Inland shipping is widely acknowledged as a sustainable mode of transportation due to its low energy consumption and emissions in comparison to road and rail transport. However, with growing concerns around reducing emissions in the transportation sector, there is pressure to address environmental issues associated with inland shipping. In the Netherlands, a Green Deal has been formulated to outline the goals for reducing CO2 emissions by 2030 and other environmental pollutants by 2035 in inland navigation, to enable us to take the next step towards a climate-neutral society by 2050. This increasing pressure raises the question of how to get insight of the energy consumption and the associated emissions from inland shipping. To date, an accurate method is lacking that is able to estimate the total resistance, the propulsive power and in turn the energy consumption in shallow water and thus to quantify the CO2 emissions. Over the years, several power estimation methods have been developed for inland vessels, with the Rijkswaterstaat power estimation method being one of the most widely recognized. Recently, Backer van Ommeren (2019) investigated the Rijkswaterstaat power estimation method and found that certain assumptions and parameters used in the method were not well-founded, and that some approximations were unnecessary.
The main objective of this study to conduct a comprehensive literature analysis on Backer van Ommeren (2019) comments and recommendations regarding the Rijkswaterstaat (RWS) or Bolt (2003) method in order to clarify to what extent these recommendations will indeed improve the Bolt (2003) method or if an alternative power method should be proposed instead. This will be accomplished through a comparison process of the power results as a function of sailing speed, water depth, and channel dimensions for various types of inland vessels, utilizing the selected methods that will be derived from the literature study along with Backer van Ommeren (2019) recommendations applied to the original method. After coding these methods in Python and analyzing their results, the best practice(s) that will be derived from the test cases, will be implemented on two classes of motor vessels an M6 and an M8 to estimate the resistance and the power and then they will suggest to Rijkswaterstaat for potential future use.
To achieve the main research objectives, the following research was conducted. Initially, a literature analysis on the available resistance methods, how they consider and divide the several resistance components, and which are the shallow water effects that affect them, was done in order to evaluate their performance in terms of power estimations. Secondly, the comments made by Backer van Ommeren were presented and analyzed. Specifically, he investigated various formulations for calculating the return flow, water level depression, and characterizing the waterway as normal, narrow, wide, or very wide. This study was accomplished through the use of specific power efficiency and resistance coefficients. Based on his study, he derived a method, the Backer method (Backer van Ommeren, 2019) and suggested a number of formulas to be further tested. After completing the literature review, the findings lead to the selection of the power methods that will be treated in this thesis and the kind of improvements that will be applied to the original Bolt (2003) method.
Subsequently, from the literature study and Backer van Ommeren (2019) review, four methods were derived to be simulated and tested in this thesis. These methods include the TU Delft method, Bolt method with speed correction, Bolt method modified by Backer, and Backer method. The simulation was achieved with two rounds of tests that are conducted, firstly the “Academic test case” and secondly the “Real-world test case”. In the “Academic test case” five methods were simulated and the most promising that met specific criteria are selected. Then, in the “Real-world test case” the selected methods as they were derived from the “Academic test case”, were further evaluated for the selection of the best practice(s). The first round of tests is applied to two classes of motor vessels in narrow and wide waterways with shallow, intermediate and deep water depth conditions and the results include the total resistance and the brake power while the second round simulates only one motor vessel of class six in wide waterways for the same depth conditions as previously and the outcome includes the delivered power. The “Real-world test case” is divided in two parts. The first part includes the comparison between the estimated and the measured delivered power in order to assess the performance of the methods with the real data. The second part evaluates the performance of the methods in the presence of a current flow, by comparing the fuel consumption in upstream, downstream and round trips.
The evaluation of the methods in a real-world test case led to a number of conclusions, and the best practices were recommended accordingly. It should be noted that the comparison process was based solely on a single real-world case, utilizing a singular set of real data. It is important to be conducted additional comparisons across multiple real cases in order to increase the understanding of the accuracy of the various methods being compared. In the context of power estimation in shallow water, both the Bolt (2003) method and TU Delft method(Jiang, Baart & van Koningsveld, 2022) have demonstrated remarkable accuracy in their predictions while Backer method and Bolt method modified by Backer are not recommended for power predictions. Notably, Bolt (2003) method has proven to be effective in estimating power within a speed range of 2.5m/s to 3.5m/s while TU Delft method (Jiang, Baart & van Koningsveld, 2022) showed accurate predictions within a speed range of 2.5m/s-4m/s (accurate as defined within 20% of the observed value). Regarding the intermediate and deep water conditions, only TU Delft method (Jiang, Baart & van Koningsveld, 2022) showed acceptable performance in power estimation again for sailing speeds varying 2.5 m/s – 5 m/s. The power demand at very low speeds for all the three methods display a considerable deviation between the estimated power output and the actual values, surpassing the acceptable rate of 20%. This can be attributed to two reasons. At low speeds, the interaction between a sailing vessel and the boundary layer becomes more pronounced, causing the ship to experience turbulent effects that dominate the boundary layer more intensively. As a result, the vessel experiences increased resistance, requiring more power. Secondly, in actual operating conditions, a ship has a minimum power engine setting that is dependent on the engine characteristics. So, when the ship is moored and the "hotel mode" is on, as the ship not having a separate auxiliary power unit, a propeller brake is used to allow the turbine to continue running and generate power without the propeller spinning. This effect does not consider by the power estimation methods that rely on parameters such as sailing speed and water depth. The Backer (2019) method demonstrated satisfactory performance in predicting resistance and power for both types of motor cargo vessels within narrow waterways. This method effectively accounted for the variations in depth by accurately estimating lower resistance and power demand as the depth increased. However, Its accuracy in wide waterways diminished due to the equations' unsuitability for such conditions, by generating nearly identical resistance and power estimations for the three different water depths. Based on the aforementioned restriction, it is not recommended to employ this particular approach for subsequent power estimations. As regards the Bolt method modified by Backer performs poorly in estimating resistance and power across narrow and wide waterways with varying depths. It consistently yields similar results for shallow, intermediate, and deep depths at a specific sailing speed. Therefore, it is not recommended as an improvement to the Bolt method. In the presence of current flow, three methods have shown promising results. Specifically, the TU Delft method (Jiang, Baart & van Koningsveld, 2022) is recommended for motor vessel, as it produces deviations from real measurements of 0.93% for upstream, 1.36% for downstream, and 0.45% for round trips. Also, TU Delft method (Jiang, Baart & van Koningsveld, 2022) is recommended in case of pushed and coupled convoys as it has been found to produce the smallest deviations in upstream sailing, with a maximum of 3.9% while the deviations observed for downstream sailing and round trips are around 1.9%. Bolt (2003 )method and Bolt method with speed correction, were found to produce acceptable deviation rates of around 7% for upstream trips, with the benefit that these methods require less detailed input data. Nevertheless, for downstream and round trips, the deviations were much higher, reaching up to 80% and 30%, respectively and event that requires additional investigation and validation.