Variation of the center of gravity of a golf club head will influence the initial velocity and rotation of speed of a ball after the golf ball is struck by golf club head. After fixing the weight of 200g of a golf head, the researcher changes the volume of golf head and the horizontal curvature of radius. He also distribute counterpoise to investigates the effect of launching of a golf ball. This thesis summarizes the ball of three-dimensional flight trajectory and offset distance. For the volume of the golf head is 400 cc, the best level of the radius of horizontal curvature is 11 in, in the 430 cc should use a radius of horizontal curvature of 12 in, and the 460 cc head club can chose a radius of horizontal curvature of 13 in. The distribution of counterpoise can effectively improve the play¡¦s habits, so the trajectory of a golf ball can be appropriately adjusted. By finite element method, the physical behavior of a series of the lunching ball can be predicted. The trajectory of golf ball can be measured by substituting the inertial value of ball into the three-dimension equations of motion. According to the trajectory of golf ball flight by this study, this study provides the characteristics for designing a golf club head.

This thesis contains the results of the development of crash prediction models for curved segments of rural two-lane two-way highways in the state of Utah. The modeling effort included the calibration of the predictive model found in the Highway Safety Manual (HSM) as well as the development of Utah-specific models developed using negative binomial regression. The data for these models came from randomly sampled curved segments in Utah, with crash data coming from years 2008-2012. The total number of randomly sampled curved segments was 1,495. The HSM predictive model for rural two-lane two-way highways consists of a safety performance function (SPF), crash modification factors (CMFs), and a jurisdiction-specific calibration factor. For this research, two sample periods were used: a three-year period from 2010 to 2012 and a five-year period from 2008 to 2012. The calibration factor for the HSM predictive model was determined to be 1.50 for the three-year period and 1.60 for the five-year period. These factors are to be used in conjunction with the HSM SPF and all applicable CMFs. A negative binomial model was used to develop Utah-specific crash prediction models based on both the three-year and five-year sample periods. A backward stepwise regression technique was used to isolate the variables that would significantly affect highway safety. The independent variables used for negative binomial regression included the same set of variables used in the HSM predictive model along with other variables such as speed limit and truck traffic that were considered to have a significant effect on potential crash occurrence. The significant variables at the 95 percent confidence level were found to be average annual daily traffic, segment length, total truck percentage, and curve radius. The main benefit of the Utah-specific crash prediction models is that they provide a reasonable level of accuracy for crash prediction yet only require four variables, thus requiring much less effort in data collection compared to using the HSM predictive model.