Oriented review to potential simulator for faults modeling in diesel engine

This paper presents a literature review on most of the faults and their models that are considered on a diesel engine. Several faults that may be produced on diesel engine have been analyzed, classified, modeled, and their influences on the global system have been shown. Thus, this paper aims to prepare an important data base on diesel engine faults which may help researchers to develop precise strategies on diesel engine fault diagnosis and prognosis, and also it helps in the development of diesel engine simulators aiming to study the behavior of the diesel engine in the presence of faults. Different fault models such as analytical, empirical, degradation models which may be represented as function of time or as function of the number of cycles, data driven models such as neural network models, or simply constant are presented and analyzed. The global overall models for diesel engine integrating faults are expressed. And finally, the use of these models with the most common failure density distribution functions is proposed giving a more realistic approach to our study.     

On the use of mathematical programming in the evaluation of transport policies

This paper focuses on the evaluation processes by which decisions regarding transportation alternatives can be assisted. A multidimensional approach usually called multiple criteria decision making is required to represent the complexity of transportation policy and systems.

The multiple criteria decision making techniques can be divided into two groups. The first is based on a ranking scheme approach and the second on a mathematical programming approach.

A multiple objective mathematical programming procedure known as Goal Programming is presented. The authors examined the use of that procedure in real transportation problems.

The results suggest that multiple objective mathematical programming techniques in general do not appear to be appropriate in transportation policy analysis involving mutually exclusive alternatives. Their use can be limited to special cases in the private sector.     

A time‐staged multi‐objective network‐design model

A multi‐objective, time‐staged network‐design problem is formulated. Through transformation, the problem is decomposed into a set of single‐period, single‐objective problems. Lexicographic ordering is instrumental in effecting this transformation; it also allows a backward‐recursion algorithm to be applied using strong pruning criteria. Furthermore, monotonicity properties enable us to solve the problem using the familiar tree‐search algorithms. The solution method has several desirable properties — as shown by an example and a case study of Tripoli Province, Libya. First, the algorithm ensures continuity of project implementation over the multi time‐periods and provides optimality in later computational stages irrespective of the decision at an interim stage. Second, the algorithm tends to provide accessibility to unconnected regions in the study area at low user‐cost without employing weights to the two objective functions of accessibility and user‐cost efficiency. Such a property is deemed advantageous for suggesting transportation investments based purely on purchasing the greatest benefit for each dollar, with political neutrality strictly maintained.     

An algorithm for finding reasonable paths in transit networks

In this paper, reasonable paths in transit networks are defined as possible paths that satisfy the acceptable time criterion and transfer‐walk criterion. A recursive algorithm for finding all of the reasonable paths in a transit network that does not involve a rapid increase in program run‐time with network size is presented. Realistic transit networks in Hong Kong and Guangzhou were selected as case studies of the different phases of the development of a trip planning system. Transport planning practitioners and potential users were invited to test the system to evaluate its performance. The results of the prototype evaluation were satisfactory, and the viability of the system as a useful tool for supporting decision‐making has been confirmed by the positive feedback that was obtained from survey questionnaires.     

Mooring line tension observed through a maximum entropy spectrum

A method for measuring mooring line tension is proposed based on observation of the natural frequencies of the mooring line segment between the winch and the fairlead. The anchor line tension is observed through the string equation where an analytical expression for the line's eigen-frequencies is obtained. The tension is observed on line by utilizing a nonparametric system identification approach in which the peaks of a maximum entropy spectrum of the transverse acceleration measures of the vibrating string are automatically identified. The method is verified against full-scale data from the Troll B floating concrete oil production platform operating in the North Sea. Received for publication on Feb. 24, 1999; accepted on July 26, 1999     

Value of travel time: An activity‐based analysis with combined RP and SP data

Under certain assumptions, values of travel time (VOT) can be divided into two parts: one associated with travel (i.e., the value of reducing travel time disutility) and the other associated with activities (the shadow price of time). The empirical results of combining RP and SP data showed that the VOT of travel was greater than that of activity. The results also showed that SP experiments that did not take or only took part of activities into consideration would underestimate VOT.     

Automation of paratransit reservation,routing, and scheduling

Santa Clara County, California experienced a sharp growth in demand‐responsive paratransit ridership for individuals with disabilities, as a result of the passage of the 1990 Americans With Disabilities Act (ADA). This paper describes an automated paratransit system for the ADA‐type paratransit operation implemented in Santa Clara County. It automated paratransit reservation, scheduling, and routing functions. The key components of this system were a digital geographic database (DGD) and an automated trip scheduling system (ATSS). Empirical evidence after one year of operation indicates numerous benefits of this automation. There were significant reductions in the paratransit operating costs and an increase in the percent shared rides. The savings in operating costs far exceeded the annualized capital cost of automation. A user survey indicates that these improvements were achieved without degradation to service quality such as vehicle on‐time performance, invehicle travel times, vehicle response to open return, and ride comfort.     

Hybrid model for prediction of bus arrival times at next station

Effective prediction of bus arrival times is important to advanced traveler information systems (ATIS). Here a hybrid model, based on support vector machine (SVM) and Kalman filtering technique, is presented to predict bus arrival times. In the model, the SVM model predicts the baseline travel times on the basic of historical trips occurring data at given time‐of‐day, weather conditions, route segment, the travel times on the current segment, and the latest travel times on the predicted segment; the Kalman filtering‐based dynamic algorithm uses the latest bus arrival information, together with estimated baseline travel times, to predict arrival times at the next point. The predicted bus arrival times are examined by data of bus no. 7 in a satellite town of Dalian in China. Results show that the hybrid model proposed in this paper is feasible and applicable in bus arrival time forecasting area, and generally provides better performance than artificial neural network (ANN)–based methods. Copyright © 2010 John Wiley & Sons, Ltd.     

The planning of aircraft routes and flight frequencies in an airline network operations

This research is aimed at developing a model that maximizes system profit when determining the aircraft routes and flight frequencies in a network. The model employs network flow techniques to effectively collect or deliver passenger flows from all origins to all destinations using non‐stop and multi‐stop flights in multi‐fleet operations. The model was formulated as a multi‐commodity network flow problem. A Lagrangian‐based algorithm was developed to solve the problem. To test the model in practice, a case study is presented.