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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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Implementation and evaluation of the unified stomatal optimization approach in the Functionally Assembled Terrestrial Ecosystem Simulator (FATES)

Abstract. Stomata play a central role in regulating the exchange of carbon dioxide and water vapor between ecosystems and the atmosphere. Their function is represented in land surface models (LSMs) by conductance models. The Functionally Assembled Terrestrial Ecosystem Simulator (FATES) is a dynamic vegetation demography model that can simulate both detailed plant demographic and physiological dynamics. To evaluate the effect of stomatal conductance model formulation on forest water and carbon fluxes in FATES, we implemented an optimality-based stomatal conductance model – the Medlyn (MED) model – that simulates the relationship between photosynthesis (A) and stomatal conductance to water vapor (gsw) as an alternative to the FATES default Ball–Woodrow–Berry (BWB) model. To evaluate how the behavior of FATES is affected by stomatal model choice, we conducted a model sensitivity analysis to explore the response of gsw to climate forcing, including atmospheric CO2 concentration, air temperature, radiation, and vapor pressure deficit in the air (VPDa). We found that modeled gsw values varied greatly between the BWB and MED formulations due to the different default stomatal slope parameters (g1). After harmonizing g1 and holding the stomatal intercept parameter (g0) constant for both model formulations, we found that the divergence in modeled gsw was limited to conditions when the VPDa exceeded 1.5 kPa. We then evaluated model simulation results against measurements from a wet evergreen forest in Panama. Results showed that both the MED and BWB model formulations were able to capture the magnitude and diurnal changes of measured gsw and A but underestimated both by about 30 % when the soil was predicted to be very dry. Comparison of modeled soil water content from FATES to a reanalysis product showed that FATES captured soil drying well, but translation of drying soil to modeled physiology reduced the models' ability to match observations. Our study suggests that the parameterization of stomatal conductance models and current model response to drought are the critical areas for improving model simulation of CO2 and water fluxes in tropical forests.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Evaluating the potential for bird‐habitat models to support biodiversity‐friendly urban planning

Abstract Urban expansion poses a major threat to wildlife populations. Biodiversity‐friendly urban landscapes could deliver benefits for both wildlife and people, by incorporating conservation and ecosystem services objectives. Well‐designed urban developments could also soften the ecological impacts of urbanization. However, delivering urban landscapes that integrate biodiversity requirements effectively remains challenging. Ecological models, designed to predict wildlife population responses to alternative urban designs, could prove effective in supporting the creation of biodiversity‐friendly urban landscapes. Here, we combine national‐scale bird abundance data with high resolution, spatially explicit habitat data to characterize relationships between bird densities and urban landscape form in Britain. From these analyses and cross validation, we evaluate the potential for well‐parameterized, species‐specific models to be used to predict bird densities in novel or modified urban areas. Our analyses indicate that responses of bird abundance to urban habitat are species‐specific and complex, with few variables consistently affecting a large proportion of species. However, contiguous areas of greenspace within urban sites are preferential for accommodating breeding birds, compared to a more fragmented arrangement of multiple, small greenspace patches. In combination, the bird‐habitat relationships identified could successfully predict observed variation in abundance for most bird species considered. Further evaluation of habitat descriptor variables, spatial scales of species' habitat use and analytical modelling approaches may be needed to improve the predictive ability of bird‐habitat models for certain species, particularly waterbirds and those observed less frequently in urban areas. Synthesis and applications . We modelled breeding bird abundance in built‐up areas with respect to the characteristics and contexts of urban environments. While most variables were important for multiple species, responses overall were species‐specific, so simple assemblage metrics, like diversity, will not describe the variation in bird communities well. However, the results illustrate the potential of an evidence‐based, spatially explicit evaluation of urban development impacts on biodiversity, by predicting the consequences for bird numbers. Subject to verification of predictive ability, practitioners can apply the models to compare, for example, land‐sparing and sharing within developments, or to quantify the biodiversity requirements for effective offsetting. This would be facilitated by incorporation into an online tool allowing user‐determined input scenarios.

Plummer, Kate E.↗
DOE OSTI2014

Parameterization and sensitivity analysis of a process‐based terrestrial ecosystem model using adjoint method

Abstract We developed an adjoint version of a process‐based biogeochemistry model, the Terrestrial Ecosystem Model (TEM). The adjoint model of TEM was then used to: (1) conduct sensitivity studies of net ecosystem production (NEP) for three terrestrial ecosystems: grassland, deciduous broadleaf forest and evergreen needle‐leaf forest; (2) rank the importance of parameters in controlling NEP; (3) optimize the model parameters by assimilating eddy flux data of NEP; and (4) evaluate parameterization by extrapolating optimal parameters to other sites that have the same plant functional type as the calibration sites. We found that: (1) the maximum rate of photosynthesis ( C MAX ) was the most important parameter in determining NEP, while the importance of the remaining parameters varied depending on plant functional type, suggesting that the same ecosystem process has different degrees of importance in modeling carbon fluxes; (2) the sensitivity of NEP to C MAX had a significant seasonal variability and the control of C MAX on NEP was much larger in growing season (defined as from April to October) than that in nongrowing season (defined as from December to March); and (3) after parameterization, TEM could reasonably reproduce carbon fluxes observed at eddy flux tower sites. This study provided an effective model‐data fusion framework of TEM, which could improve the future quantification of terrestrial ecosystem carbon fluxes at both site and regional levels.

Zhu, Qing↗
DOE OSTI2017

Contribution of feldspar and marine organic aerosols to global ice nucleating particle concentrations

Ice-nucleating particles (INPs) are known to affect the amount of ice in mixed-phase clouds, thereby influencing many of their properties. The atmospheric INP concentration changes by orders of magnitude from terrestrial to marine environments, which typically contain much lower concentrations. Many modelling studies use parameterizations for heterogeneous ice nucleation and cloud ice processes that do not account for this difference because they were developed based on INP measurements made predominantly in terrestrial environments without considering the aerosol composition. Errors in the assumed INP concentration will influence the simulated amount of ice in mixed-phase clouds, leading to errors in top-of-atmosphere radiative flux and ultimately the climate sensitivity of the model. Here we develop a global model of INP concentrations relevant for mixed-phase clouds based on laboratory and field measurements of ice nucleation by K-feldspar (an ice-active component of desert dust) and marine organic aerosols (from sea spray). The simulated global distribution of INP concentrations based on these two species agrees much better with currently available ambient measurements than when INP concentrations are assumed to depend only on temperature or particle size. Underestimation of INP concentrations in some terrestrial locations may be due to the neglect of INPs from other terrestrial sources. Our model indicates that, on a monthly average basis, desert dusts dominate the contribution to the INP population over much of the world, but marine organics become increasingly important over remote oceans and they dominate over the Southern Ocean. However, day-to-day variability is important. Because desert dust aerosol tends to be sporadic, marine organic aerosols dominate the INP population on many days per month over much of the mid- and high-latitude Northern Hemisphere. This study advances our understanding of which aerosol species need to be included in order to adequately describe the global and regional distribution of INPs in models, which will guide ice nucleation researchers on where to focus future laboratory and field work.

Vergara-Temprado, Jesús (ORCID:0000000231050946)↗
DOE OSTI2023

Modeling diffusion and types I-V sorption of water vapor in heterogeneous systems

Here, a sorption and diffusion model is developed using a mobile-immobile decomposition of the vapor concentration. Henry’s mode represents the mobile species which diffuses through the solid, while Langmuir and pooling modes represent possible immobilization processes that cause nonlinearities in sorption capacity. The model can simulate the five classical sorption types and can incorporate additional dynamics compared to models based on thermodynamic equilibrium. Additionally, the framework allows for discontinuities in material properties encountered in multi-material systems. The resulting non-linear coupled equations are solved by employing a finite element method to discretize in space, and a backward Euler method to discretize in time. The discretized system of equations is solved via a Newton-type iteration scheme at each time-step. Four different materials are parameterized for the model, which are then used in examples to demonstrate the model’s ability to capture complex sorption processes in multi-material systems.

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

A decision tree algorithm for investigation of model biases related to dynamical cores and physical parameterizations: CESM/CAM EVALUATION BY DECISION TREES

An object-based evaluation method using a pattern recognition algorithm (i.e., classification trees) is applied to the simulated orographic precipitation for idealized experimental setups using the National Center of Atmospheric Research (NCAR) Community Atmosphere Model (CAM) with the finite volume (FV) and the Eulerian spectral transform dynamical cores with varying resolutions. Daily simulations were analyzed and three different types of precipitation features were identified by the classification tree algorithm. The statistical characteristics of these features (i.e., maximum value, mean value, and variance) were calculated to quantify the difference between the dynamical cores and changing resolutions. Even with the simple and smooth topography in the idealized setups, complexity in the precipitation fields simulated by the models develops quickly. The classification tree algorithm using objective thresholding successfully detected different types of precipitation features even as the complexity of the precipitation field increased. The results show that the complexity and the bias introduced in small-scale phenomena due to the spectral transform method of CAM Eulerian spectral dynamical core is prominent, and is an important reason for its dissimilarity from the FV dynamical core. The resolvable scales, both in horizontal and vertical dimensions, have significant effect on the simulation of precipitation. The results of this study also suggest that an efficient and informative study about the biases produced by GCMs should involve daily (or even hourly) output (rather than monthly mean) analysis over local scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Why Does Deep Convection Have Different Sensitivities to Temperature Perturbations in the Lower versus Upper Troposphere?

Previous studies have documented that deep convection responds more strongly to above-the-cloud-base temperature perturbations in the lower troposphere than to those in the upper troposphere, a behavior that is important to the dynamics of large-scale moist flows, such as convectively coupled waves. A number of factors may contribute to this differing sensitivity, including differences in buoyancy, vertical velocity, and/or liquid water content in cloud updrafts in the lower versus upper troposphere. Quantifying the contributions from these factors can help to guide the development of convective parameterization schemes. We tackle this issue by tracking Lagrangian particles embedded in cloud-resolving simulations within a linear response framework. The results show that both the differences in updraft buoyancy and vertical velocity play a significant role, with the vertical velocity being the more important, and the effect of liquid water content is only secondary compared to the other two factors. These results indicate that cloud updraft vertical velocities need to be correctly modeled in convective parameterization schemes in order to properly account for the differing convective sensitivities to temperature perturbations at different heights of the free troposphere.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Cloud, Aerosol, and Complex Terrain Interactions (CACTI) Science Plan

General circulation models and downscaled regional models exhibit persistent biases in deep convective initiation location and timing, cloud top height, stratiform area and precipitation fraction, and anvil coverage. Despite important impacts on the distribution of atmospheric heating, moistening, and momentum, nearly all climate models fail to represent convective organization, while system evolution is not represented at all. Improving representation of convective systems in models requires characterization of their predictability as a function of environmental conditions, and this characterization depends on observing many cases of convective initiation, non-initiation, organization, and non-organization. The Cloud, Aerosol, and Complex Terrain Interactions (CACTI) experiment in the Sierras de Córdoba mountain range of north-central Argentina is designed to improve understanding of cloud life cycle and organization in relation to environmental conditions so that cumulus, microphysics, and aerosol parameterizations in multiscale models can be improved. The Sierras de Córdoba range has a high frequency of orographic boundary-layer clouds, many reaching congestus depths, many initiating into deep convection, and some organizing into mesoscale systems uniquely observable from a single fixed site. Some systems even grow upscale to become among the deepest, largest, and longest-lived in the world. These systems likely contribute to an observed regional trend of increasing extreme rainfall, and poor prediction of them likely contributes to a warm, dry bias in climate models downstream of the Sierras de Córdoba range in a key agricultural region. Many environmental factors influence the convective life cycle in this region, including orographic, low-level jet, and frontal circulations, surface fluxes, synoptic vertical motions influenced by the Andes, cloud detrainment, and aerosol properties. Local and long-range transport of smoke resulting from biomass burning as well as blowing dust are common in the austral spring, while changes in land surface properties as the wet season progresses impact surface fluxes and boundary-layer evolution on daily and seasonal time scales that feed back to cloud and rainfall generation. This range of environmental conditions and cloud properties coupled with a high frequency of events makes this an ideal location for improving our understanding of cloud-environment interactions. The following primary science questions will be addressed through coordinated first U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF1), mobile C-band Scanning ARM Precipitation Radar (C-SAPR2), ARM Aerial Facility (AAF) Gulfstream-1 (G-1), and guest instrument observations: How are the properties and life cycles of orographically generated cumulus humulis, mediocris, and congestus clouds affected by environmental kinematics, thermodynamics, aerosols, and surface properties? How do these cloud types alter these environmental conditions? How do environmental kinematics, thermodynamics, and aerosols impact deep convective initiation, upscale growth, and mesoscale organization? How are soil moisture, surface fluxes, and aerosol properties altered by deep convective precipitation events and seasonal accumulation of precipitation? This multi-faceted experiment involves a long-term 7-month extended operational period (EOP, 1 October, 2018–30 April, 2019) as well as a 1.5-month intensive operational period (IOP, 30 October–13 December) that will include G-1 observations coinciding with the international multi-agency Remote Sensing of Electrification, Lightning, and Meso-scale/Micro-scale Processes with Adaptive Ground Observations (RELAMPAGO) field campaign.

Convection, Andes, Argentina, cloud life cycle, cl↗
DOE OSTI2015

Parameter Estimation for Single Diode Models of Photovoltaic Modules

Many popular models for photovoltaic system performance employ a single diode model to compute the I - V curve for a module or string of modules at given irradiance and temperature conditions. A single diode model requires a number of parameters to be estimated from measured I - V curves. Many available parameter estimation methods use only short circuit, o pen circuit and maximum power points for a single I - V curve at standard test conditions together with temperature coefficients determined separately for individual cells. In contrast, module testing frequently records I - V curves over a wide range of irradi ance and temperature conditions which, when available , should also be used to parameterize the performance model. We present a parameter estimation method that makes use of a fu ll range of available I - V curves. We verify the accuracy of the method by recov ering known parameter values from simulated I - V curves . We validate the method by estimating model parameters for a module using outdoor test data and predicting the outdoor performance of the module.

14 SOLAR ENERGY↗
DOE OSTI2013

Final scientific report for DOE award title: Improving the Representation of Ice Sedimentation Rates in Global Climate Models

It is well known that cirrus clouds play a major role in regulating the earth’s climate, but the details of how this works are just beginning to be understood. This project targeted the main property of cirrus clouds that influence climate processes; the ice fall speed. That is, this project improves the representation of the mass-weighted ice particle fall velocity, V m , in climate models, used to predict future climate on global and regional scales. Prior to 2007, the dominant sizes of ice particles in cirrus clouds were poorly understood, making it virtually impossible to predict how cirrus clouds interact with sunlight and thermal radiation. Due to several studies investigating the performance of optical probes used to measure the ice particle size distribution (PSD), as well as the remote sensing results from our last ARM project, it is now well established that the anomalously high concentrations of small ice crystals often reported prior to 2007 were measurement artifacts. Advances in the design and data processing of optical probes have greatly reduced these ice artifacts that resulted from the shattering of ice particles on the probe tips and/or inlet tube, and PSD measurements from one of these improved probes (the 2-dimensional Stereo or 2D-S probe) are utilized in this project to parameterize V m for climate models. Our original plan in the proposal was to parameterize the ice PSD (in terms of temperature and ice water content) and ice particle mass and projected area (in terms of mass- and area-dimensional power laws or m-D/A-D expressions) since these are the microphysical properties that determine V m , and then proceed to calculate V m from these parameterized properties. But the 2D-S probe directly measures ice particle projected area and indirectly estimates ice particle mass for each size bin. It soon became apparent that the original plan would introduce more uncertainty in the V m calculations than simply using the 2D-S measurements to directly calculate V m . By calculating V m directly from the measured PSD, ice particle projected area and estimated mass, more accurate estimates of V m are obtained. These V m values were then parameterized for climate models by relating them to (1) sampling temperature and ice water content (IWC) and (2) the effective diameter (D e ) of the ice PSD. Parameterization (1) is appropriate for climate models having single-moment microphysical schemes whereas (2) is appropriate for double-moment microphysical schemes and yields more accurate V m estimates. These parameterizations were developed for tropical cirrus clouds, Arctic cirrus, mid-latitude synoptic cirrus and mid-latitude anvil cirrus clouds based on field campaigns in these regions. An important but unexpected result of this research was the discovery of microphysical evidence indicating the mechanisms by which ice crystals are produced in cirrus clouds. This evidence, derived from PSD measurements, indicates that homogeneous freezing ice nucleation dominates in mid-latitude synoptic cirrus clouds, whereas heterogeneous ice nucleation processes dominate in mid-latitude anvil cirrus. Based on these findings, D e was parameterized in terms of temperature (T) for conditions dominated by (1) homo- and (2) heterogeneous ice nucleation. From this, an experiment was designed for global climate models (GCMs). The net radiative forcing from cirrus clouds may be affected by the means ice is produced (homo- or heterogeneously), and this net forcing contributes to climate sensitivity (i.e. the change in mean global surface temperature resulting from a doubling of CO 2 ). The objective of this GCM experiment was to determine how a change in ice nucleation mode affects the predicted global radiation balance. In the first simulation (Run 1), the D e -T relationship for homogeneous nucleation is used at all latitudes, while in the second simulation (Run 2), the D e -T relationship for heterogeneous nucleation is used at all latitudes. For both runs, V m is calculated from D e . Two GCMs were used; the Community Atmosphere Model version 5 (CAM5) and a European GCM known as ECHAM5 (thanks to our European colleagues who collaborated with us). Similar results were obtained from both GCMs in the Northern Hemisphere mid-latitudes, with a net cooling of ~ 1.0 W m -2 due to heterogeneous nucleation, relative to Run 1. The mean global net cooling was 2.4 W m -2 for the ECHAM5 GCM while CAM5 produced a mean global net cooling of about 0.8 W m -2 . This dependence of the radiation balance on nucleation mode is substantial when one considers the direct radiative forcing from a CO 2 doubling is 4 W m -2 . The differences between GCMs in mean global net cooling estimates may demonstrate a need for improving the representation of cirrus clouds in GCMs, including the coupling between microphysical and radiative properties. Unfortunately, after completing this GCM experiment, we learned from the company that provided the 2D-S microphysical data that the data was corrupted due to a computer program coding problem. Therefore the microphysical data had to be reprocessed and reanalyzed, and the GCM experiments were redone under our current ASR project but using an improved experimental design.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Modeling strategies and data needs for representing coastal wetland vegetation in land surface models

Vegetated coastal ecosystems sequester carbon rapidly relative to terrestrial ecosystems. Coastal wetlands are poorly represented in land surface models, but work is underway to improve process-based, predictive modeling of these ecosystems. Here, in this work, we identify guiding questions, potential simulations, and data needs to make progress in improving representation of vegetation in terrestrial–aquatic interfaces, with a focus on coastal and estuarine ecosystems. We synthesize relevant plant traits and environmental controls on vegetation that influence carbon cycling in coastal ecosystems. We propose that models include separate plant functional types (PFTs) for mangroves, graminoid salt marshes, and succulent salt marshes to adequately represent the variation in aboveground and belowground productivity between common coastal wetland vegetation types. We also discuss the drivers and carbon storage consequences of shifts in dominant PFTs. We suggest several potential approaches to represent the diversity in vegetation tolerance and adaptations to fluctuations in salinity and water level, which drive key gradients in coastal wetland ecosystems. Finally, we discuss data needs for parameterizing and evaluating model implementations of coastal wetland vegetation types and function.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A Surface Radiation Balance Dataset from Siple Dome in West Antarctica for Atmospheric and Climate Model Evaluation

Abstract A field campaign at Siple Dome in West Antarctica during the austral summer 2019/20 offers an opportunity to evaluate climate model performance, particularly cloud microphysical simulation. Over Antarctic ice sheets and ice shelves, clouds are a major regulator of the surface energy balance, and in the warm season their presence occasionally induces surface melt that can gradually weaken an ice shelf structure. This dataset from Siple Dome, obtained using transportable and solar-powered equipment, includes surface energy balance measurements, meteorology, and cloud remote sensing. To demonstrate how these data can be used to evaluate model performance, comparisons are made with meteorological reanalysis known to give generally good performance over Antarctica (ERA5). Surface albedo measurements show expected variability with observed cloud amount, and can be used to evaluate a model’s snowpack parameterization. One case study discussed involves a squall with northerly winds, during which ERA5 fails to produce cloud cover throughout one of the days. A second case study illustrates how shortwave spectroradiometer measurements that encompass the 1.6- μ m atmospheric window reveal cloud phase transitions associated with cloud life cycle. Here, continuously precipitating mixed-phase clouds become mainly liquid water clouds from local morning through the afternoon, not reproduced by ERA5. We challenge researchers to run their various regional or global models in a manner that has the large-scale meteorology follow the conditions of this field campaign, compare cloud and radiation simulations with this Siple Dome dataset, and potentially investigate why cloud microphysical simulations or other model components might produce discrepancies with these observations. significance statement Antarctica is a critical region for understanding climate change and sea level rise, as the great ice sheets and the ice shelves are subject to increasing risk as global climate warms. Climate models have difficulties over Antarctica, particularly with simulation of cloud properties that regulate snow surface melting or refreezing. Atmospheric and climate-related field work has significant challenges in the Antarctic, due to the small number of research stations that can support state-of-the-art equipment. Here we present new data from a suite of transportable and solar-powered instruments that can be deployed to remote Antarctic sites, including regions where ice shelves are most at risk, and we demonstrate how key components of climate model simulations can be evaluated against these data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Techno-Economic Analysis and Life Cycle Assessment for Guiding Bioenergy Pathway Development

The Center for Bioenergy Innovation (CBI) is a bioenergy research center recently launched by the U.S. Department of Energy Office of Science's Biological and Environmental Research program. CBI's objective is to enable innovations across the bioenergy supply chain through development of poplar and switchgrass phenotypes, microorganisms for consolidated bio-processing (CBP), in which biomass fermentation and conversion is accomplished in a single unit operation, and lignin valorization processes. In addition to basic science, CBI's activities involve the application of techno-economic analysis (TEA) and life cycle assessment (LCA) to the bioenergy pathways under study. TEA and LCA is used to quantify the impacts that research and development breakthroughs have on the economic viability and sustainability of a bioenergy pathway, and to identify drivers for reducing costs and improving sustainability through targeted research efforts. Combining TEA and LCA allows for understanding the economic and sustainability benefits and trade-offs of these integrated bioenergy systems. The focus of this presentation is a parameterized, integrated TEA-LCA model, which will be discussed along with an application to bioenergy pathways currently under study. The model combines data and information developed by CBI researchers into a superstructure of potential bioenergy pathways and their life cycles. Model parameters include feedstock species and phenotype, farming, harvesting, storage and transportation practices, and the microbes used for biomass conversion and lignin valorization, among others. The parameterized TEA-LCA model allows for the rapid quantification of pathway economic and sustainability metrics such as minimum fuel selling price, payback period, fossil fuel consumption and net greenhouse gas emissions. To demonstrate the model, economic and sustainability metrics for a bioenergy pathway utilizing CBP will be quantified and compared to the same metrics for a conventional bioenergy pathway. Results of the comparison will be used to identify and prioritize high-impact research areas within the CBP pathway. fermentation and conversion is accomplished in a single unit operation, and lignin valorization processes. In addition to basic science, CBI's activities involve the application of techno-economic analysis (TEA) and life cycle assessment (LCA) to the bioenergy pathways under study. TEA and LCA is used to quantify the impacts that research and development breakthroughs have on the economic viability and sustainability of a bioenergy pathway, and to identify drivers for reducing costs and improving sustainability through targeted research efforts. Combining TEA and LCA allows for understanding the economic and sustainability benefits and trade-offs of these integrated bioenergy systems. The focus of this presentation is a parameterized, integrated TEA-LCA model, which will be discussed along with an application to bioenergy pathways currently under study. The model combines data and information developed by CBI researchers into a superstructure of potential bioenergy pathways and their life cycles. Model parameters include feedstock species and phenotype, farming, harvesting, storage and transportation practices, and the microbes used for biomass conversion and lignin valorization, among others. The parameterized TEA-LCA model allows for the rapid quantification of pathway economic and sustainability metrics such as minimum fuel selling price, payback period, fossil fuel consumption and net greenhouse gas emissions. To demonstrate the model, economic and sustainability metrics for a bioenergy pathway utilizing CBP will be quantified and compared to the same metrics for a conventional bioenergy pathway. Results of the comparison will be used to identify and prioritize high-impact research areas within the CBP pathway.

09 BIOMASS FUELS↗
DOE OSTI2020

Modeling Interfaces to Support Low-Level Waste Disposal System Performance Assessments - 20366

In low-level waste (LLW) disposal sites, interfaces between cementitious materials, used as waste forms and/or engineered barriers, and the surrounding soil or backfill material are often encountered. Reactions across these interfaces may lead to chemical and structural alteration of the cementitious and backfill materials that may ultimately affect long-term performance. For example, the ingress of carbon dioxide from soil gas into a waste tank concrete shell at the Hanford Site or Savannah River Site (SRS) or a low-level waste disposal vault at SRS leads to carbonation of cement hydration products (e.g. portlandite, calcium-silicate hydrate or C-S-H, and ettringite). The result of carbonation is a decrease in pH in the cement paste portion of the tank wall or vault concrete structure that could ultimately lead to de-passivation of the embedded structural steel and, eventually, to cracking. Cracking can lead to increased ingress of water into the structure, corresponding increased release of constituents of concern, and to subsequent increased transport of these constituents to the surrounding environment. The mobility of trace constituents (e.g., radionuclides of concern) in waste forms may increase in response to changes in pH, pore structure, and mineralogical gradients. Depletion of portlandite results in subsequent decalcification of C-S-H that leads to changes in the cement strength and may lead to structural failure. At the boundary between waste forms and concrete vaults, the migration of sulfate ions from the salt waste form (e.g., the saltstone waste form used for LLW disposal at the Savannah River Site in Saltstone Disposal Units, or SDUs) into the barrier or vault concrete has been predicted to result in expansive mineral phase formation (or 'sulfate attack'). Expansive mineral formation could result in cracking and potential loss of structural integrity in the vault concrete. In the performance assessment (PA) for the SRS SDUs, prediction of both the carbonation and sulfate attack fronts are critical to assessing the long-term performance of these LLW disposal vaults. A general purpose geochemical reactive transport model has been developed in LeachXS/ORCHESTRA to evaluate typical interfaces for LLW disposal environments, including SDUs at SRS. The model may be used to predict the long-term performance of interfaces between cementitious materials and saltstone or backfill materials with respect to primary phases by considering mass transport, cement chemistry, geochemical speciation, and multi-ionic diffusion over interfaces between different materials. The present study compares the performance and interactions between vault concrete and saltstone waste form for a representative SDU scenario. The materials were characterized using pH-dependence leaching test (EPA 1313) and semi-dynamic transport tests (EPA 1315) with test results used to parameterize the interface model. The development of a credible inter model provides an important basis for supporting future PAs where carbonation and sulfate attack are important aging and degradation mechanisms. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2014

Diagnosis of the Marine Low Cloud Simulation in the NCAR Community Earth System Model (CESM) and the NCEP Global Forecast System (GFS)-Modular Ocean Model v4 (MOM4) coupled model

We present a diagnostic analysis of the marine low cloud climatology simulated by two state-of-the-art coupled atmosphere-ocean models: the NCAR Community Earth System Model (CESM) and the NCEP Global Forecasting System (GFS). In both models, the shallow convection and boundary layer turbulence parameterizations have been recently updated: both models now use a mass-flux scheme for the parameterization of shallow convection, and a turbulence parameterization capable of handling Stratocumulus (Sc)-topped Planetary Boundary Layers (PBLs). For shallow convection, both models employ a convective trigger function based on the concept of convective inhibition and both include explicit convective overshooting/penetrative entrainment formulation. For Sc-topped PBL, both models treat explicitly turbulence mixing and cloud-top entrainment driven by cloud-top radiative cooling. Our focus is on the climatological transition from Sc to shallow Cumulus (Cu)-topped PBL in the subtropical eastern oceans. We show that in the CESM the coastal Sc-topped PBLs in the subtropical Eastern Pacific are well-simulated but the climatological transition from Sc to shallow Cu is too abrupt and happens too close to the coast. By contrast, in the GFS coupled simulation the coastal Sc amount and PBL depth are severely underestimated while the transition from Sc to shallow Cu is ³delayed² and offshore Sc cover is too extensive in the subtropical Eastern Pacific. We discuss the possible connections between such differences in the simulations and differences in the parameterizations of shallow convection and boundary layer turbulence in the two models.

Xiao, Heng↗
DOE OSTI2017

Experimental and Computational Interrogation of Fast SCR Mechanism and Active Sites on H-Form SSZ-13

Experiment and density functional theory (DFT) models are combined to develop a unified, quantitative model of the mechanism and kinetics of fast selective catalytic reduction (SCR) of NO/NO2 mixtures over H-SSZ-13 zeolite. Rates, rate orders, and apparent activation energies collected under differential conditions reveal two distinct kinetic regimes. First-principles thermodynamics simulations are used to determine the relative coverages of free Brønsted sites, chemisorbed NH4+ and physisorbed NH3 as a function of reaction conditions. First-principles metadynamics calculations show that all three sites can contribute to the rate-limiting N-N bond forming step in fast SCR. The results are used to parameterize a kinetic model that encompasses the full range of reaction conditions and recovers observed rate orders and apparent activation energies. Observed kinetic regimes are related to changes in most-abundant surface intermediates. Financial support was provided by the National Science Foundation GAOLI program under award number 1258690-CBET. We thank the Center for Research Computing at Notre

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Experimental evidence for dynamic friction on rock fractures from frequency-dependent nonlinear hysteresis and harmonic generation: Low-Frequency Torsional Dynamic Friction

Frictional properties affect the propagation of high-amplitude seismic waves across rock fractures and faults. Laboratory evidence suggests that these properties can be measured in active seismic surveys, potentially offering a route to characterizing friction in situ. Here, we present experimental results from a subresonance torsional modulus and attenuation apparatus that utilizes micron-scale sinusoidal oscillations to probe the nonlinear stress-strain relation at a range of strain amplitudes and rates. Nonlinear effects are further quantified using harmonic distortion; however, time series data best illuminate underlying physical processes. The low-frequency stress-strain hysteretic loops show stiffening at the sinusoid's static ends, but stiffening is reduced above a threshold frequency. This shape is determined by harmonic generation in the strain; the stress signal has no harmonics, confirming that the fractured sample is the source of the nonlinearity. These qualitative observations suggest the presence of rate-dependent friction and are consistent between fractures in three different rock types. We propose that static friction at the low strain rate part of the cycle, when given sufficient “healing” time at low oscillation frequencies, causes this stiffening cusp shape in the hysteresis loop. While rate-and-state friction is commonly used to represent dynamic friction, it cannot capture static friction or negative slip velocities. So we implement another dynamic friction model, based on the work of Dahl, which describes this process and produces similar results. Since the two models have a similar form, parameterizations of field data could constraint fault model inputs, such as specific location velocity strengthening or weakening properties.

58 GEOSCIENCES↗