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Effect of Matrix Material on Ballistic Limit for Composite Armor
No full textThe test team performed a comprehensive investigation into the ballistic performance of composite armor materials, with a focus on aramid and S-2 fiberglass fiber composites. The study aims to update existing testing standards, particularly MIL-STD-662F, by providing detailed insights into the effects of weave matrices and secondary impacts on ballistic strength. The research employs a rigorous experimental approach utilizing the Three-Phased Optimal Design algorithm to determine V50 values for various composite materials. Special attention is given to understanding the influence of fabric weave matrices on ballistic performance of primary and secondary impacts. Testing methodologies categorized secondary shots into close and medium shot-to-shot proximities to assess the effects of secondary impacts on V50. Results showed significant variations in ballistic performance based on matrix material, shot-to-shot distance, and delamination effects. The findings underscore the importance of matrix material selection, testing methodologies, and ongoing research to optimize composite armor design for enhanced ballistic resistance in modern conflict scenarios
Display System Interface Using Visually-Evoked Cortical Potentials
Full text linkA brain-computer interface system includes a video processor for producing a display signal, a temporal controller for producing a plurality of repetitive visual stimulus (RVS) signals with different respective temporal aspects, a display device that receives the display signal and displays a corresponding image on a plurality of different display regions and receives the RVS signals and displays corresponding RVS in respective ones of the display regions, an electroencephalographic (EEG) sensor for sensing a visually-evoked cortical potential (VECP) signal in a user with eyes fixated on a viewed one of the display regions, and a VECP processor for processing the VECP signal to identify the respective temporal aspect of the respective RVS of the viewed display region to estimate the eye fixation location. The RVS are generated independently of the display update/refresh rate and at sufficiently high frequencies to avoid flicker perceptible to the user
An Entanglement Swapping Throughput Analysis for Quantum Networks Using Linear Quantum Optics
No full textDecomposing complex systems into smaller abstract functional blocks and developing mathematical models to represent their behavior is an important activity towards developing comprehensive system understanding. In this paper, we extract an essential functional block known as Bell State Measurement from a notional quantum network system implemented using linear quantum optics. Bell State Measurement is required for the geographic distribution of unknown quantum states via quantum teleportation and entanglement swapping. A statistical model is developed to estimate the probability of successfully sending an unknown quantum state across a quantum network segment using entanglement swapping. The abstract model greatly simplifies the performance analysis of a quantum network in terms of its throughput. This paper is introductory in nature and is intended to help those who are relatively new to modeling, simulating, and analyzing ideal quantum networks
Using Rhai to Create and Benchmark Bevy Entities
No full textThe paradigm shift within the industry towards multi-threaded processing has engendered a novel approach to developing highly performant and scalable computing applications. As the fundamental constraints of Object-Oriented programming languages become increasingly apparent in such hardware environments, Data-Oriented Design (DOD) endeavors to redirect developers’ focus away from superfluous abstraction and towards the intricacies of efficiently manipulating substantial volumes of data. While this methodology effectively harnesses the capabilities of contemporary hardware, it also poses a barrier to entry for novice developers and enthusiasts. The Rhai scripting language presents a high-level Application Program Interface (API) that can seamlessly integrate into existing Rust projects, thereby fostering inclusivity within this community. An investigation into the inherent performance ramifications of adopting such an approach will be conducted within the framework of DOD-centric data structures
Book Talk on Brief: \u3ci\u3eMake a Bigger Impact by Saying Less\u3c/i\u3e by Jonathan McCormack: Ten Key Concepts and Six Lessons for Improving Communication in a World Full of Distractions
No full textThis Lunch and Learn presentation, delivered by Wheeler Hall from the D’Azzo Research Library (DRL) and hosted by the Center for Innovation in Education (CIE), focuses on the principles outlined in Joseph McCormack’s Brief: Make a Bigger Impact by Saying Less (2014). The session serves as a summary for the book and explores strategies for effective communication in a distraction-filled world, emphasizing brevity, clarity, and audience engagement. After an introduction from Jonathan Zemmer (CIE), Mr. Hall relays McCormack’s background, the practical workplace applications in Brief, and key concepts from the book, including the BRIEF mnemonic (Background, Reason, Information, Ending, Follow-up), the seven capital sins of communication, and the importance of storytelling. The presentation concludes with six lessons for refining communication, including thorough research, concise delivery, and respect for others’ time. Viewers are encouraged to borrow copies of the book from the library to further enhance their communication skills, applicable in both professional and personal contexts
Machine learning coupled laser-induced breakdown self-reversal isotopic spectrometry for determining lithium isotope concentration
No full textFrom Standardization to Personalization: Leveraging Learner Profiles to Tailor Education
No full textStatistical Reliability Estimation of Earth-Orbiting Satellites Operating from 1991 to 2020
No full textReliability analysis using satellite failure data for satellites launched in the years 1991–2020 is presented. The analysis is conducted using nonparametric as well as parametric methods. In order to derive a nonparametric reliability estimate from the raw failure data, the Kaplan–Meier estimator is utilized. In order to determine a correct distribution to parameterize the nonparametric estimate, a novel distribution identification framework is applied. The Weibull distribution is consistently identified as best and is then utilized to parameterize the behaviors seen in the nonparametric results. A novel robust regression parameterization method is also applied to improve the traditional regression methodology. Data are split into three decade-long groups with respect to launch dates to investigate time-based trends. Results from this analysis show the most recent decade (2011–2020) to be the worst performing in terms of reliability. This decade in particular is found to be plagued by early or failed reentry cases
Statistical Overview of Long-Lived Active Regions Observed Across Multiple Carrington Rotations
No full textThe study of solar active regions (ARs) is of central importance to a range of fundamental science, as well as the practical applications of space weather. Active region emergence and life cycles are two areas of particular interest, yet the lack of consistent full-Sun observations has made long-term studies of active regions difficult. Here, we present results from a study to identify and characterize long-lived active regions (LLARs), defined as those which were observed during at least two consecutive Carrington rotations and which did not undergo significant successive flux emergence once the decay phase began. Such active regions accounted for 13% of all NOAA-identified ARs between 2011 and 2019, and their distribution closely follows the annual sunspot number. This implies that LLARs are produced by the same basic driving processes as regular ARs. LLAR areas tend to be significantly larger and contain more magnetic flux compared to other ARs, but the two categories have similar magnetic complexity distributions. The most striking result, however, is that LLARs are 3-6 times more likely than other ARs to be the source of a solar flare of GOES class C or greater. This highlights the importance of studying what makes a LLAR and how to identify them at emergence with a view towards improved space weather forecasting. The further implications of these findings for AR heating spatial and temporal patterns will be explored in an upcoming study