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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 1,279 records · Page 71
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Wavefunction stability analysis without analytical electronic Hessians: application to orbital-optimised second-order Møller–Plesset theory and VV10-containing density functionals

Wavefunction stability analysis is commonly applied to converged self-consistent field (SCF) solutions to verify whether the electronic energy is a local minimum with respect to second-order variations in the orbitals. By iterative diagonalisation, the procedure calculates the lowest eigenvalue of the stability matrix or electronic Hessian. However, analytical expressions for the electronic Hessian are unavailable for most advanced post-Hartree-Fock (HF) wave function methods and even some Kohn-Sham (KS) density functionals. To address such cases, here we formulate the Hessian-vector product within the iterative diagonalisation procedure as a finite difference of the electronic gradient with respect to orbital perturbations in the direction of the vector. As a model application, following the lowest eigenvalue of the orbital-optimised second-order Møller-Plesset perturbation theory (OOMP2) Hessian during H 2 dissociation reveals the surprising stability of the spin-restricted solution at all separations, with a second independent unrestricted solution. We show that a single stable solution can be recovered by using the regularised OOMP2 method (δ-OOMP2), which contains a level shift. Internal and external stability analyses are also performed for SCF solutions of a recently developed range-separated hybrid density functional, ωB97X-V, for which the analytical Hessian is not yet available due to the complexity of its long-range non-local VV10 correlation functional.

Brueckner orbitals↗
NASA NTRS1979

Leading-edge slat optimization for maximum airfoil lift

A numerical procedure for determining the position (horizontal location, vertical location, and deflection) of a leading edge slat that maximizes the lift of multielement airfoils is presented. The structure of the flow field is calculated by iteratively coupling potential flow and boundary layer analysis. This aerodynamic calculation is combined with a constrained function minimization analysis to determine the position of a leading edge slat so that the suction peak on the nose of the main airfoil is minized. The slat position is constrained by the numerical procedure to ensure an attached boundary layer on the upper surface of the slat and to ensure negligible interaction between the slat wake and the boundary layer on the upper surface of the main airfoil. The highest angle attack at which this optimized slat position can maintain attached flow on the main airfoil defines the optimum slat position for maximum lift. The design method is demonstrated for an airfoil equipped with a leading-edge slat and a trailing edge, single-slotted flap. The theoretical results are compared with experimental data, obtained in the Ames 40 by 80 Foot Wind Tunnel, to verify experimentally the predicted slat position for maximum lift. The experimentally optimized slat position is in good agreement with the theoretical prediction, indicating that the theoretical procedure is a feasible design method.

Olson, L. E.↗
NASA NTRS2008

Laboratory and Airborne BRDF Analysis of Vegetation Leaves and Soil Samples

Laboratory-based Bidirectional Reflectance Distribution Function (BRDF) analysis of vegetation leaves, soil, and leaf litter samples is presented. The leaf litter and soil samples, numbered 1 and 2, were obtained from a site located in the savanna biome of South Africa (Skukuza: 25.0degS, 31.5degE). A third soil sample, number 3, was obtained from Etosha Pan, Namibia (19.20degS, 15.93degE, alt. 1100 m). In addition, BRDF of local fresh and dry leaves from tulip tree (Liriodendron tulipifera) and acacia tree (Acacia greggii) were studied. It is shown how the BRDF depends on the incident and scatter angles, sample size (i.e. crushed versus whole leaf,) soil samples fraction size, sample status (i.e. fresh versus dry leaves), vegetation species (poplar versus acacia), and vegetation s biochemical composition. As a demonstration of the application of the results of this study, airborne BRDF measurements acquired with NASA's Cloud Absorption Radiometer (CAR) over the same general site where the soil and leaf litter samples were obtained are compared to the laboratory results. Good agreement between laboratory and airborne measured BRDF is reported.

Georgiev, Georgi T.↗
NASA NTRS1999

Higher-Order Theory for Functionally Graded Materials

This paper presents the full generalization of the Cartesian coordinate-based higher-order theory for functionally graded materials developed by the authors during the past several years. This theory circumvents the problematic use of the standard micromechanical approach, based on the concept of a representative volume element, commonly employed in the analysis of functionally graded composites by explicitly coupling the local (microstructural) and global (macrostructural) responses. The theoretical framework is based on volumetric averaging of the various field quantities, together with imposition of boundary and interfacial conditions in an average sense between the subvolumes used to characterize the composite's functionally graded microstructure. The generalization outlined herein involves extension of the theoretical framework to enable the analysis of materials characterized by spatially variable microstructures in three directions. Specialization of the generalized theoretical framework to previously published versions of the higher-order theory for materials functionally graded in one and two directions is demonstrated. In the applications part of the paper we summarize the major findings obtained with the one-directional and two-directional versions of the higher-order theory. The results illustrate both the fundamental issues related to the influence of microstructure on microscopic and macroscopic quantities governing the response of composites and the technologically important applications. A major issue addressed herein is the applicability of the classical homogenization schemes in the analysis of functionally graded materials. The technologically important applications illustrate the utility of functionally graded microstructures in tailoring the response of structural components in a variety of applications involving uniform and gradient thermomechanical loading.

Aboudi, Jacob↗
DOE OSTI2022

Role of SaPCR2 in Zn Uptake in the Root Elongation Zone of the Zn/Cd Hyperaccumulator Sedum alfredii

Zn pollution is a potential toxicant for agriculture and the environment. Sedum alfredii is a Zn/Cd hyperaccumulator found in China and has been proven as a useful resource for the phytoremediation of Zn-contaminated sites. However, the molecular mechanism of Zn uptake in S. alfredii is limited. In this study, the function of SaPCR2 on Zn uptake in S. alfredii was identified by gene expression analysis, yeast function assays, Zn accumulation and root morphology analysis in transgenic lines to further elucidate the mechanisms of uptake and translocation of Zn in S. alfredii. The results showed that SaPCR2 was highly expressed in the root elongation zone of the hyperaccumulating ecotype (HE) S. alfredii, and high Zn exposure downregulated the expression of SaPCR2 in the HE S. alfredii root. The heterologous expression of SaPCR2 in yeast suggested that SaPCR2 was responsible for Zn influx. The overexpression of SaPCR2 in the non-hyperaccumulating ecotype (NHE) S. alfredii significantly increased the root uptake of Zn, but did not influence Mn, Cu or Fe. SR-μ-XRF technology showed that more Zn was distributed in the vascular buddle tissues, as well as in the cortex and epidermis in the transgenic lines. Root morphology was also altered after SaPCR2 overexpression, and a severe inhibition was observed. In the transgenic lines, the meristematic and elongation zones of the root were lower compared to the WT, and Zn accumulation in meristem cells was also reduced. These results indicate that SaPCR2 is responsible for Zn uptake, and mainly functions in the root elongation zone. This research on SaPCR2 could provide a theoretical basis for the use of genetic engineering technology in the modification of crops for their safe production and biological enhancement.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

A Method to Measure the Unbiased Decorrelation Timescale of the AGN Variable Signal from Structure Functions

A simple, model-independent method to quantify the stochastic variability of active galactic nuclei (AGNs) is the structure function (SF) analysis. If the SF for the timescales shorter than the decorrelation timescale τ is a single power law and for the longer ones becomes flat (i.e., white noise), then the auto-correlation function (ACF) of the signal can have the form of the power exponential (PE). We show that the signal decorrelation timescale can be measured directly from the SF as the timescale matching the amplitude 0.795 of the flat SF part (at long timescales), and only then is the measurement independent of the ACF PE power. Typically, the timescale has been measured at an arbitrarily fixed SF amplitude, but as we prove, this approach provides biased results, because the AGN SF/power spectral density slopes, and thus the ACF shape, are not constant and depend on either the AGN luminosity and/or the black hole mass. In particular, we show that using such a method for the simulated SFs that includes a combination of empirically known dependencies between the AGN luminosity L and both the SF amplitude and the PE power, and having no intrinsic τ–L dependence, produces a fake τ∝L{sup κ} relation with 0.3≲κ≲0.6, which otherwise is expected from theoretical works (κ≡0.5). Our method provides an alternative means for analyzing AGN variability to the standard SF fitting. The caveats, for both methods, are that the light curves must be sufficiently long (with a several year rest frame) and the ensemble SF assumes AGNs to have the same underlying variability process.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Position-specific isotope effects during alkaline hydrolysis of 2,4-dinitroanisole resolved by compound-specific isotope analysis, 13 C NMR, and density-functional theory

Compound-specific isotope analysis (CSIA), position-specific isotope analysis (PSIA), and computational modeling (e.g., quantum mechanical models; reactive-transport models) are increasingly being used to monitor and predict biotic and abiotic transformations of organic contaminants in the field. However, identifying the isotope effect(s) associated with a specific transformation remains challenging in many cases. We describe and interpret the position-specific isotope effects of C and N associated with a SN 2 Ar reaction mechanism by a combination of CSIA and PSIA using quantitative 13 C nuclear magnetic resonance spectrometry, and density-functional theory, using 2,4-dinitroanisole (DNAN) as a model compound. The position-specific 13 C enrichment factor of O–C 1 bond at the methoxy group attachment site (ε C1 ) was found to be approximately -41‰, a diagnostic value for transformation of DNAN to its reaction products 2,4-dinitrophenol and methanol. Theoretical kinetic isotope effects calculated for DNAN isotopologues agreed well with the position-specific isotope effects measured by CSIA and PSIA. This combination of measurements and theoretical predictions demonstrates a useful tool for evaluating degradation efficiencies and/or mechanisms of organic contaminants and may promote new and improved applications of isotope analysis in laboratory and field investigations.

13C NMR↗
DOE OSTI2025

Hydrogen Bond Benchmark: Focal‐Point Analysis and Assessment of DFT Functionals

We performed a hierarchical, convergent ab initio benchmark study and systematically analyzed the performance of density functional approximations for describing hydrogen bonds in small neutral, cationic, and anionic complexes, as well as in larger systems involving amide, urea, deltamide, and squaramide moieties. Focal point analyses (FPA), extrapolating to the ab initio limit, were carried out using correlated wave function methods up to CCSDT(Q) for the small complexes and CCSD(T) for the larger systems, together with correlation-consistent Gaussian basis sets up to the complete basis set limit. Optimized geometries and vibrational frequencies were obtained at the CCSD(T) level. The resulting FPA hydrogen-bond energies converge within a few tenths of a kcal mol −1 . These reference data were used to evaluate 60 density functionals (including 12 dispersion-corrected), spanning the local-density approximation (LDA), generalized gradient approximations (GGAs), meta-GGAs, hybrids, meta-hybrids, double-hybrids, and range-separated hybrids. Overall, the meta-hybrid M06-2X provides the best performance for both hydrogen bond energies and geometries, while the dispersion-corrected GGAs BLYP-D3(BJ) and BLYP-D4 also yield accurate hydrogen-bond data and can serve as cost-effective options for studying large and complex systems.

coupled cluster theory↗
DOE OSTI2025

Non-stoichiometry Governs the Pathway from Amorphous to Crystalline Calcium Carbonate

The controlled crystallization of calcium carbonate underlies the elaborate architectures of marine corals, the design of biomimetic materials, and the global carbon cycle. Despite its ubiquity, the chemical mechanisms that govern the crystallization of calcium carbonate from its amorphous precursor, amorphous calcium carbonate (ACC), remain elusive, largely due to the difficulty in resolving the structure and chemistry of this transient amorphous state. Here, we use time-lapse photography, image analysis, spatially resolved pH determination, in situ synchrotron pair distribution function (PDF) analysis, and dynamic nuclear polarization (DNP) solid-state nuclear magnetic resonance (NMR) spectroscopy to reveal pervasive compositional variability in ACC that underpins its metastability and crystallization. By evaluating the kinetics of the amorphous-to-crystalline transition across different solution chemistries, we demonstrate that ACC is non-stoichiometric and CO 3 -deficient. Counterions from the precursor (e.g., NO 3 - from Ca(NO 3 ) 2 ) substitute into the ACC network, displacing CO 3 ions and mediating both ACC stability and transformation. Crystallization proceeds through refinement of the stoichiometry toward CaCO 3 and uptake of free CO 3 2- anions. Furthermore, these findings are consistent across a wide range of concentrations and different carbonate sources, explaining the diverse behaviors observed for ACC and providing a chemical framework for controlling calcium carbonate crystallization.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
NASA NTRS2016

Functional Fault Model Development Process to Support Design Analysis and Operational Assessment

A functional fault model (FFM) is an abstract representation of the failure space of a givensystem. As such, it simulates the propagation of failure effects along paths between the origin ofthe system failure modes and points within the system capable of observing the failure effects. Asa result, FFMs may be used to diagnose the presence of failures in the modeled system. FFMsnecessarily contain a significant amount of information about the design, operations, and failuremodes and effects. One of the important benefits of FFMs is that they may be qualitative, ratherthan quantitative and, as a result, may be implemented early in the design process when there ismore potential to positively impact the system design. FFMs may therefore be developed andmatured throughout the monitored system's design process and may subsequently be used toprovide real-time diagnostic assessments that support system operations. This paper provides anoverview of a generalized NASA process that is being used to develop and apply FFMs. FFMtechnology has been evolving for more than 25 years. The FFM development process presented inthis paper was refined during NASA's Ares I, Space Launch System, and Ground SystemsDevelopment and Operations programs (i.e., from about 2007 to the present). Process refinementtook place as new modeling, analysis, and verification tools were created to enhance FFMcapabilities. In this paper, standard elements of a model development process (i.e., knowledgeacquisition, conceptual design, implementation & verification, and application) are describedwithin the context of FFMs. Further, newer tools and analytical capabilities that may benefit thebroader systems engineering process are identified and briefly described. The discussion isintended as a high-level guide for future FFM modelers.

Melcher, Kevin J.↗
NASA NTRS2016

Functional Fault Model Development Process to Support Design Analysis and Operational Assessment

A functional fault model (FFM) is an abstract representation of the failure space of a given system. As such, it simulates the propagation of failure effects along paths between the origin of the system failure modes and points within the system capable of observing the failure effects. As a result, FFMs may be used to diagnose the presence of failures in the modeled system. FFMs necessarily contain a significant amount of information about the design, operations, and failure modes and effects. One of the important benefits of FFMs is that they may be qualitative, rather than quantitative and, as a result, may be implemented early in the design process when there is more potential to positively impact the system design. FFMs may therefore be developed and matured throughout the monitored system's design process and may subsequently be used to provide real-time diagnostic assessments that support system operations. This paper provides an overview of a generalized NASA process that is being used to develop and apply FFMs. FFM technology has been evolving for more than 25 years. The FFM development process presented in this paper was refined during NASA's Ares I, Space Launch System, and Ground Systems Development and Operations programs (i.e., from about 2007 to the present). Process refinement took place as new modeling, analysis, and verification tools were created to enhance FFM capabilities. In this paper, standard elements of a model development process (i.e., knowledge acquisition, conceptual design, implementation & verification, and application) are described within the context of FFMs. Further, newer tools and analytical capabilities that may benefit the broader systems engineering process are identified and briefly described. The discussion is intended as a high-level guide for future FFM modelers.

Verification↗
DOE OSTI2013

Exploration of High-Dimensional Scalar Function for Nuclear Reactor Safety Analysis and Visualization

The next generation of methodologies for nuclear reactor Probabilistic Risk Assessment (PRA) explicitly accounts for the time element in modeling the probabilistic system evolution and uses numerical simulation tools to account for possible dependencies between failure events. The Monte-Carlo (MC) and the Dynamic Event Tree (DET) approaches belong to this new class of dynamic PRA methodologies. A challenge of dynamic PRA algorithms is the large amount of data they produce which may be difficult to visualize and analyze in order to extract useful information. We present a software tool that is designed to address these goals. We model a large-scale nuclear simulation dataset as a high-dimensional scalar function defined over a discrete sample of the domain. First, we provide structural analysis of such a function at multiple scales and provide insight into the relationship between the input parameters and the output. Second, we enable exploratory analysis for users, where we help the users to differentiate features from noise through multi-scale analysis on an interactive platform, based on domain knowledge and data characterization. Our analysis is performed by exploiting the topological and geometric properties of the domain, building statistical models based on its topological segmentations and providing interactive visual interfaces to facilitate such explorations. We provide a user’s guide to our software tool by highlighting its analysis and visualization capabilities, along with a use case involving dataset from a nuclear reactor safety simulation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Exploration of high-dimensional scalar function for nuclear reactor safety analysis and visualization

The next generation of methodologies for nuclear reactor Probabilistic Risk Assessment (PRA) explicitly accounts for the time element in modeling the probabilistic system evolution and uses numerical simulation tools to account for possible dependencies between failure events. The Monte-Carlo (MC) and the Dynamic Event Tree (DET) approaches belong to this new class of dynamic PRA methodologies. A challenge of dynamic PRA algorithms is the large amount of data they produce which may be difficult to visualize and analyze in order to extract useful information. We present a software tool that is designed to address these goals. We model a large-scale nuclear simulation dataset as a high-dimensional scalar function defined over a discrete sample of the domain. First, we provide structural analysis of such a function at multiple scales and provide insight into the relationship between the input parameters and the output. Second, we enable exploratory analysis for users, where we help the users to differentiate features from noise through multi-scale analysis on an interactive platform, based on domain knowledge and data characterization. Our analysis is performed by exploiting the topological and geometric properties of the domain, building statistical models based on its topological segmentations and providing interactive visual interfaces to facilitate such explorations. We provide a user's guide to our software tool by highlighting its analysis and visualization capabilities, along with a use case involving data from a nuclear reactor safety simulation. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Analysis of diagnostic calorimeter data by the transfer function technique

This paper describes the analysis procedure applied to the thermal measurements on the rear side of a carbon fibre composite calorimeter with the purpose of reconstructing the energy flux due to an ion beam colliding on the front side. The method is based on the transfer function technique and allows a fast analysis by means of the fast Fourier transform algorithm. Its efficacy has been tested both on simulated and measured temperature profiles: in all cases, the energy flux features are well reproduced and beamlets are well resolved. Limits and restrictions of the method are also discussed, providing strategies to handle issues related to signal noise and digital processing.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2011

Uncertainty Analysis via Failure Domain Characterization: Unrestricted Requirement Functions

This paper proposes an uncertainty analysis framework based on the characterization of the uncertain parameter space. This characterization enables the identification of worst-case uncertainty combinations and the approximation of the failure and safe domains with a high level of accuracy. Because these approximations are comprised of subsets of readily computable probability, they enable the calculation of arbitrarily tight upper and lower bounds to the failure probability. The methods developed herein, which are based on nonlinear constrained optimization, are applicable to requirement functions whose functional dependency on the uncertainty is arbitrary and whose explicit form may even be unknown. Some of the most prominent features of the methodology are the substantial desensitization of the calculations from the assumed uncertainty model (i.e., the probability distribution describing the uncertainty) as well as the accommodation for changes in such a model with a practically insignificant amount of computational effort.

Crespo, Luis G.↗
NASA NTRS2011

Uncertainty Analysis via Failure Domain Characterization: Polynomial Requirement Functions

This paper proposes an uncertainty analysis framework based on the characterization of the uncertain parameter space. This characterization enables the identification of worst-case uncertainty combinations and the approximation of the failure and safe domains with a high level of accuracy. Because these approximations are comprised of subsets of readily computable probability, they enable the calculation of arbitrarily tight upper and lower bounds to the failure probability. A Bernstein expansion approach is used to size hyper-rectangular subsets while a sum of squares programming approach is used to size quasi-ellipsoidal subsets. These methods are applicable to requirement functions whose functional dependency on the uncertainty is a known polynomial. Some of the most prominent features of the methodology are the substantial desensitization of the calculations from the uncertainty model assumed (i.e., the probability distribution describing the uncertainty) as well as the accommodation for changes in such a model with a practically insignificant amount of computational effort.

Crespo, Luis G.↗