Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “FLUX”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

A Comparison Between Gravity Wave Momentum Fluxes in Observations and Climate Models

For the first time, a formal comparison is made between gravity wave momentum fluxes in models and those derived from observations. Although gravity waves occur over a wide range of spatial and temporal scales, the focus of this paper is on scales that are being parameterized in present climate models, sub-1000-km scales. Only observational methods that permit derivation of gravity wave momentum fluxes over large geographical areas are discussed, and these are from satellite temperature measurements, constant-density long-duration balloons, and high-vertical-resolution radiosonde data. The models discussed include two high-resolution models in which gravity waves are explicitly modeled, Kanto and the Community Atmosphere Model, version 5 (CAM5), and three climate models containing gravity wave parameterizations,MAECHAM5, Hadley Centre Global Environmental Model 3 (HadGEM3), and the Goddard Institute for Space Studies (GISS) model. Measurements generally show similar flux magnitudes as in models, except that the fluxes derived from satellite measurements fall off more rapidly with height. This is likely due to limitations on the observable range of wavelengths, although other factors may contribute. When one accounts for this more rapid fall off, the geographical distribution of the fluxes from observations and models compare reasonably well, except for certain features that depend on the specification of the nonorographic gravity wave source functions in the climate models. For instance, both the observed fluxes and those in the high-resolution models are very small at summer high latitudes, but this is not the case for some of the climate models. This comparison between gravity wave fluxes from climate models, high-resolution models, and fluxes derived from observations indicates that such efforts offer a promising path toward improving specifications of gravity wave sources in climate models.

mathematical models↗
NASA NTRS2017

Seasonal Clear-Sky Flux and Cloud Radiative Effect Anomalies in the Arctic Atmospheric Column Associated with the Arctic Oscillation and Arctic Dipole

The impact of the Arctic Oscillation (AO) and Arctic Dipole (AD) on the radiative flux into the Arctic mean atmospheric column is quantified. 3-month-averaged AO and AD indices are regressed with corresponding surface and top-of-atmosphere (TOA) fluxes from the CERES-SFC and CERES-TOA EBAF datasets over the period 2000-2014. An increase in clear-sky fluxes into the Arctic mean atmospheric column during fall is the largest net flux anomaly associated with AO, primarily driven by a positive net longwave flux anomaly (i.e. increase of net flux into the atmospheric column) at the surface. A decrease in the Arctic mean atmospheric column cloud radiative effect during winter and spring is the largest flux anomaly associated with AD, primarily driven by a change in the longwave cloud radiative effect at the surface. These prominent responses to AO and AD are widely distributed across the ice-covered Arctic, suggesting that the physical process or processes that bring about the flux change associated with AO and AD are distributed throughout the Arctic.

Hegyi, Bradley M.↗
NASA NTRS2017

Estimation of Reconnection Flux Using Post-Eruption Arcades and Its Relevance to Magnetic Clouds at 1 AU

We report on a new method to compute the flare reconnection (RC) flux from post-eruption arcades (PEAs) and the underlying photospheric magnetic fields. In previous works, the RC flux has been computed using the cumulative flare ribbon area. Here we obtain the RC flux as the flux in half of the area underlying the PEA in EUV imaged after the flare maximum. We apply this method to a set of 21 eruptions that originated near the solar disk center in Solar Cycle 23. We find that the RC flux from the arcade method ((Phi)rA) has excellent agreement with the flux from the flare-ribbon method ((Phi)rR) according to (Phi)rA = 1.24((Phi)rR)(sup 0.99). We also find (Phi)rA to be correlated with the poloidal flux ((Phi)P) of the associated magnetic cloud at 1 AU: (Phi)P = 1.20((Phi)rA)(sup 0.85). This relation is nearly identical to that obtained by Qiu et al. (Astrophys. J. 659, 758, 2007) using a set of only 9 eruptions. Our result supports the idea that flare reconnection results in the formation of the flux rope and PEA as a common process.

Gopalswamy, N.↗
NASA NTRS2019

Integrating Remote Sensing Observations with NASA's GEOS-5 Modeling Framework in Support of Retrospective Analyses and Seasonal Prediction of Biosphere-Atmosphere CO2 Flux

The absorption of nearly half of all anthropogenic carbon dioxide (CO2) emissions by terrestrial and marine ecosystems has played a critical role in mitigating climate change. However, a persistent lack of understanding of these uptake processes impedes attribution, and thereby introduces large uncertainties into projections of the trajectory of carbon and climate in coming decades. A better understanding and quantification of the seasonal and interannual variability of carbon flux between the atmosphere and ocean and terrestrial biospheres is critically needed to improve predictions from Earth system models. We propose to bring together a diverse suite of remote sensing observations, mechanistic models, and NASA's Goddard Earth Observing System, version 5 (GEOS-5) model to address two objective 1) quantify the processes controlling the temporal variability of biosphere-atmosphere CO2 flux on seasonal and interannual timescales from 1989 to 2018 and 2) evaluating the predictability of the components of carbon flux on seasonal timescales. Because GEOS-5 has been developed to incorporate a variety of Earth system observations and includes a complete and physically consistent depiction of the atmosphere, land, and ocean carbon cycles, it represents a unique and ideal synthesis framework for this effort. By expanding the realism of processes that could be included in GEOS-5 seasonal forecasts, this effort supports NASA's goals toward an integrated Earth system modeling and prediction framework.We propose to integrate a number of observations into the GEOS-5 modeling system to refine retrospective estimates of both terrestrial and marine carbon flux and to test hypotheses regarding the effects of climate drivers on terrestrial carbon flux. This will include assimilating several satellite ocean color products in the NASA Ocean Biogeochemistry Model (NOBM) to improve the representation of ocean biology. We will also utilize remote sensing datasets to increase the temporal resolution of global land-use change estimates and fire emissions to better constrain the temporal variability of the terrestrial carbon cycle. This information will be incorporated into two NASA terrestrial biosphere models Catchment-CN, a dynamic vegetation model that is integrated within GEOS-5 and the Ecosystem Demography (ED) model, a core modeling resource supporting the Global Ecosystem Dynamics Investigation (GEDI) mission to map biomass. Fluxes will be evaluated through 1) comparison to top-down flux estimates inferred from surface CO2 observations and 2) comparison against available aircraft and satellite observations.By combining predictions of net ecosystem exchange and air-sea CO2 flux from land and ocean models with statistical predictions of land use change, fire, and fossil fuel emissions, we propose to create the first dynamical CO2 forecast on seasonal timescales. Because of the experimental nature of this endeavor, an important project objective will be to evaluate the limits to the predictability of different carbon cycle processes over lead times of 1-12 months using different satellite and surface data streams.

Ott, Lesley↗
NASA NTRS2020

The Flux of Impact Ejecta on the Lunar Surface from Scaling Considerations: Implications for Operational Hazards and Geomorphic Forcing

The impact cratering process has been critical to the evolution of the Moon’s surface over its geologic history and remains an important ongoing process today. Impact events have a major local effect, but also excavate ejecta particles that re-impact the lunar surface over a wide area. Quantifying the flux of ejecta to a given point on the Moon is the subject of this work. We also estimate how this flux is partitioned into different particle sizes and different ejecta velocities. Motivation: There are two main factors motivating this work. First, and most critically, is the assessment of the hazard posed by impact ejecta for future surface exploration (i.e., to infrastructure, spacesuits, etc.). LROC observations of new craters have led to the reemphasized need to consider this hazard. In fact, a hazard assessment of this type was made prior to Apollo, although some of the underlying assumptions of that work are now clearly obsolete (see [4]). We also now know much more about the impactor flux, scaling of impact events, and scaling of ejecta than was known in the 1960's, so revisiting this hazard assessment is appropriate.We note that also have recently revisited the earlier hazard estimates and independently revised them downward using an entirely different analytical approach. The second motivation is that several recent papers have argued that the flux of distal ejecta is the controlling factor in how fast the lunar surface evolves. For this reason, improving understanding of the ejecta mass flux and how the flux translates into geomorphic work is of interest. To be clear, it is obvious that the ejecta mass flux is much larger than the primary impactor mass flux – indeed, this is self-evident because the craters excavated by hypervelocity impacts are much larger than their impactors. On the other hand, the energy delivered by a given primary to the surface is larger than the sum of the energy delivered by all its associated ejecta, as required by conservation, aggravated by the fact that not all of an impactor’s kinetic energy is partitioned into ejecta excavation. If distal ejecta and secondaries control lunar geomorphic evolution, this suggests that re-impacting ejecta must more efficiently translate their energy into geomorphic work than primaries. It is also easy to imagine the relative efficiency of primary and secondary impacts to do geomorphic work varying with the size of the primary. Considering the details of this process is thus of significant interest for lunar geomorphology.

Fassett, C. I.↗
NASA NTRS2019

Decomposing Shortwave Top-of-Atmosphere and Surface Radiative Flux Variations in Terms of Surface and Atmospheric Contributions

Adiagnostic tool for determining surface and atmospheric contributions to interannual variations in top-of-atmosphere (TOA) reflected shortwave (SW) and net downward SW surface radiative fluxes is introduced. The method requires only upward and downward radiative fluxes at the TOA and surface as input and therefore can readily be applied to both satellite-derived and model-generated adiative fluxes. Observations from the Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) Edition 4.0 product show that 81% of the monthly variability in global mean reflected SW TOA flux anomalies is associated with atmospheric variations (mainly clouds),6%is from surface variations, and 13% is from atmosphere–surface covariability. Over the Arctic Ocean, most of the variability in both reflected SW TOA flux and net downward SW surface flux anomalies is explained by variations in sea ice and cloud fraction alone (r2 5 0.94). Compared to CERES, variability in two reanalyses—the ECMWF interim reanalysis (ERA-Interim) and NASA’s Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2)—show large differences in the regional distribution of variance for both the atmospheric and surface contributions to anomalies in net downward SW surface flux. For MERRA-2 the atmospheric contribution is 17% too large compared to CERES while ERA-Interim underestimates the variance by 15%. The difference is mainly due to how cloud variations are represented in the reanalyses. The overall surface contribution in both ERA-Interim and MERRA-2 is smaller than CERES EBAF by 15% for ERA-Interim and 58% for MERRA-2, highlighting limitations of the reanalyses in representing surface albedo variations and their influence on SW radiative fluxes.

Norman G. Loeb↗
NASA NTRSDate not supplied

CERES Top-of-atmosphere and Surface fluxes in the Arctic: A comparison with ARISE and MOSAiC measurements

Uncertainty in the NASA Clouds and the Earth’s Radiant Energy System (CERES)-derived irradiances is larger over sea ice than any other surface type and comes from several sources. This presentation summarizes results from comparisons of CERES data with the year-long Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in the central Arctic and the Arctic Radiation and Icebridge Sea ice Experiment (ARISE). The CERES Synoptic 1degree (SYN1deg) product overestimates the downwelling shortwave flux by 11.40 Wm–2 and underestimates the upwelling shortwave flux by –15.70 Wm–2 and downwelling longwave fluxes by –12.58 Wm–2 at the surface during summer. In addition, large differences are found in the upwelling longwave flux when the surface approaches the melting point (approximately 0C). The large negative bias in upwelling shortwave flux can be attributed in large part to lower surface albedo (–0.15) in satellite footprint relative to surface sensors. The CERES-MOSAiC broadband albedo differences (approximately 20 Wm–2) explain a larger portion of the upwelling shortwave flux difference than the spectral albedo shape differences (approximately 3 Wm–2). The ARISE results indicate the some of these differences in the SW are due to the scene identification and representation of anisotropy in partly cloud scenes. Switching from imager-based to passive microwave-based sea ice data in the CERES inversion process reduces the differences in the grid box average fluxes and in the sea ice partly cloudy scene anisotropy in the instantaneously-matched footprints. Our analysis indicates that calibration and sampling uncertainty limit the ability to place strong constraints (<7%) on CERES TOA fluxes with aircraft measurements. The results indicate that improvements in the surface albedo and cloud data would substantially reduce the uncertainty in the Arctic surface radiation budget derived from CERES data products.

Patrick C Taylor↗
NASA NTRSDate not supplied

A Machine Learning Approach to Determine Surface Radiative Fluxes based on CERES Observations

The Clouds and Earth’s Radiant Energy System (CERES) projects provides satellite-based observations of the radiative fluxes and clouds systems. CERES climate quality data products typically take several months of calibration and validation before release to the public. An alternative data product, Fast Longwave and Shortwave radiative Flux (FLASHFlux), was created to provide data to the applied sciences and educational users. FLASHFlux provides Top-of-Atmosphere radiative fluxes, Clouds properties, and parameterized surface radiative fluxes within four days for footprint (Level 2) data. We investigate the use of Artificial Neural Network (ANN) using MODerate resolution Imaging Spectroradiometer (MODIS) derived clouds properties and meteorology from the Global Assimilation and Meteorology Office (GMAO) scaled to the CERES footprint from the CERES Clouds Radiative Swath (CRS) data product to compute surface radiative fluxes. We test ANN produce fluxes against surface fluxes produced from the Fu-Liou model used in CRS and the Langley Parameterized Shortwave Algorithm (LPSA) and Langley Parameterized Longwave Algorithm (LPLA) used in FLASHFlux. We also validated each model with ground-based observations. Furthermore, we investigate Leave-One-Feature-Out Importance (LOFO) to evaluate the significance of each feature in our training and provide insight for future models. Advances in machine learning, along with increases in computational capabilities and available data allow us to estimate effects of unresolved processes in our climate without direct modeling. This work evaluates the ability to create accurate data-driven models to supplement or replace current models that estimate surface radiative fluxes.

Climatology↗
NASA NTRSDate not supplied

Artificial Neural Network (ANN) Surface Longwave and Shortwave Fluxes Trained on CERES Observations

The Clouds and Earth’s Radiant Energy System (CERES) project provides satellite-based observations of the radiative fluxes and clouds systems. CERES climate quality data products typically take several months of calibration and validation before release to the public. The Fast Longwave and Shortwave Radiative Flux (FLASHFlux) data product was developed to provide key data for the applied sciences and educational users within a week of observation. FLASHFlux achieves this by using simplified calibration, an operational meteorological product from Global Modeling and Assimilation Office (GMAO), and its own surface parameterizations model. The CERES FLASHFlux provides two data products: 1) an hourly Level 2 Single Scanner Footprint (SSF) data separately for Terra and NOAA-20 observations, and 2) a daily Level 3 Time Interpolated and Spatially Averaged (TISA) 1o x 1o gridded data that combines Terra and NOAA-20 observations. Currently, FLASHFlux uses the Langley Parameterized Shortwave Algorithm (LPSA) and Langley Parameterized Longwave Algorithm (LPLA) to derive its surface fluxes (Kratz et al., 2010; Gupta et al, 2001). A new Machine Learning (ML) based approach using Artificial Neural Networks to derive Surface Longwave (LW) & Shortwave (SW) fluxes based on training data from the CERES Clouds Radiative Swath (CRS) product is being investigated to replace LPSA and LPLA in the SSF surface flux products. One of the biggest hurdles in training ML model is model fitting. To overcome the problem of overfitting we use feature engineering that helps in finding the important feature and remove features that are irrelevant to the model. In our training we employed the Leave-One-Feature-Out Importance (LOFO) to evaluate the significance of each feature in our training. We intercompare ANN fluxes against surface fluxes produced from the Fu-Liou model in CRS and the LPSA/LPLA in FLASHFlux SSF. Furthermore, we validated ANN derived fluxes to the Baseline Surface Radiation Network (BSRN).

P C Sawaengphokhai↗
NASA NTRSDate not supplied

Calorimeter Heat Flux Trends in NASA’s Subscale Rotating Detonation Rocket Engine

A calorimeter-style rotating detonation rocket engine (RDRE) outer chamber body was designed, additively manufactured in GRCop-42, and hot-fire tested in test cell 105 at NASA Marshall Space Flight Center (MSFC) in Huntsville, AL in August 2024. Steady-state, spatially resolved heat flux and chamber pressure were measured at 13 and 9 locations from the injector face, respectively, for a variety of test conditions and hardware configurations with gaseous methane and oxygen propellants. The 2-in. diameter highly instrumented design, enabled by metal additive manufacturing (AM), allowed for simultaneous measurement of heat flux and chamber pressure through 44 long duration hot-fire tests without failure. Of the 44 tests, only 3 of the tests featured chamber pressures below 100 psia and are discussed in this work. Heat flux trends for this subscale hardware are explored with respect to local propellant mass flux for several different injectors, chamber lengths, and chamber “subsonic” area ratios (contraction ratios). Results show that for increasing chamber pressure, a reduced amount of energy per kilogram of propellant is transferred to the wall. Switching injectors affects the near-face heat flux and chamber pressure profiles. Chamber length does not noticeably affect the heat flux profile but increases bulk heat load. A subsonic area ratio greater than 1 reduces heat losses to the wall compared to a straight annulus case. Equivalence ratio shift did not significantly affect heat flux. Computational fluid dynamics (CFD) and conjugate heat transfer (CHT) analyses were performed to delineate 3-D heat transfer and coolant mass flow maldistribution effects and create a calorimeter transfer function to transform heat flux data and mitigate the profile distortions. Additional CFD/CHT simulations were performed using experimental data as boundary conditions to assess local nucleate boiling propensity during testing and to assess projected hot wall temperatures for future fatigue assessment. Vapor fractions were observed locally for several cases. It is anticipated that this effort will provide a common framework for coolant system design/analysis in calorimeter systems for rocket-based and air-breathing combustors, ensuring greater repeatability in calorimetry measurements across the research community.

Joseph Hernandez-McCloskey↗
DOE OSTI2012

Parallel transport of long mean-free-path plasma along open magnetic field lines: Parallel heat flux

In a long mean-free-path plasma where temperature anisotropy can be sustained, the parallel heat flux has two components with one associated with the parallel thermal energy and the other the perpendicular thermal energy. Due to the large deviation of the distribution function from local Maxwellian in an open field line plasma with low collisionality, the conventional perturbative calculation of the parallel heat flux closure in its local or non-local form is no longer applicable. Here, a non-perturbative calculation is presented for a collisionless plasma in a two-dimensional flux expander bounded by absorbing walls. Specifically, closures of previously unfamiliar form are obtained for ions and electrons, which relate two distinct components of the species parallel heat flux to the lower order fluid moments such as density, parallel flow, parallel and perpendicular temperatures, and the field quantities such as the magnetic field strength and the electrostatic potential. The plasma source and boundary condition at the absorbing wall enter explicitly in the closure calculation. Although the closure calculation does not take into account wave-particle interactions, the results based on passing orbits from steady-state collisionless drift-kinetic equation show remarkable agreement with fully kinetic-Maxwell simulations. As an example of the physical implications of the theory, the parallel heat flux closures are found to predict a surprising observation in the kinetic-Maxwell simulation of the 2D magnetic flux expander problem, where the parallel heat flux of the parallel thermal energy flows from low to high parallel temperature region.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2012

DETECTION OF THE HORIZONTAL DIVERGENT FLOW PRIOR TO THE SOLAR FLUX EMERGENCE

It is widely accepted that solar active regions including sunspots are formed by the emerging magnetic flux from the deep convection zone. In previous numerical simulations, we found that the horizontal divergent flow (HDF) occurs before the flux emergence at the photospheric height. This paper reports the HDF detection prior to the flux emergence of NOAA AR 11081, which is located away from the disk center. We use SDO/HMI data to study the temporal changes of the Doppler and magnetic patterns from those of the reference quiet Sun. As a result, the HDF appearance is found to come before the flux emergence by about 100 minutes. Also, the horizontal speed of the HDF during this time gap is estimated to be 0.6-1.5 km s{sup -1}, up to 2.3 km s{sup -1}. The HDF is caused by the plasma escaping horizontally from the rising magnetic flux. And the interval between the HDF and the flux emergence may reflect the latency during which the magnetic flux beneath the solar surface is waiting for the instability onset to the further emergence. Moreover, SMART H{alpha} images show that the chromospheric plages appear about 14 minutes later, located cospatial with the photospheric pores. This indicates that the plages are caused by plasma flowing down along the magnetic fields that connect the pores at their footpoints. One important result of observing the HDF may be the possibility of predicting the sunspot appearances that occur in several hours.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

MAGNETIC FLUX DENSITY MEASURED IN FAST AND SLOW SOLAR WIND STREAMS

The radial component of the heliospheric magnetic field vector is used to estimate the open magnetic flux density of the Sun. This parameter has been calculated using observations from the Ulysses mission that covered heliolatitudes from 80 Degree-Sign S to 80 Degree-Sign N, from 1990 to 2009 and distances from 1 to 5.4 AU, the Advanced Composition Explorer mission at 1 AU from 1997 to 2010, the OMNI interplanetary database from 1971, and the Helios 1 and 2 missions that covered the distance range from 0.3 to 1 AU. The flux density was found to be much affected by fluctuations in the magnetic field which make its calculated value dependent on heliospheric location, type of solar wind (fast or slow), and the level of solar activity. However, fluctuations are distributed symmetrically perpendicular to the average Parker direction. Therefore, distributions of the field vector in the two-dimensional plane defined by the radial and azimuthal directions in heliospheric coordinates provide a way to reduce the effects of the fluctuations on the measurement of the flux density. This leads to a better defined flux density parameter; the distributions modified by removing the effects of fluctuations then allow a clearer assessment of the dependence of the flux density on heliospheric location, solar wind type, and solar activity. This assessment indicates that the flux density normalized to 1 AU is independent of location and solar wind type (fast or slow). However, there is a residual dependence on solar activity which can be studied using the modified flux density measurements.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

High Flux Isotope Reactor Neutron Spectrum Shape Estimation From Activation Experiment Data

Here, this article provides a comprehensive review of historical irradiation dosimetry available for different locations within the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL). This article includes a summary of the available measured activation target data covering a span of over 15 years and 39 experimental campaigns, including 200 individual sample locations evaluated. Using this broad set of data, we reconstruct historic average neutron spectra shapes for HFIR at various locations, including within the flux trap region, beryllium reflectors, and hydraulic tube (HT) regions, at both the 100- and 85-MW operational power. Our findings indicate that the general axial flux distribution shows a relatively small change in transition from 100- to 85-MW operating power, with differences of -6% to +15% for the thermal energy range and around -16% to +8% for the fast range, indicating a sharper drop-off of the thermal neutron flux away from the axial center. Compared with historical dosimetry estimates of the HFIR flux shape, we generally find a moderately broader axial profile shape for thermal neutrons in the interior target regions for the 100-MW samples evaluated but relatively close agreement for the present 85-MW flux shape for both thermal and fast fluxes.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

High upward fluxes of formic acid from a boreal forest canopy

Eddy covariance fluxes of formic acid, HCOOH, were measured over a boreal forest canopy in spring/summer 2014. The HCOOH fluxes were bidirectional but mostly upward during daytime, in contrast to studies elsewhere that reported mostly downward fluxes. Downward flux episodes were explained well by modeled dry deposition rates. The sum of net observed flux and modeled dry deposition yields an upward “gross flux” of HCOOH, which could not be quantitatively explained by literature estimates of direct vegetative/soil emissions nor by efficient chemical production from other volatile organic compounds, suggesting missing or greatly underestimated HCOOH sources in the boreal ecosystem. Here, we implemented a vegetative HCOOH source into the GEOS-Chem chemical transport model to match our derived gross flux and evaluated the updated model against airborne and spaceborne observations. Model biases in the boundary layer were substantially reduced based on this revised treatment, but biases in the free troposphere remain unexplained.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Short-term favorable weather conditions are an important control of interannual variability in carbon and water fluxes

Ecosystem models often perform poorly in reproducing interannual variability in carbon and water fluxes, resulting in considerable uncertainty when estimating the land-carbon sink. While many aggregated variables (growing season length, seasonal precipitation, or temperature) have been suggested as predictors for interannual variability in carbon fluxes, their explanatory power is limited and uncertainties remain as to their relative contributions. Recent results show that the annual count of hours where evapotranspiration (ET) is larger than its 95th percentile is strongly correlated with the annual variability of ET and gross primary production (GPP) in an ecosystem model. This suggests that the occurrence of favorable conditions has a strong influence on the annual carbon budget. Here we analyzed data from eight forest sites of the AmeriFlux network with at least 7 years of continuous measurements. We show that for ET and the carbon fluxes GPP, ecosystem respiration (RE), and net ecosystem production, counting the “most active hours/days” (i.e., hours/days when the flux exceeds a high percentile) correlates well with the respective annual sums, with correlation coefficients generally larger than 0.8. Phenological transitions have much weaker explanatory power. By exploiting the relationship between most active hours and interannual variability, we classify hours as most active or less active and largely explain interannual variability in ecosystem fluxes, particularly for GPP and RE. Our results suggest that a better understanding and modeling of the occurrence of large values in high-frequency ecosystem fluxes will result in a better understanding of interannual variability of these fluxes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Characterizing the flux effect on the irradiation embrittlement of reactor pressure vessel steels using machine learning

In-service exposure to high-energy neutrons embrittles reactor pressure vessel (RPV) steels. An increase in the yield stress (Δσ y ) results in a corresponding increase in the brittle to ductile transition temperature (ΔT c ). Most existing models underpredict ΔT c at higher fluence following accelerated irradiations in test reactors. High fluence, up to 10 20 n/cm 2 in some cases, will be reached over extended RPV vessel operation of 80 years, or more, at low service flux. Embrittlement has been extensively studied in accelerated, higher flux test reaction irradiations. However, the use of test reactor data naturally raises the question of flux effects. Here, this study used a machine learning approach trained on a set of hardening data, covering a wide range of flux, fluence, and steel compositions to determine the interactive effects of both irradiation and material variables on Δσ y . The analysis included machine learning-based cross-plots of the variable dependence of Δσ y for six core steels (i.e., CM6, LC, LD, LG, LH, and LI), with controlled differences in their Cu and Ni contents. A primary objective is to evaluate an effective to actual fluence (Φt e /Φt) ratio, as a function of flux, fluence, and steel composition. This is information critical to properly use intermediate flux-high fluence data in calibrating a low flux-high fluence embrittlement model. The predicted Φt e /Φt is reasonably consistent with estimates previously derived from a physics-based solute recombination trap model.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Development of a Benchmark Eddy Flux Evapotranspiration Dataset for Evaluation of Satellite-Driven Evapotranspiration Models Over the CONUS

A large sample of ground-based evapotranspiration (ET) measurements made in the United States, primarily from eddy covariance systems, were post-processed to produce a benchmark ET dataset. The dataset was produced primarily to support the intercomparison and evaluation of the OpenET satellite-based remote sensing ET (RSET) models and could also be used to evaluate ET data from other models and approaches. OpenET is a web-based service that makes field-delineated and pixel-level ET estimates from well-established RSET models readily available to water managers, agricultural producers, and the public. The benchmark dataset is composed of flux and meteorological data from a variety of providers covering native vegetation and agricultural settings. Flux footprint predictions were developed for each station and included static flux footprints developed based on average wind direction and speed, as well as dynamic hourly footprints that were generated with a physically based model of upwind source area. The two footprint prediction methods were rigorously compared to evaluate their relative spatial coverage. Data from all sources were post-processed in a consistent and reproducible manner including data handling, gap-filling, temporal aggregation, and energy balance closure correction. The resulting dataset included 243,048 daily and 5,284 monthly ET values from 194 stations, with all data falling between 1995 and 2021. We assessed average daily energy imbalance using 172 flux sites with a total of 193,021 days of data, finding that overall turbulent fluxes were understated by about 12% on average relative to available energy. Multiple linear regression analyses indicated that daily average latent energy flux may be typically understated slightly more than sensible heat flux. This dataset was developed to provide a consistent reference to support evaluation of RSET data being developed for a wide range of applications related to water accounting and water resources management at field to watershed scales.

54 ENVIRONMENTAL SCIENCES↗