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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 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Quantum Monte Carlo study of lattice polarons in the two-dimensional three-orbital Su–Schrieffer–Heeger model

The electron–lattice interaction gives rise to a rich set of phenomena in quantum materials. Microscopically, this interaction often arises from the modulation of orbital overlaps; however, many theoretical studies neglect such couplings. Here, we present an exact diagonalization and determinant quantum Monte Carlo study of a three-orbital Su–Schrieffer–Heeger (SSH) model, on a two-dimensional Lieb lattice and in the negative charge transfer regime. At half-filling (one hole/unit cell), we observe a bipolaron insulating phase with a bond-disproportionate lattice. This phase is robust against moderate hole doping but is suppressed at large hole concentrations, leading to a metallic polaron-liquid-like state with fluctuating patches of local distortions. We also find an s-wave superconducting state at large hole doping that primarily appears on the oxygen sublattice. Our work provides a non-perturbative view of SSH-type couplings in two dimensions with implications for materials where such couplings are dominant.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Hybrid Parameter Search and Dynamic Model Selection for Mixed-Variable Bayesian Optimization

Herein this article presents a new type of hybrid model for Bayesian optimization (BO) adept at managing mixed variables, encompassing both quantitative (continuous and integer) and qualitative (categorical) types. Our proposed new hybrid models (named hybridM) merge the Monte Carlo Tree Search structure (MCTS) for categorical variables with Gaussian Processes (GP) for continuous ones. hybridM leverages the upper confidence bound tree search (UCTS) for MCTS strategy, showcasing the tree architecture’s integration into Bayesian optimization. Our innovations, including dynamic online kernel selection in the surrogate modeling phase and a unique UCTS search strategy, position our hybrid models as an advancement in mixed-variable surrogate models. Numerical experiments underscore the superiority of hybrid models, highlighting their potential in Bayesian optimization.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

MCNP6.3 Unstructured Mesh Verification: GodivR and CANDU Models

A geometric cell of the Monte Carlo N-Particle (MCNP)1 transport code is traditionally created by using Boolean operators on defined surfaces. This constructive solid geometry (CSG) capability has been available in the MCNP code since its beginning. However, a CSG model approach is limited when it comes to constructing a representative geometry for a complex model in its ability to capture a correct model representation. Starting with the version 6.0, the MCNP code has the ability of embedding an unstructured mesh (UM) model into a CSG cell to create a hybrid geometry [1]. The MCNP UM feature provides the flexibility of defining very complex geometries because computer aided design (CAD) and mesh generation software packages can be utilized to construct UM models for MCNP simulations.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1994

Implementation of a vibrationally linked chemical reaction model for DSMC

A new procedure closely linking dissociation and exchange reactions in air to the vibrational levels of the diatomic molecules has been implemented in both one- and two-dimensional versions of Direct Simulation Monte Carlo (DSMC) programs. The previous modeling of chemical reactions with DSMC was based on the continuum reaction rates for the various possible reactions. The new method is more closely related to the actual physics of dissociation and is more appropriate to the particle nature of DSMC. Two cases are presented: the relaxation to equilibrium of undissociated air initially at 10,000 K, and the axisymmetric calculation of shuttle forebody heating during reentry at 92.35 km and 7500 m/s. Although reaction rates are not used in determining the dissociations or exchange reactions, the new method produces rates which agree astonishingly well with the published rates derived from experiment. The results for gas properties and surface properties also agree well with the results produced by earlier DSMC models, equilibrium air calculations, and experiment.

Carlson, A. B.↗
DOE OSTI2025

Bayesian prior construction for uncertainty quantification in first-principles statistical mechanics

First-principles statistical mechanics enables the prediction of thermodynamic and kinetic properties of materials, but is computationally expensive. Many approaches require surrogate models to calculate energies within Monte Carlo or molecular dynamics simulations. Inexpensive surrogates such as cluster expansions enable otherwise intractable calculations by interpolating data from higher accuracy methods, such as Density Functional Theory (DFT). Surrogate models introduce uncertainty into downstream calculations, in addition to any uncertainty inherent to DFT calculations. Bayesian frameworks address this by quantifying uncertainty and incorporating expert knowledge through priors. However, constructing effective priors remains challenging. This work introduces and describes practical strategies for building Bayesian cluster expansions, focusing on basis truncation, hyperparameter selection, and ground state replication. We analyze multiple basis truncation schemes, compare cross-validation to the evidence-approximation for hyperparameter optimization, and provide methods to find and enforce ground-state-preserving models through priors. Additionally, we compare the uncertainties between different approximations to DFT (LDA, PBE, SCAN) against the uncertainty introduced with the use of cluster expansion surrogate models. These approaches are demonstrated on the BCC Li x Mg 1-x and Li x Al 1-x alloys, which are both of interest for solid-state Li batteries. Our results provide guidelines for constructing and utilizing Bayesian cluster expansions, thereby improving the transparency of materials modeling. Furthermore, the approaches and insights developed in this work can be transferred to a wide range of cluster expansion surrogate models, including the atomic cluster expansion and related machine-learned interatomic potential architectures.

Alloy theory↗
DOE OSTI2022

AR reactor neutronics multi-code validation*

The affordable, robust, compact (ARC) reactor is a tokamak fusion reactor concept currently under development by Commonwealth Fusion Systems and Massachusetts Institute of Technology. There are three important neutronics considerations for the operation of the ARC reactor: (1) breeding of enough tritium in the blanket to sustain the D–T reaction in the plasma; (2) ensuring low fluence on the superconducting toroidal field coils; and (3) assessing neutron volumetric heating in structural components. Here, this work aims to perform a validation of the neutronics analysis approach by code-to-code comparison. State-of-the-art software stacks are employed for the neutronics analysis of the ARC reactor, and a computer-aided design (CAD) model is used directly for Monte Carlo (MC) neutron transport calculations. Three software stacks, Attila-MCNP, OpenMC-DAGMC, and Shift-DAGMC, are used to perform neutronic analyses of a 90° sector CAD model of the ARC reactor. In conclusion, results show that the flux tallies calculated by the three software stacks are very close. Also, the volumetric heating and tritium breeding values have less than 0.6% relative difference between codes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1992

Evaluation of thermochemical models for particle and continuum simulations of hypersonic flow

Computations are presented for one-dimensional, strong shock waves that are typical of those that form in front of a reentering spacecraft. The fluid mechanics and thermochemistry are modeled using two different approaches. The first employs traditional continuum techniques in solving the Navier-Stokes equations. The second approach employs a particle simulation technique (the direct simulation Monte Carlo method, DSMC). The thermochemical models employed in these two techniques are quite different. The present investigation presents an evaluation of thermochemical models for nitrogen under hypersonic flow conditions. Four separate cases are considered that are dominated in turn by vibrational relaxation, weak dissociation, strong dissociation and weak ionization. In near-continuum, hypersonic flow, the nonequilibrium thermochemical models employed in continuum and particle simulations produce nearly identical solutions. Further, the two approaches are evaluated successfully against available experimental data for weakly and strongly dissociating flows.

Boyd, Iain D.↗
NASA NTRSDate not supplied

Updates to the Predictive Materials Modeling Software Tools

Updates on NASA's efforts to build predictive material models from the micro-scale to the macro-scale are presented. To complement the mission design cycle process and reduce the need for extensive testing, NASA is developing modeling and simulation tools that enable characterizing material properties and response to hot plasma experienced during atmospheric entry. The PuMA (microstructure analysis), PATO (macroscale material response), SPARTA (direct simulation Monte Carlo) and ARCHeS (arc heater modeling) codes are described. A range of applications, encompassing calculating effective material properties, study of high shear boundary layer flow over woven materials, new model of silicone-based coatings, new model of mechanical erosion, as well as approach to loose multi-physics coupling, are presented.

material modeling↗
DOE OSTI2024

Skewness and kurtosis of mean transverse momentum fluctuations at the LHC energies

The first measurements of skewness and kurtosis of mean transverse momentum ($\langle$$p_T\rangle$) fluctuations are reported in Pb–Pb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV, Xe–Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV and pp collisions at $\sqrt{s}$ = 5.02 TeV using the ALICE detector. The measurements are carried out as a function of system size $\langle$dN ch /dη$\rangle$$^{1/3}_{|η|<0.5}$, using charged particles with transverse momentum ($p_T$) and pseudorapidity (η), in the range 0.2<$p_T$<3.0 GeV/c and |η|<0.8, respectively. In Pb–Pb and Xe–Xe collisions, positive skewness is observed in the fluctuations of $\langle$$p_T\rangle$ for all centralities, which is significantly larger than what would be expected in the scenario of independent particle emission. This positive skewness is considered a crucial consequence of the hydrodynamic evolution of the hot and dense nuclear matter created in heavy-ion collisions. Furthermore, similar observations of positive skewness for minimum bias pp collisions are also reported here. Kurtosis of $\langle$$p_T\rangle$ fluctuations is found to be in good agreement with the kurtosis of Gaussian distribution, for most central Pb–Pb collisions. Hydrodynamic model calculations with MUSIC using Monte Carlo Glauber initial conditions are able to explain the measurements of both skewness and kurtosis qualitatively from semicentral to central collisions in Pb–Pb system. Color reconnection mechanism in PYTHIA8 model seems to play a pivotal role in capturing the qualitative behavior of the same measurements in pp collisions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Practical Insights on Applying Simulation-Based Control Methods in Experimental Studies

Advanced nuclear reactors are crucial to the future of energy both in the United States and around the globe. In contrast to the current operating fleet, they are characterized as being deployable in remote locations and able to operate in semi-autonomous or autonomous fashion. This leap forward necessitates a new reactor control paradigm. Because advanced nuclear reactors are still under development in the United States, the creation of new control methods to achieve autonomous operations has been based on systems modeling and simulation. However, an important factor in successfully deploying these new control methods is the ability to seamlessly transition from simulation environments to real-world settings. Control methods tested in both simulation and experimental settings need to be investigated in the context of advanced reactor applications. This work developed a series of simple controllers for Idaho National Laboratory (INL)’s Microreactor Applications Research Validation and Evaluation (MARVEL) microreactor operating in load-following scenarios. These controllers were tested in both simulation and experimental settings, and a comparative performance analysis was performed. The simulation tests leveraged the Control and Optimization Modular Modeling Application for Nuclear Deployment (COMMAND) software developed in a previous stage of the current effort, along with the MARVEL Reactor Excursion and Leak Analysis Program (RELAP5-3D) and Monte Carlo N-Particle (MCNP) models. The experimental tests leveraged the COMMAND software, MARVEL models, and the U.S. Department of Energy Microreactor Program’s Microreactor Automated Control System (MACS). MACS was developed to serve as a control method testbed. It was customized to mirror the MARVEL microreactor, and COMMAND enabled MACS to emulate the physics of MARVEL. The load-following controller was developed using the simulation platform, with efforts to emulate real systems by introducing actuator saturation and noise. These factors were incrementally accounted for in the controller design. After finalizing the controller design, it was implemented with the experimental setup. The experimental conditions tested included an initial test under conditions similar to the final simulation test, and two additional scenarios. The first scenario introduced additional actuator saturation to account for equipment aging over time, which was unknown to the controller. The second scenario introduced sensor delay, a phenomenon anticipated with the use of remote operations or wireless communication in advanced reactors. These tests revealed several notable differences. While the controller performed well in simulation, it exhibited several limitations when transitioning to hardware. The main challenges involved maintaining the steady-state target power, as evidenced by larger error values between the true reactor power and setpoint power, as well as persistent oscillations in controlled reactor power. These issues could lead to unacceptable transient conditions in real reactor testing. Introducing actuator aging and stochastic delays in the experimental setup significantly impacted controller performance, resulting in increased overshoot and undershoot, and exacerbated error and oscillations previously mentioned. These findings underscore the importance of experimental testbeds for testing and validating control methods, as controllers developed using only theory and/or simulation may perform unexpectedly when applied to actual hardware. This research emphasizes the need for an experimental testbed for achieving such validation.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
NASA NTRS1980

A radiative transfer model for remote sensing of laser induced fluorescence of phytoplankton in non-homogeneous turbid water

A radiative transfer computer model was developed to characterize the total flux of chlorophyll a fluoresced or backscattered photons when laser radiation is incident on turbid water that contains a non-homogeneous suspension of inorganic sediments and phytoplankton. The radiative transfer model is based on the Monte Carlo technique and assumes that: (1) the aquatic medium can be represented by a stratified concentration profile; and (2) that appropriate optical parameters can be defined for each layer. The model was designed to minimize the required computer resources and run time. Results are presented for an anacystis marinus culture.

Venable, D. D.↗
NASA NTRS1993

Development and application of computational aerothermodynamics flowfield computer codes

Computations are presented for one-dimensional, strong shock waves that are typical of those that form in front of a reentering spacecraft. The fluid mechanics and thermochemistry are modeled using two different approaches. The first employs traditional continuum techniques in solving the Navier-Stokes equations. The second-approach employs a particle simulation technique (the direct simulation Monte Carlo method, DSMC). The thermochemical models employed in these two techniques are quite different. The present investigation presents an evaluation of thermochemical models for nitrogen under hypersonic flow conditions. Four separate cases are considered. The cases are governed, respectively, by the following: vibrational relaxation; weak dissociation; strong dissociation; and weak ionization. In near-continuum, hypersonic flow, the nonequilibrium thermochemical models employed in continuum and particle simulations produce nearly identical solutions. Further, the two approaches are evaluated successfully against available experimental data for weakly and strongly dissociating flows.

Venkatapathy, Ethiraj↗
NASA NTRS1995

Magnetic Compton-induced pair cascade model for gamma-ray pulsars

Electrons accelerated to relativistic energies in pulsar magnetospheres will Compton scatter surface thermal emission and nonthermal optical, UV, and soft X-ray emission to gamma-ray energies, thereby initiating a pair cascade through synchrotron radiation and magnetic pair production. This process is proposed as the origin of the high-energy radiation that has been detected from six isolated pulsars. We construct an analytic model of magnetic Compton scattering near the polar cap of isolated pulsar magnetospheres and present approximate analytic derivations for scattered spectra, electron energy-loss rates, and photon luminosities. A Monte Carlo simulation is used to model the pair cascade induced by relativistic electrons scattering photons through the cyclotron resonance. For simplicity, the primary electrons are assumed to be monoenergetic and the nonresonant emission is omitted. Assuming that the angle phi(sub B) between the magnetic and spin axes is approximately equal to the polar-cap angle theta(sub pc), this model can produce both double-peaked and broad single-peaked pulse profiles and account for the trend of harder gamma-ray spectra observed from older pulsars.

Sturner, Steven J.↗
NASA NTRS2013

Nuclear Thermal Rocket Simulation in NPSS

Four nuclear thermal rocket (NTR) models have been created in the Numerical Propulsion System Simulation (NPSS) framework. The models are divided into two categories. One set is based upon the ZrC-graphite composite fuel element and tie tube-style reactor developed during the Nuclear Engine for Rocket Vehicle Application (NERVA) project in the late 1960s and early 1970s. The other reactor set is based upon a W-UO2 ceramic- metallic (CERMET) fuel element. Within each category, a small and a large thrust engine are modeled. The small engine models utilize RL-10 turbomachinery performance maps and have a thrust of approximately 33.4 kN (7,500 lbf ). The large engine models utilize scaled RL-60 turbomachinery performance maps and have a thrust of approximately 111.2 kN (25,000 lbf ). Power deposition profiles for each reactor were obtained from a detailed Monte Carlo N-Particle (MCNP5) model of the reactor cores. Performance factors such as thermodynamic state points, thrust, specific impulse, reactor power level, and maximum fuel temperature are analyzed for each engine design.

Belair, Michael L.↗
NASA NTRS2013

Nuclear Thermal Rocket Simulation in NPSS

Four nuclear thermal rocket (NTR) models have been created in the Numerical Propulsion System Simulation (NPSS) framework. The models are divided into two categories. One set is based upon the ZrC-graphite composite fuel element and tie tube-style reactor developed during the Nuclear Engine for Rocket Vehicle Application (NERVA) project in the late 1960s and early 1970s. The other reactor set is based upon a W-UO2 ceramic-metallic (CERMET) fuel element. Within each category, a small and a large thrust engine are modeled. The small engine models utilize RL-10 turbomachinery performance maps and have a thrust of approximately 33.4 kN (7,500 lbf ). The large engine models utilize scaled RL-60 turbomachinery performance maps and have a thrust of approximately 111.2 kN (25,000 lbf ). Power deposition profiles for each reactor were obtained from a detailed Monte Carlo N-Particle (MCNP5) model of the reactor cores. Performance factors such as thermodynamic state points, thrust, specific impulse, reactor power level, and maximum fuel temperature are analyzed for each engine design.

Belair, Michael L.↗
NASA NTRS2007

Simulating Flights of Future Launch Vehicles and Spacecraft

Marshall Aerospace Vehicle Representation in C (MAVERIC) is a computer program for generic, low-to-high-fidelity simulation of the flight(s) of one or more launch vehicle(s) or spacecraft. MAVERIC is designed to accommodate multi-staged vehicles, powered serially or in parallel, with multiple engines, tanks, and cargo elements. Engines can be of jet or conventional rocket types, using either liquid or solid propellants. MAVERIC includes generic subsystem software models for propulsion systems, mass properties, reaction control systems, aerodynamic properties, guidance systems, and navigation systems. Simulations can be started at points other than liftoff. Also included are guidance-system software models that accommodate the ascent, orbit, coasting, deorbiting, entry, terminal-area-energy-management, approach, and landing phases of flight. Options to use different wind profiles and atmospheres are included. A Monte Carlo capability is provided for modeling dispersions associated with atmospheric effects (including winds), propulsion, navigation, aerodynamics, and mass properties. Failures of engines and other subsystems can be modeled. The program is written in the C programming language, which makes it possible for the program to have high degrees of modularity, reusability, and maintainability, thereby also facilitating modification for modeling new vehicles.

McCarter, James W.↗
DOE OSTI2020

Langevin simulations of the half-filled cubic Holstein model

Over the past several years, reliable quantum Monte Carlo results for the charge density wave transition temperature T cdw of the half-filled two-dimensional Holstein model in square and honeycomb lattices have become available for the first time. Here, exploiting the further development of numerical methodology, here we present results in three dimensions, which are made possible through the use of Langevin evolution of the quantum phonon degrees of freedom. In addition to determining T cdw from the scaling of the charge correlations, we also examine the nature of charge order at general wave vectors for different temperatures, couplings, and phonon frequencies, and the behavior of the spectral function and specific heat.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Charge correlations suppress unconventional pairing in the Holstein model

In a recent work by Schrodi et al. [Phys. Rev. B. 104, L140506 (2021)], the authors find an unconventional superconducting state with a sign-changing order parameter using the Migdal-Eliashberg theory, including the first vertex correction. This unconventional solution arises despite using an isotropic bare electron-phonon coupling in the Hamiltonian. We examine this claim using hybrid quantum Monte Carlo for a single-band Holstein model with a cuprate-like noninteracting band structure and identical parameters to Schrodi et al.. Our Monte Carlo results for these parameters suggest that unconventional pairing correlations do not exceed their noninteracting values at any carrier concentration we have checked. Instead, strong charge-density-wave correlations persist at the lowest accessible temperatures for dilute and nearly half-filled bands. As a result, we present arguments for how vertex-corrected Migdal-Eliashberg calculation schemes can lead to uncontrolled results in the presence of Fermi surface nesting.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗