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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

A quick guide for student-driven community genome annotation

High quality gene models are necessary to expand the molecular and genetic tools available for a target organism, but these are available for only a handful of model organisms that have undergone extensive curation and experimental validation over the course of many years. The majority of gene models present in biological databases today have been identified in draft genome assemblies using automated annotation pipelines that are frequently based on orthologs from distantly related model organisms and usually have minor or major errors. Manual curation is time consuming and often requires substantial expertise, but is instrumental in improving gene model structure and identification. Manual annotation may seem to be a daunting and cost-prohibitive task for small research communities but involving undergraduates in community genome annotation consortiums can be mutually beneficial for both education and improved genomic resources. We outline a workflow for efficient manual annotation driven by a team of primarily undergraduate annotators. This model can be scaled to large teams and includes quality control processes through incremental evaluation. Moreover, it gives students an opportunity to increase their understanding of genome biology and to participate in scientific research in collaboration with peers and senior researchers at multiple institutions.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1992

What can we learn about impact mechanics from large craters on Venus?

More than 50 unequivocal peak-ring craters and multiringed impact basins have been identified on Venus from Earth-based Arecibo, Venera 15/16, and Magellan radar images. These ringed craters are relatively pristine, and so serve as an important new dataset that will further understanding of the structural and rheological properties of the venusian surface and of impact mechanics in general. They are also the most direct analogues for craters formed on the Earth in Phanerozoic time. Finite-element simulations of basin collapse and ring formation were undertaken in collaboration with V. J. Hillgren (University of Arizona). These calculations used an axisymmetric version of the viscoelastic finite element code TECTON, modeled structures on the scale of Klenova or Meitner, and demonstrated two major points. First, viscous flow and ring formation are possible on the timescale of crater collapse for the sizes of multiringed basins seen on Venus and heat flows appropriate to the plant. Second, an elastic lithosphere overlying a Newtonian viscous asthenosphere results mainly in uplift beneath the crater. Inward asthenospheric flow mainly occurs at deeper levels. Lithospheric response is dominantly vertical and flexural. Tensional stress maxima occur and ring formation by normal faulting is predicted in some cases, but these predicted rings occur too far out to explain observed ring spacings on Venus (or on the Moon). Overall, these estimates and models suggest that multiringed basin formation is indeed possible at the scales observed on Venus. Furthermore, due to the strong inverse dependence of solid-state viscosity on stress, the absence of Cordilleran-style ring faulting in craters smaller than Meitner or Klenova makes sense. The apparent increase in viscosity of shock-fluidized rock with crater diameter, greater interior temperatures accessed by larger, deeper craters, and decreased non-Newtonian viscosity associated with larger craters may conspire to make the transition with diameter from peak-ring crater to Orientale-type multiringed basin rather abrupt.

Mckinnon, William B.↗
DOE OSTI2020

Linear two-pool models are insufficient to infer soil organic matter decomposition temperature sensitivity from incubations

Abstract Terrestrial carbon (C)-climate feedbacks depend strongly on how soil organic matter (SOM) decomposition responds to temperature. This dependency is often represented in land models by the parameter Q 10 , which quantifies the relative increase of microbial soil respiration per 10 °C temperature increase. Many studies have conducted paired laboratory soil incubations and inferred “active” and “slow” pool Q 10 values by fitting linear two-pool models to measured respiration time series. Using a recently published incubation study (Qin et al. in Sci Adv 5(7):eaau1218, 2019) as an example, here we first show that the very high parametric equifinality of the linear two-pool models may render such incubation-based Q 10 estimates unreliable. In particular, we show that, accompanied by the uncertain initial active pool size, the slow pool Q 10 can span a very wide range, including values as high as 100, although all parameter combinations are producing almost equally good model fit with respect to the observations. This result is robust whether or not interactions between the active and slow pools are considered (typically these interactions are not considered when interpreting incubation data, but are part of the predictive soil carbon models). This very large parametric equifinality in the context of interpreting incubation data is consistent with the poor temporal extrapolation capability of linear multi-pool models identified in recent studies. Next, using a microbe-explicit SOM model (RESOM), we show that the inferred two pools and their associated parameters (e.g., Q 10 ) could be artificial constructs and are therefore unreliable concepts for integration into predictive models. We finally discuss uncertainties in applying linear two-pool (or more generally multiple-pool) models to estimate SOM decomposition parameters such as temperature sensitivities from laboratory incubations. We also propose new observations and model structures that could enable better process understanding and more robust predictive capabilities of soil carbon dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Structures of the ApoL1 and ApoL2 N-terminal domains reveal a non-classical four-helix bundle motif

Apolipoprotein L1 (ApoL1) is a circulating innate immunity protein protecting against trypanosome infection. However, two ApoL1 coding variants are associated with a highly increased risk of chronic kidney disease. Here we present X-ray and NMR structures of the N-terminal domain (NTD) of ApoL1 and of its closest relative ApoL2. In both proteins, four of the five NTD helices form a four-helix core structure which is different from the classical four-helix bundle and from the pore-forming domain of colicin A. The reactivity with a conformation-specific antibody and structural models predict that this four-helix motif is also present in the NTDs of ApoL3 and ApoL4, suggesting related functions within the small ApoL family. The long helix 5 of ApoL1 is conformationally flexible and contains the BH3-like region. This BH3-like α-helix resembles true BH3 domains only in sequence and structure but not in function, since it does not bind to the pro-survival members of the Bcl-2 family, suggesting a Bcl-2-independent role in cytotoxicity. These findings should expedite a more comprehensive structural and functional understanding of the ApoL immune protein family.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1992

System/observer/controller identification toolbox

System Identification is the process of constructing a mathematical model from input and output data for a system under testing, and characterizing the system uncertainties and measurement noises. The mathematical model structure can take various forms depending upon the intended use. The SYSTEM/OBSERVER/CONTROLLER IDENTIFICATION TOOLBOX (SOCIT) is a collection of functions, written in MATLAB language and expressed in M-files, that implements a variety of modern system identification techniques. For an open loop system, the central features of the SOCIT are functions for identification of a system model and its corresponding forward and backward observers directly from input and output data. The system and observers are represented by a discrete model. The identified model and observers may be used for controller design of linear systems as well as identification of modal parameters such as dampings, frequencies, and mode shapes. For a closed-loop system, an observer and its corresponding controller gain directly from input and output data.

Juang, Jer-Nan↗
DOE OSTI2020

Benchmarking and parameter sensitivity of physiological and vegetation dynamics using the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) at Barro Colorado Island, Panama

Plant functional traits determine vegetation responses to environmental variation, but variation in trait values is large, even within a single site. Likewise, uncertainty in how these traits map to Earth system feedbacks is large. We use a vegetation demographic model (VDM), the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), to explore parameter sensitivity of model predictions, and comparison to observations, at a tropical forest site: Barro Colorado Island in Panama. We define a single 12-dimensional distribution of plant trait variation, derived primarily from observations in Panama, and define plant functional types (PFTs) as random draws from this distribution. We compare several model ensembles, where individual ensemble members vary only in the plant traits that define PFTs, and separate ensembles differ from each other based on either model structural assumptions or non-trait, ecosystem-level parameters, which include (a) the number of competing PFTs present in any simulation and (b) parameters that govern disturbance and height-based light competition. While single-PFT simulations are roughly consistent with observations of productivity at Barro Colorado Island, increasing the number of competing PFTs strongly shifts model predictions towards higher productivity and biomass forests. Different ecosystem variables show greater sensitivity than others to the number of competing PFTs, with the predictions that are most dominated by large trees, such as biomass, being the most sensitive. Changing disturbance and height-sorting parameters, i.e., the rules of competitive trait filtering, shifts regimes of dominance or coexistence between early- and late-successional PFTs in the model. Increases to the extent or severity of disturbance, or to the degree of determinism in height-based light competition, all act to shift the community towards early-successional PFTs. In turn, these shifts in competitive outcomes alter predictions of ecosystem states and fluxes, with more early-successional-dominated forests having lower biomass. It is thus crucial to differentiate between plant traits, which are under competitive pressure in VDMs, from those model parameters that are not and to better understand the relationships between these two types of model parameters to quantify sources of uncertainty in VDMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

X-ray atomic mapping of quantum dots

We report a model-independent atomic-mapping technique for quantum dots (QDs) by combining Bragg reflection x-ray standing wave (XSW) and grazing incidence diffraction (GID) measurements. In this study, we choose GaAs capped InGaAs QDs/GaAs(001) as a model system to show the locations and arrangements of indium atoms within the QDs along various [hkl] directions. This technique directly reveals the actual amount of positional anisotropy and ordering fraction of indium atoms within the QDs by probing the (1¯11), (111), (311), (1¯31), (113), and (1¯13) crystallographic planes. We find that indium atoms are outwardly shifted along the [001] direction by small fractions of the lattice constant, 0.04a GaAs and 0.06a GaAs from Ga sites for 50- and 150-Å GaAs capped InGaAs QDs, respectively. We observe that an improved coherency factor of the indium atoms within the QDs by 45–60% along the [001] and [011] directions reduces the photoluminescence linewidth by 22%, thus making the QDs efficient for QD-laser and optoelectronic device applications. Here, we also find that the position and ordering of In atoms along the (113) and (1¯13) planes are most sensitive to the thickness of the GaAs cap layer. Our XSW-based results are supported by numerical calculations using a QD-macroscopic structural model based on our GID study. We thus show that this atomic-mapping technique will be useful for studying various quantum structures and tuning their properties.

36 MATERIALS SCIENCE↗
NASA NTRS2018

Real-Time Adaptive Drag Minimization Wind Tunnel Investigation of a Flexible Wing with Variable Camber Continuous Trailing Edge Flap System

This paper reports the results of a recently completed real-time adaptive drag minimization wind tunnel investigation of a highly flexible wing wind tunnel model equipped with the Variable Camber Continuous Trailing Flap (VCCTEF) technology at the University of Washington Aeronautical Laboratory (UWAL). The wind tunnel investigation is funded by NASA SBIR Phase II contract with Scientific Systems Company, Inc. (SSCI) and University of Washington (UW) as a subcontractor. The wind tunnel model is a sub-scale Common Research Model (CRM) wing constructed of foam core and fiberglass skin and is aeroelastically scaled to achieve a wing tip deflection of 10% of the wing semi-span which represents a typical wing tip deflection for a modern transport such as Boeing 787. The jig-shape twist of the CRM wing is optimized using a CART3D aero-structural model to achieve the minimum induced drag for the design cruise lift coefficient of 0.5. The wing is equipped with two chord wise cambered segments for each of the six span wise flap sections for a total of 12 individual flap segments that comprise the VCCTEF system. Each of the 12 flap segments is actively controlled by an electric servo-actuator. The real-time adaptive drag optimization strategy includes an on-board aerodynamic model identification, a model excitation, and a real-time drag optimization. The on-board aerodynamic model is constructed parametrically as a function of the angle of attack and flap positions to model the lift and drag coefficients of the wing. The lift coefficient models include a linear model and a second-order model. The drag coefficient models include a quadratic model and a higher-order up to 6th-order model to accurately model the drag coefficient at high angles of attack. The onboard aerodynamic model identification includes a recursive least-squares (RLS) algorithm and a batch least-squares (BLS) algorithm designed to estimate the model parameters. The model excitation method is designed to sample the input set that comprises the angle of attack and the flap positions. Three model excitation methods are developed: random excitation method, sweep method, and iterative angle-of-attack seeking method. The real-time drag optimization includes a generic algorithm developed by SSCI and several optimization methods developed by NASA which include a second-order gradient Newton-Raphson optimization method, an iterative gradient optimization method, a pseudo-inverse optimization method, an analytical optimization method, and an iterative refinement optimization method. The first wind tunnel test entry took place in September 2017. This test revealed major hardware issues and required further redesign of the flap servo mechanisms. The second test entry took place in April 2018. However, the test was not successful due to the issues with the onboard aerodynamic model identification RLS algorithm which incorrectly identified model parameters. This test also provides an experimental comparison study between the VCCTEF and a variable camber discrete trailing edge flap (VCDTEF) without the elastomer transition mechanisms. The experimental result confirms the benefit of the VCCTEF which produces lower drag by 5% than the VCDTEF. The third and final test entry took place in June 2018 after the issues with the RLS algorithm have been identified and corrected. Additional improvements were implemented. These include the BLS algorithm, the iterative angle-of-attack seeking method, the iterative gradient optimization method, and the pseudo-inverse optimization method. The test objectives were successfully demonstrated as the real-time drag optimization identifies several optimal solutions at off-design lift coefficients. The iterative gradient optimization method is found to achieve up to 4.7% drag reduction for the off-design lift coefficient of 0.7. The pseudo-inverse optimization method which does not require the drag coefficient model is found to be quite effective in reducing drag. Up to 9.4% drag reduction for the off-design lift coefficient of 0.7 is achieved with the pseudo-inverse optimization method. The wind tunnel investigation demonstrates the potential of real-time drag optimization technology. Several new capabilities are developed that could enable future adaptive wing technologies for flexible wings equipped with drag control devices such as the VCCTEF.

Drag Optimization↗
DOE OSTI2024

Structured information extraction from scientific text with large language models

Extracting structured knowledge from scientific text remains a challenging task for machine learning models. Here, we present a simple approach to joint named entity recognition and relation extraction and demonstrate how pretrained large language models (GPT-3, Llama-2) can be fine-tuned to extract useful records of complex scientific knowledge. We test three representative tasks in materials chemistry: linking dopants and host materials, cataloging metal-organic frameworks, and general composition/phase/morphology/application information extraction. Records are extracted from single sentences or entire paragraphs, and the output can be returned as simple English sentences or a more structured format such as a list of JSON objects. This approach represents a simple, accessible, and highly flexible route to obtaining large databases of structured specialized scientific knowledge extracted from research papers.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2022

A Review of Bayesian Networks for Spatial Data

We report Bayesian networks are a popular class of multivariate probabilistic models as they allow for the translation of prior beliefs about conditional dependencies between variables to be easily encoded into their model structure. Due to their widespread usage, they are often applied to spatial data for inferring properties of the systems under study and also generating predictions for how these systems may behave in the future. We review published research on methodologies for representing spatial data with Bayesian networks and also summarize the application areas for which Bayesian networks are employed in the modeling of spatial data. We find that a wide variety of perspectives are taken, including a GIS-centric focus on efficiently generating geospatial predictions, a statistical focus on rigorously constructing graphical models controlling for spatial correlation, as well as a range of problem-specific heuristics for mitigating the effects of spatial correlation and dependency arising in spatial data analysis. Special attention is also paid to potential future directions for integration of Bayesian networks with spatial processes.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1998

Aerodynamic Parameters of High Performance Aircraft Estimated from Wind Tunnel and Flight Test Data

A concept of system identification applied to high performance aircraft is introduced followed by a discussion on the identification methodology. Special emphasis is given to model postulation using time invariant and time dependent aerodynamic parameters, model structure determination and parameter estimation using ordinary least squares an mixed estimation methods, At the same time problems of data collinearity detection and its assessment are discussed. These parts of methodology are demonstrated in examples using flight data of the X-29A and X-31A aircraft. In the third example wind tunnel oscillatory data of the F-16XL model are used. A strong dependence of these data on frequency led to the development of models with unsteady aerodynamic terms in the form of indicial functions. The paper is completed by concluding remarks.

Klein, Vladislav↗
NASA NTRS1999

Aerodynamic Parameters of High Performance Aircraft Estimated from Wind Tunnel and Flight Test Data

A concept of system identification applied to high performance aircraft is introduced followed by a discussion on the identification methodology. Special emphasis is given to model postulation using time invariant and time dependent aerodynamic parameters, model structure determination and parameter estimation using ordinary least squares and mixed estimation methods. At the same time problems of data collinearity detection and its assessment are discussed. These parts of methodology are demonstrated in examples using flight data of the X-29A and X-31A aircraft. In the third example wind tunnel oscillatory data of the F-16XL model are used. A strong dependence of these data on frequency led to the development of models with unsteady aerodynamic terms in the form of indicial functions. The paper is completed by concluding remarks.

Klein, Vladislav↗
NASA NTRS2015

Hypersonic Inflatable Aerodynamic Decelerator Ground Test Development

Hypersonic Inflatable Aerodynamic Decelerator (HIAD) technology readiness levels have been incrementally matured by NASA over the last thirteen years, with most recent support from NASA's Space Technology Mission Directorate (STMD) Game Changing Development Program (GCDP). Recently STMD GCDP has authorized funding and support through fiscal year 2015 (FY15) for continued HIAD ground developments which support a Mars Entry, Descent, and Landing (EDL) study. The Mars study will assess the viability of various EDL architectures to enable a Mars human architecture pathfinder mission planned for mid-2020. At its conclusion in November 2014, NASA's first HIAD ground development effort had demonstrated success with fabricating a 50 W/cm2 modular thermal protection system, a 400 C capable inflatable structure, a 10-meter scale aeroshell manufacturing capability, together with calibrated thermal and structural models. Despite the unquestionable success of the first HIAD ground development effort, it was recognized that additional investment was needed in order to realize the full potential of the HIAD technology capability to enable future flight opportunities. The second HIAD ground development effort will focus on extending performance capability in key technology areas that include thermal protection system, lifting-body structures, inflation systems, flight control, stage transitions, and 15-meter aeroshell scalability. This paper presents an overview of the accomplishments under the baseline HIAD development effort and current plans for a follow-on development effort focused on extending those critical technologies needed to enable a Mars Pathfinder mission.

Del Corso, Jospeh A.↗
NASA NTRS1983

Simplified analysis techniques to support the determination of Shuttle aerodynamics

The use of deterministic and regression methods to supplement the maximum likelihood estimation programs for the determination of the stability and control parameters of the Shuttle vehicle is discussed. Examples taken from STS-2 and STS-3 flight data show the use of deterministic methods to verify the effectiveness of the pitch and roll Reaction Control System (RCS), to verify the model structure used in the maximum likelihood estimator and to indicate regions of the descent trajectory where unmodeled moments dominate the vehicle motion and the application of maximum likelihood estimation would lead to incorrect parameter values. The use of regression methods to determine selected parameters when the more sophisticated maximum likelihood programs are not required, to determine the form of the vehicle mathematical model and to select the data time intervals for most effective parameter identification are also discussed.

Suit, W. T.↗
NASA NTRS2016

A Model-Model and Data-Model Comparison for the Early Eocene Hydrological Cycle

A range of proxy observations have recently provided constraints on how Earth's hydrological cycle responded to early Eocene climatic changes. However, comparisons of proxy data to general circulation model (GCM) simulated hydrology are limited and inter-model variability remains poorly characterised. In this work, we undertake an intercomparison of GCM-derived precipitation and P - E distributions within the extended EoMIP ensemble (Eocene Modelling Intercomparison Project; Lunt et al., 2012), which includes previously published early Eocene simulations performed using five GCMs differing in boundary conditions, model structure, and precipitation-relevant parameterisation schemes. We show that an intensified hydrological cycle, manifested in enhanced global precipitation and evaporation rates, is simulated for all Eocene simulations relative to the preindustrial conditions. This is primarily due to elevated atmospheric paleo-CO2, resulting in elevated temperatures, although the effects of differences in paleogeography and ice sheets are also important in some models. For a given CO2 level, globally averaged precipitation rates vary widely between models, largely arising from different simulated surface air temperatures. Models with a similar global sensitivity of precipitation rate to temperature (dP=dT ) display different regional precipitation responses for a given temperature change. Regions that are particularly sensitive to model choice include the South Pacific, tropical Africa, and the Peri-Tethys, which may represent targets for future proxy acquisition. A comparison of early and middle Eocene leaf-fossil-derived precipitation estimates with the GCM output illustrates that GCMs generally underestimate precipitation rates at high latitudes, although a possible seasonal bias of the proxies cannot be excluded. Models which warm these regions, either via elevated CO2 or by varying poorly constrained model parameter values, are most successful in simulating a match with geologic data. Further data from low-latitude regions and better constraints on early Eocene CO2 are now required to discriminate between these model simulations given the large error bars on paleoprecipitation estimates. Given the clear differences between simulated precipitation distributions within the ensemble, our results suggest that paleohydrological data offer an independent means by which to evaluate model skill for warm climates.

Boundary conditions↗
DOE OSTI2019

Computational Evidence for Kinetically Controlled Radical Coupling during Lignification

Lignin is an alkyl-aromatic biopolymer that, despite its abundance, is underutilized as a renewable feedstock because of its highly complex structure. A method to overcome this challenge that has gained prominence in recent years leverages the plasticity and malleability of lignin biosynthesis to tune lignin structure in planta through genetic approaches. An improved understanding of lignin biosynthesis can thus provide fundamental insights critical for the development of effective tailoring and valorization strategies. Although it is widely accepted that lignin monomers and growing chains are oxidized enzymatically into radicals that then undergo kinetically controlled coupling in planta, direct experimental evidence has been scarce because of the difficulty of exactly replicating in planta lignification conditions. Here, we computationally investigate a set of radical reactions representative of lignin biosynthesis. We demonstrate that, contrary to the notion that radical coupling reactions are usually barrierless and dynamically controlled, the computed activation energies can be qualitatively consistent with key structural observations made empirically for native lignin in a variety of biomass types. We also rationalize the origins of regioselectivity in coupling reactions through structural and activation strain analyses. Our findings lay the groundwork for first-principles lignin structural models and more detailed multiscale simulations of the lignification process.

09 BIOMASS FUELS↗
DOE OSTI2023

Involvement of the Streptococcus mutans PgfE and GalE 4-epimerases in protein glycosylation, carbon metabolism, and cell division

Streptococcus mutans is a key pathogen associated with dental caries and is often implicated in infective endocarditis. This organism forms robust biofilms on tooth surfaces and can use collagen-binding proteins (CBPs) to efficiently colonize collagenous substrates, including dentin and heart valves. One of the best characterized CBPs of S. mutans is Cnm, which contributes to adhesion and invasion of oral epithelial and heart endothelial cells. These virulence properties were subsequently linked to post-translational modification (PTM) of the Cnm threonine-rich repeat region by the Pgf glycosylation machinery, which consists of 4 enzymes: PgfS, PgfM1, PgfE, and PgfM2. Inactivation of the S. mutans pgf genes leads to decreased collagen binding, reduced invasion of human coronary artery endothelial cells, and attenuated virulence in the Galleria mellonella invertebrate model. The present study aimed to better understand Cnm glycosylation and characterize the predicted 4-epimerase, PgfE. Using a truncated Cnm variant containing only 2 threonine-rich repeats, mass spectrometric analysis revealed extensive glycosylation with HexNAc2. Compositional analysis, complemented with lectin blotting, identified the HexNAc2 moieties as GlcNAc and GalNAc. Comparison of PgfE with the other S. mutans 4-epimerase GalE through structural modeling, nuclear magnetic resonance, and capillary electrophoresis demonstrated that GalE is a UDP-Glc-4-epimerase, while PgfE is a GlcNAc-4-epimerase. While PgfE exclusively participates in protein O-glycosylation, we found that GalE affects galactose metabolism and cell division. Furthermore, this study further emphasizes the importance of O-linked protein glycosylation and carbohydrate metabolism in S. mutans and identifies the PTM modifications of the key CBP, Cnm.

4-epimerases↗
NASA NTRS1997

Hysteresis Modeling in Magnetostrictive Materials Via Preisach Operators

A phenomenological characterization of hysteresis in magnetostrictive materials is presented. Such hysteresis is due to both the driving magnetic fields and stress relations within the material and is significant throughout, most of the drive range of magnetostrictive transducers. An accurate characterization of the hysteresis and material nonlinearities is necessary, to fully utilize the actuator/sensor capabilities of the magnetostrictive materials. Such a characterization is made here in the context of generalized Preisach operators. This yields a framework amenable to proving the well-posedness of structural models that incorporate the magnetostrictive transducers. It also provides a natural setting in which to develop practical approximation techniques. An example illustrating this framework in the context of a Timoshenko beam model is presented.

Smith, R. C.↗