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All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

Numerical Descriptions of Cosmic-Ray Transport

The behavior of energetic particles in the solar system is described by a well known Fokker-Planck equation. Although analytic methods yield insight into the nature of its solutions, especially in the diffusion regime, calculations that go beyond diffusion are very complicated. The reliability of these calculations is of concern, because numerical methods are notorious for their errors and artifacts. The well known Milne problem of classical transport theory was analyzed with the aid of three different numerical methods. These are: (1) The method of eigenfunctions in which the distribution function is approximated by a sum of eigenfunctions of the scattering operator, (2) Numerical solutions of a finite difference aquation; and (3) Direct simulation of the scattering and streaming of individual particles with the aid of Monte Carlo methods.

Earl, J. A.↗
NASA NTRS1987

Numerical simulation of a plane turbulent mixing layer, with applications to isothermal, rapid reactions

A hybrid method has been developed for the numerical prediction of turbulent mixing in a spatially-developing, free shear layer. Most significantly, the computation incorporates the effects of large-scale structures, Schmidt number and Reynolds number on mixing, which have been overlooked in the past. In flow field prediction, large-eddy simulation was conducted by a modified 2-D vortex method with subgrid-scale modeling. The predicted mean velocities, shear layer growth rates, Reynolds stresses, and the RMS of longitudinal velocity fluctuations were found to be in good agreement with experiments, although the lateral velocity fluctuations were overpredicted. In scalar transport, the Monte Carlo method was extended to the simulation of the time-dependent pdf transport equation. For the first time, the mixing frequency in Curl's coalescence/dispersion model was estimated by using Broadwell and Breidenthal's theory of micromixing, which involves Schmidt number, Reynolds number and the local vorticity. Numerical tests were performed for a gaseous case and an aqueous case. Evidence that pure freestream fluids are entrained into the layer by large-scale motions was found in the predicted pdf. Mean concentration profiles were found to be insensitive to Schmidt number, while the unmixedness was higher for higher Schmidt number. Applications were made to mixing layers with isothermal, fast reactions. The predicted difference in product thickness of the two cases was in reasonable quantitative agreement with experimental measurements.

Lin, P.↗
DOE OSTI2024

Enhanced Twist-Averaging Technique for Magnetic Metals: Applications Using Quantum Monte Carlo

In this study, we propose an improved twist-averaging (TA) scheme for quantum Monte Carlo methods that use converged Kohn–Sham or Hartree–Fock orbitals as the reference. This TA technique is tailored to sample the Brillouin zone of magnetic metals, although it naturally extends to nonmagnetic (NM) conducting systems. The proposed scheme aims to reproduce the reference magnetization and achieves charge neutrality by construction, thus avoiding the large energy fluctuations and the postprocessing needed to correct the energies. It shows the most robust convergence of total energy and magnetism to the thermodynamic limit (TDL) when compared to four other TA schemes. Diffusion Monte Carlo applications are shown on NM Al and ferromagnetic α-Fe. The cohesive energy of Al in the TDL shows an excellent agreement with the experimental result. Furthermore, the magnetic moments in α-Fe exhibit rapid convergence with an increasing number of twists.

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

Autoregressive Neural Network for Simulating Open Quantum Systems via a Probabilistic Formulation

The theory of open quantum systems lays the foundation for a substantial part of modern research in quantum science and engineering. Rooted in the dimensionality of their extended Hilbert spaces, the high computational complexity of simulating open quantum systems calls for the development of strategies to approximate their dynamics. In this Letter, we present an approach for tackling open quantum system dynamics. Using an exact probabilistic formulation of quantum physics based on positive operator-valued measure, we compactly represent quantum states with autoregressive neural networks; such networks bring significant algorithmic flexibility due to efficient exact sampling and tractable density. We further introduce the concept of string states to partially restore the symmetry of the autoregressive neural network and improve the description of local correlations. Efficient algorithms have been developed to simulate the dynamics of the Liouvillian superoperator using a forward-backward trapezoid method and find the steady state via a variational formulation. Our approach is benchmarked on prototypical one-dimensional and two-dimensional systems, finding results which closely track the exact solution and achieve higher accuracy than alternative approaches based on using Markov chain Monte Carlo method to sample restricted Boltzmann machines. Our Letter provides general methods for understanding quantum dynamics in various contexts, as well as techniques for solving high-dimensional probabilistic differential equations in classical setups.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1984

Atmospheric transfer of radiation above an inhomogeneous non-Lambertian reflective ground. II - Computational considerations and results

The theoretical foundation for solution of the three-dimensional radiative transfer problem described in the preceding paper is reviewed. Practical considerations involved in implementing the Fourier transform/Gauss-Seidel method on a minicomputer are discussed, along with derivations of symmetry relations and approximations which can be used to enhance the computational efficiency. Model results for a surface whose albedo varies as a step function are presented and compared with published solutions obtained by using the Monte Carlo method.

Diner, D. J.↗
NASA NTRS2019

Uncertainty Analysis of the CE-22 Advanced Nozzle Test Facility

This paper presents methods and results of a detailed measurement uncertainty analysis that was performed for the Advanced Nozzle Test Facility, CE-22, located at the NASA Glenn Research Center. Results for the uncertainty in thrust and flow coefficients, in addition to other variables of interest, are provided. Results are presented separately as random uncertainty (characterizing errors inherent to instrument or measurement environment, impacting repeatability), systematic uncertainty (capturing inaccuracies due to measurement process, calibration, installation effects or other sources which may introduce bias), and total combined uncertainty. The statistical methods and engineering judgments used to estimate elemental uncertainties are described. The analysis tool MANTUS (Measurement Analysis Tool for Uncertainty in Systems) was used to quantify instrumentation system uncertainty, and statistical analysis and engineering judgment were used to quantify other random and systematic uncertainty sources. The Monte Carlo method was used to propagate systematic and random elemental uncertainties to determine the uncertainties of various calculated variables of interest.

data quality↗
DOE OSTI2022

Hamming distance and the onset of quantum criticality

Simulating models for quantum correlated matter unveils the inherent limitations of deterministic classical computations. In particular, in the case of quantum Monte Carlo methods, this is manifested by the emergence of negative weight configurations in the sampling, that is, the sign problem (SP). There have been several recent calculations which exploit the SP to locate underlying critical behavior. Here, utilizing a metric that quantifies phase-space ergodicity in such sampling, the Hamming distance, we suggest a significant advance on these ideas to extract the location of quantum critical points in various fermionic models, in spite of the presence of a severe SP. Combined with other methods, exact diagonalization in our case, it elucidates both the nature of the different phases as well as their location, as we demonstrate explicitly for the honeycomb and triangular Hubbard models, in both their U(1) and SU(2) forms. Furthermore, our approach exemplifies a possible path allowing the exploration of the phase diagram of a variety of fermionic quantum models hitherto considered to be impractical via quantum Monte Carlo simulations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

PyOECP: A flexible open-source software library for estimating and modeling the complex permittivity based on the open-ended coaxial probe (OECP) technique

Here, we present PyOECP, a Python-based flexible open-source software for estimating and modeling the complex permittivity obtained from the open-ended coaxial probe (OECP) technique. The transformation of the measured reflection coefficient to complex permittivity is performed based on three different methods. The software library contains the dielectric spectra of common reference liquids, which can be used to transform the reflection coefficient into the dielectric spectra. Several Python routines that are commonly employed (e.g., SciPy and NumPy) in the field of science and engineering are required only so that the users can alter the software structure depending on their needs. The modeling algorithm exploits the Markov Chain Monte Carlo method for the data regression. The discrete relaxation models can be built by a proper combination of well-known relaxation models. In addition to these models, electrode polarization, a typical measurement artifact for interpreting dielectric spectra, can be incorporated into the modeling algorithm. A continuous relaxation model, which solves the Fredholm integral equation of the first kind (a mathematically ill-posed problem), is also included. This open-source software enables users to freely adjust the physical parameters to obtain physical insight into their materials under test and will be consistently updated for more accurate measurement and interpretation of dielectric spectra in an automated manner. This work describes the theoretical and mathematical background of the software, lays out the workflow, and validates the software functionality based on both synthetic and empirical data included in the software.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Electron scattering on A = 3 nuclei from quantum Monte Carlo based approaches

We perform first-principle calculations of electron-nucleus scattering on 3 He and 3 H using the Green's function Monte Carlo method and two approaches based on the factorization of the final hadronic state: the spectral-function formalism and the short-time approximation. These three methods are benchmarked among each other and compared to the experimental data for the longitudinal and transverse electromagnetic response functions of 3 He, and the inclusive cross sections of both 3 He and 3 H. Since these three approaches are based on the same description of nuclear dynamics of the initial target state, comparing their results enables a precise quantification of the uncertainties inherent to factorization schemes. At sufficiently large values of the momentum transfer, we find an excellent agreement of the Green's function Monte Carlo calculation with experimental data and with both the spectral-function formalism and the short-time approximation. Here, we also analyze the relevance of relativistic effects, whose inclusion becomes crucial to explain data at high momentum and energy transfer.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Electron scattering on ${\mathbf{A=3}}$ nuclei from quantum Monte Carlo based approaches

We perform first-principle calculations of electron-nucleus scattering on $^3$He and $^3$H using the Green's function Monte Carlo method and two approaches based on the factorization of the final hadronic state: the spectral-function formalism and the short-time approximation. These three methods are benchmarked among each other and compared to the experimental data for the longitudinal and transverse electromagnetic response functions of $^3$He, and the inclusive cross sections of both $^3$He and $^3$H. Since these three approaches are based on the same description of nuclear dynamics of the initial target state, comparing their results enables a precise quantification of the uncertainties inherent to factorization schemes. At sufficiently large values of the momentum transfer, we find an excellent agreement of the Green's function Monte Carlo calculation with experimental data and with both the spectral-function formalism and the short-time approximation. We also analyze the relevance of relativistic effects, whose inclusion becomes crucial to explain data at high momentum and energy transfer.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRSDate not supplied

Assessing Risk Due to Small Sample Size in Probability of Detection Analysis Using Tolerance Intervals

Small sample size (e.g.6-30) poses risk in results of probability of detection (POD) analysis using tolerance intervals. This method is also called as the limited sample or LS POD. The analysis is performed either during NDE procedure qualification or for assessment of reliability of an NDE procedure. The risk is primarily due to sampling error. Smaller samples are not likely to be random to the population or representative of the population. The small samples are likely to be biased. Biased samples have smaller standard deviation compared to the population. POD analysis with small biased sample can lead to overestimation of POD. Many sampling schemes are available in statistics to mitigate sampling risk. Primary objective of POD analysis is to determine a decision threshold from signal response measurements of a sample such that it is less than or equal to population decision threshold for 90% POD. Sampling error implies that this NDE reliability condition is violated. One of sampling types is called a representative sample. Representative samples reduce variance in POD estimates but also reduce magnitude of the error. Sampling sensitivity analysis for some sampling types is performed here using repetitive random sampling or Monte Carlo method. Six sampling types are considered for comparison. Some of the sampling types are similar to drawing a representative sample. LS POD model assumes random sampling. Therefore, random sampling is used as a basis for comparison with each sampling type. The sampling types used in the analysis are, A. Nominal and worst-case sampling, B. Worst-case sampling, C. Nominal case sampling, D. Random sampling, E. Random target, and sub-target sampling. F. Nominal target and sub-target sampling. Results of Monte Carlo simulation indicate that type F sampling can mitigate sampling risk and is also more practical to implement. Type A sampling may also mitigate the sampling risk, but it may be less practical to implement.

Ajay M Koshti↗
DOE OSTI2020

Shell-model studies of the astrophysical r p -process reactions S 34 ( p , γ ) Cl 35 and Cl 34 g , m ( p , γ ) Ar 35

Background: Dust grains condensed in the outflows of presolar classical novae should have been present in the protosolar nebula. Candidates for such presolar nova grains have been found in primitive meteorites and can in principle be identified by their isotopic ratios, but the ratios predicted by state-of-the-art one-dimensional hydrodynamic models are uncertain due to nuclear-physics uncertainties. Purpose: To theoretically calculate the thermonuclear rates and uncertainties of the S 34 ( p , γ ) Cl 35 and Cl 34 g , m ( p , γ ) Ar 35 reactions and investigate their impacts on the predicted 34 S/ 32 S isotopic ratio for presolar nova grains. Method: A shell-model approach in a (0 +1 ) ℏ ω model space was used to calculate the properties of resonances in the 34 S(p ,γ ) 35 Cl and 34 g,m Cl (p ,γ ) 35 Ar reactions and their thermonuclear rates. Uncertainties were estimated using a Monte Carlo method. The implications of these rates and their uncertainties on sulfur isotopic nova yields were investigated using a postprocessing nucleosynthesis code. The rates for transitions from the ground state of 34 Cl as well as from the isomeric first excited state of 34 Cl were explicitly calculated. Results: At energies in the resonance region near the proton-emission threshold, many negative-parity states appear. Energies, spectroscopic factors, and proton-decay widths are reported. The resulting thermonuclear rates are compared with previous determinations. Conclusions: The shell-model calculations alone are sufficient to constrain the variation of the 34 S/ 32 S ratios to within about 30%. Uncertainties associated with other reactions must also be considered, but in general we find that the 34 S/ 32 S ratios are not a robust diagnostic to clearly identify presolar grains made from nova ejecta.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1998

High-Density Plasma Reactors: Simulations for Design

The development of improved and more efficient plasma reactors is a costly process for the semiconductor industry. Until five years ago, the Industry made most of its advancements through a trial and error approach. More recently, the role of computational modeling in the design process has increased. Both conventional computational fluid dynamics (CFD) techniques like Navier-Stokes solvers as well as particle simulation methods are used to model plasma reactor flowfields. However, since high-density plasma reactors generally operate at low gas pressures on the order of 1 to 10 mTorr, a particle simulation may be necessary because of the failure of CFD techniques to model rarefaction effects. The direct simulation Monte Carlo method is the most widely accepted and employed particle simulation tool and has previously been used to investigate plasma reactor flowfields. A plasma DSMC code is currently under development at NASA Ames Research Center with its foundation as the object-oriented parallel Cornell DSMC code, MONACO. The present investigation is a follow up of a neutral flow investigation of the effects of process parameters as well as reactor design on etch rate and etch rate uniformity. The previous work concentrated on silicon etch of a chlorine flow in a configuration typical of electron cyclotron resonance (ECR) or helical resonator type reactors. The effects of the plasma on the dissociation chemistry were modeled by making assumptions about the electron temperature and number density. The electrons or ions themselves were not simulated.The present work extends these results by simulating the charged species.The electromagnetic fields are calculated such that power deposition is modeled self-consistently. Electron impact reactions are modeled along with mechanisms for charge exchange. An bipolar diffusion assumption is made whereby electrons remain tied to the ions. However, the velocities of tile electrons are allowed to be modified during collisions and are not confined to a Maxwellian distribution. The interaction between the neutral flow and plasma is examined, and results for etch rate uniformity from the previous research and the present plasma simulations are compared.

Hash, David B.↗
DOE OSTI2021

Theory of Trotter Error with Commutator Scaling

The Lie-Trotter formula, together with its higher-order generalizations, provides a simple approach to decomposing the exponential of a sum of operators. Despite significant effort, the error scaling of such product formulas remains poorly understood. We develop a theory of Trotter error that overcomes the limitations of truncating the Baker-Campbell-Hausdorff expansion. Our analysis directly exploits the commutativity of operator summands, producing tighter error bounds for both real- and imaginary-time evolutions. Whereas previous work achieves similar goals for systems with geometric locality or Lie-algebraic structure, our approach holds in general. We give a host of improved algorithms for digital quantum simulation and quantum Monte Carlo methods, nearly matching or even outperforming the best previous results. Our applications include: (i) a simulation of second-quantized plane-wave electronic structure, nearly matching the interaction-picture algorithm of Low and Wiebe; (ii) a simulation of $k$-local Hamiltonians almost with induced one-norm scaling, faster than the qubitization algorithm of Low and Chuang; (iii) a simulation of rapidly decaying power-law interactions, outperforming the Lieb-Robinson-based approach of Tran et al.; (iv) a hybrid simulation of clustered Hamiltonians, dramatically improving the result of Peng, Harrow, Ozols, and Wu; and (v) quantum Monte Carlo simulations of the transverse field Ising model and quantum ferromagnets, tightening previous analyses of Bravyi and Gosset. We obtain further speedups using the fact that product formulas can preserve the locality of the simulated system. Specifically, we show that local observables can be simulated with complexity independent of the system size for power-law interacting systems, which implies a Lieb-Robinson bound nearly matching a recent result of Tran et al. Our analysis reproduces known tight bounds for first- and second-order formulas. We further investigate the tightness of our bounds for higher-order formulas. For quantum simulation of a one-dimensional Heisenberg model with an even-odd ordering of terms, our result overestimates the complexity by only a factor of $5$. Our bound is also close to tight for power-law interactions and other orderings of terms. This suggests that our theory can accurately characterize Trotter error in terms of both the asymptotic scaling and the constant prefactor.

quantum computing, numerical analysis↗
NASA NTRS1993

Heat of segregation of single substitutional impurities

The method of Bozzolo, Ferrante and Smith (BFS) is applied for the calculation of the heat of segregation of single substitutional impurities in fcc metals. A simple equation for predicting the heat of segregation is derived for the rigid case (no atomic relaxations). The results of including atomic relaxation using a Monte Carlo method are also presented and the results compared with a number of experimental and theoretical results.

Bozzolo, Guillermo↗
NASA NTRS2014

Some Interesting Applications of Probabilistic Techiques in Structural Dynamic Analysis of Rocket Engines

Numerical and Analytical methods developed to determine damage accumulation in specific engine components when speed variation included. Dither Life Ratio shown to be well over factor of 2 for specific example. Steady‐State assumption shown to be accurate for most turbopump cases, allowing rapid calculation of DLR. If hot‐fire speed data unknown, Monte Carlo method developed that uses speed statistics for similar engines. Application of techniques allow analyst to reduce both uncertainty and excess conservatism. High values of DLR could allow previously unacceptable part to pass HCF criteria without redesign. Given benefit and ease of implementation, recommend that any finite life turbomachine component analysis adopt these techniques. Probability Values calculated, compared, and evaluated for several industry‐proposed methods for combining random and harmonic loads. Two new excel macros written to calculate combined load for any specific probability level. Closed form Curve fits generated for widely used 3(sigma) and 2(sigma) probability levels. For design of lightweight aerospace components, obtaining accurate, reproducible, statistically meaningful answer critical.

Brown, Andrew M.↗
NASA NTRS1992

Dynamically stratified Monte Carlo forecasting

A new method for performing Monte Carlo forecasts is introduced. The method, called dynamic stratification, selects initial perturbations based on a stratification of the error distribution. A simple implementation is presented in which the error distribution used for the stratification is estimated from a linear model derived from a large ensemble of 12-h forecasts with the full dynamic model. The stratification thus obtained is used to choose a small subsample of initial states with which to perform the dynamical Monte Carlo forecasts. Several test cases are studied using a simple two-level general circulation model with uncertain initial conditions. It is found that the method provides substantial reductions in the sampling error of the forecast mean and variance when compared to the more traditional approach of choosing the initial perturbations at random. The degree of improvement, however, is sensitive to the nature of the initial error distribution and to the base state. In practice the method may be viable only if the computational burden involved in obtaining an adequate estimate of the error distribution is shared with the data-assimilation procedure.

Schubert, Siegfried↗
DOE OSTI2021

Application of Monte Carlo Algorithms to Cardiac Imaging Reconstruction

Monte Carlo algorithms have a growing impact on nuclear medicine reconstruction processes. One ofthe main limitations of myocardial perfusion imaging (MPI) is the effective mitigation of the scattering component,which is particularly challenging in Single Photon Emission Computed Tomography (SPECT). In SPECT,no timing information can be retrieved to locate the primary source photons. Monte Carlo methods allow anevent-by-event simulation of the scattering kinematics, which can be incorporated into a model of the imagingsystem response. This approach was adopted in the late Nineties by several authors, and recently took advantageof the increased computational power made available by high-performance CPUs and GPUs. These recent developmentsenable a fast image reconstruction with improved image quality, compared to deterministic approaches.Deterministic approaches are based on energy-windowing of the detector response, and on the cumulative estimateand subtraction of the scattering component. In this paper, we review the main strategies and algorithms tocorrect the scattering effect in SPECT and focus on Monte Carlo developments, which nowadays allow the threedimensionalreconstruction of SPECT cardiac images in a few seconds.

Pharmacology & Pharmacy↗