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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 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Stability of fissile solution systems - 14614

A Dynamic System Simulation (DSS) has been developed for aqueous homogenous reactors (AHR) and subcritical accelerator-driven system employing fissile solution fuel. These models are comprised of coupled non-linear differential equations describing the neutronics, thermal hydraulic and radiolytic gas behavior in the time domain. Models of specific historic AHR, SUPO (Super Power), KEWB (Kinetics Experiment Water Boiler), and SILENE exhibit close agreement with experimental data in all operating modes including steady-state, ramp and step reactivity insertions. The set of non-linear equations have been utilized to generate a generic transfer function for this class of systems. Output from specific DSS models operating at steady-state is then utilized as input parameters into a transfer function specific to each. Traditional Bode amplitude and phase, Nyquist and Nichols plots, are then generated to examine stability. Results for SUPO and a generic accelerator-driven system suggest these systems are unconditionally stable in the linear approximation. This treatment offers a method to examine the physics and time-based evolution of a critical excursion in a fissile solution system and provides a means to examine the severity of the consequence. This approach provides insight into the characteristics of such and even and sensitivity to materials involved and configuration of the physical system. (authors)

42 ENGINEERING↗
DOE OSTI2016

THE MIRA–TITAN UNIVERSE: PRECISION PREDICTIONS FOR DARK ENERGY SURVEYS

Large-scale simulations of cosmic structure formation play an important role in interpreting cosmological observations at high precision. The simulations must cover a parameter range beyond the standard six cosmological parameters and need to be run at high mass and force resolution. A key simulation-based task is the generation of accurate theoretical predictions for observables using a finite number of simulation runs, via the method of emulation. Using a new sampling technique, we explore an eight-dimensional parameter space including massive neutrinos and a variable equation of state of dark energy. We construct trial emulators using two surrogate models (the linear power spectrum and an approximate halo mass function). The new sampling method allows us to build precision emulators from just 26 cosmological models and to systematically increase the emulator accuracy by adding new sets of simulations in a prescribed way. Emulator fidelity can now be continuously improved as new observational data sets become available and higher accuracy is required. Finally, using one ΛCDM cosmology as an example, we study the demands imposed on a simulation campaign to achieve the required statistics and accuracy when building emulators for investigations of dark energy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

A Procedure for Evaluating Modified Pulsed-Neutron- Source Experiments in Subcritical Nuclear Reactors

A theoretical interpretation of the modified pulsed-neutron-source experiments of Sjöstrand, Gozani, and Garelis and Russell is given using exact steady-state Boltzmann equations. Here, interpretation is based on a phenomenological description of the experiments and is patterned after work done on the Garelis-Russell method by Corngold. The basic approximation made is that the fundamental prompt-mode decay constant is much larger than any delayed-neutron precursor decay constant. The theoretical interpretation allows the reactivities measured by the above three modified pulsed-source techniques to be easily calculated and compared to more conventional definitions of reactivity. The calculations can be performed by any standard source-iteration code that has been modified to solve the inhomogeneous problem. Experiments were performed on the Cornell University Critical Assembly and interpreted with the aid of the above theory. Calculations and experiments agree to within 20%. Sjöstrand's method is found to give the best result for this reactor.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Data-scarce surrogate modeling of shock-induced pore collapse process

Understanding the mechanisms of shock-induced pore collapse is of great interest in various disciplines in sciences and engineering, including materials science, biological sciences, and geophysics. However, numerical modeling of the complex pore collapse processes can be costly. To this end, a strong need exists to develop surrogate models for generating economic predictions of pore collapse processes. Here, in this work, we study the use of a data-driven reduced-order model, namely dynamic mode decomposition, and a deep generative model, namely conditional generative adversarial networks, to resemble the numerical simulations of the pore collapse process at representative training shock pressures. Since the simulations are expensive, the training data are scarce, which makes training an accurate surrogate model challenging. To overcome the difficulties posed by the complex physics phenomena, we make several crucial treatments to the plain original form of the methods to increase the capability of approximating and predicting the dynamics. In particular, physics information is used as indicators or conditional inputs to guide the prediction. In realizing these methods, the training of each dynamic mode composition model takes only around 30 s on CPU. In contrast, training a generative adversarial network model takes 8 h on GPU. Moreover, using dynamic mode decomposition, the final-time relative error is around 0.3% in the reproductive cases. We also demonstrate the predictive power of the methods at unseen testing shock pressures, where the error ranges from 1.3 to 5% in the interpolatory cases and 8 to 9% in extrapolatory cases.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Determination of asymptotic normalization coefficients for the channel 16 O→ α+ 12 C: excited state 16 O(0 + ; 6.05 MeV)

Asymptotic normalization coefficients (ANC) determine the overall normalization of cross sections of peripheral radiative capture reactions. In the present paper, we treat the ANC C for the virtual decay 16 O(0 + ; 6.05 MeV)→ α+ 12 C(g.s.), the known values of which are characterized by a large spread (0.29 - 1.65) × 10 3 fm -1/2 . The ANC C is found by analytic continuation in energy of the α 12 C s-wave scattering amplitude, known from the phase-shift analysis of experimental data, to the pole corresponding to the 16O bound state and lying in the unphysical region of negative energies. To determine C, two different methods of analytic continuation are used. In the first method, the scattering data are approximated by the sum of polynomials in energy in the physical region and then extrapolated to the pole. The best way of extrapolation is chosen on the basis of the exactly solvable model. Within the second approach, the ANC C is found by solving the Schrödinger equation for the two-body α 12 C potential, the parameters of which are selected from the requirement of the best description of the phase-shift analysis data at a fixed experimental binding energy of 16 O(0 + ; 6.05 MeV) in the α+ 12 C channel. The values of the ANC C obtained within these two methods lie in the interval (886–1139) fm -1/2 .

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

An Incompressible, Depth-Averaged Lattice Boltzmann Method for Liquid Flow in Microfluidic Devices with Variable Aperture

Two-dimensional (2D) pore-scale models have successfully simulated microfluidic experiments of aqueous-phase flow with mixing-controlled reactions in devices with small aperture. A standard 2D model is not generally appropriate when the presence of mineral precipitate or biomass creates complex and irregular three-dimensional (3D) pore geometries. We modify the 2D lattice Boltzmann method (LBM) to incorporate viscous drag from the top and bottom microfluidic device (micromodel) surfaces, typically excluded in a 2D model. Viscous drag from these surfaces can be approximated by uniformly scaling a steady-state 2D velocity field at low Reynolds number. We demonstrate increased accuracy by approximating the viscous drag with an analytically-derived body force which assumes a local parabolic velocity profile across the micromodel depth. Accuracy of the generated 2D velocity field and simulation permeability have not been evaluated in geometries with variable aperture. We obtain permeabilities within approximately 10% error and accurate streamlines from the proposed 2D method relative to results obtained from 3D simulations. Additionally, the proposed method requires a CPU run time approximately 40 times less than a standard 3D method, representing a significant computational benefit for permeability calculations.

58 GEOSCIENCES↗
DOE OSTI2022

Accurate parameterization of the kinetic energy functional for calculations using exact-exchange

In this report, electronic structure calculations based on Kohn-Sham density functional theory (KSDFT) that incorporate exact exchange or hybrid functionals are associated with large computational expense, a consequence of the inherent cubic scaling bottleneck and large associated prefactor, which limits the length and time scales that can be accessed. Though orbital-free density functional theory (OFDFT) calculations scale linearly with system size and are associated with significantly smaller prefactor, they are limited by the absence of accurate density-dependent kinetic energy functionals. Therefore, the development of accurate density-dependent kinetic energy functionals is important for OFDFT calculations of large realistic systems. To this end, we propose a method to train kinetic energy functional models at the exact-exchange level of theory by using a dictionary of physically relevant terms that have been proposed in the literature in conjunction with linear or nonlinear regression methods to obtain the fitting coefficients. For our dictionary, we use gradient expansion of the kinetic energy, nonlocal models proposed in the literature and their nonlinear combinations, such as a model that incorporates spatial correlations between higher order derivatives of electron density at two points. The predictive capabilities of these models are assessed by using a variety of model one-dimensional systems that exhibit diverse bonding characteristics, such as a chain of eight hydrogens, LiF, LiH, C 4 H 2 , C 4 N 2 and C 3 O 2 . We show that by using data from model one-dimensional KSDFT calculations performed using the exact-exchange functional for only a few neutral structures, it is possible to generate models with high accuracy for charged systems as well as electron and kinetic energy densities during self-consistent field iterations. In addition, we show that it possible to learn both the orbital dependent terms, i.e., the kinetic energy and the exact-exchange energy, and models that incorporate additional nonlinearities in spatial correlations, such as a quadratic model, are needed to capture subtle features of the kinetic energy density that are present in exact-exchange-based KSDFT calculations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Small-angle scattering of particle assemblies

Small-angle scattering formulae for crystalline assemblies of arbitrary particles are derived from powder diffraction theory using the decoupling approximation. To do so, the pseudo-lattice factor is defined, and methods to overcome the limitations of the decoupling approximation are investigated. Further, approximated equations are suggested for the diffuse scattering from various defects of the first kind due to non-ideal particles, including size polydispersity, orientational disorder and positional fluctuation about their ideal positions. Calculated curves using the formalism developed herein are compared with numerical simulations computed without any approximation. For a finite-sized assembly, the scattering from the whole domain of the assembly must also be included, and this is derived using the correlation function approach.

assembly↗
DOE OSTI2014

Oscillator strengths and transition probabilities from the Breit–Pauli R-matrix method: Ne IV

The atomic parameters–oscillator strengths, line strengths, radiative decay rates (A), and lifetimes–for fine structure transitions of electric dipole (E1) type for the astrophysically abundant ion Ne IV are presented. The results include 868 fine structure levels with n≤ 10, l≤ 9, and 1/2≤J≤ 19/2 of even and odd parities, and the corresponding 83,767 E1 transitions. The calculations were carried out using the relativistic Breit–Pauli R-matrix method in the close coupling approximation. The transitions have been identified spectroscopically using an algorithm based on quantum defect analysis and other criteria. The calculated energies agree with the 103 observed and identified energies to within 3% or better for most of the levels. Some larger differences are also noted. The A-values show good to fair agreement with the very limited number of available transitions in the table compiled by NIST, but show very good agreement with the latest published multi-configuration Hartree–Fock calculations. The present transitions should be useful for diagnostics as well as for precise and complete spectral modeling in the soft X-ray to infra-red regions of astrophysical and laboratory plasmas. -- Highlights: •The first application of BPRM method for accurate E1 transitions in Ne IV is reported. •Amount of atomic data (n going up to 10) is complete for most practical applications. •The calculated energies are in very good agreement with most observed levels. •Very good agreement of A-values and lifetimes with other relativistic calculations. •The results should provide precise nebular abundances, chemical evolution etc.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

flowVS: channel-specific variance stabilization in flow cytometry

Abstract Background Comparing phenotypes of heterogeneous cell populations from multiple biological conditions is at the heart of scientific discovery based on flow cytometry (FC). When the biological signal is measured by the average expression of a biomarker, standard statistical methods require that variance be approximately stabilized in populations to be compared. Since the mean and variance of a cell population are often correlated in fluorescence-based FC measurements, a preprocessing step is needed to stabilize the within-population variances. Results We present a variance-stabilization algorithm, called flowVS, that removes the mean-variance correlations from cell populations identified in each fluorescence channel. flowVS transforms each channel from all samples of a data set by the inverse hyperbolic sine (asinh) transformation. For each channel, the parameters of the transformation are optimally selected by Bartlett’s likelihood-ratio test so that the populations attain homogeneous variances. The optimum parameters are then used to transform the corresponding channels in every sample. flowVS is therefore an explicit variance-stabilization method that stabilizes within-population variances in each channel by evaluating the homoskedasticity of clusters with a likelihood-ratio test. With two publicly available datasets, we show that flowVS removes the mean-variance dependence from raw FC data and makes the within-population variance relatively homogeneous. We demonstrate that alternative transformation techniques such as flowTrans, flowScape, logicle, and FCSTrans might not stabilize variance. Besides flow cytometry, flowVS can also be applied to stabilize variance in microarray data. With a publicly available data set we demonstrate that flowVS performs as well as the VSN software, a state-of-the-art approach developed for microarrays. Conclusions The homogeneity of variance in cell populations across FC samples is desirable when extracting features uniformly and comparing cell populations with different levels of marker expressions. The newly developed flowVS algorithm solves the variance-stabilization problem in FC and microarrays by optimally transforming data with the help of Bartlett’s likelihood-ratio test. On two publicly available FC datasets, flowVS stabilizes within-population variances more evenly than the available transformation and normalization techniques. flowVS-based variance stabilization can help in performing comparison and alignment of phenotypically identical cell populations across different samples. flowVS and the datasets used in this paper are publicly available in Bioconductor.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-G-BRC-16: Theory and Clinical Implications of the Constant Dosimetric Leaf Gap (DLG) Approximation

Purpose: Commercial dose calculation algorithms incorporate a single DLG value for a given beam energy that is applied across an entire treatment field. However, the physical processes associated with beam generation and dose delivery suggest that the DLG is not constant. The aim of this study is to evaluate the variation of DLG among all leaf pairs, to quantify how this variation impacts delivered dose, and to establish a novel method to correct dose distributions calculated using the approximation of constant DLG. Methods: A 2D diode array was used to measure the DLG for all 60 leaf pairs at several points along each leaf pair travel direction. This approach was validated by comparison to DLG values measured at select points using a 0.6 cc ion chamber with the standard formalism. In-house software was developed to enable incorporation of position dependent DLG values into dose distribution optimization and calculation. The accuracy of beam delivery of both the corrected and uncorrected treatment plans was studied through gamma pass rate evaluation. A comparison of DVH statistics in corrected and uncorrected treatment plans was made. Results: The outer 20 MLC leaf pairs (1.0 cm width) have DLG values that are 0.32 mm (mean) to 0.65 mm (maximum) lower than the central leaf-pair. VMAT plans using a large number of 1 cm wide leaves were more accurately delivered (gamma pass rate increased by 5%) and dose coverage was higher (D100 increased by 3%) when the 2D DLG was modeled. Conclusion: Using a constant DLG value for a given beam energy will result in dose optimization, dose calculation and treatment delivery inaccuracies that become significant for treatment plans with high modulation complexity scores delivered with 1 cm wide leaves.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

High-Pressure and Temperature Dependence of Electronic, Magnetic, Elastic, Thermodynamic, and Transport Properties of Full-Heusler Alloys Co{sub 2}YIn (Y = Nb, Zr)

Structural, elastic, magnetic, and electronic properties of Co{sub 2}YIn (Y = Nb, Zr) have been investigated by means of the full-potential linearized augmented plane wave along with generalized gradient approximation + U/modified Becke-Johnson method in the stable Fm-3m phase. The optimized equilibrium lattice parameter in stable phase is 6.1744 Å for Co{sub 2}NbIn and 6.2824 Å for Co{sub 2}ZrIn. We have calculated the spin-resolved density of states for both the alloys to show that the ferromagnetic behavior of Co{sub 2}NbIn is due to the exchange splitting of Co and Nb atoms and due to Co and Zr in Co{sub 2}ZrIn. In spin-up configuration, there is absence of energy gap while an energy gap can be seen in spin-down state for both the alloys exhibiting a half-metallic character. Through the elastic constants and their discussions, we have predicted the elastic behavior of the materials. The quasi-harmonic approximations have been employed to study the pressure- and temperature-dependent thermodynamic properties. The Boltzmann theory is employed to investigate the electronic transport properties of these alloys. The defined material properties may pay as a prime stand for the application of material in spintronics and thermoelectrics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Compressed sparse tensor based quadrature for vibrational quantum mechanics integrals

A new method for fast evaluation of high dimensional integrals arising in quantum mechanics is proposed. Here, the method is based on sparse approximation of a high dimensional function followed by a low-rank compression. In the first step, we interpret the high dimensional integrand as a tensor in a suitable tensor product space and determine its entries by a compressed sensing based algorithm using only a few function evaluations. Secondly, we implement a rank reduction strategy to compress this tensor in a suitable low-rank tensor format using standard tensor compression tools. This allows representing a high dimensional integrand function as a small sum of products of low dimensional functions. Finally, a low dimensional Gauss–Hermite quadrature rule is used to integrate this low-rank representation, thus alleviating the curse of dimensionality. Finally, numerical tests on synthetic functions, as well as on energy correction integrals for water and formaldehyde molecules demonstrate the efficiency of this method using very few function evaluations as compared to other integration strategies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Characterization and thermometry of dissipatively stabilized steady states

In this work we study the properties of dissipatively stabilized steady states of noisy quantum algorithms, exploring the extent to which they can be well approximated as thermal distributions, and proposing methods to extract the effective temperature T. We study an algorithm called the relaxational quantum eigensolver (RQE), which is one of a family of algorithms that attempt to find ground states and balance error in noisy quantum devices. In RQE, we weakly couple a second register of auxiliary ‘shadow’ qubits to the primary system in Trotterized evolution, thus engineering an approximate zero-temperature bath by periodically resetting the auxiliary qubits during the algorithm’s runtime. Balancing the infinite temperature bath of random gate error, RQE returns states with an average energy equal to a constant fraction of the ground state. We probe the steady states of this algorithm for a range of base error rates, using several methods for estimating both T and deviations from thermal behavior. In particular, we both confirm that the steady states of these systems are often well-approximated by thermal distributions, and show that the same resources used for cooling can be adopted for thermometry, yielding a fairly reliable measure of the temperature. These methods could be readily implemented in near-term quantum hardware, and for stabilizing and probing Hamiltonians where simulating approximate thermal states is hard for classical computers.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Debye temperature, thermal expansion, and heat capacity of TcC up to 100 GPa

Highlights: • A number of thermodynamic properties of rocksalt TcC are investigated for the first time. • The quasi-harmonic Debye model is applied to take into account the thermal effect. • The pressure and temperature up to about 100 GPa and 3000 K, respectively. - Abstract: Debye temperature, thermal expansion coefficient, and heat capacity of ideal stoichiometric TcC in the rocksalt structure have been studied systematically by using ab initio plane-wave pseudopotential density functional theory method within the generalized gradient approximation. Through the quasi-harmonic Debye model, in which the phononic effects are considered, the dependences of Debye temperature, thermal expansion coefficient, constant-volume heat capacity, and constant-pressure heat capacity on pressure and temperature are successfully predicted. All the thermodynamic properties of TcC with rocksalt phase have been predicted in the entire temperature range from 300 to 3000 K and pressure up to 100 GPa.

36 MATERIALS SCIENCE↗
DOE OSTI2018

A New Method for Interpreting Nonstationary Running Correlations and Its Application to the ENSO‐EAWM Relationship

Abstract We here propose a new statistical method to interpret nonstationary running correlations by decomposing them into a stationary part and a first‐order Taylor expansion approximation for the nonstationary part. Then, this method is applied to investigate the nonstationary behavior of the El Niño–Southern Oscillation (ENSO)‐East Asian winter monsoon (EAWM) relationship, which exhibits prominent multidecadal variations. It is demonstrated that the first‐order approximation of the nonstationary part can be expressed to a large extent by the impact of the nonlinear interaction between the Atlantic Multidecadal Oscillation (AMO) and ENSO (AMO*Niño3.4) on the EAWM. Therefore, the nonstationarity in the ENSO‐EAWM relationship comes predominantly from the impact of an AMO modulation on the ENSO‐EAWM teleconnection via this key nonlinear interaction. This general method can be applied to investigate nonstationary relationships that are often observed between various different climate phenomena.

Geng, Xin↗
DOE OSTI2024

Role of the likelihood for elastic scattering uncertainty quantification

In the last decade, uncertainty quantification (UQ) for optical model potentials (OMPs) has become a focal point for nuclear reaction theory, and several competing approaches for OMP UQ have recently been developed. Here, we clarify recent efforts to compare frequentist and Bayesian approaches in the context of OMP UQ [G. B. King et al., Phys. Rev. Lett. 122, 232502 (2019)]. We replicate a portion of that OMP UQ study but use independent statistical tools. Specifically, we compare two methods for OMP parameter inference from elastic scattering data: the Levenberg-Marquardt algorithm for χ 2 minimization on one hand and Markov chain Monte Carlo (MCMC) sampling on the other. Separately, we assess the common practice of using a renormalized likelihood (χ 2 /N), N being the number of data points, instead of the canonical weighted-least-squares likelihood (χ 2 ), as a way of accounting for unknown data correlations. Here, we show that for a generic linear model and for a five-parameter OMP analysis, frequentist and uniform-prior Bayesian approaches recover the same optimum and uncertainty estimates—not systematically larger uncertainties for the Bayesian approach, as was concluded in G. B. King et al., Phys. Rev. Lett. 122, 232502 (2019). Further, we show that if an additional, near-degenerate parameter is introduced into the same OMP analysis such that the parameter posterior becomes non-Gaussian, then covariance-based estimates of uncertainty become unreliable. Finally, we show that regardless of optimization approach, if χ 2 /N is used for the likelihood, the resulting parametric uncertainties increase by $\sqrt{N}$, and that this is responsible for the conclusions drawn in the revisited study. Based on our replication results, we find that a fortuitous cancellation of unreported errors and the renormalization factor can lead to improvement in empirical coverages, as was the case in the original comparative study. We emphasize that developing and applying a realistic likelihood function is an essential task in a UQ analysis, and that several recent UQ studies that employed a renormalized likelihood (i.e., including a 1/N factor) may have yielded unrealistically large uncertainties for elastic-scattering observables. If the parameter posterior deviates from multivariate-normal, a sampling-based approach like MCMC has a clear advantage over methods that assume the Laplace approximation holds. We note that empirical coverage can serve as an important internal check for the analyst whose model or data may have additional, unaccounted-for uncertainties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Fully converged plane-wave-based self-consistent G W calculations of periodic solids

The GW approximation is a well-known method to obtain the quasiparticle and spectral properties of systems ranging from molecules to solids. In practice, GW calculations are often employed with many different approximations and truncations. In this work, we describe the implementation of a fully self-consistent GW approach based on the solution of the Dyson equation using a plane wave basis set. Algorithmic, numerical, and technical details of the self-consistent GW approach are presented. The fully self-consistent GW calculations are performed for GaAs, ZnO, and CdS including semicores in the pseudopotentials. No further approximations and truncations apart from the truncation on the plane wave basis set are made in our implementation of the GW calculation. After adopting a special potential technique, a ~100Ry energy cutoff can be used without the loss of accuracy. We found that the self-consistent GW (sc-GW) significantly overestimates the bulk band gaps, and this overestimation is likely due to the underestimation of the macroscopic dielectric constants. On the other hand, the sc-GW accurately predicts the d-state positions, most likely because the d-state screening does not sensitively depend on the macroscopic dielectric constant. Our work indicates the need to include the high-order vertex term in order for the many-body perturbation theory to accurately predict the semiconductor band gaps. Further, it also sheds some light on why, in some cases, the G 0 W 0 bulk calculation is more accurate than the fully self-consistent GW calculation, because the initial density-functional theory has a better dielectric constant compared to experiments.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗