重力坝动力深层抗滑稳定性研究

基于我国西南某待建高碾压混凝土重力坝,建立了典型坝段三维有限元接触分析模型,分别采用强度折减动力分析法和时程安全系数分析法,综合研究了坝基动力深层抗滑稳定性。同时针对传统时程安全系数分析存在的局限性,基于概率统计深入探讨并改进了可靠度动力安全系数评价指标。研究结果表明,大坝满足动力深层抗滑稳定设计要求,本文所采用的理论方法能够考虑地震作用的往复性和随机性,评价结果更为科学合理,为重力坝动力抗滑稳定的定量判别进行了有益探索。     

Behaviour and space in agent-based modelling: Poverty patterns in East Kalimantan,Indonesia

Applied models of policy interventions are increasingly expected to consider households’ responses to these interventions, which makes agent-based modelling popular in applied policy situations. Implementing an adequate level of agent heterogeneity and mapping it into a spatial environment are critical factors of such applied modelling. However, policy applications demand the characterisation and parameterisation of behavioural response functions of heterogeneous agents and the spatial distribution of heterogeneous agents, which are neither highly transparent nor greatly tested steps in implementing agent-based models. This paper describes an agent-based model of fuel price changes for a case study in East Kalimantan, Indonesia, and specifically: (a) the characterisation and parameterisation approach, (b) resulting agent types for approximating behavioural heterogeneity, and (c) emerging spatial poverty and deforestation patterns. The model highlights the spatial dynamics of poverty dynamics, indicating that the direct impact of deforestation on poverty among forest-dwelling communities is to trigger their migration into peri-urban areas. Overall, the model suggests that poverty increases in response to fuel price reductions.     

Spatial-temporal analysis of safety risks in trajectories of construction workers based on complex network theory

Understanding the traffic patterns of construction workers on high-risk construction sites is important for implementing behaviour-based safety management. However, safety risks in worker trajectories are a complex system with high uncertainty. This resulted in few studies focusing on analysing the spatial–temporal risk in workers' trajectories from a systematic perspective. This study designs a new framework to explore the spatial–temporal patterns of safety risks in the trajectories of construction workers based on complex network theory. First, an integrated site safety risk classification method by combining hazard sources and group trajectory distribution is developed to accurately describe the spatial distribution of site risks. Second, a new complex network chronnet is used to construct complex networks containing risk information for spatial–temporal analysis. Finally, key risk areas and risk transition patterns are identified through the analysis of network measures. The study also developed a computational program that allows the network to be constructed and analysed in real-time. The feasibility and effectiveness of the method are verified through a case study. The results show that the method can reveal the risk distribution at the micro level, and explore the risk clustering and transition features in worker trajectories at the macro level. The study allows for an accurate analysis of dynamic risk patterns in construction workers' trajectories from a systematic perspective. It can also provide theoretical and practical support for personalized and adaptive behaviour-based safety management for construction workers.     

Traffic accidents involving fatigue driving and their extent of casualties

The rapid progress of motorization has increased the number of traffic-related casualties. Although fatigue driving is a major cause of traffic accidents, the public remains not rather aware of its potential harmfulness. Fatigue driving has been termed as a “silent killer.” Thus, a thorough study of traffic accidents and the risk factors associated with fatigue-related casualties is of utmost importance. In this study, we analyze traffic accident data for the period 2006–2010 in Guangdong Province, China. The study data were extracted from the traffic accident database of China's Public Security Department. A logistic regression model is used to assess the effect of driver characteristics, type of vehicles, road conditions, and environmental factors on fatigue-related traffic accident occurrence and severity. On the one hand, male drivers, trucks, driving during midnight to dawn, and morning rush hours are identified as risk factors of fatigue-related crashes but do not necessarily result in severe casualties. Driving at night without street-lights contributes to fatigue-related crashes and severe casualties. On the other hand, while factors such as less experienced drivers, unsafe vehicle status, slippery roads, driving at night with street-lights, and weekends do not have significant effect on fatigue-related crashes, yet accidents associated with these factors are likely to have severe casualties. The empirical results of the present study have important policy implications on the reduction of fatigue-related crashes as well as their severity.     

Analysis of vehicle-bicycle interactions at unsignalized crossings: A probabilistic approach and application

In the last decades, bicycle usage has been increasing in many countries due to the potential environmental and health benefits. Therefore, there is a need to better understand cyclists’ interactions with vehicles, and to build models and tools for evaluating multimodal transportation infrastructure with respect to cycling safety, accessibility, and other planning aspects. This paper presents a modeling framework to describe driver-cyclist interactions when they are approaching a conflicting zone. In particular, the car driver yielding behavior is modeled as a function of a number of explanatory variables. A two-level hierarchical, probabilistic framework (based on discrete choice theory) is proposed to capture the driver’s yielding decision process when interacting with a cyclist. The first level models the probability of the car driver perceiving a situation with a bicycle as a potential conflict whereas the second models the probability of yielding given that a conflict has been perceived by the driver. The framework also incorporates the randomness of the location of the drivers’ decision point. The methodology is applied in a case study using observations at a typical Swedish roundabout. The results show that the conflict probability is affected differently depending on the user (cyclist or driver) who arrives at the interaction zone first. The yielding probability depends on the speed of the vehicle and the proximity of the cyclist.     

A rear-end collision risk assessment model based on drivers’ collision avoidance process under influences of cell phone use and gender—A driving simulator based study

Driver’s collision avoidance performance has a direct link to the collision risk and crash severity. Previous studies demonstrated that the distracted driving, such as using a cell phone while driving, disrupted the driver’s performance on road. This study aimed to investigate the manner and extent to which cell phone use and driver’s gender affected driving performance and collision risk in a rear-end collision avoidance process. Forty-two licensed drivers completed the driving simulation experiment in three phone use conditions: no phone use, hands-free, and hand-held, in which the drivers drove in a car-following situation with potential rear-end collision risks caused by the leading vehicle’s sudden deceleration. Based on the experiment data, a rear-end collision risk assessment model was developed to assess the influence of cell phone use and driver’s gender. The cell phone use and driver’s gender were found to be significant factors that affected the braking performances in the rear-end collision avoidance process, including the brake reaction time, the deceleration adjusting time and the maximum deceleration rate. The minimum headway distance between the leading vehicle and the simulator during the rear-end collision avoidance process was the final output variable, which could be used to measure the rear-end collision risk and judge whether a collision occurred. The results showed that although cell phone use drivers took some compensatory behaviors in the collision avoidance process to reduce the mental workload, the collision risk in cell phone use conditions was still higher than that without the phone use. More importantly, the results proved that the hands-free condition did not eliminate the safety problem associated with distracted driving because it impaired the driving performance in the same way as much as the use of hand-held phones. In addition, the gender effect indicated that although female drivers had longer reaction time than male drivers in critical situation, they were more quickly in braking with larger maximum deceleration rate, and they tended to keep a larger safety margin with the leading vehicle compared to male drivers. The findings shed some light on the further development of advanced collision avoidance technologies and the targeted intervention strategies about cell phone use while driving.     

耐碱玻璃纤维ECC复合材料受压应力–应变关系

为研究耐碱玻璃纤维工程用水泥基复合材料（耐碱玻璃纤维ECC）的抗压性能及应力-应变关系，对33组高性能水泥基材料试件进行了轴压性能试验，分析了纤维掺量、纤维长度及水灰比对耐碱玻璃纤维ECC的受压性能及应力-应变关系的影响，提出了耐碱玻璃纤维ECC受压应力-应变关系计算模型。结果表明，掺入耐碱玻璃纤维可以明显改善水泥基材料在单轴受压状态下的抗裂、受力和变形性能；耐碱玻璃纤维ECC试件抗压强度和变形能力的提升程度与纤维掺量、纤维长度及水灰比有关；随着纤维掺量和长度增加，耐碱玻璃纤维ECC试件的抗压强度和变形能力大致呈递增趋势，但掺量过多会因“团聚”现象明显导致试件抗压强度降低；水灰比主要影响试件的抗压强度，水灰比越大，抗压强度越小；当纤维质量掺量为6.5%、纤维长度为18mm及水灰比为0.32时，碱玻璃纤维ECC的综合力学性能相对较优，其抗压强度和变形能力分别可提升25.6%和88%；提出的应力-应变关系模型的计算值与试验值吻合较好，可用于描述耐碱玻璃纤维ECC的受压破坏全过程。     

流场特征识别的无量纲时程深度学习方法

流场的特征直接影响结构的流致振动状态,对结构绕流流场的特征分析具有重要的研究意义。在中高雷诺数与不同流速的情况下,尾流中隐含的流场特征不同,传统数学物理方法很难对其特征进行提取与识别。该文提出了采用无量纲的物理量时程进行流场特征识别的深度学习方法,消除了不同来流速度的影响,仅通过时程的时变特征进行特征识别,扩大了特征识别方法的应用范围。采用两种不同深度学习模型对三种棱柱的尾流进行了特征提取与识别,通过比较可以发现：归一化的时程中仍包含不同形状物体所引起流场的关键特征,可用于流场的特征提取;使用归一化时程进行流场特征识别可降低模型训练难度,又提高了特征提取的精度,是一种流场特征提取的新方法。     

Adaptive PSODV algorithm for OPF with non-smooth cost functions and statistical analysis

This paper presents a particle swarm optimization with differentially perturbed velocity hybrid algorithm with adaptive acceleration coefficient (APSO-DV) for solving the optimal power flow problem with non-smooth and non-convex generator fuel cost characteristics. The APSO-DV employs differentially perturbed velocity with adaptive acceleration coefficient for updating the positions of particles for the particle swarm optimization. The feasibility of the proposed approach was tested on IEEE 30-bus and IEEE 118-bus systems with three different objective functions. Several cases were investigated to test and validate the robustness of the proposed method in finding the optimal solution. The effectiveness of the proposed approach was tested including contingency also. Simulation results demonstrate that the APSO-DV provides superior results compared to classical DE, PSO, PSO-DV and other methods recently reported in the literature. An innovative statistical analysis based on central tendency measures and dispersion measures was carried out on the bus voltage profiles and voltage stability indices.     

A node-based smoothed finite element method (NS-FEM) for upper bound solution to visco-elastoplastic analyses of solids using triangular and tetrahedral meshes

A node-based smoothed finite element method (NS-FEM) was recently proposed for the solid mechanics problems. In the NS-FEM, the system stiffness matrix is computed using the smoothed strains over the smoothing domains associated with nodes of element mesh. In this paper, the NS-FEM is further extended to more complicated visco-elastoplastic analyses of 2D and 3D solids using triangular and tetrahedral meshes, respectively. The material behavior includes perfect visco-elastoplasticity and visco-elastoplasticity with isotropic hardening and linear kinematic hardening. A dual formulation for the NS-FEM with displacements and stresses as the main variables is performed. The von-Mises yield function and the Prandtl–Reuss flow rule are used. In the numerical procedure, however, the stress variables are eliminated and the problem becomes only displacement-dependent. The numerical results show that the NS-FEM has higher computational cost than the FEM. However the NS-FEM is much more accurate than the FEM, and hence the NS-FEM is more efficient than the FEM. It is also observed from the numerical results that the NS-FEM possesses the upper bound property which is very meaningful for the visco-elastoplastic analyses which almost have not got the analytical solutions. This suggests that we can use two models, NS-FEM and FEM, to bound the solution, and can even estimate the global relative error of numerical solutions.