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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
NASA NTRS2023

Real Options Analysis for Valuation of Climate Adaptation Pathways With Application to Transit Infrastructure

Climate change and sea level rise (SLR) are expected to increase the frequency and intensity of coastal flood events, posing risks to coastal communities and infrastructure. While regional climate adaptation investments can provide substantive flood protection, existing plans often neglect uncertainty in future climate conditions and adaptation performance, consequently neglecting the option value of flexibly implementing proposed projects. Addressing this gap, we develop and employ a generalizable real options analysis (ROA) valuation framework that considers how uncertainty in adaptation project costs, SLR, flood severity, and flood losses inform the full range of adaptation performance outcomes. We further propose and apply a novel, computationally efficient flood loss sampling algorithm to estimate the consequences of randomly arriving coastal flood events. We apply this ROA framework to assess the option value of flexibly timing adaptation investments over time, investigating an adaptation pathway proposed by the City of Boston from the perspective of the regional transit system manager. Our results suggest that flexible implementation can provide significant option value in the near-to mid-term(>30 years), with highest option values under low-probability, high consequence scenarios. Our results also suggest adaptation pathway performance in the latter half of the 21stcenturyis most sensitive to uncertainty in sea level rise, flood loss estimates, and flood frequency, underscoring the importance of uncertainty quantification in the long-term valuation of adaptation investments.

Michael V. Martello↗
DOE OSTI2024

Uncertainty quantification in multivariable regression for material property prediction with Bayesian neural networks

With the increased use of data-driven approaches and machine learning-based methods in material science, the importance of reliable uncertainty quantification (UQ) of the predicted variables for informed decision-making cannot be overstated. UQ in material property prediction poses unique challenges, including multi-scale and multi-physics nature of materials, intricate interactions between numerous factors, limited availability of large curated datasets, etc. In this work, we introduce a physics-informed Bayesian Neural Networks (BNNs) approach for UQ, which integrates knowledge from governing laws in materials to guide the models toward physically consistent predictions. To evaluate the approach, we present case studies for predicting the creep rupture life of steel alloys. Experimental validation with three datasets of creep tests demonstrates that this method produces point predictions and uncertainty estimations that are competitive or exceed the performance of conventional UQ methods such as Gaussian Process Regression. Additionally, we evaluate the suitability of employing UQ in an active learning scenario and report competitive performance. The most promising framework for creep life prediction is BNNs based on Markov Chain Monte Carlo approximation of the posterior distribution of network parameters, as it provided more reliable results in comparison to BNNs based on variational inference approximation or related NNs with probabilistic outputs.

36 MATERIALS SCIENCE↗
NASA NTRS2012

Real-time Accurate Surface Reconstruction Pipeline for Vision Guided Planetary Exploration Using Unmanned Ground and Aerial Vehicles

This report discusses work completed over the summer at the Jet Propulsion Laboratory (JPL), California Institute of Technology. A system is presented to guide ground or aerial unmanned robots using computer vision. The system performs accurate camera calibration, camera pose refinement and surface extraction from images collected by a camera mounted on the vehicle. The application motivating the research is planetary exploration and the vehicles are typically rovers or unmanned aerial vehicles. The information extracted from imagery is used primarily for navigation, as robot location is the same as the camera location and the surfaces represent the terrain that rovers traverse. The processed information must be very accurate and acquired very fast in order to be useful in practice. The main challenge being addressed by this project is to achieve high estimation accuracy and high computation speed simultaneously, a difficult task due to many technical reasons.

computer vision↗
DOE OSTI2024

Risk Considerations of Transitioning CO2-EOR Field to CO2 storage Field: Case Study

In the United States (U.S.), carbon dioxide (CO2) injection wells at EOR sites are currently regulated as Class II wells under the U.S. Environmental Protection Agency’s (EPA) Underground Injection Control (UIC) program while dedicated geological CO2 storage (GCS) wells are considered Class VI wells. A CO2-EOR facility considering a transitioning from tertiary oil recovery to injecting CO2 for the primary purpose of long-term storage is required to obtain a Class VI permit where this transition poses an increased risk to underground sources of drinking water. This study considers how transitioning operations from CO2-EOR to storage can impact reservoir plume and pressure transient in the storage envelope, and how these changes could impact area of review and potential unwanted fluid migration. We developed a case study to assess subsurface response and leakage risks associated with a representative, hypothetical operation in a carbonate reservoir. This reservoir transitions from tertiary hydrocarbon recovery to dedicated GCS. Reservoir simulations were run for a set of credible CO2-EOR scenarios to estimate distributions of fluids phases and pressures throughout the model domain after CO2 flooding as well as forecasting the behavior of the reservoir after the transition to a dedicated storage phase. The evolutions from all simulated scenarios were used as the basis for leakage risk quantification using the National Risk Assessment Partnership’s Open-Source Integrated Assessment Model (NRAP-Open-IAM) with a novel reduced-order model to estimate time-dependent leakage of CO2, brine, and hydrocarbon fluids through potentially leaky wells. Results include a description of reservoir response, an estimate of the areal extent that could potentially be impacted by leakage to underground sources of drinking water, and estimates of the magnitude of potential leakage. Considerations for dedicated storage injection well selection, injectivity, and injection scheme performance and potential leakage risk are presented, with implications for risk assessment of well transition discussed. This study presents a risk-based workflow for the Class II to Class VI well transition. Integrating credible numerical simulation of viable CO2-EOR to dedicated CO2 storage with quantitative risk assessment tools, such as the NRAP-Open-IAM, will provide a valuable means to devise operational scenarios and inform decision-making related to storage benefit, leakage risk, and liability. Presented at the SPE/AAPG/SEG Carbon Capture Utilization and Storage Conference in Houston, TX, March 11-13, 2024.

Liu, Guoxiang↗
NASA NTRS1995

Space and radiation protection: scientific requirements for space research

Ionizing radiation poses a significant risk to humans living and working in space. The major sources of radiation are solar disturbances and galactic cosmic rays. The components of this radiation are energetic charged particles, protons, as well as fully ionized nuclei of all elements. The biological effects of these particles cannot be extrapolated in a straightforward manner from available data on x-rays and gamma-rays. A radiation protection program that meets the needs of spacefaring nations must have a solid scientific basis, capable not only of predicting biological effects, but also of making reliable estimates of the uncertainty in these predictions. A strategy leading to such predictions is proposed, and scientific requirements arising from this strategy are discussed.

NASA Discipline Radiation Health↗
DOE OSTI2024

Assessing the Viability of Geothermal Microgrid Deployment: A Geospatial Analysis Across the United States

Geothermal microgrids hold a potential of supplying clean and dependable power to communities throughout the United States (US), all while sidestepping the expenses associated with connecting to strained or isolated power grids. Nonetheless, their implementation is still in its early stages in the country. The objective of this analysis is to leverage available data to pinpoint regions across the US that exhibit favorable conditions for the development of geothermal microgrids. Drawing from a variety of sources, including estimates of geothermal resources, the costs associated with geothermal energy generation and electricity transmission, existing microgrid locations, and subsidy programs, we aim to identify promising areas for further exploration. By mapping out the contiguous US, Alaska, and Hawaii, we delineate regions with high relative favorability for geothermal microgrid deployment. Our findings reveal the presence of highly favorable regions across the Western states of the contiguous US, as well as isolated areas in Alaska and Hawaii. Furthermore, we delve into a discussion on state policies and incentive programs, considering their role in fostering favorable conditions or posing barriers to geothermal microgrid development.

Alaska↗
NASA NTRS2012

A Geometric Analysis to Protect Manned Assets from Newly Launched Objects - COLA Gap Analysis

A safety risk was identified for the International Space Station (ISS) by The Aerospace Corporation following the launch of GPS IIR-20 (March 24, 2009), when the spent upper stage of the launch vehicle unexpectedly crossed inside the ISS notification box shortly after launch. This event highlighted a 56-hour vulnerability period following the end of the launch Collision Avoidance (COLA) process where the ISS would be unable to react to a conjunction with a newly launched object. Current launch COLA processes screen each launched object across the launch window to determine if an object's nominal trajectory is predicted to pass within 200 km of the ISS (or any other manned/mannable object), resulting in a launch time closure. These launch COLA screens are performed from launch through separation plus I 00 minutes. Once the objects are in orbit, they are cataloged and evaluated as part of routine on-orbit conjunction assessment processes. However, as the GPS IIR-20 scenario illustrated, there is a vulnerability period in the time line between the end of launch COLA coverage and the beginning of standard on-orbit COLA assessment activities. The gap between existing launch and on-orbit COLA processes is driven by the time it takes to track and catalog a launched object, identify a conjunction, and plan and execute a collision avoidance maneuver. For the ISS, the total time required to accomplish an of these steps is 56 hours. To protect human lives, NASA/JSC has requested that an US launches take additional steps to protect the ISS during this "COLA gap" period. The uncertainty in the state of a spent upper stage can be quite large after all bums are complete and all remaining propellants are expelled to safe the stage. Simply extending the launch COLA process an additional 56 hours is not a viable option as the 3-sigma position uncertainty will far exceed the 200 km miss-distance criterion. Additionally, performing a probability of collision (Pc) analysis over this period is also not practical due to the limiting effects of these large orbit state uncertainties. An estimated upper bound for Pc for a typical spent upper stage if nominally aligned for a direct broadside collision with the ISS is only on the order of 10-6. For a smaller manned object such as a Soyuz capsule, the risk level decreases to an order of 10'8 . In comparison, the Air Force Range policy (AFI 91-217) for launch COLAs would only eliminate launch opportunities when conjunctions with objects exceed a Pc of 10'5 This paper demonstrates a conservative geometry-based methodology that may be used to determine if launch opportunities pose a threat to the ISS during the COLA gap period. The NASA Launch Services Program at Kennedy Space Center has developed this COLA gap analysis method and employed it fQr three NASA missions to identify potential ISS conjunctions and corresponding launch window closures during the 56-hour at-risk period. In the analysis, for each launch opportunity, the nominal trajectory of the spent upper stage and the orbit state of the ISS are propagated over the 56 hour period. Each time the upper stage crosses the orbit plane of the ISS, the relative radial and argument of latitude separations are calculated. A window cutout is identified if these separation differences fall within a mission-specific violation box, which is determined from the evaluation of a Monte Carlo dispersions analysis that quantifies the potential variation in the upper stage radial and argument of latitude differences. This paper details the results of these analyses and their impacts to each mission.

Hametz, Mark E.↗
DOE OSTI2025

Energy-resolved neutron imaging and diffraction including grain orientation mapping using event camera technology

Time-of-flight neutron diffraction and energy-resolved imaging each provide unique perspectives into material properties. Neutron diffraction is useful for assessing microstructural parameters such as phase composition, texture, and dislocation densities, though it typically provides averaged data over the sampled volume. Energy-resolved imaging, on the other hand, offers both spatial and spectral information by detecting Bragg edges and neutron absorption resonances, which enables detailed mapping of microstructure and isotopic composition. When combined, these techniques have the potential to enrich our understanding of material behavior across different scales, enhancing our understanding of complex materials. Traditionally, these modalities are conducted on separate instruments, which is time-consuming and poses challenges for data integration. Here, we report the integration of the LumaCam, an event-mode energy-resolved neutron imaging camera with the HIPPO time-of-flight diffractometer at LANSCE. This integration enables simultaneous diffraction and imaging across the full spectrum, with analysis optimized for diffraction and Bragg-edge imaging in the thermal range (0.45–10 Å) and resonance imaging in the epithermal range (0.5–3000 eV), facilitating comprehensive multi-modal analysis. We demonstrate its capabilities through case studies, including spatial mapping of grain orientations in a steel sample and accurate thickness estimations for irregular samples including a depleted uranium cylinder and a natural silver-containing mineral specimen. The combined setup enhances real-time sample alignment and provides comprehensive data for crystal structure, texture, and isotopic composition analysis. This approach opens new possibilities for advanced applications in nuclear engineering, archaeology, and materials science.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Inversion of Time-Lapse Seismic Reservoir Monitoring Data Using CycleGAN: A Deep Learning-Based Approach for Estimating Dynamic Reservoir Property Changes

Carbon capture and storage is being pursued globally as a geoengineering measure for reducing the emission of anthropogenic CO 2 the atmosphere. Comprehensive monitoring, verification, and accounting programs must be established for demonstrating the safe storage of injected CO 2 . One of the most commonly deployed monitoring techniques is time-lapse seismic reservoir monitoring (also known as 4-D seismic), which involves comparing 3-D seismic survey data taken at the same study site but over different times. Analyses of 4-D seismic data volumes can help improve the quality of storage reservoir characterization, track the movement of injected CO 2 plume, and identify potential CO 2 spillover/leakage from the storage reservoirblue. However, the derivation of high-resolution CO 2 saturation maps from 4-D seismic data is a highly nonlinear and ill-posed inverse problem, often requiring significant computational effort. In this research, we apply a physics-based deep learning method to facilitate the solution of both the forward and inverse problems in seismic inversion while honoring physical constraints. A cycle generative adversarial neural network (CycleGAN) model is trained to learn the bidirectional functional mappings between the reservoir dynamic property changes and seismic attribute changes, such that both forward and inverse solutions can be obtained efficiently from the trained model. We show that our CycleGAN-based approach not only improves the reliability of 4-D seismic inversion but also expedites the quantitative interpretation. Our deep learning-based workflow is generic and can be readily used for reservoir characterization and reservoir model updates involving the use of 4-D seismic data.

58 GEOSCIENCES↗
DOE OSTI2021

Towards robust autonomous impedance spectroscopy analysis: A calibrated hierarchical Bayesian approach for electrochemical impedance spectroscopy (EIS) inversion

Distribution-based analyses, such as the distribution of relaxation times (DRT) and the distribution of diffusion times (DDT), present model-free alternatives to equivalent circuit modeling for analysis of electrochemical impedance spectroscopy (EIS) data. However, reconstructing such distributions from noisy impedance data is an ill-posed problem that must be solved with specialized inversion algorithms, requiring careful control and tuning. Furthermore, most inversion algorithms developed to date can only solve problems of limited complexity. Herein, we present a new hierarchical Bayesian method for EIS inversion, leveraging efficient algorithms for optimization and Hamiltonian Monte Carlo (HMC) sampling to solve models of arbitrary complexity. We overcome the challenge of ad-hoc parameter tuning by encoding intrinsic characteristics of the DRT and DDT into flexible prior distributions and “pre-calibrating” the model to simulated data. This approach is versatile, highly robust to noise, and provides quantitative estimates of both the error structure of the data and the uncertainty in the recovered distributions. The model is validated with simulated data to demonstrate accurate recovery of the DRT and the DDT. The method also shows promise for simultaneous recovery of multiple distributions, raising the intriguing possibility of semi-autonomous EIS analysis and ad-hoc model construction. Finally, the practical utility of the method is illustrated with experimental data. Throughout, we draw comparisons to several recently published EIS inversion methodologies.

36 MATERIALS SCIENCE↗
NASA NTRS2010

Empirical Method to Estimate Hydrogen Embrittlement of Metals as a Function of Hydrogen Gas Pressure at Constant Temperature

High pressure Hydrogen (H) gas has been known to have a deleterious effect on the mechanical properties of certain metals, particularly, the notched tensile strength, fracture toughness and ductility. The ratio of these properties in Hydrogen as compared to Helium or Air is called the Hydrogen Environment Embrittlement (HEE) Index, which is a useful method to classify the severity of H embrittlement and to aid in the material screening and selection for safety usage H gas environment. A comprehensive world-wide database compilation, in the past 50 years, has shown that the HEE index is mostly collected at two conveniently high H pressure points of 5 ksi and 10 ksi near room temperature. Since H embrittlement is directly related to pressure, the lack of HEE index at other pressure points has posed a technical problem for the designers to select appropriate materials at a specific H pressure for various applications in aerospace, alternate and renewable energy sectors for an emerging hydrogen economy. Based on the Power-Law mathematical relationship, an empirical method to accurately predict the HEE index, as a function of H pressure at constant temperature, is presented with a brief review on Sievert's law for gas-metal absorption.

Lee, Jonathan A.↗
DOE OSTI2021

Material Control and Accounting Regulatory and Technical Considerations for Microreactors

New microreactors must comply with the Material Control and Accounting (MC&A) regulations in 10CFR74. The objective of MC&A is to verify that the nuclear material is not stolen or diverted to unauthorized users. Microreactors have unique features which pose new challenges to addressing these regulations. This work considers general approaches and methods for microreactor MC&A based on the reactor life cycles which have been proposed by microreactor vendors. One key aspect of MC&A is measurement of the nuclear material. Measurement of microreactor fuel could be especially important because the cores may be sealed for up to 20 years, preventing direct visual confirmation. Measurements could also be especially challenging due to the thick shielding designed around microreactors. This work evaluates a range of techniques used in medical, industrial, and nuclear fields. The cost, time, and performance of the techniques were estimated. Finally, for a promising technique of using in-core neutron detectors, the feasibility was analyzed in detail.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Scaling Optimal Allocation of Cloud Resources Using Lagrange Relaxation

The rapid growth of Cloud Computing (CC) has increased the variety of computing resources, storage, and communication services that pose significant new challenges for the efficient use of cloud resources. The cost-efficient allocation of cloud resources has become a decisive premise for the adoption of CC services. The cost-efficient selection and scheduling of these resources to meet the demands of a scientific workflow is a challenging problem that is exacerbated by the inclusion of multiple CC providers. In this paper, we present a novel strategy for the cost-efficient selection of CC resources using Lagrange relaxation. Our approach is based on preselection of resources and demand decomposition to create a series of smaller sub-problems, which allow the estimation of the best cost-structures and selection of CC service providers for a subset of the time period of the planning horizon. Decomposition of the demand is achieved through the boundary analysis of a continuous relaxation of the problem. Using the metrics defined in terms of the cost and time of completion, we demonstrate excellent performance in relation to optimal solutions. Our method reduced the computational time from hours to seconds for a representative 36-month problem and provided high-quality solutions (< 0.05% relative error). Given the importance of selecting resources and scheduling complex scientific workflows, we believe that this novel strategy will be beneficial for many researchers and users of cloud computing resources.

De La Torre, Luis↗
DOE OSTI2022

Estimating the impact of foregrounds on the future detection of Rayleigh scattering

Rayleigh scattering of the cosmic microwave background (CMB) by neutral hydrogen shortly after recombination leaves frequency-dependent imprints on intensity and polarization fluctuations. High signal-to-noise observations of CMB Rayleigh scattering would provide additional insight into the physics of recombination, including greater constraining power for parameters like the primordial helium fraction, the light relic density, and the sum of neutrino masses. However, such a measurement of CMB Rayleigh scattering is challenging due to the presence of astrophysical foregrounds, which are more intense at the high frequencies, where the effects of Rayleigh scattering are most prominent. Here we forecast the detectability of CMB Rayleigh scattering including foreground removal using blind internal linear combination methods for a set of near-future surveys. Furthermore, we show that atmospheric effects for ground-based observatories and astrophysical foregrounds pose a significant hindrance to detecting CMB Rayleigh scattering with experiments planned for this decade, though a high-significance measurement should be possible with a future CMB satellite.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Higher order mode analysis of a 915 MHz 2-cell cavity for a prototype industrial accelerator

A possible solution to reduce the complexity posed by the cryogenic systems in a superconducting RF accelerator for industrial applications, is to capitalize on the advances achieved by the Nb3Sn superconducting RF technology, as well as the feasibility of a reliable 4 K cooling system, based on commercial cryocoolers. Following this philosophy, the conceptual design for a prototype, conduction-cooled, 4 MeV, 20 kW SRF electron linac, is being developed at Jefferson Lab. Such design is based on a 915 MHz two-cell Nb3Sn cavity. In this contribution, we present the proposed cavity design, including the fundamental power coupler, and the analysis of the Higher Order Modes, using numerical simulations to estimate the potentially dangerous modes and to provide the requirements for damping for reliable operations with a cryocooler.

Rimmer, Robert↗
NASA NTRS2024

Multitemporal landslide inventory and susceptibility map for the Arun River Basin, Nepal

The transboundary Arun River Basin (ARB) spreads across Nepal and Tibet. Nearly 95% of the basin lies in Tibet through which the Pumqu River flows, forming the Arun River once it enters Nepal. The ARB has five large hydropower projects undergoing construction or planned for the future. Rainfall and earthquake-induced landslides, landslide dammed lakes and landslide-induced glacial lake outburst floods pose major risks to smooth operation of these projects. To safeguard upcoming hydropower projects, areas susceptible to landslides in the ARB must be identified. We used high-resolution satellite imagery and open-source tools to generate a multitemporal landslide inventory for the basin. The rigorously quality-controlled inventory represents a yearly record of landslides from 2011 to 2020. A data-driven approach was used to map areas susceptible to landslides within the ARB. The multitemporal landslide inventory combined with other readily available Earth observation-based variables were used to create a landslide susceptibility map. The susceptibility analysis provides a valuable initial estimate of where landslides are likely to initiate. These landslide products could form the basis of more comprehensive local studies to inform hydropower project development.

Arun River Basin↗
DOE OSTI2022

Simulation of Peach Bottom turbine trip transient with RETRAN-3D using BXFGEN

The Peach Bottom 2 Turbine Trip transient is used to evaluate the capabilities and accuracy of coupled 3-D neutronics/thermal hydraulics best estimate calculations for support of safety analysis. Selected results, obtained with RETRAN-3D, are compared to available measurements and benchmark results. The comparisons are analyzed and the application of RETRAN-3D for a best estimate analysis approach within the safety analysis methodology is discussed. Overall, both the thermal-hydraulic and neutronic results show a good comparison to the experimental data, and the model is considered to accurately predict test data. In particular, the initial acoustic response of the main steam line and the subsequent main pressurization stages are well-predicted. During the main pressurization stage, the timing and magnitude of the in-core local pressurization and associated void compression are properly predicted based upon the agreement between local power range monitors (LPRM) predictions upwards, but the shift is slightly underpredicted. This indicates the methodology is well-posed for simulating this class of transient response.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2007

Effects of Lunar Dust Simulant (JSC-1A-vf) on WI-38 Human Embryonic Lung Cells

In order to develop appropriate countermeasures for NASA's return mission to the moon, the potential toxicity of lunar dust needs to be examined. Due to its abrasiveness, reactivity, composition and small size, lunar dust may pose a serious health risk to astronauts who inhale it. This project focuses on the toxicity of lunar dust simulant (JSC-1A-vf) using WI-38 human embryonic lung cells. Past results show that the simulant has toxic effects on small animals using intratracheal instillation. Earlier studies in this lab suggest that the dust remaining in media after low speed centrifugation is toxic. In order to better assess its toxicity, the simulant has been diluted in media, filtered with a 5 micron filter before combining it with media. This filtered dust is compared with dust centrifuged in media. Whole dust toxicity is also tested. Toxicity is estimated using a 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) toxicity test which measures the activity of reducing enzymes in the mitochondria of viable cells. Preliminary results suggest that simulant which is diluted in media at different concentrations is slightly toxic. Interestingly, the cells appear to sweep up and collect the simulant. Whether this contributes to its toxicity is unclear. This project provides possible toxicity testing protocols for lunar dust and contributes to the knowledge of nanosize particle toxicity.

Currie, Stephen↗