A FLOW-BASED METHOD FOR STRIKE SURVIVAL MODELING
Computational fluid dynamics (CFD) models offer a useful approach for assessing the biological performance of a turbine if the mechanisms of injury are modeled accurately. and could be used as a design tool in the development of fish-safe designs. A novel strike intensity metric (HIT metric) derived from spherical discrete element model (DEM) particle trajectory data is correlated to observed survival outcomes in the laboratory for rainbow trout struck by a variety of blade geometries. and the model enables improved survival predictions. The modeling method also allows survival prediction for strikes with arbitrary geometries and is extensible to apply to a wide range of organisms. The CFD simulated organism can comprise a single DEM particle or a cluster of DEM particles. The simulation of organism-flowfield interaction can include both passive advection and contact dynamics.
1 . A method of modeling strike survival rate of an organism, the method comprising:
striking an organism with an object under different strike conditions;
recording a strike survival rate of the organism under each of the strike conditions;
performing a regression analysis on the recorded strike survival rates to result in a relationship between strike survival rate and strike intensity metric;
simulating the organism, the object, and the strike conditions in a computational fluid dynamic model;
calculating a strike intensity metric experienced by the simulated organism under each of the simulated strike conditions; and
estimating strike survival rates of the simulated organism under the simulated strike conditions based on the relationship between strike survival rate and strike intensity metric.
2 . The method of claim 1 , wherein the strike conditions comprise:
a strike velocity;
a geometry of the object; and
a geometry of the organism.
3 . The method of claim 2 , wherein the organism is fish, and wherein the geometry of the organism comprises a length of the fish.
4 . The method of claim 3 , wherein the length of fish is in a range of 100 mm to 600 mm.
5 . The method of claim 2 , wherein the object is a hydropower turbine blade, and wherein the geometry of the object comprises a thickness of the blade and a leading edge slant angle of the blade.
6 . The method of claim 5 , wherein the leading edge slant angle is in a range of 30 degrees to 90 degrees.
7 . The method of claim 6 , wherein the thickness of the blade is in a range of 10 mm to 250 mm.
8 . The method of claim 2 , wherein the strike velocity is in a range of 3.0 m/s to 25 m/s.
9 . The method of claim 1 , wherein the calculating strike intensity metric comprises:
determining the moment of strike, where the simulated organism contacts the simulated object;
determining components of a pre-strike velocity of the simulated organism at a first distance before the moment of strike;
determining components of a post-strike velocity of the simulated organism at a second distance after the moment of strike; and
calculating the strike intensity metric as the magnitude of components of a change in the pre-strike velocity and the post-strike velocity.
10 . The method of claim 9 , wherein the first distance and the second distance are equal.
11 . The method of claim 9 , wherein the organism is a rainbow trout having a length, and wherein the first distance and the second distance are both in a range of 0.04 times to 0.06 times of the length of the rainbow trout.
12 . The method of claim 1 , wherein the step of simulating comprises simulating the organism as spherical discrete element method (DEM) particles.
13 . The method of claim 1 , wherein the step of simulating comprises simulating the organism as non-spherical discrete element method (DEM) particles.
14 . The method of claim 1 , wherein the step of simulating comprises simulating the organism as clusters of discrete element method (DEM) particles.
15 . The method of claim 1 , wherein the regression analysis is a log-logistic regression analysis.