Impact behavior modeling of motorcycle front wheel-tire assembly

Experiments were conducted to investigate the influence of certain parameters that affect the impact response of the motorcycle front wheel-tire assembly under various impact conditions. Impact tests were conducted according to 2 _ν ^{5 − 1} fractional factorial design using a pendulum impact test apparatus with impact speed, impact mass, tire inflation pressure level, striker geometry, and impact location as design factors. Significant factors influencing the response of the wheel-tire assembly were identified. Coefficients for each factor were also determined, and empirical models were then developed for each response. An analysis indicates that the developed models fit well within the experimental ranges of the respective factors. However, for several interaction effects, the models become unrealistic, whereby they give certain deformation values when approaching zero impact mass and/or zero impact velocity. This is not consistent with the mechanics of the physical world, as there should not be any significant deformation when delivered impact energy is small enough. Efforts have been made in developing better models to resolve the inconsistency and to include a wider range, especially considering the case of the lower limit of experimental factors, which are an impact mass of 51.18 kg and/or an impact velocity of 3 m s⁻¹ (10.8 km/h) down to zero. The minimum amount of impact energy required to produce the onset of observable deformation on the wheel was incorporated in the development of new models. Finally, the present models have been developed not only to cover the lower regions but also to range up to the upper limits of the factors, which are an impact mass of 101.33 kg and an impact velocity of 6 m s⁻¹ (21.6 km/h).     

Optimal allocation of turns to lanes at an isolated signal-controlled junction

Conventional design methods require the lane marking patterns, which are painted on ground showing road users the permissible turning directions on different approach lanes, as exogenous inputs to define the traffic stream grouping for analysis. This predefined grouping of traffic movements may restrict the design of signal timings in the optimisation procedures. More recently, a lane-based design method has been developed to relax the lane markings as binary-type control variables in a mathematical programming approach. The lane marking patterns and the signal timings can then be optimised simultaneously in a unified framework. This paper presents an extension work to further relax the numbers of approach lane in traffic arms as new integer variables which can then be optimised to give optimal lane arrangement in various arms of a junction to manage the given traffic demands more efficiently. All well-defined signal timings variables in the phase-based approach as well as the lane marking and lane flow variables in the lane-based approach together with their governing constraints are all preserved in the new formulation for the reserve capacity optimisation of isolated signal-controlled junctions.     

替苹果新主塑造形象

蒂姆·库克(Tim Cook)先生,从苹果教主乔布斯手上接过CEO的黄金棒后,自此整个科技世界恐怕都会聚焦在你的身上吧。懂得你的人,都知道你那低调与默默耕耘的作风,以及相对温逊的性格,与乔布斯那万丈光芒汇聚的前台身影恰成对比。谁能忘记是你一手把苹果从一堆濒临失效的制造供应链上拯救过来?今天大家趋     

A reliability‐based network design problem

This paper presents a reliability‐based network design problem. A network reliability concept is embedded into the continuous network design problem in which travelers' route choice behavior follows the stochastic user equilibrium assumption. A new capacity‐reliability index is introduced to measure the probability that all of the network links are operated below their capacities when serving different traffic patterns deviating from the average condition. The reliability‐based network design problem is formulated as a bi‐level program in which the lower level sub‐program is the probit‐based stochastic user equilibrium problem and the upper level sub‐program is the maximization of the new capacity reliability index. The lower level sub‐program is solved by a variant of the method of successive averages using the exponential average to represent the learning process of network users on a daily basis that results in the daily variation of traffic‐flow pattern, and Monte Carlo stochastic loading. The upper level sub‐program is tackled by means of genetic algorithms. A numerical example is used to demonstrate the concept of the proposed framework.     

A schedule-based time-dependent trip assignment model for transit networks

A schedule-based time-dependent trip assignment model for transit networks is presented. First the transit network model is formulated using the schedule-based approach, in which the vehicles are assumed to arrive punctually in accordance with a scheduled time-table. Based on a previously developed time-dependent shortest path algorithm, an all-or-nothing network loading procedure is employed to assign the passenger trips onto the network. Both the passenger demand and scheduled time-table are time-varying. This provides a versatile tool for the evaluation of the performance of transit networks subject to peak period loading. A case study using the Mass Transit Railway System in Hong Kong is given to illustrate the potential applications of the model.     

A fuzzy method for predicting the demand for rail freight transportation

The demand for rail freight transportation is a continuously changing process over space and time and is affected by many quantitative and qualitative factors. In order to develop a more rational transport planning process to be followed by railway organizations, there is a need to accurately forecast freight demand under a dynamic and uncertain environment. In conventional linear regression analysis, the deviations between the observed and the estimated values are supposed to be due to observation errors. In this paper, taking a different perspective, these deviations are regarded as the fuzziness of the system's structure. The details of fuzzy linear regression method are put forward and discussed in the paper. Based on an analyzes of the characteristics of the rail transportation problem, the proposed model was successfully applied to a real example from China. The results of that application are also presented here.     

Maximum likelihood,entropy maximization,and the geometric programming approaches to the calibration of trip distribution models

Geometric programming is used to establish a formal primal-dual relationship between the maximum likelihood and the entropy maximization formulations of the trip distribution model. This relationship produces solution characteristics which agree with well known results. It provides an efficient procedure for interpreting and solving the model. A systematic method for conducting post-optimal sensitivity analysis is also available. The development is illustrated through a simple example.     

Analysis and optimization of air suspension system with independent height and stiffness tuning

Suspensions play a crucial role in vehicle comfort and handling. Different types of suspensions have been proposed to address essential comfort and handling requirements of vehicles. The conventional air suspension systems use a single flexible rubber airbag to transfer the chassis load to the wheels. In this type of air suspensions, the chassis height can be controlled by further inflating the airbag; however, the suspension stiffness is not controllable, and it depends on the airbag volume and chassis load. A recent development in a new air suspension includes two air chambers (rubber airbags), allowing independent ride height and stiffness tuning. In this air suspension system, stiffness and ride height of the vehicle can be simultaneously altered for different driving conditions by controlling the air pressure in the two air chambers. This allows the vehicle’s natural frequency and height to be adjusted according to the load and road conditions. This article discusses optimization of an air suspension design with ride height and stiffness tuning. An analytical formulation is developed to yield the optimum design of the new air suspension system. Experimental results verify the mathematical modeling and show the advantages of the new air suspension system.