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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Energy Finite Element Analysis for Computing the High Frequency Vibration of the Aluminum Testbed Cylinder and Correlating the Results to Test Data

The Energy Finite Element Analysis (EFEA) is a finite element based computational method for high frequency vibration and acoustic analysis. The EFEA solves with finite elements governing differential equations for energy variables. These equations are developed from wave equations. Recently, an EFEA method for computing high frequency vibration of structures either in vacuum or in contact with a dense fluid has been presented. The presence of fluid loading has been considered through added mass and radiation damping. The EFEA developments were validated by comparing EFEA results to solutions obtained by very dense conventional finite element models and solutions from classical techniques such as statistical energy analysis (SEA) and the modal decomposition method for bodies of revolution. EFEA results have also been compared favorably with test data for the vibration and the radiated noise generated by a large scale submersible vehicle. The primary variable in EFEA is defined as the time averaged over a period and space averaged over a wavelength energy density. A joint matrix computed from the power transmission coefficients is utilized for coupling the energy density variables across any discontinuities, such as change of plate thickness, plate/stiffener junctions etc. When considering the high frequency vibration of a periodically stiffened plate or cylinder, the flexural wavelength is smaller than the interval length between two periodic stiffeners, therefore the stiffener stiffness can not be smeared by computing an equivalent rigidity for the plate or cylinder. The periodic stiffeners must be regarded as coupling components between periodic units. In this paper, Periodic Structure (PS) theory is utilized for computing the coupling joint matrix and for accounting for the periodicity characteristics.

Vlahopoulos, Nickolas↗
NASA NTRS2000

Shipping Monitor

Through a SBIR contract between Kennedy Space Center and Silicon Designs, came the tri-axial data acquisition system, known commercially as the G-Logger. It is a portable, self-contained device that stores and analyzes shock, vibration, and temperature data during payload transport. It is sealed for protection from the weather and can be left unattended for up to three weeks as it collects data. It can easily be linked with any desktop or laptop computer in order to download the collected data. It serves uses in the automotive, shipping, aerospace, and machining industries.

Source record↗
NASA NTRS1966

Single sideband FM telemetry.

Single-sideband FM for data transmission on vibration and acoustic measurements, noting SNR PERFORMANCE, transmission link, etc

FREQUENCY MODULATION↗
NASA NTRS1976

Electric dipole moment function of the X1 Sigma/+/ state of CO - Vibration-rotation matrix elements for transitions of gas laser and astrophysical interest

The electric dipole moment function of the ground electronic state of carbon monoxide has been determined by combining numerical solutions of the radial Schrodinger equation with absolute intensity data of vibration-rotation bands. The derived dipole moment function is used to calculate matrix elements of interest to stellar astronomy and of importance in the carbon monoxide laser.

Chackerian, C., Jr.↗
NASA NTRS2009

Using the Saturn V and Titan III Vibroacoustic Databanks for Random Vibration Criteria Development

This is an update to TN D-7159, "Development and Application of Vibroacoustic Structural Data Banks in Predicting Vibration Design and Test Criteria for Rocket Vehicle Structures", which was originally published in 1973. Errors in the original document have been corrected and additional data from the Titan III program have been included. Methods for using the vibroacoustic databanks for vibration test criteria development are shown, as well as all of the data with drawings and pictures of the measurement locations. An Excel spreadsheet with the data included is available from the author.

Ferbee, R C.↗
NASA NTRS2004

Healthwatch-2 System Overview

Healthwatch-2 (HW-2) is a research tool designed to facilitate the development and testing of in-flight health monitoring algorithms. HW-2 software is written in C/C++ and executes on an x86-based computer running the Linux operating system. The executive module has interfaces for collecting various signal data, such as vibration, torque, tachometer, and GPS. It is designed to perform in-flight time or frequency averaging based on specifications defined in a user-supplied configuration file. Averaged data are then passed to a user-supplied algorithm written as a Matlab function. This allows researchers a convenient method for testing in-flight algorithms. In addition to its in-flight capabilities, HW-2 software is also capable of reading archived flight data and processing it as if collected in-flight. This allows algorithms to be developed and tested in the laboratory before being flown. Currently HW-2 has passed its checkout phase and is collecting data on a Bell OH-58C helicopter operated by the U.S. Army at NASA Ames Research Center.

Barszcz, Eric↗
DOE OSTI2025

Gold-Standard Chemical Database 137 (GSCDB137): A Diverse Set of Accurate Energy Differences for Assessing and Developing Density Functionals

We present GSCDB137, a rigorously curated benchmark library of 137 data sets (8377 entries) covering main-group and transition-metal reaction energies and barrier heights, (intra- and intermolecular) noncovalent interactions, dipole moments, polarizabilities, electric-field response energies, and vibrational frequencies. Legacy data from GMTKN55 and MGCDB84 have been updated to today's best reference values; redundant or low-quality points were removed, and many new, property-focused sets were added. Testing 29 popular density functional approximations (DFAs) confirms the expected Jacob's-ladder hierarchy overall but also reveals notable exceptions: functional performance for frequencies and electric-field properties correlates poorly with that for other ground-state energetics. ωB97M-V and ωB97X-V are the most balanced hybrid meta-GGA and hybrid GGA, respectively; B97M-V and revPBE-D4 lead the meta-GGA and GGA classes. Double hybrids lower mean errors by about 30% versus their hybrid analogues but demand careful frozen-core, basis set, and spin contamination treatment. GSCDB137 offers a comprehensive, openly documented platform for rigorous validation of DFA and universal machine learning potentials, and training of the next generation of exchange-correlation functionals.

Liang, Jiashu [University of California, Berkeley,↗
NASA NTRS1967

Study made of thin-walled pipe response to turbulent fluids

Report summarizes the experimental and theoretical data on the vibrational response of thin-walled pipe sections to the wall pressure field applied within them by a fully developed turbulent fluid flow. The predicted responses were in good agreement with previous data obtained.

Clinch, J. M.↗
DOE OSTI2021

Analytics-at-scale of Sensor Data for Digital Monitoring in Nuclear Plants: 2nd Annual Report

For economic reasons, the nuclear industry is witnessing premature closure of nuclear power plants, despite excellent safety records. Operations and Maintenance (O&M) activities are some of the largest costs in operating legacy light-water plants. By reducing O&M costs, nuclear energy can become more economically competitive with other energy sources. This can be achieved by leveraging machine-learning and artificial intelligence technologies to develop data-driven algorithms to better diagnose potential faults within the system. Improved accuracy of the models can lead to a reduction in unnecessary maintenance, thus reducing costs associated with parts, labor, and unnecessary planned, forced, or extended outages. To address these challenges, the goal of this project is to perform research and development in the area of digital monitoring, i.e., the application of advanced sensor technologies (particularly wireless sensor technologies) and data science based analytic capabilities, to advance online monitoring and predictive maintenance in nuclear plants and improve plant performance (efficiency gain and economic competitiveness). This report summarizes the fiscal year 2020 research progress encompassing (1) different wireless vibration sensor and data indicators used to assess the health of a plant asset; (2) development of diagnostic models for fault detection; and (3) development of prognostic models for estimating the health of the system up to 7 days ahead.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1986

Ground vibration test and flutter analysis of air sampling probe

The Dryden Flight Research Facility of NASA Ames Research Center conducted a ground vibration test and a flutter analysis of an air sampling probe that was to be mounted on a Convair 990 airplane. The probe was a steel, wing-shaped structure used to gather atmospheric data. The ground vibration test was conducted to update the finite-element model used in the flutter analysis. The analysis predicted flutter speeds well outside the operating flight envelope of the Convair 990 airplane.

Ellison, J. F.↗
NASA NTRS1986

Independent Orbiter Assessment (IOA): Analysis of the instrumentation subsystem

The results of the Independent Orbiter Assessment (IOA) of the Failure Modes and Effects Analysis (FMEA) and Critical Items List (CIL) are presented. The IOA approach features a top-down analysis of the hardware to determine failure modes, criticality, and potential critical items. To preserve independence, this analysis was accomplished without reliance upon the results contained within the NASA FMEA/CIL documentation. The independent analysis results for the Instrumentation Subsystem are documented. The Instrumentation Subsystem (SS) consists of transducers, signal conditioning equipment, pulse code modulation (PCM) encoding equipment, tape recorders, frequency division multiplexers, and timing equipment. For this analysis, the SS is broken into two major groupings: Operational Instrumentation (OI) equipment and Modular Auxiliary Data System (MADS) equipment. The OI equipment is required to acquire, condition, scale, digitize, interleave/multiplex, format, and distribute operational Orbiter and payload data and voice for display, recording, telemetry, and checkout. It also must provide accurate timing for time critical functions for crew and payload specialist use. The MADS provides additional instrumentation to measure and record selected pressure, temperature, strain, vibration, and event data for post-flight playback and analysis. MADS data is used to assess vehicle responses to the flight environment and to permit correlation of such data from flight to flight. The IOA analysis utilized available SS hardware drawings and schematics for identifying hardware assemblies and components and their interfaces. Criticality for each item was assigned on the basis of the worst-case effect of the failure modes identified.

Howard, B. S.↗
NASA NTRS1990

Modification Of Gear Teeth To Reduce Vibrations

Computer simulations yield data useful in designing for low noise. Effects of modifications in shape of gear teeth upon static transmission error and dynamic loading of gears now analyzed systematically. Design curves generated by conducting numerical simulations of dynamic effects at successive incremental modifications of gear systems operated at various applied loads. Modifications that result in minimum dynamic effect determined from design curves.

Townsend, Dennis P.↗
NASA NTRS1994

Smart accelerometer

The invention discloses methods and apparatus for detecting vibrations from machines which indicate an impending malfunction for the purpose of preventing additional damage and allowing for an orderly shutdown or a change in mode of operation. The method and apparatus is especially suited for reliable operation in providing thruster control data concerning unstable vibration in an electrical environment which is typically noisy and in which unrecognized ground loops may exist.

Bozeman, Richard J., Jr.↗
NASA NTRS1985

Topping turbine (103-JAT) rotor instability in 1150-STPD Kellogg ammonia plants

In two of Agrico's three plants, instabilities in the rotor/bearing system have been an ongoing problem. On occasion plant rates, i.e., machine speed, have been restricted in order to limit the exhaust and shaft relative vibration on the 103-JAT to a maximum value of 89 micrometer (0.0035) peak to peak. The purpose is to acquaint one with Agrico's experiences with exhaust end vibration and rotor instabilities on the 103-JAT topping turbine. The final conclusions arrived at were based on: (1) field acquired data both during steady state and transient conditions; (2) computer modeling of the rotor/bearing system; and (3) vibration data taken from a control rotor during a series of test runs in a high speed balancing machine from 0 to 110% of operating speed.

Thomas, R.↗
NASA NTRS1994

Monitoring Integrity Of Composite Aircraft Components

System developed that monitors integrity of composite-material structural components of aircraft in service. Includes strain gauges and accelerometers installed permanently in components to monitor vibrations, microprocessor-based data-acquisition system to process outputs of these vibration sensors, and desktop computer to analyze acquired data. By automating significant part of inspection process, system reduces amount of time needed for inspection and cost of inspection equipment. Contributes to safety by giving timely warning of hidden flaws that necessitate early, detailed inspection of critical components to determine whether components should be replaced immediately.

Tang, Shu Shing↗
DOE OSTI2026

Raman and Terahertz Spectroscopy of Low-Frequency Chiral Phonons in Amino Acids

Chiral phonons are mirror-symmetric vibrations with nonzero angular momenta that correspond to twisting and rotational motions of multiple atoms. In chiral crystals, these include low-energy terahertz (THz)-range vibrations of the molecular segments involving dozens of atoms with energies sensitive to molecular chirality. Here, we present spectral signatures of chiral phonons in circularly polarized Raman optical activity (ROA) spectra from enantiomers of amino acid crystals. Along with complementary THz circular dichroism (TCD) measurements, our ROA data reveal several vibrational bands in enantiomers of valine, alanine, tyrosine, and proline between 30 and 150 cm –1 (∼1–4.5 THz) that exhibit opposite intensities. Density functional theory calculations confirm their assignment to twisting and shearing molecular motions. The simultaneous registration of chiral phonon modes by ROA and TCD demonstrates the necessity of these complementary techniques to identify complex mirror-asymmetric vibrational modes and offers new insights into their interactions with circularly polarized light.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Unsupervised anomaly clustering via offset alignment in multivariate grid sensing data

Modern industries increasingly rely on multi-sensor technologies to acquire complex, high-dimensional data streams, enabling advanced monitoring and control systems. One critical application is online anomaly detection in electrical smart grids, where multivariate and multimodal sensing technologies play a vital role. However, detecting anomalies in such time-series data is challenging due to their inherent temporal dependencies and stochastic behavior. Traditional approaches based on supervised and semi-supervised learning methods depend on labeled datasets, which are often unavailable in real-world scenarios. While unsupervised methods have emerged as promising alternatives, these methods are highly susceptible to noise and outliers commonly present in sensing applications. Furthermore, deep learning-based anomaly detection methods, despite their performance, are often criticized for their black-box nature, limiting their applicability in safety-critical and online environments where interpretability and explainability are paramount. In this work, we propose an unsupervised anomaly clustering method leveraging a cyclic alignment-based offset detection algorithm for multivariate time-series signals. The proposed method is applied to multivariate data collected from vibrational, voltage, and magnetic field sensors deployed in a local grid substation. Our results demonstrate the robustness of the algorithm in accurately clustering various anomalies/events across different sensing modalities. Additionally, we compare the effectiveness of the proposed approach against a simple pattern-based anomaly detection method, which performs well for univariate data but fails to generalize to multivariate and multimodal time-series data.

Mukherjee, Subrata [ORNL] (ORCID:0000000309930338)↗