A Direct Solution Approach to the Inverse Shallow-Water Problem
The study of open channel flow modelling often requires an accurate representation of the channel bed topography to accurately predict the flow hydrodynamics. Experimental techniques are the most widely used approaches to measure the bed topographic elevation of open channels. However, they are usua...
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| Published in | Mathematical Problems in Engineering Vol. 2012; no. 2012; pp. 684 - 701-240 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Cairo, Egypt
Hindawi Limiteds
01.01.2012
Hindawi Publishing Corporation John Wiley & Sons, Inc |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1024-123X 1026-7077 1563-5147 1563-5147 |
| DOI | 10.1155/2012/417950 |
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| Summary: | The study of open channel flow modelling often requires an accurate representation of the channel bed topography to accurately predict the flow hydrodynamics. Experimental techniques are the most widely used approaches to measure the bed topographic elevation of open channels. However, they are usually cost and time consuming. Free surface measurement is, on the other hand, relatively easy to obtain using airborne photographic techniques. We present in this work an easy to implement and fast to solve numerical technique to identify the underlying bedrock topography from given free surface elevation data in shallow open channel flows. The main underlying idea is to derive explicit partial differential equations which govern this inverse reconstruction problem. The technique described here is a “one-shot technique” in the sense that the solution of the partial differential equation provides the solution to the inverse problem directly. The idea is tested on a set of artificial data obtained by first solving the forward problem governed by the shallow-water equations. Numerical results show that the channel bed topographic elevation can be reconstructed with a level of accuracy less than 3%. The method is also shown to be robust when noise is present in the input data. |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 1024-123X 1026-7077 1563-5147 1563-5147 |
| DOI: | 10.1155/2012/417950 |