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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 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
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 OSTI2017

SIMS microanalysis of the Strelley Pool Formation cherts and the implications for the secular-temporal oxygen-isotope trend of cherts

The significance of oxygen isotope ratios in Archean chert has long been debated. Cherts from the c. 3.4 Ga Strelley Pool Formation (SPF) (Pilbara Craton, Western Australia) host some of the oldest stromatolite and microfossil evidence for life, but the genesis and timing of silica cements has been unclear. Field relations, petrography and a combination of laser fluorination and in-situ SIMS measurements of δ 18 O in quartz show that bedded cherts of the SPF were originally precipitated as carbonates and were later widely replaced by quartz. Three localities were studied and analyzed for δ 18 O(Qz) in chert: 1) Camel Creek: foliated, metamorphosed, bedded cherts and meter-scale black chert veins; 2) Unconformity Ridge and ABDP8 drill core: stromatolitic and bedded chert overlying basal detrital quartz sandstone; and 3) the Trendall locality: “bedded” stromatolitic chert replacing original dolomite, low temperature hydrothermal quartz, and mm- to decimeter-scale chert-quartz veins. Laser fluorination (mm-scale) values of δ18O(Qz) range from: 14.2 to 18.2‰ VSMOW at Camel Creek; 9.3 to 18.9‰ at Unconformity Ridge; and 13.7 to 25.7‰ at Trendall. Values of δ 18 O(Qz) in cm to decimeter-scale hydrothermal chert veins cutting bedded carbonates at Trendall range from ca. 15 to 16‰, whereas “bedded cherts” are 17 to 26‰. These laser data include the highest δ 18 O values reported for cherts in Paleoarchean sediments and are up to 4‰ higher than the upper limit of ~22‰ reported in other studies, in apparent contrast to the long-standing secular-temporal trend which shows such high δ 18 O only in younger chert. However, analysis by laser fluorination at the 1-mm scale cannot resolve microtextures seen petrographically. In contrast, in-situ SIMS analyses can resolve petrographic microtextures and show δ 18 O(Qz) at 10-μm scale have an even greater range of 7–31‰ in “bedded” cherts at the Trendall locality, up to 9‰ above the secular-temporal trend. Textures observed optically at the Trendall locality were classified as: microquartz, mesoquartz, chalcedony, megaquartz veins, and cavity megaquartz. SEM-CL imaging shows two generations of meso- and megaquartz; bright CL with well-developed growth zoning, and dark CL with massive or mottled texture. Microquartz is the earliest textural generation of quartz and has a maximum δ 18 O(Qz) of ~22‰ by SIMS. Dark-CL mesoquartz has similar δ 18 O to microquartz and is interpreted to also be early. Bright-zoned-CL mesoquartz, which formed post-Archean, has even higher δ 18 O, up to 29‰. Vein megaquartz crosscuts most quartz generations and has a restricted range of δ 18 O, mostly from 16 to 19‰. Chalcedony pseudomorphs rhombic cavities and fractures, lines the edges of veins, and has similar δ 18 O to veins (16–19‰). Late cavity megaquartz is bright and zoned by CL, grows into late open cavities, and has the highest δ 18 O(Qz) values reported from the Pilbara, up to 31.3‰. Thus, the highest-δ 18 O quartz cements at the Trendall locality are the youngest and may be related to weathering. Early silicification and the formation of microquartz, chalcedony and low δ 18 O mesoquartz occurred during low temperature hydrothermal activity in the Archean. None of the SPF quartz examined is interpreted to have formed as a direct precipitate from Paleoarchean seawater. Thus, values of δ 18 O(Qz) do not record either water chemistry or temperature of Archean oceans. In-situ SIMS analysis shows that high-δ 18 O(Qz) values above 22‰ are only found in late-forming cavity megaquartz and bright-zoned-CL mesoquartz at the Trendall locality. The SPF results from our sample suite demonstrate the ability to resolve complex history using detailed petrography and SIMS analysis. Similar studies may show equal complexity of δ 18 O(Qz) data for other localities that are interpreted to show secular-temporal trends for chert. The apparent increase of δ 18 O(Qz) through time may reflect differences in diagenesis, and/or an inherent and previously unrecognized sampling bias that compares fundamentally different populations of quartz, such as Archean hydrothermal chert from volcanic greenstone belts, with unrelated Phanerozoic biogenic quartz.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Crystal structure of WA352 provides insight into cytoplasmic male sterility in rice

Highlights: • Identification of a C-terminal structural and functional core domain of WA352. • The crystal structure of C-terminus of WA352 was determined at 1.3 Å resolution. • Molecular mechanism whereby WA352 perturbs COX11 function to cause CMS is proposed. Plant cytoplasmic male sterility (CMS) is an important phenomenon and is widely utilized in hybrid crop breeding. The Wild Abortive CMS (CMS-WA), a well-known CMS type, has been successfully applied in the commercial production of hybrid rice seeds for more than 40 years. The CMS-WA causal gene WA352 encodes a novel transmenbrane protein and the interacts with the mitochondrial copper chaperone COX11, triggering reactive oxygen species production and resulting in male sterility in CMS-WA lines. However, the structure of WA352 is currently unknown, and the structural mechanism whereby WA352 perturbs COX11 function to cause CMS remains largely unknown. Here, we report the crystal structure of the C-terminal functional domain of WA352 at 1.3 Å resolution. This functional domain, consisting of five α helices, is spindle-shaped with a length of 42 Å, and a diameter of 28 Å. Notably, the absence of any structural similarity to a known protein structure suggests that the WA352 functional domain is a novel fold. In addition, surface conservation analysis and structural modeling of the WA352-COX11 complex revealed details about the WA352-COX11 interaction. Further structural analysis suggested that the WA352-COX11 interaction blocks the copper ion transportation activity of COX11, which is essential for the assembly of cytochrome c oxidase, resulting in male sterility in CMS-WA lines. Our study paves the way toward structural determination of the WA352-COX11 complex and provides new insight into the mechanism of plant CMS.

60 APPLIED LIFE SCIENCES↗
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↗
DOE OSTI2013

Improved mesh based photon sampling techniques for neutron activation analysis

The design of fusion power systems requires analysis of neutron activation of large, complex volumes, and the resulting particles emitted from these volumes. Structured mesh-based discretization of these problems allows for improved modeling in these activation analysis problems. Finer discretization of these problems results in large computational costs, which drives the investigation of more efficient methods. Within an ad hoc subroutine of the Monte Carlo transport code MCNP, we implement sampling of voxels and photon energies for volumetric sources using the alias method. The alias method enables efficient sampling of a discrete probability distribution, and operates in 0(1) time, whereas the simpler direct discrete method requires 0(log(n)) time. By using the alias method, voxel sampling becomes a viable alternative to sampling space with the 0(1) approach of uniformly sampling the problem volume. Additionally, with voxel sampling it is straightforward to introduce biasing of volumetric sources, and we implement this biasing of voxels as an additional variance reduction technique that can be applied. We verify our implementation and compare the alias method, with and without biasing, to direct discrete sampling of voxels, and to uniform sampling. We study the behavior of source biasing in a second set of tests and find trends between improvements and source shape, material, and material density. Overall, however, the magnitude of improvements from source biasing appears to be limited. Future work will benefit from the implementation of efficient voxel sampling - particularly with conformal unstructured meshes where the uniform sampling approach cannot be applied. (authors)

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

LANL CSSE L2: Case Study of In Situ Data Analysis in ASC Integrated Codes [Slides]

The massive, complex datasets generated by scientific simulations on next-generation computer architectures at extreme scale pose new challenges for data management and scientific understanding. A critical element in meeting these new challenges is in situ data analysis where information is reduced and analyzed as close to the point of generation as possible, for example, at run time or as the data stream to longer term storage. This milestone will demonstrate in situ data analysis in xRAGE, an ASC Eulerian Radiation Hydrodynamics code. We will work with the Eulerian Applications Project to identify target problems that will exercise physics of interest to the program, and we will work closely with users to maximize the achieved usability and productivity improvements. We will investigate enhancements to the in situ process that enable and improve techniques of data reduction and data triage in addition to improving in situ performance by using portable acceleration technology. We will report on their viability and performance in xRAGE or another ASC code. These products will provide ASC IC developers with reference codes and tools that will benefit DSW by advancing the technology for predictive science at extreme scales.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

A multi-group Monte Carlo core analysis method and its application in SCWR design

Complex geometry and spectrum have been the characteristics of many newly developed nuclear energy systems, so the suitability and precision of the traditional deterministic codes are doubtable while being applied to simulate these systems. On the contrary, the Monte Carlo method has the inherent advantages of dealing with complex geometry and spectrum. The main disadvantage of Monte Carlo method is that it takes long time to get reliable results, so the efficiency is too low for the ordinary core designs. A new Monte Carlo core analysis scheme is developed, aimed to increase the calculation efficiency. It is finished in two steps: Firstly, the assembly level simulation is performed by continuous energy Monte Carlo method, which is suitable for any geometry and spectrum configuration, and the assembly multi-group constants are tallied at the same time; Secondly, the core level calculation is performed by multi-group Monte Carlo method, using the assembly group constants generated in the first step. Compared with the heterogeneous Monte Carlo calculations of the whole core, this two-step scheme is more efficient, and the precision is acceptable for the preliminary analysis of novel nuclear systems. Using this core analysis scheme, a SCWR core was designed based on a new SCWR assembly design. The core output is about 1,100 MWe, and a cycle length of about 550 EFPDs can be achieved with 3-batch refueling pattern. The average and maximum discharge burn-up are about 53.5 and 60.9 MWD/kgU respectively. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
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↗
DOE OSTI2017

Bellerophon Environment for Analysis of Materials (BEAM)

Improvements in scientific instrumentation allow imaging at mesoscopic to atomic length scales, many spectroscopic modes, and now--with the rise of multimodal acquisition systems and the associated processing capability--the era of multidimensional, informationally dense data sets has arrived. Technical issues in these combinatorial scientific fields are exacerbated by computational challenges best summarized as a necessity for drastic improvement in the capability to transfer, store, and analyze large volumes of data. The Bellerophon Environment for Analysis of Materials (BEAM) platform provides material scientists the capability to directly leverage the integrated computational and analytical power of High Performance Computing (HPC) to perform scalable data analysis and simulation and manage uploaded data files via an intuitive, cross-platform client user interface. This framework delivers authenticated, "push-button" execution of complex user workflows that deploy data analysis algorithms and computational simulations utilizing compute-and-data cloud infrastructures and HPC environments like Titan at the Oak Ridge Leadershp Computing Facility (OLCF).

Lingerfelt, Eric J↗
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↗
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↗
DOE OSTI2020

URBANopt: An Open-Source Software Development Kit for Community and Urban District Energy Modeling: Preprint

Urban building modeling tools are developing rapidly; these tools use emerging simulation workflows for specific urban environmental design tasks, such as assessing the impacts of energy efficiency technologies at a district scale. However, with the emergence of new environmental design tasks, addressing all possible use cases and tasks is challenging and cannot be covered by a single tool. Urban-scale analysis at this level of complexity often requires linking multiple emerging tools, rather than using a single tool, to adequately evaluate a variety of possible fields in urban environmental design. To achieve this, flexible platforms are needed to support multiple input formats (e.g., geometric and non-geometric building properties), enabling the mapping of such inputs to underlying simulation engines. This paper provides an overview of the open-source URBANopt Software Development Kit (SDK) for modeling high-performance buildings and energy systems at a district scale. URBANopt's flexible SDK is composed of several modules that can be customized to integrate with other tools and generate new workflows to perform urban environmental design tasks, such as capturing interactions between individual buildings, district energy systems, distributed energy resources, and the electric distribution grid. We describe the functionality of the core SDK modules in URBANopt (called Core Gem, GeoJSON Gem, and Scenario Gem) and discuss the flexibility of these modules as a means of integration with a variety of tools. We also document and demonstrate technical details of writing and combining new modules to create customized workflows. Finally, we present a case study that uses the URBANopt SDK to model a hypothetical mixed-use urban project and simulate various scenarios to meet district energy performance goals.

buildings↗
DOE OSTI2025

Dynamic mode decomposition for gyrokinetic eigenmode analysis

Dynamic mode decomposition (DMD) is a post-processing approach to decompose a complex time series into a set of modes via spectral analysis. DMD provides a new and powerful method to recover gyrokinetic drift-wave eigenfrequencies and eigenfunctions based only on the solution of the gyrokinetic-Maxwell initial value problem with almost no added cost to the initial value solver. In the present paper, DMD is applied to the CGYRO gyrokinetic code using a newly-developed CGYRO-DMD post-processor. CGYRO-DMD is numerically efficient, even on a single CPU. It does not set any restrictions on the plasma shape, beta (ratio of the plasma pressure to the magnetic field pressure), collisionality or number of species, and allows one to resolve numerous eigenmodes, even of comparable growth rates. In addition, DMD is not limited to unstable modes, but rather can capture stable and unstable branches simultaneously. In this work, we illustrate the accuracy of DMD through gyrokinetic analysis of mode transition for electromagnetic drift wave instabilities.

drift-wave eigenmodes↗