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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Linking Large-Scale Double-ITCZ Bias to Local-Scale Drizzling Bias in Climate Models

Tropical precipitation in climate models presents significant biases in both the large-scale pattern (i.e., double intertropical convergence zone bias) and local-scale characteristics (i.e., drizzling bias with too frequent drizzle/convection and reduced occurrences of no and heavy precipitation). By untangling the coupled system and analyzing the biases in precipitation, cloud, and radiation, this study shows that local-scale drizzling bias in atmospheric models can lead to large-scale double-ITCZ bias in coupled models by inducing convective-regime-dependent biases in precipitation and cloud radiative effects (CRE). The double-ITCZ bias consists of a hemispherically asymmetric component that arises from the asymmetric SST bias and a nearly symmetric component that exists in atmospheric models without the SST bias. By increasing light rain but reducing heavy rain, local-scale drizzling bias induces positive (negative) precipitation bias in the moderate (strong) convective regime, leading to the nearly symmetric wet bias in atmospheric models. By affecting the cloud profile, local-scale drizzling bias induces positive (negative) CRE bias in the stratocumulus (convective) regime in atmospheric models. Because the stratocumulus (convective) region is climatologically more pronounced in the southern (northern) tropics, the CRE bias is deemed to be hemispherically asymmetric and drives warm and wet (cold and dry) biases in the southern (northern) tropics when coupled to ocean. Our results suggest that correcting local-scale drizzling bias is critical for fixing large-scale double-ITCZ bias. Finally, the drizzling and double-ITCZ biases are not alleviated in models with mesoscale (0.25°–0.5°) or even storm-resolving (~3 km) resolution, implying that either large-eddy simulation or fundamental improvement in small-scale subgrid parameterizations is needed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A Micromorphic Length-Scale Coupling Framework for the Determination of Higher-Order Constitutive Models and the Multi-Scale Simulation of Heterogeneous Materials [Thesis]

Heterogeneous materials and materials with complex microstructures pose a unique challenge in the development of accurate models of their response to external stimuli. These difficulties principally arise due to the difficulty in characterizing and modeling the constituents and their interactions. It is usually possible, though non-trivial, to construct an explicit representation of the microstructure (a direct numeric simulation or DNS) but the method by which the complex modes of deformation and other processes can be homogenized to a reduced-order approximation is frequently unclear. Many homogenization approaches are ad-hoc and lack a strong justification beyond ease of computation. Furthermore, the homogenization approach can, in some cases, not utilize the full breadth of information available in the computation of the macro-scale stresses and deformation measures. It is also noteworthy that homogenization, by its very nature, will tend to obfuscate details of processes occurring at the lower length-scale. It is therefore of interest to include as much information as possible in the construction of the reduced-order model so as to be predictive in a variety of loading environments. We here present a length-scale bridging technique based upon the micromorphic continuum mechanics of Eringen which incorporates volume and surface area averages as a part of its construction. This approach enforces the balance equations at the micro-scale and then studies the effect of the spatially varying nature on the macro-scale. This leads, naturally, to further balance equations which are solved at the macro-scale. This work details a homogenization framework which arises naturally from the micromorphic construction of Eringen attempting to introduce no definitions beyond which are justifiable from micro-structural considerations. One of the results of this effort is the so-called “micromorphic filter” which has been developed and applied to several DNS to demonstrate its effectively. In order to determine the macroscopic degrees of freedom we utilize the special case of an overlap coupling technique where the macro-scale is fully constrained to the micro-scale. This enables us to study the resulting material properties as expected but also allows us to further study the boundary conditions on the additional degrees of freedom at the macro-scale.

42 ENGINEERING↗
NASA NTRS2004

Full Scale Rotor Aeroacoustic Predictions and the Link to Model Scale Rotor Data

The NASA Aeroacoustic Prediction System (NAPS) is used to establish a link between model-scale and full-scale rotor predictions and is partially validated against measured wind tunnel and flight aeroacoustic data. The prediction approach of NAPS couples a comprehensive rotorcraft analysis with acoustic source noise and propagation codes. The comprehensive analysis selected for this study is CAMRAD-II, which provides the performance/trim/wake solution for a given rotor or flight condition. The post-trim capabilities of CAMRAD-II are used to compute high-resolution sectional airloads for the acoustic tone noise analysis, WOPMOD. The tone noise is propagated to observers on the ground with the propagation code, RNM (Rotor Noise Model). Aeroacoustic predictions are made with NAPS for an isolated rotor and compared to results of the second Harmonic Aeroacoustic Rotor Test (HART-II) program, which tested a 40% dynamically and Mach-scaled BO-105 main rotor at the DNW. The NAPS is validated with comparisons for three rotor conditions: a baseline condition and two Higher Harmonic Control (HHC) conditions. To establish a link between model and full-scale rotor predictions, a full-scale BO-105 main rotor input deck for NAPS is created from the 40% scale rotor input deck. The full-scale isolated rotor predictions are then compared to the model predictions. The comparisons include aerodynamic loading, acoustic levels, and acoustic pressure time histories for each of the three conditions. With this link established, full-scale predictions are made for a range of descent flight conditions and compared with measured trends from the recent Rotorcraft Operational Noise Abatement Procedures (RONAP) flight test conducted by DLR and ONERA. Additionally, the effectiveness of two HHC conditions from the HART-II program is demonstrated for the full-scale rotor in flight.

Boyd, D. Douglas, Jr.↗
DOE OSTI2024

Urbanization exacerbates continental- to regional-scale warming

Urbanization is usually ignored when estimating past changes in large-scale climate and for future climate projections since cities historically covered a small fraction of the Earth’s surface. Here, by combining global land surface temperature observations with historical estimates of urban area, we demonstrate that the urban contribution to continental- to regional-scale warming has become non-negligible, especially for rapidly urbanizing regions and countries in Asia. Consequently, expected urban expansion over the next century suggests further increased urban influence on large-scale surface climate in the future (approximately 0.16 K for North America and Europe for high-emission scenario in 2100). Based on these results, also seen for air temperature, we argue that, in line with other forms of land use/land cover change, urbanization should be explicitly included in climate change assessments. This requires incorporation of dynamic urban extent and biophysics in current-generation Earth system models to quantify potential urban feedback on the climate system across scales.

Chakraborty, TC↗
DOE OSTI2024

Examining Tropical Convection Features at Storm-Resolving Scales Over the Maritime Continent Region

Global Storm Resolving Models (GSRMs) provide a way to understand weather and climate events across scales for better-informed climate impacts. In this work, we apply the recently developed and validated CAM (Community Atmosphere Model)—MPAS (Model for Prediction Across Scales) modeling framework, based on the open-source Community Earth System Model (CESM2), to examine the tropical convection features at the storm resolving scale over the Maritime Continent region at 3 km horizontal spacing. We target two global numerical experiments during the winter season of 2018 for comparison with observation in the region. Here we focus on the investigation of the representations of the convective systems, precipitation statistics, and tropical cyclone behaviors. We found that regional-refined experiments show more accurate precipitation distributions, diurnal cycles, and better agreement with observations for tropical cyclone features in terms of intensity and strength statistics. We expect the exploration of this work will further advance the development and use of the storm-resolving model in precipitation predictions across scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

The Ecosystem as Super-Organ/ism, Revisited: Scaling Hydraulics to Forests under Climate Change

Synopsis Classic debates in community ecology focused on the complexities of considering an ecosystem as a super-organ or organism. New consideration of such perspectives could clarify mechanisms underlying the dynamics of forest carbon dioxide (CO2) uptake and water vapor loss, important for predicting and managing the future of Earth’s ecosystems and climate system. Here, we provide a rubric for considering ecosystem traits as aggregated, systemic, or emergent, i.e., representing the ecosystem as an aggregate of its individuals or as a metaphorical or literal super-organ or organism. We review recent approaches to scaling-up plant water relations (hydraulics) concepts developed for organs and organisms to enable and interpret measurements at ecosystem-level. We focus on three community-scale versions of water relations traits that have potential to provide mechanistic insight into climate change responses of forest CO2 and H2O gas exchange and productivity: leaf water potential (Ψcanopy), pressure volume curves (eco-PV), and hydraulic conductance (Keco). These analyses can reveal additional ecosystem-scale parameters analogous to those typically quantified for leaves or plants (e.g., wilting point and hydraulic vulnerability) that may act as thresholds in forest responses to drought, including growth cessation, mortality, and flammability. We unite these concepts in a novel framework to predict Ψcanopy and its approaching of critical thresholds during drought, using measurements of Keco and eco-PV curves. We thus delineate how the extension of water relations concepts from organ- and organism-scales can reveal the hydraulic constraints on the interaction of vegetation and climate and provide new mechanistic understanding and prediction of forest water use and productivity.

Zoology↗
NASA NTRS1988

Relationships between persistent large-scale flow anomalies and variation in synoptic-scale eddy activity and cyclogenesis

Observational analyses to study the relationships between large-scale flow anomalies and variations in synoptic-scale eddy activity and cyclogenesis are presented. The way in which changes in the large-scale flow influence the behavior of synoptic-scale eddies and the way in which changes in eddies may feedback to influence the large-scale flow anomalies are examined. Situations characterized by differing large-scale flows are compared, showing well-defined diferences in synoptic-scale eddy activity. The net forcings of anomalous mean flows by eddies as deduced from tendency methods and E-vector analyses suggest that synoptic-scale eddies may play an important role in maintaining certain anomalous flow patterns such as blocking.

Dole, Randall M.↗
NASA NTRS2003

An Analysis of Model Scale Data Transformation to Full Scale Flight Using Chevron Nozzles

Ground-based model scale aeroacoustic data is frequently used to predict the results of flight tests while saving time and money. The value of a model scale test is therefore dependent on how well the data can be transformed to the full scale conditions. In the spring of 2000, a model scale test was conducted to prove the value of chevron nozzles as a noise reduction device for turbojet applications. The chevron nozzle reduced noise by 2 EPNdB at an engine pressure ratio of 2.3 compared to that of the standard conic nozzle. This result led to a full scale flyover test in the spring of 2001 to verify these results. The flyover test confirmed the 2 EPNdB reduction predicted by the model scale test one year earlier. However, further analysis of the data revealed that the spectra and directivity, both on an OASPL and PNL basis, do not agree in either shape or absolute level. This paper explores these differences in an effort to improve the data transformation from model scale to full scale.

Brown, Clifford↗
DOE OSTI2025

Informing field-scale CO 2 storage simulations with sandbox experiments: The effect of small-scale heterogeneities

Small-scale heterogeneities can significantly affect the fate of the CO 2 plume and trapping during CO 2 migration. We conducted geologic carbon storage field-scale simulations to investigate the impact of small-scale heterogeneities on plume dynamics and trapping performance. Small-scale heterogeneities have been shown to increase the amount of trapped CO 2 during buoyancy-driven flow. The trapped CO 2 saturation is validated by previous sandbox experimental work during buoyancy-driven flow in realistic heterogeneous domains and is implemented through the critical CO 2 saturation parameter (i.e., the first non-zero value in the drainage CO 2 relative permeability curve). Depending on the type and degree of heterogeneity, various critical CO 2 saturation values are exhibited. Furthermore, we investigated the effect of small-scale heterogeneities when multiple capillary pressure models are employed. This study demonstrates that an increase in critical CO 2 saturation reduces the CO 2 plume size and lateral extent, accompanying an increase in residual trapping and a decrease in solubility trapping. Lastly, we show that independent of the capillary pressure model used, an increase in critical saturation leads to similar CO 2 plume dynamics distribution and trapping performance. These results emphasize the importance of quantifying the effect of small-scale heterogeneity as they affect the large-scale behavior of the CO 2 plume.

58 GEOSCIENCES↗
DOE OSTI2022

Medium-scale to large-scale implementation of cyber-physical human experiments in live traffic

Autonomous Vehicles (AVs) such as cars and trucks are being developed and tested as Cyber-Physical Human systems while the technology improves. Before these systems can achieve full autonomy, some serve as tools in the form of adaptive cruise control. The CIRCLES Consortium investigates the potential for AVs to increase fuel efficiency of highway traffic by smoothing “stop-and-go” traffic waves that result from normal human driving behavior in congestion. We have performed an experiment to evaluate the real world effects of implementing this strategy. A medium-scale experiment was performed on I-24 near Nashville, TN in August 2021. This was a precursor to a larger experiment that will take place November 2022. We examine how the human part of the experiment will change as we scale up from an 11 vehicle test (four AVs) to 100 AVs. There are many solutions to problems of the medium-scale experiment that would be inconvenient, complicate the experience, or not be practicable. The medium-scale experiment involved 11 cars of which four had a custom control algorithm installed to be engaged by the driver. The large-scale experiment will have 100 cars, all with custom control algorithm installed to act on traffic when the controller is engaged. We examine key choices made for the medium experiment, and how some will be different for the large experiment. Our experience performing the medium-scale experiment has made it clear that repeating our methods from this smaller one are inefficient or impossible if used for the large-scale experiment and will be improved.

McQuade, Sean T.↗
NASA NTRS2011

C/NOFS Satellite Electric Field and Plasma Density Observations of Plasma Instabilities Below the Equatorial F-Peak -- Evidence for Approximately 500 km-Scale Spread-F "Precursor" Waves Driven by Zonal Shear Flow and km-Scale, Narrow-Banded Irregularities

As solar activity has increased, the ionosphere F-peak has been elevated on numerous occasions above the C/NOFS satellite perigee of 400km. In particular, during the month of April, 2011, the satellite consistently journeyed below the F-peak whenever the orbit was in the region of the South Atlantic anomaly after sunset. During these passes, data from the electric field and plasma density probes on the satellite have revealed two types of instabilities which had not previously been observed in the C/NOFS data set (to our knowledge): The first is evidence for 400-500km-scale bottomside "undulations" that appear in the density and electric field data. In one case, these large scale waves are associated with a strong shear in the zonal E x B flow, as evidenced by variations in the meridional (outward) electric fields observed above and below the F-peak. These undulations are devoid of smaller scale structures in the early evening, yet appear at later local times along the same orbit associated with fully-developed spread-F with smaller scale structures. This suggests that they may be precursor waves for spread-F, driven by a collisional shear instability, following ideas advanced previously by researchers using data from the Jicamarca radar. A second new result (for C/NOFS) is the appearance of km-scale irregularities that are a common feature in the electric field and plasma density data that also appear when the satellite is below the F -peak at night. The vector electric field instrument on C/NOFS clearly shows that the electric field component of these waves is strongest in the zonal direction. These waves are strongly correlated with simultaneous observations of plasma density oscillations and appear both with, and without, evidence of larger-scale spread-F depletions. These km-scale, quasi-coherent waves strongly resemble the bottomside, sinusoidal irregularities reported in the Atmosphere Explorer satellite data set by Valladares et al. [JGR, 88, 8025, 1983]. We interpret these new observations in terms of fundamental plasma instabilities associated with the unstable, nighttime equatorial ionosphere.

Pfaff, R.↗
NASA NTRS2014

Static Aeroelastic Scaling and Analysis of a Sub-Scale Flexible Wing Wind Tunnel Model

This paper presents an approach to the development of a scaled wind tunnel model for static aeroelastic similarity with a full-scale wing model. The full-scale aircraft model is based on the NASA Generic Transport Model (GTM) with flexible wing structures referred to as the Elastically Shaped Aircraft Concept (ESAC). The baseline stiffness of the ESAC wing represents a conventionally stiff wing model. Static aeroelastic scaling is conducted on the stiff wing configuration to develop the wind tunnel model, but additional tailoring is also conducted such that the wind tunnel model achieves a 10% wing tip deflection at the wind tunnel test condition. An aeroelastic scaling procedure and analysis is conducted, and a sub-scale flexible wind tunnel model based on the full-scale's undeformed jig-shape is developed. Optimization of the flexible wind tunnel model's undeflected twist along the span, or pre-twist or wash-out, is then conducted for the design test condition. The resulting wind tunnel model is an aeroelastic model designed for the wind tunnel test condition.

Aeroelasticity↗
DOE OSTI2022

CFD-DEM Modeling of Autothermal Pyrolysis of Corn Stover with a Coupled Particle- and Reactor-Scale Framework

Autothermal operation of fast pyrolysis is an efficient process-intensification technique wherein exothermic oxidation reactions are used to overcome the heat-transfer bottleneck of conventional pyrolysis. The development of accurate, reliable modeling toolsets is imperative to generating a deeper understanding of biomass autothermal pyrolysis systems to support scale-up and industrial deployment. This modeling effort describes the development of single-particle and reactor models which incorporate detailed reaction schemes and simultaneous exothermic oxidation reactions. The particle-scale model was parameterized for corn stover feedstock with particle morphology, density, ash content, and biopolymer composition, all of which impact the emergent conversion characteristics during pyrolysis. Results were then used to parameterize a reactor-scale autothermal pyrolysis model, which was developed using a coarse-grained computational fluid dynamic-discrete element method. The simulation results compared well with experimental results, with the predicted bio-oil, light gas, and biochar yield within 3.0 wt% of the experimental yields. Further analyses were performed to test the influence of equivalence ratio, biomass injection position, and particle size distribution on autothermal pyrolysis. The analysis of the physio-chemical properties of the fluid and solid phase inside the reactor and at the reactor outlet help reveal important process interactions of autothermal pyrolysis.

BIOMASS FUELS,INORGANIC, ORGANIC, PHYSICAL, AND AN↗
DOE OSTI2025

Regional-scale soil carbon predictions can be enhanced by transferring global-scale soil–environment relationships

Accurate modelling and mapping soil organic carbon are crucial for supporting soil health restoration and climate change mitigation at both regional and global scales. However, regional soil predictions often suffer from data scarcity and high prediction uncertainty. Utilizing a pre-trained global-to-regional soil carbon predictive model can be a potential solution to address this challenge. Despite its promise, how to construct and apply the global-scale model to enhance regional-scale soil carbon mapping remains largely unexplored. Here, we propose the Global Soil Carbon Pre-trained Model (GSoilCPM), a deep-learning-based domain adaptative model, to enhance regional-scale soil carbon predictions. Based on large amount of environmental covariate data and 106,167 soil samples across the globe, we verify our hypothesis of the effectiveness of this 'global-to-regional' modelling strategy. The pre-trained model can be then transferred and fine-tuned to bridge the regional- and global-scale soil–environment relationships. We applied and validated this modelling strategy in four regional-scale study areas, three in the Northern Hemisphere and one in the Southern Hemisphere, each with distinct environmental background. Compared to traditional modelling approaches as a baseline, four case studies all demonstrated significant improvement in prediction accuracy across diverse environments and varying data availabilities. The average percentage improvement across all regions is 10.93% (absolute values decreased by 1.20 g kg−1 averagely) in MAE and 29.04% (absolute values increased by 0.10 averagely) in CCC. The applicability and future horizons of using GSoilCPM were further discussed. We further reveal that regions with fewer soil samples or lower baseline accuracy benefit more from the pre-trained global model. Our findings highlight the advantages of leveraging the generalized knowledge from global models to enhance specifically localized soil modelling, positioning a potential paradigm shift in digital soil mapping, and far-reaching implications for soil monitoring and land management.

Deep learning↗
DOE OSTI2024

Bridging molecular-scale interfacial science with continuum-scale models

Solid–water interfaces are crucial for clean water, conventional and renewable energy, and effective nuclear waste management. However, reflecting the complexity of reactive interfaces in continuum-scale models is a challenge, leading to oversimplified representations that often fail to predict real-world behavior. This is because these models use fixed parameters derived by averaging across a wide physicochemical range observed at the molecular scale. Recent studies have revealed the stochastic nature of molecular-level surface sites that define a variety of reaction mechanisms, rates, and products even across a single surface. To bridge the molecular knowledge and predictive continuum-scale models, we propose to represent surface properties with probability distributions rather than with discrete constant values derived by averaging across a heterogeneous surface. This conceptual shift in continuum-scale modeling requires exponentially rising computational power. By incorporating our molecular-scale understanding of solid–water interfaces into continuum-scale models we can pave the way for next generation critical technologies and novel environmental solutions.

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

Permeability scaling relationships of volcanic tuff from core to field scale measurements

A recent chemical explosive test in P-Tunnel at the Nevada National Security Site, Nevada, USA, was conducted to better understand how signals propagate from explosions in the subsurface. A primary signal of interest is the migration of gases that can be used to differentiate chemical from nuclear explosions. Gas migration is highly dependent on the rock permeability which is notoriously difficult to determine experimentally in the field due to a potentially large dependence on the scale over which measurements are made. Here, we present pre-explosion permeability estimates to characterize the geologic units surrounding the recent test. Permeability measurements were made at three scales of increasing size: core samples (≈2 cm), borehole packer system tests (≈1 m), and a pre-shot cavity pressurization test (> 10 m) across ten tuff units. Permeability estimates based on core measurements showed little difference from borehole packer tests. However, permeability in most rock units calibrated from cavity pressurization tests resulted in higher permeability estimates by up to two orders of magnitude. Here, we demonstrate that the scale of the measurement significantly impacts the characterization efforts of hydraulic properties in volcanic tuff, and that local-scale measurements (< 10 m scale) do not incorporate enough heterogeneity to accurately predict field-scale flow and mass transport.

Environmental sciences↗
DOE OSTI2023

Large-Scale Materials Modeling at Quantum Accuracy: Ab Initio Simulations of Quasicrystals and Interacting Extended Defects in Metallic Alloys

Ab initio electronic-structure has remained dichotomous between achievable accuracy and length-scale. Quantum many-body (QMB) methods realize quantum accuracy but fail to scale. Density functional theory (DFT) scales favorably but remains far from quantum accuracy. We present a framework that breaks this dichotomy by use of three interconnected modules: (i) invDFT: a methodological advance in inverse DFT linking QMB methods to DFT; (ii) MLXC: a machine-learned density functional trained with invDFT data, commensurate with quantum accuracy; (iii) DFT-FE-MLXC: an adaptive higher-order spectral finite-element (FE) based DFT implementation that integrates MLXC with efficient solver strategies and HPC innovations in FE-specific dense linear algebra, mixed-precision algorithms, and asynchronous compute-communication. Furthermore, we demonstrate a paradigm shift in DFT that not only provides an accuracy commensurate with QMB methods in ground-state energies, but also attains an unprecedented performance of 659.7 PFLOPS (43.1% peak FP64 performance) on 619,124 electrons using 8,000 GPU nodes of Frontier supercomputer.

density functional theory↗