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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Chiral Extrapolations of the $\boldsymbol{ρ(770)}$ Meson in $\mathbf{N_f=2+1}$ Lattice QCD Simulations

Several lattice QCD simulations of meson-meson scattering in p-wave and Isospin = 1 in Nf = 2 + 1 flavours have been carried out recently. Unitarized Chiral Perturbation Theory is used to perform extrapolations to the physical point. In contrast to previous findings on the analyses of Nf = 2 lattice data, where most of the data seems to be in agreement, some discrepancies are detected in the Nf = 2 + 1 lattice data analyses, which could be due to different masses of the strange quark, meson decay constants, initial constraints in the simulation, or other lattice artifacts. In addition, the low-energy constants are compared to the ones from a recent analysis of Nf = 2 lattice data.

Molina, Raquel↗
DOE OSTI2018

Analysis of trends in experimental observables: Reconstruction of the implosion dynamics and implications for fusion yield extrapolation for direct-drive cryogenic targets on OMEGA

This paper describes a technique for identifying trends in performance degradation for inertial con finement fusion implosion experiments. It is based on reconstruction of the implosion core with a combination of low- and mid-mode asymmetries. This technique was applied to an ensemble of hydro-equivalent deuterium-tritium implosions on OMEGA that achieved inferred hot-spot pressures ≈56 ± 7 Gbar [S. Regan et al., Phys. Rev. Lett. 117, 025001 (2016)]. All the experimental observables pertaining to the core could be reconstructed simultaneously with the same combination of low and mid modes. This suggests that in addition to low modes, that can cause a degradation of the stagnation pressure, mid modes are present that reduce the size of the neutron and x-ray producing volume. The systematic analysis shows that asymmetries can cause an overestimation of the total areal density in these implosions. Finally, it is also found that an improvement in implosion symmetry resulting from correction of either the systematic mid or low modes would result in an increase of the hot-spot pressure from 56 Gbar to ≈ 80 Gbar and could produce a burning plasma when the implosion core is extrapolated to an equivalent 1.9 MJ symmetric direct illumination [A. Bose et al., Phys. Rev. E 94, 011201(R) (2016)].

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

High-accuracy extrapolated ab initio thermochemistry. IV. A modified recipe for computational efficiency

A number of economical modifications to the high-accuracy extrapolated ab initio thermochemistry (HEAT) model chemistry are evaluated. The two resulting schemes, designated as mHEAT and mHEAT+, are designed for efficient and pragmatic evaluation of molecular energies in systems somewhat larger than can be practically studied by the unapproximated HEAT scheme. It is found that mHEAT+ produces heats of formation with nearly subchemical ± 1 kJ/mol) accuracy at a substantially reduced cost relative to the full scheme. Total atomization energies calculated using the new thermochemical recipes are compared to the results of the HEAT-345(Q) model chemistry, and enthalpies of formation for the three protocols are also compared to Active Thermochemical Tables. Finally, a small selection of transition states is studied using mHEAT and mHEAT+, which illuminates some interesting features of reaction barriers and serves as an initial benchmark of the performance of these model chemistries for chemical kinetics applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Does Bayesian model averaging improve polynomial extrapolations? Two toy problems as tests

We assess the accuracy of Bayesian polynomial extrapolations from small parameter values, x, to large values of x. We consider a set of polynomials of fixed order, intended as a proxy for a fixed-order effective field theory (EFT) description of data. We employ Bayesian model averaging (BMA) to combine results from different order polynomials (EFT orders). Our study considers two 'toy problems' where the underlying function used to generate data sets is known. We use Bayesian parameter estimation to extract the polynomial coefficients that describe these data at low x. A 'naturalness' prior is imposed on the coefficients, so that they are $\mathcal{O}(1)$. We BMA different polynomial degrees by weighting each according to its Bayesian evidence and compare the predictive performance of this BMA with that of the individual polynomials. In conclusion, the credibility intervals on the BMA forecast have the stated coverage properties more consistently than does the highest evidence polynomial, though BMA does not necessarily outperform every polynomial.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Trends in runaway electron plateau partial recombination by massive H 2 or D 2 injection in DIII-D and JET and first extrapolations to ITER and SPARC

Abstract Experimental trends in thermal plasma partial recombination resulting from massive D 2 injection into high-Z (Ar) containing runaway electron (RE) plateaus in DIII-D and JET are studied for the purpose of achieving sufficiently low electron density ( n e ≈ 10 18 m − 3 ) to increase RE final loss MHD levels. In both DIII-D and JET, thermal electron density n e is found to drop by ∼100 × when the thermal plasma partially recombines, with a minimum at a vacuum vessel-averaged D 2 density in the range 10 20 − 10 21 m − 3 . RE effective resistivity also drops after partial recombination, indicating expulsion of the Ar content. The n e level after partial recombination is found to increase as RE current is increased. The amount of initial Ar in the RE plateau is not observed to have a strong effect on partial recombination. Partial recombination timescales of order 5 ms in DIII-D and 15 ms in JET are observed. These basic trends and timescales are matched with a 1D diffusion model, which is then used to extrapolate to ITER and SPARC tokamaks. Within the approximations of this model, it is predicted that ITER will be able to achieve sufficiently low n e values on time scales faster than expected RE plateau vertical drift timescales (of order 100 ms), provided sufficient D 2 or H 2 is injected. In SPARC, it is predicted that achieving significant n e recombination will be challenging, due to the very high RE current density. In both ITER and SPARC, it is predicted that achieving low n e will be easier with Ar as a background impurity (rather than Ne).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Cross-machine comparison of runaway electron generation during tokamak start-up for extrapolation to ITER

A cross-machine comparison of global parameters that determine the runaway electron (RE) generation and loss process during tokamak start-up was carried out with the aim to extrapolate these to ITER. The study found that all considered discharges, also those that do not show signs of RE, are non-thermal at the start, i.e. have a streaming parameter larger than 0.1. During the current ramp-up the electric field, E, remains above the critical value, E c , that allows RE in the plasma. The distinction to be made is not if RE can form but, if sufficient RE can form fast enough such that they are detected or start to dominate the dynamics of the tokamak discharge. The dynamics of the value of E, density and temperature during tokamak are key to the formation of RE. It was found that larger devices operate with E closer to E c , due to their higher temperatures, hence the RE generation is relatively slower. The slower time scales for the formation of RE, estimated to be of the order of 100s of ms in ITER simplifies the development of avoidance schemes. The RE confinement time is also an important determinant of the entire process and is found to increase with the device size. The study also revealed that drift orbit losses, a mechanism often attributed as the main RE loss mechanism during the early tokamak discharge, are actually more difficult to achieve. RE losses might be more likely attributed to RE diffusion due to magnetic turbulence.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Metrics and extrapolation of resonant magnetic perturbation thresholds for ELM suppression

This large database study of resonant magnetic perturbation (RMP) edge localized mode (ELM) suppression thresholds in the AUG, DIII-D, EAST, and KSTAR tokamaks details the key strengths and weaknesses of RMP metrics. The RMP ELM suppression database used for this work contains plasma information at the time of transition from ELMing to ELM suppressed states where a clear experimental threshold is identified. The experimental threshold distributions are compared for five metrics: (1) the island overlap width, (2) pedestal top Chirikov overlap, (3) peeling edge displacement, (4) pedestal top resonant drive, and (5) edge dominant mode overlap. The distributions, the regularity of the dependence on RMP coil currents, and the sensitivities of a given metric to equilibrium reconstruction details are compared. The overlap metric proves to be a good compromise between including the appropriate plasma response physics and maintaining a numerical robustness. This quantity does not exhibit clear power-law scalings for projection, but machine learning can assist in predicting thresholds within the existing parameter ranges and providing uncertainty quantification of those predictions. Two new first-principles models, one utilizing a threshold from the non-linear Modified Rutherford equation evaluated at the pedestal top and one utilizing the SLAYER code to calculate the linear tearing threshold from torque balance, offer possible paths to extrapolation beyond the existing database parameter space.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Computationally efficient zero-noise extrapolation for quantum-gate-error mitigation

Zero noise extrapolation (ZNE) is a widely used technique for gate error mitigation on near term quantum computers because it can be implemented in software and does not require knowledge of the quantum computer noise parameters. Traditional ZNE requires a significant resource overhead in terms of quantum operations. A recent proposal using a targeted (or random) instead of fixed identity insertion method (riim versus fiim) requires significantly fewer quantum gates for the same formal precision. We start by showing that riim can allow for ZNE to be deployed on deeper circuits than fiim but requires many more measurements to maintain the same statistical uncertainty. We develop two extensions to fiim and riim. The List Identity Insertion Method (liim) allows to mitigate the error from certain cnot gates, typically those with the largest error. Set Identity Insertion Method (siim) naturally interpolates between the measurement-efficient fiim and the gate-efficient riim allowing to trade off fewer cnot gates for more measurements. Finally, we investigate a way to boost the number of measurements, namely to run ZNE in parallel, utilizing as many quantum devices as are available. We explore the performance of riim in a parallel setting where there is a non-trivial spread in noise across sets of qubits within or across quantum computers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Volume extrapolation via eigenvector continuation

Here, we develop an extension of eigenvector continuation (EC) that makes it possible to extrapolate simulations of quantum systems in finite periodic boxes across large ranges of box sizes. The formal justification for this approach, which we call finite-volume eigenvector continuation (FVEC), is provided by matching periodic functions at different box sizes. As concrete FVEC implementation we use a discrete variable representation based on plane-wave states and present several applications calculated within this framework.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Chiral extrapolations of the ρ ( 770 ) meson in N f = 2 + 1 lattice QCD simulations

Recent $N_f=2+1$ lattice data for meson-meson scattering in $p$-wave and isospin $I=1$ are analyzed using a unitarized model inspired by Chiral Perturbation Theory in the inverse-amplitude formulation for two and three flavors. We perform chiral extrapolations that postdict phase shifts extracted from experiment quite well. Additionally, the low-energy constants are compared to the ones from a recent analysis of $N_f=2$ lattice QCD simulations to check for the consistency of the hadronic model used here. Some inconsistencies are detected in the fits to $N_f=2+1$ data, in contrast to the previous analysis of $N_f=2$ data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

zPerf: A Statistical Gray-Box Approach to Performance Modeling and Extrapolation for Scientific Lossy Compression

With the scaling up of simulation-based scientific discovery on high-performance computing systems, the disparity between compute and I/O has increased, forcing domain scientists to save only a small amount of simulation data to persistent storage. This can result in the loss of essential physics fields that are needed for data analysis. While error-bounded lossy compression has made tremendous progress in bridging the gap between compute and I/O, the lack of understanding of compression performance remains a key hurdle to its wide adoption. Here, in this work, we present zPerf, a statistical gray-box performance modeling approach for scientific lossy compression. Our contributions are threefold: 1) We develop zPerf to estimate the performance of lossy compression techniques, based on in-depth understanding and statistical modeling for data features and core compression metrics; 2) We demonstrate the in-detailed implementation of zPerf using two case studies, where we derive the performance modeling for SZ and ZFP, two leading lossy compressors; 3) We evaluate the effectiveness of zPerf on real-world datasets across various domains. Based on the evaluation, we demonstrate the efficacy of the zPerf performance model; 4) We further discuss three case studies where zPerf is applied to extrapolate the compression ratio of SZ and ZFP with alternative encoding schemes as well as ZFP with an alternative transform scheme. Through the case studies, we demonstrate the potential of zPerf for exploring the design space of lossy compression, which has hardly been studied in the literature.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Using the concordance of in vitro and in vivo data to evaluate extrapolation assumptions

Linking in vitro bioactivity and in vivo toxicity on a dose basis enables the use of highthroughput in vitro assays as an alternative to traditional animal studies. In this study, we evaluated assumptions in the use of a high-throughput, physiologically based toxicokinetic (PBTK) model to relate in vitro bioactivity and rat in vivo toxicity data. The fraction unbound in plasma (fup) and intrinsic hepatic clearance (Clint) were measured for rats (for 67 and 77 chemicals, respectively), combined with fup and Clint literature data for 97 chemicals, and incorporated in the PBTK model. Of these chemicals, 84 had corresponding in vitro ToxCast bioactivity data and in vivo toxicity data. For each possible comparison of in vitro and in vivo endpoint, the concordance between the in vivo and in vitro data was evaluated by a regression analysis. For a base set of assumptions, the PBTK results were more frequently better associated than either the results from a “random” model parameterization or direct comparison of the “untransformed” values of AC50 and dose (performed best in 51%, 28%, and 21% of cases, respectively). We also investigated several assumptions in the application of PBTK for IVIVE, including clearance and internal dose selection. One of the better assumptions sets–restrictive clearance and comparing free in vivo venous plasma concentration with free in vitro concentration–outperformed the random and untransformed results in 71% of the in vitro-in vivo endpoint comparisons. These results demonstrate that applying PBTK improves our ability to observe the association between in vitro bioactivity and in vivo toxicity data in general. This suggests that potency values from in vitro screening should be transformed using in vitro-in vivo extrapolation (IVIVE) to build potentially better machine learning and other statistical models for predicting in vivo toxicity in humans

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Monte Carlo analysis: error of extrapolated thermal conductivity from molecular dynamics simulations

In this short report, we give an analysis of the extrapolated thermal conductivity of UO2 from earlier molecular dynamics (MD) simulations [1]. Because almost all material properties are functions of temperature, e.g. fission gas release, the fuel thermal conductivity is the most important parameter from a model sensitivity perspective [2]. Thus, it is useful to perform such analysis.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

A Method for Extrapolating CMM Data

This report provides a method for evaluating coordinate measuring machine (CMM) data and extrapolating the data to estimate the dimensions of a cylindrical component beyond the sampled measurements. The theoretical basis is provided, and a calculational method is presented. The report also provides detailed, formatted, printed, and plotted representations.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Bayesian Model Calibration for Extrapolative Prediction via Gibbs Posteriors

The current standard Bayesian approach to model calibration, which assigns a Gaussian process prior to the discrepancy term, often suffers from issues of unidentifiability and computational complexity and instability. When the goal is to quantify uncertainty in physical parameters for extrapolative prediction, then there is no need to perform inference on the discrepancy term. With this in mind, we introduce Gibbs posteriors as an alternative Bayesian method for model calibration, which updates the prior with a loss function connecting the data to the parameter. The target of inference is the physical parameter value which minimizes the expected loss. We propose to tune the loss scale of the Gibbs posterior to maintain nominal frequentist coverage under assumptions of the form of model discrepancy, and present a bootstrap implementation for approximating coverage rates. Our approach is highly modular, allowing an analyst to easily encode a wide variety of such assumptions. Furthermore, we provide a principled method of combining posteriors calculated from data subsets. We apply our methods to data from an experiment measuring the material properties of tantalum.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Automation and Database Collection and Extrapolation

This report highlights overall design consideration regarding automation and database collection and extrapolation prototype for Farmpod, LLC. There are potentially many combinations of software, hardware, and networking which suffices for the requirements. For this report, we suggest a Raspberry Pi 2 Model B for the hardware. We suggest the Mako application server for the user interface and RPIO python modules for automated software processes. At the present moment, security is not a major concern, but should be addressed during the initial design phase. The software stack consists of two primary components: the automated processes and application server to implement a user interface.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

An Autonomous Critical Data Extrapolator for the AGN-201m

Nuclear nonproliferation serves as a key goal, being undertaken by the International Atomic Energy Agency (IAEA). To recognize proliferation there are two pathways that states, who intend to use nuclear material for malicious purposes can take, diversion can misuse. Diversion is when fissile nuclear material is declared to the IAEA for non-weapon purposes, but then covertly removed. If the source of nuclear material, that is not declared and not fissionable, is placed inside the reactor core to create fissile material used to create weapons then the state is using the second pathway of proliferation, misuse. With the emerging development in areas of simulation and machine learning the creation of virtual models of reactor systems, digital twins, serve as a potential method to identify proliferation through detecting anomalous behavior in the reactor. A digital twin for a physical nuclear reactor has never been developed, as digital twins serve as an emerging technology. To investigate the process for development and use of a digital twin for a nuclear reactor Idaho State University’s AGN-201m serves as the nuclear reactor used for development of this digital twin. A data acquisition system has been installed to the reactor system allowing for the transfer of collected data from a reactor operation to Idaho National Laboratory’s Deeplynx data warehouse. When utilizing data to train reactor physics and machine learning models, a significant challenge encountered is the initial state of the data. Nuclear proliferation will have the capacity to be detected when the reactor immediately starts up, nor will it occur after the reactor shuts down. Generally, it will be detected when the reactor is operating at some desired power over a sufficient period for that specific reactor design. For the AGN-201m this will be when the reactor is critical (generally 1 mW or above) for a timespan that is within or less than the range of a regular business day. Datasets sent to Deeplynx have had to be manually cut to when the reactor is critical based on plots of power levels. This method is inefficient and laborious, especially when using multiple datasets at once to train a model. To provide a more streamlined approach an automated critical data extrapolator is developed, with capabilities of recognizing when the reactor operation first reaches criticality, and when the reactor undergoes a SCRAM and is shutdown.

99 GENERAL AND MISCELLANEOUS↗