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EXPERIMENTAL AND COMPUTATIONAL ANALYSIS OF AN EXTREME ENVIRONMENT HEAT EXCHANGER CO-DESIGNED FOR MANUFACTURABILITY AND THERMAL-HYDRAULIC PERFORMANCE
No full textSupercritical CO2 (sCO2) has recently attracted considerable attention due to its inherent properties, such as high density and volumetric heat capacity, making it an energy-dense and efficient heat transfer medium for various applications, including power generation systems, aerospace and electronics cooling. Heat exchangers operating in extreme conditions must adhere to strict size, weight, and power consumption (SWaP) criteria to ensure efficient thermal systems. Leveraging sCO2 offers the potential to develop high-performance, cost-effective, and compact metal heat exchangers.
Beyond the fluid selection, advanced HX design plays a crucial role in improving thermal performance. In this study, a multi-pass microchannel heat exchanger design (MPMHX) with small fins (0.18 mm width) and microchannels (0.762 mm width) was adopted to achieve high compactness (surface area density = 989 m2/m3). To successfully fabricate this complicated structure, additive manufacturing (AM) was utilized with a development of AM guidance (printing configurations and powder removal process). The multi-pass design concept was applied to fabricate a long microchannel (173 mm) inside a limited printer volume. An elevated relative roughness factor (9.6%) was observed after the manufacturing process and it was incorporated into an AM-based microchannel prediction model to assess its impact on HX thermal-hydraulic performance. The prediction results were validated by experiment, which indicated that the measured roughness increased the pressure loss by 172% while simultaneously enhancing thermal duty by 31%. Compared to other compact HX concepts in the literature, the MPMHX exhibited the highest experimentally demonstrated compactness (Q/V = 45.4 MW/m³, Q/V/dT = 0.34 MW/m³/°C) with a low pumping power of 11.75 W.
To further enhance performance, both genetic algorithm-based parametric optimization and topology optimization were implemented. When applied to a simplified heat sink model, the parametric optimization outperformed topology optimization and was subsequently used to optimize the MPMHX under operating conditions of 147 °C and 800 °C, resulting in thermal performance improvements of 47% and 97%, respectively.
This study presents a highly compact sCO₂ heat exchanger, leveraging additive manufacturing and advanced optimization techniques to enhance HX performance. The findings provide valuable theoretical/experimental insights that can drive the advancement of high-performance HXs for power generation, extreme environments, and high-efficiency applications
Towards Fully Autonomous Robot Navigation in Complex Outdoors: A Multi-Modal Perception and Learning-Based Approach
No full textAutonomous mobile robots are increasingly deployed in diverse outdoor applications such as surveillance, search and rescue, planetary exploration, delivery, and agriculture. However, navigating complex and unstructured outdoor environments remains a formidable challenge due to factors including uneven terrain, heterogeneous surface conditions, dense vegetation with varying physical properties, and the need for contextual scene understanding. This dissertation attempts to address these challenges through a multi-modal perception and learning-based framework, introducing novel algorithms for robust and adaptive outdoor navigation.
The first part of the dissertation focuses on the development of deployable deep reinforcement learning (DRL) policies. For wheeled robots, an online RL framework is proposed that leverages elevation-aware perception and a hybrid attention-based planner to enable stable traversal of highly uneven terrain and effective sim-to-real transfer. For legged robots operating in dense vegetation, an offline RL approach is introduced that integrates proprioceptive and exteroceptive sensing for stability-aware and vegetation-compliant planning. Additionally, a novel policy gradient algorithm with heavy-tailed parameterization is proposed to tackle sparse reward challenges, enabling sample-efficient training and reliable real-world deployment.
The second part explores robust perception under degraded sensing conditions. A trajectory traversability estimation framework is developed by fusing RGB images, 3D LiDAR, and odometry, with candidate paths modeled as graphs and processed using an attention-based Graph Neural Network (GNN) trained to handle partial sensor failures. Furthermore, we introduce a novel 3D object representation, the Multi-Layer Intensity Map (MIM), which leverages stacked LiDAR intensity grids to estimate obstacle height, solidity, and opacity. MIMs enable reliable differentiation between passable and impassable vegetation and structures, while an adaptive inflation scheme further enhances navigation performance in narrow or cluttered environments. The MIM formulation is also extended to support real-time transparent object detection, addressing a common failure case in LiDAR-based systems by enabling safe and reactive collision avoidance. Finally, we present AdVENTR, a general-purpose system for autonomous navigation in unstructured outdoor environments marked by uneven terrain and dense vegetation. AdVENTR integrates data from RGB cameras, 3D LiDAR, IMU, odometry, and pose estimation, processed through efficient, edge-deployable learning-based perception and planning modules.
The third part tackles context-aware navigation in long-tail and open-world scenarios using compact vision-language models (VLMs). A lightweight framework is proposed that leverages zero-shot scene understanding from VLMs to interpret user-defined behavioral instructions. Detected objects are associated with regulatory actions to construct a behavioral cost map, encoding language-driven rules into a spatial format. This enables adaptive, behavior-aware navigation that responds dynamically to scene changes. To balance motion efficiency with compliance, the framework integrates the cost map with an unconstrained Model Predictive Control (MPC) planner. The result is a flexible and interpretable navigation system capable of executing high-level objectives in complex outdoor environments
Shock Perturbations in Hypersonic Attached Shock-Wave/Turbulent-Boundary-Layer Interactions
No full textAn experimental campaign was conducted in the University of Maryland, College Park’s High-Temperature Ludwieg Tube to examine turbulent shock-wave/boundary-layer interactions (SWBLI) on a conical compression-corner configuration at Mach 6.25. The SWBLI behavior was analyzed for multiple test conditions on five cone-flare configurations–a straight cone and four compression angles of 5◦, 10◦, 15◦, and 20◦–which all result in attached interactions at the junction. Unsteady oscillatory behavior along the shock was examined through high-speed schlieren imaging. Edge-detection techniques and correlation speed analysis were used to characterize the propagation speeds of turbulent structures and resulting flare-shock disturbances, frequency content along the shock, and interaction unsteadiness. Fluctuations observed along the shock were shown to remain relatively constant in amplitude as they propagate; a spatial frequency analysis showed that these were not favorable to any specific wavenumbers. As the compression angle increased, root mean square perturbation amplitudes decreased and the spatial wavenumber spectra dropped off more rapidly. The propagation speed of the shock disturbances was found to decrease as the compression angle of the flare increased, aligning more closely with the mean propagation speed of the flare boundary layer than that of the cone boundary layer. This suggests that the region downstream of the corner has influence on the shock behavior and that the shock could be receptive to disturbances in the region downstream of the corner. Additionally, the computed perturbation amplitudes were used along with the propagation speeds of disturbances to characterize how large upstream boundary-layer structures manifested in the compression shock region. Statistical analyses revealed modest increases in the mean, standard deviation, and root mean square shock perturbation amplitudes when large disturbances were present in the upstream boundary layer. The relative increase grew slightly with increasing compression angle and diminished slightly with increasing Reynolds number. The modest trends suggest that other features within the interaction had a more dominant effect on exciting the shock perturbations
FROM THE “VACUUM CHAMBER’: HOW PRESCRIPTIVE WORK PROCESSES CONSTRAIN UX DESIGNERS' DECISION-MAKING POWER IN CORPORATE ENVIRONMENTS
No full textAbstract The study examines the tension between UX designers' holistic approach to design work and the prescriptive processes they encounter within corporate software development environments. Drawing on Franklin's (1998) theoretical framework distinguishing between holistic and prescriptive work processes, the research investigates how UX designers navigate organizational constraints that limit their decision-making authority. It implements ethnographic methods including three months of field observations and 18 semi-structured interviews at Market, a major Chinese e-commerce corporation. The research identifies a disconnection between design education, termed as “Vacuum Chamber”, and the corporate reality where soft skills and navigation of prescriptive processes prove more critical to success. The study further reveals how waterfall-based development methodologies fragment UX work into discrete, specialized tasks that undermine designers' ability to maintain control over the entire user experience. Key findings demonstrate how organizational hierarchies position UX designers as downstream implementers rather than strategic contributors, reducing them to what participants termed "mockup monkeys" who execute others' wireframes with limited input on fundamental design decisions. This study contributes to understanding how technical-creative work evolves within organizational contexts, offering insights open up the discussion on viewing UX work as technology labor
ADVANCING DIRECT LASER WRITING-BASED MICRONEEDLE ARRAYS
No full textMicroneedle arrays (MNAs) are an emerging platform for minimally invasive drug delivery applications. This thesis investigates two key limitations in current 3D-printed hollow MNAs fabricated via direct laser writing (DLW): (1) inadequate mechanical performance of polymer-based MNAs for penetration into stiffer biological tissues, and (2) increased risk of collateral damage in sensitive environments due to uniformly distributed array geometries. To address the first challenge, polyhedral oligomeric silsesquioxane (POSS)-based fused silica glass MNAs were fabricated and evaluated. Experimental penetration testing in surrogate biomaterial demonstrated that glass MNAs reliably penetrate and are retrieved intact, while polymer MNAs fail structurally. These results highlight the enhanced mechanical properties of glass and its potential for applications in rigid tissues such as cartilage and tendon. To address the second challenge, a novel design framework termed strategic microneedle arrays (SMNAs) was introduced. SMNAs omit or reposition needles based on the spatial layout of critical features (e.g., vasculature) to reduce insertion-related trauma. Proof-of-concept testing with agarose blood vessel phantoms revealed that SMNAs preserved vessel integrity while conventional MNAs induced simulated rupture and leakage. Together, these contributions demonstrate how advances in material selection and design customization can improve microneedle performance, safety, and applicability across a broader range of biological environments
THE GENERATION OF THE (18)80s: TURNING BACK TO LOOK AHEAD
No full textIn the first few decades of the 20th century, Italy found itself at the center of a great political and cultural unrest. A climate of fierce nationalism in Europe eventually led to World War I and the establishment of a fascist regime spearheaded by Benito Mussolini. Infiltrating every aspect of individual and intellectual life, external forces pressured Italian musical institutions to re-exert their dominance through a restoration of their perceived glorious musical past. Composers born in the 1880s were reaching compositional maturity around this time, and they undertook the task of creating a new Italian sound. United by their affinity for early music and the clarity and simplicity it possesses, and a conservative turn towards the past and away from the dangers of experimentalism, a group of six composers known as the “Generazione dell’Ottanta” (Generation of the 80s) began implementing certain techniques cultivated from that earlier style in their instrumental music in order to achieve this endeavor. This dissertation examines the techniques employed by the composers in the Generation of the 80s through an analysis of the social, political, and musical influences that they experienced. Mussolini’s fascist government, while not imposing strict constraints on artistic expression analogous to those placed by Stalin’s regime on Prokofiev and Shostakovich, urged Italian composers at the time to reach back to the purity of early Italian compositions. I show how the Generation of the 80s implemented compositional techniques from such works in their effort to create a nationalist style and a new Italian sound. In particular, I argue that the Generation of the 80s’ interest in and analysis of Gregorian chant and celebrated Baroque and Classical era compositions encouraged them to emphasize the perfect fifth as a melodic motif. This analytical observation, when combined within a fuller framework of the style and forms of the works presented in the three dissertation recitals, invokes a clear sense of the new Italian sound.
This new Italian sound signifies an important ideological shift in Italy’s musical timeline. The Generation of the 80s believed that Italy’s grand operatic tradition had ended, resulting in the necessity to return Italian instrumental music to the prominent position it inhabited during the Baroque period. Yet, unable to distance themselves completely from their vocal tradition, the Generation of the 80s’ style contains a propensity for song, in addition to the transparency afforded by Gregorian chant and perfect fifths. Their implementation of these elements and their willingness to go in a new musical direction fostered Italy’s rise to prominence in cinematic composition during the middle of the 20th century
ON VOTING AND POLARIZATION
No full textPolarization has become a pressing issue in today’s American society. As much as we talk about it and have a general sense of what it is, it still seems like there is more work to do to clarify the concept. The purpose of this dissertation is to explain what polarization is, what makes it bad, and what we ought to do about it. Along the way, I will consider how voting is important in practically managing and reducing polarization. In the first chapter, I will analyze polarization as it’s popularly construed and provide a way for us to evaluate it normatively through its effect on a property of society I call Stability. In the second chapter, I review a proposed solution to addressing political polarization: instant run-off voting, or IRV. I argue that while it will address the consequential worry raised in the first chapter, it misses the social and epistemic worries, and I take a look at how expressive voting provides a better model for us to understand how to address the remaining worries about polarization. In the third chapter, I describe polarization as a moral problem akin to prejudice. After looking at two kinds of polarization, I argue that if one thinks we should resist being prejudiced, then we have the same obligation to resist being polarized. I conclude this by suggesting a bottom-up approach to resisting polarization
CONSTRUCTING MECCA’S SANCTITY: SCHOLARS, CALIPHS, AND THE MAKING OF A SACRED CENTER
No full textThis dissertation examines how Mecca’s sanctity was actively constructedduring the first two centuries of Islam, arguing that it emerged through ongoing
negotiation across textual, legal, and spatial domains. Drawing on sources such as
epistles, inscriptions, historiography, and legal opinions, it explores how various
actors mobilized Mecca’s sacred space to assert political, religious, and communal
authority. Central to this process was the role of memory, particularly in narratives
linking Mecca to Yemen’s cultural and political legacy. Concepts such as ahl Allāh
(People of God) and mujāwara (devotional residence near the Kaʿba) signaled claims
to spiritual legitimacy and spatial control. The study also analyzes legal and political
tensions surrounding urban development, showing how sanctity was reinterpreted
in response to competing visions of authority. By foregrounding the dynamic
interplay of memory, power, and space, it presents Meccan sanctity as a product of
deliberate human intervention and ongoing redefinition
Scenario Generation-Based Single- and Multi-Objective Robust Optimization under Fixed and Variable Interval Uncertainty
No full textMulti-objective robust optimization is a prominent field of optimization that deals with problems that have multiple, at least partially conflicting objectives, are subject to some constraints, and contain uncertainty. The main goal of these problems is to obtain solutions that are optimal and robust – i.e. relatively insensitive (have uncertainty robustness) to any realization of the uncertain parameters.
This dissertation presents three new methods for solving single- and multi-objective robust optimization (SORO and MORO) problems under fixed and variable uncertainty. The proposed methods share an underlying single-level iterative framework and handle the uncertainty robustness via a scenario generation technique.
The first method is the original sampling-based approach (OSB-MORO) which uses a multi-objective genetic algorithm solver to solve the optimization problem, and then handles the robustness aspect by sampling the fixed uncertainty space to find the worst-case realization and iteratively shrink the feasible domain to find the robust solution. This approach is very general in nature and can be applied to a variety of problems that have fixed interval uncertainty. However, sometimes the computational burden of solving MORO problems can be infeasible, or analyzing the trade-offs between the objectives can be challenging. To address this issue, MORO problems can be reformulated as single-objective problems – namely, via utility functions. The utility-based sampling-based MORO approach (USB-MORO) is an extension of the OSB-MORO approach, where the multiple objectives are converted to a single scalar via a multi-attribute utility function. This makes it possible to apply efficient single-objective optimization techniques, rather than the expensive multi-objective genetic algorithm solver. Although the utility approach can help solve the MORO problem more efficiently, it does not solve the issue of dealing with expensive functions – i.e. functions that are based on computationally costly simulations. The second method (SSB-MORO) aims to improve the computational cost of the OSB-MORO approach by integrating an online surrogate model. A Kriging model is developed for all the functions of the problem, and is updated as the MORO algorithm progresses. The previous methods mentioned can only handle fixed interval uncertainties – i.e. the uncertainty bounds are known a priori and do not change. However, in many real-world applications the uncertainty may be dependent on the decision variables, hence the uncertainty bounds become variable. The third method (SB-SORO-DDU) aims to address this issue by extending the OSB-MORO approach to account for decision-dependent uncertainty for single-objective problems.
The key contributions in this dissertation are:
1) a single-level, sequential sampling-based single- and multi-objective robust optimization method for problems with fixed interval uncertainty (OSB-MORO);
2) a sampling-based multi-objective robust optimization method with integrated online surrogates for problems with fixed interval uncertainty (SSB-MORO); and
3) a sampling-based single-objective robust optimization method for problems with decision-dependent (or variable) interval uncertainty (SB-SORO-DDU)
A Multi-Criteria Ranking Approach for Energy Efficiency Ranking of a Cluster of Commercial Buildings
No full textBuildings are responsible for 30-40% of global energy consumption, making them prime candidates for improvements in energy efficiency. To this end, states across the U.S. are actively implementing building performance standards to regulate the operations of the existing building stock. However, when multiple buildings are being considered for energy performance
upgrades, it can be difficult for decision-makers to determine which facility to prioritize. This study presents the development of a multi-criteria ranking tool capable of facilitating rapid, reliable, and efficient virtual energy audits. The ranking generated by this tool can be used to conduct performance analyses and identify facilities with suboptimal performance. The proposed ranking of the cluster of buildings can be used to make decisions based on key metrics such as energy use intensity (EUI), net total CO2e emissions per square foot, and dollar-saving potential per square foot. By assigning different weights based on the performance of facilities relative to energy and greenhouse gas emission benchmarks from the Commercial
Building Energy Consumption Survey (CBECS) and the local/regional mandates as applicable, a cumulative score is developed for a portfolio of buildings. For the case study analyzed here, the building portfolio's end-use energy data resulted in a minimum annual average energy savings potential of 1,522 terajoules (TJ) (1,442,951 MMBtu), representing a possible 45% reduction in energy consumption. This translates to approximately 567 megajoules per square meter (MJ/sq. m.) (50 kBtu/sq. ft.) over a six-year analysis period (2018-2023). As a result, this average annual energy reduction would lead to a yearly decrease in greenhouse gas (GHG) emissions of 115,249 metric tons of CO2e, also a 45% reduction, equivalent to roughly 43 kilograms per square meter (kg/sq. m.) (4 kg/sq. ft.) over the same six-year analysis period (2018-2023). Furthermore, the potential annual average dollar savings is estimated at USD 26 million [~USD 10/sq. m. (~USD 1/sq. ft.)], reflecting a 40% cost reduction. Multi-criteria ranking models, such as the one presented here, are essential for identifying and prioritizing subpar building performance, facilitating targeted energy improvements, and allocating resources toward sustainability goals