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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↗

NASA NTRS2010

Ares I-X Flight Evaluation Tasks in Support of Ares I Development

NASA s Constellation Program successfully launched the Ares I-X Flight Test Vehicle on October 28, 2009. The Ares I-X flight was a development flight test that offered a unique opportunity for early engineering data to impact the design and development of the Ares I crew launch vehicle. As the primary customer for flight data from the Ares I-X mission, the Ares Projects Office established a set of 33 flight evaluation tasks to correlate fight results with prospective design assumptions and models. Included within these tasks were direct comparisons of flight data with pre-flight predictions and post-flight assessments utilizing models and modeling techniques being applied to design and develop Ares I. A discussion of the similarities and differences in those comparisons and the need for discipline-level model updates based upon those comparisons form the substance of this paper. The benefits of development flight testing were made evident by implementing these tasks that used Ares I-X data to partially validate tools and methodologies in technical disciplines that will ultimately influence the design and development of Ares I and future launch vehicles. The areas in which partial validation from the flight test was most significant included flight control system algorithms to predict liftoff clearance, ascent, and stage separation; structural models from rollout to separation; thermal models that have been updated based on these data; pyroshock attenuation; and the ability to predict complex flow fields during time-varying conditions including plume interactions.

Huebner, Lawrence D.↗

NASA NTRS1985

Fine pointing of the Solar Optical Telescope in the Space Shuttle environment

Instruments requiring fine (i.e., sub-arcsecond) pointing, such as the Solar Optical Telescope (SOT), must be equipped with two-stage pointing devices, coarse and fine. Coarse pointing will be performed by a gimbal system, such as the Instrument Pointing System, while the image motion compensation (IMC) will provide fine pointing. This paper describes work performed on the SOT concept design that illustrates IMC as applied to SOT. The SOT control system was modeled in the frequency domain to evaluate performance, stability, and bandwidth requirements. The two requirements of the pointing control, i.e., the 2 arcsecond reproducibility and 0.03 arcsecond rms pointing jitter, can be satisfied by use of IMC at about 20 Hz bandwidth. The need for this high bandwidth is related to Shuttle-induced disturbances that arise primarily from man push-offs and vernier thruster firings. A block diagram of SOT model/stability analysis, schematic illustrations of the SOT pointing system, and a structural model summary are included.

Gowrinathan, S.↗

NASA NTRS1982

Post-Viking models for the structure of the summer atmosphere of Mars

A model for the Mars atmosphere up to 100 km altitude and between the 60 deg latitudes is presented. Seasonal variations are considered as induced by variations in surface temperature, using data supplied by the Viking lander and Mars 6 probe. The temperature profile is provided in 2 km intervals, noting a large temperature gradient in the first 2.5 km above the surface in wintertime. An average summer pressure is calculated at 7.3 mb with a variance of about 0.5. Viking spectrometer readings indicated a 0.995 mole fraction CO2 atmosphere with a mean molecular weight of 43.49. Gravitational acceleration is determined to vary from 3.73-3.19 m/sec sq in going from surface to 100 km, and atmospheric pressure is shown to vary by 5 orders of magnitude in the same interval. Finally, the thermal tides induced by the expansion and contraction cycle in the atmosphere near the surface are described.

Seiff, A.↗

NASA NTRS1990

A mathematical model of the structure and evolution of small-scale discrete auroral arcs

A three-dimensional fluid model for the structure and evolution of small-scale discrete auroral arcs originating from Alfven waves is developed and used to study the nonlinear macroscopic plasma dynamics of these auroral arcs. The results of simulations show that stationary auroral arcs can be unstable to a collisionless tearing mode which may be responsible for the observed transverse structuring in the form of folds and curls. At late times, the plasma becomes turbulent having transverse electric field power spectra that tend toward a universal k exp -5/3 spectral form.

Seyler, Charles E.↗

NASA NTRS1995

Micromechanical models for textile structural composites

The objective is to develop micromechanical models for predicting the stiffness and strength properties of textile composite materials. Two models are presented to predict the homogeneous elastic constants and coefficients of thermal expansion of a textile composite. The first model is based on rigorous finite element analysis of the textile composite unit-cell. Periodic boundary conditions are enforced between opposite faces of the unit-cell to simulate deformations accurately. The second model implements the selective averaging method (SAM), which is based on a judicious combination of stiffness and compliance averaging. For thin textile composites, both models can predict the plate stiffness coefficients and plate thermal coefficients. The finite element procedure is extended to compute the thermal residual microstresses, and to estimate the initial failure envelope for textile composites.

Marrey, Ramesh V.↗

NASA NTRSDate not supplied

Modeling Pore Closure in the Hot Isostatic Pressing of Additively Manufactured Inconel 718 Samples

Additive manufacturing provides opportunity for a new world of possibilities for metallic component design and fabrication; however, as-built part quality is notoriously variable, anisotropic, and degraded by porous defects. To improve quality, parts are commonly post processed using a variety of techniques including hot isostatic pressing (HIP). During HIP, high temperature and pressure is employed to improve microstructure and reduce pore volume by inducing visco-plastic deformation in the metallic substrate. Validated computational capabilities can provide predictions to guide the selection of processing condition, expected pore reduction, and the effects of varying entrapped gas in the pores. This discussion describes a micro-scale finite element structural model developed to predict pore closure due to HIP in as-built additively manufactured Inconel 718 samples produced by the laser powder bed fusion process. The model accounts for plastic deformation, creep, and internal pressure for a single pore. Pores are characterized in physical samples before and after HIP, and model predictions are compared to this measured data.

defect model prediction↗

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 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↗

NASA NTRS1987

Recent advances in structural dynamics of large space structures

Recent progress in the area of structural dynamics of large space structures is reviewed. Topics include system identification, large angle slewing of flexible structures, definition of scaling limitations in structural models, and recent results on a tension-stabilized antenna concept known as the hoop-column. Increasingly complex laboratory experiments guide most of the activities leading to realistic technological developments. Theoretical progress in system identification based on system realization theory resulting in unification of several methods is reviewed. Experimental results from implementation of a theoretical large-angle slewing control approach are shown. Status and results of the development of a research computer program for analysis of the transient dynamics of large angle motion of flexible structures are presented. Correlation of results from analysis and vibration tests of the hoop-column antenna concepts are summarized.

Pinson, Larry D.↗

NASA NTRS1987

Recent advances in structural dynamics of large space structures

Pinson, Larry D.↗

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↗

NASA NTRS1975

Shuttle wing panel stability analysis

The use of the NASTRAN program in the shuttle wing stability analysis is described, and details of the actual structure, the finite element idealization, and the NASTRAN results are given. A comparison of the NASTRAN results with those obtained with another computer program and with hand generated results indicates good agreement. An alternate approach for solving eigenvalue problems is illustrated and shows a considerable savings in computer time. Some emphasis is placed on the relationship of the NASTRAN analysis in the design process bringing out more clearly the contribution of the results and showing the importance of the mode plots. A deficiency in the NASTRAN plate elements when used to model structures made up of intersecting plates is discussed.

Balderes, T.↗

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↗

NASA NTRSDate not supplied

Improving the Representation of Land Surface Processes using the Data Assimilation Research Testbed (DART)

The land surface is a critical part of the earth system as processes related to water, carbon, energy and nitrogen cycling have important implications for climate forcing, air quality, water availability and seasonal atmospheric forecasting. Despite advances in land surface modeling, land surface model performance is often limited because of errors related to initial and boundary conditions, model structure, and parameters. Data assimilation (DA) techniques combined with an expanding network of earth system observations present an opportunity to reduce these errors and improve simulations. Here we apply an Ensemble Kalman Filter DA system as part of the Data Assimilation Research Testbed to a variety of land surface simulations. First, we describe the use of remotely sensed biomass observations to provide improved simulations of plant phenology, carbon and water cycling for regions highly sensitive to climate change (Western US, China, and Arctic). We discuss approaches to account for systemic biases between models and observations, including the use of spatially-varying adaptive ensemble inflation as an alternative approach to re-scaling soil moisture observations. Finally, we discuss a strategy to incorporate complementary observations (snow water equivalent, solar-induced fluorescence) to better constrain the representation of carbon and water cycling across complex terrain.

DART↗

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↗