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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Mid-Field Sonic Boom Extrapolation Methodology

In the design cycle of low-boom airplanes, sonic boom prediction must be accurate and efficient. The classical linear method, Whitham's F-function theory, has been widely applied to predict sonic boom signatures. However, linear theory fails to capture the nonlinear effects created by large civil transport. Computational fluid dynamics (CFD) has been used successfully to predict sonic boom signals at the near and mid fields. Nevertheless, it is computationally expansive in airplane design runs. In the present study, the method of characteristics is used to predict sonic boom signals in an efficient fashion. The governing equations are the axisymmetric Euler's equations with constant enthalpy. Since the method solves Euler's equations, it captures more nonlinear effects than the classical Whitham's F-function technique. Furthermore, the method of characteristics is an efficient marching scheme for initial value problems. In this study, we will first review the current CFD extrapolation technique and the work previously done in sonic boom extrapolation. Then, we will introduce the governing equations and the method of characteristics. Finally, we will show that the present method yields the same accurate results as previous CFD techniques, but with higher efficiency.

Cheung, Samson↗
NASA NTRS2017

Extrapolating the Trends of Test Drop Data with Opening Shock Factor Calculations: the Case of the Orion Main and Drogue Parachutes Inflating to 1st Reefed Stage

We describe a new calculation of the opening shock factor C (sub k) characterizing the inflation performance of NASA's Orion spacecraft main and drogue parachutes opening under a reefing constraint (1st stage reefing), as currently tested in the Capsule Parachute Assembly System (CPAS) program. This calculation is based on an application of the Momentum-Impulse Theorem at low mass ratio (R (sub m) is less than 10 (sup -1)) and on an earlier analysis of the opening performance of drogues decelerating point masses and inflating along horizontal trajectories. Herein we extend the reach of the Theorem to include the effects of payload drag and gravitational impulse during near-vertical motion - both important pre-requisites for CPAS parachute analysis. The result is a family of C (sub k) versus R (sub m) curves which can be used for extrapolating beyond the drop-tested envelope. The paper proves this claim in the case of the CPAS Mains and Drogues opening while trailing either a Parachute Compartment Drop Test Vehicle or a Parachute Test Vehicle (an Orion capsule boiler plate). It is seen that in all cases the values of the opening shock factor can be extrapolated over a range in mass ratio that is at least twice that of the test drop data.

Potvin, Jean↗
DOE OSTI2019

Ta, Ti and Hf effects on Nb 3 Sn high-field performance: temperature-dependent dopant occupancy and failure of Kramer extrapolation

The increasing demand for improving the high-field (16-22 T) performance of Nb 3 Sn conductors requires a better understanding of the properties of modern wires much closer to irreversibility field, H Irr . In this study we investigated the impact of Ta, Ti and Hf doping on the high-field pinning properties, the upper critical field, H c2 , and H Irr . We found that the pinning force curves of commercial Ti and Ta doped wires at different temperatures do not scale and that the Kramer extrapolation, typically used by magnet designers to estimate high-field critical current density and magnet operational margins from lower field data, is not reliable and significantly overestimates the actual H Irr . In contrast, new laboratory scale conductors made with Nb-Ta-Hf alloy have improved high-field J c performance and, despite contributions by both grain boundary and point defect pinning mechanisms, have more predictable high-field behavior. Using Extended X-ray Absorption Fine Structure spectroscopy, EXAFS, we found that for the commercial Ta and Ti doped conductors, the Ta site occupancy in the A15 structure gradually changes with the heat treatment temperature whereas Ti is always located on the Nb site with clear consequences for H c2 . Finally, this work reveals the still limited understanding of what determines H c2 , H Irr and the high-field J c performance of Nb 3 Sn and the complexity of optimizing these conductors so that they can reach their full potential for high-field applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Controlling extrapolations of nuclear properties with feature selection

Predictions of nuclear properties far from measured data are inherently inaccurate because of uncertainties in our knowledge of nuclear forces and in our treatment of quantum many-body effects in strongly-interacting systems. While the model bias can be directly calculated when experimental data is available, only an estimate can be made in the absence of such measurements. Current approaches to compute the estimated bias quickly lose predictive power when their input variables are taken far from the training region, resulting in uncontrolled uncertainties in applications such as nucleosynthesis simulations. In this letter, we present a novel technique to identify the input variables of machine learning algorithms that can provide robust estimates of model bias. Our process is based on selecting input variables, or features, based on their probability distribution functions across the entire nuclear chart. We illustrate our approach on the problem of quantifying the model bias in nuclear binding energies calculated with Density Functional Theory (DFT). We prove that building model biases with only Z and N as features leads to highly unreliable extrapolations. Conversely, we show that proper feature selection can systematically improve theoretical predictions without increasing uncertainties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

Gaussian process model for extrapolation of scattering observables for complex molecules: From benzene to benzonitrile

We consider a problem of extrapolating the collision properties of a large polyatomic molecule A–H to make predictions of the dynamical properties for another molecule related to A–H by the substitution of the H atom with a small molecular group X, without explicitly computing the potential energy surface for A–X. We assume that the effect of the −H →−X substitution is embodied in a multidimensional function with unknown parameters characterizing the change of the potential energy surface. We propose to apply the Gaussian Process model to determine the dependence of the dynamical observables on the unknown parameters. This can be used to produce an interval of the observable values which corresponds to physical variations of the potential parameters. We show that the Gaussian Process model combined with classical trajectory calculations can be used to obtain the dependence of the cross sections for collisions of C{sub 6}H{sub 5}CN with He on the unknown parameters describing the interaction of the He atom with the CN fragment of the molecule. The unknown parameters are then varied within physically reasonable ranges to produce a prediction uncertainty of the cross sections. The results are normalized to the cross sections for He — C{sub 6}H{sub 6} collisions obtained from quantum scattering calculations in order to provide a prediction interval of the thermally averaged cross sections for collisions of C{sub 6}H{sub 5}CN with He.

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

Data efficiency and extrapolation trends in neural network interatomic potentials

Abstract Recently, key architectural advances have been proposed for neural network interatomic potentials (NNIPs), such as incorporating message-passing networks, equivariance, or many-body expansion terms. Although modern NNIP models exhibit small differences in test accuracy, this metric is still considered the main target when developing new NNIP architectures. In this work, we show how architectural and optimization choices influence the generalization of NNIPs, revealing trends in molecular dynamics (MD) stability, data efficiency, and loss landscapes. Using the 3BPA dataset, we uncover trends in NNIP errors and robustness to noise, showing these metrics are insufficient to predict MD stability in the high-accuracy regime. With a large-scale study on NequIP, MACE, and their optimizers, we show that our metric of loss entropy predicts out-of-distribution error and data efficiency despite being computed only on the training set. This work provides a deep learning justification for probing extrapolation and can inform the development of next-generation NNIPs.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Multigrid reduction in time with Richardson extrapolation

The advent of exascale computing will leave many users with access to more computational resources than they can simultaneously use, e.g., billion-way parallelism. In particular, this is true for time-dependent simulations that limit parallelism to the spatial domain. One method to add parallelism in time to existing simulation codes and thus take advantage of ever larger compute resources is Multigrid Reduction in Time (MGRIT). The goal is to achieve a smaller time-to-solution through parallelism in time. In this paper, MGRIT is enhanced with Richardson extrapolation in a cost-efficient way to produce a parallel-in-time method with improved accuracy. Overall, this leads to a large improvement in the accuracy per computational cost of MGRIT.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Enhanced Co-Expression Extrapolation (COXEN) Gene Selection Method for Building Anti-Cancer Drug Response Prediction Models

The co-expression extrapolation (COXEN) method has been successfully used in multiple studies to select genes for predicting the response of tumor cells to a specific drug treatment. Here, we enhance the COXEN method to select genes that are predictive of the efficacies of multiple drugs for building general drug response prediction models that are not specific to a particular drug. The enhanced COXEN method first ranks the genes according to their prediction power for each individual drug and then takes a union of top predictive genes of all the drugs, among which the algorithm further selects genes whose co-expression patterns are well preserved between cancer cases for building prediction models. We apply the proposed method on benchmark in vitro drug screening datasets and compare the performance of prediction models built based on the genes selected by the enhanced COXEN method to that of models built on genes selected by the original COXEN method and randomly picked genes. Models built with the enhanced COXEN method always present a statistically significantly improved prediction performance (adjusted p-value ≤ 0.05). Our results demonstrate the enhanced COXEN method can dramatically increase the power of gene expression data for predicting drug response.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Estimating Large Global Significances with a New Monte Carlo Extrapolation Method

In particle physics, it is needed to evaluate the possibility that excesses of events in mass spectra are due to statistical fluctuations as quantified by the standards of local and global significances. Without prior knowledge of a particle’s mass, it is especially critical to estimate its global significance. The usual approach is to count the number of times a significance limit is exceeded in a collection of simulated Monte Carlo (MC) “toy experiments”. To demonstrate this conventional method for global significance, we performed simulation studies according to a recent Compact Muon Solenoid (CMS) result to show its effectiveness. However, this counting method is not practical for computing large global significances. To address this problem, we developed a new “extrapolation” method to evaluate the global significance. We compared the global significance estimated by our new method with that of the conventional approach, and verified its feasibility and effectiveness. This method is also applicable for cases where only small toy MC samples are available. In this approach, the significance is calculated based on p-values, assuming symmetrical Gaussian distributions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

COMPARISON OF CORONAL EXTRAPOLATION METHODS FOR CYCLE 24 USING HMI DATA

Two extrapolation models of the solar coronal magnetic field are compared using magnetogram data from the Solar Dynamics Observatory /Helioseismic and Magnetic Imager instrument. The two models, a horizontal current–current sheet–source surface (HCCSSS) model and a potential field–source surface (PFSS) model, differ in their treatment of coronal currents. Each model has its own critical variable, respectively, the radius of a cusp surface and a source surface, and it is found that adjusting these heights over the period studied allows for a better fit between the models and the solar open flux at 1 au as calculated from the Interplanetary Magnetic Field (IMF). The HCCSSS model provides the better fit for the overall period from 2010 November to 2015 May as well as for two subsets of the period: the minimum/rising part of the solar cycle and the recently identified peak in the IMF from mid-2014 to mid-2015 just after solar maximum. It is found that an HCCSSS cusp surface height of 1.7 R {sub ⊙} provides the best fit to the IMF for the overall period, while 1.7 and 1.9 R {sub ⊙} give the best fits for the two subsets. The corresponding values for the PFSS source surface height are 2.1, 2.2, and 2.0 R {sub ⊙} respectively. This means that the HCCSSS cusp surface rises as the solar cycle progresses while the PFSS source surface falls.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Dead-Time Correction of Pulsed Neutron Source Experiments with the Backward Extrapolation Method

This paper introduces a novel procedure to correct pulsed neutron source experimental data for dead-time effects. The procedure is based on the application of the backward extrapolation method to the reaction rate value in each time interval (bin) of the neutron counts distribution as a function of time. The theoretical framework has been successfully applied to the experimental data (timestamps) from the YALINA Thermal facility driven by a pulsed D-D neutron source. Dead-time effects may have more than 500 pcm (1 pcm=1 E-5) impact on the effective multiplication factor calculated by the area method. (authors)

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2024

Non-resonant anomaly detection with background extrapolation

Complete anomaly detection strategies that are both signal sensitive and compatible with background estimation have largely focused on resonant signals. Non-resonant new physics scenarios are relatively under-explored and may arise from off-shell effects or final states with significant missing energy. In this paper, we extend a class of weakly supervised anomaly detection strategies developed for resonant physics to the non-resonant case. Machine learning models are trained to reweight, generate, or morph the background, extrapolated from a control region. A classifier is then trained in a signal region to distinguish the estimated background from the data. The new methods are demonstrated using a semi-visible jet signature as a benchmark signal model, and are shown to automatically identify the anomalous events without specifying the signal ahead of time.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Regularizing the linearly extrapolated BDF2 scheme for incompressible flows with time relaxation

This paper presents a highly-efficient finite element scheme for the time relaxation model (TRM). The efficiency is achieved through the second-order BDF2 time-stepping scheme with linear extrapolation (BDF2LE). The accuracy of the scheme is also greatly enhanced through the use of the divergence-free Scott-Vogeulis finite elements, and van Cittert approximate deconvolution. A complete finite element analysis is provided, which includes rigorous proofs for the stability, well-possessedness, and convergence of both velocity and pressure solutions. Furthermore, we also demonstrate that the inclusion of the linear time relaxation term preserves the long-time stability of the unregularized BDF2LE scheme. Finally, numerical experiments are presented that demonstrate the added stability and accuracy that time relaxation can provide.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Multi-faceted framework for extrapolating early age flexural strength to facilitate rapid lifting/handling of high-volume fly ash precast members

Maintaining adequate early-age structural performance for precast concrete components has grown in importance as more sustainable mix designs become more widespread. Achieving high-early flexural strength is particularly crucial to facilitate rapid removal of hardened concrete components from formwork, often within 24 h after fresh concrete placement. Limited research has assessed the effectiveness of traditional design methods in correlating flexural strength with compressive strength for next-generation mix designs, or demonstrated extrapolation of such material performance to larger-scale structural tests. This paper presents a multi-faceted framework to reassess early-age flexural strength for concretes made with relatively high proportions of fly ash from both fresh and harvested sources. Here, the framework provides several pathways, from which the user can select based upon available resources and the specific application, to improve accuracy of early-age cracking moment calculations. Furthermore, the scope includes evaluation of strength performance under curing conditions emulative of those in a precast facility, recommending modulus of rupture equations which are more performance-driven than current design provisions, and experimental tests on prefabricated concrete beams to validate the proposed methodologies. Correlations of early-age strength with both concrete age and maturity measurements compare the effectiveness of utilizing in-situ data to further enhance the prediction methods. Ultimately, the proposed framework helped reduce errors when calculating cracking moment capacity at early ages by tailoring calculations to reflect mix-dependent behavior. Furthermore, most estimates of cracking moment were within 25 % of their corresponding experimental test results, thus promoting confidence for using these strategies with high-volume fly ash precast structures.

42 ENGINEERING↗
DOE OSTI2026

Beyond interpolation: Physics-inspired gating transformers for extrapolating irradiation conditions to novel nuclear fuels

The qualification of advanced nuclear fuels relies on irradiation experiments in test reactors that emulate commercial conditions. Designing these tests requires accurate prediction of key irradiation quantities, particularly heat generation rate and burnup, yet obtaining them typically involves computationally expensive multi-step simulation workflows. We propose a physics-inspired gating transformer (PIGT) that integrates an inverse-square, distance-based attenuation into the encoder representation to bias attention toward physically relevant spatial relationships while retaining data-driven flexibility. Using MiniFuel irradiation data from the High Flux Isotope Reactor at Oak Ridge National Laboratory, we benchmark against ensemble methods, feedforward and recurrent networks, convolutional models, and standard transformers. While baseline models perform well under interpolation, they exhibit a pronounced generalization gap when evaluated on fuels not included in the training set. The proposed model consistently improves extrapolative accuracy and stability, yielding the strongest performance on unseen fuel configurations. These results indicate that a lightweight physics structure embedded within attention mechanisms can substantially improve robustness, enabling more reliable surrogate predictions to accelerate the design of nuclear fuel irradiation experiments.

Fuel qualification↗
DOE OSTI2026

Pedestal origin and extrapolation of high-density small edge-localised-modes peak parallel energy fluence in ITER and SPARC

Experimental analysis and simulations with the BOUT++ code show that small edge-localised modes (ELMs) in reactor-relevant high-density regimes originate in a region close to the separatrix and only marginally perturb the pedestal structure. The measured divertor peak parallel energy fluence (ε ∥,peak ) for a database of small ELM scenarios in DIII-D and ASDEX Upgrade can be reproduced, within 40 % accuracy on average, if an ad hoc modification of the Eich peak parallel ELM energy fluence model is applied to account for the small ELM pedestal birth location. This allows for first-order extrapolation of small-ELM divertor ε ∥,peak to ITER and SPARC, resulting in values that satisfy the nominal melting threshold of tungsten monoblocks of 12 MJ m −2 . The findings reported in this study, both via modelling and direct measurements, constitute a step forward in assessing small ELMs in high edge-collisionality scenarios as a viable plasma regime for the operation of next-generation fusion machines.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Prediction of Structures and Atomization Energies of Coinage Metals, (M)n, n < 20: Extrapolation of Normalized Clustering Energies to Predict the Cohesive Energy

The geometries of the group 11 coinage metals (n = 2-20) were optimized to determine the lowest energy isomers for each cluster size, singlets for even numbers and doublets for odd numbers. For copper and silver, 2-D (planar) geometries were favored up to n = 6. For gold, 2D (planar) geometries were favored up to n = 13. Normalized clustering energies were plotted as a function of cluster size (n-1/3, for n = 4-20) with various DFT functionals and the CCSD(T)-F12b method and were extrapolated to predict the bulk cohesive energy. In the case of copper and silver, there is excellent agreement between the cohesive energies predicted at the CCSD(T)-F12b level of theory and the experimental values. For gold, the CCSD(T)-F12b values needed to be corrected for spin-orbit relativistic effects to obtain good agreement with experiment. Electronic properties including the HOMO-LUMO gaps for the even clusters and the spin densities for the odd clusters were calculated. The lowest gap is predicted to occur for n = 16 where the HOMO and LUMO are very similar in shape.

Persuad, Rudradatt R.↗