检索结果-内蒙古大学图书馆

A study of test and statistical damage constitutive model of multi-size polypropylene fiber concrete under impact load

引用

INTERNATIONAL JOURNAL OF DAMAGE MECHANICS 2019年第7期28卷 973-989页

作者： Yang, Xin Liang, Ninghui Liu, Xinrong Zhong, Zuliang Fujian Univ Technol Sch Civil Engn Fuzhou Fujian Peoples R China Fujian Prov Univ Key Lab Underground Engn Fuzhou Fujian Peoples R China Fujian Univ Technol Inst Geotech Engn Fuzhou Fujian Peoples R China Chongqing Univ Sch Civil Engn Chongqing 400045 Peoples R China Chongqing Univ Minist Educ Key Lab New Technol Construct Cities Mt Area Chongqing Peoples R China

To investigate the effects of mixing polypropylene fiber of different sizes and the effect of fiber size on the impact characteristics of concrete, two sizes of polypropylene fine fiber and one size of polypropylene coarse fiber were selected to design and fabricate nine groups of polypropylene fiber-reinforced concrete test specimens by controlling the fiber mixing ratio and conducting a split Hopkinson pressure bar test to obtain the stress-strain curves of the test specimens in various groups, and their parameters such as the elasticity modulus, peak strength, and peak strain. The incorporation of fiber improved the pre-peak impact properties of concrete to different extents. Strain hardening did not occur in the post-peak curves, and different types of fibers exhibited different characteristics. Thus, the fine fiber could significantly improve the peak strain, while the coarse fiber could more significantly improve the elasticity modulus and peak strength. The improving effects exerted by incorporating three types of fiber were better than those exerted by incorporating two types of fiber. Moreover, the statistical damage model was used to obtain the parameters by fitting and analyzing their variation rules based on the statistical damage constitutive model and the particle swarm optimization algorithm.

关键词： Different sizes polypropylene fiber-reinforced concrete split Hopkinson pressure bar test statistical damage constitutive model particle swarm optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

Optimal design and performance analysis of solar hybrid CCHP system considering influence of building type and climate condition

引用

ENERGY 2019年 174卷 647-663页

作者： Yang, G. Zhai, X. Q. Shanghai Jiao Tong Univ Inst Refrigerat & Cryogen Shanghai 200240 Peoples R China

Incorporating solar energy technologies to the conventional combined cooling, heating and power (CCHP) system has been considered as an effective solution to mitigate the looming energy and environmental challenges. The mathematical model of a conventional CCHP system hybridized with photovoltaic (PV) panels and solar thermal collectors is built in this study. The particle swarm optimization (PSO) algorithm is employed to find the optimal size of key components of the solar hybrid CCHP system. The simulation work of solar hybrid CCHP systems in three building prototypes across seven climate zones is carried out to find appropriate design schemes of these cases. Besides, some guiding principles of the design of the solar hybrid CCHP system in early stage are summarized. The results show that the system under the following thermal load (FTL) strategy is the first choice in most cases of hospitals and hotels, except for the systems of hotels in the cold and very cold zones. On the contrary, the systems in offices perform better in the following electric load (FEL) mode in the majority of climate zones except for the hot-humid zone. Generally, the average optimal integrated performance (S) values of hospitals, hotels and offices can reach 28.95%, 28.20% and 22.69%, respectively. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Combined cooling heating and power Solar energy Hybrid system particle swarm optimization algorithm Building energy consumption Climate condition

来源：评论

学校读者我要写书评

暂无评论

Development of an expression for the volume of off-centered conical pile inside a cylindrical silo

引用

MEASUREMENT 2019年 146卷 903-911页

作者： Yigit, Enes Karamanoglu Mehmetbey Univ Fac Engn Dept Elect & Elect Engn TR-70100 Karaman Turkey

In this study, both analytical and empirical formula that expresses volume of off-centered conical pile inside a cylindrical structure are proposed. The total of 1050 off-centered cones including three parameters of dimension are acquired by computer aided design software. A volume expression enclosing conical pile parameters associated with variables of optimization is derived. Then the volume expression is obtained by substituting the variables determined by particle swarm optimization algorithm. The mean absolute percentage error between calculated and designed volumes of 1050 data are found as 0.0017% and 0.0299% for analytical and empirical expressions, respectively. Proposed calculations are also compared with another empirical formula existing in literature. In addition, two different small-scale case study are performed and the proposed formulations are verified experimentally. Results demonstrate that volume of the off-centered conical pile inside a cylindrical structure can be easily calculated with the help of empirically developed expression, without using complex mathematics. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Conical grain pile Grain level measurement particle swarm optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

Designing a New Artificial Lift Method Using Computational Simulation and Evolutionary optimization

引用

IEEE ACCESS 2019年 7卷 123846-123859页

作者： Moreira, Andre Pimentel Lepikson, Herman Augusto Schnitman, Leizer Bezerra Ramalho, Geraldo Luis Fed Inst Educ Sci & Technol Ceara Dept Ind BR-60040215 Fortaleza Ceara Brazil Mfg & Technol Integrated Campus SENAI Inst Innovat Automat & Logist BR-41650010 Salvador BA Brazil Univ Fed Bahia Ctr Technol Qualificat Ind Automat BR-40210630 Salvador BA Brazil

Oil exploitation has moved into deeper reservoirs with the advances in drilling techniques and thus the development of new pumping techniques has become a challenge to improve production. The positive displacement pumping system proposed in this paper is presented as an artificial lift technique. Here we present a new pumping device, its estimated operational curves through numerical simulations and a prototype of the device, denominated a Double Acting Submersible Linear Pump (SLP), which is a hydraulic system adapted for inside well operations. Design parameters used in the tests were optimized using the particle swarm optimization (PSO) algorithm to maximize oil production while optimizing the parameters (characterstics) of the pump, such as maximum pump diameters and submersible electric motor power, pressure and volumetric displacement of the hydraulic pump. Also presented are the operating curves estimated from the numerical simulation of the power and pump modules, as well as the SLP0 and SLP1 experimental test curves in a controlled environment using the optimized parameters obtained using PSO The data obtained were compared to the computational simulations performed with the Automation Studio (TM) software. The SLP0 and SLP1 optimal design tests showed the importance to delimit the range of operation within which the SLP must operate, since the pipes and hydraulic components must be suitable for the flow of hydraulic oil and the production oil. The findings presented here play an important role in the production process of a fully operational SLP prototype.

关键词： Artificial lift technique petroleum industry particle swarm optimization algorithm computational modeling and simulation

来源：评论

学校读者我要写书评

暂无评论

An Improved particle Filter With a Novel Hybrid Proposal Distribution for Quantitative Analysis of Gold Immunochromatographic Strips

引用

IEEE TRANSACTIONS ON NANOTECHNOLOGY 2019年 18卷 819-829页

作者： Zeng, Nianyin Wang, Zidong Zhang, Hong Kim, Kee-Eung Li, Yurong Liu, Xiaohui Xiamen Univ Dept Instrumental & Elect Engn Xiamen 361005 Fujian Peoples R China Brunel Univ Dept Comp Sci Uxbridge UB8 3PH Middx England Korea Adv Inst Sci & Technol Dept Comp Sci Daejeon 305701 South Korea Fuzhou Univ Coll Elect Engn & Automat Fuzhou 350002 Fujian Peoples R China Fujian Key Lab Med Instrumentat & Pharmaceut Tech Fuzhou 350002 Fujian Peoples R China

In this paper, a novel statistical pattern recognition method is proposed for accurately segmenting test and control lines from the gold immunochromatographic strip (GICS) images for the benefits of quantitative analysis. A new dynamic state-space model is established, based on which the segmentation task of test and control lines is transformed into a state estimation problem. Especially, the transition equation is utilized to describe the relationship between contour points on the upper and the lower boundaries of test and control lines, and a new observation equation is developed by combining the contrast of between-class variance and the uniformity measure. Then, an innovative particle filter (PF) with a hybrid proposal distribution, namely, deep-belief-network-based particle filter (DBN-PF) is put forward, where the deep belief network (DBN) provides an initial recognition result in the hybrid proposal distribution, and the particle swarm optimization algorithm moves particles to regions of high likelihood. The performance of proposed DBN-PF method is comprehensively evaluated on not only an artificial dataset but also the GICS images in terms of several indices as compared to the PF and DBN methods. It is demonstrated via experiment results that the proposed approach is effective in quantitative analysis of GICS.

关键词： Gold immunochromatographic strip particle filter proposal distribution deep belief network dynamical model image segmentation particle swarm optimization algorithm Monte Carlo

来源：评论

学校读者我要写书评

暂无评论

optimization of Power Allocation Based on particle swarm optimization in Wireless Location Network 9th

Optimization of Power Allocation Based on Particle Swarm Opt...

引用

9th China Satellite Navigation Conference (CSNC) - Location, Time of Augmentation

作者： Lin, Jinrui Li, Guangxia Tian, Shiwei Suo, Longlong Army Engn Univ PLA Coll Commun Engn Nanjing Jiangsu Peoples R China

ISBN: (纸本)9789811300295;9789811300288

Wireless location network combines data communication, contextual data collection and navigation. The purpose of this network is to determine the positions of agents based on measurements between nodes and nodes. In order to improve the positioning accuracy of wireless location network, the usual method is to increase the density of nodes, especially the density of anchor nodes, so as to optimize the topology of the network. However, the wireless location network node power is limited, especially the wireless sensor network. It is necessary to increase power consumption to meet the needs of a large number of nodes. However, it is required that a certain level of power consumption should be set in the wireless location network, and even require further reduction in power consumption in daily life. At the same time, we need to maintain a certain positioning accuracy, which requires the optimization of power allocation in the network, to make sure that power and positioning accuracy of the network can meet the needs of the actual living. In this paper, an optimization of power allocation based on particle swarm optimization in wireless location network is proposed to optimize the power allocation. The square position error bound is introduced as the evaluation standard of the network positioning accuracy. Through the power optimization, the positioning accuracy of the network is improved.

关键词： Wireless location network Power optimization allocation Square position error bound particle swarm optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

A comparative investigation of deterministic and metaheuristic algorithms for node localization in wireless sensor networks

引用

WIRELESS NETWORKS 2019年第5期25卷 2789-2803页

作者： Kulkarni, Vaishali R. Desai, Veena Kulkarni, Raghavendra V. MS Ramaiah Univ Appl Sci Bengaluru India KLS Gogte Inst Technol Belagavi India

Location-based services in wireless sensor networks demand precise information of locations of sensor nodes. Range-based localization, a problem formulated as a two-dimensional optimization problem, has been addressed in this paper as a multistage exercise using bio-inspired metaheuristics. A modified version of the shuffled frog leaping algorithm (MSFLA) has been developed for accurate sensor localization. The results of MSFLA have been compared with those of geometric trilateration, artificial bee colony and particle swarm optimization algorithms. Dependance of localization accuracies achieved by these algorithms on the environmental noise has been investigated. Simulation results show that MSFLA delivers the estimates of the locations over 30% more accurately than the geometric trilateration method does in noisy environments. However, they involve higher computational expenses. The MSFLA delivers the most accurate localization results;but, it requires the longest computational time.

关键词： Artificial bee colony algorithm particle swarm optimization algorithm Sensor localization Shuffled frog leaping algorithm Trilateration Wireless sensor networks

来源：评论

学校读者我要写书评

暂无评论

Control strategy based on Fourier transformation and intelligent optimization for planar Pendubot

引用

INFORMATION SCIENCES 2019年 491卷 279-288页

作者： Wu, Jundong Wang, Yawu Ye, Wenjun Su, Chun-Yi Concordia Univ Fac Engn & Comp Sci Montreal PQ H3G 1M8 Canada China Univ Geosci Sch Automat Wuhan 430074 Hubei Peoples R China Hubei Key Lab Adv Control & Intelligent Automat C Wuhan 430074 Hubei Peoples R China

This paper presents a new control strategy based on Fourier transformation and intelligent optimization for a planar Pendubot with a passive second link, which can be treated as a second-order nonholonomic system whose control has been an open and challenging issue. A controller acting within a time corresponding to the frequency of its fundamental harmonic term is designed to realize the system control objective, which is to move the system from its initial position to the target position. By employing Fourier transformation, a general expression of the controller composed of a constant term and harmonic terms is obtained. Next, the constant term is obtained by the angular momentum theorem, and the particle swarm optimization algorithm is employed to obtain the harmonic terms of the controller. A feedback control strategy based on a nonlinear disturbance observer is then applied to overcome the uncertainties/disturbances in the system. Finally, simulation results prove the validity of this control method. (C) 2019 Elsevier Inc. All rights reserved.

关键词： Planar Pendubot Nonholonomic systems Fourier transformation particle swarm optimization algorithm Nonlinear disturbance observer

来源：评论

学校读者我要写书评

暂无评论

A study on multi-ASC scheduling method of automated container terminals based on graph theory

引用

COMPUTERS & INDUSTRIAL ENGINEERING 2019年 129卷 404-416页

作者： Lu, Houjun Wang, Sai Shanghai Maritime Univ Coll Logist Engn 1550 Haigang Ave Shanghai 201306 Peoples R China SAIC Motor Commercial Vehicle Tech Ctr Dept Informat Technol Shanghai Peoples R China

Compared with traditional terminals, two automated stacking cranes (ASCs) are configured for each container block of automated container terminal (ACT), which interact with automated guided vehicles (AGVs) and container trucks at the two ends of a container block individually. To increase the capacity, container yards with multiple rows of blocks perpendicular to the terminal's shoreline are considered. To utilize the yard spaces, twin ASCs are set to share transport tracks installed at the two sides of a block, while interferences between the ASCs causes the routing and sequencing operations. In order to control the scheduling of twin ASCs, the interference model is established by analyzing the time overlap between tasks. Considering the influence of AGV transportation time, the model are then established to sequence the container handling tasks under the minimization of waiting time and makespan. A particle swarm optimization algorithm (PSO) based on graph theory model is design to solve the problem. Numerical experiments show that the algorithm is more competitive than traditional algorithm. Based on the model and experimental result, the practical significance of applying the algorithm to the actual situation is discussed.

关键词： Automated container terminal Automated stacking crane Automated guided vehicle particle swarm optimization algorithm Graph theory

来源：评论

学校读者我要写书评

暂无评论

A robust approach for a green periodic competitive VRP under uncertainty: DE and PSO algorithms

引用

JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2019年第6期36卷 5213-5225页

作者： Fallah, M. Tavakkoli-Moghaddam, R. Alinaghian, M. Salamatbakhsh-Varjovi, A. Islamic Azad Univ Dept Ind Engn Cent Tehran Branch Tehran Iran Univ Tehran Coll Engn Sch Ind Engn Tehran Iran Arts & M Tiers ParisTech LCFC Metz France USERN Tehran Iran Isfahan Univ Technol Dept Ind & Syst Engn Esfahan Iran Islamic Azad Univ Dept Ind Engn Sci & Res Branch Tehran Iran

The purpose of this paper is to examine and evaluate a new mathematical model of vehicle routing problem in order to optimize fuel consumption and maximize commercial profitability under the conditions of uncertainty of distributor service to customers using robust approach under scenario. According to the real world, distribution companies are interested in minimizing consumption of fuel in the distribution of goods for two reasons: the first reason is that reducing the consumption of fuel will reduce the current costs of distribution companies and ultimately increase their profits. The second reason is that reducing fuel consumption will reduce the harmful effects of greenhouse gases and air pollution. Other words, distribution companies operate in a competitive environment that has more than one distributor in the distribution network, and start time for serving customers has a significant impact on the profitability of the distributors. To calculate the efficiency of the proposed model, we used differential evolution (DE) algorithm and particle swarm optimization (PSO), and the results were compared in small and medium scales with the results of the exact solution method. To verify proceeds of proposed algorithms in large scales, a number of sample problems were created in large scales and the figures were evaluated. The computational results indicate that DE algorithm has a better computational function, but the PSO algorithm has better computational time.

关键词： Green periodic VRP robust optimization Fuel consumption particle swarm optimization 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

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

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：