Glycine-arginine-alpha-ketoisocaproic acid calcium (GAKIC) is an amino acid combination postulated to improve dynamic performance of skeletal muscle during acute, anaerobic exercise in healthy individuals. Purpose: The purpose of this study was to determine the ergogenic effects of GAKIC ingestion on resistance training performance in both trained male and female participants. Methods: Utilizing a double-blinded, crossover design, male participants completed a lower body leg press resistance exercise protocol and female participants completed a lower body leg extension resistance exercise protocol once using 10.2 g GAKIC and the other with a placebo. Results: A significant increase in TLV after GAKIC supplementation was observed in both male and female participants performing a lower body resistance exercise. No significant differences were found in lower body 1RM, HR, BLa, and Glucose between conditions in both groups. Conclusion: We concluded with the specific exercise protocols that were implemented, GAKIC increased TLV in the lower body exercises.

The intensive research on sediment transport indicates a need of an appropriate equation for predicting the total sediment load in rivers to manage reservoirs, operate dam and design in-stream hydraulic structures. None of the available equations in sediment transport has gained universal acceptance for predicting the total sediment transport rate. These facts indicate the need of a general formula to represent all these formula for predicting the sediment transport rate. The first goal of this dissertation is to find a unified total sediment transport equation for all rivers. On the other hand, scour around hydraulic structures such as spur dikes and bridge piers can be a serious problem that weakens structural stability. An investigation on the turbulent flow field and turbulence distribution around such hydraulic structures is essential to understand the mechanism of local scour and to determine which turbulence properties affect the local sediment transport. In addition, a universal turbulent model that is valid for all cases of turbulent flow in open channels does not exist. This dissertation thoroughly examined the turbulent flow field and turbulence distribution around a series of three dikes. The goal is to determine the significant turbulent properties for predicting the local sediment transport rate and to identify the appropriate turbulence model for simulating turbulent flow field around the dikes.To develop a general unified total load equation, this study evaluates 31 commonly used formulae for predicting the total sediment load. This study attributes the deviations of calculated results from different formulae to the stochastic properties of bed shear stresses and assumes that the bed shear stress satisfies the log- normal distribution. At any given bed shear stress, Monte Carlo simulation is applied to each equation, and a set of bed shear stresses are randomly generated. Total sediment load generated from each Monte Carlo realization of all the equations are assembled to represent the samples of total sediment load predicted from all the equations. The statistical properties of the resultant total sediment loads (e.g. standard deviation, mean) at each given bed shear stress are calculated. Then, a unified total sediment load equation is obtained based on the mean value from all the equations. The results showed the mean of all the equations is a power function of dimensionless bed shear stress. Reasonable agreements with measurements demonstrate that the unified equation is more accurate than any individual equation for predicting the total sediment load.An experimental study and numerical simulation of the flow field and local scour around a series of spur dikes is performed in a fixed flat bed and scoured bed condition. A micro-Acoustic Doppler Velocimeter (ADV) is used to measure the instantaneous velocity field in all the three spatial directions and the measured velocity profiles are used to calculate the turbulence properties. Results show that the local scour develops around the first dike. Turbulence intensity together with the mean velocity in the vertical direction measured at the flat bed closely correlates to the scour depth. In addition, the maximum bed shear stress, occurring at the tip of the second dike in the three-dike series, does not correspond to the maximum scour. Large bed load transport due to bed shear stress may not initiate bed scouring, but turbulence bursts (e.g. sweeps and ejections) will entrain sediment from bed surface and develop the local scour.A three-dimensional numerical model FLOW-3D is used to simulate the turbulent flow field around a series of spur dikes in flat and scoured bed. This study examines Prandtl's mixing length model, one equation model, standard two-equation model, Renormalization-Group (RNG) model, and Large Eddy Simulations (LES) turbulence model. The Prandtl's mixing length model and one equation model are not applicable to flow field around dikes. Results of mean flow field by using the standard two-equation model, and RNG turbulence model are close to the experimental data, however the simulated turbulence properties from different turbulent model deviate considerably. The calculated results from different turbulence models show that the RNG model best predicts the mean flow field for this series of spur dikes. None of the turbulence closure models can predict accurate results of turbulence properties, such as turbulence kinetic energy. Based on those results, this study recommends the use of RNG model for simulating mean flow field around dikes. Further improvements of FLOW-3D model is needed for predicting turbulence properties near this series of spur dikes under various flow conditions.

Bedload-trapping efficiencies for four types of pressure-difference bedload samplers – a standard Helley-Smith (intake-nozzle width and height of 76.2 mm x 76.2 mm), BLH-84 (76.2 mm x 76.2 mm), Elwha (203 mm x 102 mm) and Toutle River-2 (305 mm x 152 mm) a standard Helley-Smith, US BLH-84 (both with intake nozzle dimensions of 76.2 mm × 76.2 mm), Elwha (203 mm × 102 mm) and Toutle River-2 (TR-2; 305 mm × 152 mm) – were calculated from data collected during the StreamLab06 experiments in the St. Anthony Falls Laboratory Main Flume during January-March 2006. Sampler nozzle-flare ratios –the area of the nozzle's outlet divided by its inlet area – equaled 1.4 for all but the Helley-Smith sampler's nozzle-flare ratio of 3.22. A sampler's trapping coefficient quantifies its bedload-trapping efficiency. Technically supportable trapping coefficients are divided into raw trapping rates measured by the sampler to produce "true" bedload-transport rates equivalent to that which was inferred to have occurred in the absence of the sampler. Six combinations of sampler and bed types were tested; the BLH-84, Elwha, and Helley-Smith samplers were deployed atop a sand bed (D50 = 1.0 mm) during five steady flows ranging from 2.0-3.6 m3/s. The BLH-84, Elwha, and TR-2 samplers were deployed atop a gravel bed (D50 = 11.2 mm) at four steady flows ranging from 4.0-5.5 m3/s. Thirty-seven trials – repeated manual at-a-point deployments of a given bedload sampler for a given steady flow and bed type – took place. Trapping coefficients were calculated for each sampler and bed type in which it was deployed. Ergo, two of the samplers – the BLH-84 and Elwha – were each assigned two trapping efficiencies for sampling on a sand versus a gravel bed. These data were evaluated using four analytical methods: Ratio of Averages: This relatively simple and straight-forward method required calculating averages of bedload-transport rates derived for each of the 37 trials for a given bedload sampler and for up to nine combinations of weigh pans and time intervals. The computations were performed using untransformed data. Average of Ratios: This more complex method using real-space trapping data involved developing average transport rates from selected pan data for each bedload sample. Pan transport-averages were calculated for each interval equal to the duration of a single at-a-point bedload measurement, ranging from 15-180 seconds. Ratios (coefficients) were calculated by dividing each interval average into the single-sample trap rate. Those ratios were then averaged to produce a single trapping coefficient for the trial and then combined into a single average for each bedload-sampler/bed type/flow combination. Modified Thomas and Lewis Model (1993): The Thomas-Lewis Model was revised to operate using untransformed data in addition to cube-root transformed data (thus, the third and fourth analytical methods used, respectively), and to use nine pan-window combinations to calculate trapping coefficients. The original 3-step model required first regressing cube root-transformed sampler data on time-window averaged pan transport rates. The second step squared the regression residuals from the first step on the variance of the cube root of the interval-mean transport rate for the time window. The predicted values from the second-step regression were inverted and used as weights to re-estimate the first-step regression. Generalized trapping-coefficient calculations based on results from the four analytical methods for the bed-types in which the samplers were deployed follow: • BLH-84 Sampler: A 0.83 sand-bed trapping coefficient and 0.87 gravel-bed coefficient, which could be averaged to a single coefficient of 0.85. • Elwha Sampler: A 1.67 sand-bed trapping coefficient and 1.54 gravel-bed coefficient, which could be averaged to a single coefficient of 1.6 • Helley-Smith Sampler: The 3.11 sand-bed trapping coefficient could be applied as such or reasonably simplified to a value of 3.0, and • TR-2: The gravel-bed trapping coefficient equaled 1.70. An unadjusted bedload-trapping rate calculated from a sample collected by a given sampler can be divided by its trapping coefficient(s) to obtain the most reliable transport-rate value. / Ph.D.

In this study, a qualitative and comparative investigation on sediment transport equations used in prediction of rserevoir sedimentation is presented. 32 sediment transport equations, which are selected by literature review on sand and gravel size ranges, grouped according to the median particle sizes on which their derivation based. In order to compare these equations computer program DELTA, which is a one dimensional simulation program developed by Graf and Altinakar (1998) for the prediction of delta formation in resrvoirs, is used. Computer simulation is performed within each group of sediment transport equations in order to determine the most suitable equation for corresponding median diameter of sediment particles. 8 of the equations gave simulation results that are in good agreement with average values related to delta deposition extent, height and location in the reservoir. The effects of river slope change and median diameter change on delta deposition also investigated and simulation results are compared with previous model studies.

The state of Georgia has two large ports that are accessed by way of navigable entrance channels. One of these ports is located in Brunswick, Georgia, and is maintained by the United States Army Corps of Engineers via periodic dredging. Sediments removed from the channel are typically pumped several miles offshore of Brunswick and placed in dredged material mounds, thus removing the sediment from the littoral cycle. This offshore placement, while being the most economically viable method, often negatively impacts the sediment budget of the coastal region and causes erosion downdrift of the channel, specifically along Jekyll Island. Onshore placement of the dredged material is not feasible due to increased associated costs and the high fraction of fines present in the material; thus, nearshore placement is a potentially viable alternative. Nearshore placement could possibly reduce erosion rates and provide protection to property from waves and storms. The USACE initiated a thorough field data collection campaign in 2002 to study the possibility of beneficial placement of dredged material. The author analyzed the existing data to predict the rate and direction of sediment movement away from an existing dredge mound. These predictions are then compared to bathymetric survey data in an effort to validate the results and methodologies used for sediment transport predictions. The ultimate goal is to use the results of this study along with numerical models currently being developed by the Corps to assess the possibility of sediments being transported toward the shore thus re-entering the littoral cycle and providing a benefit to the coast of Georgia.