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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 1,657 records · Page 92
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NASA NTRS1991

The dynamics of the HSCT environment

Assessments of the impact of aircraft engine exhausts on stratospheric ozone levels are currently limited to 2D zonally-averaged models which, while completely representing chemistry, involve high parameterization of transport processes. Prospective 3D models under development by NASA-Goddard will use winds from a data-assimilation procedure; the upper troposphere/lower stratosphere behavior of one such model has been verified by direct comparison of model simulations with satellite, balloon, and sonde measurements. Attention is presently given to the stratosphere/troposphere exchange and nonzonal distribution of aircraft engine exhaust.

Douglass, Anne R.↗
NASA NTRS2022

AgMIP Regional Integrated Assessment of Agricultural Systems in Nioro, Senegal: Representative Agricultural Pathways, Climate, Crop and Economic Datasets

This paper describes the datasets that were used to implement an AgMIP Regional Integrated Assessment for the Nioro region of Senegal to assess the potential impacts of climate change on the principal agricultural system in the Senegal peanut basin and to assess adaptations of that system to climate change under current as well as future climate and socio-economic conditions. This dataset includes the Representative Agricultural Pathways developed for Nioro from 2000-2050; the climate data that were used to implement crop yield simulations; the data that were used to parameterize the DSSAT and APSIM crop models, including historical climate data and future climate scenarios; and the data that were used to parameterize the Tradeoff Analysis Model for Multi-dimensional Impact Assessment (TOAMD) economic simulation model, as well as simulated model outputs.

AgMIP↗
DOE OSTI2022

Plant litter traits control microbial decomposition and drive soil carbon stabilization

Efforts to manage soils for carbon (C) sequestration remain limited by our understanding of how differences in plant traits and microbial traits mechanistically drive soil organic C (SOC) storage. Addressing this uncertainty is particularly critical in bioenergy agriculture, due to its potential to enhance soil C and provide a C neutral fuel. As such, we examined differences between two contrasting feedstocks, Zea mays (corn) and Miscanthus x giganteus (miscanthus), in the ability of their litter to form new chemically resistant particulate SOC vs. physically protected mineral associated SOC and used this data to improve the parameterization of a microbial SOC model. We tested a hypothesized conceptual model whereby easy to decompose corn litters drive greater microbial carbon use efficiency (CUE) and the formation of more mineral associated SOC over particulate SOC than more complex miscanthus litters. To do this, we performed a soil microcosm experiment where we added 13 C enriched aboveground and belowground litters to soils and traced the fate of the 13 C into microbial respiration and SOC pools. We found that corn litters promoted higher microbial CUE (0.37) than miscanthus litters (0.24). In turn, corn litter formed approximately 50% more mineral associated SOC than miscanthus litters. Similarly, structurally complex root litters promoted a lower CUE and formed less mineral associated SOC than leaf and shoot litters for both crops. When we used our data to parameterize the SOC model, we found that modelling microbial trait differences uniquely allowed the model to capture the fate of litter C in SOC. Collectively, we found a robust link between litter quality, microbial efficiency, and the formation of SOC. This link bridges the empirical uncertainty in how different crops can form new soil C and provides an empirical basis for modelling SOC transformations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Sources and pathways of the upscale effects on the Southern Hemisphere jet in MPAS-CAM4 variable-resolution simulations

Impacts of regional grid refinement on large-scale circulations (“upscale effects”) were detected in a previous study that used the Model for Prediction Across Scales-Atmosphere coupled to the physics parameterizations of the Community Atmosphere Model version 4. The strongest upscale effect was identified in the Southern Hemisphere jet during austral winter. This study examines the detailed underlying processes by comparing two simulations at quasi-uniform resolutions of 30 and 120 km to three variable-resolution simulations in which the horizontal grids are regionally refined to 30 km in North America, South America, or Asia from 120 km elsewhere. In all the variable-resolution simulations, precipitation increases in convective areas inside the high-resolution domains, as in the reference quasi-uniform high-resolution simulation. With grid refinement encompassing the tropical Americas, the increased condensational heating expands the local divergent circulations (Hadley cell) meridionally such that their descending branch is shifted poleward, which also pushes the baroclinically unstable regions, momentum flux convergence, and the eddy-driven jet poleward. This teleconnection pathway is not found in the reference high-resolution simulation due to a strong resolution sensitivity of cloud radiative forcing that dominates the aforementioned teleconnection signals. The regional refinement over Asia enhances Rossby wave sources and strengthens the upper level southerly flow, both facilitating the cross-equatorial propagation of stationary waves. Evidence indicates that this teleconnection pathway is also found in the reference high-resolution simulation. Lastly, the result underlines the intricate diagnoses needed to understand the upscale effects in global variable-resolution simulations, with implications for science investigations using the computationally efficient modeling framework.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Atmospheric chemistry of hydrogen fluoride

In this study, the atmospheric chemistry, emissions, and surface boundary layer transport of hydrogen fluoride (HF) is summarized. Although HF is known to be chemically reactive and highly soluble, both factors affect transport and removal in the atmosphere, we suggest that the chemistry can be ignored when the HF concentration is at a sufficiently low level (e.g., 10 ppmv). At a low concentration, the capability for HF to react in the atmosphere is diminished and therefore the species can be mathematically treated as inert during the transport. At a sufficiently high concentration of HF (e.g., kg/s release rate and thousands of ppm), however, HF can go through a series of rigorous chemical reactions including polymerization, depolymerization, and reaction with water to form molecular complex. As such, the HF species cannot be considered as inert because the reactions could intimately influence the plume s thermodynamic properties affecting the changes in plume temperature and density. The atmospheric residence time of HF was found to be less than four (4) days, and deposition (i.e., atmosphere to surface transport) is the dominant mechanism that controls the removal of HF and its oligomers from the atmosphere. The literature data on HF dry deposition velocity was relatively high compared to many commonly found atmospheric species such as ozone, sulfur dioxide, nitrogen oxides, etc. The global average of wet deposition velocity of HF was found to be zero based on one literature source. Uptake of HF by rain drops is limited by the acidity of the rain drops, and atmospheric particulate matter contributes negligibly to HF uptake. Finally, given that the reactivity of HF at a high release rate and elevated mole concentration cannot be ignored, it is important to incorporate the reaction chemistry in the near-field dispersion close to the proximity of the release source, and to incorporate the deposition mechanism in the far-field dispersion away from the release source. In other words, a hybrid computational scheme may be needed to address transport and atmospheric chemistry of HF in a range of applications. The model uncertainty will be limited by the precision of boundary layer parameterization and ability to accurately model the atmospheric turbulence.

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

Mechanisms in Regulating the Quasi‐Biennial Oscillation in Exascale Earth System Model Version 2

Abstract The update to the deep convection parameterization in the energy exascale Earth system model version 2 (E3SMv2) makes the simulated quasi‐biennial oscillation (QBO) have a shorter period than without the update when other tunable parameters the same since the update makes convection more intense but less frequent while leaving the time‐mean convective heating tendency almost unchanged. Amplitudes of momentum fluxes of parameterized gravity waves (GWs) are intensified since they are determined by the square of convective heating tendency. In addition, stronger planetary waves are simulated in E3SMv2 with the convection scheme update, partially due to the tropospheric precipitation change. Furthermore, there is evidence that planetary waves are intensified in the stratosphere due to the dissipation of enhanced parameterized GWs. These factors are found to be responsible for modulating the QBO simulated in E3SMv2.

Li, Yuanpu [Climate and Global Dynamics Division U↗
DOE OSTI2016

Multi-objective optimization techniques to design the Pareto front of organic dielectric polymers

Here, we present two Monte Carlo algorithms to find the Pareto front of the chemical space of a class of dielectric polymers that is most interesting with respect to optimizing both the bandgap and dielectric constant. Starting with a dataset generated from density functional theory calculations, we used machine learning to construct surrogate models for the bandgaps and dielectric constants of all physically meaningful 4-block polymers (that is, polymer systems with a 4-block repeat unit). We parameterized these machine learning models in such a way that the surrogates built for the 4-block polymers were readily extendable to polymers beyond a 4-block repeat unit. By using translational invariance, chemical intuition, and domain knowledge, we were able to enumerate all possible 4, 6, and 8 block polymers and benchmark our Monte Carlo sampling of the chemical space against the exact enumeration of the surrogate predictions. We obtained exact agreement for the fronts of 4-block polymers and at least a 90% agreement for those of 6 and 8-block polymers. We present fronts for 10-block polymer that are not possible to obtain by direct enumeration. We note that our Monte Carlo methods also return polymers close to the predicted front and a measure of the closeness. Both quantities are useful information for the design and discovery of new polymers.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A dynamic kinetic model captures cell-free metabolism for improved butanol production

Cell-free systems are useful tools for prototyping metabolic pathways and optimizing the production of various bioproducts. Mechanistically-based kinetic models are uniquely suited to analyze dynamic experimental data collected from cell-free systems and provide vital qualitative insight. However, to date, dynamic kinetic models have not been applied with rigorous biological constraints or trained on adequate experimental data to the degree that they would give high confidence in predictions and broadly demonstrate the potential for widespread use of such kinetic models. In this work, we construct a large-scale dynamic model of cell-free metabolism with the goal of understanding and optimizing butanol production in a cell-free system. Using a combination of parameterization methods, the resultant model captures experimental metabolite measurements across two experimental conditions for nine metabolites at timepoints between 0 and 24 hours. Here, we present analysis of the model predictions, provide recommendations for butanol optimization, and identify the aldehyde/alcohol dehydrogenase as the primary bottleneck in butanol production. Sensitivity analysis further reveals the extent to which various parameters are constrained, and our approach for probing valid parameter ranges can be applied to other modeling efforts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Disentangling the Effects of Temperature, Moisture, and Substrate Availability on Soil CO 2 Efflux

Soil respiration ($R_s$), the largest carbon emission flux in ecosystems, is usually modeled as an empirically parameterized function of temperature, and sometimes water availability. The likely contribution by other factors, such as carbohydrate substrate supply from photosynthesis, has been recognized, but modeling capacity to use this information is limited. Wavelet transformations of the residuals of a seasonal Q 10 temperature response model indicated structure at different temporal scales. In this work, we hypothesize that this indicates the lack of explicit representation of relevant processes in the models. Using cross-spectral analysis, we found that time series of photosynthetically active radiation explained most of the diurnal variation, temperature, explained variability at multiple time scales (diurnal-synoptic), whereas volumetric soil water content correlated with variability in Rs at scales 15-30 days. The results suggest that the time domains of influence for different driving variables of $R_s$ are discrete, and largely nonoverlapping, and represent functional relationships between soil biological activity and its constraints. Analysis of phase angles showed that $R_s$ lagged photosynthetically active radiation by 1.5-3.0 hr. As this time lag was the same in both young and mature trees, with more than fivefold difference in transport distances, we hypothesize that this finding adds to the body of literature that support the pressure-concentration-wave model of carbohydrate availability in plants.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Bayesian Monte Carlo Evaluation of Imperfect (n, 233 U) Data and Model

Conventional nuclear data evaluation methods using generalized linear least squares make the following assumptions: prior and posterior probability distribution functions (PDFs) of all model parameters and data are normal (Gaussian); the linear approximation is sufficiently accurate to minimize the cost function (even for nonlinear models); the model (e.g., of neutron cross section) and experimental data (including covariance data) are without defect and prior PDFs of parameters and measured data are known perfectly. Neglect of covariance between model parameters and measured data in conventional evaluations contributes to imperfections. These assumptions are inherent to the generalized linear least squares minimization method commonly used for resolved resonance region neutron cross section evaluations but are often not justified due to the presence of non-normal PDFs, nonlinear models (e.g., R-matrix formalism), and inherent imperfections in data and models (e.g., imperfect covariance data). Here, these assumptions are removed in a mathematical framework of Bayes’ theorem, which is implemented using the Metropolis-Hastings Monte Carlo method. Most importantly, new parameters are introduced to parameterize discrepancies between the theoretical model and measured data to quantify judgement about discrepancies or imperfections in a reproducible manner. An evaluation of 233U in the eV region using the ENDF-B/VIII.0 library and transmission data (Guber et al.) is presented, and posterior parameters are compared to those obtained by conventional evaluation methods. This example illustrates the effects of removing the most harmful assumption: that of model-data perfection.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

A simple model for short-range ordering kinetics in multi-principal element alloys

Short-range ordering (SRO) in multi-principal element alloys influences material properties such as strength and corrosion. While some degree of SRO is expected at equilibrium, predicting the kinetics of its formation is challenging. We present a simplified isothermal concentration-wave (CW) model to estimate an effective relaxation time of SRO formation. Estimates from the CW model agree to within a factor of five with relaxation times obtained from kinetic Monte Carlo (kMC) simulations when above the highest ordering instability temperature. Further, the advantage of the CW model is that it only requires mobility and thermodynamic parameters, which are readily obtained from alloy mobility databases and Metropolis Monte Carlo simulations, respectively. The simple parameterization of the CW model and its analytical nature makes it an attractive tool for the design of processing conditions to promote or suppress SRO in multicomponent alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Multiscale modeling of spring phenology across Deciduous Forests in the Eastern United States

Abstract Phenological events, such as bud burst, are strongly linked to ecosystem processes in temperate deciduous forests. However, the exact nature and magnitude of how seasonal and interannual variation in air temperatures influence phenology is poorly understood, and model‐based phenology representations fail to capture local‐ to regional‐scale variability arising from differences in species composition. In this paper, we use a combination of surface meteorological data, species composition maps, remote sensing, and ground‐based observations to estimate models that better represent how community‐level species composition affects the phenological response of deciduous broadleaf forests to climate forcing at spatial scales that are typically used in ecosystem models. Using time series of canopy greenness from repeat digital photography, citizen science data from the USA National Phenology Network, and satellite remote sensing‐based observations of phenology, we estimated and tested models that predict the timing of spring leaf emergence across five different deciduous broadleaf forest types in the eastern United States. Specifically, we evaluated two different approaches: (i) using species‐specific models in combination with species composition information to ‘upscale’ model predictions and (ii) using repeat digital photography of forest canopies that observe and integrate the phenological behavior of multiple representative species at each camera site to calibrate a single model for all deciduous broadleaf forests. Our results demonstrate variability in cumulative forcing requirements and photoperiod cues across species and forest types, and show how community composition influences phenological dynamics over large areas. At the same time, the response of different species to spatial and interannual variation in weather is, under the current climate regime, sufficiently similar that the generic deciduous forest model based on repeat digital photography performed comparably to the upscaled species‐specific models. More generally, results from this analysis demonstrate how in situ observation networks and remote sensing data can be used to synergistically calibrate and assess regional parameterizations of phenology in models.

Melaas, Eli K.↗
DOE OSTI2022

A Compound Poisson Generator Approach to Point-source Inference in Astrophysics

Abstract The identification and description of point sources is one of the oldest problems in astronomy, yet even today the correct statistical treatment for point sources remains one of the field’s hardest problems. For dim or crowded sources, likelihood-based inference methods are required to estimate the uncertainty on the characteristics of the source population. In this work, a new parametric likelihood is constructed for this problem using compound Poisson generator (CPG) functionals that incorporate instrumental effects from first principles. We demonstrate that the CPG approach exhibits a number of advantages over non-Poissonian template fitting (NPTF)—an existing method—in a series of test scenarios in the context of X-ray astronomy. These demonstrations show that the effect of the point-spread function, effective area, and choice of point-source spatial distribution cannot, generally, be factorized as they are in NPTF, while the new CPG construction is validated in these scenarios. Separately, an examination of the diffuse-flux emission limit is used to show that most simple choices of priors on the standard parameterization of the population model can result in unexpected biases: when a model comprising both a point-source population and diffuse component is applied to this limit, nearly all observed flux will be assigned to either the population or to the diffuse component. A new parameterization is presented for these priors that properly estimates the uncertainties in this limit. In this choice of priors, CPG correctly identifies that the fraction of flux assigned to the population model cannot be constrained by the data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Expanding the computational frontier of multi-scale atmospheric simulation to advance understanding of low cloud / climate feedbacks: Final Technical Report

Marine boundary layer clouds are a challenge for climate models. They cover much of the oceans, but they are driven by small-scale turbulent eddies only a few hundred meters across, which in turn respond to the cloud formation. Global climate models have a grid spacing that is far too large to simulate such fluid motions, so they parameterize these cloud formation processes. Different climate modeling groups have designed different parameterizations in which the clouds turn out to be differently sensitive to a warming climate. This drives uncertainties in our best guess at the sensitivity of global warming to greenhouse gas increases. If these cloud-forming eddies could be directly simulated using the well-known equations of fluid motion, they would no longer need to be parameterized, removing a major source of climate modeling uncertainty. In this project, we overcame software engineering challenges to successfully implemented ‘ultraparameterization’ (UP), the first global model that does this, and we tested how well it works. We simulated five-year periods with present-day temperatures and with a warmer climate, and we investigated how the UP-simulated clouds responded to climate – the ‘cloud feedback’ problem. We found little response of clouds at all latitudes to the imposed climate change, which is within the range of predictions of conventional global climate models. UP is a variation on superparameterization, in which small cloud-resolving models (CRMs) are embedded in each column of the global model. In UP, the CRM grid is fine enough (250 m horizontal × 20 m vertical) to explicitly capture boundary-layer turbulent eddies and associated clouds. Because only one small columnar patch is simulated within each climate model grid cell, this is a million-fold more efficient than simulating the entire globe on this same CRM grid., but achieves much of the same effect for the cloud properties. It doesn’t work perfectly. For instance, like conventional climate models, UP simulates too little subtropical stratocumulus cloud, a bias that we are continuing to work to reduce. However, because it directly simulates the turbulent cloud-forming processes, UP is inherently more plausible for simulating how clouds will change in a perturbed climate. In future, we hope to apply UP to another key climate modeling issue: cloud-aerosol interaction and the effect of human-produced aerosols on the climate change we have already experienced and that which is likely to come.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Evaluating Clouds, Aerosols, and their Interactions in Three Global Climate Models using COSP and Satellite Observations

Accurately representing aerosol-cloud interactions in global climate models is challenging. As parameterizations evolve, it is important to evaluate their performance with appropriate use of observations. In this work we compare aerosols, clouds, and their interactions in three climate models (AM3, CAM5, ModelE) to MODIS satellite observations. Modeled cloud properties were diagnosed using the CFMIP Observations Simulator Package (COSP). Cloud droplet number concentrations (N) were derived using the same algorithm for both satellite-simulated model values and observations. We find that aerosol optical depth tau simulated by models is similar to observations. For N, AM3 and CAM5 capture the observed spatial pattern of higher values in near-coast versus remote ocean regions, though modeled values in general are higher than observed. In contrast, ModelE simulates lower N in most near-coast versus remote regions. Aerosol- cloud interactions were computed as the sensitivity of N to tau for marine liquid clouds off the coasts of South Africa and Eastern Asia where aerosol pollution varies in time. AM3 and CAM5 are in most cases more sensitive than observations, while the sensitivity for ModelE is statistically insignificant. This widely used sensitivity could be subject to misinterpretation due to the confounding influence of meteorology on both aerosols and clouds. A simple framework for assessing the N – tau sensitivity at constant meteorology illustrates that observed sensitivity can change from positive to statistically insignificant when including the confounding influence of relative humidity. Satellite simulated values of N were compared to standard model output and found to be higher with a bias of 83 cm-3.

aerosols↗
DOE OSTI2018

Analysis of heavy-ion fusion reactions using new parameterized form of the universal function of nuclear proximity potential

In the present work, we modify the original version of this formalism (Prox. 77) using a new analytical form of the universal function which is formulated based on the double-folding model with three density-dependent versions of the M3Y-type interactions, namely DDM3Y1, CDM3Y3 and BDM3Y1, for 46 fusion systems with condition 48≤Z{sub 1}Z{sub 2}≤2460 for charge product of their participant nuclei. It is found that when the Prox. 77 potential is accompanied by each of the formulated universal functions, the agreement between the theoretical and experimental data of the fusion barrier heights increase for our selected systems. The obtained results of this study reveal that the saturation property of cold nuclear matter plays a key role in the calculations of the fusion cross sections. We conclude that the Prox. 77 model with universal function based on the BDM3Y1 interactions provides the best results for fusion barrier heights and cross sections. On the basis of the prox. 77(BDM3Y1) potential model, we present the parameterized formulas for fusion barrier heights V{sub B} and positions R{sub B}. These formulas can calculate the values of R{sub B} andV{sub B} with good accuracy in comparison with the experimental data. A comparison is also presented among the theoretical results of the present work and those obtained by the modified form of the original version of proximity approach through the universal function and surface energy coefficients available in the literature.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

A reduced complexity framework to bridge the gap between AGCMs and cloud‐resolving models

Abstract The role of convective parameterizations at high horizontal resolution and their impacts on clouds, circulation, and precipitation processes represent large uncertainties in atmospheric general circulation models (AGCMs). As the statistical equilibrium in which radiative cooling is balanced by convective heating, radiative‐convective equilibrium (RCE) offers a simplified framework to investigate such uncertainties. The Community Atmosphere Model 5 is configured in a RCE setup that consists of an ocean‐covered planet with diurnally varying, spatially uniform insolation with no rotation effects. A series of simulations are performed in which the planetary radius is incrementally reduced. Because of the homogeneity of the setup, the effect is to reduce grid spacing, mimicking increased resolution without increasing the number of grid points. The results suggest that the reduced planet approach is able to reproduce the behavior of convection from full high‐resolution simulations. At grid spacing less than 20 km, convective motions are predominantly produced by resolved scales.

Reed, Kevin A.↗