Search NASA⌕ Search

SEARCH · Search NASA

Results for “experimental database”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

From natural language to control signals: a conceptual framework for semantic channel finding in complex experimental infrastructure

Modern experimental platforms such as particle accelerators, fusion devices, telescopes, and industrial process control systems expose tens to hundreds of thousands of control and diagnostic channels, accumulated over decades of hardware evolution. Operators and AI systems alike depend on informal expert knowledge, inconsistent naming conventions, and scattered documentation to locate the signals required for monitoring, troubleshooting, and automated control, creating a persistent bottleneck for reliability, scalability, and emerging language-model-driven interfaces. We formalize semantic channel finding, the task of mapping natural-language intent to concrete control-system signals, as a general problem in complex experimental infrastructure, and introduce a four-paradigm conceptual framework to guide architecture selection based on facility-specific data regimes. The paradigms span (i) direct in-context lookup over small, curated channel dictionaries, (ii) constrained hierarchical navigation through structured trees, (iii) interactive agent exploration using iterative reasoning and tool-based database queries, and (iv) ontology-grounded semantic search that decouples channel meaning from facility-specific naming conventions. We demonstrate the practical feasibility of each paradigm through proof-of-concept implementations at four operational facilities spanning two orders of magnitude in scale: from compact free-electron lasers to large synchrotron light sources, operating under diverse control-system architectures ranging from clean hierarchical naming schemes to legacy environments with decades of heterogeneous conventions. Where evaluated against expert-curated operational queries, these instantiations achieve 90%–97% accuracy, validating the framework’s applicability across real-world deployment scenarios. To accelerate adoption across the broader scientific and industrial control-system community, we release open-source, plug-and-play implementations of all three interactive paradigms-direct lookup, hierarchical navigation, and middle-layer exploration-within the Osprey framework, together with tools for channel database generation, interactive testing, and minimal-configuration deployment. This work establishes semantic channel finding as a foundational capability for human-centric and agentic AI interfaces at large-scale facilities, providing both a systematic framework for architecture design and practical resources to enable adoption without building custom infrastructure from scratch.

channel finding↗
DOE OSTI2012

Modelling the graphite fracture mechanisms

In order to define a design criterion for graphite components, it is important to identify the physical phenomena responsible for the graphite fracture, to include them in a more effective modelling. In a first step, a large panel of experiments have been realised in order to build up an important database; results of tensile tests, 3 and 4 point bending tests on smooth and notched specimens have been analysed and have demonstrated an important geometry related effects on the behavior up to fracture. Then, first simulations with an elastic or an elastoplastic bilinear constitutive law have not made it possible to simulate the experimental fracture stress variations with the specimen geometry, the fracture mechanisms of the graphite being at the microstructural scale. That is the reason why a specific F.E. model of the graphite structure has been developed in which every graphite grain has been meshed independently, the crack initiation along the basal plane of the particles as well as the crack propagation and coalescence have been modelled too. This specific model has been used to test two different approaches for fracture initiation: a critical stress criterion and two criteria of fracture mechanic type. They are all based on crystallographic considerations as a global critical stress criterion gave unsatisfactory results. The criteria of fracture mechanic type being extremely unstable and unable to represent the graphite global behaviour up to the final collapse, the critical stress criterion has been preferred to predict the results of the large range of available experiments, on both smooth and notched specimens. In so doing, the experimental observations have been correctly simulated: the geometry related effects on the experimental fracture stress dispersion, the specimen volume effects on the macroscopic fracture stress and the crack propagation at a constant stress intensity factor. In addition, the parameters of the criterion have been related to experimental observations: the local crack initiation stress of 8 MPa corresponds to the non-linearity apparition on the global behavior observed experimentally and the the maximal critical stress defined for the particle of 30 MPa is equivalent to the fracture stress of notched specimens. This innovative combination of crack modelling and a local crystallographic critical stress criterion made it possible to understand that cleavage initiation and propagation in the graphite microstructure was driven by a mean critical stress criterion. (authors)

36 MATERIALS SCIENCE↗
DOE OSTI2014

Final Technical Report for Award DE-FG02-98ER41080

The prime motivation of the project at McMaster University was to carry out the critical evaluation and compilation of Nuclear Structure and Decay data, and of nuclear astrophysics data with continued participation in the United States Nuclear Data Program (US-NDP). A large body of evaluated and compiled structure data were supplied for databases such as ENSDF, XUNDL, NSR, etc. residing on webpage of National Nuclear Data Center of the Brookhaven National Laboratory, Upton, New York, USA. Thermonuclear reaction rates of importance to stellar explosions, such as novae, x-ray bursts and supernovae, were evaluated as well. This effort was closely coupled to our ongoing experimental effort, which took advantage of radioactive ion beam and stable beam facilities worldwide to study these key reaction rates. This report contains brief descriptions of the various activities together with references to all the publications in peer-reviewed journals which were the result of work carried out with the award DE-FG02-98-ER41080, during 1998-2013.

Chen, Alan↗
NASA NTRS1991

Ulysses spacecraft control and monitoring system

The baseline Ulysses spacecraft control and monitoring system (SCMS) concepts and the converted SCMS, residing on a DEC/VAX 8350 hardware, are considered. The main functions of the system include monitoring and displaying spacecraft telemetry, preparing spacecraft commands, producing hard copies of experimental data, and archiving spacecraft telemetry. The SCMS system comprises over 20 subsystems ranging from low-level utility routines to the major monitoring and control software. These in total consist of approximately 55,000 lines of FORTRAN source code and 100 VMS command files. The SCMS major software facilities are described, including database files, telemetry processing, telecommanding, archiving of data, and display of telemetry.

Hamer, P. A.↗
DOE OSTI2018

Multi-Physics Simulations for Molten Salt Reactor Evaluation: Chemistry Modeling and Database Development

To aid in design and licensing of molten salt reactors, a framework integrating the complex interaction of reactor neutronics, thermal hydraulics, and chemistry is being developed within the Department of Energy Advanced Reactor Technology Program’s Molten Salt Reactor (MSR) campaign. The challenges of integrating thermochemical and thermophysical behavior into a multi-physics reactor simulations include the following: (1) population of data needed for refinement of current models and development of nonexistent models through experimental measurements, first principles calculations, and development of a machine learning approach (2) thermochemical and thermophysical model development, (3) further development of Thermochimica, an open-source efficient equilibrium solver used to link thermochemical models to the multi-physics code, (4) a framework for integrating kinetic phenomena: nucleation, precipitation, mass/heat transport, and corrosion models, and (5) a computational environment to efficiently utilize the data and models within a multi-physics modeling tool. These challenges are being addressed through a collaboration among Oak Ridge National Laboratory, Argonne National Laboratory, the University of South Carolina, and the University of Ontario Institute of Technology.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Learning View-Invariant Features for Person Identification in Temporally Synchronized Videos Taken by Wearable Cameras

In this paper, we study the problem of Cross-View Person Identification (CVPI), which aims at identifying the same person from temporally synchronized videos taken by different wearable cameras. Our basic idea is to utilize the human motion consistency for CVPI, where human motion can be computed by optical flow. However, optical flow is view-variant - the same person's optical flow in different videos can be very different due to view angle change. In this paper, we attempt to utilize 3D human-skeleton sequences to learn a model that can extract view-invariant motion features from optical flows in different views. For this purpose, we use 3D Mocap database to build a synthetic optical flow dataset and train a Triplet Network (TN) consisting of three sub-networks: two for optical flow sequences from different views and one for the underlying 3D Mocap skeleton sequence. Finally, sub-networks for optical flows are used to extract view-invariant features for CVPI. Experimental results show that, using only the motion information, the proposed method can achieve comparable performance with the state-of-the-art methods. Further combination of the proposed method with an appearance-based method achieves new state-of-the-art performance.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

BCM polytype structures from DFT - Data and Resources

This dataset contains structure files and results of density functional theory (DFT) calculations for the 12R (ground state) and 10H (metastable at ambient temperature) polytypes of BaCe0.25Mn0.75O3 (BCM). Starting from the experimentally determined average crystal structures, the structures were generated by sampling of the magnetic (12R and 10H) and atomic (10H) configurations based on DFT energies.

08 HYDROGEN↗
DOE OSTI2024

Modeling and Optimization of Zeolites for Contaminant Removal from Coal Combustion Impoundment Leachates

Coal Combustion Residual (CCR) landfills in the U.S. can lead to elevated contaminant concentrations in groundwater and runoff, particularly of arsenic, boron, and selenium. Zeolites can be readily synthesized from materials contained within the coal combustion ash impoundments and can be cation-exchanged to enhance adsorption capacity, selectivity, and reactivity. However, the optimization of zeolites becomes a daunting task when accounting for the variety of Si:Al ratios, the species of extra-framework cations present, and the zeolite pore structure. Molecular simulations provide methods to study and guide the design of zeolites for the sorption of contaminants from aqueous solution. In this work, models that predict the sorption of arsenic, boron, and selenium from water using cation-exchanged zeolites. Because of the lack of experimental adsorption data for these species of contaminants, models were parametrized to reproduce the results of first-principles calculations and then used to predict sorption for zeolites for a dataset containing 6000 combinations of zeolites and sorption conditions. Machine learning was used to train a model to predict sorption for materials in this database based on the results of the molecular simulations. Next, a genetic algorithm was used to optimize zeolites for the removal of each contaminant from aqueous solution for individual impoundment sites based on contaminant concentrations reported by the Electric Power Research Institute.

Findley, John↗
NASA NTRS1998

A Summary of Validation Results for LEWICE 2.0

A research project is underway at NASA Lewis to produce a computer code which can accurately predict ice growth under any meteorological conditions for any aircraft surface. This report will present results from version 2.0 of this code, which is called LEWICE. This version differs from previous releases due to its robustness and its ability to reproduce results accurately for different point spacing, and time step criteria across general computing platforms. It also differs in the extensive amount of effort undertaken to compare the results in a quantifiable manner against the database of ice shapes which have been generated in the NASA Lewis Icing, Research Tunnel (IRT), The complete set of data used for this comparison is available in a recent contractor report . The result of this comparison shows that the difference between the predicted ice shape from LEWICE 2.0 and the average of the experimental data is 7.2% while the variability of the experimental data is 2.5%.

Wright, William B.↗
NASA NTRS2002

Drag Prediction for the DLR-F4 Wing/Body using OVERFLOW and CFL3D on an Overset Mesh

This paper reviews the importance of numerical drag prediction in an aircraft design environment. A chronicle of collaborations between the authors and colleagues is discussed. This retrospective provides a road-map which illustrates some of the actions taken in the past seven years in pursuit of accurate drag prediction. The advances made possible through these collaborations have changed the manner in which business is conducted during the design of all-new aircraft. The subject of this study is the DLR-F4 wing/body transonic model. Specifically, the work conducted herein was in support of the 1st CFD Drag Prediction Workshop, which was held in conjunction with the 19th Applied Aerodynamics Conference in Anaheim, CA during June, 2001. Comprehensive sets of OVERFLOW simulations were independently performed by several users on a variety of computational platforms. CFL3D was used on a limited basis for additional comparison on the same overset mesh. Drag polars based on this database were constructed with a CFD-to-Test correction applied and compared with test data from three facilities. These comparisons show that the predicted drag polars fall inside the scatter band of the test data, at least for pre-buffet conditions. This places the corrected drag levels within 1% of the averaged experimental values. At the design point, the OVERFLOW and CFL3D drag predictions are within 1-2% of each other. In addition, drag-rise characteristics and a boundary of drag-divergence Mach number are presented.

Vassberg, John C.↗
NASA NTRS1998

Wind-Tunnel Evaluation of the Effect of Blade Nonstructural Mass Distribution on Helicopter Fixed-System Loads

This report provides data obtained during a wind-tunnel test conducted to investigate parametrically the effect of blade nonstructural mass on helicopter fixed-system vibratory loads. The data were obtained with aeroelastically scaled model rotor blades that allowed for the addition of concentrated nonstructural masses at multiple locations along the blade radius. Testing was conducted for advance ratios ranging from 0.10 to 0.35 for 10 blade-mass configurations. Three thrust levels were obtained at representative full-scale shaft angles for each blade-mass configuration. This report provides the fixed-system forces and moments measured during testing. The comprehensive database obtained is well-suited for use in correlation and development of advanced rotorcraft analyses.

ARES-1(AEROELASTIC ROTOR EXPERIMENTAL SYSTEM 1)↗
NASA NTRSDate not supplied

Critical Heat Flux of Liquid Hydrogen, Liquid Methane, and Liquid Oxygen: A Review of Available Data and Predictive Tools

Available experimental data dealing with critical heat flux (CHF) of liquid hydrogen (LH 2 ), liquid methane (LCH 4 ), and liquid oxygen (LO 2 ) in pool and flow boiling are compiled. The compiled data are compared with widely used correlations. Experimental pool boiling CHF data for the aforementioned cryogens are scarce. Based on only 25 data points found in five independent sources, the correlation of Sun and Lienhard (1970) is recommended for predicting the pool CHF of LH 2 . Only two experiments with useful CHF data for the pool boiling of LCH 4 could be found. Four different correlations including the correlation of Lurie and Noyes (1964) can predict the pool boiling CHF of LCH 4 within a factor of two for more than 70% of the data. Furthermore, based on the 19 data points taken from only two available sources, the correlation of Sun and Lienhard (1970) is recommended for the prediction of pool CHF of LO 2 . Flow boiling CHF data for LH 2 could be found in seven experimental studies, five of them from the same source. Based on the 91 data points, it is suggested that the correlation of Katto and Ohno (1984) be used to predict the flow CHF of LH 2 . No useful data could be found for flow boiling CHF of LCH 4 or LO 2 . The available databases for flow boiling of LCH 4 and LO 2 are generally deficient in all boiling regimes. This deficiency is particularly serious with respect to flow boiling.

Multi-Phase Flow↗
DOE OSTI2025

Ca X ML: Chemistry‐informed machine learning explains mutual changes between protein conformations and calcium ions in calcium‐binding proteins using structural and topological features

Proteins' flexibility is a feature in communicating changes in cell signaling instigated by binding with secondary messengers, such as calcium ions, associated with the coordination of muscle contraction, neurotransmitter release, and gene expression. When binding with the disordered parts of a protein, calcium ions must balance their charge states with the shape of calcium-binding proteins and their versatile pool of partners depending on the circumstances they transmit. Accurately determining the ionic charges of those ions is essential for understanding their role in such processes. However, it is unclear whether the limited experimental data available can be effectively used to train models to accurately predict the charges of calcium-binding protein variants. Here, we developed a chemistry-informed, machine-learning algorithm that implements a game theoretic approach to explain the output of a machine-learning model without the prerequisite of an excessively large database for high-performance prediction of atomic charges. We used the ab initio electronic structure data representing calcium ions and the structures of the disordered segments of calcium-binding peptides with surrounding water molecules to train several explainable models. Network theory was used to extract the topological features of atomic interactions in the structurally complex data dictated by the coordination chemistry of a calcium ion, a potent indicator of its charge state in protein. Our design created a computational tool of Ca X ML, which provided a framework of explainable machine learning model to annotate ionic charges of calcium ions in calcium-binding proteins in response to the chemical changes in an environment. Our framework will provide new insights into protein design for engineering functionality based on the limited size of scientific data in a genome space.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Designing shape-memory-like microstructures in intercalation materials

During the reversible insertion of ions, lattices in intercalation materials undergo structural transformations. These lattice transformations generate misfit strains and volume changes that, in turn, contribute to the structural decay of intercalation materials and limit their reversible cycling. In this paper, we draw on insights from shape-memory alloys, another class of phase transformation materials, that also undergo large lattice transformations but do so with negligible macroscopic volume changes and internal stresses. We develop a theoretical framework to predict structural transformations in intercalation compounds and identify crystallographic design rules necessary for forming shape-memory-like microstructures in intercalation materials. We use our approach to systematically screen open-source structural databases comprising $n$ > 5000 pairs of intercalation compounds. We identify candidate compounds, such as Li x Mn 2 O 4 (Spinel), Li x Ti 2 (PO 4 ) 3 (NASICON), that approximately satisfy the crystallographic design rules and can be precisely doped to form shape-memory-like microstructures. Throughout, we compare our analytical results with experimental measurements of intercalation compounds. We find a direct correlation between structural transformations, microstructures, and increased capacity retention in these materials. These results, more generally, show that crystallographic designing of intercalation materials could be a novel route to discovering compounds that do not decay with continuous usage.

36 MATERIALS SCIENCE↗
DOE OSTI2020

First-principles study on structural mechanical and thermodynamic properties of HfMoTaTiZr

This study calculates the phase diagram of HfMoTaTiZr using the TCHEA1 database in Thermo-Calc software. Furthermore, it also investigates the structural and mechanical properties of HfMoTaTiZr by applying first-principles calculations. The elastic and other mechanical properties such as Young’s modulus, pugh ratio, hardness, bulk modulus was derived and discussed. These parameters were found to be in good harmony with previously available experimental reports. Vickers hardness of HfMoTaTiZr predicted from the Tians model agrees with the available experimental result. This study also investigates the thermal coefficient of linear expansion and vibrational heat capacity of the HfMoTaTiZr using the Debye–Grüneisen theory.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Using synthetic infrared spectra derived from n/k optical constants for standoff detection of chemical deposits

We report results from a recent field experiment to test the validity of using physics-based synthetic infrared spectra to serve as endmembers in a spectral database targeted at chemical deposits. Specifically, the optical constants n and k, (the real and imaginary part of the refractive index) were used to first model infrared reflectance spectra for different thicknesses of chemical layers (e.g. acetaminophen, methylphosphonic acid – MPA, etc.) on various conducting and insulating substrates such as aluminum, wood, and glass. In the experimental portion of the research, thin films of the solid and liquid analytes were deposited onto such substrates to form micron-thick layers of the analytes at different thicknesses: Standoff data from an imaging instrument were then recorded and analyzed to not only identify the different analytes, but also quantify the layer/deposit thickness. To gauge success, the detection results using the synthetic data were compared to the results from hemispherical reflectance (HRF) spectra that were collected for the same sample planchets measured in the field via standoff methods. Preliminary results indicate good agreement between the synthetic reference data as compared to the lab-measured HRF data in terms of their ability to quantitatively reduce longwave infrared data. Specifically, modeled IR spectra for acetaminophen on an aluminum planchet at various thicknesses (1, 2, 5, 10, 15, and 20 µm) were synthesized and compared with standoff field reflectance data as well as HRF laboratory reflectance spectra for two samples: a 5.2 µm- and 12.8 µm-thick layer of acetaminophen on aluminum. Using a first-order approximation, analysis of the field data estimates the thicknesses of the samples to be 2 and 10 µm for the two samples, respectively, while the HRF laboratory data yields thickness estimates of between 5-10 µm and 10 µm, respectively. Both yield reasonable estimates, with the uncertainty most likely due to factors yet to be accounted for in the synthetic spectra such as light scattering.

complex index of refraction, optical constants, hy↗
DOE OSTI2014

Automated identification of retinal vessels using a multiscale directional contrast quantification (MDCQ) strategy

Purpose: A novel algorithm is presented to automatically identify the retinal vessels depicted in color fundus photographs. Methods: The proposed algorithm quantifies the contrast of each pixel in retinal images at multiple scales and fuses the resulting consequent contrast images in a progressive manner by leveraging their spatial difference and continuity. The multiscale strategy is to deal with the variety of retinal vessels in width, intensity, resolution, and orientation; and the progressive fusion is to combine consequent images and meanwhile avoid a sudden fusion of image noise and/or artifacts in space. To quantitatively assess the performance of the algorithm, we tested it on three publicly available databases, namely, DRIVE, STARE, and HRF. The agreement between the computer results and the manual delineation in these databases were quantified by computing their overlapping in both area and length (centerline). The measures include sensitivity, specificity, and accuracy. Results: For the DRIVE database, the sensitivities in identifying vessels in area and length were around 90% and 70%, respectively, the accuracy in pixel classification was around 99%, and the precisions in terms of both area and length were around 94%. For the STARE database, the sensitivities in identifying vessels were around 90% in area and 70% in length, and the accuracy in pixel classification was around 97%. For the HRF database, the sensitivities in identifying vessels were around 92% in area and 83% in length for the healthy subgroup, around 92% in area and 75% in length for the glaucomatous subgroup, around 91% in area and 73% in length for the diabetic retinopathy subgroup. For all three subgroups, the accuracy was around 98%. Conclusions: The experimental results demonstrate that the developed algorithm is capable of identifying retinal vessels depicted in color fundus photographs in a relatively reliable manner.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

A 1:8.7 Scale Water Tunnel Verification & Validation Test of an Axial Flow Water Turbine

As interest in waterpower technologies has increased over the last few years, there has been a growing need for a public database of measured data for these devices. This would provide a basic understanding of the technology and means to validate analytic and numerical models. Through collaboration between Sandia National Laboratories, Penn State University Applied Research Laboratory, and University of California, Davis, a new marine hydrokinetic turbine rotor was designed, fabricated at 1:8.7-scale, and experimentally tested to provide an open platform and dataset for further study and development. The water tunnel test of this three-bladed, horizontal-axis rotor recorded power production, blade loading, near-wake characterization, cavitation effects, and noise generation. This report documents the small-scale model test in detail and provides a brief discussion of the rotor design and an initial look at the results with comparison against low-order modeling tools. Detailed geometry and experimental measurements are released to Sandia National Laboratories as a data report addendum.

13 HYDRO ENERGY↗