The liner-shipping network design problem is to create a set of nonsimple cyclic sailing routes for a designated fleet of container vessels that jointly transports multiple commodities. The objective is to maximize the revenue of cargo transport while minimizing the costs of operation. The potential for making cost-effective and energy-efficient liner-shipping networks using operations research (OR) is huge and neglected. The implementation of logistic planning tools based upon OR has enhanced performance of airlines, railways, and general transportation companies, but within the field of liner shipping, applications of OR are scarce. We believe that access to domain knowledge and data is a barrier for researchers to approach the important liner-shipping network design problem. The purpose of the benchmark suite and the paper at hand is to provide easy access to the domain and the data sources of liner shipping for OR researchers in general. We describe and analyze the liner-shipping domain applied to network design and present a rich integer programming model based on services that constitute the fixed schedule of a liner shipping company. We prove the liner-shipping network design problem to be strongly NP-hard. A benchmark suite of data instances to reflect the business structure of a global liner shipping network is presented. The design of the benchmark suite is discussed in relation to industry standards, business rules, and mathematical programming. The data are based on real-life data from the largest global liner-shipping company, Maersk Line, and supplemented by data from several industry and public stakeholders. Computational results yielding the first best known solutions for six of the seven benchmark instances is provided using a heuristic combining tabu search and heuristic column generation.
Different port operating policies have the potential to reduce emissions from shipping; however, their efficacy varies for different ports. This article extends existing literature to present a consistent and transferable methodology that examines emissions reduction port policies based on ship-call data. Carbon dioxide (CO2); sulphur dioxide (SO2); nitrogen oxides (NOx); and black carbon (BC) emissions from near-port containership activities are estimated. Two emissions reduction policies are considered for typical container terminals. Participation of all calling vessels with a speed reduction scheme can lead to reductions of 8–20 per cent, 9–40 per cent and 9–17 per cent for CO2, SO2 and NOx, respectively. However, speed reduction policies may increase BC emissions by up to 10 per cent. Provision of Alternative Marine Power (AMP) for all berthing vessels can reduce in-port emissions by 48–70 per cent, 3–60 per cent, 40–60 per cent and 57–70 per cent for CO2, SO2, NOx and BC, respectively. The analysis shows that emissions depend on visiting fleet, berthing durations, baseline operating pattern of calling ships, sulphur reduction policies in force and the emissions intensity of electricity supply. The potential of emissions reduction policies varies considerably across ports making imperative the evaluation and prioritization of such policies based on the unique characteristics of each port and each vessel.
Different procedures for estimation of the extreme global wave hydroelastic responses in ships are discussed. Firstly, stochastic procedures for application in detailed numerical studies (CFD) are outlined. The use of the First Order Reliability Method (FORM) to generate critical wave episodes of short duration, less than 1 minute, with prescribed probability content is discussed for use in extreme response predictions including hydroelastic behaviour and slamming load events. The possibility of combining FORM results with Monte Carlo simulations is discussed for faster but still very accurate estimation of extreme responses. Secondly, stochastic procedures using measured time series of responses as input are considered. The Peak-over-Threshold procedure and the Weibull fitting are applied and discussed for the extreme value predictions including possible corrections for clustering effects.
This study concerns nitrogen based emissions from a hydrogen enriched ammonia fueled SI engine. These emissions deserve special attention as their formation may differ from conventional HC combustion due to the nitrogen content in the fuel. A range of experiments are conducted with a single cylinder 0.612 l CFR engine with a compression ratio varying from 7 to 15 using a fuel composition of 80 vol% NH3 and 20 vol% H2. Wet exhaust samples are analysed with an FT-IR. Emission measurements reveal that nitric oxide stem from other reaction paths than the dissociation of molecular nitrogen. This causes the NO emissions to peak around 35% rather than 10% excess air, as is typical in HC fueled SI-engines. However the magnitude of NO emissions are comparable to that of measurements conducted with gasoline due to lower flame temperatures. Nitrogen dioxide levels are higher when comparing with gasoline, but has a relatively low share of the total NOx emissions (3–4%). Nitrous oxide is a product of NH2 reacting with NO2 and NH reacting with NO. The magnitude is largely affected by ignition timing due to the temperature development during expansion and the amount of excess air, as increased oxygen availability stimulates the formation of the NH2 radical and the levels of NO2 are higher. Under ideal operating conditions (MBT ignition timing) N2O levels are very low. The dominating contributors to unburned ammonia are chamber crevices as the magnitude of these emissions is greatly affected by the compression ratio. However, levels are lower than required in order to eliminate all NOx emissions with a SCR catalyst.