TY  - CHAP
A1  - Valero, Daniel
A1  - Bung, Daniel B.
T1  - Interfacial velocity estimation in highly aerated stepped spillway flows with a single tip fibre optical probe and Artificial Neural Networks
T2  - 6th IAHR International Junior Researcher and Engineer Workshop on Hydraulic Structures, May 30th to June 1st 2016. Lübeck, Germany
N2  - Air-water flows can be found in different engineering applications: from nuclear engineering to huge hydraulic structures. In this paper, a single tip fibre optical probe has been used to record high frequency (over 1 MHz) phase functions at different locations of a stepped spillway. These phase functions have been related to the interfacial velocities by means of Artificial Neural Networks (ANN) and the measurements of a classical double tip conductivity probe. Special attention has been put to the input selection and the ANN dimensions. Finally, ANN have shown to be able to link the signal rising times and plateau shapes to the air-water interfacial velocity.
Y1  - 2016
U6  - http://dx.doi.org/10.15142/T3Q590
ER  - 
TY  - CHAP
A1  - Feldmann, M.
A1  - Döring, Bernd
A1  - Pyschny, D.
T1  - Floor systems; Sustainabilty analyses and assessments of steel bridges
T2  - Sustainable steel buildings : a practical guide for structures and envelopes
Y1  - 2016
SN  - 978-1-118-74079-8 (PDF)
SN  - 978-1-118-74111-5
SP  - 198
EP  - 223
PB  - Wiley Blackwell
CY  - Chichester, West Sussex
ER  - 
TY  - JOUR
A1  - Bung, Daniel B.
A1  - Valero, Daniel
T1  - Optical flow estimation in aerated flows
JF  - Journal of Hydraulic Research
N2  - Optical flow estimation is known from Computer Vision where it is used to determine obstacle movements through a sequence of images following an assumption of brightness conservation. This paper presents the first study on application of the optical flow method to aerated stepped spillway flows. For this purpose, the flow is captured with a high-speed camera and illuminated with a synchronized LED light source. The flow velocities, obtained using a basic Horn–Schunck method for estimation of the optical flow coupled with an image pyramid multi-resolution approach for image filtering, compare well with data from intrusive conductivity probe measurements. Application of the Horn–Schunck method yields densely populated flow field data sets with velocity information for every pixel. It is found that the image pyramid approach has the most significant effect on the accuracy compared to other image processing techniques. However, the final results show some dependency on the pixel intensity distribution, with better accuracy found for grey values between 100 and 150.
Y1  - 2016
U6  - http://dx.doi.org/10.1080/00221686.2016.1173600
VL  - 54
IS  - 5
SP  - 575
EP  - 580
PB  - Taylor & Francis
CY  - London
ER  -