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At least 1,297 records · Page 72
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Uncertainty Quantification Methodology for Sonic Boom Loudness of a Low-Boom Supersonic Concept

This paper presents a comprehensive analysis of uncertainty quantification for sonic boom loudness metrics associated with the X-59 aircraft during its acoustic validation phase. The study focuses on employing advanced methodologies to characterize uncertainties in key sonic boom parameters predicted from a database derived from a computational fluid dynamics (CFD) solver. These methodologies include creating a polynomial chaos expansion (PCE) surrogate model, which is then used to run a Monte Carlo analysis to obtain 95% uncertainty intervals for sonic boom loudness parameters across the full carpet. Atmospheric uncertainties are rigorously considered, leveraging weather models based on historical data near Edwards Air Force Base to simulate potential flight conditions. The findings include preliminary uncertainty results for the full carpet during the validation phase of the Quesst mission. Additionally, a sensitivity study reveals that the primary sources of uncertainty are humidity and cruise weight.

Laura M. White↗
DOE OSTI2022

Equation of State Optimization and Uncertainty Quantization: Implementation in the LANL EOS Production Code OpenSesame

We detail the approaches of particle swarm optimization and Bayesian inference through Markov chain Monte Carlo for equation of state development. This work includes formulation of the modeling for the equation of state, numeric optimization of the parametric models via particle swarm optimization, and generation of probability distributions of equations of state from Markov chain Monte Carlo.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2016

Panchromatic Imaging of a Transitional Disk: The Disk of GM AUR in Optical and FUV Scattered Light

We have imaged GM Aurigae with the Hubble Space Telescope, detected its disk in scattered light at 1400 and 1650 A, and compared these with observations at 3300 A, 5550 A, 1.1 micron, and 1.6 micron. The scattered light increases at shorter wavelengths. The radial surface brightness profile at 3300 A shows no evidence of the 24 au radius cavity that has been previously observed in submillimeter observations. Comparison with dust grain opacity models indicates that the surface of the entire disk is populated with submicron grains. We have compiled a spectral energy distribution from 0.1 micron to 1 mm and used it to constrain a model of the star + disk system that includes the submillimeter cavity using the Monte Carlo radiative transfer code by Barbara Whitney. The best-fit model image indicates that the cavity should be detectable in the F330W bandpass if the cavity has been cleared of both large and small dust grains, but we do not detect it. The lack of an observed cavity can be explained by the presence of submicron grains interior to the submillimeter cavity wall. We suggest one explanation for this that could be due to a planet of mass less than 9M(sub J) interior to 24 au. A unique cylindrical structure is detected in the far- UV data from the Advanced Camera for Surveys/Solar Blind Channel. It is aligned along the system semiminor axis, but does not resemble an accretion-driven jet. The structure is limb brightened and extends 190 +/- 35 au above the disk midplane. The inner radius of the limb brightening is 40 +/- 10 au, just beyond the submillimeter cavity wall.

circumstellar matter aEuro" protoplanetary disks a↗
NASA NTRS2015

Proposal for a Sample Pilot Response Model

Regulations to establish operational and performance requirements for unmanned aircraft systems (UAS) are being developed by a consortium of government, industry and academic institutions. Those requirements will apply to the new detect and avoid (DAA) systems and other equipment necessary to integrate UAS with the National Airspace System (NAS) and are determined according to their contribution to the overall safety case for such an integration. In order to perform end-to-end verification and validation of DAA requirements, a committee accepted pilot response model is needed to emulate UAS pilots in closed-loop Monte Carlo fast-time simulations. This briefing focuses on background of the pilot model used in previous Airspace Concept Evaluation System studies, identification of strengths and weaknesses in that model, and proposals on model improvements. The briefing also looks to build consensus around a common architecture and assumptions for modeling the pilot for UAS DAA systems.

Santiago, Confesor↗
DOE OSTI2020

Simulating the Trajectory and Biomass Growth of Free-Floating Macroalgal Cultivation Platforms along the U.S. West Coast

Trajectory tracking and macroalgal growth models were coupled to support a novel macroalgae-harvesting concept known as the Nautical Off-shore Macroalgal Autonomous Device (NOMAD). The NOMAD consists of 5 km long carbon-fiber longlines that are seeded and free float southward along the U.S. West Coast for approximately 3 months before harvesting off the California coast, taking advantage of favorable environmental conditions. The trajectory and macroalgal growth models were applied to answer planning questions pertinent to the techno-economic analysis such as identifying the preferred release location, approximate pathway, timing until harvest, and estimated growth. Trajectories were determined with the General NOAA Operational Modeling Environment (GNOME) model, using 11 years of current and wind data, determining probabilities by running nearly 40,000 Monte Carlo simulations varying the start time and location. An accompanying macroalgal growth model was used to estimate the growth of macroalgae based on the trajectory tracks and environmental forcing products, including light, temperature and nutrients. Model results show that NOMAD lines transit south in the months of April to September due to seasonal currents, taking approximately 3 months to reach Southern California. During transit, NOMAD lines are dispersed but typically avoid beaching or passing through marine sanctuaries. NOMAD lines can yield up to 30 kg wet weight per meter of cultivation line.

09 BIOMASS FUELS↗
NASA NTRS1998

Monte Carlo Calculations of Polarized Microwave Radiation Emerging from Cloud Structures

The last decade has seen tremendous growth in cloud dynamical and microphysical models that are able to simulate storms and storm systems with very high spatial resolution, typically of the order of a few kilometers. The fairly realistic distributions of cloud and hydrometeor properties that these models generate has in turn led to a renewed interest in the three-dimensional microwave radiative transfer modeling needed to understand the effect of cloud and rainfall inhomogeneities upon microwave observations. Monte Carlo methods, and particularly backwards Monte Carlo methods have shown themselves to be very desirable due to the quick convergence of the solutions. Unfortunately, backwards Monte Carlo methods are not well suited to treat polarized radiation. This study reviews the existing Monte Carlo methods and presents a new polarized Monte Carlo radiative transfer code. The code is based on a forward scheme but uses aliasing techniques to keep the computational requirements equivalent to the backwards solution. Radiative transfer computations have been performed using a microphysical-dynamical cloud model and the results are presented together with the algorithm description.

Kummerow, Christian↗
DOE OSTI2024

Surface Segregation Studies in Ternary Noble Metal Alloys: Comparing DFT and Machine Learning with Experimental Data

Abstract Surface segregation, whereby the surface composition of an alloy differs systematically from the bulk, has historically been hard to study, because it requires experimental and modeling methods that span alloy composition space. In this work, we study surface segregation in catalytically relevant noble and platinum‐group metal alloys with a focus on three ternary systems: AgAuCu, AuCuPd, and CuPdPt. We develop a data set of 2478 fcc slabs with those compositions including all three low‐index crystallographic orientations relaxed with Density Functional Theory using the PBEsol functional with D3 dispersion corrections. We fine‐tune a machine learning model on this data and use the model in a series of 1800 Monte Carlo simulations spanning ternary composition space for each surface orientation and ternary chemical system. The results of these simulations are validated against prior experimental surface segregation data collected using composition spread alloy films for AgAuCu and AuCuPd. Our findings reveal that simulations conducted using the (110) orientation most closely match experimentally observed surface segregation trends, and while predicted trends qualitatively match observation, biases in the PBEsol functional limit numeric accuracy. This study advances understanding of surface segregation and the utility of computational studies and highlights the need for further improvements in simulation accuracy.

Chemistry↗
DOE OSTI2021

Temperature-Dependent Configurational Entropy Calculations for Refractory High-Entropy Alloys

The cluster expansion formalism for alloys is used to construct surrogate models for three refractory high-entropy alloys (NbTiVZr, HfNbTaTiZr, and AlHfNbTaTiZr). These cluster expansion models are then used along with Monte Carlo methods and thermodynamic integration to calculate the configurational entropy of these refractory high-entropy alloys as a function of temperature. Many solid solution alloy design guidelines are based on the ideal entropy of mixing, which increases monotonically with N , the number of elements in the alloy. However, our results show that at low temperatures, the configurational entropy of these materials is largely independent of N , and the assumption described above only holds in the high-temperature limit. This suggests that alloy design guidelines based on the ideal entropy of mixing require further examination.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Multi-output multilevel best linear unbiased estimators via semidefinite programming

Multifidelity forward uncertainty quantification (UQ) problems often involve multiple quantities of interest and heterogeneous models (e.g., different grids, equations, dimensions, physics, surrogate and reduced-order models). While computational efficiency is key in this context, multi-output strategies in multilevel/multifidelity methods are either sub-optimal or non-existent. In this paper we extend multilevel best linear unbiased estimators (MLBLUE) to multi-output forward UQ problems and we present new semidefinite programming formulations for their optimal setup. Not only do these formulations yield the optimal number of samples required, but also the optimal selection of low-fidelity models to use. While existing MLBLUE approaches are single-output only and require a non-trivial nonlinear optimization procedure, the new multi-output formulations can be solved reliably and efficiently. Here, we demonstrate the efficacy of the new methods and formulations in practical UQ problems with model heterogeneity.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Thick target neutron yields from Beryllium, Carbon, Tungsten, and Lead targets irradiated by 26.7 MeV/nucleon 4 H e ions

The angular and energy distributions of secondary neutrons produced from 26.7 MeV/nucleon 4 He ions, stopping in thick Be, C, W and Pb targets are measured by the time of flight method. The GEANT4, PHITS, and FLUKA Monte Carlo simulation codes with different physics models are employed to simulate the neutron yields and the results are compared with the experimental data. For the thick Be and C targets, GEANT4 with INCL++ reproduces the experimental data reasonably well. Whereas PHITS with JQMD-2.0 overestimates the neutron yields at intermediate energies and FLUKA with PEANUT underestimated the neutron yields at intermediate energies. For W and Pb targets, FLUKA with PEANUT physics model agree with experimental data best. PHITS with JQMD-2.0 overestimates the neutron yield at intermediate energies at 0°, and GEANT4 with INCL++ underestimates the neutron yield at intermediate energies at three angles.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Jet cone radius dependence of R AA and v 2 at PbPb 5.02 TeV from JEWEL+T R ENTo+v-USPhydro

We combine, for the first time, event-by-event T R ENTo initial conditions with the relativistic viscous hydrodynamic model v-USPhydro and the Monte Carlo event generator JEWEL to make predictions for the nuclear modification factor R AA and jet azimuthal anisotropies v n { 2 } in $\sqrt{s_{NN}}$ = 5.02 TeV PbPb collisions for multiple centralities and values of the jet cone radius R. The R-dependence of R AA and v 2 { 2 } strongly depends on the presence of recoiling scattering centers. We find a small jet v 3 { 2 } in mid-central collisions and consistent results in wide jet p T regions and centralities with ATLAS data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Unveiling the Finite Temperature Physics of Hydrogen Chains via Auxiliary Field Quantum Monte Carlo

The ability to accurately predict the finite temperature properties and phase diagrams of realistic quantum solids is central to uncovering new phases and engineering materials with novel properties ripe for device applications. Nonetheless, there remain comparatively few many-body techniques capable of elucidating the finite temperature physics of solids from first principles. Here, we take a significant step toward developing such a technique by generalizing our previous, exact fully ab initio finite temperature Auxiliary Field Quantum Monte Carlo (FT-AFQMC) method to model periodic solids and employing it to uncover the finite temperature physics of periodic hydrogen chains. Our chains’ unit cells consist of 10 hydrogen atoms modeled in a minimal basis, and we sample 5 k-points from the first Brillouin zone to arrive at a supercell consisting of 50 orbitals and 50 electrons. Based upon our calculations of these chains’ many-body energies, free energies, entropies, heat capacities, double and natural occupancies, and charge and spin correlation functions, we outline their metal–insulator and magnetic ordering as a function of both H–H bond distance and temperature. At low temperatures approaching the ground state, we observe both metal–insulator and ferromagnetic–antiferromagnetic crossovers at bond lengths between 0.5 and 0.75 Å. We then demonstrate how this low-temperature ordering evolves into a metallic phase with decreasing magnetic order at higher temperatures. In order to contextualize our results, we compare the features we observe to those previously seen in one-dimensional, half-filled Hubbard models at finite temperature and in ground state hydrogen chains. Interestingly, we identify signatures of the Pomeranchuk effect in hydrogen chains for the first time and show that spin and charge excitations that typically arise at distinct temperatures in the Hubbard model are indistinguishably coupled in these systems. Beyond qualitatively revealing the many-body phase behavior of hydrogen chains in a numerically exact manner without invoking the phaseless approximation, our efforts shed light on the further theoretical developments that will be required to construct the phase diagrams of the more complex transition metal, lanthanide, and actinide solids of longstanding interest to physicists.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Modeling the Photoelectrochemical Evolution of Lead-Based, Mixed-Halide Perovskites Due to Photosegregation

Lead-based, mixed-halide perovskites such as methylammonium lead iodide-bromide [MAPb(I 1-x Br x ) 3 ] undergo anion photosegregation under illumination. This is observed as low band gap photoluminescence from photogenerated iodine-rich domains due to favorable band offsets that induce carrier funneling into them. Unfortunately, theoretical rationalizations of mixed-halide photosegregation are complicated by biases inherent to photoluminescence-based observations. Recent compositionally-weighted X-ray diffraction (XRD) measurements now reveal broad distributions of photosegregated stoichiometries not captured by existing photosegregation models. To better bridge experiment and theory, we perform kinetic Monte Carlo (KMC) simulations of photosegregation within the context of a band gap-based thermodynamic model, which has previously accounted for numerous experimental observations. Our KMC simulations are modified to consider high carrier density Fermi-Dirac statistics that result from carrier funneling and accumulation within photosegregated I-rich domains. Obtained KMC results reproduce broad x terminal distributions seen experimentally and illustrate how they are characterized by a central, heavily I-enriched stoichiometry. I-rich domain “drifting” during photosegregation rationalizes the long photosegregation timescales seen experimentally with drifting simultaneously producing a wake of variable stoichiometry I-rich inclusions that form the lion’s share of stoichiometric heterogeneities seen in compositionally-weighted XRD measurements. These simulations and accompanying rationalizations further reveal a general criterion for realizing favorable free energies to induce demixing. Central to the criterion is the statistical occupation of low gap inclusions in the parent alloy by excitations. Furthermore, the resulting model thus provides a general framework for conceptualizing mixed-halide perovskite light and temperature sensitivities, mediated by photocarriers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Quantifying uncertainty in analysis of shockless dynamic compression experiments on platinum. I. Inverse Lagrangian analysis

Absolute measurements of solid-material compressibility by magnetically driven shockless dynamic compression experiments to multi-megabar pressures have the potential to greatly improve the accuracy and precision of pressure calibration standards for use in diamond anvil cell experiments. Here, to this end, we apply characteristics-based inverse Lagrangian analysis (ILA) to 11 sets of ramp-compression data on pure platinum (Pt) metal and then reduce the resulting weighted-mean stress–strain curve to the principal isentrope and room-temperature isotherm using simple models for yield stress and Grüneisen parameter. We introduce several improvements to methods for ILA and quasi-isentrope reduction, the latter including calculation of corrections in wave speed instead of stress and pressure to render results largely independent of initial yield stress while enforcing thermodynamic consistency near zero pressure. More importantly, we quantify in detail the propagation of experimental uncertainty through ILA and model uncertainty through quasi-isentrope reduction, considering all potential sources of error except the electrode and window material models used in ILA. Compared to previous approaches, we find larger uncertainty in longitudinal stress. Monte Carlo analysis demonstrates that uncertainty in the yield-stress model constitutes by far the largest contribution to uncertainty in quasi-isentrope reduction corrections. We present a new room-temperature isotherm for Pt up to 444 GPa, with 1-sigma uncertainty at that pressure of just under ±1.2%; the latter is about a factor of three smaller than uncertainty previously reported for multi-megabar ramp-compression experiments on Pt. The result is well represented by a Vinet-form compression curve with (isothermal) bulk modulus K 0 = 270.3 ± 3.8 GPa, pressure derivative K$^{'}_{0}$= 5.66 ± 0.10, and correlation coefficient $R_{K_{0},K^{'}_{0}}$= –0.843.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Versatile stochastic model for predictive KMC simulation of fcc metal nanostructure evolution with realistic kinetics

Stochastic lattice-gas models provide the natural framework for analysis of the surface diffusion-mediated evolution of crystalline metal nanostructures on the appropriate time scale (often 10 1 –10 4 s) and length scale. Model behavior can be precisely assessed by kinetic Monte Carlo simulation, typically incorporating a rejection-free algorithm to efficiently handle the broad range of Arrhenius rates for hopping of surface atoms. The model should realistically prescribe these rates, or the associated barriers, for a diversity of local surface environments. However, commonly used generic choices for barriers fail, even qualitatively, to simultaneously describe diffusion for different low-index facets, for terrace vs step edge diffusion, etc. We introduce an alternative Unconventional Interaction–Conventional Interaction formalism to prescribe these barriers, which, even with few parameters, can realistically capture most aspects of behavior. Here, the model is illustrated for single-component fcc metal systems, mainly for the case of Ag. It is quite versatile and can be applied to describe both the post-deposition evolution of 2D nanostructures in homoepitaxial thin films (e.g., reshaping and coalescence of 2D islands) and the post-synthesis evolution of 3D nanocrystals (e.g., reshaping of nanocrystals synthesized with various faceted non-equilibrium shapes back to 3D equilibrium Wulff shapes).

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

A Forward Analytic Model of Neutron Time-of-Flight Signals for Inferring Ion Temperatures from MagLIF Experiments

A forward analytic model is required to rapidly simulate the neutron time-of-flight (nToF) signals that result from magnetized liner inertial fusion (MagLIF) experiments at Sandia’s Z Pulsed Power Facility. Various experimental parameters, such as the burn-weighted fuel-ion temperature and liner areal density, determine the shape of the nToF signal and are important for characterizing any given MagLIF experiment. Extracting these parameters from measured nToF signals requires an appropriate analytic model that includes the primary deuterium-deuterium neutron peak, once-scattered neutrons in the beryllium liner of the MagLIF target, and direct beamline attenuation. Here, mathematical expressions for this model were derived from the general-geometry time- and energy-dependent neutron transport equation with anisotropic scattering. Assumptions consistent with the time-of-flight technique were used to simplify this linear Boltzmann transport equation into a more tractable form. Models of the uncollided and once-collided neutron scalar fluxes were developed for one of the five nToF detector locations at the Z-Machine. Numerical results from these models were produced for a representative MagLIF problem and found to be in good agreement with similar neutron transport simulations. Twenty experimental MagLIF data sets were analyzed using the forward models, which were determined to only be significantly sensitive to the ion temperature. The results of this work were also found to agree with values obtained separately using a zero scatter analytic model and a high-fidelity Monte Carlo simulation. Finally, inherent difficulties in this and similar techniques are identified, and a new approach forward is suggested.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Expected ${\boldsymbol H \xrightarrow{} {\boldsymbol{\mu^+\mu^-}}} $ measurement precision with ${\boldsymbol { e^{+}e^{-}}{\bf \xrightarrow{}}{ \boldsymbol{Z(q\bar{q})H}}}$ production at the CEPC *

Here, a search for the dimuon decay of the Standard Model Higgs boson is performed using Monte Carlo simulated events to mimic data corresponding to an integrated luminosity of 5.6 ab -1 collected with the Circular Electron-Positron Collider detector in e + e - collisions at $\sqrt{s}$ =240 GeV. This study investigates the e + e - →ZH, Z → $q\bar{q}$, H → μ + μ - process, and the expected significance considering only the statistical uncertainty in the data for a background-only hypothesis for a Higgs boson with a mass of 125 GeV is found to be 6.1 σ, corresponding to a precision of 19%. The systematic impacts from the background Monte Carlo statistical fluctuations are estimated to be negligible. Moreover, the dependence of the measurement accuracy on the muon momentum resolution of the CEPC detector is investigated. It is found that the muon momentum resolution must be better than 204 MeV to discover the H →μμ process at the nominal integrated luminosity. If the resolution is 100% worse than the designed parameter, the integrated luminosity must be greater than 7.2 ab -1 to reach 5σ significance.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Determination of the mean energy of fast electron losses and anisotropies through thick-target emission on WEST

Abstract A new method to obtain the mean energy of fast electron losses in fusion plasmas using a versatile multi-energy hard x-ray (HXR) detector is presented. The method is based on measuring the thick-target emission of tungsten in the divertor region produced by fast electron losses interacting with the target and modeling the tungsten spectra by a Monte Carlo code which simulates the interaction between a beam of electrons and a solid target. The mean energy of the fast electron losses is determined through the comparison between the experimental and synthetic emission. The results show that fast electron losses during lower hybrid current drive discharges at WEST have a mean energy of 90–140 keV and represent only 2% of the total heat flux at the target. Additionally, anisotropic HXR emission has been detected for the first time at the WEST core and edge plasma, with opposite directions. It is due to the forward-peak emission of two distinctive populations of fast electrons: co-current fast electrons in the core and counter-current fast electron losses at the inner strike point. In view of future experiments like ITER where electron cyclotron current drive will generate a fast electron population, this technique could serve as a real-time monitor of fast electron losses and eventually feed an actuator on the current drive generation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗