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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Enabling Space Biological Knowledge Discovery Through Image and Video Data Sharing

Increased biomedical risks associated with deep space crewed missions (cis-Lunar, Mars transit/surface) require development of health countermeasures, novel ecosystem support, risk modeling, and fundamental space biological knowledge discovery. Molecular-omics, physiological-phenotypic-behavioral, and environmental-radiation telemetry data from space biological and health studies are needed for reuse by scientists to address these tasks. The data as well as space-relevant biospecimens are being made more findable, accessible, interoperable, and reusable through NASA’s Open Science Data Repository (OSDR). This new OSDR umbrella grouping includes NASA GeneLab, the NASA Ames Life Sciences Data Archive (ALSDA), and the NASA Biological Institutional Scientific Collection. The OSDR system design appropriately handles metadata and processed-tabular results from ALSDA studies collected from space experiments. But raw and processed ALSDA bioimage and video datasets require an expansion of OSDR’s data architecture to handle ingestion, curation, and egress. The academic-industry bioimaging field saw a scientific renaissance in the past several years through leveraging open-source software, international collaborations, machine learning, and other open science/programming approaches. As crewed missions and more biological experiments are on the deep space horizon, OSDR is embracing data stewardship through listening to feedback from subject matter experts and designing an expanded architecture which is appropriate for NASA’s goals to enable analysis and reuse of bioimaging and video data for the public science community.Discovery Through Image and Video Data Sharing

space biology↗
DOE OSTI2020

Deep Learning for Automated Identification of Eels in Sonar Data

Freshwater eels, such as the American eel (Anguilla rostrata) present numerous challenges related to safe downstream fish passage at hydroelectric facilities. One of those challenges is effective monitoring of their abundance, movements, and behavior to facilitate design and operation of eel protection and passage facilities. A previous EPRI study documented the ability of human analysts to reliably identify American eels in data obtained with a 1100/1800 kHz, multibeam sonar. This report describes a project to develop deep learning (a subset of artificial intelligence) tools to automate the time-consuming, subjective process of eel identification in multibeam sonar data. The project exploited new data collected in the laboratory and the existing data from the prior EPRI field study to develop and test deep learning and other data analytic tools, including wavelet filtering, differencing for static object removal, and convolutional neural network analysis. The analysis of the laboratory data demonstrated feasibility of the approach, revealed object characteristics observed with the sonar that distinguish eels from similarly sized and shaped acoustic targets, and provided additional data for algorithm selection and training. Deep learning algorithms trained and tested on the laboratory data alone achieved accuracy rates of greater than 98% when classifying acoustic images of eels and similar-sized neutrally buoyant sticks. The algorithm trained and tested on the pre-existing field data alone, and yielded classification accuracy of 9.3% false positives and 13.3% false negatives when distinguishing between eels and sticks/PVC pipes based on video clips (i.e., multiple, consecutive images). This performance is comparable to the classification accuracy achieved by human analysts in the prior study. The deep learning algorithm trained on a combination of video clips obtained in the laboratory and the field and tested on video clips from the field, was able to distinguish eels from sticks and PVC pipes (a river debris analog) of similar size with 100% accuracy. Outreach to the hardware, software, and end-user communities early in the project helped to identify needs and specify the application space. Outreach to those communities at the end of the project communicated project results and opportunities for further development. The project achieved proof of concept for automated identification of eel in multibeam sonar data. Future work should focus on acquisition of additional data for more robust algorithm training and testing; modification of the software tools to accommodate multiple acoustic targets in the acoustic field at a given time; identification of additional object classes; incorporation of motion in the object identification and classification algorithms; operationalizing the software tools, including integration with other existing sonar data analysis tools; and partnering with hardware and software providers for distribution of the software tools with their commercial products.

13 HYDRO ENERGY↗
DOE OSTI2023

Time-Resolved Radioluminescence of the Polynuclear Copper(I) Phosphor Cu4I6²–. Different Temporal responses to Photo, X-Ray, β-Ray and α-Particle Excitation

Described for the first time are the time-resolved radioluminescence (TRRL) properties of the highly luminescent copper(I) cluster Cu4I62– using X-ray, b-ray and a-particle excitation. The copper(I) phosphors are two crystalline salts of this anion, [Na2(18-crown-6)2(H2O)3][Cu4I6] (I) and [Li(benzo-15-crown-5)2(H2O)]2[Cu4I6] (II), that had been shown to display strong photoluminescence (PL) when excited with ultraviolet light. The integrated radioluminescence (RL) spectra observed when pulsed X-rays were used as the excitation source are virtually the same as the PL spectra under comparable conditions. These temporal RL spectra are invariant at all observation times indicating that the observed scintillation occurs from a common excited state (or set of excited states). When the TRRL is collected from excitation with a pulsed X-ray source, b-ray decay from 90Sr or a-decay from 244Cm, the longer components (>2 μs) of the TRRL displayed (in each case) lifetimes comparable to those of the strictly exponential PL decays recorded under pulsed laser UV excitation. However, at shorter observation times (< 500 ns), the RL decay deviated from the exponential model, indicating a markedly different temporal luminescence behavior when these materials were excited with pulsed high energy radiation. Furthermore, this effect was the most pronounced for the a-particle excitation. These results suggest that the absorption of a very high energy X-ray photon, b-ray or a-particle at a site within the crystalline solid leads to a high local density of electronic excited states and that coupling between these states provides an alternative channel for excited state decay. Given that the patterns observed

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2026

A statistical approach to analyzing domain dynamics in ferroelectric crystals using X-ray photon correlation spectroscopy

Ferroelectric materials exhibit strong electromechanical coupling, largely influenced by their domain structures. Numerous microstructural studies indicate that smaller domains with higher domain wall density generally enhance domain wall motion, although some inconsistencies have been reported. In this work, we use X-ray photon correlation spectroscopy (XPCS) to probe dynamic response in Pb(Mg 1/3 Nb 2/3 )O 3 -29PbTiO 3 (PMN-29PT) single crystals under applied electric fields. We introduce a two-field correlation approach, adapted from conventional two-time correlation to quantify dynamics. Statistical analysis reveals that both [001]-oriented direct current (DC) and alternating current (AC) poled samples show Poisson-like behavior within specific electric field regions. The DC-poled samples exhibit more frequent domain wall jump events but with smaller amount of decorrelation per jump event, whereas the AC-poled samples show fewer jump events with larger decorrelation per jump event. This observation aligns with the prevalence of 109° domain walls in the AC-poled samples, which contribute to more domain wall motion. These findings provide experimental evidence of collective domain wall motion and establish a direct connection between mesoscale dynamics and electromechanical response.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Chemical Bonding Governs Complex Magnetism in MnPt 5 P

Subtle changes in chemical bonds may result in dramatic revolutions in magnetic properties in solid-state materials. MnPt 5 P, a derivative of the rare-earth-free ferromagnetic MnPt 5 As, was discovered and is presented in this work. Specifically, MnPt 5 P was synthesized, and its crystal structure and chemical composition were characterized by X-ray diffraction as well as energy-dispersive X-ray spectroscopy. Accordingly, MnPt 5 P crystallizes in the layered tetragonal structure with the space group P4/mmm (No. 123), in which the face-shared Mn@Pt 12 polyhedral layers are separated by P layers. In contrast to the ferromagnetism observed in MnPt 5 As, the magnetic properties measurements on MnPt 5 P show antiferromagnetic ordering occurs at ~188 K with a strong magnetic anisotropy in and out of the ab-plane. Moreover, a spin-flop transition appears when a high magnetic field is applied. An A-type antiferromagnetic structure was obtained from the analysis of powder neutron diffraction (PND) patterns collected at 150 and 9 K. Calculated electronic structures imply that hybridization of Mn-3d and Pt-5d orbitals is critical for both the structural stability and observed magnetic properties. Semiempirical molecular orbitals calculations on both MnPt 5 P and MnPt 5 As indicate that the lack of 4p character on the P atoms at the highest occupied molecular orbital (HOMO) in MnPt 5 P may cause the different magnetic behavior in MnPt 5 P compared to MnPt 5 As. The discovery of MnPt 5 P, along with our previously reported MnPt5As, parametrizes the end points of a tunable system to study the chemical bonding which tunes the magnetic ordering from ferromagnetism to antiferromagnetism with the strong spin–orbit coupling (SOC) effect.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

SSRS (Stochastic Soaring Raptor Simulator)

SSRS (Stochastic Soaring Raptor Simulator) is a generalizable, probabilistic, and predictive tool for wind energy developers, ecologists, wildlife managers and industry consultants to estimate the potential for soaring raptors to interact with operating wind turbines, without the need for site-specific data collection. Rapid expansion of wind energy development across the world has exposed the risk of turbine collisions for birds and bats. The risk to obligate soaring raptors such as golden eagles is of particular concern due to their small population and influence on ecological balance. Golden eagles rely heavily on updrafts to subsidize their flight, putting them in direct conflict with operational wind turbines that utilize the same wind resource. Understanding the behavior of soaring raptors with varying atmospheric conditions is crucial for predicting and mitigating the risk of turbine collision. This software contains a predictive movement model that simulates individual flight paths of golden eagles during updraft-subsidized long-distance flight, including migration. For a given set of atmospheric conditions, the model simulates thousands of eagles at turbine-scale spatial resolution (50m) to produce a relative presence density map. The simulated eagles rely on updrafts to pursue uninterrupted directional flight with minimal energy expenditure, following fluid-flow principles. The simulator includes a stochastic model of eagle behavior and a systematic method of accounting for spatiotemporal variations in atmospheric conditions. This framework only requires publicly available atmospheric data to estimate orographic and thermal updrafts, ensuring general usability.

Sandhu, Rimple↗
DOE OSTI2024

Turbo-Turtle v0.12.1

A collection of solid body modeling tools for 2D sketched, 2D axisymmetric, and 3D revolved models. It also contains general purpose meshing and image generation utilities appropriate for any model, not just those created with this package. Implemented for Abaqus and Cubit as backend modeling and meshing software. Orginal implementation targeted Abaqus so most options and descriptions use Abaqus modeling concepts and language. Turbo-Turtle makes a best effort to maintain common behaviors and features across each third-party software’s modeling concepts. As much as possible, the work for each subcommand is performed in Python 3 to minimize solution approach duplication in third-party tools. The third-party scripting interface is only accessed when creating the final tool specific objects and output. The tools contained in this project can be expanded to drive other meshing utilities in the future, as needed by the user community. This project derives its name from the origins as a sphere partitioning utility following the turtle shell (or soccer ball) pattern.s.

Brindley, Kyle↗
NASA NTRS1984

Oculometric indices of simulator and aircraft motion

The effects on eye scan behavior of both simulator and aircraft motion and sensitivity of an oculometric measure to motion effects was demonstrated. It was found that fixation time is sensitive to motion effects. Differences between simulator motion and no motion conditions during a series of simulated ILS approaches were studied. The mean fixation time for the no motion condition was found to be significantly longer than for the motion conditions. Eye scan parameters based on data collected in flight, and in fixed base simulation were investigated. Motion effects were evident when the subject was viewing a display supplying attitude and flight path information. The nature of the information provided by motion was examined. The mean fixation times for the no motion condition were significantly longer than for either motion condition, while the two motion conditions did not differ. It is shown that motion serves an alerting function, providing a cue or clue to the pilot that something happened. It is suggested that simulation without motion cues may represent an understatement of the true capacity of the pilot.

Comstock, J. R.↗
NASA NTRSDate not supplied

The Doppler Wind Temperature Sensor (DWTS) Flight Evaluation and Experiments (TES-16,17)

The Doppler Wind Temperature Sensor instrument (DWTS), developed by Global Atmospheric Technologies and Sciences (GATS), is a powerful yet simple tool with the potential of becoming a new window to upper atmosphere dynamics. Based around a defense-grade infrared camera peering through a static gas cell used as a scanning spectral filter, the DWTS is designed to measure the fingerprints of wind and thermal waves as they propagate to the mesosphere and lower thermosphere. DWTS achieves this scanning by measuring the induced change in the doppler shift of the emission as it passes through the DWTS field of view. DWTS holds promise to aid in more accurate weather determination (Gordley, et al), and the core technology can be easily adapted to study other atmospheres of interest. In partnership with GATS, NOAA, and other collaborators, NASA Ames and the Nano Orbital Workshop group have been working to evaluate the DWTS instrument on orbit and optimize it as a flexible cube satellite payload. The first mission selected for DWTS evaluation is preparing for flight in early 2024, followed by a more capable science mission in 2025, with both missions part of the TES-n/NOW flight series. The first flight, TES-16/DWTS-A, will incorporate a single DWTS instrument in an approximately 2U payload volume with the imaging aperture perpendicular to the flight velocity vector. With an estimated power consumption of 20 watts, supplied via a custom NOW-designed GaN converter, the instrument will maintain the imaging sensor plane at 80K using an integrated pulse-tube cryocooler during instrument evaluation periods. Data from DWTS will be captured via a NOW-designed custom data processor before being transmitted via S-band radio back to select ground stations, with instrument command and control operated via L-band global-coverage radio. After the TES-16/DWTS-A initial demonstration mission, the subsequent TES-17/DWTS-B mission will be a dedicated science mission equipped with three DWTS instruments, each hosting a different gas cell to obtain full altitude coverage from 20 to 200 km both day and night from a single cube satellite. The intention of the flight series, and one of NASA’s interests in the instrument, is to advance a Martian atmospheric instrument (Colaprete, Gordley, et al) which, if successful, would greatly further understanding of Martian atmospheric behavior. The proposed paper will review the flight series in detail, including challenges from the TES-16 flight tests and the projected challenges and application to Mars study. Additional detail regarding the possible applications of a Cognitive Communication technique in current flight development by NOW collaborators at the NASA Glenn Research Center will also be discussed, including the implications of using an automated User Initiated Service (UIS) protocol to maximize the data collected per orbit.

Doppler Wind Temperature Sensor↗
NASA NTRSDate not supplied

On-Orbit Performance of the NOAA-21 Advanced Technology Microwave Sounder (ATMS)

The Advanced Technology Microwave Sounder (ATMS) instrument provides sounding measurements of Earth’s atmosphere to collect temperature and water vapor data for NOAA’s Joint Polar Satellite System (JPSS) program. ATMS is a total-power passive microwave radiometer with 22 channels spanning a frequency range from 22 to 183 GHz. A general description of the ATMS instrument is detailed in [1]. Three ATMS units are currently on-orbit. The Suomi National Polar-orbiting Partnership (SNPP) unit was launched in 2011 and the NOAA-20 (previously JPSS-1) unit was launch in 2017. Both SNPP and NOAA-20 ATMS units are currently operational and the data is used for numerical weather prediction (NWP) models. The NOAA-21 (formerly JPSS-2) ATMS unit was launched on November 10, 2022 from Vandenberg Space Force Base in California [2]. The ATMS instrument began generating radiance data on November 21, 2022. At the time of this abstract NOAA-21 ATMS is currently completing on-orbit commissioning and checkout activities; it is expected that the commissioning activities will be complete by the IGARSS 2023 conference. This paper will focus on the on-orbit performance of the NOAA-21 ATMS instrument based on measurements and activities from the commissioning period. Comparisons will be made to specifications and to expected performance based on pre-launch test activities. Pre-launch JPSS-2 (NOAA-21) ATMS performance is detailed in [4]. Additionally, the NOAA-21 performance will be compared to the on-orbit performance of the SNPP and NOAA-21 ATMS units. The post-launch performance of SNPP ATMS is detailed in [1][5][6][7]. The post-launch performance of NOAA-20 ATMS is detailed in [5][7][8]. On-orbit performance is evaluated through data collects from nominal mission operations as well as specific post-launch tests and spacecraft maneuvers. Nominal mission operations can be used to evaluate parameters such as instrument thermal stability, Noise Equivalent Delta Temperature (NEDT)/radiometric sensitivity, geolocation, inter-channel noise correlation, striping, and radiometric bias and stability. Shortly after instrument activation, the instrument thermal stability as measured from onboard temperature sensors is evaluated to demonstrate stable and steady-state behavior. Methods for computing NEDT are described in [9][10][11]. Passive geolocation measurements are performed using the coastline inflection point (CIP) method, described in [8][12]. The striping index, used as a metric to quantify striping, is the ratio of along-track variance to cross-track variance of the observed brightness temperature [4][8][14]. Inter-channel noise correlation has been previously reported for SNPP and NOAA-20 [1][8]. Dedicated post-launch tests and spacecraft maneuvers are utilized during the commissioning phase for further evaluation of on-orbit instrument performance. These activities provide information on the optimal space view selection, noise power spectral density (PSD), gain stability, scan bias, interference from onboard transmitters, reflector emissivity, active geolocation, and radiometric bias and stability detection methods. The optimal space view selection is used to determine which of ATMS space view sectors is preferred for minimizing contamination of the space view [1]. Point and stare testing is used to generate noise PSD and gain stability information, as described in [1][8]. Spacecraft roll and pitch maneuvers allow the ATMS to view different zones, including deep space, and the data can be used to provide information on scan biases and antenna sidelobe contamination [1][8]. The pitch maneuver can also be used to assess interference from onboard Ka-band transmitters and reflector emissivity [8]. Active geolocation is evaluated as a method for geolocation, described in [15].

Edward Kim↗
NASA NTRSDate not supplied

The Doppler Wind Temperature Sensor (DWTS) Flight Evaluation and Experiments (TES-16, 17)

The Doppler Wind and Temperature Sounder instrument (DWTS), developed by Global Atmospheric Technologies and Sciences (GATS), is a simple but powerful tool that has the potential to become a new window through which to study the dynamics of the upper atmosphere. Based around a defense-grade infrared camera peering through a static gas cell used as a scanning spectral filter, the DWTS instrument infers wind velocities and kinetic temperatures through the stratosphere and lower thermosphere. The DWTS achieves this scanning by measuring the induced Doppler shift and Doppler broadening of emissions as they pass through the DWTS field of view (Gordley, et al., 2011). The DWTS holds promise in improving accuracy in weather determination , and the core technology can be adapted to study other planetary atmospheres. In partnership with GATS, NOAA, and other collaborators, NASA Ames and the Nano Orbital Workshop group have been working to evaluate the DWTS instrument on orbit and optimize it as a flexible nanosatellite payload. The first mission selected for DWTS evaluation is preparing for flight in early 2024, which will be followed by a more capable science mission in 2025, with both missions being part of the TES-n/NOW heritage flight series. The first rapid technology demonstration flight, TES-16/DWTS-A, will demonstrate a single DWTS instrument in an approximately 2U payload volume with the imaging aperture perpendicular to the flight velocity vector. With an estimated power consumption of 50 watts, supplied via a custom NOW-designed DC-DC converter, the instrument will maintain the imaging sensor plane at 80K during instrument evaluation periods using an integrated pulse-tube cryocooler. Data from DWTS will be captured and processed via a NOW-designed custom data interface unit before being transmitted via S-band radio back to select ground stations, with instrument command and control operated via L-band global-coverage radio. The subsequent TES-17/DWTS-B mission will be a dedicated science mission to obtain full altitude coverage from 20 to 200 km during both day and night, all from a single small-satellite equipped with three DWTS instruments, each hosting a different gas cell chemistry. The intention of this flight series, and one of NASA’s interests in this instrument, is to advance a Martian atmospheric instrument (Colaprete, Gordley, et al) which, if successful, would greatly further understanding of Martian atmospheric behavior. The proposed paper will review the flight series in detail, including challenges facing the TES-16 flight tests and the projected challenges and application to Mars study. Additional detail regarding the possible applications of a Cognitive Communication technique in current flight development by NOW collaborators at the NASA Glenn Research Center will also be discussed, including the implications of using an automated User Initiated Service (UIS) protocol to maximize the data collected per orbit.

nanosatellite↗
NASA NTRSDate not supplied

Preliminary Findings of the Experimental Development Unit Cold Flow Test for a Generation Zero Nuclear Propulsion Engine

Nuclear thermal propulsion (NTP) technology will greatly benefit human travel to Mars by significantly shortening transit times, improving crew safety, and providing more mission flexibility than traditional chemical rockets. As part of DRACO follow-on work to develop, build, and fly a generation zero NTP engine, a full scale flight-like experimental design unit (EDU) reactor was constructed to collect sufficient on-ground performance data to characterize flow induced vibrations (FIV) of critical reactor structures/components, inform development of the engine and reactor control algorithm, and collect pressure drop and flow distribution data across the reactor. The fluid conditions for the test program were designed to achieve system responses equivalent to that of an operational engine through all phases of engine operation including reactor startup, mainstage operation, reactor shutdown, and reactor cooldown. Over 100 tests were executed, flowing either GN2 or GHe through the EDU at varying flow rates and pressures. This experiment provided early validation of flow behavior and vibration risks before nuclear testing, boosted critical subsystem TRLs, informed design iterations, and reduced future test costs. The steady-state flow parameters for the experiment were modeled in Ansys Thermal Desktop, allowing rapid tuning and experiment-informed updates to a flight-like test matrix. The EDU dynamic environment was characterized with accelerometers, strain gauges, and high-frequency pressure transducers all sampled at 20 kHz. While many narrow-band oscillations were identified, no significant FIV occurred; the reactor structural responses tend to be enveloped by typical launch vehicle ascent vibration environments (defined up to 2 kHz), although significant energy is also present at higher frequencies.

Flow Induced Vibration↗
DOE OSTI2020

Investigation of impurity driven corrosion behavior in molten 2LiF-BeF 2 salt

A 1000 -h corrosion experiment of 316H stainless steel at 700 °C investigated the role of metal fluoride impurities CrF 2 and FeF 2 in LiF-BeF 2 (66-34 mole %) (FLiBe) salt. Inductively coupled plasma-optical emission spectroscopy (ICP-OES) demonstrated the ability to measure changes in the concentration of these fluorides in FLiBe salt. Cyclic voltammetry (CV) showed the potential for real-time quantitative concentration measurement of corrosion products in the molten salt. Materials characterization revealed that both impurity species influence the dissolution of Cr from the alloy. The collective results from these analysis methods advance the understanding of the influence impurities have on materials corrosion.

2LiF-BeF2↗
DOE OSTI2023

Simulations with machine learning potentials identify the ion conduction mechanism mediating non-Arrhenius behavior in LGPS

Abstract Li 10 Ge(PS 6 ) 2 (LGPS) is a highly concentrated solid electrolyte, in which Coulombic repulsion between neighboring cations is hypothesized as the underlying reason for concerted ion hopping, a mechanism common among superionic conductors such as Li 7 La 3 Zr 2 O 12 (LLZO) and Li 1.3 Al 0.3 Ti 1.7 (PO 4 ) 3 (LATP). While first principles simulations using molecular dynamics (MD) provide insight into the Li + transport mechanism, historically, there has been a gap in the temperature ranges studied in simulations and experiments. Here, we used a neural network potential trained on density functional theory (DFT) simulations, to run up to 40-nanosecond long MD simulations at DFT-like accuracy to characterize the ion conduction mechanisms across a range of temperatures that includes previous simulations and experimental studies. We have confirmed a Li + sublattice phase transition in LGPS around 400 K, below which the ab -plane diffusivity D a b ∗ is drastically reduced. Concomitant with the sublattice phase transition near 400 K, there is less cation-cation (cross) correlation, as characterized by Haven ratios closer to 1, and the vibrations in the system are more harmonic at lower temperature. Intuitively, at high temperature, the collection of vibrational modes may be sufficient to drive concerted ion hops. However, near room temperature, the vibrational modes available may be insufficient to overcome electrostatic repulsion, thus resulting in less correlated ion motion and comparatively slower ion conduction. Such phenomena of a sublattice phase transition, below which concerted hopping plays a less significant role, may be extended to other highly concentrated solid electrolytes such as LLZO and LATP.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

The Cancer Microbiome: Distinguishing Direct and Indirect Effects Requires a Systemic View

The collection of microbes that live in and on the human body – the human microbiome – can impact on cancer initiation, progression, and response to therapy, including cancer immunotherapy. The mechanisms by which microbiomes impact on cancers can yield new diagnostics and treatments, but much remains unknown. The interactions between microbes, diet, host factors, drugs, and cell–cell interactions within the cancer itself likely involve intricate feedbacks, and no single component can explain all the behavior of the system. Understanding the role of host-associated microbial communities in cancer systems will require a multidisciplinary approach combining microbial ecology, immunology, cancer cell biology, and computational biology – a systems biology approach.

Xavier, Joao B.↗
DOE OSTI2023

Molecular hydrodynamic theory of the velocity autocorrelation function

The velocity autocorrelation function (VACF) encapsulates extensive information about a fluid’s molecular-structural and hydrodynamic properties. We address the following fundamental question: How well can a purely hydrodynamic description recover the molecular features of a fluid as exhibited by the VACF? To this end, we formulate a bona fide hydrodynamic theory of the tagged-particle VACF for simple fluids. Our approach is distinguished from previous efforts in two key ways: collective hydrodynamic modes and tagged-particle self-motion are modeled by linear hydrodynamic equations; the fluid’s spatial velocity power spectrum is identified as a necessary initial condition for the momentum current correlation. This formulation leads to a natural physical interpretation of the VACF as a superposition of products of quasinormal hydrodynamic modes weighted commensurately with the spatial velocity power spectrum, the latter of which appears to physically bridge continuum hydrodynamical behavior and discrete-particle kinetics. The methodology yields VACF calculations quantitatively on par with existing approaches for liquid noble gases and alkali metals. Furthermore, we obtain a new, hydrodynamic form of the self-intermediate scattering function whose description has been extended to low densities where the Schmidt number is of order unity; various calculations are performed for gaseous and supercritical argon to support the general validity of the theory. Excellent quantitative agreement is obtained with recent MD calculations for a dense supercritical Lennard-Jones fluid.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

A spatially regularized detector for emergent/re-emergent disease outbreaks

Early detection of outbreaks caused by emergent pathogens, using epidemiological surveillance data i.e., daily case counts, is difficult. This is because the data tend to be noisy during the early epoch of the outbreak. In contrast, the spread-rate of the disease tends to be well-behaved, as it depends only on the mixing patterns of the population and the characteristics of the pathogen, neither of which behave erratically in space-time. In this report, we explore whether the spread-rate can be used for epidemiological surveillance, conditional on case count data. Estimating the spread-rate from case count data allows us to exploit exogenous information, e.g., incubation period distributions etc., which can considerably smooth out any erratic temporal behavior. Further, epidemiological dynamics are spatially correlated, and if case counts are available for multiple areal units e.g., counties, these correlations could potentially be used to suppress noise in the early epoch data. These exogenous information and structure are not exploited by conventional syndromic surveillance detectors to extract a well-behaved latent variable for monitoring purposes. The technical challenge lies in the estimation of the spread-rate field jointly over a collection of areal units; further, the spread-rate varies over time. We develop a method based on mean-field variational inference to approximately estimate the spread-rate field, using a Gaussian Random Field Model for spatial regularization. The method is tested on the estimation of spread-rate in the thirty-three counties of New Mexico and detect the arrival of the Fall 2020 COVID-19 wave in September 2020. We find that the method is scalable, but underestimates the uncertainty in the estimated spread-rate field. We detect the arrival of the Fall 2020 wave a week ahead of conventional syndromic surveillance algorithms, but our simplistic detection algorithm, based on simple anomaly detection, suffers from a high false positive rate, similar to conventional detectors.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1999

Combustion of Aerosolized Metal Particles in Microgravity

The combustion behavior and interaction effects of multiple metal particles are addressed in this project. The microgravity environment presents a unique opportunity to create an "aerosol" consisting of relatively large, 50-300 micron diameter particles, so that both cloud flame structure and individual particle combustion behavior can be characterized simultaneously. The microgravity experiments are conducted using the 2.2 s NASA Lewis Research Center drop tower. Each test includes aerosolizing metal particles under microgravity, a delay required to produce a steady aerosol, and igniting such an "aerosol" at constant pressure using a hot wire igniter. The flame structure and details of individual particle combustion are visualized using both high speed movie and regular speed video cameras. Combustion products are collected and analyzed after the experiment. A detailed description of the experimental apparatus is given elsewhere. Microgravity experiments with magnesium particle aerosols have been conducted and experiments with zirconium particles are currently in progress. A numerical, time dependent model of the flame propagation in magnesium aerosol is being developed.

Dreizin, E. L.↗