Multiple Pursuer-Based Intercept via Forward Stochastic Reachability.
Abstract not provided.
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Abstract not provided.
Interception of a moving and potentially evading target can be a challenging problem, in particular for conditions in which the target may be moving at high speeds and difficult to detect. We have proposed to merge two Sandia LDRD efforts, the SPARR Spiking/Processing Array (neuromorphic event-driven sensing) and the Dragonfly-Inspired Algorithms for Intercept- Trajectory Planning (neural-inspired algorithms for interception) toward a unified system with direct application to national security. Neuromorphic systems demonstrate the most potential for speed and efficiency gains when communication is event-driven and computations are simple but parallelizable. Accordingly, we anticipate fully realizing potential benefits from a neuromorphic interception system if event-driven sensing is combined with processing and acting also implemented on event-driven (spiking) systems. We have successfully translated a neural-inspired interception algorithm to a neural network architecture for evaluation on neuromorphic hardware. Preliminary implementations of the neural network designed for implementation on the Loihi chip are still too immature for conclusive evaluation, but the results of this effort have demonstrated a viable path for a previously developed dragonfly-inspired interception algorithm to be implemented on neuromorphic hardware.
Changes in canopy architecture traits have been shown to contribute to yield increases. Optimizing both light interception and light interception efficiency of agricultural crop canopies will be essential to meeting the growing food needs. Canopy architecture is inherently three-dimensional (3D), but many approaches to measuring canopy architecture component traits treat the canopy as a two-dimensional (2D) structure to make large scale measurement, selective breeding, and gene identification logistically feasible. We develop a high throughput voxel carving strategy to reconstruct 3D representations of sorghum from a small number of RGB photos. Our approach builds on the voxel carving algorithm to allow for fully automatic reconstruction of hundreds of plants. It was employed to generate 3D reconstructions of individual plants within a sorghum association population at the late vegetative stage of development. Light interception parameters estimated from these reconstructions enabled the identification of known and previously unreported loci controlling light interception efficiency in sorghum. The approach is generalizable and scalable, and it enables 3D reconstructions from existing plant high throughput phenotyping datasets. We also propose a set of best practices to increase 3D reconstructions’ accuracy.
Borrowing from nature, neural-inspired interception algorithms were implemented onboard a vehicle. To maximize success, work was conducted in parallel within a simulated environment and on physical hardware. The intercept vehicle used only optical imaging to detect and track the target. A successful outcome is the proof-of-concept demonstration of a neural-inspired algorithm autonomously guiding a vehicle to intercept a moving target. This work tried to establish the key parameters for the intercept algorithm (sensors and vehicle) and expand the knowledge and capabilities of implementing neural-inspired algorithms in simulation and on hardware.
Snowpack accumulation in forested watersheds depends on the amount of snow intercepted in the canopy and its partitioning into sublimation, unloading, and melt. A lack of canopy snow measurements limits our ability to evaluate models that simulate canopy processes and predict snowpack. We tested whether monitoring changes in wind-induced tree sway is a viable technique for detecting snow interception and quantifying canopy snow water equivalent (SWE). Over a 6 year period in Colorado, we monitored hourly sway of two conifers, each instrumented with an accelerometer sampling at 12 Hz. We developed an approach to distinguish changes in sway frequency due to thermal effects on tree rigidity versus intercepted snow mass. Over 60% of days with canopy snow had a sway signal that could not be distinguished from thermal effects. However, larger changes in tree sway could not generally be attributed to thermal effects, and canopy snow was present 93%–95% of the time, as confirmed with classified PhenoCam imagery. Using sway tests, we converted changes in sway to canopy SWE, which were correlated with total snowstorm amounts from a nearby SNOTEL site (Spearman r = 0.72 to 0.80, p < 0.001). Greater canopy SWE was associated with storm temperatures between -7°C and 0°C and wind speeds less than 4 m s -1 . Lower canopy SWE prevailed in storms with lower temperatures and higher wind speeds. Monitoring tree sway is a viable approach for quantifying canopy SWE, but challenges remain in converting changes in sway to mass and distinguishing thermal and snow mass effects on tree sway.
Dragonflies are known to be highly successful hunters (achieving 90-95% success rate in nature) that implement a guidance law like proportional navigation to intercept their prey. This project tested the hypothesis that dragonflies are able to implement proportional navigation using prey-image translation on their eyes. The model dragonfly presented here calculates changes in pitch and yaw to maintain the prey's image at a designated location (the fovea) on a two-dimensional screen (the model's eyes ). When the model also uses self-knowledge of its own maneuvers as an error signal to adjust the location of the fovea, its interception trajectory becomes equivalent to proportional navigation. I also show that this model can also be applied successfully (in a limited number of scenarios) against maneuvering prey. My results provide a proof-of-concept demonstration of the potential of using the dragonfly nervous system to design a robust interception algorithm for implementation on a man-made system.
High-energy particles, including photons (x-ray, γ-ray, bremsstrahlung), electrons, and protons, possess the capability to penetrate materials and deposit energy within them. The degree of absorption depends on both the energy and type of particles, as well as the properties of the materials with which they interact. This energy deposition can manifest either at the material's surface or throughout its volume, potentially resulting in various failure modes. The primary aim of this paper is to establish a structured analysis methodology for evaluating the structural integrity of beam-intercepting devices when subjected to high-energy particles. Here, the paper also reviews some of the underlying physics, pertinent to the scope of the thermomechanical analysis, potential failure modes, and introduces verification and validation methodologies. Engineers and researchers can utilize the guidelines presented in this paper to effectively plan the development of beam intercepting devices, thereby ensuring their reliability and performance in the presence of high-energy particle exposure.
A previous publication [P. D. McChesney, “Multi-plate interceptive electron beam energy diagnostic—Theoretical design,” AIP Adv. (submitted)] reported a new interceptive electron beam kinetic energy measurement technique based on the beam penetration depth within a stack of conductive plates and gave results on the theoretical design of such a device. This paper expands on this and gives further results on the actual implementation of the diagnostic. The device geometry and measurement electronics system are described in detail. A prototype version of the multi-plate diagnostic was fabricated and tested using an electron linear accelerator at the Idaho Accelerator Center (IAC). A high-precision magnetic spectrometer system was designed and built for the purpose of validating the multi-plate diagnostic’s energy measurement capabilities. It was found that the diagnostic provides electron beam energy estimates that are accurate to better than the 10% level.
The talk concerns the summary of the Working Group E related to Instrumentation and Intercepting Devices
When a fusion plasma suddenly intercepts a solid surface (wall or pellet), thermal collapse is distinctly kinetic & has novel physics. VPIC simulations & theory revealed the fascinating dynamics of four propagating fronts controlling parallel electron temperature cooling.
Nuclear grade fine-grain graphite has played a central role in particle accelerator Beam Intercepting Devices, BID (e.g. targets or beam dumps) for decades, especially for high beam power facilities, such as at Fermilab, CERN, PSI and JPARC. Operations of these facilities have demonstrated graphite’s reliable performance at beam powers up to about 1 MW and enduring over 10 million thermal shock cycles of over 3x10 7 K/s. Planned future accelerator facilities will push BID beam power capability into the multi-MW regime. The material challenges of such MW-class accelerator facilities, how graphite may meet those challenges, as well as an overview of recent and current research on graphite for high power accelerator BID will be presented.
Abstract not provided
A comparative analysis of the attachment efficacy of sharpened vs blunted air terminals under a strong background DC electric field, similar to conditions found in naturally occurring lightning events, is presented. Testing was conducted using an oil-free, 17-stage, 1.4 MV bipolar Marx generator with a biased discharge plane that emulated the conditions found prior to the lightning return stroke. The biased discharge plane allowed the introduction of a strong DC electric field and subsequent corona formation on a time scale much longer than the brief duration over which the downward leader propagates. Initial observations indicate that despite a higher background electric field at the sharpened terminals, leading to pre-discharge corona formation where none is seen on the blunt terminal, both the sharpened and blunted terminals exhibit similar attachment probabilities during discharge events, with some discharge events attaching to both terminals.
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The results of experimental studies into the application of anisotropic pyrolytic graphite (APG) as grid structures in power microwave devices with a dispenser cathode are detailed. The dependences of emission characteristics of molybdenum, hafnium, and APG in diodes and electron guns on the electron-flow power dissipated at the studied samples and on cathode temperature are presented. It is demonstrated that the power dissipation capacity of APG grid structures (without parasitic thermionic emission) is up to 20 and 9 times higher than that of molybdenum and hafnium grids, respectively.
Abstract not provided.