Abstract:Based on the previous tornado-induced wind load identification results of long-span bridges， the calculation and analysis of the tornado-induced responses of a long-span suspension bridge were conducted， and the tornado-induced responses were further compared with the synoptic wind-induced responses to discuss the possibility of using synoptic wind load in tornado-resistant design of bridges. The results show that， the influence of tornado load is local， and the lift force is relatively significant， which differs from that of the synoptic wind load. The tornado-induced structural responses of the suspension bridge can be influenced by parameters such as the swirl ratio， relative distance of the tornado， and the axial position of the loading points， whose impacts vary with different types of structural responses. Synoptic wind-induced responses differ both qualitatively and quantitatively from tornado-induced responses， leading to unresolved issues regarding load equivalence between the two.

Abstract:By embedding these cracks on the model， the effects on the structural responses and fatigue life of the cracked orthotropic steel deck （OSD） and the pavement are presented with comparison to the crack-free condition. The results show that a penetrating crack can hardly affect the local stiffness before it completely penetrates thorough the deck plate and grows to a considerable length. However， the penetrating crack will always be a problem as it may lead to the strain concentration at the bottom of the pavement， resulting in a significant reduction of its fatigue life. Based on the strain-life relationship of the pavement， it is estimated that when the depth of the cracks reaches 1/2 and 3/4 of the deck plate thickness， the pavement fatigue life can be reduced by about 15% and 35%， respectively.

Abstract:This paper presents unit tests under static loading conditions to investigate the uniaxial tensile and shear behavior at the interface between the reinforcing material and concrete and analyzes the failure modes， ultimate bearing capacity， average bond strength， load-displacement curves， and the strain variation at the interface. Additionally， it examines the influence of different adhesive thicknesses， expansion bolt grades， and concrete surface roughness on the mechanical properties of the bond interface. The experimental results indicate that the final failure mode of the bonding interface is mainly concrete cohesive failure under interfacial tension conditions， the final failure mode of the bonding interface is mainly the detachment of the interface between the steel ring and the bonding agent under shear conditions. The ultimate bearing capacity and bonding strength of the bonding interface increase with the decrease of the adhesive thickness， while the tensile and shear ultimate bearing capacity corresponding to an interface thickness of 1mm only increase by 4.6% and 5.6% compared to a 2 mm thickness， which greatly increases the difficulty of epoxy resin grouting. Therefore， choosing an interface thickness of 2 mm is more reasonable. Adding expansion bolts for reinforcement can significantly improve the tensile and shear strength of the bonding interface. It is recommended to use M18 expansion bolts， and under special working conditions， M20 can also be used to enhance the reinforcement performance. The bonding strength of the bonding interface increases with the roughness of the concrete surface. The influence of concrete surface roughness on the tensile bonding strength of the bonding interface is greater than that on the shear bonding strength.

Abstract:This paper investigated the nonlinear characteristics of the annular joints of assembled structures under the action of bending moment and axial force. Based on the contact state， force characteristics， and deformation coordination relationship at joints， a mechanical model was proposed for the stress states of compression-bending， pure bending， and tension-bending. The distribution of internal force regions in the development process of bending deformation and its identification method were analyzed. A three-dimensional numerical model was adopted to validate it. It is shown that the main deformation process of the joint can be characterized by four bending modes. The specific dimensions and material parameters of the components can be substituted into the relevant angle expressions to determine the development process of joints. On-site measurement of bending moment and axial force indicates that the bending modes of the annular joint can be accurately identified， and the mechanical characteristics and safety status of the joint can be provided.

Abstract:The main factors influencing the bearing capacity of a single pile were analyzed， the cone penetration test data were preprocessed using the dimensionality reduction algorithm， the main features were screened using the importance analysis function of tree model， and the hyperparameters were determined using the Bayesian optimization algorithm. A prediction model of vertical bearing capacity of driven pile was proposed based on the machine learning algorithm. The validity and robustness of the prediction model were evaluated using accuracy test and Monte Carlo simulation test， and compared with the empirical models. The results show that the support vector machine （SVM） model， the random forest （RF） model， and the extreme gradient boosting （XGBoost） model can accurately predict the vertical bearing capacity of driven piles， whose accuracy is significantly higher than that of the empirical relationship model. The comprehensive analysis indicates that the XGBoost model should be selected to predict the vertical bearing capacity of driven piles.

Abstract:To provide high computational efficiency， accuracy and stability integration algorithms for real-time hybrid simulation （RTHS）， the high order accurate， unconditionally stable new dual-explicit （NDE）， and new semi-explicit （NSE） algorithms were developed based on the second-order accurate unconditionally stable and explicit Chen-Ricles （CR） and Chang algorithms. Based on the discrete control theory， the closed-loop discrete transfer function of the RTHS system using the two new algorithms were derived. The influences of time delay， damping ratio， stiffness proportional ratio， and integration algorithm on the stability of the RTHS system were investigated. Additionally， the approximation solution and accurate solution derived from the delay differential equation were also adopted for reference. The analytical results show that the time delay decreases the stability of the RTHS system. Increasing the stiffness proportional ratio reduces the difference between different analysis results. Increasing the damping ratio improves the stability of the RTHS system， enlarges the difference between the stability with and without considering the integration algorithm， and magnifies the difference between the stability using different integration algorithms. The stability of the RTHS system using the two high-order accurate integration algorithms is superior to that of the two second-order accurate integration algorithms.

Abstract:This paper， using Xuhui District of Shanghai as a representative of urban areas and Jinshan District as a representative of suburban coastal areas， analyzed meteorological data from the perspective of street trees， focusing on the maximum wind speed and direction during periods of high typhoon frequency. Then， it inputted these basic data into CFD（computational fluid dynamics） simulations to model the wind environment of the study area. Afterwards， it evaluated the “wind-tree” ecology of the streets based on wind speed grades， street orientation， and the road greening structure. Finally， it obtained the comprehensive evaluation results of the wind environment in the targeted areas.

Abstract:Based on the data of takeover cases in autonomous driving road testing， this paper analyzes the types of takeover interventions， and sets up three types of risky scenarios： trust， risk-avoidance， and optimization takeovers. By developing a CARLA-SUMO joint simulation platform under the OpenCDA framework and using the counterfactual inference method， the operating conditions of autonomous driving in risky scenarios are deduced from the road-testing datasets. From the perspectives of safety， efficiency， comfort， etc.， multi-dimensional evaluation indicators for the intelligent driving level of autonomous driving are proposed. The results show that the counterfactual inference method is capable of achieving the deduction of risky scenarios under the takeover conditions. In similar risky scenarios， the intelligent driving of autonomous passenger cars is better than that of trucks. The differences in fundamental elements and operational indicators among risky scenarios are significant， and intelligent driving in risk-avoidance takeover scenarios is more reliable compared to trust takeover scenarios.

Abstract:To address the shortcomings of traditional traverse method such as significant deviation between the traverse and the horizontal curve， this paper proposes a “two-point method” for basic horizontal alignment design. It is only necessary to use the two endpoints named “point of tangent to spiral” and “point of spiral to tangent” to obtain the basic type horizontal curve family consisting of three elements including the transition curves and the circular curve. The total deflection angle （α） and total tangent length （T） of the horizontal curve family are known fixed parameters. First， the theoretical minimum and maximum values of the transition curve length （L_S） or the radius of circular curve （R） are calculated using the iterative method （for symmetric type） or squeeze theorem analysis method （for asymmetric type）， respectively. Then， the design value range of L_S or R is determined based on the technical requirements of horizontal alignment. Afterwards， the traversal cycle is performed based on L_S or R， and the corresponding deflection angle of the transition curve （β） is calculated using an iterative calculation method. Finally， the remaining parameters of each element is determined. The results indicate that， the “horizontal curve family” obtained through the “two-point method” has a regular distribution and does not overlap with each other， and all of the curves are located in “a specific design area” with narrow ends and wide-thick middle. The variation of parameters such as L_S， R， circular curve length （L_C）， and total horizontal curve length （L_H） is very regular. The increasing and decreasing of LS are opposite to those of R and L_C， while the average of L_H is approximately fixed. Furthermore， the ratio of the total tangent lengths is only solvable within the range from 0.5 to 2.0. The “two-point method” highlights the controlling role of coordinate location points， making the alignment layout efficient. The design outcome presents a series of horizontal curve families within a specific area， rather than a single curve. This is beneficial for comparing and selecting alignments based on actual topography and design intentions， thereby contributing to the advancement of intelligent route design.

Abstract:A bidirectional red and green waves coordination design method for bus arterial road was proposed to ensure punctuality and improve operation efficiency. By defining punctual control intersection and green wave intersection， the red wave or green wave control mode of upstream signalized intersections was determined based on the distribution of bus stop positions. By applying equivalent transformations to the coordination design speed and establishing the characteristic equation for the bus red and green wave trajectory， the general formula for calculating the ideal distance between intersections was derived. This included calculating the offset rate of intersection centers and an algebraic method was provided to optimize the coordination control scheme of arterial road for bus signals， aiming to balance bus punctuality with green wave travel. Additionally， an optimization method was provided for developing bus arrival timetables. The case experiment shows that the design scheme of this method can ensure that 97.6% of buses arrive at the bus station within the predetermined signal cycle， and the average deviation between the actual arrival time and the planned arrival time of buses is 5.5 s， and the average number of stops for buses at green wave intersections is 0.06 with an average delay time of 2.97 s.

Abstract:This paper investigates the issue of network short-term capacity loss due to general emergencies on high-speed rail （HSR）， which results in train delays. It introduces the concept of resilience to evaluate the recovery ability of HSR network from delays and proposes a definition for HSR network delay resilience. It establishes evaluation indicators based on two metrics， recovery degree and recovery speed， to assess the delay recovery ability of HSR network during general emergencies. Additionally， it explores methods for network delay resilience analysis and optimization through operation adjustment， and develops a multi-objective mixed integer programming model for delay resilience optimization in the affected section and adjacent sections. Moreover， it conducts a case study using the partial HSR network of the East China Bureau. Finally， it analyzes the propagation characteristics of HSR delays during general emergencies， providing insights for HSR dispatching management in adjusting operations.

Abstract:Considering the requirement of certain service frequency of high-speed railway stations and trains， a collaborative optimization mixed integer programming model of train diagram generation and compression， and a two-stage solution algorithm were proposed， taking the shortest train diagram drawing time and total train running time as the optimization objective. First， the benchmarking train schedule was fixed， the train stopping scheme， overrunning scheme， and track utilization scheme were solved， and the initial train diagram was generated. Then， without changing the above three schemes， the unnecessary redundant time was reduced， the train services were moved forward， and the compressed train diagram was obtained. Taking the Beijing-Shanghai high-speed railway as an example， the numerical experiment shows that the two-stage solution algorithm can reduce the complexity of determining the running relationship between the two trains， realizing the fast and effective solution of the model on a large-scale data.

Abstract:Inspired by the concepts of “excess commuting”， the novel idea of “excess living-trip” is proposed， along with the development of evaluation indicators using distance as the primary measure， which assesses the adequacy of community facilities from the perspective of residents’ needs. Typical communities were selected， and the characteristics of living trips were analyzed with comparisons made based on the 2021 Shanghai residents’ travel survey data. The results reveal significant spatial differences： communities closer to downtown tend to have better infrastructure， and the phenomenon of excess living-trip is less pronounced.

Abstract:This paper， focusing on the housing market in Shanghai and using atlas data and Baidu Map POI open data to develop a model of the spatial distribution characteristics of residential prices， explores the impact of accessibility to super-large residential structures， urban transportation facilities， public service facilities， commercial service facilities， and ecological environment service facilities on residential prices. It employs a geographically weighted model （GWR） to analyze the spatial heterogeneity of these impacts. The findings indicate that the accessibility of urban service facilities is the main factor influencing the spatial distribution of residential prices. This paper concludes with a discussion of the implications for urban planning at both macro and micro levels.

Abstract:This paper， using an overall SBM-DDF （slack-based measured directional distance function） model on 279 sample cities， measures and evaluates green development in Chinese cities from both static and dynamic perspectives. The static analysis focuses on the current state of green development， while dynamic efficiency provides insights into development trends. Quadrant analysis identifies cities with strengths and weaknesses in green development， offering valuable insights for inter-city learning， competition， and cooperation， and the formulation of targeted strategies. Although green development in China is improving from a city-level perspective， it exhibits significant spatial variability. Only a small number of cities have both high static development levels and high dynamic efficiencies. In the future， China’s high-quality green development is likely to experience a two-tier differentiation.

Abstract:Urban real-time delivery faces challenges such as distorted road network data， uncertain supply-demand information， and network disruptions in large-scale public health emergencies. Therefore， it is essential to consider information uncertainty and network disruptions when optimizing urban real-time delivery networks. To address these challenges， first， the problem of road network construction under road restrictions caused by lockdown measures was addressed， the underlying urban road network was established and the Floyd algorithm was improved for efficient solutions. Then， for open multi-delivery point urban real-time delivery problems， considering supply-demand uncertainty and facility service disruptions， the Monte Carlo simulation was conducted to construct a scenario tree， a multi-objective stochastic programming model was constructed， and a hybrid evolutionary based on GA-SA was designed to solve the problem. Finally， taking the COVID-19 pandemic in Shanghai in 2022 as an example， a comprehensive analysis was conducted. The results reveal that large-scale public health emergencies can lead to sudden changes in delivery facility capacity， road network capacity， and customer demands. The mismatch between supply and demand in the delivery system can result in issues like excessive orders and stockouts. Interestingly， facility disruptions do not necessarily lead to an increase in delivery costs. Instead， the total cost is amplified by a reduction in customer satisfaction. Furthermore， increasing the number of vehicles does not necessarily lead to an increase in costs.

Abstract:Existing studies on fuzzy zero-sum games fail to account for variations in environmental complexity and overlook the specific process of construction payoff matrices. To address these limitations， a multi-objective programming model for solving T-spherical fuzzy zero-sum game based on hybrid variable experts integration weights is proposed in this paper， which is able to help players choose the optimal competition strategy when the total amount of resources remains relatively constant and all parties in the game pursue the maximization of their own interests. First， a novel dynamic expert integration weight calculation model， considering objective individual and subjective evaluation information simultaneously， is devised. The expert weights obtained by the above model can vary with subjective evaluation information provided by experts， which are closer to the actual practices. Then， in virtue of the weighted average method， a multi-objective programming framework for T-spherical fuzzy zero-sum game is formulated to determine the optimal mixed strategies for players， which can present the specific feasibility and divergence degree of each competitive strategy and be less impacted by the number of strategies. Finally， an illustrative example and several comparative analyses validate the reasonability and effectiveness of the proposed model. The results demonstrate that the proposed model offer higher decision-making efficiency， lower computational complexity， and reduced sensitivity to the number of alternatives. Additionally， the hybrid solution， expressed as probabilities， can effectively reflect the differences between alternatives. When the optimal strategy fails， alternative suggestions can be provided， helping to avoid redundant decision-making and minimizing resource wastage.

Abstract:To address the issue of service quality improvement in electric vehicle （EV） timeshare rental projects in the era of big data， this paper， by combining text mining techniques with quality function deployment （QFD）， identifies customer demands and improves the service quality of EV rental enterprises， taking EVCARD， a typical Shanghai-based company， as a case study. First， customer review data were collected， segmented， and tagged for parts of speech. Using regular expressions， feature-emotion word pairs were extracted， their word frequency and comprehensive sentiment values were calculated， and eight customer demands requiring improvement were identified. Based on these findings， the QFD tool was applied， and a method combining customer demand attention with comprehensive sentiment values was used to determine customer demand weights in the construction of the left wall of the quality house. Subsequently， through literature research and expert interviews， 17 service quality elements were identified， ranked， and classified. Finally. recommendations for service quality improvement， such as customized service systems， were proposed for enterprises.