Search NASA⌕ Search

SEARCH · Search NASA

Results for “EXTRAPOLATION”

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 1,423 records · Page 79
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Machine learning a molecular Hamiltonian for predicting electron dynamics

We develop a computational method to learn a molecular Hamiltonian matrix from matrix-valued time series of the electron density. As we demonstrate for three small molecules, the resulting Hamiltonians can be used for electron density evolution, producing highly accurate results even when propagating 1,000 time steps beyond the training data. As a more rigorous test, we use the learned Hamiltonians to simulate electron dynamics in the presence of an applied electric field, extrapolating to a problem that is beyond the field-free training data. We find that the resulting electron dynamics predicted by our learned Hamiltonian are in close quantitative agreement with the ground truth. Our method relies on combining a reduced-dimensional, linear statistical model of the Hamiltonian with a time-discretization of the quantum Liouville equation within time-dependent Hartree Fock theory. In conclusion, we train the model using a least-squares solver, avoiding numerous, CPU-intensive optimization steps. For both field-free and field-on problems, we quantify training and propagation errors, highlighting areas for future development.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Taming nuclear mass models with Gaussian processes

We propose a new set of nuclear mass predictions based on multiple theoretical mass models. By employing Gaussian process regression with the Matérn kernel, we achieved root-mean-square (rms) deviations below 100 keV for the training dataset. The best-performing mass models achieved rms deviations below 150 keV for the new precise mass data from AME2020, whereas the ensemble average showed robust performance across the nuclear chart. Our approach uniquely combines: (1) systematic refinement of eight mass models through their residuals, (2) physics-informed features, including magic numbers, nucleon parity numbers, neutron excess, and nuclear collectivity, and (3) theory-to-theory validation demonstrating robust extrapolation capability. We find that the Matérn kernel provides superior uncertainty quantification compared to the RBF kernel, with a length-scale analysis revealing enhanced inter-nuclei correlations. We provide complete mass predictions for all unknown nuclides in AME2020, offering valuable constraints for nuclear structure studies and astrophysical modeling when used with proper uncertainty propagation.

Gaussian processes↗
DOE OSTI2013

Anomalous structural evolution and liquid fragility signatures in Cu-Zr and Cu-Hf liquids and glasses

The results of high energy X-ray scattering studies of equilibrium and supercooled Cu 100-x Zr x (x = 46 and 54) and Cu x Hf 100-x (x = 55 and 60.8) liquids and the corresponding glasses are presented. The liquid data were obtained in a containerless environment using the beamline electrostatic levitation (BESL) technique. The total structure factor and total pair correlation functions were measured as a function of temperature for the liquids, and for the glasses at room temperature. A developing asymmetry in the peak of the first coordination shell in the total pair correlation function suggests chemical ordering in the liquids with cooling. This asymmetry takes the form of two prominent peaks, suggesting two prominent ordering length scales. When the magnitudes of these peaks are extrapolated to the glass transition temperature a discontinuity is observed, indicating that an abrupt increase in the magnitude is required to match the observed peak heights in the glass. This suggests that the structure of the supercooled liquid orders more rapidly near the glass transition temperature, a conclusion that is supported by molecular dynamics simulations. This observed structural evolution of the liquid indicates that the concept of fragility, typically defined from the behavior of viscosity with temperature, has a measurable structural signature as well, which can be observed in X-ray diffraction studies.

Mauro, N. A.↗
DOE OSTI2020

Plastic deformation of single crystals of the equiatomic Cr-Mn-Fe-Co-Ni high-entropy alloy in tension and compression from 10 K to 1273 K

In this report the plastic deformation behavior of single crystals of the quinary, equiatomic Cr-Mn-Fe-Co-Ni high-entropy alloy (HEA) with the face-centered cubic structure has been investigated in tension and compression as a function of crystal orientation and temperature from 10 K to 1373 K. The critical resolved shear stress (CRSS) for {111}<110> slip at room temperature is 42-45 MPa. It does not depend much on crystal orientation (i.e., the Schmid law holds true) and the sense (tension vs. compression) of the applied load. The CRSS for {111}<110> slip increases with the decrease in temperature, without showing any significant inertia effects at cryogenic temperatures below 77 K. Extrapolation from the measured yield stresses down to 10 K yields a CRSS value at 0 K of 168 MPa. At cryogenic temperatures, the measured strain-rate sensitivity of flow stress is consistent with a very small activation volume. The concept of stress equivalence holds true both for the temperature dependence of CRSS and the stress dependence of activation volume, indicating that solid-solution hardening is the major strengthening mechanism. Deformation twinning occurs at 77 K but not at room temperature, resulting in higher tensile elongation to failure at 77 K than at room temperature. Deformation twinning at 77 K occurs at a shear stress of 378 MPa on conjugate ($\bar1\bar11$) planes in the form of Lüders deformation after large plastic strain (about 85%) achieved by the stage I (easy glide) and stage II (linear work-hardening) deformation.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Long-term thermal aging behavior and strength reduction in a laser powder bed fusion 316H stainless steel

The long-term thermal stability of structural alloys is essential for ensuring the safe and reliable operation of nuclear reactors and other power plants. While extensive research has explored the effects of thermal aging on conventional stainless steels, the behavior of additively manufactured (AM) alloys remains less understood. This study examines the thermal aging response of laser powder bed fusion (LPBF) 316H stainless steel (SS) at temperatures ranging from 550 °C to 750 °C over durations of up to 10,000 h (approximately 1.14 years). Advanced characterization techniques, including electron microscopy and synchrotron X-ray diffraction, were used to investigate dislocation recovery and phase evolution. Based on these findings, a time-temperature-precipitation (TTP) diagram was developed for LPBF 316H SS, revealing a 10- to100-fold acceleration in precipitation kinetics compared to wrought 316H SS. A physics-informed model was calibrated using the short-term experimental data, enabling predictions of average precipitate sizes, volume fractions of M 23 C 6 and Laves phases, and changes in molybdenum solute concentration for aging up to 1 × 10⁶ h (114 years). These microstructural insights were further utilized to estimate yield strength and extrapolate strength reduction factors over the extended aging period. Despite the accelerated aging kinetics, LPBF 316H SS demonstrated superior yield strength retention compared to its wrought counterpart. In conclusion, this study establishes a framework for evaluating long-term performance using short-term experimental data and supports the accelerated qualification of AM materials for high-temperature structural applications.

Laser powder bed fusion↗
DOE OSTI2026

Establishing an acoustic-property relationship in laser powder bed fusion with machine learning

Quality control of Laser Powder Bed Fusion (PBF-LB) additively manufactured parts is an important hurdle inhibiting the technology’s use structural applications. Acoustic monitoring of the laser powder bed fusion process can detect defects in-situ that are known to degrade mechanical properties. However, processing-structure-property (PSP) relationships are required to extrapolate from detected defects to part performance. Here, this study explores how acoustics may be a suitable signature linking processing conditions to properties, thus effectively substituting for structure in the PSP relationship. Establishing such a relationship would enable a part’s mechanical performance to be directly predicted from its acoustic signature, reducing the need for destructive testing or microstructural analysis to ensure a part will meet performance requirements. One hundred CoCrFeMnNi high entropy alloy tensile bars were printed across 13 process conditions in a series of 6 prints. The acoustic signatures of these tensile bars were used to train machine learning models to predict each part’s mechanical properties. By using both process information and acoustic information to predict mechanical properties, yield strength was predicted 18% more accurately and ductility to failure was predicted 10% more accurately than is achieved when using duplicate parts to predict part performance. Finally, individual acoustic frequencies were investigated to determine why acoustic signatures improve mechanical property predictions and the potential physical origins of these signatures. This work demonstrates how blending acoustics, process information, and machine learning can provide in-situ diagnostics of mechanical properties and improve the reliability of the PBF-LB process.

Acoustic emission↗
DOE OSTI2015

Copper fine-structure K-shell electron impact ionization cross sections for fast-electron diagnostic in laser-solid experiments

The K-shell electron impact ionization (EII) cross section, along with the K-shell fluorescence yield, is one of the key atomic parameters for fast-electron diagnostic in laser-solid experiments through the K-shell emission cross section. In addition, copper is a material that has been often used in those experiments because it has a maximum total K-shell emission yield. Furthermore, in a campaign dedicated to the modeling of the K lines of astrophysical interest (Palmeri et al., 2012), the K-shell fluorescence yields for the K-vacancy fine-structure atomic levels of all the copper isonuclear ions have been calculated. In this study, the K-shell EII cross sections connecting the ground and the metastable levels of the parent copper ions to the daughter ions K-vacancy levels considered in Palmeri et al. (2012) have been determined. The relativistic distorted-wave (DW) approximation implemented in the FAC atomic code has been used for the incident electron kinetic energies up to 10 times the K-shell threshold energies. Moreover, the resulting DW cross sections have been extrapolated at higher energies using the asymptotic form proposed by Davies et al. (2013)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

Vanadium fine-structure K-shell electron impact ionization cross sections for fast-electron diagnostic in laser–solid experiments

The K-shell electron impact ionization (EII) cross section, along with the K-shell fluorescence yield, is one of the key atomic parameters for fast-electron diagnostic in laser–solid experiments through the K-shell emission cross section. In addition, in a campaign dedicated to the modeling of the K lines of astrophysical interest (Palmeri et al. (2012)), the K-shell fluorescence yields for the K-vacancy fine-structure atomic levels of all the vanadium isonuclear ions have been calculated. In this study, the K-shell EII cross sections connecting the ground and the metastable levels of the parent vanadium ions to the daughter ions K-vacancy levels considered in Palmeri et al. (2012) have been determined. The relativistic distorted-wave (DW) approximation implemented in the FAC atomic code has been used for the incident electron kinetic energies up to 20 times the K-shell threshold energies. Moreover, the resulting DW cross sections have been extrapolated at higher energies using the asymptotic behavior of the modified relativistic binary encounter Bethe model (MRBEB) of Guerra et al. (2012) with the density-effect correction proposed by Davies et al. (2013)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

Calculations of photo-induced X-ray production cross-sections in the energy range 1–150 keV and average fluorescence yields for Zn, Cd and Hg

In this paper, we calculate the K-, L- and M-shells X-ray production, and X-ray fluorescence cross-sections after photo-induced ionization, for Zn, Cd, and Hg, and for incident photon energy range from 1 to 150 keV. For this purpose, the corresponding average fluorescence yields for Zn, Cd, and Hg as well as the photoionization cross-sections were calculated using the Dirac–Fock method. Subshell fluorescence, intrashell and intershell yields are obtained consistently from radiative and radiationless transitions calculated in the exact same method. A comprehensive account of the relations between the X-ray production, X-ray fluorescence cross-sections and the photoionization cross-sections and these yields is presented. Comparisons are made with results from other authors. The obtained values for the photoionization cross-sections are in good agreement with the widely used data of Scofield in the studied energy range. However our results for the X-ray fluorescence cross sections seem to favor some data relatively to others. The energy dependence of the average fluorescence yields is discussed, in particular, the reliability of extrapolated data for lighter elements from measurements and calculations in heavier elements above the inner shell absorption edges is questioned. Tabulated data on photoionization and X-ray production cross-sections are presented for the incident photon energy range 1–150 keV in steps of 1 keV.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Quantifying and reducing the differences in forest CO 2 -fluxes estimated by eddy covariance, biometric and chamber methods: A global synthesis

Carbon dioxide (CO 2 ) fluxes between terrestrial ecosystems and the atmosphere are primarily measured with eddy covariance (EC), biometric, and chamber methods. However, it is unclear why the estimates of CO 2 -fluxes, when measured using these different methods, converge at some sites but diverge at others. We synthesized a novel global dataset of forest CO 2 -fluxes to evaluate the consistency between EC and biometric or chamber methods for quantifying CO 2 budget in forests. The EC approach, comparing with the other two methods, tended to produce 25% higher estimate of net ecosystem production (NEP, 0.52Mg C ha-1 yr-1), mainly resulting from lower EC-estimated Re; 10% lower ecosystem respiration (Re, 1.39Mg C ha-1 yr-1); and 3% lower gross primary production (0.48 Mg C ha-1 yr-1) The discrepancies between EC and the other methods were higher at sites with complex topography and dense canopies versus those with flat topography and open canopies. Forest age also influenced the discrepancy through the change of leaf area index. The open-path EC system induced >50% of the discrepancy in NEP, presumably due to its surface heating effect. These results provided strong evidence that EC produces biased estimates of NEP and Re in forest ecosystems. A global extrapolation suggested that the discrepancies in CO 2 fluxes between methods were consistent with a global underestimation of Re, and overestimation of NEP, by the EC method. Accounting for these discrepancies would substantially improve the our estimates of the terrestrial carbon budget .

Wang, Xingchang↗
DOE OSTI2019

From plot to scale: ex-ante assessment of conservation agriculture in Zambia

This study combined bottom-up and top-down approaches to assess the ex-ante effects of conservation agriculture (CA)-based systems in Zambia considering both biophysical and economic factors and prevailing farm systems characteristics. For continuous maize cropping we compared a CA-based system of no-tillage with crop residue retention to a control system of conventional tillage with crop residue removal. First, we simulated yield effects that were calibrated and evaluated against multiple datasets, including on-farm agronomic trials from two seasons and six sites. Next, we extrapolated our simulations to all maize-growing areas in Zambia using gridded climate and soil datasets. Then simulated yields (in kg ha( -1 )) were combined with economic data from a nationally-representative household survey to construct economic indicators including benefit-cost ratios (based on gross benefits and variable costs both in $ ha( -1 )) that captured the implicit value of crop residues and labor demands. The field scale (per ha) indicators were scaled out using harvested areas as an expansion factor. All indicators were calculated over 3-, 10-, and 20-year simulation periods using an interpolated sequence of historical climate data. Finally, we conducted a spatial farm typology analysis to help understand the spatial variation in our field-scale indicators and provide insights into trade-offs and the suitability of CA-based systems for farmers. Average changes in yield from using CA-based systems (compared with the control) at the district scale ranged from -37% to 70% (average 33%), with a similar range of changes in benefit-cost ratios once economic factors were included, in addition to intra-district yield variability. Combining the changes in benefit cost ratios with maize harvested area resulted in an average annual change in district-scale net benefit ranging from US $ - 3.9 to US $9.9 million (with an average of US $1.1 million). The heterogeneity in biophysical and economic factors gave a ranking of provinces different according to biophysical or economic indicators, reinforcing the importance of coupling biophysical and economic approaches. The spatial farm typology analysis highlighted the specific contexts of farmers relevant to the suitability of CA, such as their mineral fertilizer applications rates, ownership of livestock, and prevailing soil texture and rainfall.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Maximizing machine learning interatomic potential transferability for the discovery of the novel stellated octadecagon Bi18-Pt24 cage structure

Achieving true transferability remains the central challenge for Machine Learning Interatomic Potentials (ML-IAPs) in modeling complex bimetallic nanoclusters across their vast potential energy surfaces. We systematically investigate data selection strategies to optimize the Chebyshev Interaction Model for Efficient Simulation (ChIMES) potential for the Bi-Pt nanoclusters by comparing three innovative sampling methods: Principal Component Analysis (PCA)/k-means (structural diversity), t-distributedStochasticNeighborEmbedding (t-SNE)/k-means (force-space diversity), and hierarchical clustering. Quantitatively, the PCA/k-means strategy proved most effective for global accuracy, yielding the lowest force errors and achieving energy root mean square errors (RMSE) values competitive with Density Functional Theory (DFT), demonstrating excellent accuracy (19.16meV/atom). Structural validation on 34 unique DFT-optimized isomers further confirmed the potential’s high fidelity, with the best model PCA/k-means reproducing structures with an average root mean square deviation (RMSD) of 0.10 Å. However, the t-SNE methods, by maximizing diversity in the force space, demonstrated superior extrapolative power, leading to the more precise prediction of a novel stellated octadecagon Bi18⁢Pt24 cage structure, demonstrating the potential for exploring previously unseen morphologies. Our results establish a clear methodology for strategic data sampling that successfully maximizes ML-IAP transferability, providing an accurate and computationally efficient tool that accelerates the theoretical discovery of complex bimetallic architectures.

Vangheluwe, Raphaël [Université Paris-Saclay, CNRS↗
DOE OSTI2022

Chromium-coated cladding analysis under simulated LOCA burst conditions

Of the near-term accident-tolerant fuel concepts identified, chromium coatings have been shown to slow cladding oxidation without altering fuel system geometry or greatly affecting neutronic performance. To identify how coated cladding tubes perform under high-temperature accident conditions, pressurized-tube burst tests were conducted in the Severe Accident Test Station at Oak Ridge National Laboratory. To analyze how the coating affects cladding behavior, coated and uncoated cladding burst tests were simulated by using the BISON fuel performance code. Thermocouple data from these tests were fit into axial and azimuthal profiles and combined to generate 3D cladding surface temperatures, and pressure transducer data were compared until cladding failure. Additionally, the cladding temperatures at failure and the internal gas pressure evolution show relatively good agreement between the simulation and experiment results. Simulations were then extrapolated to demonstrate the coatings effectiveness to increasing the cladding burst temperature by using a parametric evaluation of the initial tube gas pressure. This work demonstrates the possibility of an increased cladding failure margin under transient conditions due to the addition of chromium coating, and more pertinently, an increased cladding failure margin from more accurate experimental characterization.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Effect of neutron beamline irradiation on hydrogen equilibrium vapor pressure over hydrided Zircaloy-4

Here, the effect of neutron irradiation on the hydrogen equilibrium vapor pressure over hydrided samples of nickel-plated Zircaloy-4 was evaluated at the Washington State University Research Reactor’s epithermal beamline facility. To enable this study, a measurement capability was designed and assembled to obtain low pressure (<0.1 Pa) measurements over the temperature range of interest (i.e., ~300° - 400°C). Measurement results were in good agreement with tends extrapolated from previous data obtained at higher temperatures as well as recent thermodynamic data. No irradiation enhancement of vapor pressure was observed under the incident flux of epithermal neutrons over this temperature range.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2014

The Thomas–Fermi quark model: Non-relativistic aspects

The first numerical investigation of non-relativistic aspects of the Thomas–Fermi (TF) statistical multi-quark model is given. We begin with a review of the traditional TF model without an explicit spin interaction and find that the spin splittings are too small in this approach. An explicit spin interaction is then introduced which entails the definition of a generalized spin “flavor”. We investigate baryonic states in this approach which can be described with two inequivalent wave functions; such states can however apply to multiple degenerate flavors. We find that the model requires a spatial separation of quark flavors, even if completely degenerate. Although the TF model is designed to investigate the possibility of many-quark states, we find surprisingly that it may be used to fit the low energy spectrum of almost all ground state octet and decuplet baryons. The charge radii of such states are determined and compared with lattice calculations and other models. The low energy fit obtained allows us to extrapolate to the six-quark doubly strange H-dibaryon state, flavor symmetric strange states of higher quark content and possible six quark nucleon–nucleon resonances. The emphasis here is on the systematics revealed in this approach. We view our model as a versatile and convenient tool for quickly assessing the characteristics of new, possibly bound, particle states of higher quark number content. -- Highlights: • First application of the statistical Thomas–Fermi quark model to baryonic systems. • Novel aspects: spin as generalized flavor; spatial separation of quark flavor phases. • The model is statistical, but the low energy baryonic spectrum is successfully fit. • Numerical applications include the H-dibaryon, strange states and nucleon resonances. • The statistical point of view does not encourage the idea of bound many-quark baryons.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Modeling occupancy-driven building loads for large and diversified building stocks through the use of parametric schedules

Building energy modeling provides a fundamental tool to assess the potential for energy efficiency to contribute to reducing world energy consumption and global emissions. Occupancy-related operations are a key source of uncertainty for building energy analysis, particularly for aggregated building stocks. At a district or city level, it is critical to estimate aggregated power load profiles for sizing power grid infrastructure, power plant capacity allocation, and energy efficiency measures. The stochastic nature of behavior-related operations complicates the creation of models that accurately capture building load profiles for entire building stocks. This research introduces a new methodology called parametric schedules to model occupancy-driven schedules for large and diverse building stocks. In contrast to computationally expensive methodologies proposed in the literature, our work does not use a recursive time-consuming step. Occupancy is estimated by the extrapolation of operation times directly from metered electric consumption data; occupancy-related schedules are stochastically assigned to each building model, guaranteeing diversity of operation times in the stock. Our procedure has been tested on a large, diversified data-set of 25,000 commercial buildings in Los Angeles, California. It proved to be able to adequately represent the stochastic schedules diversity of the stock and to refine the stock calibration process by 1%. This innovative approach represents a useful asset for utility companies, grid operators, urban planners, and balancing authorities, seeking to improve building stock modeling and better estimate the impact of energy conservation measures. – This work is part of a larger stock modeling tool called ComStock, which is under development by NREL.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Effects of land-based wind turbine upsizing on community sound levels and power and energy density

Multiple technological, social, and market factors of wind power are evolving rapidly. Most notably, significant wind turbine scaling is occurring and is forecasted to continue. While the larger turbines expected to be deployed in the future are more powerful and efficient, they are also expected to operate at higher sound levels and require larger setbacks than those installed in the last decade. These sometimes-competing deployment trends and impacts cannot be understood via simple extrapolations of past trends. This study analyzes the effect of these future larger turbines on wind turbine micro-siting, project-level power and energy density, and community noise impacts. Due to their taller heights, larger rotors, and higher sound power levels, future wind turbines will require larger setbacks from homes and greater inter-turbine spacing, resulting in fewer turbines deployed for a given land area. This research finds these changes more than offset the effect of the higher turbine sound emissions, significantly decreasing the average sound levels that wind plant hosting communities experience. Yet, simultaneously, plant layouts using future turbine designs also result in projects with higher installed capacities and annual energy output for a given land area. These increases will likely lead to increased tax benefits and local income in the community. The deployment of fewer turbines on a smaller number of parcels could have implications on siting flexibility and landowner payments.

17 WIND ENERGY↗