Calculation of Wave Inputs Required When Predicting Shoreline Erosion Caused by Vessels Operating in Inland Waterways
- A. E. Jenkins (KTH Royal Institute of Technology) | K. Garme (KTH Royal Institute of Technology)
- Document ID
- International Society of Offshore and Polar Engineers
- The 28th International Ocean and Polar Engineering Conference, 10-15 June, Sapporo, Japan
- Publication Date
- Document Type
- Conference Paper
- 2018. International Society of Offshore and Polar Engineers
- modelling, shoreline erosion, wake wash, inland waterways
- 1 in the last 30 days
- 14 since 2007
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This paper is part of a research project titled Modelling wash -assessing fuel consumption and erosivity, which is financed by Trafikverket, Swedish Transport Administration. The project aims at developing a computational model to calculate the shoreline erosion caused by ships travelling in inland waterways. This paper covers a field study into possible linear methods which could be implemented to find the wave inputs required to predict shoreline erosion. Thin-ship theory was decided upon and implemented to calculate wave resistance and elevation. Results show the thin-ship model to be accurate for all tested ships between Froude numbers of 0.35-0.7. However, the model does under predict the wave resistance at Froude numbers below 0.35 for vessels with a transom stern.
There is currently a strong need for research into the shoreline erosion caused by inland waterway ships. Independent studies have been carried out by various organisations, which are discussed by working group PIANC, (Andreas, Linke and Zimmermann 2000; Kofoed-Hansen & Parnell, 2001; Parnell, Mcdonald and Burke, 2007). (Stumbo, Fox, Dvorak and Elliot, 1999; Glamore, 2008 and Macfarlane & Phil, 2012) have also made attempts to model the impact of ship waves on inland waterways, with results from Macfarlane & Phil (2012) proving to be promising within reasonable limits. A conclusion drawn across this research is that there is a need for more quantitative studies, with the key limitations being outlined by Gourlay (2011). The erosion process is affected by the waterway bank form, material properties, water level and salinity. These parameters are what make it difficult to quantitatively estimate the effect of vessel traffic on erosion. Continued waterway erosion can result in concerns for the quality of drinking water, loss of property and loss of aquatic habitat.
The purpose of this research project is to develop a computational model to calculate the risk of erosion caused by both ships in their initial design phase and existing ships operating in inland waterways. The model should be able to rank a variety of ships with respect to the risk of erosion that they could cause. When addressing this problem as a naval architect, the first step is to model the vessel's wave inputs required to calculate the erosion potential. According to (Gourlay, 2011 and Reynolds, 2003) the key wave inputs are the wave length, wave elevation and wave energy. The differences in nature between boat waves and wind waves make it difficult to derive an exact equation for sediment movement, however, both authors agree that in order to understand shoreline erosion from ships it is first important to calculate the total transmitted wave energy from the ship. It is this task of finding the wave energy and other required inputs that will be addressed in this paper. It is estimated that there are well over 1000 papers published on the study of ship waves. The research dates to the 19th century with scientists such as Green, Airy and Stokes discovering foundational concepts for surface waves and potential. Some of these concepts, along with work from Froude, Lord Kelvin and Lamb were then applied directly to the prediction of a ships wave prediction by Michell, (1898). Michell's thin-ship theory was recognized in 1923 by Havelock and Wigley, with both researchers investigating the theories applicability and advancing on the concepts. Additional linear potential methods were proposed over the 20th century, with the most well-known examples being Neuman-Kelvin theory, low speed theory, slender ship theory and linear panel methods from (Hess & Smith, 1962; Gadd, 1976; and Dawson, 1977).
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