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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 379 records · Page 21

A fourth-order phase-field fracture model: Formulation and numerical solution using a continuous/discontinuous Galerkin method

Modeling crack initiation and propagation in brittle materials is of great importance to be able to predict sudden loss of load-carrying capacity and prevent catastrophic failure under severe dynamic loading conditions. Second-order phase-field fracture models have gained wide adoption given their ability to capture the formation of complex fracture patterns, e.g. via crack merging and branching, and their suitability for implementation within the context of the conventional finite element method. Higher-order phase-field models have also been proposed to increase the regularity of the exact solution and thus increase the spatial convergence rate of its numerical approximation. However, they require special numerical techniques to enforce the necessary continuity of the phase field solution. In this paper, we derive a fourth-order phase-field model of fracture in two independent ways; namely, from Hamilton’s principle and from a higher-order micromechanics-based approach. The latter approach is novel, and provides a physical interpretation of the higher-order terms in the model. In addition, we propose a continuous/discontinuous Galerkin (C/DG) method for use in computing the approximate phase-field solution. This method employs Lagrange polynomial shape functions to guarantee -continuity of the solution at inter-element boundaries, and enforces the required regularity with the aid of additional variational and interior penalty terms in the weak form. Finally, the phase-field equation is coupled with the momentum balance equation to model dynamic fracture problems in hyper-elastic materials. Two benchmark problems are presented to compare the numerical behavior of the C/DG method with mixed finite element methods.

42 ENGINEERING↗

A hybrid numerical and machine learning framework for evaluating the performance of a 780 cm 2 aqueous organic redox flow battery

Aqueous organic redox flow battery (AORFB) is a promising cost-competitive technology for large-scale energy storage. Among existing work, the dihydroxyphenazine (DHP)-based AORFB has demonstrated high energy density and low capacity degradation in 10 cm2 cells during lab tests. However, its commercial-scale performance in more complex environments remains unknown, posing a barrier for commercialization. To address this gap, this work presents a comprehensive performance evaluation of a 780 cm 2 DHP-based AORFB by combining physics-based numerical model, machine learning (ML)-based surrogate models, and ML-derived sensitivity quantification. Specifically, we first select 12 key battery parameters that include 10 physicochemical quantities and 2 operation quantities, then select 6 performance metrics that include energy efficiency (EE), discharging capacity, charging energy, and power losses due to concentration, activation, and ohmic over-potentials. With such selection, 12800 combinations of the 12 parameters are subsequently generated using the Latin Hypercube Sampling method. These combinations, together with 38 pre-defined State of Charge, are then integrated to a validated AORFB model developed in COMSOL to compute the performance metrics. With both input parameters and performance metrics, 60 deep neural network (DNN) surrogate models are then trained to approximate the relationship between the 10 physicochemical quantities and 6 performance metrics at each flow rate and current density. Sensitivity scores are then calculated based on the DNN models. Two additional sensitivity analysis tools, i.e., MARS, and SHAP, are also used to cross-validate the sensitivity scores from the DNN. The results demonstrate that 1) the standard potential ranks the first in controlling EE and charging energy, 2) the membrane conductivity is most critical for power loss and EE, and 3) specific area and reaction rate control activation power loss.

25 ENERGY STORAGE↗

Agent-based modeling of supply disruptions in the global rare earths market

Several independent assessments have identified rare earth elements (REEs) as critical materials, notably neodymium (Nd), praseodymium (Pr), and dysprosium (Dy) used in permanent magnets. Factors affecting their criticality include expected growth in demand arising from their unique performance-enhancing properties in consumer, energy, and military applications and the supply risk associated with China's dominance in their production. We demonstrate the use of Argonne's Global Critical Materials (GCMat) agent-based model to explore the possible consequences to REE market dynamics of different types of regional supply disruptions including a temporary loss of production, shutdown of capacity, and diversion of supply. Results suggest that supply disruptions may foster earlier and more REE mine starts outside of China, although some of these mines may not be able to sustain operations post disruption. Further, price and associated market responses such as production, capacity, and demand tended to extend beyond the disruption period. Such market impacts in the magnet supply chain could affect the costs and availability of a number of emerging clean energy technology applications such as electric vehicles and wind turbines. In the future, GCMat could be used to evaluate the effectiveness of mitigation strategies - including recycling, conservation, product substitution, and diversification of supplies - on reducing the severity of disruptions in REE markets.

36 MATERIALS SCIENCE↗

River Regulation Alleviates the Impacts of Climate Change on US Thermoelectricity Production

Climate change and anthropogenic activities can both influence stream temperature, which is a critical indicator of thermoelectric power generation potential. Previous studies emphasized the vulnerability of power-generation systems to climate warming (ref 1, 2). Despite the fact that two-thirds of the global rivers are regulated by dams (ref 3), the relative impacts of water management and climate change on stream temperature and thermoelectric production have not yet been evaluated. Using an integrated modeling system applied to the conterminous United States, simulations confirm the dominant role of climate change in shaping the future trends of stream temperature. However, water management, reservoir regulation in particular, can mitigate the stream temperature warming and reduce the frequency and magnitude of extreme high stream temperatures through redistribution of the seasonal streamflow. Moreover, water management can alleviate the loss of power plant usable capacity from climate change to the level of reduced warming from emission mitigation. By regulating the flow and temperature regimes, water management is a promising adaptation measure to alleviate climate change induced effects in the water-energy nexus.

Zhang, Xiao↗

Future bioenergy expansion could alter carbon sequestration potential and exacerbate water stress in the United States

The maximum future projected bioenergy expansion potential, in scenarios limiting warming to 2°C or below, is equivalent to half of present-day croplands. We quantify the impacts of large-scale bioenergy expansion against re/afforestation, which remain elusive, using an integrated human-natural system modeling framework with explicit representation of perennial bioenergy crops. The end-of-century net carbon sequestration due to bioenergy deployment coupled with carbon capture and storage largely depends on fossil fuel displacement types, ranging from 11.4 to 31.2 PgC over the conterminous United States. These net carbon sequestration benefits are inclusive of a 10 PgC carbon release due to land use conversions and a 2.4 PgC loss of additional carbon sink capacity associated with bioenergy-driven deforestation. Moreover, nearly one-fourth of U.S. land areas will suffer severe water stress by 2100 due to either reduced availability or deteriorated quality. These broader impacts of bioenergy expansion should be weighed against the costs and benefits of re/afforestation-based strategies.

09 BIOMASS FUELS↗

Investigating the Effects of Lithium Deposition on the Abuse Response of Lithium-Ion Batteries

Li deposition at the graphitic anode is widely reported in literature as one of the leading causes of capacity fade in lithium-ion batteries (LIBs). Previous literature has linked Li deposition resulting from low-temperature ageing to diminished safety characteristics, however no current research has probed the effects of Li deposition on the abuse response of well-characterized cells. Using overtemperature testing, a relationship between increased concentrations of Li deposition and exacerbated abuse response in 1 Ah pouch cells has been established. A novel Li deposition technique is also investigated, where cells with n:p < 1 (anode-limiting) have been cycled at a high rate to exploit Li + diffusion limitations at the anode. Scanning Electron Microscopy of harvested anodes indicates substantial Li deposition in low n:p cells after 20 cycles, with intricate networks of Li(s) deposits which hinder Li + intercalation/deintercalation. Peak broadening and decreased amplitude of differential capacity plots further validates a loss of lithium inventory to Li + dissolution, and Powder X-ray Diffraction indicates Li + intercalation with staging in anode interstitial sites as the extent of Li deposition increases. A cradle-to-grave approach is leveraged on cell fabrication and testing to eliminate uncertainty involving the effects of cell additives on Li deposition and other degradation mechanisms.

25 ENERGY STORAGE↗

Hydraulic Testing of the Lost Lake Aquifer Near Recovery Wells RWM 6 and RWM 7

Hydrologic tests were conducted on the Lost Lake Aquifer Zone (LLAZ) at recovery wells RWM 6 and RWM 7 in accordance with the approved test plan (Dixon, 2023). The objective of the testing was to determine well performance parameters of RWM 6 and aquifer hydraulic properties near RWM 6 and RWM 7. Tests at RWM 6 consisted of a step-drawdown test to determine well performance parameters, a constant rate pump test to determine aquifer hydraulic properties, and an aquifer recovery test also used to determine aquifer hydraulic properties. Well performance parameters determined included specific capacity, well efficiency, and head loss coefficients. Prior to testing at RWM 6, a constant rate pump test was conducted at RWM 7. Data from this testing was used to determine aquifer hydraulic properties near RWM 7.

42 ENGINEERING↗

Extrapolation Domains for Aggregating Environmental Outcomes from Local to Regional Levels

Billions of dollars are invested every year to run field experiments to quantify the response of crops to new technologies and associated environmental outcomes. Given the diversity of environments where crop production occurs, conducting these research studies without a robust framework for research site selection and upscaling results to larger spatial scales is inefficient. In this project, researchers from the University of Nebraska-Lincoln used their unique Technology Extrapolation Domains framework (TED) as a tool to guide the selection of experimental sites and as basis for aggregating and validating environmental outcomes from local to regional levels. In the present project, we first used the TED framework to evaluate the current distribution and area coverage of the current SMARTFARM sites. The purpose was to showcase how it is possible to use the TED framework to guide site selection and extrapolate results over space. Additionally, the original TED framework was expanded to account for other factors influencing environmental outcomes by inclusion of three additional variables: soil organic matter, soil texture, and topographic wetness index. The resulting expanded framework (TED-E) was validated using nitrogen (N) losses from corn in the United States as a case study. To do so, we used N balance as a proxy to N losses and we evaluated the capacity of the framework to explain variation in N balance across fields and across countries. We found that the TED-E has substantially higher predictive power than the original TED framework to explain spatial variation in N balance. However, improvements in predictive power with the TED-E tool come at the expense of a higher number of TEDs needed to achieve a given crop area coverage compared with the original TED framework. We conclude that the new TED-E framework can help aggregate and extrapolate environmental outcomes from research sites to regional levels and improve the visualization of their spatial patterns across the United States. An online version of the framework is available at: https://www.toolted.org/

54 ENVIRONMENTAL SCIENCES↗

Evaluating large scale aqueous organic redox flow battery performance with a hybrid numerical and machine learning framework

Aqueous organic redox flow battery (AORFB) is a promising cost-competitive technology for large-scale energy storage. Among existing work, the dihydroxyphenazine (DHP)-based AORFB has demonstrated high energy density and low-capacity degradation in 10 cm$^2$ cells during lab tests. However, its commercial-scale performance in more complex environments remains unknown, posing a barrier to commercialization. To address this gap, this work presents a comprehensive performance evaluation of a 780 cm$^2$ DHP-based AORFB by combining a physics-based numerical model, machine learning (ML)-based surrogate models, and ML-derived sensitivity quantification. Specifically, we first select 12 key battery parameters that include 10 physicochemical and 2 operation quantities, then select 6 performance metrics that include energy efficiency (EE), discharging capacity, charging energy, and power losses due to concentration, activation, and ohmic over-potentials. With such selection, 12800 combinations of the 12 parameters are subsequently generated using the Latin Hypercube Sampling method. Such combinations, together with 38 pre-defined State of Charge, are then integrated to a validated AORFB model developed in COMSOL to compute the performance metrics. With both input parameters and performance metrics, 60 deep neural network (DNN) surrogate models are then trained to approximate the relationship between the 10 physicochemical quantities and 6 performance metrics at each flow rate and current density. Sensitivity scores are then calculated based on the DNN models. Two additional sensitivity analysis tools, i.e., MARS, and SHAP, are also used to cross-validate the sensitivity scores from the DNN. The results demonstrate that 1) the standard potential ranks first in controlling EE and charging energy, 2) the membrane conductivity is most critical for power loss and EE, and 3) specific area and reaction rate control activation power loss.

25 ENERGY STORAGE↗

Automating Detection and Diagnosis of Faults, Failures, and Underperformance in PV Plants

The project developed hybrid physics-based and machine-learning methods for near-real-time detection of balance-of-system faults (e.g., string, combiner, and tracker outages) in utility-scale Photovoltaic plants, achieving over 50% true positive rates with under 10% false positives and significantly reducing engineering setup time. In the extended phase, the scope expanded to plant-level underperformance analysis and industry benchmarking through the SUPER.epri.com platform. SUPER standardizes data processing and performance metrics across more than 9 GWac and 120+ plants, enabling robust comparisons and insights into loss rates, inverter downtime, and capacity degradation.

14 SOLAR ENERGY↗

Analysis of cryogenic propellant logistics.

Large launch vehicle cryogenic propellant logistics including storage and production capacity optimization, cost and heat loss analyses by computer simulation

PROPELLANT STORAGE↗

Secondary iron-air batteries

Self discharge, capacity maintenance, oxidation, and water loss problems in secondary iron-air batteries

Wagner, O. C.↗

Acceptance Testing of a Satellite SCADA Photovoltaic-Diesel Hybrid System

Satellite Supervisory Control and Data Acquisition (SCADA) of a Photovoltaic (PV)/diesel hybrid system was tested using NASA's Advanced Communication Technology Satellite (ACTS) and Ultra Small Aperture Terminal (USAT) ground stations. The setup consisted of a custom-designed PV/diesel hybrid system, located at the Florida Solar Energy Center (FSEC), which was controlled and monitored at a "remote" hub via Ka-band satellite link connecting two 1/4 Watt USATs in a SCADA arrangement. The robustness of the communications link was tested for remote monitoring of the health and performance of a PV/diesel hybrid system, and for investigating load control and battery charging strategies to maximize battery capacity and lifetime, and minimize loss of critical load probability. Baseline hardware performance test results demonstrated that continuous two-second data transfers can be accomplished under clear sky conditions with an error rate of less than 1%. The delay introduced by the satellite (1/4 sec) was transparent to synchronization of satellite modem as well as to the PV/diesel-hybrid computer. End-to-end communications link recovery times were less than 36 seconds for loss of power and less than one second for loss of link. The system recovered by resuming operation without any manual intervention, which is important since the 4 dB margin is not sufficient to prevent loss of the satellite link during moderate to heavy rain. Hybrid operations during loss of communications link continued seamlessly but real-time monitoring was interrupted. For this sub-tropical region, the estimated amount of time that the signal fade will exceed the 4 dB margin is about 10%. These results suggest that data rates of 4800 bps and a link margin of 4 dB with a 1/4 Watt transmitter are sufficient for end-to-end operation in this SCADA application.

Kalu, A.↗

Utilizing Strain Rate Jump Testing to Predict Flow Formability of Al Alloys Sensitive to Portevin-Le Chatelier Instabilities

Predicting the flow formability of Al alloys is challenging due to the incremental deformation, complex loading path, and wide range of strain rates characteristic of the process. State-of-the-art research efforts have primarily focused on formability metrics derived from ambient temperature, constant strain rate uniaxial tensile testing. However, Al alloys in formable tempers tend to exhibit serrated Portevin-Le Chatelier (PLC) flow. The appearance of PLC instabilities implies a negative strain rate sensitivity, loss of tensile area reduction capacity, and decreased formability. Elevated temperature and interrupted strain rate tensile tests of relevant Al alloys were conducted to investigate the effects of rapid changes in strain rate (analogous to a forming increment by a passing roller) on common formability metrics. Emphasis was placed on the character/extent of PLC instabilities using digital image correlation strain measurements. The outcome of this work highlights the possibility of predicting flow formability using strain rate jump testing.

flow forming↗

The Effects of Chronic Sleep Restriction on Multiple Object Tracking

The ability to simultaneously track numerous moving objects in the presence of irrelevant stimuli is essential for carrying out a variety of tasks. Sleep loss has been found to impair neurocognitive functioning and, as a result, attentional processing capacity is reduced. A common form of sleep loss is chronic sleep restriction (CSR), in which an inadequate amount of sleep is obtained over consecutive days. The objective of the current study was to determine if performance on the multiple object tracking (MOT) task was adversely impacted by a week of CSR. Twelve healthy participants (6 males, 6 females) kept a fixed sleep-wake schedule, with a constant waketime, at home for four weeks (activity monitors worn on the participant’s nondominant wrist were used to confirm compliance). Weeks one and three were deemed washout weeks, during which participants maintained a 9-hour sleep-wake schedule. Weeks two and four were deemed experimental weeks, during which participants were randomly assigned a 5-hour (CSR) and 9-hour (sleep satiation) sleep-wake schedule. Following night seven of each experimental week, participants completed a 13-hour laboratory visit under dim light (less than 15 lux) where they maintained a constant posture and were provided with hourly isocaloric snacks. MOT was presented at approximately 6 and 8 hours after waking. Participants were required to track four, five, or six moving targets in the presence of identical distractors (always 12 total objects). It was found that participants slept significantly less during the week of CSR compared to the week of sleep satiation. There was no difference in the overall proportion of correct MOT responses following the CSR and sleep satiation weeks. However, an additional analysis examining only the 6 target condition found that the proportion of correct responses was significantly lower following the week of CSR. These findings suggest that CSR has an adverse impact on tracking performance when the cognitive demand was higher. This has implications for individuals, such as air traffic controllers and truck drivers, who must visually track multiple moving objects under high workload situations, often while chronically sleep deprived.

sleep restriction↗

Battery500 Consortium: Development of High-Capacity Cathodes and Robust Solid Electrolytes

The goal off this EERE-BMR-Battery 500 consortium project was to provide the supporting science and to lead the Keystone 1 project. Key findings include: identification of 1st cycle loss of high nickel NMC materials as a major opportunity to increase the capacity of these cathode materials. The selective use of substituents and surface coatings was identified as a potential way of decreasing the 1st cycle loss and in increasing capacity retention. Niobium at around the 1% level was found to be optimum. In addition, operando DSC was utilized to scope out the stability range of electrolytes developed by the Battery 500 team.

25 ENERGY STORAGE↗

Sound at Scale: Characterizing Impacts of Noise Ordinances on the Onshore Wind Energy Technical Potential for the United States

Recent surveys have documented the rapid rise of sound ordinances across state and county jurisdictions, which has become crucial for wind energy siting. However, the lack of information on ordinances and computational challenges in turbine sound modeling create uncertainties regarding how evolving policies may affect resource potential and clean energy objectives. Therefore, we develop an approach to evaluate wind turbine sound profiles at millions of locations across the U.S. and translate them into setback distances for every residential structure. Compared to a baseline reference scenario, we find a 7% reduction in the national wind energy capacity potential when accounting for counties with existing sound ordinances. Additionally, when expanding the surveyed sound ordinances nationwide, we observe a potential loss of 53% of the national wind capacity under the most stringent ordinances, with a disproportionate share of this lost capacity coming from high-quality and low-cost wind resource. This work reveals that neglecting sound ordinances results in a significant overestimation of wind resource potential and highlights the important trade-offs between increased wind energy deployment to meet target decarbonization goals and the social/environmental impacts of this deployment that must be considered.

aeroacoustics↗

Multi-Gigawatt Electric Highway

Ultra-Compact Electrical Transmission Lines are a new transmission line technology that uses large, hollow, aluminum beams to carry current instead of thin wires. Capacity is 4.5 times higher, power losses are 3 times lower, and cost per mile is a little lower than conventional lines. Resilience and reliability are higher. The beams are enclosed within concrete walls and out of the weather, protected from high winds, ice storms, fires, and lightning. The 230 kV version is 9 feet high x 11 feet wide and can use existing rights of way next to existing transmission lines or highways. With a little landscaping, these transmission lines are not an eyesore and will be much easier to permit on existing rights of way.

24 POWER TRANSMISSION AND DISTRIBUTION↗