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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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NASA NTRS1992

Investigation of the flight mechanics simulation of a hovering helicopter

The flight mechanics simulation of a hovering helicopter is investigated by comparing the results of two different numerical models with flight test data for a hovering AH-64 Apache. The two models are the U.S. Army BEMAP and the Technion model. These nonlinear models are linearized by applying a numerical linearization procedure. The results of the linear models are compared with identification results in terms of eigenvalues, stability and control derivatives, and frequency responses. Detailed time histories of the responses of the complete nonlinear models, as a result of various pilots' inputs, are compared with flight test results. In addition the sensitivity of the models to various effects are also investigated. The results are discussed and problematic aspects of the simulation are identified.

Chaimovich, M.↗
DOE OSTI2024

Development of an Improved RELAP5-3D Model for the High Temperature Test Facility

High-temperature gas-cooled reactors (HTGRs) are rapidly approaching deployment. Confidence in transient analysis of these systems for design, optimization, and licensing calculations requires modeling and simulation tools that have been validated against data relevant to HTGR conditions. The High Temperature Test Facility (HTTF) is an integral effects thermal hydraulics test facility for prismatic HTGRs. In spring and summer of 2019, HTTF was used for a series of experiments that now serve as the basis for the OECD/NEA Thermal Hydraulic Code Validation Benchmark for High Temperature Gas-Cooled Reactors using HTTF Data (HTGR T/H Benchmark). This benchmark contains problems for systems code, computational fluid dynamics (CFD), and coupled systems code/CFD modeling representing lower plenum mixing and both the depressurized and pressurized conduction cooldown (DCC and PCC respectively) transients. Benchmark problems include exercises for code-to-code and code-to-data comparisons as well as an exercise for error scaling between HTTF and the Modular High Temperature Gas-Cooled Reactor, which serves as the basis for the HTTF design. Previous analysis as part of the HTGR T/H benchmark used a RELAP5-3D model developed at Idaho National Laboratory (INL) and demonstrated an ability to reproduce trends in the measured data but difficulties reproducing experimental values within their uncertainty. These difficulties were largely attributed to assumptions made during the development of the initial RELAP5-3D model, which predated the HTTF experiments. A significant cause of difficulty reproducing the measured temperatures may be the radial nodalization of the previous RELAP5-3D model. The new model provides a finer nodalization to assess the impact of radial nodalization and allows for asymmetric heating within the core, which was a feature of multiple HTTF experiments. In this paper, we present the new RELAP5-3D model of HTTF. In addition to describing the new model, this paper compares the new and old models and provides results for a full-power steady state, a DCC, and a PCC in HTTF. These analyses are based on the code-to-code comparison exercises for the DCC and PCC problems of the HTGR T/H benchmark. We present the results of these exercises from the new model and compare them to the results of the old model.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Simulating Long–Term Dynamics of Radiation Belt Electrons Using DREAM3D Model

Here, we compared the performance of DREAM3D simulations in reproducing the long-term radiation belt dynamics observed by Van Allen Probes over the entire year of 2017 with various boundary conditions (BCs) and model inputs. Specifically, we investigated the effects of three different outer boundary conditions, two different low-energy boundary conditions for seed electrons, four different radial diffusion (RD) coefficients (DLL), four hiss wave models, and two chorus wave models from the literature. Using the outer boundary condition driven by GOES data, our benchmark simulation generally well reproduces the observed radiation belt dynamics inside L* = 6, with a better model performance at lower μ than higher μ, where μ is the first adiabatic invariant. By varying the boundary conditions and inputs, we find that: (a) The data-driven outer boundary condition is critical to the model performance, while adding in the data-driven seed population doesn't further improve the performance. (b) The model shows comparable performance with DLL from Brautigam and Albert (2000, https://doi.org/10.1029/1999ja900344), Ozeke et al. (2014, https://doi.org/10.1002/2013ja019204), and Liu et al. (2016, https://doi.org/10.1002/2015gl067398), while with DLL from Ali et al. (2016, https://doi.org/10.1002/2016ja023002) the model shows less RD compared to data. (c) The model performance is similar with data-based hiss models, but the results show faster loss is still needed inside the plasmasphere. (d) The model performs similarly with the two different chorus models, but better capturing the electron enhancement at higher μ using the Wang et al. (2019, https://doi.org/10.1029/2018ja026183) model due to its stronger wave power, since local heating for higher energy electrons is under-reproduced in the current model.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Soil carbon sensitivity to temperature and carbon use efficiency compared across microbial-ecosystem models of varying complexity

Global ecosystem models may require microbial components to accurately predict feedbacks between climate warming and soil decomposition, but it is unclear what parameters and levels of complexity are ideal for scaling up to the globe. Here we conducted a model comparison using a conventional model with first-order decay and three microbial models of increasing complexity that simulate short- to long-term soil carbon dynamics. We focused on soil carbon responses to microbial carbon use efficiency (CUE) and temperature. Three scenarios were implemented in all models: constant CUE (held at 0.31), varied CUE ( 0.016 C 1), and 50 % acclimated CUE ( 0.008 C 1). Whereas the conventional model always showed soil carbon losses with increasing temperature, the microbial models each predicted a temperature threshold above which warming led to soil carbon gain. The location of this threshold depended on CUE scenario, with higher temperature thresholds under the acclimated and constant scenarios. This result suggests that the temperature sensitivity of CUE and the structure of the soil carbon model together regulate the long-term soil carbon response to warming. Equilibrium soil carbon stocks predicted by the microbial models were much less sensitive to changing inputs compared to the conventional model. Although many soil carbon dynamics were similar across microbial models, the most complex model showed less pronounced oscillations. Thus, adding model complexity (i.e. including enzyme pools) could improve the mechanistic representation of soil carbon dynamics during the transient phase in certain ecosystems. This study suggests that model structure and CUE parameterization should be carefully evaluated when scaling up microbial models to ecosystems and the globe.

Li, Jianwei↗
DOE OSTI2015

Comparing the cardiovascular therapeutic indices of glycopyrronium and tiotropium in an integrated rat pharmacokinetic, pharmacodynamic and safety model

Long acting inhaled muscarinic receptor antagonists, such as tiotropium, are widely used as bronchodilator therapy for chronic obstructive pulmonary disease (COPD). Although this class of compounds is generally considered to be safe and well tolerated in COPD patients the cardiovascular safety of tiotropium has recently been questioned. We describe a rat in vivo model that allows the concurrent assessment of muscarinic antagonist potency, bronchodilator efficacy and a potential for side effects, and we use this model to compare tiotropium with NVA237 (glycopyrronium bromide), a recently approved inhaled muscarinic antagonist for COPD. Anaesthetized Brown Norway rats were dosed intratracheally at 1 or 6 h prior to receiving increasing doses of intravenous methacholine. Changes in airway resistance and cardiovascular function were recorded and therapeutic indices were calculated against the ED{sub 50} values for the inhibition of methacholine-induced bronchoconstriction. At both time points studied, greater therapeutic indices for hypotension and bradycardia were observed with glycopyrronium (19.5 and 28.5 fold at 1 h; > 200 fold at 6 h) than with tiotropium (1.5 and 4.2 fold at 1 h; 4.6 and 5.5 fold at 6 h). Pharmacokinetic, protein plasma binding and rat muscarinic receptor binding properties for both compounds were determined and used to generate an integrated model of systemic M{sub 2} muscarinic receptor occupancy, which predicted significantly higher M{sub 2} receptor blockade at ED{sub 50} doses with tiotropium than with glycopyrronium. In our preclinical model there was an improved safety profile for glycopyrronium when compared with tiotropium. - Highlights: • We use an in vivo rat model to study CV safety of inhaled muscarinic antagonists. • We integrate protein and receptor binding and PK of tiotropium and glycopyrrolate. • At ED{sub 50} doses for bronchoprotection we model systemic M{sub 2} receptor occupancy. • Glycopyrrolate demonstrates lower M{sub 2} occupancy at bronchoprotective doses. • Glycopyrrolate demonstrates an improved CV safety profile, versus tiotropium.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1988

Entrance and exit region friction factor models for annular seal analysis

The Mach number definition and boundary conditions in Nelson's nominally-centered, annular gas seal analysis are revised. A method is described for determining the wall shear stress characteristics of an annular gas seal experimentally. Two friction factor models are developed for annular seal analysis; one model is based on flat-plate flow theory; the other uses empirical entrance and exit region friction factors. The friction factor predictions of the models are compared to experimental results. Each friction model is used in an annular gas seal analysis. The seal characteristics predicted by the two seal analyses are compared to experimental results and to the predictions of Nelson's analysis. The comparisons are for smooth-rotor seals with smooth and honeycomb stators. The comparisons show that the analysis which uses empirical entrance and exit region shear stress models predicts the static and stability characteristics of annular gas seals better than the other analyses. The analyses predict direct stiffness poorly.

Elrod, David Alan↗
DOE OSTI2018

The Quasi-Biennial Oscillation in Model-Simulated and Observed Equatorial Temperature of the Lower Stratosphere

In an otherwise thorough survey of metrics for models that simulate the Quasi-Biennial Oscillation, Schenzinger et al. say “there is no comparable observational dataset” to compare with model-simulated stratospheric temperatures (Geosci. Model Dev. 10, 2157-2168, 2017). They compare model temperatures only with reanalysis datasets, which come from numerical weather prediction models and therefore are not direct observations. But stratospheric brightness temperatures have been directly observed by microwave radiometers on board a series of satellites since 1979. Christy and Drouilhet (J. Climate 7, 106-120, 1994) found a QBO signal in 1979-1992 data from the Microwave Sounding Unit’s lower stratospheric Channel 4 (with peak weighting function at the 75hPa pressure level and half-power values at 120 and 40hPa, about 20±5 km altitude). To detect the QBO signal, Christy and Drouilhet used a latitude weighting that matches the QBO’s anti-correlation between the Equator and ±15°. Fernandez et al. also found a QBO signal in 1979-2000 MSU data, using EOF analysis (J. Climate 17, 3934-3946, 2004). Recently, Christy and Covey extended Christy and Drouilhet’s analysis through 2017 (“Stratospheric Temperature,” Section 2b5 in State of the Climate in 2017. Bull. Amer. Meteor. Soc. 99, S150–S152; Figure 2.10c). The QBO signal was again clearly visible. Although temperature trends for the lower atmosphere are sensitive to inter-satellite calibration and other processing details, giving rise to some controversy, data for the lower stratosphere are more robust. Christy and Covey’s Figure 2.9 shows that data processed separately by the National Oceanic and Atmospheric Administration (NOAA) and by Remote Sensing Systems (RSS) gives a QBO index that is virtually identical to that of Christy’s group at the University of Alabama at Huntsville (UAH).

58 GEOSCIENCES↗
NASA NTRS1970

Computer discrimination procedures applicable to aerial and ERTS multispectral data

Two statistical models are compared in the classification of crops recorded on color aerial photographs. A theory of error ellipses is applied to the pattern recognition problem. An elliptical boundary condition classification model (EBC), useful for recognition of candidate patterns, evolves out of error ellipse theory. The EBC model is compared with the minimum distance to the mean (MDM) classification model in terms of pattern recognition ability. The pattern recognition results of both models are interpreted graphically using scatter diagrams to represent measurement space. Measurement space, for this report, is determined by optical density measurements collected from Kodak Ektachrome Infrared Aero Film 8443 (EIR). The EBC model is shown to be a significant improvement over the MDM model.

Richardson, A. J.↗
NASA NTRS1982

A comparative study of atmospheric density models in the context of definitive and predictive earth satellite orbit determination

The results of a comparative orbit determination study of four global atmospheric density models (modified Harris-Priester, Jacchia-Roberts, Mass Spectrometer/Incoherent Scatter (MSIS), and Simple Exponential Model (SEM)) are presented. Utilizing these models, definitive orbit determination consistency and accuracy are evaluated using the maximum position differences that occur during 6-hour overlap periods between ephemerides generated from 30-hour data arcs. Propagated ephemerides are compared with definitive orbit solutions to evaluate predictive accuracy. The results indicate that, for satellites above 300 kilometers, all four atmospheric density models produce comparable orbit determination accuracies when an atmospheric drag scaling factor and the satellite state vector are estimated in the orbit determination process.

Shanklin, R. E., Jr.↗
DOE OSTI2018

MS–STEM–FEM: A parallelized multi-slice fluctuation TEM simulation tool

Atomic configurations of glassy or amorphous materials containing medium-range order (MRO) may be identified by comparing fluctuation transmission electron microscopy (FTEM) measurements to FTEM simulations obtained using model configurations. Candidate model sizes have traditionally been much thinner than the samples measured experimentally, and publicly available FTEM simulation software has until now omitted microscope parameters, dynamical scattering, and the phase of the diffracted electron wave. We introduce MS–STEM–FEM, an open-source software package for simulating FTEM experiments using established multi-slice TEM simulation techniques to emulate experiment more closely by incorporating microscope parameters and simulating electron scattering and propagation as a complex valued wave. Simulations using established models are compared with results of experimental STEM–FEM to validate the software. Several statistical measures of diffraction are implemented and their responses to model features are compared. Dynamical scattering is found to be less influential than the variety of crystallite orientations which occur in thicker models. Simulations of variable resolution microscopy confirm that cumulative intensity of the FTEM signal decreases with reduced model MRO and increased coherence volume. In conclusion, advantageous model scaling characteristics and efficient processor performance scaling are demonstrated, along with a study of convergence with respect to pertinent simulation parameters to identify accuracy requirements.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Comparison of plug flow and multi-node stratified tank modeling approaches regarding computational efficiency and accuracy

Residential water heaters contain water stratified by temperature-driven density differences. This implies that a water tank can reach a state in which the top and bottom sections have different temperatures, unless mixing happens. A high degree of thermal stratification can improve the efficiency of some water heaters, by saving the amount of energy required for the heat-up process. Studies of stratification became popular in the 1970s and it remains an active research topic today. The research has led to the development of different models and techniques to better predict and define a stratified tanks behavior. By comparing these models and techniques used previously to describe thermal stratification, the phenomenon could be better understood, exploited, and used to increase efficiency and thermal energy capacity in modern water tanks. From the existing models, we found the one-dimensional standard plug-flow and a multi node model to be appropriate for analyzing the processes of the heat up and cool-down in a water tank. These two models are based on energy balances. This work involved comparing the accuracy and computational effort needed to implement these models. To assess accuracy, we compared both types of existing models to experimental data (also collected in this work) which included a heat up process using an external heat pump. This external process included a layering process that has an eddy diffusivity at five times the rate of thermal diffusion. For this project, we implemented the models in MATLAB, the multi-paradigm numerical computing environment. We quantified model accuracy using the root mean squared error between modeled data and experimental data for six measured tank temperatures. Comparing the accuracy and the computational time taken to run the simulation provides a method to contrast the performance of each model and a way to rate it. The multi node model was run using from 6 to 96 spatial nodes; the plug flow model was run using 1 to 0.001 º C temperature bin sizes. Additionally, timesteps were varied from 4 to 236 s. The results quantify the tradeoff between accuracy and computational time, providing guidance for simulations to intelligently select the best model type and simulation parameters. This research can be used to validate the pre-existing models and possibly improve the modern water tank.

Bulnes, Fernando Karg↗
DOE OSTI2023

Development of a new quantum trajectory molecular dynamics framework

An extension to the wave packet description of quantum plasmas is presented, where the wave packet can be elongated in arbitrary directions. A generalized Ewald summation is constructed for the wave packet models accounting for long-range Coulomb interactions and fermionic effects are approximated by purpose-built Pauli potentials, self-consistent with the wave packets used. We demonstrate its numerical implementation with good parallel support and close to linear scaling in particle number, used for comparisons with the more common wave packet employing isotropic states. Ground state and thermal properties are compared between the models with differences occurring primarily in the electronic subsystem. Especially, the electrical conductivity of dense hydrogen is investigated where a 15% increase in DC conductivity can be seen in our wave packet model compared with other models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Subseasonal Forecasting and MJO Teleconnections in Machine Learning Weather Prediction Models

Abstract In recent years, machine‐learning (ML) models trained on reanalysis data have rivaled physics‐based forecast models in terms of performance skill for global weather forecasting. With increased rollout stability, the question of how these models perform for subseasonal to seasonal (S2S, week 3–8) forecasting has emerged. In this study we run a large set of subseasonal hindcasts over 2004–2023 to evaluate two ML weather forecast models at the S2S time scale, SFNO‐HENS (Nvidia, fully ML) and NeuralGCM (Google Research, hybrid). Corresponding hindcasts from the European Centre for Medium‐Range Weather Forecasts (ECMWF) are used as a baseline for comparison to a physics‐based model. Because our focus is on predicting moisture transport over the Western United States between October and March, we evaluate the models' prediction skill for the Madden‐Julian Oscillation (MJO) and its associated teleconnections in the North Pacific. We find that both ML models are competitive with the ECWMF model, with comparable skill in predicting the North Pacific large‐scale circulation and the MJO at week 3 and beyond. Even though overall the mid‐latitude subseasonal prediction skill remains low, the ML models exhibit interesting behavior such as a realistic propagation of the MJO across the Maritime Continent and realistic teleconnections. A SFNO‐HENS sensitivity experiment with altered initial conditions in the tropics demonstrates the stability of the model, and it illustrates the capability of ML models to represent important physical processes of the atmosphere at the S2S time scale. Plain Language Summary Predicting weather patterns and precipitation a few weeks in advance (subseasonal time scale) is of great interest for stakeholders such as water managers in the Southwest United States (US), where arid conditions prevail. Subseasonal forecasts from traditional weather forecast models exhibit low skill in the region, limiting their applicability. Here we examine whether the recent breakthrough in weather forecasting made with machine learning/artificial intelligence models can translate to improved subseasonal forecasts. Recently‐developed machine learning models exhibit comparable skill to a state‐of‐the‐art physics‐based model for predicting weather patterns in the North Pacific/North America region, and associated moisture transport. The same applies to their skill in predicting the tropical pattern, the Madden‐Julian Oscillation, and its important remote perturbations over the midlatitude East Pacific and Southwest US. Additionally, a perturbation experiment carried out with one of the machine learning models illustrates their ability to not only predict the evolution of atmospheric fields, but also to learn and represent physical processes such as tropics‐extratropics Rossby wave propagation. Key Points Two machine learning weather forecast models exhibit state‐of‐the‐art prediction skill at the subseasonal time scale in the Pacific sector The models equal ECWMF in terms of Madden‐Julian oscillation (MJO) prediction skill, and they accurately predict the MJO propagation and associated teleconnections The two machine‐learning models represent key physical processes for subseasonal prediction, despite being trained for weather forecasting

Peings, Yannick↗
DOE OSTI2023

Net Load Forecasting With Disaggregated Behind-the-Meter PV Generation

As worldwide use of residential photovoltaic (PV) systems grows, system operators and utilities will need to transition from forecasting pure demand to forecasting net load with behind-the-meter (BTM) PV generation. However, PV generation can be difficult to predict and the measurements of PV generation from BTM residential systems are often invisible behind a measurement of the net load, making net load forecasting challenging. This paper proposes a novel two-stage framework for net load forecasting in areas with limited observability and high BTM PV generation. First, the profiles of observable customers are used to disaggregate the net load measurements into the pure load and PV generation. Then, separate models are used to forecast the PV generation and pure load individually, and the results are combined for a net load forecast. Further, this paper also proposes a compensator for correcting the error of the net load forecast, using historical forecast errors of the PV generation, pure load, and net load. The proposed framework is tested through two case studies for areas with high BTM PV penetration and less than 10% observable customers. The two-stage forecasting model is compared to two benchmark methods - a time series forecasting model, and a model that forecasts the net load directly using historical net load measurements. Results show that the proposed disaggregation-forecasting framework reduces the error of the net load forecast compared to both benchmark models. In addition, when the net load forecast error is periodic, the compensator can correct the error to improve the forecast accuracy.

14 SOLAR ENERGY↗
NASA NTRS2012

Deep Solar Activity Minimum 2007-2009: Solar Wind Properties and Major Effects on the Terrestrial Magnetosphere

We discuss the temporal variations and frequency distributions of solar wind and interplanetary magnetic field parameters during the solar minimum of 2007 - 2009 from measurements returned by the IMPACT and PLASTIC instruments on STEREO-A.We find that the density and total field strength were significantly weaker than in the previous minimum. The Alfven Mach number was higher than typical. This reflects the weakness of magnetohydrodynamic (MHD) forces, and has a direct effect on the solar wind-magnetosphere interactions.We then discuss two major aspects that this weak solar activity had on the magnetosphere, using data from Wind and ground-based observations: i) the dayside contribution to the cross-polar cap potential (CPCP), and ii) the shapes of the magnetopause and bow shock. For i) we find a low interplanetary electric field of 1.3+/-0.9 mV/m and a CPCP of 37.3+/-20.2 kV. The auroral activity is closely correlated to the prevalent stream-stream interactions. We suggest that the Alfven wave trains in the fast streams and Kelvin-Helmholtz instability were the predominant agents mediating the transfer of solar wind momentum and energy to the magnetosphere during this three-year period. For ii) we determine 328 magnetopause and 271 bow shock crossings made by Geotail, Cluster 1, and the THEMIS B and C spacecraft during a three-month interval when the daily averages of the magnetic and kinetic energy densities attained their lowest value during the three years under survey.We use the same numerical approach as in Fairfield's empirical model and compare our findings with three magnetopause models. The stand-off distance of the subsolar magnetopause and bow shock were 11.8 R(sub E) and 14.35 R(sub E), respectively. When comparing with Fairfield's classic result, we find that the subsolar magnetosheath is thinner by approx. 1 R(sub E). This is mainly due to the low dynamic pressure which results in a sunward shift of the magnetopause. The magnetopause is more flared than in Fairfield's model. By contrast the bow shock is less flared, and the latter is the result of weaker MHD forces.

solar minimum↗
DOE OSTI2018

Numerical Simulation of Multiphase Magnetohydrodynamic Flow and Deformation of Electrolyte–Metal Interface in Aluminum Electrolysis Cells

A computational fluid dynamics based multiphase magnetohydrodynamic (MHD) flow model for simulating the melt flow and bath–metal interface deformation in realistic aluminum reduction cells is presented. The model accounts for the complex physics of the MHD problem in aluminum reduction cells by coupling two immiscible fluids, electromagnetic field, Lorentz force, flow turbulence, and complex cell geometry with large length scale. Especially, the deformation of bath–metal interface is tracked directly in the simulation, and the condition of constant anode–cathode distance (ACD) is maintained by moving anode bottom dynamically with the deforming bath–metal interface. The metal pad deformation and melt flow predicted by the current model are compared to the predictions using a simplified model where the bath–metal interface is assumed flat. The effects of the induced electric current due to fluid flow and the magnetic field due to the interior cell current on the metal pad deformation and melt flow are investigated. The presented model extends the conventional simplified box model by including detailed cell geometry such as the ledge profile and all channels (side, central, and cross-channels). The simulations show the model sensitivity to different side ledge profiles and the cross-channel width by comparing the predicted melt flow and metal pad heaving. In addition, the model dependencies upon the reduction cell operation conditions such as ACD, current distribution on cathode surface and open/closed channel top, are discussed.

42 ENGINEERING↗
DOE OSTI2018

Emission or atmospheric processes? An attempt to attribute the source of large bias of aerosols in eastern China simulated by global climate models

Here, global climate models often underestimate aerosol loadings in China, and these biases can have significant implications for anthropogenic aerosol radiative forcing and climate effects. The biases may be caused by either the emission inventory or the treatment of aerosol processes in the models, or both, but so far no consensus has been reached. In this study, a relatively new emission inventory based on energy statistics and technology, Multi-resolution Emission Inventory for China (MEIC), is used to drive the Community Atmosphere Model version 5 (CAM5) to evaluate aerosol distribution and radiative effects against observations in China. The model results are compared with the model simulations with the widely used Intergovernmental Panel on Climate Change Fifth Assessment Report (IPCC AR5) emission inventory. We find that the new MEIC emission improves the aerosol optical depth (AOD) simulations in eastern China and explains 22–28 % of the AOD low bias simulated with the AR5 emission. However, AOD is still biased low in eastern China. Seasonal variation of the MEIC emission leads to a better agreement with the observed seasonal variation of primary aerosols than the AR5 emission, but the concentrations are still underestimated. This implies that the atmospheric loadings of primary aerosols are closely related to the emission, which may still be underestimated over eastern China. In contrast, the seasonal variations of secondary aerosols depend more on aerosol processes (e.g., gas- and aqueous-phase production from precursor gases) that are associated with meteorological conditions and to a lesser extent on the emission. It indicates that the emissions of precursor gases for the secondary aerosols alone cannot explain the low bias in the model. Aerosol secondary production processes in CAM5 should also be revisited. The simulation using MEIC estimates the annual-average aerosol direct radiative effects (ADREs) at the top of the atmosphere (TOA), at the surface, and in the atmosphere to be –5.02, –18.47, and 13.45 W m –2 , respectively, over eastern China, which are enhanced by –0.91, –3.48, and 2.57 W m –2 compared with the AR5 emission. The differences of ADREs by using MEIC and AR5 emissions are larger than the decadal changes of the modeled ADREs, indicating the uncertainty of the emission inventories. This study highlights the importance of improving both the emission and aerosol secondary production processes in modeling the atmospheric aerosols and their radiative effects. Yet, if the estimations of MEIC emissions in trace gases do not suffer similar biases to those in the AOD, our findings will help affirm a fundamental error in the conversion from precursor gases to secondary aerosols as hinted in other recent studies following different approaches.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Comprehensive Model of Single Particle Pulverized Coal Combustion Extended to Oxy-Coal Conditions

Oxy-fired coal combustion is a promising potential carbon capture technology. Predictive CFD simulations are valuable tools in evaluating and deploying oxy-fuel and other carbon capture technologies either as retrofit technologies or for new construction. But, accurate predictive simulations require physically realistic submodels with low computational requirements. In particular, comprehensive char oxidation and gasification models have been developed that describe multiple reaction and diffusion processes. Our work extends a comprehensive char conversion code (CCK), which treats surface oxidation and gasification reactions as well as processes such as film diffusion, pore diffusion, ash encapsulation, and annealing. In this work several submodels in the CCK code were updated with more realistic physics or otherwise extended to function in oxy-coal conditions. Improved submodels include the annealing model, the swelling model, the mode of burning parameter, and the kinetic model, as well as the addition of the chemical percolation devolatilization (CPD) model. We compare our results of the char combustion model to oxy-coal data, and further compared to parallel data sets near conventional conditions. A potential method to apply the detailed code in CFD work is given.

01 COAL, LIGNITE, AND PEAT↗