两种直接波浪能转换系统性能的比较:阿基米德波浪摆和波能浮筒(英文)

Many wave energy conversion devices have not been well received. The main reasons are that they are too complicated and not economical. However, in the last two decades direct conversion systems have drawn the attention of researchers to their widely distributed energy source due to their simple structure and low cost. The most well-known direct conversion systems presently in use include the Archimedes Wave Swing (AWS) and Power Buoy (PB). In this paper, these two systems were simulated in the same conditions and their behaviors were studied in different wave conditions. In order to verify the simulations, results of the generator of the finite element computations were followed. An attempt was made to determine the merits and drawbacks of each method under different wave conditions by comparing the performance of the two systems. The wave conditions suitable for each system were specified.     

双通线加热的热力学及实验分析(英文)

The present investigation deals with process analysis of oxy-acetylene flame assisted double pass line heating for varying plate thickness. oxy-acetylene flame as the heat source for multi pass line heating to achieve 3-D bending of plates with varying thicknesses was studied. The oxy-acetylene flame was modeled as the moving heat source in the FEM analysis. The transient thermal histories were predicted taking into account the temperature dependent thermo-mechanical properties. A comparative study between single pass and double pass line heating residual deformation was also carried out. The temperature distribution and residual deformations predicted by the numerical model developed in the present work compared fairly well with those of the experimental ones.     

Experimental Investigation of TARMAX Model for Modeling of Hydrodynamic Forces on Cylinder-like Structures

A new approach that models lift and drag hydrodynamic force signals operating over cylindrical structures was developed and validated. This approach is based on stochastic auto regressive moving average with exogenous (ARMAX) input and its time-varying form, TARMAX. Model structure selection and parameter estimation were discussed while considering the validation stage. In this paper, the cylindrical structure was considered as a dynamic system with an incoming water wave and resulting forces as the input a...     

A generic class of first order node models for dynamic macroscopic simulation of traffic flows

Node models for macroscopic simulation have attracted relatively little attention in the literature. Nevertheless, in dynamic network loading (DNL) models for congested road networks, node models are as important as the extensively studied link models. This paper provides an overview of macroscopic node models found in the literature, explaining both their contributions and shortcomings. A formulation defining a generic class of first order macroscopic node models is presented, satisfying a list of requirements necessary to produce node models with realistic, consistent results. Defining a specific node model instance of this class requires the specification of a supply constraint interaction rule and (optionally) node supply constraints. Following this theoretical discussion, specific macroscopic node model instances for unsignalized and signalized intersections are proposed. These models apply an oriented capacity proportional distribution of the available supply over the incoming links of a node. A computationally efficient algorithm to solve the node models exactly is included.     

Large-scale application of MILATRAS: case study of the Toronto transit network

This paper documents the efforts to operationalize the conceptual framework of MIcrosimulation Learning-based Approach to TRansit Assignment (MILATRAS) and its component models of departure time and path choices. It presents a large-scale real-world application, namely the multi-modal transit network of Toronto which is operated by the Toronto Transit Commission (TTC). This large-scale network is represented by over 500 branches with more than 10,000 stops. About 332,000 passenger-agents are modelled to represent the demand for the TTC in the AM peak period. A learning-based departure time and path choice model was adopted using the concept of mental models for the modelling of the transit assignment problem. The choice model parameters were calibrated such that the entropy of the simulated route loads was optimized with reference to the observed route loads, and validated with individual choices. A Parallel Genetic Algorithm engine was used for the parameter calibration process. The modelled route loads, based on the calibrated parameters, greatly approximate the distribution underlying the observed loads. 75% of the exact sequence of transfer point choices were correctly predicted by the off-stop/on-stop choice mechanism. The model predictability of the exact sequence of route transfers was about 60%. In this application, transit passengers were assumed to plan their transit trip based on their experience with the transportation network; with no prior (or perfect) knowledge of service performance.     

Simulating the impacts of household travel on greenhouse gas emissions,urban air quality,and population exposure

This paper establishes a link between an activity-based model for the Greater Toronto Area (GTA), dynamic traffic assignment, emission modelling, and air quality simulation. This provides agent-based output that allows vehicle emissions to be tracked back to individuals and households who are producing them. In addition, roadway emissions are dispersed and the resulting ambient air concentrations are linked with individual time-activity patterns in order to assess population exposure to air pollution. This framework is applied to evaluate the effects of a range of policy interventions and 2031 scenarios on the generation of vehicle emissions and greenhouse gases in the GTA. Results show that the predicted increase of approximately 2.6 million people and 1.3 million jobs in the region by 2031 compared to 2001 levels poses a major challenge in achieving meaningful reductions in GHGs and air pollution.     

Analysis of the environmental benefits of a motorcycle idling stop policy at urban intersections

In an attempt to reduce CO₂ emissions from motorized transport, the Taiwanese government introduced an idling stop policy for vehicles in early 2007. This paper seeks to quantify the environmental benefits of the policy based on a stated preference analysis. Motorcyclists were surveyed at urban intersections in Taiwan, to identify the amount of time they would be willing to turn off their engines while waiting at traffic lights (the WTO). A contingent valuation framework based on stated preference questions was designed to determine the WTO. Results obtained from the Spike model showed that the average motorcyclist’s WTO is 82 s. In another analysis, in which other variables were taken into consideration, such as the possibility that the policy will be enacted as legislation, the expected WTO increased to 101 s. In both cases, an idling stop policy would have positive environmental effects, reducing gasoline usage by 1021 L per hour and reducing CO₂ emissions by 0.56 metric tons per hour at the intersection studied during peak periods.     

Discretionary activity location choice: in-home or out-of-home?

This paper examines the location choice associated with discretionary activities (in-home vs. out-of-home). These substitution patterns are important in terms of travel demand as in-home activities do not necessitate travel while out-of-home activities incur travel. Mixed logit models are estimated using an activity dataset (2003 CHASE data) to analyze the factors associated with this choice at the individual activity-level. Results suggest that the attributes of an activity significantly contribute to understanding the likelihood of engaging in out-of-home activities. Activity type interaction terms reveal the varying influence that socio-demographics, activity attributes and travel have over four different activity types modeled. The results reveal that the location choice (in-home vs. out-of-home) is sensitive to travel characteristics. As the travel time and cost increases, an individual is less likely to engage in an activity out-of-home. Compared to passive and social activities, the location of active activities is more sensitive to changes in travel attributes.     

Analysis of cost estimation disclosure in environmental impact statements for surface transportation projects

Reliability in cost estimates in publicly funded projects is more important today than ever with increased governmental funding to infrastructure projects and associated accountability requirements, but surface transportation projects, large and small, in the United States have a legacy of cost overruns. The problems with these overruns start with the cost estimation process before projects begin. Studies have shown that early cost estimations reflect best-case scenarios rather than realistic expectations, and have attributed technical, economic, psychological, and political reasons for underestimation. The primary objectives of this research were to determine how costs have been presented and updated in environmental impact statements, to identify endemic technical problems with cost estimation during the environmental review of surface transportation projects, and to develop recommendations for improving cost estimation and disclosure. Cost estimation methods were analyzed from the documents of 100 projects, including draft environmental impact statements, final environmental impact statements, and records of decision. The study concluded that the lack of guidance on how to include cost estimation in environmental review revealed itself in the level of detail and attention given to estimating costs. Agencies omitted or included various aspects of cost estimation randomly. Professional organizations should fill the gap of the need for specific guidance to cost estimation for environmental review so it can evolve as a state of the practice.     

Managing passenger behavioral intention: an integrated framework for service quality,satisfaction, perceived value,and switching barriers

This paper seeks to improve our understanding of passengers’ behavioral intention by proposing an integrated framework from the attitudinal perspective. According to the literature in marketing research, we establish a causal relationship model that considers “service quality-satisfaction-behavioral intentions” paradigm, perceived value theory, and switching barrier theory. Exploring passengers’ behavioral intention from satisfaction and perceived value help to understand how passengers are attracted by the company, while switching barriers assist in realizing how passengers are “locked” into a relationship with the current company. Furthermore, in order to capture the nature of service quality, we adopt a hierarchical factor structure which serves service quality as the higher-order factor. In this study, coach industry is selected as our research subject. The empirical results, as hypothesized, show that all causal relationships are statistically significant, and perceived value us the most important predictor of satisfaction and passengers’ behavioral intention. In conclusion, the managerial implications and suggestions for future research are discussed.