https://etd.auburn.edu/handle/10415/1 2026-04-25T11:50:45Z 2026-04-25T11:50:45Z Saloglu, Keziban https://etd.auburn.edu/handle/10415/10334 2026-04-24T21:29:36Z 2026-04-24T00:00:00Z

On the Connection of Optimal Impulsive and Low-Thrust Trajectories Saloglu, Keziban Space missions are designed for a range of objectives, including scientific exploration, telecommunications, Earth observation, and establishing a sustained human presence around the Moon and Mars. Trajectory optimization plays an essential role in achieving these objectives, informing the spacecraft design and launch window selection. The spacecraft's propulsion system influences the resulting trajectory optimization problem. This study considers two primary propulsion systems: chemical and electric. The velocity change due to thrusting with a chemical thruster is modeled as an instantaneous velocity change, consistent with impulsive trajectories. Electric propulsion systems, however, must operate over a finite duration to achieve a velocity change, owing to their lower thrust compared to chemical thrusters. The resulting low-thrust trajectory optimization problems typically seek minimum-fuel or minimum-time solutions and are challenging to solve due to discontinuities in spacecraft states, nonlinear dynamics, and unknown thrust or impulse structures. For impulsive trajectories, the structure corresponds to the number, location, magnitude, and direction of impulses. In contrast, for low-thrust trajectories, the thrust structure comprises the number of thrust arcs, their durations, and the thrust vector direction. Numerical approaches for solving optimal control problems are categorized as direct or indirect, producing nonlinear programming or boundary-value problems. This dissertation advances spacecraft trajectory optimization by proposing new methods and improving upon the existing numerical approaches. Since the initial guess is essential for achieving convergence in trajectory optimization problems, this dissertation investigates methods to bridge the gap between impulsive and low-thrust trajectories to improve initialization strategies. Therefore, the main goal is to investigate the relationships between impulsive and low-thrust trajectories and leverage them to improve numerical methods. Starting from low-thrust solutions, the initialization of impulsive trajectory optimization problems is investigated. The investigations led to the development of a novel analytical approach to impulsive trajectory generation, revealing infinitely many iso-impulse trajectories across a range of mission-specific parameters (e.g., maneuver time). The iso-impulse trajectories are then used to generate corresponding minimum-fuel low-thrust trajectories, completing the framework that connects the low-thrust and impulsive domains. Additionally, the dissertation explores methods for obtaining more realistic low-thrust trajectories, further improving practitioners' ability to generate these trajectories and broadening their applicability to mission design.

2026-04-24T00:00:00Z Lancaster, Anna https://etd.auburn.edu/handle/10415/10333 2026-04-24T20:52:21Z 2026-04-24T00:00:00Z

Monitoring and detection of internal erosion in unsaturated slopes Lancaster, Anna Internal erosion is a major cause of failure in embankments and natural slopes, yet early-stage processes in unsaturated soils remain difficult to detect because subsurface flow paths develop below the ground surface and often produce no visible indicators. This research investigates concentrated leak erosion in unsaturated clayey sand and evaluates how hydraulic and mechanical sensing methods capture erosion-related responses during controlled large-scale experiments. Test slopes were constructed with full-pipe and partial-pipe defects and instrumented with volumetric water content (VWC) sensors, suction sensors, and a low-cost internal erosion (IE) sensor developed and calibrated as part of this study. VWC sensors recorded wetting-front movement, seepage migration, and the reactivation of preferential pathways, providing clear hydraulic precursors to erosion. Suction measurements did not contribute meaningful information due to loss of hydraulic continuity. The IE sensor detected localized deformations associated with pipe enlargement, collapse, and shallow sliding, capturing mechanical activity not reflected in moisture data. No single sensor type captured the full sequence of erosion processes, and the most complete interpretation emerged from combining distributed moisture sensing with deformation-sensitive instrumentation. These findings clarify how internal erosion progresses in unsaturated soils and provide a framework for integrating hydraulic and mechanical measurements into practical monitoring systems for early detection.

2026-04-24T00:00:00Z Pfitzer, Jeremiah https://etd.auburn.edu/handle/10415/10332 2026-04-24T20:37:46Z 2026-04-24T00:00:00Z

Molecular pharmacogenomics-guided development of novel targeted therapies for drug-resistant human cancers Pfitzer, Jeremiah Despite unprecedented therapeutic advances, multiple myeloma remains incurable, with nearly all patients eventually developing drug resistance and disease relapse. This urgent clinical challenge demands innovative approaches to identify and validate novel therapeutic targets in relapsed/refractory disease. This dissertation implements a machine learning-guided preclinical platform for rational drug target identification and validates its predictive power through experimental confirmation of multiple therapeutic candidates for relapsed/refractory multiple myeloma (RRMM). We developed an integrated computational-experimental pipeline combining multi-omics datasets, large-scale cytotoxicity screening, and machine learning algorithms to systematically identify dysregulated pathways in B-cell malignancies. This approach successfully predicted several high-priority therapeutic targets for RRMM, which we subsequently validated through rigorous pharmacological testing. Our experimental validation focused on three key findings. First, we addressed the historically "undruggable" RAS-MAPK pathway, found to be mutated in two-thirds of RRMM patients, by developing CRISPR-engineered Ras-mutant models and screening novel inhibitors across >50 human myeloma cell lines, revealing RAS and RAC1 as viable downstream targets. Second, we identified convergent evidence from both direct omics screening and the SecDrug predictive algorithm identifying BIRC5 (Survivin) as a potent therapeutic target, with MCL-1 co-inhibition producing synergistic pro-apoptotic effects. Third, we traced these effects upstream to DDX5, a transcriptional regulator, and characterized novel analogs with improved pharmacological properties. This work demonstrates that machine learning-guided target identification coupled with systematic experimental validation can successfully predict effective therapies for treatment-resistant cancers. The validated targets, particularly RAS pathway components, BIRC5, and DDX5, represent viable candidates for clinical development in RRMM and potentially other B-cell malignancies, offering new hope for patients who have exhausted current treatment options.

2026-04-24T00:00:00Z Hargett, Holden https://etd.auburn.edu/handle/10415/10331 2026-04-24T20:16:54Z 2026-04-24T00:00:00Z

Full Depth Reclamation as an Adaptation Approach to Flood Resilience Hargett, Holden Flooding presents a massive threat to asphalt pavement performance as moisture inundation into the pavement structure can cause a reduction in strength, stiffness, and structural capacity. Full Depth Reclamation (FDR) is a rehabilitation technique that is able to improve the flood resilience of pavements through the stabilization of the existing materials. This study, in connection with the Virginia Department of Transportation (VDOT), evaluates the moisture susceptibility and structural performance of various FDR mixtures stabilized with portland cement, foamed asphalt, and asphalt emulsion. The mixtures developed were based on three different blends of material, representative of that found in Virginia. Laboratory mix designs were developed based on VDOT specifications and evaluated using unconfined compressive strength (UCS), indirect tensile strength (ITS), and resilient modulus (MR) tests. The moisture susceptibility of each blend was assessed after testing specimens with and without moisture conditioning. Moisture conditioning was completed for UCS and ITS tests by submerging compacted samples into a temperature controlled water bath for 24 to 72 hours prior to testing. Back-saturation was used to moisture condition MR specimens until no further increase in saturation level could be achieved. Results showed that cement-stabilized FDR exhibited negligible reductions in strength and stiffness after saturation while foamed asphalt-stabilized FDR experienced approximately 30% reductions in both. Asphalt emulsion-stabilized FDR displayed similar reductions in strength, approximately 30%, based on the saturated and unsaturated ITS results. However, reductions in MR were recorded as 15% or less. For all stabilizing agents, any moisture-induced damages occurred within the first 24 hours of saturation as there was minimal difference between one day and three day conditioning periods. The resilient modulus results were inputted into AASHTOWare Pavement ME Design to assess the long-term pavement performance of pavement structures with and without an FDR layer. The modeling results showed that pavement structures including an FDR layer outperformed a typical asphalt pavement of a similar thickness, regardless of the stabilizing agent used. Each model was run at unsaturated and saturated conditions in which the results showed that cross sections with a stabilized FDR layer successfully enhance the flood resilience of pavement structures.

2026-04-24T00:00:00Z