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Water vapor and CO₂ sorption and transport in carbon molecular sieve membranes and moisture swing materials
Get PDFCarbon Molecular Sieve (CMS) membranes have been extensively studied for gas separations. Many gas separation applications involve humidified streams, but reports on water vapor transport in CMS membranes are limited. In this study, water permeability, diffusivity, and solubility were determined as a function of water activity for CMS membranes. Water transport properties of membranes synthesized at different pyrolysis temperatures (550 °C and 800 °C) and with different polyimide precursors were examined. Water sorption followed Type V isotherms as previously observed for the adsorption of water in microporous carbons. Water permeability was much higher at all water activity values for CMS samples prepared at lower pyrolysis temperature. Water permeabilities as a function of water activity of the three different polyimides pyrolyzed at 800 °C were very similar. Water permeability of CMS membranes was high compared to many other polymeric materials, showing potential for dehydration applications. Water vapor sorption and transport is of major importance to many industries, including membrane air and gases dehumidification, packaging and clothing materials, protective apparel, and humidity control in closed environments. However, water vapor sorption and transport measurements are challenging and require systematic experimental protocols for their accurate determination. Pure and multicomponent water vapor sorption in polymeric materials is also of a major importance for Direct Air Capture (DAC). In DAC, sorbents are exposed to ambient air with different levels of relative humidity (%RH). There are many reports on pure water and pure CO₂ sorption in sorbents, but reports on mixed water and CO₂ sorption are very limited due to the difficulty of obtaining accurate experimental data, and the need for careful design of custom-made equipment. Here, we describe the construction and operation of a multicomponent closed system to determine CO₂ sorption in sorbent materials as a function of %RH, CO₂ partial pressure, and temperature. An Infrared Gas Analyzer (IRGA) was incorporated into the system to measure CO₂ and water concentration in real time without altering experimental conditions due to gas sampling. Blank experiments showed that no CO₂ and/or water was sorbed in the system itself, and any change in gas concentration was due to sorption in the sorbent. To validate the system operation, CO₂ sorption capacities in a commercial material were measured, and the results were compared to a literature report, yielding satisfactory agreement. Moisture-swing (MS) sorption is a promising DAC technology to achieve negative CO₂ emissions and counteract global warming. In this work, MS CO₂ sorption in a model MS sorbent, IRA900, was comprehensively investigated. IRA900 is a macroporous commercial strong base anion exchange resin (AER) with quaternary ammonium functional groups. A rigorous CO₂ desorption process was developed to desorb all the CO₂ from the sample to obtain the CO₂ sorption isotherms as a function of relative humidity, CO₂ partial pressure, and temperature. Remarkably, the total CO₂ uptake in the sorption isotherms matched the ion exchange capacity (IEC) of the material, suggesting a stoichiometry of one CO₂ molecule reacting per active site. An isotherm model for CO₂ sorption starting with empty sorption sites (i.e. in the OH⁻ form) described the experimental data well, supporting the hypothesis that the bicarbonate loaded AER unloaded fully to the OH⁻ state following rigorous CO₂ desorption. CO₂ sorption kinetics were studied, and carbon diffusion coefficients were estimated as a function of %RH, and CO₂ partial pressure.Chemical Engineerin
Reactive and predictive whole-body control for agile, robust, versatile, and deployable humanoids
No full textThe humanoid robotics industry is rapidly expanding, yet deploying versatile humanoids in human environments remains a significant challenge. To thrive in such settings, humanoid robots must possess extensive sensing and actuation capabilities alongside high-performance control systems. At the core of this lies the need for robust whole-body planning and control frameworks that seamlessly integrate with intelligent high-level decision-making. These components are essential for enabling humanoids to perform a wide range of tasks across dynamic and unstructured environments. Agility, versatility, robustness, and deployability are therefore critical dimensions of performance, allowing humanoid robots to adapt to diverse mission requirements, navigate complex terrains, and maintain operational reliability under varying environmental conditions. This dissertation focuses on developing innovative control strategies that leverage both model-based and data-driven techniques to advance these performance dimensions, paving the way for more capable humanoids in real-world loco-manipulation missions. To empower humanoid robots with complex actuation principles to perform diverse tasks, achieving high tracking performance under systematic and environmental constraints is crucial. This work presents a whole-body feedback controller (WBC) that effectively manages intricate mechanical transmission—specifically rolling contact joints—enabling precise trajectory tracking while satisfying multiple control objectives. This controller has been successfully deployed on DARCO 3, an adult-sized humanoid robot, to enable robust locomotion and manipulation capabilities. For versatile locomotion behaviors, a trajectory optimization framework is introduced, incorporating a pre-trained centroidal inertia network to handle the effects of heavy distal mass. This approach enables the generation of diverse locomotion behaviors, including running over cluttered terrain and jumping over obstacles, broadening the operational scope of humanoids. High-speed locomotion is critical for humanoids to perform human-level tasks in dynamic settings. To address this, a Model Predictive Controller (MPC) was developed to mitigate discrepancies between full-body and reduced-order models. Integrating this MPC with the WBC enhances locomotion performance, achieving stable walking at higher velocities while ensuring control robustness under dynamic conditions. For agile and robust bipedal locomotion, an online footstep planning strategy is introduced, combining MPC and reinforcement learning (RL). This strategy allows bipeds to continuously adjust footstep positions, maintaining balance and achieving agile, fast maneuvers even in the presence of external disturbances or challenging terrain, demonstrating robustness and adaptability. Finally, safe and reliable deployment of control algorithms requires rigorous simulation-based evaluation. To this end, a comprehensive software architecture has been developed, integrating multiple physics-based simulators, model-based planning and control modules, visualization tools, logging utilities, and operator interfaces. This architecture supports intuitive deployment, thorough testing, and iterative refinement of control algorithms, significantly enhancing the reliability and efficiency of robotic control deployment in complex settings.Aerospace Engineerin
Lipid-based nanoparticles for drug delivery
Get PDFLipid-based nanoparticles represent a promising strategy for the delivery of therapeutics, offering potential treatment avenues for various diseases. The thesis aimed to explore two examples of lipid-based nanoparticle systems, focusing on their efficacy, safety, and stability to evaluate their suitability for future clinical use. Solid lipid nanoparticles (SLNs) were investigated as a synthetic lipid nanoparticle for delivering PD1-siRNA. The SLNs were found to effectively downregulate protein PD1 expression in macrophages both in vitro and in a mouse tumor model, leading to significant tumor growth inhibition. Importantly, another study highlighted the critical role of cationic lipids (DOTAP) in the formulation of SLNs, demonstrating that while DOTAP is essential for TNF- α siRNA encapsulation, its concentration must be carefully optimized to reduce cytotoxicity and proinflammatory side effects without compromising the therapeutic efficacy of the nanoparticles. In addition to synthetic SLNs, the study explored natural lipid-based nanoparticles, specifically extracellular vesicles known as connectosomes. These vesicles faced challenges related to storage stability, as their functionality diminished when stored in liquid form. To overcome this, the connectosomes were converted into a dry powder via thin-film freeze-drying. This approach successfully preserved their structural integrity and functionality, even under suboptimal storage temperature conditions, making them a viable option for drug delivery. The findings of these studies underscore the significant potential of the lipid-based nanoparticles as versatile drug delivery systems. By addressing key issues such as efficacy, safety, and stability, lipid-based nanoparticles can be further developed into reliable tools for the delivery of a wide range of therapeutic agents, potentially transforming the treatment landscape for various diseases.Pharmaceutical Science
Computational investigation of rocket nozzle plume impingement for space debris detumbling
Get PDFThis work examines the effectiveness of rocket nozzle plume impingement as a technique for detumbling space debris. By employing the Direct Simulation Monte Carlo (DSMC) method, this research investigates the forces and moments on a flat plate target exerted by warm gas thrusters to facilitate the stabilization and control of debris. Initial phases involve conducting DSMC simulations in conjunction with corresponding vacuum chamber experiments to analyze the impingement effects of a warm gas thruster plume, varying both back pressure and target positioning. Subsequently, the investigation is extended to simulation of single and multi-nozzle plume impingement under space-like vacuum conditions, assessing different target offsets and rotational configurations. Results reveal that the interaction of plumes in multi-nozzle configurations leads to the formation of a more focused and narrower flow beam, generating greater counter-torque on the target over a wider range of orientations. This finding indicates that multi-nozzle configurations significantly enhance torque application, thereby demonstrating greater efficiency in detumbling operations.Aerospace Engineerin
Doctoral thesis recital (harp (chamber))
No full textSonata for flute, viola and harp, L. 137 / Claude Debussy -- Pastorales de Noël : pour flûte, basson et harpe / André Jolivet -- Tango 99 : for flute, viola and harp / Milton Barnes -- Cuban dream after the storm : for four pedal harps or harp ensemble / Alfredo Rolando Ortiz.MusicName of supervisor not provided on program
Early warning credit risk default prediction using machine learning for small and medium American businesses
Get PDFThere has been a lot of research and variants in credit risk prediction in the past using traditional operations research and quantitative analytical models. The purpose of this applied research study was to understand industry standard modern machine learning models used for small and medium American businesses. The goal was to analyze 50 organizations belonging to five different sectors namely retail, fmcg, transportation, commercial services and utilities over 11 years from 2013-2023. Scraping 27 financial indicators from publicly available yet reliable sources, a study was made to identify the financial indicators which has the most impact on the accuracy of the model. Grey correlation analysis was used to find and rank weighted financial indicators which were then used to identify the number of principal components. Evaluating a number of different models, ensemble methods and correlation subsets to find the best combination of machine learning models, explainable AI techniques were used to perform a sector wise analysis on the misclassified data to derive valuable insights.Operations Research and Industrial Engineerin
Called to Testify: Congressional Oversight of the Armed Forces (Spring 2025)
No full textCommittee hearings are a key mechanism by which Congress conducts oversight and shapes defense policy. The expertise Congress chooses to draw upon in these settings can have important implications for the substance of national security choices, the time horizons associated with alternative resourcing investments, and the public’s perceptions of the proper purveyors of defense policy. But few studies have systematically examined which types of witnesses—government civilians, military officers, or outside experts—congressional committees call to testify when investigating defense matters. In a survey of more than 6,500 witness appearances before the House Armed Services Committee from 1975 to 2016, we find that Congress has turned to government civilians and senior military officers in increasingly equal measure when seeking testimony on defense matters. The share of civilian and military witnesses appearing before the House Armed Services Committee remained remarkably stable over time, even when accounting for changes in the committee’s party leadership and increasing occurrences of divided government and rising partisan polarization within Congress. These findings have important implications for the formulation of defense policy and Congress’s underappreciated role in exercising civilian control over the armed forces.LBJ School of Public Affair
Reclaiming narratives : an analysis of youth critical multiliteracy efforts in libraries
Get PDFThis paper seeks to investigate the youth information landscape and the concerted efforts of librarians to mitigate, analyze, and critique the quality of information consumed and created by children and teens. More so, how the use of Critical Multiliteracies in libraries can provide an avenue through which effective multifaceted and multimodal youth services can be offered. A qualitative content analysis was therefore conducted analyzing youth Critical Information Literacy (CIL), Critical Media Literacy (CML), and Critical Literacy (CL) services in libraries, K-12 schools, and education organizations. The review revealed Curriculum & Instruction, Collection Management, Digital Culture & New Media, and Role-Play were the preferred instructional methods for librarians, educators, and media specialists. As for service features, activities and materials incorporated and prioritized the presence of the following elements: Relevance, Multimodality, Agency, Behavior Modeling, and Counternarratives. While the review offered insight into preferred and effective service approaches and features, it also revealed the absence of criticality in library literacy services and the restricted nature of services based on the roles and responsibilities of librarians. Educators and media specialists, however, demonstrated dynamic ways to incorporate CML, CIL, and CL instruction in classrooms. Such efforts by non-library practitioners provided insight into effective service approaches and features that librarians could adopt and presented an opportunity for collaboration under the Critical Multiliteracies umbrella. Embracing Critical Multiliteracies services, therefore, gives librarians the ability to collaborate with diverse practitioners, incorporate diverse instructional and implementation methods, and recreate the diverse information landscape children and teens find themselves in.Informatio
Playing in the threshold : devising theatre for the very young with teens
Get PDFTheatrical performances for audiences under the age of five are often nonlinear, low- or non-verbal, and participatory. Coupled with the societal marginalization of young children, these dramaturgical conventions position theatre for the very young (TVY) in opposition to mainstream theatre for adults. Many TVY artists defiantly embrace opposition to theatrical tradition while simultaneously seeking to legitimize TVY as theatre. Thus, TVY is defined as both theatre and not-theatre. In this MFA thesis, I apply the theories of social change scholar AnaLouise Keating to theatre for the very young, conceptualizing the inherent contradictions of TVY as thresholds. Based on Keating’s scholarship, I define thresholds as generative spaces of productive disorientation betwixt and between seemingly incompatible ideas. This phenomenological study examines thresholds in the experiences of students and facilitators in a fifteen-week TVY devising course at the ZACH Performing Arts Academy in Austin, Texas. Analyzing my reflective journal, reflective participant maps, and post-project interviews, I identify three major thresholds navigated by participants. For each of these thresholds, I examine two participant cases in detail, evaluating whether these experiences led to individual or institutional shifts. By conceptualizing the frictions of a TVY-making process as spaces of possibility, I hope to highlight the change-making potential of Theatre for the Very Young as a post-oppositional practice.Theatre and Danc
PyKokkos : a performance portability framework for Python
Get PDFHigh-performance computing (HPC) hardware is becoming increasingly heterogeneous, with most modern supercomputers containing different types of processors, such as central processing units (CPUs) and graphics processing units (GPUs), from a variety of different hardware vendors, such as NVIDIA, AMD, and Intel. To enable programmers to write software that extracts the maximum possible performance from their processors, hardware vendors typically provide programming frameworks that specifically target their own hardware. Developing software with these frameworks results in code that is tightly coupled to the targeted processor since the frameworks have different application programming interfaces (APIs) and usage guidelines. Using these frameworks, programmers write parallel, high-performance functions, which are known as kernels. The APIs allow programmers to interface with the processors while the usage guidelines provide directions on how to write kernel code that extracts the highest possible performance. Differences in these APIs and usage guidelines means that porting code from one type of processor to another requires considerable effort from programmers: they must rewrite their code to use the new framework's API and learn its usage guidelines and best practices in order to achieve good performance on the new processor. Finally, they have to maintain two versions of the same code, one for each processor. As new processors and programming frameworks are constantly emerging, programmers must keep updating their code to take advantage of the new hardware and software, which is not a scalable approach to software development. An alternative approach is to use programming frameworks that enable writing code that runs on different types of processors with good performance, a concept known as performance portability. One such framework is Kokkos, a performance portable programming model with a C++ implementation which aims to provide a single API that runs efficiently on different hardware. While Kokkos achieves its goals of performance portability, its availability as a C++-only library negatively impacts usability. C++ is a powerful and widely used programming language but is notorious for being difficult to use. This is especially true for scientists with no formal training in software development, a group that forms a large portion of Kokkos's user base. Instead, these users prefer higher level languages such as Python, a high-level, dynamically-typed, and interpreted language that has historically prioritized usability over performance. This dissertation presents PyKokkos, a Python framework for writing parallel performance portable kernels, as well as PyFuser, a kernel fusion framework which provides further speedups. Unlike C++ Kokkos, PyKokkos enables performance portability in Python by providing software abstractions that allows programmers to write their kernels entirely in Python. Internally, PyKokkos translates the Python kernel code to C++ Kokkos code, and automatically generates language bindings to allow for interoperability between Python and the generated C++ code. Using PyKokkos, we ported a number of existing C++ Kokkos examples to Python and showed that the PyKokkos kernels match the original kernels in terms of performance while being easier to write. These examples include ExaMiniMD, a ~3k lines of code molecular dynamics mini-application. Furthermore, PyKokkos achieves better performance than Numba, the state-of-the-art Python library for writing kernels.Electrical and Computer Engineerin