Humans learn to interact with many complex physical systems. For example, humans learn to fly aircraft, operate drones, and drive automobiles. We present results from human-in-the-loop (HITL) experiments, where human subjects interact with dynamic systems while performing command-following tasks multiple times over a one-week period. We use a new subsystem identification (SSID) algorithm to estimate the control strategies (feedforward, feedforward delay, feedback, and feedback delay) that human subjects use during their trials. We use experimental and SSID results to examine the effects of system characteristics (e.g., system zeros, relative degree, system order, phase lag, time delay), reference command, and command-following objectives on humans command-following performance and on the control strategies that the humans learn. Results suggest that nonminimum-phase zeros, relative degree, phase lag, and time delay tend to make dynamic systems difficult for human to control. Subjects can generalize their control strategies from one task to another and use prediction of the reference command to improve their command-following performance. However, this dissertation also provides evidence that humans can learn to improve performance without prediction. This dissertation also presents a new SSID algorithm to model the control strategies that human subjects use in HITL experiments where they interact with dynamic systems. This SSID algorithm uses a two-candidate-pool multi-convex-optimization approach to identify feedback-and-feedforward subsystems with time delay that are interconnected in closed loop with a known subsystem. This SSID method is used to analyze the human control behavior in the HITL experiments discussed above.

Majority of the products get discarded at end-of-life (EoL), causing environmental pollution, and resulting in a complete loss of all materials and embodied energy. Adopting a closed-loop material flow approach can aid preventing such losses and enable EoL value recovery from these products. Design and engineering decisions made and how products are used impact the capability to implement EOL strategies such as disassembly and remanufacturing. Some underlying factors affecting the capability to implement these EOL strategies have been discussed in previous studies. However, relevant metrics and attributes are not well defined and comprehensive methods to quantitatively evaluate them are lacking. This study will first identify key lifecycle oriented metrics affecting disassemblability and remanufacturability. Then a methodology is proposed for the quantitative evaluation of these strategies considering the quality of returns, product-design characteristics and process technology requirements. Finally, an industrial case-study is presented to demonstrate the application of the proposed method.

This thesis investigates potential materials to be used in the rotary sealing industry that provide low power loss and minimize cost. The studied rotary valve utilizes slots that act as timing valves to allow for flow axially, through the seal face, at particular times within a heat pump cycle. This investigation examines various combinations of multiple PTFE materials, plastics, and soft metals that have been proven to provide low friction coefficients. Leakage and wear requirements are stated for the future use of the rotary valve and are used to determine the effectiveness of sealing the fluid while examining the power loss. In conclusion, the study finds the combination of a modified PTFE stationary ring and Aluminum Bronze rotating face to provide the lowest power loss. Numerical analysis was completed to verify the lubrication regime to be partial lubrication and was also used to investigate geometry changes and impact on the power loss.

This thesis presents a real-time autonomous guidance and control method for a quadrotor in a GPS-denied environment. The quadrotor autonomously seeks a destination while it avoids obstacles whose shape and position are initially unknown. We implement the obstacle avoidance and destination seeking methods using off-the-shelf sensors, including a vision-sensing camera. The vision-sensing camera detects the positions of points on the surface of obstacles. We use this obstacle position data and a potential-field method to generate velocity commands. We present a backstepping controller that uses the velocity commands to generate the quadrotor's control inputs. In indoor experiments, we demonstrate that the guidance and control methods provide the quadrotor with sufficient autonomy to fly point to point, while avoiding obstacles.

Empirical models based on flow resistivity are commonly used to determine the bulk properties of porous sound absorbing materials. The bulk properties include the complex wavenumber and complex characteristic impedance which can be used directly in simulation models. Moreover, the bulk properties can also be utilized to determine the normal incidence sound absorption and specific acoustic impedance for sound absorbing materials of any thickness and for design of layered materials. The sound absorption coefficient of sound absorbing materials is measured in an impedance tube using wave decomposition and the measured data is used to determine the flow resistivity of the materials by least squares curve fitting to empirical equations. Results for several commonly used foams and fibers are tabulated to form a rudimentary materials database. The same approach is then used to determine the flow resistivity of compressed sound absorbing materials. The flow resistivities of the compressed materials are determined as a function of the compression ratio. Results are then used in conjunction with transfer matrix theory to predict the sound absorptive performance of layered compressed absorbers with good agreement to measurement.

AISI 4140 alloy steel has been a very common material to be investigated in automotive and aerospace industries for several decades. AISI 4140 alloy steel is chromium, molybdenum, and manganese containing low alloy steel. It has high fatigue strength, abrasion and impact resistance, toughness, and torsional strength. The functional performance is largely determined by the surface states after machining. The aim of the present study is to explore the polishing methods and surface analysis after machining AISI 4140 alloy steel in different cutting speeds and cooling conditions. The surface analysis includes surface roughness, hardness and residual stresses. Compared to traditional polishing, an innovative experimental work was conducted on electro-polishing technology for removing surface layer before subsurface residual stress measurement. The results of this work show that the electro-polishing method is a significant approach for the residual stress analysis. High cutting speed and cooling conditions can improve the surface quality to achieve lower surface roughness, higher microhardness and more compressive residual stresses after machining AISI 4140 alloy steel.

Partial enclosures are commonly used to reduce machinery noise. However, it is well known in industry that enclosures sometimes amplify the sound at low frequencies due to strong acoustic resonances compromising the performance. These noise issues are preventable if predicted prior to prototyping and production. Though boundary and finite element approaches can be used to accurately predict partial enclosure insertion loss, modifications to the model require time for remeshing and solving. In this work, partial enclosure performance at low frequencies is simulated using a plane wave transfer matrix approach. Models can be constructed and the effect of design modifications can be predicted rapidly. Results are compared to finite element analysis and measurement with good agreement. The approach is then used to design and place resonators into a sample enclosure. Improvements in enclosure performance are predicted using plane wave simulation, compared with acoustic finite element analysis, and then validated via measurement.

Balancing trade-offs between production cost and holding cost is critical for production and operations management. Utilization of an operating room affects production cost, which relates to makespan, and patient flowtime affects holding cost. There are trade-offs between two objectives, to minimize makespan and to minimize flowtime. However, most existing constructive heuristics focus only on single-objective optimization. In the current literature, NEH is the best constructive heuristic to minimize makespan, and LR heuristic is the best to minimize flowtime. In this thesis, we propose a current and future deviation (CFD) heuristic to balance trade-offs between makespan and flowtime minimizations. Based on 5400 randomly generated instances and 120 instances in Taillard’s benchmarks, our CFD heuristic outperforms NEH and LR heuristics on trade-off balancing, and achieves the most stable performances from the perspective of statistical process control.

The operating room (OR) is accountable for most hospital admissions and is one of the most cost and work intensive areas in the hospital. From recent trends, we discover an unexpected parallel increase in expenditure and waiting time. Therefore, improving OR planning has become obligatory, particularly regarding utilization, and service level. Significant challenges in OR planning are the high variations in demand, processing times of surgical specialties, the trade-off between the objectives, and control of OR performance in long-term. Our model provides OR configurations at a strategical level of OR planning to minimize the tradeoff between the utilization and service level accounting for variation in both demand and processing times of surgical specialties. An adaptive control scheme is proposed to aid OR managers to maintain the OR performance within the prescribed controllable limits. Our model is validated using a simulation of demand and processing time data of surgical services at University of Kentucky Health Care.

The effects of system pressure on the performance stability of flow-through capacitive deionization (CDI) cells was investigated. Initial data showed that the highly porous carbon electrodes possessed air/oxygen in the micropores, and the increased system pressure boosts the gases solubility in saline solution and carries them out of the cell in the effluent. Upon applying a potential difference to the electrodes, capacitive-based ion adsorption occurs in competition with faradaic reactions that consume oxygen. Through the addition of backpressure, the rate of degradation decreases, allowing the cell to maintain its salt adsorption capacity (SAC) longer. The removal of oxygen from the pore space of the electrodes makes it no longer immediately accessible to faradaic reactions, thus hindering the rate of reactions and giving the competing ion adsorption an advantage that is progressively seen throughout the life of the cell. A quick calculation shows that the energy penalty to power the pump is fairly insignificant, especially in comparison to the cost of replacing the electrodes in the cell. Thus, operating at elevated pressures is shown to be cost effective for continuous operation through the reduced electrode replenishment costs.