Wani, Jayaprakash Vemuri and Rajaram Chenna
Near-fault pulse-like ground motions have distinct and very severe effects on reinforced concrete (RC) structures. However, there is a paucity of recorded data from Near-Fault…
Abstract
Purpose
Near-fault pulse-like ground motions have distinct and very severe effects on reinforced concrete (RC) structures. However, there is a paucity of recorded data from Near-Fault Ground Motions (NFGMs), and thus forecasting the dynamic seismic response of structures, using conventional techniques, under such intense ground motions has remained a challenge.
Design/methodology/approach
The present study utilizes a 2D finite element model of an RC structure subjected to near-fault pulse-like ground motions with a focus on the storey drift ratio (SDR) as the key demand parameter. Five machine learning classifiers (MLCs), namely decision tree, k-nearest neighbor, random forest, support vector machine and Naïve Bayes classifier , were evaluated to classify the damage states of the RC structure.
Findings
The results such as confusion matrix, accuracy and mean square error indicate that the Naïve Bayes classifier model outperforms other MLCs with 80.0% accuracy. Furthermore, three MLC models with accuracy greater than 75% were trained using a voting classifier to enhance the performance score of the models. Finally, a sensitivity analysis was performed to evaluate the model's resilience and dependability.
Originality/value
The objective of the current study is to predict the nonlinear storey drift demand for low-rise RC structures using machine learning techniques, instead of labor-intensive nonlinear dynamic analysis.
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This study aims to discuss the simultaneous longitudinal and lateral flight control of the octorotor, a rotary wing unmanned aerial vehicle (UAV), for the first time under the…
Abstract
Purpose
This study aims to discuss the simultaneous longitudinal and lateral flight control of the octorotor, a rotary wing unmanned aerial vehicle (UAV), for the first time under the effect of morphing and to improve autonomous flight performance.
Design/methodology/approach
This study aims to design and control the octorotor flight control system with stochastic optimal tuning under morphnig effect. For this purpose, models of different arm lengths of the octorotor were drawn in the Solidworks program. The morphing was carried out by simultaneously lengthening or shortening the arm lengths of the octorotor. The morphing rate was estimated by using simultaneous perturbation stochastic approximation (SPSA). The stochastic gradient descent algorithm, which is frequently used in machine learning, was used to estimate the changing moments of inertia with the change of arm lengths. The proportional integral derivative (PID) controller has been preferred as an octorotor control algorithm because of its simplicity of structure. The PID gains required to control both longitudinal and lateral flight were also estimated with SPSA.
Findings
With SPSA, three longitudinal flight PID gains, three lateral flight PID gains and one morphing ratio were estimated. PID gains remained within the limits set for SPSA, giving satisfactory results. In addition, the cost index created was 93% successful. The gradient descent algorithm used for the moment of inertia estimation achieved the optimum result in 1,570 iterations. However, in the simulations made with the obtained data, longitudinal and lateral flight was successfully carried out.
Originality/value
Octorotor longitudinal and lateral flight control was performed quickly and effectively with the proposed method. In addition, the desired parameters were obtained with the optimization methods used, and the longitudinal and lateral flight of the octorotor was successfully carried out in the desired trajectory.
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Mehmet Eren Uz, Pezhman Sharafi, Mahya Askarian, Weiqing Fu and Chunmei Zhang
The preliminary layout design of structures impacts upon the entire design process and, consequently, the total cost. The purpose of this paper is to select the most economical…
Abstract
Purpose
The preliminary layout design of structures impacts upon the entire design process and, consequently, the total cost. The purpose of this paper is to select the most economical layouts that satisfy structural and architectural requirements, while considering the reciprocal effects of cost factors and layout variables at the preliminary stages of design.
Design/methodology/approach
This paper presents an automated method for cost optimization of geometric layout design of multi-span reinforced concrete (RC) beams subjected to dynamic loading by using the charged system search (CSS) algorithm. First, a novel cost optimization approach for geometric layout problems is introduced, in which both cost parameters and dynamic responses are considered in the preliminary layout design of beams. The proposed structural optimization problem with constraints on the static and dynamic equilibrium, architectural dimensions and structural action effects is solved using the CSS algorithm.
Findings
The proposed CSS algorithm for solving the cost optimization problem can be easily used for optimizing the span lengths and is also capable of working with various cost functions. The presented examples show that the proposed algorithm using the new cost optimization function provides satisfactory results and can result in over 7 per cent cost saving.
Originality/value
This is an original paper proposing a novel methodology for preliminary layout design of concrete beams.