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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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

A Goddard Multi-Scale Modeling System with Unified Physics

A multi-scale modeling system with unified physics has been developed at NASA Goddard Space Flight Center (GSFC). The system consists of an MMF, the coupled NASA Goddard finite-volume GCM (fvGCM) and Goddard Cumulus Ensemble model (GCE, a CRM); the state-of-the-art Weather Research and Forecasting model (WRF) and the stand alone GCE. These models can share the same microphysical schemes, radiation (including explicitly calculated cloud optical properties), and surface models that have been developed, improved and tested for different environments. In this talk, I will present: (1) A brief review on GCE model and its applications on the impact of the aerosol on deep precipitation processes, (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) A discussion on the Goddard WRF version (its developments and applications). We are also performing the inline tracer calculation to comprehend the physical processes (i.e., boundary layer and each quadrant in the boundary layer) related to the development and structure of hurricanes and mesoscale convective systems. In addition, high - resolution (spatial. 2km, and temporal, I minute) visualization showing the model results will be presented.

Tao, Wei-Kuo↗
DOE OSTI2024

Ice-shelf freshwater triggers for the Filchner–Ronne Ice Shelf melt tipping point in a global ocean–sea-ice model

Some ocean modeling studies have identified a potential tipping point from a low to a high basal melt regime beneath the Filchner–Ronne Ice Shelf (FRIS), Antarctica, with significant implications for subsequent Antarctic ice sheet mass loss. To date, investigation of the climate drivers and impacts of this possible event have been limited because ice-shelf cavities and ice-shelf melting are only now starting to be included in global climate models. Using a global ocean–sea-ice configuration of the Energy Exascale Earth System Model (E3SM) that represents both ocean circulations and melting within ice-shelf cavities, we explore freshwater triggers (iceberg melt and ice-shelf basal melt) of a transition to a high-melt regime at FRIS in a low-resolution (30 km in the Southern Ocean) global ocean–sea-ice model. We find that a realistic spatial distribution of iceberg melt fluxes is necessary to prevent the FRIS melt regime change from unrealistically occurring under historical-reanalysis-based atmospheric forcing. Further, improvement of the default parameterization for mesoscale eddy mixing significantly reduces a large regional fresh bias and weak Antarctic Slope Front structure, both of which precondition the model to melt regime change. Using two different stable model con figurations, we explore the sensitivity of FRIS melt regime change to regional ice-sheet freshwater fluxes. Through a series of sensitivity experiments prescribing incrementally increasing melt rates from the smaller, neighboring ice shelves in the eastern Weddell Sea, we demonstrate the potential for an ice-shelf melt “domino effect” should the upstream ice shelves experience increased melt rates. The experiments also reveal that modest ice-shelf melt biases in a model, especially at coarse ocean resolution where narrow continental shelf dynamics are not well resolved, can lead to an unrealistic melt regime change at downstream ice shelves. Thus, we find that remote connections between melt fluxes at different ice shelves are sensitive to baseline model conditions. Our results highlight both the potential and the peril of simulating prognostic Antarctic ice-shelf melt rates in a low-resolution global model.

58 GEOSCIENCES↗
DOE OSTI2024

Ice-shelf freshwater triggers for the Filchner–Ronne Ice Shelf melt tipping point in a global ocean–sea-ice model

Abstract. Some ocean modeling studies have identified a potential tipping point from a low to a high basal melt regime beneath the Filchner–Ronne Ice Shelf (FRIS), Antarctica, with significant implications for subsequent Antarctic ice sheet mass loss. To date, investigation of the climate drivers and impacts of this possible event have been limited because ice-shelf cavities and ice-shelf melting are only now starting to be included in global climate models. Using a global ocean–sea-ice configuration of the Energy Exascale Earth System Model (E3SM) that represents both ocean circulations and melting within ice-shelf cavities, we explore freshwater triggers (iceberg melt and ice-shelf basal melt) of a transition to a high-melt regime at FRIS in a low-resolution (30 km in the Southern Ocean) global ocean–sea-ice model. We find that a realistic spatial distribution of iceberg melt fluxes is necessary to prevent the FRIS melt regime change from unrealistically occurring under historical-reanalysis-based atmospheric forcing. Further, improvement of the default parameterization for mesoscale eddy mixing significantly reduces a large regional fresh bias and weak Antarctic Slope Front structure, both of which precondition the model to melt regime change. Using two different stable model configurations, we explore the sensitivity of FRIS melt regime change to regional ice-sheet freshwater fluxes. Through a series of sensitivity experiments prescribing incrementally increasing melt rates from the smaller, neighboring ice shelves in the eastern Weddell Sea, we demonstrate the potential for an ice-shelf melt “domino effect” should the upstream ice shelves experience increased melt rates. The experiments also reveal that modest ice-shelf melt biases in a model, especially at coarse ocean resolution where narrow continental shelf dynamics are not well resolved, can lead to an unrealistic melt regime change at downstream ice shelves. Thus, we find that remote connections between melt fluxes at different ice shelves are sensitive to baseline model conditions. Our results highlight both the potential and the peril of simulating prognostic Antarctic ice-shelf melt rates in a low-resolution global model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Mesoscale structural gradients in human tooth enamel

The outstanding mechanical and chemical properties of dental enamel emerge from its complex hierarchical architecture. An accurate, detailed multiscale model of the structure and composition of enamel is important for understanding lesion formation in tooth decay (dental caries), enamel development (amelogenesis) and associated pathologies (e.g., amelogenesis imperfecta or molar hypomineralization), and minimally invasive dentistry. Although features at length scales smaller than 100 nm (individual crystallites) and greater than 50 µm (multiple rods) are well understood, competing field of view and sampling considerations have hindered exploration of mesoscale features, i.e., at the level of single enamel rods and the interrod enamel (1 to 10 µm). Here, we combine synchrotron X-ray diffraction at submicrometer resolution, analysis of crystallite orientation distribution, and unsupervised machine learning to show that crystallographic parameters differ between rod head and rod tail/interrod enamel. This variation strongly suggests that crystallites in different microarchitectural domains also differ in their composition. Thus, we use a dilute linear model to predict the concentrations of minority ions in hydroxylapatite (Mg 2+ and CO 3 2- /Na + ) that plausibly explain the observed lattice parameter variations. While differences within samples are highly significant and of similar magnitude, absolute values and the sign of the effect for some crystallographic parameters show interindividual variation that warrants further investigation. In conclusion, by revealing additional complexity at the rod/interrod level of human enamel and leaving open the possibility of modulation across larger length scales, these results inform future investigations into mechanisms governing amelogenesis and introduce another feature to consider when modeling the mechanical and chemical performance of enamel.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2001

Dynamical Interpolation of Mesoscale Flows in the TOPEX/Poseidon Diamond Surrounding the U.S. Joint Global Ocean Flux Study Bermuda Atlantic Time-Series Study Site

An open boundary ocean model is configured in a domain bounded by the four TOPEX/Poseidon (T/P) ground tracks surrounding the US Joint Global Ocean Flux Study Bermuda Atlantic Time-Series Study (BATS) site. This implementation facilitates prescription of model boundary conditions directly from altimetric measurements (both TIP and ERS-2). The expected error characteristics for a domain of this size with periodically updated boundary conditions are established with idealized numerical experiments using simulated data. A hindcast simulation is then constructed using actual altimetric observations during the period October 1992 through September 1998. Quantitative evaluation of the simulation suggests significant skill. The correlation coefficient between predicted sea level anomaly and ERS observations in the model interior is 0.89; that for predicted versus observed dynamic height anomaly based on hydrography at the BATS site is 0.73. Comparison with the idealized experiments suggests that the main source of error in the hindcast is temporal undersampling of the boundary conditions. The hindcast simulation described herein provides a basis for retrospective analysis of BATS observations in the context of the mesoscale eddy field.

McGillicuddy, Dennis J., Jr.↗
DOE OSTI2022

The COMBLE campaign: a study of marine boundary-layer clouds in Arctic cold-air outbreaks

One of the most intense air mass transformations on Earth happens when cold air flows from frozen surfaces to much warmer open water in cold-air outbreaks (CAOs), a process captured beautifully in satellite imagery. Despite the ubiquity of the CAO cloud regime over high-latitude oceans, we have a rather poor understanding of its properties, its role in energy and water cycles, and its treatment in weather and climate models. The Cold-air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) was conducted to better understand this regime and its representation in models. COMBLE aimed to examine the relations between surface fluxes, boundary-layer structure, aerosol, cloud and precipitation properties, and mesoscale circulations in marine CAOs. Processes affecting these properties largely fall in a range of scales where boundary-layer processes, convection, and precipitation are tightly coupled, which makes accurate representation of the CAO cloud regime in numerical weather prediction and global climate models most challenging. COMBLE deployed an Atmospheric Radiation Measurement Mobile Facility at a coastal site in northern Scandinavia (69°N), with additional instruments on Bear Island (75°N), from December 2019 to May 2020. CAO conditions were experienced 19% (21%) of the time at the main site (on Bear Island). A comprehensive suite of continuous in situ and remote sensing observations of atmospheric conditions, clouds, precipitation, and aerosol were collected. Because of the clouds’ well-defined origin, their shallow depth, and the broad range of observed temperature and aerosol concentrations, the COMBLE dataset provides a powerful modeling test bed for improving the representation of mixed-phase cloud processes in large-eddy simulations and large-scale models.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1986

Constraints on resolving meso-alpha and meso-beta phenomena using a space-based Doppler lidar wind profiler

Lidar shot management and wind computation algorithms are used to determine the constraints on resolving mesoscale (alpha and beta) wind fields. Examples of simulated Doppler lidar performance in resolving wind gradient features are presented using currently proposed scan and signal processing parameters, and GCM model outputs are used as input wind fields. Results indicate that with the present constraints on lidar lifetime, scan rates, and orbit altitudes, the limits of mesoscale wind feature resolution are close to wavelengths of 100 km.

Emmitt, G. D.↗
NASA NTRS2019

POLARRIS: A POLArimetric Radar Retrieval and Instrument Simulator

This paper introduces a synthetic polarimetric radar simulator and retrieval package, POLArimetric Radar Retrieval and Instrument Simulator (POLARRIS), for evaluating cloud‐resolving models (CRMs). POLARRIS is composed of forward (POLARRIS‐f) and inverse (retrieval and diagnostic) components (iPOLARRIS) to generate not only polarimetric radar observables (Zh, Zdr, Kdp, ρhv) but also radar‐consistent geophysical parameters such as hydrometeor identification, vertical velocity, and rainfall rates retrieved from CRM data. To demonstrate its application and uncertainties, POLARRIS is applied to simulations of a mesoscale convective system over the Southern Great Plains on 23 May 2011, using the Weather Research and Forecasting model with both spectral bin microphysics (SBM) and the Goddard single‐moment bulk 4ICE microphysics. Statistical composites reveal a significant dependence of simulated polarimetric observables (Zdr, Kdp) on the assumptions of the particle axis ratio (oblateness) and orientation angle distributions. The simulated polarimetric variables differ considerably between the SBM and 4ICE microphysics in part due to the differences in their ice particle size distributions as revealed by comparisons with aircraft measurements. Regardless of these uncertainties, simulated hydrometeor identification distributions overestimate graupel and hail fractions, especially from the simulation with SBM. To minimize uncertainties in forward model, the particle shape and orientation angle distributions of frozen particles should be predicted in a microphysics scheme in addition to the size distributions and particle densities.

Toshi Matsui↗
DOE OSTI2022

Flow Reduction in Pore Networks of Packed Silica Nanoparticles: Insights from Mesoscopic Fluid Models

A modified many-body dissipative particle dynamics (mDPD) model is rigorously calibrated to achieve realistic fluid–fluid/solid interphase properties and applied for mesoscale flow simulations to elucidate the transport mechanisms of heptane liquid and water, respectively, through pore networks formed by packed silica nanoparticles with a uniform diameter of 30 nm. Two million CPU core hours were used to complete the simulation studies. Results show reduction of permeability by 54–64% in heptane flow and by 88–91% in water flow, respectively, compared to the Kozeny–Carman equation. In these nanopores, a large portion of the fluids are in the near-wall regions and thus not mobile due to the confinement effect, resulting in reduced hydraulic conductivity. Moreover, intense oscillations in the calculated flow velocities also indicate the confinement effect that contests the external driven force to flow. Here, the generic form of Darcy’s law is considered valid for flow through homogeneous nanopore networks, while permeability depends collectively on pore size and surface wettability. This fluid-permeability dependency is unique to flow in nanopores. In addition, potential dependence of permeability on pore connectivity is observed when the porosity remains the same in different core specimens.

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

Mesoscale Cellular Convection Detection and Classification Using Convolutional Neural Networks: Insights From Long-Term Observations at ARM Eastern North Atlantic Site

Marine boundary layer clouds are crucial in Earth's climate system. They frequently manifest as closed or open cell mesoscale cellular convection (MCC). MCC clouds are challenging to represent accurately in current climate models, highlighting the need for detailed observational data sets and in-depth analyses. This study utilizes over 8 years of observations from the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) User Facility Eastern North Atlantic (ENA) site at Graciosa Island, Azores, to investigate these clouds. We first apply a convolutional neural network with a U-Net architecture to classify open and closed cells, marking the first application of such an approach for automatically detecting MCC patterns from ground-based radar measurements. This method addresses some observational gaps in satellite data related to low temporal resolution, nighttime challenges, and limited vertical structure capture. The analysis of the MCC cases shows clear differences between closed and open MCCs: Closed MCC clouds are characterized by lower cloud tops and bases, shallower cloud geometrical depth, weaker horizontal wind speeds, stronger atmospheric stability, and a more homogeneous liquid water path than open MCCs. Finally, we demonstrate two potential applications of our radar-based MCC classifications: (a) facilitating the investigation of aerosol-cloud interactions and (b) exploring meteorological factors along with MCC's evolution by integrating satellite imagery and back-trajectory analysis. The identified MCC cases offer a valuable resource for the scientific community to study MCC processes further and improve climate model accuracy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Evidence for Bootstrap Percolation Dynamics in a Photoinduced Phase Transition

Upon intense femtosecond photo-excitation, a many-body system can undergo a phase transition through a non-equilibrium route, but understanding these pathways remains an outstanding challenge. Here, we use time-resolved second harmonic generation to investigate a photo-induced phase transition in Ca 3 Ru 2 O 7 and show that mesoscale inhomogeneity profoundly influences the transition dynamics. We observe a marked slowing down of the characteristic time τ that quantifies the transition between two structures. τ evolves non-monotonically as a function of photo-excitation fluence, rising from below 200 fs to ~1.4 ps, then falling again to below 200 fs. To account for the observed behavior, we perform a bootstrap percolation simulation that demonstrates how local structural interactions govern the transition kinetics. Finally, our work highlights the importance of percolating mesoscale inhomogeneity in the dynamics of photo-induced phase transitions and provides a model that may be useful for understanding such transitions more broadly.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Dependencies of Four Mechanisms of Secondary Ice Production on Cloud-Top Temperature in a Continental Convective Storm

Various mechanisms of secondary ice production (SIP) cause multiplication of numbers of ice particle, after the onset of primary ice. A measure of SIP is the ice enhancement ratio (“IE ratio”) defined here as the ratio between number concentrations of total ice (excluding homogeneously nucleated ice) and active ice-nucleating particles (INPs). A convective line observed on 11 May 2011 over the Southern Great Plains in the Mesoscale Continental Convective Cloud Experiment (MC3E) campaign was simulated with the “Aerosol–Cloud” (AC) model. AC is validated against coincident MC3E observations by aircraft, ground-based instruments, and satellite. Four SIP mechanisms are represented in AC: the Hallett–Mossop (HM) process of rime splintering, and fragmentation during ice–ice collisions, raindrop freezing, and sublimation. The vertical profile of the IE ratio, averaged over the entire simulation, is almost uniform (10 2 to 10 3 ) because fragmentation in ice–ice collisions dominates at long time scales, driving the ice concentration toward a theoretical maximum. The IE ratio increases with both the updraft (HM process, fragmentation during raindrop freezing, and ice–ice collisions) and downdraft speed (fragmentation during ice–ice collisions and sublimation). As reported historically in aircraft sampling, IE ratios were predicted to peak near 10 3 for cloud-top temperatures close to the −12°C level, mostly due to the HM process in typically young clouds with their age less than 15 min. Here, at higher altitudes with temperatures of −20° to −30°C, the predicted IE ratios were smaller, ranging from 10 to 10 2 , and mainly resulted from fragmentation in ice–ice collisions.

Aerosols↗
DOE OSTI2022

Robotic Planning under Uncertainty in Spatiotemporal Environments in Expeditionary Science

In the expeditionary sciences, spatiotemporally varying environments -- hydrothermal plumes, algal blooms, lava flows, or animal migrations -- are ubiquitous. Mobile robots are uniquely well-suited to study these dynamic, mesoscale natural environments. We formalize expeditionary science as a sequential decision-making problem, modeled using the language of partially-observable Markov decision processes (POMDPs). Solving the expeditionary science POMDP under real-world constraints requires efficient probabilistic modeling and decision-making in problems with complex dynamics and observational models. Previous work in informative path planning, adaptive sampling, and experimental design have shown compelling results, largely in static environments, using data-driven models and information-based rewards. However, these methodologies do not trivially extend to expeditionary science in spatiotemporal environments: they generally do not make use of scientific knowledge such as equations of state dynamics, they focus on information gathering as opposed to scientific task execution, and they make use of decision-making approaches that scale poorly to large, continuous problems with long planning horizons and real-time operational constraints. In this work, we discuss these and other challenges related to probabilistic modeling and decision-making in expeditionary science, and present some of our preliminary work that addresses these gaps. We ground our results in a real expeditionary science deployment of an autonomous underwater vehicle (AUV) in the deep ocean for hydrothermal vent discovery and characterization. Our concluding thoughts highlight remaining work to be done, and the challenges that merit consideration by the reinforcement learning and decision-making community.

Preston, Victoria↗
NASA NTRS2001

The Use of CASES-97 Observations to Assess and Parameterize the Impact of Land-Surface Heterogeneity on Area-Average Surface Heat Fluxes for Large-Scale Coupled Atmosphere-Hydrology Models

To understand the effects of land-surface heterogeneity and the interactions between the land-surface and the planetary boundary layer at different scales, we develop a multiscale data set. This data set, based on the Cooperative Atmosphere-Surface Exchange Study (CASES97) observations, includes atmospheric, surface, and sub-surface observations obtained from a dense observation network covering a large region on the order of 100 km. We use this data set to drive three land-surface models (LSMs) to generate multi-scale (with three resolutions of 1, 5, and 10 kilometers) gridded surface heat flux maps for the CASES area. Upon validating these flux maps with measurements from surface station and aircraft, we utilize them to investigate several approaches for estimating the area-integrated surface heat flux for the CASES97 domain of 71x74 square kilometers, which is crucial for land surface model development/validation and area water and energy budget studies. This research is aimed at understanding the relative contribution of random turbulence versus organized mesoscale circulations to the area-integrated surface flux at the scale of 100 kilometers, and identifying the most important effective parameters for characterizing the subgrid-scale variability for large-scale atmosphere-hydrology models.

Chen, Fei↗
DOE OSTI2025

Multiscale Modeling Framework for Lithium Nucleation in 3D Porous Carbon Anodes

Porous carbon scaffolds offer a promising route for mitigating non-uniform lithium (Li) plating to enhance the safety and longevity of Li metal batteries. However, the influence of microstructural morphology on Li nucleation is not well understood. Here, we present a multiscale modeling framework to investigate how the porous microstructure of carbon materials affects Li nucleation behavior. Ab initio molecular dynamics simulations quantify the nucleation energy barriers of Li on graphene as a function of Li content, surface curvature, and applied potential, providing key parameters for a classical nucleation theory (CNT) model. From macroscale half-cell simulations, we obtained Li concentration and electrical potential profiles to define boundary conditions for mesoscopic simulations. At the mesoscale, three distinct synthetic 3D microstructures with different porosities and characteristic feature sizes are generated to resolve local distributions of Li flux, current density, and mechanical stress. These outputs are integrated into the CNT model to map spatial variation in nucleation rates. Our findings reveal trade-offs between suppressing nucleation rates and achieving spatial uniformity, offering design guidelines for optimizing porous carbon anodes to balance nucleation control and mechanical integrity.

Materials science↗
NASA NTRS2001

Dynamical Interpolation of Mesoscale Flows in the TOPEX/ Poseidon Diamond Surrounding the U.S. Joint Global Ocean Flux Study Bermuda Atlantic Time-Series Study Site

An open boundary ocean model is configured in a domain bounded by the four TOPEX/Poseidon (TIP) ground tracks surrounding the U.S. Joint Global Ocean Flux Study Bermuda Atlantic Time-series Study (BATS) site. This implementation facilitates prescription of model boundary conditions directly from altimetric measurements (both TIP and ERS-2). The expected error characteristics for a domain of this size with periodically updated boundary conditions are established with idealized numerical experiments using simulated data. A hindcast simulation is then constructed using actual altimetric observations during the period October 1992 through September 1998. Quantitative evaluation of the simulation suggests significant skill. The correlation coefficient between predicted sea level anomaly and ERS observations in the model interior is 0.89; that for predicted versus observed dynamic height anomaly based on hydrography at the BATS site is 0.73. Comparison with the idealized experiments suggests that the main source of error in the hindcast is temporal undersampling of the boundary conditions. The hindcast simulation described herein provides a basis for retrospective analysis of BATS observations in the context of the mesoscale eddy field.

McGillicuddy, D. J.↗
DOE OSTI2024

Mesoscale Convective Systems Represented in High Resolution E3SMv2 and Impact of New Cloud and Convection Parameterizations

Mesoscale convective systems (MCSs) play an important role in modulating the global hydrological cycle, general circulation, and radiative energy budget. In this study, we evaluate MCS simulations in the second version of U.S. Department of Energy (DOE) Energy Exascale Earth System Model (E3SMv2). E3SMv2 atmosphere model (EAMv2) is run at the uniform 0.25? horizontal resolution. We track MCSs consistently in the model and observations using the PyFLEXTRKR algorithm, which defines MCS based on both cloud-top brightness temperature (Tb) and surface precipitation. Results from using Tb only to define MCS, commonly used in previous studies, are also discussed. Furthermore, sensitivity experiments are performed to examine the impact of new cloud and convection parameterizations developed for EAMv3 on simulated MCSs. Our results show that EAMv2 simulated MCS precipitation is largely underestimated in the tropics and contiguous United States. This is mainly attributed to the underestimated precipitation intensity in EAMv2. In contrast, the simulated MCS frequency becomes more comparable to observations if MCSs are defined only based on cloud-top Tb. The Tb-based MCS tracking method, however, includes many cloud systems with very weak precipitation which conflicts with the MCS definition. This result illustrates the importance of accounting for precipitation in evaluating simulated MCSs. We also find that the new physics parameterizations help increase the relative contribution of convective precipitation to total precipitation in the tropics, but the simulated MCS properties are generally not improved. This suggests that simulating MCSs will remain a challenge for the next version of E3SM.

Zhang, Meng↗