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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Model-Based Detection of Coordinated Attacks (DCA) in Distribution Systems

The fast-paced growth in digitization of smart grid components enhances system observability and remote-control capabilities through efficient communication. However, enhanced connectivity results in heightened system vulnerability towards cybersecurity risks in the cyber-physical power system. Coordinated cyber-attacks (CCA), when undetected, lead to system-wide impact in terms of large disturbances or widespread outages. Detecting CCA in the cyber layer is critical to thwart cyber-attacks in real-time before the attack impacts the physical system. The challenge of locating CCA stems from the complex grid dynamics, making it difficult to distinguish between normal operational variations and cyber-attack impact. CCA often employs multiple attack vectors targeting geographically distributed components, further complicating CCA identification. Existing research in intrusion detection is primarily focused on the transmission network and limited to detecting individual attacks. In this paper, a novel proactive DCA strategy is proposed for early detection of CCA by establishing correlations among distinct attack events through model-based reinforcement learning that utilizes abductive reasoning to conclude the attacker goal. The solution includes understanding the system model, learning the system dynamics, and correlating individual cyber-attacks to extract the attacker’s objective. The developed learning algorithm identifies the most probable attack path to reach the attacker’s objective by predicting the next attack steps. A DNP3-based cyber-physical co-simulation testbed is developed to test the proposed algorithm using the IEEE 13-node test feeder.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Numerical study of groundwater flow cycling controlled by seawater/freshwater interaction in Woodville Karst Plain

Seawater intrusion due to sea level rise and climate change could significantly contaminate coastal groundwater resources, particularly in Florida, the flat low-land state in the United States. Based on the field investigation and hydrological measurements, a three-dimensional SEAWAT model is developed to evaluate the groundwater flow cycling and seawater intrusion to freshwater system in the Woodville Karst Plain (WKP), a typical karst groundwater system in the Floridan aquifer. The karst conduit network in the aquifer acts as fast flow pathway for groundwater flow and solute transport, so seawater could deeply intrude into the aquifer. Wakulla Spring, an inland spring 17 km from the coast and a coastal submarine spring, Spring Creek Spring Complex are connected through the conduit network. The flow direction between the two springs switches under various rainfall conditions in this region, thus the discharges at two karst springs are used to estimate the location of seawater/freshwater mixing interface. The SEAWAT modeling results indicate that the mixing interface, defined as 2 PSU (Practical Salinity Unit), intrudes 3 to 5 km through the subsurface karst conduit during the dry season and severely contaminates nearly 1 km width of groundwater around the conduit. The salinity distribution and the distance of seawater intrusion through the conduit system are very sensitive to precipitation variation and the sea level boundary condition. Furthermore, predictions are made for seawater intrusion to the aquifer under various sea level rise, precipitation scenarios and water pumping. The results show that the seawater intrusion could reach and contaminate inland freshwater systems if sea level rises 1.0 m or during a long-term no-precipitation season. Finally, this study provides insights for modeling and predicting the vulnerability of a coastal karst aquifer through the simulation of variable-density flow.

58 GEOSCIENCES↗
DOE OSTI2025

Integrated modeling of RF-induced tungsten erosion at ICRH antenna structures in the WEST tokamak *

This paper introduces STRIPE (Simulated Transport of RF Impurity Production and Emission), an advanced modeling framework developed to analyze material erosion and the global transport of eroded impurities originating from radio-frequency (RF) antenna structures in magnetic confinement fusion devices. STRIPE integrates multiple physics modules: SolEdge3x for scrape-off-layer plasma profiles, COMSOL for 3D RF rectified sheath potentials, RustBCA for erosion yields and surface interactions, and global impurity transport for 3D ion energy-angle distributions and impurity transport. The framework is applied to an ion cyclotron RF-heated L-mode discharge (#57877) in the WEST tokamak, where it predicts a thirty-fold increase in gross tungsten erosion at antenna limiters during the transition from ohmic to ICRH operation. Additionally, under ICRH conditions, a tenfold enhancement in erosion is observed when comparing RF sheath effects to purely thermal sheath conditions. High-charge-state oxygen ions ($\mathrm{O}$ 6+ and above) are identified as the dominant contributors to tungsten sputtering. To validate the model, a synthetic diagnostic tool based on inverse photon efficiency (S/XB coefficients) from the ColRadPy collisional-radiative model enables direct comparison with spectroscopic measurements. Model predictions using a plasma composition of 1% oxygen and 99% deuterium show good agreement with observed W − I (400.9 nm) emission for discharge #57877, supporting the accuracy of the STRIPE framework. This study focuses specifically on gross erosion calculations to demonstrate STRIPE’s capabilities. Future extensions of this work will incorporate net erosion, re-deposition, self-sputtering effects, and whole-device modeling of sputtered tungsten impurity transport. STRIPE is also being applied to other RF-heated linear and toroidal devices, offering valuable insights for antenna design, impurity control, and performance optimization in next-generation fusion reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2013

Random Sampling Process Leads to Overestimation of β-Diversity of Microbial Communities

The site-to-site variability in species composition, known as β-diversity, is crucial to understanding spatiotemporal patterns of species diversity and the mechanisms controlling community composition and structure. However, quantifying β-diversity in microbial ecology using sequencing-based technologies is a great challenge because of a high number of sequencing errors, bias, and poor reproducibility and quantification. Herein, based on general sampling theory, a mathematical framework is first developed for simulating the effects of random sampling processes on quantifying β-diversity when the community size is known or unknown. Also, using an analogous ball example under Poisson sampling with limited sampling efforts, the developed mathematical framework can exactly predict the low reproducibility among technically replicate samples from the same community of a certain species abundance distribution, which provides explicit evidences of random sampling processes as the main factor causing high percentages of technical variations. In addition, the predicted values under Poisson random sampling were highly consistent with the observed low percentages of operational taxonomic unit (OTU) overlap (<30% and <20% for two and three tags, respectively, based on both Jaccard and Bray-Curtis dissimilarity indexes), further supporting the hypothesis that the poor reproducibility among technical replicates is due to the artifacts associated with random sampling processes. Finally, a mathematical framework was developed for predicting sampling efforts to achieve a desired overlap among replicate samples. Our modeling simulations predict that several orders of magnitude more sequencing efforts are needed to achieve desired high technical reproducibility. These results suggest that great caution needs to be taken in quantifying and interpreting β-diversity for microbial community analysis using next-generation sequencing technologies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Thermodynamic and Kinetic Modulation of Methylammonium Lead Bromide Crystallization Revealed by In Situ Monitoring

Hybrid organic–inorganic perovskite (HOIP) crystals are promising optoelectronic materials, but little is known about either the thermodynamic and kinetic controls on crystal growth or the underlying growth mechanism(s). Herein, we use fluid cell atomic force microscopy (AFM) and solution nuclear magnetic resonance (NMR) spectroscopy to investigate growth of the model HOIP crystal CH 3 NH 3 PbBr 3 (MAPbBr 3 ) and to determine how formic acid (HCOOH) modulates the thermodynamics and kinetics of growth. The results show that growth of MAPbBr 3 in dimethylformamide (DMF) proceeds through the classical pathway by the spreading of atomic crystal steps generated at screw dislocations on the {100} surface. Temperature dependent step velocity measurements demonstrate that with increasing concentration, HCOOH decreases both the solubility of MAPbBr 3 and the kinetic coefficient (b) of step movement. 1 H-NMR measurements indicate that HCOOH increases the lifetime of the methylammonium (MA + ) ions and promotes the association of MAPbBr 3 , thus tuning the solubility of the perovskite. HCOOH also alters the molecular tumbling motion and bulk diffusion of the MA + ions, possibly via H-bonding. Further, our findings establish a direct correlation between the mesoscale crystal growth kinetics and the molecular-scale interactions between organic additives and constituent ions, providing unprecedented insights for developing predictive syntheses of HOIP crystals with defined size, crystal habit and shape, and defect distribution.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Identifying multiscale zonation and assessing the relative importance of polygon geomorphology on carbon fluxes in an Arctic tundra ecosystem

Abstract We develop a multiscale zonation approach to characterize the spatial variability of Arctic polygonal ground geomorphology and to assess the relative controls of these elements on land surface and subsurface properties and carbon fluxes. Working within an ice wedge polygonal region near Barrow, Alaska, we consider two scales of zonation: polygon features (troughs, centers, and rims of polygons) that are nested within different polygon types (high, flat, and low centered). In this study, we first delineated polygons using a digital elevation map and clustered the polygons into four types along two transects, using geophysical and kite‐based landscape‐imaging data sets. We extrapolated those data‐defined polygon types to all the polygons over the study site, using the polygon statistics extracted from the digital elevation map. Based on the point measurements, we characterized the distribution of vegetation, hydrological, thermal, and geochemical properties, as well as carbon fluxes, all as a function of polygon types and polygon features. Results show that nested polygon geomorphic zonation—polygon types and polygon features—can be used to represent distinct distributions of carbon fluxes and associated properties, as well as covariability among those properties. Importantly, the results indicate that polygon types have more power to explain the variations in those properties than polygon features. The approach is expected to be useful for improved system understanding, site characterization, and parameterization of numerical models aimed at predicting ecosystem feedbacks to the climate.

Wainwright, Haruko M.↗
DOE OSTI2015

Controlling Subsurface Fractures and Fluid Flow: A Basic Research Agenda

From beneath the surface of the earth, we currently obtain about 80-percent of the energy our nation consumes each year. In the future we have the potential to generate billions of watts of electrical power from clean, green, geothermal energy sources. Our planet’s subsurface can also serve as a reservoir for storing energy produced from intermittent sources such as wind and solar, and it could provide safe, long-term storage of excess carbon dioxide, energy waste products and other hazardous materials. However, it is impossible to underestimate the complexities of the subsurface world. These complexities challenge our ability to acquire the scientific knowledge needed for the efficient and safe exploitation of its resources. To more effectively harness subsurface resources while mitigating the impacts of developing and using these resources, the U.S. Department of Energy established SubTER – the Subsurface Technology and Engineering RD&D Crosscut team. This DOE multi-office team engaged scientists and engineers from the national laboratories to assess and make recommendations for improving energy-related subsurface engineering. The SubTER team produced a plan with the overall objective of “adaptive control of subsurface fractures and fluid flow.”This plan revolved around four core technological pillars—Intelligent Wellbore Systems that sustain the integrity of the wellbore environment; Subsurface Stress and Induced Seismicity programs that guide and optimize sustainable energy strategies while reducing the risks associated with subsurface injections; Permeability Manipulation studies that improve methods of enhancing, impeding and eliminating fluid flow; and New Subsurface Signals that transform our ability to see into and characterize subsurface systems. The SubTER team developed an extensive R&D plan for advancing technologies within these four core pillars and also identified several areas where new technologies would require additional basic research. In response, the Office of Science, through its Office of Basic Energy Science (BES), convened a roundtable consisting of 15 national lab, university and industry geoscience experts to brainstorm basic research areas that underpin the SubTER goals but are currently underrepresented in the BES research portfolio. Held in Germantown, Maryland on May 22, 2015, the round-table participants developed a basic research agenda that is detailed in this report. Highlights include the following: -A grand challenge calling for advanced imaging of stress and geological processes to help understand how stresses and chemical substances are distributed in the subsurface—knowledge that is critical to all aspects of subsurface engineering; -A priority research direction aimed at achieving control of fluid flow through fractured media; -A priority research direction aimed at better understanding how mechanical and geochemical perturbations to subsurface rock systems are coupled through fluid and mineral interactions; -A priority research direction aimed at studying the structure, permeability, reactivity and other properties of nanoporous rocks, like shale, which have become critical energy materials and exhibit important hallmarks of mesoscale materials; -A cross-cutting theme that would accelerate development of advanced computational methods to describe heterogeneous time-dependent geologic systems that could, among other potential benefits, provide new and vastly improved models of hydraulic fracturing and its environmental impacts; -A cross-cutting theme that would lead to the creation of “geo-architected materials” with controlled repeatable heterogeneity and structure that can be tested under a variety of thermal, hydraulic, chemical and mechanical conditions relevant to subsurface systems; -A cross-cutting theme calling for new laboratory studies on both natural and geo-architected subsurface materials that deploy advanced high-resolution 3D imaging and chemical analysis methods to determine the ;rates and mechanisms of fluid-rock processes, and to test predictive models of such phenomena. Many of the key energy challenges of the future demand a greater understanding of the subsurface world in all of its complexity. This greater under- standing will improve the ability to control and manipulate the subsurface world in ways that will benefit both the economy and the environment. This report provides specific basic research pathways to address some of the most fundamental issues of energy-related subsurface engineering.

15 GEOTHERMAL ENERGY↗
DOE OSTI2016

Modeling the formation of methane hydrate-bearing intervals in fine-grained sediments

Sediment grain size exerts a fundamental control on how methane hydrates are distributed within the pore space. Fine-grained muds are the predominant sediments in continental margins, and hydrates in these sediments have often been observed in semi-vertical veins and fractures. In several instances, these hydrate veins/fractures are found in discrete depth intervals a few tens meters thick within the gas hydrate stability zone (GHSZ) surrounded by hydrate-free sediments above and below. As they are not obviously connected with free gas occurring beneath the base of the GHSZ, these isolated hydrate-bearing intervals have been interpreted as formed by microbial methane generated in situ. To investigate further the formation of these hydrate deposits, we applied a time-dependent advection-diffusion-reaction model that includes the effects of sedimentation, solute diffusion, and microbial methane generation. The microbial methane generation term depends on the amount of metabolizable organic carbon deposited at the seafloor, which is degraded at a prescribed rate resulting in methane formation beneath the sulfate reduction zone. In the model, methane hydrate precipitates once the dissolved methane concentration is greater than solubility, or hydrate dissolves if concentration goes below solubility. If the deposition of organic carbon at the seafloor is kept constant in time, we found that the predicted amounts of hydrate formed in discrete intervals within the GHSZ are much less than those estimated from observations. We then investigated the effect of temporal variations in the deposition of organic carbon. If greater amounts of organic carbon are deposited during some time interval, methane generation is enhanced during burial in the corresponding sediment interval. With variations in organic carbon deposition that are consistent with observations in continental margin sediments, we were able to reproduce the methane hydrate contents estimated in discrete depth intervals. Our results support the suggestion that in situ microbial methane generation is the source for hydrates within fine-grained sediments.

Malinverno, Alberto↗
DOE OSTI2023

Utah FORGE: Optimization of a Plug-and-Perf Stimulation (Fervo Energy)

Information around the plug-and-perf treatment design at Utah FORGE by Fervo Energy. Objective and Purpose: - Develop a multistage hydraulic stimulation approach designed specifically to target the top three factors that control the technical and commercial viability of an EGS system: i) Achieving sufficient injectivity to support high cross-well flow rates ii) Distributing flow evenly across the wellbore and reservoir to maximize heat mining efficiency, ensure sustained heat transfer, and mitigate thermal breakthrough iii) Overcoming the effects of stress heterogeneity, stress shadowing, and variations in natural fracture properties during the stimulation treatment, leading to a more predictable stimulated reservoir volume and offset well placement - The following activities will be performed: i) Design, plan, and execute a multistage plug-and-perf stimulation treatment at a Fervo site with data acquisition and well testing activities aimed at addressing key technical aspects of the issues above ii) Perform data processing and interpretation of field results to translate the results form the Fervo site to a site-specific design at the Utah FORGE site iii) Design, plan, and execute a multistage plug-and-perf stimulation treatment design at the Utah FORGE site Methods and Approach: - Design a detailed data acquisition plan to maximize learning around: i) DFIT testing ii) Petrophysical logging, image logging iii) Permanent DAS/DTS fiber optic monitoring iv) Deep borehole microseismic monitoring v) Shallow borehole induced seismicity monitoring vi) Injection/production testing (RTA analysis, tracer testing) vii) Integrated numerical modeling and production forecasting

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Effects of Reactive Power on Photovoltaic Inverter Reliability and Lifetime

This paper performs research on predicting Photovoltaic (PV) inverters reliability and lifetime based on thermal cycling. Thermal cycling is considered the most important stressors in an inverter system. In order to achieve this, a detailed electro-thermal model of the PV inverter will be developed along with their controllers capable of providing voltage support through reactive power. An in-house inverter was built, and a PV inverter model was developed to match the physical inverter. The PV inverter electrothermal model was validated for different ambient temperatures to match the in-house inverter hardware. The in-house inverter was placed inside a thermal chamber to emulate different ambient temperatures and their losses and temperature rises within the system were measured. After the validation of the model, a reduced order model of the inverter will be implemented to translate the mission profile of ambient temperature and solar irradiance into load profile of junction temperatures of the switches. The junction temperature data will be used to identify the reliability indices and hence predict the useful lifetime of the inverter system. Along with the model to predict useful lifetime of the system, the impact of reactive power on the overall reliability of the system will be studied. The key observation in this paper shows that lifetime of the inverter decreases as the operating power factor moves away from unity.

14 SOLAR ENERGY↗
DOE OSTI2025

Source Analysis of Ozone Pollution in Liaoyuan City’s Atmosphere Based on Machine Learning Models and HYSPLIT Clustering Method

Firstly, this study investigates the spatiotemporal distribution characteristics of the ozone (O 3 ) pollution in Liaoyuan City using monitoring data from 2015 to 2024. Then, three machine learning models (ML)—random forest (RF), support vector machine (SVM), and artificial neural network (ANN)—are employed to quantify the influence of meteorological and non-meteorological factors on O 3 concentrations. Finally, the HYSPLIT clustering method and CMAQ model are utilized to analyze inter-regional transport characteristics, identifying the causes of O 3 pollution. The results indicate that O 3 pollution in Liaoyuan exhibits a distinct seasonal pattern, with the highest concentrations found in spring and summer, peaking in the afternoon. Among the three ML models, the random forest model demonstrates the best predictive performance (R 2 = 0.9043). Feature importance identifies NO 2 as the primary driving factor, followed by meteorological conditions in the second quarter and land surface characteristics. Furthermore, regional transport significantly contributes to O 3 pollution, with approximately 80% of air mass trajectories in heavily polluted episodes originating from adjacent industrial areas and the sea. The combined effects of transboundary precursors and O 3 transport with local emissions and meteorological conditions further increase the O 3 pollution level. This study highlights the need to strengthen coordinated NO X and VOCs emission reductions and enhance regional joint prevention and control strategies in China.

HYSPLIT clustering↗
DOE OSTI2018

Evaluating the functionality and streamflow impacts of explicitly modelling forest-snow interactions and canopy gaps in a distributed hydrologic model

Many plot-scale observational studies found that snow cover dynamics in forest gaps are distinctly different from open and continuously forested areas, and canopy gaps have the potential to increase snow retention and alter the snow regime. However, our knowledge on forest-snow interactions in discontinuous forests with canopy gaps and their implications for forest and water management is far more limited. We address this knowledge gap through a major enhancement of a widely used distributed hydrologic model, DHSVM. We developed a canopy gap component as a unique vegetation type that is characterized on the subgrid scale, with physics-based representation of processes that allow independent evolution of snowpack in forest gaps. We validated the enhanced DHSVM for three experimental sites in close proximity consisting of a completely open site, a densely forested site, and a canopy gap site. Despite the scale mismatch between point measurements and grid-scale simulations, the modeled snow water equivalent (SWE) agreed reasonably well with the continuous observations collected during one full ablation season at all sites. Evaluation of snowpack energetics suggested that snow ablation at three sites was controlled primarily by net radiation that critically depends on the canopy cover and structure. While the rate of snowmelt remained relatively constant in the forest during the ablation season, the gap demonstrated marked temporal variability in ablation rate as a result of complex interplay between canopy structure of the adjacent forest and the angle of solar incidence. The comparison of this enhanced version to the original DHSVM highlighted the importance of explicitly accounting for forest impacts on the gap snowpack energy balance. Between the two versions, the greatest difference in snow ablation rates was found in smaller gaps. The enhanced model tends to predict notably later melt for small to medium canopy gaps (the ratio of gap radius to canopy height r/h = 1.3), and snow melt rates exhibit great sensitivity to changing gap size in medium-size gaps (0.5 = r/h = 1.3).

Forest-Snow Dynamics, Canopy Gap, Snow Hydrology, ↗
DOE OSTI2014

The impact of including spatially longitudinal heterogeneities of vessel oxygen content and vascular fraction in 3D tumor oxygenation models on predicted radiation sensitivity

Purpose: Oxygen distribution models have been used to analyze the influences of oxygen tensions on tissue response after radiotherapy. These distributions are often generated assuming constant oxygen tension in the blood vessels. However, as red blood cells progress through the vessels, oxygen is continuously released into the plasma and the surrounding tissue, resulting in longitudinally varying oxygen levels in the blood vessels. In the present study, the authors investigated whether a tumor oxygenation model that incorporated longitudinally varying oxygen levels would provide different predictions of necrotic fractions and radiosensitivity compared to commonly used models with a constant oxygen pressure. Methods: Our models simulated oxygen diffusion based on a Green's function approach and oxygen consumption according to the Michaelis-Menten equation. The authors constructed tumor models with different vascular fractions (VFs), from which they generated depth oxygenation curves and a look-up table of oxygen pressure gradients. The authors evaluated models of spherical tumors of various sizes, from 1 to 10{sup 4} mg. The authors compared the results from a model with constant vessel oxygen (CVO) pressure to those from models with longitudinal variations in oxygen saturation and either a constant VF (CVF) or variable VF (VVF) within the tumor tissue. The authors monitored the necrotic fractions, defined as tumor regions with an oxygen pressure below 1 mmHg. Tumor radiation sensitivity was expressed as D{sub 99,} the homogeneous radiation dose required for a tumor control probability of 0.99. Results: In the CVO saturation model, no necrosis was observed, and decreasing the VF could only decrease the D{sub 99} by up to 10%. Furthermore, the D{sub 99} vs VF dependence was similar for different tumor masses. Compared to the CVO model, the extended CVF and VVF models provided clearly different results, including pronounced effects of VF and tumor size on the necrotic fraction and D{sub 99}, necrotic fractions ranging from 0% to 97%, and a maximal D{sub 99} increment of 57%. Only minor differences were observed between different vessel architectures, i.e., CVF vs VVF. In the smallest tumor with a low necrotic fraction, the D{sub 99} strictly decreased with increasing blood velocity. Increasing blood velocity also decreased the necrotic fraction in all tumor sizes. VF had the most profound influence on both the necrotic fraction and on D{sub 99}. Conclusions: Our present analysis of necrotic formation and the impact of tumor oxygenation on D{sub 99} demonstrated the importance of including longitudinal variations in vessel oxygen content in tumor models. For small tumors, radiosensitivity was particularly dependent on VF and slightly dependent on the blood velocity and vessel arrangement. These dependences decreased with increasing tumor size, because the necrotic fraction also increased, thereby decreasing the number of viable tumor cells that required sterilization. The authors anticipate that the present model will be useful for estimating tumor oxygenation and radiation response in future detailed studies.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Orthoimagery and Shapefiles Documenting Pre- and Post-August 2019 Slope Disturbances, Teller Road Site, Seward Peninsula, Alaska, 2018-2019

This dataset was derived from UAS aerial photos and dGPS data collected at the Teller mile marker 47 site in 2018 and 2019 and used to support research quantifying the timing and rate of surface movements and analyze soil transport process in Arctic landscapes. In July 2018, a Phantom uncrewed aerial system (UAS) collected >6800 high resolution aerial photos of the lower portion of the Teller 47 watershed (see for raw photos; pending archive NGA281). During the UAS survey, 25 x 25 cm tile ground control points (GCPs) were laid out and secured with one rebar rod in the center. The four corners and rebar tops were surveyed with differential GPS, and these coordinates were used to construct and validate an orthomosaic of the site. These points were resurveyed in August 2019 and used to track annual movement. Changes in position between the two surveys are reported in (Lathrop et al. 2022; NGA254). Agisoft Metashape photogrammetry software was used to construct a georeferenced orthomosaic image (*.tif file) of a portion (0.68 km2) of the watershed with a final resolution of ~1 cm. Manual delineation of the perimeters of failures visible in the UAS imagery (*.tif files) was conducted to create shapefile polygons (two *.zip files). The failures were identified by the exposure of bare mineral soils, which were made visible by disruption of the overlying tundra vegetation. The shapefiles were then used to analyse the topographic distribution and sizes of the failures. In August 2019 an additional ~300 georeferenced UAS images of slope instability features were collected (data pending submission) and compared with the 2018 orthomosaic. Overview maps of the failure locations included as a *.pdf.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

The structure of graphene on graphene/C60/Cu interfaces: a molecular dynamics study

Two experimental studies reported the spontaneous formation of amorphous and crystalline structures of C 60 molecules intercalated between graphene and a surface. The findings observed included interesting phenomena ranging from reaction between fullerene C60s ('C 60 s' stands for plural of C 60 ) under graphene to graphene sheets sagging between C 60 s and control of strain in these sheets. Motivated by this work, we performed fully atomistic reactive molecular dynamics simulations to investigate the formation and thermal stability of graphene sheet wrinkles as well as graphene attachment to and detachment from a surface when the sheet is laid over a previously distributed array of C 60 molecules on a copper surface at different temperatures. As graphene compresses the C 60 s against the surface, and graphene attachment to the surface in between C 60 s depends on the height of the wrinkles in the graphene sheet, configurations with both frozen and non-frozen fullerenes were investigated in the simulations in order to examine the experimental result of stable, sagged graphene sheets when the distance between C 60 s is about 4 nm and the height of the wrinkles in the sheet is about 0.8 nm. Below a distance of 4 nm between fullerenes, the graphene is predicted to become locally suspended and less strained. The simulations predict that this happens when the fullerenes can deform under the compressive action of the graphene sheet. If the fullerenes are kept frozen, spontaneous 'blanketing' of graphene is predicted only when the distance between neighbouring C 60 s is equal to or great than about 7 nm. These predictions agree with a mechanical model relating the rigidity of a graphene sheet to the energy of graphene-surface adhesion. This work further reveals the structure of intercalated molecules and the role of stability and sheet wrinkling on the preferred configuration of graphene. This study thus might assist in the development of two-dimensional confined nanoreactors for chemical reactions.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2011

QCD Structure of Nuclear Interactions

This dissertation investigated selected processes involving baryons and nuclei in hard scattering reactions. Through these processes, this work explored the constituent structure of baryons and the mechanisms through which the interactions between these constituents ultimately control the selected reactions. First, hard nucleon-nucleon elastic scattering was studied considering the quark exchange (QE) between the nucleons to be the dominant mechanism of interaction in the constituent picture. It was found that an angular asymmetry exhibited by proton-neutron (pn) elastic scattering data is explained within this framework if a quark-diquark picture dominates the nucleon's structure instead of a more traditional SU(6) model. The latter yields an asymmetry around 90 deg center of mass scattering with a sign opposite to what is experimentally observed. The second process is the hard breakup by a photon of a nucleon-nucleon system in light nuclei. Proton-proton (pp) and pn breakup in 3 He, and double Δ-isobars production in deuteron breakup were analyzed in the hard rescattering model (HRM), which in conjunction with the QE mechanism provides a QCD description of the reaction. Cross sections for both channels in 3 He photodisintegration were computed without the need of a fitting parameter. The results presented here for pp breakup show excellent agreement with recent experimental data. In double Δ-isobars production in deuteron breakup, HRM angular distributions for the two double Δ channels were compared to the pn channel and to each other. An important prediction from this study is that the Δ ++ Δ - channel consistently dominates Δ + Δ 0 , which is in contrast with models that unlike the HRM consider a double Δ system in the initial state of the interaction. For such models both channels should have the same strength.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Modeling pair distribution functions of rare-earth phosphate glasses using principal component analysis

The use of principal component analysis (PCA) to statistically infer features of local structure from experimental pair distribution function (PDF) data is assessed on a case study of rare-earth phosphate glasses (REPGs). Such glasses, co-doped with two rare-earth ions (R and R’) of different sizes and optical properties, are of interest to the laser industry. The determination of structure-property relationships in these materials is an important aspect of their technological development. Yet, realizing the local structure of co-doped REPGs presents significant challenges relative to their singly-doped counterparts; specifically, R and R’ are difficult to distinguish in terms of establishing relative material compositions, identifying atomic pairwise correlation profiles in a PDF that are associated with each ion, and resolving peak overlap of such profiles in PDFs. This study demonstrates that PCA can be employed to help overcome these structural complications, by statistically inferring trends in PDFs that exist for a restricted set of experimental data on REPGs, and using these as training data to predict material compositions and PDF profiles in unknown co-doped REPGs. The application of these PCA methods to resolve individual atomic pairwise correlations in t(r) signatures is also presented. The training methods developed for these structural predictions are pre-validated by testing their ability to reproduce known physical phenomena, such as the lanthanide contraction, on PDF signatures of the structurally simpler singly-doped REPGs. The intrinsic limitations of applying PCA to analyze PDFs relative to the quality control of source data, data processing, and sample definition, are also considered. Furthermore, while this case study is limited to lanthanide-doped REPGs, this type of statistical inference may easily be extended to other inorganic solid-state materials, and be exploited in large-scale data-mining efforts that probe many t(r) functions.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Challenges to Evaluating Ecological Risks in Performance Assessments - 18424

Performance assessments (PAs), whether probabilistic or deterministic, have largely focused on evaluating human health effects of radionuclides. In the past, it was asserted that protecting human health would automatically protect the environment. This blanket assertion has been questioned, so tools and methodologies to directly estimate non-human biota dose have been developed and made available since the early 2000's. For example, the Biota Dose Assessment Committee (BDAC) guidance led to the development of the RESRAD-BIOTA (RESRAD stands for Residual Radioactive materials) software to implement this guidance. The BDAC was a US Department of Energy (DOE) led working group with members from academia and consultancies in addition to DOE technical staff. Parallel efforts have been in place in Europe with the development of the ERICA tool (Environmental Risk from Ionising Contaminants: Assessment and Management). More recently, interpretation of the requirements of US Department of Energy (DOE) Order O458.1 have led some waste management facilities to include ecological risks in addition to human health effects in their PAs. We have recently developed methodologies to assess ecological risks within probabilistic PAs (PPAs) for two Federal facilities. One of the challenges in applying the non-human biota assessment models to PPAs is that ecological risk assessments following US Environmental Protection Agency (EPA) or DOE guidance start with protective screening assessments before moving into more site-specific ecological risk assessments. Conservative assumptions bias the screening assessments and greatly overestimate the risks posed by contaminants. However, although the screens are biased they can be useful in ruling out model spatial domain areas or types of biota from requiring further assessment. In some cases, the results of the screen could entirely rule out ecological risks from further assessment. For a more refined and unbiased estimate of dose to non-human biota, one would typically conduct site-specific studies to better define exposure through the food web or adverse effects based on eco-toxicity studies of environmental, and generally weathered, contaminant mixtures. However, for PPAs that consider future site conditions after the loss of institutional control, such site-specific studies are not possible. Rather, site-specific future ecological risk models use probabilistic inputs that result in a distribution of population doses or exposures and calculate the distribution of possible adverse effects to ecological populations. This approach considers both radionuclide and chemical inventory. For both Federal facilities, the model spatial domains include riparian and aquatic environments located downstream of the waste management site. These riparian and aquatic environments represent linear exposure elements for some wildlife populations and require special consideration of exposures to individuals and to populations along such spatial domains. At a minimum, wildlife foraging should be focused along the axis of such water bodies. Another challenge is how to incorporate ecologically relevant spatial scales into models that have contaminant transport as the primary focus. Riparian and aquatic environments also have threatened and endangered (T and E) species, which necessitate greater levels of protection given their rarity. A final challenge for conducting ecological risk assessments is how to evaluate T and E species in the future. This might be addressed by evaluating potential for impacts on individuals of feeding guilds with species that are currently threatened or endangered. We also have to consider how ecological populations might change as a result of climate change. It is a more difficult problem to predict what species might become rare in the future, and how to best assess future populations of threatened or endangered species. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗