A project sponsored by the Texas Department of Transportation (TxDOT), involves the development of a reward function and analysis components in a Python Jupyter notebook to train the module dictating the cycle length and green time allocation of a simulated intersection. Artificial Intelligence (AI) techniques are implemented in a Reinforcement Learning setting to incorporate equity and efficiency into decisions of green times for each approaching lane. Equity is determined through the Gini coefficient of wait times for all vehicles as well as for directions/routes traveled, to provide the most equitable intersection timing allocation given a simulated population of vehicles utilizing the intersection.

The main advantage of frames is its redundancy. Frames are used for signal processing, lossy image and sound compression methods, and wavelet transforms. The redundancy ensures no loss of information. A frame is a spanning set of N vectors in dimension C^d where N>=d. A tight frame is a type of frame that is similar to an orthonormal basis, but without linear independence. This project focuses on the different combinations of discrete finite transform (DFT) matrices that form a tight frame in dimension d = 3. A DFT matrix is a matrix composed of different powers of the Nth root of unity. Finite Unit Norm Tight Frames (FUNTFs) are created by taking d rows in the DFT matrix and putting them into a new matrix U. The vectors that form the FUNTF are the columns of U. Our goal is to classify which FUNTF’s for C^3 formed from the DFT can be decomposed into more FUNTFs.

An investigation was done in order to study the strength of three common single-shear nailed and toenail lumber connections. Several pieces of literature were read and served as guidelines for the designing and calculations of lumber connections. The connections were configured and built and the NDS Wood Connection Calculator was used to calculate the design value and yield modes of three connections. The connections were built using Douglas fir-larch 2x4 nominal lumber, 20-gauge Simpson Strong-Tie steel side-plates, and common nails were used for testing. The first connection was made between a steel plate and a 2”x4” using a 6d common nail. The second connection was made between two 2”x4”s using a 10d common nail. Those connections were tested in shear using an Instron Press. The final connection was a toenail connection which used four 8d nails and was tested using a lateral shear force. It was found that the tested values of the connections were notably higher than that of the design value as well as the yield modes. This led to the conclusion that design calculations are conservative relative to their real-life performance.

Frictional loses and wear are an inevitable means in machine life. The researchers have been trying to minimize wear reductions and decrease frictional coefficients for quite some time. External lubricants have been known to increase efficiency and longevity of machinery. Ionic liquids have been proven to be successful neat lubricants or additives. In addition, 2-D materials have shown important improvements when added to base lubricants. In this tribological study the protic ionic liquid, Eet (2-hydroxyethylammonium 2-ethylhexanoate) is used as a lubricant and lubricant additive across several conditions, some of which include two different kinds of layers of Mxene (fx and mx). Nine different samples under similar conditions were tested using a ball-on-flat reciprocating tribometer. Each test used approximately 2ml of solution and ran for a 30 minute test duration under a 2 Newton loading. The use of neat Eet proved to help decrease frictional coefficients and wear. The addition of Mxene layers yielded a significant decrease in frictional coefficients across all conditions. The wear mechanisms as well as surface interactions will also be discussed.