Journal of Northeastern University(Natural Science)

Time-Divided SIQR Model for COVID-19 Analysis and Prediction in Consideration of Public Opinion

BAO Yu-bin， LIU Ji-ting， LI Xiao-yu

2022, 43 (8): 1065-1073. DOI: 10.12068/j.issn.1005-3026.2022.08.001

Abstract ( 1017 )

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In order to scientifically identify and judge the trend of local COVID-19 recurrence， and to control and prevent the spread of its epidemic， a novel time-divided SIQR coronavirus pneumonia infection model with nonlinear parameters is established. It divides the epidemic spread into three periods， and comprehensively considers the intervention effect of public opinion and prevention measures on each period. The simulation results on several real datasets show that the rapid enhancement of the screening of infected and uncontrolled people will significantly interfere with the spread of the epidemic and make the inflection point of slowing down the number of infections come early. The prediction results of the epidemic situation at Dalian in December 2020 by the proposed model not only have smaller mean square error， but also the change trend of the predication curve is closer to the reality compared with other baseline models. Additionally， the epidemic situation with longer free transmission period and stronger aggregation is simulated by the proposed model. The prediction error is also smaller than that of the compared models on the real data. This shows that the model has certain universality and robustness.

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Traffic Target Detection in Complex Scenes Based on Improved YOLOv5 Algorithm

GU De-ying， LUO Yu-lun， LI Wen-chao

2022, 43 (8): 1073-1079. DOI: 10.12068/j.issn.1005-3026.2022.08.002

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Real-time target detection in traffic scenarios is the prerequisite of electronic monitoring， automatic driving， and other functions. In view of the low detection efficiency of existing target detection algorithms and the low accuracy of most light target detection algorithms， which are easy to obtain wrong or insufficient target detection， this paper adopts the improved YOLOv5 target detection algorithm for model training， and the pseudo-label strategy for training process optimization. Then， the KITTI traffic target dataset tags are merged into three categories for model training and testing. Through the experimental comparison， the improved YOLOv5 model in this paper achieves 92.5% mAP in all categories， which is 3% higher than the original YOLOv5 training model. Finally， the three categories of the trained models are deployed on the Jetson Nano embedded platform for inference testing， and TensorRT is used to accelerate inference. The average inference time per frame of image is 77ms， which meets the goal of real-time detection.

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A Method of Model Parameters Subset Selection for Left Ventricle Pressure Waveform Individual Estimation

LIU Jun， HAO Li-ling， HE Guang-yu， XU Li-sheng

2022, 43 (8): 1080-1088. DOI: 10.12068/j.issn.1005-3026.2022.08.003

Abstract ( 577 )

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Since the left ventricle pressure waveform(LVPW)estimation is based on the model with numerous patient specific parameters， there is a great need to reduce the computation cost. A parameter subset selection strategy based on sensitivity analysis is proposed to solve these problems. LVPW features are chosen as outputs of a systemic circulation model. The meta model is created by adaptive sparse polynomial chaos expansion algorithm， and then Sobol sensitivity index is computed. Finally， the parameters which have large impact on LVPW features are selected as parameter subset. The parameter subset selection proposed in this paper can provide help for applying model to patient specific situations in clinical applications. Meantime， the results indicate that the reducing size of parameter subset can decrease the complex computation of parameter optimization significantly. Furthermore， LVPW estimation based on the proposed method has high correlation with that based on full model parameters.

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Aided Diagnosis Method of Alzheimer’s Disease Based on Sequential Discriminative Subgraph

XIN Jun-chang， GUO En-ming， ZHANG Jia-zheng

2022, 43 (8): 1089-1096. DOI: 10.12068/j.issn.1005-3026.2022.08.004

Abstract ( 811 )

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In order to solve the problem of ignoring the dynamic connection changes of the brain network in the aided diagnosis of Alzheimer’s disease by the existing discriminative subgraph method， an aided diagnosis method based on the sequential discriminative subgraph was proposed. The functional magnetic resonance imaging (fMRI) is processed to form binary matrices， and multiple dynamic brain networks of the same subject form sequential difference graphs， and then frequent subgraph mining and frequent sequence mining are performed to screen out biomarkers(sequential discriminative subgraph)that retain the time sequence characteristics of the brain network. A set of data from the ADNI public data set was obtained for experiments， and a large number of experimental comparisons were conducted with the existing early Alzheimer’s disease aided diagnosis methods， which proves that the aided diagnosis accuracy of this method is improved by 12.7% on this data set and the effectiveness of the proposed method.

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Simulation on Variable Thickness Rolling Process of 2205 Duplex Stainless Steel

JI Ya-feng， NIU Jing， WANG Xiao-jun， SUN Jie

2022, 43 (8): 1097-1105. DOI: 10.12068/j.issn.1005-3026.2022.08.005

Abstract ( 607 )

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The edge cracks in stainless steels during variable thickness rolling(VTR) process greatly affect the product quality. Based on the VTR and plastic deformation theory， the hot-deformation constitutive equation of 2205 duplex stainless steel and mechanical model of different rolling regions to solve the edge crack problem are built， combining with experimental data from Gleeble-3800 thermal simulation. In the cross VTR process， different reduction rates in the edge and middle regions of the strip can be controlled. Using DEFORM software to simulate the rolling process， the edge damages from the cross VTR and ordinary rolling are compared and the metal flows in different thickness are analyzed. The results show that the factor of edge damage in the cross VRT process is reduced by 22% than that in ordinary one， and changing the curve of edge variable thickness can effectively solve the edge damage problem， so as to improve the product quantity and quality of stainless steel plate and strip.

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Interfacial Reaction and Thermal Stability of SiC_f/Ti₂AlNb Composites

FU Yue-chun， WEI Ze-qi， YANG Li-na， WANG Yu-min

2022, 43 (8): 1105-1112. DOI: 10.12068/j.issn.1005-3026.2022.08.006

Abstract ( 501 )

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The layer of interfacial reaction(IR)is an important influencing factor on mechanical properties of SiC fiber (SiC_f) reinforced titanium matrix composites. The interfacial reaction， element distribution at the interface and interfacial thermal stability of SiC_f/Ti₂AlNb composites during hot isostatic pressing and thermal exposure procedures are studied. The results show that the main IR product in SiC_f/Ti₂ AlNb composites is TiC， and the TiSi₂ and NbSi₂ phases are observed during the thermal exposure procedure. The thickness of IR layer in the SiC_f/Ti₂AlNb composite obeys the Arrhenius law， and the growth rate of IR layer increases with the thermal exposure temperature. The activation energy for the IR layer growth is 24.27kJ/mol， and the frequency factor is 2.80×10^-4 m/s^1/2. The interface of SiC_f/Ti₂AlNb composites shows good thermal stability at 700℃ and below.

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Influence of In-Wheel Motors Eccentricity on Ride Comfort of Electric Vehicles on Random Roads

LI Jie， JIA Chang-wang， CHENG Lin-hai， ZHAO Qi

2022, 43 (8): 1113-1119. DOI: 10.12068/j.issn.1005-3026.2022.08.007

Abstract ( 647 )

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To analyze the influence of in-wheel motors eccentricity on the ride comfort of electric vehicles， a four degree-of-freedom vibration model of electric vehicles was established to consider the mass and excitation of in-wheel motors. The corresponding state equation and output vector expression were derived， and the ride comfort evaluation index was determined. The random road excitation of the front wheel was established by using the filtered white noise method. The random road excitation relationship between the rear wheel and the front wheel was obtained by combining the Laplace transformation and the fourth-order symmetric Pade approximation. The whole vertical excitation of a typical four-phase 8/6-pole switched reluctance motor was presented. The simulation of random road excitation and in-wheel motor excitation was realized， and the ride comfort simulation and comparison of four working conditions were carried out on a B-grade road. The results showed that in-wheel motors eccentricity has an important influence on the ride comfort of electric vehicles on random roads， and the negative effect of in-wheel motors eccentricity should be considered in the design of electric vehicles.

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Multi-objective Optimization Layout of Aero-Engine Pipe Routing Based on IMOFA

ZHANG Yu， LU Hao， LYU Dong， GONG Ya-dong

2022, 43 (8): 1120-1126. DOI: 10.12068/j.issn.1005-3026.2022.08.008

Abstract ( 626 )

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To solve the existing problems of pipe routing layout for aero-engines， a multi-objective optimization layout method of aero-engine pipe routing based on improved multi-objective firefly algorithm(IMOFA) is proposed. In the method， the multi-objective optimization layout mathematical model of aero-engine pipe routing is established， which takes the shortest pipe length， the least number of elbows， and the minimal energy value as the optimization objectives. Then， by combining with adaptive disturbance strategy and elite strategy， an IMOFA algorithm for multi-objective optimization layout of aero-engine pipe routing is provided， which realizes the multi-objective optimal layout of aero-engines pipe routing. Finally， the feasibility and effectiveness of the proposed method is verified by case studies.

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Grinding Wheel Wear Experiment Based on Acoustic Emission Monitoring

YIN Guo-qiang， WANG Dong， GUAN Yun-yun， WANG Jia-hui

2022, 43 (8): 1127-1133. DOI: 10.12068/j.issn.1005-3026.2022.08.009

Abstract ( 614 )

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Due to the high hardness and wear resistance of difficult-to-machine materials， the grinding wheel wears faster in the grinding process. At present， the dressing and replacement cycle of the grinding wheel is mainly judged by experience， which may lead to untimely dressing. Accordingly， the wear state of grinding wheel was accurately monitored by combining acoustic emission signals and grinding force signals. By analyzing the characteristic parameters of acoustic emission signals， the changes of grinding force and grinding force ratio during the grinding of grinding wheels with different wear states， the wear state of grinding wheels during the experimental process was comprehensively judged. The results showed that the acoustic emission signals are all correlated with the grinding wheels’ wear state， and the grinding force ratio is the most correlated with the grinding wheels’ wear degree， which proves the effectiveness of the acoustic emission monitoring technology in grinding wheel dressing and provides theoretical guidance for the actual production process.

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An Unevenness Coefficient Method of Modal Displacements for Intra-laminar Damage Detection in Composite Laminates

ZHANG Xu，LYU Jian-qi， LI Wei， LI Xiao-peng

2022, 43 (8): 1134-1141. DOI: 10.12068/j.issn.1005-3026.2022.08.010

Abstract ( 573 )

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A new detection method using the power function of modal curvature differences as damage index was proposed to accurately identify the location and extent of composite material damage. Based on the APDL language of ANSYS， the Shell181 element was used to establish the simply supported laminate model， and the intra-laminar fiber failure model was constructed according to the Camanho damage criterion. The natural frequency of the laminate and the modal displacement of mesh nodes were obtained by modal analysis. The Gaussian curvature of the surface was obtained by the difference method， and the change of the Gaussian curvature difference before and after damage with the damage location and extent was studied. The square of the Gaussian curvature difference was used to increase the gap between the peak value and that of the other regions， which was defined as the modal displacement unevenness coefficient to detect the intra-laminar damage location and extent. The results show that the modal displacement unevenness coefficient improves the accuracy of the damage location detection， and it increases with the rise of the damage extent. The research conclusions provide guidance for improving the non-destructive testing methods for the intra-laminar damage of composite laminates.

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Simulation Method of Damage and Fracture for Brittle Rock Based on Microplane Model and Regularization

YUAN Yang， XU Tao， ZHOU Guang-lei， LE Zhi-hua

2022, 43 (8): 1141-1148. DOI: 10.12068/j.issn.1005-3026.2022.08.011

Abstract ( 458 )

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To solve the mesh dependence of finite element method in simulating the failure of brittle rock， an improved microplane damage model was built based on the microplane model and regularization method. And the numerical simulations were compared with the experimental results under uniaxial compression test. Heterogeneous indexes were introduced for the damage process simulation of three points bending tests. The results showed that the damage area was more concentrated at the high heterogeneous index. In addition， the three points bending tests with different characteristic length were simulated by regularization based on higher-order deformation gradients. The results showed that the damage evolution of microplane damage models with regularization are analogous when the characteristic length is 1mm， while the microplane damage model without regularization has a significant mesh-dependence at different mesh size. Finally， the load-displacement relationship of normal model and regularization model was contrasted. Mesh density has little effect on the microplane damage model based on regularization with higher-order deformation gradients.

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Sensitivity Analysis on the Estimation of Mechanical Parameters for Rock Mass Around Large Cavern Based on RMR and H-B Criterion

LIU Guo-feng， ZHOU Chi， LI Zhi-qiang， HE Ben-guo

2022, 43 (8): 1149-1158. DOI: 10.12068/j.issn.1005-3026.2022.08.012

Abstract ( 402 )

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Using RMR(rock mass rating)and Hoek-Brown(H-B)criterion to estimate mechanical parameters of rock mass is an effective way to determine parameters of the surrounding rock mass around large underground cavern. Considering that the uncertainty of input parameters directly affects the estimation accuracy of mechanical parameter of rock mass， relying on the large underground powerhouse engineering of Baihetan Hydropower Station， the sensitivity between the input parameters of H-B criterion and mechanical parameters of rock mass is studied through in-situ test， laboratory test and numerical simulation， in which the sensitivity factor is used to describe the sensitivity relationships. The results show that the sensitivity of mechanical parameters of rock mass to input parameters is ranked as RMR>σ_ci(uniaxial compressive strength of rock)>m_i(rock material constant)， and the influence of RMR is the most significant. The error of ±5% in the determination of RMR would result in a deviation of about 20%， 22% and 13% in the estimated results of elastic modulus， internal friction angle and cohesion， respectively. When the error of σ_ci and m_i is less than ±20%， the influence of them on the estimation results of internal friction angle and cohesion is less than 4% and 10%， respectively. This research can provide reference for the accuracy evaluation on estimation of mechanical parameter of rock mass around similar large underground caverns.

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Numerical Simulation of Dynamic Response of Surrounding Rock Anchored by NPR Bolt/Cable

GUO Long-ji， HE Man-chao， QU Ding-jun， TAO Zhi-gang

2022, 43 (8): 1159-1167. DOI: 10.12068/j.issn.1005-3026.2022.08.013

Abstract ( 1635 )

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In this paper， a coal mine is used as the research region to study the problems caused by deep mining， such as rock burst， large deformation and failure of conventional bolt/cable. Based on the large deformation failure mechanism of high in-situ stress soft rock， the FLAC3D-PFC3D coupling modeling method was used to carry out the dynamic numerical simulation study of NPR (negative Poisson’s ratio) bolt/cable for the first time. Numerical models of two support schemes of PR and NPR bolt/cable were established， and the stress and displacement of the surrounding rock of the chamber and the bolt/cable under dynamic loads were compared and analyzed. The results show that under the impact load of 25MPa， 21 of the 25 PR support bolts/cables failed， the surrounding rock was damaged in a large area， the coupling wall was severely deformed， and the chamber presented inner convex arc-shaped deformation and failure. Under the same conditions， none of the NPR bolts/cables failed， and the stability of the surrounding rock of the chamber remained good.

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Effect of Mechanical Activation on Pozzolanic Activity of Iron Tailings

GU Xiao-wei， YIN Shi-qi， ZHANG Wei-feng， LI Xiao-hui

2022, 43 (8): 1168-1176. DOI: 10.12068/j.issn.1005-3026.2022.08.014

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In order to improve the pozzolanic activity of iron tailings， the effects of different activation time and ball to material ratios on the activity index of iron tailing mortar were studied by means of PSD， XRD and SEM. The test results showed that the mechanically activated iron tailings have potential cementitious property， and its activity index is greatly affected by the activation time and ball to material ratio. The activity index of iron tailings with mechanical activation for 40min， ball to material ratio of 9∶4 and mechanical activation for 30min， and ball to material ratio of 2∶1 can meet the application requirements of pozzolanic mixtures. The cementitious property of mechanically activated iron tailings is greater than its micro-filling effect， and the micro-grading uniformity of activated iron tailings is less than that of non-activated iron tailings. The addition of iron tailings changes the alkalinity of cement systems and the pore structure of hydration products， and makes more CO₂ enter the mortar， resulting in more carbonate products.

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FDS Simulation of Internal Pressure of Air-Supported Membrane Structure Under Fire

YU Yang， CAO Zheng-gang， SUN Ying， WU Yue

2022, 43 (8): 1176-1182. DOI: 10.12068/j.issn.1005-3026.2022.08.015

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Taking the air-supported membrane structure as the research object， using the fire dynamics simulator(FDS)， and considering the air leakage in the subgrid， the influencing factors of the internal pressure of the air-supported membrane structure without fire and the simulation method of the internal pressure under fire were studied. The results showed that the influence of air supply volume and leakage area should be considered in the internal pressure simulation of the air-supported membrane structure， and the larger the air supply volume， the smaller the leakage area， and the larger the corresponding stability value of the internal pressure. Based on the theoretical derivation and numerical simulation results， the internal pressure prediction formula of the air-supported membrane structure considering the influence of air supply volume and leakage area is obtained， and the prediction results of the formula are in good agreement with the simulation results. The simulation study on the internal pressure of the structure under fire finds that the internal pressure at ignition and the fire’s heat release rate only affect the change process of the internal pressure but has no effect on the stability value of the internal pressure. Therefore， the fire can be ignited when the internal pressure is 0Pa， so as to obtain the maximum value of the internal pressure of the fire and save the simulation time.

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Seismic Behavior of Steel Frame Infilled with Recycled Aggregate Concrete Hollow Slat Wall

PENG Li-gang， SUN Yi-li-quan， ZHAO Yu-xi， YUAN Jing

2022, 43 (8): 1183-1191. DOI: 10.12068/j.issn.1005-3026.2022.08.016

Abstract ( 467 )

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The low cyclic loading tests on two steel frames infilled with recycled aggregate concrete hollow slat walls were conducted to investigate the seismic behavior of each specimen. Combined with the feasibility verification of finite element simulation， the effects of wall opening on the failure mode， ductility， bearing strength and stiffness of specimens were studied. The results show that the wall opening has no significant effect on the failure mode of specimen; however， the wall opening has a slightly negative effect on the ductility， bearing strength and stiffness of specimen， which can still meet the seismic requirements. Meanwhile， some improvement suggestions were put forward for the installation process and connection method of hollow slat wall. The results of finite element simulation were in good agreement with the actual test results， which verifies the feasibility of the structural system and provides a reference for its seismic design.

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Dynamic Response of Double-Skin Steel-Concrete Composite Panel Under Impact Loading

AN Guo-qing， WANG Rui， ZHAO Hui， LI Tie-ying

2022, 43 (8): 1192-1200. DOI: 10.12068/j.issn.1005-3026.2022.08.017

Abstract ( 409 )

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In order to study the impact-resistant performance of double-skin steel-concrete composite(SC)panel， the ABAQUS software was utilized to establish the finite element(FE)models of SC panel subjected to drop hammer impact. The accuracy of numerical models was verified by comparing the FE simulations with the test results. Based on the validated models， the influences of steel plate ratio， impact height， material strength， boundary condition and indenter shape on the dynamic responses of SC specimen were revealed. Finally， the energy method was employed to calculate the maximum mid-span deflection of SC panel. The results indicate that steel plate ratio， impact height， indenter shape and boundary condition present significant effects on the dynamic response within the parameter range of this work， and the effects are more obvious when the steel plate ratio exceeds 4%. The theoretical calculation method used in this study can reasonably predict the maximum mid-span deflection of SC panel under impact loading.

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Chinese Investors’ Multi-perspective Sentiment Analysis and Its Role in Stock Market Forecasting

MA Yuan-yuan， LIU Yan-ze， LIU Cheng-long， ZHANG Tian-jie

2022, 43 (8): 1201-1209. DOI: 10.12068/j.issn.1005-3026.2022.08.018

Abstract ( 647 )

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There are irrational phenomena related to investor sentiment in the stock market， and the quantitative study of investor sentiment and stock market is important for discovering stock market patterns and aiding investment forecasting. Based on the investor statements in forums， a CNN-TLDA hybrid model is innovatively built to quantify investor sentiment from multiple perspectives， and explore the interaction between investor sentiment and the stock market from both positive and topic. The roles of investor sentiment in forecasting are investigated based on LSTM (long short-term memory) network. It is shown that Chinese stock market investors are generally pessimistic， and both investor optimism and topics of interest are highly correlated with the stock market. The multi-perspective sentiment analysis reduces the prediction error to 41%. The results of the study can assist investors in their investment decisions and also provide a scientific reference for the analysis and utilization of individual investors′ sentiment in the stock market.

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Impact of High-Commitment Human Resources Management Practice on Radical Innovation

YAN Jia-qi， JIA Jian-feng， ZHAO Ruo-nan， LIAN Yue-feng

2022, 43 (8): 1209-1216. DOI: 10.12068/j.issn.1005-3026.2022.08.019

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Based on the survey data of top managers from 362 companies at three time points， the impact mechanism of the high-commitment human resources management practice on radical innovation is investigated from the perspective of process-based and content-based human resources management integration. It is found that: 1)the high-commitment human resources management practice is significantly related to external knowledge acquisition; 2)the external knowledge acquisition mediates the impact of high-commitment human resources management practice on radical innovation; 3)the strength of the human resources management practice moderates the relationship between high-commitment human resources management practice and external knowledge acquisition. When the strength of the human resources management practice is stronger， the relationship between high-commitment human resources management practice and external knowledge acquisition is higher; 4)the strength of the human resources management practice moderates the mediating effect of external knowledge acquisition on the relationship between high-commitment human resources management practice and radical innovation.

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