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CONTINUUM FLUID DYNAMICS
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Objective:
To derive the various forms of differential and integral equations
most commonly encountered in hydroinformatics.
Syllabus:
A) Basic concepts and physical characteristics of fluids: continuum,
density, specific volume, weight and gravity, pressure and shear force,
viscosity, compressibility of fluids and gases, rotation, vorticity,
mass, momentum and energy fluxes.
B) Introduction to thermodynamics: first and second laws of
thermodynamics, reversible and irreversible processes.
C) Continuous forms of conservation laws: mass, momentum and
energy conservation, differential forms and their equivalence for
reversible processes, vector and tensor notation, Cauchy's differential
equation.
D) Various forms of equations - derivations and equivalences:
Navier-Stokes equations, Euler equations, Bernoulli equation, Reynolds
equations, characteristic forms, algorithmic forms, divergence forms,
de Saint Venant equations.
E) Weak forms of conservation laws: fronts, hydraulic jumps
and their energy losses, non-equivalence of momentum and energy formulations
at discontinuities.
F) Energy and momentum diffusing terms. Introduction to 2-D
flows. |
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NUMERICAL METHODS
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Objective:
To introduce some methods for solving and analysing differential equations.
Syllabus:
A) Introduction: solving differential equations, derivatives
and finite differences.
B) Ordinary differential equations: initial value problems,
accuracy, stability, treatment of non-linearities
C) First order, partial differential equations: finite difference
formulations, Taylor's series expansion, Fourier analysis, amplitude
and phase portraits, explicit and implicit formulations, initial and
boundary data, solution algorithms.
D) Second order, partial differential equations: schemes and
algorithms for parabolic, hyperbolic and elliptic systems, double
sweep algorithm. |
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FREE SURFACE FLOW MODELLING
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Objective:
To obtain experience in the development, construction and testing
of an actual mathematical model.
Syllabus:
A) Problem description: governing equations, simplifications.
B) Discretisation: finite difference scheme, finite difference
approximations.
C) Initial and boundary conditions: required data, discretisation.
D) Solution algorithm: double sweep algorithm, recurrence relations,
boundary conditions.
E) Programming: writing, inputting and debugging the computer
program.
F) Testing: static test, steady-state test, seiche test, discussion
of tests.
G) Reporting: presentation of results, comments about accuracy
and quality of the model. |
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1D MODELLING
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Objective:
To obtain experience in recognising and solving some common problems
encountered when using advanced 1D modelling systems
Syllabus:
A set of input files for the Mike-11 modelling system have been prepared.
These files represent very simple hydraulic situations, however, the
examples may have unexpected or unrealistic results. The aim of the
exercise is to determine the source of the errors and to offer solutions
for the various situations. |
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2D MODELLING
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Objective:
To obtain experience in the use of advanced 2D modelling systems
Syllabus:
The Mike-21 modelling system is used to model and solve real-world
coastal engineering problems. |
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ENVIRONMENTAL HYDRAULICS AND MODELLING
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Objective:
To introduce concepts of mathematical modelling when applied to problems
of environmental engineering and water quality.
Syllabus:
A) basic hydraulics; properties of water; Froude number; sub-
and supercritical flows; steady and non-steady flows.
B) mass and momentum conservation laws; Euler equations; velocity
distribution; roughness; conveyance.
C) de Saint Venant equations; backwater curve computation; Euler
and Improved Euler method; Cauchy equation.
D) growth and decay models; reservoir routing; water quality
modelling.
E) pure advection processes; advection equation; finite-difference
approximations; consistency, accuracy and stability; numerical and
real diffusion. |
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ARTIFICIAL NEURAL NETWORKS
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Objective:
To introduce artificial neural networks as a technique for the application
to the modelling and management of water
Syllabus:
A) The impact of modern information technology (IT) upon numerical
modelling techniques. The use of artificial intelligence techniques.
B) Symbolic and sub-symbolic paradigms. Emergence. Data mining. A
comparison with traditional techniques.
C) Introduction to artificial neural networks (ANNs). Perceptrons
and linear classifiers.
D) Mulit-layer networks. Supervised learning. Generalised delat rule.
E) Some other common types of ANN; radial basis function networks,
Hopfield networks, Kohonen networks, auto-regressive ANN
F) Examples from research and practice. |
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ECOHYDRAULICS
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| Syllabus under development
General:
The Eco-hydraulics approach to river management is multi-objective,
balancing the beneficial uses for power generation, water supply
and agriculture with the protection and enhancement of the riverine
habitat, water quality, recreational use and aesthetics. These restoration
and enhancement approaches place an emphasis on allowing the physical
processes to drive the ecological healing by natural evolution,
rather than an instantaneous engineering fix. Implementing this
restoration philosophy, developing management plans, simulating
the hydrological or ecological responses and untangling the complexities
of aquatic systems require an interdisciplinary approach, which
crosses the boundaries of traditional science and engineering programmes.
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