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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 469 records · Page 26

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DOE OSTI2020

Reshaping of Truncated Pd Nanocubes: Energetic and Kinetic Analysis Integrating Transmission Electron Microscopy with Atomistic-Level and Coarse-Grained Modeling

Stability against reshaping of metallic fcc nanocrystals synthesized with tailored far-from-equilibrium shapes is key to maintaining optimal properties for applications such as catalysis. Yet Arrhenius analysis of experimental reshaping kinetics, and appropriate theory and simulation, is lacking. As such, we use TEM to monitor the reshaping of Pd nanocubes of ~25 nm side length between 410 °C (over ~4.5 h) and 440 °C (over ~0.25 h), extracting a high effective energy barrier of E eff ≈ 4.6 eV. We also provide an analytic determination of the energy variation along the optimal pathway for reshaping that involves transfer of atoms across the nanocube surface from edges or corners to form new layers on side {100} facets. The effective barrier from this analysis is shown to increase strongly with the degree of truncation of edges and corners in the synthesized nanocube. Theory matches experiment for the appropriate degree of truncation. In addition, we perform simulations of a stochastic atomistic-level model incorporating a realistic description of diffusive hopping for undercoordinated surface atoms, thereby providing a visualization of the initial reshaping process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2017

Improvements to the APBS biomolecular solvation software suite: Improvements to the APBS Software Suite

The Adaptive Poisson-Boltzmann Solver (APBS) software was developed to solve the equations of continuum electrostatics for large biomolecular assemblages that has provided impact in the study of a broad range of chemical, biological, and biomedical applications. APBS addresses three key technology challenges for understanding solvation and electrostatics in biomedical applications: accurate and efficient models for biomolecular solvation and electrostatics, robust and scalable software for applying those theories to biomolecular systems, and mechanisms for sharing and analyzing biomolecular electrostatics data in the scientific community. To address new research applications and advancing computational capabilities, we have continually updated APBS and its suite of accompanying software since its release in 2001. In this manuscript, we discuss the models and capabilities that have recently been implemented within the APBS software package including: a Poisson-Boltzmann analytical and a semi-analytical solver, an optimized boundary element solver, a geometry-based geometric flow solvation model, a graph theory based algorithm for determining pKa values, and an improved web-based visualization tool for viewing electrostatics.

Biomedical applications↗

DOE OSTI2022

Machine Intelligence-Centered System for Automated Characterization of Functional Materials and Interfaces

Classic design of experiment relies on a time-intensive workflow that requires planning, data interpretation, and hypothesis building by experienced researchers. Here, in this paper, we describe an integrated, machine-intelligent experimental system which enables simultaneous dynamic tests of electrical, optical, gravimetric, and viscoelastic properties of materials under a programmable dynamic environment. Specially designed software controls the experiment and performs on-the-fly extensive data analysis and dynamic modeling, real-time iterative feedback for dynamic control of experimental conditions, and rapid visualization of experimental results. The system operates with minimal human intervention and enables time-efficient characterization of complex dynamic multifunctional environmental responses of materials with simultaneous data processing and analytics. The system provides a viable platform for artificial intelligence (AI)-centered material characterization, which, when coupled with an AI-controlled synthesis system, could lead to accelerated discovery of multifunctional materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Stress field measurements using quantitative schlieren

Quantitative schlieren analysis is extended here to optically transparent solids in quasi-static and dynamic experiments to measure stress distributions. The quasi-static experiments in polymethyl methacrylate (PMMA) compared refraction angles and stress gradients calculated from schlieren images to the analytical Flamant solution of a line load on a half-space. The quantitative schlieren measurements of the stress field in the thin sample with a load compared well to the analytical solution. The analysis method was then extended to explosive induced shock waves in PMMA. The explosive induced response of PMMA was experimentally studied using high-speed schlieren to visualize the shock propagation in conjunction with Photon Doppler Velocimetry (PDV) to record surface velocity histories. The stress state estimated from the schlieren images was compared to the stress calculated from the PDV measurements. High-speed imaging limitations caused the shock wave to not be fully resolved in the images, but was resolved in the PDV measurement. The stress state behind the shock calculated from the high-speed images followed a similar trend to the stress calculated from the PDV measurements.

Physics↗

NASA NTRS1973

A method for determining the preferred orientation of crystallites normal to a surface

Techniques representing the angular distribution of a particular direction in a crystallographic reference frame or analytical methods were developed. The data required by these techniques for displaying preferred orientation is obtained by measuring the orientation of a large number of crystallites. This may be done visually using etch-pit or Laue techniques which, experimentally, are both tedious and difficult. The intensities of X ray diffraction maxima are proportional to the number of crystallites whose crystallographic plane normals bisect the incident and diffracted beams. Parameters used in calculating powder patterns are also presented.

Snyder, R. L.↗

DOE OSTI2022

Digitalization of an experimental electrochemical reactor via the smart manufacturing innovation platform

The exponential increase in data produced over the last two decades has revolutionized the way we collect, store, process, analyze, model, and interpret information to improve profitability. Manufacturing is no exception. How- ever, Smart Manufacturing, the digital practice, organization, workforce, and infrastructure transformation for collection and deployment of data and models at scale and at all levels of manufacturing, is a complex, costly, and labor-intensive journey that is still seeing slow adoption. The Clean Energy Smart Manufacturing Innovation Institute (CESMII), a national Manufacturing USA public-private partnership sponsored by the Department of Energy, is addressing this scaled use of data and modeling in manufacturing. CESMII has focused on how to col- lect and use operating data for numerous applications that improve productivity, precision, and performance of manufacturing operations from factory floor to supply chain using process simulation, predictive analytics, mon- itoring and control, and real-time optimization. Because contextualized data are key, CESMII has developed the Smart Manufacturing Innovation Platform (SMIP) to lower the barriers to the data that are needed to accelerate data-based model building, improve data visualization, and more quickly gain insights. Reusable, standards-based ways of doing data collection, ingestion, and contextualization are particularly important for scaling access and use of data. The SMIP uses a standards-based definition and construct for reusable information models called an SM Profile. When an SM Profile is used in conjunction with the SMIP, the SMIP ensures the availability of contextualized, operational data for model building. The present work demonstrates Smart Manufacturing and the application of the SMIP for building several data-centered models for the operation and control of an ex- perimental electrochemical reactor that reduces carbon dioxide (CO 2 ) gas to valuable liquid and gas chemicals, such as alcohols, olefins, and syngas. We describe how the SMIP plays a central role in more effective model building and we demonstrate how the electochemical reactor can be controlled and optimized for the desired products. Use of the SMIP involves the transmission of real-time sensor measurements to a cloud resource so that the operating data are available to all model building experts. The data collection and transmission process is fully automated to greatly reduce the need for manual manipulation of the data. Data-driven machine learning models are used for advanced real-time state estimation, real-time optimization, and model-based feedback control for the reactor. The application models are implemented as a system to monitor the data flow and control the electrochemical reactor with a single visualization interface. SM Profiles are used to demonstrate reusability of the information models for the reactor and the instrumentation. The application packages, algorithms, and user interfaces developed are cast as Docker images in a library to facilitate reusability of the application models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1994

Performance Measurement, Visualization and Modeling of Parallel and Distributed Programs

This paper presents a methodology for debugging the performance of message-passing programs on both tightly coupled and loosely coupled distributed-memory machines. The AIMS (Automated Instrumentation and Monitoring System) toolkit, a suite of software tools for measurement and analysis of performance, is introduced and its application illustrated using several benchmark programs drawn from the field of computational fluid dynamics. AIMS includes (i) Xinstrument, a powerful source-code instrumentor, which supports both Fortran77 and C as well as a number of different message-passing libraries including Intel's NX Thinking Machines' CMMD, and PVM; (ii) Monitor, a library of timestamping and trace -collection routines that run on supercomputers (such as Intel's iPSC/860, Delta, and Paragon and Thinking Machines' CM5) as well as on networks of workstations (including Convex Cluster and SparcStations connected by a LAN); (iii) Visualization Kernel, a trace-animation facility that supports source-code clickback, simultaneous visualization of computation and communication patterns, as well as analysis of data movements; (iv) Statistics Kernel, an advanced profiling facility, that associates a variety of performance data with various syntactic components of a parallel program; (v) Index Kernel, a diagnostic tool that helps pinpoint performance bottlenecks through the use of abstract indices; (vi) Modeling Kernel, a facility for automated modeling of message-passing programs that supports both simulation -based and analytical approaches to performance prediction and scalability analysis; (vii) Intrusion Compensator, a utility for recovering true performance from observed performance by removing the overheads of monitoring and their effects on the communication pattern of the program; and (viii) Compatibility Tools, that convert AIMS-generated traces into formats used by other performance-visualization tools, such as ParaGraph, Pablo, and certain AVS/Explorer modules.

Yan, Jerry C.↗

NASA NTRS1977

An analytical model for highly seperated flow on airfoils at low speeds

A computer program was developed to solve the low speed flow around airfoils with highly separated flow. A new flow model included all of the major physical features in the separated region. Flow visualization tests also were made which gave substantiation to the validity of the model. The computation involves the matching of the potential flow, boundary layer and flows in the separated regions. Head's entrainment theory was used for boundary layer calculations and Korst's jet mixing analysis was used in the separated regions. A free stagnation point aft of the airfoil and a standing vortex in the separated region were modelled and computed.

Zunnalt, G. W.↗

NASA NTRS2007

Visual End-Effector Position Error Compensation for Planetary Robotics

This paper describes a vision-guided manipulation algorithm that improves arm end-effector positioning to subpixel accuracy and meets the highly restrictive imaging and computational constraints of a planetary robotic flight system. Analytical, simulation-based, and experimental analyses of the algorithm's effectiveness and sensitivity to camera and arm model error is presented along with results on several prototype research systems and 'ground-in-the-loop' technology experiments on the Mars Exploration Rover (MER) vehicles. A computationally efficient and robust subpixel end-effector fiducial detector that is instrumental to the algorithm's ability to achieve high accuracy is also described along with its validation results on MER data.

vision-guided manipulation algorithm↗

NASA NTRS2007

Visual end-effector position error compensation for planetary robotics

This paper describes a vision-guided manipulation algorithm that improves arm end-effector positioning to subpixel accuracy and meets the highly restrictive imaging and computational constraints of a planetary robotic flight system. Analytical, simulation-based, and experimental analyses of the algorithm's effectiveness and sensitivity to camera and arm model error is presented along with results on several prototype research systems and ground-in-the-loop technology experiments on the Mars Exploration Rover (MER) vehicles. A computationally efficient and robust subpixel end-effector fiducial detector that is instrumental to the algorithm's ability to achieve high accuracy is also described along with its validation results on MER data.

Nickels, Kevin↗

DOE OSTI2017

Analytical Techniques Used to Detect DNA Binding Modes of Ruthenium(II) Complexes with Extended Phenanthroline Ring

This review describes the analytical techniques used to detect DNA-probes such as Ru(II) complexes with hetero cyclic imidazo phenanthroline (IP) ligands. Studies on drug-DNA interactions are useful biochemical techniques for visualization of DNA both in vitro and in vivo. The interactions of small molecules that binds to DNA are mainly classified into two major classes, one involving covalent binding and another non-covalent binding. Covalent binding in DNA can be irreversible and may leads to inhibition of all DNA processes which subsequently leads to cell death. Usually, covalent interactions leads to permanent changes in the structure of nucleic acids. The non-covalent interaction of molecules with DNA can be due to electrostatic interaction, intercalation and groove binding. These interactions of DNA probes can be explored by various spectroscopic techniques viz. UV–visible, emission, emission quenching spectroscopy, viscosity and thermal denaturation measurements.

74 ATOMIC AND MOLECULAR PHYSICS↗

NASA NTRS1991

Applied high-speed imaging for the icing research program at NASA Lewis Research Center

The Icing Research Tunnel at NASA Lewis Research Center provides scientists a scaled, controlled environment to simulate natural icing events. The closed-loop, low speed, refrigerated wind tunnel offers the experimental capability to test for icing certification requirements, analytical model validation and calibration techniques, cloud physics instrumentation refinement, advanced ice protection systems, and rotorcraft icing methodology development. The test procedures for these objectives all require a high degree of visual documentation, both in real-time data acquisition and post-test image processing. Information is provided to scientific, technical, and industrial imaging specialists as well as to research personnel about the high-speed and conventional imaging systems will be on the recent ice protection technology program. Various imaging examples for some of the tests are presented. Additional imaging examples are available from the NASA Lewis Research Center's Photographic and Printing Branch.

Slater, Howard↗

NASA NTRS1992

Applied high-speed imaging for the icing research program at NASA Lewis Research Center

Slater, Howard↗

NASA NTRS2010

Process to Selectively Distinguish Viable from Non-Viable Bacterial Cells

The combination of ethidium monoazide (EMA) and post-fragmentation, randomly primed DNA amplification technologies will enhance the analytical capability to discern viable from non-viable bacterial cells in spacecraft-related samples. Intercalating agents have been widely used since the inception of molecular biology to stain and visualize nucleic acids. Only recently, intercalating agents such as EMA have been exploited to selectively distinguish viable from dead bacterial cells. Intercalating dyes can only penetrate the membranes of dead cells. Once through the membrane and actually inside the cell, they intercalate DNA and, upon photolysis with visible light, produce stable DNA monoadducts. Once the DNA is crosslinked, it becomes insoluble and unable to be fragmented for post-fragmentation, randomly primed DNA library formation. Viable organisms DNA remains unaffected by the intercalating agents, allowing for amplification via post-fragmentation, randomly primed technologies. This results in the ability to carry out downstream nucleic acid-based analyses on viable microbes to the exclusion of all non-viable cells.

LaDuc, Myron T.↗

NASA NTRS2026

Hydrology Copilot: A Cloud-Native Ai System for Hydrological Data Analysis

The emergence of AI-driven Earth observation systems promises to broaden access to petabyte-scale geospatial data beyond domain specialists. However, translating this vision into operational scientific infrastructure requires addressing fundamental challenges in data virtualization, code transparency, and domain-specific reasoning. We present Hydrology Copilot, a cloud-native AI framework for natural-language-driven analysis of Earth observation data. To demonstrate operational capabilities at scale, we implement the system using NASA's North American Land Data Assimilation System version 3 (NLDAS-3), which provides surface meteorological forcing and land-surface model output across North and Central America at 1-km resolution, from which drought diagnostics are derived. The system integrates five core contributions: (1) scalable data virtualization using Kerchunk-based cloud optimized access, achieving a 1.5 to 4.6 times improvement in I/O latency across benchmark queries spanning regional single-day extractions (4.6 times speedup) to continental monthly aggregations (1.5 times speedup); (2) transparent code generation through Microsoft Azure AI Foundry agents that expose executable Python workflows for scientific verification; (3) persistent conversational memory enabling multi-turn analytical discourse across sessions; (4) intelligent query validation that enforces dataset boundaries and resolves ambiguous requests before execution; and (5) a multi-agent architecture coordinating query parsing, code generation, and visualization. We evaluate the system through drought-monitoring workflows, demonstrating reliable code generation, accurate results validated against reference computations and the operational U.S. Drought Monitor, and efficient operation across increasingly complex tasks. By bridging natural-language interfaces with rigorous hydrological analysis, Hydrology Copilot advances beyond proof-of-concept demonstrations to provide a deployable framework for operational Earth science applications.

Data virtualization↗

NASA NTRS2017

Engine Icing Data - An Analytics Approach

Engine icing researchers at the NASA Glenn Research Center use the Escort data acquisition system in the Propulsion Systems Laboratory (PSL) to generate and collect a tremendous amount of data every day. Currently these researchers spend countless hours processing and formatting their data, selecting important variables, and plotting relationships between variables, all by hand, generally analyzing data in a spreadsheet-style program (such as Microsoft Excel). Though spreadsheet-style analysis is familiar and intuitive to many, processing data in spreadsheets is often unreproducible and small mistakes are easily overlooked. Spreadsheet-style analysis is also time inefficient. The same formatting, processing, and plotting procedure has to be repeated for every dataset, which leads to researchers performing the same tedious data munging process over and over instead of making discoveries within their data. This paper documents a data analysis tool written in Python hosted in a Jupyter notebook that vastly simplifies the analysis process. From the file path of any folder containing time series datasets, this tool batch loads every dataset in the folder, processes the datasets in parallel, and ingests them into a widget where users can search for and interactively plot subsets of columns in a number of ways with a click of a button, easily and intuitively comparing their data and discovering interesting dynamics. Furthermore, comparing variables across data sets and integrating video data (while extremely difficult with spreadsheet-style programs) is quite simplified in this tool. This tool has also gathered interest outside the engine icing branch, and will be used by researchers across NASA Glenn Research Center. This project exemplifies the enormous benefit of automating data processing, analysis, and visualization, and will help researchers move from raw data to insight in a much smaller time frame.

Engine Icing↗

DOE OSTI2021

Data Package of Results from Salt Spill Testing

This document provides or identifies the full suite of data that was measured in laboratory salt spill tests on molten salt spreading and heat transfer, molten salt flowing and freezing in tubing, stainless steel corrosion kinetics in molten salt, and molten salt splashing and aerosol generation. The background, motivation, and methods for the work are explained in detail in an accompanying report (Thomas and Jackson, 2021), which includes representative results for all measurements. Quantitative data are tabulated to facilitate use in follow-on calculations and qualitative data in the form of visual and infrared video files are indexed for reference.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Coupling SCALE with DAKOTA for Axial Burnup Profiles Assessment in Burnup Credit

This paper presents a computational study that demonstrates the application of the SCALE code system in conjunction with the Design Analysis Kit for Optimization and Terascale Applications (DAKOTA) for the analysis of key factors influencing the evaluation of burnup credit (BUC) in pressurized water reactors (PWRs). The primary objective of this analysis is to characterize the model by utilizing parameterization, uncertainty quantification, and optimization studies. Using this approach, we can comprehensively assess the system and conduct informed predictive studies. This study highlights the effectiveness of the SCALE code system integrated within the DAKOTA framework in terms of efficiency and capability. With the coupling of the burnup code ORIGAMI with the CSAS or TSUNAMI-3D sequence embedded in a DAKOTA analysis, we can characterize the factors that influence the k eff of PWR 17x17 spent nuclear fuel (SNF) in the GBC-32 computational benchmark cask for the assessment of BUC in criticality safety analysis. The coupling methodology used in this study is not exclusive to BUC analysis. However, the choice to apply this methodology to the BUC problem is particularly significant because of the diverse range of aspects it encompasses in nuclear criticality safety analyses. This problem presents a unique opportunity to explore and address multiple facets of such analyses related to BUC and illustrates the capability of the SCALE code system with DAKOTA. This analysis makes use of historical reference data for the axial burnup profile, where the entire space within the bounds is considered. Both SCALE and DAKOTA are currently integrated in the Nuclear Energy Advanced Modeling Simulation (NEAMS) Workbench code system, which has a user-friendly graphical interface that simplifies the setup of simulations and configuration of input parameters as well as the visualization of simulation results.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗