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Chapter 2 - State of the art
2.6 Measurement technique and data treatment
The present section is not exhaustive. It presents a small selection of articles concerning different
measurement techniques and data treatments.
a) Bed level measurement
SMART (1999) studied velocity profiles and the bed friction in gravel bed rivers. He proposed to
define the water depth based on the analysis of a logarithmic velocity profile. This can be particularely
useful with mobile beds if the channel ground cannot be clearly determined.
YANKIELUN & ZABILANSKY (2000) developed a measurement device to dynamically record the
evolution of scour in site and in the laboratory. The device is based on the propagation time of a
frequency modulated signal (as used in radar applications, but directional) captured by burried
sensors.
b) Sediment sampling
SIBANDA ET.AL. (2000) presented a new sampling technique for determination of the composition
of the surface and subsurface of a sediment bedformed during flume experiments. This technique
called wax coring was used in two flume experiments and showed good results but at a considerable
effort compared to the sampling technique that will be used in the present study (see
4.4.6 e) on page 90)
c) Velocity measurement technique
ROLLAND (1995) (see also LEMMIN & ROLLAND, 1997 and ROLLAND & LEMMIN, 1997) developed
an ultrasonic velocity profiler based on the Doppler effect. The instrument allows the simultaneous
measurement of the velocity fluctuations in 3 directions. His study gives a detailed
overview of the governing equations and the measurement technique. 1
d) Dimensional analysis
The similitude and approximation theory of KLINE (1965) presents the basics of dimensional analysis.
Furthermore he regrouped and extended works of various authors to establish his approximation
theory. Based on considerations of the main influences on a physical process, the resulting
forces are combined with each other to obtain physically correct dimensionless parameters.
e) Genetic algorithm
KEIJZER & BABOVIC (1999) developed a genetic algorithm allowing to search for functions fitting
to a given data sets. The big advantage of this genetic algorithm is a dimensionally aware treatment
of the data allowing to facilitate physical interpretation of the results and enhance the search efficiency.
RODRIGUEZ AGUILERA (2000) gave an overview of the program using this genetic algorithm.
Applications in hydraulic engineering were documented by BABOVIC ET AL. (2001).
1. The used velocity-measurement device is documented in § 4.4.4 and in METFLOW (2000).
page 18 / November 9, 2002
Wall roughness effects on flow and scouring