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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 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
NASA NTRS1980

Tectonic stress - Models and magnitudes

It is shown that global data on directions of principal stresses in plate interiors can serve as a test of possible plate tectonic force models. Such tests performed to date favor force models in which ridge pushing forces play a significant role. For such models the general magnitude of regional deviatoric stresses is comparable to the 200-300 bar compressive stress exerted by spreading ridges. An alternative approach to estimating magnitudes of regional deviatoric stresses from stress orientations is to seek regions of local stress either demonstrably smaller than or larger than the regional stresses. The regional stresses in oceanic intraplate regions are larger than the 100-bar compression exerted by the Ninetyeast Ridge and less than the bending stresses (not less than 1 kbar) beneath Hawaii.

Solomon, S. C.↗
DOE OSTI2026

Modelling the Sensitivity of Yukon River Biogeochemical Dynamics to Environmental and Chemical Drivers: Implications for Dissolved Organic Carbon

Riverine dissolved organic carbon (DOC) is a critical biogeochemical component that transmits information from Arctic soils to the Arctic Ocean, significantly influencing carbon dynamics in this unique ecosystem. As DOC travels downstream, it undergoes transformations that alter its composition and fate. The Yukon River serves as an effective testbed for modelling these dynamics, offering sufficient scale to capture key biogeochemical processes while having a simpler hydrology than other major Arctic rivers, as well as long-term DOC observational data for model validation. To investigate DOC transformations during transit in the Yukon River, we adapted our Arctic Riverine Organic Macromolecular Model by applying regional-specific parameterisations. Our model simulates the transport and transformation of 15 organic macromolecules, including CDOM (coloured dissolved organic matter), proteins, polysaccharides, lipids, lignin phenols, and humic substances. Initial DOC concentrations were derived from observed soil organic carbon stocks in the surrounding watershed, while chemical transformations and hydrological dynamics were modelled along the river's course. Sensitivity and uncertainty analyses were conducted using a Monte Carlo approach under two experimental setups. Results revealed that variability in DOC and CDOM concentrations at the river mouth were predominantly driven by initial DOC concentration (~70% of variability explained) and dilution at confluence points (~10%). The refractory fraction of DOC explained 21%–88% of the variability in 14 macromolecular concentrations and ranked in the top five sensitive parameters for all outputs when a uniform parameter distribution was assumed. However, when a more likely variability was applied to this parameter, its influence on DOC and CDOM decreased. Given that refractory DOC accounts for ~80% of total DOC in Arctic Rivers, this suggests that most DOC resists degradation and retains its chemical composition during transport to the coastal environment. River velocity, which determines residence time, explained 8%–47% of the variability in protein, polysaccharide, lipid, pigments, and lignin phenols at the river mouth. In contrast, chemical turnover times contributed only 1%–5% to output variability. Our findings underscore the need for improved land-specific headwater observations, including seasonal soil moisture and lateral transport dynamics that control the initial tributary-specific DOC inputs. With accelerated permafrost thaw and increasing river discharge, extending our model to other Arctic River systems and seasons will enhance understanding of Arctic riverine carbon fluxes and their contributions to the Arctic Ocean.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Step-loaded creep testing of Zircaloy-4 cladding at higher temperatures in the α-phase

A refined understanding of zirconium-based cladding thermomechanical performance during rapid transients is essential for enhancing the safety and operation of light-water reactors. Traditional models for zirconium alloys under accident conditions generally assume that creep dominates fuel cladding performance. Here, these historic models have largely remained unchanged and serve as the basis for safety criteria development. As the U.S. nuclear industry pursues higher burnup levels, the increased release of fission gases during transients raises the risk of cladding failure in the low-temperature hcp α-phase, making the fidelity of these models of greater importance. Creep testing was conducted from 550–700°C with 25–120 MPa applied hoop stresses to investigate Zircaloy-4 deformation at accident-relevant temperatures in the α-phase. Step-loading was employed to capture creep behavior across a wide stress range from a single sample. The stress-strain rate data at higher temperatures (650 and 700°C) were well-described by isotropic versions of the Erbacher and Kaddour models, while the lower temperature data (550 and 600°C) were underpredicted by both anisotropic and isotropic model variants. Greater strain rates during the initial loading step at 650 and 700°C were attributed to recrystallization and grain growth of sub-micron crystallites. Yet, texture analysis revealed the basal split texture remained after testing. These observations produced results suggesting Zircaloy-4 claddings experience higher creep rates across the α-phase than previously thought, possibly related to dynamic anisotropy due to temperature dependent activation of deformation mechanisms, effects of biaxial loading, and variation in material condition between the current testing used in previous model development.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Identifying synoptic controls on boundary layer thermodynamic and cloud properties in a regional forecast model

Although most of our understanding of boundary layer cloudiness is based on idealized, subtropical, barotropic marine environments, boundary layer clouds exist across a range of conditions. In this study, we use the Naval Research Laboratory's Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS) and an automated cold-front-relative analysis framework to explore the boundary layer structure associated with low clouds across a transect through the cold front of a midlatitude synoptic cyclone. The model credibly captures boundary layer structure in line with conceptual models of midlatitude cyclones and ground-based observations at Graciosa Island in the Azores. The warm sector is conditionally unstable, with clouds that are too shallow and with too little liquid water, compared to cloud property retrievals from satellite and surface-based instruments. The cold-frontal region exhibits convection associated with weak stability and ascent. Northwest of the cold front, the boundary layer is well mixed, deeper, and capped by a strong inversion maintained by large-scale subsidence. Simulated clouds in frontal and post-frontal regions are mostly too thick, with too much liquid water and too little cloud base drizzle. The post-frontal clouds are associated with grid-scale updrafts, which appear to be the model's attempt to represent mesoscale organization of cellular convection typically observed in the cold sector of midlatitude cyclones. The deep, well-mixed post-frontal boundary layers and cloudiness are maintained by strong surface fluxes, as in cold air outbreaks. Our analysis framework serves as a unique approach to model verification, and our results offer insights into differences in boundary layer cloud behavior between subtropical and synoptic cold-sector regimes.

Eissner, Jordan M. [Univ. of Kansas, Lawrence, KS ↗
DOE OSTI2019

An Integrated Hydrological Model for Long-Term Monitoring in Tims Branch Watershed, SC - 19435

The Tims Branch watershed in Savannah River Site (SRS), South Carolina is a small-scale watershed that has been impacted by contaminated runoff and discharge wastewater from nuclear research facilities located within the watershed over the past century. Innovative remediation technologies, such as tin injection and pump and treat, have been implemented to remove heavy metals and volatile organic compounds (VOCs) from the watershed. Today, the Tims Branch watershed serves as a test-bed for monitoring the performance of remediation activities. This study describes the development of the two-dimensional integrated surface water/groundwater model for Tims Branch watershed to assess the impact of cleanup activities on hydrological processes in this watershed. This model will serve as a tool to simulate the effect of climatic events on overland flow distribution and further on will be used to assess contaminant transport. This paper illustrates the application of the developed model for simulation of overland flow depth and velocity in Tims Branch watershed and streamflow in A-014 outfall tributary. The watershed includes the second order Tims Branch stream, several outfalls, and a network of tributaries. Simulation of non-calibrated overland flow was conducted for the years 2016 using available stream flow data within the watershed. Recent flow data from a newly deployed stage gauge was also used to assess the model results. The results show the model ability to simulate overland flow and stream flow and can be used as a tool to represent the hydrological conditions in the Tims Branch watershed. The results of this model simulation will be further used to develop contaminant transport model. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Surrogate modeling of Cellular-Potts agent-based models as a segmentation task using the U-Net neural network architecture

The Cellular-Potts model is a powerful and ubiquitous framework for developing computational models for simulating complex multicellular biological systems. Cellular-Potts models (CPMs) are often computationally expensive due to the explicit modeling of interactions among large numbers of individual model agents and diffusive fields described by partial differential equations (PDEs). In this work, we develop a convolutional neural network (CNN) surrogate model using a U-Net architecture that accounts for periodic boundary conditions. We use this model to accelerate the evaluation of a mechanistic CPM previously used to investigate in vitro vasculogenesis. The surrogate model was trained to predict 100 computational steps ahead (Monte-Carlo steps, MCS), accelerating simulation evaluations by a factor of 562 times compared to single-core CPM code execution on CPU. Over short timescales of up to 3 recursive evaluations, or 300 MCS, our model captures the emergent behaviors demonstrated by the original Cellular-Potts model such as vessel sprouting, extension and anastomosis, and contraction of vascular lacunae. This approach demonstrates the potential for deep learning to serve as a step toward efficient surrogate models for CPM simulations, enabling faster evaluation of computationally expensive CPM simulations of biological processes.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1990

Numerical prediction of turbulent flame stability in premixed/prevaporized (HSCT) combustors

A numerical analysis of combustion instabilities that induce flashback in a lean, premixed, prevaporized dump combustor is performed. KIVA-II, a finite volume CFD code for the modeling of transient, multidimensional, chemically reactive flows, serves as the principal analytical tool. The experiment of Proctor and T'ien is used as a reference for developing the computational model. An experimentally derived combustion instability mechanism is presented on the basis of the observations of Proctor and T'ien and other investigators of instabilities in low speed (M less than 0.1) dump combustors. The analysis comprises two independent procedures that begin from a calculated stable flame: The first is a linear increase of the equivalence ratio and the second is the linear decrease of the inflow velocity. The objective is to observe changes in the aerothermochemical features of the flow field prior to flashback. It was found that only the linear increase of the equivalence ratio elicits a calculated flashback result. Though this result did not exhibit large scale coherent vortices in the turbulent shear layer coincident with a flame flickering mode as was observed experimentally, there were interesting acoustic effects which were resolved quite well in the calculation. A discussion of the k-e turbulence model used by KIVA-II is prompted by the absence of combustion instabilities in the model as the inflow velocity is linearly decreased. Finally, recommendations are made for further numerical analysis that may improve correlation with experimentally observed combustion instabilities.

Winowich, Nicholas S.↗
NASA NTRS1994

Competition between pressure and gravity confinement in Lyman Alpha forest observations

A break in the distribution function of Lyman Alpha clouds (at a typical redshift of 2.5) has been reported by Petit-jean et al. (1993). This feature is what would be expected from a transition between pressure confinement and gravity confinement (as predicted in Charlton, Salpeter & Hogan 1993). The column density at which the feature occurs has been used to determine the external confining pressure approximately 10 per cu cm K, which could be due to a hot, intergalactic medium. For models that provide a good fit to the data, the contribution of the gas in clouds to omega is small. The specific shape of the distribution function at the transition (predicted by models to have a nonmonotonic slope) can serve as a diagnostic of the distribution of dark matter around Lyman Alpha forest clouds, and the present data already eliminate certain models.

Charlton, Jane C.↗
NASA NTRS2012

QuakeSim 2.0

QuakeSim 2.0 improves understanding of earthquake processes by providing modeling tools and integrating model applications and various heterogeneous data sources within a Web services environment. QuakeSim is a multisource, synergistic, data-intensive environment for modeling the behavior of earthquake faults individually, and as part of complex interacting systems. Remotely sensed geodetic data products may be explored, compared with faults and landscape features, mined by pattern analysis applications, and integrated with models and pattern analysis applications in a rich Web-based and visualization environment. Integration of heterogeneous data products with pattern informatics tools enables efficient development of models. Federated database components and visualization tools allow rapid exploration of large datasets, while pattern informatics enables identification of subtle, but important, features in large data sets. QuakeSim is valuable for earthquake investigations and modeling in its current state, and also serves as a prototype and nucleus for broader systems under development. The framework provides access to physics-based simulation tools that model the earthquake cycle and related crustal deformation. Spaceborne GPS and Inter ferometric Synthetic Aperture (InSAR) data provide information on near-term crustal deformation, while paleoseismic geologic data provide longerterm information on earthquake fault processes. These data sources are integrated into QuakeSim's QuakeTables database system, and are accessible by users or various model applications. UAVSAR repeat pass interferometry data products are added to the QuakeTables database, and are available through a browseable map interface or Representational State Transfer (REST) interfaces. Model applications can retrieve data from Quake Tables, or from third-party GPS velocity data services; alternatively, users can manually input parameters into the models. Pattern analysis of GPS and seismicity data has proved useful for mid-term forecasting of earthquakes, and for detecting subtle changes in crustal deformation. The GPS time series analysis has also proved useful as a data-quality tool, enabling the discovery of station anomalies and data processing and distribution errors. Improved visualization tools enable more efficient data exploration and understanding. Tools provide flexibility to science users for exploring data in new ways through download links, but also facilitate standard, intuitive, and routine uses for science users and end users such as emergency responders.

Donnellan, Andrea↗
DOE OSTI2024

Nanosecond Transient Validation of Surge Arrester Models to Predict Electromagnetic Pulse Response

The impact of high-altitude electromagnetic pulse events on the electric grid is not fully understood, and validated modeling of mitigations, such as lightning surge arresters (LSAs) is necessary to predict the propagation of very fast transients on the grid. Experimental validation of high frequency models for surge arresters is an active area of research. Further, this article serves to experimentally validate a previously defined ZnO LSA model using four metal-oxide varistor pucks and nanosecond scale pulses to measure voltage and current responses. The SPICE circuit models of the pucks showed good predictability when compared to the measured arrester response when accounting for a testbed inductance of approximately 100 nH. Additionally, the comparatively high capacitance of low-profile arresters show a favorable response to high-speed transients that indicates the potential for effective electromagnetic pulse mitigation with future materials design.

42 ENGINEERING↗
NASA NTRS2017

Quantifying the Causes of Differences in Tropospheric OH Within Global Models

The hydroxyl radical (OH) is the primary daytime oxidant in the troposphere and provides the main loss mechanism for many pollutants and greenhouse gases, including methane (CH4). Global mean tropospheric OH differs by as much as 80% among various global models, for reasons that are not well understood. We use neural networks (NNs), trained using archived output from eight chemical transport models (CTMs) that participated in the Polar Study using Aircraft, Remote Sensing, Surface Measurements and Models, of Climate, Chemistry, Aerosols and Transport Model Intercomparison Project (POLMIP), to quantify the factors responsible for differences in tropospheric OH and resulting CH4 lifetime (Tau CH4) between these models. Annual average Tau CH4, for loss by OH only, ranges from 8.0 to 11.6 years for the eight POLMIP CTMs. The factors driving these differences were quantified by inputting 3-D chemical fields from one CTM into the trained NN of another CTM. Across all CTMs, the largest mean differences in Tau CH4 (Delta Tau CH4) result from variations in chemical mechanisms (Delta Tau CH4 = 0.46 years), the photolysis frequency (J) of O3 yields O(D-1) (0.31 years), local O3 (0.30 years), and CO (0.23 years). The Delta Tau CH4 due to CTM differences in NO(x) (NO + NO2) is relatively low (0.17 years), although large regional variation in OH between the CTMs is attributed to NO(x). Differences in isoprene and J(NO2) have negligible overall effect on globally averaged tropospheric OH, although the extent of OH variations due to each factor depends on the model being examined. This study demonstrates that NNs can serve as a useful tool for quantifying why tropospheric OH varies between global models, provided that essential chemical fields are archived.

Surface Measurements and Models↗
DOE OSTI2025

WRF-ELM v1.0: a regional climate model to study land–atmosphere interactions over heterogeneous land use regions

Abstract. The Energy Exascale Earth System Model (E3SM) Land Model (ELM) is a state-of-the-art land surface model that simulates the intricate interactions between the terrestrial land surface and other components of the Earth system. Originating from the Community Land Model (CLM) version 4.5, ELM has been under active development, with added new features and functionality, including plant hydraulics, radiation–topography interaction, subsurface multiphase flow, and more explicit land use and management practices. This study integrates ELM v2.1 with the Weather Research and Forecasting (WRF; WRF-ELM) model through a modified Lightweight Infrastructure for Land Atmosphere Coupling (LILAC) framework, enabling affordable high-resolution regional modeling by leveraging ELM's innovative features alongside WRF's diverse atmospheric parameterization options. This framework includes a top-level driver for variable communication between WRF and ELM and Earth System Modeling Framework (ESMF) caps for the WRF atmospheric component and ELM workflow control, encompassing initialization, execution, and finalization. Importantly, this LILAC–ESMF framework demonstrates a more modular approach compared to previous coupling efforts between WRF and land surface models. It maintains the integrity of ELM's source code structure and facilitates the transfer of future developments in ELM to WRF-ELM. To test the ability of the coupled model to capture land–atmosphere interactions over regions with a variety of land uses and land covers, we conducted high-resolution (4 km) WRF-ELM ensemble simulations over the Great Lakes region (GLR) in the summer of 2018 and systematically compared the results against observations, reanalysis data, and WRF-CTSM (WRF coupled with the Community Terrestrial Systems Model). In general, the coupled WRF-ELM model has reasonably captured the spatial distribution of surface state variables and fluxes across the GLR, particularly over the natural vegetation areas. The evaluation results provide a baseline reference for further improvements in ELM in the regional application of high-resolution weather and climate predictions. Our work serves as an example to the model development community for expanding an advanced land surface model's capability to represent fully-coupled land–atmosphere interactions at fine spatial scales. The development and release of WRF-ELM marks a significant advancement for the ELM user community, providing opportunities for fine-scale regional representation, parameter calibration in coupled mode, and examination of new schemes with atmospheric feedback.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

ENSO Tropical Cloud and TOA radiative signatures from the CERES observation

The Clouds and the Earth's Radiant Energy System (CERES) project now has over 15 years accurately observed top-of-the-atmosphere (TOA) flux record for climate monitoring and diagnostic studies. The CERES flux-by-cloud-type dataset, which contains cloud properties and radiative fluxes for 42 cloud types sorted by cloud top pressure and cloud optical depth, is used to investigate the clouds and their associated TOA (top-of-the-atmosphere) fluxes changes over the tropical area during ENSO events during the observed period. Unlike past studies, this study shows the impact of ENSO on cloud properties like optical depth, cloud top effective pressure and temperature and TOA LW and SW fluxes for each sub cloud type. The study reveals the detailed contributions from different cloud types for radiative characteristics during different phases of ENSO. This is especially important for very small net TOA radiative balance due to the cancellation of the fluxes from different cloud types. To further demonstrate the usefulness of this dataset, NCAR Community Atmosphere Model (CAM) is used to simulate the cloud and radiative changes during the period. The model cloud properties are converted to MODIS like cloud properties using modified MODIS simulator. The dataset serves as a more stringent validation of the model for cloud properties and radiative fluxes.

Moguo Sun↗
NASA NTRS1974

Direct integration transmittance model

A transmittance model has been developed for interpretation of high spectral resolution measurements of laboratory absorption and of planetary thermal emission. The high spectral resolution requires transmittances to be computed monochromatically by summing the contribution of individual molecular absorption lines. A magnetic tape atlas of H2O, O3, and CO2 molecular line parameters serves as input to the transmittance model with simple empirical representations used for continuum regions wherever suitable laboratory data exist. The theoretical formulation of the transmittance model and the computational procedures used for the evaluation of the transmittances are discussed, and application of the model to several homogeneous-path laboratory absorption examples is demonstrated.

Kunde, V. G.↗
NASA NTRS2021

Passive Microwave Brightness Temperature Assimilation to Improve Snow Mass Estimation across Complex Terrain in Pakistan, Afghanistan, and Tajikistan

An ensemble Kalman filter is used to assimilate Advanced Microwave Scanning Radiometer-2 (AMSR2) observations of passive microwave (PMW) brightness temperatures (spectral differences, ΔT b ) into land surface model estimates of snow mass over northwestern high mountain Asia (HMA). Trained support vector machines serve as the observation operator and map the geophysical modeled variables into ΔT b space within the assimilation framework. Evaluation of the assimilation routine is carried out through comparison of assimilated snow mass estimates with an in situ dataset. The assimilation framework helps improve the land surface model estimates through PMW ΔT b assimilation, particularly in terms of decreasing the domain-wide bias. The assimilation framework proved more effective during the (dry) snow accumulation season and decreased the bias and root-mean-square error (RMSE) in snow mass estimates at 76% and 58% of the comparative pixels, respectively. During the snow ablation season, the PMW brightness temperature signal contained less information related to snow mass due to the presence of other concurrent geophysical features that effectively serve as noise during the snow mass update. The utilization of PMW ΔT b for accurate snow mass estimation in complex terrain such as HMA is dependent on a multitude of factors for optimal results; however, it does add utility to the land surface model if the relevant pitfalls are taken into consideration prior to the state variable update.

Jawairia Ahmad↗
NASA NTRS2003

Radar Reflectivity Simulated by a 2-D Spectra Bin Model: Sensitivity of Cloud-aerosol Interaction

The Goddard Cumulus Ensemble (GCE) model with bin spectra microphysics is used to simulate mesoscale convective systems.The model uses explicit bins to represent size spectra of cloud nuclei, water drops, ice crystals, snow and graupel. Each hydrometeorite category is described by 33 mass bins. The simulations provide a unique data set of simulated raindrop size distribution in a realistic dynamic frame. Calculations of radar parameters using simulated drop size distribution serve as an evaluation of numerical model performance. In addition, the GCE bin spectra modes is a very useful tool to study uncertainties related to radar observations; all the environmental parameters are precisely known. In this presentation, we concentrate on the discussion of Z-R (ZDR-R) relation in the simulated systems. Due to computational limitations, the spectra bin model has been run in two dimensions with 31 stretched vertical layers and 1026 horizontal grid points (1 km resolution). Two different cases, one in midlatitude continent, the other in tropical ocean, have been simulated. The continental case is a strong convection which lasted for two hours. The oceanic case is a persistent system with more than 10 hours' life span. It is shown that the simulated Z-R (ZDR-R) relations generally agree with observations using radar and rain gauge data. The spatial and temporal variations of Z-R relation in different locations are also analyzed. Impact of aerosols on cloud formation and raindrop size distribution was studied. Both clean (low CCN) and dirty (high CCN) cases are simulated. The Z-R relation is shown to vary considerable in the initial CCN concentrations.

Li, Kiaowen↗
NASA NTRS1973

Direct integration transmittance model

A transmittance model was developed for the 200-2000/cm region for interpretation of high spectral resolution measurements of laboratory absorption and of planetary thermal emission. The high spectral resolution requires transmittances to be computed monochromatically by summing the contribution of individual molecular absorption lines. A magnetic tape atlas of H2O,O3, and CO2 molecular line parameters serves as input to the transmittance model with simple empirical representations used for continuum regions wherever suitable laboratory data exist. The theoretical formulation of the transmittance model and the computational procedures used for the evaluation of the transmittances are discussed. Application is demonstrated of the model to several homogenous path laboratory absorption examples.

Kunde, V. G.↗
NASA NTRS1981

A meteorologically driven grain sorghum stress indicator model

A grain sorghum soil moisture and temperature stress model is described. It was developed to serve as a meteorological data filter to alert commodity analysts to potential stress conditions and crop phenology in selected grain sorghum production areas. The model also identifies optimum conditions on a daily basis and planting/harvest problems associated with poor tractability.

Taylor, T. W.↗