检索结果-内蒙古大学图书馆

multi-objective optimization of nanofluid-based direct absorption solar collector for low-temperature applications

JOURNAL OF BUILDING ENGINEERING 2023年 72卷

作者： Baro, Rajani Kant Kotecha, Prakash Anandalakshmi, R. Indian Inst Technol Guwahati Dept Chem Engn Gauhati 781039 Assam India Indian Inst Technol Guwahati Sch Business Gauhati 781039 Assam India

This article investigates the multi-objective optimization of nanofluid-based direct absorption solar collector (NDASC) for optimal thermal efficiency and temperature rise using a computational fluid dynamics-based optimization approach. The mass, momentum, and energy balance equations are solved for a three-dimensional computational model of NDASC. The wavelength-dependent radiative transport equation is numerically solved to yield the volumetric heat generation term in the energy balance equation. Thermal efficiency and temperature rise are chosen as objective functions with a maximum temperature rise of low-temperature NDASC as a constraint for multi-objective optimization. Conventional computational intelligence techniques such as the multi-objective genetic algorithm (MOGA), multi-objective particle swarm optimization (MOPSO), and multi-objective differential evolution (MODE) are employed. Decision variables such as geometrical parameters of the collector (length, width, and height), structural parameter of nanoparticles (volume fraction), and operational parameters of the collector (mass flow rate and fluid inlet temperature) showed a significant effect on the thermal efficiency and temperature rise of the NDASC. MOPSO outperformed other algorithms based on objective functions and solution convergence. Pareto solutions are obtained, and a sensitivity analysis is carried out using the corner point solutions of the Pareto determined by MOPSO as the reference. Temperature contours and profiles are also analyzed for the corner point solutions of the Pareto determined by MOPSO. The thermal efficiency of NDASC is found to be between 59.9% and 98.4%, with a temperature rise between 7.81 K and 71.93 K, subject to the constraint of T-in + ?T < 373 K, where T-in and ?T are the fluid inlet temperature and temperature rise for multi-objective optimization of NDASC. This work will aid in developing compact and efficient NDASC designs to deliver an optimal thermal efficienc

关键词： Nanofluid-based direct absorption solar collector Thermal efficiency Temperature rise multi-objective genetic algorithm multi-objective particle swarm optimization multi-objective differential evolution

来源：评论

学校读者我要写书评

暂无评论

multi-objective reliability based design optimization of coupled acoustic-structural system

引用

ENGINEERING STRUCTURES 2019年 197卷 109389-000页

作者： Dammak, Khalil El Hami, Abdelkhalak Univ Rouen INSA Rouen Normandy LMN F-76801 St Etienne De Rouvray France

Vibro-acoustic optimization for coupled acoustic-structural system signifies one of the key topics of research to improve its performances. However, majority of the studies have not considered the presence of uncertainties while it has been shown that a deterministic optimization leads to an unreliable design. This paper proposes a methodology to perform the multi-objective reliability-based design optimization (MORBDO) for a coupled acoustic-structural system. This methodology consists in coupling the hybrid method with the genetic algorithm in order to integrate the reliability analysis. This problem consists in two flexible plates coupled with an acoustic rectangular cavity, in which an analytical formulation was developed to investigate the acoustic pressure inside the cavity as well as the plates displacements. The results show that the multi-objective genetic algorithm (MOGA) coupled with the hybrid method (HM) was capable to generate well-distributed reliable Pareto solutions. The effectiveness of the methodology is illustrated by a coupled acoustic-structural application.

关键词： multi-objective reliability-based design optimization Coupled acoustic-structural multi-objective genetic algorithm Hybrid method Uncertainties

来源：评论

学校读者我要写书评

暂无评论

Outranking Relations based multi-criteria Recommender System for Analysis of Health Risk using multi-objective Feature Selection Approach

引用

DATA & KNOWLEDGE ENGINEERING 2023年第1期145卷

作者： Kuanr, Madhusree Mohapatra, Puspanjali IIIT Bhubaneswar Dept Comp Sci & Engn Bhubaneswar 751003 Odisha India

The recommender system filters out important information from a large pool of information to set some important decisions in terms of recommendation. It has had an impact in almost every domain, including health, where it can extract information from massive amounts of digital data on patients to provide a better understanding of their clinical status and predict diseases. It is found that most of the real-world problems are dealing with multiple (conflicting) criteria, and handling those criteria in decision making is a challenging task too. In this context, this paper has proposed a health recommender system based on multi-criteria ranking and a multi-objective feature selection approach. Certain risk factors for the development of cervical cancer in women have been recommended by the proposed system, as well as some models for reliable prediction of this disease. The performance of the proposed system is tested and analysed by implementing it on the Cervical Risk Classification dataset with the three different ranking algorithms of multi-Criteria Decision (MCDM) Making. It is found that the MOORA (multi-objective Optimisation on the Basis of Ratio Analysis) MCDM algorithm outperforms the other two algorithms in terms of Precision@N, Recall@N, F1-score@N and Mean Reciprocal Rank (MRR)@N. The performance of the proposed system is also verified using four other benchmarking disease datasets, and statistical Anova and Wilcoxon tests have been done to validate the results.

关键词： Recommender system multi-Criteria Decision Making Feature selection multi-objective genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

An Inventive Method for Eco-Efficient Operation of Home Energy Management Systems

引用

ENERGIES 2018年第11期11卷 3091-3091页

作者： Hussain, Bilal Javaid, Nadeem Ul Hasan, Qadeer Javaid, Sakeena Khan, Asif Malik, Shahzad A. COMSATS Univ Islamabad Dept Elect Engn Islamabad 44000 Pakistan COMSATS Univ Islamabad Dept Comp Sci Islamabad 44000 Pakistan

A demand response (DR) based home energy management systems (HEMS) synergies with renewable energy sources (RESs) and energy storage systems (ESSs). In this work, a three-step simulation based posteriori method is proposed to develop a scheme for eco-efficient operation of HEMS. The proposed method provides the trade-off between the net cost of energy (CEnet) and the time-based discomfort (TBD) due to shifting of home appliances (HAs). At step-1, primary trade-offs for CEnet, TBD and minimal emissions TEMiss are generated through a heuristic method. This method takes into account photovoltaic availability, the state of charge, the related rates for the storage system, mixed shifting of HAs, inclining block rates, the sharing-based parallel operation of power sources, and selling of the renewable energy to the utility. The search has been driven through multi-objective genetic algorithm and Pareto based optimization. A filtration mechanism (based on the trends exhibited by TEMiss in consideration of CEnet and TBD) is devised to harness the trade-offs with minimal emissions. At step-2, a constraint filter based on the average value of TEMiss is used to filter out the trade-offs with extremely high values of TEMiss. At step-3, another constraint filter (made up of an average surface fit for TEMiss) is applied to screen out the trade-offs with marginally high values of TEMiss. The surface fit is developed using polynomial models for regression based on the least sum of squared errors. The selected solutions are classified for critical trade-off analysis to enable the consumer choice for the best options. Furthermore, simulations validate our proposed method in terms of aforementioned objectives.

关键词： eco-efficient home energy management dispatch of renewables and energy storage systems load-shedding-compensating dispatchable generators optimization using surface fitting techniques multi-objective genetic algorithm Pareto optimization

来源：评论

学校读者我要写书评

暂无评论

Optimizing the Thickness of multilayer Thermal Insulation on Different Pipelines for Minimizing Overall Cost-Associated Heat Loss

引用

PROCESSES 2024年第2期12卷 318页

作者： Alrasheed, Mohammed R. A. King Saud Univ Dept Mech Engn Riyadh 11421 Saudi Arabia

Optimizing the multilayer thermal insulation of pipelines transporting liquids and gases at higher than ambient temperatures is crucial for heat energy conservation and cost optimization. This study utilizes a multi-objective genetic algorithm to optimize the multilayer thermal insulation thickness around a pipe carrying fluid to minimize heat loss and associated costs. The model adopted mathematical associations between design variables and the overall installation cost of layers over a pipe from the available literature. The proposed model considered one or more insulation layers of rock wool and calcium silicate to oil pipelines containing steam, furfural, reduced crude or 300-distillate oil. All calculations considered fixed-charge rates as a fraction of 1 or 0.15. The results were compared with standard values and those predicted by other researchers in the literature. For the steam line, the standard insulation thickness was 50 mm, jumping to 327 mm for rock wool and 232 mm for calcium silicate. However, it decreased to 38 mm for double-layer calcium silicate and 138 mm for double-layer rock wool. For furfural, the insulation thickness was 40 mm, which rose to 159 mm for rock wool and 112 mm for calcium silicate. In general, for all four cases, the results show that using normal insulation thickness is inadequate and not economical. For example, for 300-distillate oil, the present practice puts the cost function at 54 USD/m, which drops to 20 USD/m for rock wool and 24 USD/m each for single-layer silicate and double-layer insulation. This amounts to almost 60% cost savings. Similar trends are observed for the other three cases. This model can provide up to 60% savings in cost and a 92% reduction in heat loss at optimum insulation thickness compared to other models.

关键词： thermal insulation multilayer insulation multi-objective genetic algorithm optimization energy savings life cycle cost analysis

来源：评论

学校读者我要写书评

暂无评论

Design and multi-objective optimization of reactive pressure-swing distillation process for separating tetrahydrofuran-methanol-water

引用

SEPARATION AND PURIFICATION TECHNOLOGY 2024年 329卷

作者： Liu, Xiaojing Xu, Qilei Ma, Cuncheng Zhang, Fangkun Cui, Peizhe Wang, Yinglong Shan, Baoming Qingdao Univ Sci & Technol Coll Automat & Elect Engn Qingdao 266061 Peoples R China Qingdao Univ Sci & Technol Coll Chem Engn Qingdao 266042 Peoples R China

The low-energy and low-cost process development and design has always been a hot topic and challenge in separating azeotropic systems in the world. In this paper, a novel, energy-saving reactive pressure-swing distillation (RPSD) was, for the first time, designed for separating the ternary mixture of tetrahydrofuran (THF)-methanol-water. In the reactive distillation column, the process of reacting water with ethylene oxide to produce ethylene glycol for the first time was used to separate THF-methanol-water mixture, then the residual mixtures were separated by two pressure-swing distillation columns. Two feasible RPSD separation processes were investigated in terms of thermodynamic modeling and T-xy phase diagram analysis to achieve optimal separation sequence. The two designed separation processes were optimized by a multi-objective genetic algorithm and heat integration to maximize economic benefit. Results demonstrated that, compared to the conventional pressure-swing distillation process, the total annual cost of the designed two heat-integrated processes based on the RPSD-B process were greatly reduced, i.e., 45.9% and 52.2%, respectively. This paper has important guiding significance for the separation and purification of multicomponent azeotropes.

关键词： Reactive pressure-swing distillation THF-methanol-water multi-objective genetic algorithm Energy savings

来源：评论

学校读者我要写书评

暂无评论

Local mean decomposition and artificial neural network approach to mitigate tool chatter and improve material removal rate in turning operation

引用

APPLIED SOFT COMPUTING 2020年 96卷 106714-106714页

作者： Gupta, Pankaj Singh, Bhagat Jaypee Univ Engn & Technol Guna MP India

Productivity has always been a major concern in the industry. It can be improved by increasing material removal rate. Regenerative chatter during machining is the major obstacle to attain this. In the present work, a methodology has been proposed to select a proper combination of input cutting parameters for stable turning with improved metal removal rate (MRR). Chatter signals generated during the turning of Al 6061 have been acquired using a microphone. Initially, acquired signals have been processed using local mean decomposition (LMD) signal processing technique. The decomposed signals have been analyzed using different statistical chatter indicators considering Nakagami distribution approach for ascertaining the thresholds of chatter severity. Prediction models of most effective statistical chatter indicator and MRR have been developed using an artificial neural network (ANN). Moreover, this prediction models have been optimized using multi-objective genetic algorithm for ascertaining the optimal range of cutting parameters for stable turning with higher MRR. Finally, obtained stable range has been validated by performing more experiments. (C) 2020 Elsevier B.V. All rights reserved.

关键词： Tool chatter Local mean decomposition Nakagami distribution Artificial neural network multi-objective genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

Cost-effective sensor placement optimization for large-scale urban sewage surveillance

引用

SUSTAINABLE CITIES AND SOCIETY 2024年 103卷

作者： Wang, Sunyu Xu, Ke Zhou, Yulun Univ Hong Kong Dept Urban Planning & Design Hong Kong Peoples R China Univ Calif Los Angeles Samueli Sch Engn Los Angeles CA 90095 USA Univ Hong Kong Musketeers Fdn Inst Data Sci Hong Kong Peoples R China

Early pandemic outbreak detection in cities is a crucial but challenging task. Complementary to the costly massive individual testing, urban sewage surveillance offers a rare, cost-effective solution for large-scale monitoring of pandemic spread in cities with minimal interference to people's lives. One emerging question is how to derive a cost-effective sensor placement plan in city -scale sewage networks having complicated topologies. Inspired by remote sensing, we first provide a general multi -objective formulation of the optimal sensor placement problem on directed networks. Then, we introduce a connectivity -based objective evaluation approach and embed it into an NSGA-II algorithm to enable efficient optimization on large-scale directed graphs. The effectiveness of the proposed method is verified on a real -world sewage network in Hong Kong serving more than 500,000 urban residents. Results show that the proposed method efficiently generated optimal sensor placement plans on city -scale networks. Optimized sensor placement plans outperformed human placement heuristics by a significant margin of 102%, highlighting the necessity for data -driven decision support for large-scale urban sensing. Methodologically, this study provides a benchmark problem and datasets for network -based spatial optimization studies. Codes and datasets developed in this study are open -sourced to support future research in a real -world scenario.

关键词： Optimal sensor placement Network-based spatial optimization multi-objective genetic algorithm Sewage surveillance Pandemic control

来源：评论

学校读者我要写书评

暂无评论

Shape Optimization to Reduce Wind Pressure on the Surfaces of a Rectangular Building with Horizontal Limbs

引用

PERIODICA POLYTECHNICA-CIVIL ENGINEERING 2021年第1期65卷 134-149页

作者： Paul, Rajdip Dalui, Sujit Kumar Indian Inst Engn Sci & Technol Civil Engn Dept PO Bot Garden Howrah 711103 W Bengal India

The present study consists of shape optimization of a rectangular plan shaped tall building with horizontal limbs under wind attack, which would minimize the wind pressure on all the faces of the building model simultaneously. For the purpose, the external pressure coefficients on different faces of the building (C-pe) are selected as the objective functions. The position of the limbs and the wind incidence angle are taken as design variables. The design of experiment (DOE) is done using random sampling. The values of the objective functions are obtained by using Computational Fluid Dynamics method of simulated wind flow at each design point. The building model has a constant plan area 22500 mm(2). The length and velocity scales are taken as 1:300 and 1:5, respectively. The results are used to construct the surrogate models of the objective functions using Response Surface Approximation method. The optimization study is done using the multi-objective genetic algorithm. The building shapes corresponding to the Pareto optimal decision variables are shown. The function values corresponding to the decision variables are verified by further introducing a CFD study.

关键词： tall building wind pressure coefficient optimization multi-objective genetic algorithm pareto-optimal solutions Response Surface Approximation

来源：评论

学校读者我要写书评

暂无评论

Demand Side Management Strategy for multi-objective Day-Ahead Scheduling Considering Wind Energy in Smart Grid

引用

ENERGIES 2022年第19期15卷 6900-6900页

作者： Ullah, Kalim Khan, Taimoor Ahmad Hafeez, Ghulam Khan, Imran Murawwat, Sadia Alamri, Basem Ali, Faheem Ali, Sajjad Khan, Sheraz Univ Engn & Technol Dept Elect Engn Mardan 23200 Pakistan Lahore Coll Women Univ Dept Elect Engn Lahore 54000 Pakistan Taif Univ Coll Engn Dept Elect Engn POB 11099 Taif 21944 Saudi Arabia Univ Engn & Technol Dept Elect Engn Peshawar 25000 Pakistan Univ Engn & Technol Dept Telecommun Engn Mardan 23200 Pakistan

Distributed energy resources (DERs) and demand side management (DSM) strategy implementation in smart grids (SGs) lead to environmental and economic benefits. In this paper, a new DSM strategy is proposed for the day-ahead scheduling problem in SGs with a high penetration of wind energy to optimize the tri-objective problem in SGs: operating cost and pollution emission minimization, the minimization of the cost associated with load curtailment, and the minimization of the deviation between wind turbine (WT) output power and demand. Due to climatic conditions, the nature of the wind energy source is uncertain, and its prediction for day-ahead scheduling is challenging. Monte Carlo simulation (MCS) was used to predict wind energy before integrating with the SG. The DSM strategy used in this study consists of real-time pricing and incentives, which is a hybrid demand response program (H-DRP). To solve the proposed tri-objective SG scheduling problem, an optimization technique, the multi-objective genetic algorithm (MOGA), is proposed, which results in non-dominated solutions in the feasible search area. Besides, the decision-making mechanism (DMM) was applied to find the optimal solution amongst the non-dominated solutions in the feasible search area. The proposed scheduling model successfully optimizes the objective functions. For the simulation, MATLAB 2021a was used. For the validation of this model, it was tested on the SG using multiple balancing constraints for power balance at the consumer end.

关键词： hybrid demand response programs smart grid renewable energy sources multi-objective genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：