Theses and Dissertations at Montana State University (MSU)
Permanent URI for this collectionhttps://scholarworks.montana.edu/handle/1/733
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Item Piping and related problems at large culvert installations in Montana(Montana State University - Bozeman, College of Engineering, 1966) Funk, Harvey DavidItem Rating system for rural culvert crossing repair and maintenance(Montana State University - Bozeman, College of Engineering, 2001) Baker, Daniel W.Item Behavior of the reconstructed Wolf Creek culvert(Montana State University - Bozeman, College of Engineering, 1967) Willett, Gerald AnsonItem Sensitivity of 1-D hydraulic models of fish passage in culverts to descriptions of fish swimming performance(Montana State University - Bozeman, College of Engineering, 2009) Nixon, Kyle Marshall; Chairperson, Graduate Committee: Joel CahoonOne way culverts become barriers to the upstream movement of fish is by creating excessive velocities exceeding a fish's swimming ability. FishXing, a common tool for indirectly assessing fish passage, uses fish swimming ability information with one-dimensional culvert hydraulics to predict barrier status of culverts. However, since fish swimming ability data is scarce for many fish species, predictions of a culvert's barrier status can be inaccurate and overly conservative, possibly leading to misclassification or uneconomical design. Additional fish swimming ability research is necessary to strengthen these models. The primary goal of this study was to determine the effects of different swimming ability algorithms on velocity barrier flow rates predicted by one-dimensional culvert hydraulics models. A one-dimensional culvert hydraulics model was created in Visual Basic. This model was designed to mimic FishXing's fish swimming algorithm, or use more complex fish swimming algorithms. Three diverse test culverts were selected to show how varying culvert properties (length, geometry, flow regime, and embedment) influences which fish swimming ability algorithm most affects the predicted velocity barrier flow rate. A "test fish" was designed based upon fish swimming ability literature. Each culvert was subjected to six tests, each testing the sensitivity of a particular fish swimming algorithm. This study determined that for different types of culverts, different components of fish swimming ability algorithms substantially affect the velocity barrier flow rate. The study needed only three test culverts to show that accurate quantification of the fish species' burst speed, burst duration, the burst speed/duration relationship, prolonged swimming speed, and constant deceleration time from burst to prolonged speed is necessary to model diverse fish passage situations. This study also showed that if a fish has a substantial deceleration time, a constant deceleration is probably sufficient to model it. In the future, if programs like FishXing adapt to include deceleration in fish swimming models, constant deceleration is an adequate addition. With this analysis, fish swimming ability variables substantially affecting fish passage were determined. The study can be used to guide further research so swimming ability studies can gather swimming data that is most crucial to predicting fish passage.Item Empirical velocity predictions at culvert inlets(Montana State University - Bozeman, College of Engineering, 2006) Patton, Jesse Earl; Chairperson, Graduate Committee: Joel CahoonThe velocity distribution at the entrance cross section of a culvert is typically diverse, reflecting the nuances of the bed material, debris and other hydraulic factors just upstream of the culvert. These diverse inlet velocity fields have been observed to perpetuate some distance into the culvert, impacting the ability of fish to travel upstream in the culvert barrel. It is important to be able to quantitatively describe the inlet velocity field, especially as this serves as a necessary boundary condition for three-dimensional modeling of fluid flow in culverts. While there are various theory-based models of velocity distributions in open channels, velocity distributions at culvert inlets tend to be chaotic and are not well represented by analytic methods. The goal of this project was to use field data collected at existing culverts to estimate the density at which velocity observations should be collected to adequately describe the nature of the velocity at the culvert inlet. Two methods of data analysis were utilized to determine the required density of velocity observations. The first approach randomly selected velocities to be used as predictors and did not stress the location of the predictors, but instead emphasized the number of velocity observations needed to describe the nature of the velocity at the culvert inlet. The second method employed the idea that the location of the predictors was more important than quantity of predictors used. Results indicate that the pattern of velocity measurements is important - that is, velocities should not be measured at randomly selected positions in the cross section, but should follow a geometric pattern where the measurement density increases in zones having larger velocities. Also, it appears that if one follows the rigorous implementation of the USGS method for measuring stream flow (often referred to as the velocity-area method in texts), velocity predictions can be extrapolated using the inverse-distance-squared technique to adequately describe the inlet velocity field. The implication of this research is that there are steps that can be followed to adequately describe the nature of the velocity at culvert inlet even through the velocity distributions are chaotic in these regions.Item Advanced Studies of fish passage through culverts : 1-D and 3-D hydraulic modeling of velocity, fish energy expenditure, and a new barrier assessment method(Montana State University - Bozeman, College of Engineering, 2008) Blank, Matthew David; Chairperson, Graduate Committee: Joel Cahoon; Thomas E. McMahon (co-chair)Fish passage through culverts is an important component of road and stream crossing design. Although no comprehensive inventory of the number of culverts on fishbearing streams in the United States is available, there is an estimated 1.4 million streamroad crossings. The most common physical characteristics that create barriers to fish passage include excessive water velocity, insufficient water depth and large outlet drop heights. Over the past decade, interest in the effect culvert barriers have on aquatic systems has grown; accordingly, various passage assessment techniques have been used to determine whether a structure is a barrier and to what degree (its "barrierity"). Recent research has shown that determining the barrierity of a culvert is not trivial, and that different methods are often not congruent in their classification of "barrierity". The purpose of this research was to investigate the effect of velocity on fish passage in great detail by: testing the use of computational fluid dynamics (CFD) for estimating the 3-D velocity field through a culvert; quantifying velocity diversity through culverts for a range of flows; characterizing the energy expenditure paths through a culvert and identifying the passageways Yellowstone cutthroat trout used to successfully negotiate passage; and developing and testing a new barrier assessment method. The research was done, in part, by studying fish passage through culverts in Mulherin Creek, an important spawning tributary for Yellowstone cutthrout trout migrating from the Yellowstone River. Comparisons between predicted and observed velocities show 86% and 82% of variation in the observed velocity data were explained by the CFD model, for flow rates of 1.44 m3/s and 0.87 m3/s, respectively. The diverse velocity field through the culvert barrel created a range of energy expenditure paths through the entire culvert length. Fish movement observations showed successful passage only for trout seeking and using the minimum energy path created, in part, by the skew between the upstream channel and the culvert. This research investigated a new hydraulic approach to assessing barriers that uses the 3-D velocity field. Comparisons between estimated passage and measured passage show the 3-D method most accurately indicated passability compared to a 1-D method.