In this study, the periodic train timetabling problem is formulated using a time-space graph formulation that exploits the properties of a symmetric timetable. Three solution methods are proposed and compared where solutions are built by what we define as a dive-and-cut-and-price procedure. An LP relaxed version of the problem with a subset of constraints is solved using column generation where each column corresponds to the train paths of a line. Violated constraints are added by separation and a heuristic process is applied to help to find integer solutions. The passenger travel time is computed based on a solution timetable and Benders’ optimality cuts are generated allowing the method to integrate the routing of the passengers. We propose two large neighborhood search methods where the solution is iteratively destroyed and repaired into a new one and one random iterative method. The problem is tested on the morning rush hour period of the Regional and InterCity train network of Zealand, Denmark. The solution approaches show robust performance in a variety of scenarios, being able to find good quality solutions in terms of travel time and path length relatively fast. The inclusion of the proposed Benders’ cuts provide stronger relaxations to the problem. In addition, the graph formulation covers different real-life constraints and has the potential to easily be extended to accommodate more constraints.
A conceptual design framework for collision and grounding analysis is proposed to evaluate the crashworthiness of double-hull structures. This work attempts to simplify the input parameters needed for the analysis, which can be considered as a step towards a design-oriented procedure against collision and grounding. Four typical collision and grounding scenarios are considered: (1) side structure struck by a bulbous bow, (2) side structure struck by a straight bow, (3) bottom raking, (4) bottom stranding. The analyses of these scenarios are based on statistical data of striking ship dimensions, velocities, collision angles and locations, as well as seabed shapes and sizes, grounding depth and location. The evaluation of the damage extent considers the 50- and 90-percentile values from the statistics of collision and grounding accidents. The external dynamics and internal mechanics are combined to analyse systematically the ship structural damage and energy absorption under accidental loadings.
In this paper, full-scale data for two ships have been used for the comparison of five different added resistance methods. The effect of using separate wave spectra for wind waves and swell on performance prediction has been explored. The importance of the peak enhancement factor(γ) in the JONSWAP spectrum for added resistance computation has been studied. Simulation model including calm water resistance, added resistance and wind resistance has been used. Ships have been simulated in the same weather conditions and propeller speed as in the case of full-scale ships using different methods for added resistance. The performance of these methods has been quantified by comparing speed and power predictions with the full-scale data. The paper also discusses the challenges involved in using full-scale data for such a comparison because of difficulty in isolating the effect of added resistance in full-scale data. It was observed that three out of five methods were able to predict added resistance even in high waveheights. Even though these methods showed significantly different RAOs, its effect on speed and power prediction was minor. Simulation results were not sensitive to the choice of peak enhancement factor(γ) in the JONSWAP spectrum. There was minor improvement in results by using separate wave spectra for wind waves and swell instead of single wave spectrum for combined wind waves and swell.
This study presents a novel approach to forecast freight rates in container shipping by integrating soft facts in the form of measures originating from surveys among practitioners asked about their sentiment, confidence or perception about present and future market development. As a base case, an autoregressive integrated moving average (ARIMA) model was used and compared the results with multivariate modelling frameworks that could integrate exogenous variables, that is, ARIMAX and Vector Autoregressive (VAR). We find that incorporating the Logistics Confidence Index (LCI) provided by Transport Intelligence into the ARIMAX model improves forecast performance greatly. Hence, a sampling of sentiments, perceptions and/or confidence from a panel of practitioners active in the maritime shipping market contributes to an improved predictive power, even when compared to models that integrate hard facts in the sense of factual data collected by official statistical sources. While investigating the Far East to Northern Europe trade route only, we believe that the proposed approach of integrating such judgements by practitioners can improve forecast performance for other trade routes and shipping markets, too, and probably allows detection of market changes and/or economic development notably earlier than factual data available at that time.
Increasing concerns related to fossil fuels have led to the introducing the concept of emission-free ships (EF-Ships) in marine industry. One of the well-known combinations of green energy resources in EF-Ships is the hybridization of fuel cells (FCs) with energy storage systems (ESSs) and cold-ironing (CI). Due to the high investment cost of FCs and ESSs, the aging factors of these resources should be considered in the energy management of EF-Ships. This article proposes a nonlinear model for optimal energy management of EF-Ships with hybrid FC/ESS/CI as energy resources considering the aging factors of the FCs and ESSs. Total operation costs and aging factors of FCs and ESSs are chosen as problem objectives. Moreover, a stochastic model predictive control method is adapted to the model to consider the uncertainties during the optimization horizon. The proposed model is applied to an actual case test system and the results are discussed.
This paper addresses the connection between added wave resistance and required propulsion power of ships, having focus on the early stage of new ship designs, notably tankers and bulk carriers. The paper investigates how mean added wave resistance affects the required torque of a fixed pitch propeller and thus also the operational conditions of a directly coupled main engine. The interest of the study has its background in the assessment of minimum propulsion power, and the study considers the prescriptive guidelines of the IMO as basis. Specifically, the study focuses on an assessment of the minimum forward speed attainable under consideration of the propeller light running margin and static load limits of engines in the early phase of new ship designs, where details of hull geometry are not available. The study considers three semi-empirical methods for predicting mean added wave resistance. All methods are known to be applied in the industry, emphasising that only methods relying solely on main particulars, together with information about sea state and advance speed, are of interest. The paper contains a case study used to illustrate the importance of the added wave resistance prediction with respect to the loading of the main engine. It is shown that, despite small absolute differences, the consequence in relation to the loading of the propeller and hereby the directly coupled main engine can be relatively large. Furthermore, the study illustrates that the propeller light running margin of a fixed pitch propeller directly coupled to the main engine has crucial influence on the attainable speed during adverse weather conditions.
This paper examines the statistical properties and the quality of the speed through water (STW) measurement based on data extracted from almost 200 container ships of Maersk Line’s fleet for 3 years of operation. The analysis uses high-frequency sensor data along with additional data sources derived from external providers. The interest of the study has its background in the accuracy of STW measurement as the most important parameter in the assessment of a ship’s performance analysis. The paper contains a thorough analysis of the measurements assumed to be related with the STW error, along with a descriptive decomposition of the main variables by sea region including sea state, vessel class, vessel IMO number and manufacturer of the speed-log installed in each ship. The paper suggests a semi-empirical method using a threshold to identify potential error in a ship’s STW measurement. The study revealed that the sea region is the most influential factor for the STW accuracy and that 26% of the ships of the dataset’s fleet warrant further investigation.
Ship air emissions are recognized as one of the key concerns of the maritime industry. Competent authorities have issued various regulations to manage air emissions from ships. Although the authorities are policy makers, the effectiveness of policies is up to the shipping industry who operates the vessels and terminals to fulfill maritime transportation works. Given this characteristic, bi-level optimization model has been widely adopted in studies that optimize policy design or evaluate its effectiveness. The framework of a typical bi-level optimization model for ship emission management problem is given to show the basic structure of similar issues. A series of applications of bi-level optimization model in managing ship emissions is reviewed, including cases of Energy Efficiency Design Index, Emissions Control Area, Market Based Measure, Carbon Intensity Indicator, and Vessel Speed Reduction Incentive Program. We hope this paper can enlighten scholars interested in this area and provide help for them.
This paper studies real-time deterministic prediction of wave-induced ship motions using the autocorrelation functions (ACFs) from short-time measurements, namely the instantaneous ACFs. The Prolate Spheroidal Wave Functions (PSWF) are introduced to correct the large lag time errors in the instantaneous sample ACF, together with a modification of the autocorrelation (AC) matrix for ensuring its positive definiteness. The validity of the PSWF-based ACFs is first examined by using the ship motion measurements from model experiment under stationary wave excitations. It is shown that the use of PSWF-based ACFs leads to better prediction accuracy than direct use of sample ACFs. The validation is then extended to ship motion prediction using in-service data from a container ship, and an improvement of the prediction accuracy by PSWF-based ACFs is again found. Finally, the effectiveness of use of the instantaneous ACFs for non-stationary wave-induced responses is highlighted by comparing with the prediction results based on the ACFs from long-time measurements.
This report is in the context of the DMA-DTU project on Market Based Measures (MBMs) The aim of this project is to provide an overview and discussion of potential Market Based Measures under the Initial IMO Strategy for the reduction of green house gas (GHG) emissions from ships. In this context, some related developments are also seen as directly relevant to the scope of the project, mainly in the context of the possible inclusion of shipping into the EU Emissions Trading System (ETS). In 2010 an Expert Group was appointed by the IMO’s Secretary General after solicitation of member states and was tasked to evaluate as many as eleven (11) separate MBM proposals, submitted by various member states and other organizations. All MBM proposals described programs and procedures that would target GHG reductions through either ‘in-sector’ emissions reductions from shipping, or ‘out-of-sector’ reductions via the collection of funds to be used for mitigation activities in other sectors that would contribute towards global reduction of GHG emissions.