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Soil Temperature and Moisture Control in Ground Source Heat Pump Systems
No full textThis numerical study focuses on exploring passive methods to control soil temperature rise and restore favorable thermal conditions in ground source heat pump (GSHP) systems. The three methods investigated were soil moisture control, presence of thermosiphon (TS), and effects of soil type. A single U-loop of a GSHP system was modeled in a soil domain using a finite element analysis (FEA) software Ansys Mechanical. The Backward Euler formulation and the Sparse Direct Solver were used to discretize and solve the governing heat conduction equation. Four moisture contents (high, low-to-high, high-to-low, low) and two soil types (sandy loam, clay loam) were considered, along with the presence (TS case) and absence (non-TS case) of a single thermosiphon. Soil temperature profiles were plotted at multiple points to examine the effects of moisture level and soil type, and the temperature difference between TS- and non-TS cases was plotted to study the thermosiphon effect. Curve-fitting of soil temperature profiles was done to quantify the rate of soil temperature rise at different depths. The results showed that soil temperatures decreased with moisture content. Soil temperatures were lower for TS cases than for non-TS cases, and the TS effect also decreased with moisture content. Moreover, clay loam resulted in higher soil temperatures than sandy loam at all moisture levels considered. In summary, to maintain and restore soil thermal conditions favorable to GSHP systems, moisture control is recommended for GSHPs in high thermal diffusivity soils, while thermosiphon use is preferred for GSHPs in low thermal diffusivity and dry (low moisture content) soils
OSHA Citations and Beyond: Strategies for Ensuring Combustible Dust Compliance
No full textManaging dust in the ever-changing world of industrial operations cannot be emphasized enough. Dust, frequently observed due to numerous industrial processes, poses several complex challenges that require careful consideration and proactive control. The appropriate handling of dust emerges as a crucial component of industrial processes, from the standpoints of safety and health to the optimization of operational efficiency. This project outlines the OSHA (Occupational Safety & Health Administration) citation data that was gathered against the citations obtained in response to the "dust" query from 2019 to 2023. The data from the citations was studied to understand which type of industries had received the most citations from OSHA. Furthermore, the equipment of concern was studied and analyzed, and the citations received from 2019 to 2023 were then compared with 2018, explaining the relevance of the shifting industries, citations, and industrywide concerns about handling dust within the above-mentioned timeframe. In total, there were 45 citations related to dust in 2018, which decreased over the years. In 2023, 42 citations were found under the general duty clause in the term "dust." There were also some citations where NFPA (National Fire Protection Association) standards were outlined, referred to, and explained. In the years considered in the project, over 95 percent of citations were classified as ' serious, ' with scarce instances of 'failure to abate' and ���willful��� violations. All penalties were compared case-wise, industry-wise, and year-wise to understand the cost relationships with incidents. New citations after the year 2018 were also assessed and evaluated. Further measures and standard requirements to ensure safety compliance against dust hazards were discussed in detail. This project emphasizes the critical significance of managing dust in industrial operations, highlighting its multifaceted challenges and pivotal role in safety, health, and operational efficiency. Through a detailed analysis of OSHA citation data from 2019 to 2023, industry trends, equipment concerns, and penalty assessments were investigated, providing a comprehensive understanding of the evolving landscape and imperative measures for ensuring safety compliance in handling dust hazards
Contrast-Independent Partially Explicit Time Discretization for Multiscale Problems and Its Application
No full textPartial differential equations are widely used in modeling and simulations. In many applications, there are high contrast changes in media properties. The implicit methods are typically used for temporal discretization and are unconditionally stable such that the time step size can be large during the computation. However, the implicit methods are more complicated to solve, especially for nonlinear problems. In contrast, the explicit methods are relatively easier to compute, while they require a much smaller time step size. This work focus on developing a contrast-independent partially explicit time discretization scheme for multiscale problems, specifically, nonlinear problems and also its application. The proposed method divides the spatial space into two components: contrast dependent (fast) and contrast independent (slow) spaces defined via multiscale space decomposition. Following this decomposition, temporal splitting is proposed that treats fast components implicitly and slow components explicitly. As a result, the scheme contains two equations, one implicit and the other explicit. The space decomposition and temporal splitting are chosen such that it guarantees a stability and formulate a condition for the time stepping. With the appropriate construction of spaces and stability analysis, we find that the required time step in our proposed scheme scales as the coarse mesh size, which creates a significant computational saving.
We first apply this approach on the parabolic diffusion reaction equations. We present numerical results and show that the proposed methods provide accuracy similar to implicit methods and the required time step size is independent of the contrast.
Nonlinear time fractional partial differential equations has wide application in physics and engineering. For the case of time fractional diffusion equations, the constraints on time steps are more severe and we extend our partially explicit methods to help alleviate this problem.
In our scheme, the implicit solution part can still be expensive, especially for nonlinear problems. Therefore, we introduce a modified partial machine learning algorithm to replace the implicit solution part of the original algorithm. Then we compute the explicit part of the solution using our splitting strategy. In addition, we use Proper Orthogonal Decomposition based model reduction to further improve our algorithms.
We extend the proposed scheme to solve multi-physics problems. We propose a partially explicit scheme with physics-based splitting. We take the convection diffusion equation as an example. In this scheme, we do a physics-based splitting, i.e. the convection equation is solved using the exact solution, and then we solve the diffusion equation via the partially explicit scheme
Electric Vehicle-Induced Grid Impact Analysis and Its Minimization
No full textElectric vehicles are a major component of the clean energy transition. With significant technology improvement and government policies, EVs have increased to 10 million globally. A major bottleneck to accommodate the projected EVs is the development of an affordable and convenient charging infrastructure without needing long waiting times or long-distance travel for charging. As EV chargers draw power from the utility grid, adding the EV charging load impacts the utility grid significantly.
This thesis investigates the impact of EV charging load on three vital grid-performance indicators (voltage profile, load demand curve, and harmonic profile) and develops solutions to minimize them. Firstly, the power electronic circuitry and control algorithms are studied to identify a grid-connected EV load���s power/energy requirements and harmonic profile. Moreover, considering the inter-dependency of voltage profile and power demand, these two parameters are investigated together.
An IEEE 33-bus system is considered, and the actual load data of Qatar���s utility grid is used to define it. A novel two-step EV distribution algorithm has been developed, which helps estimate the 24-hour EV hosting capacity of the network without any intermediate line sections. Furthermore, the impact of the unavailability of DC fast chargers and level-2 chargers (located in parking lots) on EV hosting capacity is investigated to observe whether domestic chargers can address this shortfall.
Renewable-based distributed generators (DG) are optimally placed in the grid using an optimization algorithm to improve the voltage profile and EV hosting capacity. The constraints to this optimization problem reflect the real-world challenges and discourage any transformer or line feeder upgrade. This strategy, known as the non-wire alternative approach, reflects the modular and active solution-based approach of extending the grid performance. The results are assessed and compared with the pre-DG results regarding voltage profile, EV hosting capacity improvement, and peak-shifting phenomenon.
As both the EV charging current and DG injected current contain harmonics, the grid voltage contaminates and thereby deteriorates the power quality of the network. The impact of this deterioration on the grid must be quantified and compared with the actual distribution network. To analyze the overall impact, EVs and DGs are modeled as harmonic sources and added to the utility grid. This modifies the existing harmonic profile of the grid (due to original harmonic loads). Conventional methods of load-side filtering will be ineffective when the penetration levels of these components increase. To address this concern, a novel distributed filtering algorithm is developed, which analyzes the harmonic profile of the entire grid to determine the optimal location of active filters and their power rating. Post-filter placement, the distribution network becomes IEEE 519-2014 compliant
Nitrogen-Containing Organic Bases for Molecular Electronic and Biological Investigations
No full textThis dissertation shows the efforts towards tailor-made nitrogen-containing organic base molecules for modular electronic studies as well as biological investigations. The first part features the development of two different kinds of aniline-derived conjugated molecules and their applications as molecular models for single-molecule junction studies. The second part of this dissertation describes the development of a series of polyamine-based detergents and their applications in native mass spectrometry studies of membrane proteins.
First, a general introduction of nitrogen-containing organic bases is presented in Chapter I. Example molecules and their applications including pharmaceuticals, metalorganic frameworks (MOFs) and conducting polymers, specifically polyaniline (PANI), are discussed.
In Chapter II, the design and synthesis of a ladder-type polyaniline-inspired single-molecule switch are presented. With exceptional electrochemical stability rendered by the ladder-type constitution, the molecule can be converted between three distinct molecular states characterized by varying levels of protonation and oxidation. In collaboration with the Schroeder Group at UIUC, we demonstrate its superior conductance and multi-state switching capabilities through electrochemical scanning tunneling microscope break-junction (STM-BJ) experiments. Our results suggest that ladder-type molecules are promising candidates for advanced single-molecule electronics. This work also sheds light on the mechanism of electronic conductivity of redox-active conductive polymers.
Chapter III describes the motivations of a model study involving oligo(para-phenylene)s within a graphene single-molecule junction for mechanistic studies of RCM in the synthesis of ladder polymers or oligomers. The design and synthetic efforts towards the target molecules are the main foci of this chapter.
Next, in Chapter IV, synthesis and purification towards spermine-derived detergents are described. These detergents are employed as additives/co-detergents in native mass spectrometry (MS) studies of various membrane proteins. Their effectiveness in achieving reduced average protein charge states and preserving membrane proteins in more intact states has been demonstrated. Our research in this area laid the groundwork for the molecular design principles of charge-reducing detergents with enhanced protein solubility and improved compatibility with commercial detergents. These principles are crucial for conducting native mass spectrometry studies of membrane protein complexes.
Lastly, Chapter V concludes the entire dissertation by providing an overview of the findings presented in the preceding chapters. Additionally, future research perspectives that promise to shed further light on both fields are discussed
Optimizing Markov Decision Process Models of Intermittently-Observed Multi-Agent Systems
No full textA challenging category of robotics problems arises when sensing incurs substantial costs. This thesis examines settings in which a robot wishes to limit its observations of state, for instance, motivated by specific considerations of energy management, stealth, or implicit coordination between multiple agents. We consider the problem of planning under uncertainty when a robot���s observations are intermittent under two specific circumstances. In one, their timing is known via a pre-declared schedule, whereas in the other the timing arises dynamically from multiple robots working together to generate observations.
After establishing the appropriate notion of an optimal policy for each setting, we find that the pre-declared case requires tackling the problem of joint optimization of the cumulative execution cost and the number of state observations, both in expectation under discounts. To approach this multi-objective optimization problem, we introduce an algorithm that can identify the Pareto front for a class of schedules that are advantageous in the discounted setting. The algorithm proceeds in an accumulative fashion, prepending additions to a working set of schedules and then computing incremental changes to the value functions. Because full exhaustive construction becomes computationally prohibitive for moderate-sized problems, we propose a filtering approach to prune the working set. Empirical results demonstrate that this filtering is effective at reducing computation while incurring only negligible reduction in quality. In summarizing our findings, we provide a characterization of the run-time vs quality trade-off involved.
We explore as well the dynamic observation scenario, by developing a formulation for renegotiation of observations throughout execution. The formulation is additionally expanded to support the navigation of multiple agents in a single, joint MDP. We conclude with a hardware demonstration featuring two robots maintaining formation whilst moving down a corridor, subject to motion uncertainty and turning to look at each other intermittently to gauge their states
Structural Composite Electrode for Space Applications
No full textStructural batteries offer a solution for more range-efficient vehicles with its multifunctional ability to hold mechanical load and store energy. The earth���s atmosphere and space environment require vehicles and satellites to have structures which are sturdy against potential environmental debris collisions and able to withstand low temperature. This thesis focuses on the material processing and electrochemical performance of a multifunctional structural composite electrode which consists of carbon fibers for structural reinforcement and a structural biphasic bicontinuous electrolyte (SBBE) for the composite matrix. The SBBE-coated carbon fiber versus lithium half-cell is studied in coin cell configuration. The solid biphasic bicontinuous electrolyte is made from lithium bis(trifluoromethanesulfonyl)imide salt, diglyme, and fluoroethylene carbonate for the liquid electrolyte ionic-conducting phase and resin for high modulus phase.
The effect of the pre-cured volume of SBBE (i.e., volume of SBBE pipetted on top of carbon fiber fabric prior to curing) on the electrochemical performance of the carbon fiber versus lithium foil half-cell in coin cell configuration was studied. After the solid biphasic electrolyte is cured as a layer on the carbon fiber fabric composite electrode, electrochemical characterizations were performed on structural composite electrode half cells with pre-cured SBBE volumes ranging from 25 to 100 ��������. Results indicated that the optimal structural battery volume is 50 �������� because it has the highest electrochemical charge and discharge capacity for the structural composite electrode versus lithium metal foil half-cell at 180 mAh/g for the first cycle, the lowest charge transfer resistance from the electrochemical impedance spectra, and relatively the highest anodic peak when comparing 5th cycle cyclic voltammograms of structural composite electrode with pre-cured SBBE volumes ranging from 25 to 100 ��������. Future work includes testing samples with biphasic electrolyte coated on desized carbon fiber tows on an in-situ electrochemo-mechanical coupling machine
Application of Image-based Techniques to Analyze Coastal Flows and to Evaluate Temporal Wetland Changes
No full textCoastal transport processes occurring at the landward edge of tidal and wave action are important for the diversity of coastal ecosystems, determining nutrient fluxes, the dynamics of sediment and marine pollution during tidal mixing, and controlling coastal geomorphology. Understanding these processes requires large-scale field observations over modest spatial domains to fully resolve their governing mechanisms and to validate and update algorithms in existing numerical and laboratory simulations. This dissertation investigates the application of remote sensing techniques based on UAS and satellite imagery to monitor large-scale coastal processes along the Texas coast, particularly focusing on Galveston Bay, TX. First, surface current mapping methods using UAS video sequences are presented to provide a means of practical measurements of ocean surface currents for the effective prediction of tidal mixing exchange dynamics. The main method, introduced by Stre��er et al. (2017), utilizes a two-dimensional space-plus-time Fourier transform of UAS imagery, linked to the Doppler-shifted dispersion relation fitting technique for surface gravity waves. The resulting current fields reveal the flow structures of tidal currents through inlets at Freeport Harbor and Galveston Bay entrance in flexible spatial resolution. Second, satellite images from Sentinel-2 near Galveston Bay inlet are utilized to bridge the knowledge gap between a series of laboratory, numerical, and limited field studies on tidal vortices to observe their large-scale formation and the influence of coastal currents. A classification scheme is introduced to identify two types of vortex flow patterns observed in the satellite imagery. This classification scheme is validated at Galveston Bay using different satellite images from MODIS with a larger dataset. Lastly, shoreline change monitoring at coastal wetlands in Galveston Bay is explored, leveraging geospatial mapping from UAS imagery enhanced by a new georectification technique adapting the particle image velocimetry (PIV) algorithm. A time series of wetland maps, generated using a Structure-from-Motion (SfM) technique, facilitates the computation of shoreline change rates along the observed wetland boundaries. Subsequent statistical analysis of these rates allows for an assessment of the impact of seasonal variations and storm events on short-term wetland evolution
Electrokinetic Convection-Enhanced Delivery of Macromolecules to the Brain
No full textElectrokinetic convection-enhanced delivery (ECED) utilizes an external electric field to drive the delivery of molecules and bioactive substances to local regions of the brain through electroosmosis and electrophoresis, without the need for an applied pressure. We studied the implementation of ECED to direct a neutrally charged fluorophore (3 kDa) from a doped biocompatible acrylic acid/acrylamide hydrogel placed on the cortical surface. Ex vivo (N = 18) and in vivo (N = 12) experiments were conducted to compare fluorophore infusion using ECED (time = 30 min, current = 50 ��A) and diffusion-only control trials. The linear intensity profile of infusion was significantly higher in ECED compared to control trials, both for in vivo and ex vivo. The linear distance of infusion, area of infusion, and the displacement of peak fluorescence intensity along the direction of infusion in ECED trials compared to control trials were significantly larger for in vivo trials, but not for ex vivo trials. These results demonstrate the effectiveness of ECED to direct a solute from a surface hydrogel towards inside the brain parenchyma based predominantly on the electroosmotic vector
Ira Greenbaum field notebook: GK1-GK500.pdf
No full textBound book, each page corresponds to a karyotype slide data.Data pages for GK1-GK500 corresponding to unique identifiers of specimens/samples examined for biological research. Specimens are primarily housed at Texas A&M University; Biodiverstiy Research and Teaching Collection