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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Structure-aware Initialization via Numerical Continuation and Informed Priors

Scientific machine learning (SciML) often operates in ill-conditioned, weakly identifiable regimes due to limited data or indirect observations. In such settings, optimization and inference are highly sensitive to the starting point, making initialization--often under-reported--a consequential degree of freedom. Random initialization is not a neutral default as it induces an implicit prior over candidate solutions and can systematically bias the result, producing large run-to-run variability. Here, we formalize this view by treating initialization as a hidden confounder in SciML and develop a unifying theory for structure-aware initialization via numerical continuation, constructing warm starts from related problem instances. Across representative tasks, including physics-informed neural networks, maximum likelihood estimation, and variational inference, warm starts have been shown to consistently reduce optimization effort and improve reliability.

Data integrity↗
DOE OSTI2020

Enhanced Tensor Completion Based Approaches for State Estimation in Distribution Systems

Grid state estimation is essential for effective control and management of distribution systems. While weighted least squares has been the conventional method for state estimation, sparsity-aware methods have become popular due to their superior performance with limited data. Matrix completion and compressed sensing-based state estimation approaches exploit the underlying smoothness in the state variables. However, classic matrix completion methods do not take into account the temporal correlation of system states. Compressed sensing methods, on the other hand, require an appropriate choice of sparsifying basis that may not be easy to identify. This paper proposes a blocktensor completion based framework which uses an alternative approach to estimate voltage phasor, power injections and branch currents. This approach utilizes the temporal correlation of the system states in a tensor trace-norm minimization formulation with power flow equations as constraints. Herein, feature scaling is introduced in the problem formulation to benefit from the improved sensitivity of the tensor trace norm to the matrix columns in the scaled unfoldings of the tensor. Weighted tensor norm is utilized to exploit the structures of the different unfoldings of the state measurement tensor to improve the voltage estimation. The estimation accuracy is further improved by alternatively estimating the tensor columns and increasing the available data at each stage in the tensor completion process. The proposed methods are evaluated on the IEEE-33, 37 test systems and a 100- node test system. The proposed methods are shown to provide significant performance gains relative to the classic matrix and tensor completion based approaches.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

A Large Language Model for Determining Partial Tripping of Distributed Energy Resources

Knowing the status of individual distributed energy resources, i.e., being tripped or not, after a contingency can inform the development of an aggregated DER model. Here, this letter presents a large language model application to determine the partial tripping of distributed energy resources depending on the types, locations, and duration of faults in the transmission network. The large language model, or more specifically BERT-based approach can streamline the fault information into tokenized input, which not only reduces the complexity of the machine learning model but also demonstrates a robust performance with only limited data sets.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

LLM-Based Adaptive Distribution Voltage Regulation Under Frequent Topology Changes: An In-Context MPC Framework

This paper proposes a large language model (LLM) based adaptive inverter control for distribution voltage regulation under frequent topology changes. We leverage the ability of the LLM to perform in-context learning and create a topology-adaptive surrogate model for power flow calculation. The surrogate model is then integrated with a long short-term memory-based load forecaster and a model predictive control (MPC) scheme to achieve the optimal inverter control that adapts to frequent topology changes. Unlike many existing works that assume fixed-topology grids or require the knowledge of all possible topologies when training a model, the proposed in-context MPC method tackles the distribution voltage control problem under various topologies and adapts to unknown topologies with limited data requirement for fine-tuning. The effectiveness of our method is demonstrated on a modified IEEE 123-bus test system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Critical habitat identification of peripheral Sage Thrashers under climate change

Abstract The Sage Thrasher ( Oreoscoptes montanus ) has been assessed as “Endangered” in Canada since 1992. Like other species with a geographic range that barely extends into Canada, Sage Thrashers are rare. Thirty‐one percent of Canada's bird species listed for recovery under the Canadian Species at Risk Act (SARA) are at the periphery of their range. A listing of “endangered” under SARA requires identification of critical habitat for the species. With anticipated climate change, recovery of species requires a more proactive intervention than relying on historical occurrence to locate suitable habitat. We synthesized 19 years of Sage Thrasher occurrence and related habitat data across the species' northern range in British Columbia (BC) and Washington (WA) to define critical habitat characteristics. We found Sage Thrashers selected less leaf litter and less grass cover in flat or low‐slope regions farther from anthropogenic or natural habitat breaks; habitat sensitive to the expected climate change impacts of fire, changes in precipitation, and invasive species establishment. By augmenting the BC data collected in the species' peripheral range with data from their core distribution in WA, we identified key habitat elements of an otherwise data‐poor species that do not breed in sufficient numbers in Canada to reliably characterize their habitat. These methods improve the identification of “critical habitat” for peripheral species like Sage Thrashers in preparation for climate‐induced range expansion northward. The framework developed demonstrates a useful template for conservation strategies for data‐limited peripheral populations in other regions. Focusing on the landscape‐level variables that indicate good habitat, and not the locations of habitat, can identify suitable future areas for conservation.

Millikin, Rhonda L.↗
DOE OSTI2020

Much stronger tundra methane emissions during autumn-freeze than spring-thaw

Warming in the Arctic has been more apparent in the non-growing season than in the typical growing season. In this context, methane (CH 4 ) emissions in the non-growing season, particularly in the shoulder seasons, account for a substantial proportion of the annual budget. However, CH 4 emissions in spring and autumn shoulders are often underestimated by land models and measurements due to limited data availability and unknown mechanisms. This study investigates CH 4 emissions during spring thaw and autumn freeze using eddy covariance CH 4 measurements from three Arctic sites with multi-year observations. We find that the shoulder seasons contribute to about a quarter (25.6±2.3%, mean ± standard deviation) of annual total CH 4 emissions. Our study highlights the three to four times higher contribution of autumn freeze CH 4 emission to total annual emission than that of spring thaw. Autumn freeze exhibits significantly higher CH 4 flux (0.88±0.03 mg m -2 h -1 ) than spring thaw (0.48±0.04 mg m -2 h -1 ). The mean duration of autumn freeze (58.94±26.39 days) is significantly longer than that of spring thaw (20.94±7.79 days), which predominates the much higher cumulative CH 4 emission during autumn freeze (1212.31±280.39 mg m -2 yr -1 ) than that during spring thaw (307.39±46.11 mg m -2 yr -1 ). Near-surface soil temperatures cannot completely reflect the freeze-thaw processes in deeper soil layers and appears to have a hysteresis effect on CH 4 emissions from early spring thaw to late autumn freeze. Therefore, it is necessary to consider commonalities and differences in CH 4 emissions during spring thaw versus autumn freeze to accurately estimate CH 4 source from tundra ecosystems for evaluating carbon-climate feedback in Arctic.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

From Depletion to Restoration: Lessons From Long‐Term Monitoring of Carbon Gains and Losses in Cropping Systems

As global atmospheric CO 2 rapidly approaches a key tipping point, there is an urgent need to implement strategies to reverse this pattern. A generally accepted understanding of carbon (C) in agricultural fields includes: (H1) substantial C loss occurs when natural vegetation is converted to crops, (H2) soils typically reach a steady-state C concentration under contemporary practices, and (H3) improved management or crop selection can enhance soil C stocks over time. Significant variability exists, but studies consistently show large C losses from agricultural ecosystems, supporting H1. Although steady-state C levels (H2) are commonly assumed, measuring C gains or losses in mature agroecosystems is challenging. Efforts to increase soil C storage (H3) have limited data due to the diversity of potential practices, compounded by substantial variability in soil C measurements. Here, long-term (7–17 year) ecosystem C flux data from diverse cropping systems revealed that conventionally tilled annual row crops (maize and soybean) act as significant long-term atmospheric C sources, challenging H2. Furthermore, conservation tillage practices reduced C losses compared with conventional tillage but showed minimal evidence for long-term ecosystem C storage, even after 20+ years. This indicates that no-till practices reduce C losses but imply that no soil C is added, challenging H3. By contrast, perennial Miscanthus × giganteus, Panicum virgatum, and restored tallgrass prairie systems store C at the ecosystem scale more effectively than minimally tilled annual row crops. Analysis over multiple years demonstrates significant ecosystem C storage with perennial crops, varying by species, starting in the first year of transition. These findings, although focused on one region, suggest that the assumptions of steady-state C levels and increased storage from conservation practices do not universally apply and that significant changes to agroecosystems are required to increase C storage.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Preface for the special topic collection honoring Dr. Scott Chambers’ 70th birthday and his leadership in the science and technology of oxide thin films

It is an honor to dedicate this special issue to Dr. Scott A. Chambers, who has had a rewarding and impactful career in surface science, spectroscopy, and thin film synthesis. His research career, spanning from his graduate work in the 1970’s to the present day, was built upon pioneering early work in precision thin film synthesis and spectroscopic characterization that occurred beginning in the 1960’s. Notably, this includes the contributions of both Art Gossard to precision film synthesis by molecular beam epitaxy (MBE) and Chuck Fadley to photoelectron spectroscopy; both Art and Chuck were recently honored with JVSTA commemorative issues of their own. Yet Scott is no mere copycat; he extended and expanded their contributions to further advance the field of surface science, and he applied the same scientific rigor to the emerging field of precision epitaxial oxide synthesis. This rigor was perhaps not always appreciated by the more “enthusiastic” members of the community who tended to draw exciting conclusions from limited data. He was once referred to, fondly, by a collaborator as a “spoilsport” for his penchant for using careful, defensible synthesis and characterization to prove that popular models and assumptions of the day did not stand up to scrutiny.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

129 I and 247 Cm in meteorites constrain the last astrophysical source of solar r-process elements

The composition of the early Solar System can be inferred from meteorites. Many elements heavier than iron were formed by the rapid neutron capture process (r-process), but the astrophysical sources where this occurred remain poorly understood. We demonstrate that the near-identical half-lives (≃15.6 million years) of the radioactive r-process nuclei iodine-129 and curium-247 preserve their ratio, irrespective of the time between production and incorporation into the Solar System. We constrain the last r-process source by comparing the measured meteoritic ratio 129 I/ 247 Cm = 438 ± 184 with nucleosynthesis calculations based on neutron star merger and magneto-rotational supernova simulations. Moderately neutron-rich conditions, often found in merger disk ejecta simulations, are most consistent with the meteoritic value. Uncertain nuclear physics data limit our confidence in this conclusion.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Virulence factors and antimicrobial resistance profiles of Campylobacter isolates recovered from consecutively reused broiler litter

ABSTRACT Campylobacterinfections are a leading cause of bacterial diarrhea in humans globally. Infections are due to consumption of contaminated food products and are highly associated with chicken meat, with chickens being an important reservoir forCampylobacter. Here, we characterized the genetic diversity ofCampylobacter jejuni(C. jejuni) andCampylobacter coli(C. coli) detected in broiler chicken litter over three consecutive flocks and determined their antimicrobial resistance (ARM) and virulence factor (VF) profiles.Campylobacterwas detected in 9.38% (27/288) of litter samples collected. Antimicrobial susceptibility testing and whole genome sequencing were performed onC. jejuni(n= 39) andC. coli(n= 5) isolates.Campylobactervirulence factors differed within and across broiler houses but were explained by the broiler flock cohort raised on litter,Campylobacterspecies andCampylobactermultilocus sequence type (MLST). Virulence factors involved in the ability to invade and colonize host tissues and evade host defenses were present inC. jejuniisolates (ST-464) from flock cohorts 1 and 2 but absent inC. jejuniisolates (ST-48) from flock cohort 3.C. jejuniisolates from house three harbored a significantly higher proportion of virulence genes with functions related to glycosylation and immune evasion thanC. jejuniisolates from houses 1 and 2 (P< 0.01). AllC. jejuniisolates were susceptible to all antibiotics tested whileC. coli(n= 4) were resistant to tetracycline and harbored the tetracycline resistant ribosomal protection protein (TetO). Our results suggest that house environment and broiler management practices imposed selective pressures on virulence factors and antimicrobial resistance genes ofCampylobacter. IMPORTANCE Campylobacteris a leading cause of foodborne illness in the United States due to consumption of contaminated or mishandled food products, often associated with chicken meat.Campylobacteris common in the microbiota of avian and mammalian gut; however, acquisition of antimicrobial resistance genes (ARGs) and virulence factors (VFs) may result in strains that pose significant threat to public health. Although there are studies investigating the genetic diversity ofCampylobacterstrains isolated from post-harvest chicken samples, there are limited data on the genome characteristics of isolates recovered from preharvest broiler production. Here, we show thatCampylobacter jejuniandCampylobacter colidiffer in their carriage of antimicrobial resistance and virulence factors may also differ in their ability to persist in litter during consecutive grow-out of broiler flocks. We found that presence/absence of virulence factors needed for evasion of host defense mechanisms and gut colonization played an integral role in differentiatingCampylobacterstrains.

Microbiology↗
DOE OSTI2023

Shell-model calculations for two-neutron transfer near the $N=20$ island of inversion

We describe connections between shell-model calculation results and predictions for two-nucleon transfer reactions. Measurements of the 30 Mg(t,p) 32 Mg reaction were used to identify a low-lying shape-coexisting 0 + state in 32 Mg. Interpretations of those early, limited data were based on simple empirical models. The cross sections for two-nucleon transfer are, however, extremely sensitive to the details of the nuclear-structure. Motivated by the possibility of new high-resolution two-nucleon transfer measurements around the N = 20 Island of Inversion, we have performed shell-model calculations wave functions for states in the nuclei 30,32 Mg using the SDPF-M and SDPF-MU interactions, and from those calculations obtain the two-nucleon transfer amplitudes that we use to predict cross sections for the 28,30 Mg(t,p) 30,32 Mg reactions. The combined results show how the nuclear structure properties influence experimental observables for the (t,p) reaction. We compare our results with the existing data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Nonlinear optimal recovery in Hilbert spaces

Here, this paper investigates solution strategies for nonlinear problems in Hilbert spaces, such as nonlinear partial differential equations (PDEs) in Sobolev spaces, when only finite measurements are available. We formulate this as a nonlinear optimal recovery problem, establishing its well-posedness and proving its convergence to the true solution as the number of measurements increases. However, the resulting formulation might not have a finite-dimensional solution in general. We thus present a sufficient condition for the finite dimensionality of the solution, applicable to problems with well-defined point evaluation measurements. To address the broader setting, we introduce a relaxed nonlinear optimal recovery and provide a detailed convergence analysis. An illustrative example is given to demonstrate that our formulations and theoretical findings offer a comprehensive framework for solving nonlinear problems in infinite-dimensional spaces with limited data.

convergence↗
DOE OSTI2023

Characterization of Cycle-Aged Commercial NMC and NCA Lithium-ion Cells: I. Temperature-Dependent Degradation

Lithium-ion batteries are widely used in applications from consumer electronic devices to stationary energy storage. Appropriate management of batteries is challenging due to limited data on their performance and materials degradation. Previous studies have focused on characterization of single cells under specific operating conditions. In the present work, commercial 18650 lithium-ion cells with LiNi x Mn y Co 1-x-y O 2 (NMC) and LiNi x Co y Al 1-x-y O 2 (NCA) positive electrodes were characterized by a wide range of electrochemical and materials techniques after cycling at 15, 25, or 35 °C to ∼80% capacity. The NCA cells exhibit weak temperature dependence in their cycle aging and materials degradation. The NMC cells exhibited increased capacity fade and materials degradation as ambient temperature decreased. All cells exhibited loss of lithium inventory as their primary degradation mode. However, the NCA cells only showed evidence of solid electrolyte interphase (SEI) growth whereas the NMC cells showed signs of Li plating at 15 °C, transitioning to SEI growth at 35 °C. The NMC cells displayed signs of loss of active material at the positive electrode at lower temperatures, suggesting that Li plating is correlated to additional processes that increase the rate of degradation. These results highlight the importance of avoiding broad generalizations about Li-ion battery temperature dependence.

25 ENERGY STORAGE↗
DOE OSTI2020

Path Properties of Atmospheric Transitions: Illustration with a Low-Order Sudden Stratospheric Warming Model

Many rare weather events, including hurricanes, droughts, and floods, dramatically impact human life. To accurately forecast these events and characterize their climatology requires specialized mathematical techniques to fully leverage the limited data that are available. Here we describe transition path theory (TPT), a framework originally developed for molecular simulation, and argue that it is a useful paradigm for developing mechanistic understanding of rare climate events. TPT provides a method to calculate statistical properties of the paths into the event. As an initial demonstration of the utility of TPT, we analyze a low-order model of sudden stratospheric warming (SSW), a dramatic disturbance to the polar vortex that can induce extreme cold spells at the surface in the midlatitudes. SSW events pose a major challenge for seasonal weather prediction because of their rapid, complex onset and development. Climate models struggle to capture the long-term statistics of SSW, owing to their diversity and intermittent nature. We use a stochastically forced Holton–Mass-type model with two stable states, corresponding to radiative equilibrium and a vacillating SSW-like regime. In this stochastic bistable setting, from certain probabilistic forecasts TPT facilitates estimation of dominant transition pathways and return times of transitions. These “dynamical statistics” are obtained by solving partial differential equations in the model’s phase space. With future application to more complex models, TPT and its constituent quantities promise to improve the predictability of extreme weather events through both generation and principled evaluation of forecasts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Curves, Coriolis, and Cross-Channel Circulation in the Hudson River Estuary

Abstract Despite its relatively small magnitude, cross-channel circulation in estuaries can influence the along-channel momentum balance, dispersion, and transport. We investigate spatial and temporal variation in cross-channel circulation at two contrasting sites in the Hudson River estuary. The two sites differ in the relative strength and direction of Coriolis and curvature forcing. We contrast the patterns and magnitudes of flow at the two sites during varying conditions in stratification driven by tidal amplitude and river discharge. We found well-defined flows during flood tides at both sites, characterized by mainly two-layer structures when the water column was more homogeneous and structures with three or more layers when the water column was more stratified. Ebb tides had generally weaker and less definite flows, except at one site where curvature and Coriolis reinforced each other during spring tide ebbs. Cross-channel currents had similar patterns, but were oppositely directed at the two sites, demonstrating the importance of curvature even in channels with relatively gradual curves. Coriolis and curvature dominated the measured terms in the cross-channel momentum balance. Their combination was generally consistent with driving the observed patterns and directions of flow, but local acceleration and cross-channel advection made some notable contributions. A large residual in the momentum balance indicates that some combination of vertical stress divergence, baroclinic pressure gradients, and along-channel and vertical advection must play an essential role, but data limitations prevented an accurate estimation of these terms. Cross-channel advection affected the along-channel momentum balance at times, with implications for the exchange flow’s strength. Significance Statement Currents that flow across the channel in an estuary move slower than those flowing along the channel, but they can transport materials and change water properties in important ways, affecting human uses of estuaries such as shipping, aquaculture, and recreation. We wanted to better understand cross-channel currents in the Hudson River estuary. We found that larger tides produced the strongest cross-channel currents with a two-layer pattern, compared to weaker currents with three layers during smaller tides. Higher or lower river flow also affected current strength. Comparing two locations, we saw cross-channel currents moving in opposite directions because of differences in the curvature of the river channel. Our results show how channel curvature and Earth’s rotation combine to produce cross-channel currents.

Conley, Margaret M.↗
DOE OSTI2026

Modeling and Calibration of Supplier Selection Problem in Freight Agent-Based Simulations

Freight transportation modeling often struggles with data limitations, especially in accurately representing complex supplier selection processes and their impact on network flows. This research addresses this critical gap by developing a large-scale, calibrated agent-based model for supplier selection, complemented by a probabilistic heuristic for international shipments. Our approach integrates trade relationships between industry sectors, transportation costs, and a supplier-rating model adapted from existing literature. The model’s core objective is to minimize the discrepancy between modeled and observed commodity flows while ensuring a close match to regional shipping distance distributions. Implemented and tested across four major U.S. metropolitan areas—Atlanta, Chicago, Dallas–Fort Worth, and Los Angeles—the model demonstrates high fidelity in replicating observed freight patterns. Key findings reveal consistent alignment with national shipping distance trends and highlight significant spatial variations in commodity trade assignments and demand across the study regions. This behaviorally informed and transport-sensitive framework is designed to approximate real-world decision making, providing a robust tool for policymakers and planners to evaluate targeted interventions, assess infrastructure investments, and enhance supply chain resilience in the face of disruptions.

Ismael, Abdelrahman (ORCID:0000000303712110)↗
DOE OSTI2021

Relaxation behavior in low-frequency complex conductivity of sands caused by bacterial growth and biofilm formation by Shewanella oneidensis under a high-salinity condition

Complex electrical conductivity is increasingly used to monitor subsurface processes associated with microbial activities because microbial cells mostly have surface charges and thus electrical double layers. Although highly saline environments are frequently encountered in coastal and marine sediments, there are limited data available on the complex conductivity associated with microbial activities under a high-salinity condition. Therefore, we have developed the spectral responses of complex conductivity of sand associated with bacterial growth and biofilm formation under a highly saline condition of approximately 1% salinity and approximately 2 S/m pore water conductivity with an emphasis on relaxation behavior. A column test is performed, in which the model bacteria Shewanella oneidensis MR-1 are stimulated for cell growth and biofilm formation in a sand pack, whereas the complex conductivity is monitored from 0.01 Hz to 10 kHz. The test results indicate that the real conductivity increases in the early stage due to the microbial metabolites and the increased surface conduction with cell growth but soon begin to decrease because of the reduction of charge passages due to bioclogging. However, the imaginary conductivity significantly increases with time, and clear bell-shaped relaxation behaviors are observed with the peak frequency of 0.1–1 Hz, associated with the double-layer polarization of cells and electrically conductive pili and biofilms. The Cole-Cole relaxation model appears to capture such relaxation behaviors well, and the modeling results indicate gradual increases in normalized chargeability and decreases in relaxation time during bacterial growth and biofilm formation in the highly saline condition. Comparison with previous literature confirms that the high-salinity condition further increases the normalized chargeability, whereas it suppresses the phase shift and thus the imaginary conductivity. Our results suggest that the complex conductivity can effectively capture microbial biomass formation in sands under a highly saline condition.

58 GEOSCIENCES↗
DOE OSTI2023

Enabling AI in synthetic biology through Construction File specification

The Construction File (CF) specification establishes a standardized interface for molecular biology operations, laying a foundation for automation and enhanced efficiency in experiment design. It is implemented across three distinct software projects: PyDNA_CF_Simulator, a Python project featuring a ChatGPT plugin for interactive parsing and simulating experiments; ConstructionFileSimulator, a field-tested Java project that showcases 'Experiment' objects expressed as flat files; and C6-Tools, a JavaScript project integrated with Google Sheets via Apps Script, providing a user-friendly interface for authoring and simulation of CF. The CF specification not only standardizes and modularizes molecular biology operations but also promotes collaboration, automation, and reuse, significantly reducing potential errors. The potential integration of CF with artificial intelligence, particularly GPT-4, suggests innovative automation strategies for synthetic biology. While challenges such as token limits, data storage, and biosecurity remain, proposed solutions promise a way forward in harnessing AI for experiment design. This shift from human-driven design to AI-assisted workflows, steered by high-level objectives, charts a potential future path in synthetic biology, envisioning an environment where complexities are managed more effectively.

59 BASIC BIOLOGICAL SCIENCES↗