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Minimum Time Escape from a Circular Region of a Dubins Car
No full textA turn-constrained evader strives to escape a circular region in minimum time
Characterizing Military Medical Evacuation Dispatching and Delivery Policies via a Self-Exciting Spatio-Temporal Hawkes Process Model
No full textThe military medical evacuation (MEDEVAC) system is the primary method to evacuate time-sensitive combat casualties from the battlefield to appropriately staffed and equipped medical treatment facilities (MTFs). The intent of this paper is to analyze how MTF capability and capacity impact MEDEVAC system performance. We develop a self-exciting spatio-temporal Hawkes process model as well as a notional, synthetically generated MEDEVAC scenario of the post-Bosnian War to evaluate and compare eight distinct MEDEVAC dispatching and delivery policies within a high-intensity combat environment. The results garnered from this paper highlight the substantial impact MTFs have on MEDEVAC systems and should be considered in future research
Mo-Re-W Alloys for High temperature Applications: Phase stability, elasticity, and thermal property insights via multi-cell Monte Carlo and machine learning
No full textThe increasing demand for materials capable of withstanding high temperatures and harsh environments necessitates the discovery of advanced alloys. This study introduces a computational routine to predict solid-state phase stability and calculates elastic constants to determine high temperature viability. With it, machine learning models were trained on 1,014 Mo-Re-W structures to enable a large compilation of elastic and thermal properties over the complete Mo-Re-W compositional domain with extreme resolution. A series of heat maps spanning the full compositional domain were generated to visually present the impact of alloy constituents on the alloy properties. Our findings identified a balanced (Mo,W) + Re blend as a promising composition for high temperature applications, attributed to a strong and stable (Mo,W) matrix with high Re content and the formation of strengthening (W,Re) precipitates that enhanced mechanical performance at 1600°C. Several Mo-Re-W compositions were manufactured to experimentally validate the computational predictions. This approach provides an efficient and system-agnostic pathway for designing and optimizing alloys for high-temperature applications
Numerically Efficient Coherent Mode Representations for Partially Coherent Beams with Separable Phases
Get PDFWe present a method to numerically compute the coherent mode representations (CMRs) for partially coherent beams with separable phases. This special class of random light field has the ability to self-focus and is resistant to turbulence-induced degradation, making it potentially useful in applications such as optical communications. We validate our method by generating (in simulation) two such sources from the literature using their computed CMRs. Lastly, we conclude with a summary of our approach and a discussion of potential applications
Rotorcraft Assisted Aircraft Inspection System: Creation and Component Assessment
Get PDFAircraft require frequent inspections to perform their missions safely. Current visual inspection methods are time-consuming and dangerous for inspection personnel, but they are necessary to spot flaws that could endanger the aircraft during flight. This research explores a set of methods for transforming a set of target inspection criteria into camera specifications that will allow a UAS aircraft inspection system to perform inspections on the top skin of an aircraft. Given the minimum distance for the UAS to fly above the aircraft, minimum flaw size to search for on the aircraft, minimum number of pixels to display that flaw size, and the resolution of a camera to be assessed, the paper presents a series of calculations to find the minimum lens focal length needed to achieve the desired clarity and how long it would take to inspect an aircraft of a given size. Hover tests and motion tests using a camera with a focal length calculated with these methods provided clear imagery of a target minimum flaw size, validating the focal length calculation methods. In addition, a proof-of-concept UAS inspection system consisting of two Allied Vision Mako G-507B cameras running on a NVIDIA Jetson Xavier NX developer kit was created. The inspection camera uses a zoom lens to observe flaws while the navigation camera uses a fisheye lens capable of multicasting to the Xavier and a ground station. Autonomous Navigation Center personnel will continue to iterate on this inspection system and integrate autonomous navigation capabilities and image search capabilities in pursuit of a fully viable system usable by aircraft inspectors
The Behavior of ½⟨111⟩ Screw Dislocations in W–Mo Alloys Analyzed through Atomistic Simulations
No full textAnalyzing plastic flow in refractory alloys is relevant to many different commercial and technological applications. In this study, screw dislocation statics and dynamics were studied for various compositions of the body-centered cubic binary alloy tungsten–molybdenum (W–Mo). The core structure did not appear to change for different alloy compositions, consistent with the literature. The pure tungsten and pure molybdenum samples had the lowest plastic flow, while the highest dislocation velocities were observed for equiatomic, W0.5Mo0.5 alloys. In general, dislocation velocities were found to largely align with a well-established dislocation mobility phenomenological model supporting two discrete dislocation mobility regimes, defined by kink-pair nucleation and migration and phonon drag, respectively. Velocities were observed to increase with temperature and applied shear stress and with decreasing kink-pair formation energies. The 50 at. % W alloy was found to possess the lowest kink-pair formation energy, consistent with its higher dislocation velocity. Furthermore, molybdenum segregation to the dislocation line was found to be thermodynamically favorable specifically at low temperatures and was observed to significantly delay the onset of dislocation glide and then generally enhance dislocation velocities thereafter. This behavior was explained by examining the energy landscape of dislocation glide. Furthermore, a segregation/de-segregation phase transition was observed to occur around 2500 K beyond which no preferential segregation to the dislocation was found. Overall, our findings suggest strong dependencies of plastic flow in W–Mo alloys on composition and elemental segregation, in agreement with the available literature, and may provide useful information to guide the design of next generation structural materials
Exploring Quaternion Neural Network Loss Surfaces
Get PDFThis paper explores the superior performance of quaternion multi-layer perceptron (QMLP) neural networks over real-valued multi-layer perceptron (MLP) neural networks, a phenomenon that has been empirically observed but not thoroughly investigated. The study utilizes loss surface visualization and projection techniques to examine quaternion-based optimization loss surfaces for the first time. The primary contribution of this research is the statistical evidence that QMLP models yield smoother loss surfaces than real-valued neural networks, which are measured and compared using a robust quantitative measure of loss surface “goodness” based on estimates of surface curvature. Extensive computational testing validates the effectiveness of these surface curvature estimates. The paper presents a comprehensive comparison of the average surface curvature of a tuned QMLP model and a tuned real-valued MLP model on both a regression task and a classification task. The results provide strong support for the improved optimization performance observed in QMLPs across various problem domains
Temporal Metadata Analysis: A Learning Classifier System Approach
Get PDFDigital forensics is a complex field that requires expert knowledge (EK) and specialized tools to collect, analyze, and report on digital evidence. Temporal metadata analysis is particularly challenging, requiring expert knowledge to understand and interpret underlying traces and associate them with their source. This paper introduces Digital Trace Inspector (DTI), a Learning Classifier System (LCS)-based decision support tool for temporal metadata analysis. DTI leverages a binary Michigan-style LCS to locate and group corroborating temporal digital traces of targeted user activity. Rules are built from expert-created atomics encoded as feature vectors using patterns defined in a structured EK rule framework. The system is evaluated on 10 scenarios of typical user behavior on a Windows 10 workstation. Results show that all models achieved perfect recall, had an average F1 score of 0.98, and required little training data.
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Production Box Cost Estimating Relationships for DoD Avionics
Get PDFThe authors use historical information obtained from the Cost Assessment Data Enterprise to estimate recurring production unit cost for DoD avionics via cost estimating relationships (CERs). The specific modeled responses include mean unit cost, median unit cost, and the 100th production unit cost (T100) utilizing learning curve theory. For T100, the authors adopt both a multiplicative and an additive error for CER comparison. Recommended CERs consist of the mean unit cost and the T100 utilizing a multiplicative error. Moreover, results reveal that weight has a significant effect on cost as well as a potential underaccounting of real price change or technology complexity of 3%, according to the selected sample