In this study, the incompressible viscous flow over a circular cylinder is studied numerically. The Navier-Stokes equations are solved numerically in 2D with the pressure-correction method and second-order finite difference scheme on a uniform Cartesian mesh. The circular cylinder is treated numerically by using the immersed boundary method originally developed by Peskin (1972). The simulations were performed at three different Reynolds numbers, ReD, based on the cylinder diameter ranging between 55 and 100. The numerical results such as the mean drag coefficient are compared at three different Reynolds numbers with experimental results.

Autonomous control systems are critical for the operation of aerial vehicles and spacecraft. This project focuses on the development of an autonomous control system for a robotic vehicle by simulating the model of the vehicle using computer software. This model will then be used for testing various control schemes. In particular, variation of the proportional-integral-derivative (PID) controller will be used and tested. The main goal of this research is to implement the autonomous control system on the vehicle and compare the response of the vehicle to those generated by our computer simulation. Specifically, the research will focus on the development process of the PID controller. Our results will then verify whether the developed mathematical model is accurate for the purpose of predicting actual system response. The objective of the analysis is to confirm the advantages and disadvantages of each control scheme and to develop an autonomous control algorithm for the vehicle. In-depth analysis will also provide insights into the difficulties and challenges of developing a mathematical model that accurately simulates all states of the system, as well as the complications involved in creating a system that precisely controls the vehicle as desired by the user.

A continuous measurement of wall shear stress can be achieved using shear sensitive liquid crystal coatings (SSLCC). Utilizing thin films of polymer-embedded birefringent liquid crystals as sensors, they deform elastically when subjected to shear stresses. The light passing through the SSLCC is recorded with a charge-coupled device camera and is processed by the specialized birefringence detecting Milliview. Shear magnitude and direction are determined from the results. A single coating comprises of polymers, solvents, and liquid crystals in varying proportions. When applied to a surface, solvents vaporize, leaving liquid crysals embedded inside polymer structures. By adjusting the proportions of the components, the viscosity and curing rate of the coatings can be controlled to match the method of application. A series of formulations were applied to a flat, glass substrate using methods such as airbrushing and direct deposition. Each combination was tested repeatedly at free-stream speeds ranging from 5 m/s to 36 m/s. The best coatings were determined by optical clarity, surface smoothness, signal strength, and reusability both through visual observation and testing in a small wind tunnel. Few combinations yielded both a high signal strength and reusability.

Engineered vehicles capable of matching the performance of natural systems in collision avoidance have not yet been developed. The purpose of our research is to translate the collision avoidance capability of schooling fish to an algorithm that could be applied to engineered vehicles. We want to determine if collision avoidance in schooling fish is related to an engineering method of collision avoidance termed collision cones. The collision cone is a set of velocities for one fish (or agent) that indicates it will collide with another fish (or agent). In order to avoid collision, the fish’s velocity vector must lie outside all collision cones. Constraints with this method are that it only works under certain conditions: each vehicle has constant velocities, uniform and full view sensing, noiseless measurements, and planar motion. This method already works well for engineered systems under these conditions. Our research is exploring how to alter the conditions to encompass the biological characteristics of the fish. As of now, the data that has been collected has revealed promising results. If further research reveals that collision cones do not match schooling fish’s collision avoidance capability, other algorithms will be explored. This research is significant in that it will impact the development of UAVs (Unmanned Aerial Vehicles) and other autonomous technology.