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Dissimilar material structure has the advantages of both cost and performance, and has become an important means of lightweight for the new generation of autobody closure panels. However, the difference between physical properties of sheets and the complex change of adhesive material properties are easy to lead to structural curing mismatch deformation. In order to eliminate the structure deformation, a method for deformation prediction and surface reconstruction pre-compensation was proposed. Then, considering the material property transformation effect of curing degree, chemical shrinkage, and stress relaxation, a thermal-chemical-structural field coupled model for high temperature curing of hemming adhesive was established. Taking the typical aluminum/steel sheet curved-edge hemming structure as the research object, the multi-physics field curing process was simulated and analyzed, and the deformation of aluminum alloy outer panel was predicted, which was verified by non-contact measurement experiment using digital image correlation (DIC) method. Finally, the geometric compensation of curing deformation was conducted, the compensation efficiency of constraint direction, connection direction, and normal direction was compared and analyzed, and the reliability of the method was verified by experiment. The results show that compared with the traditional viscoelastic model, the multi-physics field coupling model can more accurately reflect the high temperature curing deformation of hemming structures with dissimilar materials. The geometric compensation method based on non-uniform rational B-splines (NURBS) surface reconstruction can effectively reduce the curing deformation of structures, and the normal direction compensation method is more efficient. This paper provides an important reference for the improvement of manufacturing accuracy and process optimization of the new generation of autobody closure panels with dissimilar materials.

In the roll-hemming forming process of door cover, the non-metallic flanging adhesive and the interaction between light metal and flanging adhesive will affect the manufacturing accuracy and performance of the door cover, and increase the difficulty of roll-hemming forming and quality control of automobile body sheet with adhesive. Therefore, a numerical analysis model for roll-hemming forming of aluminum alloy sheet with adhesive was proposed based on the finite element method and the smooth particle hydrodynamic (FEM-SPH) method. First, SPH was used to simulate the extrusion flow process of the flanging adhesive, and a roll-hemming simulation model of sheet metal with adhesive was established in combination with FEM. Then, an experimental platform for two-pass roll-hemming forming of aluminum alloy sheet with adhesive was built, and the roll-hemming loss and surface wave coefficient were taken as the roll-hemming forming quality index to analysis and verify the validity of the numerical model. After that, the quality change between the first pass and the last pass and the key process parameters affecting quality were studied based on the orthogonal test method. Finally, the fitting relationship between roll-hemming forming quality and process parameters was established. The results show that the roll-hemming loss and the surface wave coefficient of the last pass are reduced compared with the first pass. The process parameters that affect the surface wave coefficient in descending order are flanging height, fillet radius, TCP-RTP value, and roller diameter. The process parameters that affect the roll-hemming loss in descending order are TCP-RTP value, fillet radius, flanging height, and roller diameter. The fitting relationship can support the prediction of roll-hemming forming quality of aluminum alloy sheet with adhesive.

This study aims to understand how attitudinal factors influence individuals' choices for further developing carsharing. To address the gap, a household survey was carried out to obtain the individual's attitudes toward carsharing. The Transtheoretical Model is used to divide the adoption process of carsharing into five stages, including precontemplation, contemplation, preparation, action, and maintenance. Two Integrated Choice and Latent Variable Models with or without the attitudinal features are evaluated for the effects of latent attitudes on the above five stages. Additionally, the attitudinal factors at each stage are analyzed and compared, and the effects of the flexible and hard measures on the adoption process are discussed. The results indicate that the proposed attitudinal factors well reflect individuals' adoption stage of carsharing and show different effects on the five adoption stages. The policy implications for facilitating carsharing require coordinating flexible and hard measures in different cognitive stages. [ABSTRACT FROM AUTHOR]

Rapid growth rate indicates that the free-floating electric vehicle sharing (FFEVS) system leads to a new carsharing idea. Like other carsharing systems, the FFEVS system faces significant regional demand fluctuations. In such a situation, the rental stations and charging stations should be constructed in high-demand areas to reduce the scheduling costs. However, the planning of the FFEVS system includes a series of aspects of rental stations and charging stations, such as the location, size, and number, which interact with each other. In this paper, we first provide a method for forecasting the demand for car sharing based on the land characteristics of Beijing FFEVS station catchment areas. Then, the multi-objective MILP model for planning FFEVS systems is developed, which considers the requirements of vehicle relocation and electric vehicle charging. Afterward, the capabilities of the proposed models are demonstrated by the real data obtained from Beijing, China. Finally, the sensitivity analysis of the model is made based on varying demand and subsidy levels. From the results, the proposed model can provide decision-makers with useful insights about the planning of FFEVS systems, which bring great benefits to formulating more rational policies. [ABSTRACT FROM AUTHOR]

In order to meet the stricter requirements for appearance accuracy of aluminum alloy automotive bodies, a roller pose compensation method was proposed for the dimensional deviation of automotive bodies. The dimensional deviation matrix was obtained by equidistant discretization of the dimensional deviation interval and the die edge. Based on the Frenet scale frame and Cartesian coordinate transformation, the dimensional deviation was mapped to the roller pose, and the deviation matrix of roller pose was obtained. The roller pose compensation amount was converted into the adjustment amount of the row number of the deviation matrix of roller pose, and the compensated roller pose was obtained. Among them, the deviation matrix of roller pose was determined by the surface/curve equation of die, the roller angle and the quantization model of dimensional deviation and the value of tool center point-robot target point(TCP-RTP). The quantization model of dimensional deviation and the value of TCPRTP was obtained by finite element simulation of finite element method-smoothed particle hydrodynamics. The results show that the average value of the dimensional deviation is reduced from 0.32mm to 0.14mm after the roller pose compensation. [ABSTRACT FROM AUTHOR]

Despite the benefits of cycling being widely accepted, bicycle safety—especially severe injury—has received increasing attention due to the vulnerability of bicyclists on the road. Factors contributing to varying bicycle injury severity have been identified in the literature. For the zonal factors, variables related to sociodemographic and household characteristics, built environments, land use, and traffic conditions are considered. However, it is rare that the heterogeneity and hierarchal features of bicycle injury severity are simultaneously considered. This study contributes to the literature by investigating the heterogeneous effects of zonal factors on varying bicycle injury severity, using a 3-year crash data set from the Lower Layer Super Output Areas of London. A combination of latent class clustering and partial proportional odds methods was developed. First, five subgroups of bicycle crashes were identified based on the latent class clustering method. Afterward, partial proportional models were developed separately for different clusters. Results indicate that a series of factors is found to be associated with the occurrence of severe bicycle injuries. However, effects of these factors could be distinctive among different clusters. For example, some factors only have significant impacts in the specific crash clusters. Furthermore, heterogeneous effects of the same factors in one or different clusters are discovered. The findings of this study can be helpful for the development of cycle infrastructures, traffic management, and safety education that can enhance the risk perception of bicyclists and reduce the occurrence of severe bicycle injuries. [ABSTRACT FROM AUTHOR]

It is of paramount importance for mitigating road crash losses to characterize the relationship between crash injury severities and contributing factors. Existing studies have revealed mechanism differences of single-vehicle (SV) and multi-vehicle (MV) crashes. This study positions itself at exploring the differences from spatiotemporal, road-environment, driver-vehicle, and collision characteristics. A model comparison as well as the elasticities for the optimal model (partial proportional odds model) is implemented based on 18,083 SV crashes and 22,162 MV crashes in China. The results evidenced the great differences that time, road, speed, lighting, and weather are found to have a positive correlation with only SV crash injury severity, yet negatively related with only MV crash injury severity. Area, location, and angle are significant only for SV crashes, while day, interference, and wind are significant only for MV crashes. The findings revealed that gender, age, collision, location, and time are more influencing factors in SV crashes, while collision, age, gender, vehicle, and wind have more contributions to MV crashes. The findings could provide an insightful reference for prioritizing effective countermeasures to mitigate traffic crash losses. [ABSTRACT FROM AUTHOR]

Electric vehicle timeshare rentals (EVTRs) have been recognized as promising solutions to growingly severe problems of traffic congestion, air pollution, and insufficient parking spaces. This study aims to explore the factors that affect the adoption of EVTRs. To achieve the research objective, the household survey is conducted to obtain the travelers' attitudes towards their travel. Ten latent attitudinal factors are extracted based on the technology acceptance model (TAM) and the theory of planned behavior (TPB). The multi-index and multi-cause (MIMIC) method simultaneously estimates the correlations between the attitudinal factors. Two logit models with attitudinal factors or not are constructed to estimate the quantitative relationship between various factors and EVTR adoption. The results show that the accuracy of the mixed logit model with latent attitude variables is better than the binary logit model without attitude latent variables. This indicates that attitude latent factors could be well matched with the traveler's travel behavior and could better reflect travelers' travel demand. Perceived comfort, perceived efficient, subjective evaluation, use preference, and use willingness significantly impact EVTR use frequency. The inconvenience in travelers, rental stations, shared vehicles, and use modes have significant negative impacts. Finally, social pressure has no significant impact. Findings provide valuable insights regarding the efficient planning of the EVTR system and allow decision-makers to develop scientific and practical measures of EVTRs. [ABSTRACT FROM AUTHOR]