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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Fully consistent Eulerian Monte Carlo fields method for solving probability density function transport equations in turbulence modeling

The probability density function (PDF) transport equation method is a sophisticated model for the closure of turbulent mixing and turbulent reactive flows. An efficient solution approach for solving the PDF transport equation has been vital for the method to be widely used in applications. The Eulerian Monte Carlo fields (EMCF) method has been developed to solve the PDF transport equation efficiently for decades. A recent work by Wang et al. revealed a serious issue of the EMCF method for not being fully consistent with the PDF transport equation for which the method is designed to solve. This work advances the state of the art by introducing fully consistent EMCF methods for solving the PDF transport equation. The fully consistent EMCF formulations are derived for two different PDF equation forms. The consistency of the EMCF formulations is mathematically confirmed by examining the derived moment transport equations from the EMCF formulations and from the PDF transport equation. The method of manufactured solutions is employed to further verify the consistency and convergence of the different EMCF formulations numerically. The newly introduced EMCF formulations bring the EMCF method to full consistency with the PDF transport equations for the first time.

42 ENGINEERING↗
DOE OSTI2024

Multifidelity methods for uncertainty quantification of a nonlocal model for phase changes in materials

This study is devoted to the construction of a multifidelity Monte Carlo (MFMC) method for the uncertainty quantification of a nonlocal, non-mass-conserving Cahn-Hilliard model for phase transitions with an obstacle potential. Here, we are interested in estimating the expected value of an output of interest (OoI) that depends on the solution of the nonlocal Cahn-Hilliard model. As opposed to its local counterpart, the nonlocal model captures sharp interfaces without the need for significant mesh refinement. However, the computational cost of the nonlocal Cahn-Hilliard model is higher than that of its local counterpart with similar mesh refinement, inhibiting its use for outer-loop applications such as uncertainty quantification. The MFMC method augments the desired high-fidelity, high-cost OoI with a set of lower-fidelity, lower-cost OoIs to alleviate the computational burden associated with nonlocality. Most of the computational budget is allocated to sampling the cheap surrogate models to achieve speedup, whereas the high-fidelity model is sparsely sampled to maintain accuracy. For the non-mass-conserving nonlocal Cahn-Hilliard model, the use of the MFMC method results in, for a given computational budget, about an order of magnitude reduction in the mean-squared error of the expected value of the OoI relative to that of the Monte Carlo method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Covariance-Free Bifidelity Control Variates Importance Sampling for Rare Event Reliability Analysis

Multifidelity modeling has been steadily gaining attention as a tool to address the problem of exorbitant model evaluation costs that makes the estimation of failure probabilities a significant computational challenge for complex real-world problems, particularly when failure is a rare event. To implement multifidelity modeling, estimators that efficiently combine information from multiple models/sources are necessary. In past works, the variance reduction techniques of control variates (CV) and importance sampling (IS) have been leveraged for this task. In this paper, we present the CVIS framework—a creative take on a coupled CV and IS estimator for bifidelity reliability analysis. The framework addresses some of the practical challenges of the CV method by using an estimator for the control variate mean and sidestepping the need to estimate the covariance between the original estimator and the control variate through a clever choice for the tuning constant. Furthermore, the task of selecting an efficient IS distribution is also considered, with a view towards maximally leveraging the bifidelity structure and maintaining expressivity. Additionally, a diagnostic is provided that indicates both the efficiency of the algorithm as well as the relative predictive quality of the models utilized. Finally, the behavior and performance of the framework is explored through analytical and numerical examples.

Markov chain Monte Carlo↗
DOE OSTI2023

Direct Monte Carlo Simulations of Chemical Equilibrium Composition of Molecular Fluid Mixtures Under Shock Conditions

A new Monte Carlo simulation method is implemented which holds the number and kind of atoms constant rather than the number and kind of molecules for a molecular fluid mixture. Chemical reactions are allowed as a correlated move of atoms such as an interchange of atoms between molecules. Equilibrium chemical composition is determined as an average over the simulation along with equation of state quantities. Results are presented for N 2 + O 2 → 2NO at 30GPa and 3000K. The equilibrium composition is shown to be sensitive to the potentials between unlike species.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

First operation and validation of simulations for the divertor cryo-vacuum pump in Wendelstein 7-X

Ten cryo-vacuum pumps (CVPs) were installed in the subdivertor region of each island divertor in the stellarator Wendelstein 7-X (W7-X) and operated for the first time during the recently completed plasma campaign OP2.1. A pumping speed of 70 ± 1 $\frac{m^3}{s}$ was measured during dedicated tests with known hydrogen gas injection. Based on a conductance model, the estimated pumping speed ranges from 86-93 $\frac{m^3}{s}$ for different sticking coefficients between 0.6 and 0.8. After completion of the initial tests the CVPs were operated successfully throughout the campaign, with regeneration performed once a week. Neutral gas pressures in the subdivertor in the range of 10 −4 mbar are well within the molecular flow regime and limit the particle exhaust capabilities of the CVPs. Simulations of the neutral gas pressure in the three-dimensional complex geometry of the subdivertor were performed using the DIVGAS code based on the direct simulation Monte Carlo method and a model implemented in the steady-state thermal package in ANSYS, which are in agreement with the measured values during plasma operation.

Cryo-vacuum pumping↗
DOE OSTI2023

Model to inform the expansion of hydrogen distribution infrastructure

A growing hydrogen economy requires new hydrogen distribution infrastructure to link geographically distributed hubs of supply and demand. The Hydrogen Optimization with Deployment of Infrastructure (HOwDI) Model helps meet this requirement. The model is a spatially resolved optimization framework that determines location-specific hydrogen production and distribution infrastructure to cost-optimally meet a specified location-based demand. While these results are useful in understanding hydrogen infrastructure development, there is uncertainty in some costs that the model uses for inputs. Thus, the project team took the modeling effort a step further and developed a Monte Carlo methodology to help manage uncertainties. Seven scenarios were run using existing infrastructure and new demand in Texas exploring different policy and tax approaches. The inclusion of tax credits increased the percentage of runs that could deliver hydrogen at <$\$4$ /kg from 31% to 77% and decreased the average dispensed cost from $\$4.35$ /kg to $\$3.55$ /kg. However, even with tax credits there are still some runs where unabated SMR is deployed to meet new demand as the low-carbon production options are not competitive. Every scenario, except for the zero-carbon scenario (without tax credits), resulted in at least 20% of the runs meeting the $\$4$ /kg dispensed fuel cost target. This indicates that multiple pathways exist to deliver $\$4$ /kg hydrogen.

08 HYDROGEN↗
DOE OSTI2025

Comparing Control Performance Between Simulation and Experiment using the Microreactor Automated Control System Testbed

In the advanced reactor domain, a flexible and scalable software/hardware infrastructure is crucial for integrating and validating various control technologies. This study used the Microreactor Automated Control System (MACS) hardware platform as a testbed. MACS was originally designed to mirror Idaho National Laboratory (INL)'s Microreactor Applications Research Validation and Evaluation (MARVEL), a 85-kW thermal fission microreactor. It features control drums for simulated reactivity control; lights that function as a surrogate reactor core, with the brightness being proportional to the reactor power; and light sensors that emulate neutron detectors. To transform MACS into a physical twin of MARVEL for evaluating control methods, the Control and Optimization Modular Modeling Application for Nuclear Deployment (COMMAND) software was employed. This software integrated the hardware with two models of the MARVEL core, based on Reactor Excursion and Leak Analysis Program (RELAP5-3D) and Monte Carlo N-Particle (MCNP) models. The study aimed to demonstrate the gap between control theory and actual practice—a gap that often necessitates empirical adjustments such as control gain retuning, filters, time discretization, and integrator anti-windup measures. Controllers were developed based on increasingly complex simulations without hardware, starting from the base MARVEL model and then introducing actuator saturation constraints and sensor noise. The final control strategy was then tested using MACS, and a comparative performance analysis was conducted.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2020

Molten Salt Reactor Experiment Benchmark Evaluation

As one of the six advanced reactor concepts selected by the 2002 Generation IV roadmap as a technology meriting future research, Molten Salt Reactors (MSRs) attracted broad attention and multiple private and public entities are working towards its commercialization. Facing stringent regulatory requirements, validations of computational codes used to calculate and prove the safety characteristics of MSRs play a key role. This project developed the world-first, MSR-related reactor physics benchmark based on a series of zero-power experiments conducted at the Molten Salt Reactor Experiment (MSRE). The benchmark was successfully reviewed by the International Reactor Physics Experiment Evaluation Project (IRPhEP) committee and is available in the IRPhEP handbook starting form the 2019 edition. To benchmark experimental data from the MSRE, a three-dimensional high-fidelity model was developed using the Monte Carlo neutron transport code Serpent 2 and ad-hoc methods have been implemented to account for the unique feature of fuel salt motion. The calculated effective multiplication factor, k eff , for the first criticality experiment, when 235 U was progressively added to the fuel salt in order to achieve criticality with stationary salt and isothermal conditions, was 1.02132 (±3 pcm). The total uncertainty for experimental k eff was estimated to be 420 pcm. The calculated k eff is 2.154% larger than the experimental and benchmark model value, which is approximately five times the benchmark model uncertainty. It is to be noted that, for systems containing large volume of graphite (or other carbonaceous materials), Monte Carlo codes tend to overestimate the keff of the benchmark model by 1% to 2%. The bias is possibly due to uncertainties in the impurity content of the graphite blocks, uncertainty in the neutron capture cross section of carbon or uncertainty in the properties of nuclear-grade graphite. The calculated reactivity coefficient of 235 U concentration (0.2228 ± 0.0014, represented as the change of reactivity over the relative change of 235 U mass in loop) matches well with the experimental value (0.223 ± 0.006), strengthening the confidence on the accurate representation of the fuel salt composition in the MSRE benchmark. Additional reactivity effect calculations, including the control rod bank worth, reactivity effects of fuel circulation and isothermal and fuel temperature coefficients show good agreement with the experimental values (within 1σ) as well.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Diagrammatic Monte Carlo Approach to Real‐frequency Response Functions and the Spin‐Fermion Model of Hot Spots (Final Report)

This three‐year research project was focused on two outstanding condensed matter problems (i) Real‐frequency response functions in Coulomb systems at finite temperature, and Fermi surface (FS) reconstruction in the Spin-Fermion (SF) model. The uniform electron gas (jellium) model, describing electrons interacting via long‐range Coulomb forces on positive neutralizing background, is fundamentally important both for understanding the physics of correlated electrons and for formulation of the time‐dependent density functional theory (TDDFT). The spin-fermion model has found a wide range of applications in the physics of cuprates and iron‐based superconductors to explain the “strange metal" behavior and to suggest a possible pairing mechanism for high‐temperature superconductivity. The project’s goals were development and application of the Diagrammatic Monte Carlo (DiagMC) techniques for solving the above problems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Fluctuating intertwined stripes in the strange metal regime of the Hubbard model

Strongly correlated electron systems host a variety of poorly understood correlations in their high-temperature normal state. Unlike ordered phases defined by order parameters, regions of the normal state are often defined through unconventional properties such as strange metallic transport or spectroscopic pseudogaps. Characterizing the microscopic correlations in the normal state is necessary to elucidate mechanisms that lead to these properties and their connection to ground-state orders. Here, in this paper, we establish the presence of intertwined charge and spin stripes in the strange metal normal state of the Hubbard model using determinant quantum Monte Carlo calculations. The charge and spin density waves constituting the stripes are fluctuating and short ranged; yet they obey a mutual commensurability relation and remain microscopically interlocked, as evidenced through measurements of three-point spin-spin-hole correlation functions. Our findings demonstrate the ability of many-body numerical simulations to unravel the microscopic correlations that define quantum states of matter.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Antiferromagnetic character of the quantum phase transition in the Hubbard model on the honeycomb lattice

In this work we provide a unified, comprehensive treatment of all operators that contribute to the antiferromagnetic, ferromagnetic, and charge-density-wave structure factors and order parameters of the hexagonal Hubbard Model. We use the Hybrid Monte Carlo algorithm to perform a systematic, carefully controlled analysis in the temporal Trotter error and of the thermodynamic limit. We expect our findings to improve the consistency of Monte Carlo determinations of critical exponents. We perform a data collapse analysis and determine the critical exponent β = 0.898 (37) for the semimetal-Mott insulator transition in the hexagonal Hubbard Model. Our methods are applicable to a wide range of lattice theories of strongly correlated electrons.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Implementation of Triply Periodic Minimal Surfaces (TPMS) as surface objects in OpenMC

Triply Periodic Minimal Surfaces (TPMS) represent a promising geometry for future fuel designs due to their significant surface-to-volume ratio, which facilitates efficient cooling of nuclear fuel, a crucial factor for safety and efficiency. Demonstrating the remarkable capabilities of TPMS fuel requires initial modeling and simulation. This paper presents an implementation of TPMS in the Monte Carlo code OpenMC, enabling reactor physics modeling of TPMS. Here, the primary advantages over traditional methods using CAD files include reduced memory requirements for computations and high-fidelity implementation. This implementation has been tested against CAD files loaded in Serpent2, yielding promising results with low biases in the $k_{\textrm{eff}}$, comparable to biases in the material balance sheet. The implementation presented in this work will be used in future reactor physics computations related to new reactor designs involving TPMS-based fuels.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Zero Power Reactor Database (ZPRD) Development Plan

Past sodium-cooled fast reactors (SFR) were built with an active experimental program in place to support the design and development work. Most of the experimental facilities in the United States that were important for SFR design were shutdown in the 1980s and 1990s. Reactor licensing and construction requires any reactor design to be verified against existing reactor facilities or experimental measurements. With the absence of those experimental facilities, modern SFR projects must rely on historical measurements to demonstrate that the engineering modeling software and data being used for the new reactor design work are reliable. There has been a considerable push in the last 6 years by both DOE and commercial companies to obtain historical experimental measurements that are relevant for SFRs, in particular those with features that are important for the new reactor designs of interest. The zero power reactor experiments carried out at Argonne National Laboratory’s critical facilities (ZPR-3, ZPR-6, ZPR-9, and ZPPR) from the 1950s to the 1980s are some of the best reactor physics experiments on SFR technology that are available today. Of particular interest today are the ZPPR-15 measurements done at the ZPPR facility for the Integral Fast Reactor project in the 1980s as they are in line with most commercial and DOE interests today. In the past 10 years, the measurements done on ZPPR-15 have been processed into both Monte Carlo (MCNP) and deterministic models (MC2-3 and DIF3D) useable for validating the engineering modeling software for key parts of the SFR design work. To achieve this, a detailed model description must be created for the experiment and the experimental measurement that the engineering modeling software is to reproduce. Then, an assessment of the uncertainty on the measured quantity which considers all of the sources of uncertainty in defining the model must be obtained and documented. The models created for ZPPR-15 provide the best validation basis available today for neutronics modeling software. Reference 2 is a good resource to understand how these models were built and how the uncertainties on the measured quantities were derived. The intention of the Zero Power Reactor Database (ZPRD), hosted at frdb.ne.anl.gov, is to make available the experimental measurements and models that have been constructed to-date. Though ZPPR-15 measurements are the primary data requested for validation needs, other measurements on ZPPR, ZPR-6, and ZPR-9 in support of the Clinch River Breeder Reactor (CRBR) and Fast Test Reactor (FFTF) should also be considered important for future software validation needs. In this manuscript, the details of available measurements on ZPR-3, ZPR-6, ZPR-9, and ZPPR facilities are summarized, and a general organization of the web interface is displayed. Many of the documents associated with the measurements are export controlled information so access to the database will also have to be controlled.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Validation of realistic Monte Carlo plasma gamma-ray source on JET discharges

A novel modelling methodology has been developed for the creation of a realistic plasma gamma-ray source for Monte Carlo transport simulations in the tokamak JET. The methodology couples the TRANSP code for plasma transport calculations with the MCNP Monte Carlo particle transport code, thus connecting plasma physics with gamma-ray transport. Here, we present the validation of the developed source methodology by comparing calculated gamma-ray spectra with measurements performed at JET. The validation focuses on gamma-ray spectra measured by the tangential gamma-ray spectrometer during two JET three ion RF scenario discharges, performed in the JET 2019 deuterium experimental campaign. For validation the calculated plasma gamma-ray spectrum was combined with the neutron induced prompt gamma-ray background, originating in the vacuum vessel, and scaled to absolute values calculating the total number of plasma gamma-ray and neutron emitting reactions. The comparison between calculated and measured gamma-ray spectra shows good agreement with the shape of the calculated gamma-ray spectra matching that of measurements for both studied discharges. Moreover, the calculated absolute values of the gamma-ray spectra were of the same order of magnitude at the position of the gamma-ray detector located at the end of a long line-of-sight in a biological shield. Finally, the comparison has validated the developed plasma gamma-ray source methodology for MCNP photon transport calculations at JET. The validation provides a basis for the developed plasma gamma-ray source to be used as a support for the development of future tokamaks such as DEMO.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Grain Boundary-Limited Thermal Transport in Suspended Thin Graphite across an Unexplored Thickness Regime

Here, we present systematic thermal conductivity (κ) measurements of suspended thin graphite ribbons, 234–527 nm thick, using a four-probe 3ω method. Unlike recent reports of phonon hydrodynamics and exceptionally high κ in micrometer-thick graphite ( Science, 2020), we observe significantly lower κ and no signatures of collective phonon flow in this intermediate thickness regime. Instead, our measured κ lies between few-layer graphene and bulk graphite. These results agree with a first-principles-informed Peierls–Boltzmann transport model with spatially resolved Monte Carlo sampling. Additionally, the temperature for the peak κ shifts lower with increasing thickness, due to the interplay of phonon-boundary and phonon-isotope scattering. Incorporating grain boundary scattering into simulations is necessary to replicate the experimental trends. These findings delineate the boundary between ballistic, hydrodynamic, and diffusive transport regimes in graphite and underscore the dominant role of disorder and geometry in phonon transport in quasi-two-dimensional materials, offering insights for nanoscale thermal management.

Boltzmann transport model↗
DOE OSTI2023

Mechanisms of Ethylene Epoxidation over Silver from Machine Learning-Accelerated First-Principles Modeling and Microkinetic Simulations

In this work we employed machine learning-augmented density functional theory (DFT) thermodynamic calculations to assess the stability of different AgO x structures under catalytic ethylene epoxidation reaction conditions. We found that there are multiple AgO x surface motifs that could co-exist under the relevant conditions. These included Ag surface oxides (e.g., AgO_p(4 × 4) and Ag 1.83 O) and atomic oxygen-covered Ag(111) surfaces. Furthermore, we employed DFT calculations to evaluate the energetics of different reaction mechanisms by which ethylene and oxygen can react on these surfaces. These studies revealed several energetically viable reaction pathways for ethylene epoxidation. Microkinetic modeling analyses, based on the DFT-calculated reaction pathways, showed that ethylene epoxidation can proceed on all surfaces and that multiple pathways, including those involving Langmuir–Hinshelwood and Eley–Rideal mechanisms, could be involved in selective and unselective reactions. The diversity of mechanisms that we discovered in the context of the relatively simple ethylene epoxidation reaction on Ag suggests that the richness and complexity of surface chemistry are most likely a rule rather than an exception in heterogeneous catalytic chemical transformations on metal surfaces and that the concept of a single or even a dominant mechanism and reaction intermediates might need to be revisited for many reactions.

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

A modified Susceptible-Infected-Recovered model for observed under-reported incidence data

Fitting Susceptible-Infected-Recovered (SIR) models to incidence data is problematic when not all infected individuals are reported. Assuming an underlying SIR model with general but known distribution for the time to recovery, this paper derives the implied differential-integral equations for observed incidence data when a fixed fraction of newly infected individuals are not observed. The parameters of the resulting system of differential equations are identifiable. Using these differential equations, we develop a stochastic model for the conditional distribution of current disease incidence given the entire past history of reported cases. We estimate the model parameters using Bayesian Markov Chain Monte-Carlo sampling of the posterior distribution. We use our model to estimate the transmission rate and fraction of asymptomatic individuals for the current Coronavirus 2019 outbreak in eight American Countries: the United States of America, Brazil, Mexico, Argentina, Chile, Colombia, Peru, and Panama, from January 2020 to May 2021. Our analysis reveals that the fraction of reported cases varies across all countries. For example, the reported incidence fraction for the United States of America varies from 0.3 to 0.6, while for Brazil it varies from 0.2 to 0.4.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Solidification and crystallographic texture modeling of laser powder bed fusion Ti-6Al-4V using finite difference-monte carlo method

Laser powder bed fusion (LPBF) additive manufacturing makes near-net-shaped parts with reduced material cost and time, rising as a promising technology to fabricate Ti-6Al-4V, a widely used titanium alloy in aerospace and medical industries. However, LPBF Ti-6Al-4V parts produced with 67° rotation between layers, a scan strategy commonly used to reduce microstructure and property inhomogeneity, have varying grain morphologies and weak crystallographic textures that change depending on processing parameters. Here, this study predicts LPBF Ti-6Al-4V solidification at three energy levels using a finite difference-Monte Carlo method and validates the simulations with large-area electron backscatter diffraction (EBSD) scans. The developed model accurately shows that a <001> texture forms at low energy and a <111> texture occurs at higher energies parallel to the build direction but with a lower strength than the textures observed from EBSD. A validated and well-established method of combining spatial correlation and general spherical harmonics representation of texture is developed to calculate a difference score between simulations and experiments. The quantitative comparison enables effective fine-tuning of nucleation density (N 0 ) input, which shows a nonlinear relationship with increasing energy level. Future improvements in texture prediction code and a more comprehensive study of N 0 with different energy levels will further advance the optimization of LPBF Ti-6Al-4V components. These developments contribute a novel understanding of crystallographic texture formation in LPBF Ti-6Al-4V, the development of robust model validation and calibration pipeline methodologies, and provide a platform for mechanical property prediction and process parameter optimization.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗