This paper presents how finite-element analysis can be used as a tool to design aboveground wavy pipeline layouts in order to avoid any excessive lateral movements under normal operating conditions. The paper also presents some field measurements of a typical pipeline layout and outlines the remedial work required to avoid having the pipeline from falling off its supports. A sensitivity analysis on the factors that affect the pipeline structural integrity was conducted using finite-element modeling. The effects of operating pressure, temperature, pipe diameter and wall thickness, pipeline wavelength, friction between the pipes and their supports, as well as support spacing on the pipeline lateral movements have been studied. It was found that the maximum pipeline lateral movement increases as the operating pressure, temperature, pipeline wavelength, and support spacing increase; whereas it decreases as the pipe diameter and wall thickness, friction coefficient and pipeline offset angle increase. The finite-element results also indicated possible pipeline layouts that cause excessive pipeline lateral movements to fall off their supports. In addition, a developed artificial neural network model showed that the offset angle contributes significantly $(\approx 51\%)$ to the pipeline lateral movement and reduces it by 10 times for an offset angle of $10°$ as compared to a straight pipeline layout.

This paper investigates the problem of estimating dynamic origin–destination $(O–D)$ trip matrices in large-scale transportation networks, using automatic link traffic counts and uncertain prior demand information, to facilitate the real-time monitoring of network traffic conditions through intelligent transportation systems. The paper proposes and evaluates the performance of two algorithms to estimate the temporal distribution of trip departures used to produce dynamic $O–D$ matrices, through several test experimentations in a real case study. The accuracy and the computing speed of the proposed algorithms is investigated in relation to different bounds, wherein trip departure estimates are sought to be included, levels of link count availability and network sizes. Results show that an optimization algorithm proposed for the fast estimation of trip departure rates with incorporated lower and upper bound constraints lead to dynamic $O–D$ matrices with considerably increased reliability, in comparison to the algorithm that intrinsically excludes demand constraints.

High-resolution vehicle speed profiles obtained from sophisticated devices such as global positioning system (GPS) receivers provide an opportunity to accurately measure intersection delay, composed of deceleration delay, stopped delay, and acceleration delay. Although the delay components can be measured by manually examining the speed profiles or derived time–space diagrams, identifying when vehicles begin to decelerate or stop accelerating is not always a straightforward task. In addition, a manual identification process may be laborious and time consuming when handling a large network or numerous runs. More importantly, the results from a manual process may not be consistent between analysts or even for a single analyst over time. This paper proposes a new approach to identifying control delay components based on second-by-second vehicle speed profiles obtained from GPS devices. The proposed approach utilizes both denoised speed and acceleration profiles for capturing critical points associated with each delay component. Speed profiles are used for the identification of stopped time periods, and acceleration profiles are used for detecting deceleration onset points and acceleration ending points. The writers applied this methodology to sampled runs collected from GPS-equipped instrumented vehicles and concluded that it satisfactorily computed delay components under normal traffic conditions and for the intersections not affected by adjacent intersections.

The use of a truck appointment system is gaining momentum in the marine container industry. It is used to regulate the number of trucks that can enter the terminal. Terminals employing appointment systems put a cap on the number of trucks that can enter a zone in the yard per time window. Limiting truck arrivals can be beneficial to some extent; however, if the caps are not set properly, it could be detrimental to both the terminal and the truckers. This paper examines the effect of limiting truck arrivals on truck turn time and crane utilization. In addition, it proposes a methodology to assist terminal operators with determining the optimal number of trucks to accept for the appointment system to be effective. The proposed methodology, which is a combination of mathematical formulation and simulation, seeks a solution that is beneficial for both the terminal operator and the trucker. Furthermore, the solution is robust to account for truckers with appointments showing up late or not showing up at all.