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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 OSTI2019

MCNP AND CFD MODELING OF A SODIUM FAST REACTOR SUB-ASSEMBLY CHANNEL TO CAPTURE LOCALIZED TEMPERATURE PEAKING

Typical evaluation tools for sodium-cooled fast reactors (SFR) use simplified neutronic/thermal models to efficiently compute the power and temperature distributions within the core. However, their modeling capability can be limited in extreme cases such as when sharp inter-assembly power gradients occur, or for non-standard SFR assembly geometries. Higher fidelity tools that rely on Monte Carlo methods for neutron transport, and Computational Fluid Dynamics (CFD) for thermal analysis, are better suited in these instances. The higher accuracy comes at the cost of higher computational expense. MCNP and STAR CCM+ were selected for this analysis. While MCNP is capable of generating pin-level power distributions for a whole-core SFR model, it is prohibitively expensive to then conduct CFD analysis for every single assembly. A semi-empirical model was therefore developed to rapidly estimate pin temperature distributions throughout the whole core. It relies on a geometric correction factor for turbulent flow-mixing. The correction factor is obtained from a CFD simulation of a single fuel assembly with a uniform power distribution and an adiabatic boundary condition. Without using CFD, each sub-channel outlet temperature is calculated separately using 1-D heat-balance and Nusselt number correlations and the MCNP calculated pin-powers. The rudimentary 1-D model is then corrected for the flow-mixing effect based on the CFD data. The temperature calculation is performed by a code written in the Python language called CFD Monte-Carlo Developed Reconstruction of Sub-channel at a Quasi-Representative Level (CMDR-SQRL). CMDR-SQRL was shown to adequately predict CFD evaluated temperature distribution for a wide range of SFR configurations, including an extreme case with fuel assemblies nearby containing moderating material. The agreement demonstrates how geometric and power-driven effects can be decoupled within an SFR assembly. CMDR-SQRL is intended to be mainly used for scoping studies to provide core-wide evaluations efficiently.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Industrial Control System Risk

Risk is integrated into all business processes, and leaders work to limit risk to as low as reasonable within their systems. Within Industrial Control System networks, risk is especially challenging due to the second- and third-order effects that an attack can incur. We present a new equation for risk and analyze its appropriateness in determining risk through Monte Carlo methods. We believe that this new equation has merit in allowing leadership to more quickly access and mitigate risk based off factors within the decision maker’s control, understanding how capable an attacker may be, how much impact an attack would have on the system, and how intensely an attacker may want to cause damage to the system. These variables will allow a leader to provide strategic vision to the business that he/she leads.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Tetraquarks made of sufficiently unequal-mass heavy quarks are bound in QCD

Tetraquarks, bound states composed of two quarks and two antiquarks, have been the subject of intense study but are challenging to understand from first principles. We apply variational and Green’s function Monte Carlo methods to compute tetraquark ground-state energies in potential nonrelativistic QCD using a wide range of color and spatial wave functions. We find no evidence for bound tetraquarks composed of equal-mass quarks and antiquarks. Conversely, we find clear evidence for the existence of bound tetraquarks for sufficiently unequal quark/antiquark mass ratios at all overall mass scales where our effective theory results are applicable. We predict the critical mass ratios for bound state formation and study tetraquark bound states’ spatial and color structure at leading order and next-to-leading order in potential nonrelativistic QCD. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Pulse-noise approach for classical spin systems

For systems of classical spins interacting with the bath via damping and thermal noise, a technique is suggested to replace the white noise by a pulse noise acting at regular time intervals Δ t , within which the system evolves conservatively. The method is working well in the typical case of a small dimensionless damping constant λ and allows a considerable speedup of computations by using high-order numerical integrators with a large time step δ t (up to a fraction of the precession period), while keeping δ t ≪ Δ t to reduce the relative contribution of noise-related operations. In cases when precession can be discarded, δ t can be increased up to a fraction of the relaxation time ∝ 1 / λ that leads to a further speedup. This makes equilibration speed comparable with that of the Metropolis Monte Carlo method. The pulse-noise approach is tested on single-spin and multispin models.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Modeling Unconventional Superconductivity at the Crossover between Strong and Weak Electronic Interactions

High-temperature superconductivity emerges in many different quantum materials, often in regions of the phase diagram where the electronic kinetic energy is comparable to the electron-electron repulsion. Describing such intermediate-coupling regimes has proven challenging as standard perturbative approaches are inapplicable. In this study, we employ quantum Monte Carlo methods to solve a multiband Hubbard model that does not suffer from the sign problem and in which only repulsive interband interactions are present. In contrast to previous sign-problem-free studies, we treat magnetic, superconducting, and charge degrees of freedom on an equal footing. We find an antiferromagnetic dome accompanied by a metal-to-insulator crossover line in the intermediate-coupling regime, with a smaller superconducting dome appearing in the metallic region. Across the antiferromagnetic dome, the magnetic fluctuations change from overdamped in the metallic region to propagating in the insulating region. Our findings shed new light on the intertwining between superconductivity, magnetism, and charge correlations in quantum materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Auxiliary field diffusion Monte Carlo calculations of magnetic moments of light nuclei with chiral effective field theory interactions

We calculate the magnetic moments of light nuclei $( A < 20 )$ using the auxiliary field diffusion Monte Carlo method and local two- and three-nucleon forces with electromagnetic currents from chiral effective field theory. For all nuclei under consideration, we also calculate the ground-state energies and charge radii. We generally find a good agreement with experimental values for all of these observables. For the electromagnetic currents, we explore the impact of employing two different power counting schemes, and study theoretical uncertainties stemming from the truncation of the chiral expansion order by order for select nuclei within these two approaches. In conclusion, we find that it is crucial to employ consistent power counting schemes for interactions and currents to achieve a systematic order-by-order convergence.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Behavioral and Population Data-Driven Distribution System Load Modeling

Distribution system residential load modeling and analysis for different geographic areas within a utility or an independent system operator territory are critical for enabling small-scale, aggregated distributed energy resources to participate in grid services under Federal Energy Regulatory Commission Order No. 2222 [1]. In this study, we develop a methodology of modeling residential load profiles in different geographic areas with a focus on human behavior impact. First, we construct a behavior-based load profile model leveraging state-of-the-art appliance models. We simulate human activity and occupancy using Markov chain Monte Carlo methods calibrated with the American Time Use Survey data set. Second, we link our model with cleaned Current Population Survey data from the U.S. Census Bureau. Finally, we populate two sets of 500 households using California and Texas census data, respectively, to perform an initial analysis of the load in different geographic areas with various group features (e.g., different income levels). To distinguish the effect of population behavior differences on aggregated load, we simulate load profiles for both sets assuming fixed physical household parameters and weather data. Analysis shows that average daily load profiles vary significantly by income and income dependency varies by locality.

American Time Use Survey↗
DOE OSTI2013

Hiereachical Bayesian Model for Combining Geochemical and Geophysical Data for Environmental Applications Software

Development of a hierarchical Bayesian model to estimate the spatiotemporal distribution of aqueous geochemical parameters associated with in-situ bioremediation using surface spectral induced polarization (SIP) data and borehole geochemical measurements collected during a bioremediation experiment at a uranium-contaminated site near Rifle, Colorado. The SIP data are first inverted for Cole-Cole parameters including chargeability, time constant, resistivity at the DC frequency and dependence factor, at each pixel of two-dimensional grids using a previously developed stochastic method. Correlations between the inverted Cole-Cole parameters and the wellbore-based groundwater chemistry measurements indicative of key metabolic processes within the aquifer (e.g. ferrous iron, sulfate, uranium) were established and used as a basis for petrophysical model development. The developed Bayesian model consists of three levels of statistical sub-models: 1) data model, providing links between geochemical and geophysical attributes, 2) process model, describing the spatial and temporal variability of geochemical properties in the subsurface system, and 3) parameter model, describing prior distributions of various parameters and initial conditions. The unknown parameters are estimated using Markov chain Monte Carlo methods. By combining the temporally distributed geochemical data with the spatially distributed geophysical data, we obtain the spatio-temporal distribution of ferrous iron, sulfate and sulfide, and their associated uncertainity information. The obtained results can be used to assess the efficacy of the bioremediation treatment over space and time and to constrain reactive transport models.

Chen, Jinsong↗
NASA NTRS1991

Accretion and evolution of solar system bodies

We use a combination of analytical and numerical methods to study dynamical processes involved in the formation of planets and smaller bodies in the solar system. Our goal was to identify and understand critical processes and to link them in a numerical model of planetesimal accretion. We study effects of these processes by applying them in the context of the standard model of solar system formation, which involves accretion of the terrestrial planets and cores of the giant planet from small planetesimals. The principal focus of our research effort is the numerical simulation of accretion of a swarm of planetesimals into bodies of planetary size. Our computer code uses a Monte Carlo method to determine collisional interactions within the swarm. These interactions are not determined simply by a relative velocity, but rather by explicit distributions of keplerian orbital elements. The planetesimal swarm is divided into a number of zones in semimajor axis, which are allowed to interact. The present version of our code has the capability of following detailed distributions of size, eccentricity, and inclination in each zone.

Weidenschilling, S. J.↗
DOE OSTI2022

Quantum membrane phases in synthetic lattices of cold molecules or Rydberg atoms

Here, we calculate properties of dipolar interacting ultracold molecules or Rydberg atoms in a semisynthetic three-dimensional configuration—one synthetic dimension plus a two-dimensional real-space optical lattice or periodic microtrap array—using the stochastic Green's function quantum Monte Carlo method. Through a calculation of thermodynamic quantities and appropriate correlation functions, along with their finite-size scalings, we show that there is a second-order transition to a low-temperature phase in which two-dimensional “sheets” form in the synthetic dimension of internal rotational or electronic states of the molecules or Rydberg atoms, respectively. Simulations for different values of the interaction V, which acts between atoms or molecules that are adjacent both in real and synthetic space, allow us to compute a phase diagram. We find a finite-temperature transition at sufficiently large V as well as a quantum phase transition—a critical value V c below which the transition temperature vanishes.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2017

Soot and Spectral Radiation Modeling for a High-Pressure Turbulent Spray Flame

Simulations are performed of a transient high-pressure turbulent n-dodecane spray flame under engine-relevant conditions. An unsteady RANS formulation is used, with detailed chemistry, a semi-empirical two-equation soot model, and a particle-based transported composition probability density function (PDF) method to account for unresolved turbulent fluctuations in composition and temperature. Results from the PDF model are compared with those from a locally well-stirred reactor (WSR) model to quantify the effects of turbulence-chemistry-soot interactions. Computed liquid and vapor penetration versus time, ignition delay, and flame lift-off height are in good agreement with experiment, and relatively small differences are seen between the WSR and PDF models for these global quantities. Computed soot levels and spatial soot distributions from the WSR and PDF models show large differences, with PDF results being in better agreement with experimental measurements. An uncoupled photon Monte Carlo method with line-by-line spectral resolution is used to compute the spectral intensity distribution of the radiation leaving the flame. This provides new insight into the relative importance of molecular gas radiation versus soot radiation, and the importance of turbulent fluctuations on radiative heat transfer.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Quantum Monte Carlo determination of the principal Hugoniot of deuterium

Here, we present coupled electron-ion Monte Carlo results for the principal Hugoniot of deuterium together with an accurate study of the initial reference state of shock-wave experiments. We discuss the influence of nuclear quantum effects, thermal electronic excitations, and the convergence of the potential energy surface by wave-function optimization within variational Monte Carlo and projection quantum Monte Carlo methods. Compared to a previous study, our calculations also include low pressure-temperature (P,T) conditions resulting in close agreement with experimental data, while our revised results at higher (P,T) conditions still predict a more compressible Hugoniot than experimentally observed.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Coherence temperature in the diluted periodic Anderson model

The Kondo and periodic Anderson model (PAM) are known to provide a microscopic picture of many of the fundamental properties of heavy-fermion materials and, more generally, a variety of strong correlation phenomena in 4f and 5f systems. Here, we apply the determinant quantum Monte Carlo method to include disorder in the PAM, specifically the removal of a fraction x of the localized orbitals. We determine the evolution of the coherence temperature T*, where the local moments and conduction electrons become entwined in a heavy-fermion fluid, with x and with the hybridization V between localized and conduction orbitals. We recover several of the principal observed trends in T* of doped heavy fermions, and we also show that, within this theoretical framework, the calculated nuclear magnetic resonance relaxation rate tracks the experimentally measured behavior in pure and doped CeCoIn 5 . Finally, our results contribute to important issues in the interpretation of local probes of disordered, strongly correlated systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

TU-H-CAMPUS-IeP1-01: Bias and Computational Efficiency of Variance Reduction Methods for the Monte Carlo Simulation of Imaging Detectors

Purpose: Variance reduction techniques (VRTs) are employed in Monte Carlo simulations to obtain estimates with reduced statistical uncertainty for a given simulation time. In this work, we study the bias and efficiency of a VRT for estimating the response of imaging detectors. Methods: We implemented Directed Sampling (DS), preferentially directing a fraction of emitted optical photons directly towards the detector by altering the isotropic model. The weight of each optical photon is appropriately modified to maintain simulation estimates unbiased. We use a Monte Carlo tool called fastDETECT2 (part of the hybridMANTIS open-source package) for optical transport, modified for VRT. The weight of each photon is calculated as the ratio of original probability (no VRT) and the new probability for a particular direction. For our analysis of bias and efficiency, we use pulse height spectra, point response functions, and Swank factors. We obtain results for a variety of cases including analog (no VRT, isotropic distribution), and DS with 0.2 and 0.8 optical photons directed towards the sensor plane. We used 10,000, 25-keV primaries. Results: The Swank factor for all cases in our simplified model converged fast (within the first 100 primaries) to a stable value of 0.9. The root mean square error per pixel for DS VRT for the point response function between analog and VRT cases was approximately 5e-4. Conclusion: Our preliminary results suggest that DS VRT does not affect the estimate of the mean for the Swank factor. Our findings indicate that it may be possible to design VRTs for imaging detector simulations to increase computational efficiency without introducing bias.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Effect of Confinement of SIA Cluster Diffusion by Impurities on Radiation Defect Accumulation due to 14MeV neutrons in Tungsten

Impurities acting as traps, reduce the self-interstitial atom (SIA) cluster mobility, thereby increasing recombination and in turn enhancing radiation-resistance of polycrystalline materials. However, at elevated temperatures, depending on SIA-trap (impurity) binding energy, SIA clusters may trap and detrap (detach) numerous times. In tungsten, SIA clusters of all sizes glide one-dimensionally (1D) along their Burgers vector direction. Hence, detrapped SIAs would retrace their path, confining their 1D-glide between traps. However, small SIA clusters can change the direction of their 1D-glide by overcoming a rotation barrier. In addition, impurities or solutes are known to reduce this barrier. A lower rotation barrier can result in detrapped SIA clusters that diffuse in a random 1D direction, effectively leading to 3D (net-3D) diffusion. Here we investigate the effect of two cases of SIA diffusion, namely confined-1D diffusion and net-3D diffusion, on the damage accumulation in polycrystalline tungsten under 14 MeV neutron irradiation using the object kinetic Monte Carlo method. Simulations were performed using cascade debris obtained from molecular dynamics simulations with primary knock-on atom (PKA) energies corresponding to 14 MeV neutrons. In the simulations with net-3D diffusion, SIA clusters of all sizes diffuse in a random 1D direction after the clusters detrap. While for the confined 1D diffusion case, SIA clusters larger than size 5 retain their original direction of 1D-glide. In both types of simulations, trapped vacancies are assumed to be permanently immobilized. Unexpectedly, the damage accumulation was lower with confined 1D diffusion than that with net-3D. We present a systematic comparison of the influence of the two cases of SIA diffusion on the radiation damage accumulation as a function of dose rate, detrapping barrier, and impurity concentration at 1025 K.

Accumulation and recovery of lattice damage, tungs↗
DOE OSTI2015

Parameter estimation by implicit sampling

© 2015 Mathematical Sciences Publishers. Implicit sampling is a weighted sampling method that is used in data assimilation to sequentially update state estimates of a stochastic model based on noisy and incomplete data. Here we apply implicit sampling to sample the posterior probability density of parameter estimation problems. The posterior probability combines prior information about the parameter with information from a numerical model, e.g., a partial differential equation (PDE), and noisy data. The result of our computations are parameters that lead to simulations that are compatible with the data. We demonstrate the usefulness of our implicit sampling algorithm with an example from subsurface flow. For an efficient implementation, we make use of multiple grids, BFGS optimization coupled to adjoint equations, and Karhunen-Loève expansions for dimensional reduction. Several difficulties of Markov chain Monte Carlo methods, e.g., estimation of burn-in times or correlations among the samples, are avoided because the implicit samples are independent.

Morzfeld, Matthias↗
DOE OSTI2025

Thermodynamic assessment of the quaternary WTaCrV refractory high entropy alloy as a means to guide experimental approaches

The deployment of fusion energy poses challenges for materials in plasma facing components to withstand high temperatures and thermal gradients, particle implantation and neutron damage. The current material of choice is tungsten, although property degradation limits its consideration in future fusion reactors. Hence, materials with better resistance to harsh environments need to be developed for fusion energy to become a reality. High entropy alloys are being explored as potential candidates with some compositions showing good radiation resistance to defect cluster formation. One of these materials is the WTaCrV system, although only one composition has been tested under ion irradiation. In this work, we study the thermodynamic properties of the entire quaternary alloy composition range. Coupling first principles calculations, cluster expansion approaches, and Monte Carlo methods, we access the free energy functionals, short-range ordering as a function of temperature, and atomic configurations that can be compared to experimental observations. We use this data to inform experiments into compositions with higher propensity to form solid solutions, instead of phase separating. With this formalism we have developed thermodynamic database (TDB) files that can be used to plot quaternary phase diagrams.

Cluster Expansion↗