A vortex shedding model is developed to predict the flow fields around turbine flowmeter blades. This model is used to simulate the flow separation and reattachment in the leading edge areas and the wake flows of the blades. Lewis's inverse blade design method is developed and quite successfully applied to simulate the displacement effect of the separation bubbles in the leading edge areas. A new method is introduced to apply the Kutta condition in unsteady flows around the blades wi th separation points on a blade surface or the flow with blade interaction. This method does not require a large amount of iterative calculation. A model is built up to predict the turbine flowmeter performance when the inlet flow conditions are known. The panel method is applied to predict the inlet flow conditions for the cases without inlet swirl. An experimental study of the flow inside a turbine flowmeter is carried out using Laser Doppler Anemometry(LDA) to measure the throughout velocity fields around a flowmeter at different flowrates and with different inlet swirls. A clear picture of the flow field is thus obtained. The measured resul ts are also used to validate the developed turbine flowmeter performance prediction model. The numerical prediction are tested with experimental results. The theoretical and experimental data agree with each other very well in the cases without inlet swirl and reasonably ",ell in other tested cases with inlet swirl.

This dissertation presents the development of two unique measurement platforms. <br><br>The first system is a high-temperature Z-Meter. This system is designed to simultaneously measure the electrical resistivity, Seebeck coefficient, and thermal conductivity of a thermoelectric sample to accurately determine the figure of merit, ZT, for that material. It is designed to operated at sample temperatures of up to 1000C, and with temperature gradients on the order of 500C across the sample. This system also provides <i>in situ</i> load monitoring for contact pressure and allows the user to adjust loading during the experiment. <br><br>The second part of this dissertation focuses on the development of enhanced composite phase change material (PCM) heat sinks to improve passive thermal management in mobile electronics. We present a new design for a composite PCM heat sink and utilize off-the-shelf PCMs to show characterize the performance. In order to accurately investigate the performance enhancement of these designs, we develop a turn-key thermal management evaluation platform to allow the user complete control over the power profiles and cycling applied to the test chip, as well as providing <i>in situ</i> temperature monitoring within the chip. The proposed package designs show significant improvement in the length of time extended before reaching the cut-off temperature within the heatfluxes tested, 6 - 14 W/cm^2, and accomplish this while weighing less than the equivalent sensible heat storage design.<br><br><br><br>

<div>With robots expanding their applications in more and more scenarios, practical problems from different scenarios are challenging current 3D measurement techniques. For instance, infrastructure inspection robots need large-scale and high-spatial-resolution 3D data for crack and defect detection, medical robots need 3D data well registered with temperature information, and warehouse robots need multi-resolution 3D shape measurement to adapt to different tasks. In the past decades, a lot of progress has been made in improving the performance of 3D shape measurement methods. Yet, measurement scale and speed and the fusion of multiple modalities of 3D shape measurement techniques remain vital aspects to be improved for robots to have a more complete perception of the real scene. In this dissertation, we will focus on the digital fringe projection technique, which usually can achieve high-accuracy 3D data, and expand the capability of that technique to complicated robot applications by 1) extending the measurement scale, 2) registering with multi-modal information, and 3) improving the measurement speed of the digital fringe projection technique.</div><div><br></div><div>The measurement scale of the digital fringe projection technique mainly focused on a small scale, from several centimeters to tens of centimeters, due to the lack of a flexible and convenient calibration method for a large-scale digital fringe projection system. In this study, we first developed a flexible and convenient large-scale calibration method and then extended the measurement scale of the digital fringe projection technique to several meters. The meter scale is needed in many large-scale robot applications, including large infrastructure inspection. Our proposed method includes two steps: 1) accurately calibrate intrinsics (i.e., focal lengths and principal points) with a small calibration board at close range where both the camera and projector are out of focus, and 2) calibrate the extrinsic parameters (translation and rotation) from camera to projector with the assistance of a low-accuracy large-scale 3D sensor (e.g., Microsoft Kinect). The two-step strategy avoids fabricating a large and accurate calibration target, which is usually expensive and inconvenient for doing pose adjustments. With a small calibration board and a low-cost 3D sensor, we calibrated a large-scale 3D shape measurement system with a FOV of (1120 x 1900 x 1000) mm^3 and verified the correctness of our method.</div><div><br></div><div> Multi-modal information is required in applications such as medical robots, which may need both to capture the 3D geometry of objects and to monitor their temperature. To allow robots to have a more complete perception of the scene, we further developed a hardware system that can achieve real-time 3D geometry and temperature measurement. Specifically, we proposed a holistic approach to calibrate both a structured light system and a thermal camera under exactly the same world coordinate system, even though these two sensors do not share the same wavelength; and a computational framework to determine the sub-pixel corresponding temperature for each 3D point, as well as to discard those occluded points. Since the thermal 2D imaging and 3D visible imaging systems do not share the same spectrum of light, they can perform sensing simultaneously in real time. We developed a hardware system that achieved real-time 3D geometry and temperature measurement at 26Hz with 768 x 960 points per frame.</div><div><br></div><div> In dynamic applications, where the measured object or the 3D sensor could be in motion, the measurement speed will become an important factor to be considered. Previously, people projected additional fringe patterns for absolute phase unwrapping, which slowed down the measurement speed. To achieve higher measurement speed, we developed a method to unwrap a phase pixel by pixel by solely using geometric constraints of the structured light system without requiring additional image acquisition. Specifically, an artificial absolute phase map $\Phi_{min}$, at a given virtual depth plane $z = z_{min}$, is created from geometric constraints of the calibrated structured light system, such that the wrapped phase can be pixel-by-pixel unwrapped by referring to $\Phi_{min}$. Since $\Phi_{min}$ is defined in the projector space, the unwrapped phase obtained from this method is an absolute phase for each pixel. Experimental results demonstrate the success of this proposed novel absolute-phase unwrapping method. However, the geometric constraint-based phase unwrapping method using a virtual plane is constrained in a certain depth range. The depth range limitations cause difficulties in two measurement scenarios: measuring an object with larger depth variation, and measuring a dynamic object that could move beyond the depth range. To address the problem of depth limitation, we further propose to take advantage of an additional 3D scanner and use additional external information to extend the maximum measurement range of the pixel-wise phase unwrapping method. The additional 3D scanner can provide a more detailed reference phase map $\Phi_{ref}$ to assist us to do absolute phase unwrapping without the depth constraint. Experiments demonstrate that our method, assisted by an additional 3D scanner, can work for a large depth range, and the maximum speed of the low-cost 3D scanner is not necessarily an upper bound of the speed of the structured light system. Assisted by Kinect V2, our structured light system achieved 53Hz with a resolution 1600 x 1000 pixels when we measured dynamic objects that were moving in a large depth range.</div><div><br></div><div> In summary, we significantly advanced the 3D shape measurement technology for robots to have a more complete perception of the scene by enhancing the digital fringe projection technique in measurement scale (space domain), speed (time domain), and fusion with other modality information. This research can potentially enable robots to have a better understanding of the scene for more complicated tasks, and broadly impact many other academic studies and industrial practices.</div>

<div>In this thesis, the design and implementation of an autonomous system that will equip a multi-rotor unmanned aerial vehicle (UAV) for visual detection and tracking of other UAVs is presented. The results from detection and tracking are used for real-time motion planning.</div><div><br></div><div>The goal is to effectively detect unwanted UAVs, track them and finally capture them with a net. Having a net that traps the UAVs and enables dragging intruders to another location is of great importance, since these could be carrying dangerous loads.</div><div><br></div><div>The project consists of three main tasks: object detection using a stereo camera, video tracking using a Kalman filter based algorithm, and lastly executing an optimal flight plan to aim a net at the detected intruder UAV. The computer vision, motion tracking and planning algorithms are implemented as ROS nodes what makes them executable on a reduced size onboard computer that is installed on the aerial vehicle.</div><div><br></div><div>Previous work related to this project consists of either a UAV detection system with computationally heavy algorithms or a tracking algorithm that does not include information about the dynamics of the UAVs. For the capture methods, previous ideas do not consider autonomous decisions or an optimized method to guarantee capture. In this thesis, these three aspects are considered to develop a simple solution that can be mounted on any commercially available UAV.</div>

<div>Rare circulating cells are becoming a subject of interest due to their potential clinical applications to replace invasive procedures. Due their low presence in blood (as low as 1 in 1 ml of blood) various platforms are developed to capture and isolate them. Common limitations of current platforms include the inability to process large volumes of blood without an initial volume reduction step such as centrifugation, reliance on a single antibody for the capture, and the difficulty of releasing and retrieving the captured cells with high purity. A rare cell retrieval platform with high throughput operation and high purity retrieval is needed to capture these rare cells by processing large volumes of blood.</div><div><br></div><div>In this thesis study, we have developed a two-tiered microchip system to capture and retrieve rare cells from blood samples with high purity. The first module of the system is a high throughput microfluidic interface that is used to immunomagnetically isolate targeted rare cells from whole blood, and discard > 99.999% of the unwanted leukocytes. The second module is a microwell array that furthers the purification by magnetically guiding each cell into a separate well concurrently, and allows individual retrieval of each cell. Even though the system we have developed is applicable to many fields pertaining to rare cell capture, here we demonstrate the proof-of-concept using model cell lines that represent circulating fetal trophoblasts. We describe the design, operation as well as the experimental characterization of the system. Our characterization results show that the process can be completed within 145 minutes from the very beginning till the retrieval of a target cell, and can provide efficiencies and purities that are as high as 100%. </div><div><br></div><div>In order to demonstrate a real-world use case for our device, we present preliminary experiments done with blood samples from pregnant women. We show that we are able to retrieve candidate fetal cells under 167 minutes. Future work will be focused on sequencing the candidate fetal cells retrieved from maternal samples to confirm their fetal origin as well as enhancing system performance in maximizing the number of cells captured.</div><div><br></div>

<p dir="ltr">Emission and absorption spectroscopy diagnostics are useful for providing non-invasive,<br>quantitative measurements of various gas properties in combustion environments, including<br>temperature and species concentrations. These measurements become even more useful<br>when they are applied with high spatial and temporal resolution. This dissertation describes<br>several ways that both emission and absorption diagnostics were advanced through leveraging<br>improvements in mid-IR camera and laser technology and through refining the use of existing<br>techniques.<br>A literature review is provided for both laser absorption and emission spectroscopy. Previous advancements in spatially resolved techniques are explained. The fundamental equations<br>of spectroscopic diagnostics are reviewed, starting from statistical mechanics.<br>A spectrally-resolved emission imaging diagnostic is presented. This diagnostic provided<br>1-dimensional measurements of gas temperature and relative mole fraction of CO₂ and HCl<br>in flames. An imaging spectrometer and a high-speed mid-infrared camera were used to<br>provide 1D measurements of CO₂and HCl emission spectra with a spectral resolution of<br>0.46 cm^-1 at rates up to 2 kHz. Measurements were acquired in HMX and AP-HTPB flames<br>burning in air at 1 atm. This diagnostic was applied to characterize how the path-integrated<br>gas temperature of HMX flames varies in time and with distance above the burning surface.<br>Additionally, Abel inversion with Tikhonov regularization was applied to determine the radial<br>distribution of temperature and relative concentration of CO₂ and HCl within the core of<br>AP-HTPB flames.<br>Next, a similar emission imaging diagnostic is presented which uses spectrally-resolved<br>measurements of emission spectra at visible wavelengths, unlike the mid-infrared measure-<br>ments in the rest of this dissertation. This diagnostic provided 1D temperature measure-<br>ments of aluminum oxide (AlO), an intermediate product of aluminum combustion. While<br>this author created the AlO diagnostic, these measurements were performed alongside a CO<br>absorption diagnostic used by a different researcher to compare the flame bath gas (via CO)<br>and the region immediately around aluminum particles (via AlO) when varying forms of<br>aluminum powder were used in a propellant. This comparison allows analysis of the burning regime of aluminum particles. Evidence was found that nano-aluminum particles burn in<br>the kinetically controlled combustion regime, while micron-aluminum particles burn in the<br>diffusion-controlled regime.<br>Multi-spectral emission imaging of hypergolic ignition of ammonia borane (AB) is then<br>presented. Three high-speed cameras with multiple optical filters were used to capture<br>infrared and visible wavelength videos of four individual species during AB ignition: BO,<br>BO₂, HBO₂, and the B-H stretch mode of AB were imaged. The ignition process was<br>observed to act in two steps: gas evolution and then propagation of a premixed flame. The<br>evolution of the species and flame front revealed that boranes may continue to complete<br>combustion to a further degree than other boron fuels. This author performed the infrared<br>camera imaging and also ran infrared spectrograph measurements to confirm which species<br>were viewed through the optical filters.<br>Next, a scanned-wavelength direct-absorption diagnostic for directly measuring NH₃ in<br>high-temperature combustion environments is presented. A quantum cascade laser (QCL)<br>was scanned at 5 kHz over multiple NH₃ transitions between 959.9 cm⁻¹ and 960.3 cm⁻¹ to<br>measure path-integrated NH₃ temperature and mole fraction. Many NH₃ transitions overlap<br>with high-temperature water lines at commonly used diagnostic frequencies, severely limiting<br>those diagnostics’ capabilities in water-rich, high-temperature environments that are typical<br>of combustion applications. The optical frequencies used in this diagnostic are insensitive<br>to water absorption and thus remedy this issue. This diagnostic was demonstrated within<br>the flame of ammonia borane. AB-based fuels were burned in ambient air and translated<br>vertically to effectively scan the measurement line-of-sight vertically through the flame. Ad-<br>ditionally, flames of these fuels were characterized at a stationary height in an opposed-flow<br>burner (OFB) under O₂ flow.<br>The final chapter presents scanned-wavelength direct-absorption measurements of path-<br>integrated temperature and CO mole fraction in opposed-flow diffusion flames of hydroxyl-<br>terminated polybutadiene (HTPB). HTPB strands were held in an opposed-flow burner<br>under an opposed flow of O2 or 50/50 O₂/N₂ to create quasi-steady and quasi-1D diffusion<br>flames above the fuel strand. The opposed-flow burner was translated vertically to effectively<br>scan the measurement line-of-sight vertically through the flame. A quantum-cascade laser (QCL) was scanned across the P(2,20), P(0,31), and P(3,14) absorption transitions in CO’s<br>fundamental vibration bands near 2008 cm⁻¹ at 10 kHz to determine the path-integrated<br>temperature and CO mole fraction. The laser beam was passed through sapphire rods<br>held close to the flame edge to bypass the flame boundary and provide a well defined path<br>length for mole fraction measurements. The measured profiles and fuel regression rates<br>were compared to predictions produced by a steady opposed-flow 1D diffusion flame model<br>produced by researchers at the Army Research Lab. The model was generated with chemical<br>kinetics mechanisms employing two different assumptions for the nascent gaseous product of<br>HTPB pyrolysis: C₄H₆ or C₂₀H₃₂. It was found that the C₂₀H₃₂ model produced temperature<br>and CO profiles along with regression rates that agreed more closely with the measured<br>results.<br></p>

The transportation sector consumes around 70% of all petroleum in the US. In recent years, there have been improvements in the efficiency of the vehicles, and hybrid techniques that have been used to improve efficiency for conventional combustion vehicles. Hydraulic systems have been used as an alternative to conventional electric regenerative systems with good results. It has been proven that hydraulic systems can improve energy consumption in conventional combustion vehicles and in refuse collection vehicles. The control strategy has a large impact on the performance of the system and studies have shown the control strategy selection should be optimized and selected based on application. The performance of a hydraulic accumulator was compared with the performance of a set of ultracapacitors with the same energy storage capacity. The energy efficiency for the ultracapacitor was around 79% and the energy efficiency of the hydraulic accumulator was 87.7%. The power/mass ratio in the set of ultracapacitors was 2.21 kW/kg and 2.69 kW/kg in the hydraulic accumulator. The cost/power ratio is 217 US$/kW in the ultracapacitors and 75 US$/kW in the hydraulic accumulator. Based on these results, the hydraulic accumulator was selected as the energy storage device for the system. A testbench was designed, modeled, implemented to test the energy storage system in different conditions of operation. The experimental results of the testbench show how system can be actively controlled for different operating conditions. The operating conditions in the system can be adjusted by changing the number of rheostats connected to the electric generator. Different variables in the system were measured such as the angular shaft speed in the hydraulic pump, the torque and speed in the hydraulic motor, the pressure in the system, the flow rate, and the current and voltage in the electric generator. The control algorithm was successfully implemented, the results for the pressure in the system and the angular speed in the electric generator show how the control system can follow a desired reference value. Two different controllers were implemented: one controller for the pressure in the system, and one controller for the speed.

<p dir="ltr">Transportation and energy production industries strongly rely on improvements in gas turbine performance. The quantification of these improvements is dependent on the accuracy of the measurements performed during testing. An increase of 0.5\% in efficiency is sufficient to secure a new development program worth millions of dollars, but in the case of temperature measurements, uncertainties below 0.5 K are required, which presents a challenge. This work selects heat flux estimation and total temperature measurement uncertainties as major contributors for efficiency uncertainty.</p><ul><li>Heat flux measurements are critical to evaluate the impact on the efficiency. Additionally, thermal fatigue in turbine airfoils defines the life cycle of the engine core. This work performs an estimation of the heat transfer via a simplified numerical model that uses infrared (IR) measurements in the surface of the casing to predict the temperature of the passage wall. The model is validated with real cool-down data of the turbine to yield results within a 10\% of the actual temperature.</li><li>Total temperature measurement suffers from errors due to heat transfer effects in the probe. Two dominant sources of errors are convection and conduction between the thermocouple wires, the probe support, and the flow. These effects can be treated in two different categories: the velocity error, created by a non-isentropic reduction of the flow velocity upstream the thermocouple junction, and the thermal equilibrium effects between the junction and the probe support, involving heat transfer through the wire to the shield and the probe stem due to temperature differences between each component (the so-called \emph{conduction error}). An open jet stand is used to evaluate the effects of velocity error at various Mach numbers. The conduction error is addressed with the design and manufacturing of dual-wire thermocouple probes. The readings from two wires with different length-to-diameter ratios are used to correct for the flow total temperature. This probe yielded a recovery factor of 0.99 +/- 0.01 at Mach 0.6.</li></ul><p></p>

<p>One of the most often utilized machinery in fluid power applications is the material-handling machines, which includes telehandlers, forklifts, cranes, and scissor lifts that are used from constructions to mining.<br> Counterbalance valves (CBVs), hydraulic components that protect the system from failures and manage the load under overrunning load conditions due to their distinctive design, are used in material-handling devices to ensure both the operators' and most off-road vehicles' safety. However, they present a significant shortcoming: the over-pressurization of the supply line, which leads to constringent energy consumption. The primary motivation for this work is this drawback. In this work, a CBV-based system with an adjustable pilot has been investigated using a truck-mounted hydraulic crane as a reference machine.</p> <p>By analyzing theoretically and experimentally the behavior of this novel hydraulic system, it is possible to achieve up to 90% of energy-saving than a baseline configuration of a load-holding machine by controlling the opening of the CBV by adjusting the pressure at the pilot stage. After exploring the capabilities of the studied system and the possible control strategies to control opening of the CBV, this work suggests two different solutions to control the system: “Smart CBV” and “Smart System” modes. By properly controlling the signal on the pilot stage of the CBV, "Smart CBV" enables energy savings of up to 80%. On the other hand, the "Smart System" mode can save up to 95% of energy by using the CBV as a meter-out element that successfully regulates the flow to the actuator and, consequently, its velocity. To attain these outstanding results, it is essential to maintain proper system control.</p> <p>Moreover, since safety is one of the priorities of this type of machine, a Condition Monitoring (CM) model is developed to ensure the actual functionalities of the novel proposed system. By identifying faulty conditions and preventing breakdowns before they occur, CM can be utilized to improve the safety of these type of machines. However, training a CM model using experimental data is time-consuming and expensive since it requires abundant data with different extent of machine failures from the field test. The solution suggested in this work is to generate faulty and healthy data for the reference machine using a high-fidelity simulation tool to train a CM model.</p> <p>Particular focus is given to the counterbalance valve (CBV), a crucial element for the hydraulic system of material handling machines, and the linear actuator (hydraulic cylinder). The different types of faults on two elements are modeled with an approach validated using experimental tests. Considering that the simulation model provides comparable outcomes to training on empirical data, the CM model is trained in a single fault condition and multi faults conditions using simulated data. Instead, the CM model is tested using the experimental tests in multiple faulty conditions on the chosen components.</p> <p>Moreover, finding the best CM model for this case study is another goal of this work. As a result, several CM models are investigated: Random Forest (RF), K-Nearest Neighbor (KNN), and Support Vector Machine (SVM). In terms of precision and recall, metrics frequently employed in the CM field to assess the performances of the designed CM model, the results generally indicate more than 90% accuracy.</p>

<p dir="ltr">This project aimed to develop an instrumentation and control system for a micro-drilling robot based on Industrial Internet of Things (IIoT) technologies. The automation system integrated IIoT technological tools to create a robust automation system capable of being used in drilling operations. The system incorporated industrial-grade sensors, which carried out direct measurements of the critical variables of the process. The indirect variables relevant to the control of the robot were calculated from the measured parameters. The system also considered the telemetry architecture necessary to reliably transmit data from the down-the-hole (DTH) robot to a receiver on the surface. Telemetry was based on wireless communication through long-range radio frequency (LoRa). The system developed had models based on Artificial Intelligence (AI) and Machine Learning (ML) for determining the mode of operation, detecting changes in the process, and changes in drilling variables in critical hydraulic components for the drilling process. Algorithms based on AI and ML models also allowed the user to make better decisions based on the variables' correlation to optimize the drilling process (e.g., dynamic change of flow, pressure, and RPMs based on automatic rock identification). A user interface (UI) was developed, and digital tools to perform data analysis were implemented. Safety assessment in all robot systems (e.g., electrical, hardware, software) was contemplated as a critical design component. The result of this research project provides innovative micro-drilling robots with the necessary technological tools to optimize the drilling process. The system made drilling more efficient, reliable, and safe, providing diagnostic and prognostic tools that allowed planning maintenance based on the actual health of the devices. The system that was developed was tested in a test bench under controlled conditions within a laboratory to characterize the system and collect data that allowed ML models' development, training, validation, and testing. The prototype of a micro-drilling robot installed on the test bench served as a case study to assess the implemented models' reliability and the proposed telemetry.</p>