Mechanical Engineering Theses and Dissertations

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    (2023) Elsibaie, Sherief; Ayyub, Bilal M.; Reliability Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    The North American railroad system can be well represented by a network with 302,943 links (track segments) and 250,388 nodes (stations, junctions, and waypoints), and other points of interest based on publicly accessible geographical information obtained from the Bureau of Transportation Statistics (BTS) and the Federal Railroad Administration (FRA). From this large network a slightly more consolidated subnetwork representing the major freight railroads and Amtrak was selected for analysis. Recent improvements in network and graph theory and improvements in all-pairs shortest path algorithms make it more feasible to process certain characteristics on large networks with reduced computation time and resources. The characteristics of networks at issue to support network-level risk and resilience studies include node efficiency, node eccentricity, and other attributes derived from those measures, such as network arithmetic efficiency, network geometric central node, radius, and diameter, and some distribution measures of the node characteristics. Rail distance weighting factors, representing the length of each rail line derived from BTS data, are mapped to corresponding links, and are used as link weights for the purpose of computing all pair shortest paths and subsequent characteristics. This study also compares the characteristics of North American railroad infrastructure subnetworks divided by Class I carriers, which are the largest railroad carriers classified by the Surface Transportation Board (STB) by annual operating revenue, and which together comprise most of the North American railroad network. These network characteristics can be used to inform placement of resources and plan for natural hazard and disaster scenarios. They relate to many practical applications such as network efficiency to distribute traffic and a network’s ability to recover from disruptions. The primary contribution of this thesis is the novel characterization of a detailed network representation of the North American railroad network and Class I carrier subnetworks, with established as well novel network characteristics.
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    (2023) Gandikota, Ibaad; McCluskey, Francis Patrick; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Silicone encapsulations are widely used in high-temperature electronic applications, providing excellent properties like thermal stability, high purity, and chemical resistance. However, silicone is susceptible to moisture-induced failures due to high moisture permeability. This study mainly focuses on improving the moisture ingression characteristics of the silicone encapsulation by adding a polyurethane moisture barrier layer. This study focuses on the effects of moisture ingression by adding polyurethane and testing with embedded relative humidity sensors at different environmental conditions. The diffusivity of both the bi-layered composites and the pure encapsulation materials was assessed using two distinct experimental methods for the calculation of diffusivity based on the principles of 1-dimensional Fick's law of diffusion. The diffusivities were statistically analyzed to determine significant differences between the samples, and the experiment yielded a minimum of 65% reduction in diffusivity across the samples. Furthermore, a thermomechanical analysis was performed on two different GaN power MOSFETs by the application of different underfill and potting encapsulations to determine stresses and strains on the solder bumps.
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    (2023) Gigioli, Samuel George; Gupta, Ashwani K; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    This work presents the progress towards a mathematical modeling of the Arnold Engineering Development Complex (AEDC) Wind Tunnel 9 control law during the blow phase of a given tunnel run, composing of electrical analog physics, ideal gas control volume physics, incompressible fluid mechanics, and force balance kinematics. This work is unique to Tunnel 9 and unique in respect to other works, as no other existing models of the current control law exist. The primary goal of this work is to provide enhanced support to the Tunnel 9 engineers with the ability to model different run conditions. Key facility measurements can be estimated, aiding in the determination if proposed non-standard run conditions will meet or maintain the facility capabilities, and if the facility can be operated under safe operating limits. The secondary goal of this model is to progress toward a digitally controlled valve system to replace the current analog system. Such will help provide advantages in the facility (1) performance, (2) health monitoring, (3) maintainability, and (4) sustainment.
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    (2023) Patel, Mital; McCluskey, Patrick; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Within our increasingly digital world, there is a demand to integrate electronics into every industry to take advantage of applications in communication, optimization, and artificial intelligence. Relatively untapped areas for electronics implementation are the extreme environments where high temperatures (>300°C) are present. These environments are common within energy, automotive, and aerospace industry es. Current high temperature technologies limit reliable use of electronics to ~200°C. Emerging technologies, such as transient liquid phase (TLP) bonding, copper sintering, and thick films, have not yet demonstrated resilient operation above 300°C. Possessing various remarkable properties, diamond is a promising material that can be used in manufacturing electronic devices operable well above 500°C. Graphene and graphite additionally can serve as conductive material for circuitry or other electronic elements. The compatibility and versatility of these three materials demonstrate the potential for robust, all-carbon electronics for high temperature applications. Chemical vapor deposition (CVD), the predominant method of synthesizing diamond for electronics, involves very costly, long processes at extreme temperatures. A relatively underdeveloped, alternative method utilizes the pyrolysis of polymer precursors into diamond. This study aims to further explore this method using Poly(naphthalene-co-hydridocarbyne) (PNHC). The polymer synthesis, processing, and pyrolysis have been performed here, and the process parameters and outcomes at each step have been documented. Native graphite and graphene growth on diamond surfaces allows for the integration of conductive material on insulating diamond. Four known methods of diamond graphitization, assisted with the metal catalysts nickel, copper, and iron, have also been applied to support the fabrication of carbon-based electronics. Ultimately in this study, the synthesis of diamond has been unsuccessful, but multi-layer graphene has been grown on polycrystalline diamond with high sheet carrier concentration and mobility values of 1.0*1015 cm-2 and 629.1 cm2 Vs-1, respectively.
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    Dynamic Control of Dexterous Soft Robotic Systems
    (2023) Weerakoon, Weerakoon Mudiyanselage Lasitha Tharinda; Chopra, Nikhil; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Soft robotics has grown exponentially during the past two decades due to the possibility of expanded manipulation capabilities over existing rigid robots in complex, unstructured environments. Additionally, soft robots can mitigate current safety risks associated with rigid robots due to their softness. The inspiration for soft robotics has been mainly due to the many examples from nature, such as the agile environmental interactions of the elephant trunk and octopus tentacles. Over the past two decades, several applications ranging from underwater operations to minimally invasive surgeries to space operations have been identified for soft robots. Motivated by these, the overall objective of this dissertation is to study and develop control frameworks for high-fidelity motion control of soft robotic systems. This entails exploiting generalized dynamics models for robust/adaptive control strategies for achieving various operational tasks involved in non-ideal environments, utilizing integrated sensing technologies, and investigating control of underactuated soft robotic systems. This dissertation delve into passivity-based adaptive task space control for soft robots, mitigating uncertainty in the parameters as accurate parameter estimation is particularly hard in soft robotic systems. Further, this approach is extended to task space bilateral teleoperation of a soft follower-rigid leader system exploiting null space velocity tracking to achieve sub-task goals such as conforming to the degree of curvature limits in the soft robot. An enhanced dynamics model is also introduced tailored for planar soft robots and elaborate on passivity-based robust control methods for task space trajectory tracking within this context. This enhanced dynamics model is subsequently extended to encompass 3D spatial soft robots and a comprehensive framework for passivity-based robust task space bilateral teleoperation is discussed. Extensive numerical simulations and experiments are conducted to illustrate the efficacy of these proposed control frameworks. Moreover, to deploy soft robots in the real world, this dissertation study integrated sensing and control of soft robots and a stretchable soft-sensing skin for proprioception s introduced. The mapping from the strain signal to the curvature degree is estimated using a recurrent neural network. Further, an adaptive control framework for curvature tracking is proposed, leveraging the soft stretchable sensing skins and providing experimental evidence of its successful application. This dissertation also introduces a novel robotic system known as the hybrid rigid-soft robot, composed of serially attached rigid and soft links, offering a fusion of the dexterity inherent to soft robots with the precision and payload capacity associated with rigid counterparts. Notably, the study demonstrates that well-established passivity-based adaptive and robust control techniques can effectively apply to this unique class of robots. A soft inverted pendulum with a revolute base is also introduced, establishing a scientific foundation and a methodological approach for introducing innovative soft robots in various practical applications. An energy-based controller is discussed for the swing-up and stabilization of the soft inverted pendulum system, highlighting the efficacy of the controller through simulations. Further, a comprehensive control architecture is developed for the swing-up and stabilization of a class of underactuated mechanical systems, including the soft inverted pendulum, by applying output partial feedback linearization and linear control techniques that avoid switching between controllers. The utility of this control architecture is illustrated using numerical simulations on the soft inverted pendulum. These research endeavors collectively contribute to advancing the understanding of soft robotics and developing effective control strategies for various dexterous soft robotic systems.
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    (2023) Smith, Gabriel Lewis; Bergbreiter, Sarah; Sochol, Ryan; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Direct Laser Write (DLW) through two-photon polymerization (2PP) empowers us to delveinto the realm of genuine three-dimensional design complexity for microsystems, enabling features smaller than a single micrometer. This dissertation develops two novel fabrication processes that leverage DLW for functional fluidic microsystems. In the first process, we are inspired by arachnids that use internal hemolymph pressure to actuate extension in one or more of their leg joints. The inherent large foot displacement-to-body length ratio that arachnids can achieve through hydraulics relative to muscle-based actuators is both energy and volumetrically efficient. Until recent advances in nano/microscale 3-D printing with 2PP, the physical realization of synthetic complex ‘soft’ joints would have been impossible to replicate and fill with a hydraulic fluid into a sealed sub-millimeter system. This dissertation demonstrates the smallest scale 3D-printed hydraulic actuator 4.9 × 10^−4 mm^3 by more than an order of magnitude. The use of stiff 2PP polymers with micron-scale dimensions enable compliant membranes similar to exoskeletons seen in nature without the requirement for low-modulus materials. The bio-inspired system is designed to mimic similar hydraulic pressure-activated mechanisms in arachnid joints utilized for large displacement motions relative to body length. Using variations on this actuator design, we demonstrate the ability to transmit forces with relatively large magnitudes (milliNewtons) in 3D space, as well as the ability to direct motion that is useful towards microrobotics and medical applications. Microscale hydraulic actuation provides a promising approach to the transmission of large forces and 3D motions at small scales, previously unattainable in wafer-level 2D microelecromechanical systems (MEMS). The second fabrication process focuses on incorporating functionality through the use of liquid metals in 3D DLW structures. Room temperature eutectic Gallium Indium (eGaIn)- based liquid metal devices with stretchable, conductive, and reconfigurable behavior show great promise across many areas of technology, including robotics, communications, and medicine. Microfluidics provide one means of creating eGaIn devices and circuits, but these devices are typically limited to larger feature sizes. Developments in 3D printing via DLW have enabled sub-100 µm complex microfluidic devices, though interfacing microfluidic devices manufactured with DLW to larger millimeter-scale systems is difficult. The reduced channel diameter creates challenges for removing resist from the channels, filling microchannels with eGaIn, and electrically integrating them to larger channels or other circuitry. These challenges have prevented microscale liquid metal devices from being used more widely. In this dissertation, we demonstrate a facile, low-cost multiscale process for printing DLW microchannels and devices onto centimeter-scale custom fluidic channel substrates fabricated via stereolithography (SLA). This work demonstrates a robust interface between the two independently printed materials and greatly simplifies the filling of eGaIn microfluidic channels down to 50 µm in diameter, with the potential to achieve even smaller feature sizes of liquid metals. This work also demonstrates eGaIn coils with resistance of 43-770 mΩ and inductance of 2-4 nH. As a result, this process empowers us to manufacture interfaces that are not only low-temperature but also conductive and flexible. These interfaces find their application in connecting with sensors, actuators, and integrated circuits, thereby opening new avenues in the field of 3D electronics. Furthermore, our approach extends the lower limits of size-dependent properties for passive electronic components like resistors, capacitors, and inductors crafted from liquid metal, expanding the frontiers of possibilities in miniature electronic design.
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    (2023) RAY, UPAMANYU; Li, Teng; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Cellulose, the abundantly available natural biopolymer, has the potential to be a next generation wonder material. The motivation behind this thesis stems from the efforts to obtain mechanical properties of two novel cellulose-based materials, which were fabricated using top-down (densified engineered wood) and bottoms-up (graphite-cellulose composite) approaches. It was observed that the mechanical properties of both the engineered wood (strength~596 MPa; toughness ~3.9 MJ/m3) and cellulose-graphite composite (strength~715 MPa; toughness ~27.7 MJ/m3) surpassed the equivalent features of other conventional structural materials (e.g., stainless steel, Al alloys etc.). However, these appealing properties are still considerably inferior to individual cellulose fibrils whose diameters are in the order of nanometers. A significant research effort needs to be initiated to effectively transfer the mechanical properties of the hierarchical cellulose fibers from the atomistic level to the continuum. To achieve that, a detailed understanding of the interplay of cellulose molecular chains that affects the properties of the bulk cellulosic material, is needed. Modeling investigations can shed light on such underlying mechanisms that ultimately dictate multiple properties (e.g., mechanics, thermal transport) of these cellulosic materials. To that end, this thesis (1) applies molecular dynamics simulations to decipher why microfibers made of aligned nanocellulose and carbon nanotubes possess excellent mechanical strength, along with understanding the role of water in fully recovering elastic wood under compression; (2) delineates an atomistically informed multi-scale, scalable, coarse grained (CG) modeling scheme to study the effect of cellulose fibers under different representative loads (shearing and opening), and to demonstrate a qualitative guideline for cellulose nanopaper design by understanding its failure mechanism; (3) utilizes the developed multi-scale CG scheme to illustrate the reason why a hybrid biodegradable straw, experimentally fabricated using both nano- and micro-fibers, exhibits higher mechanical strength than individual straws that were built using only nano or microfibers; (4) investigates the individual role of nanocellulose and boron nitride nanotubes in increasing the mechanical properties (tensile strength, stiffness) of the derived nanocellulose/boron-nitride nanotube hybrid material; (5) employs reverse molecular dynamics approach to explore how the boron nitride nanotube based fillers can improve thermal conductivity (k) of a nanocellulose derived material. In addition, this thesis also intends to educate the readers on two perspectives. The common link connecting them is the method of engineering intermolecular bonds. The first discussion presents a few novel mechanical design strategies to fabricate high-performance, cellulose-based functional materials. All these strategies are categorized under a few broad themes (interface engineering, topology engineering, structural engineering etc.). Another discussion has been included by branching out to other materials that, like nanocellulose, can also be tuned by intermolecular bonds engineering to achieve unique applications. Avenues for future work have been suggested which, hopefully, can act as a knowledge base for future researchers and help them formulate their own research ideas. This thesis extends the fundamental knowledge of nanocellulose-based polymer sciences and aims to facilitate the design of sustainable and programmable nanomaterials.
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    (2023) Nave, Gilad; McCluskey, Patrick; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    The growing demands of electrification are driving research into new electronic materials. These electronic materials must have high electrical conductivity, withstand harsh environments and high temperatures and demonstrate reliable solutions as part of complete electronic packaging solutions. This dissertation focuses on characterizing the initial stage of the manufacturing process of Transient Liquid Phase Sinter (TLPS) alloys in a paste form as candidates for Pb-free high-temperature and high-power electronic materials.The main objective of this dissertation work is to investigate the factors and decouple the multiple cross effects occurring during the first stage of TLPS processing in order to improve the understanding of material evolution. The work proposes, develops, and conducts in-situ electrical resistivity tests to directly measure material properties and analyze the dynamics at different stages of the material's evolution. The research explores various factors, including alloying elements, organic binders, and heating rates, to understand their effects on the development of electrical performance in electronic materials. More specifically, the work examines the performance of Ag-In, Ag-Sn and Cu-Sn TLPS paste systems. Additionally, packing density and changes in cross-section are investigated using imaging techniques and image processing to gain insights into the early formation of the material's structural backbone. An Arrhenius relationship together with Linear Mixed Models (LMM) techniques are used to extract the activation energies involved with each of the processing stages. The study then develops procedures to model different states of the TLPS microstructures at different heating stages based on experimentally observed data. Using these models, the study uses Finite Element Method (FEM) analysis to verify the experimental results and gain a better understanding and visualization into the involved mechanisms. This investigation not only sheds light on the material's behavior but also has implications for robust additive manufacturing (AM) applications.
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    (2023) Knight, Ryan; DeVoe, Don L; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    A quadruple mass Microelectromechanical System (MEMS) Coriolis vibratory gyroscope has been re-engineered with the singular focus of minimizing nonlinear transduction mechanisms, thereby allowing for angle random walk (ARW) noise reduction when operating at amplitudes higher than 2 μm. The redesign involved six primary steps: (i) the creation of an aspect-ratio independent deep reactive ion etch with minimal notching on 100 μm thick silicon-on-insulator device layer, (ii) the creation of micro-torr vacuum packaging capability, enabling operation at the thermoelastic dissipation limit of silicon, (iii) the redesign of Coriolis mass folded flexures and shuttle springs, (iv) the linearization of the antiphase coupler spring rate while maintaining parasitic modal separation, (v) the substitution of parallel plate transducers with linear combs, and (vi) the implementation of dedicated force-balanced electrostatic frequency tuners. Cross-axis stiffness is also reduced through folded-flexure moment balancing to further reduce ARW. By balancing positive and negative Duffing frequency contributions, net fractional frequency nonlinearity was reduced to -20 ppm. The gyroscope presented in this research has achieved, a first reported of its kind, an ARW of 0.0005 °/√hr, with an uncompensated bias instability of 0.08 °/hr. These advancements hold promise for enhancing navigation and North-finding applications. In tandem with gyroscope performance enhancements, vacuum packaging of ceramic chip carrier physics packages has achieved pressure levels below 1 micro-torr, a first in the field and remains state-of-the-art. Besides high-performance MEMS inertial sensors, ultrahigh vacuum packaging proves beneficial for chip scale atomic clocks, which require micro-torr vacuum levels to maintain fractional frequencies less than 10^-12. Finally, an approach to tuning the quality factor mismatch between degenerate modes in as-fabricated gyroscopes has demonstrated a reduction in gyroscope bias instability. This tuning can be achieved by incorporating lead zirconate titanate into regions where the trade-off between mechanical Q, tuning Q, and bias instability reduction is balanced. Both modeling and empirical frequency data justify this approach, suggesting, for typical MEMS foundry Q mismatch of 7%, a 70× reduction in bias instability.
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    Direct Laser Writing-Enabled Microstructures with Tailored Reflectivity for Optical Coherence Tomography Phantoms
    (2023) Fitzgerald, Declan Morgan; Sochol, Ryan D; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    As the continuous push to improve medical imaging techniques produces increasingly complex systems, so too must the phantoms critical to the accurate evaluation of these systems evolve. The inclusion of precise geometries is a well documented gap in optical coherence tomography (OCT) phantoms, a gap felt more severely as the technology improves. This thesis seeks to investigate the feasibility of utilizing new manufacturing techniques in the production of OCT phantoms with complex geometries while developing a phantom to determine the sensitivity of OCT systems. The new manufacturing methods include the replication of microstructures printed via direct laser writing into PMMA photoresist, the tailored smoothing of surface roughness inherent to direct laser writing, and the selective retention of surface roughness in certain regions. Each of these methods were implemented in the manufacture of an OCT sensitivity phantom and were found to be effective in each of their respective goals.The efficacy of the sensitivity phantom in evaluating the minimum reflectance still detectable by an OCT system shows promise. Effective reflectivity ranging from 0 to ~1 was accomplished within a single angled element and should provide a basis for determining the minimum reflectivity that results in a signal-to-noise ratio of 1. Further improvements must be made to the phantom footprint and manufacturing before the phantom’s reliability is certain.
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    (2023) Zhang, Xiguang; Duncan, James; Liu, Xinan; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    The effects of temperature and surfactant on secondary droplets produced by the impact of raindrops on water surface were experimentally studied in a rain facility that consists of a rain generator and a deep water pool. The rain generator is a 0.9 m × 0.6 m rectangular tank with 360 hypodermic needles mounted on its bottom. A constant water height is maintained in the tank to obtain a constant dripping rate of raindrops from the needles. The rain generator is placed 2.2 meters above the water pool that is 1.22 m long by 1.22 m wide with a water depth of 0.31 m. A circular motion of the rain generator varies the impact locations of the raindrops on the water surface.Both the raindrops and secondary droplets are measured with an in-line holographic technique that employs a collimated laser beam and a high-speed camera. The diameters and two-dimensional positions of the raindrops and secondary droplets were first reconstructed in each holographic image using a GPU-based holographic reconstruction algorithm. Then an in-house particle tracking code was implemented to compute their diameters, trajectories and instantaneous velocities. The measurement data shown in this thesis was taken at 9.5 cm above the water surface of the pool. In this study, the effects of temperature and surface tension on the production of the secondary droplets were examined separately. When studying the temperature effect, the temperature of the water in the rain generator varied from 7 degrees Celsius to 20 degrees Celsius (room temperature) while the water temperature in the pool was maintained at room temperature. When studying the surface tension effect, certain amounts of soluble surfactant (Triton X-100) was added into the water pool to vary the surface tension from 40 mN/m to 73 mN/m, while the rain water is kept clean with a surface tension of 73 mN/m. It is found that both the rain temperature and the surface tension of the water pool have an impact on the production of secondary droplets. The temperature of the rain could change the viscosity by more than 40%, therefore resulting in a significant difference in the number and the size distribution of the production of secondary droplets. On the other hand, while the surface tension of the water pool does not heavily influence the number of secondary droplets, it does contribute to a difference in size distributions of these droplets at around R = 120 μm.
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    (2023) Sangepu, Lokesh; Das, Diganta; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Electronic part manufacturers often provide reliability values in metrics such as Mean Time Between Failures (MTBF) and its inverse, Failures in Time (FIT). These metrics assume a constant failure rate and do not account for damage accumulation or wear-out phenomena, making the part selection and management based on this information meaningless.This thesis will report on the challenges associated with manufacturers' avoidance of sharing critical part information and how insufficient information hampers decision-making for part selection. The thesis uses four die-level failure mechanisms (Electromigration, Time-Dependent Dielectric Breakdown, Hot Carrier Injection, and Negative Bias Temperature Instability) as demonstration cases. It investigates the extent to which industry-published documents can be used to obtain the data necessary to simulate these mechanisms. It will report on methods of selecting an appropriate failure model based on the part technology level and identifying the required parameters for estimating the part's time to failure. Various scattered part information sources, literature, and industry-published documents may include the input parameters of failure models. The thesis provides insights into the complexity of understanding these information sources and various methods to obtain the required parameters to estimate the time to failure distributions. The methodology considers the susceptibility of parts to die-level failure mechanisms and compares components for reliability. A simulation template that facilitates practical implementation by enabling designers, engineers, and procurement teams to make informed decisions while selecting electronic parts for specific applications is introduced. The research findings and methodology presented provide valuable insights for users to improve the reliability and performance of electronic systems through effective part selection.
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    (2023) Kamrah, Eesh; Fuge, Mark D; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Design researchers have struggled to produce quantitative predictions for exactly why andwhen diversity might help or hinder design search efforts. This thesis addresses that problem by studying one ubiquitously used search strategy—Bayesian Optimization (BO)—on different ND test problems with modifiable convexity and difficulty. Specifically, we test how providing diverse versus non-diverse initial samples to BO affects its performance during search and introduce a fast ranked-DPP method for computing diverse sets, which we need to detect sets of highly diverse or non-diverse initial samples. We initially found, to our surprise, that diversity did not appear to affect BO, neither helping nor hurting the optimizer’s convergence. However, follow-on experiments illuminated a key trade-off. Non-diverse initial samples hastened posterior convergence for the underlying model hyper-parameters—a Model Building advantage. In contrast, diverse initial samples accelerated exploring the function itself—a Space Exploration advantage. Both advantages help BO, but in different ways, and the initial sample diversity directly modulates how BO trades those advantages. Indeed, we show that fixing the BO hyper-parameters removes the Model Building advantage, causing diverse initial samples to always outperform models trained with non-diverse samples. These findings shed light on why, at least for BO-type optimizers, the use of diversity has mixed effects and cautions against the ubiquitous use of space-filling initializations in BO. To the extent that humans use explore-exploit search strategies similar to BO, our results provide a testable conjecture for why and when diversity may affect human-subject or design team experiments. The thesis is organized as follows: Chapter 2 provides an overview of existing studies that explore the impact of different initial stimuli. In Chapter 3, we explain the methodology used in the subsequent experiments. Chapter 4 presents the results of our initial study on the diverse initialization of BO (Bayesian Optimization) applied to the wildcat wells function. In this chapter we also investigate the conditions under which less diverse initial examples perform better and expand on these findings in Chapter 5 by considering additional ND continuous functions. The final chapter discusses the limitations of our findings and proposes potential areas for future research.
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    In-situ investigation of lithium dendrite growth and its interactions with a polymer separator in a lithium metal cell
    (2023) Kong, Lingxi; Pecht, Michael; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Lithium dendrites are metallic structures that initiate and grow inside a lithium battery duringcharging. Lithium dendrite growth can negatively affect battery cycle life and safety. Observing the dendrite growth process and revealing its interaction with other components is necessary to improve battery safety. This study uses a transparent optical cell to directly observe the dendrite growth process, explore the lithium dendrite growth modes under various current densities, evaluate the interactions between the dendrite and separator, and explore the effect of electrolyte additives on dendrite growth behavior. The dendrite growth under different current densities showed the transition of dendrite morphologies from a dense structure to a porous structure. The examination of the dendrite-separator interaction regions showed that dendrites can deform and penetrate the separator. We show that additives can enhance the uniformity of lithium dendrite distribution compared with the dendrite formed in the electrolyte without additives.
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    Measurement of Effective Cure Shrinkage of Epoxy Molding Compound and Induced In-line Warpage during Molding Process
    (2023) Kim, Changsu; Han, Bongtae; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Cure shrinkage accumulated only after the gel point is known as effective cure shrinkage (ECS), which produces residual stresses inside molded components. The ECS of an epoxy-based molding compound (EMC) is measured by an embedded fiber Bragg grating (FBG) sensor. Under a typical molding condition, a high mold pressure inherently produces large friction between EMC and mold inner surfaces, which hinders EMC from contracting freely during curing. A two-stage curing process is developed to cope with the problem. In the first stage, an FBG sensor is embedded in EMC by a molding process, and the FBG-EMC assembly is separated from the mold at room temperature. The molded specimen is heated to a cure temperature rapidly in the second stage using a constraint-free curing fixture. The ECS of an EMC with a filler content of 88 wt% is measured by the proposed method, and its value is 0.077%. The measured ECS can be used to predict the warpage caused by molding processes. The validity of the prediction can be verified only by measuring the warpage during molding. A point-based measurement technique utilizing uniquely-generated multiple beams and binarization-based beam tracing method is developed to cope with the challenges associated with the warpage measurement during molding. The proposed method is implemented successfully to measure the warpage of a bimaterial disk that consists of aluminum and EMC as a function of time during molding process. Measurements are repeated to establish the measurement accuracy of the proposed method.
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    (2023) Klein, Ellery; Radermacher, Reinhard; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Air-to-refrigerant heat exchangers are a key component for heating, ventilation, air conditioning, and refrigeration (HVAC&R) systems. The performance of these heat exchangers is limited by their air-side thermal resistance. Finless non-round bare tube designs have the potential to improve the air-side thermal-hydraulic performance over their finned counterparts and consequently improve the coefficient of performance (COP) of air-conditioning systems. Previous researchers have used heuristic methods such as multi-objective genetic algorithms (MOGA) with approximation-assisted optimization (AAO) methods utilizing computational fluid dynamics (CFD) based metamodels to shape and topology optimize non-round bare tube heat exchangers. A rather unexplored optimization technique used for heat exchanger optimizations is the gradient based adjoint method. CFD solvers utilizing discrete adjoint methods can be used to shape optimize bare tube heat exchangers and can reveal unintuitive, organic, and potentially superior designs. Additionally, additive manufacturing technology has the capability of building these previously unrealizable heat exchanger designs.The objectives of this dissertation are to experimentally evaluate the performance of shape and topology optimized compact bare tube heat exchangers with non-round bare tubes on a 1) component level, and 2) system level integrated into an air conditioner. Plus, 3) develop new shape optimized variable geometry compact bare tube heat exchangers using discrete adjoint methods for HVAC&R applications. First, a comprehensive experimental investigation of multiple shape and topology optimized compact non-round bare tube heat exchangers was conducted under dry and wet evaporator, condenser, and radiator conditions. For all heat exchangers, air-side pressure drop and heat transfer capacity were predicted within 37% and 15%, respectively. Next, an experimental test facility capable of evaluating the system level performance of a 7.03-8.79 kW commercial packaged air conditioning unit was designed and constructed. The performance of the air conditioning unit was evaluated before and after its conventional tube-fin evaporator was replaced with a shape and topology optimized bare tube evaporator. Results are presented and discussed. Lastly, an ε-constraint and penalty method optimization scheme was implemented which utilizes a commercial CFD software with a built-in discrete adjoint solver to perform multi-objective shape optimizations of 2D bare tube heat exchangers. Critical solver/mesh set-up to best optimize heat exchangers with 0.5-10.0 mm diameter bare tubes were identified and established. The optimized designs can achieve a 40-50% reduction in air-side pressure drop with at least the same heat transfer capacity compared to the initial circular bare tube geometry. An adjoint shape optimized 500 W bare tube radiator was additively manufactured in polymer and experimentally tested. Air-side pressure drop and heat transfer capacity were predicted within 15% and 10%, respectively. The experimental performance confirms the adjoint method shape optimized designs improve the thermal-hydraulic performance over the initial circular bare tube geometry.
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    (2023) Chanpiwat, Pattanun; Gabriel, Steven A.; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    This dissertation comprises three main essays that share a common theme: developing methods to promote sustainable and renewable energy from both the supply and demand sides, from an application perspective. The first essay (Chapter 2) addresses demand response (DR) scheduling using dynamic programming (DP) and customer classification. The goal is to analyze and cluster residential households into homogeneous groups based on their electricity load. This allows retail electric providers (REPs) to reduce energy use and financial risks during peak demand periods. Compared to a business-as-usual heuristic, the proposed approach has an average 2.3% improvement in profitability and runs approximately 70 times faster by avoiding the need to run the DR dynamic programming separately for each household. The second essay in Chapter 3 analyzes the integration of renewable energy sources and battery storage in energy systems. It develops a stochastic mixed complementarity problem (MCP) for analyzing oligopolistic generation with battery storage, taking into account both conventional and variable renewable energy supplies. This contribution is novel because it considers multi-stage stochastic MCPs with recourse decisions. The sensitivity analysis shows that increasing battery capacity can reduce price volatility and variance of power generation. However, it has a small impact on carbon emissions reduction. Using a stochastic MCP approach can increase power producers' profits by almost 20 percent, as proposed by the value of stochastic equilibrium solutions. Higher battery storage capacity reduces the uncertainty of the system in all cases related to average delivered prices. Nevertheless, investing in enlarging battery storage has diminishing returns to producers' profits at a certain point restricted by market limitations such as demand and supply or pricing structure. The third essay (Chapter 4) proposes a new practical application of the stochastic dual dynamic programming (SDDP) algorithm that considers uncertainties in the electricity market, such as electricity prices, residential photovoltaic (PV) generation, and loads. The SDDP model optimizes the scheduling of battery storage usage for sequential decision-making over a planning horizon by considering predicted uncertainty scenarios and their associated probabilities. After examining the benefits of shared battery storage in housing companies, the results show that the SDDP model improves the average objective function values (i.e., costs) by approximately 32% compared to a model without it. The results also indicate that the mean objective function values at the end of the first stage of the proposed SDDP model with battery storage and the deterministic LP model equivalent (with perfect foresight) with battery storage differ by less than 30%. The models and insights developed in this dissertation are valuable for facilitating energy policy-making in a rapidly evolving industry. Furthermore, these contributions can advance computational techniques, encourage the use and development of renewable energy sources, and increase public education on energy efficiency and environmental awareness.
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    Experimental Analysis and Numerical Modeling of Ignition of Lignocellulosic Building Materials Subjected to Glowing Firebrand Piles
    (2023) De Beer, Jacques Andre; Stoliarov, Stanislav I; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    The prevalence and severity of Wildland-Urban Interface (WUI) fires is on the rise globally. Wildfires that spread into urban areas are known as WUI fires, with firebrand exposure a leading cause of structure losses during these WUI fire events. However, the complex ignition process of WUI building materials by glowing firebrand piles has not been fully resolved. The objective of this research was to develop a numerical ignition model capable of predicting the ignition probability of any horizontally-mounted flammable substrate when exposed to a pile of glowing firebrands. This development process was based on: extensive experimental data quantifying the mechanisms controlling the ignition process; a novel empirical firebrand pile heat flux model; and comprehensive pyrolysis models of three commonly-used lignocellulosic building materials.Experiments were conducted in a bench-scale wind tunnel where a glowing firebrand pile of controlled geometry was deposited onto a horizontally-mounted substrate. Forced air flow velocities in the range of 0.9 – 2.7 m s-1 and two firebrand pile coverage densities (0.06 and 0.16 g cm-2) were used, significantly expanding the range of conditions used in earlier laboratory-scale studies. The firebrand pile thermal exposure and burning intensity were quantified using time-resolved back surface temperature and combustion heat release rate data. Flammable substrate flaming ignition and extinction statistics, as well as burning intensity data, were also collected. A custom inverse heat flux modeling technique, utilizing a solid-phase pyrolysis solver, ThermaKin, and infrared thermal imaging back surface temperature data, was employed to generate incident firebrand pile heat flux profiles directly underneath and in front of a glowing firebrand pile. The time-dependent firebrand pile heat flux behavior was captured using a three-step piecewise linear function. Further, a novel empirical firebrand pile heat flux model was developed, capable of generating time-dependent firebrand pile heat flux profiles over a range of forced air flows (0 – 4 m s-1) and for all firebrand pile coverage densities and geometries. A hierarchical modeling approach was used to develop a comprehensive pyrolysis model for each lignocellulosic substrate through inverse analysis of milligram- and gram-scale experimental data. All relevant kinetics, thermodynamics, and thermal transport properties of pyrolysis was parameterized. Finally, a novel numerical ignition model used to predict the ignition probability of any flammable target substrate when exposed to a glowing firebrand pile under wind was developed. A newly-defined dimensionless flame stability parameter was used as a material-independent criterion to characterize the ignition of a flammable substrate surface. The model captured the stochastic ignition behavior of flammable substrates by firebrand piles, as well as the reduced burning intensity of the piles deposited onto a flammable substrate surface. A logistic growth function was found to most accurately capture the ignition probability dependence on the dimensionless flame stability parameter and was, on average, capable of predicting the ignition probability within 14% of the experimental data. Further, using a critical dimensionless flame stability parameter, the absolute average difference between all experimental and predicted ignition timing and burning duration data was 11 and 26 s respectively.
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    (2023) Wang, Lingzhe; Srebric, Jelena; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    The indoor environment has significant impacts on the health and comfort of building occupants. In addition, occupant behavior can affect building energy consumption. It is essential to consider actual occupant needs when controlling indoor environmental systems. To provide a healthy, comfortable, and energy-efficient indoor environment, the present dissertation presents a comprehensive research framework for occupant-oriented indoor environmental controls by conducting (i) air quality characterization in occupant breathing zone, (ii) data-driven thermal comfort identification, and (iii) simultaneous air quality, thermal comfort, and building energy controls.For air quality characterization in occupant breathing zone, the present dissertation characterized aerosol plumes associated with the risk of airborne virus transmission to investigate the occupant requirements for air quality controls. The study considered both the aerosol plume source strength and convective transport capability by conducting experiments with 18 human subjects. The source strength was characterized by the source aerosol emission rate, and the convective transport capability was characterized by the plume influence distance. The performances of multiple mitigation strategies were tested. The findings show that controlling the air quality in the breathing zone is crucial for protecting occupants from getting infected by airborne infectious microorganisms. For data-driven thermal comfort identification, the present dissertation developed data-driven models to predict actual occupant thermal comfort based on physiological variables. By incorporating multiple HRV indices along with wrist temperatures, the performance of the models was significantly improved, achieving more than four times the accuracy compared to models based solely on wrist temperatures. This highlights the crucial role of HRV as physiological variables in accurately predicting thermal comfort. With the F1 score, the performance evaluation index of the developed machine learning thermal comfort model, exceeded the value of 0.90, this investigation provides a reliable thermal comfort prediction method, which could be used in actual building occupant-oriented controls. For simultaneous air quality, thermal comfort, and building energy controls, this dissertation developed a wearable micro air cleaner and deployed the extremum seeking control. The wearable micro air cleaner achieved 60% - 70% protective efficiency for both nasal and mouth breathing. Importantly, unlike current mitigation methods such as masks, this device allows users to be thermal comfortable when the indoor air temperature is above 25 °C. Additionally, this dissertation implemented the extremum seeking control to balance the trade-offs between individual thermal comfort preferences and building energy consumption in real-time. This control method successfully achieved energy savings of up to 22% compared to a constant temperature setpoint of 24 °C. The developed framework for simultaneous air quality, thermal comfort, and building energy controls holds great potential in providing building occupants with a healthy, comfortable, and energy-efficient indoor environment.
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    Development of a Lagrangian-Eulerian Modeling Framework to Describe Thermal Degradation of Porous Fuel Particles in Simulations of Wildland Fire Behavior at Flame Scale
    (2023) Ahmed, Mohamed Mohsen; Trouvé, Arnaud; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    The dynamics of wildland fires involve multi-physics phenomena occurring at multiple scales ranging from sub-millimeter scale representative of small vegetation particles to several kilometers representative of meteorological scales. The objective of this research is to develop an advanced physics-based computational tool for detailed modeling of the coupling between the solid-phase and the gas-phase processes that control the dynamics of flame spread in wildland fire problems. This work focuses on a modeling approach that resolves processes occurring at flame and vegetation scales, i.e., the formation of flammable vapors from the porous biomass vegetation due to pyrolysis, the subsequent combustion of these fuel vapors with ambient air, the establishment of a turbulent flow because of heat release and buoyant acceleration, and the thermal feedback to the solid biomass through radiative and convective heat transfer. A modeling capability called PBRFoam is developed in this dissertation based on the general-purpose Computational Fluid Dynamics (CFD) library OpenFOAM and an in-house Lagrangian Particle Burning Rate (PBR) model that treats drying, thermal pyrolysis, oxidative pyrolysis, and char oxidation using a one-dimensional porous medium formulation. This modeling capability allows the description of fire spread in vegetation fuel beds comprised of mono- or poly-dispersed porous particles including thermal degradation processes occurring during both flaming and smoldering combustion.The modeling capability is calibrated for cardboard and pine wood using available micro- and bench-scale experimental data obtained. Then it is applied to simulate the fire spread across the idealized fuel beds made of laser-cut cardboard sticks that have been studied experimentally at the Missoula Fire Sciences Laboratory. The simulations are conducted with prescribed particle and environmental properties (i.e., fuel bed height, fuel bed packing, particle size, moisture content, and wind velocity) that match the experimental conditions. The model is first validated against experimental measurements and observations such as the rate of spread of the fire and the flame residence time. The modeling capability is then used to provide insights into local as well as global behavior at the individual particle level and the fuel bed level with variations of the fuel packing. The modeling capability is also applied to simulations of fire spread across idealized vegetation beds corresponding to mixed-size cylindrical-shaped sticks of pine wood under prescribed wind conditions. Depending on the particle size distribution, the simulations feature complete fuel consumption with a successful transition from flaming to smoldering combustion or partial fuel consumption with no or limited smoldering. These simulations show the existence of either a mixed mode of heat transfer through convection and radiation for small particles or a radiation-dominant heat transfer mode for larger particles. The results are interpreted using a novel diagnostic called the Pseudo Incident Heat Flux (PIHF) and 2-D maps that characterize single particle response as a function of the PIHF and the flame residence time.