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.     

Development of jacket platform tsunami risk rating system in waters offshore North Borneo

This work details the simulation of tsunami waves generated by seaquakes in the Manila Trench and their effect on fixed oil and gas jacket platforms in waters offshore North Borneo. For this study, a four-leg living quarter jacket platform located in a water depth of 63m is modelled in SACS v5.3. Malaysia has traditionally been perceived to be safe from the hazards of earthquakes and tsunamis. Local design practices tend to neglect tsunami waves and include no such provisions. In 2004, a 9.3M _w seaquake occurred off the northwest coast of Aceh, which generated tsunami waves that caused destruction in Malaysia totalling US$ 25 million and 68 deaths. This event prompted an awareness of the need to study the reliability of fixed offshore platforms scattered throughout Malaysian waters. In this paper, we present a review of research on the seismicity of the Manila Trench, which is perceived to be high risk for Southeast Asia. From the tsunami numerical model TUNA-M2, we extract computer-simulated tsunami waves at prescribed grid points in the vicinity of the platforms in the region. Using wave heights as input, we simulate the tsunami using SACS v5.3 structural analysis software of offshore platforms, which is widely accepted by the industry. We employ the nonlinear solitary wave theory in our tsunami loading calculations for the platforms, and formulate a platform-specific risk quantification system. We then perform an intensive structural sensitivity analysis and derive a corresponding platform-specific risk rating model.