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Multi-objective optimization for joint actuator and sensor placement for guided waves based structural health monitoring using fibre Bragg grating sensors

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ULTRASONICS 2022年 119卷 106605-106605页

作者： Soman, Rohan Polish Acad Sci Inst Fluid Flow Machinery Fiszera 14 PL-80231 Gdansk Poland

Structural Health Monitoring (SHM) systems have a potential to reduce lifecycle costs of structures. As a result, there is a lot of active research in the area for SHM of civil and mechanical structures. Guided waves (GW) based SHM techniques allow monitoring of large plate-like structures with a few sensors and have been identified as the most promising of techniques for SHM. Fibre Bragg grating (FBG) sensors due to their low weight, and ability to be multiplexed have been long thought to be ideal sensors for SHM. The recent development of the edge filtering approach has increased their sensitivity to GW sensing and made them ideal sensors. Unfortunately the FBG sensors are passive sensors and show directional sensitivity. These operational constraints make extension of the earlier developed GW based SHM techniques for FBG sensors difficult. Recently the authors developed a technique for damage detection specifically designed for a network with FBG sensors. This paper builds on the past work by the authors and develops a methodology for a design of an actuator-sensor (AS) network for improving the damage assessment capability of the previously proposed method. The paper develops a multi objective optimization technique for the joint optimization of actuator and sensor placement for a network with FBG sensors. The joint optimization of the actuators and sensors is necessary due to the passive nature of the FBG sensors and also incorporates the directional nature of the FBG sensors. The paper develops an integer encoded nsga-ii for the optimization of the AS network. The objectives for the optimization are derived from the specific damage detection technique tailored for the use of FBG sensors. The objective are: coverage with at least 2 AS pairs, coverage with at least 1 edge reflected path and the cost of the deployed network. The results indicate that the encoding of the objectives of the optimization is valid and indeed the damage detection capabilities of the AS

关键词： Guide waves (GW) Optimization Actuator FBG sensors nsga-ii algorithm Multiobjective optimization

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RSDM-AHSnet: Designing a robust stochastic dynamic model to allocating health service network under disturbance situations with limited capacity using algorithms nsga-ii and PSO

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COMPUTERS IN BIOLOGY AND MEDICINE 2022年 147卷 105649-105649页

作者： Attari, Mahdi Yousefi Nejad Ahmadi, Mohsen Ala, Ali Moghadamnia, Elham Islamic Azad Univ Dept Ind Engn Bonab Branch Bonab Iran Urmia Univ Technol Dept Ind Engn Orumiyeh Iran Shanghai Jiao Tong Univ Dept Ind Engn & Management Shanghai Peoples R China Islamic Azad Univ Fac Management Dept Technol Management Sci & Res Branch Tehran Iran

In the present study, health services networks were classified into low-level hospitals (provision of public health services) and high-level hospitals (providing specialized health services), which are at risk of being disrupted. They refer the patients to high-level hospitals for inpatient visits or emergencies by ambulance. In the present case, patients are divided into two categories: high priority (the category in which immediate service delivery is needed) and low priority. A stochastic robust dynamic mathematical model for location and allocation of health network regarding limited capacity and disturbance is developed to reduce the total costs and include the basic features of a real problem such as limited capacity. Regarding limited capacity for hospitals, the health network needs redefinition of different layers in the disturbance situation. In this study, we reduce the total costs by reducing hospital costs and costs such as transportation and service to patients. Two metaheuristic algorithms consisting of Non-dominated Sorting Genetic algorithm ii (nsga-ii) and Particle Swarm Optimization (PSO) have been applied to solve the model. Taguchi method design minimizes the cost of parameter tuning, including the level of factors related to the proposed. The results showed the method's applicability for large-scale problems that could evaluate different tools for decision-makers to select effective management strategies in constructing a dependable and robust healthcare network. For example, the total cost is minimized in conditions considered in the genetic algorithm, the population parameter at the highest level, 150, the intersection parameters, and the probability of mutation at the lowest level, 0.7 and 0.1.

关键词： Healthcare network location Robust stochastic model Limited capacity nsga-ii algorithm Particle swarm optimization And disruption

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Aerodynamic Shape Optimization of a Square Cylinder with Multi-Parameter Corner Recession Modifications

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ATMOSPHERE 2022年第11期13卷 1782-1782页

作者： Wang, Zhaoyong Zheng, Chaorong Mulyanto, Joshua Adriel Wu, Yue Harbin Inst Technol Sch Civil Engn Harbin 150090 Peoples R China Harbin Inst Technol Minist Educ Key Lab Struct Dynam Behav & Control Harbin 150090 Peoples R China

Corner modifications can reduce wind loads acting on supertall buildings and modify the corresponding flow structures. The present study investigated the aerodynamic shape optimization of the corner recession square cylinders with multiple geometric parameters in a large design space via the GA-GRNN surrogate model updating-based multi-objective optimization framework. Six typical optimal aerodynamic shape sections M1 similar to M6 were selected from the Pareto optimal front, and the effects of multiple geometric parameters of these sections on the aerodynamic performance and flow field were analyzed. The results showed that the present multi-objective optimization framework can significantly reduce the computational load and time cost, and significantly improve the optimization efficiency in solving complex engineering problems. The optimal corner recession sections can obviously reduce the mean drag coefficient C-D and root mean square lift coefficient C-sigma L while significantly increasing the Strouhal number St of the square cylinder, and it is concluded that the aerodynamic shape optimization can significantly improve the aerodynamic performance of square-sectional supertall buildings. When compared with the benchmark section, the C-D and C-sigma L of the optimal section M1 can be reduced up to 45.7% and 84.5%, respectively. Based on the analysis of the flow structures around the optimal sections, the flow mechanism can be attributed to the fact that the corner recession modifications postpone the flow separation, and deflect the separated shear layer towards the side surfaces and suppress the development of vortex shedding in the wake, which leads to significant elongation of the wake length and reduction of the width of the recirculation region. The proposed multi-objective optimization framework in this study can provide an important reference for the aerodynamic shape optimization of building structures and relevant studies.

关键词： aerodynamic shape optimization square cylinder corner recession modification GA-GRNN surrogate model nsga-ii algorithm wind load flow mechanism

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Efficient power analysis and five-objective optimization for a simple endoreversible closed Brayton cycle

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CASE STUDIES IN THERMAL ENGINEERING 2022年 39卷

作者： Qiu, Xingfu Chen, Lingen Ge, Yanlin Gong, Qirui Feng, Huijun Inst Thermal Sci & Power Engn Wuhan Inst Technol Wuhan 430205 Peoples R China Hubei Prov Engn Technol Res Ctr Green Chem Equipme Wuhan 430205 Peoples R China Wuhan Inst Technol Sch Mech & Elect Engn Wuhan 430205 Peoples R China

Based on a simple endoreversible closed Brayton cycle model established in the previous litera-ture, this paper performs thermodynamic analyses and multi-objective optimizations by applying finite-time thermodynamics and nsga-ii. Cycle efficient power expression of the cycle is derived and analyzed. Heat exchanger heat conductance distribution and cycle pressure ratio are used as optimization variables, and cycle power output, ecological function, thermal efficiency, power density and efficient power are taken as optimization goals. The results obtained with LINMAP, TOPSIS and Shannon Entropy decision-making methods used in five-objective optimization are compared with those of five single-objective optimizations. The results show that efficiency at the maximum efficient power is higher than that at the maximum power;there are an optimal values of heat conductance distribution and pressure ratio make efficient power reaches the maximum;in the five-objective optimization, deviation indices with LINMAP, TOPSIS and Shannon Entropy decision-making methods are 0.2443, 0.2443 and 0.2400, respectively, deviation index with Shannon Entropy approach is the smallest, and the result is closer to ideal scheme;while the deviation indices for five single-objective optimizations with power, efficiency, ecological func-tion, power density and efficient power are 0.4111, 0.6750, 0.2651, 0.2443 and 0.2400, respectively.

关键词： Endoreversible closed brayton cycle Optimal pressure ratio Optimal heat conductivity distribution Multi -objective optimization nsga-ii algorithm Finite -time thermodynamics

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Modeling and optimization of the thermal-hydraulic performance of direct contact heat exchanger using quasi-opposite Jaya algorithm

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INTERNATIONAL JOURNAL OF THERMAL SCIENCES 2022年 173卷

作者： Li, Biao Li, Zexi Yang, Puyi Xu, Jianxin Wang, Hua Kunming Univ Sci & Technol Engn Res Ctr Met Energy Conservat & Emiss Reduct Minist Educ Kunming 650093 Yunnan Peoples R China Kunming Univ Sci & Technol Natl Joint Engn Res Ctr Energy Saving & Environm Kunming 650093 Yunnan Peoples R China Kunming Univ Sci & Technol Faulty Met & Energy Engn Kunming 650093 Yunnan Peoples R China Florida Inst Technol Dept Mech & Civil Engn Melbourne FL 32901 USA Kunming Univ Sci & Technol Faulty Management & Econ Kunming 650093 Yunnan Peoples R China

In this study, the thermal-hydraulic performance of a direct contact heat exchanger (DCHE) was explored and optimized by applying the multi-objective quasi-opposite Jaya (MOQO-Jaya) algorithm. Inlet temperature of the continuous phase, continuous phase flow rate, dispersed phase flow rate, evaporator height, nozzle diameter, and number of jets were considered as the design variables for the optimization. The optimization functions were the volumetric heat transfer coefficient (VHTC), entransy dissipation, and entropy production. Study results indicated that the entransy dissipation and entropy production were negatively correlated with the heat transfer capacity in a DCHE, with a Pearson correlation coefficient above 0.96;that is, the smaller the entransy dissipation and entropy production, the better the heat transfer performance in the DCHE. The sensitivity of design parameters demonstrated that temperature played an important role. The optimization results and performance of the MOQO-Jaya algorithm were compared with those of the non-dominated sorting genetic algorithm (nsgaii). The convergence of MOQO-Jaya was 2.24 times quicker than that of nsga-ii in DCHE optimization. The correctness of numerical model for optimizing the DCHE was verified through experiments. The errors of the experimental and algorithm optimizations both were within +/- 10%. Results demonstrated that after multiobjective optimization, the VHTC increased by 33.89% and entransy dissipation reduced by 44%, compared with those of traditional experiments.

关键词： Direct contact heat transfer MOQO-Jaya algorithm nsga-ii algorithm Multi-objective optimization Entransy dissipation

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Optimization of falling film thermosyphons bundle arrangement for large-scale cooling applications by genetic algorithm

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APPLIED THERMAL ENGINEERING 2020年 169卷 114892-000页

作者： Zhong, Wei Cao, Xiaoling Yuan, Yanping Southwest Jiaotong Univ Sch Mech Engn Chengdu 610031 Peoples R China

Two-phase traditional thermosyphons (TTS) are passive heat exchangers with low thermal resistance for heat transfer. An advanced thermosyphon system named falling film thermosyphon (FFTS) is developed and introduced in this paper, which eliminates several limits of TTS and improves heat transfer performance. FFTS applications are preferred for large-scale heat transfer applications. In this work, a tube bank of FFTS modules is integrated into a power plant to condense water vapor of the flue gas. Axial- and cross- flow are both analyzed with inline and staggered arrangements. The numerical simulation of vapor condensation in the flue gas is developed, and the results are compared to previously published experimental data. The accuracy of model is validated. The Non-dominated Sorting Genetic algorithm, version 2 (nsga-ii) is implemented to improve the thermal performance with low material consumption and pressure drop for tube banks. Several parameters of the configuration are optimized. As a result, smaller diameter tubes with longer length can gain better heat transfer performance, however, resulting in a higher pressure drop. The optimized arrangements can improve 60-70% condensation rate and reduce up to 80% material consumption with allowable pressure loss compared to a baseline geometry.

关键词： Thermosyphon Heat transfer Condensation nsga-ii algorithm Tube bank

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A quantitative model and solution of reaction heat for microfluidic chips based on Kriging and nsga-ii

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THERMOCHIMICA ACTA 2020年 694卷 178803-178803页

作者： Gan, Yi Yang, Minghao Sun, FuJia Yang, Lihong Univ Shanghai Sci & Technol Sch Mech Engn Shanghai Peoples R China Chuo Univ Fac Sci & Engn Tokyo Japan

Microfluidic chips have been widely used in microfluidic calorimeters. The thermoelectric power can be obtained by measuring the laminar flow peak value of the reaction liquid. Due to heat dissipation and heat inhomogeneity, thermodynamic parameters can not accurately describe the thermal state and thermal properties. With the inlet velocity and velocity ratio in Y-channel as the two key parameters affecting the peak value of thermoelectric power, the reaction heat governing equation is established. The Kriging method is used to establish the reaction heat quantification model and Nondominated Sorting Genetic algorithm (nsga-ii) is used in global optimization. Then, the Pareto solution set of optimal inlet velocity and optimal velocity ratio is obtained. Finally, the established reaction heat governing model was experimentally verified;The predicted values of the Kriging quantitative model were consistent with the experimental results;The three sets of Pareto solutions can accurately describe the thermal state and thermal properties.

关键词： nsga-ii algorithm Kriging (KRG) model Microfluidic chip Chemical reaction heat Multi-objective optimization

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Multi-objective optimization of rolling schedule for tandem cold strip rolling based on nsga-ii

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JOURNAL OF MANUFACTURING PROCESSES 2020年 60卷 257-267页

作者： Wang, Yu Li, Changsheng Jin, Xin Xiang, Yongguang Li, Xiaogang Northeastern Univ State Key Lab Rolling & Automat Shenyang 110819 Peoples R China HBIS Grp Tangsteel Co Tangshan 063012 Peoples R China

A multi-objective optimization model of rolling schedule based on nsga-ii algorithm was presented, and three objective functions are defined as motor power balance, good flatness and preventing slippage. The experimental results show the excellent performance of nsga-ii in obtaining non-dominated front which could suggest several alternative solutions to rolling schedule in a single run of the algorithm. Additionally, considering that the rolling load distribution strategy dynamically adjusts are required to balance the impact of roll surface condition changes on the rolling process, a model of weighted-sum approach with variable weight coefficients based on rolling length was proposed. In this model, a roll change cycle was divided into four optimization stages which are given different weight coefficients. Moreover, a smooth correction model of weight coefficient was proposed to ensure the quality of strip flatness. Compared to the traditional weighted-sum approach, the presented model on the basis of variable weight coefficients can make full use of Pareto set, and has better adaptability to changing rolling conditions. Finally, the proposed model was applied to the multi-objective optimization model above, the results showed that the final optimal solutions have better performance in almost all objective dimensions than the empirical one. The practical application has further confirmed the effectiveness of the multi objective optimization for rolling schedule.

关键词： Tandem cold rolling Rolling schedule Multi-objective optimization Smooth correction model nsga-ii algorithm

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A multi-objective emergency vehicle scheduling optimisation model

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INTERNATIONAL JOURNAL OF SENSOR NETWORKS 2020年第4期34卷 236-243页

作者： Yao, Jiao Shao, Chuwei Xia, Xiaomei Wang, Pincheng Wei, Yu Wang, Jin Univ Shanghai Sci & Technol Business Sch 334 Jungong Rd Shanghai Peoples R China Changsha Univ Sci & Technol Sch Comp & Commun Engn 960 South Rd Wangjiali Changsha 410114 Peoples R China

Various types of emergencies incidents occur frequently, which may cause casualties and huge economic losses. How to optimise the scheduling of emergency rescue vehicles and improve their rescue efficiency is of great significance. Based on the analysis of its influencing factors the emergency vehicle scheduling optimisation model was firstly established, which was oriented to achieve three objects, minimising total travel time, total cost of dispatching travel, and maximising the path reliability. Moreover, the model was solved by Non-dominated Sorting Genetic algorithm with elite strategy (nsga-ii algorithm). Finally, the local road network in Huangpu District, Shanghai, China was taken as to verify the model in this study. The results show that the optimal solution of the model can achieve the optimal total travel time, and total travel cost and path reliability of the scheduling scheme can also satisfy requirements, which means good validity and practicability.

关键词： emergency vehicle scheduling optimisation model multi-objective planning nsga-ii algorithm effectiveness coefficient comprehensive evaluation method influencing factors travel time cost of scheduling path reliability

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A scheduling optimization method for maintenance, repair and operations service resources of complex products

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JOURNAL OF INTELLIGENT MANUFACTURING 2020年第7期31卷 1673-1691页

作者： Li, Hao Mi, Shanghua Li, Qifeng Wen, Xiaoyu Qiao, Dongping Luo, Guofu Zhengzhou Univ Light Ind Henan Prov Key Lab Intelligent Mfg Mech Equipment Zhengzhou 450002 Peoples R China

Scheduling optimization of maintenance, repair and operations (MRO) service resources of complex product can help an enterprise improve customer service satisfaction, build value-added products, and enhance the enterprise's market competitiveness. This paper studies a scheduling optimization method for the MRO service resources of complex product. First, the scheduling problem in service resources is analyzed, a mathematical model for the service scheduling problem is given, and three objective functions to be optimized are proposed, which are to reduce customer waiting time, reduce excessive human resources, and maximize the cost performance index of the resources. Then, three separate objectives for optimizing service resource scheduling are analyzed based on three proposed methods which are improved genetic algorithm method, combined weight coefficient optimization method, and multi-objective optimization method based on the nondominated sorting genetic algorithm ii (nsga-ii). Finally, we use the three methods to carry out scheduling optimization of MRO service resources in the case of a large vertical mill. According to the analysis and comparison of results, the multi-objective optimization method based on the nsga-ii algorithm has an advantage in the scheduling optimization of complex product MRO service resources. In the engineering application, the service scheduling of complex products for managers provides theoretical basis, and can reduce the loss caused by subjective judgment.

关键词： Maintenance repair and operations Scheduling optimization Improved genetic algorithm nsga-ii algorithm

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