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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A minimal SufB 2 C 2 complex functions as a [4Fe-4S] cluster scaffold in methanogenic archaea

Iron-sulfur clusters are essential cofactors in all domains of life, yet their biogenesis in obligately anaerobic archaea remains poorly understood. Here, we characterized the minimal two-protein SUF system in methanogenic archaea, composed solely of SufB and SufC. Using Methanococcus maripaludis as a model, we demonstrate that the SUF proteins from its native host form a stable SufB 2 C 2 heterotetramer that binds a [4Fe-4S] cluster via three conserved cysteines in SufC. Mutations of conserved cysteine and histidine residues of SufB do not impair cluster binding. The complex interacts with the SAM-containing methanogenesis marker protein 10 (MmpX), suggesting direct Fe-S cluster transfer from SufB 2 C 2 to target proteins. Mutational analysis of Methanothermococcus thermolithotrophicus proteins confirmed that SufC is the primary cluster-binding component, while SufB enhances ATPase and cluster transfer activities. Evolutionary comparisons suggest that this two-protein SUF system represents an ancestral form of Fe-S cluster biogenesis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data

Zero-shot and prompt-based models have excelled at visual reasoning tasks by leveraging large-scale natural image corpora, but they often fail on sparse and domain-specific scientific image data. We introduce Zenesis, a no-code interactive computer vision platform designed to reduce data readiness bottlenecks in scientific imaging workflows. Zenesis integrates lightweight multimodal adaptation for zero-shot inference on raw scientific data, human-in-the-loop refinement, and heuristic-based temporal enhancement. We validate our approach on Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) datasets of catalyst-loaded membranes. Zenesis outperforms baselines, achieving an average accuracy of 0.947, Intersection over Union (IoU) of 0.858, and Dice score of 0.923 on amorphous catalyst samples; and 0.987 accuracy, 0.857 IoU, and 0.923 Dice on crystalline samples. These results represent a significant performance gain over conventional methods such as Otsu thresholding and standalone models like the Segment Anything Model (SAM). Zenesis enables effective image segmentation in domains where annotated datasets are limited, offering a scalable solution for scientific discovery.

Mukherjee, Shubhabrata↗
DOE OSTI2020

reV (The Renewable Energy Potential Model - Open Source) [SWR-21-59, SWR-20-20 and SWR-17-34]

The Renewable Energy Potential (reV) model is a platform for the detailed assessment of renewable energy resources and their geospatial intersection with grid infrastructure and land use characteristics. The reV model currently supports photovoltaic (PV), concentrating solar power (CSP), and land-based wind turbine technologies. Modules in the reV framework function at different spatial and temporal resolutions, allowing for the assessment of resource potential, technical potential, and supply curves at varying levels of detail. The platform runs on the National Renewable Energy Laboratory’s (NREL’s) high-performance computing system, providing scalable and efficient performance from a single location up to a continent, for a single year or decades of time-series resource data. Coupled with NREL’s System Advisor Model (SAM), reV supports resource assessments from 5-minute to hourly temporal resolutions and supports the analysis of long-term (i.e., year-on-year) variability of renewable generation (e.g., interannual variability and exceedance probabilities).

Maclaurin, Galen↗
DOE OSTI2021

Explainable Neural Architecture Search (XNAS)

Code for the paper Learning Interpretable Models Through Multi-Objective Neural Architecture Search by Zachariah Carmichael, Tim Moon, and Sam Ade Jacobs. Monumental advances in deep learning have led to unprecedented achievements across a multitude of domains. While the performance of deep neural networks is indubitable, the architectural design and interpretability of such models are nontrivial. Research has been introduced to automate the design of neural network architectures through neural architecture search (NAS). Recent progress has made these methods more pragmatic by exploiting distributed computation and novel optimization algorithms. However, there is little work in optimizing architectures for interpretability. To this end, we propose a multiobjective distributed NAS framework that optimizes for both task performance and introspection. We leverage the non-dominated sorting genetic algorithm (NSGA-II) and explainable AI (XAI) techniques to reward architectures that can be better comprehended by humans. The framework is evaluated on several image classification datasets. We demonstrate that jointly optimizing for introspection ability and task error leads to more disentangled architectures that perform within tolerable error.

Carmichael, ZachariahJ↗
DOE OSTI2024

pnnl/SuperSAM

Our SuperSAM approach transforms the Segment Anything Model (SAM) into an `elastic' supernetwork, enabling the derivation of subnetworks with varying architectures tailored to a wide range of resource constraints.

Tallent, Nathan↗
DOE OSTI2024

test-grid-buildouts [SWR-23-112]

Test-grid-buildouts is a set of notebooks for creating buildouts of synthetic transmission grids with various levels of renewable energy. Workflows can be used to augment various test grid with varying levels of wind/solar generation. Aggregated renewable energy time series (actuals and scenarios) at grid buses can then be used for various transmission grid operation problems. Highly customizable workflow consists of parsing of synthetic grid files, setting up SAM & reV simulations, application of exclusion masks, creating of custom renewable generators on the grid, aggregating of power time series, and writing of modified grid description files.

Satkauskas, Ignas↗
DOE OSTI2025

fife-utils

This is a collection of scripts related to the FIFE project at Fermilab, including utiltities for performing bulk oprations with our SAM and MetaCat (github)data handling systems. The most heavily used is the fife_launch/fife_wrap script pair, which is used to convert physics analysis executables into distributed grid jobs.

Mengel, Marc [Fermi National Accelerator Laborator↗
DOE OSTI2021

Convective and turbulent motions in non-precipitating Cu. Part 1: Method of separation of convective and turbulent motions

Atmospheric motions in clouds and cloud surroundings have a wide range of scales, from several kilometers to centimeters. These motions have different impacts on cloud dynamics and microphysics. Larger-scale motions (hereafter referred to as convective motions) are responsible for mass transport over distances comparable with cloud scale, while motions of smaller scales (hereafter referred to as turbulent motions) are stochastic and responsible for mixing and cloud dilution. This distinction substantially simplifies the analysis of dynamic and microphysical processes in clouds. The present research is Part I of the study aimed at describing the method for separating the motion scale into a convective component and a turbulent component. An idealized flow is constructed, which is a sum of an initially prescribed field of the convective velocity with updrafts in the cloud core and downdrafts outside the core, and a stochastic turbulent velocity field obeying the turbulent properties, including the -5/3 law and the 2/3 structure function law. A wavelet method is developed allowing separation of the velocity field into the convective and turbulent components, with parameter values being in a good agreement with those prescribed initially. The efficiency of the method is demonstrated by an example of a vertical velocity field of a cumulus cloud simulated using the System for Atmospheric Modeling (SAM) with bin microphysics and resolution of 10 m. It is shown that vertical velocity in clouds indeed can be represented as a sum of convective velocity (forming zone of cloud updrafts and subsiding shell) and a stochastic velocity obeying laws of homogeneous and isotropic turbulence.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Shallow Cumulus Properties as Captured by Adiabatic Fraction in High-Resolution LES Simulations

Abstract Shallow convective clouds are important players in Earth’s energy budget and hydrological cycle, and are abundant in the tropical and subtropical belts. They greatly contribute to the uncertainty in climate predictions due to their unresolved, complex processes that include coupling between the dynamics and microphysics. Analysis of cloud structure can be simplified by considering cloud motions as a combination of moist adiabatic motions like adiabatic updrafts and turbulent motions leading to deviation from adiabaticity. In this work, we study the sizes and occurrence of adiabatic regions in shallow cumulus clouds during their growth and mature stages, and use the adiabatic fraction (AF) as a continuous metric to describe cloud processes and properties from the core to the edge. To do so, we simulate isolated trade wind cumulus clouds of different sizes using the System of Atmospheric Modeling (SAM) model in high resolution (10 m) with the Hebrew University spectral bin microphysics (SBM). The fine features in the clouds’ dynamics and microphysics, including small near-adiabatic volumes and a thin transition zone at the edge of the cloud (∼20–40 m in width), are captured. The AF is shown to be an efficient measure for analyzing cloud properties and key processes determining the droplet-size distribution formation and shape during the cloud evolution. Physical processes governing the properties of droplet size distributions at different cloud regions (e.g., core, edge) are analyzed in relation to AF. Significance Statement 1) This study investigates the evolution of cumulus clouds (Cu) using a 10-m-resolution LES model with spectral bin microphysics. 2) The study improves the understanding of the mutual effects of adiabatic updrafts and lateral entrainment and mixing. 3) The study demonstrates the existence of an adiabatic core in nonprecipitating Cu. 4) Shapes of the droplet size distributions are closely related to the adiabatic fraction values. 5) Utilization of high resolution reveals the existence of physically significant small features in the cloud structure, such as a narrow cloud interface zone and small adiabatic volumes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Convective and Turbulent Motions in Nonprecipitating Cu. Part III: Characteristics of Turbulence Motions

Velocity field in a nonprecipitating Cu under BOMEX conditions, simulated by SAM with 10-m resolution and spectral bin microphysics is separated into the convective part and the turbulent part, using a wavelet filtering. In Part II of the study properties of convective motions of this Cu were investigated. Here in Part III of the study, the parameters of cloud turbulence are calculated in the cloud updraft zone at different stages of cloud development. The main points of this study are (i) application of a fine-scale LES model of a single convective cloud allowed a direct estimation of turbulence parameters using the resolved flow in the cloud and (ii) the separation of the resolved flow into the turbulence flow and the nonturbulence flow allowed us to estimate different turbulent parameters with sufficient statistical accuracy. We calculated height and time dependences of the main turbulent parameters such as turbulence kinetic energy (TKE), spectra of TKE, dissipation rate, and the turbulent coefficient. It was found that the main source of turbulence in the cloud is buoyancy whose contribution is described by the buoyancy production term (BPT). The shear production term (SPT) increases with height and reaches its maximum near cloud top, and so does BPT. In agreement with the behavior of BPT and SPT, turbulence in the lower cloud part (below the inversion level) is weak and hardly affects the processes of mixing and entrainment. The fact that BPT is larger than SPT determines many properties of cloud turbulence. For instance, the turbulence is nonisotropic, so the vertical component of TKE is substantially larger than the horizontal components. Another consequence of the fact that BPT is larger than STP manifests itself in the finding that the turbulence spectrum largely obeys the -11/5 Bolgiano–Obukhov scaling. The classical Kolmogorov -5/3 scaling dominates for the low part of a cloud largely at the dissolving stage of cloud evolution. Using the spectra obtained we evaluated an “effective” dissipation rate which increases with height from nearly zero at cloud base up to 20 cm 2 s -3 near cloud top. The coefficient of turbulent diffusion was found to increase with height and ranged from 5 m 2 s -1 near cloud base to 25 m 2 s -1 near cloud top. In conclusion, the possible role of turbulence in the process of lateral entrainment and mixing is discussed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

An Investigation of LES Wall Modeling for Rayleigh–Bénard Convection via Interpretable and Physics-Aware Feedforward Neural Networks with DNS

Abstract The traditional approach of using the Monin–Obukhov similarity theory (MOST) to model near-surface processes in large-eddy simulations (LESs) can lead to significant errors in natural convection. In this study, we propose an alternative approach based on feedforward neural networks (FNNs) trained on output from direct numerical simulation (DNS). To evaluate the performance, we conduct both a priori and a posteriori tests. In the a priori (offline) tests, we compare the statistics of the surface shear stress and heat flux, computed from filtered DNS input variables, to the stress and flux obtained from the filtered DNS. Additionally, we investigate the importance of various input features using the Shapley additive explanations value and the conditional average of the filter grid cells. In the a posteriori (online) tests, we implement the trained models in the System for Atmospheric Modeling (SAM) LES and compare the LES-generated surface shear stress and heat flux with those in the DNS. Our findings reveal that vertical velocity, a traditionally overlooked flow quantity, is one of the most important input features for determining the wall fluxes. Increasing the number of input features improves the a priori test results but does not always improve the model performance in the a posteriori tests because of the differences in input variables between the LES and DNS. Last, we show that physics-aware FNN models trained with logarithmic and scaled parameters can well extrapolate to more intense convection scenarios than in the training dataset, whereas those trained with primitive flow quantities cannot. Significance Statement The traditional near-surface turbulence model, based on a shear-dominated boundary layer flow, does not represent near-surface turbulence in natural convection. Using a feedforward neural network (FNN), we can construct a more accurate model that better represents the near-surface turbulence in various flows and reveals previously overlooked controlling factors and process interactions. Our study shows that the FNN-generated models outperform the traditional model and highlight the importance of the near-surface vertical velocity. Furthermore, the physics-aware FNN models exhibit the potential to extrapolate to convective flows of various intensities beyond the range of the training dataset, suggesting their broader applicability for more accurate modeling of near-surface turbulence.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Causal Interactions between Southern Ocean Polynyas and High-Latitude Atmosphere–Ocean Variability

Abstract Weddell Sea open-ocean polynyas have been observed to occasionally release heat from the deep ocean to the atmosphere, indicating that their sporadic appearances may be an important feature of high-latitude atmosphere–ocean variability. Yet, observations of the phenomenon are sparse and many standard-resolution models represent these features poorly, if at all. We use a fully coupled, synoptic-scale preindustrial control simulation of the Energy Exascale Earth System Model (E3SMv0-HR) to effectively simulate open-ocean polynyas and investigate their role in the climate system. Our approach employs statistical tests of Granger causality to diagnose local and remote drivers of, and responses to, polynya heat loss on interannual to decadal time scales. First, we find that polynya heat loss Granger causes a persistent increase in surface air temperature over the Weddell Sea, strengthening the local cyclonic wind circulation. Along with responding to polynyas, atmospheric conditions also facilitate their development. When the Southern Ocean experiences a rapid poleward shift in the circumpolar westerlies following a prolonged negative phase of the southern annular mode (SAM), Weddell Sea salinity increases, promoting density destratification and convection in the water column. Finally, we find that the reduction of surface heat fluxes during periods of full ice cover is not fully compensated by ocean heat transport into the high latitudes. This imbalance leads to a buildup of ocean heat content that supplies polynya heat loss. These results disentangle the complex, coupled climate processes that both enable the polynya’s existence and respond to it, providing insights to improve the representation of these highly episodic sea ice features in climate models.

Kaufman, Zachary S.↗
DOE OSTI2020

Role of Tropical Variability in Driving Decadal Shifts in the Southern Hemisphere Summertime Eddy-Driven Jet

The Southern Hemisphere summertime eddy-driven jet and storm tracks have shifted poleward over the recent few decades. In previous studies, explanations have mainly stressed the influence of external forcing in driving this trend. Here we examine the role of internal tropical SST variability in controlling the austral summer jet’s poleward migration, with a focus on interdecadal time scales. The role of external forcing and internal variability are isolated by using a hierarchy of Community Earth System Model version 1 (CESM1) simulations, including the pre-industrial control, large ensemble, and pacemaker runs. Model simulations suggest that in the early twenty-first century, both external forcing and internal tropical Pacific SST variability are important in driving a positive southern annular mode (SAM) phase and a poleward migration of the eddy-driven jet. Tropical Pacific SST variability, associated with the negative phase of the interdecadal Pacific oscillation (IPO), acts to shift the jet poleward over the southern Indian and southwestern Pacific Oceans and intensify the jet in the southeastern Pacific basin, while external forcing drives a significant poleward jet shift in the South Atlantic basin. In response to both external forcing and decadal Pacific SST variability, the transient eddy momentum flux convergence belt in the middle latitudes experiences a poleward migration due to the enhanced meridional temperature gradient, leading to a zonally symmetric southward migration of the eddy-driven jet. This mechanism distinguishes the influence of the IPO on the midlatitude circulation from the dynamical impact of ENSO, with the latter mainly promoting the subtropical wave-breaking critical latitude poleward and pushing the midlatitude jet to higher latitudes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Representation of Modes of Variability in Six U.S. Climate Models

We compare the performance of several modes of variability across six U.S. climate modeling groups, with a focus on identifying robust improvements in recent models [including those participating in phase 6 of the Coupled Model Intercomparison Project (CMIP)] compared to previous versions. In particular, we examine the representation of the Madden–Julian oscillation (MJO), El Niño–Southern Oscillation (ENSO), the Pacific decadal oscillation (PDO), the quasi-biennial oscillation (QBO) in the tropical stratosphere, and the dominant modes of extratropical variability, including the southern annular mode (SAM), the northern annular mode (NAM) [and the closely related North Atlantic Oscillation (NAO)], and the Pacific–North American pattern (PNA). Where feasible, we explore the processes driving these improvements through the use of “intermediary” experiments that utilize model versions between CMIP3/5 and CMIP6 as well as targeted sensitivity experiments in which individual modeling parameters are altered. We find clear and systematic improvements in the MJO and QBO and in the teleconnection patterns associated with the PDO and ENSO. Some gains arise from better process representation, while others (e.g., the QBO) from higher resolution that allows for a greater range of interactions. Our results demonstrate that the incremental development processes in multiple climate model groups lead to more realistic simulations over time.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Benchmarking performance changes in the simulation of extratropical modes of variability across CMIP generations

In this work, we evaluate extratropical modes of variability in the three most recent phases of the Coupled Model Intercomparison Project (CMIP3, 5, and 6) to gauge improvement of climate models over time. A suite of high-level metrics is employed to objectively evaluate how well climate models simulate the qobserved Northern Annular Mode (NAM), North Atlantic Oscillation (NAO), Pacific North America pattern (PNA), Southern Annular Mode (SAM), Pacific Decadal Oscillation (PDO), North Pacific Oscillation (NPO), and North Pacific Gyre Oscillation (NPGO). We apply a Common Basis Function (CBF) approach that projects model anomalies onto observed empirical orthogonal functions (EOFs), together with the traditional EOF approach, to CMIP Historical and AMIP models. We find simulated spatial patterns of those modes have been significantly improved in the newer models, although the skill improvement is sensitive to the mode and season considered. We identify some potential contributions to the pattern improvement of certain modes (e.g., the Southern Hemisphere jet and High-top vertical coordinate), however the performance changes are likely attributed to gradual improvement of the base climate and multiple relevant processes. Less performance improvement is evident in the mode amplitude of these modes and systematic overestimation of the mode amplitude in spring remains in the newer climate models. We find that the post-dominant season amplitude errors in atmospheric modes are not limited to coupled runs but are often already evident in AMIP simulations. This suggests that rectifying the egregious post-dominant season amplitude errors found in many models can be addressed in an atmospheric-only framework making it more tractable to address in the model development process.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Differential Credibility of Climate Modes in CMIP6

This work quantitatively evaluates the fidelity with which the northern annular mode (NAM), southern annular mode (SAM), Pacific–North American pattern (PNA), El Niño–Southern Oscillation (ENSO), Pacific decadal oscillation (PDO), Atlantic multidecadal oscillation (AMO), and the first-order mode interactions are represented in Earth system model (ESM) output from the CMIP6 archive. Several skill metrics are used as part of a differential credibility assessment (DCA) of both spatial and temporal characteristics of the modes across ESMs, ESM families, and specific ESM realizations relative to ERA5. The spatial patterns and probability distributions are generally well represented but skill scores that measure the degree to which the frequencies of maximum variance are captured are consistently lower for most ESMs and climate modes. Substantial variability in skill scores manifests across realizations from individual ESMs for the PNA and oceanic modes. Further, the ESMs consistently overestimate the strength of the NAM–PNA first-order interaction and underestimate the NAM–AMO connection. Furthermore, these results suggest that the choice of ESM and ESM realizations will continue to play a critical role in determining climate projections at the global and regional scale at least in the near term.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Life Cycle of Major Sudden Stratospheric Warmings in the Southern Hemisphere from a Multimillennial GCM Simulation

Abstract Sudden stratospheric warmings (SSWs) are rare in the Southern Hemisphere (SH), making it difficult to study possible precursors or subsequent impacts. Using a multimillennial coupled climate model simulation producing 161 SSWs in the SH, we present a detailed study of their life cycle. We show that SH SSWs are predominantly displacement events forced by wave-1 planetary waves, and that a surface signature similar to the negative phase of the Southern Annular Mode (SAM) is detectable up to two months before the onset date, but there is a tendency for a transition from wave 1 before to zonally symmetric anomalies after onset. We identify a strong weakening of the Amundsen Sea low as one of the most prominent precursors, which weakens the climatological wave-2 and wave-3 stationary waves and strengthens wave-1 forcing. Compared to their northern counterparts, SH SSWs generally have a longer time scale, and while there is evidence of pre-onset forcing related to tropical sea surface temperatures, the Indian Ocean dipole is more important than El Niño–Southern Oscillation. Significance Statement Sudden stratospheric warmings (SSWs) are extreme events where the winter polar stratosphere warms within a few days to temperatures usually only experienced in summer. These events are rare in the Southern Hemisphere. Therefore, both the observational record and standard climate model simulations are not enough to understand how SSWs develop, or how they might change surface weather. Here we use very long global climate simulations that produce a large number of SSWs in the Southern Hemisphere to study the development and impact of these events. This includes possible precursors as well as the influence they have on surface weather after they occur.

Meteorology & Atmospheric Sciences↗
DOE OSTI2022

Neutronics and thermal-hydraulics simulation of generic pebble-bed fluoride-salt-cooled high-temperature reactor (gFHR)

The fluoride-salt-cooled high-temperature reactor (FHR) is one type of the advanced reactors and has been attracting great interest from the research institutes and commercial companies in the recent years. However, currently the technology is relatively immature. To facilitate the design and safety analysis of FHRs, Kairos Power published the generic FHR (gFHR) benchmark. In this paper, a hybrid method combining the stochastic code and deterministic code is developed to simulate the gFHR benchmark. Serpent 2 is employed as a few-group cross section generator and the cross sections are applied to the finite difference neutron diffusion code AGREE. A good consistency with the gFHR benchmark is achieved. The agreement between the Serpent 2 results and the AGREE results shows that the hybrid method is applicable to FHRs. The thermal-hydraulics are coupled to neutronics for the steady-state calculations and good agreement between AGREE and SAM is achieved. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗