Improved teaching-learning-based optimization for estimation of temperature-dependent radiative properties of semitransparent media

Wei, Linyang; Qi, Hong; Li, Guojun; Zhang, Weijun

doi:10.1016/j.ijthermalsci.2020.106694

Cited by 21 publications

(2 citation statements)

References 40 publications

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“…They reported that this algorithm performed better than GA and TLBO applied by Khosravi et al 30 to optimize three design parameters and the annual operating cost of a 100 MW solar power tower system. Wei et al 29 reported that a forward and inverse method, when combined with the TLBO algorithm, can solve complex heat transfer problems. The researchers first computed coupled radiation-conduction heat transfer in a semitransparent medium using a forward method and then implemented TLBO and an inverse method to compute radiative properties.…”

Section: Introductionmentioning

confidence: 99%

“…Another widely used optimization technique in heat transfer-related research is the teaching-learning-based optimization algorithm (TLBO). ,− Rao and Patel implemented multiobjective TLBO for optimizing plate-fin and shell-tube types of heat exchangers, with annual operating cost as a design parameter. They reported that this algorithm performed better than GA and TLBO applied by Khosravi et al to optimize three design parameters and the annual operating cost of a 100 MW solar power tower system.…”

Section: Introductionmentioning

confidence: 99%

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Optimizing the Heat Loss from an Insulation Material and Boundary Layer Thickness of Airflow through a Hot Plate Using Nonlinear Least-Squares Error and Linear Programming Algorithms

Alrasheed

2023

ACS Omega

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Heat loss is a major challenge in heat transfer problems. Several researchers have minimized heat loss for different heat transfer cases, focusing on one optimization technique; however, not all optimization techniques are suitable for a given problem. A limited number of studies have compared different techniques for a given problem under boundary conditions and constraints. This review revisits basic heat transfer problems and identifies a promising technique for each problem to minimize heat loss. The paper considers three techniques: nonlinear least-squares error (LSE), interior point linear programming (IPLP), and genetic algorithm. Two cases are studied: 1. heat loss optimization from cylindrical insulating surfaces and 2. laminar airflow on a heated plate. The results are compared for each technique, and a suitable technique is recommended for each considered case. Nonlinear LSE is found to be most suitable for case 1. IPLP and GA are recommended for the Case 2 problem. The average thermal conductivity is found to be 0.081 W/mK. The average insulation thickness is found to be 213.25 mm. This research will act as a basis for future research to justify and implement suitable techniques for different heat transfer problems.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimizing the Heat Loss from an Insulation Material and Boundary Layer Thickness of Airflow through a Hot Plate Using Nonlinear Least-Squares Error and Linear Programming Algorithms

Alrasheed

2023

ACS Omega

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Supporting distributed energy resources with optimal placement and sizing of voltage regulators on the distribution system by an improved teaching‐learning‐based optimization algorithm

Taheri

Salles

Khan

2021

Int Trans Electr Energ Syst

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Summary The continuous increase of the distributed energy resources (DERs) penetration levels leads to voltage stability problems in the distribution system. One of the approaches for the mentioned emerging challenge is the proper placement of automatic voltage regulators (AVRs). This paper investigates the optimal placement and sizing of AVRs in a distribution network by presenting a new modification of the teaching‐learning‐based optimization (TLBO) algorithm. The objective functions consist of minimizing the distribution system voltage deviation, energy generation cost, and electrical losses. The modification improves the convergence velocity and accuracy of the TLBO algorithm using the combination of mutation technique and quasi‐opposition‐based‐learning concept. This paper compares the performance of the proposed algorithm with other famous evolutionary algorithms. The test distribution system contains installed DERs that work more efficiently after the placement of AVRs based on the mentioned objective functions by the proposed optimization algorithm. The simulation results display the best optimization algorithms for AVRs placement with a significant level of less than 0.10 (ie, probability‐value). The proposed multiobjective optimization algorithm's considerable merit is the accuracy and convergence velocity in solving this specific optimization problem.

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Two ımproved teaching–learning-based optimization algorithms for the solution of ınverse boundary design problems

et al. 2023

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Improved teaching-learning-based optimization for estimation of temperature-dependent radiative properties of semitransparent media

Cited by 21 publications

References 40 publications

Optimizing the Heat Loss from an Insulation Material and Boundary Layer Thickness of Airflow through a Hot Plate Using Nonlinear Least-Squares Error and Linear Programming Algorithms

Optimizing the Heat Loss from an Insulation Material and Boundary Layer Thickness of Airflow through a Hot Plate Using Nonlinear Least-Squares Error and Linear Programming Algorithms

Supporting distributed energy resources with optimal placement and sizing of voltage regulators on the distribution system by an improved teaching‐learning‐based optimization algorithm

Two ımproved teaching–learning-based optimization algorithms for the solution of ınverse boundary design problems

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