<p>  </p> <p>The major concern about vehicle crashes has led to a great amount of research on the topic in the road safety area. Nevertheless, real-world crash data collection periods are often extensive and they result in a great delay in improving safety. Therefore, surrogate measures of safety, such as traffic conflicts, are considered for safety management.</p> <p>The definition of a traffic conflict has evolved over the course of half a century. One of the current definitions encompasses a failure-based road event that inevitably results in a crash if no evasive action is taken by involved road users. This counterfactual concept was validated with specific road events datasets, including rear-end events and vehicle-bicycle encounters. However, observing conflicts for an extended period is still a major difficulty. For example, a LIDAR-based technique applicable to intersections can collect conflict data for a relatively short period of several days. The LiDAR-collected data are then converted to the corresponding expected crash frequency during the observation period, which eventually must be expanded to the corresponding annual value. The conversion step has not been sufficiently addressed in the past research. Thus, an important task of estimating the annual expected crash frequency based on a short-term estimate remains unanswered. Addressing this need is the research objectives and contribution of this study.</p> <p>Advanced statistical methods allow developing models to estimate expected crash frequencies for annual and short periods. The ratio of such two estimates is defined as an expansion factor in this study. This thesis presents the modeling effort and its results for different types of crashes at signalized and unsignalized intersections in Indiana. Traditional and emerging data, such as traffic volume, speed, road characteristics, weather, and other features were collected and assembled at randomly selected 194 intersections. Then, they were used to estimate the logistic models of hourly crash probability. The models were then utilized to calculate expansion factors for a specific intersection.to evaluate the method.</p>

A seal is a component used in a turbomachine to reduce internal leakage of the working fluid and to increase the machine's efficiency. The stability of a turbomachine partially depends upon the rotodynamic coefficients of the seal. The integral control volume based rotodynamic coefficient prediction programs are no more accurate than the accuracy of the leakage mass flow rate estimation. Thus an accurate prediction of the mass flow rate through seals is extremely important, especially for rotodynamic analysis of turbomachinery. For labyrinth seals, which are widely used, the energy dissipation is achieved by a series of constrictions and cavities. When the fluid flows through the constriction (under each tooth), a part of the pressure head is converted into kinetic energy, which is dissipated through small scale turbulence-viscosity interaction in the cavity that follows. Therefore, a leakage flow rate prediction equation can be developed by comparing the seal to a series of orifices and cavities. Using this analogy, the mass flow rate is modeled as a function of the flow coefficient under each tooth and the carry over coefficient, which accounts for the turbulent dissipation of kinetic energy in a cavity. This work, based upon FLUENT CFD simulations, initially studies the influence of flow parameters, in addition to geometry, on the carry over coefficient of a cavity, developing a better model for the same. It is found that the Reynolds number and clearance to pitch ratios have a major influence and tooth width has a secondary influence on the carry over coefficient and models for the same were developed for a generic rectangular tooth on stator labyrinth seal. The discharge coefficient of the labyrinth seal tooth (with the preceding cavity) was found to be a function of the discharge coefficient of a single tooth (with no preceding cavity) and the carry over coefficient. The discharge coefficient of a single tooth is established as a function of the Reynolds number and width to clearance ratio of the tooth and a model for the same is developed. It is also verified that this model describes the discharge coefficient of the first tooth in the labyrinth seal. By comparing the coefficients of discharge of compressible flow to that of incompressible flow at the same Reynolds number, the expansion factor was found to depend only upon the pressure ratio and ratio of specific heats. A model for the same was developed. Thus using the developed models, it is possible to compute the leakage mass flow rate as well as the axial distribution of cavity pressure across the seal for known inlet and exit pressures. The model is validated against prior experimental data.

Labyrinth seals are often utilized in locations where contact seals cannot be utilized due to the large displacements of the rotating shaft. The performance evaluation of a labyrinth seal is very important to make sure that optimum performance of turbomachinery is attained. Performance parameters such as carryover coefficient, discharge coefficient were evaluated for a see through triangular tooth on stator labyrinth seal. This computational study investigates how flow conditions and seal parameter variations for see through tooth on stator triangular cavity labyrinth seals affect the value of the carryover coefficient and discharge coefficient. A Finite volume CFD commercial code was used to accomplish the above study. The influence of Reynolds number, rotational speed, seal radial clearance, pitch, tooth angle, tooth width are considered using the finite volume method of computational fluid dynamics. It was found that Reynolds number, high shaft speed and clearance have a significant effect on the carryover coefficient and the discharge coefficient. Clearance is the major influential parameter to be considered among all seal geometric parameters to optimize an ideal seal.