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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Freshwater Biogeochemical Hotspots: High Primary Production and Ecosystem Respiration in Shallow Waterbodies

Abstract Ponds, wetlands, and shallow lakes (collectively “shallow waterbodies”) are among the most biogeochemically active freshwater ecosystems. Measurements of gross primary production (GPP), respiration (R), and net ecosystem production (NEP) are rare in shallow waterbodies compared to larger and deeper lakes, which can bias our understanding of lentic ecosystem processes. In this study, we calculated GPP, R, and NEP in 26 small, shallow waterbodies across temperate North America and Europe. We observed high rates of GPP (mean 8.4 g O 2 m −3 d −1 ) and R (mean −9.1 g O 2 m −3 d −1 ), while NEP varied from net heterotrophic to autotrophic. Metabolism rates were affected by depth and aquatic vegetation cover, and the shallowest waterbodies had the highest GPP, R, and the most variable NEP. The shallow waterbodies from this study had considerably higher metabolism rates compared to deeper lakes, stressing the importance of these systems as highly productive biogeochemical hotspots.

Geology↗
DOE OSTI2024

Cepheids with giant companions: II. Spectroscopic confirmation of nine new double-lined binary systems composed of two Cepheids

Context.Binary Cepheids with giant companions are crucial for studying the physical properties of Cepheid variables, in particular providing the best means to measure their masses. Systems composed of two Cepheids are even more important, but to date, only one such system has been identified, in the Large Magellanic Cloud (LMC). Aims.Our current aim is to increase the number of these systems known tenfold and to provide their basic characteristics. The final goal is to obtain the physical properties of the component Cepheids, including their masses and radii, and to learn about their evolution in the multiple systems, also revealing their origin. Methods.We started a spectroscopic monitoring campaign of nine unresolved pairs of Cepheids from the OGLE catalog to check if they are gravitationally bound. Two of these so-called double Cepheids are located in the LMC, five are in the Small Magellanic Cloud (SMC), and two are in the Milky Way (MW). Results.We report a spectroscopic detection of the binarity of all nine of these double Cepheids with orbital periods ranging from 2 to 18 years. This increases the number of known binary double (BIND) Cepheids from 1 to 10 and triples the number of all confirmed double-lined binary (SB2) Cepheids. For five BIND Cepheids, the disentangled pulsational light curves of the components show anti-correlated phase shifts due to orbital motion. We show the first empirical evidence that typical period–luminosity relations (PLRs) are rather binary Cepheid PLRs, as they include light of the companion. Conclusions.The statistics of pulsation period ratios of BIND Cepheids do not agree with those expected for pairs of Cepheids of the same age. These ratios together with the determined mass ratios far from unity suggest a merger origin of at least one component for about half of the systems. The SMC and MW objects are the first found in SB2 systems composed of giants in their host galaxies. The Milky Way BIND Cepheids are also the closest such systems, being located at about 11 and 26 kpc.

Astronomy & Astrophysics↗
DOE OSTI2023

Understanding uncertainties in projections of western North Pacific tropical cyclogenesis

Reliable projections of tropical cyclone (TC) activities in the western North Pacific (WNP) are crucial for climate policy-making in densely-populated coastal Asia. Existing projections, however, exhibit considerable uncertainties with unclear sources. Here, based on future projections by the latest Coupled Model Intercomparison Project Phase 6 climate models, we identify a new and prevailing source of uncertainty arising from different TC identification schemes. Notable differences in projections of detected TCs and empirical genesis potential indices are found to be caused by inconsistent changes in dynamic and thermodynamic environmental factors affecting TC formations. While model uncertainty holds the secondary importance, we show large potential in reducing it through improved model simulations of present-day TC characteristics. Internal variability noticeably impacts near-term projections of the WNP tropical cyclogenesis, while the relative contribution of scenario uncertainty remains small. Our findings provide valuable insights into model development and TC projections, thereby aiding in adaptation decisions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Thermophysical modeling of raw glaze liquidus temperature and viscosity

Raw glazes, which do not contain pre-melted glass frits, are widely used due to their low cost. The natural variability of the mineral compositions used in raw glazes affects their viscosity during firing. Molten glaze viscosity plays an important role in determining the final surface quality; therefore, it is important to determine how raw glaze composition and firing conditions affect viscosity. Thermophysical modeling provides a way to evaluate the liquidus temperature and viscosity of molten glazes as a function of composition and oxygen activity. Equilibrium phase volume fraction and composition of 242 raw glaze recipes were evaluated under oxidizing and reducing conditions. Undissolved or precipitation of solid phases explain the secondary flux transition from anti-fluxing to fluxing near the liquidus temperature. The liquidus temperature and viscosity of iron glazes decrease as a function of increasing iron content under a reducing atmosphere. The empirical probability distribution of molten glaze viscosity follows a lognormal distribution, with lead glazes having significantly lower viscosity compared with glazes without lead. Here, the peak firing temperature viscosity of lead-free glazes is near the working point of glass. Multiple linear regression analysis shows that the peak firing temperature viscosity and liquidus temperature significantly predict the viscosity factor.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Machine Learning Approach for Spatiotemporal Multivariate Optimization of Environmental Monitoring Sensor Locations

Abstract Long-term environmental monitoring is critical for managing the soil and groundwater at contaminated sites. Recent improvements in state-of-the-art sensor technology, communication networks, and artificial intelligence have created opportunities to modernize this monitoring activity for automated, fast, robust, and predictive monitoring. In such modernization, it is required that sensor locations be optimized to capture the spatiotemporal dynamics of all monitoring variables as well as to make it cost-effective. The legacy monitoring datasets of the target area are important to perform this optimization. In this study, we have developed a machine-learning approach to optimize sensor locations for soil and groundwater monitoring based on ensemble supervised learning and majority voting. For spatial optimization, Gaussian process regression (GPR) is used for spatial interpolation, while the majority voting is applied to accommodate the multivariate temporal dimension. Results show that the algorithms significantly outperform the random selection of the sensor locations for predictive spatiotemporal interpolation. While the method has been applied to a four-dimensional dataset (with two-dimensional space, time, and multiple contaminants), we anticipate that it can be generalizable to higher-dimensional datasets for environmental monitoring sensor location optimization.

Siddiquee, Masudur R.↗
DOE OSTI2020

A Conceptual Framework to Describe Energy Efficiency and Demand Response Interactions

Energy efficiency (EE) and demand response (DR) resources provide important utility system and ratepayer benefits. At the same time, the rapid change in the amount and type of variable renewable energy, like solar and wind, is reshaping the role and economic value of EE and DR, and will likely affect time-dependent valuation of EE and DR measures. Utilities are increasingly interested in integrating EE and DR measures and technologies (as well as other distributed energy resources) as a strategic approach to improve their collective cost-effectiveness and performance. However, the specific EE and DR features that may be best integrated, the interplay between changing EE and DR resource potential, and the resulting utility system impacts, are not well understood. We develop a framework to identify the EE and DR attributes, system conditions, and technological factors that are likely to drive interactions between EE and DR. We apply the framework to example measures with different technology specifics (e.g., presence of controls, building type, and targeted end use) in the context of different system conditions (e.g., peak demand, load-building periods during high renewable generation output). Ultimately, the framework defines EE and DR interactions not only by the change in discretionary load (i.e., DR potential) but also by the change in likelihood of participation in EE and DR programs—as well as the change in system need for, and the overall availability of, EE and DR resources. The framework is intended to improve the integration of EE and DR in utility operational and planning activities.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

LandRAY Final Report

The overarching Project objective is to demonstrate the feasibility of using an innovative Power Take-Off (PTO) Module, to be used in the Columbia Power Technologies, Inc. (C·Power) utility-scale wave energy converter (WEC). The PTO Module uniquely combines a large-diameter, direct-drive, rotary permanent magnet generator; a patent-pending rail-bearing system; and a corrosion-resistant fiber-reinforced-plastic structure. The rail bearing system allows for: • A flexible non-rigid and low-cost generator frame as compared to conventional machines. • A reduction of air gap and consequently lower cost electromagnetic design • Ability to reduce costs by increasing diameter to much larger dimensions, while maintaining the small air gap. • A direct drive electro-mechanical solution that is the fastest and most precise approach for responding to the dynamic variability of forces from wave energy. The land-based test of the PTO Module (DDP1) will provide an important risk reduction phase, to demonstrate the reliability and feasibility of a large-diameter, small air-gap generator that is capable of delivering high efficiency, fault-tolerance and relatively simple "at-sea" maintenance capabilities – qualities that are essential for cost-effective wave energy devices. This is the first known test of such a system.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

A Conceptual Framework to Describe Energy Efficiency and Demand Response Interactions

Energy efficiency (EE) and demand response (DR) resources provide important utility systems and ratepayer benefits. At the same time, the rapid change in the amount and type of variable renewable energy, like solar and wind, is reshaping the role and economic value of EE and DR, and will likely affect the time-dependent valuation of EE and DR measures. Utilities are increasingly interested in integrating EE and DR measures as a strategic approach to improve their collective cost-effectiveness and performance. We develop a framework to identify the EE and DR attributes, system conditions, and technological factors that are likely to drive interactions between EE and DR. We apply the framework to example measures with different technology specifics in the context of different utility system conditions. We find that EE and DR interactions are likely driven by changes in discretionary load, the addition of controls or other capabilities to shift loads, and the coincidence of savings with system peak or load building periods. Our analysis suggests increasing complexity in evaluating EE and DR interactions when moving from standalone equipment to integrated systems. The framework can be applied to research on integrated building systems by grouping measures into portfolios with different likely implications for EE and DR interactions.

Satchwell, Andrew J. (ORCID:0000000244053599)↗
DOE OSTI2025

Fungal Spore Seasons Advanced Across the US Over Two Decades of Climate Change

Abstract Phenological shifts due to climate change have been extensively studied in plants and animals. Yet, the responses of fungal spores—organisms important to ecosystems and major airborne allergens—remain understudied. This knowledge gap limits our understanding of their ecological and public health implications. To address this, we analyzed a long‐term (2003–2022), large‐scale (the continental US) data set of airborne fungal spores collected by the US National Allergy Bureau. We first pre‐processed the spore data by gap‐filling and smoothing. Afterward, we extracted 10 metrics describing the phenology (e.g., start and end of season) and intensity (e.g., peak concentration and integral) of fungal spore seasons. These metrics were derived using two complementary but not mutually exclusive approaches—ecological and public health approaches, defined as percentiles of total spore concentration and allergenic thresholds of spore concentration, respectively. Using linear mixed‐effects models, we quantified annual shifts in these metrics across the continental US. We revealed a significant advancement in the onset of the spore seasons defined in both ecological (11 days, 95% confidence interval: 0.4–23 days) and public health (22 days, 6–38 days) approaches over two decades. Meanwhile, total spore concentrations in an annual cycle and in a spore allergy season tended to decrease over time. The earlier start of the spore season was significantly correlated with climatic variables, such as warmer temperatures and altered precipitations. Overall, our findings suggest possible climate‐driven advanced fungal spore seasons, highlighting the importance of climate change mitigation and adaptation in public health decision‐making.

Environmental Sciences & Ecology↗
DOE OSTI2022

Propagating Parameter Uncertainty in Power System Nonlinear Dynamic Simulations Using a Koopman Operator-Based Surrogate Model

In this work, we propose a Koopman operator-based surrogate model for propagating parameter uncertainties in power system nonlinear dynamic simulations. First, we augment a priori known state-space model by reformulating parameters deemed uncertain as pseudo-state variables. Then, we apply the Koopman operator theory to the resulting state-space model and obtain a linear dynamical system model. This transformation allows us to analyze the evolution of the system dynamics through its Koopman eigenfunctions, eigenvalues, and modes. Of particular importance for this letter, the obtained linear dynamical system is a surrogate that enables the evaluation of parameter uncertainties by simply perturbing the initial conditions of the Koopman eigenfunctions associated with the pseudo-state variables. Simulations carried out on the New England test system reveal the excellent performance of the proposed method in terms of accuracy and computational efficiency.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Testing the reliability of interpretable neural networks in geoscience using the Madden–Julian oscillation

Abstract. We test the reliability of two neural network interpretation techniques, backward optimization and layerwise relevance propagation, within geoscientific applications by applying them to a commonly studied geophysical phenomenon, the Madden–Julian oscillation. The Madden–Julian oscillation is a multi-scale pattern within the tropical atmosphere that has been extensively studied over the past decades, which makes it an ideal test case to ensure the interpretability methods can recover the current state of knowledge regarding its spatial structure. The neural networks can, indeed, reproduce the current state of knowledge and can also provide new insights into the seasonality of the Madden–Julian oscillation and its relationships with atmospheric state variables. The neural network identifies the phase of the Madden–Julian oscillation twice as accurately as a linear regression approach, which means that nonlinearities used by the neural network are important to the structure of the Madden–Julian oscillation. Interpretations of the neural network show that it accurately captures the spatial structures of the Madden–Julian oscillation, suggest that the nonlinearities of the Madden–Julian oscillation are manifested through the uniqueness of each event, and offer physically meaningful insights into its relationship with atmospheric state variables. We also use the interpretations to identify the seasonality of the Madden–Julian oscillation and find that the conventionally defined extended seasons should be shifted later by 1 month. More generally, this study suggests that neural networks can be reliably interpreted for geoscientific applications and may thereby serve as a dependable method for testing geoscientific hypotheses.

58 GEOSCIENCES↗
DOE OSTI2025

Spatial Replication Is Important for Developing Landscape Genetic Inferences for a Wetland Salamander

Habitat fragmentation is a pressing threat to wildlife populations, and maintenance of gene flow between populations is an essential goal of conservation. Resistance surfaces have emerged as an important tool for modelling connectivity and developing management strategies to mitigate effects of habitat fragmentation. However, recent studies have noted inconsistencies in the factors most strongly associated with connectivity across different landscapes. Thus, replication of genetic-based resistance surface optimisation across landscapes may be necessary for making robust conclusions about the influence of environmental variables. Accordingly, replication represents a substantive challenge and opportunity in the field of landscape genetics. In this study, we conducted replicated landscape genetic analyses across five landscapes in Tennessee and Kentucky for a threatened wetland amphibian, the four-toed salamander (Hemidactylium scutatum). We tested multiple hypotheses of how different landscape features that could directly affect small, desiccation-intolerant amphibians (e.g., canopy cover) influenced gene flow and assessed the appropriate scale at which to model different features. We found some concordance in the landscape features that influenced gene flow (e.g., a common importance of forest cover and topography), but also some differences—potentially owing to the difference in variability of predictors across landscapes. We also found discordance in the scale of effect of different features across landscapes. In conclusion, our work emphasises that flat areas of moist forest not bisected by roads may be important for H. scutatum conservation, and our replicated design allows us to identify relationships that would have been missed if only using one study site.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Mechanisms of Zn removal from water by amorphous geopolymer: Molecular-level insights from X-ray absorption spectroscopy, isotope fractionation, and surface complexation modeling

Porous geopolymers have attracted widespread attention as promising heavy metal adsorbents that can be synthesized from aluminosilicate solid wastes. However, the precise microstructural evidence for adsorbed heavy metals on geopolymers remains unclear due to the insensitivity of conventional characterization techniques on minerals with amorphous structure and surface disorder. Batch adsorption and column experiments coupled with X-ray absorption spectroscopy (XAS), Zn stable isotope, and surface complexation model (SCM) were employed to reveal the Zn removal mechanisms with coal fly ash porous geopolymer (CFAPG) at a molecular scale. The macroscopic kinetic and isothermal adsorption of Zn on CFAPG were well described by the pseudo-second-order model and Bi_Langmuir equation, respectively, indicating the presence of abundant heterogeneous active sites on the CFAPG surface. Further, two types of active sites on the CFAPG surface were identified by XAS coupled with Zn isotopes in batch experiments at pH <= 6.0: one is pH-dependent and associated with tetrahedral zinc coordi-nation, and the other is pH-insensitive and associated with octahedral zinc coordination; these sites were confirmed by the bidentate SCM as the variable charge site (surface complexation, >S-OH) and the permanent negative charge site (cation exchange, >X - ), respectively. Furthermore, the important contribution of surface co -precipitation besides surface complexation and cation exchange to the Zn adsorption on CFAPG was identified by XAS coupled with SCM in a flow-through column experiment at pH >6.0. These investigations provide a systemic understanding of the Zn adsorption mechanisms on CFAPG and an SCM reference for the application and prediction of geopolymers in heavy metal-contaminated water remediations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

The DOE E3SM Model Version 2: Overview of the Physical Model and Initial Model Evaluation

Abstract This work documents version two of the Department of Energy's Energy Exascale Earth System Model (E3SM). E3SMv2 is a significant evolution from its predecessor E3SMv1, resulting in a model that is nearly twice as fast and with a simulated climate that is improved in many metrics. We describe the physical climate model in its lower horizontal resolution configuration consisting of 110 km atmosphere, 165 km land, 0.5° river routing model, and an ocean and sea ice with mesh spacing varying between 60 km in the mid‐latitudes and 30 km at the equator and poles. The model performance is evaluated with Coupled Model Intercomparison Project Phase 6 Diagnosis, Evaluation, and Characterization of Klima simulations augmented with historical simulations as well as simulations to evaluate impacts of different forcing agents. The simulated climate has many realistic features of the climate system, with notable improvements in clouds and precipitation compared to E3SMv1. E3SMv1 suffered from an excessively high equilibrium climate sensitivity (ECS) of 5.3 K. In E3SMv2, ECS is reduced to 4.0 K which is now within the plausible range based on a recent World Climate Research Program assessment. However, a number of important biases remain including a weak Atlantic Meridional Overturning Circulation, deficiencies in the characteristics and spectral distribution of tropical atmospheric variability, and a significant underestimation of the observed warming in the second half of the historical period. An analysis of single‐forcing simulations indicates that correcting the historical temperature bias would require a substantial reduction in the magnitude of the aerosol‐related forcing.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Regime-Dependence of Nocturnal Nitrate Formation via N 2 O 5 Hydrolysis and Its Implication for Mitigating Nitrate Pollution

The heterogeneous hydrolysis of dinitrogen pentoxide (N 2 O 5 ) is an important pathway in nitrate formation; however, its formation rate and relative contribution to total particulate nitrate (pNO 3 - ) are highly variable. Here we report that nocturnal pNO 3 - formation via N 2 O 5 hydrolysis is dependent on the regime defined by the ratio of NO 2 to O 3 . Nocturnal pNO 3 - formation via N 2 O 5 hydrolysis is suppressed in an O 3 -limited regime but enhanced in a NO 2 -limited regime. The results have crucial implications for effective control of nitrate pollution in the future. An exclusive decrease in NO 2 will decrease nocturnal pNO 3 - formation in a NO 2 -limited regime but may be less effective or even increase nocturnal pNO 3 - formation in an O 3 -limited regime.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

BeyondPlanck: I. Global Bayesian analysis of the Planck Low Frequency Instrument data

We describe the BEYONDPLANCK project in terms of our motivation, methodology, and main products, and provide a guide to a set of companion papers that describe each result in more detail. Building directly on experience from ESA’s Planck mission, we implemented a complete end-to-end Bayesian analysis framework for the Planck Low Frequency Instrument (LFI) observations. The primary product is a full joint posterior distribution P(ω | d), where ω represents the set of all free instrumental (gain, correlated noise, bandpass, etc.), astrophysical (synchrotron, free-free, thermal dust emission, etc.), and cosmological (cosmic microwave background – CMB – map, power spectrum, etc.) parameters. Some notable advantages of this approach compared to a traditional pipeline procedure are seamless end-to-end propagation of uncertainties; accurate modeling of both astrophysical and instrumental effects in the most natural basis for each uncertain quantity; optimized computational costs with little or no need for intermediate human interaction between various analysis steps; and a complete overview of the entire analysis process within one single framework. As a practical demonstration of this framework, we focus in particular on low-ℓ CMB polarization reconstruction with Planck LFI. In this process, we identify several important new effects that have not been accounted for in previous pipelines, including gain over-smoothing and time-variable and non-1/f correlated noise in the 30 and 44 GHz channels. Modeling and mitigating both previously known and newly discovered systematic effects, we find that all results are consistent with the ΛCDM model, and we constrained the reionization optical depth to τ = 0.066 ± 0.013, with a low-resolution CMB-based χ 2 probability to exceed of 32%. This uncertainty is about 30% larger than the official pipelines, arising from taking a more complete instrumental model into account. The marginal CMB solar dipole amplitude is 3362.7 ± 1.4 μK, where the error bar was derived directly from the posterior distribution without the need of any ad hoc instrumental corrections. We are currently not aware of any significant unmodeled systematic effects remaining in the Planck LFI data, and, for the first time, the 44 GHz channel is fully exploited in the current analysis. We argue that this framework can play a central role in the analysis of many current and future high-sensitivity CMB experiments, including LiteBIRD, and it will serve as the computational foundation of the emerging community-wide COSMOGLOBE effort, which aims to combine state-of-the-art radio, microwave, and submillimeter data sets into one global astrophysical model.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

An open-source framework for balancing computational speed and fidelity in production cost models

Studies of bulk power system operations need to incorporate uncertainty and sensitivity analyses, especially around exposure to weather and climate variability and extremes, but this remains a computational modeling challenge. Commercial production cost models (PCMs) have shorter runtimes, but also important limitations (opacity, license restrictions) that do not fully support stochastic simulation. Open-source PCMs represent a potential solution. They allow for multiple, simultaneous runs in high-performance computing environments and offer flexibility in model parameterization. Yet, developers must balance computational speed (i.e. runtime) with model fidelity (i.e. accuracy). In this paper, we present Grid Operations (GO), a framework for instantiating open-source, scale-adaptive PCMs. GO allows users to search across parameter spaces to identify model versions that appropriately balance computational speed and fidelity based on experimental needs and resource limits. Results provide generalizable insights on how to navigate the fidelity and computational speed tradeoff through parameter selection. We show that models with coarser network topologies can accurately mimic market operations, sometimes better than higher-resolution models. It is thus possible to conduct large simulation experiments that characterize operational risks related to climate and weather extremes while maintaining sufficient model accuracy.

42 ENGINEERING↗
DOE OSTI2020

Coherent photon coincidence spectroscopy of single quantum systems

In this report nonequilibrium photon correlations of coherently excited single quantum systems can reveal their internal quantum dynamics and provide spectroscopic access. Here we propose and discuss the fundamentals of a coherent photon coincidence spectroscopy based on the application of laser pulses with variable delay and the detection of a time-averaged two-photon coincidence rate. For demonstration, two simple but important cases, i.e., an exciton-biexciton in a quantum dot and two coupled quantum emitters, are investigated based on quantum dynamics simulations demonstrating that this nonlinear spectroscopy reveals information specific to the particular single quantum system.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗