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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Periodic Trends within Actinyl(VI) Nitrates and Their Structures, Vibrational Spectra, and Electronic Properties

In this work, a series of actinyl(VI) nitrate salts of the form MAnO 2 (NO 3 ) 3 , where M = NH 4 + K + , Rb + , Cs + , and Me 4 N + and AnO 2 2+ = U, Np, Pu, and AnO 2 (NO 3 ) 2 (H 2 O) 2 ·H 2 O, and the uranyl tetranitrates M 2 UO 2 (NO 3 ) 4 have been synthesized from aqueous solution and their structures determined using single-crystal X-ray diffraction. Together, these complexes represent an isostructural series of actinide complexes among the salts crystallized with the same charge-compensating cation and have been studied using vibrational spectroscopy including Raman and Fourier-transform infrared. Periodic trends in both the structural properties of these complexes and their vibrational spectra are presented and discussed, in particular the invariant nature of the O≡An≡O asymmetric stretching frequencies observed across the actinyl series. Electronic structure calculations were performed at a variety of levels of theory to aid in the interpretation of the vibrational data and to correlate trends in the data with the underlying electronic properties of these molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Modeling Seismic Recordings of High-Frequency Guided Infrasound on Mars

NASA's Interior Exploration using Seismic Investigations, Geodesy and Heat Transport (InSight) mission records several high-frequency (>0.5 Hz) dispersive seismic signals on Mars. These signals are due to the acoustic-to-seismic coupling of infrasound generated by the entry and impact of meteorites. This dispersion property is due to infrasound propagating in a structured atmosphere, and we refer to this dispersive infrasound as guided infrasound. We propose to model the propagation of guided infrasound and the seismic coupling to the ground analytically; we use a 1D layered atmosphere on a three-layer solid subsurface medium. The synthetic ground movements fit the observed dispersive seismic signals well and the fitting indicates that the regolith beneath InSight is about 40-m in thickness. We also examine and validate the previously-published subsurface models derived from InSight ambient seismic vibration data.

58 GEOSCIENCES↗
DOE OSTI2022

Measuring nonlinearities of a cantilever beam using a low-cost efficient wireless intelligent sensor for strain (LEWIS-S)

In the context of experimental vibration data, strain gauges can obtain linear and nonlinear dynamic measurements. However, measuring strain can be disincentivizing and expensive due to the complexity of data acquisition systems, lack of portability, and high costs. This research introduces the use of a low-cost efficient wireless intelligent sensor for strain (LEWIS-S) that is based on a portable-sensor-design platform that streamlines strain sensing. Additionally, the softening behavior of a cantilever beam with geometric and inertial nonlinearities is characterized by the LEWIS-S based on high force level inputs. Two experiments were performed on a nonlinear cantilever beam with measurements obtained by the LEWIS-S sensor and an accelerometer. First, a sine sweep test was performed through the fundamental resonance of the system, then a ring-down test was performed from a large initial static deformation. Good agreement was revealed in quantities of interest such as frequency response functions, the continuous wavelet transforms, and softening behavior in the backbone curves.

42 ENGINEERING↗
DOE OSTI2023

High phase resolution: Probing interactions in complex interfaces with sum frequency generation

An often-quoted statement attributed to Wolfgang Pauli is that God made the bulk, but the surface was invented by the devil. Although humorous, the statement really reflects frustration in developing a detailed picture of a surface. In the last several decades, that frustration has begun to abate with numerous techniques providing clues to interactions and reactions at surfaces. Often these techniques require considerable prior knowledge. Complex mixtures on irregular or soft surfaces—complex interfaces—thus represent the last frontier. Two optical techniques: sum frequency generation (SFG) and second harmonic generation (SHG) are beginning to lift the veil on complex interfaces. Of these techniques, SFG with one excitation in the infrared has the potential to provide exquisite molecular- and moiety-specific vibrational data. This Perspective is intended both to aid newcomers in gaining traction in this field and to demonstrate the impact of high-phase resolution. It starts with a basic description of light-induced surface polarization that is at the heart of SFG. The sum frequency is generated when the input fields are sufficiently intense that the interaction is nonlinear. This nonlinearity represents a challenge for disentangling data to reveal the molecular-level picture. Three, high-phase-resolution methods that reveal interactions at the surface are described.

Biophysics↗
DOE OSTI2020

From Atom to Engine: Understanding Fundamental Effects of Structure on Combustion Using Tandem Experiment and Computation

The ability to tie structural features to a fuel candidate’s ignition properties provides a path for rational design of advantaged fuels that facilitate higher-efficiency, lower-emitting combustion in engines. The time evolution of a fuel’s radical population directly correlates with global combustion parameters, and because the generated radicals depend on the initial structure and reaction pathways of the fuel molecule, it follows that the molecular structure of a fuel has a direct impact on this cascade, and therefore salient ignition-tied fuel properties. This work aims to understand the impact of structural features in the context of global combustion properties for direct application to emerging engine technologies. Specifically, we highlight the ability to identify potential fuel blendstocks for specific engine strategies by examining and elucidating the radical cascade tied to ignition. A representative subset of alcohols possessing a variety of structural features (e.g. branching, chain length) was selected for study using a robust combination of experimental and computational methods. The approach begins with identifying short-lived radicals and likely abstraction sites upon pyrolysis in a microreactor coupled with photoionization mass spectrometry for direct detection of product species. In tandem, electronic structure calculations were performed to calculate the relevant potential energy surfaces for fuel pyrolysis as well as the subsequent O2 addition-isomerization reactions, which govern ignition behavior. Furthermore, the theoretical energetic and ro-vibrational data are used to calculate rate constants for direct ignition modeling to explore how structural effects impact NTC behavior. The microreactor data combined with electronic structure theory calculations provide a well-informed picture of the reactions relevant to ignition for each fuel in this study, as well as the most likely radicals generated under engine conditions. This thorough fundamental picture of fuel decomposition and ignition chemistry is used to correlate the observed ignition behavior to molecular structural effects.

advanced biofuels↗
DOE OSTI2024

Lab Scale Demonstration of Pipeline Third-Party Damage Classification Using Convolutional Neural Networks

This research aims to propose a simple experiment for third party damage classification problem by generating a dataset of third-party damage events on a laboratory scale utilizing single mode-multi mode-single mode (SMS) fiber acoustic sensor. The sound samples representative of various third-party activities, such as vehicle movements, excavation, and digging, were sourced from open-source databases. These samples were then played through a speaker in proximity to an SMS sensor, and the resultant fiber acoustic vibration data were recorded for each event. This process yielded a collection of 200 samples across 13 distinct third-party events. Convolutional Neural Networks (CNNs) were employed to classify these samples into their respective categories, and an accuracy exceeding 97% was obtained from our results.

Bukka, Sandeep Reddy↗
DOE OSTI2024

Lab-Scale Demonstration of Pipeline Third-Party Damage Classification Using Convolutional Neural Networks

This research aims to mitigate the challenges of field tests for classification of third-party damages by generating a dataset of third-party damage events on a laboratory scale utilizing single mode-multi mode-single mode (SMS) fiber acoustic sensor. The sound samples representative of various third-party activities, such as vehicle movements, excavation, and digging, were sourced from open-source databases. These samples were then played through a speaker in proximity to an SMS sensor, and the resultant fiber acoustic vibration data were recorded for each event. This process yielded a collection of 200 samples across 13 distinct third-party events. Convolutional Neural Networks (CNNs) were employed to classify these samples into their respective categories, and an accuracy exceeding 97% was obtained from our results.

Bukka, Sandeep Reddy↗
DOE OSTI2021

Field Data Analysis and Modeling of Drillstring Vibrations to Identify Inefficiency in Deep Geothermal Drilling

One challenge that hinders efficient drilling and causes downhole tool failures is severe drillstring vibrations. The objective of this paper is to identify the root cause of drillstring vibrations in deep geothermal wells and investigate their effect on drilling performance using data analytics and vibration modeling. A near-bit sub was utilized to collect vibration data, where the burst data was used to obtain the drillstring torsional natural frequency. The data showed that the highest lateral acceleration and stick-slip severities (SSS) occur at the higher mechanical specific energy (MSE) range, while the low vibration levels were encountered in the optimum range of the MSE curve. The elevated SSS levels consistently occur at the low to mid-range of applied RPM and the highest sonic velocity. Additionally, the lateral acceleration levels are higher at the low to mid-range of the applied RPM. The effect of drillstring vibration on drilling performance was recognized by the presented MSE analysis.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Vibrationally resolved ionization cross sections for the ground state and electronically excited states of the hydrogen molecule and its isotopomeres

An existing set of vibrationally resolved ionization cross section for the ground state and the first excited states of the hydrogen molecule, based on the Gryzinski method, is extended by cross sections for the isotopomeres of H{sub 2} (i.e. D{sub 2}, T{sub 2}, HD, HT, and DT), both for non-dissociative and dissociative ionizations. The comparison of cross sections for non-dissociative ionization of H{sub 2} with results obtained by the Molecular Convergent Close-Coupling method gives a very good agreement. The compiled tables give non-dissociative and dissociative cross sections for the ground state and the five energetically lowest electronically excited states of H{sub 2} and its isotopomeres, in each case for the first 9 vibrational levels. Data for all vibrational levels of the excited states is available online.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Investigation of Multiple Data Streams for Gearbox Bearing Fault Prediction Through Machine-Learning Models

Operations and maintenance (O&M) cost of wind plant accounts up to 30% of total energy cost, which can be reduced through continuous monitoring and successfully detecting incipient wind turbine failures. To accomplish this, condition monitoring and predictive maintenance systems are being implemented in wind industry to support O&M decision making. A wide range of approaches for condition monitoring and fault prediction have been developed. These approaches generally use historical data of wind turbines collected by Supervisory Control and Data Acquisition (SCADA) system to identify patterns that lead to failure. These SCADA data show the overall condition of a wind turbine and can be leveraged to detect when the turbine's performance is degrading and to identify if a fault is developing. However, it becomes challenging to predict the failure of a specific wind turbine gearbox bearing, because the SCADA data are often not directly linked to the component. To bridge the gap, we have investigated features calculated from SCADA data using physics-based models and the gearbox design over the years. The damaged metric we used in the physics domain is frictional energy. Combining these physics domain variables with SCADA data as inputs to various machine learning models for gearbox bearing fault prediction, we have demonstrated the benefits of leveraging both physics and data domain models. It was an attempt to improve frictional-energy-based damage metric by adding data domain inputs, as we had learned that the frictional-energy-based damage metric alone is not sufficient to single out failed bearings from healthy. As condition monitoring data (either vibration or oil debris data) has become available at more and more wind plants, we would like to evaluate whether by adding the condition monitoring data can help further improve the performance of frictional-energy-based damage metric for gearbox bearing fault prediction. Both cases by modeling through various machine learning algorithms are discussed in this study along with some observations.

fault prediction↗
DOE OSTI2025

Seismic monitoring of underground vibration: database of seismic data and ground truth

Seismic waves provide valuable insights into underground activities, serving as an essential tool for monitoring anomalies that could signal containment breaches in geological repositories. We aim to test and refine underground detection and geolocation techniques to identify anomalous vibration signals indicative of potential breaches, thereby strengthening georepository safeguards. We evaluate the effectiveness of two distinct, low-maintenance sensing technologies (surface geophones and underground distributed acoustic sensing (DAS) fiber optic cable) leveraging existing datasets. This report details the experimental designs, instrumentation, and data characteristics for both seismic and DAS arrays. Additionally, we provide a ground truth database documenting relevant operational activities for each experiment.

58 GEOSCIENCES↗
DOE OSTI2026

Pioneer WEC v1 Ocean Deployment

There are seven zip files of data pertaining to the Pioneer WEC v1 ocean deployment.(1-6) Pioneer multiple sensor data "Month Year".zip: contains monthly data from the majority of onboard instruments (e.g., electrical power, mechanical motion, etc.)(7) Pioneer vibration sensor data full 6 months.zip: contains data from the vibration sensor instrument for the full 6 month deployment

Ocean sensing↗
DOE OSTI2021

Optical vibrational spectra and proposed crystal structure of ε-UO 3

ε-UO 3 is an exotic polymorph in the uranium trioxide system with an undetermined crystal structure and limited optical vibrational spectroscopic data. To improve understanding of this compound, we synthesize and investigate the crystal structure and optical vibrational spectra of ε-UO 3 . Infrared spectra collected for ε-UO 3 are in good agreement with previously published results, and our studies extend the available data into the low-energy (600–100 cm –1 ) regime. For the first time, Raman spectra are presented for ε-UO 3 using both 785 and 532 nm excitation wavelengths. Previous reports suggest an impurity phase may be present in ε-UO 3 produced by calcination of U 3 O 8 ; however, spectral center-of-mass calculations, principal component analyses, and Raman spectroscopic mapping employed to investigate this possibility indicate that the product of U 3 O 8 calcined in O 3 (g) in this work is likely phase-pure. A possible novel structure solution for ε-UO 3 is determined via Rietveld refinement of powder X-ray diffraction data and is triclinic, P-1, with a = 4.01 Å, b = 3.85 Å, c = 4.18 Å, and α = 98.26°, β = 90.41°, γ = 120.46° (R wp = 8.30%). The asymmetric unit of ε-UO 3 consists of U(VI) in hexagonal bipyramidal coordination with displaced equatorial oxygen. Further analysis reveals that the structure of ε-UO3 is best described by a 2 × 1 × 2 supercell structure in P-1 with a = 8.03 Å, b = 3.86 Å, c = 8.37 Å with α = 98.26°, β = 90.41°, and γ = 120.46°, although a higher-symmetry structure is possible. Optical vibrational spectroscopic and structural measurements of ε-UO 3 presented here furthers our understanding of this complex uranium oxide and clarifies the origin of reported structural similarity to U 3 O 8 .

-UO3↗
DOE OSTI2021

Characterization data of an (AlFeNiTiVZr) 1-x Cr x multi-principal element alloy continuous composition spread library

The data provided in this article is related to the research article entitled “Phase stabilization and oxidation of a continuous composition spread multi-principal element (AlFeNiTiVZr) 1-x Cr x alloy”. This data article describes the high-throughput synthesis and characterization processes of an (AlFeNiTiVZr) 1-x Cr x alloy system. Continuous composition spread (CCS) thin-film libraries were synthesized by co-depositing an AlFeNiTiVZr metal alloy target and Cr target via magnetron sputtering. Post-processing was performed on the sample libraries with a vacuum anneal at 873 K and an air anneal at 873 K. Compositional data was determined via WDS in order to verify parameters provided by an in-house sputter model. Crystallographic data was captured via synchrotron diffraction and diffractograms were compared as a function of the change in Cr concentration. These measurements were taken in order to observe phase behavior after oxidation throughout the composition library. Furthermore, vibrational spectrographic data is provided of the oxidized library to show surface speciation along the composition gradient of the alloy system. The structural and oxidative behavior of the (AlFeNiTiVZr) 1-x Cr x alloy can be analysed using the data provided in this article. Additionally, this characterization dataset can be utilized in machine learning algorithms for determining important features and parameters for future hypothesis generation of functional multi-principal element alloys (MPEAs).

36 MATERIALS SCIENCE↗
DOE OSTI2021

Collective Vibrational Strong Coupling Effects on Molecular Vibrational Relaxation and Energy Transfer: Numerical Insights via Cavity Molecular Dynamics Simulations**

Abstract For a small fraction of hot CO 2 molecules immersed in a liquid‐phase CO 2 thermal bath, classical cavity molecular dynamics simulations show that forming collective vibrational strong coupling (VSC) between the C=O asymmetric stretch of CO 2 molecules and a cavity mode accelerates hot‐molecule relaxation. This acceleration stems from the fact that polaritons can be transiently excited during the nonequilibrium process, which facilitates intermolecular vibrational energy transfer. The VSC effects on these rates 1) resonantly depend on the cavity mode detuning, 2) cooperatively depend on Rabi splitting, and 3) collectively scale with the number of hot molecules. For larger cavity volumes, the average VSC effect per molecule can remain meaningful for up to N ≈10 4 molecules forming VSC. Moreover, the transiently excited lower polariton prefers to relax by transferring its energy to the tail of the molecular energy distribution rather than distributing it equally to all thermal molecules. As far as the parameter dependence is concerned, the vibrational relaxation data presented here appear analogous to VSC catalysis in Fabry–Pérot microcavities.

Li, Tao E.↗
DOE OSTI2021

Collective Vibrational Strong Coupling Effects on Molecular Vibrational Relaxation and Energy Transfer: Numerical Insights via Cavity Molecular Dynamics Simulations**

Abstract For a small fraction of hot CO 2 molecules immersed in a liquid‐phase CO 2 thermal bath, classical cavity molecular dynamics simulations show that forming collective vibrational strong coupling (VSC) between the C=O asymmetric stretch of CO 2 molecules and a cavity mode accelerates hot‐molecule relaxation. This acceleration stems from the fact that polaritons can be transiently excited during the nonequilibrium process, which facilitates intermolecular vibrational energy transfer. The VSC effects on these rates 1) resonantly depend on the cavity mode detuning, 2) cooperatively depend on Rabi splitting, and 3) collectively scale with the number of hot molecules. For larger cavity volumes, the average VSC effect per molecule can remain meaningful for up to N ≈10 4 molecules forming VSC. Moreover, the transiently excited lower polariton prefers to relax by transferring its energy to the tail of the molecular energy distribution rather than distributing it equally to all thermal molecules. As far as the parameter dependence is concerned, the vibrational relaxation data presented here appear analogous to VSC catalysis in Fabry–Pérot microcavities.

Li, Tao E.↗