检索结果-内蒙古大学图书馆

Design, optimization and control of extractive distillation for the separation of isopropanol-water using ionic liquids

引用

SEPARATION AND PURIFICATION TECHNOLOGY 2019年 209卷 833-850页

作者： Ma, Shoutao Shang, Xianyong Zhu, Minyan Li, Jinfang Sun, Lanyi China Univ Petr East China Coll Chem Engn State Key Lab Heavy Oil Proc Qingdao 266580 Shandong Peoples R China

As an excellent solvent, ionic liquids (ILs) have received much attention in the last two decades. One of the most important applications is to be used as an extractant for separation of azeotropic mixtures via extractive distillation (ED). In this work, 1-ethyl-3-methylimidazolium dicyanamide ([emim][N(CN)2]) is selected as the extractant to separate isopropanol (IPA)-water azeotrope based on two ED processes. multi-objective genetic algorithm (MOGA) is used to determine the operating parameters for these ED processes. Total annual cost (TAO, efficiency indicator of extractive section (E-ext), efficiency indicator of per tray in extractive section (e(ext)) and energy consumption per product flow rate (GEO are selected as objective functions in the ED process optimization, and the Pareto front provides a series of solutions satisfying the constraints with different operating parameters. The results show that TAC of the process 2 with two evaporators used in the phase of solvent recovery is 4.26% lower than that of process 1 with one evaporator. In addition, the thermodynamic efficiency (eta) and CO2 emissions are calculated for different cases, and they provide the reference for the selection of operating parameters. On this basis, the control structures of ED processes are further studied, and the traditional two-point temperature control structure works pretty well for disturbances of both feed rate and feed composition.

关键词： Ionic liquids (ILs) Extractive distillation multi-objective genetic algorithm Process optimization Dynamic control

来源：评论

学校读者我要写书评

暂无评论

Strategy development for retrofitting ships for implementing shore side electricity

引用

TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT 2019年第Sep.期74卷 201-213页

作者： Yu, Jingjing Voss, Stefan Tang, Guolei Dalian Univ Technol Fac Infrastruct Engn State Key Lab Coastal & Offshore Engn Dalian 116023 Liaoning Peoples R China Univ Hamburg Inst Informat Syst Von Melle Pk 5 D-20146 Hamburg Germany

Shore side electricity (SSE) is the use of electricity from the shore to power a ship's system when it is berthing at ports. It is a solution to reduce the emissions of auxiliary engines at berth and to improve the local and regional air quality. This paper develops a multi-objective model that integrates spatial and temporal dimensions for strategic planning regarding whether and when to retrofit ships to use SSE. The strategic planning problem is to maximize the environmental benefit and to minimize the payback period of the investment over the entire planning horizon. By adopting an improved multi-objective genetic algorithm (NSGA-II), a series of retrofit strategies for container ships calling at Dalian Port in China are obtained under a projected annual visiting frequency of ships with different ship sizes and shipping lines. Depending on a selected retrofit strategy, the sum of the payback periods of ships that are determined to be retrofitted is 46 years (on average less than four years) and the environmental benefit of using SSE can be up to 128 million USD for Dalian Port in the planning horizon from 2020 to 2035. The results show that using SSE is an efficient method to decline emissions within the maritime sector and validate that the proposed methodology can be useful to ship owners to decide upon investing in SSE applications and to promote the development of green shipping and green ports.

关键词： Shore side electricity Ship retrofitting multi-objective optimization multi-objective genetic algorithm Green port

来源：评论

学校读者我要写书评

暂无评论

A multi-objective approach for multi-material topology and shape optimization

引用

ENGINEERING OPTIMIZATION 2019年第6期51卷 915-940页

作者： Queiroz Zuliani, Joao Batista Cohen, Miri Weiss Guimaraes, Frederico Gadelha Severiano Junior, Carlos Alberto Ctr Fed Educ Tecnol Minas Gerais Timoteo Brazil Braude Coll Engn Dept Software Engn Karmiel Israel Univ Fed Minas Gerais Dept Elect Engn Belo Horizonte MG Brazil Inst Fed Minas Gerais Campus Sabara Sabara Brazil

An automated multi-material approach that integrates multi-objective Topology Optimization (TO) and multi-objective shape optimization is presented. A new ant colony optimization algorithm is presented and applied to solving the TO problem, estimating a trade-off set of initial topologies or distributions of material. The solutions found usually present irregular boundaries, which are not desirable in applications. Thus, shape parameterization of the internal boundaries of the design region, and subsequent shape optimization, is performed to improve the quality of the estimated Pareto-optimal solutions. The selection of solutions for shape optimization is done by using the PROMETHEE II decision-making method. The parameterization process involves identifying the boundaries of different materials and describing these boundaries by non-uniform rational B-spline curves. The proposed approach is applied to the optimization of a C-core magnetic actuator, with two objectives: the maximization of the attractive force on the armature and the minimization of the volume of permanent magnet material.

关键词： Topology optimization shape optimization multi-objective ant colony optimization multi-objective genetic algorithm PROMETHEE II

来源：评论

学校读者我要写书评

暂无评论

Numerical investigation on the application of elliptical tubes in a spiral-wound heat exchanger used in LNG plant

引用

INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER 2019年 130卷 333-341页

作者： Jian, Guanping Wang, Simin Sun, Lijuan Wen, Jian Xi An Jiao Tong Univ Sch Chem Engn & Technol Xian 710049 Shanxi Peoples R China Xi An Jiao Tong Univ Sch Energy & Power Engn Xian 710049 Peoples R China

The elliptical tubes were proposed to use in a spiral-wound heat exchanger to boost the shell-side transfer rate with the decrease of shell-side pressure drop. The effects of major axis and minor axis of elliptical tubes on thermal hydraulic performance are numerically investigated. The results show that, compared with the circular tube, the SWHE with elliptical tubes have a better heat transfer ability when the shell-side pressure drop is equal to that with circular tubes. With the increase of the major axis of the elliptical tube, the friction factor f decrease firstly and then increase. While with the increase of the minor axis, the variations of the f have an opposite trend with the increase of the major axis. For the heat transfer, the Nu decreases firstly with the increase of major axis and then increases. However, Nu number increases monotonously with the minor axis because elliptical tube bundle promotes the shell-side turbulent mixing. Based on the numerical data, the multi-objective optimization is performed by genetic algorithm. The optimal results show that, by contrast with the original structure, the comprehensive performance (K/Delta P) of the optimized structures increases by an average of 315.4% and the pumping consumption decreases by an average of 65.5%. (C)2018 Elsevier Ltd. All rights reserved.

关键词： Spiral-wound heat exchanger Elliptical tube multi-objective genetic algorithm Optimization

来源：评论

学校读者我要写书评

暂无评论

Interdisciplinary application of numerical and machine-learning-based models to predict half-hourly suspended sediment concentrations during typhoons

引用

JOURNAL OF HYDROLOGY 2019年 573卷 661-675页

作者： Huang, Cheng-Chia Fang, Hsi-Ting Ho, Hao-Che Jhong, Bing-Chen Natl Taiwan Univ Dept Civil Engn Taipei 10617 Taiwan Taiwan Integrated Disaster Prevent Technol Engn C New Taipei 23678 Taiwan Kyoto Univ Grad Sch Engn Dept Civil & Earth Resources Engn Kyoto 6158540 Japan

Accurate forecasting of hourly suspended sediment concentration is a critical issue for reservoir management, especially during typhoon periods. This research proposes a two-stage forecasting approach integrating numerical and machine-learning-based models to provide accurate real-time forecasts of half-hourly suspended sediment concentration. In the first stage, the density current model, SRH2D, was verified and applied by the historical typhoon events due to the lack of measured suspended sediment concentration. Next, in the second stage, the calculated results from SRH2D based on the spatial-temporal relation were employed as the input of the MGSVM-based model. Finally, an application in the Shi-Men reservoir was conducted to demonstrate the forecasting performance of the proposed approach. The results indicated that the calculated data from the SRH2D model corresponded to the trend of measured data in spatial-temporal variation. Moreover, the proposed forecasting approach enables reasonably acceptable 0.5- to 3-h ahead forecasts of suspended sediment concentration by using the simulated data of half-hourly suspended sediment concentration. The accurate forecast conducted by the proposed approach is expected to be properly applied to reservoir management.

关键词： Suspended sediment concentration forecasting Density current Reservoir multi-objective genetic algorithm Support vector machine Typhoon

来源：评论

学校读者我要写书评

暂无评论

Stochastic partially optimized cyclic shift crossover for multi-objective genetic algorithms for the vehicle routing problem with time-windows

引用

APPLIED SOFT COMPUTING 2017年 52卷 863-876页

作者： Pierre, Djamalladine Mahamat Zakaria, Nordin Univ Teknol PETRONAS High Performance Comp Ctr Tronoh 32610 Perak Malaysia

This paper presents a stochastic partially optimized cyclic shift crossover operator for the optimization of the multi-objective vehicle routing problem with time windows using genetic algorithms. The aim of the paper is to show how the combination of simple stochastic rules and sequential appendage policies addresses a common limitation of the traditional genetic algorithm when optimizing complex combinatorial problems. The limitation, in question, is the inability of the traditional genetic algorithm to perform local optimization. A series of tests based on the Solomon benchmark instances show the level of competitiveness of the newly introduced crossover operator. (C) 2016 Elsevier B.V. All rights reserved

关键词： multi-objective vehicle routing problems multi-objective genetic algorithm Crossover

来源：评论

学校读者我要写书评

暂无评论

Optimal policies for control of the novel coronavirus disease (COVID-19) outbreak

引用

CHAOS SOLITONS & FRACTALS 2020年 136卷 109883-109883页

作者： Yousefpour, Amin Jahanshahi, Hadi Bekiros, Stelios Univ Tehran Coll Engn Sch Mech Engn Tehran 111554563 Iran Univ Manitoba Dept Mech Engn Winnipeg MB R3T 5V6 Canada European Univ Inst Dept Econ Via Fontanelle 18 I-50014 Florence Italy Wilfrid Laurier Univ RCEA LH3079 75 Univ Ave W Waterloo ON N2L 3C5 Canada

Understanding the early transmission dynamics of diseases and estimating the effectiveness of control policies play inevitable roles in the prevention of epidemic diseases. To this end, this paper is concerned with the design of optimal control strategies for the novel coronavirus disease (COVID-19). A mathematical model of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission based on Wuhan's data is considered. To solve the problem effectively and efficiently, a multi-objective genetic algorithm is proposed to achieve high-quality schedules for various factors including contact rate and transition rate of symptomatic infected individuals to the quarantined infected class. By changing these factors, two optimal policies are successfully designed. This study has two main scientific contributions that are: (1) This is pioneer research that proposes policies regarding COVID-19, (2) This is also the first research that addresses COVID-19 and considers its economic consequences through a multi-objective evolutionary algorithm. Numerical simulations conspicuously demonstrate that by applying the proposed optimal policies, governments could find useful and practical ways for control of the disease.

关键词： Novel coronavirus Mathematical modeling Optimal control multi-objective genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

POLYNOMIAL NARX MODEL STRUCTURE OPTIMIZATION USING multi-objective genetic algorithm

引用

INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL 2012年第10B期8卷 7341-7362页

作者： Loghmanian, Sayed Mohammad Reza Yusof, Rubiyah Khalid, Marzuki Ismail, Fatimah Sham Univ Teknol Malaysia Ctr Artificial Intelligence & Robot Kuala Lumpur Malaysia

Model structure selection is an important step in system identification which involves the selection of variables and terms of a model. The important issue is choosing a compact model representation where only significant terms are selected among all the possible ones beside good performance. This research explores the use of multi-objective optimization to minimize the complexity of a model structure and its predictive error simultaneously. The model structure representation is a polynomial non-linear autoregressive with exogenous input model. A new modified elitist non-dominated sorting genetic algorithm using clustered crowding distance (CCD) is proposed to find the exact model among non-dominated solutions, using some simulated examples which generate data set by mathematical equations. Simulation results demonstrated that the proposed algorithm can find the correct model with exact terms and values in all cases of problem. Furthermore, the effectiveness of the proposed algorithm is also studied by applying to the real process data sets, and the final model can be chosen from a set of non-dominated solutions referred as Pareto optimal front. The results show that the proposed clustered CD has better performance compared with the basic CD method.

关键词： NARX multi-objective genetic algorithm NSGA-II System identification Model structure selection Clustered crowding distance

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

Optimal design of classroom spaces in naturally-ventilated buildings to maximize occupant satisfaction with human bioeffluents/body odor levels

引用

BUILDING AND ENVIRONMENT 2020年 169卷 106543-000页

作者： Acosta-Acosta, Dario F. El-Rayes, Khaled Univ Illinois Dept Civil & Environm Engn 3112 Newmark Civil Engn Bldg205 N Mathews Urbana IL 61801 USA Univ Panamer Fac Ingn Alvaro Del Portillo 49 Zapopan 45010 Jalisco Mexico

Inadequate indoor air quality in education buildings has been reported to cause health problems, contagion, poor academic performance and absenteeism of occupants. To minimize these adverse effects, the use of natural ventilation systems and hybrid ventilation systems in buildings have increased in recent years. This paper presents the development of a novel optimization model that provides the capability of optimizing education building design in order to maximize occupant satisfaction in the classrooms space in terms of perception of human bioeffluents/body odor while minimizing the construction cost. The multi-objective optimization model is developed in three main stages: (1) model formulation stage that identifies relevant design variables, objective functions and constraints;(2) model implementation stage that executes the optimization computations;and (3) model evaluation stage that analyses the performance of the developed model using an application example. The findings of this performance analysis illustrates the capability of the developed optimization model to generate a wide range of optimal trade-offs solutions, where each provides a unique and optimal trade-off between occupant satisfaction with human bioeffluents/body odor levels and its construction cost. This enables designers to generate and analyze these optimal trade-offs and accordingly identify an optimal set of design decisions that maximize satisfaction with human bioeffluents/body odor levels of occupants while complying with specified budget constraint.

关键词： Natural ventilation Indoor air quality Human bioeffluents Human body odor Education buildings 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：