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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS1997

Validity of the Temperature Reconstruction from Water Isotopes in Ice Cores

Well-documented present-day distributions of stable water isotopes (HDO and others) show the existence, in middle and high latitudes, of a linear relationship between the mean annual isotope content of precipitation (SD and 51"0) and the mean annual temperature at the precipitation site. Paleoclimatologists have used this relationship, which is particularly well obeyed over Greenland and Antarctica, to infer paleotemperatures from ice core data. There is, however, growing evidence that spatial and temporal isotope/ surface temperature slopes differ, thus complicating the use of stable water isotopes as paleothermometers. In this paper we review empirical estimates of temporal slopes in polar regions and relevant information that can be inferred from isotope models: simple, Rayleigh-type distillation models and (particularly over Greenland) general circulation models (GCMS) fitted with isotope tracer diagnostics. Empirical estimates of temporal slopes appear consistently lower than present-day spatial slopes and are dependent on the timescale considered. This difference is most probably due to changes in the evaporative origins of moisture, changes in the seasonality of the precipitation, changes in the strength of the inversion layer, or some combination of these changes. Isotope models have not yet been used to evaluate the relative influences of these different factors. The apparent disagreement in the temporal and spatial slopes clearly makes calibrating the isotope paleothermometer difficult. Nevertheless, the use of a (calibrated) isotope paleothermometer appears justified; empirical estimates and most (though not all) GCM results support the practice of interpreting ice core isotope records in terms of local temperature changes.

Jouzel, J.↗

DOE OSTI2023

Industrial PLC Network Modeling and Parameter Identification Using Sensitivity Analysis and Mean Field Variational Inference

A multiple input multiple output (MIMO) power line communication (PLC) model for industrial facilities was developed that uses the physics of a bottom-up model but can be calibrated like top-down models. The PLC model considers 4-conductor cables (three-phase conductors and a ground conductor) and has several load types, including motor loads. The model is calibrated to data using mean field variational inference with a sensitivity analysis to reduce the parameter space. The results show that the inference method can accurately identify many of the model parameters, and the model is accurate even when the network is modified.

47 OTHER INSTRUMENTATION↗

DOE OSTI2022

A deep learning approach to real-time HIV outbreak detection using genetic data

Pathogen genomic sequence data are increasingly made available for epidemiological monitoring. A main interest is to identify and assess the potential of infectious disease outbreaks. While popular methods to analyze sequence data often involve phylogenetic tree inference, they are vulnerable to errors from recombination and impose a high computational cost, making it difficult to obtain real-time results when the number of sequences is in or above the thousands. Here, we propose an alternative strategy to outbreak detection using genomic data based on deep learning methods developed for image classification. The key idea is to use a pairwise genetic distance matrix calculated from viral sequences as an image, and develop convolutional neutral network (CNN) models to classify areas of the images that show signatures of active outbreak, leading to identification of subsets of sequences taken from an active outbreak. We showed that our method is efficient in finding HIV-1 outbreaks with R0 ≥ 2.5, and overall a specificity exceeding 98% and sensitivity better than 92%. We validated our approach using data from HIV-1 CRF01 in Europe, containing both endemic sequences and a well-known dual outbreak in intravenous drug users. Our model accurately identified known outbreak sequences in the background of slower spreading HIV. Importantly, we detected both outbreaks early on, before they were over, implying that had this method been applied in real-time as data became available, one would have been able to intervene and possibly prevent the extent of these outbreaks. This approach is scalable to processing hundreds of thousands of sequences, making it useful for current and future real-time epidemiological investigations, including public health monitoring using large databases and especially for rapid outbreak identification.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Deep Learning Prediction of Interspecies Interactions from Self-organized Spatiotemporal Patterns of Co-evolving Organisms

Microorganisms colonizing natural habits such as soils co-evolve to form specific spatial patterns through interspecies interactions. These self-organized patterns are a key ecological phenotype, which provides critical information on their interaction mechanisms. However, conventional network inference techniques that analyze species population data in bulk have yet to be extended to account for such spatial heterogeneity. Here we proposed supervised deep learning as a new network inference tool for predicting interspecies interactions from spatiotemporal patterns of microbial evolution. Due to lack of biological imaging data that can be used for training deep learning networks, we used in silico data generated from high-fidelity agent-based models to determine model structure and parameters. Even though networks were trained under simple configurations where interaction coefficients are assumed to be spatially invariant, we demonstrated that the resulting model can be utilized to successfully predict spatial variation of interactions in more complex domains (i.e., configured with a context-dependent mixture of interaction coefficients) as well as in simple domains without further training. In the further test against real biological data obtained through imaging experiments of a binary consortium (Pseudomonas fluorescens and a mutant of Escherichia coli), our model also predicted the dramatic shifts in interactions of the two organisms across different environmental contexts. Through various successful demonstrations in this work, the combined use of the agent-based model and machine learning algorithm provides a means to use new type of data - microscopic images - for extracting microbial interactions, therefore presenting itself as a useful tool for the analysis of more complex microbial community interactions.

Lee, Joon-Yong↗

NASA NTRS1996

Far-Infrared Spectroscopy of Planetary Nebulae with the KAO

We present new far-infrared line observations of the planetary nebulae (PNs) NGC 7027, NGC 7009, and NGC 6210 obtained with the Kuiper Airborne Observatory (KAO). The bulk of our data are for NGC 7027 and NGC 7009, including [Ne(V)] 24 micrometers, [O(IV)] 26 micrometers, [O(III)] (52, 88) micrometers, and [N(III)] 57 micrometers. Our data for [O(III)] (52, 88) and [N(III)] 57 in NGC 7027 represent the first measurements of these lines in this source. The large [O(III)] 52/88-micrometer flux ratio implies an electron density (cubic cm) of log N(sub e)[O(III)] = 4.19, the largest Ne ever inferred from these lines. We derive N(++)/O(++) = 0.394 +/- 0.062 for NGC 7027 and 0.179 +/- 0.043 for NGC 6210. We are able to infer the O(+3)/O(++) ionic ratio from our data. As gauged by this ionic ratio, NGC 7027 is substantially higher ionization than is NGC 7009 - consistent with our observation that the former produces copious [Ne(V)] emission while the latter does not. These data help characterize the stellar ionizing radiation field. From our [O(IV)] and [O(III)] fluxes, we are able to show that O(++) is by far the dominant oxygen ion in NGC 7009. As a result, the O/H abundance inferred using these data tends to corroborate the value found from UV/optical, collisionally excited lines. We determined accurate rest wavelengths for the [Ne(V)] 2s(2)2p(2)P(sub 1) to 2s(2)2p(2)3P(sub 0) (lambda(sub rest) = 24.316 +/- 0.008 micrometers) and [O(IV)] 2s(2)2p(2)P(sup 0, sub 3/2) to 2s(2)2p(2)P(sup 0, sub 1/2) (lambda(sub rest) = 25.887 +/- 0.007 micrometers) transitions from observations of one or both of the bright PNs NGC 7027 and NGC 7009. Our [O(IV)] value, to the best of our knowledge, is the most accurate direct determination of this lambda(sub rest). These new KAO data will be beneficial for comparison with ISO observations of these PNs.

Rubin, Robert H.↗

NASA NTRS1988

Microwave remote sensing of sea ice

The long term objectives are: (1) to understand the physics of the multispectral microwave radiative characteristics of sea ice as it goes through different phases; (2) to improve characterization of sea ice cover using satellite microwave sensors; and (3) to study ice/ocean physical and biological processes associated with polynya formations and variability of the marginal sea ice region. Two field experiments were conducted to pursue these objectives. One involved measurements of radiative and physical characteristics of sea ice from a ship during a 3-month long cruise through the Weddell Sea ice pack during the Austral winter of 1986. The other involved similar measurements from two aircrafts and a submarine over the Central Arctic and Greenland Sea region. Preliminary results have already led to an enhanced understanding of the microwave signatures of pancake ice, nilas, first year ice, multiyear ice and effects of snow cover. Coastal and deep ocean polynyas and their role in bottom water formation and ocean circulation were studied using a time series of ice images from SMMR. An unsupervised cluster analysis of Arctic sea ice using SMMR and THIR emissivity and brightness temperature data was implemented. The analysis indicates the existence of several unique and persistent clusters in the Central Arctic region during winter and that the sum of the area of these clusters excluding those of first year ice is about 20 percent less than minimum ice cover area inferred from a previous summer data. This result is consistent with saline surface for some multiyear ice floes as observed during MIZEZ and suggests that a significant fraction of multiyear ice floes in the Arctic have first year ice signatures.

Comiso, J. C.↗

NASA NTRS1992

Sea surface mean square slope from Ku-band backscatter data

A surface mean-square-slope parameter analysis is conducted for 14-GHz airborne radar altimeter near-nadir, quasi-specular backscatter data, which in raw form obtained by least-squares fitting of an optical scattering model to the return waveform show an approximately linear dependence over the 7-15 m/sec wind speed range. Slope data are used to draw inferences on the structure of the high-wavenumber portion of the spectrum. A directionally-integrated model height spectrum that encompasses wind speed-dependent k exp -5/2 and classical Phillips k exp -3 power laws subranges in the range of gravity waves is supported by the data.

Jackson, F. C.↗

NASA NTRS2022

Remote Sensing of Aerosol Water Fraction, Dry Size Distribution and Soluble Fraction Using Multi-Angle, Multi-Spectral Polarimetry

A framework to infer volume water fraction, soluble fraction and dry size distributions of fine mode aerosol from multi-angle, multi-spectral polarimetry retrievals of column-averaged ambient aerosol properties is presented. The method is applied to observations of the Research Scanning Polarimeter (RSP) obtained during two NASA aircraft campaigns, namely the Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) and the Cloud, Aerosol, and Monsoon Processes-Philippines Experiment (CAMP2Ex). All aerosol retrievals are statistically evaluated using in situ data. Volume water fraction is inferred from the retrieved ambient real part of the refractive index, assuming a dry refractive index of 1.54 and by applying a volume mixing rule to obtain the effective ambient refractive index. The uncertainties in inferred volume water fraction resulting from this simplified model are discussed and estimated to be lower than 0.2 and decreasing with increasing volume water fraction. The daily mean retrieved volume water fractions correlate well with the in situ values with a mean absolute difference of 0.09. Polarimeter-retrieved ambient effective radius for daily data is shown to increase as a function of volume water fraction as expected. Furthermore, the effective variance of the size distributions also increases with increasing effective radius, which we show is consistent with an external mixture of soluble and insoluble aerosol. The relative variations of effective radius and variance over an observation period are then used to estimate the soluble fraction of the aerosol. Daily results of soluble fraction correlate well with in situ observed sulfate mass fraction with a correlation coefficient of 0.79. Subsequently, inferred water and soluble fractions are used to derive dry fine-mode size distributions from their ambient counterparts. While dry effective radii obtained in situ and from RSP show similar ranges, in situ values are generally substantially smaller during the ACTIVATE deployments, which may be due to biases in RSP retrievals or in the in situ observations, or both. Both RSP and in situ observations indicate the dominance of aerosol with low hygroscopicity during the ACTIVATE and CAMP2Ex campaigns. Furthermore, RSP indicates a high degree of external mixing of particles with low and high hygroscopicity. These retrievals of fine mode water volume fraction and soluble fraction may be used for the evaluation of water uptake in atmospheric models. Furthermore, the framework allows to estimate the variation in the concentration of fine-mode aerosol larger than a specific dry radius limit, which can be used as a proxy for the variation in cloud condensation nucleus concentrations. This framework may be applied to multi-angle, multi-spectral satellite data expected to be available in the near future.

Bastiaan Van Diedenhoven↗

DOE OSTI2023

Deriving spatially explicit direct and indirect interaction networks from animal movement data

Abstract Quantifying spatiotemporally explicit interactions within animal populations facilitates the understanding of social structure and its relationship with ecological processes. Data from animal tracking technologies (Global Positioning Systems [“GPS”]) can circumvent longstanding challenges in the estimation of spatiotemporally explicit interactions, but the discrete nature and coarse temporal resolution of data mean that ephemeral interactions that occur between consecutive GPS locations go undetected. Here, we developed a method to quantify individual and spatial patterns of interaction using continuous‐time movement models (CTMMs) fit to GPS tracking data. We first applied CTMMs to infer the full movement trajectories at an arbitrarily fine temporal scale before estimating interactions, thus allowing inference of interactions occurring between observed GPS locations. Our framework then infers indirect interactions—individuals occurring at the same location, but at different times—while allowing the identification of indirect interactions to vary with ecological context based on CTMM outputs. We assessed the performance of our new method using simulations and illustrated its implementation by deriving disease‐relevant interaction networks for two behaviorally differentiated species, wild pigs ( Sus scrofa ) that can host African Swine Fever and mule deer ( Odocoileus hemionus ) that can host chronic wasting disease. Simulations showed that interactions derived from observed GPS data can be substantially underestimated when temporal resolution of movement data exceeds 30‐min intervals. Empirical application suggested that underestimation occurred in both interaction rates and their spatial distributions. CTMM‐Interaction method, which can introduce uncertainties, recovered majority of true interactions. Our method leverages advances in movement ecology to quantify fine‐scale spatiotemporal interactions between individuals from lower temporal resolution GPS data. It can be leveraged to infer dynamic social networks, transmission potential in disease systems, consumer–resource interactions, information sharing, and beyond. The method also sets the stage for future predictive models linking observed spatiotemporal interaction patterns to environmental drivers.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2022

Remote Sensing of Aerosol Water Fraction, Dry Size Distribution and Soluble Fraction Using Multi-Angle, Multi-Spectral Polarimetry

A framework to infer volume water fraction, soluble fraction and dry size distributions of fine-mode aerosol from multi-angle, multi-spectral polarimetry retrievals of column-averaged ambient aerosol properties is presented. The method is applied to observations of the Research Scanning Polarimeter (RSP) obtained during two NASA aircraft campaigns, namely the Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) and the Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2Ex). All aerosol retrievals are statistically evaluated using in situ data. Volume water fraction is inferred from the retrieved ambient real part of the refractive index, assuming a dry refractive index of 1.54 and by applying a volume mixing rule to obtain the effective ambient refractive index. The uncertainties in inferred volume water fraction resulting from this simplified model are discussed and estimated to be lower than 0.2 and decreasing with increasing volume water fraction. The daily mean retrieved volume water fractions correlate well with the in situ values with a mean absolute difference of 0.09. Polarimeter-retrieved ambient effective radius for daily data is shown to increase as a function of volume water fraction as expected. Furthermore, the effective variance of the size distributions also increases with increasing effective radius, which we show is consistent with an external mixture of soluble and insoluble aerosol. The relative variations of effective radius and variance over an observation period are then used to estimate the soluble fraction of the aerosol. Daily results of soluble fraction correlate well with in situ-observed sulfate mass fraction with a correlation coefficient of 0.79. Subsequently, inferred water and soluble fractions are used to derive dry fine-mode size distributions from their ambient counterparts. While dry effective radii obtained in situ and from RSP show similar ranges, in situ values are generally substantially smaller during the ACTIVATE deployments, which may be due to biases in RSP retrievals or in the in situ observations, or both. Both RSP and in situ observations indicate the dominance of aerosol with low hygroscopicity during the ACTIVATE and CAMP2Ex campaigns. Furthermore, RSP indicates a high degree of external mixing of particles with low and high hygroscopicity. These retrievals of fine-mode water volume fraction and soluble fraction may be used for the evaluation of water uptake in atmospheric models. Furthermore, the framework allows us to estimate the variation in the concentration of fine-mode aerosol larger than a specific dry radius limit, which can be used as a proxy for the variation in cloud condensation nucleus concentrations. This framework may be applied to multi-angle, multi-spectral satellite data expected to be available in the near future.

Amount of water in particulate matter↗

NASA NTRS2003

Global and Local Helioseismic Studies of Solar Convection Zone Dynamics Using SOI-MDI on SOHO

Our joint collaborative analyses of global mode data to characterize the solar differential rotation (e.g. Thompson et al. 1996, Schou et al. 1998), and most recently to detect and analyze temporal variations in angular velocity Omega profiles both within the convection zone and in the deeper radiative interior (e.g. Howe et al 2000a,b; Toomre et al. 2000), have led to a series of fascinating discoveries. These should be pursued further as the solar cycle continues. The physical deductions being made from these studies have been greatly strengthened by utilizing both SOI-MDI and GONG data in order to have two independent observational realizations of Doppler images spanning a five-year interval, using two separate procedures to determine global mode splittings, and then analyzing those splitting data sets using both RLS and SOLA inversion procedures. There are considerable subtleties in the effects of instrumental response functions and calibrations, sensitivity of peak finding algorithms and their mode leakage estimates, and stochastic variations in mode amplitudes that can all contribute to apparent changes in the Omega profiles being inferred from sequences of helioseismic data. We have come to understand the implications of many of these calibration and analysis steps, greatly aided by frequent multi-week collaborative working sessions in our Helioseismic Analysis Facility (HAF) at JILA involving many members of the SO1 dynamics and inversion team, including most of our Co-Is during the summer months when we hold intensive working sessions. Considerable further focused attention is required in a collaborative setting on such global mode issues as we continue studying the changing sun.

Toomre, Juri↗

NASA NTRS1993

Do the spectral energy distributions of GK Tauri and HK Tauri indicate the presence of planetary companions?

The interpretation of the spectral dips of three objects (DF Tau, GK Tau, and HK Tau) for which lunar occultation data are available is discussed. Arguments against an alternate interpretation of the spectral dips (the 'disk-shell' model) are presented, and lunar occultation data are used to constrain the properties of the inferred orbiting companions. In the case of DF Tau, the occultation data indicate a stellar mass companion whose orbital radius is consistent with the present inferred gap location. For GK Tau and HK Tau, no such companions are visible, which suggests that the companions responsible for the inferred gaps are substellar. In either case, the estimated gap width is not consistent with a single orbiting body, but is consistent with a group of planets or planetesimals.

Marsh, Kenneth A.↗

NASA NTRS1994

Theoretical, observational, and isotopic estimates of the lifetime of the solar nebula

There are a variety of isotopic data for meteorites which suggest that the protostellar nebula existed and was involved in making planetary materials for some 10(exp 7) yr or more. Many cosmochemists, however, advocate alternative interpretations of such data in order to comply with a perceived constraint, from theoretical considerations, that the nebula existed only for a much shorter time, usually stated as less than or = 10(exp 6) yr. In this paper, we review evidence relevant to solar nebula duration which is available through three different disciplines: theoretical modelling of star formation, isotopic data from meteorites, and astronomical observations of T Tauri stars. Theoretical models based on observations of present star-forming regions indicate that stars like the Sun form by dynamical gravitational collapse of dense cores of cold molecular clouds in the interstellar medium. The collapse to a star and disk occurs rapidly on a time scale of the order 10(exp 5) yr. Disks evolve by dissipating energy while redistributing angular momentum, but it is difficult to predict the rate of evolution, particularly for low mass (compared to the star) disks which nonetheless still contain enough material to account for the observed planetary system. There is no compelling evidence, from available theories of disk structure and evolution, that the solar nebula must have evolved rapidly and could not have persisted for more than 1 Ma. In considering chronologically relevant isotopic data for meteorites, we focus on three methodologies: absolute ages by U-Pb/Pb-Pb, and relative ages by short-lived radionuclides (especially Al-26) and by evolution of Sr-87/Sr-86. Two kinds of meteoritic materials-refractory inclusions such as CAIs and differentiated meteorites (eucrites and angrites) - appear to have experience potentially dateable nebular events. In both case, the most straightforward interpretations of the available data indicate nebular events spanning several Ma. We also consider alternative interpretations, particularly the hypothesis of radically heterogeneous distribution of Al-26, which would avoid these chronological interpretations. The principal impetus for such alternative interpretations seems to be precisely the obviation of the chronological interpretation (i.e., the presumption rather than the inference of a short (less than or = Ma) lifetime of the nebula). Astronomical observations of T Tauri stars indicate that the presence of dusty disks is a common if not universal feature, that the disks are massive enough to accomodate a planetary system such as ours, and that at least some persist for 10(exp 7) yr or more. The results are consistent with the time scales inferred from the meteorite isotopic data. They cannot be considered conclusive with regard to solar nebula time scales, however,in part because it is difficult to relate disk observations to processes that affect meteorites, and in part because the ages assigned for these stars could be wrong by a factor of several in either direction. We conclude that the balance of available evidence favors the view that the nebula existed and was active for at least several Ma. However, because the evidence is not definitive, it is important that the issue be perceived to be an open question, whose answer should be sought rather than presumed.

Podosek, Frank A.↗

NASA NTRS1994

Theoretical, observational, and isotopic estimates of the lifetime of the solar nebula

There are a variety of isotopic data for meteorites which suggest that the protostellar nebula existed and was involved in making planetary materials for some 10(exp 7) yr or more. Many cosmochemists, however, advocate alternative interpretations of such data in order to comply with a perceived constraint, from theoretical considerations, that the nebula existed only for a much shorter time, usually stated as less than or equal to 10(exp 6) yr. In this paper, we review evidence relevant to solar nebula duration which is available through three different disciplines: theoretical modeling of star formation, isotopic data from meteorites, and astronomical observations of T Tauri stars. Theoretical models based on observations of present star-forming regions indicate that stars like the Sun form by dynamical gravitational collapse of dense cores of cold molcular clouds in the interstellar clouds in the interstellar medium. The collapse to a star and disk occurs rapidly, on a time scale of the order 10(exp 5) yr. Disks evolve by dissipating energy while redistributing angular momentum, but it is difficult to predict the rate of evolution, particularly for low mass (compared to the star) disks which nonetheless still contain enough material to account for the observed planetary system. There is no compelling evidence, from available theories of disk structure and evolution, that the solar nebula must have evolved rapidly and could not have persisted for more than 1 Ma. In considering chronoloically relevant isotopic data for meteorites, we focus on three methodologies: absolute ages by U-Pb/Pb-Pb, and relative ages by short-lived radionuclides (especially Al-26) and by evolution of Sr-87/Sr-86. Two kinds of meteoritic materials-refractory inclusions such as CAIs and differential meteorites (eucrites and augrites) -- appear to have experienced potentially dateable nebular events. In both cases, the most straightforward interpretations of the available data indicate nebular events spanning several Ma. We also consider alternative interpretations, particularly the hypothesis of radically heterogeneous distribution of Al-26, which would avoid these chronological interpretations. The principal impetus for such alternative interpretations seems to be precisely the obviation of the chronological interpretation (i.e., the presumption rather than the inference of a short (less than or equal to 1 Ma) lifetime of the nebula). Astronomical observations of T Tauri stars indicate that the presence of dusty disks is a common if not universal feature, that the disks are massive enough to accomodate a planetary system such as ours, and that at least some persist for 110(exp 7) yr or more. The results are consistent with the time scales inferred from the meteoritic isotopic data. They cannot be considered conclusive with regard to solar nebula time scales, however, in part because it is difficult to relate disk observations to processes that affect meteorites, and in part because the ages assigned for these stars could be wrong by a factor of several in either direction. We conclude that the balance of available evidence favors the view that the nebula existed and was active for at least several Ma. However, because the evidence is not definitive, it is important that the issue be perceived to be an open question, whose answer should be sought rather than presumed.

Podosek, Frank A.↗

DOE OSTI2021

Application-driven Privacy-preserving Data Publishing with Correlated Attributes

Recent advances in computing have allowed for the possibility to collect large amounts of data on personal activities and private living spaces. To address the privacy concerns of users in this environment, we propose a novel framework called PR-GAN that offers privacy-preserving mechanism using generative adversarial networks. Given a target application, PR-GAN automatically modifies the data to hide sensitive attributes - which may be hidden and can be inferred by machine learning algorithms - while preserving the data utility in the target application. Unlike prior works, the public's possible knowledge of the correlation between the target application and sensitive attributes is built into our modeling. We formulate our problem as an optimization problem, show that an optimal solution exists and use generative adversarial networks (GAN) to create perturbations. We further show that our method provides privacy guarantees under the Pufferfish framework, an elegant generalization of the differential privacy that allows for the modeling of prior knowledge on data and correlations. Through experiments, we show that our method outperforms conventional methods in effectively hiding the sensitive attributes while guaranteeing high performance in the target application, for both property inference and training purposes. Finally, we demonstrate through further experiments that once our model learns a privacy-preserving task, such as hiding subjects' identity, on a group of individuals, it can perform the same task on a separate group with minimal performance drops.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Deceptive Infusion of Data: A Novel Data Masking Paradigm for High-Valued Systems

This work addresses how analysts of a high-valued system (e.g., nuclear reactor, aircraft turbine designs) can extract findable, accessible, interoperable, and reusable scientific data for public dissemination to artificial intelligence and machine-learning (AI/ML) researchers in a manner that cannot be reverse-engineered, potentially compromising sensitive or proprietary information. State-of-the-art methods address this problem through data masking techniques, which allow access to a subset of the information while obfuscating private and potentially identifying information (e.g., personally identifying medical data). These methods are unsuitable for industrial engineering processes, where AI/ML tools need explicit access to all the data available to draw the best inference about the system to help optimize its performance and identify its vulnerabilities, etc. Our novel deceptive infusion of data paradigm provides a solution to this conundrum by developing a mathematical approach capable of concealing the identity of the system while providing full access to all the features employed by AI/ML tools to ensure their optimal performance.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

A Data-Agnostic, Continuous Machine Learning Framework for Application in High Energy Physics and Beyond: Phase 1 Final Scientific/Technical Report

This Phase 1 effort has focused on the development of continual learning frameworks for use in machine learning, specifically in the applied context of High Energy Physics (HEP). Machine learning (ML) is a transformative technology by which computers, typically through the use of neural networks, are able to perform tasks with proficiency that rivals or surpasses that of human users. Model Degradation & Catastrophic Forgetting are two undesired phenomena which can occur in ML where the performance of a model degrades when either deployed on novel data streams, or trained on novel data which are sufficiently different than the data the models were initially trained on. A natural example where these sorts of effects can be observed is in the performance of detectors in harsh environments, where the detector signature may change over the lifetime of the detector as it ages and deteriorates — precisely what occurs in the experiments conducted in HEP. Real world HEP data is therefore an excellent test-ground and use-case for Continual Learning paradigms, which are techniques used in ML to counteract these problems. Ensemble learning is one such technique, where multiple smaller models are trained on subsets of the overall data and are ensembled together during inference. The intuition behind this technique is that, although there are shifts in the distributions which govern the incoming data streams, these shifts are not expected to be homogeneous or global. If a sufficient diversity in solutions within the various sub-models has been achieved, then at least one sub-model is expected to retain its performance within the overall ensemble. One further strength of this approach is that the architectures of the various models do not need to be identical, and in fact even different modalities of data can naturally be combined in this way. This work focused on applying ensemble learning techniques to derive results using two main datasets, anomaly detection in HEP data & time-series forecasting in semiconductor manufacturing data. Semiconductor manufacturing involves data with surprising similarity to that of HEP (e.g. wafer maps look very similar to digi-occupancy maps) and Cerium Lab’s prominence within the semiconductor industry makes semiconductor manufacturing a natural opportunity for commercialization of this work. Our efforts have led to two strong results. The first is that we evaluated the proposed ensembling techniques using previously proposed machine learning architectures for use in anomaly detection, namely AutoEncoder based models and their derivatives. We also developed new architectures which have not been evaluated in this context before. In fact, this work marks the first use of Vision Transformers for anomaly detection in HEP. Second, we demonstrated that ensemble learning significantly improves model performance in scenarios prone to degradation, validating its effectiveness across both HEP and semiconductor datasets. These results further support ensemble learning as a powerful strategy for mitigating catastrophic forgetting and maintaining robust performance in evolving data environments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1973

The Nimbus-4 backscatter ultraviolet (BUV) atmospheric ozone experiment two years operation

The Backscatter Ultraviolet (BUV) experiment aboard the Nimbus-4 satellite is discussed. This double monochromator experiment measures ultraviolet terrestrial radiance at 12 discrete wavelengths between 2550 A and 3400 A. Approximately 100 scans covering a 230 kilometer square are made between terminator crossings on the daylight side of the earth. A colinear photometer channel with the same field of view is used to derive the Lambert reflectivity of the lower boundary of the scattering atmosphere. The extraterrestrial solar irradiance is measured at the northern terminator. The instrument has currently produced almost three years of nearly continuous data which are being used to infer the high-level ozone distribution and total ozone on a global basis. The high-level ozone data have been verified by independent coincident rocket ozone soundings, and the total ozone values show good agreement with Dobson spectrophotometer determinations as well as those made with the Infrared Interferometer Spectrometer also on Nimbus-4.

Heath, D. F.↗