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Coach Simplified Structure modeling and Optimization Study Based on the PBM Method

Chinese Journal of Mechanical Engineering 2016年第5期29卷 1010-1018页

作者： ZHANG Miaoli REN Jindong YIN Ying DU Jian State Key lab of Automotive simulation and Control Jilin University Hyundai Motor Technology & Engineering Center (China) Ltd. R&D Center FAW Group

For the coach industry, rapid modeling and efficient optimization methods are desirable for structure modeling and optimization based on simplified structures, especially for use early in the concept phase and with capabilities of accurately expressing the mechanical properties of structure and with flexible section forms. However, the present dimension-based methods cannot easily meet these requirements. To achieve these goals, the property-based modeling （PBM） beam modeling method is studied based on the PBM theory and in conjunction with the characteristics of coach structure of taking beam as the main component. For a beam component of concrete length, its mechanical characteristics are primarily affected by the section properties. Four section parameters are adopted to describe the mechanical properties of a beam, including the section area, the principal moments of inertia about the two principal axles, and the torsion constant of the section. Based on the equivalent stiffness strategy, expressions for the above section parameters are derived, and the PBM beam element is implemented in HyperMesh software. A case is realized using this method, in which the structure of a passenger coach is simplified. The model precision is validated by comparing the basic performance of the total structure with that of the original structure, including the bending and torsion stiffness and the first-order bending and torsional modal frequencies. Sensitivity analysis is conducted to choose design variables. The optimal Latin hypercube experiment design is adopted to sample the test points, and polynomial response surfaces are used to fit these points. To improve the bending and torsion stiffness and the first-order torsional frequency and taking the allowable maximum stresses of the braking and left turning conditions as constraints, the multi-objective optimization of the structure is conducted using the NSGA-II genetic algorithm on the ISIGHT platform. The result of the Paret

关键词： coach structure property-based modeling (PBM) simplification modeling multi-objective optimization

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The Gamma/Weibull Customer Lifetime Model

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Communications in Mathematics and Statistics 2019年第1期7卷 33-59页

作者： Gen Ye Songjian Wang Key lab of Statistical modeling and Data Analysis of Yunnan Province Yunnan UniversityKunming 650091People’s Republic of China

This paper proposes a new customer lifetime model:the Gamma/Weibull distribution(G/W).Similar to the Pareto/NBD model,we propose a G/W/NBD model by combining the G/W distribution with a negative binomial distribution(NBD)and study its properties such as(i)the probability that a customer to be alive at a time point;(ii)the expectation and variance of the number of transactions for a customer during a fixed time period;(iii)the conditional expectation and conditional variance of the number of future transactions for a customer during a fixed time *** simulation studies are conducted to investigate the forecasting accuracy and flexibility of the proposed model.A CDNOW data set is analyzed by the proposed model.

关键词： Customer lifetime Gamma distribution Negative binomial distribution Purchase history Weibull distribution

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Industrial Application of a Deep Purification Technology for Flue Gas Involving Phase-Transition Agglomeration and Dehumidification

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Engineering 2018年第3期4卷 416-420页

作者： Jianmin Liu Fahua Zhu Xiuyuan Ma State Power Environmental Protection Research Institute State Environmental Protection Key Lab for Air Physical Simulation & Pollution Control Nanjing 210031 China

A moist plume forms when the flue gas emitted from wet desulfurization equipment exits into the ambi- ent air, resulting in a waste of water resources and visual pollution. In addition, sulfur trioxide （SO3）, water with dissolved salts, and particles in the wet flue gas form secondary pollution in the surrounding atmosphere. In this study, a deep purification technology for flue gas involving phase-transition agglom- eration and dehumidification （PAD） is proposed. This deep purification technology includes two technical routes： the integrated technology of phase-transition agglomeration and a wet electrostatic precipitator （PAW）; and the integrated technology of phase-transition agglomeration and a mist eliminator （PAM）. Industrial applications of PAW and PAM were carried out on 630 and 1000 MW coal-fired units, respectively. The results show that the average amount of recycled water obtained from wet flue gas by means of PAD is more than 4 g.（kg.℃）-1 Decreasing the wet flue gas temperature by 1.5-5.3 ℃ allows 5%-20% of the moisture in the flue gas to be recycled; therefore, this process could effectively save water resources and significantly reduce water vapor emissions. In addition, the moist plume is effectively elim- inated. With the use of this process, the ion concentration in droplets of flue gas is decreased by more than 65%, the SO3 removal efficiency from flue gas is greater than 75%, and the removal efficiency of par- ticulate matter is 92.53%.

关键词： Moist plume Phase-transition agglomeration Dehumidification Dissolved salts SO3 particulate matter

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A Client Selection Method Based on Loss Function Optimization for Federated Learning

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Computer modeling in Engineering & Sciences 2023年第10期137卷 1047-1064页

作者： Yan Zeng Siyuan Teng Tian Xiang Jilin Zhang Yuankai Mu Yongjian Ren Jian Wan School of Computer Science and Technology Hangzhou Dianzi UniversityHangzhou310018China Key laboratory of Complex System modeling and simulation Ministry of EducationHangzhou310018China Zhejiang Engineering Research Center of Data Security Governance Hangzhou310018China Intelligent Robotics Research Center Zhejiang LabHangzhou311100China HDU-ITMO Joint Institute Hangzhou Dianzi UniversityHangzhou310018China

Federated learning is a distributedmachine learningmethod that can solve the increasingly serious problemof data islands and user data privacy,as it allows training data to be kept locally and not shared with other *** trains a globalmodel by aggregating locally-computedmodels of clients rather than their ***,the divergence of local models caused by data heterogeneity of different clients may lead to slow convergence of the global *** this problem,we focus on the client selection with federated learning,which can affect the convergence performance of the global model with the selected local *** propose FedChoice,a client selection method based on loss function optimization,to select appropriate local models to improve the convergence of the global *** firstly sets selected probability for clients with the value of loss function,and the client with high loss will be set higher selected probability,which can make them more likely to participate in ***,it introduces a local control vector and a global control vector to predict the local gradient direction and global gradient direction,respectively,and calculates the gradient correction vector to correct the gradient direction to reduce the cumulative deviationof the local gradient causedby *** experiments to verify the validity of FedChoice on CIFAR-10,CINIC-10,MNIST,EMNITS,and FEMNIST datasets,and the results show that the convergence of FedChoice is significantly improved,compared with FedAvg,FedProx,and FedNova.

关键词： Federated learning model aggregation Non-IID

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Enhanced secondary pollution offset reduction of primary emissions during COVID-19 lockdown in China

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National Science Review 2021年第2期8卷 51-59页

作者： Xin Huang Aijun Ding Jian Gao Bo Zheng Derong Zhou Ximeng Qi Rong Tang Jiaping Wang Chuanhua Ren Wei Nie Xuguang Chi Zheng Xu Liangduo Chen Yuanyuan Li Fei Che Nini Pang Haikun Wang Dan Tong Wei Qin Wei Cheng Weijing Liu Qingyan Fu Baoxian Liu Fahe Chai Steven J.Davis Qiang Zhang Kebin He School of Atmospheric Sciences Nanjing University Chinese Research Academy of Environmental Sciences Department of Earth System Science Tsinghua University State Key Joint laboratory of Environment simulation and Pollution Control School of EnvironmentTsinghua University Department of Earth System Science University of California Jiangsu Environmental Monitoring Center Jiangsu Provincial Academy of Environment Science Shanghai Environmental Monitoring Center Beijing Key laboratory of Airborne particulate Matter Monitoring Technology Beijing Municipal Environmental Monitoring Center

To control the spread of the 2019 novel coronavirus(COVID-19), China imposed nationwide restrictions on the movement of its population(lockdown) after the Chinese New Year of 2020, leading to large reductions in economic activities and associated emissions. Despite such large decreases in primary pollution, there were nonetheless several periods of heavy haze pollution in eastern China, raising questions about the well-established relationship between human activities and air quality. Here, using comprehensive measurements and modeling, we show that the haze during the COVID lockdown was driven by enhancements of secondary pollution. In particular, large decreases in NOx emissions from transportation increased ozone and nighttime NO3radical formation, and these increases in atmospheric oxidizing capacity in turn facilitated the formation of secondary particulate matter. Our results, afforded by the tragic natural experiment of the COVID-19 pandemic, indicate that haze mitigation depends upon a coordinated and balanced strategy for controlling multiple pollutants.

关键词： COVID-19 haze pollution ozone emission reduction secondary pollution

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Robotic Etiquette:Socially Acceptable Navigation of Service Robots with Human Motion Pattern Learning and Prediction

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Journal of Bionic Engineering 2010年第2期7卷 150-160页

作者： Kun Qian,Xudong Ma,Xianzhong Dai,Fang Fang Key lab of Measurement and Control of Complex systems of Engineering (Ministry of Education,China), Southeast University,Nanjing 210096,P.R.China [a] Key lab of Measurement Control of Complex systems of Engineering (Ministry of Education China) Southeast University Nanjing 210096 P. R. China

Nonverbal and noncontact behaviors play a significant role in allowing service robots to structure their interactions *** this paper, a novel human-mimic mechanism of robot’s navigational skills was proposed for developing sociallyacceptable robotic *** on the sociological and physiological concerns of interpersonal interactions in movement,several criteria in navigation were represented by constraints and incorporated into a unified probabilistic cost grid for safemotion planning and control, followed by an emphasis on the prediction of the human’s movement for adjusting the robot’spre-collision navigational *** human motion prediction utilizes a clustering-based algorithm for modeling humans’indoor motion patterns as well as the combination of the long-term and short-term tendency prediction that takes into accountthe uncertainties of both velocity and heading *** simulation and real-world experiments verified the effectivenessand reliability of the method to ensure human’s safety and comfort in navigation.A statistical user trials study was also given tovalidate the users’favorable views of the human-friendly navigational behavior.

关键词： robotic etiquette navigation human motion prediction human-robot interaction service robot

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Chemical characteristics of fine particulate matter emitted from commercial cooking

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Frontiers of Environmental Science & Engineering 2016年第3期10卷 559-568页

作者： Bing PEI Hongyang CUI Huan LIU Naiqiang YAN School of Environmental Science and Engineering Shanghai Jiao Tong University Shanghai 200040 China Shanghai Environmental Monitoring Center Shanghai 200030 China Ministry of Education Key laboratory for Earth System modeling Center for Earth System Science Tsinghua University Beijing 100084 China School of Environment State Key Joint Laboratory of Environment Simulation and Pollution Control (SKLESPC) Tsinghua University Beijing 100084 China

The chemical characteristics of fine particulate matter （PM2.5） emitted from commercial cooking were explored in this study. Three typical commercial restau- rants in Shanghai, i.e., a Shanghai-style one （SHS）, a Sichuan-style one （SCS） and an Italian-style one （ITS）, were selected to conduct PM2.5 sampling. particulate organic matter （POM） was found to be the predominant contributor to cooking-related PM2.5 mass in all the tested restaurants, with a proportion of 69.1% to 77.1%. Specifically, 80 trace organic compounds were identified and quantified by gas chromatography/mass spectrometry （GC/MS）, which accounted for 3.8%-6.5% of the total PM2.5 mass. Among the quantified organic compounds, unsaturated fatty acids had the highest concentration, followed by saturated fatty acids. Comparatively, the impacts of other kinds of organic compounds were much smaller. Oleic acid was the most abundant single species in both SCS and ITS. However, in the case of SHS, linoleic acid was the richest one. ITS produced a much larger mass fraction of most organic species in POM than the two Chinese cooking styles except for monosaccharide anhy-drides and sterols. The results of this study could be utilized to explore the contribution of cooking emissions to PM2.5 pollution and to develop the emission inventory of PM2.5 from cooking, which could then help the policymakers design efficient treatment measures and control strategies on cooking emissions in the future.

关键词： commercial cooking PM2.5 chemical char- acteristics organic matter

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Impact of China’s Air Pollution Prevention and Control Action Plan on PM2.5 chemical composition over eastern China

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Science China Earth Sciences 2019年第12期62卷 1872-1884页

作者： Guannan GENG Qingyang XIAO Yixuan ZHENG Dan TONG Yuxuan ZHANG Xiaoye ZHANG Qiang ZHANG Kebin HE Yang LIU Department of Environmental Health Rollins School of Public HealthEmory UniversityAtlantaGeorgia 30322USA Ministry of Education Key laboratory for Earth System modeling Department of Earth System ScienceTsinghua UniversityBeijing 100084China State Key Joint laboratory of Environment simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing 100084China Key laboratory for Atmospheric Chemistry Chinese Academy of Meteorological SciencesCMABeijing 100081China

China promulgated the Air Pollution Prevention and Control Action Plan(the Action Plan)in 2013 and developed stringent control measures to mitigate fine particulate matter(PM2.5) ***,we investigated the PM2.5 chemical composition changes over eastern China associated with the Action Plan during 2013-2017 using satellite-based PM2.5 chemical composition data derived using CMAQ simulations and satellite *** PM2.5 concentrations decreased considerably during this time as a result of the reductions in all chemical species in *** population-weighted mean concentrations over eastern China decreased from 11.1 to 6.7μgm-3 for SO42-,13.8-13.1μgm-3 for NO3-,7.4-5.8μgm-3 for NH4+,9.9-8.4μgm-3 for OM,4.6-3.8μg m-3 for BC and 12.9-9.6μg m-3 for other species in ***42-had the largest reduction of 40%,while NO3-had the lowest reduction of 5%,resulting in a greater fraction of NO3-and a smaller fraction of SO42-in *** the three key regions,Beijing-Tianjin-Hebei had the largest reduction in PM2.5 and its chemical *** decrease in SO42-concentrations was in line with the reduction of SO2 emissions,and the major driver of the SO2 emission reductions was the industrial *** decrease in NO3 concentrations was limited because the decrease in SO2 emissions and the stable NH3 emissions facilitated the formation of NO3-from HNO3,which partially offset the reduction in NOx emissions driven by the power *** mitigate PM2.5 pollution more effectively,future efforts are needed to reduce NH3 emissions.

关键词： PM25 chemical composition Air Pollution Prevention and Control Action Plan Satellite remote sensing

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Faults identification of underwater vehicle based on the states-switching unscented Kalman Filter

Faults identification of underwater vehicle based on the sta...

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第25届中国控制与决策会议

作者： Fang Yuan Yinzhong Ye lab of Underwater Vehicles and Intelligent systems Shanghai Maritime University Shanghai Institute of Technology

ISBN: (纸本)9781467355322

Fault detection and identification play a key role in the active fault-tolerant control of underwater vehicles. A fault identification model based on the states-switching unscented Kalman Filters is constructed in this paper to the common sensor and actuator faults of the underwater vehicles. Firstly, states of underwater vehicle in each work mode are estimated by two groups of states-switching unscented Kalman Filters respectively. Then, each probability of the underwater vehicles work mode is calculated by Bayesian formula recursively. According to the probability value, faults can be identified. The simulation results indicate that the states-switching unscented Kalman Filters can estimate the underwater vehicle states rapidly and accurately with less computation. The faults identification system can identify various faults mode timelier and more accurately based on the states-switching unscented Kalman Filters states estimation.

关键词： Underwater vehicle Sensor Actuator States-switching unscented Kalman Filter Fault identification

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Development of database of real-world diesel vehicle emission factors for China

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Journal of Environmental Sciences 2015年第5期27卷 209-220页

作者： Xianbao Shen Zhiliang Yao Qiang Zhang David Vance Wagner Hong Huo Yingzhi Zhang Bo Zheng Kebin He State Key Joint laboratory of Environment simulation and Pollution Control School of Environment Tsinghua University School of Food and Chemical Engineering Beijing Technology and Business University Ministry of Education Key laboratory for Earth System modeling Center for Earth System Science Tsinghua University International Council on Clean Transportation (ICCT) Institute of Energy Environment and Economy Tsinghua University State Environmental Protection Key laboratory of Sources and Control of Air Pollution Complex Tsinghua University

A database of real-world diesel vehicle emission factors, based on type and technology, has been developed following tests on more than 300 diesel vehicles in China using a portable emission measurement system. The database provides better understanding of diesel vehicle emissions under actual driving conditions. We found that although new regulations have reduced real-world emission levels of diesel trucks and buses significantly for most pollutants in China, NOx emissions have been inadequately controlled by the current standards, especially for diesel buses, because of bad driving conditions in the real world. We also compared the emission factors in the database with those calculated by emission factor models and used in inventory studies. The emission factors derived from COPERT（Computer Programmer to calculate Emissions from Road Transport） and MOBILE may both underestimate real emission factors, whereas the updated COPERT and PART5（Highway Vehicle particulate Emission modeling Software） models may overestimate emission factors in China. Real-world measurement results and emission factors used in recent emission inventory studies are inconsistent,which has led to inaccurate estimates of emissions from diesel trucks and buses over recent years. This suggests that emission factors derived from European or US-based models will not truly represent real-world emissions in China. Therefore, it is useful and necessary to conduct systematic real-world measurements of vehicle emissions in China in order to obtain the optimum inputs for emission inventory models.

关键词： Diesel vehicle Emission factor Portable emission measurement system Database China

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