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At least 811 records · Page 45

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DOE OSTI2023

Developing Methods to Assess Changes in Mechanical Properties of Shale Modified by Engineered Mineral Precipitation

Fractures in subsurface shale formations serve multiple purposes, for example, in the recovery of resources in hydraulic fracturing or as potential harmful leakage passages through caprocks that may contribute undesired fluids to the atmosphere or functional groundwater aquifers. A proposed method to seal or influence fracture properties is Ureolysis-Induced Calcium Carbonate Precipitation (UICP), a bio-mineralization technology driven by the enzymatic hydrolysis of urea, resulting in the formation of calcium carbonate. The resulting calcium carbonate can bridge the gaps in fractured shale and reduce fluid flow through fractures. This study represents the first step toward determining the influence of UICP treatment on shale material and its subsequent mechanical strength properties. The goal of this preliminary work is twofold: first, we aim to identify a method to test tensile strength along a core axis and second, we seek to assess the effect of temperature on the tensile strength of intact, unfractured shale cores (2.54 cm (1 in) diameter, 5.08 cm (2 in) long for comparison with future fractured and UICP-treated cores. A modified Brazilian indirect tensile strength test successfully measured splitting tensile strength of shale cores from Eagle Ford and Wolfcamp formations at room temperature and 60°C.

clastic rock↗

DOE OSTI2025

Atoms-to-devices models for post-irradiation annealing kinetics in III-V semiconductors

Understanding atomic displacement damage and propagating this understanding into validated defect-aware radiation damage models is a critical step toward achieving predictive, atoms-to-systems assessment of radiation vulnerabilities of microelectronics. These models are essential for evaluating the performance and reliability of nuclear stockpile components or space-based electronics (satellites). The goal of this project was to bridge a fundamental science gap between defect spectroscopies and atomistic modeling of radiation-induced defects on the one hand, and simulations of device response on the other hand, to develop predictive defect-aware damage models for high-fidelity device simulations of radiation-damaged III-V semiconductors.

36 MATERIALS SCIENCE↗

NASA NTRS2019

Myco-Architecture off Planet: Growing Surface Structures at Destination

Our work focused on filling major select key technical knowledge gaps, and technical aspects to be addressed in a Phase II proposal were identified such as the secretion of glues or plastics by the fungi or bacteria to form biocomposites. Specifically, we raised the technical TRL by assessing the growth of in-house mycelial-producing strains on potential food substrates and analyzed the advantages and disadvantages to their use off planet. Growth of the mycelia on sawdust and powdered nutrients including dried, powdered algae, was used as a baseline. We measured growth as a function of temperature, tested the relevant material properties of the mycelia products produced, and measured the mass of input and output volume for production per volume of material. Mycotecture was produced in a bag simulating the proposed mission implementation. Post-production such as heat treatment (as is done with terrestrial mycotecture)was assessed.The material properties of the dried, frozen and baked mycelial outputs included density, strength,thermal insulation and flame retardation. Tensile/compression testing on biocomposite material specimens was performed to obtain three-dimensional elastic constants, as well as to examine deformation and fracture behavior. These mechanical tests were performed on both dormant and activated samples to understand the evolution of the structural material. In addition, experimental data obtained from the mechanical testing was used to build a failure prediction model that accounts for material anisotropy. This aided in future structural design through a quantitative understanding of the mechanical limits of the material. To examine the texture, defects, fracture surfaces of the material, high-resolution microstructural imaging was utilized before and after the mechanical tests. This microstructural analysis informed us about the macro-structural behavior and influenced structural design. Thermal decomposition analysis was also performed tounderstand the thermal limits.

Biocomposites↗

NASA NTRS2019

Assessing the Use of SAR/Optical Data Fusion and TensorFlow for Improved Mangrove Mapping

Mangrove forests are found in intertidal zones of tropical regions around the world and provide important ecological and economic benefits – they are considered carbon sequesters, habitats for flora and fauna, and natural barriers to hurricanes and tsunamis. Wood from mangrove forests are used as fuel and building materials in surrounding coastal communities, therefore promoting local livelihoods. Despite the importance of these ecosystems, mangrove forests have historically been degraded in natural processes such as severe weather, and anthropogenic factors like conversion to agriculture and aquaculture. This study assesses change in mangrove forests in Nigeria and Mozambique from 2015 to 2018 using SAR and optical data fusion. Due to frequent cloud cover over the study area, SAR and optical data is fused to obtain gap-free imagery without clouds. Landsat-8 OLI and Sentinel-1 imagery is fused with TensorFlow, an open source platform used in developing machine learning models. The resulting images are classified to discriminate mangrove forest cover from other land cover types, and change is estimated using image differencing. Understanding the rates and magnitude of mangrove change across space and time can aid in identifying priority areas for forest regeneration, and can help construct sustainable management practices for the future.

Strattman, Katherine↗

NASA NTRSDate not supplied

Development and Initial Validation of HFBP-EM Short-Form Surveys

The Human Factors and Behavioral Performance Exploration Measures (HFBP-EM) suite includes self-report surveys designed to assess Behavioral Medicine (BMed) and Team risks for future exploration class missions. Survey data was collected during the Human Exploration Research Analog (HERA) Campaign 4 (C4), HERA Campaign 5 (C5), and during SIRIUS19 missions in the Russian Ground Based Experiment Complex, NEK. Crew time in spaceflight analogs and in spaceflight is typically limited. Extensive self-report surveys can be a significant burden to participants and are not operationally acceptable for spaceflight. The purpose of this project was to comprehensively assess the reliability and validity of the standard-length HFBP-EM surveys, identify acceptable short forms to administer during HERA C6, examine initial validation evidence for the proposed short form measures, and identify key measurement gaps in HFBP-EM coverage. In this presentation, we will report reliability and validity metrics of standard form data, describe the proposed new short forms, and present initial psychometric analyses supporting the use of these short forms.

S T Bell↗

NASA NTRSDate not supplied

Advancing Satellite-Constrained Modeled Air-Sea CO 2 Fluxes With a Focus on the Strength of the Southern Ocean Carbon Sink

Challenge and Motivation: The ocean plays a critical role in mitigating climate change by removing approximately a quarter of annual anthropogenic CO 2 emissions from the atmosphere. Model-based estimates point to the Southern Ocean as a key marine region, responsible for approximately 40 % of the anthropogenic carbon uptake by the global ocean. However, the contemporary strength of the Southern Ocean carbon sink has recently come into question. On the one hand, airborne-based observations of atmospheric CO 2 gradients indicate that the Southern Ocean represents a strong net sink of atmospheric CO 2 , consistent in magnitude with atmospheric inversion estimates and surface-ocean partial pressure of CO 2 (pCO 2 )-based products. On the other hand, estimates of pCO 2 based on in situ pH measurements taken by biogeochemical profiling floats yield strong wintertime outgassing fluxes that greatly reduce the Southern Ocean’s annually integrated CO 2 uptake. This uncertainty in the strength of the Southern Ocean air-sea CO 2 flux and its role in the global carbon cycle hinders our ability to constrain global carbon fluxes, one of the major goals of NASA’s Carbon Monitoring System (CMS). Opportunity: The NASA Ocean Biogeochemical Model (NOBM) produces near-global pCO 2 and air-sea CO 2 flux estimates that are currently included into the NASA’s Goddard Earth Observing System (GEOS) models in support of the CMS effort to monitor global carbon fluxes. The NOBM assimilates ocean color data to improve the representation of biogeochemical fluxes and overcome spatial and temporal gaps in the space-based retrievals. Here, we propose to advance the satellite-constrained flux estimates by investigating the uncertainties in the Southern Ocean air-sea CO 2 flux produced by the NOBM, and assess the value that remote sensing ocean color data can have in providing improved estimates of carbon fluxes in the ocean. Our proposed work includes the delivery of refined in situ float-based carbon fluxes to serve as a constraint on the model-based estimates. Taking advantage of the model’s integration of satellite ocean color data to represent multiple phytoplankton groups, we propose to deliver maps of biogenic carbon export specific to each modeled phytoplankton type and investigate the role of ecological plankton complexity in regulating marine carbon uptake and export. Goals: (a) Delivery of seasonally-adjusted float-based Southern Ocean air-sea CO 2 fluxes: We will produce updated and improved float-based air-sea CO 2 fluxes that will serve as a bias-reduced float-based constraint to evaluate our model-based estimates of the NOBM. (b) Investigation of uncertainties in Southern Ocean air-sea CO 2 flux from the NOBM: Modeled air-sea carbon fluxes will be evaluated against the updated float product as well as ship- and airborne-based data to identify uncertainties and potential model deficiencies. (c) Delivery of model-based carbon export partitioning by phytoplankton functional types (PFTs): We will produce depth-resolved maps of particulate organic export production integrated for all phytoplankton groups and allocated to each individual PFT in the model. The expected significance of this goal is to quantify the role that the functional-oriented diversity in phytoplankton groups represented in the NOBM plays in regulating air-sea CO 2 fluxes in the Southern Ocean.

Lionel A. Arteaga↗

DOE OSTI2022

Instrumentation for Assessing DC Electrical Distribution Systems in Buildings

Direct current (DC) distribution systems is emerging as a favorable option over alternating current in buildings due to its energy and non-energy benefits (e.g., efficiency, resilience, safety). However, limited guidelines exist to evaluate the DC electrical distribution infrastructure. This paper aims to fill that gap by detailing our experience with metering a building-level electrical DC distribution system. Our case study is a DC microgrid at the Direct Energy Partners Research & Development facility located in Charlotte, North Carolina. This paper presents our approach, technical challenges, and lessons learned with DC metering and instrumentation.

buildings↗

DOE OSTI2020

Assessment of the Dominican Republic’s Commercial and Industrial Scale Energy Efficiency Sector

In this paper the National Renewable Energy Laboratory (NREL) explores the commercial and industrial (C&I) energy efficiency market in the Dominican Republic, including the market’s current status. During NREL’s engagement with its Dominican counterparts, NREL noted market gaps, identified by both public and private sector market actors, that became the focus of this report. The intent is two-fold. First, to assist potential customers, project financing institutions, and various government agencies understand where the energy efficiency sector stands, in August 2020. Second to help them recognize the scope, scale, and opportunity for energy savings from untapped potential large reductions in energy expenditures. This research identified how savings could be captured through improvements to the enabling environment, technical capacity, and level of activity in the sector. Moreover, it determined that through taking action to catalyze energy efficiency investment, the government could make significant progress towards its self-declared NDC goals, and result in tens of millions of dollars in savings across the Dominican economy for both the private and public sectors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS2020

Building a landslide hazard indicator with machine learning and land surface models

The U.S. Pacific Northwest has a history of frequent and occasionally deadly landslides caused by various factors. Using a multivariate, machine-learning approach, we combined a Pacific Northwest Landslide Inventory with a 36-year gridded hydrologic dataset from the National Climate Assessment – Land Data Assimilation System to produce a landslide hazard indicator (LHI) on a daily 0.125-degree grid. The LHI identified where and when landslides were most probable over the years 1979–2016, addressing issues of bias and completeness that muddy the analysis of multi-decadal landslide inventories. The seasonal cycle was strong along the west coast, with a peak in the winter, but weaker east of the Cascade Range. This lagging indicator can fill gaps in the observational record to identify the seasonality of landslides over a large spatiotemporal domain and show how landslide hazard has responded to a changing climate.

XGBoost↗

DOE OSTI2020

Population genomics and history of speciation reveal fishery management gaps in two related redfish species ( Sebastes mentella and Sebastes fasciatus )

Abstract Understanding the processes shaping population structure and reproductive isolation of marine organisms can improve their management and conservation. Using genomic markers combined with estimation of individual ancestries, assignment tests, spatial ecology, and demographic modeling, we (i) characterized the contemporary population structure, (ii) assessed the influence of space, fishing depth, and sampling years on contemporary distribution, and (iii) reconstructed the speciation history of two cryptic redfish species, Sebastes mentella and S. fasciatus . We genotyped 860 individuals in the Northwest Atlantic Ocean using 24,603 filtered single nucleotide polymorphisms (SNPs). Our results confirmed the clear genetic distinctiveness of the two species and identified three ecotypes within S. mentella and five populations in S. fasciatus . Multivariate analyses highlighted the influence of spatial distribution and depth on the overall genomic variation, while demographic modeling revealed that secondary contact models best explained inter‐ and intragenomic divergence. These species, ecotypes, and populations can be considered as a rare and wide continuum of genomic divergence in the marine environment. This acquired knowledge pertaining to the evolutionary processes driving population divergence and reproductive isolation will help optimizing the assessment of demographic units and possibly to refine fishery management units.

Benestan, Laura M.↗

DOE OSTI2025

Myco-CORPSE simulations assessing mycorrhizal carbon allocation across U.S. forests and global change scenarios

Plants allocate a substantial portion of their fixed carbon belowground to mycorrhizal fungi in exchange for nutrients and other benefits. However, most current ecosystem models omit mycorrhizal processes, limiting our ability to predict plant–soil carbon dynamics under environmental change. To address this gap, we used a mycorrhiza-explicit soil biogeochemical model, Myco-CORPSE (Mycorrhizal Carbon, Organisms, Rhizosphere, and Protection in the Soil Environment), to simulate tree carbon allocation to arbuscular mycorrhizal (AM) and ectomycorrhizal (ECM) fungi in temperate forests.The dataset includes outputs from two sets of model simulations:1. Perturbation experiments: Simulations across gradients of ECM dominance (0–100%), nitrogen deposition, soil temperature, and net primary productivity (NPP) to test how these factors affect mycorrhizal C allocation and nutrient cycling.2. FIA-based simulations: Model applications to over 1,800 U.S. forest sites using site-specific data from the U.S. Forest Inventory and Analysis (FIA) program, including vegetation composition, mycorrhizal type, climate, litter traits, soil properties, and N deposition.Model outputs include simulated mycorrhizal carbon allocation and related biogeochemical variables, such as soil and microbial carbon and nitrogen stocks. Data are provided in CSV format and organized by experiment type (in separate ZIP files). Python scripts for running simulations, plotting, and spatial mapping are also included and organized similarly. No proprietary software is required. These outputs support a peer-reviewed study and were used to generate figures and tables in the associated publication.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Regulatory utility of physiologically based pharmacokinetic modeling for assessing food impact in bioequivalence studies: A workshop summary report

This workshop report summarizes the presentations and panel discussion related to the use of physiologically based pharmacokinetic (PBPK) modeling approaches for food effect assessment, collected from Session 2 of Day 2 of the workshop titled “Regulatory Utility of Mechanistic Modeling to Support Alternative Bioequivalence Approaches.” The US Food and Drug Administration in collaboration with the Center for Research on Complex Generics organized this workshop where this particular session titled “Oral PBPK for Evaluating the Impact of Food on BE” presented successful cases of PBPK modeling approaches for food effect assessment. Recently, PBPK modeling has started to gain popularity among academia, industries, and regulatory agencies for its potential utility during bioavailability (BA) and/or bioequivalence (BE) studies of new and generic drug products to assess the impact of food on BA/BE. Considering the promises of PBPK modeling in generic drug development, the aim of this workshop session was to facilitate knowledge sharing among academia, industries, and regulatory agencies to understand the knowledge gap and guide the path forward. This report collects and summarizes the information presented and discussed during this session to disseminate the information into a broader audience for further advancement in this area.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Estimation of sensor measurement errors in reactor coolant systems using multi-sensor fusion

A nuclear power plant is typically instrumented with a variety of sensors to continually monitor its variables, and their sensor’s measurements may be used to assess the plant state and initiate safety actions, if needed. Errors in sensor measurements, due to factors such as calibration drifts, critically affect such state assessments. Here, we address a problem of estimating sensor errors using physics-informed machine learning methods that use measurements collected under known plant conditions. For a given sensor, we propose an information fusion method that uses measurements from other sensors to estimate its output assuming it is error-free and provides its difference from an actual measurement as an error estimate. We present the ensemble of trees and support vector machine fusers, and evaluate their performance using measurements collected over an emulated test loop of a pressurized water reactor. The plant variables are related to each other through the underlying physical laws under inertial constraints that place bounds on their derivatives, which analytically justify the applicability of machine learning methods for computing these fusers. Under twenty scenarios, we assess their sensor error estimates for pressure sensors of the heat exchanger of a reactor’s primary coolant system. Multiple types of errors are captured by both fusers under externally induced calibration drifts, blockages, minor leaks and air gaps in sensing lines, and electromagnetic interference; the root mean square error of the estimation of error is under 2.2% percent of the maximum measurement. We present generalization equations, in the framework of statistical learning theory, for these methods that characterize the confidence probability that the estimation error is bounded by a specified parameter in future test scenarios.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2025

Descriptor: High Temporal Resolution Meteorological Data at Oak Ridge Reservation (ORR-HiResMet)

Access to continuous, quality assessed meteorological data is critical for understanding the climatology and atmospheric dynamics of a region. Research facilities like Oak Ridge National Laboratory (ORNL) rely on such data to assess site-specific climatology, model potential emissions, establish safety baselines, and prepare for emergency scenarios. To meet these needs, on-site towers at ORNL collect meteorological data at 15-minute and hourly intervals. However, data measurements from meteorological towers are affected by sensor sensitivity, degradation, lightning strikes, power fluctuations, glitching, and sensor failures, all of which can affect data quality. To address these challenges, we conducted a comprehensive quality assessment and processing of five years of meteorological data collected from ORNL at 15-minute intervals, including measurements of temperature, pressure, humidity, wind, and solar radiation. The time series of each variable was pre-processed and gap-filled using established meteorological data collection and cleaning techniques, i.e., the time series were subjected to structural standardization, data integrity testing, automated and manual outlier detection, and gap-filling. The data product and highly generalizable processing workflow developed in Python Jupyter notebooks are publicly accessible online. As a key contribution of this study, the evaluated 5-year data will be used to train atmospheric dispersion models that simulate dispersion dynamics across the complex ridge-and-valley topography of the Oak Ridge Reservation in East Tennessee.

Steckler, Morgan R. [Oak Ridge National Laboratory↗

DOE OSTI2025

Physical and Hydraulic Properties of RCRA Borehole Samples from the Hanford Site : Final Report, Fiscal Years 2023-2024

Sediment from 44 core samples collected from Resource Conservation and Recovery Act (RCRA) boreholes drilled in the 200 East and 200 West areas of the Hanford Site were characterized for physical and hydraulic properties (Table S.1). Characterization data included gravimetric water contents and matric potentials, grain-size distributions, saturated hydraulic conductivity, water retention characteristics, and unsaturated hydraulic conductivity. These properties provide site-specific data and parameters that can be used in subsurface flow and contaminant transport models to assess the transport and fate of contaminants in the vadose zone and underlying aquifer systems. The analyzed core samples come from specific areas and depth intervals at the Hanford Site that were targeted for sampling to address data gaps identified by site contractors (Khaleel 2020). X-ray computed tomography (XCT) was used to evaluate the general textural characteristics of the samples and to determine which samples to use for further physical and hydraulic property characterization. Subsequent sample selection was determined by consensus after review of the XCT images by Pacific Northwest National Laboratory, Central Plateau Cleanup Company, and INTERA staff.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRSDate not supplied

Research Needs for Developing Qualification Standards for Flight Simulation Training Devices with Head Mounted Displays

This presentation discusses research needs to support evidence-based qualification standards for Flight Simulation Training Devices (FSTDs) with head mounted displays (HMDs). Currently, the FAA and EASA have no qualification standards specifically for FSTDs using HMDs and extended reality (XR) visuals, and existing qualification standards may not be sufficient. Special Conditions can be prescribed for the evaluation and qualification of individual devices, but these Special Conditions need to be assessed and adjusted on a case-by-case basis resulting in an elaborate process. Furthermore, test tolerances used in Special Conditions are often based on conventional visual systems and may not be adequate. This presentation first identifies gaps in the current knowledge of using HMDs in pilot training, and, more specifically, using HMDs in the training of manual aircraft control with motion cues. Next, research is proposed to help close these gaps, inform the development of qualification criteria and tolerances, and guide efforts to update regulations. The Vertical Motion Simulator (VMS) at NASA Ames Research Center, with its large motion capability, is currently undergoing significant upgrades including a state-of-the-art out-the-window visual system. In addition, an HMD capability will be introduced to use in conjunction with the conventional visual system. With its long history of setting standards in the simulation industry, the VMS is the ultimate tool to conduct research that could help accelerate the development of standards for the use of HMDs in FSTDs. The goal of the talk is ultimately to spark a discussion about the research needs and priorities to best serve the development of new qualification standards.

XR↗

NASA NTRS2026

Towards an improved understanding of the Antarctic coastal zone and its contribution to future global sea level

Understanding the coastal zone of the Antarctic Ice Sheet, where it interacts with the Southern Ocean and warmer air masses, is crucial for predicting Antarctica's influence on the global climate. This region has multiple tipping mechanisms that could trigger large, rapid, and potentially irreversible changes in the coming centuries. The Antarctic Ice Sheet remains the largest source of uncertainty in future sea-level projections. Insufficient knowledge of bed topography beneath the ice shelves and the coastal ice sheet is not yet well documented, but is a major source of this uncertainty. This review assesses current knowledge of the coastal zone and highlights methods to investigate it, including aerogeophysical surveys, ground- and ship-based measurements, satellite observations, and computer modeling. An ensemble analysis of published bed topography datasets identifies significant data gaps and their regional distribution, framed in the context of current ice-sheet behavior and potential instability. We propose scientific priorities and guidelines for future aerogeophysical surveys, advocating for a comprehensive, coordinated international effort to build a next-generation dataset of Antarctic bed properties. Such an initiative would significantly advance understanding of the role of coastal processes in ice-sheet dynamics, reducing uncertainties in sea-level rise projections and enhancing predictions of future ocean and climate changes.

Kenichi Matsuoka↗

NASA NTRS2013

Evidence of a Discontinuous Disk Structure Around the Herbig Ae Star HD 139614

The formation and evolution of a planetary system are intrinsically linked to the evolution of the primordial accretion disk and its dust and gas content. A new class of pre-main sequence objects has been recently identified as pre-transitional disks. They present near-infrared excess coupled to a flux deficit at about 10 microns and a rising mid-infrared and far-infrared spectrum. These features suggest a disk structure with inner and outer dust components, separated by a dust-depleted region (or gap). This could be the result of particular planet formation mechanisms that occur during the disk evolution. We here report on the first interferometric observations of the disk around the Herbig Ae star HD 139614. Its infrared spectrum suggests a flared disk, and presents pre-transitional features, namely a substantial near-infrared excess accompanied by a dip around 6 microns and a rising mid-infrared part. In this framework, we performed a study of the spectral energy distribution (SED) and the mid-infrared VLTI/MIDI interferometric data to constrain the spatial structure of the inner dust disk region and assess its possibly multi-component structure. We based our work on a temperature-gradient disk model that includes dust opacity.While we could not reproduce the SED and interferometric visibilities with a one-component disk, a better agreement was obtained with a two-component disk model composed of an optically thin inner disk extending from 0.22 to 2.3 AU, a gap, and an outer temperature-gradient disk starting at 5.6 AU. Therefore, our modeling favors an extended and optically thin inner dust component and in principle rules out the possibility that the near-infrared excess originates only from a spatially confined region. Moreover, the outer disk is characterized by a very steep temperature profile and a temperature higher than 300 K at its inner edge. This suggests the existence of a warm component corresponding to a scenario where the inner edge of the outer disk is directly illuminated by the central star. This is an expected consequence of the presence of a gap, thus indicative of a "pre-transitional" structure.

primordial accretion disk↗