On the numerical accuracy of the wave load distribution on a ship advancing in short and steep waves

Defining numerical uncertainty is an important part of the practical application of a numerical method. In the case of a ship advancing in short and steep waves, little knowledge exists on the solution behaviour as a function of discretisation resolution. This paper studies an interface-capturing (VOF) solution for a passenger ship advancing in steep (kA = 0.24) and short waves (L _w /L _pp = 0.16). The focus is to estimate quantitative uncertainties for the longitudinal distributions of the first–third harmonic wave loads in the ship bow area. These estimates are derived from the results of three systematically refined discretisation resolutions. The obtained uncertainty distributions reveal that even the uncertainty of the first harmonic wave load varies significantly along the ship bow area. It is shown that the largest local uncertainties of the first harmonic wave load relate to the differences in the local details of the propagating and deforming encountered waves along the hull. This paper also discusses the challenges that were encountered in the quantification of the uncertainties for this complex flow case.     

Travel experience matters: Expected personal mobility impacts after simulated L3/L4 automated driving

Transportation - Automated vehicles (AVs) are expected to change personal mobility in the near future. Most studies on the mobility impacts of AVs focus on fully automated (SAE L5) vehicles, but...     

Short-Term Prediction of Travel Time using Neural Networks on an Interurban Highway

The main purpose of this study was to investigate the predictability of travel time with a model based on travel time data measured in the field on an interurban highway. Another purpose was to determine whether the forecasts would be accurate enough to implement the model in an actual online travel time information service. The study was carried out on a 28-kilometre-long rural two-lane road section where traffic congestion was a problem during weekend peak hours. The section was equipped with an automatic travel time monitoring and information system. The prediction models were made as feedforward multilayer perceptron neural networks. The main results showed that the majority of the forecasts were close to the actual measured values. Consequently, use of the prediction model would improve the quality of travel time information based directly on the sum of the latest measured travel times.     

Online Prediction of Travel Time: Experience From a Pilot Trial

Abstract

This study was designed to present an online model which predicted travel times on an interurban two-lane two-way highway section on the basis of field measurements. The study included two parts: an evaluation of the performance of the model, and an examination of the possibility to improve the model in case of unsatisfactory performance. The model was based on MLP neural networks. The main results of the evaluation showed that the prediction model outperformed a non-predictive system. However, the model for one section had not performed as well during the trial period as was expected. This might be due to a slight change in the congestion phenomenon. After further development, the findings showed that the model could be improved considerably with new data. The main implication was that even a simple prediction model improves the quality of travel time information substantially, compared to estimates based directly on the latest measurements.     

Computational and experimental study on local ship loads in short and steep waves

Currently, little information exists on the validity of interface-capturing methods in predicting local ship wave loads in short and steep waves. This study compares computational and experimental results in such a case (kA = 0.24, L _wave /L _ship = 0.16). The results allow the variation of wave loading between ten locations in the bow area of the ship to be observed. The computations were performed with an unstructured RANS solver that models free-surface flows with a volume-of-fluid method. In the model tests, the wave loads were measured with pressure sensors. The analysis of the results focuses on the wave conditions and on the pressure histories of the local wave loads. The computational and experimental results are in good qualitative agreement and encourage the further use of the computational results.