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DOE OSTI2022

Exploiting Machine Learning in Multiscale Modelling of Materials

Recent developments in efficient machine learning algorithms have spurred significant interest in the materials community. The inherently complex and multiscale problems in Materials Science and Engineering pose a formidable challenge. The present scenario of machine learning research in Materials Science has a clear lacunae, where efficient algorithms are being developed as a separate endeavour, while such methods are being applied as ‘black-box’ models by others. The present article aims to discuss pertinent issues related to the development and application of machine learning algorithms for various aspects of multiscale materials modelling. The authors present an overview of machine learning of equivariant properties, machine learning-aided statistical mechanics, the incorporation of ab initio approaches in multiscale models of materials processing and application of machine learning in uncertainty quantification. In addition to the above, the applicability of Bayesian approach for multiscale modelling will be discussed. Critical issues related to the multiscale materials modelling are also discussed.

42 ENGINEERING↗

NASA NTRS2020

On the Role of Trend and Variability of Hydroxyl Radical (OH) in the Global Methane Budget

Decadal trends and interannual variations in the hydroxyl radical (OH), while poorly constrained at present, are critical for understanding the observed evolution of atmospheric methane (CH4). Through analyzing the OH fields simulated by the model ensemble of the Chemistry-Climate Model Initiative (CCMI), we find (1) the negative OH anomalies during the El Niño years mainly corresponding to the enhanced carbon monoxide (CO) emissions from biomass burning and (2) a positive OH trend during 1980-2010 dominated by the elevated primary production and the reduced loss of OH due to decreasing CO after 2000. Both two-box model inversions and variational 4D inversions suggest that ignoring the negative anomaly of OH during the El Niño years leads to a large overestimation of the increase in global CH4 emissions by up to10±3Tg yr-1to match the observed CH4 increase over these years. Not accounting for the increasing OH trends given by the CCMI models leads to an underestimation of the CH4 emission increase by 23±9Tg yr-1from 1986 to 2010. The variational inversion estimated CH4 emissions show that the tropical regions contribute most to the uncertainties related to OH. This study highlights the significant impact of climate and chemical feedbacks related to OH on the top-down estimates of the global CH4 budget.

Hydroxyl radical (OH)↗

NASA NTRS1991

Ion pickup, scattering, and stochastic acceleration in the cometary environment of P/Giacobini-Zinner

Observations and theory related to the scattering and acceleration of cometary pickup ions are reviewed with emphasis on Comet P/Giacobini-Zinner. A comparison of the regions upstream and downstream of the bow shock is made to assess the relative merits of each as a site for stochastic acceleration of ions above the pickup energy through interaction with low-frequency MHD waves. In the far upstream region the data are most consistent with a model where pickup ions generate a low level of MHD waves but remain relatively scatter-free. In the downstream region intense magnetic fluctuations gives rise to rapid isotropization of the ions and a second-order stochastic acceleration. The properties of the MHD power spectrum are related to the energetic ion spectrum in the framework of a leaky box model where the bulk of the acceleration occurs downstream of the shock throughout the cometosheath. Good agreement of the observations with theory is evident for both P/Giacobini-Zinner and P/Halley.

Barbosa, D. D.↗

NASA NTRS1988

Stellar nucleosynthesis and chemical evolution of the solar neighborhood

Current theoretical models of nucleosynthesis (N) in stars are reviewed, with an emphasis on their implications for Galactic chemical evolution. Topics addressed include the Galactic population II red giants and early N; N in the big bang; star formation, stellar evolution, and the ejection of thermonuclearly evolved debris; the chemical evolution of an idealized disk galaxy; analytical solutions for a closed-box model with continuous infall; and nuclear burning processes and yields. Consideration is given to shell N in massive stars, N related to degenerate cores, and the types of observational data used to constrain N models. Extensive diagrams, graphs, and tables of numerical data are provided.

Clayton, Donald D.↗

NASA NTRS1987

Origin and propagation of galactic cosmic rays

The study of systematic trends in elemental abundances is important for unfolding the nuclear and/or atomic effects that should govern the shaping of source abundances and in constraining the parameters of cosmic ray acceleration models. In principle, much can be learned about the large-scale distributions of cosmic rays in the galaxy from all-sky gamma ray surveys such as COS-B and SAS-2. Because of the uncertainties in the matter distribution which come from the inability to measure the abundance of molecular hydrogen, the results are somewhat controversial. The leaky-box model accounts for a surprising amount of the data on heavy nuclei. However, a growing body of data indicates that the simple picture may have to be abandoned in favor of more complex models which contain additional parameters. Future experiments on the Spacelab and space station will hopefully be made of the spectra of individual nuclei at high energy. Antiprotons must be studied in the background free environment above the atmosphere with much higher reliability and presion to obtain spectral information.

Cesarsky, Catherine J.↗

NASA NTRS2023

An Observation-Based, Reduced-Form Model for Oxidation in the Remote Marine Troposphere

The hydroxyl radical (OH) fuels atmospheric chemical cycling as the main sink for methane and a driver of the formation and loss of many air pollutants, but direct OH observations are sparse. We develop and evaluate an observation-based proxy for short term, spatial variations in OH (Proxy OH ) in the remote marine troposphere using unprecedented and comprehensive measurements from the NASA Atmospheric Tomography (ATom) airborne campaign. Proxy OH is a reduced form of the OH steady-state equation representing the dominant OH production and loss pathways in the remote marine troposphere, according to box model simulations of OH constrained with ATom observations. Proxy OH comprises only eight variables that are generally observed by routine ground- or satellite-based instruments. ProxyOH scales linearly with in situ [OH] spatial variations along the ATom flight tracks (median r 2 = 0.90, interquartile range = 0.80 – 0.94 across 2 km altitude by 20° latitudinal regions). We deconstruct spatial variations in Proxy OH as a first-order approximation of the sensitivity of OH variations to individual terms. Two terms modulate within-region Proxy OH variations—water vapor (H 2 O) and, to a lesser extent, nitric oxide (NO). This implies that a limited set of observations could offer a novel avenue for observation-based mapping of OH spatial variations over much of the remote marine troposphere. Both H 2 O and NO are expected to change with climate, while NO also varies strongly with human activities. We also illustrate the utility of Proxy OH as a process-based approach for evaluating inter-model differences in remote marine tropospheric OH.

Colleen B. Baublitz↗

NASA NTRS2016

Non-OH Chemistry in Oxidation Flow Reactors for the Study of Atmospheric Chemistry Systematically Examined by Modeling

Oxidation flow reactors (OFRs) using low-pressure Hg lamp emission at 185 and 254 nm produce OH radicals efficiently and are widely used in atmospheric chemistry and other fields. However, knowledge of detailed OFR chemistry is limited, allowing speculation in the literature about whether some non-OH reactants, including several not relevant for tropospheric chemistry, may play an important role in these OFRs. These non-OH reactants are UV radiation, O(1D), O(3P), and O3. In this study, we investigate the relative importance of other reactants to OH for the fate of reactant species in OFR under a wide range of conditions via box modeling. The relative importance of non-OH species is less sensitive to UV light intensity than to relative humidity (RH) and external OH reactivity (OHRext), as both non-OH reactants and OH scale roughly proportional to UV intensity. We show that for field studies in forested regions and also the urban area of Los Angeles, reactants of atmospheric interest are predominantly consumed by OH. We find that O(1D), O(3P), and O3 have relative contributions to VOC consumption that are similar or lower than in the troposphere. The impact of O atoms can be neglected under most conditions in both OFR and troposphere. Under pathological OFR conditions of low RH and/or high OHRext, the importance of non-OH reactants is enhanced because OH is suppressed. Some biogenics can have substantial destructions by O3, and photolysis at non-tropospheric wavelengths (185 and 254 nm) may also play a significant role in the degradation of some aromatics under pathological conditions. Working under low O2 with the OFR185 mode allows OH to completely dominate over O3 reactions even for the biogenic species most reactive with O3. Non-tropospheric VOC photolysis may have been a problem in some laboratory and source studies, but can be avoided or lessened in future studies by diluting source emissions and working at lower precursor concentrations in lab studies, and by humidification. SOA photolysis is shown to be insignificant for most functional groups, except for nitrates and especially aromatics, which may be photolyzed at high UV flux settings. Our work further establishes the OFR's usefulness as a tool to study atmospheric chemistry and enables better experiment design and interpretation, as well as improved future reactor design.

Peng, Zhe↗

NASA NTRS2016

Non-OH Chemistry in Oxidation Flow Reactors for the Study of Atmospheric Chemistry Systematically Examined by Modeling

Peng, Zhe↗

NASA NTRS2013

Missing Peroxy Radical Sources Within a Rural Forest Canopy

Organic peroxy (RO2) and hydroperoxy (HO2) radicals are key intermediates in the photochemical processes that generate ozone, secondary organic aerosol and reactive nitrogen reservoirs throughout the troposphere. In regions with ample biogenic hydrocarbons, the richness and complexity of peroxy radical chemistry presents a significant challenge to current-generation models, especially given the scarcity of measurements in such environments. We present peroxy radical observations acquired within a Ponderosa pine forest during the summer 2010 Bio-hydro-atmosphere interactions of Energy, Aerosols, Carbon, H2O, Organics and Nitrogen - Rocky Mountain Organic Carbon Study (BEACHON-ROCS). Total peroxy radical mixing ratios reach as high as 180 pptv and are among the highest yet recorded. Using the comprehensive measurement suite to constrain a near-explicit 0-D box model, we investigate the sources, sinks and distribution of peroxy radicals below the forest canopy. The base chemical mechanism underestimates total peroxy radicals by as much as a factor of 3. Since primary reaction partners for peroxy radicals are either measured (NO) or under-predicted (HO2 and RO2, i.e. self-reaction), missing sources are the most likely explanation for this result. A close comparison of model output with observations reveals at least two distinct source signatures. The first missing source, characterized by a sharp midday maximum and a strong dependence on solar radiation, is consistent with photolytic production of HO2. The diel profile of the second missing source peaks in the afternoon and suggests a process that generates RO2 independently of sun-driven photochemistry, such as ozonolysis of reactive hydrocarbons. The maximum magnitudes of these missing sources (approximately 120 and 50 pptv min−1, respectively) are consistent with previous observations alluding to unexpectedly intense oxidation within forests. We conclude that a similar mechanism may underlie many such observations.

atmosphere↗

DOE OSTI2024

Modeling Novel Aqueous Particle and Cloud Chemistry Processes of Biomass Burning Phenols and Their Potential to Form Secondary Organic Aerosols

Phenols emitted from biomass burning contribute significantly to secondary organic aerosol (SOA) formation through the partitioning of semivolatile products formed from gas-phase chemistry and multiphase chemistry in aerosol liquid water and clouds. The aqueous-phase SOA (aqSOA) formed via hydroxyl radical (˙OH), singlet molecular oxygen ( 1 O 2 *), and triplet excited states of organic compounds ( 3 C*), which oxidize dissolved phenols in the aqueous phase, might play a significant role in the evolution of organic aerosol (OA). However, a quantitative and predictive understanding of aqSOA has been challenging. Here, we develop a stand-alone box model to investigate the formation of SOA from gas-phase ˙OH chemistry and aqSOA formed by the dissolution of phenols followed by their aqueous-phase reactions with ˙OH, 1 O 2 *, and 3 C* in cloud droplets and aerosol liquid water. Here, we investigate four phenolic compounds, i.e., phenol, guaiacol, syringol, and guaiacyl acetone (GA), which represent some of the key potential sources of aqSOA from biomass burning in clouds. For the same initial precursor organic gas that dissolves in aerosol/cloud liquid water and subsequently reacts with aqueous phase oxidants, we predict that the aqSOA formation potential (defined as aqSOA formed per unit dissolved organic gas concentration) of these phenols is higher than that of isoprene-epoxydiol (IEPOX), a well-known aqSOA precursor. Cloud droplets can dissolve a broader range of soluble phenols compared to aqueous aerosols, since the liquid water contents of aerosols are orders of magnitude smaller than cloud droplets. Further, our simulations suggest that highly soluble and reactive multifunctional phenols like GA would predominantly undergo cloud chemistry within cloud layers, while gas-phase chemistry is likely to be more important for less soluble phenols. But in the absence of clouds, the condensation of low-volatility products from gas-phase oxidation followed by their reversible partitioning to organic aerosols dominates SOA formation, while the SOA formed through aqueous aerosol chemistry increases with relative humidity (RH), approaching 40% of the sum of gas and aqueous aerosol chemistry at 95% RH for GA. Our model developments of biomass-burning phenols and their aqueous chemistry can be readily implemented in regional and global atmospheric chemistry models to investigate the aqueous aerosol and cloud chemistry of biomass-burning organic gases in the atmosphere.

09 BIOMASS FUELS↗

DOE OSTI2021

Novel estimation of aerosol processes with particle size distribution measurements: a case study with the TOMAS algorithm v1.0.0

Atmospheric aerosol microphysical processes are a significant source of uncertainty in predicting climate change. Specifically, aerosol nucleation, emissions, and growth rates, which are simulated in chemical transport models to predict the particle size distribution, are not understood well. However, long-term size distribution measurements made at several ground-based sites across Europe implicitly contain information about the processes that created those size distributions. This work aims to extract that information by developing and applying an inverse technique to constrain aerosol emissions as well as nucleation and growth rates based on hourly size distribution measurements. We developed an inverse method based upon process control theory into an online estimation technique to scale aerosol nucleation, emissions, and growth so that the model–measurement bias in three measured aerosol properties exponentially decays. The properties, which are calculated from the measured and predicted size distributions, used to constrain aerosol nucleation, emission, and growth rates are the number of particles with a diameter between 3 and 6 nm, the number with a diameter greater than 10 nm, and the total dry volume of aerosol ( N 3–6 , N 10 , V dry ), respectively. In this paper, we focus on developing and applying the estimation methodology in a zero-dimensional “box” model as a proof of concept before applying it to a three-dimensional simulation in subsequent work. The methodology is first tested on a dataset of synthetic and perfect measurements that span diverse environments in which the true particle emissions, growth, and nucleation rates are known. The inverse technique accurately estimates the aerosol microphysical process rates with an average and maximum error of 2 % and 13 %, respectively. Next, we investigate the effect that measurement noise has on the estimated rates. The method is robust to typical instrument noise in the aerosol properties as there is a negligible increase in the bias of the estimated process rates. Finally, the methodology is applied to long-term datasets of in situ size distribution measurements in western Europe from May 2006 through June 2007. At Melpitz, Germany, and Hyytiälä, Finland, the average diurnal profiles of estimated 3 nm particle formation rates are reasonable, having peaks near noon local time with average peak values of 1 and 0.15 cm –3 s –1 , respectively. The normalized absolute error in estimated N 3–6 , N 10 , and V dry at three European measurement sites is less than 15 %, showing that the estimation framework developed here has potential to decrease model–measurement bias while constraining uncertain aerosol microphysical processes.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2006

A Model-based Interpretation of Low-frequency Changes in the Carbon Cycle during the Last 120,000 years and its Implications for the Reconstruction of Atmospheric (delta) 14-C

A main caveat in the interpretation of observed changes in atmospheric (Delta)C-l4 during the last 50,000 years is the unknown variability of the carbon cycle, which together with changes in the C-14 production rates determines the C-14 dynamics. A plausible scenario explaining glacial/interglacial dynamics seen in atmospheric CO2 and (delta)C-13 was proposed recently (Kohler et al., 2005a). A similar approach that expands its interpretation to the C-14 cycle is an important step toward a deeper understanding of (Delta)C-14 variability. This approach is based on an ocean/atmosphere/biosphere box model of the global carbon cycle (BICYCLE) to reproduce low-frequency changes in atmospheric CO2 as seen in Antarctic ice cores. The model is forced forward in time by various paleoclimatic records derived from ice and sediment cores. The simulation results of our proposed scenario match a compiled CO2 record from various ice cores during the last 120,000 years with high accuracy (r(sup 2) = 0.89). We analyze scenarios with different C-14 production rates, which are either constant or based on Be-10 measured in Greenland ice cores or the recent high-resolution geomagnetic field reconstruction GLOPIS-75 and compare them with the available (Delta)C-14 data covering the last 50,000 years. Our results suggest that during the last glacial cycle in general less than 110%0o f the increased atmospheric (Delta)C-14 is based on variations in the carbon cycle, while the largest part (5/6) of the variations has to be explained by other factors. Glacial atmospheric (Delta)C-14 larger than 700% cannot not be explained within our framework, neither through carbon cycle-based changes nor through variable C-14 production. Superimposed on these general trends might lie positive anomalies in atmospheric (Delta)C-14 of approx. 50% caused by millennial-scale variability of the northern deep water production during Heinrich events and Dansgaard/Oeschger climate fluctuations. According to our model, the dominant processes that increase glacial (Delta)C-14 are a reduced glacial ocean circulation (+ approx.40%0), a restricted glacial gas exchange between the atmosphere and the surface ocean through sea ice coverage (+ approx. 20%), and the enrichment of dissolved inorganic carbon with C-14 in the surface waters through isotopic fractionation during higher glacial marine export production caused by iron fertilization (+ approx.10%).

Koehler, Peter↗

DOE OSTI2025

Leveraging interpolation models and error bounds for verifiable scientific machine learning

Effective verification and validation techniques for modern scientific machine learning workflows are challenging to devise. Statistical methods are abundant and easily deployed, but often rely on speculative assumptions about the data and methods involved. Error bounds for classical interpolation techniques can provide mathematically rigorous estimates of accuracy, but often are difficult or impractical to determine computationally. Here, in this work, we present a best-of-both-worlds approach to verifiable scientific machine learning by demonstrating that (1) multiple standard interpolation techniques have informative error bounds that can be computed or estimated efficiently; (2) comparative performance among distinct interpolants can aid in validation goals; (3) deploying interpolation methods on latent spaces generated by deep learning techniques enables some interpretability for black-box models. We present a detailed case study of our approach for predicting lift-drag ratios from airfoil images. Code developed for this work is available in a public Github repository.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Multi-resolution partial differential equations preserved learning framework for spatiotemporal dynamics

Traditional data-driven deep learning models often struggle with high training costs, error accumulation, and poor generalizability in complex physical processes. Physics-informed deep learning (PiDL) addresses these challenges by incorporating physical principles into the model. Most PiDL approaches regularize training by embedding governing equations into the loss function, yet this depends heavily on extensive hyperparameter tuning to weigh each loss term. To this end, we propose to leverage physics prior knowledge by “baking” the discretized governing equations into the neural network architecture via the connection between the partial differential equations (PDE) operators and network structures, resulting in a PDE-preserved neural network (PPNN). This method, embedding discretized PDEs through convolutional residual networks in a multi-resolution setting, largely improves the generalizability and long-term prediction accuracy, outperforming conventional black-box models. The effectiveness and merit of the proposed methods have been demonstrated across various spatiotemporal dynamical systems governed by spatiotemporal PDEs, including reaction-diffusion, Burgers’, and Navier-Stokes equations.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2018

Wintertime Overnight NOx Removal in a Southeastern United States Coal-Fired Power Plant Plume: A Model for Understanding Winter NOx Processing and Its Implications

Nitric oxide (NO) is emitted in large quantities from coal-burning power plants. During the day, the plumes from these sources are efficiently mixed into the boundary layer, while at night, they may remain concentrated due to limited vertical mixing during which they undergo horizontal fanning. At night, the degree to which NO is converted to HNO3 and therefore unable to participate in next-day ozone (O3) formation depends on the mixing rate of the plume, the composition of power plant emissions, and the composition of the background atmosphere. In this study, we use observed plume intercepts from the Wintertime INvestigation of Transport, Emissions and Reactivity (WINTER) campaign to test sensitivity of overnight NOx removal to the N2O5 loss rate constant, plume mixing rate, background O3, and background levels of volatile organic compounds using a 2-D box model of power plant plume transport and chemistry. The factor that exerted the greatest control over NOx removal was the loss rate constant of N2O5. At the lowest observed N2O5 loss rate constant, no other combination of conditions converts more than 10 percent of the initial NOx to HNO3. The other factors did not influence NOx removal to the same degree.

air quality↗

NASA NTRS1983

The application of forest classification from Landsat data as a basis for natural hydrocarbon emission estimation and photochemical oxidant model simulations in southeastern Virginia

The possible contribution by natural hydrocarbon emissions to the total ozone budget recorded in the Tidewater region of southeastern Virginia during the height of the summer period was examined. Natural sources investigated were limited to the primary HC emitters and most prevalent natural vegetation, the forests. Three types and their areal coverage were determined for Region VI of the Virginia State Air Pollution Control Board using remotely sensed data from Landsat, a NASA experimental earth resources satellite. Emission factors appropriate to the specific types (coniferous 0.24 x 10 to the 13th, mixed 0.63 x 10 to the 13th, deciduous 1.92 x 10 to the 13th, microgram/h), derived from contemporary procedures, were applied to produce an overall regional emission rate of 2.79 x 10 to the 13th microgram/h for natural non-methane hydrocarbons (NMHC). This rate was used with estimates of the anthropogenic NO(x) and NMHC loading, as input into a photochemical box model. Additional HC loading on the order of that estimated to be produced by the natural forest communities was required in order to reach certain measured summer peak ozone levels as the computer simulation was unable to account for the measured episodic levels on the basis of the anthropogenic inventory alone.

Salop, J.↗

DOE OSTI2020

Anthropogenic Impacts on Atmospheric Carbonyl Sulfide Since the 19th Century Inferred From Polar Firn Air and Ice Core Measurements

Carbonyl sulfide (COS) was measured in firn air collected during seven different field campaigns carried out at four different sites in Greenland and Antarctica between 2001 and 2015. A Bayesian probabilistic statistical model is used to conduct multisite inversions and to reconstruct separate atmospheric histories for Greenland and Antarctica. The firn air inversions cover most of the 20th century over Greenland and extend back to the 19th century over Antarctica. The derived atmospheric histories are consistent with independent surface air time series data from the corresponding sites and the Antarctic ice core COS records during periods of overlap. Atmospheric COS levels began to increase over preindustrial levels starting in the 19th century, and the increase continued for much of the 20th century. Atmospheric COS peaked at higher than present-day levels around 1975 CE over Greenland and around 1987 CE over Antarctica. An atmosphere/surface ocean box model is used to investigate the possible causes of observed variability. The results suggest that changes in the magnitude and location of anthropogenic sources have had a strong influence on the observed atmospheric COS variability.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1990

New aspects of heavy cosmic rays from calcium to nickel (Z = 20 to 28)

Over the two year course of this grant a study was conducted to explore the implications of composition measurements of heavy cosmic rays made by the Third High Energy Astronomy Observatory (HEAO-3). To interpret these and other measurements this study combined for the first time new laboratory measurements of the fragmentation cross sections of heavy nuclei, a new semi-empirical cross section formula, and the latest in cosmic ray propagation and solar modulation models. These models were used to interpret abundance measurements from six recent satellite experiments, including, in particular, two from HEAO-3. The principal results of the study were: (1) an improved interpretation of the Mn-54 clock in cosmic rays, including predictions of the isotopic abundances of Mn for comparison with future isotope measurements; (2) the first realization of the effect of Mn-54 decay on studies of the source abundances of Fe isotopes; (3) improved source abundances of the elements Ar, Ca, Cr, Mn, Fe, and Ni in the cosmic ray source material; (4) an improved fit to the abundances of Fe secondaries in cosmic rays; and (5) additional evidence that supports the validity of the leaky-box model of cosmic ray propagation in the galaxy. This final report summarizes these new results, the new tools that were developed to obtain them, and presents a bibliography of talks and publications that resulted from this work.

Mewaldt, Richard A.↗