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Neutron Spectrum Unfolding from Activation Foils Irradiated in Gamble II using Deuterated Polyethylene Anodes
Get PDFNeutrons can cause irreparable harm to electronics, and experiments are needed to understand their effects fully. This work explores using pulsed power, which is low-cost compared to other sources, to create a useful neutron-rich environment. Deuterated polyethylene was used as anode and catcher material to generate the neutrons from the Deuterium-Deuterium (DD) fusion reaction. A simple, effective, and repeatable method was employed to directly cast deuterated polyethylene onto polyethylene sheets to fabricate the anode and catcher. The DD reactions were made by an ion beam-driven pulsed power generator, Gamble II, with the catcher located in the cathode. Zinc, copper, aluminum, and indium activation foils were used with gamma counting on High-Purity Germanium (HPGe) detectors to unfold the neutron energy spectrum from Gamble II shots. Even though significant uncertainty exists, unfolding results from two shots showed the neutron fluence varying from approximately 10^10 to 10^12 [n/cm2] in the 2.5 MeV energy range. Bubble detectors and neutron time of flight (nTOF) diagnostics were also used to complement the activation foils. While bubble detector measurements did not agree with the unfolded spectrum, they did qualitatively illustrate a strong presence of neutrons. Lastly, the nTOF data showed peaks corresponding to 1.8 and 5.2 MeV. The 1.8 MeV peak seems plausible from a deuteron-on-carbon reaction, and the 5.2 MeV peak is likely associated with 2.45 MeV neutrons. However, additional work is required to verify the presence of those neutrons. It was thought that 14.1 MeV neutrons from a Deuterium-Tritium (DT) might be possible in this experiment, but the nTOF measurements did not indicate their presence. Regardless, these results encourage the potential utilization of Gamble II as a neutron effects platform; however, further work is needed to characterize the neutron spectrum more accurately
Selection of Soil Stabilization Methods for Low-Volume Road Applications
Get PDFThis study examines a potential method of selecting an ideal soil additive to assist road planners in selecting an ideal soil stabilizer for low-volume road construction with in-situ soils. Essential for the socioeconomic success of rural communities, low-volume soil or gravel roads account for approximately 54% of US road expenditures to maintain and remediate. Soil stabilization can provide significant savings in regards to the cost, effectiveness, and environmental impacts of these roads. With hundreds of commercially available soil treatment products available with significant variations to their effects, it can be difficult for road planners to select the most appropriate product. This thesis demonstrates a selection tool using the Analytical Hierarchy Process to evaluate the ideal soil additive among five alternatives including Portland Cement, Class “C” Fly Ash, Enzyme Soil Treatment, Geogrid stabilization, and Magnesium Chloride chemical treatment. The process is demonstrated for US Forest Service roadways in the Black Hills National Forest of South Dakota and Wyoming. The results indicate the preferred alternative for enzyme soil treatment for roads within arid fine-grained soil conditions with a global priority of 24.36% global priority towards the goal. For soils within temperate coarse-grained soil conditions, the results indicate a preference for Portland Cement with a global priority of 27.37%. The results indicate the preferred treatments with user designed weights are based on environmental conditions as well as subjective needs and desires of the user
Navigating Model-Based Systems Engineering (MBSE) Transition in the Department of Defense (DOD): A Capability-Based Assessment (CBA) Use Case
Get PDFThe Department of Defense (DOD) wants to implement Model-Based System Engineering (MBSE) to accelerate and improve the acquisition process of increasingly complex systems. However, the department has not provided the necessary guidance on how to fully implement MBSE into our systems. This provided the following research opportunity: select a common DOD process, create an MBSE methodology, generate a model in accordance with that developed method, record the cost of modeling, and interview the model recipients to characterize their opinions on the investment. The research created a twelve-step methodology for application towards the gap analysis and characterization phase of a Capability-Based Assessment (CBA) for the Joint Forward Edge Command and Control (C2) CBA report. The research identified thirteen data groups: The model took 149.6 creation hours, with 69.8 hours devoted toward data structure and ontology, and 79.75 hours modeling the specific instance. The total cost for the software tool, training, and labor equated to just under $20,000. When interviewed, stakeholders viewed the model as being beneficial through traceability, ease of iteration, and reuse, far outweighing the time and financial cost spent building the model. Additional opportunities for future research include altering the analysis technique and expanding the model’s scope
Center Fixing Tropical Depressions and Tropical Storms Using Machine Learning-Nighttime Visible Imagery
Get PDFThe first step in most TC-retrieval algorithms is determining the storm’s central position. In mature TCs, the center is highlighted by a distinct eye and curved band pattern; however, in intensifying and decaying storms, the center is often obscured by thick clouds or overlying cirrus. This study assesses the benefits of incorporating machine learning-derived nighttime visual imagery to improve analysis of center fix in intensifying and decaying TD- and TS-strength TCs during periods of darkness and when polar orbiting satellites are unavailable. The study is divided into two parts: the first, an objective analysis using the ARCHER-2 algorithm, and the second, a subjective imagery analysis with the JTWC. For the objective analysis, 955 NVI, SWIR, and LWIR image sets, comprised of TD- and TS-strength cyclones, were ingested into ARCHER-2. Results showed that NVI improved center fix forecasts by 21.6 and 49.3 kilometers over SWIR and LWIR, respectively
Proving the Existence of Equichordal Tight Fusion Frames using the Newton–Kantorovich Theorem
Get PDFAn equichordal tight fusion frame (ECTFF) is an example of an optimal packing of subspaces. In particular, an ECTFF is an optimal packing of points in the Grassmannian with respect to chordal distance. Equivalently, every ECTFF is an arrangement of subspaces that meet certain criteria; tightness and equichordality. The existence of an ECTFF can be rephrased as, a certain polynomial mapping as a root. Hence, one can prove the existence of an ECTFF by applying Newton–Kantorovich theorem to this polynomial mapping, given a close enough approximation of one. Newton–Kantorovich requires checking an inequality within a neighborhood of the approximate root, but a sufficient condition can be adapted that only involves checking one inequality at the approximate root. This inequality can then be checked using computer software (such as MAT) to provide an exact answer, which will determine if we have proven the existence of an ECTFF. Additionally, ECTFFs can be created using translations of cyclic groups, which can provide ECTFFs of larger size because of some redundancy in their structure. In this paper, we provide background proofs used in our methodology for completeness, along with detailed discussion about our methodology itself. We provide specific examples of ECTFFs, as well as a complete list of ECTFFs we have existence proofs for, including ECTFFs that had not previously been proven to exist
Comparative analysis of \u3ci\u3eC\u3c/i\u3e \u3ci\u3en\u3c/i\u3e 2 estimation methods for sonic anemometer data
No full textWind speed and sonic temperature measured with ultrasonic anemometers are often utilized to estimate the refractive index structure parameter Cn2, a vital parameter for optical propagation. In this work, we compare four methods to estimate Cn2 from CT2, using the same temporal sonic temperature data streams for two separated sonic anemometers on a homogenous path. Values of Cn2 obtained with these four methods using field trial data are compared to those from a commercial scintillometer and from the differential image motion method using a grid of light sources positioned at the end of a common path. In addition to the comparison between the methods, we also consider appropriate error bars for Cn2 based on sonic temperature considering only the errors from having a finite number of turbulent samples. The Bayesian and power spectral methods were found to give adequate estimates for strong turbulence levels but consistently overestimated the Cn2 for weak turbulence. The nearest neighbors and structure function methods performed well under all turbulence strengths tested
Constraining Accreted Neutron Star Crust Shallow Heating with the Inferred Depth of Carbon Ignition in X-ray Superbursts
Get PDFEvidence has accumulated for an as-yet unaccounted for source of heat located at shallow depths within the accreted neutron star crust. However, the nature of this heat source is unknown. I demonstrate that the inferred depth of carbon ignition in X-ray superbursts can be used as an additional constraint for the magnitude and depth of shallow heating. The inferred shallow heating properties are relatively insensitive to the assumed crust composition and carbon fusion reaction rate. For low-accretion rates, the results are weakly dependent on the duration of the accretion outburst, so long as accretion has ensued for enough time to replace the ocean down to the superburst ignition depth. For accretion rates at the Eddington rate, results show a stronger dependence on the outburst duration. Consistent with earlier work, it is shown that urca cooling does not impact the calculated superburst ignition depth unless there is some proximity in depth between the heating and cooling sources
Leveraging Large Language Models for Word Sense Disambiguation
No full textNatural language processing (NLP) is difficult because human language contains ambiguity. The same word can have a different meaning depending on the context and may result in different interpretations given biases held by a NLP technique. Correctly interpreting this ambiguity is not simply an important task in its own right but is a key enabler to major NLP activities such as machine translation and question answering. This research proposes three techniques to evaluate a large language models’(LLMs) ability to perform word sense disambiguation (WSD) and explores the efficacy of seven generative LLMs. The first technique assesses whether LLMs can, given a context sentence, select the correct word sense from a menu of options. The second asks LLMs, without options provided, to state whether or not a provided word sense is correct. The third technique presents the LLMs with context and an unseen word, assessing whether the LLMs can infer from context the sense of a word that it has not seen during training. Results demonstrate a strong relationship between model size and performance. Applications of WSD are demonstrated as part of an information extraction pipelines supporting sentiment analysis and as part of an LLM-evaluation suite to support machine learning operations
A Comparative Study of the Business Models Used in the U.S. and Saudi Arabia Firms in Relation to Venture Capital
Get PDFWhile venture capital (VC) has expanded globally, challenges in comparing international VC strategies remain due to data limitations and theoretical variability. This study contrasts VC investment philosophies, support mechanisms, and exit strategies in mature US firms with those in developing Saudi Arabia from 2016-2021. Analyzing fundraising, sector focus, deal volume, and exit outcomes, it finds significant differences attributed to ecosystem maturity, with some convergence in contracting and mentoring. The findings highlight the need for US VC models to adapt strategically in Islamic markets, suggesting regulatory reforms for market development. This research provides guidelines for effective cross-border VC strategy adaptation