SEARCH · Search NASA

Results for “Structural models”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,063 records · Page 59

All sources NASA NTRS DOE OSTI

DOE OSTI2018

Quantifying the effect of forest age in annual net forest carbon balance

Forests dominate carbon (C) exchanges between the terrestrial biosphere and the atmosphere on land. In the long term, the net carbon flux between forests and the atmosphere has been significantly impacted by changes in forest cover area and structure due to ecological disturbances and management activities. Current empirical approaches for estimating net ecosystem productivity (NEP) rarely consider forest age as a predictor, which represents variation in physiological processes that can respond differently to environmental drivers, and regrowth following disturbance. Here, we conduct an observational synthesis to empirically determine to what extent climate, soil properties, nitrogen deposition, forest age and management influence the spatial and interannual variability of forest NEP across 126 forest eddy-covariance flux sites worldwide. The empirical models explained up to 62% and 71% of spatio-temporal and across-site variability of annual NEP, respectively. An investigation of model structures revealed that forest age was a dominant factor of NEP spatio-temporal variability in both space and time at the global scale as compared to abiotic factors, such as nutrient availability, soil characteristics and climate. These findings emphasize the importance of forest age in quantifying spatio-temporal variation in NEP using empirical approaches.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

BMC Caller: a webtool to identify and analyze bacterial microcompartment types in sequence data

Bacterial microcompartments (BMCs) are protein-based organelles found across the bacterial tree of life. They consist of a shell, made of proteins that oligomerize into hexagonally and pentagonally shaped building blocks, that surrounds enzymes constituting a segment of a metabolic pathway. The proteins of the shell are unique to BMCs. They also provide selective permeability; this selectivity is dictated by the requirements of their cargo enzymes. We have recently surveyed the wealth of different BMC types and their occurrence in all available genome sequence data by analyzing and categorizing their components found in chromosomal loci using HMM (Hidden Markov Model) protein profiles. To make this a “do-it yourself” analysis for the public we have devised a webserver, BMC Caller (https://bmc-caller.prl.msu.edu), that compares user input sequences to our HMM profiles, creates a BMC locus visualization, and defines the functional type of BMC, if known. Shell proteins in the input sequence data are also classified according to our function-agnostic naming system and there are links to similar proteins in our database as well as an external link to a structure prediction website to easily generate structural models of the shell proteins, which facilitates understanding permeability properties of the shell. Additionally, the BMC Caller website contains a wealth of information on previously analyzed BMC loci with links to detailed data for each BMC protein and phylogenetic information on the BMC shell proteins. Our tools greatly facilitate BMC type identification to provide the user information about the associated organism’s metabolism and enable discovery of new BMC types by providing a reference database of all currently known examples.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2011

Membrane Protein Crystallization in Lipidic Mesophases. Hosting Lipid Effects on the Crystallization and Structure of a Transmembrane Peptide

Gramicidin is an apolar pentadecapeptide antibiotic consisting of alternating d- and l-amino acids. It functions, in part, by creating pores in membranes of susceptible cells rendering them leaky to monovalent cations. The peptide should be able to traverse the host membrane either as a double-stranded, intertwined double helix (DSDH) or as a head-to-head single-stranded helix (HHSH). Current structure models are based on macromolecular X-ray crystallography (MX) and nuclear magnetic resonance (NMR). However, the HHSH form has only been observed by NMR. The shape and size of the different gramicidin conformations differ. We speculated therefore that reconstituting it into a lipidic mesophase with bilayers of different microstructures would preferentially stabilize one form over the other. By using such mesophases for in meso crystallogenesis, the expectation was that at least one would generate crystals of gramicidin in the HHSH form for structure determination by MX. This was tested using commercial and in-house synthesized lipids that support in meso crystallogenesis. Lipid acyl chain lengths were varied from 14 to 18 carbons to provide mesophases with a range of bilayer thicknesses. Unexpectedly, all lipids produced high-quality, structure-grade crystals with gramicidin only in the DSDH conformation.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Modelling single atom catalysts for water splitting and fuel cells: A tutorial review

Here, in this tutorial review, we report the state-of-the-art of the modeling approaches of Single Atom Catalysts (SAC) for water splitting and fuel cells reactions. The discussion applies for Hydrogen Evolution Reaction (HER), Oxygen Reduction Reaction (OER), Hydrogen Oxidation Reaction (HOR), and Oxygen Reduction Reaction (ORR). The main scope of this work is to underline the relevant aspects of SACs modelling. On the one hand, the review could help computational chemists aiming to start the study of SACs. On the other hand, experimentalists could find the critical analysis of DFT results of interest to understand better the strengths and weaknesses of simulations, and how to interpret computational results. After an introductory section of SACs, we start by briefly presenting the state-of-the-art methodologies. Then, we analyze the critical aspects for a reliable prediction of the electronic properties, and we discuss the robustness of the structural models and ways to validate them. Furthermore, we discuss the main approaches to predict catalytic activity and selectivity, which is the final goal of the computational catalysis. We conclude this review with a critical analysis of the current challenges in the field, and the main limitations of the modeling approaches that are described.

25 ENERGY STORAGE↗

DOE OSTI2014

Computer code for double beta decay QRPA based calculations

The computer code developed by our group some years ago for the evaluation of nuclear matrix elements, within the QRPA and PQRPA nuclear structure models, involved in neutrino-nucleus reactions, muon capture and β{sup ±} processes, is extended to include also the nuclear double beta decay.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

Detection of significant antiviral drug effects on COVID-19 with reasonable sample sizes in randomized controlled trials: A modeling study

Development of an effective antiviral drug for Coronavirus Disease 2019 (COVID-19) is a global health priority. Although several candidate drugs have been identified through in vitro and in vivo models, consistent and compelling evidence from clinical studies is limited. The lack of evidence from clinical trials may stem in part from the imperfect design of the trials. We investigated how clinical trials for antivirals need to be designed, especially focusing on the sample size in randomized controlled trials. A modeling study was conducted to help understand the reasons behind inconsistent clinical trial findings and to design better clinical trials. We first analyzed longitudinal viral load data for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) without antiviral treatment by use of a within-host virus dynamics model. The fitted viral load was categorized into 3 different groups by a clustering approach. Comparison of the estimated parameters showed that the 3 distinct groups were characterized by different virus decay rates (p-value < 0.001). The mean decay rates were 1.17 d -1 (95% CI: 1.06 to 1.27 d -1 ), 0.777 d -1 (0.716 to 0.838 d -1 ), and 0.450 d -1 (0.378 to 0.522 d -1 ) for the 3 groups, respectively. Such heterogeneity in virus dynamics could be a confounding variable if it is associated with treatment allocation in compassionate use programs (i.e., observational studies). Subsequently, we mimicked randomized controlled trials of antivirals by simulation. An antiviral effect causing a 95% to 99% reduction in viral replication was added to the model. To be realistic, we assumed that randomization and treatment are initiated with some time lag after symptom onset. Using the duration of virus shedding as an outcome, the sample size to detect a statistically significant mean difference between the treatment and placebo groups (1:1 allocation) was 13,603 and 11,670 (when the antiviral effect was 95% and 99%, respectively) per group if all patients are enrolled regardless of timing of randomization. The sample size was reduced to 584 and 458 (when the antiviral effect was 95% and 99%, respectively) if only patients who are treated within 1 day of symptom onset are enrolled. We confirmed the sample size was similarly reduced when using cumulative viral load in log scale as an outcome. We used a conventional virus dynamics model, which may not fully reflect the detailed mechanisms of viral dynamics of SARS-CoV-2. The model needs to be calibrated in terms of both parameter settings and model structure, which would yield more reliable sample size calculation. In this study, we found that estimated association in observational studies can be biased due to large heterogeneity in viral dynamics among infected individuals, and statistically significant effect in randomized controlled trials may be difficult to be detected due to small sample size. The sample size can be dramatically reduced by recruiting patients immediately after developing symptoms. We believe this is the first study investigated the study design of clinical trials for antiviral treatment using the viral dynamics model.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2018

Friction Stir Scribe Joining of Carbon Fiber Reinforced Polymer (CFRP) to Aluminum

The purpose of this project was to develop the critical process technology, models, and tools necessary to advance the Friction Stir Scribe, FSS, joining method through experimentation, validation at the laboratory scale, and integration into a production-like robotic environment. Implementation of FSS technology for joining polymer composites to metals will enable greater use of lightweight materials by providing technology capable of joining linear configurations without the use of adhesives or other third-body fasteners by creating an in-situ joint from the parent materials. As FSS technology provides the capability to join multi-material structures on robotic platforms using linear configurations, the development of this technology for use on the BIW will impact a great diversity of CFRP joints within the vehicle; thus, allowing a greater reduction in vehicle mass through more specifically designed structures. The FSS process has been developed to include integration of the FSS tool with a stationary shoulder, which has been shown to be required to achieve the desired surface quality (i.e., crown flash level). However, the targeted joint strength has not been achieved because the resulting stirred CFRP microstructure does not provide similar performance as the as-molded composite leading to low fracture strengths despite our efforts investigating various unique alternative approaches. In support of the experimental work, a process-structure model was developed and validated for the FSS joining (FSSJ) process using surrogate materials (steel and Al). The cyclic corrosion testing of the FSS joints and self-piercing riveted (SPR) joints revealed different modes of galvanic corrosion in the two types of joints. The SPR samples exhibited a greater amount of corrosion on the external surfaces. The presence of steel rivets in these joints exacerbated the situation, with the rivets getting preferentially corroded. The FSSJ samples despite exhibiting less surface corrosion, exhibited severe corrosion under the joint overlap area.

36 MATERIALS SCIENCE↗

DOE OSTI2016

Illuminating structural proteins in viral "dark matter" with metaproteomics

Viruses are ecologically important, yet environmental virology is limited by dominance of unannotated genomic sequences representing taxonomic and functional "viral dark matter." Although recent analytical advances are rapidly improving taxonomic annotations, identifying functional darkmatter remains problematic. Here, we apply paired metaproteomics and dsDNA-targeted metagenomics to identify 1,875 virion-associated proteins from the ocean. Over one-half of these proteins were newly functionally annotated and represent abundant and widespread viral metagenome-derived protein clusters (PCs). One primarily unannotated PC dominated the dataset, but structural modeling and genomic context identified this PC as a previously unidentified capsid protein from multiple uncultivated tailed virus families. Furthermore, four of the five most abundant PCs in the metaproteome represent capsid proteins containing the HK97-like protein fold previously found in many viruses that infect all three domains of life. The dominance of these proteins within our dataset, as well as their global distribution throughout the world's oceans and seas, supports prior hypotheses that this HK97-like protein fold is the most abundant biological structure on Earth. Altogether, these culture-independent analyses improve virion-associated protein annotations, facilitate the investigation of proteins within natural viral communities, and offer a high-throughput means of illuminating functional viral dark matter.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2011

DEEP MIXING IN EVOLVED STARS. II. INTERPRETING Li ABUNDANCES IN RED GIANT BRANCH AND ASYMPTOTIC GIANT BRANCH STARS

We reanalyze the problem of Li abundances in red giants of nearly solar metallicity. After outlining the problems affecting our knowledge of the Li content in low-mass stars (M {<=} 3 M{sub sun}), we discuss deep-mixing models for the red giant branch stages suitable to account for the observed trends and for the correlated variations of the carbon isotope ratio; we find that Li destruction in these phases is limited to masses below about 2.3 M{sub sun}. Subsequently, we concentrate on the final stages of evolution for both O-rich and C-rich asymptotic giant branch (AGB) stars. Here, the constraints on extra-mixing phenomena previously derived from heavier nuclei (from C to Al), coupled to recent updates in stellar structure models (including both the input physics and the set of reaction rates used), are suitable to account for the observations of Li abundances below A(Li) {identical_to} log {epsilon}(Li) {approx_equal} 1.5 (and sometimes more). Also, their relations with other nucleosynthesis signatures of AGB phases (like the abundance of F, and the C/O and {sup 12}C/{sup 13}C ratios) can be explained. This requires generally moderate efficiencies (M-dot < or approx. 0.3-0.5 x 10{sup -6} M{sub sun} yr{sup -1}) for non-convective mass transport. At such rates, slow extra mixing does not remarkably modify Li abundances in early AGB phases; on the other hand, faster mixing encounters a physical limit in destroying Li, set by the mixing velocity. Beyond this limit, Li starts to be produced; therefore, its destruction on the AGB is modest. Li is then significantly produced by the third dredge up. We also show that effective circulation episodes, while not destroying Li, would easily bring the {sup 12}C/{sup 13}C ratios to equilibrium, contrary to the evidence in most AGB stars, and would burn F beyond the limits shown by C(N) giants. Hence, we do not confirm the common idea that efficient extra mixing drastically reduces the Li content of C stars with respect to K-M giants. This misleading appearance is induced by biases in the data, namely: (1) the difficulty of measuring very low Li abundances in O-rich AGB stars due to the presence of TiO bands and (2) the fact that many, relatively massive (M > 3 M{sub sun}) K- and M-type giants may remain Li-rich, not evolving to the C-rich stages. Efficient extra mixing on the AGB is instead typical of very low masses (M {approx}< 1.5 M{sub sun}). It also characterizes CJ stars, where it produces Li and reduces F and the carbon isotope ratio, as observed in these peculiar objects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2017

Spatial representation of organic carbon and active-layer thickness of high latitude soils in CMIP5 earth system models

Soil properties such as soil organic carbon (SOC) stocks and active-layer thickness are used in earth system models (F.SMs) to predict anthropogenic and climatic impacts on soil carbon dynamics, future changes in atmospheric greenhouse gas concentrations, and associated climate changes in the permafrost regions. Accurate representation of spatial and vertical distribution of these soil properties in ESMs is a prerequisite for redudng existing uncertainty in predicting carbon-climate feedbacks. We compared the spatial representation of SOC stocks and active-layer thicknesses predicted by the coupled Modellntercomparison Project Phase 5 { CMIP5) ESMs with those predicted from geospatial predictions, based on observation data for the state of Alaska, USA. For the geospatial modeling. we used soil profile observations {585 for SOC stocks and 153 for active-layer thickness) and environmental variables (climate, topography, land cover, and surficial geology types) and generated fine-resolution (50-m spatial resolution) predictions of SOC stocks (to 1-m depth) and active-layer thickness across Alaska. We found large inter-quartile range (2.5-5.5 m) in predicted active-layer thickness of CMIP5 modeled results and small inter-quartile range (11.5-22 kg m-2) in predicted SOC stocks. The spatial coefficient of variability of active-layer thickness and SOC stocks were lower in CMIP5 predictions compared to our geospatial estimates when gridded at similar spatial resolutions (24.7 compared to 30% and 29 compared to 38%, respectively). However, prediction errors. when calculated for independent validation sites, were several times larger in ESM predictions compared to geospatial predictions. Primaly factors leading to observed differences were ( 1) lack of spatial heterogeneity in ESM predictions, (2) differences in assumptions concerning environmental controls, and (3) the absence of pedogenic processes in ESM model structures. Our results suggest that efforts to incorporate these factors in F.SMs should reduce current uncertainties associated with ESM predictions of carbon-climate feedbacks.

Active-layer thickness↗

DOE OSTI2023

Integrating Reservoirs into the Dissolved Organic Matter Versus Primary Production Paradigm: How Does Chlorophyll-$a$ Change Across Dissolved Organic Carbon Concentrations in Reservoirs?

Primary production in freshwater ecosystems is largely a function of light and nutrient availability, both of which have been changing in many lakes and reservoirs in response to anthropogenic pressures. Recent studies focusing on natural lakes have found a hump-shaped response of primary production (sometimes measured as chlorophyll-$a$) to dissolved organic matter (DOM, measured as dissolved organic carbon, DOC), which has both light-absorbing chromophoric properties and DOM-bound nutrients. We used the United States National Lakes Assessment dataset to integrate reservoirs into this paradigm in comparison with natural lakes and assessed the relative differences in the predicted response’s model structure, regression parameter values, and drivers of the chlorophyll-$a$ residuals. We found that chlorophyll-$a$ in reservoirs exhibited a hump-shaped response to DOC, while natural lakes from this dataset were better fit with a linear response, differing from previous studies focused on boreal lakes. Despite this, reservoirs had a greater maximum chlorophyll-a response compared to natural lakes in this study (45.5 versus 33.8 μg L -1 ), which occurred at a lower DOC concentration threshold (18.3 versus 26.4 mg L -1 ) when compared using quadratic models. Reservoirs had lower median light:nutrient values compared to natural lakes, and greater median surface area and total phosphorus (TP), that can all influence the light environment and the peak chlorophyll-a responses. In both reservoirs and natural lakes, chlorophyll-$a$ residuals were most strongly influenced by TP, where TP < 25-30 µg L -1 suppressed chlorophyll-a residuals and higher TP amplified them. Light:nutrient values were somewhat important predictors, and patterns with chlorophyll-$a$ residuals supported previous work showing low light:nutrient values amplified chlorophyll-$a$ responses and higher values suppressed them. In conclusion, quantifying the shape of the response of primary production to DOM quantity and quality as well as the drivers of the residuals, namely TP for lakes and reservoirs in this dataset, will be important for understanding the effects that changes in water quality may have on primary production and freshwater ecosystem processes.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

Computational Tools and Techniques for Modeling of Heterogeneous Materials

The specific goal of this CRADA was the development of computational tools and techniques for meso-to-macroscale modeling of transport processes to predict bulk properties of particulate and composite-based heterogeneous materials. These computational tools are particularly useful in exploring the relationship between a product's constituent materials, manufacturing process, resulting microstructure and bulk properties. The specific results of this project are: (i) advancements to the granular package and rigid body capability of the particle dynamics software, LAMMPS, for simulating fine cohesive particles and non-spherical granular particles; (ii) a software tool kit, documentation, and tutorials for statistical characterization, artificial reconstruction, and property-structure model analysis of material microstructure.

Lechman, Jeremy↗

DOE OSTI2016

Room-temperature fabrication of light-emitting thin films based on amorphous oxide semiconductor

We propose a light-emitting thin film using an amorphous oxide semiconductor (AOS) because AOS has low defect density even fabricated at room temperature. Eu-doped amorphous In-Ga-Zn-O thin films fabricated at room temperature emitted intense red emission at 614 nm. It is achieved by precise control of oxygen pressure so as to suppress oxygen-deficiency/excess-related defects and free carriers. An electronic structure model is proposed, suggesting that non-radiative process is enhanced mainly by defects near the excited states. AOS would be a promising host for a thin film phosphor applicable to flexible displays as well as to light-emitting transistors.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Integration of theory and experiment in the modelling of heterogeneous electrocatalysis.

Theoretical modelling is essential to deepen our understanding of heterogeneous electrocatalytic energy conversion processes, such as water splitting. Here, Sharon Hammes-Schiffer and Giulia Galli offer their perspectives on the best strategies for successfully studying such systems. Heterogeneous electrocatalysis is critical to many energy conversion processes. Theoretical and computational approaches are essential to interpret experimental data and provide the mechanistic understanding necessary to design more effective catalysts. However, automated general procedures to build predictive theoretical and computational frameworks are not readily available; specific choices must be made in terms of the atomistic structural model and the level of theory, as well as the experimental data used to inform and validate these choices. Here we outline some best practices for modelling heterogeneous systems and present examples in the context of catalysis at metal electrodes and oxides. The level of theory should be chosen for the specific system and properties of interest, and experimental validation is essential from the beginning to the end of the study. Continuous feedback and ultimate integration between experiment and theory enhances the power of calculations to elucidate mechanisms, identify effective descriptors and clarify design principles.

Hammes-Schiffer, Sharon↗

DOE OSTI2020

Kβ X-ray Emission Spectroscopy as a Probe of Cu(I) Sites: Application to the Cu(I) Site in Preprocessed Galactose Oxidase

Cu(I) active sites in metalloproteins are involved in O 2 activation, but their O 2 reactivity is difficult to study due to the Cu(I) d 10 closed shell which precludes the use of conventional spectroscopic methods. Kβ X-ray emission spectroscopy (XES) is a promising technique for investigating Cu(I) sites as it detects photons emitted by electronic transitions from occupied orbitals. Here, we demonstrate the utility of Kβ XES in probing Cu(I) sites in model complexes and a metalloprotein. Using Cu(I)Cl, emission features from double-ionization (DI) states are identified using varying incident X-ray photon energies, and a reasonable method to correct the data to remove DI contributions is presented. Kβ XES spectra of Cu(I) model complexes, having biologically relevant N/S ligands and different coordination numbers, are compared and analyzed, with the aid of density functional theory (DFT) calculations, to evaluate the sensitivity of the spectral features to the ligand environment. While the low-energy Kβ 2,5 emission feature reflects the ionization energy of ligand np valence orbitals, the high-energy Kβ 2,5 emission feature corresponds to transitions from molecular orbitals (MOs) having mainly Cu 3d character with the intensities determined by ligand-mediated d–p mixing. A Kβ XES spectrum of the Cu(I) site in preprocessed galactose oxidase (GO pre ) supports the 1Tyr/2His structural model that was determined by our previous X-ray absorption spectroscopy and DFT study. Finally, the high-energy Kβ 2,5 emission feature in the Cu(I)-GO pre data has information about the MO containing mostly Cu 3d x 2 –y 2 character that is the frontier molecular orbital (FMO) for O 2 activation, which shows the potential of Kβ XES in probing the Cu(I) FMO associated with small-molecule activation in metalloproteins.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Subseasonal Tropical Convection Characteristics in the Energy Exascale Earth System Model Version 2

Accurate simulation of subseasonal tropical moist convection remains a key challenge for Earth system models. The difficulties stem from the reliance of cumulus cloud processes on model parameterizations and the need to represent the multiscale nature of interactions among clouds, radiation, moisture, circulation, and surface energy fluxes. Equatorial convection drives circulation anomalies that can affect weather patterns and extremes globally, motivating efforts to better understand and simulate these tropical disturbances. Here, a detailed review of subseasonal tropical convective behavior as simulated in the Energy Exascale Earth System Model version 2 (E3SMv2) is presented, with comparison to its predecessor version 1 (E3SMv1) and reference data sets. Model structural changes to the deep convective trigger function and surface fluxes, along with parametric tuning of the cloud and microphysics schemes, together result in an improved depiction of organized tropical convection across scales. In particular, E3SMv2 exhibits a more realistic Madden‐Julian oscillation (MJO) and low‐frequency Kelvin waves—owing to a sharper time mean equatorial meridional moisture gradient and improved convection‐circulation coupling —as well as a better depiction of MJO Northern Hemisphere teleconnections. Despite these improvements, subseasonal precipitation variance continues to be strongly underestimated in E3SMv2. Use of a cloud plume model also reveals that the coupling between daily averaged tropical precipitation and lower tropospheric instability in E3SM is inconsistent with observations, a bias that could potentially impact the simulation of intraseasonal disturbances.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Parametric Sensitivity and Uncertainty Quantification in the Version 1 of E3SM Atmosphere Model Based on Short Perturbed Parameter Ensemble Simulations

Abstract The atmospheric component of Energy Exascale Earth System Model version 1 has included many new features in the physics parameterizations compared to its predecessors. Potential complex nonlinear interactions among the new features create a significant challenge for understanding the model behaviors and parameter tuning. Using the one‐at‐a‐time method, the benefit of tuning one parameter may offset the benefit of tuning another parameter, or improvement in one target variable may lead to degradation in another target variable. To better understand the Energy Exascale Earth System Model version 1 model behaviors and physics, we conducted a large number of short simulations (three days) in which 18 parameters carefully selected from parameterizations of deep convection, shallow convection, and cloud macrophysics and microphysics were perturbed simultaneously using the Latin hypercube sampling method. From the perturbed parameter ensemble simulations and use of different skill score functions, we identified the most sensitive parameters, quantified how the model responds to changes of the parameters for both global mean and spatial distribution, and estimated the maximum likelihood of model parameter space for a number of important fidelity metrics. Comparison of the parametric sensitivity using simulations of two different lengths suggests that perturbed parameter ensemble using short simulations has some bearing on understanding parametric sensitivity of longer simulations. Results from this analysis provide a more comprehensive picture of the Energy Exascale Earth System Model version 1 behavior. The difficulty in reducing biases in multiple variables simultaneously highlights the need of characterizing model structural uncertainty (so‐called embedded errors) to inform future development efforts.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

An improved geodetic source model for the 1999 M W 6.3 Chamoli earthquake, India

Here, we introduce a distributed slip model for the 1999 M W 6.3 Chamoli earthquake of north India using interferometric synthetic aperture radar (InSAR) data from both ascending and descending orbits and Bayesian estimation of confidence levels and trade-offs of the model geometry parameters. The results of fault-slip inversion in an elastic half-space show that the earthquake ruptured a |$9 _{ - 2.2}^{\circ + 3.4}$| northeast-dipping plane with a maximum slip of ~1 m. The fault plane is located at a depth of ~|$15.9_{ - 3.0}^{ + 1.1}$| and is ~120 km north of the Main Frontal Thrust, implying that the rupture plane was on the northernmost detachment near the mid-crustal ramp of the Main Himalayan Thrust. The InSAR-determined moment is 3.35 × 10 18 Nm with a shear modulus of 30 GPa, equivalent to M W 6.3, which is smaller than the seismic moment estimates of M W 6.4-6.6. Possible reasons for this discrepancy include the trade-off between moment and depth, uncertainties in seismic moment tensor components for shallow dip-slip earthquakes and the role of earth structure models in the inversions. The released seismic energy from recent earthquakes in the Garhwal region is far less than the accumulated strain energy since the 1803 M S 7.5 earthquake, indicating substantial hazard of future great earthquakes.

58 GEOSCIENCES↗