Reliability of the Ultimate Strength of Ship Stiffened Panel Subjected to Random Corrosion Degradation

Attentions have been increasingly paid to the influence of the corrosion on the ultimate strength of ship structures. In consideration of the random characteristics of the corrosion of ship structures, the method for the ultimate strength analysis of the ship stiffened panel structure subjected to random corrosion degradation is presented. According to the measured corrosion data of the bulk carriers, the distribution characteristics of the corrosion data for the stiffened panel on the midship deck are analyzed, and a random corrosion model is established. The ultimate strength of the corroded stiffened panel is calculated by lhe nonlinear finite element analysis. The statistical descriptions of the ultimate strength of the corroded stiffened panel are defined through the Monte Carlo simulations. A formula is proposed on the ultimate strength reduction of the stiffened panel as a function of the corrosion volume. The reliability analysis of the ultimate strength of the corroded deck stiffened panel is performed. It shows that both the corrosion data of the deck stiffened panel and the ultimate strength of the random corroded deck stiffened panel follow the log-normal distribution. The ultimate stress ratio of the stiffened panel is inversely proportional to the corrosion volume ratio.

Bayesian Reliability Modeling and Assessment Solution for NC Machine Tools under Small-sample Data

Although Markov chain Monte Carlo（MCMC） algorithms are accurate, many factors may cause instability when they are utilized in reliability analysis; such instability makes these algorithms unsuitable for widespread engineering applications. Thus, a reliability modeling and assessment solution aimed at small-sample data of numerical control（NC） machine tools is proposed on the basis of Bayes theories. An expert-judgment process of fusing multi-source prior information is developed to obtain the Weibull parameters＇ prior distributions and reduce the subjective bias of usual expert-judgment methods. The grid approximation method is applied to two-parameter Weibull distribution to derive the formulas for the parameters＇ posterior distributions and solve the calculation difficulty of high-dimensional integration. The method is then applied to the real data of a type of NC machine tool to implement a reliability assessment and obtain the mean time between failures（MTBF）. The relative error of the proposed method is 5.8020×10-4 compared with the MTBF obtained by the MCMC algorithm. This result indicates that the proposed method is as accurate as MCMC. The newly developed solution for reliability modeling and assessment of NC machine tools under small-sample data is easy, practical, and highly suitable for widespread application in the engineering field; in addition, the solution does not reduce accuracy.

Impacts of Bus Lane on Bus Travel Time Reliability:a Case Study in Shenzhen

The aim of the paper is to evaluate the impacts of bus lane on bus travel time reliability.The data used are the Geographic Positioning System(GPS) data of two bus lines running parallel streets in Shenzhen,China,one of which is a bus lane and the other is a regular lane.Two linear regression models are developed to evaluate the influence of bus lane which has a separated right of way.Other factors including running direction,day of week,time of day,dwell time,and delay at the start point are also considered in the model.Without published time tables,coefficient of variance(CV) of travel time is employed to explore the impacts of bus lane.The results indicate that bus lane can save 22.0% of travel time,reduce 11.5% of the CV of travel time,and decrease the variance of headway by 17.4%.The analysis on bus travel time reliability could help operators and drivers improve the quality of transit service.It also sheds light on how to assess the effectiveness of bus lane for transit planners and service operators.

Assessing travel time reliability implications due to roadworks on private vehicles and public transport services in urban road networks

Roadworks are perhaps the most controversial topic in transport professional field. On one hand, they are a necessity to assure the current and future functionality of the traffic network, while on the other, they are seen as a major disturbance by road users with concerns for excessive travel time delays. The impact of roadworks is usually analysed at a local level however the network-wide effects are crucial to ensure reliable travel times. Moreover the analysis usually focusses on private cars and the reliability impact on public transport services are too important to ignore. This paper investigates the impact of roadworks undertaken on a given road link over wider parts of the network and assesses travel time reliability for both cars and buses. This research involves setting up of a con- ventional network assignment model to arrive at the route choice of drivers as a result of the roadworks and then integrates the outcomes with a microsimulation model to generate space-time trajectories to arrive at travel times of individual vehicles. We adopted a reli- ability measure from the literature to compute travel time reliability of a given type of vehicle by unique origin-destination （O-D） pair combinations and also more generally to provide a wider picture at an aggregated network level. The method was tested on a real life network in England, and travel time reliability results were analysed both at the network scale and significant O-D pair level for private cars and bus routes.

Understanding network travel time reliability with on-demand ride service data

Travel time reliability is of increasing importance for travelers, shippers, and transportation managers because traffic congestion has become worse in major urban areas in recent years. To better evaluate the urban network-wide travel time reliability, five indices based on the emerging on-demand ride service data are proposed:network free flow time rate(NFFTR), network travel time rate(NTTR), network planning time rate(NPTR), network buffer time rate(NBTR), and network buffer time rate index(NBTRI). These indices take into account the probability distribution of the travel time rate(i.e., travel time spent for the unit distance, in min/km) of each origindestination(OD) pair in the road network. We use realworld data extracted from DiDi-Chuxing, which is the largest on-demand ride service platform in China. For demonstrative purposes, the network-wide travel time reliability of Beijing is analyzed in detail from two dimensions of time and space. The results show that the road network is more unreliable in AM/PM peaks than other time periods, and the most reliable time period is the early morning. Additionally, we can find that the central region is more unreliable than other regions of the city based on the spatial analysis results. The proposed network travel time reliability indices provide insights for the comprehensive evaluation of the road network traffic dynamics and day-to-day travel time variations.

Travel time reliability with and without the dynamic use of hard shoulder:Field assessment from a French motorway

Traffic management aims to ensure a high quality of service for most users by decreasing congestion and increasing safety. However, uncertainty regarding travel time decreases the quality of service and leads end-users to change their routes and schedules even when the average travel time is low, Indicators describing travel time reliability are being developed and should be used in the future both for the optimization and the assessment of active traffic management operation. This paper describes a managed lane experience on a motorway weaving section in France - hard shoulder running operation in rush hours. The paper is focused on travel time reliability indicators and their use for reliability assessment. It provides some discussions about the advantages and drawbacks of reliability indicators under different traffic conditions. It particularly shows the difference between using buffer times and buffer indexes. The paper also discusses the difficulty of interpreting the skew of travel time distribution for travel reliability,

Optimization of transit total bus stop time models

Several factors influence bus transit reliability which includes bus stop conditions along the route, traffic conditions, route of travel and time of day. The overall transit bus reli- ability is generally affected by dwell time （DT）, the fare payment method, the bus stop location, and the number of passengers alighting or boarding. A new variable is defined in this study, total bus stop time （TBST）, which is the summation of DT and the time it takes a bus to effectively park at a bus stop and the re-entering the traffic stream. It is suggested that the overall bus transit reliability along routes could be improved if the TBST is mini- mized at bus stops. In this study, TBST models for bus stops located at mid-blocks and near intersections were developed based on multivariate regression analysis using ordinary least squares method. Data collection was conducted at 60 bus stops, 30 of which were near intersections and 30 at mid-blocks, in Washington DC during morning, mid-day and evening peak hours. The variables observed at each bus stop are as follows： number of passengers alighting or boarding, DT, TBST, bus stop type, bus pad, length number of lanes on approach to the bus stop, and permitted parking. Statistical inferences were based on 5% level of significance. From the results, it was inferred that the new variable, TBST, could potentially be used to improve scheduling and transit bus systems planning in a dense urban area.