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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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At least 541 records · Page 30
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NASA NTRS2018

Overview of Solar-Induced Chlorophyll Fluorescence (SIF) from the Orbiting Carbon Observatory-2: Retrieval, Cross-Mission Comparison, and Global Monitoring for GPP

The Orbiting Carbon Observatory-2 (OCO-2), launched in July 2014, is capable of measuring Solar-Induced chlorophyll Fluorescence (SIF), a functional proxy for terrestrial gross primary productivity (GPP). Although its primary mission is to measure the column-averaged mixing ratio of CO2 (Xco(sub 2)) to constrain global carbon source/sink distribution, one of the OCO-2 spectrometers allows for a robust SIF retrieval solely based on solar Fraunhofer lines. Here we present a technical overview of the OCO-2 SIF product, aiming to provide the scientific community guidance on best practices for data analysis, interpretation, and application. This overview consists of the retrieval algorithms, OCO-2 specific bias correction, retrieval uncertainty evaluation, cross-mission comparison with other existing SIF products, and a global-scale examination of the SIF-GPP relationship. With the initial three years of data (September 2014 onward), we compared OCO-2 SIF with retrievals from Greenhouse Gases Observing Satellite (GOSAT) and Global Ozone Monitoring Experiment-2 (GOME-2), and examined its relationship with FLUXCOM and MODIS GPP datasets. Our results show that OCO-2 SIF, along with GOSAT products, closely resemble the mean spatial and temporal patterns of FLUXCOM GPP from regions to the globe. Compared with GOME-2, however, OCO-2 depicts a more realistic spatial contrast between the tropics and extra-tropics. The linear relationship between OCO-2 SIF and existing modeled GPP products diverges somewhat across biomes at the global scale, consistent with previous GOSAT or GOME-2 based findings when modeled GPP products were used, but in contrast to a consistent cross-biome SIF-GPP relationship obtained at flux tower sites with OCO-2 products. This contrast suggests a critical need to reconcile differences in diverse SIF and GPP products and the relationships among them. Overall, the OCO-2 SIF products are robust and valuable for monitoring the global terrestrial carbon cycle and for constraining the carbon source/sink strengths of the Earth system. Finally, insights are offered for future satellite missions optimized for SIF retrievals.

GPP↗
DOE OSTI2015

New Surface Radiolabeling Schemes of Super Paramagnetic Iron Oxide Nanoparticles (SPIONs) for Biodistribution Studies

Nanomaterial based drug delivery systems allow for the independent tuning of the surface chemical and physical properties that affect their biodistribution in vivo and the therapeutic payloads that they are intended to deliver. Additionally, the added therapeutic and diagnostic value of their inherent material properties often provides extra functionality. Iron based nanomaterials with their magnetic properties and 10 easily tailorable surface chemistry are of particular interest as model systems. In this study the core radius of the iron oxide nanoparticles (NPs) was 14.08 3.92 nm while the hydrodynamic radius of the NPs, as determined by Dynamic Light Scattering (DLS), was between 90 110 nm. In this study, different approaches were explored to create radiolabeled NPs that are stable in solution. The NPs were functionalized with polycarboxylate or polyamine surface functional groups. Polycarboxylate 15 functionalized NPs had a zeta potential of -35 mV and polyamine functionalized NPs had a zeta potential of +40 mV. The polycarboxylate functionalized NPs were chosen for in vivo biodistribution studies and hence were radiolabeled with 14 C, with a final activity of 0.097 nCi/mg -1 of NPs. In chronic studies, the biodistribution profile is tracked using low level radiolabeled proxies of the nanoparticles of interest. Conventionally, these radiolabeled proxies are chemically similar but not chemically identical to the non-20 radiolabeled NPs of interest. This study is novel as different approaches were explored to create radiolabeled NPs that are stable, possess a hydrodynamic radius of <100 nm and most importantly they exhibit an identical surface chemical functionality as their non-radiolabeled counterparts. Identical chemical functionality of the radiolabeled probes to the non-radiolabeled probes was an important consideration to generate statistically similar biodistribution data sets using multiple imaging and 25 detection techniques. The radiolabeling approach described here is applicable to the synthesis of a large class of nanomaterials with multiple core and surface functionalities. This work combined with the biodistribution data suggests that the radiolabeling schemes carried out in this study have broad implications for use in pharmacokinetic studies for a variety of nanomaterials.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2016

Variability of fire emissions on interannual to multi-decadal timescales in two Earth System models

Connections between wildfires and modes of variability in climate are sought as a means for predicting fire activity on interannual to multi-decadal timescales. Several fire drivers, such as temperature and local drought index, have been shown to vary on these timescales, and analysis of tree-ring data suggests covariance between fires and climate oscillation indices in some regions. HBut, the shortness of the satellite record of global fire events limits investigations on larger spatial scales. Here we explore the interplay between climate variability and wildfire emissions with the preindustrial long control numerical experiments and historical ensembles of CESM1 and the NOAA/GFDL ESM2Mb. We find that interannual variability in fires is underpredicted in both Earth System models (ESMs) compared to present day fire emission inventories. Modeled fire emissions respond to the El Niño/southern oscillation (ENSO) and Pacific decadal oscillation (PDO) with increases in southeast Asia and boreal North America emissions, and decreases in southern North America and Sahel emissions, during the ENSO warm phase in both ESMs, and the PDO warm phase in CESM1. In addition, CESM1 produces decreases in boreal northern hemisphere fire emissions for the warm phase of the Atlantic Meridional Oscillation. Through analysis of the long control simulations, we show that the 20th century trends in both ESMs are statistically significant, meaning that the signal of anthropogenic activity on fire emissions over this time period is detectable above the annual to decadal timescale noise. However, the trends simulated by the two ESMs are of opposite sign (CESM1 decreasing, ESM2Mb increasing), highlighting the need for improved understanding, proxy observations, and modeling to resolve this discrepancy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

HeCS-SZ: The hectospec survey of Sunyaev–Zeldovich-selected clusters

We estimate cluster masses and velocity dispersions for 123 clusters from optical spectroscopy to compare the Sunyaev–Zeldovich (SZ) mass proxy and dynamical masses. Our new survey, HeCS-SZ (Hectospec Cluster Survey of SZ-selected clusters), includes 7721 new or remeasured redshifts from MMT/Hectospec observations of 21 SZ-selected clusters at redshifts z = 0.05–0.20. We supplement the Hectospec data with spectra from the Sloan Digital Sky Survey (SDSS) and cluster data from the Cluster Infall Regions in SDSS project and the Hectospec Cluster Survey, our Hectospec survey of clusters selected by X-ray flux. We measure the scaling relation between velocity dispersion and SZ mass estimates from the integrated Compton parameter for an SZ-complete sample of 83 clusters. The observed relation agrees very well with a simple virial scaling from mass (based on SZ) to velocity dispersion. The SZ mass estimates (calibrated with hydrostatic X-ray mass estimates) are not significantly biased compared to dynamical mass estimates under the assumption of small velocity bias of galaxies compared to dark matter particles. Significant mass bias in SZ mass estimates could relieve tension between cosmological results from Planck SZ cluster counts and Planck CMB data. In principle, SZ mass bias and velocity bias of galaxies could conspire to yield good agreement, but the required velocity bias is σ{sub galaxy}≈0.77σ{sub DM}, outside the range of recent models of velocity bias in the literature. More likely, SZ mass bias and velocity bias are both small, and the tension between SZ cluster counts and CMB data requires another explanation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

DGaaS: GPU as a Service on Distributed Computing System

In the rapidly evolving landscape of scientific computing, Graphics Processing Units (GPUs) have become indispensable for their unparalleled ability to handle parallel tasks in complex calculations, simulations, and data analysis. Their utility is further magnified in machine learning and AI applications, where they significantly accelerate model training and predictive analytics. Within this context, the Triton Inference Server emerges as a pivotal open-source tool, specializing in AI inferencing and optimizing GPU utilization across various platforms and frameworks. This paper presents an in-depth study on distributed High Throughput Computing (HTC), specifically focusing on the HTCondor framework and its resource provisioning tools, GlideinWMS and HEPCloud. These systems enable large-scale scientific experiments like CMS and DUNE to efficiently access and utilize vast computational resources. The paper explores the core architectural components of GlideinWMS, including jobs, user pools, and worker nodes, and discusses their integration with GPUs and the Triton server. The primary aim of this research is to develop a solution that optimizes GPU utilization by leveraging Glideins and containers. This approach allows computational jobs, particularly those involving AI models, to use GPUs only when essential, thereby facilitating efficient sharing of limited GPU resources. To validate this architecture, the study conducted three key tests involving custom scripts, container-based servers, and Triton server deployments. However, the study faces challenges, notably in locating the Triton server and ensuring secure remote access. To address these issues, future work will focus on developing a proxy mechanism and enhancing security protocols. In conclusion, this study offers a comprehensive roadmap for effective and efficient GPU utilization in distributed High Throughput Computing. It aims to contribute significantly to the scientific community by solving pressing problems and implementing robust solutions in collaboration with the GlideinWMS and HEPCloud teams. The research sets the stage for a more efficient, scalable, and cost-effective paradigm in scientific computing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Using elliptical galaxy kinematics to compare the strength of gravity in cosmological regions of differing gravitational potential – a first look

ABSTRACT Various models of modified gravity invoke ‘screening’ mechanisms that are sensitive to the value of the local gravitational potential. This could have observable consequences for galaxies. These consequences might be seen by comparing two proxies for galaxy mass – their luminosity and their internal kinematics – as a function of local galaxy density. Motivated by this prospect, we have compared the observed properties of luminous red galaxies (LRGs) inside and outside of voids in the cosmic large scale structure. We used archival measurements of line widths, luminosities, redshifts, colours, and positions of galaxies in conjunction with recent void catalogues to construct comparison LRG samples inside and outside of voids. We fitted these two samples to the well-established fundamental plane of elliptical galaxies to constrain any differences between the inferred value of the Newtonian gravitational constant G for the two samples. We obtained a null result, with an upper limit on any fractional difference in G within and outside of cosmological voids to be α = δG/G ∼ 40 per cent. This upper bound is dominated by the small-number statistics of our N ∼ 100 within-void LRG sample. With the caveat that environmental effects could influence various parameters such as star formation, we estimate that a 1 per cent statistical limit on α could be attained with data from 105 elliptical galaxies within voids. This is within the reach of future photometric and spectroscopic surveys, both of which are required to pursue this method.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Tracing fetal and childhood exposure to lead using isotope analysis of deciduous teeth

We report progress in using the isotopic composition and concentration of Pb in the dentine and enamel of deciduous teeth to provide a high resolution time frame of exposure to Pb during fetal development and early childhood. Isotope measurements (total Pb and {sup 208}Pb/{sup 206}Pb, {sup 207}Pb/{sup 206}Pb ratios) were acquired by laser ablation inductively coupled mass spectrometry at contiguous 100 micron intervals across thin sections of the teeth; from the outer enamel surface to the pulp cavity. Teeth samples (n=10) were selected from two cohorts of children, aged 5–8 years, living in NE England. By integrating the isotope data with histological analysis of the teeth, using the daily incremental lines in dentine, we were able to assign true estimated ages to each ablation point (first 2–3 years for molars, first 1–2 years for incisors+pre-natal growth). Significant differences were observed in the isotope composition and concentration of Pb between children, reflecting differences in the timing and sources of exposure during early childhood. Those born in 2000, after the withdrawal of leaded petrol in 1999, have the lowest dentine Pb levels (<0.2 µg Pb/g) with {sup 208}Pb/{sup 206}Pb (mean ±2σ: 2.126–2.079) {sup 208}Pb/{sup 206}Pb (mean ±2σ: 0.879–0.856) ratios that correlate very closely with modern day Western European industrial aerosols (PM{sub 10}, PM{sub 2.5}) suggesting that diffuse airborne pollution was probably the primary source and exposure pathway. Legacy lead, if present, is insignificant. For those born in 1997, dentine lead levels are typically higher (>0.4 µgPb/g) with {sup 208}Pb/{sup 206}Pb (mean ±2σ: 2.145–2.117) {sup 208}Pb/{sup 206}Pb (mean ±2σ: 0.898–0.882) ratios that can be modelled as a binary mix between industrial aerosols and leaded petrol emissions. Short duration, high intensity exposure events (1–2 months) were readily identified, together with evidence that dentine provides a good proxy for childhood changes in the isotope composition of blood Pb. Our pilot study confirms that laser ablation Pb isotope analysis of deciduous teeth, when carried out in conjunction with histological analysis, permits a reconstruction of the timing, duration and source of exposure to Pb during early childhood. With further development, this approach has the potential to study larger cohorts and appraise environments where the levels of exposure to Pb are much higher. - Highlights: • Reconstructing a high resolution chronology of early childhood exposure to lead. • Combined laser ablation lead isotope – histological analysis of children's teeth. • Using dentine to recover information on the intensity, duration and source of lead. • Importance of industrial airborne lead pollution in a post-leaded petrol era.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2020

Biomass Estimation from Simulated GEDI, ICESat-2 and NISAR Across Environmental Gradients in Sonoma County, California

Estimates of the magnitude and distribution of aboveground carbon in Earth’s forests remain uncertain, yet knowledge of forest carbon content at a global scale is critical for forest management in support of climate mitigation. In light of this knowledge gap, several upcoming spaceborne missions aim to map forest aboveground biomass, and many new biomass products are expected from these datasets. As these new missions host different technologies, each with relative strengths and weaknesses for biomass retrieval, as well as different spatial resolutions, consistently comparing or combining biomass estimates from these new datasets will be challenging. This paper presents a demonstration of an inter-comparison of biomass estimates from simulations of three NASA missions (GEDI, ICESat-2 and NISAR) over Sonoma county in California, USA. We use a high resolution, locally calibrated airborne lidar map as our reference dataset, and emphasize the importance of considering uncertainties in both reference maps and spaceborne estimates when conducting biomass product validation. GEDI and ICESat-2 were simulated from airborne lidar point clouds, while UAVSAR’s L-band backscatter was used as a proxy for NISAR. To estimate biomass for the lidar missions we used GEDI’s footprint-level biomass algorithms, and also adapted these for application to ICESat-2. For UAVSAR, we developed a locally trained biomass model, calibrated against the ALS reference map. Each mission simulation was evaluated in comparison to the local reference map at its native product resolution (25 m, 100m transect, and 1 ha) yielding RMSEs of 57%, 75%, and 89% for GEDI, NISAR, and ICESat-2 respectively. RMSE values increased for GEDI’s power beam during simulated daytime conditions (64%), coverage beam during nighttime conditions (72%), and coverage beam daytime conditions (87%). We also test the application of GEDI’s biomass modeling framework for estimation of biomass from ICESat-2, and fine that ICESat-2 yields reasonable biomass estimates, particularly in relatively short, open canopies. Results suggest that while all three missions will produce datasets useful for biomass mapping, tall, dense canopies such as those found in Sonoma County present the greatest challenges for all three missions, while steep slopes also prove challenging for single-date SAR based biomass retrieval. Our methods provide guidance for the inter-comparison and validation of spaceborne biomass estimates through the use of airborne lidar reference maps, and could be repeated with on-orbit estimates in any area with high quality field plot and ALS data. These methods allow for regional interpretations and filtering of multi-mission biomass estimates toward improved wall-to-wall biomass maps through data fusion.

GEDI↗
DOE OSTI2022

BASS XXXII: Studying the Nuclear Millimeter-wave Continuum Emission of AGNs with ALMA at Scales ≲100–200 pc

To understand the origin of nuclear (≲100 pc) millimeter-wave (mm-wave) continuum emission in active galactic nuclei (AGNs), we systematically analyzed subarcsecond resolution Band-6 (211–275 GHz) Atacama Large Millimeter/submillimeter Array data of 98 nearby AGNs (z < 0.05) from the 70 month Swift/BAT catalog. The sample, almost unbiased for obscured systems, provides the largest number of AGNs to date with high mm-wave spatial resolution sampling (~1–200 pc), and spans broad ranges of 14–150 keV luminosity {$40\lt \mathrm{log}[{L}_{14-150}/(\mathrm{erg}\,{{\rm{s}}}^{-1})]\lt 45$}, black hole mass $[5\lt \mathrm{log}({M}_{\mathrm{BH}}/{M}_{\odot })\lt 10$], and Eddington ratio ($-4\lt \mathrm{log}{\lambda }_{\mathrm{Edd}}\lt 2$). We find a significant correlation between 1.3 mm (230 GHz) and 14–150 keV luminosities. Its scatter is ≈0.36 dex, and the mm-wave emission may serve as a good proxy of the AGN luminosity, free of dust extinction up to N H ~ 10 26 cm –2 . While the mm-wave emission could be self-absorbed synchrotron radiation around the X-ray corona according to past works, we also discuss different possible origins of the mm-wave emission: AGN-related dust emission, outflow-driven shocks, and a small-scale (<200 pc) jet. The dust emission is unlikely to be dominant, as the mm-wave slope is generally flatter than expected. Also, due to no increase in the mm-wave luminosity with the Eddington ratio, a radiation-driven outflow model is possibly not the common mechanism. Furthermore, we find independence of the mm-wave luminosity on indicators of the inclination angle from the polar axis of the nuclear structure, which is inconsistent with a jet model whose luminosity depends only on the angle.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2011

Status of Precise Orbit Determination for Jason-2 Using GPS

The JASON-2 satellite, launched in June 2008, is the latest follow-on to the successful TOPEX/Poseidon (T/P) and JASON-I altimetry missions. JASON-2 is equipped with a TRSR Blackjack GPS dual-frequency receiver, a laser retroreflector array, and a DORIS receiver for precise orbit determination (POD). The most recent time series of orbits computed at NASA GSFC, based on SLR/DORIS data have been completed using both ITRF2005 and ITRF2008. These orbits have been shown to agree radially at 1 cm RMS for dynamic vs SLRlDORIS reduced-dynamic orbits and in comparison with orbits produced by other analysis centers (Lemoine et al., 2010; Zelensky et al., 2010; Cerri et al., 2010). We have recently upgraded the GEODYN software to implement model improvements for GPS processing. We describe the implementation of IGS standards to the Jason2 GEODYN GPS processing, and other dynamical and measurement model improvements. Our GPS-only JASON-2 orbit accuracy is assessed using a number of tests including analysis of independent SLR and altimeter crossover residuals, orbit overlap differences, and direct comparison to orbits generated at GSFC using SLR and DORIS tracking, and to orbits generated externally at other centers. Tests based on SLR and the altimeter crossover residuals provide the best performance indicator for independent validation of the NASAlGSFC GPS-only reduced dynamic orbits. For the ITRF2005 and ITRF2008 implementation of our GPS-only obits we are using the IGS05 and IGS08 standards. Reduced dynamic versus dynamic orbit differences are used to characterize the remaining force model error and TRF instability. We evaluate the GPS vs SLR & DORIS orbits produced using the GEODYN software and assess in particular their consistency radially and the stability of the altimeter satellite reference frame in the Z direction for both ITRF2005 and ITRF2008 as a proxy to assess the consistency of the reference frame for altimeter satellite POD.

Melachroinos, S.↗
NASA NTRS2011

Intraseasonal Variations in Tropical Energy Balance: Relevance to Climate Sensitivity?

Intraseasonal variability of deep convection represents a fundamental mode of organization for tropical convection. While most studies of intraseasonal oscillations (ISOs) have focused on the spatial propagation and dynamics of convectively coupled circulations, here we examine the projection of ISOs on the tropically-averaged heat and moisture budget. One unresolved question concerns the degree to which observable variations in the "fast" processes (e.g. convection, radiative / turbulent fluxes) can inform our understanding of feedback mechanisms operable in the context of climate change. Our analysis use daily data from satellite observations, the Modern Era analysis for Research and Applications (MERRA), and other model integrations to address these questions: (i) How are tropospheric temperature variations related to that tropical deep convection and the associated ice cloud fractional amount (ICF), ice water path (IWP), and properties of warmer liquid clouds? (ii) What role does moisture transport play vis-a-vis ocean latent heat flux in enabling the evolution of deep convection to mediate PBL - free atmospheric temperature equilibration? (iii) What affect do convectively generated upper-tropospheric clouds have on the TOA radiation budget? Our methodology is similar to that of Spencer et al., (2007 GRL ) whereby a composite time series of various quantities over 60+ ISO events is built using tropical mean tropospheric temperature signal as a reference to which the variables are related at various lag times (from -30 to +30 days). The area of interest encompasses the global oceans between 20oN/S. The increase of convective precipitation cannot be sustained by evaporation within the domain, implying strong moisture transports into the tropical ocean area. The decrease in net TOA radiation that develops after the peak in deep convective rainfall, is part of the response that constitutes a "discharge" / "recharge" mechanism that facilitates tropical heat balance maintenance on these time scales. However, water vapor and hydrologic scaling relationships for this mode of variability cast doubt on the utility of ISO variations as proxies for climate sensitivity response to external radiatively forced (e.g. greenhouse gas-induced) climate change.

Robertson, Franklin R.↗
DOE OSTI2025

How does ion temperature gradient turbulence depend on magnetic geometry? Insights from data and machine learning

Magnetic geometry has a significant effect on the level of turbulent transport in fusion plasmas. Here, we model and analyse this dependence using multiple machine learning methods and a dataset of >200 000 nonlinear gyrokinetic simulations of ion-temperature-gradient turbulence in diverse non-axisymmetric geometries. The dataset is generated using a large collection of both optimised and randomly generated stellarator equilibria. At fixed gradients and other input parameters, the turbulent heat flux varies between geometries by several orders of magnitude. Trends are apparent among the configurations with particularly high or particularly low heat flux. Regression and classification techniques from machine learning are then applied to extract patterns in the dataset. Due to a symmetry of the gyrokinetic equation, the heat flux and regressions thereof should be invariant to translations of the raw features in the parallel coordinate, similar to translation invariance in computer vision applications. Multiple regression models including convolutional neural networks (CNNs) and decision trees can achieve reasonable predictive power for the heat flux in held-out test configurations, with highest accuracy for the CNNs. Using Spearman correlation, sequential feature selection and Shapley values to measure feature importance, it is consistently found that the most important geometric lever on the heat flux is the flux surface compression in regions of bad curvature. The second most important geometric feature relates to the magnitude of geodesic curvature. These two features align remarkably with surrogates that have been proposed based on theory, while the methods here allow a natural extension to more features for increased accuracy. The dataset, released with this publication, may also be used to test other proposed surrogates, and we find that many previously published proxies do correlate well with both the heat flux and stability boundary.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Protecting and Defending against Autonomous Control Systems and Digital Twin Cyber Attacks: Response Strategy for Hyperparameter attacks of Digital Twin Machine Learning Models in Nuclear Power Plants (Final)

Navigating through the complex tapestry of technological advancements, "Response Strategy for Hyperparameter attacks of Digital Twin Machine Learning Model in Nuclear Power Plants" stands at the intersection of cybersecurity and nuclear power plant operations, embarking on a journey through the intricacies of securing digital twins against malicious cyber activities. As nuclear power plants progressively integrate digital twin technology and machine learning models to optimize operations and ensure system reliability, they inadvertently expose themselves to a new spectrum of vulnerabilities, notably in the realm of hyperparameter attacks. Hyperparameters, integral in machine learning model tuning and optimal performance of digital twins, have emerged as a target for adversaries aiming to destabilize the predictive capabilities and therefore, the operational accuracy of these digital entities within critical infrastructures like nuclear plants. This paper, therefore, meticulously threads the needle through the development of a robust response strategy, poised to shield these digital reflections against calculated hyperparameter manipulations, ensuring that the digital twin can effectively and securely function as a reliable proxy for its physical counterpart. The ensuing sections delve into the orchestrated maelstrom of multi-rate time-changing intelligent coordinated hyperparameter attacks and the implementation of event-triggered predictive control, laying down a structured, predictive, and responsive framework that safeguards the nexus where the digital and physical realms of nuclear power plants coalesce. The operational integrity of digital twins in nuclear power plants depends critically on the security of machine learning hyperparameters. This study makes two different contributions. First, a decision-based idea known as a multi-rate time changing intelligent coordinated hyperparameter attack is put forth. In this attack, many hyperparameters are repeatedly changed using both random and intelligent optimal techniques by the attacker. These assaults introduce varied rates at different attack steps, compromise various amounts of hyperparameters, and improve stealth and flexibility. Second, a technique is developed for event triggered predictive control to rapidly respond to potential hyperparameter attacks. This control integrates a sliding window framework, retaining a history of previous data points and employing linear regression to predict the next data point from the current dataset. The control gain K is determined using the Lyapunov-Krasovskii method, and subsequently, an action is developed. Finally, the outcome of the simulation demonstrates the viability of the proposed method for defending nuclear power plant digital twins from hyperparameter attacks.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Climate impact on fluvial-lake system evolution, Eocene Green River Formation, Uinta Basin, Utah, USA

In light of a modern understanding of early Eocene greenhouse climate fluctuations and new highly seasonal fluvial system faces models, the role of climate in the evolution of one classically-cited continental, terminal lake system is re-examined. Detailed stratigraphic description and elemental abundance data from fifteen cores and seven outcrop regions of the Green River Formation were used to construct a ~150 km cross section across the Uinta Basin, Utah, USA. Lake Uinta in the Uinta Basin is divided into five lake phases: (1) post-Paleocene Eocene Thermal Maximum, (2) peak Eocene hyperthermal, (3) waning hyperthermal, Early Eocene Climatic Optimum (EECO), (4) post-hyperthermal, and (5) post-EECO regimes, based primarily on climatically driven changes in fluvial style in combination with sedimentary indicators of lacustrine carbonate deposition, organic matter preservation, salinity, and lake depth. Basinwide siliciclastic dominated intervals were deposited by highly seasonal fluvial systems and record negative organic carbon isotope excursions associated with early Eocene abrupt, transient global warming (hyperthermal) events. Carbonate dominated or organic rich intervals record stable, less seasonal climate periods between hyperthermals, with lower siliciclastic sediment supply allowing the development of carbonate and organic matter preservation. The stratigraphic progression from alternating organic rich and lean zones to the overlying organic rich Mahogany and R8 zones represents the global transition out of the pulsed early Eocene hyperthermal climate regime to a time of sediment starvation and lake stratification, sequestering sedimentary organic carbon. This study provides a novel approach to terrestrial paleoclimate reconstruction that relies largely on unique sedimentary indicators and secondarily on isotopic proxy records within the context of a large basin-wide sedimentologic and stratigraphic data set, thus setting the stage for future detailed geochemical terrestrial paleoclimate proxy development.

Geology↗
DOE OSTI2024

Evaluation of GlassNet for physics-informed machine learning of glass stability and glass-forming ability

Glassy materials form the basis of many modern applications, including nuclear waste immobilization, touch-screen displays, and optical fibers, and also hold great potential for future medical and environmental applications. However, their structural complexity and large composition space make design and optimization challenging for certain applications. Of particular importance for glass processing and design is an estimate of a given composition's glass-forming ability (GFA). However, there remain many open questions regarding the underlying physical mechanisms of glass formation, especially in oxide glasses. It is apparent that a proxy for GFA would be highly useful in glass processing and design, but identifying such a surrogate property has proven itself to be difficult. While glass stability (GS) parameters have historically been used as a GFA surrogate, recent research has demonstrated that most of these parameters are not accurate predictors of the GFA of oxide glasses. Here, in this work, we explore the application of an open-source pre-trained neural network model, GlassNet, that can predict the characteristic temperatures necessary to compute GS with reasonable performance and assess the feasibility of using these physics-informed machine learning (PIML)-predicted GS parameters to estimate GFA. In doing so, we track the uncertainties at each step of the computation—from the original ML prediction errors to the compounding of errors during GS estimation, and finally to the final estimation of GFA. While GlassNet exhibits reasonable accuracy on all individual properties, we observe a large compounding of error in the combination of these individual predictions for the PIML prediction of GS, finding that random forest models offer similar accuracy to GlassNet. We also break down the performance of GlassNet on different glass families and find that the error in GS prediction is correlated with the error in crystallization peak temperature prediction. Lastly, we utilize this finding to assess the relationship between top-performing GS parameters and GFA for two ternary glass systems: sodium borosilicate and sodium iron phosphate glasses. We conclude that to obtain true ML predictive capability of GFA, significantly more data needs to be collected.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Satellite solar-induced chlorophyll fluorescence and near-infrared reflectance capture complementary aspects of dryland vegetation productivity dynamics

Mounting evidence indicates dryland ecosystems play an important role in driving the interannual variability and trend of the terrestrial carbon sink. Nevertheless, our understanding of the seasonal dynamics of dryland ecosystem carbon uptake through photosynthesis [gross primary productivity (GPP)] remains relatively limited due in part to the limited availability of long-term data and unique challenges associated with satellite remote sensing across dryland ecosystems. Here, we comprehensively evaluated longstanding and emerging satellite vegetation proxies in their ability to capture seasonal dryland GPP dynamics. Specifically, we evaluated: 1) reflectance-based proxies normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), near infrared reflectance index (NIR v ), and kernel NDVI (kNDVI) from the MODerate resolution Imaging Spectroradiometer (MODIS); and 2) newly available physiologically-based proxy solar-induced chlorophyll fluorescence (SIF) from the TROPOspheric Monitoring Instrument (TROPOMI). As a performance benchmark, we used GPP estimates from a robust network of 21 western United States eddy covariance tower sites that span representative gradients in dryland ecosystem climate and functional composition. We found that NIR v and SIF were the best performing GPP proxies and captured complementary aspects of seasonal GPP dynamics across dryland ecosystem types. NIR v offered better performance than the other proxies across relatively low-productivity, sparsely non-evergreen vegetated sites (R 2 = 0.59 ± 0.13); whereas SIF best captured seasonal dynamics across relatively high-productivity sites, including evergreen-dominated sites (R 2 = 0.74 ± 0.07). Notably, across grass-dominated sites, all reflectance-based proxies (NDVI, SAVI, NIRv and kNDVI) showed significant seasonal bias (hysteresis) that strengthened with the total fraction of woody vegetation cover, likely due to seasonal patterns in woody vegetation reflectance that are unrelated to or decoupled from GPP. In conclusion, future efforts to fully integrate the complementary strengths of NIR v and SIF could significantly improve our understanding and representation of dryland GPP dynamics in satellite-based models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

FIELD IMPLEMENTATION PLAN FOR A WILLISTON BASIN BRINE EXTRACTION AND STORAGE TEST

The Energy & Environmental Research Center (EERC) successfully completed all technical work of Phase I, including development of a field implementation plan (FIP) for a brine extraction and storage test (BEST) in the North Dakota portion of the Williston Basin. This implementation plan was commissioned by the U.S. Department of Energy (DOE) National Energy Technology Laboratory (NETL) as a proxy for managing formation pressure plumes and measuring/monitoring the movement of differential pressure and CO2 plumes in the subsurface for future saline CO2 storage projects. BEST comprises the demonstration and validation of active reservoir management (ARM) strategies and extracted brine treatment technologies. Two prospective commercial brine injection sites were evaluated for BEST to satisfy DOE’s goals. Ultimately, an active saltwater disposal (SWD) site, Johnsons Corner, was selected because it possesses an ideal combination of key factors making it uniquely suited to host BEST. This site is located in western North Dakota and operated by Nuverra Environmental Solutions (Nuverra), a national leader in brine handling, treatment, and injection. An integrated management approach was used to incorporate local and regional geologic characterization activities with geologic and simulation models, inform a monitoring, verification, and accounting (MVA) plan, and to conduct a risk assessment. This approach was used to design a FIP for an ARM schema and an extracted brine treatment technology test bed facility. The FIP leverages an existing pressure plume generated by two commercial SWD wells. These wells, in conjunction with a new brine extraction well, will be used to conduct the ARM schema. Results of these tests will be quantified based on their impact on the performance of the existing SWD wells and the surrounding reservoir system. Extracted brine will be injected into an underlying deep saline formation through a new injection well. The locations of proposed extraction and injection wells were selected during the Phase I efforts. These wells will be permitted as North Dakota Administrative Code Underground Injection Control Class II wells and will yield additional characterization data which will further refine the FIP in Phase II. An array of surface and downhole monitoring techniques will validate ARM performance against predictive simulation results. Infrastructure will be constructed to manage extracted fluids at the surface and provide brine to a treatment test bed facility. Treatment of extracted brine can provide a means of reducing extracted brine disposal volumes, an alternate source of water, and/or salable products for beneficial use. A test bed facility will be constructed to provide a means of demonstrating these technologies on a wide range of brine concentrations. Screening criteria based on a techno-economic and life cycle assessment were developed to select high-salinity brine treatment technologies for extended duration treatment (30–60 days) in Phase II. A detailed cost assessment determined total implementation costs for BEST of $19,901,065 million (DOE share $15,680,505). These costs are inclusive of all necessary equipment, infrastructure construction, operations and project closeout costs required to implement BEST. An ideal combination of key factors makes the Johnsons Corner site uniquely suited to be the BEST demonstration.

10 SYNTHETIC FUELS↗
NASA NTRS2022

Constraining Clouds and Convective Parameterizations in A Climate Model Using Paleoclimate Data

Cloud and convective parameterizations strongly influence uncertainties in equilibrium climate sensitivity. We provide a proof-of-concept study to constrain these parameterizations in a perturbed parameter ensemble of the atmosphere-only version of the Goddard Institute for Space Studies Model E2.1 simulations by evaluating model biases in the present-day runs using multiple satellite climatologies and by comparing simulated δ 18 O of precipitation (δ 18 O p ), known to be sensitive to parameterization schemes, with a global database of speleothem δ 18 O records covering the Last Glacial Maximum (LGM), mid-Holocene (MH) and pre-industrial (PI) periods. Relative to modern interannual variability, paleoclimate simulations show greater sensitivity to parameter changes, allowing for an evaluation of model uncertainties over a broader range of climate forcing and the identification of parts of the world that are parameter sensitive. Certain simulations reproduced absolute δ 18 O p values across all time periods, along with LGM and MH δ 18 O p anomalies relative to the PI, better than the default parameterization. No single set of parameterizations worked well in all climate states, likely due to the non-stationarity of cloud feedbacks under varying boundary conditions. Future work that involves varying multiple parameter sets simultaneously with coupled ocean feedbacks will likely provide improved constraints on cloud and convective parameterizations.

cloud and convective parameterization↗