The two-dimensional study of the interaction between liquid loshing and elastic structures

Sloshing phenomenon in the liquid cargo carriers has caught the attention of researchers as the interaction between the sloshing waves and structure is one of the key point and difficulty in the study of sloshing. In this paper, we captured the free surface with a volume of fluid (VOF) method and then calculated the motions and responses of the structure by adopting the Reynolds-averaged Navier-Stokes (RANS) equations for the whole fluid domain. With the use of user defined functions (UDF) in Fluent, the interaction between fluid and structure was then simulated. As a reasonable simplification, the authors studied the response of a single cantilever in a tank under sloshing loads; Further study should pay more attention to the mechanisms of interaction between sloshing waves and elastic structures.     

Research of scalability of the belt-type sensor networks

For the large-scale application requirements of the belt-type networks, the mathematical modeling as well as quantitative analysis for the scalability of the network based on average path length is completed in this paper, and the theorem for the scale scalability of the belt-type networks is derived. The theorem provides a calculation formula for the upper limit of node scale theory of the belt-type networks and a calculation formula for the upper limit of single node load theory.     

Robust design optimization of suspension system considering steering pull reduction

This paper presents robust design optimization method to reduce steering pull phenomenon. One of the biggest causes of steering pull phenomenon is tolerance of suspension system such as hard point, spring, damper and bush. Therefore, the relationship between suspension systems and steering pull phenomenon has as nonlinear characteristics. But, it can be very difficult to evaluate the analytical design sensitivity. Thus, it is impossible to directly apply a well-developed optimization algorithm based on gradient information. To avoid these difficulty, this study uses sequential approximation optimization process based on a meta-model. The robust design process has 28 random design variables with tolerance. For efficient design process, the sample variances for the design goals are approximated from meta-models. The proposed approach required only 62 evaluations until it converged. Optimal design reduced the drift by 80% and its deviation by 38.7%, respectively. This result proves that the suggested design method of suspension system is effective and useful.     

Cooling performance of 25 kW in-wheel motor for electric vehicles

The in-wheel motor used in electric vehicles was designed and constructed for an electric direct-drive traction system. It is difficult to connect cooling water piping to the in-wheel motor because the in-wheel motor is located within the wheel structure. In the air cooling structure for the in-wheel motor, an outer surface on the housing is provided with cooling grooves to increase the heat transfer area. In this study, we carried out the analysis on the fluid flow and thermal characteristics of the in-wheel motor for various motor speeds and heat generations. In order to resolve heat release, the analysis has been performed using conjugate heat transfer (conduction and convection). As a result, flow fields and temperature distribution inside the in-wheel motor were obtained for base speed condition (1250 rpm) and maximum speed condition (5000 rpm). The thermo-flow analysis of the in-wheel motor for vehicles was performed in consideration of ram air effect. Also, in order to improve cooling effect of the motor, we variously changed geometries of housing. Therefore, we confirmed the feasibility of the air cooling for the motors of 25 kW capacity with housing geometry having cooling grooves and investigated the cooling performance enhancement. We found that the cooling effect was most excellent, in case that cooling groove direction was same with air flow direction and arranged densely.     

Angular position error detection of variable reluctance resolver using simulation-based approach

The variable reluctance type resolver is widely used in an electric motor for hybrid electric vehicles as a rotor position sensor. The purpose of this paper is to present a simulation-based approach capable of determining a more accurate rotor shape of variable reluctance resolver in order to cut the time and cost of its development before testing a physical prototype. For the verification of the simulation-based approach to the position error detection of rotor, experiments for 8XVR resolver were conducted. Based on this approach, an optimal salient-pole rotor shape of 4X-VR resolver is proposed.     

Research of order allocation model based on cloud and hybrid genetic algorithm under ecommerce environment

For massive order allocation problem of the third party logistics (TPL) in ecommerce, this paper proposes a general order allocation model based on cloud architecture and hybrid genetic algorithm (GA), implementing cloud deployable MapReduce (MR) code to parallelize allocation process, using heuristic rule to fix illegal chromosome during encoding process and adopting mixed integer programming (MIP) as fitness function to guarantee rationality of chromosome fitness. The simulation experiment shows that in mass processing of orders, the model performance in a multi-server cluster environment is remarkable superior to that in stand-alone environment. This model can be directly applied to cloud based logistics information platform (LIP) in near future, implementing fast auto-allocation for massive concurrent orders, with great application value.     

Longer-term changes in mode choice decisions in Chennai: a comparison between cross-sectional and dynamic models

The rapid and continuing changes in travel and mobility needs in India over the last decade necessitates the development and use of dynamic models for travel demand forecasting rather than cross-sectional models. In this context, this paper investigates mode choice dynamics among workers in Chennai city, India over a period of five years (1999–2004). Dynamics in mode choice is captured at four levels: exogenous variable change, state-dependence, changes in users’ sensitivity to attributes, and unobserved error terms. The results show that the dynamic models provide a substantial improvement (of over 500 log-likelihood points and ρ² increases from 44% to 68%) over the cross-sectional model. The performance was compared using two illustrative policy scenarios with important methodological and practical implications. The results indicate that cross-sectional models tend to provide inflated estimates of potential improvement measures. Improving the Level of Service (LOS) alone will not produce the anticipated benefits to transit agencies, as it fails to overcome the persistent inertia captured in the state-dependence factors. The results and models have important applications in the context of growing motorization and congestion management in developing countries.

The transition to electric bikes in China: history and key reasons for rapid growth

Annual electric bike (e-bike) sales in China grew from 40,000 in 1998 to 10 million in 2005. This rapid transition from human-powered bicycles, buses and gasoline-powered scooters to an all-electric vehicle/fuel technology system is special in the evolution of transportation technology and, thus far, unique to China. We examine how and why e-bikes developed so quickly in China with particular focus on the key technical, economic, and political factors involved. This case study provides important insights to policy makers in China and abroad on how timely regulatory policy can change the purchase choice of millions and create a new mode of transportation. These lessons are especially important to China as it embarks on a large-scale transition to personal vehicles, but also to other countries seeking more sustainable forms of transportation.

Design and development of a stated choice experiment for interdependent agents: accounting for interactions between buyers and sellers of urban freight services

Stated choice experiments have proven to be a powerful tool in eliciting preferences across a broad range of choice settings. This paper outlines the elements of a group-based experiment designed for interdependent urban freight stakeholders, along with the procedure to administer the questionnaire sequentially. The focus is on the design of a computer-assisted personal survey instrument and the value in disseminating the details of a new approach to design and collect stated choice data for interacting agents. The paper also discusses how to specify a reference alternative, and then how to recruit appropriate real-market or representative decision-making group members to participate in a subsequent phase of the survey, which incorporates the reference alternative and contextual information from an initial phase. The empirical strategy, set out in some detail, provides a new framework within which to understand more fully the role that specific attributes, such as variable user charges, influencing freight distribution chains might play, and who in the supply chain is affected by specific attributes in terms of willingness to pay for the gains in distribution efficiency.