Simulation on progressive collapse behaviour of whole ship model under extreme waves using idealized structural unit method

To ensure the safety of navigating ship, working loads and structural load-carrying capacity are two important aspects. In the present paper, a total simulation system combing load calculation and structural collapse analysis is applied to simulate progressive collapse behaviour of a single-hull Kamsarmax type bulk carrier. A three dimensional singularity distribution method is adopted to calculate pressure distribution with time history. A mixed structural model, collapse part simulated by ISUM elements and remaining part by elastic FEM elements with relative coarse mesh, is proposed for collapse analysis. Progressive collapse behaviour obtained by ISUM is good agreement with that by nonlinear software package, MARC. However, the calculation time of ISUM analysis is about 1/70 of MARC analysis. The applicability to structure system, high accuracy and sufficient efficiency of ISUM had been demonstrated.     

西南红层软岩地区铁路滑坡形成机理分析及治理措施

红层软岩地区铁路工程建设中滑坡问题突出。本文结合西南地区一铁路红层滑坡治理工程,利用该地区红层滑坡的现场调查结果,从红层软岩特性、地层岩性、地质地貌、水文地质条件、深孔位移监测数据等多方面对该地区铁路滑坡形成机理进行分析,并论述红层滑坡与一般滑坡的不同点,分析红层软岩岩体力学特性、地层主要成分以及红层软岩中的粉砂质泥岩在不同风化程度下的力学特性。根据分析结果提出治理措施,并对治理措施进行评价。总结得出地层岩性、地质水文、人为因素是导致红层滑坡病害发生的主要因素。     

Vehicle kilometers traveled reduction impacts of Transit-Oriented Development: Evidence from Shanghai City

The role of residential self-selection has become a major subject in the debate over the relationships between the built environment and travel behavior. Numerous previous empirical studies on this subject have provided valuable insights into the associations between the built environment and travel behavior. However, the vast majority of the studies were conducted in North American and European cities; yet this research is still in its infancy in most developing countries, including China, where residential and transport choices are likely to be more constrained and travel-related attitudes quite different from those in the developed world. Using the data collected from 2038 residents currently living in TOD neighborhoods and non-TOD neighborhoods in Shanghai City, this paper aims to partly fill the gaps by investigating the causal relationship between the built environment and travel behavior in the Chinese context. More specifically, this paper employs Heckman’s sample selection model to examine the reduction impacts of TOD on personal vehicle kilometers traveled (VKT), controlling for self-selection. The results show that whilst the effects of residential self-selection are apparent; the built environment exhibits the most significant impacts on travel behavior, playing the dominant role. These findings produce a sound basis for local policymakers to better understand the nature and magnitude toward the impacts of the built environment on travel behavior. Providing the government department with reassurance that effective interventions and policies on land use aimed toward altering the built environment would actually lead to meaningful changes in travel behavior.     

格拉斯磁环匀强磁场分析

以毕奥-萨伐尔定律为基础,建立亥姆霍兹线圈以及格拉斯磁环中心磁场分布模型,并计算了它们内部的轴向磁感应强度分布,绘出了空间分布图,分析了轴向磁感应强度与x、y坐标的关系,分析结果得到了亥姆霍兹线圈和格拉斯磁环内部匀强磁场分布区域,通过比较得到格拉斯磁环内部的匀强磁场区域比亥姆霍兹线圈内部的匀强磁场分布区域更大的结论。     

Investigation of tailpipe and evaporative emissions from China IV and Tier 2 passenger vehicles with different gasolines

The limited understanding of vehicular emissions in China, especially evaporative emissions, is one obstacle to establishing tighter standards. To evaluate tailpipe and evaporative emissions, two typical China IV vehicles and one Tier 2 vehicle with an onboard refuelling vapour recovery (ORVR) system were selected and tested. One of the China IV vehicles was fuelled with gasoline, E10 and M15, respectively, to investigate the effect of fuel properties on vehicular emissions. For each vehicle, cold-start tailpipe emission tests were conducted first, followed by an evaporation test. Based on the emission factors and real-world vehicle activity data, the annual tailpipe and evaporative hydrocarbon (HC) emissions of each vehicle were calculated and compared. The results show that E10 and M15 significantly reduced the tailpipe CO and particle number (PN) emissions but seriously aggravated the NOx emissions, especially for M15. The hot soak losses (HSLs) and diurnal breathing losses (DBLs) were slightly impacted by the fuel properties. The annual evaporative emissions with E10 and M15 were higher than that with gasoline. The ORVR system effectively controlled the evaporative emissions, especially for DBLs. Evaporative emissions from the China IV vehicles were 1.1–1.4 times the tailpipe HC emissions. Additionally, the evaporative emission factors of the China IV vehicles were almost 50% lower than the standard (2.0 g/test), whereas their annual evaporative emissions were almost 1.8–2.8 times higher than those from the Tier 2 vehicle. Therefore, controlling evaporative emissions currently remains a great need in China, and the ORVR might be a recommended evaporative control technology.     

An improved cellular automaton with axis information for microscopic traffic simulation

Cellular Automaton (CA), an efficient dynamic modeling method that is widely used in traffic engineering, is newly introduced for traffic load modeling. This modeling method significantly addresses the modest traffic loads for long-span bridges. It does, however, require improvement to calculate precise load effects. This paper proposed an improved cellular automaton with axis information, defined as the Multi-axle Single-cell Cellular Automaton (MSCA), for the precise micro-simulation of random traffic loads on bridges. Four main ingredients of lattice, cells’ states, neighborhoods and transition rules are redefined in MSCA to generate microscopic vehicle sequences with detailed vehicle axle positions, user-defined cell sizes and time steps. The simulation methodology of MSCA is then proposed. Finally, MSCA is carefully calibrated and validated using site-specific WIM data. The results indicate: (1) the relative errors (REs) for the traffic parameters, such as volumes, speeds, weights, and headways, from MSCA are basically no more than ±10% of those of WIM data; (2) the load effects of three typical influence lines (ILs) with varied lengths of 50, 200 and 1000 m are also confidently comparable, both of which validate the rationality and precision of MSCA. Furthermore, the accurate vehicle parameters and gaps generated from MSCA can be applied not only for precise traffic loading on infrastructures but also for the accurate estimation of vehicle dynamics and safety. Hence, wide application of MSCA can potentially be expected.     

Definition of wind blowers for vehicles testing at chassis-dyno facilities using a CFD approach

The need to increase measurement accuracy of fuel consumption and pollutant emissions in vehicles is forcing the market to develop chassis-dyno test cells that reproduce on-road conditions realistically.Air-cooling is key to vehicle performance. It is therefore critical that the design of a test cell guarantees realistic cooling of all vehicle components, as important errors in fuel consumption and emissions measurements may otherwise arise. In a test-room, a blower placed in front of the vehicle supplies the cooling air. While there are some guidelines in the literature for the selection of fans required for emissions measurements for standard driving cycles, the information for designing the air supply system for specific tests in other areas is scarce.New Real Driving Emissions (RDE) legislation will force manufacturers to perform on-road measurements of pollutants. This represents a significant challenge due to the variability of conditions coming from non-controlled parameters. In order to optimize vehicles, different tests are performed in cells equipped with a chassis-dyno where the on-road flow field around the vehicle is reproduced as closely as possible.This work provides some guidelines for the definition of the airflow supply system of chassis-dyno facilities for vehicle optimization tests, based on a CFD analysis of the flow characteristics around the vehicle. By comparison with the solution obtained for a vehicle in real road driving conditions, the exit section of the blower and the distance between the blower exit and the car that best reproduce realistic on-road flow conditions in a test room are determined.     

Estimating traffic volumes for signalized intersections using connected vehicle data

Recently connected vehicle (CV) technology has received significant attention thanks to active pilot deployments supported by the US Department of Transportation (USDOT). At signalized intersections, CVs may serve as mobile sensors, providing opportunities of reducing dependencies on conventional vehicle detectors for signal operation. However, most of the existing studies mainly focus on scenarios that penetration rates of CVs reach certain level, e.g., 25%, which may not be feasible in the near future. How to utilize data from a small number of CVs to improve traffic signal operation remains an open question. In this work, we develop an approach to estimate traffic volume, a key input to many signal optimization algorithms, using GPS trajectory data from CV or navigation devices under low market penetration rates. To estimate traffic volumes, we model vehicle arrivals at signalized intersections as a time-dependent Poisson process, which can account for signal coordination. The estimation problem is formulated as a maximum likelihood problem given multiple observed trajectories from CVs approaching to the intersection. An expectation maximization (EM) procedure is derived to solve the estimation problem. Two case studies were conducted to validate our estimation algorithm. One uses the CV data from the Safety Pilot Model Deployment (SPMD) project, in which around 2800 CVs were deployed in the City of Ann Arbor, MI. The other uses vehicle trajectory data from users of a commercial navigation service in China. Mean absolute percentage error (MAPE) of the estimation is found to be 9–12%, based on benchmark data manually collected and data from loop detectors. Considering the existing scale of CV deployments, the proposed approach could be of significant help to traffic management agencies for evaluating and operating traffic signals, paving the way of using CVs for detector-free signal operation in the future.     

Adoption of alternative fuel vehicles: Influence from neighbors,family and coworkers

During the last years, many governments have set targets for increasing the share of biofuels in the transportation sector. Understanding consumer behavior is essential in designing policies that efficiently increase the uptake of cleaner technologies. In this paper we analyze adopters and non-adopters of alternative fuel vehicles (AFVs). We use diffusion of innovation theory and the established notion that the social system and interpersonal influence play important roles in adoption. Based on a nationwide database of car owners we analyze interpersonal influence on adoption from three social domains: neighbors, family and coworkers. The results point primarily at a neighbor effect in that AFV adoption is more likely if neighbors also have adopted. The results also point at significant effects of interpersonal influence from coworkers and family members but these effects weaken or disappear when income, education level, marriage, age, gender and green party votes are controlled for. The results extend the diffusion of innovation and AFV literature with empirical support for interpersonal influence based on objective data where response bias is not a factor. Implications for further research, environmental and transport policy, and practitioners are discussed.     

Liner shipping network design with emission control areas: A genetic algorithm-based approach

To curb emissions, containerized shipping lines face the traditional trade-off between cost and emissions (CO₂ and SO_x) reduction. This paper considers this element in the context of liner service design and proposes a mixed integer linear programming (MILP) model based on a multi-commodity pickup and delivery arc-flow formulation. The objective is to maximize the profit by selecting the ports to be visited, the sequence of port visit, the cargo flows between ports, as well as the number/operating speeds of vessels on each arc of the selected route. The problem also considers that Emission Control Areas (ECAs) exist in the liner network and accounts for the vessel carrying capacity. In addition to using the MILP solver of CPLEX, we develop in the paper a specific genetic algorithm (GA) based heuristic and show that it gives the possibility to reach an optimal solution when solving large size instances.