TY  - CHAP
A1  - Chanson, Hubert
A1  - Bung, Daniel B.
A1  - Matos, J.
T1  - Stepped spillways and cascades
T2  - Energy dissipation in hydraulic structures / Hubert Chanson (ed.)
Y1  - 2015
SN  - 978-1-138-02755-8 (print) ; 978-1-315-68029-3 (e-Book)
SP  - 45
EP  - 64
PB  - CRC Press
CY  - Boca Raton, Fla. [u.a.]
ER  - 
TY  - JOUR
A1  - Kramer, Matthias
A1  - Valero, Daniel
A1  - Chanson, Hubert
A1  - Bung, Daniel B.
T1  - Towards reliable turbulence estimations with phase-detection probes: an adaptive window cross-correlation technique
JF  - Experiments in Fluids
Y1  - 2019
U6  - http://dx.doi.org/10.1007/s00348-018-2650-9
SN  - 1432-1114
VL  - 60
EP  - Article number 2
PB  - Springer
CY  - Berlin
ER  - 
TY  - JOUR
A1  - Valero, Daniel
A1  - Chanson, Hubert
A1  - Bung, Daniel B.
T1  - Robust estimators for turbulence properties assessment
Y1  - 2019
SP  - 1
EP  - 24
ER  - 
TY  - JOUR
A1  - Valero, Daniel
A1  - Chanson, Hubert
A1  - Bung, Daniel B.
T1  - Robust estimators for free surface turbulence characterization: A stepped spillway application
JF  - Flow Measurement and Instrumentation
N2  - Robust estimators are parameters insensitive to the presence of outliers. However, they presume the shape of the variables’ probability density function. This study exemplifies the sensitivity of turbulent quantities to the use of classic and robust estimators and the presence of outliers in turbulent flow depth time series. A wide range of turbulence quantities was analysed based upon a stepped spillway case study, using flow depths sampled with Acoustic Displacement Meters as the flow variable of interest. The studied parameters include: the expected free surface level, the expected fluctuation intensity, the depth skewness, the autocorrelation timescales, the vertical velocity fluctuation intensity, the perturbations celerity and the one-dimensional free surface turbulence spectrum. Three levels of filtering were utilised prior to applying classic and robust estimators, showing that comparable robustness can be obtained either using classic estimators together with an intermediate filtering technique or using robust estimators instead, without any filtering technique.
Y1  - 2020
U6  - http://dx.doi.org/10.1016/j.flowmeasinst.2020.101809
SN  - 0955-5986
VL  - 76
IS  - Art. 101809
PB  - Elsevier
CY  - Amsterdam
ER  - 
TY  - CHAP
A1  - Valero, Daniel
A1  - Kramer, Matthias
A1  - Bung, Daniel B.
A1  - Chanson, Hubert
T1  - A stochastic bubble generator for air-water flow research
T2  - E-proceedings of the 38th IAHR World Congress, September 1-6, 2019, Panama City, Panama
Y1  - 2019
U6  - http://dx.doi.org/10.3850/38WC092019-0909
SP  - 5714
EP  - 5721
ER  -