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Article
Publication date: 10 August 2018

Nebojsa B. Raicevic, Slavoljub R. Aleksic, Željko Hederic, Marinko Barukcic and Ilona Iatcheva

The purpose of this paper is to present a new calculation method for increasing the shielded volume in which the external electromagnetic field is maximally reduced. In a…

Abstract

Purpose

The purpose of this paper is to present a new calculation method for increasing the shielded volume in which the external electromagnetic field is maximally reduced. In a space shielded in the way mentioned in this paper, it is possible to introduce measurement instruments and increase the accuracy of results obtained with them, as well as reduce the risk of unwanted electrostatic field influence on living organisms.

Design/methodology/approach

A new numerical procedure for the optimization of the coaxial ring conductor system for electrostatic shielding is developed in the paper. The optimization of the functional that consists of electrostatic energy density and a system of equations derived from the equipotential character of the conductor system is used. The system of nonlinear equations is obtained and then numerically solved by minimizing this functional. The first presented optimization procedure is based on the analytical optimization method using the Lagrange coefficients and gradient of the objective function.

Findings

It is possible to design a large number of protective ring formations. Applying the differential evolution optimization method, an optimal arrangement can be obtained for any specific number of rings. The differential evolution optimization method, which belongs to the class of evolutionary algorithms, is used for solving this very complex optimization problem. In combination with the above-mentioned method, excellent results in the elimination of the external electric field have been obtained. Although a larger number of rings provides more efficient protection, this number is limited from the economic point of view. Therefore, it is necessary to achieve a compromise between the number of rings, the size of volume shielded and the quality of protection.

Research limitations/implications

There are few papers that address this problem, although the elimination of the influence of the external electromagnetic field has gained more importance lately. The presented method can be applied to increase the reliability of measured data, protection of the environment, in space research, etc. The main limiting factor for using a larger number of rings that provide better protection is the economical one.

Originality/value

The proposed method is suitable for the generalization of procedures, for the protection of the space where the external electric field needs to be reduced or eliminated.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 37 no. 4
Type: Research Article
ISSN: 0332-1649

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Article
Publication date: 31 January 2020

Nebojsa B. Raicevic, Slavoljub R. Aleksic, Ilona Iatcheva and Marinko Barukcic

This paper aims to present a new approach to the numerical solution of skin effect integral equations in cylindrical conductors. An approximate, but very simple and…

Abstract

Purpose

This paper aims to present a new approach to the numerical solution of skin effect integral equations in cylindrical conductors. An approximate, but very simple and accurate method for calculating the current density distribution, skin-effect resistance and inductance, in pulse regime of cylindrical conductor, having a circular or rectangular cross-section, is considered. The differential evolution method is applied for minimization of error functional. Because of its application in the practice, the lightning impulse is observed. Direct and inverse fast Fourier transform is applied.

Design/methodology/approach

This method contributes to increasing of correctness and much faster convergence. As the electromagnetic field components depend on the current density derivation, the proposed method gives a very accurate solution not only for current density distribution and resistance but also for field components and for internal inductance coefficients. Distribution of current and electromagnetic field in bus-bars can be successfully determined if the proximity effect is included together with the skin effect in calculations.

Findings

The study shows the strong influence of direct lightning strikes on the distribution of electrical current in cables used in lightning protection systems. The current impulse causes an increase in the current density at all points of the cross-section of the conductor, and in particular the skin effect on the external periphery. Based on the data calculated by using the proposed method, it is possible to calculate the minimum dimensions of the conductors to prevent system failures.

Research limitations/implications

There are a number of approximations of lightning strike impulse in the literature. This is a limiting factor that affects the reliability and agreement between measured data with calculated values.

Originality/value

In contrast with other methods, the current density function is approximated by finite functional series, which automatically satisfy wave equation and existing boundary conditions. It is necessary to minimize the functional. This approach leads to a very accurate solution, even in the case when only two terms in current approximation are adopted.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering , vol. 39 no. 3
Type: Research Article
ISSN: 0332-1649

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Article
Publication date: 24 July 2007

J. Smirnova, L. Silva, B. Monasse, J‐M. Haudin and J‐L. Chenot

This paper sets out to show the feasibility of the genetic algorithm inverse method for the determination of the parameters of crystallization kinetics laws in isothermal…

Abstract

Purpose

This paper sets out to show the feasibility of the genetic algorithm inverse method for the determination of the parameters of crystallization kinetics laws in isothermal and non‐isothermal conditions, using multiple experiments.

Design/methodology/approach

The mathematical model for crystallization kinetics determination and the numerical methods of its resolution are introduced. Crystallization kinetic parameters determined by approximate physical analysis and the inverse genetic algorithm method are presented. Injection molding simulations taking into account crystallization are performed using the finite element method.

Findings

It is necessary to perform the optimization on two parameters, transformed volume fraction and number of spherulites to obtain correct results. It is possible to use results from different samples, in spite of the dispersion of some values.

Research limitations/implications

Experimental data for isothermal and non‐isothermal conditions were used and obtained good results for the parameters of crystallization kinetics laws from which the evolutions of overall crystallization kinetics and crystalline microstructure were deduced. Nevertheless, the dispersion of the experimental data concerning the number of spherulites obtained with different samples is important. The evolution of the number of spherulites is required for the optimization to get correct results.

Practical implications

An important result of this work is that the genetic algorithm optimization can be applied to this problem where the experiments cannot be performed with a single sample and the experimental data for the number of spherulites have low precision. Even if only the crystallization kinetics was considered, the feasibility in molding simulation has been shown.

Originality/value

Simulation of crystallization in injection molding is very important for a later prediction of the end‐use properties.

Details

Engineering Computations, vol. 24 no. 5
Type: Research Article
ISSN: 0264-4401

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Article
Publication date: 16 April 2018

Marina Tsili, Eleftherios I. Amoiralis, Jean Vianei Leite, Sinvaldo R. Moreno and Leandro dos Santos Coelho

Real-world applications in engineering and other fields usually involve simultaneous optimization of multiple objectives, which are generally non-commensurable and…

Abstract

Purpose

Real-world applications in engineering and other fields usually involve simultaneous optimization of multiple objectives, which are generally non-commensurable and conflicting with each other. This paper aims to treat the transformer design optimization (TDO) as a multiobjective problem (MOP), to minimize the manufacturing cost and the total owing cost, taking into consideration design constraints.

Design/methodology/approach

To deal with this optimization problem, a new method is proposed that combines the unrestricted population-size evolutionary multiobjective optimization algorithm (UPS-EMOA) with differential evolution, also applying lognormal distribution for tuning the scale factor and the beta distribution to adjust the crossover rate (UPS-DELFBC). The proposed UPS-DELFBC is useful to maintain the adequate diversity in the population and avoid the premature convergence during the generational cycle. Numerical results using UPS-DELFBC applied to the transform design optimization of 160, 400 and 630 kVA are promising in terms of spacing and convergence criteria.

Findings

Numerical results using UPS-DELFBC applied to the transform design optimization of 160, 400 and 630 kVA are promising in terms of spacing and convergence criteria.

Originality/value

This paper develops a promising UPS-DELFBC approach to solve MOPs. The TDO problems for three different transformer specifications, with 160, 400 and 630 kVA, have been addressed in this paper. Optimization results show the potential and efficiency of the UPS-DELFBC to solve multiobjective TDO and to produce multiple Pareto solutions.

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Article
Publication date: 29 July 2014

Xiaohua Yang, Chongli Di, Ying Mei, Yu-Qi Li and Jian-Qiang Li

The purpose of this paper is to reduce the computational burden and improve the precision of the parameter optimization in the convection-diffusion equation, a new…

Abstract

Purpose

The purpose of this paper is to reduce the computational burden and improve the precision of the parameter optimization in the convection-diffusion equation, a new algorithm, the refined gray-encoded evolution algorithm (RGEA), is proposed.

Design/methodology/approach

In the new algorithm, the differential evolution algorithm (DEA) is introduced to refine the solutions and to improve the search efficiency in the evolution process; the rapid cycle operation is also introduced to accelerate the convergence rate. The authors apply this algorithm to parameter optimization in convection-diffusion equations.

Findings

Two cases for parameter optimization in convection-diffusion equations are studied by using the new algorithm. The results indicate that the sum of absolute errors by the RGEA decreases from 74.14 to 99.29 percent and from 99.32 to 99.98 percent, respectively, compared to those by the gray-encoded genetic algorithm (GGA) and the DEA. And the RGEA has a faster convergent speed than does the GGA or DEA.

Research limitations/implications

A more complete convergence analysis of the method is under investigation. The authors will also explore the possibility of adapting the method to identify the initial condition and boundary condition in high-dimension convection-diffusion equations.

Practical implications

This paper will have an important impact on the applications of the parameter optimization in the field of environmental flow analysis.

Social implications

This paper will have an important significance for a sustainable social development.

Originality/value

The authors establish a new RGEA algorithm for parameter optimization in solving convection-diffusion equations. The application results make a valuable contribution to the parameter optimization in the field of environmental flow analysis.

Details

International Journal of Numerical Methods for Heat & Fluid Flow, vol. 24 no. 6
Type: Research Article
ISSN: 0961-5539

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Article
Publication date: 30 September 2014

Gai-Ge Wang, Amir Hossein Gandomi, Xin-She Yang and Amir Hossein Alavi

Meta-heuristic algorithms are efficient in achieving the optimal solution for engineering problems. Hybridization of different algorithms may enhance the quality of the…

Abstract

Purpose

Meta-heuristic algorithms are efficient in achieving the optimal solution for engineering problems. Hybridization of different algorithms may enhance the quality of the solutions and improve the efficiency of the algorithms. The purpose of this paper is to propose a novel, robust hybrid meta-heuristic optimization approach by adding differential evolution (DE) mutation operator to the accelerated particle swarm optimization (APSO) algorithm to solve numerical optimization problems.

Design/methodology/approach

The improvement includes the addition of DE mutation operator to the APSO updating equations so as to speed up convergence.

Findings

A new optimization method is proposed by introducing DE-type mutation into APSO, and the hybrid algorithm is called differential evolution accelerated particle swarm optimization (DPSO). The difference between DPSO and APSO is that the mutation operator is employed to fine-tune the newly generated solution for each particle, rather than random walks used in APSO.

Originality/value

A novel hybrid method is proposed and used to optimize 51 functions. It is compared with other methods to show its effectiveness. The effect of the DPSO parameters on convergence and performance is also studied and analyzed by detailed parameter sensitivity studies.

Details

Engineering Computations, vol. 31 no. 7
Type: Research Article
ISSN: 0264-4401

Keywords

Content available
Article
Publication date: 9 July 2021

Jianran Liu, Bing Liang and Wen Ji

Artificial intelligence is gradually penetrating into human society. In the network era, the interaction between human and artificial intelligence, even between artificial…

Abstract

Purpose

Artificial intelligence is gradually penetrating into human society. In the network era, the interaction between human and artificial intelligence, even between artificial intelligence, becomes more and more complex. Therefore, it is necessary to describe and intervene the evolution of crowd intelligence network dynamically. This paper aims to detect the abnormal agents at the early stage of intelligent evolution.

Design/methodology/approach

In this paper, differential evolution (DE) and K-means clustering are used to detect the crowd intelligence with abnormal evolutionary trend.

Findings

This study abstracts the evolution process of crowd intelligence into the solution process of DE and use K-means clustering to identify individuals who are not conducive to evolution in the early stage of intelligent evolution.

Practical implications

Experiments show that the method we proposed are able to find out individual intelligence without evolutionary trend as early as possible, even in the complex crowd intelligent interactive environment of practical application. As a result, it can avoid the waste of time and computing resources.

Originality/value

In this paper, DE and K-means clustering are combined to analyze the evolution of crowd intelligent interaction.

Details

International Journal of Crowd Science, vol. 5 no. 2
Type: Research Article
ISSN: 2398-7294

Keywords

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Article
Publication date: 1 February 2006

Hui‐Yuan Fan, Jouni Lampinen and Yeshayahou Levy

To present and validate a new differential evolution (DE) method for multi‐objective optimization method.

Abstract

Purpose

To present and validate a new differential evolution (DE) method for multi‐objective optimization method.

Design/methodology/approach

A new selection scheme was designed to replace the existing one in DE to enable DE applicable to either single objective or multi‐objective optimizations.

Findings

The new method was validated with three simple multi‐objective optimization problems. The simulation results show that the approach is capable of generating an approximated Pareto‐front for each selected problem. The new DE method was used to optimize a prototype air mixer subject to two objective functions to be minimized. The results demonstrate that the new DE approach can handle this practical multi‐objective problem successfully.

Originality/value

The new method is an easy‐to‐implement evolutionary method and has the potential for application for any complicated engineering optimizations.

Details

Engineering Computations, vol. 23 no. 2
Type: Research Article
ISSN: 0264-4401

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Article
Publication date: 1 April 2005

B.V. Babu, Pallavi G. Chakole and J.H. Syed Mubeen

This paper presents the application of Differential Evolution (DE), an evolutionary computation technique for the optimal design of gas transmission network. As a gas…

Abstract

This paper presents the application of Differential Evolution (DE), an evolutionary computation technique for the optimal design of gas transmission network. As a gas transmission system includes source of gas, delivery sites with pipeline segments and compressors, the design of efficient and economical network involves lot of parameters. In addition, there are many equality and inequality constraints to be satisfied making the problem highly non‐linear. Hence an efficient strategy is needed in searching for the global optimum. In this study, DE has been successfully applied for optimal design of gas transmission network. The results obtained are compared with those of nonlinear programming technique and branch and bound algorithm. DE is able to find an optimal solution with a cost that is less than reported in the earlier literature. The proposed strategy takes less computational time to converge when compared to the existing techniques without compromising with the accuracy of the parameter estimates.

Details

Multidiscipline Modeling in Materials and Structures, vol. 1 no. 4
Type: Research Article
ISSN: 1573-6105

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Book part
Publication date: 5 October 2018

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…

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.

Details

Fuzzy Hybrid Computing in Construction Engineering and Management
Type: Book
ISBN: 978-1-78743-868-2

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