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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 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Roles of External Forcing and Internal Variability in Precipitation Changes of a Sub-Region of the U.S. Mid-Atlantic During 1979–2019

Observations of the seasonal mean precipitation averaged over a sub-region of the U.S. mid-Atlantic show significant increases in summer but no changes in winter during 1979–2019. Clarifying the drivers of these observed changes is important for understanding and interpreting future projections of regional precipitation by climate models. Herein, this study examines the relative effects of external forcing and internal variability in the observed multi-decadal changes using the historical and RCP8.5/SSP585 simulations from 37 models in the Coupled Model Intercomparison Project phase 5 (CMIP5), 35 models in CMIP6, as well as large ensemble simulations from 6 models, each including more than 20 members. During 1979–2019, enhanced warming over land relative to ocean due to external forcing induces low pressure anomalies over land that contribute to the wetting summer. While similar wetting also occurs during winter, such effect is offset by the drying associated with the positive phase of the North Atlantic Oscillation (NAO) in recent decades. Internal variability produces large uncertainty in the multi-decadal precipitation changes simulated by climate models through changes in large-scale circulation associated with the NAO in winter and the North Atlantic Subtropical High in summer. These multi-decadal relationships between precipitation and large-scale circulation under internal variability also manifest on inter-annual timescale. These relationships highlight enhanced moisture transport from the Gulf of Mexico and North Atlantic in winter and near the mid-Atlantic coast in summer that modulates precipitation change in the study region.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2022

Space Weather Modeling and Prediction for Intermediate Time-scales

Much of solar activity within a sunspot cycle occurs as bursts, or 'seasons' of strong activity over several months, separated by periods of much less activity. The most important space weather effects occur during these bursts. Previous modeling and forecasting efforts have focused on time-scales of hours-to-days and decades-to-centuries. The recent discovery of Rossby waves in the Sun, together with recently developed global models of solar MHD Rossby waves and their interactions with differential rotation and spot-producing magnetic fields, reveal the opportunity to simulate and predict the occurrence, strength and location of enhanced activity bursts a few weeks up to several months in advance. We now have a golden opportunity to fill in this gap in time-scales of forecasting space weather. This requires a) continuous observations of solar Rossby waves by various techniques; b) development of coupled nonlinear MHD models that simulate both global Rossby waves and the much smaller spatial scale emergence of new active regions; c) application of advanced data assimilation techniques to couple surface observations to update the model-system to integrate forward in time for creating forecasts months ahead. Then it will be possible to build operational prediction models to meet the needs of customers and stakeholders, including support of future NASA missions, regarding what kind and level of space weather to expect a few weeks to several months ahead.

SMD↗
DOE OSTI2024

Platform for Integrated Land use And Transportation Experiments and Simulation (PILATES) v1.0

PILATES allows for flexibly and at-scale coupling of multiple models to allow for multi-scale and multi-resolution simulation of regional-scale transport networks. In particular, it couples the MATSim-derived transportation modeling framework for Behavior, Energy, Autonomy and Mobility (BEAM) with other models operating at different time scales. Rather than tightly coupling supply and demand models using shared agents and memory within the same software process, PILATES orchestrates different model runs in a containerized framework. This structure requires passing information from the demand models to BEAM in the format of a synthetic population and agent plans, and from BEAM to the demand models in terms or origin/destination tables (also known as "skims"). This allows it to take advantage of the behavioral sophistication of existing activity-based models as well as the reinforcement learning structure of MATSim replanning and adopted by BEAM, in a way that requires minimal changes to existing models. It also takes advantage of the computational performance of BEAM, which allows for simulations with millions of agents to complete in reasonable time as well as allowing for detailed mechanistic simulation of the operation of on-demand modes.

Needell, Zachary↗
DOE OSTI2020

ExaWind: A multifidelity modeling and simulation environment for wind energy

We introduce the open-source ExaWind modeling and simulation environment for wind energy. The primary physics codes of ExaWind are Nalu-Wind and OpenFAST. Nalu-Wind is a wind-focused computational fluid dynamics (CFD) code that is coupled to the whole-turbine simulation code OpenFAST. The ExaWind environment was created under U.S. Department of Energy funding to achieve the highest-fidelity simulations of wind turbines and wind farms to date, with the goal of enabling disruptive changes to turbine and plant design and operation. Innovation will be gleaned through better understanding of the complex flow dynamics in wind farms, including wake evolution and the impact of wakes on downstream turbines and turbulent flow from complex terrain. High-fidelity predictive simulations employ hybrid turbulence models, geometry/boundary-layer-resolving CFD meshes, atmospheric turbulence, nonlinear structural dynamics, and fluid-structure interaction. While there is an emphasis on very high-fidelity simulations (e.g., blade resolved with full fluid-structure coupling), the ExaWind environment supports lower-fidelity modeling capabilities including actuator-line and -disk methods. Important in the development of ExaWind codes is that the codes scale well on today's largest petascale supercomputers and on the next-generation platforms that will enable exascale computing.

17 WIND ENERGY↗
NASA NTRS2000

Probabilistic Multi-Scale, Multi-Level, Multi-Disciplinary Analysis and Optimization of Engine Structures

Aircraft engines are assemblies of dynamically interacting components. Engine updates to keep present aircraft flying safely and engines for new aircraft are progressively required to operate in more demanding technological and environmental requirements. Designs to effectively meet those requirements are necessarily collections of multi-scale, multi-level, multi-disciplinary analysis and optimization methods and probabilistic methods are necessary to quantify respective uncertainties. These types of methods are the only ones that can formally evaluate advanced composite designs which satisfy those progressively demanding requirements while assuring minimum cost, maximum reliability and maximum durability. Recent research activities at NASA Glenn Research Center have focused on developing multi-scale, multi-level, multidisciplinary analysis and optimization methods. Multi-scale refers to formal methods which describe complex material behavior metal or composite; multi-level refers to integration of participating disciplines to describe a structural response at the scale of interest; multidisciplinary refers to open-ended for various existing and yet to be developed discipline constructs required to formally predict/describe a structural response in engine operating environments. For example, these include but are not limited to: multi-factor models for material behavior, multi-scale composite mechanics, general purpose structural analysis, progressive structural fracture for evaluating durability and integrity, noise and acoustic fatigue, emission requirements, hot fluid mechanics, heat-transfer and probabilistic simulations. Many of these, as well as others, are encompassed in an integrated computer code identified as Engine Structures Technology Benefits Estimator (EST/BEST) or Multi-faceted/Engine Structures Optimization (MP/ESTOP). The discipline modules integrated in MP/ESTOP include: engine cycle (thermodynamics), engine weights, internal fluid mechanics, cost, mission and coupled structural/thermal, various composite property simulators and probabilistic methods to evaluate uncertainty effects (scatter ranges) in all the design parameters. The objective of the proposed paper is to briefly describe a multi-faceted design analysis and optimization capability for coupled multi-discipline engine structures optimization. Results are presented for engine and aircraft type metrics to illustrate the versatility of that capability. Results are also presented for reliability, noise and fatigue to illustrate its inclusiveness. For example, replacing metal rotors with composites reduces the engine weight by 20 percent, 15 percent noise reduction, and an order of magnitude improvement in reliability. Composite designs exist to increase fatigue life by at least two orders of magnitude compared to state-of-the-art metals.

Chamis, Christos C.↗
NASA NTRS2024

Evaluation of CMIP6 Model Simulations of PM 2.5 and its Components Over China

Earth system models (ESMs) participating in the latest Coupled Model Intercomparison Project Phase 6 (CMIP6) simulate various components of fine particulate matter (PM 2.5 ) as major climate forcers. Yet the model performance for PM 2.5 components remains little evaluated due in part to a lack of observational data. Here, we evaluate near-surface concentrations of PM 2.5 and its five main components over China as simulated by 14 CMIP6 models, including organic carbon (OC; available in 14 models), black carbon (BC; 14 models), sulfate (14 models), nitrate (4 models), and ammonium (5 models). For this purpose, we collect observational data between 2000 and 2014 from a satellite-based dataset for total PM2.5 and from 2469 measurement records in the literature for PM 2.5 components. Seven models output total PM 2.5 concentrations, and they all underestimate the observed total PM 2.5 over eastern China, with GFDL-ESM4 (−1.5 %) and MPI-ESM-1-2-HAM (−1.1 %) exhibiting the smallest biases averaged over the whole country. The other seven models, for which we recalculate total PM 2.5 from the available component output, underestimate the total PM 2.5 concentrations partly because of the missing model representations of nitrate and ammonium. Concentrations of the five individual components are underestimated in almost all models, except that sulfate is overestimated in MPI-ESM-1-2-HAM by 12.6 % and in MRI-ESM2-0 by 24.5 %. The underestimation is the largest for OC (by −71.2 % to −37.8 % across the 14 models) and the smallest for BC (−47.9 % to −12.1 %). The multi-model mean (MMM) reproduces the observed spatial pattern for OC (R = 0.51), sulfate (R = 0.57), nitrate (R = 0.70) and ammonium (R = 0.74) fairly well, yet the agreement is poorer for BC (R = 0.39). The varying performances of ESMs on total PM 2.5 and its components have important implications for the modeled magnitude and spatial pattern of aerosol radiative forcing.

CMIP6↗
NASA NTRS1996

Fundamental processes in the expansion, energization, and coupling of single- and multi-Ion plasmas in space: Laboratory simulation experiments

We have conducted a laboratory investigation into the physics of plasma expansions and their associated energization processes. We studied single- and multi-ion plasma processes in self-expansions, and included light and heavy ions and heavy/light mixtures to encompass the phenomenological regimes of the solar and polar winds and the AMPTE and CRRES chemical release programs. The laboratory experiments provided spatially-distributed time-dependent measurements of total plasma density, temperature, and density fluctuation power spectra with the data confirming the long-theorized electron energization process in an expanding cloud - a result that was impossible to determine in spaceborne experiments (as e.g., in the CRRES program). These results provided the missing link in previous laboratory and spaceborne programs. confirming important elements in our understanding of such solar-terrestrial processes as manifested in expanding plasmas in the solar wind (e.g., CMES) and in ionospheric outflow in plasmaspheric fluctuate refilling after a storm. The energization signatures were seen in an entire series of runs that varied the ion species (Ar', Xe', Kr' and Ne'), and correlative studies included spectral analyses of electrostatic waves collocated with the energized electron distributions. In all cases wave energies were most intense during the times in which the suprathermal populations were present, with wave intensity increasing with the intensity of the suprathermal electron population. This is consistent with theoretical expectations wherein the energization process is directly attributable to wave particle interactions. No resonance conditions were observed, in an overall framework in which the general wave characteristics were broadband with power decreasing with increasing frequency.

Szuszczewicz, E. P.↗
DOE OSTI2019

Full-torus impurity transport simulation for optimizing plasma discharge operation using a multi-species impurity powder dropper in the large helical device

The transport of impurities supplied by a multi-species impurity powder dropper (IPD) in the large helical device (LHD) is investigated using a three-dimensional peripheral plasma fluid code (EMC3-EIRENE) coupled with a dust transport simulation code (DUSTT). The trajectories of impurity powder particles (Boron, Carbon, Iron, and Tungsten) dropped from the IPD and the impurity transport in the peripheral plasma are studied in a full-torus geometry. The simulation reveals an appropriate size of the impurity powder particles and an optimum operational range of the dust drop rates for investigating the impurity transport without inducing radiation collapse. The simulation also predicts a favourable plasma discharge condition for wall conditioning (boronization) using the IPD in order to deposit boron to high plasma flux and neutral particle density areas in the divertor region in the inboard side of the torus.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Effect of net direct current on the properties of radio frequency sheaths: simulation and cross-code comparison

In order to understand, predict and control ion cyclotron range of frequency (ICRF) interactions with tokamak scrape-off layer plasmas, computational tools which can model radio frequency (RF) sheaths are needed. In particular, models for the effective surface impedance and DC rectified sheath potentials may be coupled with full wave RF simulation codes to predict self-consistent wave fields near surfaces and the resulting power dissipation and plasma-material interactions from ion sputtering. In this study, previous work assuming zero net DC current flow through the sheath is generalized to allow the surface to collect net positive or negative current, as is often observed in experiments. The waveforms, DC potential and RF admittance are investigated by means of analytical theory, nonlinear fluid and particle-in-cell (PIC) codes. Cross-code comparisons provide detailed model verification and elucidate the roles of ion and electron kinetics. When the sheath draws negative (positive) DC current, the voltage rectification is reduced (increased) compared with the zero-current case, and the magnitude of both the real and imaginary parts of the admittance are increased (reduced). In conclusion, a previous four-input parametrization of the sheath rectification and admittance properties is generalized to include a fifth parameter describing the DC sheath current.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

The impact of simplified window and exhaust fan assumptions on indoor air quality in multifamily buildings

In residential buildings, the indoor air quality can be significantly affected by ventilation measures initiated by occupants, including the operation of windows and in-unit exhaust fans in kitchens and bathrooms. Many simulations simplify these factors by disregarding window opening behaviors and using fixed schedules for exhaust fan operation across all residential units. To estimate the impact of these simplifications in the U.S. context, this study used coupled CONTAM and EnergyPlus models to simulate airflow and contaminant transport in multifamily buildings. The coupled models parametrically varied climate zone, building airtightness, and mechanical ventilation system types. The study conducted a sensitivity analysis on two key occupant behaviors: (1) operating kitchen and bathroom exhausts on different schedules in individual dwelling units, and (2) scheduling open windows on ground and top floors. The simplified assumptions (i.e. uniform in-unit exhaust fan operation and window operation) had a minimal impact on inter-unit air flow and contaminant transport simulations across a broad range of building air leakage and mechanical ventilation system types. These findings suggest that for buildings with tight construction it is reasonable for most modelling and simulation efforts to ignore the effects of non-uniform exhaust fan operation and window opening.

Occupant behavior↗
DOE OSTI2025

Hydrology controls thermokarst and alters carbon cycling and methane emissions in peatlands near the southern limit of permafrost

Permafrost peatlands store vast amounts of frozen carbon across northern landscapes. When ground ice melts, surface subsidence produces thermokarst landforms that expand wetlands at the edges of permafrost plateaus. Thermokarst represents an accelerating climate feedback, but uncertainties remain about how ground ice, hydrology, and vegetation interact to shape landscape change and carbon fluxes. We extended the process-based model ecosys to simulate thermokarst dynamics in laterally coupled 2D transects at a well-characterized boreal peatland site in Canada’s Northwest Territories. After benchmarking against site observations, we varied ground ice content and hydrologic boundary conditions across ranges typical near the southern permafrost limit. Simulations revealed distinct degradation regimes governed by the elevation difference between the frost table and the external water table. Rates of lateral retreat, the thaw-driven encroachment of wetlands into adjacent plateaus, ranged from 0 to >2 m yr −1 under identical weather forcing, consistent with observations and highlighting the strong role of WT and ground ice. Simulated vegetation dynamics indicate that black spruce mortality cannot be explained by anoxia alone, pointing to additional stressors such as root damage, pathogens, or physical destabilization. Despite large hydrologic shifts, net ecosystem CO 2 exchange remained a slight sink after collapse, while methane (CH 4 ) emissions rose by one to two orders of magnitude. As a result, lateral retreat substantially increases the greenhouse warming potential of permafrost peatlands (1.7 million km 2 in area), with simulated emissions of 0.1–10 Mt CO 2 -eq decade −1 depending on hydrology and retreat rates. These results underscore the need to account for both ground ice and hydrologic dynamics when assessing thermokarst-driven climate feedbacks.

carbon cycling↗
DOE OSTI2022

TDycores-Project/TDycore

The terrestrial dycores will solve tightly coupled conservation of water and energy equations. While the land dycore will simulate processes for a three-dimensional subsurface coupled to a one-dimensional plant’s vascular system, the river dycore will simulate two-dimensional processes in the river.

Bisht, Gautam↗
DOE OSTI2023

Model simulations of Plum Island Ecosystems LTER low marsh site using ELM-PFLOTRAN

Model simulations using the E3SM Land Model (ELM) coupled to the PFLOTRAN reactive transport model via the Alquimia interface. The simulations were conducted for a tidal salt marsh at the Plum Island Ecosystems LTER near Rowley, Massachusetts, USA. Model simulations were forced using site-specific tidal cycles and salinity, and the simulations used a biogeochemical reaction network including aerobic decomposition, sulfate reduction, iron reduction, and methanogenesis. Model outputs include simulated carbon stocks, carbon dioxide and methane fluxes, and porewater concentrations of key solutes related to sulfur, iron, and carbon cycling. The model simulations included a saline simulation (with tidal sulfate inputs), a fresh simulation (with low salinity and low sulfate inputs), and a saline simulation with lower vegetation productivity to represent the effect of salinity on vegetation. These simulations were conducted to demonstrate that a new model framework incorporating subsurface redox and biogeochemical interactions into a land surface model could reproduce measured surface greenhouse gas fluxes and biogeochemical dynamics in tidal marsh ecosystems, and to test whether including redox interactions in a land surface model would allow the model to resolve contrasts in biogeochemical cycling and greenhouse gas production between saline and freshwater wetlands.The data package includes gzipped tar archives (which can be expanded using standard tar and gzip utilities) of model outputs from three model configurations: saline subsurface and reduced vegetation productivity related to salinity; saline subsurface with vegetation productivity not reduced; and freshwater. Also included are code for the modified E3SM model, Alquimia interface, and PFLOTRAN reactive transport simulator in gzipped tar format; plain text parameter and configuration files; python code files for visualizing model output and defining model configurations; and model output, tide and salinity forcing, and configuration files in netCDF format. See the README.md file in the data package for a detailed description of all files contained in the package. All files are in netCDF (.nc), gzipped tar archive (.tar.gz or .tgz), or text (all other files).Updated: May 13, 2024. Model output, E3SM code, PFLOTRAN input files, and python codes for visualizing results were updated to reflect changes made for the manuscript revision. The updated archive reflects the code and model output from the final accepted manuscript. Changes included updated reaction parameters reflecting improved parameterization and additional comparisons with field measurements. E3SM code changes included better support for multiple grid cells and improved flow and transport parameterization.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2015

Applying Advanced Ground-Based Remote Sensing in the Southeast Asian Maritime Continent to Characterize Regional Proficiencies in Smoke Transport Modeling

This work describes some of the most extensive ground-based observations of the aerosol profile collected in Southeast Asia to date, highlighting the challenges in simulating these observations with a mesoscale perspective. An 84-h WRF Model coupled with chemistry (WRF-Chem) mesoscale simulation of smoke particle transport at Kuching, Malaysia, in the southern Maritime Continent of Southeast Asia is evaluated relative to a unique collection of continuous ground-based lidar, sun photometer, and 4-h radiosonde profiling. The period was marked by relatively dry conditions, allowing smoke layers transported to the site unperturbed by wet deposition to be common regionally. The model depiction is reasonable overall. Core thermodynamics, including landsea-breeze structure, are well resolved. Total model smoke extinction and, by proxy, mass concentration are low relative to observation. Smoke emissions source products are likely low because of undersampling of fires in infrared sun-synchronous satellite products, which is exacerbated regionally by endemic low-level cloud cover. Differences are identified between the model mass profile and the lidar profile, particularly during periods of afternoon convective mixing. A static smoke mass injection height parameterized for this study potentially influences this result. The model does not resolve the convective mixing of aerosol particles into the lower free troposphere or the enhancement of near-surface extinction from nighttime cooling and hygroscopic effects.

Aerosols; Air quality; Lidars/Lidar observations; ↗
DOE OSTI2021

Tuning Hybrid exciton–Photon Fano Resonances in Two-Dimensional Organic–Inorganic Perovskite Thin Films

As easy-to-grow quantum wells with narrow excitonic features at room temperature, two-dimensional (2D) Ruddleson–Popper perovskites are promising for realizing novel nanophotonic devices based on exciton–photon interactions. Here, we demonstrate a distinct hybrid exciton–photon Fano resonance in (C 4 H 9 NH 3 ) 2 PbI 4 thin films prepared via spin coating. Using a classical coupled-oscillator model and finite-difference time-domain simulations, we link the Fano interference to the coupling of the exciton with the Rayleigh-like scattering of the film microstructure. Combining colloidal plasmonic cavities with the 2D perovskite films, we demonstrate tuning of the Fano resonance. In combination with silver nanoparticles, the exciton–photon Fano interference couples to the in-plane plasmonic modes with indications of Rabi splitting. By creating a nanoparticle on mirror geometry, we address the out-of-plane excitonic component, reaching an intermediate coupling regime. Furthermore, these structures suggest possible photonic targets for biomolecular self-assembly applications.

2D perovskites↗
DOE OSTI2025

Transport of Delocalized Excitons through DNA-Based Molecular Photonic Wires

Molecular photonic wires conduct electronic energy via their rapid transport properties. In photosynthesis, nature achieves efficient transport across large distances using delocalized excitons, generated by strong excitonic coupling between chromophores. How, or even whether, delocalization facilitates long-distance energy transport in synthetic systems has been challenging to experimentally test and optimize. Thus, far, studies have been limited to strongly coupled, heterogeneous chromophore aggregates or weakly coupled chromophore monomers. Here, in this work, we employed DNA nanostructures to engineer molecular photonic wires constructed from a series of excitonically coupled indocarbocyanine chromophores─achieving the intermediate and strong coupling regimes. Using time-resolved fluorescence spectroscopy and complementary simulations, we demonstrated that an intermediate intermolecular electronic coupling (∼ k B T ) enables up to 40% faster exciton transport as compared to strongly coupled chromophores. The delocalized excitons generated in the intermediate coupling regime exhibited properties conducive to rapid diffusivity, similar to their monomeric counterparts. Thus, intermediate excitonic coupling, analogous to natural systems, achieves long-distance exciton transport with the high chromophore density required for energy capture.

DNA origami↗
DOE OSTI2022

Marmot V2

MARMOT is a robust numerical tool for mesoscale modeling of fuel performance developed under the NEAMS Fuels technical area to predict the coevolution of microstructure and properties in fuel and cladding materials. MARMOT accomplishes this using the phase field method coupled with finite strain mechanics and heat conduction. MARMOT is based on the open source Multiphysics Object-Oriented Simulation Environment (MOOSE) and solves the coupled partial differential equations defining the physics using the finite element method. MARMOT is being developed in order to facilitate the development of improved materials models for fuel performance, but it is also being developed as a powerful tool in and of itself for the simulation of mesoscale fuel performance.

Aagesen, LarryK.↗
DOE OSTI2022

Coupling localized Noah-MP-Crop model with the WRF model improved dynamic crop growth simulation across Northeast China

Croplands play a critical role in regulating the energy and moisture exchanges between the land surface and atmosphere. However, the interactions between cropland and climate are usually poorly represented due to a lack of detailed representation in crop types and field management. Here, we coupled the Noah-MP-Crop model with the state-of-the-art Weather Research and Forecasting (WRF) model to explore and evaluate the crop growth dynamics in response to climate variations across Northeast China. The default parameters of the crop model were not exactly suitable for the agricultural ecosystems in Northeast China. The detailed cropland distribution, and crop phenology parameters including growing degree days (GDD) and planting (harvesting) date were first created using multi-source remote sensing products and reanalysis data, and was then successfully used to simulate the growth and yield for corn and soybean and associated energy exchanges. We also optimized and calibrated other crop parameters using the time-series of the Moderate Resolution Imaging Spectroradiometer (MODIS) land surface products. The modified crop model substantially improved the simulation of crop growth, plant physiology, and biomass accumulation for both corn and soybean. Coupling the localized dynamic crop model into the WRF led to considerable decreases in the simulated mean-absolute-errors (MAEs) and biases of the leaf area index, evapotranspiration, and gross primary production compared with the MODIS observed values. Compared with the statistical yield from each province, the modified crop model underestimated the corn yield from 11.1% to 48.6%, whereas overestimated the soybean yield from 16.5% to 162.6%.

54 ENVIRONMENTAL SCIENCES↗