Inverse Geometry Design of Radiative Enclosures Using Particle Swarm Optimization Algorithms

Qi, Hong; Sun, Shaofang; He, Zhen-Zong; Ruan, Shi-Ting; Li-MingRuan,; Tan, He-Ping

doi:10.5772/62351

Cited by 3 publications

(4 citation statements)

References 34 publications

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“…The analogy between the LG algorithm and DIA is presented in Table 3. Based on the work of Nhleko and Musingwini [11] and Qi et al [15], the generic PSO algorithm was adapted for the optimisation of the stope layout as applied in the DIA. Figure 2 illustrates a schematic mapping of the PSO parameters to the DIA parameters.…”

Section: Dual Interchange Algorithm Anatomymentioning

confidence: 99%

Optimisation of Three-Dimensional Stope Layouts Using a Dual Interchange Algorithm for Improved Value Creation

Nhleko

Musingwini

2022

Minerals

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Optimisation of three-dimensional (3D) underground stope layouts is a computationally complex process since it involves the modelling of many variables and constraints. As the number of variables and constraints increases to reflect the actual mining practice, the model complexity and solution time tend to increase exponentially, making the optimisation problem intractable. Metaheuristic approaches have therefore been used predominantly to solve the problem, but do not guarantee ‘true’ optimality. To minimise this limitation, a dual interchange algorithm (DIA) was developed by combining the strengths of two metaheuristic generic algorithms, namely the particle swarm optimisation (PSO) and genetic algorithm (GA). The DIA performance was compared to that of the Mineable Shape Optimizer (MSO) on four different design scenarios. The DIA generated stope layout economic values (SLEV) for three scenarios which were 0.3%, 3.4%, and 8.3% higher than for MSO under fixed and variable stope width conditions, while MSO produced a SLEV which was 9.7% higher than the DIA for a fixed stope width. This paper demonstrates that the DIA is a novel way of solving 3D optimisation of stope layouts under variable stope widths as encountered in actual mining practice.

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Section: Dual Interchange Algorithm Anatomymentioning

confidence: 99%

Optimisation of Three-Dimensional Stope Layouts Using a Dual Interchange Algorithm for Improved Value Creation

Nhleko

Musingwini

2022

Minerals

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“…Since the subproblem (17) is an approximation of the original optimization task (16), it is possible that no feasible solution can be achieved by solving the subproblem (17) even though there is feasible solution in the original problem (16). If the approximation is failed, the following QP subproblem is considered:…”

Section: Sequential Quadratic Programming Algorithmmentioning

confidence: 99%

“…For 9 instance, Sarvari applied genetic algorithm (GA) to determine the optimal shape of a 2D radiative enclosure to produce a desired heat flux 11 distribution on the specified design surface. Farahmand et al used particle swarm optimization (PSO) algorithm to design the geometry of a 2D radiative enclosure to create the desired temperature and heat flux distributions, and PSO algorithm achieved higher accuracy than GA. Qi 15,16 et al employed PSO and krill herd (KH) algorithms to optimize the geometry of a 2D complex radiative enclosure, through which uniform distributions of radiative heat flux on the design surface were obtained. conjugate gradient regularization, and simulated annealing in solving inverse design problems.…”

Section: Introductionmentioning

confidence: 99%

Geometric Optimization of Radiative Enclosures Using Sequential Quadratic Programming Algorithm

Sun¹

2019

ES Energy Environ.

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The sequential quadratic programming (SQP) algorithm is introduced to optimize the geometry of radiative enclosures filled with participating medium. The design goal is to produce a uniform distribution of radiative heat flux on the pre-specified surface of a 2D radiative enclosure. The direct problem involves radiative heat transfer in the participating medium is solved by the discrete ordinate method in a body-fitted coordinate system. The inverse design task is formulated as an optimization problem. The SQP algorithm is applied to optimize the spatial positions of control points, and the Akima interpolation technique is employed to approximate the geometry of the design surface. The effects of radiative properties of participating medium, the number of control points, and temperature of heating surface on the optimization results are investigated. Retrieval results show that the design goal can be successfully satisfied using the SQP algorithm, and the present methodology is proved to be more efficient than other optimization techniques.

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“…Various inverse problems have been solved by stochastic algorithms. For example, Qi et al [19][20][21] used particle swarm optimization (PSO) algorithm to identify the physical parameters of participating medium and optimize the geometric shape of radiative enclosure. Li et al [22] applied ant colony optimization (ACO) algorithm to determine the heat source position by solving IHTPs.…”

Section: Introductionmentioning

confidence: 99%

An efficient inverse approach for reconstructing time- and space-dependent heat flux of participating medium*

2020

Self Cite

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The decentralized fuzzy inference method (DFIM) is employed as an optimization technique to reconstruct time- and space-dependent heat flux of two-dimensional (2D) participating medium. The forward coupled radiative and conductive heat transfer problem is solved by a combination of finite volume method and discrete ordinate method. The reconstruction task is formulated as an inverse problem, and the DFIM is used to reconstruct the unknown heat flux. No prior information on the heat flux distribution is required for the inverse analysis. All retrieval results illustrate that the time- and space-dependent heat flux of participating medium can be exactly recovered by the DFIM. The present method is proved to be more efficient and accurate than other optimization techniques. The effects of heat flux form, initial guess, medium property, and measurement error on reconstruction results are investigated. Simulated results indicate that the DFIM is robust to reconstruct different kinds of heat fluxes even with noisy data.

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Inverse Geometry Design of Radiative Enclosures Using Particle Swarm Optimization Algorithms

Cited by 3 publications

References 34 publications

Optimisation of Three-Dimensional Stope Layouts Using a Dual Interchange Algorithm for Improved Value Creation

Optimisation of Three-Dimensional Stope Layouts Using a Dual Interchange Algorithm for Improved Value Creation

Geometric Optimization of Radiative Enclosures Using Sequential Quadratic Programming Algorithm

An efficient inverse approach for reconstructing time- and space-dependent heat flux of participating medium*

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