Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Monte Carlo method”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Performance evaluation of cosmic ray muon trajectory estimation algorithms

Muons, being elementary particles with minimal interaction with nuclear materials and abundant at sea level, have sparked interest in utilizing them for imaging various applications, such as mining [Borselli et al., Sci. Rep. 12, 22329 (2022)], volcano imaging [Nagamine et al., Nucl. Instrum. Meth. A, 356, 585(1995)], and underground tunnel detection [Guardincerri et al., Pure Appl. Geophys. 174, 2133 (2017)]. Recently, their use in nuclear nonproliferation and safeguard verification has gained attention, particularly in cargo screening for nuclear waste smuggling [Baesso et al., J. Instrum. 9, C10041 (2014)], source localization [L. J. Schultz et al., Nucl. Instrum. Meth. A 519, 687 (2004)], and locating nuclear fuel debris in reactors [Borozdin et al., Phys. Rev. Let. 109, 152501 (2012)]. However, the resolution of muon image reconstruction techniques is limited due to multiple Coulomb scattering (MCS) within the target object. To achieve robust muon tomography, it is crucial to develop efficient and flexible physics-based algorithms that can model the MCS process accurately and estimate the most probable trajectory of muons as they pass through the target object. To address this limitation, in this study, a novel algorithmic approach utilizing the Bayesian probability theory and Gaussian approximation of MCS is chosen. Different energy levels, materials, and target sizes were considered in the evaluations. The results demonstrate that the Generalized Muon Trajectory Estimation (GMTE) algorithm offers significant improvements over currently used algorithms. Across all test scenarios, the GMTE algorithm demonstrated ~50% and 38% increase in precision compared to Straight Line Path (SLP) and Point of Closest Approach (PoCA) algorithms, respectively. Furthermore, it exhibited 10%–35% and 10%–15% increases in muon flux utilization for high and medium Z materials, respectively, compared to the PoCA algorithm. In conclusion, the extensive simulations confirm the enhanced performance and efficiency of the GMTE algorithm, offering improved resolution and reduced measurement time for cosmic ray muon imaging compared to the current SLP and PoCA algorithms.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

3D reconstruction of an inertial-confinement fusion implosion with neural networks using multiple heterogeneous data sources

3D asymmetries are major degradation mechanisms in inertial-confinement fusion implosions at the National Ignition Facility (NIF). These asymmetries can be diagnosed and reconstructed with the neutron imaging system (NIS) on three lines of sight around the NIF target chamber. Conventional tomographic reconstructions are used to reconstruct the 3D morphology of the implosion using NIS [Volegov et al., J. Appl. Phys. 127, 083301 (2020)], but the problem is ill-posed with only three imaging lines of sight. Asymmetries can also be diagnosed with the real-time neutron activation diagnostics (RTNAD) and the neutron time-of-flight (nToF) suite. Since the NIS, RTNAD, and nToF each sample a different part of the implosion using different physical principles, we propose that it is possible to overcome the limitations of too few imaging lines of sight by performing 3D reconstructions that combine information from all three heterogeneous data sources. This work presents a new machine learning-based reconstruction technique to do just this. By using a simple physics model and group of neural networks to map 3D morphologies to data, this technique can easily account for data of multiple different types. A simple proof-of-principle is presented, demonstrating that this technique can accurately reconstruct a hot-spot shape using synthetic primary neutron images and a hot-spot velocity vector. In particular, the hot-spot’s asymmetry, quantified as spherical harmonic coefficients, is reconstructed to within ±4% of the radius in 90% of test cases. In the future, this technique will be applied to actual NIS, RTNAD, and nToF data to better understand 3D asymmetries at the NIF.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Diagnosing hot-spot symmetry in surrogate ignition experiments via secondary DT-neutron spectroscopy at the NIF

The directional energy spectrum of neutrons generated from the in-flight fusion reaction of 1-MeV tritons contains information about the hot-spot symmetry. The National Ignition Facility (NIF) fields Symmetry Capsule (Symcap) implosions, which have historically measured the symmetry of the radiation, drive by measuring the hot-spot shape via x-ray self-emission. Symcaps are used to tune the hot-spot symmetry for ignition experiments at the NIF. This work shows the relationship between directional secondary DT-n spectra and x-ray imaging data for a large database of Symcap implosions. A correlation is observed between the relative widths of the DT-n spectra measured with nTOFs and the shape measured with x-ray imaging. A Monte Carlo model, which computes the directional secondary DT-n spectrum, is used to interpret the results. A comparison of the x-ray and secondary DT-n data with the Monte Carlo model indicates that 56% of the variance between the two datasets is explained by a P2 asymmetry. More advanced simulations using HYDRA suggest that the unaccounted variance is due to P1 and P4 asymmetries present in the hot spot. The comparison of secondary DT-n data and x-ray imaging data to the modeling shows the DT-n data contain important information that supplements current P2 measurements and contain new information about the P1 asymmetry.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Solvent structure and dynamics over Brønsted acid MWW zeolite nanosheets

In the liquid phase of heterogeneous catalysis, solvent plays an important role and governs the kinetics and thermodynamics of a reaction. Although it is often difficult to quantify the role of the solvent, it becomes particularly challenging when a zeolite is used as the catalyst. This difficulty arises from the complex nature of the liquid/zeolite interface and the different solvation environments around catalytically active sites. Here, we use ab initio molecular dynamics simulations to probe the local solvation structure and dynamics of methanol and water over MWW zeolite nanosheets with varying Brønsted acidity. We find that the zeolite framework and the number and location of the acid sites in the zeolite influence the structure and dynamics of the solvent. In particular, methanol is more likely to be in the vicinity of the aluminum (Al 3+ ) at the T4 site than at T1 due to easy accessibility. The methanol oxygen binds strongly to the Al at the T4 site, weakening the Al–O for the bridging acid site, which results in the formation of the silanol group, significantly reducing the acidity of the site. The behavior of methanol is in direct contrast to that of water, where protons can easily propagate from the zeolite to the solvent molecules regardless of the acid site location. Furthermore, our work provides molecular-level insights into how solvent interacts with zeolite surfaces, leading to an improved understanding of the catalytic site in the MWW zeolite nanosheet.

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

General guide concepts for compact, high-brilliance neutron moderators

The trend in neutron sciences is toward integrating compact, high-brightness moderators into new or upgraded facilities. Transporting neutrons from the source to the sample position with a phase-space distribution tailored to specific requirements is crucial to leverage high source brilliance. Here we have investigated four guide concepts using Monte Carlo ray tracing simulations: Montel beamline with nested Kirkpatrick–Baez mirrors, curved-tapered beamline with a bender and straight sections, straight-elliptical beamline, and curved-elliptical beamline. The straight-elliptical (curved-elliptical) beamline features two half-ellipse guides connected by a straight (non-straight) guide section. The neutron transport efficiency and phase space homogeneity have been quantitatively compared. Our results show that the straight-elliptical beamline performs best because of few neutron bounces on the guide surface with small reflection angles, minimizing flux loss. The Montel beamline provides the best spatial confinement of neutrons within the desired region; however, there is a high thermal-neutron loss due to large reflection angles. The curved-tapered beamline suffers from significant flux loss due to high bounces, and it shows a non-uniform angular distribution related to broad ranges of bounces and reflection angles. The non-straight guide section of the curved-elliptical beamline increases the phase space inhomogeneity, leading to a spatially non-uniform beam profile. The results apply to general neutron instruments that require transporting thermal and cold neutrons from a compact, high-brilliance moderator to the sample location with a moderate phase-space volume.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

In-situ relative calibration of Bragg crystals with Monte Carlo line ratio analysis

X-ray line emission spectra can thoroughly characterize hot plasmas, especially when line shapes and ratios convey distinct aspects of plasma conditions. However, the high spectral resolution required for observing line shapes is often at odds with the large bandwidth required to observe many line ratios across a wide spectral range. One strategy to obtain high spectral resolution over a wide bandwidth is to use multiple crystals with calibrated reflectivity so that line intensities across different crystals can be compared. Here, we explore the use of a low-resolution, wide-bandwidth mica survey spectrometer to infer relative reflectivity of two high-resolution, narrow-bandwidth quartz crystals. Finally, a Monte Carlo error analysis determines comparable x-ray line ratios measured from both spectrometers, resulting in an in situ calibration factor and associated uncertainty for the relative reflectivity of the high-resolution crystals.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Modeling ethanol/water adsorption in all-silica zeolites using the real adsorbed solution theory

A comprehensive set of single-component and binary isotherms were collected for ethanol/water adsorption into the siliceous forms of 185 known zeolites using grand-canonical Monte Carlo simulations. Using these data, a systematic analysis of ideal/real adsorbed-solution theory (IAST/RAST) was conducted and activity coefficients were derived for ethanol/water mixtures adsorbed in different zeolites based on RAST. It was found that activity coefficients of ethanol are close to unity while activity coefficients of water are larger in most zeolites, indicating a positive excess free energy of the mixture. This observation can be attributed to water/ethanol interactions being less favorable than water/water interactions in the single-component adsorption of water at comparable loadings. The deviation from ideal behavior can be highly structure-dependent but no clear correlation with pore diameters was identified. Furthermore, our analysis also demonstrates the following: (1) accurate unary isotherms in the low-loading regime are critical for obtaining physically sensible activity coefficients; (2) the global regression scheme to solve for activity model parameters performs better than fitting activity models to activity coefficients calculated locally at each binary state point; and (3) including the dependence on adsorption potential offers only a minor benefit for describing binary adsorption at the lowest fugacities. Finally, the Margules activity model was found incapable of capturing the non-ideal adsorption behavior over the entire range of fugacities and compositions in all zeolites, but for conditions typical of solution-phase adsorption, RAST predictions using zeolite-specific or even bulk Margules parameters provide an improved description compared to IAST.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

A compact x-ray spectrometer for measurements of electron temperature distributions in inertial confinement fusion implosions at OMEGA

The Wedge Range Filter (WRF), commonly used for proton spectroscopy at the OMEGA Laser Facility and National Ignition Facility, is adapted to measure the x-ray continuum spectrum through transmission measurement using a continuous-gradient filter. Continuum x rays emitted from the hotspot of an implosion contain information about the plasma composition and electron temperature. The WRF data are leveraged to probe this distribution, specifically the electron temperature distribution. In this work, the data recorded with the WRF are forward modeled using a temperature distribution model folded with the WRF response function. An uncertainty analysis is conducted through a Bayesian regression algorithm using a Hamiltonian Monte Carlo sampler. This analysis enables the uncertainties in the instrument response to be folded into the uncertainty estimation of the electron temperature and absolute x-ray emission. Data analysis for a series of OMEGA implosions is presented and compared with radiation hydrodynamic simulations.

Lasers↗
DOE OSTI2025

Constraining the 3He + 3He Gamow energy probed in high energy density plasmas at the National Ignition Facility

Polar-direct-drive implosions at the National Ignition Facility generated large plasma volumes to study the 3He + 3He fusion reaction. The ion temperature, which determines the Gamow peak energy, was constrained by isolating the thermal contribution to the D3He-proton spectral width in a 3He plasma doped with deuterium. X-ray penumbral imaging was used to measure electron temperature, density, and hotspot volume, which was subsequently used to model the spectral broadening from plasma stopping power. Results showed 30% of the D3He-proton spectral width was due to stopping power, with residual flows contributing ≈10%. The 3He temperature was determined as T3He = 12.4 ± 3.2 keV, corresponding to a Gamow energy of 95 ± 14 keV. These experiments achieved the lowest Gamow energy to date for studying 3He + 3He fusion in high energy density plasma, approaching conditions in the Sun.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Statistical inference of collision frequencies from x-ray Thomson scattering spectra

Thomson scattering spectra measure the response of plasma particles to incident radiation. In warm dense matter, which is opaque to visible light, x-ray Thomson scattering (XRTS) enables a detailed probe of the electron distribution and has been used as a diagnostic for electron temperature, density, and plasma ionization. In this work, we examine the sensitivities of inelastic XRTS signatures to modeling details, including the dynamic collision frequency and the electronic density of states. Applying verified Monte Carlo inversion methods to dynamic structure factors obtained from time-dependent density functional theory, we assess the utility of XRTS signals as a way to inform the dynamic collision frequency, especially its direct-current limit, which is directly related to the electrical conductivity.

Collision frequency↗
DOE OSTI2024

A discretized representation for Monte Carlo simulation of deformed semiflexible chains

In this study, we present a novel orientation discretization approach based on the rhombic triacontahedron for Monte Carlo simulations of semiflexible polymer chains, aiming at enhancing structural analysis through rheo-small-angle scattering (rheo-SAS). Our approach provides a more accurate representation of the geometric features of semiflexible chains under deformation, surpassing the capabilities of traditional lattice structures. Validation against the Kratky–Porod chain system demonstrated superior consistency, underscoring its potential to significantly improve the precision of uncovering geometric details from rheo-SAS data. Further, this approach opens new avenues for investigating the conformations of semiflexible polymers and mechanically induced phase transitions in more complex polymer structures, offering deeper insights into their behavior under various conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Incident beam optics optimization for the single crystal neutron diffractometer Pioneer with a polarized beam option

Pioneer, a next-generation single-crystal neutron diffractometer, is under development for Oak Ridge National Laboratory’s Second Target Station. Designed to address a wide range of scientific questions, Pioneer will deliver homogeneous neutron beams with customizable size and divergence and provide a polarized beam option. This article introduces its incident beam optics, highlighting the optimization methodology and the simulated performance. Pioneer will utilize a modified elliptical-straight guide for neutron transport and deploy slit packages and insertable apertures to control beam size and divergence. The optimized guide geometry matches the optimal-and-full-sample-illumination condition, and the beam control system effectively filters out unwanted neutrons while preserving the desired ones. In addition, we have found that polygon-approximated guides provide satisfactory transport efficiency and beam homogeneity, eliminating the need for truly curved guides. Further, to enhance neutronics performance and reduce cost, the coatings of supermirror elements are individually optimized to the lowest half-integer m-values that are sufficient to deliver the desired neutrons. After evaluating polarizing V-cavities and 3 He spin filters over the default polarized wavelength band of 1.2–5.5 Å, we selected a translatable multichannel polarizing V-cavity as the incident beam polarizer. Strategically placed at a location where the beam divergence is low and a large in-guide gap has negligible impact on transport efficiency, the optimized V-cavity achieves an average P 2 T of ~35%.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Charge regulation effects on colloidal mixture nanoparticles

Changes in pH within a system containing dissociable sites affect the protonation and deprotonation of these groups, thereby influencing their physical properties. In response, the system modifies their surface charge, affecting electrostatic interactions, aggregation, stability, and structural behavior. Although the pH can be tuned in experiments, it is difficult to model this phenomenon using simulations or theoretical approaches. Here, we perform hybrid Monte Carlo-molecular dynamics simulations to model charge regulation effects in an equimolar colloidal charged system. We compare charge regulation effects with those of a system in which the charges of colloidal nanoparticles are not dissociable. The comparison between the two cases modifies the phase diagram, and it changes the volume fraction where a percolation network of nanoparticles is found. Charge regulation is found to destroy network formation, as the charge in the nanoparticles is modified because of the cooperativity dependency of the degree of charge dissociation sites among the nanoparticles favoring cluster formation. Furthermore, our work suggests that the ionic and/or electronic conductivity in functionalized nanoparticles can be modified by changing pH values. It also guides the experimental design of oppositely charged nanoparticles as inks for 3D printing processes.

Classical statistical mechanics↗
DOE OSTI2025

Developing reliable machine learning interatomic potential for Fe–Cr–Ni austenitic alloys

Gaining atomistic understanding of mechanical behavior of heat-resistant structural materials such as Fe–Cr–Ni-based alloys requires an approach with an accuracy close to density functional theory (DFT) that considers the intrinsic properties of the bulk lattice and important defects such as stacking faults, grain boundaries, and surfaces. This work aims to develop reliable machine learning interatomic potential (MLIAP) at cross-scale for Fe–Cr–Ni ternary alloys with a focus on the face-centered-cubic (fcc) solid solution structure. Leveraging the advantages of moment tensor potentials, which typically necessitate a relatively small training dataset and enable rapid calculations using the large-scale atomic/molecular massively parallel simulator package, we ensure the stability and accuracy of the trained potentials. Important defects such as stacking faults, grain boundaries, and surfaces for wide-range compositions are investigated. Structural, thermal, elastic, and defect properties are determined from molecular dynamics simulations comprising several thousand atoms, generated via canonical Monte Carlo simulations guided by the trained potential. The trained potential allows efficient atomic simulations of structural, thermal, and mechanical properties of fcc Fe–Cr–Ni solid solution alloys as a function of composition and temperature. Therefore, the MLIAP approach represents a major advancement from DFT calculations that are limited to small simulation sizes and traditional molecular dynamics simulations using relatively low accuracy potentials. Furthermore, this work outlines a practical foundation for further investigating the structural evolution and mechanical behavior of austenitic stainless steel and nickel-based alloys in a wide array of applications in extreme environments.

Crystal structure↗
DOE OSTI2025

Simultaneous inference of equation of state parameters and unknown data errors with uncertainty quantification via hierarchical Bayesian posterior maximization

Equations of state (EOSs) are a key component in running hydrodynamic simulations as they relate the thermodynamic states for the material. The Davis reactants EOS is commonly used for modeling high explosives (HEs), and the EOS model parameters are calibrated using material specific data. The calibrations are often performed with uncertainty quantification via Bayesian inference to account for uncertainty in the data and generate ensembles of likely parameters. However, there are relatively few HE data sets to use for calibration and many are historical and lack error information. In this work, we simultaneously calibrate the Davis reactants EOS model parameters and unknown data error terms for the high explosive PBX 9501. To quantify the uncertainty in the models and the data, we use a Bayesian framework for the calibration and compute the hierarchical Bayesian posterior distribution with both a posteriori maximization approach and Markov Chain Monte Carlo. In general, we find that, given our assumptions, the two approaches result in similar calibrated parameters, posterior covariance matrices, and insights about the parameters but that the posterior maximization requires far less computational resources.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Confinement-controlled selective CO 2 insertion into a dicopper dihydride core: A multiscale mechanistic study

CO 2 is an abundant C 1 feedstock for fuel and chemical synthesis. We have previously demonstrated experimentally a stepwise insertion of CO 2 into a [Cu 2 H 2 ] core via a solid–gas in crystallo reaction, forming formate species that are unstable and inaccessible under solution-phase conditions. This work elucidates how structural confinement within the crystal lattice enables such selective reactivity. In particular, co-crystallized tetrahydrofuran molecules induce site asymmetry around the [Cu 2 H 2 ] unit, modulating both the local electronic environment and CO 2 diffusion pathways. Using a multiscale computational approach that combines classical molecular mechanics, hybrid quantum mechanics/molecular mechanics molecular dynamics, and enhanced-sampling free energy calculations, we demonstrate how site asymmetry affects CO 2 binding affinities and reaction pathways. These results provide detailed mechanistic insight into CO 2 insertion and hydride transfer, highlighting key differences between crystal- and solution-phase pathways and offering a general framework for understanding how lattice confinement shapes chemical reactivity.

Chemical bonding↗
DOE OSTI2025

Two-frequency RF fields induced multipactor in coaxial transmission lines

This study presents a comprehensive investigation of two-surface multipactor discharge in coaxial transmission lines under two-frequency radio frequency (RF) excitation using one-dimensional Monte Carlo simulations validated against three-dimensional particle-in-cell simulations and experimental data. The results show that introducing a second carrier mode can suppress multipactor by reshaping and shrinking the susceptibility region, with the extent and location of suppression strongly dependent on the device's aspect ratio and the relative phase of the second carrier mode. Distinct suppression patterns are observed across different fd regimes, while in some cases, susceptibility expansion also occurs under two-frequency operation. A key outcome is the identification and delineation of pure and mixed multipactor modes in coaxial geometry, where analytical mode boundaries are not readily available. Unlike planar geometries, pure-mode regions in coaxial systems overlap with mixed-mode domains, complicating mode identification. Additionally, image charge forces are found to have negligible influence on susceptibility thresholds but strongly affect electron growth rates. These findings offer valuable insights into the use of waveform engineering for controlling multipactor in high-power RF systems.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Development of interatomic potential and effect of ordering on defect properties in CrMnV

Developing materials that can withstand extreme environments, such as high radiation doses and elevated temperatures, is crucial for next-generation particle accelerators, including the 2.4 MW Long-Baseline Neutrino Facility. High-Entropy Alloys have emerged as promising candidates for beam window materials due to their superior mechanical strength, corrosion resistance, and radiation tolerance. In this study, we focus on the Cr–Mn–V alloy system, developing and employing machine-learning interatomic potentials (MLIPs) to investigate the formation of an ordered phase and its influence on defect properties. Using hybrid Monte Carlo-Molecular Dynamics simulations, we observe the formation of a B2-ordered phase at lower temperatures, consistent with Density Functional Theory (DFT) predictions. Ordered structures display a bimodal distribution of migration energies and reduced mean square displacement values, indicating suppressed vacancy diffusion. Our results also show that the migration energy barrier varies based on the atomic species, with Mn and V exhibiting the highest and lowest average barriers, respectively. These findings suggest that atomic ordering inhibits defect mobility, potentially enhancing the radiation resistance of CrMnV alloys. The validated MLIP provides a reliable framework for simulations that are faster than traditional DFT while maintaining the accuracy required to study defect and ordering properties.

36 MATERIALS SCIENCE↗