Simulating Fish Motion through a Diagonal Reversible Turbine

Abstract

Utilization of unharnessed hydro-power necessitates designing fish-friendly hydraulic machinery. Towards this effort, the present work investigates various methods for tracking fish motion, ranging from particle tracking methods to accurate, but computationally expensive, body tracking methods, such as immersed boundaries and overset meshes. Moreover, a novel uncoupled 6-Degree of Freedom tracking technique is proposed, based on an approximated pressure field around the tracked body of interest, using steady-state flow field data, and including collision detection to walls. The proposed method shows promising results in terms of accuracy, being comparable to the more computationally expensive fully coupled methods at a tiny fraction of the execution time. The new method reveals location of fish–blade impact, as well as statistics of forces, pressure and flow shear that a passing fish is subjected to, both in the normal and reverse operation of the turbine. The low computational cost of the proposed method renders it attractive for optimization studies.

State of the Art in Designing Fish-Friendly Turbines: Concepts and Performance Indicators

“…The major underlying assumption is that the body mass of the tracked object is insignificant compared to the flow momentum; hence, it does not significantly alter the flow field. Numerical experiments have shown that this assumption seems valid when considering fish sizes with characteristic dimensions at most 50 times smaller than a turbine (see [105,108]); indeed, the predicted trajectory with the uncoupled fast tracking is very similar to the fully coupled 6-DoF either with immersed boundaries [105] or overset meshes [108], in the case of axial and diagonal (Deriaz)-type turbines. A recent variant [108] to the more computationally expensive 6-DoF techniques decouples the flow field from the body tracking.…”

“…Numerical experiments have shown that this assumption seems valid when considering fish sizes with characteristic dimensions at most 50 times smaller than a turbine (see [105,108]); indeed, the predicted trajectory with the uncoupled fast tracking is very similar to the fully coupled 6-DoF either with immersed boundaries [105] or overset meshes [108], in the case of axial and diagonal (Deriaz)-type turbines. A recent variant [108] to the more computationally expensive 6-DoF techniques decouples the flow field from the body tracking. This decoupling makes it possible to solve the flow field with steady-state moving reference frames, which greatly speeds up the solution by roughly two orders of magnitude, allowing for the derivation of statistics (see indicatively Figure 10, where a specifically designed reversible, fish-friendly Deriaz turbine [109] was tested).…”

“…Recently, the lattice Boltzmann method with immersed boundaries was employed for tracking fish motion through axial turbines [107]; the reported computational cost was in the order of 500-800 h for 1-3 simulated fish. In the author's experience [105] (see also, e.g., Figure 9), immersed boundary techniques can be efficiently applied for bodies roughly 50 times smaller than the turbine; beyond that point, the computational cost becomes prohibitive, unless adaptive refinement is used around the tracked object. The immersed boundary method (IBM) is a technique of mapping solid geometry on a background mesh [106]; this can be achieved either by altering the flow equations, e.g., through the introduction of appropriate source terms in the momentum equation, or by actually altering the computational mesh through cell-cutting to conform to the body shape.…”

“…Recently, the lattice Boltzmann method with immersed boundaries was employed for tracking fish motion through axial turbines [107]; the reported computational cost was in the order of 500-800 h for 1-3 simulated fish. In the author's experience [105] (see also, e.g., Figure 9), immersed boundary techniques can be efficiently applied for bodies roughly 50 times smaller than the turbine; beyond that point, the computational cost becomes prohibitive, unless adaptive refinement is used around the tracked object. A recent variant [108] to the more computationally expensive 6-DoF techniques decouples the flow field from the body tracking.…”

“…In the author's experience [105] (see also, e.g., Figure 9), immersed boundary techniques can be efficiently applied for bodies roughly 50 times smaller than the turbine; beyond that point, the computational cost becomes prohibitive, unless adaptive refinement is used around the tracked object. A recent variant [108] to the more computationally expensive 6-DoF techniques decouples the flow field from the body tracking. This decoupling makes it possible to solve the flow field with steady-state moving reference frames, which greatly speeds up the solution by roughly two orders of magnitude, allowing for the derivation of statistics (see indicatively Figure 10, where a specifically designed reversible, fish-friendly Deriaz turbine [109] was tested).…”