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- Genre: Masters Thesis
- Creators: Phelan, Patrick
Description
A Compact Linear Fresnel Reflector (CLFR) is a simple, cost-effective, and scalable option for generating solar power by concentrating the sun rays. To make a most feasible application, design parameters of the CLFR, such as solar concentrator design parameters, receiver design parameters, heat transfer, power block parameters, etc., should be optimized to achieve optimum efficiency. Many researchers have carried out modeling and optimization of CLFR with various numerical or analytical methods. However, often computational time and cost are significant in these existing approaches. This research attempts to address this issue by proposing a novel computational approach with the help of increased computational efficiency and machine learning. The approach consists of two parts: the algorithm and the machine learning model. The algorithm has been created to fulfill the requirement of the Monte Carlo Ray tracing method for CLFR collector simulation, which is a simplified version of the conventional ray-tracing method. For various configurations of the CLFR system, optical losses and optical efficiency are calculated by employing these design parameters, such as the number of mirrors, mirror length, mirror width, space between adjacent mirrors, and orientation angle of the CLFR system. Further, to reduce the computational time, a machine learning method is used to predict the optical efficiency for the various configurations of the CLFR system. This entire method is validated using an existing approach (SolTrace) for the optical losses and optical efficiency of a CLFR system. It is observed that the program requires 6.63 CPU-hours of computational time are required by the program to calculate efficiency. In contrast, the novel machine learning approach took only seconds to predict the optical efficiency with great accuracy. Therefore, this method can be used to optimize a CLFR system based on the location and land configuration with reduced computational time. This will be beneficial for CLFR to be a potential candidate for concentrating solar power option.
ContributorsLunagariya, Shyam (Author) / Phelan, Patrick (Thesis advisor) / Kwon, Beomjin (Committee member) / Zhuang, Houlong (Committee member) / Arizona State University (Publisher)
Created2021
Description
This thesis work presents two separate studies:The first study assesses standing balance under various 2-dimensional (2D) compliant environments simulated using a dual-axis robotic platform and vision conditions. Directional virtual time-to-contact (VTC) measures were introduced to better characterize postural balance from both temporal and spatial aspects, and enable prediction of fall-relevant directions. Twenty healthy young adults were recruited to perform quiet standing tasks on the platform. Conventional stability measures, namely center-of-pressure (COP) path length and COP area, were also adopted for further comparisons with the proposed VTC. The results indicated that postural balance was adversely impacted, evidenced by significant decreases in VTC and increases in COP path length/area measures, as the ground compliance increased and/or in the absence of vision (ps < 0.001). Interaction effects between environment and vision were observed in VTC and COP path length measures (ps ≤ 0.05), but not COP area (p = 0.103). The estimated likelihood of falls in anterior-posterior (AP) and medio-lateral (ML) directions converged to nearly 50% (almost independent of the foot setting) as the experimental condition became significantly challenging.
The second study introduces a deep learning approach using convolutional neural network (CNN) for predicting environments based on instant observations of sway during balance tasks. COP data were collected from fourteen subjects while standing on the 2D compliant environments. Different window sizes for data segmentation were examined to identify its minimal length for reliable prediction. Commonly-used machine learning models were also tested to compare their effectiveness with that of the presented CNN model. The CNN achieved above 94.5% in the overall prediction accuracy even with 2.5-second length data, which cannot be achieved by traditional machine learning models (ps < 0.05). Increasing data length beyond 2.5 seconds slightly improved the accuracy of CNN but substantially increased training time (60% longer). Importantly, averaged normalized confusion matrices revealed that CNN is much more capable of differentiating the mid-level environmental condition.
These two studies provide new perspectives in human postural balance, which cannot be
interpreted by conventional stability analyses. Outcomes of these studies contribute to the advancement of human interactive robots/devices for fall prevention and rehabilitation.
ContributorsPhan, Vu Nguyen (Author) / Lee, Hyunglae (Thesis advisor) / Peterson, Daniel (Committee member) / Marvi, Hamidreza (Committee member) / Arizona State University (Publisher)
Created2021
Description
This thesis presents a study on the user adaptive variable impedance control of a wearable ankle robot for robot-aided rehabilitation with a primary focus on enhancing accuracy and speed. The controller adjusts the impedance parameters based on the user's kinematic data to provide personalized assistance. Bayesian optimization is employed to minimize an objective function formulated from the user's kinematic data to adapt the impedance parameters per user, thereby enhancing speed and accuracy. Gaussian process is used as a surrogate model for optimization to account for uncertainties and outliers inherent to human experiments. Student-t process based outlier detection is utilized to enhance optimization robustness and accuracy. The efficacy of the optimization is evaluated based on measures of speed, accuracy, and effort, and compared with an untuned variable impedance controller during 2D curved trajectory following tasks. User effort was measured based on muscle activation data from the tibialis anterior, peroneus longus, soleus, and gastrocnemius muscles. The optimized controller was evaluated on 15 healthy subjects and demonstrated an average increase in speed of 9.85% and a decrease in deviation from the ideal trajectory of 7.57%, compared to an unoptimized variable impedance controller. The strategy also reduced the time to complete tasks by 6.57%, while maintaining a similar level of user effort.
ContributorsManoharan, Gautham (Author) / Lee, Hyunglae (Thesis advisor) / Berman, Spring (Committee member) / Xu, Zhe (Committee member) / Arizona State University (Publisher)
Created2023
Description
According to Our World in Data, the industry sector contributes approximately 5.2 percent of the world's greenhouse gas emissions in 2016 [1]. Of that percentage, the cement industry contributes approximately 3 percent, thus accounting for more than 57 percent of all greenhouse gas emissions within the industry sector. Industrial-scale heating that is powered by renewable energy sources has the potential to combat this issue. This paper aims to analyze and model the Reverse Brayton Cycle to be used as a heat pump in a novel cement production system. The Simple Reverse Brayton Cycle and its potential concerning performance indicators such as coefficient of performance and scalability are determined. A Regenerative Brayton cycle is modeled in MATLAB® programming in order to be optimized and compared to conventional processes that require higher temperatures. Traditional manufacturing methods are discussed. Furthermore, possible methods of improvement are explored to view its effect on performance and temperatures between stages within the cycle.
ContributorsRivera, Daniel E (Author) / Phelan, Patrick (Thesis advisor) / Milcarek, Ryan (Committee member) / Calhoun, Ronald (Committee member) / Arizona State University (Publisher)
Created2024
Description
The Endoscopic Submucosal Dissection (ESD) method is increasingly becoming the method of choice for surgeons attempting to remove precancerous and early-stage cancerous lesions in the lining of the Gastrointestinal (GI) tract. Being an endoscopic procedure, it is less invasive than most other procedures used for tumor removal. However, this procedure has a steep learning curve and a high number of surgical complications. The primary reason for this is the limited ability of the surgeon to retract mucosal (stomach lining) tissue while they dissect under it. Unlike in traditional surgery, the surgeon lacks a second hand to leverage tissue during dissection in endoscopic procedures. This study proposed the deployment of an endoscopic clip to the surface of the lesion. The clip had a permanent magnet connected to it. In addition, a large permanent external magnet mounted to the end-effector of a robotic arm was positioned above the magnetic clip to pull the internal magnet and retract tissue. Magnetic Force simulations were conducted in the design processes for the magnets to determine whether sufficient force for tissue retraction was being achieved. The use of fiber optic shape sensors to track and localize the internal magnet was also explored. Experimental validations of the external and internal magnet designs as well as tracking of the internal magnet were performed in surgical trials on ex-vivo and live porcine models. Compared to traditional ESD, the use of magnetic retraction in ESD significantly improved tissue exposure for dissection, decreased the required time for the dissection stage of the ESD procedure, and reduced the incidence of surgical complications. Therefore, this technology holds substantial potential for enhancing ESD procedures, advancing the non-invasive treatment of colorectal cancer, and potentially improving patient outcomes significantly.
ContributorsAskari, Tabsheer Ali (Author) / Marvi, Hamidreza (Thesis advisor) / Lee, Hyunglae (Committee member) / Xu, Zhe (Committee member) / Arizona State University (Publisher)
Created2024
Description
The objective of this thesis is to propose two novel interval observer designs for different classes of linear and hybrid systems with nonlinear observations. The first part of the thesis presents a novel interval observer design for uncertain locally Lipschitz continuous-time (CT) and discrete-time (DT) systems with noisy nonlinear observations. The observer is constructed using mixed-monotone decompositions, which ensures correctness and positivity without additional constraints/assumptions. The proposed design also involves additional degrees of freedom that may improve the performance of the observer design. The proposed observer is input-to-state stable (ISS) and minimizes the L1-gain of the observer error system with respect to the uncertainties. The observer gains are computed using mixed-integer (linear) programs. The second part of the thesis addresses the problem of designing a novel asymptotically stable interval estimator design for hybrid systems with nonlinear dynamics and observations under the assumption of known jump times. The proposed architecture leverages mixed-monotone decompositions to construct a hybrid interval observer that is guaranteed to frame the true states. Moreover, using common Lyapunov analysis and the positive/cooperative property of the error dynamics, two approaches were proposed for constructing the observer gains to achieve uniform asymptotic stability of the error system based on mixed-integer semidefinite and linear programs, and additional degrees of freedom are incorporated to provide potential advantages similar to coordinate transformations. The effectiveness of both observer designs is demonstrated through simulation examples.
ContributorsDaddala, Sai Praveen Praveen (Author) / Yong, Sze Zheng (Thesis advisor) / Tsakalis, Konstantinos (Thesis advisor) / Lee, Hyunglae (Committee member) / Arizona State University (Publisher)
Created2023
Description
Solid Oxide Fuel Cells (SOFCs) generate electricity using only hydrogen and oxygen and they form H2O as the only byproduct, giving them the potential to significantly reduce carbon emissions and the impacts of global warming. In order to meet the global power demands today, SOFCs need to significantly increase their power density and improve robustness in startup and cycling operations. This study explores the impact of decreasing the anode thickness to improve the mass transport of the fuel through the anode of a micro-tubular (mT) SOFC because few studies have reported the correlation between the two. Decreasing the thickness decreases the chance for concentration overpotential which is caused by not enough of the reactants being able to reach the reaction site while products are not able to be removed quickly enough. Experiments were performed in a split tube furnace heated to 750°C with nickel-yttria stabilized zirconia (Ni-YSZ) supported cells. Pure hydrogen was supplied to the cell at rates of 10, 20, 30, and 40 mL/min while the cathode was supplied air from the environment. The cell's performance was studied using the current-voltage method to generate polarization curves and electrochemical impedance spectroscopy to create Bode and Nyquist plots. The results from the electrochemical impedance spectroscopy show a lower impedance for the frequencies pertaining to the gas diffusion in the anode for the thinner cells. This suggests that decreasing the anode thickness increases the mass transport of the gas. Additionally, through a distribution of relaxation times (DRT) analysis, the peaks vary between the two cell thicknesses at the frequencies pertaining to gas diffusion in anode-supported cells, implicating the decreased resistance created by thinning the anode layer.
ContributorsPhillips, Kristina (Author) / Milcarek, Ryan (Thesis advisor) / Wang, Robert (Committee member) / Phelan, Patrick (Committee member) / Arizona State University (Publisher)
Created2023
Description
Chronic ankle instability (CAI) is caused by the failure to seek treatment and rehabilitation after an acute ankle sprain. Typically, clinical assessment of ankle sprains is done under unloaded conditions, despite the fact that ankle sprains occur during weight loading. Characterization of ankle stiffness, a representation of ankle stability during weight loading, is crucial to quantify ankle stability. Patients with CAI suffer from gait asymmetry, and the descriptions of the asymmetry ratio vary widely throughout the research community. Bilateral ankle stiffness could be a systematic metric to describe the gait asymmetry of CAI patients. Additionally, women generally have higher ankle joint and ligamentous laxity than men, and lower ankle stiffness, which has been thoroughly investigated in previous literature. However, differences in bilateral ankle stiffness between sexes still need to be investigated. Using twin dual-axis robotic platforms, this study investigated the weight loading effect on ankle stiffness in the frontal plane during standing, the bilateral difference in stiffness between the dominant and non-dominant ankle, and the sex difference in bilateral ankle stiffness during standing for varying weight distribution. The group average results of 20 healthy subjects showed that ankle stiffness increased with increasing weight loading on the ankle, which is speculated to be caused by active muscle contraction and changes in passive structure due to weight loading. For the bilateral difference of the group, the statistical analysis showed that there was no significant difference between dominant and non-dominant ankle stiffness for all the weight distributions considered. Although the group average result of the difference in bilateral ankle stiffness was statistically insignificant, individual analysis confirmed the importance of subject-specific investigation of bilateral ankle stiffness, as there were more cases of dominant ankle stiffness being larger than non-dominant ankle stiffness, and the bilateral difference was subject-specific. Investigations into sex differences in bilateral ankle stiffness showed that ankle stiffness in males is significantly greater than in females, even after normalizing the stiffness by weight, which is speculated to be caused by higher joint and ligamentous laxity in females regardless of laterality.
ContributorsPaing, Soe Lin (Author) / Lee, Hyunglae (Thesis advisor) / Berman, Spring (Committee member) / Peterson, Daniel (Committee member) / Arizona State University (Publisher)
Created2023
Description
This study introduces a new outdoor accelerated testing method called “Field Accelerated Stress Testing (FAST)” for photovoltaic (PV) modules performed at two
different climatic sites in Arizona (hot-dry) and Florida (hot-humid). FAST is a combined
accelerated test methodology that simultaneously accounts for all the field-specific stresses
and accelerates only key stresses, such as temperature, to forecast the failure modes by 2-
7 times in advance depending on the activation energy of the degradation mechanism (i.e.,
10th year reliability issues can potentially be predicted in the 2nd year itself for an
acceleration factor of 5). In this outdoor combined accelerated stress study, the
temperatures of test modules were increased (by 16-19℃ compared to control modules)
using thermal insulations on the back of the modules. All other conditions (ambient
temperature, humidity, natural sunlight, wind speed, wind direction, and tilt angle) were
left constant for both test modules (with back thermal insulation) and control modules
(without thermal insulation). In this study, a total of sixteen 4-cell modules with two different construction types (glass/glass [GG] and glass/backsheet [GB]) and two different encapsulant types (ethylene
vinyl acetate [EVA] and polyolefin elastomer [POE]), were investigated at both sites with
eight modules at each site (four insulated and four non-insulated modules at each site). All
the modules were extensively characterized before installation in the field and after field
exposure over two years. The methods used for characterizing the devices included I-V
(current-voltage curves), EL (electroluminescence), UVF (ultraviolet fluorescence), and
reflectance. The key findings of this study are: i) the GG modules tend to operate at a higher temperature (1-3℃) than the GB modules at both sites of Arizona and Florida (a lower
lifetime is expected for GG modules compared to GB modules); ii) the GG modules tend
to experience a higher level of encapsulant discoloration and grid finger degradation than
the GB modules at both sites (a higher level of the degradation rate is expected in GG
modules compared to GB modules); and, iii) the EVA-based modules tend to have a higher
level of discoloration and finger degradation compared to the POE-based modules at both
sites.
ContributorsThayumanavan, Rishi Gokul (Author) / Tamizhmani, Govindasamy (Thesis advisor) / Phelan, Patrick (Thesis advisor) / Calhoun, Ronald (Committee member) / Arizona State University (Publisher)
Created2023
Description
Mechanical impedance is a concept that is used to model biomechanical propertiesof human joints. These models can then be utilized to provide insight into the inner
workings of the human neuromuscular system or to provide insight into how to best
design controllers for robotic applications that either attempt to mimic capabilities of
the human neuromuscular system or physically interact with it. To further elucidate
patterns and properties of how the human neuromuscular system modulates mechanical
impedance at the human ankle joint, multiple studies were conducted. The first
study was to assess the ability of linear regression models to characterize the change
in stiffness - a component of mechanical impedance - seen at the human ankle during
the stance phase of walking in the Dorsiflexion-Plantarflexion (DP) direction. A
collection of biomechanical variables were used as input variables. The R^2 value of
the best performing model was 0.71. The second and third studies were performed to
showcase the ability of a newly developed twin dual-axis platform, which goes beyond
the limits of a single dual-axis platform, to quantify bilateral stiffness properties. The
second study quantified the bilateral mechanical stiffness of the human ankle joint
for healthy able-bodied subjects during the stance phase of walking and during quiet
standing in both the DP and inversion-eversion directions. Subjects showed a high
level of subject specific symmetry. Lastly, a similar bilateral ankle characterization
study was conducted on a set of subjects with multiple sclerosis, but only during
quiet standing and in the DP direction. Results showed a high level of discrepancy
between the subject’s most-affected and least-affected limbs with a larger range and
variance than in the healthy population.
ContributorsRussell, Joshua (Author) / Lee, Hyunglae (Thesis advisor) / Honeycutt, Claire (Committee member) / Marvi, Hamid (Committee member) / Arizona State University (Publisher)
Created2022