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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Quantifying the Influence of Redox Conditions on the Seismic Properties of Olivine

A series of eight olivine specimens were fabricated by hot-pressing at 1200 degrees Celsius and 300 megapascals (MPa). Each hot-pressed specimen was then wrapped in Pt, Ni or NiFe foil to vary oxygen fugacity (fO2), and interrogated via forced torsional oscillation. Mechanical testing was conducted at 10 oscillation periods between 1 and 1000 seconds, at a confining pressure of 200 MPa, during a slow staged-cooling from a maximum temperature of 1200 degrees Celsius to room temperature. After mechanical testing, each specimen was axially sectioned and EBSD (Electron BackScatter Diffraction) was used for the determination of the representative grain size, and grain size distribution of each sample. In addition, each longitudinal section was mapped via FTIR (Fourier Transform InfraRed spectroscopy) to determine the spatial distribution and concentrations of chemically bound and molecular water. Amongst these specimens, chemically bound ‘water’ contents were observed to vary between 0 and 1150 atom ppm (parts per million) H/Si, and molecular water concentrations varied between 0 and 245 atom ppm H/Si. Our forced-oscillation results demonstrate that the measured magnitude of anelastic relaxation within the experimental ‘window’ of oscillation periods is unrelated to the water content. Rather, a relationship was observed between the magnitude of anelastic relaxation and the prevailing redox conditions, which is influenced by the choice of metal sleeving used during the mechanical test. Further, regardless of water content or metal sleeving, each specimen exhibits coupled variations in shear modulus and dissipation within the observational window, indicative of ‘high-temperature background’ behavior, that can be described by a Burgers-type model. During initial fitting of the Burgers models, the unrelaxed shear modulus at a reference temperature of 900 degrees Celsius (G (sub UR)) and the temperature derivative of the unrelaxed shear modulus (dG (sub U)/dT), were treated as adjustable parameters. For all Fe-bearing olivine samples (but not a hydrous and oxidized Fe-free sample) we observe deficits of G (sub UR), and increased values of dG (sub U)/dT, relative to the expected elastic (anharmonic) behavior of Fo90 olivine. This behavior is indicative of anelastic relaxation occurring at shorter periods than observable within the ‘window’ of oscillation periods used in the mechanical test. Moving towards a comprehensive seismologically applicable Burgers model, which includes this newly observed effect of redox conditions on anelastic relaxation, we will present our progress in reconciling truly anharmonic and elastic behavior of Fo (sub 90) olivine with our observed forced-oscillation data.

Cline, Christopher, II↗
NASA NTRS2019

The Influence of Redox Conditions on the Seismic Properties of Polycrystalline Olivine

Eight olivine specimens were fabricated by use of a solgel method and hot-pressing at 1200 degrees Centigrade and 300 megapascals (MPa) inside of welded Pt capsules. Each hot-pressed specimen was then recovered, precision ground, and wrapped in Pt, Ni or NiFe foil to vary oxygen fugacity (fO2) during the subsequent forced torsional oscillation measurements. Mechanical testing was conducted at 10 oscillation periods between 1 and 1000 seconds, at a confining pressure of 200 MPa, during a slow staged-cooling from a maximum temperature of 1200 degrees Centigrade down to room temperature. After mechanical testing, each specimen was axially sectioned and EBSD (Electron BackScatter Diffraction) was used for the determination of the representative grain size, and grain size distribution of each sample. In addition, each longitudinal section was mapped via FTIR (Fourier Transform Infrared Spectroscopy) to determine the spatial distribution and concentrations of chemically bound and molecular water. Amongst these eight specimens, chemically bound ‘water’ contents were observed to vary between 0 and 1150 atom parts per million (ppm) H/Si, and molecular water concentrations varied between 0 and 245 atom ppm H/Si. Our forced-oscillation results demonstrate that the measured magnitude of anelastic relaxation within the experimental ‘window’ of oscillation periods is unrelated to the water content. Rather, a relationship was observed between the magnitude of anelastic relaxation and the prevailing redox conditions, which is influenced by the choice of metal sleeving used during the mechanical test. Further, regardless of water content or metal sleeving, each specimen exhibits coupled variations in shear modulus and dissipation within the observational window, indicative of ‘high-temperature background’ behavior, that can be described by a Burgers-type model. During initial fitting of the Burgers models, the unrelaxed shear modulus at a reference temperature of 900°C (elastic unloading/reloading shear modulus G (sub UR)) and the temperature derivative of the unrelaxed shear modulus (dGU/dT), were treated as adjustable parameters. For all Fe-bearing olivine samples we observe deficits of G (sub UR) and increased values of dGU/dT, relative to the expected elastic (anharmonic) behavior for Fo (Forsterite content percentage) (sub 90) olivine. This behavior is indicative of anelastic relaxation occurring at shorter periods than observable within the ‘window’ of oscillation periods used in the mechanical test. Moving towards a comprehensive and seismologically applicable Burgers model, which includes this newly observed effect of redox conditions on anelastic relaxation, we will present our progress on reconciling truly anharmonic and elastic behavior of Fo (sub 90) olivine with our observed forced-oscillation data.

Cline, C. J., II↗
NASA NTRS2020

Molecular Simulations of Ultrafast Radiation Induced Melting at Metal-Semiconductor Interfaces

Understanding radiation induced ultrafast melting at material interfaces is essential in designing robust electronic devices for aviation/space applications and in laser machining. While it is difficult to achieve the spatial and temporal resolution required to quantify the phenomenon experimentally, simulations can provide the detailed mechanisms of the structural changes that happen during phase transition. In this work, we use molecular simulations to study the effect of radiation damage on silicon carbide (SiC) - tungsten (W) interfaces which is of interest in high power electronics. A multi-scale approach is involved wherein the reactions at the interfaces are quantified using ab-initio molecular dynamics (MD) simulations and classical MD simulations are employed to understand the structural and diffusional changes across the material interface. Finally, coarse-grained Lennard-Jones type models are used to study the larger scale mechanisms and structures obtained due to the induced damages. We show that the response of the material to radiation damage depends on factors such as energy of the incident radiation, thermal properties, and molecular structure of the material.

Ravichandran, Ashwin↗
NASA NTRSDate not supplied

Comparison of Prediction Modeling Methodologies for Aeroacoustic Characterization of Hovering sUAS Rotors

This work compared artificial neural network and multivariate orthogonal function modeling methodologies for the prediction and characterization of isolated hovering sUAS rotor aerodynamics and aeroacoustics. Design of Experiments was used to create input feature spaces over 9 input features: the number of rotor blades, rotor size, rotor speed, the amount of blade twist, blade taper ratio, tip chord length, collective pitch, airfoil camber, and airfoil thickness. CAMRAD~II and AARON were executed at the points defined by the input feature space to predict aerodynamic and aeroacoustic quantities. These predicted aerodynamic and aeroacoustic data were then used to generate artificial neural networks and polynomial response surface models. The two prediction model methodologies were evaluated over test data previously unseen by the models, which showed good prediction capabilities for both model types, with slightly lower prediction error for the artificial neural networks. A characterization study was performed, which showed that input features correspondent to the spanwise sectional blade lift and drag were the most significant factors to the aerodynamic thrust and power, respectively. It was also shown that the aeroacoustic quantities were highly dependent on variations in rotor speed and size, which affect the Doppler factor for tonal noise and the spanwise Reynolds number for broadband noise.

Christopher S Thurman↗
DOE OSTI2020

Tritium Transport Phenomena in Molten-Salt Reactors

In this work, we review phenomena relevant to tritium transport in molten-salt reactors, which produce tritium from lithium and beryllium salts at significantly higher levels than other reactor types. Modeling of such phenomena began following MSRE operations, and these early models attempted to predict measured tritium distributions in the MSRE, accounting for turbulent mass-transport processes (using established heat transfer correlations), permeation through a variety of metal structures such as heat exchanger tubes, and transport to and from bubbles introduced into the salt by gas sparging. The models reasonably reproduced the MSRE data, but did so best when the permeability of structures was reduced by about a factor of 1,000. This issue does not appear to have been conclusively resolved, and all of the more recent attempts to model tritium transport in molten salts appear to make use of the same methodology. MSRE remains, however, essentially our only source of integral tritium transport data relevant to MSRs. Here, we generalize the MSRE approach to permeation in order to include potential rate-limiting effects at interfaces, as well the effects of added hydrogen. Appropriately non-dimensionalized, this system of equations identifies two dimensionless numbers whose relative values clearly delineate the conditions under which mass transport, surface effects, permeation, and hydrogen swamping are expected to become rate-limiting. We also describe the preliminary conceptual design of a forced convection FLiBe loop, into which tritium would be introduced for the purpose of providing validation data for such a model. The primary purpose of this is to investigate the coupled transport phenomena described above and identify those that are rate-limiting in MSRs. Additional test section configurations are described that would address other transport phenomena relevant to MSRs, including bubbly flows and graphite interactions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Detecting Process Equipment Failures Using Acoustic Data and Machine Learning

Nuclear power plant (NPP) process equipment such as fans, motors, valves, and pumps generate frequent or continuous noise, and deviations from the normal operational sounds made by this equipment can indicate potential issues. These deviations can be identified via automated acoustic anomaly detection, which involves using acoustic sensors (i.e., microphones) alongside detection algorithms to continuously monitor for changes in acoustic signatures. This task is made challenging by the substantial background noise that exists, such as operators opening and closing doors, manipulating valves, and conversing—in addition to typical plant noises. In collaboration with a nuclear power utility partner, this effort assessed the efficacy of acoustic anomaly detection when using a specific acoustic sensor that compresses data into a fixed set of features that are transferable over a standard Internet of Things communication protocol, thereby improving usability but potentially degrading detection performance. Two methods of performing automated acoustic anomaly detection were evaluated: one-class support vector machine (OC-SVM) and isolation forest (iForest). To enable the use of high-quality acoustic data encompassing both normal and anomalous conditions, the study utilized the publicly available Malfunctioning Industrial Machine Investigation and Inspection dataset, which includes real measured acoustic sensor data for a range of equipment types, model numbers, and signal-to-noise ratios (SNRs), along with a benchmark set of detection results. Using this dataset, the methods were tested and then compared against the benchmark results. The results indicated that although the specific acoustic sensor did not enable as rich a feature set extraction, the proposed methods with the limited feature set performed just as well. This provides solid justification for both the methods and the use of the proposed acoustic sensor.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2026

Neural Scaling Laws for Jet Generation

Recently observed empirical scaling laws describe the performance of foundation-type models as three independent key quantities -- dataset size, compute, and model parameters -- are modified. Extracting these scaling laws informs the training of large complex models for which the tuning of hyperparameters in traditional ways is not feasible. This work for the first time explores if scaling laws can also be observed for the task of particle jet generation -- both relevant as a pre-training objective for foundation models and as in-situ simulation by itself. We indeed replicate the key logarithmic scaling law behavior for model-size scaling. Beyond studying the next token prediction validation loss of the generative model, we also study the sliced Wasserstein distance of five physical quantities that are not immediately available to the model during training. Our study shows that this quantity is monotonically related to the next token prediction validation loss, meaning that this loss is indeed a good proxy for the physics performance. For the scaling with dataset size and compute, we observe substantially weaker scaling behavior of both the loss and the sliced Wasserstein distance. We analyze this behavior by introducing the concept of a learnable window, and argue that autoregressive next token prediction on jet constituents exhibits comparatively rapid saturation relative to language-model studies. We discuss possible origins of this behavior, including the stochastic nature of QCD radiation and differences between generative and supervised learning tasks in collider physics.

Amram, Oz [Fermilab]↗
DOE OSTI2023

Modeling diffusion and types I-V sorption of water vapor in heterogeneous systems

Here, a sorption and diffusion model is developed using a mobile-immobile decomposition of the vapor concentration. Henry’s mode represents the mobile species which diffuses through the solid, while Langmuir and pooling modes represent possible immobilization processes that cause nonlinearities in sorption capacity. The model can simulate the five classical sorption types and can incorporate additional dynamics compared to models based on thermodynamic equilibrium. Additionally, the framework allows for discontinuities in material properties encountered in multi-material systems. The resulting non-linear coupled equations are solved by employing a finite element method to discretize in space, and a backward Euler method to discretize in time. The discretized system of equations is solved via a Newton-type iteration scheme at each time-step. Four different materials are parameterized for the model, which are then used in examples to demonstrate the model’s ability to capture complex sorption processes in multi-material systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1993

Origin of the Apollo 15 very low Ti green glass. A perspective from the compositional diversity in the very low Ti glasses

The very low Ti green glasses from the Apollo 15 site have intrigued scientists for over 20 years. Their primitive composition has been used to understand magmatic processes and the structure of the moon. The compositional variability observed in the Apollo 15 glass population has long been a point of debate. Initial studies did not recognize the compositional diversity in the glasses. Stolper et al. documented the major element variability and concluded it could not be produced by magmatic processes and therefore concluded that these glasses must be of impact origin. Subsequent studies confirmed a volcanic origin for the glass population and attempted to elucidate magmatic processes to account for its compositional variability. Models that have been proposed for these glasses include the following: (1) the crystallization of single or multiple phases (olivine, pyroxene, Fe metal, immiscible sulfide); (2) the incompatible behavior of Ni and Co during multiple phase crystallization at extremely low fO2; and (3) magma or source mixing. All of these models have problems. Type (1) models appear not to be consistent with recent trace element studies on the glasses; model (2) is dependent on the debatable incompatible behavior of Ni and Co, and, in models of type (3), the origin and nature of mixing models are somewhat unconstrained. This study compares the Apollo 15 green glasses with the very low Ti picritic glasses from other landing sites.

Shearer, C. K.↗
NASA NTRS1993

Spectra of low-mass helium star models and the type Ic supernova SN 1987M

The question of whether the low-mass helium star models reproduce the helium-poor Type Ic spectrum of SN 1987M is investigated by comparing the theoretical spectrum from the 3.3-solar-mass model of Shigeyama et al. (1990) to observations of SN 1987M reported by Filippenko et al. (1990). The results indicate a number of positive correlations between the observed and the computed spectra. In both types of spectra, Ca II, O I, and Mg I emission lines dominate at late times, and, if extensive composition mixing is imposed, good fits can be made to the shapes of the emission features and good agreement can be found with the observed ratio of the forbidden and IR triplet blends of Ca II. The former indicates that the 3.3-solar-mass model predicts the proper density/velocity structure, and the latter indicates that the computed temperature structure is consistent with the observation though the lines are too strong relative to the continuum. This result is roughly independent of the He abundance. The computed and observed spectra are consistent with a small Ni-56 production in contrast to Type Ia thermonuclear events whose spectra are dominated by Fe-group lines at late times.

Swartz, Douglas A.↗
DOE OSTI2022

Extension of the Generic Multi-Frequency Modelling Method for Type 3 Wind Turbines

Reflecting potential non-linearities of converter-based systems, especially frequency and sequence couplings, is an ongoing challenge for linearized multi-frequency models. Besides, design details are required to develop such models, which either are the intellectual property of manufacturers or require experimental tests. The generic multi-frequency modelling method has been proposed to fill this gap; however, it is only developed for converter-connected systems, e.g., Type 4 Wind Turbines (WT). This paper proposes to extend the application of the generic multi-frequency modelling method for Type 3 WTs. In this way, a theory for patterns of the couplings in Type 3 WTs is proposed. Accordingly, a group of emissions and couplings are Rotor-Speed-Dependent (RSD). The RSD emissions and couplings are particular characteristics of Type 3 WTs, which should be addressed in the generic multi-frequency models. Additionally, the proposed theory is verified by unique-worldwide experimental perturbation tests on a 2 MVA Type 3 WT using a 7 MVA grid emulator. Accordingly, a limited number of RSD couplings and emissions are observed in the test results, mainly in low frequencies (below 1 kHz). Therefore, addressing the RSD couplings is practical and important to extend the generic multi-frequency modelling for Type 3 WTs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

High-Fidelity Modeling of a Type-5 Wind Turbine Gearbox

Type-5 wind turbines are characterized by their use of a hydraulic torque converter and permanent synchronous generator. This combination promotes steady and grid-ready energy without the use of a power converter. Thus, researchers were prompted to study the potential impact on grid reliability, stability, and resilience using a Real Time Digital Simulator (RTDS) model of the type-5 turbine, including a high-fidelity model of its gear box.

13 - HYDRO ENERGY↗
NASA NTRS1972

Preliminary experiments on the noise generated by target-type thrust reverser models

Experiments are reported on the noise generated by model V-gutter and semicylindrical target-type reversers with circular nozzles. Nozzles were 5.24 and 7.78 cm in diameter. Nozzle pressure ratio ranged from 1.25 to 1.72. The spacing between reversers and nozzle, as well as the reverser orientation, was also varied. More noise was generated with reversers than with the nozzle alone. The measured maximum overall sound pressure level varied with the sixth power of the nozzle exit velocity. Noise levels were more uniform in regard to directivity with reversers than with the nozzle alone. It is concluded that thrust reversers, can be a significant noise problem, especially for STOL aircraft using thrust reversers during approach.

Gutierrez, O. A.↗
DOE OSTI2022

SALT3-NIR: Taking the Open-source Type Ia Supernova Model to Longer Wavelengths for Next-generation Cosmological Measurements

Abstract A large fraction of Type Ia supernova (SN Ia) observations over the next decade will be in the near-infrared (NIR), at wavelengths beyond the reach of the current standard light-curve model for SN Ia cosmology, SALT3 (∼2800–8700 Å central filter wavelength). To harness this new SN Ia sample and reduce future light-curve standardization systematic uncertainties, we train SALT3 at NIR wavelengths (SALT3-NIR) up to 2 μ m with the open-source model-training software SALTshaker , which can easily accommodate future observations. Using simulated data, we show that the training process constrains the NIR model to ∼2%–3% across the phase range (−20 to 50 days). We find that Hubble residual (HR) scatter is smaller using the NIR alone or optical+NIR compared to optical alone, by up to ∼30% depending on filter choice (95% confidence). There is significant correlation between NIR light-curve stretch measurements and luminosity, with stretch and color corrections often improving HR scatter by up to ∼20%. For SN Ia observations expected from the Roman Space Telescope, SALT3-NIR increases the amount of usable data in the SALT framework by ∼20% at redshift z ≲ 0.4 and by ∼50% at z ≲ 0.15. The SALT3-NIR model is part of the open-source SNCosmo and SNANA SN Ia cosmology packages.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2015

Calibration of Predictor Models Using Multiple Validation Experiments

This paper presents a framework for calibrating computational models using data from several and possibly dissimilar validation experiments. The offset between model predictions and observations, which might be caused by measurement noise, model-form uncertainty, and numerical error, drives the process by which uncertainty in the models parameters is characterized. The resulting description of uncertainty along with the computational model constitute a predictor model. Two types of predictor models are studied: Interval Predictor Models (IPMs) and Random Predictor Models (RPMs). IPMs use sets to characterize uncertainty, whereas RPMs use random vectors. The propagation of a set through a model makes the response an interval valued function of the state, whereas the propagation of a random vector yields a random process. Optimization-based strategies for calculating both types of predictor models are proposed. Whereas the formulations used to calculate IPMs target solutions leading to the interval value function of minimal spread containing all observations, those for RPMs seek to maximize the models' ability to reproduce the distribution of observations. Regarding RPMs, we choose a structure for the random vector (i.e., the assignment of probability to points in the parameter space) solely dependent on the prediction error. As such, the probabilistic description of uncertainty is not a subjective assignment of belief, nor is it expected to asymptotically converge to a fixed value, but instead it casts the model's ability to reproduce the experimental data. This framework enables evaluating the spread and distribution of the predicted response of target applications depending on the same parameters beyond the validation domain.

Crespo, Luis G.↗