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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Thermophysical Properties of Liquid Tritium: A Path Integral Monte Carlo Study

Here, we present worm-algorithm, path integral Monte Carlo simulations of bulk liquid tritium. The simulations are benchmarked against empirically known thermophysical properties of liquid deuterium and liquid tritium. Results for the pair correlation function, chemical potential, isothermal compressibility, isochoric heat capacity, and single-particle momentum distributions are reported. Given the benchmark comparisons, our predictions of liquid tritium properties are expected to be accurate to within a few percent. Our simulations unambiguously demonstrate the significance of nuclear quantum effects to the properties of liquid tritium. In particular, under saturated vapor pressure, the average molecular kinetic energy of the liquid is found to be more than 60% higher than the value expected from the classical equipartition theorem.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Sign Problem in Tensor-Network Contraction

We investigate how the computational difficulty of contracting tensor networks depends on the sign structure of the tensor entries. Using results from computational complexity, we observe that the approximate contraction of tensor networks with only positive entries has lower computational complexity as compared to tensor networks with general real or complex entries. This raises the question of how this transition in computational complexity manifests itself in the hardness of different tensor-network-contraction schemes. We pursue this question by studying random tensor networks with varying bias toward positive entries. First, we consider contraction via Monte Carlo sampling and find that the transition from hard to easy occurs when the tensor entries become predominantly positive; this can be understood as a tensor-network manifestation of the well-known negative-sign problem in quantum Monte Carlo. Second, we analyze the commonly used contraction based on boundary tensor networks. The performance of this scheme is governed by the number of correlations in contiguous parts of the tensor network (which by analogy can be thought of as entanglement). Remarkably, we find that the transition from hard to easy—i.e., from a volume-law to a boundary-law scaling of entanglement—already occurs for a slight bias of the tensor entries toward a positive mean, scaling inversely with the bond dimension D , and thus the problem becomes easy the earlier the larger D occurs. This is in contrast both to expectations and to the behavior found in Monte Carlo contraction, where the hardness at fixed bias increases with the bond dimension. To provide insight into this early breakdown of computational hardness and the accompanying entanglement transition, we construct an effective classical statistical-mechanical model that predicts a transition at a bias of the tensor entries of 1 / D , confirming our observations. We conclude by investigating the computational difficulty of computing expectation values of tensor-network wave functions (projected entangled-pair states, PEPSs) and find that in this setting, the complexity of entanglement-based contraction always remains low. We explain this by providing a local transformation that maps PEPS expectation values to a positive-valued tensor network. This not only provides insight into the origin of the observed boundary-law entanglement scaling but also suggests new approaches toward PEPS contraction based on positive decompositions. Published by the American Physical Society 2025

Chen, Jielun (ORCID:0000000178411545)↗
NASA NTRS1994

The effect of wave-particle interactions on the polar wind: Preliminary results

A Monte Carlo simulation was developed in order to study the effects of wave-particle interactions (WPI) on the plasma outflow in the polar wind. The simulation also considered the other mechanisms included in the `classical' polar wind studies such as gravity, the polarization electrostatic field, and the divergence of geomagnetic field lines. Although the plasma consisted of electrons, H(+) and O(+) ions, we emphasized the behavior of H(+) in this preliminary study. The ion distribution function, as well as the profiles of its moments (density, drift velocity, temperatures, etc.) were found for different levels of WPI, that is, for different values of normalized diffusion rates in the velocity space (normalized D(sub perpendicular) H(+)). We found that as the WPI strength increases: (1) the ion drift velocity increases and its density decreases; (2) the perpendicular temperature T(sub perpendicular) (H(+)) increases; (3) the parallel temperature T(sub parallel) (H(+)) first decreases and then increases due to the balance between the parallel adiabatic cooling and the transfer of the energy from the perpendicular to the parallel direction; and (4) the temperature anisotropy ((T(sub parallel) (H(+))/T(sub perpendicular) (H(+)) is reduced and even reversed in some cases. For strong WPI (normalized D(sub perpendicular) (H(+) much greater than 1), the ion distribution function shows weak conic features at high altitudes.

Barakat, A. R.↗
NASA NTRS2001

Transport Phenomena of Off-Axis Sputtering Deposition

Various high quality epitaxial films, especially oxides, have been synthesized using off-axis sputtering deposition. In this presentation, we report the experiment results of ZnO films grown by the off-axis sputtering deposition. Films were synthesized in temperatures ranged from room temperature to 600 C, and pressures from 5 mTorr to 150 mTorr. Film growth rate was measured by surface profilometer, ellipsometer, and wavelength dispersive spectrometry. Due to the collisions between the sputtered species and the residue gases, the kinetic energy of species was reduced and the transport of depositing species changed from a ballistic movement for low pressure to a diffusive drift for high pressure in which the transport species were almost thermalized. The measurements show an increase of growth rates along the gravity vector when the Knudsen number of transport species is less than 0.05, which suggests that gravity affected the transport characterization in off-axis sputtering deposition. Because the product of pressure (p) and travel distance (d) of sputtered species, pd, exceeds several mTorr-cm during film deposition, the classical simulations for sputtering process in high vacuum system may not be applied. Based on these experimental measurements, a transport process of the off-axis sputtering deposition is proposed. Several models including the Monte Carlo method and gravity-driven flow dynamics simulation will be discussed.

Zhu, S.↗
NASA NTRS2001

Transport Phenomena of Off-Axis Sputtering Deposition

Various high quality epitaxial films, especially oxides, have been synthesized using off-axis sputtering deposition. In this presentation, we report the experiment results of ZnO films grown by the off-axis sputtering deposition. Films were synthesized in temperatures ranged from room temperature to 600 C, and pressures from 5 mTorr to 150 mTorr. Film growth rate was measured by surface profilometer, ellipsometer, and wavelength dispersive spectrometry. Due to the collisions between the sputtered species and the residue gases, the kinetic energy of species was reduced and the transport of depositing species changed from a ballistic movement for low pressure to a diffuse drift for high pressure in which the transport species were almost thermalized. The measurements show an increase of growth rates along the gravity vector when the Knodson (Knudsen??) number of transport species is less than 0.05, which suggests that gravity affected the transport characterization in off-axis sputtering deposition. Because the product of pressure (p) and travel distance (d) of sputtered species, p exceeds several mTorr-cm during film deposition, the classical simulations for sputtering process in high vacuum system may not be applied. Based on these experimental measurements, a transport process of the off-axis sputtering deposition is proposed. Several methods including the Monte Carlo method and gravity-driven flow dynamics simulation will be discussed.

Zhu, S.↗
DOE OSTI2024

Optimization using pathwise algorithmic derivatives of electromagnetic shower simulations

Among the well-known methods to approximate derivatives of expectancies computed by Monte-Carlo simulations, averages of pathwise derivatives are often the easiest one to apply. Computing them via algorithmic differentiation typically does not require major manual analysis and rewriting of the code, even for very complex programs like simulations of particle-detector interactions in high-energy physics. However, the pathwise derivative estimator can be biased if there are discontinuities in the program, which may diminish its value for applications. This work integrates algorithmic differentiation into the electromagnetic shower simulation code HepEmShow based on G4HepEm, allowing us to study how well pathwise derivatives approximate derivatives of energy depositions in a sampling calorimeter with respect to parameters of the beam and geometry. We found that when multiple scattering is disabled in the simulation, means of pathwise derivatives converge quickly to their expected values, and these are close to the actual derivatives of the energy deposition. Additionally, we demonstrate the applicability of this novel gradient estimator for stochastic gradient-based optimization in a model example.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1972

An algorithm for targeting finite burn maneuvers

An algorithm was developed to solve the following problem: given the characteristics of the engine to be used to make a finite burn maneuver and given the desired orbit, when must the engine be ignited and what must be the orientation of the thrust vector so as to obtain the desired orbit? The desired orbit is characterized by classical elements and functions of these elements whereas the control parameters are characterized by the time to initiate the maneuver and three direction cosines which locate the thrust vector. The algorithm was built with a Monte Carlo capability whereby samples are taken from the distribution of errors associated with the estimate of the state and from the distribution of errors associated with the engine to be used to make the maneuver.

Barbieri, R. W.↗
DOE OSTI2026

IRMA

IRMA (In)elastic Representation of Materials As S(α,β) evaluations IRMA turns one phonon model into three outputs that usually require three separate tool chains: an evaluated nuclear-data file, predicted neutron-scattering spectra, and scattering kernels for Monte Carlo transport. The three outputs draw on a single, consistent description of the material, so the evaluation, the spectroscopy that can validate it, and the transport that uses it always agree about the physics. Nuclear data. IRMA writes ENDF-6 File 7 thermal scattering evaluations on automatically constructed (α, β) grids. This part reimplements and generalizes NJOY's LEAPR: the classic kernels reproduce freshly generated NJOY2016 tapes digit for digit and published reference tapes to about 1e-4, and the generalized paths add the exact coherent one-phonon term, anisotropic Debye-Waller tensors, coherent elastic for arbitrary crystals, and a per-species partition for polyatomic materials. The tapes feed NJOY, AMPX, FUDGE, and every transport code downstream of them. Neutron spectroscopy. The irma.spectra forward model projects the same physics onto an instrument's kinematics and resolution: INS spectra for VISION and generic indirect geometries, and 2-D S(Q,E) powder maps for direct-geometry spectrometers, from a phonopy model or straight from a phonon DOS. It can be used to predict a proposed measurement before beam time; in analysis, it supplies the calculated single-scattering counterpart of a measured spectrum, from the same material description the evaluation was built from. Monte Carlo transport. The irma.ncrystal exporter writes per-temperature scattering kernels for the companion NCrystal plugin, so McStas, OpenMC, and other NCrystal-aware codes sample the same physics. The exported kernels carry the per-site anisotropic Debye-Waller tensors, keeping directional coherent-elastic physics that NCrystal's standard scalar treatment does not represent. With the same physics inside a transport code, an entire beamline becomes a virtual experiment: IRMA's end-to-end validation ran a custom McStas implementation of the ARCS spectrometer, assembled from the existing McVine and McStas models, against measured data. From a bare crystal structure. The irma mlip front end builds the phonon model itself: a structure file and a choice of potential are enough. Nine pretrained machine-learned interatomic potentials are supported, on a laptop CPU, with no first-principles calculation; an approximate phonon model for a new material costs minutes, not a DFT campaign, and the build emits prefilled inputs for all three outputs. The result is a good starting point rather than a finished evaluation: survey-quality physics with every parameter exposed for review. A converged atomistic calculation enters the same way, as a phonopy model, when higher fidelity is needed.

Ramic, Kemal [Oak Ridge National Laboratory (ORNL)↗
DOE OSTI2026

Improved Kelbg Potentials for Z > 1 and Application to Carbon Plasmas

In this work, we present a general form for the electron‐ion diffractive potential derived from the quantum pair density matrix and fit to the improved Kelbg potential for atomic numbers up to $Z = 54$. We apply classical molecular dynamics using the improved Kelbg potential for carbon with various forms of the Pauli potential to compute internal energies and pressures for hot, dense plasma conditions. Our results are compared to an equation of state model based on path integral Monte Carlo and density functional theory simulations to examine the extent to which the improved Kelbg potential reproduces the internal energy and pressure of carbon plasmas. The regions of validity for carbon agree generally with those derived previously for hydrogen once pressure ionization effects are incorporated. Based on our carbon results and previously published hydrogen studies, we discuss the general applicability and limitations of these potentials for equation of state studies in warm dense matter and high energy density plasmas.

general physics↗
DOE OSTI2026

Quantum Monte Carlo and Fewer-Body Approaches to Scattering, Reactions, and Related Properties of Nuclei

The overall goals of this project were to advance understanding of reactions and scattering states in light nuclei, as well as related properties of bound states, and to facilitate application of that understanding to astrophysics and cosmology. These goals were pursued mainly using quantum Monte Carlo methods to compute nuclear properties using protons and neutrons as the basic degrees of freedom.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Langevin Dynamics modeling of gas-phase ion-ion recombination (Final Technical Report)

A self-consistent trajectory simulation approach to model MN reactions (Fig. 1) which incorporates the probability of electron transfer as a Monte Carlo operator (Fig. 2) was developed and published as Liu et al. J. Chem. Phys. 159, 114111 (2023). The electron transfer probability p ET estimated using the two-state Landau-Zener (LZ) theory was incorporated into classical trajectory simulations to elicit predictions of MN reaction cross-section σ (vacuum) or rate constant β (finite pressure). Electronic structure calculations with multireference configuration interaction (MRCI) and large correlation consistent basis sets were used to derive inputs to the LZ theory. The key advance of our trajectory simulation approach is the incorporation of electron transfer probability and the inclusion of the effect of ion-neutral interactions on MN using a Langevin representation of the effect of neutral gas on ions. For H + – H - and Li + – H(D) - pairs, our approach quantitatively agrees with measured speed-dependent cross-sections for up to ~10 5 m/s. For the ion pair Ne + – Cl - , our predictions of the MN rate constant at ~1 torr are a factor of ~2 – 3 higher than the experimentally measured value. Similarly, for Xe + – F - in the pressure range of ~20000 – 80000 Pa, our predictions of the MN rate constant are ~20% lower but are in excellent qualitative agreement with experimental data. The paradigm of using trajectory simulations to self-consistently model MN reactions is the basis for inclusion of additional non-classical, and static magnetic and electric field effects. Subsequent work, published as Roy et al. focused on modeling recombination rate constant for three ion pairs (rare gas Ar + cation and halide anions): Ar + – Cl - , Ar + – Br - , Ar + – I - , 2) considering spin-orbit couplings in the electronic structure calculations to obtain high-fidelity estimates of the electron transfer probability and incorporated within the classical trajectory simulations to elicit predictions. In addition to calculations of ion-ion recombination rate constants, a classical trajectory simulation technique (published as Roy et al. J. Chem. Phys. 162(9), 094104 (2023)) that uses quaternions to represent orientation of non-spherical particles (ions or aerosol particles) was developed to simulate the recombination of diatomic or more generally, polyatomic molecules. Finally, several other ion pairs such as Ne + – Cl - , Kr + – Cl - , were explored using the developed semi-classical trajectory simulations to understand various challenges in tackling electronic structure calculations. Using empirical approaches to parameterize the electron transfer radius, trajectory simulations were also used to probe the effect of ion number density on MN rate constant.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2008

Ares I Flight Control System Overview

This paper describes the control challenges posed by the Ares I vehicle, the flight control system design and performance analyses used to test and verify the design. The major challenges in developing the control system are structural dynamics, dynamic effects from the powerful first stage booster, aerodynamics, first stage separation and large uncertainties in the dynamic models for all these. Classical control techniques were employed using innovative methods for structural mode filter design and an anti-drift feature to compensate for translational and rotational disturbances. This design was coded into an integrated vehicle flight simulation and tested by Monte Carlo methods. The product of this effort is a linear, robust controller design that is easy to implement, verify and test.

Hall, Charles↗
NASA NTRS2006

Convective Weather Forecast Quality Metrics for Air Traffic Management Decision-Making

Since numerical weather prediction models are unable to accurately forecast the severity and the location of the storm cells several hours into the future when compared with observation data, there has been a growing interest in probabilistic description of convective weather. The classical approach for generating uncertainty bounds consists of integrating the state equations and covariance propagation equations forward in time. This step is readily recognized as the process update step of the Kalman Filter algorithm. The second well known method, known as the Monte Carlo method, consists of generating output samples by driving the forecast algorithm with input samples selected from distributions. The statistical properties of the distributions of the output samples are then used for defining the uncertainty bounds of the output variables. This method is computationally expensive for a complex model compared to the covariance propagation method. The main advantage of the Monte Carlo method is that a complex non-linear model can be easily handled. Recently, a few different methods for probabilistic forecasting have appeared in the literature. A method for computing probability of convection in a region using forecast data is described in Ref. 5. Probability at a grid location is computed as the fraction of grid points, within a box of specified dimensions around the grid location, with forecast convection precipitation exceeding a specified threshold. The main limitation of this method is that the results are dependent on the chosen dimensions of the box. The examples presented Ref. 5 show that this process is equivalent to low-pass filtering of the forecast data with a finite support spatial filter. References 6 and 7 describe the technique for computing percentage coverage within a 92 x 92 square-kilometer box and assigning the value to the center 4 x 4 square-kilometer box. This technique is same as that described in Ref. 5. Characterizing the forecast, following the process described in Refs. 5 through 7, in terms of percentage coverage or confidence level is notionally sound compared to characterizing in terms of probabilities because the probability of the forecast being correct can only be determined using actual observations. References 5 through 7 only use the forecast data and not the observations. The method for computing the probability of detection, false alarm ratio and several forecast quality metrics (Skill Scores) using both the forecast and observation data are given in Ref. 2. This paper extends the statistical verification method in Ref. 2 to determine co-occurrence probabilities. The method consists of computing the probability that a severe weather cell (grid location) is detected in the observation data in the neighborhood of the severe weather cell in the forecast data. Probabilities of occurrence at the grid location and in its neighborhood with higher severity, and with lower severity in the observation data compared to that in the forecast data are examined. The method proposed in Refs. 5 through 7 is used for computing the probability that a certain number of cells in the neighborhood of severe weather cells in the forecast data are seen as severe weather cells in the observation data. Finally, the probability of existence of gaps in the observation data in the neighborhood of severe weather cells in forecast data is computed. Gaps are defined as openings between severe weather cells through which an aircraft can safely fly to its intended destination. The rest of the paper is organized as follows. Section II summarizes the statistical verification method described in Ref. 2. The extension of this method for computing the co-occurrence probabilities in discussed in Section HI. Numerical examples using NCWF forecast data and NCWD observation data are presented in Section III to elucidate the characteristics of the co-occurrence probabilities. This section also discusses the procedure for computing throbabilities that the severity of convection in the observation data will be higher or lower in the neighborhood of grid locations compared to that indicated at the grid locations in the forecast data. The probability of coverage of neighborhood grid cells is also described via examples in this section. Section IV discusses the gap detection algorithm and presents a numerical example to illustrate the method. The locations of the detected gaps in the observation data are used along with the locations of convective weather cells in the forecast data to determine the probability of existence of gaps in the neighborhood of these cells. Finally, the paper is concluded in Section V.

Chatterji, Gano B.↗
DOE OSTI2024

Spinbox: tools for many-body quantum systems in a Monte Carlo context

Spinbox is a piece of software that facilitates quantum mechanical calculations relevant to Monte Carlo simulation of atomic nuclei. At the front lines of research on the nuclear many-body problem are a large number of supercomputer-scale simulation codes. These codes produce valuable results but can be hard to understand, especially for those without intimate knowledge of the relevant theoretical methods. Thus, tools that fill pedagogical roles are extremely valuable. Spinbox makes it easy for one to replicate and analyze the computational processes relevant to a Quantum Monte Carlo (QMC) simulation that may be difficult to understand/debug/analyze due to the scale of the corresponding simulation software. Spinbox is written in Python using other state-of-the-art Python modules for numerical calculations. While a number of Python libraries exist that are suited to general quantum many-body calculations, the motivation of Spinbox is quite particular. In Diffusion Monte Carlo methods (DMC, GFMC, AFDMC), the central calculation is the imaginary-time propagation of individual samples of the many-body wavefunction. Although quantum wavefunctions generally must be described by a probability distribution over a basis, DMC imbues particles (within one sample) with classical spatial coordinates. This method is unusual, so other Python packages are typically not set up to do this easily. Furthermore, the software has built-in options for nuclear systems assuming isospin symmetry, which can be set up with other libraries but is a nontrivial process to do so. Features: - numerical representation of samples of the many-body wavefunctions, including tensor-product states (used in AFDMC) - numerical representation of many-body operators, including tensor-product operators: general, spin, imaginary-time propagation, etc. - the correct associated arithmetic and algebra, implemented as class methods - classes for representing realistic nuclear two- and three-body Hamiltonians (e.g. Argonne V18, Illinois NNN) - large-scale parallel integration over random variables, crucial for the AFDMC method My goal is to make this package open source so that anyone may use it and contribute to it, particularly other researchers doing AFDMC calculations

Fox, Jordan↗
NASA NTRS1982

The influence of thermospheric winds on exospheric hydrogen on Venus

Monte Carlo models of the distribution of atomic hydrogen in the exosphere of Venus were computed which simulate the effects of thermospheric winds and the production of a 'hot' hydrogen component by charge exchange of H(+) and H and Q in the exosphere, as well as classic exospheric processes. A thermosphere wind system that is approximated by a retrograde rotating component with equatorial speed of 100 m/sec superimposed on a diurnal solar tide with cross-terminator day-to-night winds of 200 m/sec is shown to be compatible with the thermospheric hydrogen distribution deduced from Pioneer Venus orbiter measurements.

Hodges, R. R., Jr.↗
NASA NTRS2012

Modeling the Flow of Rarefied Gases at NASA

At modest temperatures, the thermal energy of atmospheric diatomic gases such as nitrogen is primarily distributed between only translational and rotational energy modes. Furthermore, these energy modes are fully excited such that the specific heat at constant volume is well approximated by the simple expression C(sub v) = 5/2 R. As a result, classical mechanics provides a suitable approximation at such temperatures of the true quantum mechanical behavior of the inter-molecular collisions of such molecules. Using classical mechanics, the transfer of energy between rotational and translation energy modes is studied. The approach of Lordi and Mates is adopted to compute the trajectories and time dependent rotational orientations and energies during the collision of two non-polar diatomic molecules. A Monte-Carlo analysis is performed collecting data from the results of many such simulations in order to estimate the rotational relaxation time. A Graphical Processing Unit (GPU) is employed to improve the performance of the Monte-Carlo analysis. A comparison of the performance of the GPU implementation to an implementation on traditional computer architecture is made. Effects of the assumed inter-molecular potential on the relaxation time are studied. The seminar will also present highlights of computational analyses performed at NASA Johnson Space Center of heat transfer in rarefied gases.

Forrest E. Lumpkin, III↗
DOE OSTI2025

Parton distribution functions from scalar light-front parton gas model

Here, we propose an application of a microcanonical ensemble with light-front kinematics to model the phase-space distribution of relativistic constituents of a bound state. These constituents denoted by partons are treated as classical spin-zero particles confined inside the bound state with inter-parton collisions as their only interaction. The microcanonical molecular dynamics ensemble is applied to obtain the phase-space distribution of such a thermodynamic system. We sample this phase-space distribution using Monte Carlo algorithms to obtain the parton distribution functions (PDFs) in scenarios with 3, 4, and 5 identical partons. In addition PDFs when a selected number of massless partons are mixed with 3 massive partons are also presented.

Microcanonical ensemble↗
DOE OSTI2025

Low-metallicity Nova Explosions: A Site for Weak rp -process Nucleosynthesis

Classical novae are common cataclysmic events involving a binary system of a white dwarf and a main-sequence or red giant companion star. In metal-poor environments, these explosions produce ejecta differently from their solar counterparts due to the accretion of subsolar-metallicity material onto the white dwarf. In particular, it has been suggested that the nucleosynthesis flow in such low-metallicity nova explosions extends up to the Cu–Zn region, much beyond the expected endpoint, around Ca, predicted for solar-metallicity classical novae. This behavior resembles a weak rp-process, and such nuclear activity has never been observed in accreting white dwarf binaries with typical accretion flows. In this work, we study the characteristics of the weak rp-process for four nova models with metallicities Z = 2 × 10 −9 , 10 −7 , 2 × 10 −6 , and 2 × 10 −5 , and explore the impact of the nuclear physics uncertainties via a Monte Carlo sensitivity study. We identify nuclear reactions whose uncertainties affect the production of intermediate-mass nuclei under these conditions. These reactions and relevant nuclear quantities are targets for measurements at stable or radioactive beam facilities to reduce their rate uncertainties.

Classical novae↗