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Modeling fish passage and energy exp...
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Plymesser, Kathryn Elizabeth.
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Modeling fish passage and energy expenditure for American shad in a steeppass fishway using a computational fluid dynamics model.
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Modeling fish passage and energy expenditure for American shad in a steeppass fishway using a computational fluid dynamics model./
Author:
Plymesser, Kathryn Elizabeth.
Description:
178 p.
Notes:
Source: Dissertation Abstracts International, Volume: 75-07(E), Section: B.
Contained By:
Dissertation Abstracts International75-07B(E).
Subject:
Engineering, Civil. -
Online resource:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3615487
ISBN:
9781303815010
Modeling fish passage and energy expenditure for American shad in a steeppass fishway using a computational fluid dynamics model.
Plymesser, Kathryn Elizabeth.
Modeling fish passage and energy expenditure for American shad in a steeppass fishway using a computational fluid dynamics model.
- 178 p.
Source: Dissertation Abstracts International, Volume: 75-07(E), Section: B.
Thesis (Ph.D.)--Montana State University, 2014.
The Alaska steeppass is a fishway used extensively in the eastern U.S. and in remote locations. The baffles in the steeppass fishway tend to reduce water velocity to magnitudes negotiable by many species. A computational fluid dynamics (CFD) model was developed for common combinations of fishway slope and head pond elevation. Three-dimensional hydraulics information from the CFD model was used as a basis to predict passage success for American shad in the steeppass. The passage model considered six unique algorithms for swim path during ascent, and both the optimal swim speed approach of Castro-Santos (2005) and newly developed swim-speed information based on the laboratory study of Haro, Odeh, Castro-Santos, and Noreika (1999). The passage model was incorporated into a Monte Carlo framework to facilitate robust comparisons between the passage success predicted by the model and the experimental observations of Haro, Odeh, Castro-Santos, and Noreika (1999). The methods of Webb (1975) and Belke (1991) were then adapted to develop predictions of the energy expenditure of American shad. Findings included the observation that fish in the laboratory study did not tend to utilize the distance-optimizing prolonged swim speed of Castro-Santos (2005), but instead travelled at a faster velocity (more similar to the distance-optimizing burst speed) that resulted in significantly lower energy expenditures. The passage model did not indicate that the steeppass fishway presented a substantial velocity challenge to American shad. Comparisons of the passage model results with passage success in the study by Haro, Odeh, Castro-Santos, and Noreika (1999) led to the observation that other hydraulic factors (such as turbulence) or volitional issues should be the subject of further studies. The passage model was reformulated, creating a conceptual fishway of infinite length, to examine the distance at which model fish fail due to fatigue. The infinite-length model predicted that a fishway of 25 feet in length passed 99.0% of fish without fatigue failure. The velocity distributions from the CFD models also suggested that the zones of low velocity that existed near the bottom of the fishway under high head conditions may be desirable for successful ascent.
ISBN: 9781303815010Subjects--Topical Terms:
783781
Engineering, Civil.
Modeling fish passage and energy expenditure for American shad in a steeppass fishway using a computational fluid dynamics model.
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Modeling fish passage and energy expenditure for American shad in a steeppass fishway using a computational fluid dynamics model.
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Source: Dissertation Abstracts International, Volume: 75-07(E), Section: B.
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The Alaska steeppass is a fishway used extensively in the eastern U.S. and in remote locations. The baffles in the steeppass fishway tend to reduce water velocity to magnitudes negotiable by many species. A computational fluid dynamics (CFD) model was developed for common combinations of fishway slope and head pond elevation. Three-dimensional hydraulics information from the CFD model was used as a basis to predict passage success for American shad in the steeppass. The passage model considered six unique algorithms for swim path during ascent, and both the optimal swim speed approach of Castro-Santos (2005) and newly developed swim-speed information based on the laboratory study of Haro, Odeh, Castro-Santos, and Noreika (1999). The passage model was incorporated into a Monte Carlo framework to facilitate robust comparisons between the passage success predicted by the model and the experimental observations of Haro, Odeh, Castro-Santos, and Noreika (1999). The methods of Webb (1975) and Belke (1991) were then adapted to develop predictions of the energy expenditure of American shad. Findings included the observation that fish in the laboratory study did not tend to utilize the distance-optimizing prolonged swim speed of Castro-Santos (2005), but instead travelled at a faster velocity (more similar to the distance-optimizing burst speed) that resulted in significantly lower energy expenditures. The passage model did not indicate that the steeppass fishway presented a substantial velocity challenge to American shad. Comparisons of the passage model results with passage success in the study by Haro, Odeh, Castro-Santos, and Noreika (1999) led to the observation that other hydraulic factors (such as turbulence) or volitional issues should be the subject of further studies. The passage model was reformulated, creating a conceptual fishway of infinite length, to examine the distance at which model fish fail due to fatigue. The infinite-length model predicted that a fishway of 25 feet in length passed 99.0% of fish without fatigue failure. The velocity distributions from the CFD models also suggested that the zones of low velocity that existed near the bottom of the fishway under high head conditions may be desirable for successful ascent.
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http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3615487
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