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Testing the Benefits of Using Silicon Photomultipliers on Organic Scintillator Portal Monitors
No full textRapid and accurate detection of radiation at checkpoints is of vital importance to national security. One proposed method for improving radiation detection capabilities is using Silicon Photomultipliers (SiPMs) on the organic scintillation panels used at checkpoints to detect radiation. Research on SiPMs has been relegated to small detectors with volumes in the cubic millimeter range, but large portal monitors are often used at ports of entry and traffic control points to monitor radiation. This research examined the efficacy of SiPMs placed on larger plastic scintillators with volumes orders of magnitude larger than previous tests have analyzed. For this research two arrays of SiPMs were determined to be the most advantageous due to superior intrinsic efficiency and were tested on plastic scintillators using three different gamma emitting isotopes. Experiments testing a single SiPM to a PMT when placed in geometrically similar configurations gave an average SiPM to PMT total count ratio of 0.0963 �� 0.0006 for the highest-energy gammas, which was within 5% of the expected value based on the ratio of the active areas of the single SiPM and PMT. However, when two arrays of SiPMs were selected based on numerical simulations and tested, the best ratio of SiPM to PMT total count ratio for a single array observing a source was 0.394 �� 0.001, which was within 5% of the active area ratio. SiPM arrays and PMTs were also compared by the ratio of source counts to background counts observed for each isotope, with the best SiPM array observing a ratio of 1.391 �� 0.003 while the PMT���s ratio was 1.584 �� 0.003 for the same isotope. Ultimately, the results of the study do not suggest that SiPMs are an optimal substitute for PMTs on large-volume plastic scintillators, but this result is not concluded decisively by the experiment���s results
High-Throughput Oxidation Prediction Framework and Assessment of Refractory High-Entropy Alloys and MAX Phases
No full textAs a mode of the design process, compensating for failure is every bit as important the solution itself. Regardless of our best and most innovative efforts, devices and systems breakdown and wear out. In this work, we will examine two regimes of advanced complex alloys, MAX phases and High-entropy alloys, and make predictions on the outcomes of oxidation decomposition. To meet this goal we devise a High-throughput Finite Temperature Phase-prediction framework for simulating oxidation environments for arbitrary metallic alloys. This end-to-end framework projects ground state alloy information into the finite temperature regime with the machine-learning fitted Bartel Model. Using a least-squares algorithm, we take our studied material and the possible secondary phases to minimize the total energy of the system following semi-grand ensemble constraints at rising temperatures. By incriminating allowable oxygen, we then get a map of rapidly determined material decomposition. As an application of design in the High-entropy alloy (HEA) space, or more specifically Refractory HEA space, we sweep the combinatorial alloys regime for MoWTaTiZr materials for favorable alloy candidates for oxidation resistance. From 10%-%30 variations of constituent element concentrations, we generate 51 unique BCC via Monte Carlo Special Quasirandom Structure (MCSQS) algorithm. Applying the framework and appending an innovative metric, area-under-the-curve2 (AUC2), presented in this work, We analyzed and rank ordered the structures using a pareto front method measuring survivability of the RHEA and it���s secondary phases. Oxidation Experiments were conducted at 1373K on four samples, measuring thickness scales and mass change. Finally, and a Pillings-Bedforth ratio based "lack of monotonicity" metric we utilized to make a final design determination. We predict and experimentally confirm that HEAs composition Mo10T a30T i30W10Zr20 is the most favorable alloy. We then use this same framework as an investigation tool for previously performed Oxidation Wedge experiments for T2AlC. We do confirm a substantial aligning of oxidation decomposition and evolution. Additionally we extend this analysis for 30 211-structured MAX phases whose components are governed by the formula Mn+1AXn, where "M" is an early transition metal, "A" is an A block element, "X" is Carbon or Nitrogen and n=1,2,3. We focus on discussions of Cr2AlC, Ti2AlC, and Ti2SiC. We thus conclude an effective low cost screening process for favorable MAX phases
A Massively Parallelizable Surrogate-Based Modeling Framework for Nonlinear Static Aeroelasticity and Structural Design
No full textAnalyzing the multiphysical coupling between a deformable structural body and the forces
imposed on that body from a surrounding fluid can be a challenging and computationally expensive
task, especially when the structure and/or fluid exhibit highly nonlinear behavior. Consequently,
preliminary design of aerostructures often relies upon simplified mathematical models
limited to linear fluid and structural regimes to enable tractable exploration within a design space
predominantly defined by convention and engineering expertise. While this has historically proven
reliable, such design practices are inadequate for developing next-generation aerial systems requiring novel structural solutions for in situ geometric reconfigurations that enable continuous
optimization of aerodynamic performance, enhanced control authority, and expansion of operational
capacity. Accordingly, there exists a need for novel reduced-order multidisciplinary analysis
techniques agnostic to the underlying complexities of the physical problem that make efficient
use of high-fidelity computational models to resolve the exchange of field information between
disparate physics subdomains. This work explores a highly parallelizable non-intrusive reduced-order
modeling technique that seeks to construct an aeroelastic surrogate model approximating the
function composition of the high-fidelity structural model and fluid model in terms of shape parameters characterizing a reduced geometric description of the deformed interface boundary between physics domains. The proposed methodology removes the need for a reduced-order representation of the traction field acting on the structure, eliminates computationally expensive fluid evaluations during structural design procedures, and requires no explicit communication between independent fluid and structural models. Furthermore, while this data-driven modeling approach is highly enabling for parametric multi-objective structural design optimization during preliminary design
stages, identifying structural design variables requires foreknowledge of the structural topology.
This work applies many of the same principles to develop a novel reduced-order aeroelastic topology
optimization framework that supplements conceptual design stages with knowledge of the static aeroelastic response while considering nonlinear aerodynamics
Connecting the Dots: Improving Information Extraction by Modeling the Non-Sequential Dependencies of Entity Mentions
No full textInformation Extraction (IE) aims at automatically extracting structured information from unstructured and semi-structured documents. It is an important and challenging topic in Natural Language Processing (NLP) that plays a critical role in downstream applications such as Question Answering and Summarizing. It includes many sub-tasks like Named Entity Recognition (NER), Relation Extraction, Event Extraction, Table Annotations, etc.
Previous works on IE mainly focus on extracting knowledge from a document sentence by sentence and the text encoding models (e.g., RNNs, CNNs, and Transformers) regard the text as a linear sequence from the left to the right or from the right to the left. However, we humans do not always understand a document by sequentially reading it. We tend to connect the concepts across the whole document and then form structural knowledge in our brains. Motivated by the intuition, this work proposes to introduce the non-sequential connections within a document, and uses the relations among the entity mentions as the surrogates for the non-sequential conceptual connections to further improve the performance of the IE systems.
Firstly, I propose to connect the related entity mentions in a document and enforce information flow among them for consistent entity type predictions. Specifically, the work connects both the local dependency relations and global coreference relations for the entity mentions to build better entity mention representations. Experimental results show that applying Graph Neural Networks (GNNs) on the connections can improve the NER performance over strong baselines on two domain-specific datasets.
Secondly, I propose to connect the conceptually related regions in a document and encourage semantic interactions within and among regions. In particular, it builds the connections among the candidate role fillers (i.e., entity mentions from an event mention) for the event extraction task, and characterizes the connections based on different regional affiliations. Then edge-aware GNNs are applied to update the representations of the candidates for false positive filtering. Empirical results show that the proposed method can yield new state-of-the-art performance on two document-level event extraction datasets in two different languages.
Lastly, I propose to connect the entity mentions from semi-structured tables and incorporate the table structures into the table element representations, benefiting table annotation (knowledge extraction from tables) tasks. Specifically, the system will first build hyper-graphs for the cell values coming from the same row or column and then apply the hyper-graph Neural Networks to learn better table representations. The evaluation and analysis show the effectiveness of the structure-aware table representations in improving the table annotation tasks
Assessing the Potential for Antibiotics to Alter Horizontal Gene Transfer Rates in Aquifers via Artificial Recharge of Treated Wastewater
No full textThe managed artificial recharge (MAR) of groundwater is a topic of growing interest regarding water resource management. MAR utilizes alternative sources of water, including treated wastewater effluent, to augment natural recharge rates and slow water table declines. MAR can be accomplished through constructed infiltration basins with high infiltration rates to the water table, or injection wells screened at the depth of the aquifer bypassing the vadose zone. One emerging contaminant commonly detected in treated wastewater is antibiotics used to treat bacterial infections in humans and agriculture. Sulfamethoxazole and trimethoprim antibiotics are commonly co-detected in treated wastewater. This thesis aims to examine the potential dissemination of antibiotic resistance in groundwater influenced by the artificial recharge of treated wastewater effluent. Recent research suggests that antibiotics can potentially modify the dissemination of antibiotic-resistant bacteria in the environment by inducing horizontal gene transfer (HGT) frequencies. HGT is the exchange of antibiotic resistance, mainly through conjugation, from resistant bacteria to susceptible bacteria. While native subsurface bacteria are often resistant to antibiotics, they pose no direct risk to humans unless pathogens acquire that resistance and an exposure pathway exists. Experimental work includes investigating the background levels of antibiotic resistance in soils and changes in antibiotic resistance after subjecting soil microbiomes to varying antibiotic concentrations. A literature review on artificial recharge, wastewater treatment, bacterial and antibiotic transport in the subsurface influenced by artificial recharge was also conducted. A series of one dimensional, variably saturated flow and solute transport simulations were conducted for an artificial recharge environment using Hydrus 1D and a range of reported concentrations and solute transport parameters in soils from the literature review. Expected results include that artificial recharge of treated wastewater may provide rapid antibiotic solute transport through the soil column and into the water table, highly dependent upon linear sorption coefficients and first-order degradation constants. Significant further research on horizontal gene transfer frequencies in native subsurface microbiomes at sulfamethoxazole and trimethoprim concentrations many times below the minimum inhibitory concentrations is needed to determine the potential risks of enhancing the environmental antibiotic resistance problem in managed artificial recharge
Influence of Rock Types on Porosity-Permeability Relations in Clastic and Carbonate Reservoirs with Application to CO2 Storage Site Characterization
No full textAccurate site characterization is essential for evaluating geological carbon dioxide storage potential. Geoscientists can model and monitor the behavior of injected carbon dioxide and rock interactions with knowledge of spatial variation of porosity and permeability. This thesis aims to estimate and understand permeability in carbonate and clastic reservoirs with geological analysis and acoustic well log data.
Jennings and Lucia (2003) model is used to calculate rock fabric numbers (����) in a carbonate reservoir in the Michigan Basin. By integrating information about the cored sections, three distinct classes were identified from rock fabric numbers. With Sun model (2004), a shear-frame flexibility factor (������ ) is calculated from acoustic properties and is used to relate permeability to rock pore structures. The shear-frame flexibility factor (������ ) is related to rock fabric numbers (����) through a linear transformation. The relations between shear-frame flexibility factor and rock fabric numbers will be very useful to estimate permeability from acoustic log and 3D seismic data, which will help predict CO2 pathways in potential CO2 storage sites.
This research also indicates that with sonic logs, we can calculate volume of shale in clastic reservoirs and relate to permeability. Permeability is controlled more by clay content in higher porosity zones. Higher volume of shale values indicates lower permeability values and that mechanical strength and pore structure play a greater role when constraining permeability values. Volume of shale can be related to elastic properties with Sun model (2004). The shear-frame flexibility factor can help constrain ranges of permeability in clastic reservoirs more accurately when porosity is at least 20%.
In addition, a fluid substitution model can be produced with Gassmann���s equations (1951). The impact of different fluid saturation changes is caused by CO2 injection on elastic properties and can be detected from synthetic seismic modeling and related to post-stack inversion results.
The theoretical results of this thesis are valuable for site characterization and locating potential CO2 storage, especially with the use of these rock physics models. With these results, geoscientists can use these methods to better comprehend the behavior of injected CO2 and rock interactions in the reservoir
The Experiences of Queer Undergraduate Students in Engineering at Two Predominantly White Research Institutions
No full textLGBTQ+ students in engineering are an underrepresented group that is often treated differently in the field. In this study, I use the term queer throughout to describe this population. Engineering is a male dominated discipline comprised of white, cisgender, heterosexual males, and those who differ from this demographic are often perceived as the outsider. While the literature gives attention to queer students in STEM as a whole, few studies address engineering specifically. Progress has been made for the queer population, such as gender-neutral bathrooms and anti-discrimination policies, however, more work is needed across higher education and within STEM for this vulnerable population. This qualitative study examined the experiences of 14 queer undergraduate engineering students at two predominantly white institutions in Texas, 10 from one PWI and four from the other. The study sample consisted of participants who represented a variety of ethnicities, gender identity or expression, sexual identities, and engineering disciplines.
This study used Self-Determination Theory (SDT) and Queer Theory (QT) frameworks to understand how power and privilege either make or hinder academic experiences and choices. Participants shared their perceptions of the engineering discipline as a whole, such as interactions between and among students and professors, and how the major is taught compared to other courses outside of engineering. Participants expressed feeling unlike their peers, invisible in the classroom, and how their gender and sexual identities interfered with their daily lives. Administrators, faculty, families, and peers can learn from the findings to understand the needs of and create safe spaces for queer students in engineering where their identities are affirmed, valued, and heard. They found support during their academic journeys, shared how politics in Texas influenced their perceptions and educational experiences, and described what institutions could do better to help students succeed in engineering. Findings from this study draw implications for systemic change to make queer undergraduate students in engineering feel like they belong
Investigation on Wellbore Cement Integrity During Carbon Capture and Storage (CCS) and Underground Hydrogen Storage (UHS)
No full textThe interactions between hydrogen and carbon dioxide (CO2) with wellbore cement are not fully understood, raising concerns about potential degradation and failure of cement barriers during carbon capture and storage (CCS) and underground hydrogen storage (UHS). This study offers an in-depth analysis of the geochemical, petrophysical, and geo-mechanical properties of cement before and after exposure to hydrogen and CO2. In this study, the cement samples were saturated in 30,000 ppm brine and exposed to the different gases at a pressure of 500 psi and temperature of 50 C for 30 days. In the hydrogen experiment, a notable chemical alteration within the cement matrix was observed, marked by a 50% increase in brownmillerite and a 70% decrease in ettringite. Computed tomography (CT) scans revealed both diminished and clogged pores, along with areas of denser material precipitation. Correspondingly, porosity and permeability measurements showed decreases of 2% and 40%, respectively, while compressive strength and Young's modulus experienced increases of 35% and 6%. The exposure of the cement to CO2 showed significant mineralogical changes, with calcite appearing, constituting 8.7% of the mineral composition, and a complete depletion of alite, signaling extensive carbonation. CT scans highlighted a substantial reduction in pore size and sealed fractures due to calcite precipitation, dramatically affecting porosity and permeability, which decreased by 98% and 87%, respectively. Moreover, the mechanical properties saw remarkable improvements, with compressive strength and Young's modulus increasing by 126% and 161%.
This research is a first of its kind, providing a comprehensive characterization of cement samples before and after exposure to hydrogen, and comparing the results with that of CO2 exposure at the same experimental conditions. The methodological and detailed experimental and analysis approach provided a clear understanding of the interrelationship between the petrophysical, geochemical, and geomechanical impact of exposing the fluids to cement. The findings indicate that in the absence of cyclic and confining stresses, hydrogen and CO2 will not degrade the strength of the cement but, in some cases, could offer healing of fractures and microcannulas if present. The reduction in porosity and permeability of the samples suggests that losses will be reduced when the cement is exposed to hydrogen or CO2
Design and Evaluation of Scancap: A Low-Cost, Reusable Tethered Capsule Endoscope with Digital Chromo-Endoscopy Imaging for Unsedated Screening and Early Detection of Barrett���s Esophagus
No full textEsophageal adenocarcinoma (EAC) is the sixth leading cause of cancer death worldwide. Early detection and treatment of Barrett���s esophagus (BE), a precursor to EAC, increases the five-year survival rate from 18% to 98%. BE is a global challenge; however, current endoscopes for early detection of BE are costly and require extensive infrastructure for patient examination and sedation. We describe the design and evaluation of the first prototype of ScanCap, a high-resolution optical endoscopy system with a reusable, low-cost tethered capsule designed to provide high-definition, digital chromoendoscopic imaging for early detection of BE in unsedated patients. The tethered capsule (12.8 mm diameter, 35.5 mm length) contains a color camera and rotating mirror and is designed to be swallowed; images are collected as the capsule is retracted manually via the tether. The tether provides electrical power and illumination at wavelengths of 415 nm and 565 nm and transmits data from the camera to a tablet. The ScanCap prototype capsule was used to image the oral mucosa in normal volunteers and ex vivo esophageal resections; images were compared to those obtained using an Olympus CV-180 endoscope. Images of superficial capillaries in intact oral mucosa were clearly visible in ScanCap images. Diagnostically relevant features of BE, including irregular Z-lines, distorted mucosa, and dilated vasculature, were clearly visible in ScanCap images of ex-vivo esophageal specimens
Musculoskeletal Pain and Preferred Pain Management Strategies Among Dental Professionals and Dental Students
No full textDental professionals and students are predisposed to musculoskeletal pain. However, few primary research studies have investigated musculoskeletal pain and pain management strategies among US-based dental professionals and students. Examining musculoskeletal pain and pain management experiences among dental professionals and students may provide inform opportunities to prevent musculoskeletal pain, thus improving their performance and retention in the workforce.
The primary purposes of this dissertation study were to: (1) understand issues that predispose dental professionals (workers and students) to musculoskeletal pain; (2) explain the associations between musculoskeletal pain and the strategies used for pain management; and (3) identify potentially harmful postures that could cause musculoskeletal pain among dental professionals by performing a concordance analysis of traditional ergonomic evaluation versus computer-based motion capture system assessment of select dental procedures.
The first study, a scoping review that examined musculoskeletal pain and pain management experiences of dental professionals and students, found musculoskeletal pain prevalence between 46% and 92.2%. The neck, wrist/hands, shoulders, and back had the most self-reported pain, while complementary alternative medicine (CAM) was the commonly used pain management strategy.
The second study administered internet-based surveys to dental professionals and dental students. Of the 1,510 study participants, 68.2% self-reported musculoskeletal pain. About 79.2% dental students, 70.6% dental assistants and hygienists, 65.7% dentists, and 60.4% dental therapists reported musculoskeletal pain. CAM (61.3%) and medication (49.7%) were the commonly used pain management strategies.
The third study, a concordance analysis of traditional (Rapid Entire Body Assessment, Rapid Upper Limb Assessment, and Strain Index) and computer-based ergonomic assessment (Humantech motion capture system) on non-participatory observation data, assessed the risk of developing musculoskeletal disorders among dental hygienists. Findings showed slight-to-fair agreement between traditional and computer-based ergonomic assessments. Findings suggest further refinement and testing of digital ergonomic assessment technologies are needed for the dental professions.
Taken together, this dissertation highlights the magnitude of musculoskeletal pain among dental professionals and students in the US and their preferences in strategies to manage pain. It illuminates factors associated with pain, the need for ergonomic assessment, and the potential for digital ergonomic assessment to detect harmful positions, which may cause or exacerbate musculoskeletal pain