Multi-objective optimization method for nuclear reactor radiation shielding design based on PSO algorithm

Wu, Xing; Yang, Yinping; Han, Song; Zhao, Zelong; Peng, Fang; Gao, Qingyu

doi:10.1016/j.anucene.2021.108404

Cited by 29 publications

(7 citation statements)

References 32 publications

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“…w is the inertia weight factor. In the algorithm, the inertia weight factor is usually set as a constant [64]. When calculated in this way, the particle cannot vary the inertia weight according to the current position in the optimization process, and cannot balance the local and global optimization ability of the particle [65].…”

Section: Expert Decision Model Of Ipso Algorithmmentioning

confidence: 99%

Dynamic Quality Monitoring System to Assess the Quality of Asphalt Concrete Pavement

Zhang

Philbin

et al. 2021

Buildings

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With the rapid development of new technologies, such as big data, the Internet of Things (IoT) and intelligent sensing, the traditional asphalt pavement construction quality evaluation method has been unable to meet the needs of road digital construction. At the same time, the development of such technologies enables a new management system for asphalt pavement construction. In this study, firstly, the dynamic quality monitoring system of asphalt concrete pavement is established by adopting the BeiDou Navigation Satellite System, intelligent sensing, the IoT and 5G technology. This allows key technical indicators to be collected and transmitted for the whole process of asphalt mixture, which includes the mixing plant, transport vehicle, paving and compaction. Secondly, combined with AHP and the entropy weight (EW) method, the index combination weight is calculated. The comprehensive index for the pavement digital construction quality index (PCQ) is proposed to reflect the impact of monitoring indicators on pavement quality. An expert decision-making model is formed by using the improved particle swarm optimization (PSO) algorithm coupled with radial basis function neural network (RBF). Finally, the digital monitoring index and pavement performance index are connected to establish a full-time and multi-dimensional digital construction quality evaluation model. This study is verified by a database created from the digital monitoring data of pavement construction collected from a highway construction project. The system proposed in this study can accurately reflect the quality of pavement digital construction and solve the lag problem existing in the feedback of construction site.

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Section: Expert Decision Model Of Ipso Algorithmmentioning

confidence: 99%

Dynamic Quality Monitoring System to Assess the Quality of Asphalt Concrete Pavement

Zhang

Philbin

et al. 2021

Buildings

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show abstract

“… [ 61 ] Radiation shielding design GA The multi-objective optimization design method can be used to find a better scheme more comprehensively. [ 70 ] Radiation shielding design MACNOS Able to seek for the shielding design that minimizes the total weight by changing the thickness and the material of the shield with constraints satisfied [ 71 ] Mass attenuation coefficient prediction for shielding material ANN A high determination coefficient of 1 and a root mean square error of 0.0033 [ 72 ] Radiation shielding design BPNN and GA Significantly reducing the computational cost of shielding structure design optimization for marine reactors [ 73 ] Radiation shielding design PSO An automatic optimization program was developed and proved effective on marine reactors [ 74 ] …”

Section: Introductionmentioning

confidence: 99%

A review of the application of artificial intelligence to nuclear reactors: Where we are and what's next

Huang

Peng

Deng

et al. 2023

Heliyon

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“…Furthermore, as the common multi-objective optimization algorithms, both particle swarm optimization (PSO) and genetic algorithms (GA) have the property of searching for the best solution from a large number of solutions. For instance, PSO is applied to perform validation calculations on optimization schemes [24], conduct the multi-objective optimization of equipment capacity and operation [25] and solve the extended travelling salesman problem [26]. GA is applied to assess system reliability [27], estimate energy plant size [28] and determine optimal operating parameters [29].…”

Section: Introductionmentioning

confidence: 99%

An Investment Decision-Making Approach for Power Grid Projects: A Multi-Objective Optimization Model

Gao

2022

Energies

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With the reform of the power system in China, investments in power grid projects across the whole power system are increasing. However, there are various objectives to achieve in the investment decision processes of power grid projects, so the rational investments of a grid project can be seen as a multi-objective optimization problem. Meanwhile, these issues have rarely been studied at home and abroad, and this paper will fill this gap. As a result, this study critically analyzed the application of a multi-objective optimization model to power grid investment. Firstly, the objective factors of grid investments were explored, which were quantified through quantitative methods. Secondly, based on the characteristics of power grid investment, a multi-objective optimization model was established, and the assumptions and constraints of the model were presented. Finally, NSGA-II was used for solving the multi-objective optimization model. The results show that: (1) Multi-objective optimization models are suitable for the study of and deriving solutions for power grid investment by establishing suitable objective functions, assumptions and constraints, (2) According to the conventional steps of NSGA-II, suitable steps can be established to search for an optimal solution to the objective set of a power grid investment and (3) Due to the different concerns of different project scenarios, Pareto frontier solutions can be selected as the practical references of power grid projects. Therefore, the solution set makes the implementation scheme more flexible.

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Multi-objective optimization method for nuclear reactor radiation shielding design based on PSO algorithm

Cited by 29 publications

References 32 publications

Dynamic Quality Monitoring System to Assess the Quality of Asphalt Concrete Pavement

Dynamic Quality Monitoring System to Assess the Quality of Asphalt Concrete Pavement

A review of the application of artificial intelligence to nuclear reactors: Where we are and what's next

An Investment Decision-Making Approach for Power Grid Projects: A Multi-Objective Optimization Model

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