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- no (34)
A comparative performance analysis of the CFD platforms OpenFOAM and FLOW-3D is presented, focusing on a 3D swirling turbulent flow: a steady hydraulic jump at low Reynolds number. Turbulence is treated using RANS approach RNG k-ε. A Volume Of Fluid (VOF) method is used to track the air–water interface, consequently aeration is modeled using an Eulerian–Eulerian approach. Structured meshes of cubic elements are used to discretize the channel geometry. The numerical model accuracy is assessed comparing representative hydraulic jump variables (sequent depth ratio, roller length, mean velocity profiles, velocity decay or free surface profile) to experimental data. The model results are also compared to previous studies to broaden the result validation. Both codes reproduced the phenomenon under study concurring with experimental data, although special care must be taken when swirling flows occur. Both models can be used to reproduce the hydraulic performance of energy dissipation structures at low Reynolds numbers.
Application of the optical flow method to velocity determination in hydraulic structure models
(2016)
As with most high-velocity free-surface flows, stepped spillway flows become self-aerated when the drop height exceeds a critical value. Due to the step-induced macro-roughness, the flow field becomes more turbulent than on a similar smooth-invert chute. For this reason, cascades are oftentimes used as re-aeration structures in wastewater treatment. However, for stepped spillways as flood release structures downstream of deoxygenated reservoirs, gas transfer is also of crucial significance to meet ecological requirements. Prediction of mass transfer velocities becomes challenging, as the flow regime differs from typical previously studied flow conditions. In this paper, detailed air-water flow measurements are conducted on stepped spillway models with different geometry, with the aim to estimate the specific air-water interface. Re-aeration performances are determined by applying the absorption method. In contrast to earlier studies, the aerated water body is considered a continuous mixture up to a level where 75% air concentration is reached. Above this level, a homogenous surface wave field is considered, which is found to significantly affect the total air-water interface available for mass transfer. Geometrical characteristics of these surface waves are obtained from high-speed camera investigations. The results show that both the mean air concentration and the mean flow velocity have influence on the mass transfer. Finally, an empirical relationship for the mass transfer on stepped spillway models is proposed.
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.
Self-aeration is traditionally explained by the water turbulent boundary layer outer edge intersection with the free surface. This paper presents a discussion on the commonly accepted hypothesis behind the computation of the critical point of self-aeration in spillway flows and a new formulation is proposed based on the existence of a developing air flow over the free surface. Upstream of the inception point of self-aeration, some surface roughening has been often reported in previous studies which consequently implies some entrapped air transport and air–water flows coupling. Such air flow is proven in this study by presenting measured air velocities and computing the air boundary layer thickness for a 1V:2H smooth chute flow. Additionally, the growth rate of free surface waves has been analysed by means of Ultrasonic Sensors measurements, obtaining also the entrapped air concentration. High-speed camera imaging has been used for qualitative study of the flow perturbations.
A new formulation for the prediction of free surface dynamics related to the turbulence occurring nearby is proposed. This formulation, altogether with a breakup criterion, can be used to compute the inception of self-aeration in high velocity flows like those occurring in hydraulic structures. Assuming a simple perturbation geometry, a kinematic and a non-linear momentum-based dynamic equation are formulated and forces acting on a control volume are approximated. Limiting steepness is proposed as an adequate breakup criterion. Role of the velocity fluctuations normal to the free surface is shown to be the main turbulence quantity related to self-aeration and the role of the scales contained in the turbulence spectrum are depicted. Surface tension force is integrated accounting for large displacements by using differential geometry for the curvature estimation. Gravity and pressure effects are also contemplated in the proposed formulation. The obtained equations can be numerically integrated for each wavelength, hence resulting in different growth rates and allowing computation of the free surface roughness wavelength distribution. Application to a prototype scale spillway (at the Aviemore dam) revealed that most unstable wavelength was close to the Taylor lengthscale. Amplitude distributions have been also obtained observing different scaling for perturbations stabilized by gravity or surface tension. The proposed theoretical framework represents a new conceptualization of self-aeration which explains the characteristic rough surface at the non-aerated region as well as other previous experimental observations which remained unresolved for several decades.
Vectrino profiler spatial filtering for shear flows based on the mean velocity gradient equation
(2018)
A new methodology is proposed to spatially filter acoustic Doppler velocimetry data from a Vectrino profiler based on the differential mean velocity equation. Lower and upper bounds are formulated in terms of physically based flow constraints. Practical implementation is discussed, and its application is tested against data gathered from an open-channel flow over a stepped macroroughness surface. The method has proven to detect outliers occurring all over the distance range sampled by the Vectrino profiler and has shown to remain applicable out of the region of validity of the velocity gradient equation. Finally, a statistical analysis suggests that physically obtained bounds are asymptotically representative.
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.