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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 127 records · Page 7

Native bee Pollination Ecosystem Services in Agricultural Wetlands and Riparian Protected Lands

Abstract Many freshwater wetlands and riparian systems are protected within agricultural landscapes. Yet, pollinator ecosystem services are seldom considered key ecosystem services provided by these conservation easements. The purpose of this study is to explore the extent of protected aquatic lands to provide pollination ecosystem services by assessing pollinator abundances, crop yield changes, and value estimations of increased soybean yields from a subset of common native solitary bees. We created a novel geodatabase of United States Department of Agriculture (USDA) conservation easements and used this database in the InVEST crop pollination model to model wild solitary bee pollination. We then estimated the monetary value of yield increases provided by pollinators. We found that wetland uplands provided the greatest potential for pollination services for ground nesting bees, followed by herbaceous and forested riparian respectively. Stem nesters preferred forested riparian, then upland habitats. In soybeans fields, we found wild pollinators can provide up to 5.5% yield response from current private aquatic conservation lands. The current landscape is not optimized to use wetlands and riparian conservation lands as pollinator habitat, but these results suggest protected aquatic lands can sustainably increase wild pollination services to agricultural crops if landscapes are managed, protected, and optimized with pollinator services as co-benefit.

Hinson, Audra L. (ORCID:0000000242314820)↗

Sensitivity analysis of generic deep geologic repository with focus on spatial heterogeneity induced by stochastic fracture network generation

Geologic Disposal Safety Assessment Framework is a state-of-the-art simulation software toolkit for probabilistic post-closure performance assessment of systems for deep geologic disposal of nuclear waste developed by the United States Department of Energy. This paper presents a generic reference case and shows how it is being used to develop and demonstrate performance assessment methods within the Geologic Disposal Safety Assessment Framework that mitigate some of the challenges posed by high uncertainty and limited computational resources. Variance-based global sensitivity analysis is applied to assess the effects of spatial heterogeneity using graph-based summary measures for scalar and time-varying quantities of interest. Behavior of the system with respect to spatial heterogeneity is further investigated using ratios of water fluxes. This analysis shows that spatial heterogeneity is a dominant uncertainty in predictions of repository performance which can be identified in global sensitivity analysis using proxy variables derived from graph descriptions of discrete fracture networks. New quantities of interest defined using water fluxes proved useful for better understanding overall system behavior.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Unraveling the effects of management and climate on carbon fluxes of U.S. croplands using the USDA Long-Term Agroecosystem (LTAR) network

Understanding the carbon fluxes and dynamics from a broad range of agricultural systems has the potential to improve our ability to increase carbon sequestration while maintaining crop yields. Short-term, single-location studies have limited applicability, but long-term data from a network of many locations can provide a broader understanding across gradients of climate and management choices. Here we examine eddy covariance measured carbon dioxide (CO 2 ) fluxes from cropland sites across the United States Department of Agriculture's Long-Term Agroecosystem Research (LTAR) network. The dataset was collected between 2001 and 2020, spanning 13 sites for a total of 182 site-years. Average seasonal patterns of net ecosystem CO 2 exchange (NEE), gross primary productivity (GPP), and ecosystem respiration (R eco ) were determined, and subsequent regression analysis on these “flux climatologies” was used to identify relationships to mean annual temperature (MAT), mean annual precipitation (MAP), cropping systems, and management practices. At rainfed sites, carbon fluxes were better correlated with MAP (r2 ≤ 0.5) than MAT (r2 ≤ 0.22). Net carbon balance was different among cropping systems (p < 0.001), with the greatest net carbon uptake occurring in sugarcane (Saccharum spp. hybrids) and the least in soybean (Glycine max) fields. Crop type had a greater effect on carbon balance than irrigation management at a Nebraska site. Across cropping systems, grain crops often had higher GPP and were more likely to have net uptake when compared to legume crops. This multi-site analysis highlights the potential of the LTAR network to further carbon flux research using eddy covariance measurements.

54 ENVIRONMENTAL SCIENCES↗

Ultra high energy cosmic rays The intersection of the Cosmic and Energy Frontiers

The present white paper is submitted as part of the "Snowmass" process to help inform the long-term plans of the United States Department of Energy and the National Science Foundation for high-energy physics. Further, it summarizes the science questions driving the Ultra-High-Energy Cosmic-Ray (UHECR) community and provides recommendations on the strategy to answer them in the next two decades.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Ultra high energy cosmic rays The intersection of the Cosmic and Energy Frontiers

The present white paper is submitted as part of the “Snowmass” process to help inform the long-term plans of the United States Department of Energy and the National Science Foundation for high-energy physics. It summarizes the science questions driving the Ultra-High-Energy Cosmic-Ray (UHECR) community and provides recommendations on the strategy to answer them in the next two decades.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Effect of solution concentration on ethylene propylene diene monomer (EPDM) nonmetallic components used in caustic liquid waste transfer lines

The hose-in-hose transfer lines (HIHTL) used to transfer waste at the United States Department of Energy’s Hanford Site Tank Farm are fabricated from an ethylene propylene diene monomer (EPDM) synthetic rubber. During waste transport, these hoses are exposed to several stressors including caustic solutions at high temperatures and high pressures, as well as β and γ radiation. The aging behavior of HIHTL and dog-bone shaped EPDM specimens were evaluated by exposure to solutions at 77 °C containing 0.00, 6.25, 12.50, and 25.00 % (v/v) sodium hydroxide (NaOH) for 12-months. After the exposure, the material properties of the specimens were measured and compared to the unaged samples. The material properties evaluated included the tensile strength of the EPDM dog-bone samples and the burst pressure of the HIHTL. Both the tensile strength of the EPDM dog-bone samples and the burst pressure of the HIHTL specimens exposed to the 6.25 % NaOH solution exhibited the most significant deterioration and those exposed to 25.00 % NaOH solution had the least deterioration. Finally, examination of the HIHTL and the EPDM dog-bone specimens with scanning electron microscopy showed that the deterioration for the specimens exposed to 6.25 % NaOH solution were the most severe and the samples exposed to 25.00 % NaOH solution had the least deterioration.

42 ENGINEERING↗

Material analysis of metal hydrides for bulk hydrogen storage

The United States Department of Energy (DOE) Hydrogen Storage Engineering Center of Excellence (HSECoE), 2009–2014, was established to evaluate the viability of material-based hydrogen storage for light duty vehicles. The HSECoE concluded that there were no metal hydrides that simultaneously met the DOE targets for gravimetric and volumetric capacity, and rate of onboard refueling. However, it was noted by the DOE that potential applications existed for stationary hydrogen storage systems. An application of particular interest is using a metal-hydride to store a hydrogen supply for fuel cell backup power to a 5 MWe data center. A generalized numerical model that coupled mass and energy conservation, chemical kinetics and thermodynamics was developed to simulate the discharge process for a given metal-hydride. The model was applied to an interstitial and a complex metal-hydride. In conclusion, it was found that the interstitial metal-hydride, which is discharged by a pressure swing is preferrable in a practical sense to the complex metal-hydride, which requires a temperature swing discharge process.

08 HYDROGEN↗

Slot-die-coating operability windows for polymer electrolyte membrane fuel cell cathode catalyst layers

Roll-to-roll (R2R) slot-die coating of polymer electrolyte membrane fuel cell (PEMFC) catalyst layers represents a scalable deposition method for producing 10–20 m 2 ·min -1 of catalyst-coated gas diffusion layers (GDLs). This high-throughput production technique will help lower the cost of PEMFC catalyst layers. The uniformity of the wet layer applied by slot die deposition is affected by process parameters such as substrate speed, vacuum pressure applied at the upstream meniscus, gap between the slot die lips and substrate, ink rheology, and other ink and substrate properties. The set of conditions for producing a defect-free coating with a dilute ink typically requires little to no upstream vacuum pressure, so suitable operating conditions can be found easily through trial and error and operator intuition. However, the higher viscosity of more concentrated inks dramatically shifts the range of settings that result in a homogeneous coating to higher vacuum levels, which are harder to find through hit or miss. A predictive model showing the range of operable conditions decreases material wastage inherent in experimentally searching for suitable parameters. In this study, the defect-free coating parameter window is explored experimentally and theoretically for two concentrations of PEFC cathode inks. Both a full capillary hydrodynamic model and a computationally cheaper viscocapillary model successfully predict the experimentally determined coating window within the experimental and model uncertainty limits for inks with 5.3 wt% and 12.0 wt% solids ink while maintaining the 0.1 mg Pt ·cm -2 Pt areal loading target. Here, this paper demonstrates a viable pathway for meeting the $30/kW net ultimate cost target of the United States Department of Energy (U.S. DOE) Hydrogen Fuel Cells Technologies Office (HFTO). The concentrated ink lowers the thermal energy and capital expenditure (CapEx) budget of the coating process by decreasing the amount of time, energy, and floorspace required for drying the coating.

25 ENERGY STORAGE↗

Glass Design Using Machine Learning Property Models with Prediction Uncertainties: Nuclear Waste Glass Formulation

The United States Department of Energy is responsible for managing the legacy nuclear waste stored in underground tanks at the Hanford Site. The waste will be separately vitrified as low-activity waste and high-level waste fractions. Waste glass formulation algorithms have been traditionally developed using partial quadratic mixture property-composition models. Recently, machine learning (ML) techniques have been used to predict glass properties and discover new glass materials for nuclear waste vitrification, and these advancements can be utilized to improve waste glass composition design. In this proof-of-principle study, ML algorithms such as Gaussian process regression (GPR) were used to interpolate glass properties (e.g., viscosity, electrical conductivity, chemical durability). After selecting appropriate sets of GPR hyper-parameters for each property, an optimization program was developed to formulate glass compositions to maximize waste loading while simultaneously satisfying property within constraints. The results of the ML-based waste loadings and glass compositions were compared to those obtained using the traditional methods. Comparing to the previous glass design framework, the ML-based optimization methods offer improved glass designs and a streamlined approach to generation of optimally designed data and near real-time updates.

glass formulation, machine learning, constraints, ↗

Low Activity Waste Glass Optimization with Property Models from Machine Learning, Part 2: Experimental Validation and Active Learning

The United States Department of Energy is responsible for managing legacy nuclear waste stored in underground tanks at the Hanford Site. To treat the waste, it is planned as the current baseline to separately vitrify low-activity waste (LAW) and high-level waste fractions. Previously, machine learning (ML) based glass property models (e.g., chemical durability, viscosity, electrical conductivity and SO3 solubility) were developed with prediction uncertainties. A waste glass optimization approach was then established to enable the capability of using these ML models in LAW glass formulation. In this study, the previous ML models were first experimentally validated, and the results were incorporated back into the database to update the ML models. The updated models and formulations showed increased waste loading while reducing the failure rate, demonstrating improved predictive accuracy, reduced uncertainties, and the effectiveness of active learning in guiding high-dimensional, nonlinear LAW glass design. This represents the first experimental validation of ML based LAW glass formulation, with practical benefits such as higher waste loading, shorter mission duration, and lower operational risk.

Lu, Xiaonan (ORCID:0000000179708148)↗

Sensitivity study of coupled chemical-CFD simulations for analyzing aluminum-clad spent nuclear fuel storage in sealed canisters

We report the United States Department of Energy (DOE) manages over 50 Metric Tons Heavy Metal (MTHM) of aluminum-clad spent nuclear fuel. One main source for DOE’s Aluminum-clad spent nuclear fuel (ASNF) inventory is the advanced test reactor (ATR) at the INL site, which makes this fuel of particular interest for storage scenarios. Road-ready and final disposition packaging configurations for the ATR fuel dictates storage within helium-backfilled, sealed DOE standard canisters. The conditions within these sealed canisters for extended (greater than50 year dry) storage is of interest. To further this goal, a three-dimensional (3D) multi-physics computational fluid dynamics (CFD) model is developed of the sealed DOE standard canisters. This 3D CFD model is one-way coupled with bulk gas radiolysis reactions considering sealed canisters with inert gas and possible trace amounts of air and water vapor. This study looks at the evolution of the thermal history of the canisters over a 50 year time period with a coupling to the chemical reactions occurring from radiolytic breakdown of residual water. A sensitivity study is then carried out over the parameters of the model including the fuel decay heat, residual water content, sealed pressure, canister external temperature, and canister emissivity. In pure helium, hydrogen generation rates are low, under 10 ppm, but hydrogen generation rates are affected greatly by the presence of even 1% residual air, increasing by 50-plus-fold, and nitric acid generation with residual air also occurs ranging from 500 to 4000 ppm after 50 years. The fuel decay heat and the residual water content show the most importance in the generation of hydrogen gas in pure air, and for nitric acid with a residual air condition. External temperature, canister emissivity and sealed pressure all show minor sensitivity effects to the generation of potentially harmful species.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

A review of criticality dosimetry at the Y-12 National Security Complex and practical importance of dose accuracy in emergency response

A nuclear criticality results in the emission of both neutron and gamma radiation and can produce doses to personnel near the event that exceed 0.1 Gy (10 rad). The primary purpose of nuclear accident dosimetry is to rapidly identify affected personnel in need of prompt medical treatment and to reassure personnel who have been only minimally exposed. While accurate dosimetry is desired, it must be recognized that dose determinations made from whole-body dosimeters or simple triage methods are very rough estimates and contain significant uncertainties. Even when accounting for factors like varying neutron energy spectra, mean photon energies, body orientation within the radiation field, and transient effects on dosimeter response, etc., the end value is a dosimetric quantity defined for very specific radiological conditions and determined within a simple phantom usually at a single depth. Of more importance is the biological response to the radiation, which will vary by person and can be affected by the individual’s radiation sensitivity, age, gender, mass, and underlying health conditions. The overall biological, person-specific response to a given dose cannot be precisely determined except by patient symptom observation and individual biological dosimetry (e.g. chromosome analysis, lymphocyte ratios, etc.). This work describes and discusses the criticality accident dosimetry program at the Y-12 National Security Complex, a United States Department of Energy National Nuclear Security Administration facility. In conclusion, the primary goals of the Y-12 accident dosimetry program are, among others, the rapid identification of significantly exposed persons, prompt routing of exposed workers for medical evaluation and treatment, and the ultimate processing of dosimeters to assign doses to personnel.

61 RADIATION PROTECTION AND DOSIMETRY↗

A review of risk and uncertainty assessment for geologic carbon storage

Carbon capture, utilization, and storage (CCUS) in geological formations play a key role in mitigating anthropogenic CO 2 emissions and achieving the aggressive goal of net-zero greenhouse gas emissions. Risk and uncertainty assessment is crucial for ensuring the safety and reliability of geologic carbon storage (GCS) by evaluating CO 2 migration in subsurface, forecasting potential leakage and induced seismicity risks, and optimizing operational and monitoring plans. In this review, the use and progress of risk assessment for GCS over the last few decades are examined. Here, we use the Southwest Regional Partnership on Carbon Sequestration (SWP), which is one of the seven regional partnerships supported by the United States Department of Energy (U.S. DOE), as an example of large-scale CCUS projects in North America. Additionally, future trends and requirements for risk assessment in GCS are discussed. The information provided in this review can help readers understand the significance of risk and uncertainty assessment and apply it effectively in large-scale GCS projects.

58 GEOSCIENCES↗

Extreme fast charging of commercial Li-ion batteries via combined thermal switching and self-heating approaches

Abstract The mass adoption of electric vehicles is hindered by the inadequate extreme fast charging (XFC) performance (i.e., less than 15 min charging time to reach 80% state of charge) of commercial high-specific-energy (i.e., >200 Wh/kg) lithium-ion batteries (LIBs). Here, to enable the XFC of commercial LIBs, we propose the regulation of the battery’s self-generated heat via active thermal switching. We demonstrate that retaining the heat during XFC with the switch OFF boosts the cell’s kinetics while dissipating the heat after XFC with the switch ON reduces detrimental reactions in the battery. Without modifying cell materials or structures, the proposed XFC approach enables reliable battery operation by applying <15 min of charge and 1 h of discharge. These results are almost identical regarding operativity for the same battery type tested applying a 1 h of charge and 1 h of discharge, thus, meeting the XFC targets set by the United States Department of Energy. Finally, we also demonstrate the feasibility of integrating the XFC approach in a commercial battery thermal management system.

25 ENERGY STORAGE↗

Reconstructed lung doses for the million person study cohort of 26,650 Tennessee Eastman corporation workers employed between 1942 and 1947

Abstract Tennessee Eastman Corporation workers were exposed to uranium dust resulting in high-linear energy transfer (LET) irradiation to lung tissue. In this work, radiation lung doses were reconstructed for 26 650 men and women working at the plant between 1942 and 1947. Site air monitoring data of uranium concentrations and payroll records were used to determine the daily inhaled activities and annualized lung doses. Variations in the activity median aerodynamic diameter of the uranium dust, the solubility of particulate matter in the lungs and the sex-specific breathing rate were investigated as part of a sensitivity analysis. Male and female mean lung doses of 18.9 and 32.7 mGy, respectively, from high-LET alpha irradiation, and there was general agreement with evaluations from previously published epidemiological studies. Annual lung dose estimates and sensitivity analysis for the 26 650 workers in the TEC cohort have been archived on the United States Department of Energy Comprehensive Epidemiologic Data Resource.

61 RADIATION PROTECTION AND DOSIMETRY↗

Review of solar-enabled desalination and implications for zero-liquid-discharge applications

Abstract The production of freshwater from desalinating abundant saline water on the planet is increasingly considered a climate change adaptation measure. Yet, there are challenges associated with the high cost, intensive energy demand, and environmental implications of desalination. Effective integration of solar energy generation and freshwater production can address both issues. This review article highlights recent key advances in such integration achieved in a joint-research university-national laboratory partnership under the auspices of the United States Department of Energy and parallel efforts worldwide. First, an overview of current and emerging desalination technologies and associated pretreatment, brine treatment, and valorization technologies that together can result in zero-liquid-discharge systems is presented, and their technological readiness levels are evaluated. Then, advanced modeling techniques and new software platforms that enable optimization of solar-desalination applications with the dual objective of cost and environmental impact minimization are discussed.

14 SOLAR ENERGY↗

AI for Materials Design and Discovery Using Atomistic Scale Information [Industrial and Governmental Activities]

The design and discovery of materials with desired functional properties is pivotal to the scientific mission of the United States Department of Energy (US-DOE) [1], which includes within its portfolio several important applications for the national economy and security. Importantly, these applications range from: renewable energy (e.g., solar cells, organic photovoltaics, and organic light-emitting diodes), energy storage (e.g., batteries and supercapacitors), and carbon capture and sequestration, to synthesis of manufacturing of new materials (e.g., drugs, or materials with desired conductivity, thermal stability, and catalytic activity), and nuclear energy (e.g., highly performant nuclear fuels and materials with improved nuclear shielding properties).

97 MATHEMATICS AND COMPUTING↗

So you think you can track?

This work introduces a multi-camera tracking dataset consisting of 234 hours of video data recorded concurrently from 234 overlapping HD cameras covering a 4.2 mile stretch of 8-10 lane interstate highway near Nashville, TN. Video is recorded in cooperation with Tennessee State Department of Transportation and its policies. The video is recorded during a period of high traffic density with 500+ objects typically visible within the scene and typical object longevities of 3-15 minutes. GPS trajectories from 270 vehicle passes through the scene are manually corrected in the video data to provide a set of ground-truth trajectories for recall-oriented tracking metrics, and object detections are provided for each camera in the scene (159 million total before cross-camera fusion). Initial benchmarking of tracking-by-detection algorithms is performed against the GPS trajectories, and a best HOTA of only 9.5% is obtained (best recall 75.9% at IOU 0.1, 47.9 average IDs per ground truth object), indicating the benchmarked trackers do not perform sufficiently well at the long temporal and spatial durations required for traffic scene understanding. Video data, scene information, and vehicle trajectories are made publicly available at i24motion.org.

42 ENGINEERING↗