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Computational Hydraulics is a field in which numerical methods are used to solve hydraulics problems. This course offers an in depth exposure to the solutions of flow and transport phenomena in rivers, estuaries or networks of channels and pipes with predominantly free surface flow.
The main emphasis of the course is on understanding how the methods of finite differences and finite volumes are applied to solve unsteady free surface flow and transport equations. The course covers both historic and current practices in order to build up an understanding of Computational Hydraulics development.
During the week, theoretical and practical classes are carefully mixed to facilitate intake of new concepts and allow participants an active role in learning. Upon completion of the course, participants will understand the difficulties of developing a numerical model for the solution of free surface flow and transport equations. The course also provides basic training for people interested in further development of such models.
The course will provide delegates with the necessary skills to competently use computational hydraulics software to solve engineering problems:
Upon completion, delegates will have an understanding of the governing equations and numerical methods used for solution of flow and transport phenomena. They will:
Please note that our courses are reviewed regularly, both in response to feedback and so that information about recent research and developments can be included. Thus, content may be subject to change.
We offer a 30 percent discount to full time students and to Newcastle University staff.
The course fee includes tuition, course materials, lunch and refreshments.
Formal assessment may be available for this Course. Assessment attracts an additional fee of £285, and delegates will be issued with a transcript and Certificate of Credit Achieved. Owing to visa restrictions the assessment option is not available to international students outside the European Economic Area (EEA).
This course is also delivered as a Module (code CEG8517) on at least one of the School's Masters programmes, the majority of which can be studied part time, making them suitable for those in employment. Delegates will attend with full and part time registered students. The Academic Module Outline is available via the University's Module Catalogue.