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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Using automated machine learning for the upscaling of gross primary productivity

Estimating gross primary productivity (GPP) over space and time is fundamental for understanding the response of the terrestrial biosphere to climate change. Eddy covariance flux towers provide in situ estimates of GPP at the ecosystem scale, but their sparse geographical distribution limits larger-scale inference. Machine learning (ML) techniques have been used to address this problem by extrapolating local GPP measurements over space using satellite remote sensing data. However, the accuracy of the regression model can be affected by uncertainties introduced by model selection, parameterization, and choice of explanatory features, among others. Recent advances in automated ML (AutoML) provide a novel automated way to select and synthesize different ML models. In this work, we explore the potential of AutoML by training three major AutoML frameworks on eddy covariance measurements of GPP at 243 globally distributed sites. We compared their ability to predict GPP and its spatial and temporal variability based on different sets of remote sensing explanatory variables. Explanatory variables from only Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance data and photosynthetically active radiation explained over 70 % of the monthly variability in GPP, while satellite-derived proxies for canopy structure, photosynthetic activity, environmental stressors, and meteorological variables from reanalysis (ERA5-Land) further improved the frameworks' predictive ability. We found that the AutoML framework Auto-sklearn consistently outperformed other AutoML frameworks as well as a classical random forest regressor in predicting GPP but with small performance differences, reaching an r 2 of up to 0.75. We deployed the best-performing framework to generate global wall-to-wall maps highlighting GPP patterns in good agreement with satellite-derived reference data. This research benchmarks the application of AutoML in GPP estimation and assesses its potential and limitations in quantifying global photosynthetic activity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Effects of pre-existing ice crystals on cirrus clouds and comparison between different ice nucleation parameterizations with the Community Atmosphere Model (CAM5)

In order to improve the treatment of ice nucleation in a more realistic manner in the Community Atmosphere Model version 5.3 (CAM5.3), the effects of pre-existing ice crystals on ice nucleation in cirrus clouds are considered. In addition, by considering the in-cloud variability in ice saturation ratio, homogeneous nucleation takes place spatially only in a portion of the cirrus cloud rather than in the whole area of the cirrus cloud. Compared to observations, the ice number concentrations and the probability distributions of ice number concentration are both improved with the updated treatment. The pre-existing ice crystals significantly reduce ice number concentrations in cirrus clouds, especially at mid- to high latitudes in the upper troposphere (by a factor of ~10). Furthermore, the contribution of heterogeneous ice nucleation to cirrus ice crystal number increases considerably. Besides the default ice nucleation parameterization of Liu and Penner (2005, hereafter LP) in CAM5.3, two other ice nucleation parameterizations of Barahona and Nenes (2009, hereafter BN) and Kärcher et al. (2006, hereafter KL) are implemented in CAM5.3 for the comparison. In-cloud ice crystal number concentration, percentage contribution from heterogeneous ice nucleation to total ice crystal number, and pre-existing ice effects simulated by the three ice nucleation parameterizations have similar patterns in the simulations with present-day aerosol emissions. However, the change (present-day minus pre-industrial times) in global annual mean column ice number concentration from the KL parameterization (3.24 × 10 6 m -2 ) is less than that from the LP (8.46 × 10 6 m -2 ) and BN (5.62 × 10 6 m -2 ) parameterizations. As a result, the experiment using the KL parameterization predicts a much smaller anthropogenic aerosol long-wave indirect forcing (0.24 W m -2 ) than that using the LP (0.46 W m −2 ) and BN (0.39 W m -2 ) parameterizations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Calibration and validation of the foundation for a multiphase strength model for tin

In this work, the Common Model of Multi-phase Strength and Equation of State (CMMP) model was applied to tin. Specifically, calibrations of the strength-specific elements of the CMMP foundation were developed with a combination of experiments and theory, and then the model was validated experimentally. The first element of the foundation is a multi-phase analytic treatment of the melt temperature and the shear modulus for the solid phases. These models were parameterized for each phase based on ab initio calculations using the software VASP (Vienna Ab initio Simulations Package) based on density functional theory. The shear modulus model for the ambient phase was validated with ultrasonic sound speed measurements as a function of pressure and temperature. The second element of the foundation is a viscoplastic strength model for the phase, upon which strength for inaccessible higher-pressure phases can be scaled as necessary. The stress–strain response of tin was measured at strain rates of 10 -3 to 3 x 10 3 s -1 and temperatures ranging from 87 to 373 K. The Preston–Tonks–Wallace (PTW) strength model was fit to that data using Bayesian model calibration. For validation, six forward and two reverse Taylor impact experiments were performed at different velocities to measure large plastic deformation of tin at strain rates up to ⁠10 5 s -1 . The PTW model accurately predicted the deformed shapes of the cylinders, with modest discrepancies attributed to the inability of PTW to capture the effects of twinning and dynamic recrystallization. Some material in the simulations of higher velocity Taylor cylinders reached the melting temperature, thus testing the multiphase model because of the presence of a second phase, the liquid. In simulations using a traditional modeling approach, the abrupt reduction of strength upon melt resulted in poor predictions of the deformed shape and non-physical temperatures. With CMMP, the most deformed material points evolved gradually to a mixed solid–liquid but never a fully liquid state, never fully lost strength, stayed at the melt temperature as the latent heat of fusion was absorbed, and predicted the deformed shape well.

36 MATERIALS SCIENCE↗
DOE OSTI2014

The AeroCom evaluation and intercomparison of organic aerosol in global models

This paper evaluates the current status of global modeling of the organic aerosol (OA) in the troposphere and analyzes the differences between models as well as between models and observations. Thirty-one global chemistry transport models (CTMs) and general circulation models (GCMs) have participated in this intercomparison, in the framework of AeroCom phase II. The simulation of OA varies greatly between models in terms of the magnitude of primary emissions, secondary OA (SOA) formation, the number of OA species used (2 to 62), the complexity of OA parameterizations (gas-particle partitioning, chemical aging, multiphase chemistry, aerosol microphysics), and the OA physical, chemical and optical properties. The diversity of the global OA simulation results has increased since earlier AeroCom experiments, mainly due to the increasing complexity of the SOA parameterization in models, and the implementation of new, highly uncertain, OA sources. Diversity of over one order of magnitude exists in the modeled vertical distribution of OA concentrations that deserves a dedicated future study. Furthermore, although the OA / OC ratio depends on OA sources and atmospheric processing, and is important for model evaluation against OA and OC observations, it is resolved only by a few global models. The median global primary OA (POA) source strength is 56 Tg a –1 (range 34–144 Tg a −1 ) and the median SOA source strength (natural and anthropogenic) is 19 Tg a –1 (range 13–121 Tg a −1 ). Among the models that take into account the semi-volatile SOA nature, the median source is calculated to be 51 Tg a –1 (range 16–121 Tg a −1 ), much larger than the median value of the models that calculate SOA in a more simplistic way (19 Tg a –1 ; range 13–20 Tg a –1 , with one model at 37 Tg a −1 ). The median atmospheric burden of OA is 1.4 Tg (24 models in the range of 0.6–2.0 Tg and 4 between 2.0 and 3.8 Tg), with a median OA lifetime of 5.4 days (range 3.8–9.6 days). In models that reported both OA and sulfate burdens, the median value of the OA/sulfate burden ratio is calculated to be 0.77; 13 models calculate a ratio lower than 1, and 9 models higher than 1. For 26 models that reported OA deposition fluxes, the median wet removal is 70 Tg a –1 (range 28–209 Tg a −1 ), which is on average 85% of the total OA deposition. Fine aerosol organic carbon (OC) and OA observations from continuous monitoring networks and individual field campaigns have been used for model evaluation. At urban locations, the model–observation comparison indicates missing knowledge on anthropogenic OA sources, both strength and seasonality. The combined model–measurements analysis suggests the existence of increased OA levels during summer due to biogenic SOA formation over large areas of the USA that can be of the same order of magnitude as the POA, even at urban locations, and contribute to the measured urban seasonal pattern. Global models are able to simulate the high secondary character of OA observed in the atmosphere as a result of SOA formation and POA aging, although the amount of OA present in the atmosphere remains largely underestimated, with a mean normalized bias (MNB) equal to –0.62 (–0.51) based on the comparison against OC (OA) urban data of all models at the surface, –0.15 (+0.51) when compared with remote measurements, and –0.30 for marine locations with OC data. The mean temporal correlations across all stations are low when compared with OC (OA) measurements: 0.47 (0.52) for urban stations, 0.39 (0.37) for remote stations, and 0.25 for marine stations with OC data. The combination of high (negative) MNB and higher correlation at urban stations when compared with the low MNB and lower correlation at remote sites suggests that knowledge about the processes that govern aerosol processing, transport and removal, on top of their sources, is important at the remote stations. There is no clear change in model skill with increasing model complexity with regard to OC or OA mass concentration. As a result, the complexity is needed in models in order to distinguish between anthropogenic and natural OA as needed for climate mitigation, and to calculate the impact of OA on climate accurately.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

SU-E-T-43: Analytical Model for Photon Peripheral Dose in Radiotherapy Treatments

Purpose: The higher survival rate of radiotherapy patients entails a growing concern on second cancers associated to peripheral doses. Currently, dosimetry of out-of field doses is still under development. Our group has developed a methodology to estimate neutron equivalent dose in organs (1,2). We aimed to propose a model to estimate out-of-field photon doses in isocentric treatments from basic clinical data. Methods: The proposed function models the dose as the sum of leakage and scatter terms. The latter is modeled as a virtual source at the collimator, which suffers from attenuation in air and tissue, corrected by the inverse-square-law. The model was parameterized using experimental measurements with TLD700 chips placed inside an anthropomorphic phantom (6–18MV) irradiated with conformal and modulated techniques in Elekta, Siemens and Varian linacs. This model provides photon dose at a point as a function of clinical parameters as prescription dose/UM, PTV volume, distance to the field edge, height of the MLC leaves and distance from the the MLC to the isocenter. Model was tested against independent measurements (TLD100) for a VMAT treatment on a Elekta. Dose to organs is modeled from dose to points along the head-to-feet axis of the organ of a “standard man” escalated by patient height. Results: Our semi-empirical model depends on 3 given parameters (leakage parameter can be individualized). A novelty of our model, over other models (e.g., PERIDOSE), arises from its applicability to any technique (independently of the number of MU needed to deliver a dose). Differences between predictions and measurements were < 0.005mSv/UM. Conclusion: We have proposed a unique model which successfully account for photon peripheral organ dose. This model can be applied in the day-to-day clinic as it only needs a few basic parameters which are readily accessible.1. Radiother. Oncol. 107:234–243, 2013. 2. Phys. Med. Biol. 57:6167–6191, 2012.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Calibration and validation of the foundation for a multiphase strength model for tin

In this work, the Common Model of Multi-phase Strength and Equation of State (CMMP) model was applied to tin. Specifically, calibrations of the strength-specific elements of the CMMP foundation were developed with a combination of experiments and theory, and then the model was validated experimentally. The first element of the foundation is a 10 multi-phase analytic treatment of the melt temperature and the shear modulus for the solid phases. These models were parameterized for each phase based on ab initio calculations using the software VASP (Vienna Ab initio Simulations Package) based on density functional theory (DFT). The shear modulus model for the ambient β phase was validated with ultrasonic sound speed measurements as a function of pressure and temperature. The second element of the foundation is a viscoplastic strength model for the β phase, upon which strength for inaccessible higher-pressure phases can be scaled as necessary. The stress-strain response of tin was measured at strain rates of 10 -3 to 3 x 10 3 s -1 and temperatures ranging from 87 to 373 K. The Preston-Tonks-Wallace (PTW) strength model was fit to that data using Bayesian model calibration. For validation, six forward and two reverse Taylor impact experiments were performed at different velocities to measure large plastic deformation of tin at strain rates up to 10 5 s -1 . The PTW model accurately predicted the deformed shapes of the cylinders, with modest discrepancies attributed to the inability 20 of PTW to capture the effects of twinning and dynamic recrystallization. Some material in the simulations of higher velocity Taylor cylinders reached the melting temperature, thus testing the multiphase model because of the presence of a second phase, the liquid. In simulations using a traditional modeling approach, the abrupt reduction of strength upon melt resulted in poor predictions of the deformed shape and non-physical temperatures. With CMMP, the most deformed material points evolved gradually to a mixed solid-liquid but never fully liquid state, never fully lost strength, 25 stayed at the melt temperature as the latent heat of fusion was absorbed, and predicted the deformed shape well.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Representing surface heterogeneity in land–atmosphere coupling in E3SMv1 single-column model over ARM SGP during summertime

Abstract. The Earth's land surface features spatial and temporal heterogeneity over a wide range of scales below those resolved by current Earth system models (ESMs). State-of-the-art land and atmosphere models employ parameterizations to represent their subgrid heterogeneity, but the land–atmosphere coupling in ESMs typically operates on the grid scale. Communicating the information on the land surface heterogeneity with the overlying atmospheric boundary layer (ABL) remains a challenge in modeling land–atmosphere interactions. In order to account for the subgrid-scale heterogeneity in land–atmosphere coupling, we implement a new coupling scheme in the Energy Exascale Earth system model version 1 (E3SMv1) that uses adjusted surface variances and covariance of potential temperature and specific water content as the lower boundary condition for the atmosphere model. The new lower boundary condition accounts for both the variability of individual subgrid land surface patches and the inter-patch variability. The E3SMv1 single-column model (SCM) simulations over the Atmospheric Radiation Measurement (ARM) Southern Great Plain (SGP) site were performed to assess the impacts. We find that the new coupling parameterization increases the magnitude and diurnal cycle of the temperature variance and humidity variance in the lower ABL on non-precipitating days. The impacts are primarily attributed to subgrid inter-patch variability rather than the variability of individual patches. These effects extend vertically from the surface to several levels in the lower ABL on clear days. We also find that accounting for surface heterogeneity increases low cloud cover and liquid water path (LWP). These cloud changes are associated with the change in cloud regime indicated by the skewness of the probability density function (PDF) of the subgrid vertical velocity. In precipitating days, the inter-patch variability reduces significantly so that the impact of accounting for surface heterogeneity vanishes. These results highlight the importance of accounting for subgrid heterogeneity in land–atmosphere coupling in next-generation ESMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Determining Best Estimates and Uncertainties in Cloud Microphysical Parameters from ARM Field Data: Implications for Models, Retrieval Schemes and Aerosol-Cloud-Radiation Interactions

We proposed to analyze in-situ cloud data collected during ARM/ASR field campaigns to create databases of cloud microphysical properties and their uncertainties as needed for the development of improved cloud parameterizations for models and remote sensing retrievals, and for evaluation of model simulations and retrievals. In particular, we proposed to analyze data collected over the Southern Great Plains (SGP) during the Mid-latitude Continental Convective Clouds Experiment (MC3E), the Storm Peak Laboratory Cloud Property Validation Experiment (STORMVEX), the Small Particles in Cirrus (SPARTICUS) Experiment and the Routine AAF Clouds with Low Optical Water Depths (CLOWD) Optical Radiative Observations (RACORO) field campaign, over the North Slope of Alaska during the Indirect and Semi-Direct Aerosol Campaign (ISDAC) and the Mixed-Phase Arctic Cloud Experiment (M-PACE), and over the Tropical Western Pacific (TWP) during The Tropical Warm Pool International Cloud Experiment (TWP-ICE), to meet the following 3 objectives; derive statistical databases of single ice particle properties (aspect ratio AR, dominant habit, mass, projected area) and distributions of ice crystals (size distributions SDs, mass-dimension m-D, area-dimension A-D relations, mass-weighted fall speeds, single-scattering properties, total concentrations N, ice mass contents IWC), complete with uncertainty estimates; assess processes by which aerosols modulate cloud properties in arctic stratus and mid-latitude cumuli, and quantify aerosol’s influence in context of varying meteorological and surface conditions; and determine how ice cloud microphysical, single-scattering and fall-out properties and contributions of small ice crystals to such properties vary according to location, environment, surface, meteorological and aerosol conditions, and develop parameterizations of such effects.In this report we describe the accomplishments that we made on all 3 research objectives.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Investigation of representing hysteresis in macroscopic models of two-phase flow in porous media using intermediate scale experimental data

Incorporating hysteresis into models is important to accurately capture the two phase flow behavior when porous media systems undergo cycles of drainage and imbibition such as in the cases of injection and post-injection redistribution of CO 2 during geological CO 2 storage (GCS). In the traditional model of two-phase flow, existing constitutive models that parameterize the hysteresis associated with these processes are generally based on the empirical relationships. This manuscript presents development and testing of mathematical hysteretic capillary pressure—saturation—relative permeability models with the objective of more accurately representing the redistribution of the fluids after injection. The constitutive models are developed by relating macroscopic variables to basic physics of two-phase capillary displacements at pore-scale and void space distribution properties. The modeling approach with the developed constitutive models with and without hysteresis as input is tested against some intermediate-scale flow cell experiments to test the ability of the models to represent movement and capillary trapping of immiscible fluids under macroscopically homogeneous and heterogeneous conditions. The hysteretic two-phase flow model predicted the overall plume migration and distribution during and post injection reasonably well and represented the postinjection behavior of the plume more accurately than the nonhysteretic models. In conclusion, based on the results in this study, neglecting hysteresis in the constitutive models of the traditional two-phase flow theory can seriously overpredict or underpredict the injected fluid distribution during post-injection under both homogeneous and heterogeneous conditions, depending on the selected value of the residual saturation in the nonhysteretic models.

58 GEOSCIENCES↗
DOE OSTI2026

Semi-Dynamic Leach Testing of Densified Silicon-based Iodine Waste Forms

Iodine waste forms (IWF) require a conceptual corrosion release model (CCRM) to provide iodine (I) release rates for performance modeling nuclear waste disposal repositories. To develop a CCRM, an understanding of the corrosion mechanisms of the IWF are required along with data from consistent test methods to parameterize the model. The present study has advanced both areas by providing and assessing the corrosion resistance of IWF types based on their processing history in minor variations of semi-dynamic leach tests. The test included a series of semi-dynamic leach tests using monolithic IWFs in deionized water (leachant). Several experiments were conducted under alternate test conditions with changes to temperature, leachant replacement, leachant pH, leachant volume, masking, and surface finish to elucidate if varying these conditions impacted IWF corrosion behavior. Tests were conducted on two classes of IWFs: (1) I-bearing silver-mordenite (AgZ) materials processed by hot isostatic pressing (HIP) at different temperatures, pressures, sizes, and times; and (2) I-bearing silver-functionalized silica aerogels (SFA) processed by either HIP or spark plasma sintering (SPS). The corrosion susceptibility of AgZ samples was influenced by HIP temperature and pressure. The SPS SFAs retained I far better than HIP SFAs. Additional findings in this study include: (1) The iodine dissolution rate decreased with decreasing temperature, (2) a common ion effect may occur and slow dissolution of the host phase if the leachant is not regularly replaced, (3) pH controls the dissolution rate, and (4) the iodine dissolution rate slows with extended test time (up to 224 days). Based on this work, these parameters should thus be represented when developing a CCRM.

corrosion↗
DOE OSTI2022

Comparing Model Representations of Physiological Limits on Transpiration at a Semi-arid Ponderosa Pine Site

Mechanistic representations of biogeochemical processes in ecosystem models are rapidly advancing, requiring advancements in model evaluation approaches. Here we quantify multiple aspects of model functional performance to evaluate improved process representations in ecosystem models. We compare semi-empirical stomatal models with hydraulic constraints against more mechanistic representations of stomatal and hydraulic functioning at a semi-arid pine site using a suite of metrics and analytical tools. We find that models generally perform similarly under unstressed conditions, but performance diverges under atmospheric and soil drought. The more empirical models better capture synergistic information flows between soil water potential and vapor pressure deficit to transpiration, while the more mechanistic models are overly deterministic. Although models can be parameterized to yield similar functional performance, alternate parameterizations could not overcome structural model constraints that underestimate the unique information contained in soil water potential about transpiration. Additionally, both multilayer canopy and big-leaf models were unable to capture the magnitude of canopy temperature divergence from air temperature, and we demonstrate that errors in leaf temperature can propagate to considerable error in simulated transpiration. This study demonstrates the value of merging underutilized observational data streams with emerging analytical tools to characterize ecosystem function and discriminate among model process representations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

A coordination-based model for transition metal alloy nanoparticles

We present a simple approach for predicting the relative energies of bimetallic nanoparticles spanning a wide-ranging combinatorial space, using only the identity and nearest-neighbor coordination number of individual metal atoms as independent parameters. By performing straightforward metal atom adsorption calculations on surface slab models, we parameterize expressions for the energy of metal atoms as a function of their coordination number in 21 bimetallic pairings of fcc metals. Here, we rigorously establish the transferability of our model by predicting relative energies of a series of nanoparticles across a large number of morphologies, sizes, atomic compositions, and arrangements. The model is particularly accurate in predicting atomic rearrangements at or near the metal surfaces, which is essential for its potential applications when studying segregation phenomena or dynamic processes in heterogeneous catalysis. By rapidly forecasting site stabilities with atomic specificity across generic structural and compositional features, our model is able to reverse engineer thermodynamically feasible motifs of active sites in bimetallic nanoparticles through robust property &hArr; structure relations.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2019

Within-host infectious disease models accommodating cellular coinfection, with an application to influenza

Within-host models are useful tools for understanding the processes regulating viral load dynamics. While existing models have considered a wide range of within-host processes, at their core these models have shown remarkable structural similarity. Specifically, the structure of these models generally consider target cells to be either uninfected or infected, with the possibility of accommodating further resolution (e.g. cells that are in an eclipse phase). Recent findings, however, indicate that cellular coinfection is the norm rather than the exception for many viral infectious diseases, and that cells with high multiplicity of infection are present over at least some duration of an infection. The reality of these cellular coinfection dynamics is not accommodated in current within-host models although it may be critical for understanding within-host dynamics. This is particularly the case if multiplicity of infection impacts infected cell phenotypes such as their death rate and their viral production rates. Here, we present a new class of within-host disease models that allow for cellular coinfection in a scalable manner by retaining the low-dimensionality that is a desirable feature of many current within-host models. The models we propose adopt the general structure of epidemiological ‘macroparasite’ models that allow hosts to be variably infected by parasites such as nematodes and host phenotypes to flexibly depend on parasite burden. Specifically, our within-host models consider target cells as ‘hosts’ and viral particles as ‘macroparasites’, and allow viral output and infected cell lifespans, among other phenotypes, to depend on a cell’s multiplicity of infection. We show with an application to influenza that these models can be statistically fit to viral load and other within-host data, and demonstrate using model selection approaches that they have the ability to outperform traditional within-host viral dynamic models. Important in vivo quantities such as the mean multiplicity of cellular infection and time-evolving reassortant frequencies can also be quantified in a straightforward manner once these macroparasite models have been parameterized. The within-host model structure we develop here provides a mathematical way forward to address questions related to the roles of cellular coinfection, collective viral interactions, and viral complementation in within-host viral dynamics and evolution.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Collaborative Project. 3D Radiative Transfer Parameterization Over Mountains/Snow for High-Resolution Climate Models. Fast physics and Applications

Under the support of the aforementioned DOE Grant, we have made two fundamental contributions to atmospheric and climate sciences: (1) Develop an efficient 3-D radiative transfer parameterization for application to intense and intricate inhomogeneous mountain/snow regions. (2) Innovate a stochastic parameterization for light absorption by internally mixed black carbon and dust particles in snow grains for understanding and physical insight into snow albedo reduction in climate models. With reference to item (1), we divided solar fluxes reaching mountain surfaces into five components: direct and diffuse fluxes, direct- and diffuse-reflected fluxes, and coupled mountain-mountain flux. “Exact” 3D Monte Carlo photon tracing computations can then be performed for these solar flux components to compare with those calculated from the conventional plane-parallel (PP) radiative transfer program readily available in climate models. Subsequently, Parameterizations of the deviations of 3D from PP results for five flux components are carried out by means of the multiple linear regression analysis associated with topographic information, including elevation, solar incident angle, sky view factor, and terrain configuration factor. We derived five regression equations with high statistical correlations for flux deviations and successfully incorporated this efficient parameterization into WRF model, which was used as the testbed in connection with the Fu-Liou-Gu PP radiation scheme that has been included in the WRF physics package. Incorporating this 3D parameterization program, we conducted simulations of WRF and CCSM4 to understand and evaluate the mountain/snow effect on snow albedo reduction during seasonal transition and the interannual variability for snowmelt, cloud cover, and precipitation over the Western United States presented in the final report. With reference to item (2), we developed in our previous research a geometric-optics surface-wave approach (GOS) for the computation of light absorption and scattering by complex and inhomogeneous particles for application to aggregates and snow grains with external and internal mixing structures. We demonstrated that a small black (BC) particle on the order of 1 μm internally mixed with snow grains could effectively reduce visible snow albedo by as much as 5–10%. Following this work and within the context of DOE support, we have made two key accomplishments presented in the attached final report.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Application of physiologically based pharmacokinetic modeling for sertraline dosing recommendations in pregnancy

Pregnancy is a period of significant change that impacts physiological and metabolic status leading to alterations in the disposition of drugs. Uncertainty in drug dosing in pregnancy can lead to suboptimal therapy, which can contribute to disease exacerbation. A few studies show there are increased dosing requirements for antidepressants in late pregnancy; however, the quantitative data to guide dose adjustments are sparse. We aimed to develop a physiologically based pharmacokinetic (PBPK) model that allows gestational-age dependent prediction of sertraline dosing in pregnancy. A minimal physiological model with defined gut, liver, plasma, and lumped placental-fetal compartments was constructed using the ordinary differential equation solver package, ‘mrgsolve’, in R. We extracted data from the literature to parameterize the model, including sertraline physicochemical properties, in vitro metabolism studies, disposition in nonpregnant women, and physiological changes during pregnancy. The model predicted the pharmacokinetic parameters from a clinical study with eight subjects for the second trimester and six subjects for the third trimester. Based on the model, gestational-dependent changes in physiology and metabolism account for increased clearance of sertraline (up to 143% at 40 weeks gestational age), potentially leading to under-dosing of pregnant women when nonpregnancy doses are used. The PBPK model was converted to a prototype web-based interactive dosing tool to demonstrate how the output of a PBPK model may translate into optimal sertraline dosing in pregnancy. Quantitative prediction of drug exposure using PBPK modeling in pregnancy will support clinically appropriate dosing and increase the therapeutic benefit for pregnant women.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Modeling of Aircraft Measurements of Ice Crystal Concentration in the Arctic and a Parameterization for Mixed-Phase Cloud

Abstract In this study, two parameterizations of ice nucleation rate on dust particles are used in a parcel model to simulate aircraft measurements of ice crystal number concentration Ni in the Arctic. The parcel model has detailed microphysics for droplet and ice nucleation, growth, and evaporation with prescribed vertical air velocities. Three dynamic regimes are considered, including large-scale ascent, cloud-top generating cells, and their combination. With observed meteorological conditions and aerosol concentrations, the parcel model predicts the number concentrations of size-resolved ice crystals, which may be compared to aircraft measurements. Model results show rapid changes with height/time in relative humidity, Ni, and thermodynamic phase partitioning, which is not resolved in current climate and weather forecasting models. Parameterizations for ice number and nucleation rate in mixed-phase stratus clouds are thus developed based on the parcel model results to represent the time-integrated effect of some microphysical processes in large-scale models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Final Technical Report for "High-resolution global modeling of the effects of subgrid-scale clouds and turbulence on precipitating cloud systems"

The Multiscale Modeling Framework (MMF) embeds a cloud-resolving model in each grid column of a General Circulation Model (GCM). A MMF model does not need to use a deep convective parameterization, and thereby dispenses with the uncertainties in such parameterizations. However, MMF models grossly under-resolve shallow boundary-layer clouds, and hence those clouds may still benefit from parameterization. In this grant, we successfully created a climate model that embeds a cloud parameterization (“CLUBB”) within a MMF model. This involved interfacing CLUBB’s clouds with microphysics and reducing computational cost. We have evaluated the resulting simulated clouds and precipitation with satellite observations. The chief benefit of the project is to provide a MMF model that has an improved representation of clouds and that provides improved simulations of precipitation.

47 OTHER INSTRUMENTATION↗