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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 541 records · Page 30

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NASA NTRS2011

Experiments in Reconstructing Twentieth-Century Sea Levels

One approach to reconstructing historical sea level from the relatively sparse tide-gauge network is to employ Empirical Orthogonal Functions (EOFs) as interpolatory spatial basis functions. The EOFs are determined from independent global data, generally sea-surface heights from either satellite altimetry or a numerical ocean model. The problem is revisited here for sea level since 1900. A new approach to handling the tide-gauge datum problem by direct solution offers possible advantages over the method of integrating sea-level differences, with the potential of eventually adjusting datums into the global terrestrial reference frame. The resulting time series of global mean sea levels appears fairly insensitive to the adopted set of EOFs. In contrast, charts of regional sea level anomalies and trends are very sensitive to the adopted set of EOFs, especially for the sparser network of gauges in the early 20th century. The reconstructions appear especially suspect before 1950 in the tropical Pacific. While this limits some applications of the sea-level reconstructions, the sensitivity does appear adequately captured by formal uncertainties. All our solutions show regional trends over the past five decades to be fairly uniform throughout the global ocean, in contrast to trends observed over the shorter altimeter era. Consistent with several previous estimates, the global sea-level rise since 1900 is 1.70 +/- 0.26 mm/yr. The global trend since 1995 exceeds 3 mm/yr which is consistent with altimeter measurements, but this large trend was possibly also reached between 1935 and 1950.

Ray, Richard D.↗

NASA NTRS2016

Pitfalls and Precautions When Using Predicted Failure Data for Quantitative Analysis of Safety Risk for Human Rated Launch Vehicles

Launch vehicle reliability analysis is largely dependent upon using predicted failure rates from data sources such as MIL-HDBK-217F. Reliability prediction methodologies based on component data do not take into account system integration risks such as those attributable to manufacturing and assembly. These sources often dominate component level risk. While consequence of failure is often understood, using predicted values in a risk model to estimate the probability of occurrence may underestimate the actual risk. Managers and decision makers use the probability of occurrence to influence the determination whether to accept the risk or require a design modification. The actual risk threshold for acceptance may not be fully understood due to the absence of system level test data or operational data. This paper will establish a method and approach to identify the pitfalls and precautions of accepting risk based solely upon predicted failure data. This approach will provide a set of guidelines that may be useful to arrive at a more realistic quantification of risk prior to acceptance by a program.

Hatfield, Glen S.↗

DOE OSTI2022

Digitalization, Management and Synthesis of Thermal Hydraulic Legacy Data Using Dynamical System Scaling

A unique attribute of the nuclear industry is the extent by which designers, developers, operators, and regulators pay attention to demonstrating the safety case. The safety case for nuclear systems is a written, traceable expression of safety, demonstrating the system’s protective measures against uncontrolled radiological releases. The nuclear installation resiliency or safety takes overriding priority over function and performance. The preparation of the safety case heavily relies on extensive experimental campaigns that challenge the target design under a spectrum of postulated accident scenarios. For safety reasons, these experiments are typically conducted in sub-scale test apparatuses intended to reproduce the postulated accident scenarios and event sequences realistically but subject to proven similarity criteria, often referred to as scaling analyses. Since the dawn of the nuclear industry, significant resources have been committed to the construction and operation of such test facilities and a massive amount of data has been generated. Such test data have been and are still used to validate the fundamental assumptions of nuclear power plant phenomena. As we move into the digital world, capturing this multi-decades worth of information in a transparent, easily accessible, and usable manner for the public and industry stakeholders is of paramount importance. Over the last few years FPoliSolutions has been actively developing an enterprise digital data ontology platform (FPoliDON) intended to do just that. The concept was introduced in a paper at the previous NURETH edition and has been significantly enhanced since. With the vision of helping designers use the data to assess their safety case evaluation models, the platform was designed not only to ontologically organize the experimental data, but also to guide the user in the complex analytics associated with the interpretation and use of such test results. A new feature which has been recently added is the ability for the user to access a library of sophisticated mathematical procedures for performing scaling analyses. For this purpose, the Dynamical System Scaling (DSS) procedure invented by Dr. Jose’ Reyes was formulated as one of the services in the digital platform. These methods have been demonstrated to provide an excelled mathematical apparatus to identify similarity criteria or quantify distortions between measured data and the target prototypical conditions. Moreover, DSS can provide a level of synthesis across SETs and IETs which has the promise to yield efficiency in the evaluation code assessment activities. This is often a daunting and expensive task to set up evaluation models that support the safety case of current and future nuclear power plants.

Reyes, Jose↗

NASA NTRS2016

System-Level Prognostics for the National Airspace

In the National Airspace System (NAS), safety is assured through a set of rules, regulations, and procedures to respond to unsafe events. However, safety stands to benefit immensely from the introduction of tools and methodologies from Prognostics and Health Management (PHM). PHM will enable the NAS to stochastically predict unsafe states within the NAS, enabling a proactive preventative response strategy, as opposed to a reactive mitigative one. However, current PHM methods do not directly apply to the NAS for several reasons: they typically apply only at the component level, are implemented in a centralized manner, and are focused only on predicting remaining useful life. In this paper, we extend the model-based prognostics approach to PHM in order to provide a framework that can be applied to the NAS. We offer a system-level approach that supports a distributed implementation, and provide algorithms to predict the probability of an unsafe state, either at a specific time or within a time interval, and to predict the time of an unsafe state. Experimental results in simulation demonstrate the new approach.

prognostics↗

DOE OSTI2018

Electronic Energies Are Not Enough: An Ion Mobility-Aided, Quantum Chemical Benchmark Analysis of H + GPGG Conformers

Peptides and proteins exist not as single, lowest energy structures but as ensembles of states separated by small barriers. In order to study these species we must be able to correctly identify their gas phase conformational distributions, and ion mobility spectrometry (IMS) has arisen as an experimental method for assessing the gas phase energetics of flexible peptides. Here, we present a thorough exploration and benchmarking of the low energy conformers of the small, hairpin peptide H+ GPGG with the aid of ion mobility spectrometry against a wide swath of density functionals (35 dispersion-corrected and uncorrected functionals represented by 21 unique exchange–correlation functionals) and wave function theory methods (15 total levels of theory). The three experimentally resolved IMS peaks were found to correspond to three distinct pairs of conformers, each pair composed of species differing only by the chair or boat configuration of the proline. Two of the H+ GPGG conformer pairs possess a cis configuration about the Pro–Gly1 peptide bond while the other adopts a trans configuration. While the experimental spectrum reports a higher intensity for the cis-1 conformer than the trans conformer, 13 WFT levels of theory, including a complete basis set CCSD(T) extrapolation, obtain trans to be favored in terms of the electronic energy. This same effect is seen in 14 of the 18 dispersion-corrected density functionals studied, whereas the remaining 17 functionals show more variety. Only when Gibbs free energies are considered do the WFT methods and dispersion-corrected functionals reflect the experimental distribution. CAM-B3LYP-D3BJ emerges as the best-performing density functional, matching the experimental distribution and the CCSD(T)/CBS relative energies within 6%. Further analysis reveals the trans conformer to be favored electronically, but entropically disfavored, leading to the experimental preference of the cis-1 conformer. Furthermore, these results highlight the danger in considering only the electronic energies, which is common practice in electronic structure theory predictions of conformational energy distributions. Additionally, the effects of temperature and scaling of the frequencies used in obtaining the Gibbs free energies are explored.

Energy↗

NASA NTRS1988

Color graphics workstations used for simultaneous display of satellite and model data sets

Model-measurement display methods for studying actual or synthetic satellite measurements of cloudiness are developed. Visualization and animation techniques are employed to analyze the data. Two types of animation sequences, one based on Insat IR geosynchronous satellite imagery combined with upper level velocity potentials calculations and isoline depictions of the high amplitude centers of low frequency cloudiness activity, and the other combines a mesoscale cloud model simulation of a severe hail storm and synthetic microwave radiation signatures, are described.

Cooper, Harry J.↗

NASA NTRS1994

Learning random networks for compression of still and moving images

Image compression for both still and moving images is an extremely important area of investigation, with numerous applications to videoconferencing, interactive education, home entertainment, and potential applications to earth observations, medical imaging, digital libraries, and many other areas. We describe work on a neural network methodology to compress/decompress still and moving images. We use the 'point-process' type neural network model which is closer to biophysical reality than standard models, and yet is mathematically much more tractable. We currently achieve compression ratios of the order of 120:1 for moving grey-level images, based on a combination of motion detection and compression. The observed signal-to-noise ratio varies from values above 25 to more than 35. The method is computationally fast so that compression and decompression can be carried out in real-time. It uses the adaptive capabilities of a set of neural networks so as to select varying compression ratios in real-time as a function of quality achieved. It also uses a motion detector which will avoid retransmitting portions of the image which have varied little from the previous frame. Further improvements can be achieved by using on-line learning during compression, and by appropriate compensation of nonlinearities in the compression/decompression scheme. We expect to go well beyond the 250:1 compression level for color images with good quality levels.

Gelenbe, Erol↗

NASA NTRS2013

Safety Sufficiency for NextGen: Assessment of Selected Existing Safety Methods, Tools, Processes, and Regulations

NextGen is a complex socio-technical system and, in many ways, it is expected to be more complex than the current system. It is vital to assess the safety impact of the NextGen elements (technologies, systems, and procedures) in a rigorous and systematic way and to ensure that they do not compromise safety. In this study, the NextGen elements in the form of Operational Improvements (OIs), Enablers, Research Activities, Development Activities, and Policy Issues were identified. The overall hazard situation in NextGen was outlined; a high-level hazard analysis was conducted with respect to multiple elements in a representative NextGen OI known as OI-0349 (Automation Support for Separation Management); and the hazards resulting from the highly dynamic complexity involved in an OI-0349 scenario were illustrated. A selected but representative set of the existing safety methods, tools, processes, and regulations was then reviewed and analyzed regarding whether they are sufficient to assess safety in the elements of that OI and ensure that safety will not be compromised and whether they might incur intolerably high costs.

Xu, Xidong↗

DOE OSTI2018

Push it to the limit: comparing periodic and local approaches to density functional theory for intermolecular interactions

With the aim of systematically comparing two popular approaches to density functional theory–all-electron calculations with local basis sets, and periodic calculations employing plane wave basis sets and norm-conserving pseudopotentials–we have computed complete-basis binding energies across the S22 set of intermolecular interactions, a dataset consisting of noncovalent interactions of small- and medium-sized molecules containing first- and second-row atoms, using the Troullier-Martins norm-conserving pseudopotentials with SPW92, a local spin-density approximation; and PBE, a generalised gradient approximation. Here, we have found that it is challenging to reach the basis set limit with these periodic calculations; for the methods and systems examined, a minimum vacuum distance of 30 Å between a system and its nearest images is necessary–unless some form of dipole correction is employed–as is a kinetic energy cutoff of at least 80 Ry. The trends in convergence with respect to vacuum size and kinetic energy cutoff are largely independent of the level of density functional approximation employed. A sense of the impact of each hyperparameter on basis set error provides a foundation for ensuring quality calculations in future studies and allows us to quantify the basis set errors incurred in existing studies on similar systems.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2018

Green’s Function Coupled-Cluster Approach: Simulating Photoelectron Spectra for Realistic Molecular Systems

In this paper we present an efficient implementation for the analytical energy- dependent coupled cluster Green’s function with singles and doubles (GFCCSD) approach with our first practice being computing spectral functions of real molecular systems. Due to its algebraic structure, the presented method is highly scalable, and is capable of computing spectral function for a given molecular system in any energy region. Several typical examples have been given to demonstrate its capability of computing spectral functions not only in the valence band, but also in the core-level energy region. Satellite peaks have been observed in the inner valence band and core-level energy region where many-body effect becomes significant and single particle picture of ionization often breaks down. The accuracy test has been carried out by extensively comparing our GFCCSD results with experimental results as well as the theoretical results from other methods. It turns out GFCCSD method is able to provide qualitative or semi-quantitative level of description of ionization processes in both the core and valence regimes. To significantly improve the GFCCSD results for the main states, larger basis set can usually be employed, whereas the improvement of the GFCCSD results for the satellite states needs higher order many-body terms to be included in the GFCC implementation.

electronic structure theory↗

DOE OSTI2017

Guided ion beam and theoretical studies of the bond energy of SmS +

Previous work has shown that atomic samarium cations react with carbonyl sulfide to form SmS + + CO in an exothermic and barrierless process. To characterize this reaction further, the bond energy of SmS + is determined in the present study using guided ion beam tandem mass spectrometry. Reactions of SmS + with Xe, CO, and O 2 are examined. Results for collision-induced dissociation processes with all three molecules along with the endothermicity of the SmS + + CO → Sm + + COS exchange reaction are combined to yield D 0 (Sm + –S) = 3.37 ± 0.20 eV. The CO and O 2 reactions also yield a SmSO + product, with measured endothermicities that indicate D 0 (SSm + –O) = 3.73 ± 0.16 eV and D 0 (OSm + –S) = 1.38 ± 0.27 eV. The SmS + bond energy is compared with theoretical values characterized at several levels of theory, including CCSD(T) complete basis set extrapolations using all-electron basis sets. Multireference configuration interaction calculations with explicit spin-orbit calculations along with composite thermochemistry using the Feller-Peterson-Dixon method and all-electron basis sets were also explored for SmS+, and for comparison, SmO, SmO + , and EuO

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2017

Network-based integration of systems genetics data reveals pathways associated with lignocellulosic biomass accumulation and processing

As a consequence of their remarkable adaptability, fast growth, and superior wood properties, eucalypt tree plantations have emerged as key renewable feedstocks (over 20 million ha globally) for the production of pulp, paper, bioenergy, and other lignocellulosic products. However, most biomass properties such as growth, wood density, and wood chemistry are complex traits that are hard to improve in long-lived perennials. Systems genetics, a process of harnessing multiple levels of component trait information (e.g., transcript, protein, and metabolite variation) in populations that vary in complex traits, has proven effective for dissecting the genetics and biology of such traits. We have applied a network-based data integration (NBDI) method for a systems-level analysis of genes, processes and pathways underlying biomass and bioenergy-related traits using a segregating Eucalyptus hybrid population. We show that the integrative approach can link biologically meaningful sets of genes to complex traits and at the same time reveal the molecular basis of trait variation. Gene sets identified for related woody biomass traits were found to share regulatory loci, cluster in network neighborhoods, and exhibit enrichment for molecular functions such as xylan metabolism and cell wall development. These findings offer a framework for identifying the molecular underpinnings of complex biomass and bioprocessing-related traits. Furthermore, a more thorough understanding of the molecular basis of plant biomass traits should provide additional opportunities for the establishment of a sustainable bio-based economy.

09 BIOMASS FUELS↗

DOE OSTI2022

Search for the weak decay ψ (3686) → $Λ^{+}_{c}$ $\overline{Σ}$ - + c.c. *

Using (448.1 ± 2.9) x 10 6 ψ (3686) events collected with the BESIII detector, we perform the first search for the weak baryonic decay ψ (3686) → $Λ^{+}_{c}$ $\overline{Σ}$ - + c.c. . The analysis procedure is optimized using a blinded method. No significant signal is observed, and the upper limit on the branching fraction ($\mathcal{B}$) of ψ (3686) → $Λ^{+}_{c}$ $\overline{Σ}$ - + c.c. is set as 1.4 x 10 -5 at the 90% confidence level.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2017

Nested Tracking Graphs

Tracking graphs are a well established tool in topological analysis to visualize the evolution of components and their properties over time, i.e., when components appear, disappear, merge, and split. However, tracking graphs are limited to a single level threshold and the graphs may vary substantially even under small changes to the threshold. To examine the evolution of features for varying levels, users have to compare multiple tracking graphs without a direct visual link between them. We propose a novel, interactive, nested graph visualization based on the fact that the tracked superlevel set components for different levels are related to each other through their nesting hierarchy. This approach allows us to set multiple tracking graphs in context to each other and enables users to effectively follow the evolution of components for different levels simultaneously. We show the effectiveness of our approach on datasets from finite pointset methods, computational fluid dynamics, and cosmology simulations.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

SIERRA Multimechanics Module: Aria User Manual (V.4.44)

Aria is a Galerkin finite element based program for solving coupled-physics problems described by systems of PDEs and is capable of solving nonlinear, implicit, transient and direct-to-steady state problems in two and three dimensions on parallel architectures. The suite of physics currently supported by Aria includes thermal energy transport, species transport, and electrostatics as well as generalized scalar, vector and tensor transport equations. Additionally, Aria includes support for manufacturing process flows via the incompressible Navier-Stokes equations specialized to a low Reynolds number ( %3C 1 ) regime. Enhanced modeling support of manufacturing processing is made possible through use of either arbitrary Lagrangian- Eulerian (ALE) and level set based free and moving boundary tracking in conjunction with quasi-static nonlinear elastic solid mechanics for mesh control. Coupled physics problems are solved in several ways including fully-coupled Newton's method with analytic or numerical sensitivities, fully-coupled Newton- Krylov methods and a loosely-coupled nonlinear iteration about subsets of the system that are solved using combinations of the aforementioned methods. Error estimation, uniform and dynamic h -adaptivity and dynamic load balancing are some of Aria's more advanced capabilities. Aria is based upon the Sierra Framework.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

SIERRA Multimechanics Module: Aria User Manual Version 4.46.

Aria is a Galerkin fnite element based program for solving coupled-physics problems described by systems of PDEs and is capable of solving nonlinear, implicit, transient and direct-to-steady state problems in two and three dimensions on parallel architectures. The suite of physics currently supported by Aria includes thermal energy transport, species transport, and electrostatics as well as generalized scalar, vector and tensor transport equations. Additionally, Aria includes support for manufacturing process fows via the incompressible Navier-Stokes equations specialized to a low Reynolds number ( %3C 1 ) regime. Enhanced modeling support of manufacturing processing is made possible through use of either arbitrary Lagrangian- Eulerian (ALE) and level set based free and moving boundary tracking in conjunction with quasi-static nonlinear elastic solid mechanics for mesh control. Coupled physics problems are solved in several ways including fully-coupled Newton's method with analytic or numerical sensitivities, fully-coupled Newton- Krylov methods and a loosely-coupled nonlinear iteration about subsets of the system that are solved using combinations of the aforementioned methods. Error estimation, uniform and dynamic h -adaptivity and dynamic load balancing are some of Aria's more advanced capabilities. Aria is based upon the Sierra Framework.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

SIERRA Multimechanics Module: Aria User Manual - Version 4.50

Aria is a Galerkin finite element based program for solving coupled-physics problems described by systems of PDEs and is capable of solving nonlinear, implicit, transient and direct-to-steady state problems in two and three dimensions on parallel architectures. The suite of physics currently supported by Aria includes thermal energy transport, species transport, and electrostatics as well as generalized scalar, vector and tensor transport equations. Additionally, Aria includes support for manufacturing process fows via the incompressible Navier-Stokes equations specialized to a low Reynolds number ( Re < 1 ) regime. Enhanced modeling support of manufacturing processing is made possible through use of either arbitrary Lagrangian- Eulerian (ALE) and level set based free and moving boundary tracking in conjunction with quasi-static nonlinear elastic solid mechanics for mesh control. Coupled physics problems are solved in several ways including fully-coupled Newton's method with analytic or numerical sensitivities, fully-coupled Newton- Krylov methods and a loosely-coupled nonlinear iteration about subsets of the system that are solved using combinations of the aforementioned methods. Error estimation, uniform and dynamic h-adaptivity and dynamic load balancing are some of Aria's more advanced capabilities.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

SIERRA Multimechanics Module: Aria User Manual (Version 4.48)

Aria is a Galerkin finite element based program for solving coupled-physics problems described by systems of PDEs and is capable of solving nonlinear, implicit, transient and direct-to-steady state problems in two and three dimensions on parallel architectures. The suite of physics currently supported by Aria includes thermal energy transport, species transport, and electrostatics as well as generalized scalar, vector and tensor transport equations. Additionally, Aria includes support for manufacturing process flows via the incompressible Navier-Stokes equations specialized to a low Reynolds number ($Re$ < 1) regime. Enhanced modeling support of manufacturing processing is made possible through use of either arbitrary Lagrangian- Eulerian (ALE) and level set based free and moving boundary tracking in conjunction with quasi-static nonlinear elastic solid mechanics for mesh control. Coupled physics problems are solved in several ways including fully-coupled Newton's method with analytic or numerical sensitivities, fully-coupled Newton-Krylov methods and a loosely-coupled nonlinear iteration about subsets of the system that are solved using combinations of the aforementioned methods. Error estimation, uniform and dynamic $h$-adaptivity and dynamic load balancing are some of Aria's more advanced capabilities.

97 MATHEMATICS AND COMPUTING↗