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    01 April 2020, Volume 25 Issue 2 Previous Issue    Next Issue

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    Demand Analysis and Management Suggestion: Sharing Epidemiological Data Among Medical Institutions in Megacities for Epidemic Prevention and Control
    CAI Qinyi (蔡沁怡), MI Yiqun (宓轶群), CHU Zhaowu (储昭武), ZHENG Yuanyi (郑元义), CHEN Fang (陈方), LIU Yicheng (刘义成)
    2020, 25 (2):  137-139.  doi: 10.1007/s12204-020-2166-3
    Abstract ( 428 )   PDF (105KB) ( 297 )  
    During the prevention of coronavirus disease 2019 (COVID-19), epidemiological data is essential for controlling the source of infection, cutting off the route of transmission, and protecting vulnerable populations. Following Law of the People’s Republic of China on Prevention and Treatment of Infectious Diseases and other related regulations, medical institutions have been authorized to collect the detailed information of patients, while it is still a formidable task in megacities because of the significant patient mobility and the existing information sharing barrier. As a smart city which strengthens precise epidemic prevention and control, Shanghai has established a multi-department platform named “one-net management” on dynamic information monitoring. By sharing epidemiological data with medical institutions under a safe environment, we believe that the ability to prevent and control epidemics among medical institutions will be effectively and comprehensively improved.
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    Prediction of COVID-19 Outbreak in China and Optimal Return Date for University Students Based on Propagation Dynamics
    HUANG Ganyu (黄甘雨), PAN Qiaoyi (潘荍仪), ZHAO Shuangying (赵双楹), GAO Yucen (高宇岑), GAO Xiaofeng (高晓沨)
    2020, 25 (2):  140-146.  doi: 10.1007/s12204-020-2167-2
    Abstract ( 494 )   PDF (550KB) ( 311 )  
    On 12 December 2019, a novel coronavirus disease, named COVID-19, began to spread around the world from Wuhan, China. It is useful and urgent to consider the future trend of this outbreak. We establish the 4+1 penta-group model to predict the development of the COVID-19 outbreak. In this model, we use the collected data to calibrate the parameters, and let the recovery rate and mortality change according to the actual situation. Furthermore, we propose the BAT model, which is composed of three parts: simulation of the return rush (Back), analytic hierarchy process (AHP) method, and technique for order preference by similarity to an ideal solution (TOPSIS) method, to figure out the best return date for university students. We also discuss the impacts of some factors that may occur in the future, such as secondary infection, emergence of effective drugs, and population flow from Korea to China.
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    CIRD-F: Spread and Influence of COVID-19 in China
    ZHOU Lingyun (周凌云), WU Kaiwei (吴凯伟), LIU Hanzhi (刘涵之), GAO Yuanning (高远宁), GAO Xiaofeng (高晓沨)
    2020, 25 (2):  147-156.  doi: 10.1007/s12204-020-2168-1
    Abstract ( 746 )   PDF (887KB) ( 350 )  
    The outbreak of coronavirus disease 2019 (COVID-19) has been spreading rapidly in China and the Chinese government took a series of policies to control the epidemic. Therefore, it will be helpful to predict the tendency of the epidemic and analyze the influence of official policies. Existing models for prediction, such as cabin models and individual-based models, are either oversimplified or too meticulous, and the influence of the epidemic was studied much more than that of official policies. To predict the epidemic tendency, we consider four groups of people, and establish a propagation dynamics model. We also create a negative feedback to quantify the public vigilance to the epidemic. We evaluate the tendency of epidemic in Hubei and China except Hubei separately to predict the situation of the whole country. Experiments show that the epidemic will terminate around 17 March 2020 and the final number of cumulative infections will be about 78 191 (prediction interval, 74 872 to 82 474). By changing the parameters of the model accordingly, we demonstrate the control effect of the policies of the government on the epidemic situation, which can reduce about 68% possible infections. At the same time, we use the capital asset pricing model with dummy variable to evaluate the effects of the epidemic and official policies on the revenue of multiple industries.
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    Preliminary Assessment of the COVID-19 Outbreak Using 3-Staged Model e-ISHR
    LI Sijia (李斯佳), SONG Kun (宋琨), YANG Boran (杨博然), GAO Yucen (高宇岑), GAO Xiaofeng (高晓沨)
    2020, 25 (2):  157-164.  doi: 10.1007/s12204-020-2169-0
    Abstract ( 372 )   PDF (472KB) ( 219 )  
    The outbreak of coronavirus disease 2019 (COVID-19) in Wuhan has aroused widespread concern and attention from all over the world. Many articles have predicted the development of the epidemic. Most of them only use very basic SEIR model without considering the real situation. In this paper, we build a model called e-ISHR model based on SEIR model. Then we add hospital system and time delay system into the original model to simulate the spread of COVID-19 better. Besides, in order to take the government’s control and people’s awareness into consideration, we change our e-ISHR model into a 3-staged model which effectively shows the impact of these factors on the spread of the disease. By using this e-ISHR model, we fit and predict the number of confirmed cases in Wuhan and China except Hubei. We also change some of parameters in our model. The results indicate the importance of isolation and increasing the number of beds in hospital.
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    D2EA: Depict the Epidemic Picture of COVID-19
    LIU Chenzhengyi (刘陈正轶), ZHAO Jingwei (赵经纬), LIU Guohang (刘国航), GAO Yuanning (高远宁), GAO Xiaofeng (高晓沨)
    2020, 25 (2):  165-176.  doi: 10.1007/s12204-020-2170-7
    Abstract ( 377 )   PDF (748KB) ( 296 )  
    The outbreak of coronavirus disease 2019 (COVID-19) has aroused a global alert. To release social panic and guide future schedules, this article proposes a novel mathematical model, the Delay Differential Epidemic Analyzer (D2EA), to analyze the dynamics of epidemic and forecast its future trends. Based on the traditional Susceptible-Exposed-Infectious-Recovered (SEIR) model, the D2EA model innovatively introduces a set of quarantine states and applies both ordinary differential equations and delay differential equations to describe the transition between two states. Potential variations of practical factors are further considered to reveal the true epidemic picture. In the experiment part, we use the D2EA model to simulate the epidemic in Hubei Province. Fitting to the collected real data as non-linear optimization, the D2EA model forecasts that the accumulated confirmed infected cases in Hubei Province will reach the peak at the end of February and then steady down. We also evaluate the effectiveness of the quarantine measures and schedule the date to reopen Hubei Province.
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    Derivations of Exact Lattice Boltzmann Evolution Equation
    YE Huanfeng (叶欢锋), KUANG Bo (匡波), YANG Yanhua (杨燕华)
    2020, 25 (2):  177-185.  doi: 10.1007/s12204-020-2158-3
    Abstract ( 348 )   PDF  
    A comparative analysis on the schemes for exact lattice Boltzmann (LB) evolution equation is presented in this paper. It includes two classical exact LB schemes, i.e., B¨osch-Karlin (BK) scheme and He-Luo (HL) scheme, and the present Taylor-expansion (TE) scheme. TE scheme originates from the extension of BK scheme. The mathematical mechanism and the equilibrium distribution evolution behind these exact schemes have been detailedly addressed. After that, an analysis is carried out to discuss the cause of the LB equation difference among the schemes, which offers an insight of the exactness in these schemes and brings up their continuity precondition. At last, the schemes are systematically addressed for their pros and cons in the further development of LB equations.
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    Prediction of Fluid Force Exerted on Bluff Body by Neural Network Method
    ZHAO Yong (赵勇), MENG Yang (孟杨), YU Pengyao (于鹏垚), WANG Tianlin (王天霖), SU Shaojuan (苏绍娟)
    2020, 25 (2):  186-192.  doi: 10.1007/s12204-019-2140-0
    Abstract ( 295 )   PDF (298KB) ( 40 )  
    With the development of artificial intelligence, artificial neural network (ANN) has been widely used in recent years. In this paper, the method is applied to the prediction of the fluid force exerted on the bluff body when flow passes around. Firstly, back propagation (BP) model and convolutional neural network (CNN) model are introduced; then the mapping relation between the shape of bluff body and the fluid force, which is calculated by computational fluid dynamics (CFD), is established by sample training. Finally, it is used to predict the fluid force of the new shape bluff body. By taking the CFD results as benchmark, CNN model is capable of predicting both the resistance and lift force, while BP model is incompetent to predict lift force. Furthermore, both CNN and BP models have a significant advantage in prediction efficiency, compared by CFD calculation method.
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    Extended Inverse Gaussian Distribution: Properties and Application
    LAI Junfeng (赖俊峰), JI Dandan (季丹丹), YAN Zaizai (闫在在)
    2020, 25 (2):  193-200.  doi: 10.1007/s12204-019-2144-9
    Abstract ( 285 )   PDF (277KB) ( 50 )  
    In this paper, a new distribution called the extended inverse Gaussian (EIG) distribution is introduced. By means of the method of T-X family, the new distribution is compounded by the inverse Gaussian (IG) and Weibull distributions. We study its fundamental properties, such as probability density function, hazard rate function, raw moments, moments generating function, skewness and kurtosis, and residual life. We also discuss the maximum likelihood estimators and asymptotic confident intervals of parameters in new distribution. Finally, the EIG distribution and several other competing distributions are fitted into an actual data set and it is shown that the EIG distribution has a superior performance among the compared distributions by making use of various goodness-of-fit tests.
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    Attacking Strategy of Multiple Unmanned Surface Vehicles with Improved GWO Algorithm Under Control of Unmanned Aerial Vehicles
    WU Xin (武星), PU Juan (蒲娟), XIE Shaorong (谢少荣)
    2020, 25 (2):  201-207.  doi: 10.1007/s12204-020-2159-2
    Abstract ( 298 )   PDF (240KB) ( 34 )  
    Unmanned combat system is one of the important means to capture information superiority, carry out precision strike and accomplish special combat tasks in information war. Unmanned attack strategy plays a crucial role in unmanned combat system, which has to ensure the attack by unmanned surface vehicles (USVs) from failure. To meet the challenge, we propose a task allocation algorithm called distributed auction mechanism task allocation with grey wolf optimization (DAGWO). The traditional grey wolf optimization (GWO) algorithm is improved with a distributed auction mechanism (DAM) to constrain the initialization of wolves, which improves the optimization process according to the actual situation. In addition, one unmanned aerial vehicle (UAV) is employed as the central control system to establish task allocation model and construct fitness function for the multiple constraints of USV attack problem. The proposed DAGWO algorithm can not only ensure the diversity of wolves, but also avoid the local optimum problem. Simulation results show that the proposed DAGWO algorithm can effectively solve the problem of attack task allocation among multiple USVs.
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    Detection and Quantization Technique of Optical Distributed Acoustic Coupling Based on φ-OTDR
    ZHANG Yang (张洋), XU Hongxuan (徐弘萱), ZHU Xianxun (朱贤训), ZHAO Zhiyang (赵之阳), ZUO Jiancun (左健存)
    2020, 25 (2):  208-213.  doi: 10.1007/s12204-020-2161-8
    Abstract ( 276 )   PDF (866KB) ( 33 )  
    The detection of multiple acoustic disturbances by optical fiber is a hot research topic in the field of optical fiber sensing. This paper considers adopting an optical distributed acoustic sensing (DAS) system to detect multiple acoustic disturbances, proposes a new approach to processing the DAS signal based on time-space average in frequency domain, and overcomes the randomness of DAS time domain signal. Finally, it obtains a functional model of single-frequency (50—1 000 Hz) sound pressure level and DAS signal intensity, and also the cut-off frequency of acoustic disturbance is detected by DAS system.
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    Feature Recognition and Selection Method of the Equipment State Based on Improved Mahalanobis-Taguchi System
    WANG Ning (王宁), ZHANG Zhuo (张卓)
    2020, 25 (2):  214-222.  doi: 10.1007/s12204-019-2107-1
    Abstract ( 265 )   PDF (246KB) ( 37 )  
    Mahalanobis-Taguchi system (MTS) is a kind of data mining and pattern recognition method which can identify the attribute characteristics of multidimensional data by constructing Mahalanobis distance (MD) measurement scale. In this paper, considering the influence of irregular distribution of the sample data and abnormal variation of the normal data on accuracy of MTS, a feature recognition and selection model of the equipment state based on the improved MTS is proposed, and two aspects of the model namely construction of the original Mahalanobis space (MS) and determination of the threshold are studied. Firstly, the original training sample space is statistically controlled by the X-bar-S control chart, and extreme data of the single characteristic attribute is filtered to reduce the impact of extreme condition on the accuracy of the model, so as to construct a more robust MS. Furthermore, the box plot method is used to determine the threshold of the model. And the stability of the model and the tolerance to the extreme condition are improved by leaving sufficient range of the variation for the extreme condition which is identified as in the normal range. Finally, the improved model is compared with the traditional one based on the unimproved MTS by using the data from the literature. The result shows that compared with the traditional model, the accuracy and sensitivity of the improved model for state identification can be greatly enhanced.
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    Finite Element Simulation Study on Blade Coating of Wind Turbine
    CEN Haitang (岑海堂), WEI Ruitao (魏瑞涛), TIAN Wenliang (田文良), HUANG Jinlei (黄金磊), NA Risu (那日苏)
    2020, 25 (2):  223-229.  doi: 10.1007/s12204-019-2090-6
    Abstract ( 312 )   PDF (2307KB) ( 38 )  
    Due to the surface protection structure of wind turbine blades, coating plays a key role in ensuring the surface quality of blades and improving the working performance of wind turbine. In this paper, a simplified method of finite element simulation on blade coating of wind turbine is carried out by means of theoretical analysis and computer software simulation. The influence of particle erosion velocity, mass flow rate and particle diameter was made clear on the coating erosion. This will provide a theoretical reference for improving the cover technique of wind turbine blade coating and improving the coating reliability.
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    Key-Component Force and Modal Analysis of Chamfering Machine for Curved Side-Shaped Ice Spoon
    GAO Zhifa (高志发), CHEN Qiang (陈强), WU Jianxin (武建新), LIU Xiaoyu (刘晓宇)
    2020, 25 (2):  230-236.  doi: 10.1007/s12204-019-2145-8
    Abstract ( 321 )   PDF (1116KB) ( 42 )  
    The edge-curved ice spoon is a wooden tool to eat ice cream, and the machine tool adopted to chamfer and deburr the unformed curved edge ice spoon is called surface-taking machine (chamfering machine). In the course of cutting, the results are primarily dependent on the speed of cutter shaft. In order to guarantee the quality of the spoon, scraping-edge device of the surface-taking machine is anatomized and designed, and the working principle of the surface picking machine is introduced. The cutting force is analyzed from theoretical and experiential perspectives. The device is modeled in the SolidWorks and simulated by ADAMS to attain time-varying curves of scraping-edge device displacement and contact force of the cam and wheel. The modal analysis of the cutter shaft is carried out on ANSYS Workbench, the vibration frequency and vibration mode of the former six steps are attained, and the critical speed of the cutter shaft is calculated to determine the rotational speed of the cutter shaft, which effectively avoids the resonance zone and ensures the effective operation of device. Additionally, the actual production and processing are able to lay a theoretical basis.
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    Statistical Inference of Reliability with Multivariate Accelerated Degradation Data
    ZHOU Yuan (周源), WANG Haowei (王浩伟), Lü Weimin (吕卫民)
    2020, 25 (2):  237-245.  doi: 10.1007/s12204-019-2124-0
    Abstract ( 240 )   PDF (308KB) ( 38 )  
    Accelerated degradation test (ADT) has become an efficient approach to assess the reliability of degradation products within limited time and budget. Some products have more than one degradation process that is responsible for failure of product, which introduces some problems of modeling accelerated degradation data and estimating unknown parameters. In order to solve the problems, a practical method of inferring reliability with multivariate accelerated degradation data is proposed in this paper. Stochastic processes are used to fit accelerated degradation data, and then margin reliability functions are derived from the degradation models. Unlike the traditional assumption that the degradation increments of multivariate degradation processes at the same observing time are mutually dependent, the margin reliabilities at the same time are considered to be dependent, which is applicable to the situation that multivariate degradation data is not simultaneously observed. Copula functions are used to describe the dependency between marginal reliabilities, and the two situations that copula parameter is independent of accelerated stress or dependent on accelerated stress are both considered. In the case study, the bivariate accelerated degradation data of O-ring rubber is used to demonstrate our proposed method. The research results indicate that the proposed method provides a practical and feasible approach to reliability inference with multivariate accelerated degradation data.
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    Reliability Design of an Electronic Cam Curve for Flying Shear Machine in Short Materials Cutting
    BI Junxi (毕俊喜), FAN Wenze (樊文泽), HUANG Hongzhong (黄洪钟), LIU Bin (刘斌)
    2020, 25 (2):  246-252.  doi: 10.1007/s12204-019-2106-2
    Abstract ( 303 )   PDF (386KB) ( 35 )  
    The structure and the production process for flying shear machine are introduced first. Then, a quintic polynomial is applied to the design of an electronic cam system for the rotary knife axis in short materials cutting. The dimensionless equation for a quintic polynomial cam curve is deduced. Finally, the curve is plotted with the cam constructor integrated into Siemens engineering development software SCOUT and it is tested with a laboratory platform, which consists of a motion controller SIMOTION and motor drivers SINAMICS S120. The results show that the running stability of the flying shear machine and the position control accuracy of the rotary knife can be effectively improved by using the curve designed in this paper.
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    Optimization of Linear Consecutive-k-Out-of-n Systems with Birnbaum Importance Based Ant Colony Optimization Algorithm
    WANG Wei (王伟), CAI Zhiqiang (蔡志强), ZHAO Jiangbin (赵江滨), SI Shubin (司书宾)
    2020, 25 (2):  253-260.  doi: 10.1007/s12204-019-2125-z
    Abstract ( 238 )   PDF (169KB) ( 44 )  
    The linear consecutive-k-out-of-n: failure (good) (Lin/Con/k/n:F(G)) system consists of n interchangeable components that have different reliabilities. These components are arranged in a line path and different component assignments change the system reliability. The optimization of Lin/Con/k/n:F(G) system is to find an optimal component assignment to maximize the system reliability. As the number of components increases, the computation time for this problem increases considerably. In this paper, we propose a Birnbaum importance-based ant colony optimization (BIACO) algorithm to obtain quasi optimal assignments for such problems. We compare its performance using the Birnbaum importance based two-stage approach (BITA) and Birnbaum importancebased genetic local search (BIGLS) algorithm from previous researches. The experimental results show that the BIACO algorithm has a good performance in the optimization of Lin/Con/k/n:F(G) system.
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    Fatigue Life Analysis of Longitudinal Welding Seam for Wind Turbine Tower
    GUO Wenqiang (郭文强), SUN Pengwen (孙鹏文), NIU Lei (牛磊), WANG Zongtao (王宗涛)
    2020, 25 (2):  261-265.  doi: 10.1007/s12204-020-2171-6
    Abstract ( 230 )   PDF (302KB) ( 38 )  
    Tower is an important fundamental component of large-scale wind turbines. The fatigue performance of the tower welded part directly affects the running safety and reliability of wind turbines. A fatigue life predicting method for the longitudinal welding seam of the tower is proposed in this paper. Under the precondition of satisfying the limit strength, the time series stress of each working condition is obtained by DIN18800-4 section stress calculation. Combined with the rain-flow counting method and the Miner linear cumulative damage theory, the fatigue life of the tower longitudinal weld is predicted. The results show that the tower structure meets the design requirement, and the feasibility and effectiveness of the method are verified.
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    Probability Model of Residual Strength of Materials Under Uncertain Cyclic Load
    GAO Jianxiong (高建雄), AN Zongwen (安宗文), MA Qiang (马强), ZHAO Shendan (赵申诞)
    2020, 25 (2):  266-272.  doi: 10.1007/s12204-020-2172-5
    Abstract ( 260 )   PDF (400KB) ( 41 )  
    Residual strength is usually used to characterize the degradation rule of material performance under the cyclic load, which is critical to fatigue life prediction as well as reliability assessment of materials. In order to reveal the probability characteristics of residual strength of material under uncertain cyclic load, the relationship between external stress and fatigue life (i.e., the equation of S-N curve) is considered in this study. Firstly, the probability density function of fatigue life under uncertain cyclic load is derived from the probability density function of external stress. Then, a probability model of residual strength is proposed on the basis of a fundamental assumption that the residual strength and the remaining life of material depend on the same damage state. Finally, the validity of the proposed model is verified by an illustrative example. The results indicate that the probability distribution of residual strength of material is affected by both the external factor (i.e., probability characteristics of the load) and the internal factor (i.e., fatigue performance parameters of material).
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