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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Metal-silicate Partitioning and Its Role in Core Formation and Composition on Super-Earths

We use a thermodynamic framework for silicate-metal partitioning to determine the possible compositions of metallic cores on super-Earths. We compare results using literature values of the partition coefficients of Si and Ni, as well as new partition coefficients calculated using results from laser shock-induced melting of powdered metal-dunite targets at pressures up to 276 GPa, which approaches those found within the deep mantles of super-Earths. We find that larger planets may have little to no light elements in their cores because the Si partition coefficient decreases at high pressures. The planet mass at which this occurs will depend on the metal-silicate equilibration depth. We also extrapolate the equations of state (EOS) of FeO and FeSi alloys to high pressures, and present mass–radius diagrams using self-consistent planet compositions assuming equilibrated mantles and cores. We confirm the results of previous studies that the distribution of elements between mantle and core will not be detectable from mass and radius measurements alone. While observations may be insensitive to interior structure, further modeling is sensitive to compositionally dependent properties, such as mantle viscosity and core freeze-out properties. We therefore emphasize the need for additional high pressure measurements of partitioning as well as EOSs, and highlight the utility of the Sandia Z-facilities for this type of work.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1985

Selecting step sizes in sensitivity analysis by finite differences

This paper deals with methods for obtaining near-optimum step sizes for finite difference approximations to first derivatives with particular application to sensitivity analysis. A technique denoted the finite difference (FD) algorithm, previously described in the literature and applicable to one derivative at a time, is extended to the calculation of several simultaneously. Both the original and extended FD algorithms are applied to sensitivity analysis for a data-fitting problem in which derivatives of the coefficients of an interpolation polynomial are calculated with respect to uncertainties in the data. The methods are also applied to sensitivity analysis of the structural response of a finite-element-modeled swept wing. In a previous study, this sensitivity analysis of the swept wing required a time-consuming trial-and-error effort to obtain a suitable step size, but it proved to be a routine application for the extended FD algorithm herein.

Iott, J.↗
NASA NTRS1985

Autocorrelation of wind observations

Autocorrelation and variance statistics are calculated for cloud motion measurements from four different sources, rawinsonde wind reports, synoptic land station reports, ship reports, aircraft reports, automatic aircraft reports gathered during the Global Weather Experiment, and Seasat scatterometer winds from September 1978. The last of these data sources exhibited the highest autocorrelations and lowest standard deviations over short distances. Structure function plots of autocovariances against separation distance between observations indicated that Seasat was most sensitive to wind field structure by having low autovariance at short distances.

Wylie, D. P.↗
DOE OSTI2021

Protein conformational switch discerned via network centrality properties

Network analysis has emerged as a powerful tool for examining structural biology systems. The spatial organization of the components of a biomolecular structure has been rendered as a graph representation and analyses have been performed to deduce the biophysical and mechanistic properties of these components. For proteins, the analysis of protein structure networks (PSNs), especially via network centrality measurements and cluster coefficients, has led to identifying amino acid residues that play key functional roles and classifying amino acid residues in general. Whether these network properties examined in various studies are sensitive to subtle (yet biologically significant) conformational changes remained to be addressed. Here, we focused on four types of network centrality properties (betweenness, closeness, degree, and eigenvector centralities) for conformational changes upon ligand binding of a sensor protein (constitutive androstane receptor) and an allosteric enzyme (ribonucleotide reductase). We found that eigenvector centrality is sensitive and can distinguish salient structural features between protein conformational states while other centrality measures, especially closeness centrality, are less sensitive and rather generic with respect to the structural specificity. We also demonstrated that an ensembleinformed, modified PSN with static edges removed (which we term PSN*) has enhanced sensitivity at discerning structural changes.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2019

Improving Accuracy of Structural Dynamic Modification with Augmented Residual Vectors

It is often important to perform sensitivity analysis to determine how a structural model will be impacted by design changes. Often, the structural analysts will manually make changes to the finite element model (FEM) to determine the effects. But when dealing with a large FEM with millions of degrees of freedom these manual changes can be cumbersome and calculation of the effects can computationally expensive. Therefore, it is desirable to determine the effects of model changes through approximation methods. One common technique is to determine the analytical sensitivity of the FEM model with respect to the given change. These analytical sensitivities are valid when small changes are made to the structural model, but invalid if large changes need to be assessed. Another approach is to use Structural Dynamic Modification (SDM) to create a surrogate model to analyze model changes. SDM is a widely-used sensitivity method and is used in applications of model updating, uncertainty quantification, and model design studies. SMD is valid for moderate (10-20 percent) changes in the structural model, but model approximations are often needed for large parameter changes (greater than 20 percent). Structural Dynamic Modification can be improved by using residual vectors to augment the surrogate model formulation from SDM. Adding the residual modes increases the fidelity of the surrogate model while keeping the computational cost low. This paper discusses the application and limitations of the augmented residual modes method to two structures: the Integrated Spacecraft and Payload Element (ISPE) of the Space Launch System (SLS) and the full SLS as it is configured during its Integrated Modal Test (IMT).

Stewart, Eric C.↗
DOE OSTI2022

Electrospun porous La–Sr–Co–Ni–O nanofibers for highly sensitive non-enzymatic glucose detection

Glucose biosensors are widely used for clinical, industrial, and environmental applications. Nonenzymatic electrochemical glucose biosensors based on metal oxides with a perovskite structure have exhibited high sensitivity, excellent stability, and cost efficiency. In this work, porous La–Sr–Co–Ni–O (LSCNO) nanofibers, with an ABO 3 -type perovskite structure, were prepared through optimizing the A-site and B-site elements by electrospinning, followed with calcination at 700 °C for 5 h. Characterized by scanning and transmission electron microscopy, X-ray diffraction, and X-ray photoelectron spectroscopy, fabricated nanofibers were confirmed to be porous and nanosized polycrystalline grains with high crystallinity. A novel La 0.75 Sr 0.25 Co 0.5 Ni 0.5 O 3 -based nonenzymatic electrochemical biosensor was developed, which is sensitive to glucose because of an electrochemically catalytic mechanism, a mediated electron transfer involving Ni(II)/Ni(III) or Co(II)/Co(III), accompanying with gluconic acid complexation. The glucose biosensor presented a linear response in the range of 0.1–1.0 mM with a calibration sensitivity of 924 ± 28 μA mM –1 , a proportion of the variance of 0.9926, and a lower limit of detection of 0.083 mM, respectively, demonstrating an outstanding analytical performance. The biosensor showed no response to the most widely used anionic surfactant, sodium dodecyl sulfate, and low sensitivity to other biomolecules, such as fructose, lactose, galactose, mannose, dopamine, and ascorbic acid. A urine sample was tested by this novel nonenzymatic electrochemical biosensor by standard addition method, suggesting a potential application for clinical test.

36 MATERIALS SCIENCE↗
NASA NTRS2010

Buckling Imperfection Sensitivity of Axially Compressed Orthotropic Cylinders

Structural stability is a major consideration in the design of lightweight shell structures. However, the theoretical predictions of geometrically perfect structures often considerably over predict the buckling loads of inherently imperfect real structures. It is reasonably well understood how the shell geometry affects the imperfection sensitivity of axially compressed cylindrical shells; however, the effects of shell anisotropy on the imperfection sensitivity is less well understood. In the present paper, the development of an analytical model for assessing the imperfection sensitivity of axially compressed orthotropic cylinders is discussed. Results from the analytical model for four shell designs are compared with those from a general-purpose finite-element code, and good qualitative agreement is found. Reasons for discrepancies are discussed, and potential design implications of this line of research are discussed.

Schultz, Marc R.↗
NASA NTRS1993

Sensitivity analysis of Lyapunov and Riccati equations with application to controls-structures integrated design

Controls-structure integrated design is a complicated multidisciplinary design optimization problem which involves the state equations pertaining to open-loop eigenvalues and control laws. In order to alleviate the intensity of the computation, this study uses the adjoint variable method to derive sensitivity equations for the eigenvalue, Liapunov, and Riccati equations. These individual sensitivity equations are then combined together to form the multidisciplinary sensitivity equations for the control structure integrated design problems. A set of linear sensitivity equations, proportional in number to the number of performance functions involved in the optimization process, are solved. This proposed approach may provide a great saving in computer resources. The validity of the newly developed sensitivity equations is verified by numerical examples.

Hou, Gene↗
DOE OSTI2016

A structure of CdS/Cu{sub x}S quantum dots sensitized solar cells

This work introduces a type of CdS/Cu{sub x}S quantum dots (QDs) as sensitizers in quantum dot sensitized solar cells by in-situ cationic exchange reaction method where CdS photoanode is directly immersed in CuCl{sub 2} methanol solution to replace Cd{sup 2+} by Cu{sup 2+}. The p-type Cu{sub x}S layer on the surface of the CdS QDs can be considered as hole transport material, which not only enhances the light harvesting of photoanode but also boosts the charge separation after photo-excitation. Therefore, both the electron collection efficiency and power conversion efficiency of the solar cell are improved from 80% to 92% and from 1.21% to 2.78%, respectively.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1994

Correlations in cosmic density fields

A method is proposed to place constraints on the functional form of the high-order correlation functions zeta(sub n) that arise in cosmic density fields at large scales. This technique is based on a mass-in-cell statistic and a difference of mass in partitions of a cell. The relationship between these measures is sensitive to the formal structure of the zeta(sub n) as well as their amplitudes. This relationship is quantified in several theoretical models of structure, based on the hierarchical clustering paradigm. The results lead to a test for specific types of hierarchical clustering that is sensitive to correlations of all orders. The method is applied to examples of simulated large-scaled structure dominated by cold dark matter. In the preliminary study, the hierarchical paradigm appears to be a realistic approximation over a broad range of the scales. Furthermore, there is evidence that graphs of low-order vertices are dominant. On the basis of simulated data a phenomological model is specified that gives a good representation of clustering from linear scales to the strongly clustered regime (zeta(sub 2) approximately 500).

Bromley, B. C.↗
NASA NTRS1985

Interactive aircraft flight control and aeroelastic stabilization

An analytical model of a 3-D airfoil was used to study an optimization procedure formulated to enhance stability of an airfoil through integrated structural and control synthesis. This procedure is discussed together with preliminary results. These results show that a sensitivity derivative approach utilizing structural parameters, weighting matrix parameters and optimal control parameters (in this case, the design airspeed) is effective in determining the best structural/control design.

Weisshaar, T. A.↗
NASA NTRSDate not supplied

Simulation of Lift plus Cruise Vehicle Models to Define a Full-Scale Crash Test Campaign

A series of dynamic simulations were completed on the National Aeronautics and Space Administration(NASA) Lift plus Cruise (LPC) concept electric Vertical Take-off and Landing (eVTOL) vehicle in preparation for an anticipated future full-scale crash-test campaign. The crash test campaign is envisioned as a data gathering exercise with an intent generating full-scale test data to inform eVTOL crashworthiness regulations, evaluate the use of energy absorbing concepts within vehicle design, and validate finite element modeling techniques used in crashworthiness predictions. This report discusses the two main objectives for the simulation efforts: the development of a structural cabin section, and a series of analyses utilized to determine the sensitivities of impact variables. A structural cabin section was created based from previous research efforts involving the LPC vehicle utilized for occupant response. To refine for the structural modifications, the wing and tail sections of the vehicle were removed. The tail was replaced with a representative mass at the aft of the fuselage. The overhead wing was replaced with a beam structure sized to approximate the bending response of the wing under crash loading conditions. The beam structure was fixed to the fuselage similar to the original Wingbox design in order to properly capture effects of this overhead mass on survivable volume within the vehicle. The fidelity of the fuselage frame structure within the FEM was increased to quantify the effect of frame sizing on structural response. From this an eVTOL test article design was developed, which satisfied basic crashworthiness requirements, was reconfigurable to assess the effect of various design avenues on structural response and optimized to improve manufacturability. The impact variable sensitivity results primarily show the orientation of the impact vector played a major role in types of injuries sustained, along with their severity. The vehicle was largely insensitive to small variations in pitch attitude but highly sensitive to both impact surface at certain angles and landing gear location.

eVTOL↗
DOE OSTI2026

Contrasting Parametric Sensitivities in Two Global Vegetation Models Using Parameter Perturbation Ensembles

Uncertainty in land model projections remains high and the roles of parametric and structural uncertainty are difficult to disentangle. To compare parametric sensitivity across model structures we present two parameter perturbation ensembles using the Community Land Model (CLM) operating in satellite phenology mode. The ensembles contrast two vegetation modules: (a) the default CLM vegetation module and (b) the Functionally Assembled Terrestrial Ecosystem Simulator (CLM-FATES). We perturbed over 300 parameters and quantified their effects on biophysical fluxes globally and across biomes. Most parameters have minimal impact on biophysical fluxes, with only a few substantially influencing results. While both models exhibit similar parameter sensitivity for some fluxes, CLM-FATES shows larger spread in gross primary productivity (GPP), driven by strong sensitivity to carboxylation rate. CLM-FATES also shows a weaker GPP response to soil hydrology parameters and exhibits higher water use efficiency (WUE). Cross-model comparisons reveal similar sensitivities for some parameters (e.g., leaf dimension) but divergent responses to others (e.g., stomatal intercept), highlighting underlying structural differences. Differences in WUE and sensitivity to hydrology and stomatal conductance parameters underscore how model structure fundamentally alters parametric sensitivity. The data sets generated from these ensembles can be used to identify influential parameters and guide future calibration efforts.

Foster, A. C. [NSF National Center for Atmospheric↗