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At least 217 records · Page 12

Interface Conductance Under a Real Electronics Box

Electronics Boxes with high heat dissipations use a thermal interface material to increase heat transfer to the radiator in a vacuum/space environment. There are lots of materials to choose from, but for Spacecraft applications, there are more than high heat transfer metrics which must be met. Contamination (both particle generation and outgassing), ease of cutting, and removal are just as important metrics in material selection. However, vendor data of material thermal conductance is usually based on a 1" X 1" piece of material under high uniform pressures. Large Electronics boxes almost never have optimal pressures, as they are bolted along the perimeter and leave gaps in the center regions. In order to characterize the relative thermal conductance for large Electronics boxes, an 8" X 8" plate was fabricated to simulate an electronics box bottom and bolted around the perimeter to a cold plate. Various thermal interface materials were inserted between the box and cold plate, and overall thermal conductance's were calculated. A table was generated which compares the full gamut of thermal interface materials for large boxes, from a dry joint to a wet joint. Materials were placed in order of high to low conductance's, so an engineer can compare the benefit of each material in a real-world scenario.

Thermal Interface Conductance↗

Laser Light Sheet Flow Visualization of the Space Launch System Booster Separation Test

Planar flow visualizations were obtained in a wind tunnel test in the NASA Langley Research Center’s Unitary Plan Wind Tunnel using the laser-light-sheet method. This method uses a laser to illuminate fine particles generated in the wind tunnel to visualize flow structures. The test article was designed to simulate the separation of the two solid rocket boosters (SRBs) from the core stage of the NASA Space Launch System (SLS) at Mach 4 using a scale model. The test was run on of the SLS Block 1B Cargo (27005) configuration and the SLS Block 1B Crew (28005) configuration. Planar flow visualization was obtained only on the crew configuration. Air at pressures up to 1500 psi was used to simulate plumes from the booster separation motors (BSMs) located at the nose, and aft skirt of the two boosters. The facility free stream was seeded with water vapor, which condensed and froze into small ice crystals in the tunnel nozzle expansion. A continuous wave green (532 nm) laser sheet was used to illuminate the ice crystals, and the resulting Mie-scattered light was collected with a camera. The resulting images clearly identify shock waves and other flow features including BSM plume shapes. Measurements were acquired for different BSM pressures and booster separation locations.

Danehy, Paul M.↗

Quantitative Radiation Thermometry Using Commercially Available High-Speed Video Cameras

In order to understand the risk posed to astronauts by electric arc-generated particles, high-speed, high-resolution, quantitative thermal imaging was needed. The measurement requirements appeared to be beyond the capabilities of commercial thermal imaging systems, but the particles were known to have a significant amount of emission in the visible spectrum. This led to the use of commercially available, high-speed video cameras as imaging radiometers. Measured particle temperatures were consistent with predictions and other measurement data. The optical temperature measurement method, results, and conclusions are presented, along with recommendations for further work.

Thermal imaging↗

Development and Evaluation of the Raindrop Size Distribution Parameters for the NASA Global Precipitation Measurement Mission Ground Validation Program

The National Aeronautics and Space Administration Global Precipitation Measurement (GPM) mission ground validation program uses dual-polarization radar moments to estimate raindrop size distribution (DSD) parameters, the mass-weighted mean drop diameter Dmass, and normalized intercept parameter NW, to validate the GPM Core Observatory–derived DSD parameters. The disdrometer-based Dmass and NW are derived through empirical relationships between Dmass and differential reflectivity ZDR, and between NW, reflectivity ZH, and Dmass. This study employs large datasets collected from two-dimensional video disdrometers (2DVD) during six different field studies to derive the requisite empirical relationships. The uncertainty of the derived Dmass(ZDR) relationship is evaluated through comparisons of 2DVD-calculated and ZDR-estimated Dmass, where ZDR is calculated directly from 2DVD observations. Similarly, the uncertainty of the NW(ZH, Dmass) relationship is evaluated through 2DVD-calculated and Dmass and ZH-estimated NW, where Dmass and ZH are directly calculated from 2DVD observations. This study also presents the sensitivity of Dmass(ZDR) relationships to climate regime and to disdrometer type after developing three additional Dmass(ZDR) relationships from second-generation Particle Size Velocity (PARSIVEL2) disdrometer (P2) observations collected in the Pacific Northwest, in Iowa, and at Kwajalein Atoll in the tropical Pacific Ocean. The application of P2-derived Dmass(ZDR) relationship based on precipitation in the northwestern United States to P2 observations collected over the tropical ocean resulted in the highest error among comparisons of the three datasets.

Ali Tokay↗

An Overview of Experiments in The Entry Systems Modeling Project

The Entry Systems Modeling (ESM) project has invested in experiments designed to enhance understanding of salient interactions between thermal protection materials (TPS) and mission-relevant planetary entry environments. An arc-jet campaign has been carried out at the Aerodynamic Heating Facility (AHF) to investigate the spallation of fiber particles as a function of gas composition and to measure the effect of pyrolysis gas flow on the in-depth temperature response of phenolic impregnated carbon ablator (PICA). Moreover, fundamental insights into the pyrolysis and oxidation mechanisms of the phenolic binding agent of FiberForm will be discussed. Finally, two new apparatus developed at NASA will be presented that were designed to interrogate phenomena associated with the production of gases and particles generated under simulated flight conditions.

Material Response↗

An Overview of Experiments in The Entry Systems Modeling Project

The Entry Systems Modeling (ESM) project has invested in experiments designed to enhance understanding of salient interactions between thermal protection materials (TPS) and mission-relevant planetary entry environments. An arc-jet campaign has been carried out at the Aerodynamic Heating Facility (AHF) to investigate the spallation of fiber particles as a function of gas composition and to measure the effect of pyrolysis gas flow on the in-depth temperature response of phenolic impregnated carbon ablator (PICA). Moreover, fundamental insights into the pyrolysis and oxidation mechanisms of the phenolic binding agent of FiberForm will be discussed. Finally, two new apparatus developed at NASA will be presented that were designed to interrogate phenomena associated with the production of gases and particles generated under simulated flight conditions.

Varcum↗

The Trajectory of Recent Solid State Fusion Results

Both NASA and Google have explored and funded Low Energy Nuclear Reaction (LENR) aka Solid-State Fusion or Lattice Confinement Fusion (LCF) research. NASA has funded efforts since 1989, and Google Research began in 2014. Google, and researchers initially-funded by Google, published significant scientific papers in Nature, Nature Communications and the Journal of Applied Physics. NASA began a significant set of LENR-triggering programs in 2012 resulting in papers in Physical Review C, the Journal of Electroanalytical Chemistry and the Journal of Condensed Matter Nuclear Science. Both NASA and Google engaged researchers across fields of nuclear physics, chemistry, electrochemistry, material science and more. NASA built upon early novel gas pumping experiments then followed the patented work of the US Navy SPAWAR (US8,419,919, “System and Method to Generate Particles”) and experiments with the Naval Surface Warfare Centers. Google supported researchers at Lawrence Berkeley National Laboratory (LBNL), the University of British Columbia (UBC), MIT and others. This resulted in patent applications and two granted patents (US10264661B2, “Target structure for enhanced electron screening” and US10566094B2 “Enhanced electron screening through plasmon oscillations”). These separate efforts, unknown to the researchers at the time, provided the impetus for the DoE ARPA-E LENR program followed by the DARPA DSO “Mechanisms for Amplification of Fusion Reaction Rates in Solids” (MARRS) program. This document briefly describes the overlapping NASA and Google Research efforts in plasma loading and electron screening emphasizing the results of the latest paper in Nature Communications. The papers and patents cited are listed.

electron screening↗

Flow matching beyond kinematics: Generating jets with particle identification and trajectory displacement information

We introduce the first generative model trained on the etlass dataset. Our model generates jets at the constituent level, and it is a permutation-equivariant continuous normalizing flow (CNF) trained with the flow matching technique. It is conditioned on the jet type, so that a single model can be used to generate the ten different jet types of etlass. For the first time, we also introduce a generative model that goes beyond the kinematic features of jet constituents. The etlass dataset includes more features, such as particle-ID and track impact parameter, and we demonstrate that our CNF can accurately model all of these additional features as well. Our generative model for etlass expands on the versatility of existing jet generation techniques, enhancing their potential utility in high-energy physics research, and offering a more comprehensive understanding of the generated jets. Published by the American Physical Society 2025

Birk, Joschka (ORCID:0000000219310127)↗

Conditional guided generative diffusion for particle accelerator beam diagnostics

Abstract Advanced accelerator-based light sources such as free electron lasers (FEL) accelerate highly relativistic electron beams to generate incredibly short (10s of femtoseconds) coherent flashes of light for dynamic imaging, whose brightness exceeds that of traditional synchrotron-based light sources by orders of magnitude. FEL operation requires precise control of the shape and energy of the extremely short electron bunches whose characteristics directly translate into the properties of the produced light. Control of short intense beams is difficult due to beam characteristics drifting with time and complex collective effects such as space charge and coherent synchrotron radiation. Detailed diagnostics of beam properties are therefore essential for precise beam control. Such measurements typically rely on a destructive approach based on a combination of a transverse deflecting resonant cavity followed by a dipole magnet in order to measure a beam’s 2D time vs energy longitudinal phase-space distribution. In this paper, we develop a non-invasive virtual diagnostic of an electron beam’s longitudinal phase space at megapixel resolution (1024 × 1024) based on a generative conditional diffusion model. We demonstrate the model’s generative ability on experimental data from the European X-ray FEL.

43 PARTICLE ACCELERATORS↗

Optical properties and composition of viscous organic particles found in the Southern Great Plains

Abstract. Atmospheric high-viscosity organic particles (HVOPs) were observed in samples of ambient aerosols collected in April and May 2016 in the Southern Great Plains of the United States. These particles were apportioned as either airborne soil organic particles (ASOPs) or tar balls (TBs) from biomass burning based on spetro-microscopic imaging and assessments of meteorological records of smoke and precipitation data. Regardless of their apportionment, the number fractions of HVOPs were positively correlated (R2=0.85) with increased values of absorption Ångström exponent (AAE) measured in situ for ambient aerosol at the site. Extending this correlation to 100 % HVOPs yields an AAE of 2.6, similar to previous literature reports of the class of light-absorbing organic particles known as brown carbon (BrC). One out of the three samples investigated had a significant number of ASOPs, while the other two samples contained TBs. Although there are chemical similarities between ASOPs and TBs, they can be distinguished based on composition inferred from near-edge absorption X-ray fine structure (NEXAFS) spectroscopy. ASOPs were distinguished from TBs based on their average -COOH/C=C and -COOH/COH peak ratios, with ASOPs having lower ratios. NEXAFS spectra of filtered soil organic brine particles nebulized from field samples of standing water deposited after rain were consistent with ASOPs when laboratory particles were generated by bubble bursting at the air–organic brine interface. However, particles generated by nebulizing the bulk volume of soil organic brine had a particle composition different from ASOPs. These observations are consistent with the raindrop generation mechanism responsible for ASOP emissions in the area of study. In contrast, nebulized samples carry with them higher fractions of soil inorganics dissolved in the bulk volume of soil brine, which are not aerosolized by the raindrop mechanism. Our results support the bubble bursting mechanism of particle generation during rainfall resulting in the ejection of soil organics into the atmosphere. In addition, our results show that ASOPs may only be atmospherically relevant during times when suitable emission conditions are met.

54 ENVIRONMENTAL SCIENCES↗

Generative Ensemble Regression: Learning Particle Dynamics from Observations of Ensembles with Physics-informed Deep Generative Models

Here, we propose a new method for inferring the governing stochastic ordinary differential equations (SODEs) by observing particle ensembles at discrete and sparse time instants, i.e., multiple “snapshots.” Particle coordinates at a single time instant, possibly noisy or truncated, are recorded in each snapshot but are unpaired across the snapshots. By training a physics-informed generative model that generates “fake” sample paths, we aim to fit the observed particle ensemble distributions with a curve in the probability measure space, which is induced from the inferred particle dynamics. We employ different metrics to quantify the differences between distributions, e.g., the sliced Wasserstein distances and the adversarial losses in generative adversarial networks. We refer to this method as generative “ensemble-regression” (GER), in analogy to the classic “point-regression,” where we infer the dynamics by performing regression in the Euclidean space. We illustrate the GER by learning the drift and diffusion terms of particle ensembles governed by SODEs with Brownian motions and Lévy processes up to 100 dimensions. We also discuss how to treat cases with noisy or truncated observations. Apart from systems consisting of independent particles, we also tackle nonlocal interacting particle systems with unknown interaction potential parameters by constructing a physics-informed loss function. Finally, we investigate scenarios of paired observations and discuss how to reduce the dimensionality in such cases by proving a convergence theorem that provides theoretical support.

97 MATHEMATICS AND COMPUTING↗

The generation of entangled states from independent particle sources

The generation of entangled states of two systems from product states is discussed for the case in which the paths of the two systems do not overlap. A particular method of measuring allows one to project out the nonlocal entangled state. An application to the production of four photon entangled states is outlined.

Rubin, Morton H.↗

Particle Acceleration, Magnetic Field Generation and Emission from Relativistic Jets and Supernova Remnants

We performed numerical simulations of particle acceleration, magnetic field generation, and emission from shocks in order to understand the observed emission from relativistic jets and supernova remnants. The investigation involves the study of collisionless shocks, where the Weibel instability is responsible for particle acceleration as well as magnetic field generation. A 3-D relativistic particle-in-cell (RPIC) code has been used to investigate the shock processes in electron-positron plasmas. The evolution of theWeibe1 instability and its associated magnetic field generation and particle acceleration are studied with two different jet velocities (0 = 2,5 - slow, fast) corresponding to either outflows in supernova remnants or relativistic jets, such as those found in AGNs and microquasars. Slow jets have intrinsically different structures in both the generated magnetic fields and the accelerated particle spectrum. In particular, the jet head has a very weak magnetic field and the ambient electrons are strongly accelerated and dragged by the jet particles. The simulation results exhibit jitter radiation from inhomogeneous magnetic fields, generated by the Weibel instability, which has different spectral properties than standard synchrotron emission in a homogeneous magnetic field.

Nishikawa, K.-I.↗

The Solid Rocket Motor Slag Population: Results of a Radar-Based Regressive Statistical Evaluation

Solid rocket motor (SRM) slag has been identified as a potential source of man-made orbital debris. The possibility that SRMs (in addition to generating dust particles in the sub-millimeter range) may generate particles up to centimeters in size has caused concern regarding their contribution to the debris environment. Returned surfaces from space do not have sufficient area or exposure time to provide a clear picture of the SRM millimeter and centimeter debris population. Currently, radar observation is probably the only way to collect data showing the debris contribution from SRMs. Such observation is used to sample the debris environment, but it is difficult to obtain accurate orbital elements for the detected debris objects. NASA has developed several models to describe the different orbital debris populations, based on assumed debris production mechanisms to create clouds of debris objects that can be propagated in time. The NASA model, LEGEND (LEO-to-GEO Environment Debris), functions as a time-tested debris model for most debris sources. However, the current LEGEND model does not include contributions from the SRM population. An SRM model has recently been developed by NASA, based on purely theoretical details of SRM production and known SRM launches, but verification with hard data is needed. Because the detections of individual SRM objects cannot be deterministically separated from the total debris observed by radar, the validation of the SRM model can only be done by combining it with the LEGEND breakup model and comparing it with data. By applying observational constraints, the degree of SRM slag contribution to the environment may be estimated. This serves as an observationally sound method from which to calibrate a purely theoretical model into something more realistic. For this study, we use the populations observed by the Haystack radar from 1996 to present. For the SRM debris, we use a historical database of SRM launches, propellant masses, and estimated locations and times of tailoff to produce and propagate the SRM debris clouds. Comparisons with radar data from the ensuing years were made, and the SRM model was altered with respect to size and mass production of slag particles to reflect the populations estimated from the data. The result is a model SRM population that fits within the bounds of the observed environment and estimates of the production and contribution of SRM debris to the environment.

Horstman, Matthew F.↗

Particle Loading Tests on HEPA Flat Sheet Media at Sub-Ambient Pressures Using a Lunar Dust Simulant

When humans return to the moon under the NASA Artemis program, their activities on the lunar surface will inevitably lead to the intrusion of some level of lunar dust into the lander cabin. Therein the crew would be exposed to the potential hazards of lunar dust and the possibility of subsequent transfer into orbiting segments after docking. The spacecraft’s cabin filtration system will need to be effective at removing the airborne lunar dust to properly purify the breathable cabin air and minimize the spreading of the dust throughout the vehicle and orbital segments through the mission duration. The fine nature of the lunar dust will require high efficiency filtration, such as HEPA. A series of tests were performed in a specially designed recirculating sealed flow loop, for testing filter media and filter elements at the NASA Glenn Research Center. The flow loop was used to assess the performance and capacity of flat sheet filter media at representative cabin pressures using JSC-1AF lunar dust simulant and at high rates of particle loading. The pressure drop across the filter media was measured as a function of accumulated particle mass load at ambient pressure and at two sub-ambient pressures, 0.0703MPa and 0.0565MPa, and at a media velocity that was scaled relative to its pleated configuration. The challenge particle flows were generated by a custom designed particle generator that introduces dispersed particles of the lunar simulant at high concentrations. An optical particle counting instrument provided filter efficiency measurements within the sealed environment. The pressure drop was found to increase linearly with the amount of dust load on the media, for all test conditions, while the starting pressure drop was found to be lower at the lowest sub-ambient pressure case. High filter efficiency was maintained after high particle loads on the media.

Sub-ambient↗

Particle Loading Tests on HEPA Flat Sheet Media at Sub-Ambient Pressures Using a Lunar Dust Simulant

When humans return to the moon under the NASA Artemis program, their activities on the lunar surface will inevitably lead to the intrusion of some level of lunar dust into the lander cabin. Therein the crew would be exposed to the potential hazards of lunar dust and the possibility of subsequent transfer into orbiting segments after docking. The spacecraft’s cabin filtration system will need to be effective at removing the airborne lunar dust to properly purify the breathable cabin air and minimize the spreading of the dust throughout the vehicle and orbital segments through the mission duration. The fine nature of the lunar dust will require high efficiency filtration, such as HEPA. A series of tests were performed in a specially designed recirculating sealed flow loop, for testing filter media and filter elements at the NASA Glenn Research Center. The flow loop was used to assess the performance and capacity of flat sheet filter media at representative cabin pressures using JSC-1AF lunar he filter media was measured as a function of accumulated particle mdust simulant and at high rates of particle loading. The pressure drop across tass load at ambient pressure and at two sub-ambient pressures, 0.0703MPa and 0.0565MPa, and at a media velocity that was scaled relative to its pleated configuration. The challenge particle flows were generated by a custom designed particle generator that introduces dispersed particles of the lunar simulant at high concentrations. An optical particle counting instrument provided filter efficiency measurements within the sealed environment. The pressure drop was found to increase linearly with the amount of dust load on the media, for all test conditions, while the starting pressure drop was found to be lower at the lowest sub-ambient pressure case. High filter efficiency was maintained after high particle loads on the media

Sub-ambient↗

High-dimensional maximum-entropy phase space tomography using normalizing flows

Particle accelerators generate charged-particle beams with tailored distributions in six-dimensional position-momentum space (phase space). Knowledge of the phase space distribution enables model-based beam optimization and control. In the absence of direct measurements, the distribution must be tomographically reconstructed from its projections. In this paper, we highlight that such problems can be severely underdetermined and that entropy maximization is the most conservative solution strategy. We leverage —invertible generative models—to extend maximum-entropy tomography to six-dimensional phase space and perform numerical experiments to validate the model's performance. Our numerical experiments demonstrate consistency with exact two-dimensional maximum-entropy solutions and the ability to fit complicated six-dimensional distributions to large measurement sets in reasonable time. Published by the American Physical Society 2024

43 PARTICLE ACCELERATORS↗