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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Stochastic Real-Time Second-Order Green’s Function Theory for Neutral Excitations in Molecules and Nanostructures

We present a real-time second-order Green’s function (GF) method for computing excited states in molecules and nanostructures, with a computational scaling of O(N e 3 ), where N e is the number of electrons. The cubic scaling is achieved by adopting the stochastic resolution of the identity to decouple the 4-index electron repulsion integrals. To improve the time propagation and the spectral resolution, we adopt the dynamic mode decomposition technique and assess the accuracy and efficiency of the combined approach for a chain of hydrogen dimer molecules of different lengths. We find that the stochastic implementation accurately reproduces the deterministic results for the electronic dynamics and excitation energies. Furthermore, we provide a detailed analysis of the statistical errors, bias, and long-time extrapolation. Overall, the approach offers an efficient route to investigate excited states in extended systems with open or closed boundary conditions.

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

Rate coefficients for rotational state-to-state transitions in H 2 O + H 2 O collisions for cometary and planetary applications, as predicted by mixed quantum-classical theory

We present new calculations of collision cross sections for state-to-state transitions between the rotational states in an H 2 O + H 2 O system, which are used to generate a new database of collisional rate coefficients for cometary and planetary applications. Calculations were carried out using a mixed quantum-classical theory approach that is implemented in the code MQCT. The large basis set of rotational states used in these calculations permits us to predict thermally averaged cross sections for 441 transitions in para- and ortho-H 2 O in a broad range of temperatures. It is found that all state-to-state transitions in the H 2 O + H 2 O system split into two well-defined groups, one with higher cross-section values and lower energy transfer, which corresponds to the dipole-dipole driven processes. The other group has smaller cross sections and higher energy transfer, driven by higher-order interaction terms. We present a detailed analysis of the theoretical error bars, and we symmetrized the state-to-state transition matrixes to ensure that excitation and quenching processes for each transition satisfy the principle of microscopic reversibility. We also compare our results with other data available from the literature for H 2 O + H 2 O collisions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Coordinated activities on evaluation of collisional data for fusion applications

It is the role of the Atomic and Molecular Data Unit of the International Atomic Energy Agency to review progress in the production, compilation and evaluation of atomic, molecular and plasma-surface interaction (AM/PSI) data for the fusion program and to support the development of internationally recommended libraries of AM/PSI data for fusion. In response to increasing requests from the fusion community the Unit has increased its effort to promote the assessment of data quality by organizing a series of meetings on the relevant issues: 1) Error propagation and sensitivity analysis, 2) Current status of evaluated databases, 3) Uncertainty estimates of theoretical data, 4) Experimental data evaluation, 5) Data evaluation methods and semi-empirical fits and 6) Establishment of an evaluators' network. The discussions and conclusions are summarized here.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2013

On the atomic line profiles in high pressure plasmas

In a previous contribution to this journal [H. P. Stormberg, J. Appl. Phys. 51(4), 1963 (1980)], Stormberg presented an analytical expression for the convolution of Lorentz and Levy line profiles, which models atomic radiative transitions in high pressure plasmas. Unfortunately, the derivations are flawed with errors and the final expression, while correct, is accompanied by misguiding comments about the meaning of the symbols used therein, in particular the “complex error function.” In this paper, we discuss the broadening mechanisms that give rise to Stormberg's model and present a correct derivation of his final result. We will also provide an alternative expression, based on the Faddeeva function, which has decisive computational advantages and emphasizes the real-valuedness of the result. The MATLAB/Octave scripts of our implementation have been made available on the publisher's website for future reference.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

High precision quantum-chemical treatment of adsorption: Benchmarking physisorption of molecular hydrogen on graphane

A multilevel hierarchical ab initio protocol for calculating adsorption on non-conducting surfaces is presented. It employs fully periodic treatment, which reaches local Møller-Plesset perturbation theory of second order (MP2) with correction for the basis set incompleteness via the local F12 technique. Post-MP2 corrections are calculated using finite clusters. That includes the coupled cluster treatment in the local and canonical frameworks (up to perturbative quadruples) and correlated core (with MP2). Using this protocol, the potential surface of hydrogen molecules adsorbed on graphane was computed. According to the calculations, hydrogen molecules are adsorbed on graphane in a perpendicular to the surface orientation with the minimum of the potential surface of around −3.6 kJ/mol located at the distance of 3.85 Å between the bond center of the hydrogen molecule and the mid-plane of graphane. The adsorption sites along the path from the downward-pointing carbon to the ring center of the graphane are energetically virtually equally preferable, which can enable nearly free translations of hydrogen molecules along these paths. Consequently, the hydrogen molecules on graphane most likely form a non-commensurate monolayer. The analysis of the remaining errors reveals a very high accuracy of the computed potential surface with an error bar of a few tenths of a kJ/mol. The obtained results are a high-precision benchmark for further theoretical and experimental studies of hydrogen molecules interacting with graphane.

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

Density functional theory of water with the machine-learned DM21 functional

The delicate interplay between functional-driven and density-driven errors in density functional theory (DFT) has hindered traditional density functional approximations (DFAs) from providing an accurate description of water for over 30 years. Recently, the deep-learned DeepMind 21 (DM21) functional has been shown to overcome the limitations of traditional DFAs as it is free of delocalization error. To determine if DM21 can enable a molecular-level description of the physical properties of aqueous systems within Kohn–Sham DFT, we assess the accuracy of the DM21 functional for neutral, protonated, and deprotonated water clusters. Furthermore, we find that the ability of DM21 to accurately predict the energetics of aqueous clusters varies significantly with cluster size. Additionally, we introduce the many-body MB-DM21 potential derived from DM21 data within the many-body expansion of the energy and use it in simulations of liquid water as a function of temperature at ambient pressure. We find that size-dependent functional-driven errors identified in the analysis of the energetics of small clusters calculated with the DM21 functional result in the MB-DM21 potential systematically overestimating the hydrogen-bond strength and, consequently, predicting a more ice-like local structure of water at room temperature.

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

Picosecond magneto-optic thermometry measurements of nanoscale thermal transport in AlN thin films

The thermal conductivity Λ of wide bandgap semiconductor thin films, such as AlN, affects the performance of high-frequency devices, power devices, and optoelectronics. However, accurate measurements of Λ in thin films with sub-micrometer thicknesses and Λ > 100 W m -1 K -1 is challenging. Widely used pump/probe metrologies, such as time–domain thermoreflectance (TDTR) and frequency–domain thermoreflectance, lack the spatiotemporal resolution necessary to accurately quantify thermal properties of sub-micrometer thin films with high Λ. In this work, we use a combination of magneto-optic thermometry and TiN interfacial layers to significantly enhance the spatiotemporal resolution of pump/probe thermal transport measurements. We use our approach to measure Λ of 100, 400, and 1000 nm AlN thin films. We coat AlN thin films with a ferromagnetic thin-film transducer with the geometry of (1 nm-Pt/0.4 nm-Co) x3 /(2 nm-TiN). This PtCo/TiN transducer has a fast thermal response time of <50 ps, which allows us to differentiate between the thermal response of the transducer, AlN thin film, and substrate. For the 100, 400, and 1000 nm thick AlN films, we determine Λ to be 200 ± 80, 165 ± 35, and 300 ± 70 W m -1 K -1 , respectively. We conclude with an uncertainty analysis that quantifies the errors associated with pump/probe measurements of thermal conductivity, as a function of transducer type, thin-film thermal conductivity, and thin-film thickness. Time resolved magneto-optic Kerr effect experiments can measure films that are three to five times thinner than is possible with standard pump/probe metrologies, such as TDTR. This advance in metrology will enable better characterization of nanoscale heat transfer in high thermal conductivity material systems like wide bandgap semiconductor heterostructures and devices.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Analytical solutions of a fractional diffusion-advection equation for solar cosmic-ray transport

Motivated by recent applications of superdiffusive transport models to shock-accelerated particle distributions in the heliosphere, we analytically solve a one-dimensional fractional diffusion-advection equation for the particle density. We derive an exact Fourier transform solution, simplify it in a weak diffusion approximation, and compare the new solution with previously available analytical results and with a semi-numerical solution based on a Fourier series expansion. We apply the results to the problem of describing the transport of energetic particles, accelerated at a traveling heliospheric shock. Our analysis shows that significant errors may result from assuming an infinite initial distance between the shock and the observer. We argue that the shock travel time should be a parameter of a realistic superdiffusive transport model.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Dark Energy Survey Year 1 results: weak lensing mass calibration of redMaPPer galaxy clusters

We constrain the mass-richness scaling relation of redMaPPer galaxy clusters identified in the Dark Energy Survey Year 1 data using weak gravitational lensing. We split clusters into 4 x 3 bins of richness lambda and redshift z for lambda >= 20 and 0.2 <= z <= 0.65 and measure the mean masses of these bins using their stacked weak lensing signal. By modelling the scaling relation as M-200m|lambda, M-0(lambda/40)(F)((1 + /1.35)(G), we constrain the normalization of the scaling relation at the 5.0 per cent level, finding M-0 = [3.081 +/- 0.075(stat) +/- 0.133(sys)] center dot 10(14) M-aS (TM) at lambda = 40 and = 0.35. The recovered richness scaling index is F = 1.356 +/- 0.051 (stat) +/- 0.008 (sys) and the redshift scaling index G = -0.30 +/- 0.30 (stat) +/- 0.06 (sys). These are the tightest measurements of the normalization and richness scaling index made to date from a weak lensing experiment. We use a semi-analytic covariance matrix to characterize the statistical errors in the recovered weak lensing profiles. Our analysis accounts for the following sources of systematic error: shear and photometric redshift errors, cluster miscentring, cluster member dilution of the source sample, systematic uncertainties in the modelling of the halo-mass correlation function, halo triaxiality, and projection effects. We discuss prospects for reducing our systematic error budget, which dominates the uncertainty on M-0. Our result is in excellent agreement with, but has significantly smaller uncertainties than, previous measurements in the literature, and augurs well for the power of the DES cluster survey as a tool for precision cosmology and upcoming galaxy surveys such as LSST, Euclid, and WFIRST

clusters↗
DOE OSTI2020

Moments of nucleon isovector structure functions in 2+1+1-flavor QCD

We present results on the isovector momentum fraction, $\langle x \rangle_{u–d}$ , helicity moment, $\langle x \rangle_{Δ u–Δd}$ , and the transversity moment, $\langle x \rangle_{δu–δd}$, of the nucleon obtained using nine ensembles of gauge configurations generated by the MILC Collaboration using 2 + 1 + 1 -flavors of dynamical highly improved staggered quarks. The correlation functions are calculated using the Wilson-Clover action, and the renormalization of the three operators is carried out nonperturbatively on the lattice in the RI'–MOM scheme. The data have been collected at lattice spacings a ≈ 0.15 , 0.12, 0.09, and 0.06 fm and $M_π$ ≈ 310 , 220, and 135 MeV, which are used to obtain the physical values using a simultaneous chiral-continuum-finite-volume fit. The final results, in the $\overline{\text{MS}}$ scheme at 2 GeV, are $\langle$ x $\rangle$ u – d = 0.173 ( 14 ) ( 07 ) , $\langle x \rangle_{Δu–Δd}$ = 0.213 ( 15 ) ( 22 ) , and $\langle x \rangle_{δu–δd}$ = 0.208 ( 19 ) ( 24 ) , where the first error is the overall analysis uncertainty and the second is an additional systematic uncertainty due to possible residual excited-state contributions. These results are consistent with other recent lattice calculations and phenomenological global fit values.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Nearly Optimal Lattice Simulation by Product Formulas

We consider simulating an n-qubit Hamiltonian with nearest-neighbor interactions evolving for time t on a quantum computer. We show that this simulation has gate complexity (nt)1+o(1) using product formulas, a straightforward approach that has been demonstrated by several experimental groups. While it is reasonable to expect this complexity—in particular, this was claimed without rigorous justification by Jordan, Lee, and Preskill—we are not aware of a straightforward proof. Furthermore, our approach is based on an analysis of the local error structure of product formulas, as introduced by Descombes and Thalhammer and significantly simplified here. We prove error bounds for canonical product formulas, which include well-known constructions such as the Lie-Trotter-Suzuki formulas. We also develop a local error representation for time-dependent Hamiltonian simulation, and we discuss generalizations to periodic boundary conditions, constant-range interactions, and higher dimensions. Combined with a previous lower bound, our result implies that product formulas can simulate lattice Hamiltonians with nearly optimal gate complexity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Separability of Mesh Bias and Parametric Uncertainty for a Full System Thermal Analysis

When making computational simulation predictions of multiphysics engineering systems, sources of uncertainty in the prediction need to be acknowledged and included in the analysis within the current paradigm of striving for simulation credibility. A thermal analysis of an aerospace geometry was performed at Sandia National Laboratories. Here, for this analysis, a verification, validation, and uncertainty quantification (VVUQ) workflow provided structure for the analysis, resulting in the quantification of significant uncertainty sources including spatial numerical error and material property parametric uncertainty. It was hypothesized that the parametric uncertainty and numerical errors were independent and separable for this application. This hypothesis was supported by performing uncertainty quantification (UQ) simulations at multiple mesh resolutions, while being limited by resources to minimize the number of medium and high resolution simulations. In conclusion, based on this supported hypothesis, a prediction including parametric uncertainty and a systematic mesh bias is used to make a margin assessment that avoids unnecessary uncertainty obscuring the results and optimizes use of computing resources.

42 ENGINEERING↗
DOE OSTI2016

SU-F-T-463: Light-Field Based Dynalog Verification

Purpose: To independently verify leaf positions in so-called dynalog files for a Varian iX linac with a Millennium 120 MLC. This verification provides a measure of confidence that the files can be used directly as part of a more extensive intensity modulated radiation therapy / volumetric modulated arc therapy QA program. Methods: Initial testing used white paper placed at the collimator plane and a standard hand-held digital camera to image the light and shadow of a static MLC field through the paper. Known markings on the paper allow for image calibration. Noise reduction was attempted with removal of ‘inherent noise’ from an open-field light image through the paper, but the method was found to be inconsequential. This is likely because the environment could not be controlled to the precision required for the sort of reproducible characterization of the quantum noise needed in order to meaningfully characterize and account for it. A multi-scale iterative edge detection algorithm was used for localizing the leaf ends. These were compared with the planned locations from the treatment console. Results: With a very basic setup, the image of the central bank A leaves 15–45, which are arguably the most important for beam modulation, differed from the planned location by [0.38±0.28] mm. Similarly, for bank B leaves 15–45 had a difference of [0.42±0.28] mm Conclusion: It should be possible to determine leaf position accurately with not much more than a modern hand-held camera and some software. This means we can have a periodic and independent verification of the dynalog file information. This is indicated by the precision already achieved using a basic setup and analysis methodology. Currently, work is being done to reduce imaging and setup errors, which will bring the leaf position error down further, and allow meaningful analysis over the full range of leaves.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

MIONet: Learning Multiple-Input Operators via Tensor Product

As an emerging paradigm in scientific machine learning, neural operators aim to learn operators, via neural networks, that map between infinite-dimensional function spaces. Several neural operators have been recently developed. However, all the existing neural operators are only designed to learn operators defined on a single Banach space; i.e., the input of the operator is a single function. Here, for the first time, we study the operator regression via neural networks for multiple-input operators defined on the product of Banach spaces. We first prove a universal approximation theorem of continuous multiple-input operators. We also provide a detailed theoretical analysis including the approximation error, which provides guidance for the design of the network architecture. Based on our theory and a low-rank approximation, we propose a novel neural operator, MIONet, to learn multiple-input operators. MIONet consists of several branch nets for encoding the input functions and a trunk net for encoding the domain of the output function. Here, we demonstrate that MIONet can learn solution operators involving systems governed by ordinary and partial differential equations. In our computational examples, we also show that we can endow MIONet with prior knowledge of the underlying system, such as linearity and periodicity, to further improve accuracy.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Sensitivity and Uncertainty Analysis of Plutonium and Cesium Isotopes in Modeling of BR3 Reactor Spent Fuel

Nuclear forensics has a broad task to characterize recovered nuclear or radiological material and interpret the results of investigation. One approach to isotopic characterization of nuclear material obtained from a reactor is to chemically separate and perform isotopic measurements on the sample and verify the results with modeling of the sample history, for example, operation of a nuclear reactor. The major actinide plutonium and fission product cesium are commonly measured signatures of the fuel history in a reactor core. This study investigates the uncertainty of the plutonium and cesium isotope ratios of a fuel rod discharged from a research pressurized water reactor when the location of the sample is not known a priori. A sensitivity analysis showed overpredicted values for the 240 Pu/ 239 Pu ratio toward the axial center of the rod and revealed a lower probability of the rod of interest (ROI) being on the periphery of the assembly. The uncertainty analysis found the relative errors due to only the rod position and boron concentration to be 17% to 36% and 7% to 15% for the 240 Pu/ 239 Pu and 137 Cs/ 135 Cs ratios, respectively. Lastly, this study provides a method for uncertainty quantification of isotope concentrations due to the location of the ROI. Similar analyses can be performed to verify future chemical and isotopic analyses.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

Muon g-2: An Interplay between Beam Dynamics and a Muon Decay Experiment at the Precision Frontier

The Muon g-2 Experiment at Fermilab (E989) will use the higher proton flux delivered by the Fermilab accelerator complex and improvements to the experimental apparatus to measure the anomalous magnetic moment of the muon to unprecedented precision. In addition to the increased statistics beyond the most recent measurement, the experiment relies on detailed understanding of the beam dynamics in the experiment’s storage ring as well as the incoming muon beam properties for proper assessments of systematic errors in the data analysis. Modeling and measurements of beam and storage ring properties, from proton targeting to muon storage, produce a unique unification of particle beam physics with a high energy physics experiment. Here the beam dynamics issues and analysis techniques essential to the g-2 experiment are presented and discussed.

43 PARTICLE ACCELERATORS↗
DOE OSTI2014

Statistical Approaches to Aerosol Dynamics for Climate Simulation

In this work, we introduce two general non-parametric regression analysis methods for errors-in-variable (EIV) models: the compound regression, and the constrained regression. It is shown that these approaches are equivalent to each other and, to the general parametric structural modeling approach. The advantages of these methods lie in their intuitive geometric representations, their distribution free nature, and their ability to offer a practical solution when the ratio of the error variances is unknown. Each includes the classic non-parametric regression methods of ordinary least squares, geometric mean regression, and orthogonal regression as special cases. Both methods can be readily generalized to multiple linear regression with two or more random regressors.

Compound regression↗
DOE OSTI2017

Report on SNL RCBC control options

The attractive performance of the S-CO 2 recompression cycle arises from the thermo-physical properties of carbon dioxide near the critical point. However, to ensure efficient operation of the cycle near the critical point, precise control of the heat removal rate by the Printed Circuit Heat Exchanger (PCHE) upstream of the main compressor is required. Accomplishing this task is not trivial because of the large variations in fluid properties with respect to temperature and pressure near the critical point. The use of a model-based approach for the design of a robust feedback regulator is being investigated to achieve acceptable control of heat removal rate at different operating conditions. A first step in this procedure is the development of a dynamic model of the heat exchanger. In this work, a one-dimensional (1-D) control-oriented model of the PCHE was developed using the General Plant Analyzer and System Simulator (GPASS) code. GPASS is a transient simulation code that supports analysis and control of power conversion cycles based on the S-CO 2 Brayton cycle. This modeling capability was used this fiscal year to analyze experiment data obtained from the heat exchanger in the SNL recompression Brayton cycle. The analysis suggested that the error in the water flowrate measurement was greater than required for achieving precise control of heat removal rate. Accordingly, a new water flowmeter was installed, significantly improving the quality of the measurement. Comparison of heat exchanger measurements in subsequent experiments with code simulations yielded good agreement establishing a reliable basis for the use of the GPASS PCHE model for future development of a model-based feedback controller.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗