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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 OSTI2021

Spin–Orbit Natural Transition Orbitals and Spin-Forbidden Transitions

Natural transition orbitals (NTOs) are in widespread use for visualizing and analyzing electronic transitions. Here, the present work introduces the analysis of formally spin-forbidden transitions with the help of complex-valued spin-orbit (SO) NTOs. The analysis specifically focuses on the components in such transitions that cause their intensity to be non-zero because of SO coupling. Transition properties such as transition dipole moments are partitioned into SO-NTO hole-particle pairs, such that contributions to the intensity from specific occupied and unoccupied orbitals are obtained. The method has been implemented within the restricted active space (RAS) self-consistent field wave function theory framework, with SO coupling treated by RAS state interaction. SO-NTOs have a broad range of potential applications, which is illustrated by the T 2 -S 1 state mixing in pyrazine, spin-forbidden vs. spin-allowed 4f–5d transitions in the Tb 3+ ion, and the phosphorescence of tris(2-phenylpyridine) iridium [Ir(ppy) 3 ].

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Sheaves as a Framework for Understanding and Interpreting Model Fit

As data grows in size and complexity, finding frameworks which aid in interpretation and analysis has become critical. This is particularly true when data comes from complex systems where extensive structure is available, but must be drawn from peripheral sources. In this paper we argue that in such situations, sheaves can provide a natural framework to analyze how well a statistical model fits at the local level (that is, on subsets of related datapoints) vs the global level (on all the data). The sheaf-based approach that we propose is suitably general enough to be useful in a range of applications, from analyzing sensor networks to understanding the feature space of a deep learning model.

Kvinge, Henry J.↗
NASA NTRS1981

Analysis of the inversion monitoring capabilities of a monostatic acoustic radar in complex terrain

A qualitative interpretation of the records from a monostatic acoustic radar is presented. This is achieved with the aid of airplane, helicopter, and rawinsonde temperature soundings. The diurnal structure of a mountain valley circulation pattern is studied with the use of two acoustic radars, one located in the valley and one on the downwind ridge. The monostatic acoustic radar was found to be sufficiently accurate in locating the heights of the inversions and the mixed layer depth to warrant use by industry even in complex terrain.

Koepf, D.↗
DOE OSTI2019

Properties of Equivalent Source Distributions Useful for Inverse Thermal Analysis

A general approach for inverse thermal analysis of heat deposition processes is parametric modeling of such processes using effective or equivalent source distributions (ESDs). ESDs can be adjusted conveniently for calculation of temperature fields, which are constrained according to boundary and temperature constraint conditions. This study applies properties of ESDs useful for parametric modeling of heat deposition processes. Inverse thermal analysis of a friction stir weld is presented, which is prototypical of processes tending to be complex with respect to energy deposition morphology. This analysis demonstrates properties of ESDs providing relatively optimal parametric modeling of energy deposition processes.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Quantitative approaches for multiscale structural analysis with atomic resolution electron microscopy

Atomic-resolution imaging with scanning transmission electron microscopy is a powerful tool for characterizing the nanoscale structure of materials, in particular features such as defects, local strains, and symmetry-breaking distortions. In addition to advanced instrumentation, the effectiveness of the technique depends on computational image analysis to extract meaningful features from complex datasets recorded in experiments, which can be complicated by the presence of noise and artifacts, small or overlapping features, and the need to scale analysis over large representative areas. Here, we present image analysis approaches which synergize real and reciprocal space information to efficiently and reliably obtain meaningful structural information with picometer scale precision across hundreds of nanometers of material from atomic-resolution electron microscope images. Damping superstructure peaks in reciprocal space allows symmetry-breaking structural distortions to be disentangled from other sources of inhomogeneity and measured with high precision. Real-space fitting of the wavelike signals resulting from Fourier filtering enables absolute quantification of lattice parameter variations and strain, as well as the uncertainty associated with these measurements. Implementations of these algorithms are made available as an open source python package.

36 MATERIALS SCIENCE↗
NASA NTRS1974

Selected reliability studies for the NERVA program

An investigation was made into certain methods of reliability analysis that are particularly suitable for complex mechanisms or systems in which there are many interactions. The methods developed were intended to assist in the design of such mechanisms, especially for analysis of failure sensitivity to parameter variations and for estimating reliability where extensive and meaningful life testing is not feasible. The system is modeled by a network of interconnected nodes. Each node is a state or mode of operation, or is an input or output node, and the branches are interactions. The network, with its probabilistic and time-dependent paths is also analyzed for reliability and failure modes by a Monte Carlo, computerized simulation of system performance.

Hoover, S. V.↗
NASA NTRS1990

A superelement methodology for coupled loads analysis of Space Station Freedom

A technique for calculating the effects of on-orbit loads on the structural dynamics of the International Space Station is developed on the basis of MSC/NASTRAN superelement solution sequences. The complexity of the Space Station program with its multiple configurations, international partners, and contractors is stressed, and the impact of this complexity on the dynamic-load analysis process is indicated. The MSC/NASTRAN-based approach is outlined, and its application to two versions of the Permanent Manned Capability configuration is described in detail, including component mode synthesis, GFSC/FLAME coupled-loads analysis (with components from the system FEM model or from the Work Package), and ISI/MATRIX-X generation of closed-loop forcing functions. The results of these sample analyses are presented in extensive tables and graphs and briefly characterized.

Del Basso, Steve↗
DOE OSTI2022

Effects of oxygen on the adsorption/oxidation of aqueous Sb(III) by Fe-loaded biochar: An X-ray absorption spectroscopy study

Fe-loaded biochar (FeBC) has been considered for Sb(III) adsorption, but the effects of oxygen (O 2 ) on the adsorption need further investigation. Liquid-/solid-phase analyses were conducted to investigate the role of O 2 in the Sb(III) adsorption by FeBC. The adsorption was best described by the pseudo-second-order (PSO) model for kinetic results and by the Langmuir model for thermodynamic results. More than 96.8 % of Sb(III) was adsorbed by FeBC, and available O 2 increased the liquid-phase Sb(III) oxidation efficiency by 2.1–7.5 times. The peak changes at ~1640 and 3450 cm -1 in FTIR spectra indicated the occurrence of inner-sphere complexation between Sb(III)/Sb(V) and hydroxyl (–OH)/carboxyl (–COOH) groups in FeBC under aerobic and anaerobic conditions. Fe/Sb X-ray absorption spectroscopy (XAS) analysis results showed aqueous Sb(III) complexed to the edge-sharing Fe(III)-O-Fe(III) in FeBC. Regardless of whether O 2 was available or not, solid-phase edge-sharing Fe(III)-O-Sb(V) complexes (~3.05 Å), which had lower toxicity and migration ability than aqueous Sb(III), formed through a ligand-to-metal charge-transfer (LMCT) process. More than 91 % of adsorbed Sb(III) was oxidized to edge-sharing Fe(III)-O-Sb(V) complexes in 3 h. Additionally, the Sb(V) from liquid-phase oxidation could also directly complex to the Fe(III)-O-Fe(III) and form edge-sharing Fe(III)-O-Sb(V) complexes. Here these results provide evidence to inform further FeBC application for the Sb-contaminated water treatment.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1977

Deformation at the Decaturville impact structure, Missouri

The Decaturville structure is a small area of intense disturbance marked by surface exposure of Precambrian rock and minor lead-zinc mineralization. The present paper gives a detailed analysis of the associated deformation processes on the basis of detailed mapping and study of drill core. The presence of shock-deformation features and the complex structural pattern revealed from the analysis are strong indications that the Decaturville structure was formed by impact of an extraterrestrial body.

Offield, T. W.↗
NASA NTRS1992

Development of an advanced spacecraft tandem mass spectrometer

The purpose of this research was to apply current advanced technology in electronics and materials to the development of a miniaturized Tandem Mass Spectrometer that would have the potential for future development into a package suitable for spacecraft use. The mass spectrometer to be used as a basis for the tandem instrument would be a magnetic sector instrument, of Nier-Johnson configuration, as used on the Viking Mars Lander mission. This instrument configuration would then be matched with a suitable second stage MS to provide the benefits of tandem MS operation for rapid identification of unknown organic compounds. This tandem instrument is configured with a newly designed GC system to aid in separation of complex mixtures prior to MS analysis. A number of important results were achieved in the course of this project. Among them were the development of a miniaturized GC subsystem, with a unique desorber-injector, fully temperature feedback controlled oven with powered cooling for rapid reset to ambient conditions, a unique combination inlet system to the MS that provides for both membrane sampling and direct capillary column sample transfer, a compact and ruggedized alignment configuration for the MS, an improved ion source design for increased sensitivity, and a simple, rugged tandem MS configuration that is particularly adaptable to spacecraft use because of its low power and low vacuum pumping requirements. The potential applications of this research include use in manned spacecraft like the space station as a real-time detection and warning device for the presence of potentially harmful trace contaminants of the spacecraft atmosphere, use as an analytical device for evaluating samples collected on the Moon or a planetary surface, or even use in connection with monitoring potentially hazardous conditions that may exist in terrestrial locations such as launch pads, environmental test chambers or other sensitive areas. Commercial development of the technology could lead to a new family of environmental test instruments that would be small and portable, yet would give quick analyses of complex samples.

Drew, Russell C.↗
DOE OSTI2024

Overdestabilization vs Overstabilization in the Theoretical Analysis of f-Orbital Covalency

The complex nature of the f-orbital electronic structures and their interaction with the chemical environment pose significant computational challenges. Advanced computational techniques that variationally include scalar relativities and spin–orbit coupling directly at the molecular orbital level have been developed to address this complexity. Among these, variational relativistic multiconfigurational multireference methods stand out for their high accuracy and systematic improvement in studies of f-block complexes. Additionally, these advanced methods offer the potential for calibrating low-scaling electronic structure methods such as density functional theory. However, studies on the Cl K-edge X-ray absorption spectra of the [Ce(III)Cl 6 ] 3– and [Ce(IV)Cl 6 ] 2– complexes show that time-dependent density functional theory with approximate exchange–correlation kernels can lead to inaccuracies, resulting in an overstabilization of 4f orbitals and incorrect assessments of covalency. In contrast, approaches utilizing small active space wave function methods may understate the stability of these orbitals. The results herein demonstrate the need for large active space, multireference, and variational relativistic methods in studying f-block complexes.

chemical calculations↗
DOE OSTI2021

A Simple, Cost-Effective, and Automation-Friendly Direct PCR Approach for Bacterial Community Analysis

Understanding bacterial interactions and assembly in complex microbial communities using 16S rRNA sequencing normally requires a large experimental load. However, the current DNA extraction methods, including cell disruption and genomic DNA purification, are normally biased, costly, time-consuming, labor-intensive, and not amenable to miniaturization by droplets or 1,536-well plates due to the significant DNA loss during the purification step for tiny-volume and low-cell-density samples.

16S rRNA sequencing↗
DOE OSTI2024

Assessing and benchmarking the fidelity of posterior inference methods for astrophysics data analysis

In this era of large and complex astronomical survey data, interpreting, validating, and comparing inference techniques becomes increasingly difficult. This is particularly critical for emerging inference methods like Simulation-Based Inference (SBI), which offer significant speedup potential and posterior modeling flexibility, especially when deep learning is incorporated. We present a study to assess and compare the performance and uncertainty prediction capability of Bayesian inference algorithms – from traditional MCMC sampling of analytic functions to deep learning-enabled SBI. We focus on testing the capacity of hierarchical inference modeling in those scenarios. Before we extend this study to cosmology, we first use astrophysical simulation data to ensure interpretability. We demonstrate a probabilistic programming implementation of hierarchical and non-hierarchical Bayesian inference using simulations derived from the DeepBench software library, a benchmarking tool developed by our group that generates simple and controllable astrophysical objects from first principles. This study will enable astronomers and physicists to harness the inference potential of these methods with confidence.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1989

Using an instrumented manikin for Space Station Freedom analysis

One of the most intriguing and complex areas of current computer graphics research is animating human figures to behave in a realistic manner. Believable, accurate human models are desirable for many everyday uses including industrial and architectural design, medical applications, and human factors evaluations. For zero-gravity (0-g) spacecraft design and mission planning scenarios, they are particularly valuable since 0-g conditions are difficult to simulate in a one-gravity Earth environment. At NASA/JSC, an in-house human modeling package called PLAID is currently being used to produce animations for human factors evaluation of Space Station Freedom design issues. Presented here is an introductory background discussion of problems encountered in existing techniques for animating human models and how an instrumented manikin can help improve the realism of these models.

Orr, Linda↗
DOE OSTI2018

The Application of MCNP6.2 Unstructured Mesh Geometry Capabilities to the Study of Heavy Ion Single Event Effect on Microelectronic Devices and the Reactor Physics Analysis - 25691

Unstructured meshes allow irregular or complex geometries to be modeled precisely in Monte Carlo radiation transport codes. Through this capability, it is possible to share an unstructured mesh model between multiple codes that use unstructured mesh geometry and thus improving coupled multi-physics simulations. In this work, unstructured meshes are used to model energy deposition from heavy ion strikes for single event effects on microelectronic devices as well as neutron flux mapping of nuclear reactor configurations. In each case, MCNP6.2's unstructured mesh functionality and applicability to the problem is demonstrated and analyzed. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

RAG for FLAG: AI Assistance for a Physics Code

Artificial intelligence (AI) has quickly become an important tool in scientific research, where significant efforts are underway to develop tools that will expedite the research process. One area of particular impact is scientific software, which can be particularly complex, and therefore time consuming to learn and use effectively. AI assistants are increasingly helping to streamline the process by performing tasks such as interactively answering user questions or suggesting solutions. Los Alamos National Laboratory (LANL) develops several advanced scientific codes, such as FLAG, which can be used to run multiphysics simulations. With this study, our goal was to develop an AI assistant for FLAG that could help make the process of understanding the software and running physics simulations more efficient. To develop an AI assistant for FLAG, we used a method called retrieval-augmented generation (RAG), which is a technique that uses information from relevant data sources to enhance the accuracy of large language models (LLMs). We used the FLAG user manual and other FLAG documentation as the knowledge base for the RAG system. When a user provides a query, RAG retrieves relevant sections from the knowledge base in response, then uses those excerpts to generate grounded and contextually rich answers. We found that our AI assistant was able to provide context aware answers and source references to user queries. To evaluate performance, we developed a set of 40 benchmark questions and compared the accuracy of the responses to those of two standard LLMs without retrieval. Our AI assistant significantly outperformed the standard LLMs at answering FLAG-related questions, with an 82.5% accuracy rate, compared to 47.5% for both of the standard LLMs. This has the potential to make the process of learning and using FLAG much easier, especially for new users. Ultimately, it supports LANL’s broader mission by empowering scientists and engineers to focus more on discovery and analysis rather than on navigating complex software systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

GrAMME: Semisupervised Learning Using Multilayered Graph Attention Models

Modern data analysis pipelines are becoming increasingly complex due to the presence of multiview information sources. While graphs are effective in modeling complex relationships, in many scenarios, a single graph is rarely sufficient to succinctly represent all interactions, and hence, multilayered graphs have become popular. Though this leads to richer representations, extending solutions from the single-graph case is not straightforward. Consequently, there is a strong need for novel solutions to solve classical problems, such as node classification, in the multilayered case. In this article, we consider the problem of semisupervised learning with multilayered graphs. Though deep network embeddings, e.g., DeepWalk, are widely adopted for community discovery, we argue that feature learning with random node attributes, using graph neural networks, can be more effective. To this end, we propose to use attention models for effective feature learning and develop two novel architectures, GrAMME-SG and GrAMME-Fusion, that exploit the interlayer dependences for building multilayered graph embeddings. Using empirical studies on several benchmark data sets, we evaluate the proposed approaches and demonstrate significant performance improvements in comparison with the state-of-the-art network embedding strategies. The results also show that using simple random features is an effective choice, even in cases where explicit node attributes are not available.

97 MATHEMATICS AND COMPUTING↗