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At least 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Self-Healing Cements with Improved Toughness at Casing and Formation Interfaces for Subsurface Applications (CRADA 530)

Over the three-year CRADA, Pacific Northwest National Laboratory (PNNL) advanced a new class of Molecular Velcro™ self-healing wellbore cements designed to improve the long-term integrity of wells used for geothermal energy production and carbon storage. Conventional wellbore cement can crack due to repeated mechanical loading, temperature swings, and exposure to aggressive subsurface fluids. Once cracks form, they can create leakage pathways, drive expensive remediation (“workovers”), and in extreme cases shorten well life. This project addressed that problem by developing polymer-modified cement systems that can autonomously re-seal cracks and better tolerate the extreme conditions experienced in subsurface wells, while remaining compatible with practical cementing operations.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Spectral solar irradiance on inclined surfaces: A fast Monte Carlo approach

Estimating spectral plane-of-array (POA) solar irradiance on inclined surfaces is an important step in the design and performance evaluation of both photovoltaic and concentrated solar plants. This work introduces a fast, line-by-line spectral, Monte Carlo (MC) radiative transfer model approach to simulate anisotropic distributions of shortwave radiation through the atmosphere as photon bundles impinge on inclined surfaces. This fast Monte Carlo approach reproduces the angular distribution of solar irradiance without the undesirable effects of spatial discretization and thus computes detailed POA irradiance values on surfaces at any orientation and also when surfaces are subjected to the anisotropic ground and atmospheric scattering. Polarization effects are also easily incorporated into this approach that can be considered as direct numerical simulation of the physics involved. Here, we compare our Monte Carlo radiative transfer model with the most widely used empirical transposition model, Perez4, under various conditions. The results show that the Perez4 model reproduces the more detailed Monte Carlo simulations with less than 10% deviation under clear skies for all relevant surface tilt and azimuth angles. When optically thin clouds are present, observed deviations are larger, especially when the receiving surface is strongly tilted. Deviations are also observed for large azimuth angle differences between the receiving surface and the solar position. When optically thick clouds are present, the two models agree within 15% deviation for nearly all surface orientation and tilt angles. The overall deviations are smaller when compared with cases for optically thin clouds. The Perez4 model performs very well (6.0% deviation) in comparison with the detailed MC simulations for all cases, thus validating its widespread use for practical solar applications. When detailed atmospheric profiles and cloud optical properties are available, the proposed fast Monte Carlo radiative model reproduces accurate spectral and angular POA irradiance levels for various atmospheric and cloud cover conditions, surface orientations, and different surface and ground properties.

42 ENGINEERING↗
NASA NTRS1998

Large-Scale Dynamics of the Magnetospheric Boundary: Comparisons between Global MHD Simulation Results and ISTP Observations

Understanding the large-scale dynamics of the magnetospheric boundary is an important step towards achieving the ISTP mission's broad objective of assessing the global transport of plasma and energy through the geospace environment. Our approach is based on three-dimensional global magnetohydrodynamic (MHD) simulations of the solar wind-magnetosphere- ionosphere system, and consists of using interplanetary magnetic field (IMF) and plasma parameters measured by solar wind monitors upstream of the bow shock as input to the simulations for predicting the large-scale dynamics of the magnetospheric boundary. The validity of these predictions is tested by comparing local data streams with time series measured by downstream spacecraft crossing the magnetospheric boundary. In this paper, we review results from several case studies which confirm that our MHD model reproduces very well the large-scale motion of the magnetospheric boundary. The first case illustrates the complexity of the magnetic field topology that can occur at the dayside magnetospheric boundary for periods of northward IMF with strong Bx and By components. The second comparison reviewed combines dynamic and topological aspects in an investigation of the evolution of the distant tail at 200 R(sub E) from the Earth.

Berchem, J.↗
DOE OSTI2020

Multiperspective Automotive Labeling

Supervised machine learning techniques inherently rely on datasets to be trained. With image datasets traditionally being annotated by humans, many advancements in image annotation tools have been made to ensure creation of rich datasets with accurate labels. Nevertheless, users still find it challenging to create and use their own datasets with labels that reflect their problem domain. We propose a streamlined labeling process that aligns multiperspective images and allows a transition from a labeled perspective to other perspectives. The main goal of this work is to reduce the human effort required for labeling vehicle images under favorable conditions where the image perspectives are correlated and one or more perspectives are known. A case study is described and analyzed to show the effectiveness of the process, as well as constraints and limitations when applied to other cases.

training dataset, multiperspective images, supervi↗
DOE OSTI2022

Uncertainty analysis for VERA problem 2 using the cell-code Condor v2.8.05

Condor is a cell-level neutronic calculation code that applies multi-group collision probabilities with heterogeneous response coupling method within generic geometry configurations. Under the Condor's code continuous development, the incorporation of up-to-date methodologies and state-of-the-art practices in reactor analysis represents a driving force. In this work, the capabilities of Condor v2.8.05 to develop an uncertainty analysis for realistic PWR-kind fuel assemblies are studied. The Total Monte Carlo approach is applied to quantify the impact of fabrication tolerances in the code's results for reactivity and power distributions, by means of randomly sampled input values using the VERA problem 2 as basis. The VERA problem 2 proposes a series of Westinghouse 2D 17 x 17-type fuel lattices, to be calculated reflected at beginning-of-life without Xe. The configurations correspond to a modern PWR. Selected neutronic parameters from Condor runs are thus analyzed in terms of the observed spread as well as the obtained distributions for the randomly perturbed cases, showing the capability of the code to handle the required input data, as well as its ability to provide valuable insights regarding uncertainty quantification.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2008

Improving Coastal Ocean Color Validation Capabilities through Application of Inherent Optical Properties (IOPs)

Understanding how the different components of seawater alter the path of incident sunlight through scattering and absorption is essential to using remotely sensed ocean color observations effectively. This is particularly apropos in coastal waters where the different optically significant components (phytoplankton, detrital material, inorganic minerals, etc.) vary widely in concentration, often independently from one another. Inherent Optical Properties (IOPs) form the link between these biogeochemical constituents and the Apparent Optical Properties (AOPs). understanding this interrelationship is at the heart of successfully carrying out inversions of satellite-measured radiance to biogeochemical properties. While sufficient covariation of seawater constituents in case I waters typically allows empirical algorithms connecting AOPs and biogeochemical parameters to behave well, these empirical algorithms normally do not hold for case I1 regimes (Carder et al. 2003). Validation in the context of ocean color remote sensing refers to in-situ measurements used to verify or characterize algorithm products or any assumption used as input to an algorithm. In this project, validation capabilities are considered those measurement capabilities, techniques, methods, models, etc. that allow effective validation. Enhancing current validation capabilities by incorporating state-of-the-art IOP measurements and optical models is the purpose of this work. Involved in this pursuit is improving core IOP measurement capabilities (spectral, angular, spatio-temporal resolutions), improving our understanding of the behavior of analytical AOP-IOP approximations in complex coastal waters, and improving the spatial and temporal resolution of biogeochemical data for validation by applying biogeochemical-IOP inversion models so that these parameters can be computed from real-time IOP sensors with high sampling rates. Research cruises supported by this project provides for collection and processing of seawater samples for biogeochemical (pigments, DOC and POC) and optical (CDOM and POM absorption coefficients) analyses to enhance our understanding of the linkages between in-water optical measurements (IOPs and AOPs) and biogeochemical constituents and to provide a more comprehensive suite of validation products.

Mannino, Antonio↗
DOE OSTI2020

Estimating rates and patterns of diversification with incomplete sampling: a case study in the rosids

Premise Recent advances in generating large‐scale phylogenies enable broad‐scale estimation of species diversification. These now common approaches typically are characterized by (1) incomplete species coverage without explicit sampling methodologies and/or (2) sparse backbone representation, and usually rely on presumed phylogenetic placements to account for species without molecular data. We used empirical examples to examine the effects of incomplete sampling on diversification estimation and provide constructive suggestions to ecologists and evolutionary biologists based on those results. Methods We used a supermatrix for rosids and one well‐sampled subclade (Cucurbitaceae) as empirical case studies. We compared results using these large phylogenies with those based on a previously inferred, smaller supermatrix and on a synthetic tree resource with complete taxonomic coverage. Finally, we simulated random and representative taxon sampling and explored the impact of sampling on three commonly used methods, both parametric (RPANDA and BAMM) and semiparametric (DR). Results We found that the impact of sampling on diversification estimates was idiosyncratic and often strong. Compared to full empirical sampling, representative and random sampling schemes either depressed or inflated speciation rates, depending on methods and sampling schemes. No method was entirely robust to poor sampling, but BAMM was least sensitive to moderate levels of missing taxa. Conclusions We suggest caution against uncritical modeling of missing taxa using taxonomic data for poorly sampled trees and in the use of summary backbone trees and other data sets with high representative bias, and we stress the importance of explicit sampling methodologies in macroevolutionary studies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Tropospheric and stratospheric wildfire smoke profiling with lidar: mass, surface area, CCN, and INP retrieval

We present retrievals of tropospheric and stratospheric height profiles of particle mass, volume, surface area, and number concentrations in the case of wildfire smoke layers as well as estimates of smoke-related cloud condensation nuclei (CCN) and ice-nucleating particle (INP) concentrations from backscatter lidar measurements on the ground and in space. Conversion factors used to convert the optical measurements into microphysical properties play a central role in the data analysis, in addition to estimates of the smoke extinction-to-backscatter ratios required to obtain smoke extinction coefficients. The set of needed conversion parameters for wildfire smoke is derived from AERONET observations of major smoke events, e.g., in western Canada in August 2017, California in September 2020, and southeastern Australia in January–February 2020 as well as from AERONET long-term observations of smoke in the Amazon region, southern Africa, and Southeast Asia. The new smoke analysis scheme is applied to CALIPSO observations of tropospheric smoke plumes over the United States in September 2020 and to ground-based lidar observation in Punta Arenas, in southern Chile, in aged Australian smoke layers in the stratosphere in January 2020. These case studies show the potential of spaceborne and ground-based lidars to document large-scale and long-lasting wildfire smoke events in detail and thus to provide valuable information for climate, cloud, and air chemistry modeling efforts performed to investigate the role of wildfire smoke in the atmospheric system.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1985

Rotor-to-stator rub vibration in centrifugal compressor

One example of excessive vibration encountered during loading of a centrifugal compressor train (H type compressor with HP casing) is discussed. An investigation was made of the effects of the dynamic load on the bearing stiffness and the rotor-bearing system critical speed. The high vibration occurred at a "threshold load," but the machine didn't run smoothly due to rubs even when it had passed through the threshold load. The acquisition and discussion of the data taken in the field as well as a description of the case history which utilizes background information to identify the malfunction conditions is presented. The analysis shows that the failures, including full reverse precession rub and exact one half subharmonic vibration, were caused by the oversize bearings and displacement of the rotor center due to foundation deformation and misalignment between gear shafts, etc. The corrective actions taken to alleviate excessive vibration and the problems which remain to be solved are also presented.

Gao, J. J.↗
DOE OSTI2020

Benefits and risks of lead halide perovskite photovoltaics

Photovoltaics (PV) do not emit anything during operation, but, over their life-cycle, emissions are generated from the use of fossil-fuels in the extraction and production of materials and in the manufacturing and installation of PV components and systems. Nonetheless, these emissions are always very small compared to those from conventional combustion-based generators of electricity. The case for CO2 emissions has been well documented; over their lifetime, they range from 10 g CO2-eq / kWh for CdTe PV system installed in high-irradiation (2300 kWh/(m2-yr) locations to 80 g CO2-eq / kWh for Chinese single-crystalline silicon PV systems installed in low-irradiation (1000 kWh/(m2-yr) locations,1 compared to ~1000 g CO2-eq/kWh for electricity from coal. However, in the case of the rapidly emerging lead halide perovskite PV (LHP-PV) technology, concerns are raised regarding the potential of emissions of lead from the life-cycles of LHP-PV, including at their end of life. This warranted an evaluation of lead emissions from PV and comparisons with emissions in other power generation life-cycles.

Perovskites, PV, Lead, Risks↗
DOE OSTI2025

A flexible test facility for liquid xenon detector development

As liquid xenon time projection chambers scale to ever-larger sizes, so too do the engineering challenges they pose. Here, we describe a large, flexible, multipurpose test facility capable of supporting the development of a number of key aspects of liquid xenon detector systems. Example applications of this facility include characterization of large-area light and charge sensor arrays, tests of xenon purification techniques and materials compatibility, and investigations into high-voltage phenomena. This facility uses an automated and remotely monitored cryo-cooling system based on immersion of the test chamber in a liquid bath rather than conductive coupling, leading to advantages in temperature and pressure stability, as well as increasing required response times in the case of cooling-power loss. Design advantages, operational procedures, and performance of the facility are described, as well as five examples of liquid xenon test chambers that use the facility.

Dark Matter detectors↗
DOE OSTI2022

High CO2 Capture Rate Cost and Performance for F- and H-Class Natural Gas Combined Cycles (NGCC)

The National Energy Technology Laboratory (NETL) is updating its study titled “Cost and Performance Baselines for Fossil Energy Plants, Volume 1: Bituminous Coal and Natural Gas to Electricity.” Revision 4 was published in 2019. Pulverized coal (PC) and natural gas combined cycle (NGCC) cases with carbon capture in that study capture carbon dioxide (CO2) at 90% efficiency. Field-testing of post-combustion CO2 capture technology as well as vendor and industry feedback on projects currently in the planning stages (including FEED projects sponsored by DOE) indicate that capture rates as high as 95% are feasible for both coal- and natural gas-fueled electricity generating units. Technology suppliers (as reflected in vendor-supplied information provided to DOE for this study that included cost and performance estimates for both NGCC (97%) and PC (99%) study cases) as well as subject matter experts acknowledge and support that solvent-based post-combustion CO2 capture technologies are capable of achieving CO2 removal rates beyond 95% on low-purity streams representative of fossil-fueled combustion; however, the relatively limited experience with design and operation of capture systems that can routinely, reliably, and economically achieve very high removal rates (e.g., 97% for NGCC flue gas) requires further study. This presentation will address performance and cost estimates for 90%, 95%, and 97% capture for F- and H-class NGCC plants. This presentation was given at the 2022 Pittsburgh Coal Conference.

Fout, Timothy↗
DOE OSTI2026

The future of subsurface monitoring: AEC’s breakthroughs in CCS technology

Carbon capture and storage (CCS) has emerged as a key solution in the fight against climate change. However, for CCS to succeed, it is crucial to ensure that the sequestered CO2 stays safely trapped underground. The U.S. Department of Energy (DOE) has emphasized the need for advancements in subsurface monitoring, measurement, reporting, and verification. Aside from caprock integrity failure, the other primary failure points usually involve defective cement in the casing annulus of wellbores or plugged and abandoned wells. In addition, many energy producers (e.g., oil and gas, geothermal) and storage and disposal operators (e.g., H2 and water) must deal with the same issue. Poorly placed or degraded cement can create pathways for gas or fluid to escape from casing annuli and in plugged and abandoned or orphan wells, posing environmental risks. Yet, a reliable and cost-effective way to monitor cement and well integrity over multiple decades is still unavailable. Traditional geophysical methods like 4D seismic imaging and surface-based electromagnetic monitoring lack the resolution and accuracy for detecting these types of failures (Vasco et al., 2022; Fawad and Mondol, 2021). Wireline logging is expensive to run continuously and is obtrusive to the operation. While fiber optics can potentially be a solution, its bulkiness can significantly compromise the cement's integrity. To address these challenges, the Advanced Energy Consortium (AEC) at The University of Texas at Austin’s Bureau of Economic Geology (the Bureau) has been pioneering research in subsurface monitoring using its portfolio of distributed autonomous microfabricated sensors for harsh subsurface environments since 2008. A class of these microsensors [System on a Chip (SoC)] can be mixed in cement and permanently placed without compromising the cement column; the sensors would then communicate with each other or a data acquisition (DAQ) master node. Another class of the AEC microsensors can be fully autonomous, with rechargeable micro-batteries capable of exceeding 100°C, flash memory, and, currently, a pressure and temperature sensor. They are designed to circulate in mud, geothermal fluids, U-loops, or pipelines. They can log data into memory and are unobtrusive to operations. Our team has been working on a multi-year DOE-funded project (DE-FE0031856)—supported by $2.95M in federal funding and $0.75M in cost-matching from the AEC—to demonstrate SoC sensor utility for CO2 leakage monitoring in CCS applications. This multi-institutional collaboration developed a novel sensing architecture utilizing radiofrequency (RF) microsensors embedded within the cement sheath. These sensors detect CO2 migration and are interrogated via a Smart Casing Collar (SCC).

58 GEOSCIENCES↗
DOE OSTI2025

Developing a Prototype Methodology to Rank CO2-EOR Wells and Assess Their Reuse Potential for Geologic Carbon Sequestration

This study presents a prototype methodology for evaluating the reuse potential of Class II CO₂-enhanced oil recovery (CO₂-EOR) wells as Class VI wells for geologic carbon sequestration. The approach focuses on assessing wellbore construction materials—casing, cement, tubing, and packers—based on U.S. Environmental Protection Agency (EPA) Class VI well conversion guidelines. Utilizing Python scripts and JSON representations, the methodology automates checks on digitized Texas Railroad Commission (TRRC) data to rank wells based on regulatory and integrity criteria. Key factors include casing integrity, cementing techniques, tubing compatibility, and packer selection. Due to limitations in digitized data, manual verification is required for certain sections. Future enhancements include incorporating non-digitized data via web scraping and machine learning. This research provides a practical framework for well owners and regulators, supporting informed decision-making for sustainable CO₂ storage.

carbon sequestration↗
NASA NTRS1976

The Shaw chondrite. I - The case of the missing metal

The mineralogy as well as the elemental and isotopic composition of the Shaw meteorite indicate that it is a highly metamorphosed L-group chondrite which has lost a portion of its metal and sulfide. The metal which remains has an unusual composition relative to that in other L-group chondrites. It is enriched in Ga, Ge, Ir, Mo, Os, Pt, Re, and Ru but depleted in As, Au, Cu, and Sb. A comparison of the relative enrichments and depletions in Shaw with those observed in San Cristobal, the extreme end-member of group IAB iron meteorites, shows that the metal phases in these two meteorites have complementary compositions. This implies that the metal in Shaw represents the residual solid of a partial melting process while the missing metal, which drained away, may have gone to form an iron meteorite, like San Cristobal.

Rambaldi, E. R.↗
NASA NTRS2021

The Effects of Surface Fossil Magnetic Fields on Massive Star Evolution – III. the Case of τ Sco

τ Sco, a well-studied magnetic B-type star in the Upper Sco association, has a number of surprising characteristics. It rotates very slowly and shows nitrogen excess. Its surface magnetic field is much more complex than a purely dipolar configuration which is unusual for a magnetic massive star. We employ the CMFGEN radiative transfer code to determine the fundamental parameters and surface CNO and helium abundances. Then, we employ MESA and GENEC stellar evolution models accounting for the effects of surface magnetic fields. To reconcile τ Sco’s properties with single-star models, an increase is necessary in the efficiency of rotational mixing by a factor of 3–10 and in the efficiency of magnetic braking by a factor of 10. The spin-down could be explained by assuming a magnetic field decay scenario. However, the simultaneous chemical enrichment challenges the single-star scenario. Previous works indeed suggested a stellar merger origin for τ Sco. However, the merger scenario also faces similar challenges as our magnetic single-star models to explain τ Sco’s simultaneous slow rotation and nitrogen excess. In conclusion, the single-star channel seems less likely and versatile to explain these discrepancies, while the merger scenario and other potential binary-evolution channels still require further assessment as to whether they may self-consistently explain the observables of τ Sco.

stars: evolution↗
NASA NTRS2007

Multispacecraft Observations of Solar Flare Particles in the Inner Heliosphere

For a number of impulsive solar particle events we examine variations of maximum intensities and times to maximum intensity as a function of longitude, using observations from the two Helios spacecraft and near the Earth. We find that electrons in the MeV range can be detected more than 80 deg. from the flare longitude, corresponding to a considerably wider "well connected" region than that (approx. 20 deg. half width) reported for He-3-rich impulsive solar events. This wide range and the decrease of peak intensities with increasing connection angle revive the concept of some propagation process in the low corona that has a diffusive nature. Delays to the intensity maximum are not systematically correlated with connection angles. We argue that interplanetary scattering parallel to the average interplanetary magnetic field, that varies with position in space, plays an important role in flare particle events. In a specific case variations of the time profiles with radial distance and with particle rigidity are used to quantitatively confirm spatial diffusion. For a few cases near the edges of the well connected region the very long times to maximum intensity might result from interplanetary lateral transport.

Wibberenz, G.↗
NASA NTRSDate not supplied

Comparison between Computational and Experimental Wall-Shear Stress and Pressure Measurements in a Supersonic Wind Tunnel

We study the performance of two selected RANS models (SST-$k$-$\omega$ and Baldwin-Lomax) to simulate the mean wall-shear and pressure data obtained from a distributed-roughness-related experimental campaign conducted at Ahmic Aerospace, LLC, located in Ohio, US. A structured compressible Navier-Stokes in-house solver, DPLR, is used to conduct the RANS simulations. As the final objective is to perform the studies under high-enthalpy flow conditions, such as inside the AHF facility at NASA-Ames Research Center (ARC), the current investigation focuses on the low-enthalpy cases using Ahmic's high-Reynolds-number supersonic wind tunnel as the initial step to simplify the flow physics. Furthermore, the wind tunnel simulations are conducted with perfectly-smooth walls to further simplify the problem and perform the initial testing of different solver-based RANS models. The Baldwin-Lomax model is observed to be more accurate than the SST model. However, when these RANS models and their roughness augmentation models are utilized to study their accuracy with respect to the experimental datasets, where the roughness effects are activated, both models perform well for a low roughness height case. However, as the roughness height increases, the SST model more accurately predicts the wall data (shear and pressure) than the Baldwin-Lomax model. Therefore, this present work has built a solid foundation for selecting the best RANS model to study the wall data under high-enthalpy flow conditions at the AHF facility soon.

Prakash Shrestha↗