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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 433 records · Page 24

Classification of Methane Emissions from Industrial Meters, Vintage vs Modern Plastic Pipe, and Plastic-lined Steel and Cast-Iron Pipe (Final Report)

The project focus was to improve the characterization of methane (CH 4 ) emissions currently detailed in the U.S. Environmental Protection Agency (EPA) Greenhouse Gas Inventory (GHGI) for categories of assets within the Natural Gas (NG) distribution system to isolate what is driving inflation or deflation behind current, nationwide, aggregated Emission Factors (EFs). These specific categories included industrial/commercial NG customer meters, modern and vintage plastic pipe, along with plastic-lined steel and cast-iron pipe. CH 4 emission rate data was gathered during 25 sampling campaigns at industrial/commercial meter sites, vintage and modern plastic pipe sites, as well as plastic-lined steel and cast-iron sites located within NG distribution networks.

03 NATURAL GAS↗

A Near-infrared Chemical Inventory of the Atmosphere of 55 Cancri e

We present high-resolution near-infrared spectra taken during eight transits of 55 Cancri e, a nearby low-density super-Earth with a short orbital period (<18 hr). While this exoplanet’s bulk density indicates a possible atmosphere, one has not been detected definitively. Our analysis relies on the Doppler cross-correlation technique, which takes advantage of the high spectral resolution and broad wavelength coverage of our data, to search for the thousands of absorption features from hydrogen-, carbon-, and nitrogen-rich molecular species in the planetary atmosphere. Although we are unable to detect an atmosphere around 55 Cancri e, we do place strong constraints on the levels of HCN, NH{sub 3}, and C{sub 2}H{sub 2} that may be present. In particular, at a mean molecular weight of 5 amu, we can rule out the presence of HCN in the atmosphere down to a volume mixing ratio (VMR) of 0.02%, NH{sub 3} down to a VMR of 0.08%, and C{sub 2}H{sub 2} down to a VMR of 1.0%. If the mean molecular weight is relaxed to 2 amu, we can rule out the presence of HCN, NH{sub 3}, and C{sub 2}H{sub 2} down to VMRs of 0.001%, 0.0025%, and 0.08%, respectively. Our results reduce the parameter space of possible atmospheres consistent with the analysis of Hubble Space Telescope/WFC3 observations by Tsiaras et al. and indicate that if 55 Cancri e harbors an atmosphere, it must have a high mean molecular weight or clouds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Gravity-based, non-invasive reactor system and method for coolant inventory monitoring

A gravity-based, non-invasive method of measuring a level of fluid in a container comprises use of at least one gravity meter located as proximate a center of mass of the fluid as possible. In a nuclear reactor system a method for monitoring the level of fluid in a nuclear reactor module, a report of a loss or gain of fluid within a cylindrical module may be generated from capturing a time series of gravity data from a first gravity meter mounted as an upper gravity meter and a second gravity meter mounted as a lower gravity meter, for example, proximate a cylindrical nuclear reactor module so as not to require any invasive conduit through, for example, a containment pressure vessel (CPV) or a reactor pressure vessel (RPV). In one embodiment, the upper and lower gravity meters are mounted on stable mounts as close to the fluid in the module as possible within a coolant pool or a structure containing cooled air. If a coolant pool of water surrounds a nuclear reactor module, the meters may be housed within a dry housing in the coolant pool such that the meters may be accessed from above the coolant pool and are located as close as possible to the reactor module and its contained mass of fluid.

Bloom, Scott Harris↗

Tritium Fires: Simulation and Safety Assessment

This is the Sandia report from a joint NSRD project between Sandia National Labs and Savannah River National Labs. The project involved development of simulation tools and data intended to be useful for tritium operations safety assessment. Tritium is a synthetic isotope of hydrogen that has a limited lifetime, and it is found at many tritium facilities in the form of elemental gas (T 2 ). The most serious risk of reasonable probability in an accident scenario is when the tritium is released and reacts with oxygen to form a water molecule, which is subsequently absorbed into the human body. This tritium oxide is more readily absorbed by the body and therefore represents a limiting factor for safety analysis. The abnormal condition of a fire may result in conversion of the safer T 2 inventory to the more hazardous oxidized form. It is this risk that tends to govern the safety protocols. Tritium fire datasets do not exist, so prescriptive safety guidance is largely conservative and reliant on means other than testing to formulate guidelines. This can have a consequence in terms of expensive and/or unnecessary mitigation design, handling protocols, and operational activities. This issue can be addressed through added studies on the behavior of tritium under representative conditions. Due to the hazards associated with the tests, this is being approached mainly from a modeling and simulation standpoint and surrogate testing. This study largely establishes the capability to generate simulation predictions with sufficiently credible characteristics to be accepted for safety guidelines as a surrogate for actual data through a variety of testing and modeling activities.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Addressing Limitations of the Endpoint Slippage Analysis

Some rate of oxidation and reduction side-reactions will inevitably coexist in most rechargeable batteries. While parasitic reduction traps electrons, parasitic oxidation donates electrons to the cell’s inventory and may cause temporary capacity gain. Consequently, capacity measurements can provide unreliable information about the total extent of side-reactions occurring in the cell. The most widely used method to determine the rate of both these parasitic processes involves analyzing the slippage of endpoints, which consists in tracking the termination of cell charge and discharge when data is represented along a cumulative capacity axis. Here, we argue that this approach could lead to inaccuracies when applied to certain systems, which includes Si electrodes in Li-ion batteries and hard carbon in Na-ion batteries. This inaccuracy originates from the smooth nature of the voltage profiles of these materials at low and high alkali-ion content, causing the termination of charge and discharge to be dictated by voltage changes at both the positive and negative electrodes. We analyze this issue in quantitative terms and propose equations that can provide true rates of parasitic processes from experimental endpoint slippage data. This work shows that, in battery science, well-established analytical approaches may not be directly transferrable to new electrode systems.

25 ENERGY STORAGE↗

Short Communication: Observation of Initial Burst Release of Fission Gas from High-Burnup UO 2 Nuclear Fuel During Thermal Transient

A system was developed and tested to provide a deeper understanding of the fission gas release kinetics from nuclear fuel during thermal transients. Pressure, temperature, spectral data, and optical images were simultaneously collected during resistive sample heating, and all released gases were collected in liquid nitrogen-cooled charcoal traps. Standup testing was performed with a high-burnup nuclear fuel segment from rod section with an average local burnup of 77 GWd/tU. During heating, the segment released approximately 6 ± 2% of generated fission gas inventory after ramp heating to 460°C. Here, heating ceased when the sample ejected from the holder, as observed by constant imaging.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Neural Posterior Estimation for Scalable and Accurate Inverse Parameter Inference in Li-Ion Batteries

Diagnosing the internal state of Li-ion batteries is critical for battery research, operation of real-world systems, and prognostic evaluation of remaining lifetime. By using physics-based models to perform probabilistic parameter estimation via Bayesian calibration, diagnostics can account for the uncertainty due to model fitness, data noise, and the observability of any given parameter. However, Bayesian calibration in Li-ion batteries using electrochemical data is computationally intensive even when using a fast surrogate in place of physics-based models, requiring many thousands of model evaluations. A fully amortized alternative is neural posterior estimation (NPE). NPE shifts the computational burden from the parameter estimation step to data generation and model training, reducing the parameter estimation time from minutes to milliseconds, enabling real-time applications. The present work shows that NPE can infer parameters equally or more accurately than Bayesian calibration, even if it leads to higher voltage reconstruction errors. We also demonstrate that the higher computational costs for data generation are tractable even in high-dimensional cases (ranging from 6 to 27 estimated parameters). The NPE method also offers several interpretability advantages over Bayesian calibration, such as local parameter sensitivity to specific regions of the voltage curve. The NPE method is demonstrated using an experimental fast charge dataset, with parameter estimates validated against measurements of loss of lithium inventory and loss of active material. The implementation is made available in a companion repository (https://github.com/NatLabRockies/BatFIT).

25 ENERGY STORAGE↗

SRS Composite Analysis Monitoring Plan (FY2019 Model Validation)

Using a projected end-state date of 2065 (SRNS 2015b), the Savannah River Site (SRS) Composite Analysis (CA) modeling for each facility and waste site began on the inventory year assigned to it so that source depletion and radionuclide transport out of the system could be appropriately captured. Some SRS waste sites that have already achieved their end states (i.e. end-state inventories and end-state configuration) are currently contributing to the potential off-site public dose through source release, groundwater transport, discharge to on-site surface streams, and stream transport to the CA point of assessments (POAs). The inventory year assigned to these waste sites is 2002 or before. This means that SRS CA results from 2002 and beyond are a reasonable representation for these waste sites that have already achieved their end states and are currently contributing to the potential off-site public dose. The SRS Annual Environmental Report (AER) monitoring can differentiate and separate liquid pathway data allowing the data representing only waste sites at their end state to be produced. Because the SRS CA has projected reasonable end-state impacts from 2002 and beyond, and the AER monitoring can differentiate and separate operating and end-state contributions to annual liquid pathway release, an opportunity exists to use the AER monitoring data to validate the SRS CA model. The CA model validation program uses a graded and systematic approach for taking corrective action, starting with an SRS established administrative dose limit of 15 mrem/yr, below which no action is required. Based on the location of the 2010 SRS CA POAs, the only potential exposure pathway for the public is through surface water. The completion of the FY2019 CA model validation indicates that the SRS CA projected dose, while generally conservative, provides a reasonable representation of the maximum annual doses. These doses are well below the administrative limit; therefore, no additional action is required.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Model Validation for the FY2021 SRS Composite Analysis Monitoring Plan

Using a projected end-state date of 2065 (SRNS 2015b), the Savannah River Site (SRS) Composite Analysis (CA) modeling for each facility and waste site began on the inventory year assigned to it so that source depletion and radionuclide transport out of the system could be appropriately captured. Some SRS waste sites that have already achieved their end states (i.e., end-state inventories and end-state configuration) are currently contributing to the potential off-site public dose through source release, groundwater transport, discharge to on-site surface streams, and stream transport to the CA point of assessments (POAs). The inventory year assigned to these waste sites is 2002 or before. This means that SRS CA results from 2002 and beyond are a reasonable representation for these waste sites that have already achieved their end states and are currently contributing to the potential off-site public dose. The SRS Annual Environmental Report (AER) monitoring can differentiate and separate liquid pathway data allowing the data representing only waste sites at their end state to be produced. Because the SRS CA has projected reasonable end-state impacts from 2002 and beyond, and the AER monitoring can differentiate and separate operating and end-state contributions to annual liquid pathway release, an opportunity exists to use the AER monitoring data to validate the SRS CA model.

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Integrated Process Optimization for Biochemical Conversion

This research is motivated by the challenges faced during biomass processing in bioenergy plants. It has been observed that variations in biomass characteristics, such as moisture, ash, and carbohydrate contents cause variations in feeding of the system which led to underutilization of equipment and the reactor. The objective of this research is to ensure a continuous flow of biomass to the reactor in plants that use the biochemical conversion process to generate liquid fuels. The overall goal is to lower the cost of producing biofuels, which could lead to improving US’s energy independency and growing US’s rural economy. The research team developed analytical models, such as discrete element method (DEM) models and mathematical models. The DEM models are unit-level models that explicitly capture biomass characteristics and quantify the impacts of biomass characteristics on bulk material properties and the performance of specific equipment. The mathematical models are system-level models that capture the impacts of system infeed rate, equipment processing rate, storage location and capacity, and biomass characteristics on system throughput. The functional relations predicting the bulk material properties from DEM models are incorporated to the mathematical models. The models developed were validated and evaluated using data collected at Idaho National Laboratory’s biomass processing facility. Via these models, we identified process control strategies that ensure a continuous flow of biomass to the reactor, while meeting the requirements of biochemical conversion process. Our analysis indicates that sequencing of biomass bales based on moisture level, and carbohydrate contents could have a positive impact on reducing processing time and inventory level and increasing throughput rate. Short bale sequences that repeat frequently, seem to have the greatest impact on improving system’s performance. Based on our experiments, the total annual system operating costs reduced by 20-30%, and the maximum inventory level reduced by 3 to 4 times. The operating costs include the annual equipment amortization cost and processing cost. The implementation of the models developed requires the use of standardized bale format, Radio Frequency Identification technology, sensing and real time monitoring of material attributes, automated material handling equipment, and automated process control. The scope of the model proposed can be extended to include the whole supply chain. The supply chain models help identify how many bales of different biomass feedstock to purchase given biomass availability in the region, biomass price and quality, and the biomass processing capabilities of the biorefinery. Thus, the outcomes of supply chain models can be used to inform the design of long-term contracts among farmers and the biorefinery.

09 BIOMASS FUELS↗

Life Cycle Analysis of Natural Gas Extraction and Power Generation: U.S. 2020 Emissions Profile

This analysis expands upon previous life cycle analyses (LCAs) of natural gas systems performed by the National Energy Technology Laboratory (NETL). It provides a complete inventory of emissions to air and water, water consumption, and land use change. These environmental burdens are detailed for all supply chain steps from natural gas production through natural gas distribution. This package includes the report, the NETL Natural Gas Model, and appendices that include several Excel workbooks and a python script to provide transparent access to the calculations and resulting data.<p>To access the NETL Natural Gas Lifecycle model, visit https://doi.org/10.18141/2476250.</p><p>To access the 2020 Report Appendices, visit https://doi.org/10.18141/2438472.</p>

03 NATURAL GAS↗

Life Cycle Analysis of Natural Gas Extraction and Power Generation: U.S. 2020 Emissions Profile

This analysis expands upon previous life cycle analyses (LCAs) of natural gas systems performed by the National Energy Technology Laboratory (NETL). It provides a complete inventory of emissions to air and water, water consumption, and land use change. These environmental burdens are detailed for all supply chain steps from natural gas production through natural gas distribution. This package includes the report, the NETL Natural Gas Model, and appendices that include several Excel workbooks and a python script to provide transparent access to the calculations and resulting data. This is revision 1 of the 2024 study (published December 17, 2024 and updated on January 24, 2025) and corrects a modeling error in natural gas composition. See the errata on page 2 for more information.

03 NATURAL GAS↗

Battery state-of-health diagnostics during fast cycling using physics-informed deep-learning

Rapid, in-situ Li-ion battery state-of-health (SOH) quantification is challenging. Li-ion battery aging can vary significantly with chemistry, operating conditions, cycling demands, electrode design, and operation history. As a cell ages, optimal and safe operating conditions need to be adapted to account for battery degradation by tracking critical aging modes such as loss-of-lithium-inventory (LLI), loss-of-active-material (LAM) in either electrode, and/or impedance rise. This manuscript describes a framework for identifying battery aging modes in-operando using fast-rate voltage charge/discharge responses. The framework uses a physically based Li-ion battery model to produce synthetic high-rate responses at aged states. The aging model is calibrated against experimental data from cells with different electrode loadings and cycled under a variety of fast-charging conditions (1 h, 15 min, 10 min, and 7 min charging). The synthetically generated high-rate responses at aged states are then used to train a deep-learning model to identify real cell state-of-health from fast charge/discharge battery voltage responses. The synthetically trained deep-learning model performance is validated by comparing to standard incremental capacity analysis and half-cell measurements. Finally, the framework demonstrates the benefits of using high-rate physics-based models to generate synthetic data for training deep-learning models.

25 ENERGY STORAGE↗

Hanford 200 West Area Flowsheet Data to Support Waste Treatment and Disposal Request for Proposal

This report documents the 200 West Area (200W) flowsheet supplemental data needed to support the Request for Proposal (RFP) to procure onsite and/or offsite treatment and disposal capabilities for West Area pretreated1 tank waste (PTW). The data provided in this document is based on the results of a 200W flowsheet model run evaluating single-shell tank (SST) retrievals for all S, SX, and U Farms, except for Tank S-112, which was retrieved in March of 2007 (HNF-EP-0182, Waste Tank Summary Report for Month End August 31, 2024). The evaluation also includes the waste inventory in double-shell tanks (DSTs) in SY Farm.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Where Is the Water? Jupiter-like C/H Ratio but Strong H{sub 2}O Depletion Found on τ Boötis b Using SPIRou

The present-day envelope of gaseous planets is a relic of how these giant planets originated and evolved. Measuring their elemental composition therefore presents a powerful opportunity to answer long-standing questions regarding planet formation. Obtaining precise observational constraints on the elemental inventory of giant exoplanets has, however, remained challenging owing to the limited simultaneous wavelength coverage of current space-based instruments. Here, we present thermal emission observations of the nontransiting hot Jupiter τ Boo b using the new wide wavelength coverage (0.95–2.50 μm) and high spectral resolution (R = 70,000) CFHT/SPIRou spectrograph. By combining a total of 20 hr of SPIRou data obtained over five nights in a full atmospheric retrieval framework designed for high-resolution data, we constrain the abundances of all the major oxygen- and carbon-bearing molecules and recover a noninverted temperature structure using a new free-shape, nonparametric temperature–pressure profile retrieval approach. We find a volume mixing ratio of log(CO) = -2.46{sub -0.29}{sup +0.25} and a highly depleted water abundance of less than 0.0072 times the expected value for a solar composition envelope. Combined with upper limits on the abundances of CH{sub 4}, CO{sub 2}, HCN, TiO, and C{sub 2}H{sub 2}, this results in a gas-phase C/H ratio of 5.85{sub -2.82}{sup +4.44} × solar, consistent with the value of Jupiter, and an envelope C/O ratio robustly greater than 0.60, even when taking into account the oxygen that may be sequestered out of the gas phase. Combined, the inferred supersolar C/H, O/H, and C/O ratios on τ Boo b support a formation scenario beyond the water snowline in a disk enriched in CO owing to pebble drift.

74 ATOMIC AND MOLECULAR PHYSICS↗

North‐East Peri‐Tethyan Water Column Deoxygenation and Euxinia at the Paleocene Eocene Thermal Maximum

Abstract The Paleocene–Eocene Thermal Maximum (PETM) is associated with climatic change and biological turnover. It shares features with the Oceanic Anoxic Events (OAEs) of the Mesozoic, such as transient global warming and biogeochemical perturbations. However, the PETM experienced a more muted expansion of marine anoxia compared to the Mesozoic OAEs (especially OAE2), with geographically limited evidence for photic zone euxinia (PZE). We explore the extent and drivers of marine deoxygenation during the PETM using biomarkers for water column euxinia and anoxia as well as an intermediate complexity Earth system model (cGEnIE). These reveal that the water column in the North‐East Peri‐Tethys became anoxic, with euxinic conditions reaching the photic zone (PZE) during the PETM. Our model shows that euxinia developed due to a global increase in the ocean nutrient inventory with concomitant oxygen consumption, similar to findings for OAE2. The particularly strong regional response in the NE Peri‐Tethys appears to arise from a combination of global CO 2 ‐weathering forcing, regionally restricted circulation and upwelling of sulphidic thermocline waters. Unlike OAE2, anoxia and PZE do not become widespread in our PETM simulations, consistent with new and existing geochemical and biological proxy data. This globally muted response could result from reduced biogeochemical feedbacks to climate forcing relative to the mid‐Cretaceous climate. Our observations suggest that similar mechanisms operated in response to disparate Cenozoic (PETM) and Mesozoic (OAEs) transient global warming events, while also highlighting that background conditions are crucial in modulating the sensitivity of Earth's system to them.

Behrooz, L.↗

Regional Oil and gas Aerial Methane Synthesis model (Analytica) (ROAMS Analytica) v1.5.2

The Regional Oil and gas Aerial Methane Synthesis model (Analytica) is a tool to convert the results of wide-area, source-resolved aerial methane remote sensing surveys of oil and natural gas infrastructure in a given region into methane emissions inventories (estimates of the magnitude and breakdown of methane emissions from the surveyed infrastructure). This version is written in the Analytica programming language, and this version accompanies a correction in preparation for submission to Sherwin et al. 2024 (Nature). The tool leverages databases of source-resolved methane emissions detected in aerial surveys, aerial survey coverage information (which areas were measured and when), data summarizing surveyed oil and natural gas infrastructure and production (derived from third-party databases), as well as state-of-the-art mechanistic emissions simulation tools to characterize emissions too small for the aerial system to see. The regional methane emissions estimates produced by this tool are much more granular in both space and asset type than common satellite- or flux tower-based regional estimates. Unlike other tools for converting site-level measurements into regional emissions estimates, our unique geostatistical approach integrates aerially measured emissions with limited need for statistical extrapolation, which can be highly sensitive to modeler assumptions. As a result, ROAMS-based estimates of regional methane emissions from oil and gas activity are widely viewed as highly credible, as evidenced by the success of Dr. Sherwin's recent paper in Nature.

Sherwin, Evan [Lawrence Berkeley National Laborato↗

Field-Scale Lysimeter Studies of Glass and Cementitious Waste Forms at the Hanford Site - 20392

The Hanford site Integrated Disposal Facility (IDF) will receive waste forms from vitrification activities at the Hanford Waste Treatment and Immobilization Plant (WTP). The waste form inventory to be disposed of at the IDF will consist of vitrified low-activity waste (LAW) in glass forms and solidified (or encapsulated) secondary wastes in cementitious forms. The IDF is a near-surface burial facility located near Hanford's Waste Treatment and Immobilization Plant in the 200 East Area of the site's Central Plateau. An extensive set of laboratory experimental data has been collected to support IDF performance assessment calculations of the eventual degradation of waste forms and mobility of contaminants. This paper describes the start of a field experiment to generate waste-form performance data on a larger scale (tens of centimeters), over a longer duration (five years or more), and under field conditions representative of the IDF. Results from this study are expected to improve model descriptions of contaminant mobility, reduce uncertainties about the representativeness of laboratory results in the IDF performance assessment, improve stakeholder confidence in the safe disposal of treated waste at the IDF, and facilitate the adoption of informed facility designs with the potential to reduce operational costs. A lysimeter test facility near Hanford's 200 West Area has been repurposed to carry out long-term assessments of waste forms buried in sediments excavated from the IDF. The waste forms are buried in large drainage lysimeters, open caissons that are two meters in diameter and three meters deep. Waste forms are buried in up to six locations in each lysimeter. Samplers collect pore water and drainage water beneath the waste forms and air from the pore space adjacent to waste forms. Sensors measure temperature, soil water content, soil water tension, and drainage flux. One lysimeter containing cementitious waste forms and one containing glass waste forms have been completed, along with a control lysimeter (without waste forms). The cementitious waste forms are Cast Stone grout formulations using a liquid secondary waste simulant and a generic Hanford high-salt simulant, as well as a hydrated lime-based grout formulation using a liquid secondary waste simulant. Technetium-99 and iodine-127 were added as tracers to monitor contaminant mobility. Glass waste forms were fabricated in two formulations (LAWA44 and ORLEC28), with rhenium and molybdenum tracers to monitor waste form degradation. The predicted performance of the waste forms in the lysimeters was modeled prior to installation to determine waste form size, tracer concentration/activity, and locations of sensors and samplers. (authors)

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