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Results for “Monte Carlo Modelling”

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 1,729 records · Page 96
All sourcesNASA NTRSDOE OSTI
NASA NTRS1974

The economic value of remote sensing of earth resources from space: An ERTS overview and the value of continuity of service. Volume 3: Intensive use of living resources, agriculture. Part 2: Distribution effects

The results of an investigation of the value of improving information for forecasting future crop harvests are described. A theoretical model is developed to calculate the value of increased speed of availablitiy of that information. The analysis of U.S. domestic wheat consumption was implemented. New estimates of a demand function for wheat and of a cost of storage function were involved, along with a Monte Carlo simulation for the wheat spot and future markets and a model of market determinations of wheat inventories. Results are shown to depend critically on the accuracy of current and proposed measurement techniques.

Bradford, D. F.↗
NASA NTRS1981

Modeling of thin-film GaAs growth

Efforts to produce a Monte Carlo computer program for the analysis of crystal growth are briefly discussed. A literature survey was conducted of articles relating to the subject. A list of references reviewed is presented.

Heinbockel, J. H.↗
NASA NTRS1995

Recent advances in PDF modeling of turbulent reacting flows

This viewgraph presentation concludes that a Monte Carlo probability density function (PDF) solution successfully couples with an existing finite volume code; PDF solution method applied to turbulent reacting flows shows good agreement with data; and PDF methods must be run on parallel machines for practical use.

Leonard, Andrew D.↗
NASA NTRS2000

Model for radial dependence of frequency distributions for energy imparted in nanometer volumes from HZE particles

This paper develops a deterministic model of frequency distributions for energy imparted (total energy deposition) in small volumes similar to DNA molecules from high-energy ions of interest for space radiation protection and cancer therapy. Frequency distributions for energy imparted are useful for considering radiation quality and for modeling biological damage produced by ionizing radiation. For high-energy ions, secondary electron (delta-ray) tracks originating from a primary ion track make dominant contributions to energy deposition events in small volumes. Our method uses the distribution of electrons produced about an ion's path and incorporates results from Monte Carlo simulation of electron tracks to predict frequency distributions for ions, including their dependence on radial distance. The contribution from primary ion events is treated using an impact parameter formalism of spatially restricted linear energy transfer (LET) and energy-transfer straggling. We validate our model by comparing it directly to results from Monte Carlo simulations for proton and alpha-particle tracks. We show for the first time frequency distributions of energy imparted in DNA structures by several high-energy ions such as cosmic-ray iron ions. Our comparison with results from Monte Carlo simulations at low energies indicates the accuracy of the method.

Non-NASA Center↗
DOE OSTI2026

Li1−xNiO2 Many-body DMC Benchmark Dataset

The dataset contains all numerical data generated in support of the manuscript “Many‑body Benchmark of Electronic Charge and Spin Densities for Li1–xNiO2​” (Journal of Chemical Theory and Computation, DOI: 10.1021/acs.jctc.5c02097, URL: https://pubs.acs.org/doi/10.1021/acs.jctc.5c02097). The materials included in this repository are: 1. Data files used to produce all figures and tables in the main manuscript and supporting information. 2. Benchmark density‑functional theory (DFT) datasets used for the charge‑ and spin‑density analyses. 3. Reference many‑body diffusion Monte Carlo (DMC) calculations and associated input/output files.

36 MATERIALS SCIENCE↗
NASA NTRS2016

Probabilistic Prognosis of Non-Planar Fatigue Crack Growth

Quantifying the uncertainty in model parameters for the purpose of damage prognosis can be accomplished utilizing Bayesian inference and damage diagnosis data from sources such as non-destructive evaluation or structural health monitoring. The number of samples required to solve the Bayesian inverse problem through common sampling techniques (e.g., Markov chain Monte Carlo) renders high-fidelity finite element-based damage growth models unusable due to prohibitive computation times. However, these types of models are often the only option when attempting to model complex damage growth in real-world structures. Here, a recently developed high-fidelity crack growth model is used which, when compared to finite element-based modeling, has demonstrated reductions in computation times of three orders of magnitude through the use of surrogate models and machine learning. The model is flexible in that only the expensive computation of the crack driving forces is replaced by the surrogate models, leaving the remaining parameters accessible for uncertainty quantification. A probabilistic prognosis framework incorporating this model is developed and demonstrated for non-planar crack growth in a modified, edge-notched, aluminum tensile specimen. Predictions of remaining useful life are made over time for five updates of the damage diagnosis data, and prognostic metrics are utilized to evaluate the performance of the prognostic framework. Challenges specific to the probabilistic prognosis of non-planar fatigue crack growth are highlighted and discussed in the context of the experimental results.

Leser, Patrick E.↗
DOE OSTI2023

Solving the nuclear pairing model with neural network quantum states

In this work, we present a variational Monte Carlo method that solves the nuclear many-body problem in the occupation number formalism exploiting an artificial neural network representation of the groundstate wave function. A memory-efficient version of the stochastic reconfiguration algorithm is developed to train the network by minimizing the expectation value of the Hamiltonian. We benchmark this approach against widely used nuclear many-body methods by solving a model used to describe pairing in nuclei for different types of interaction and different values of the interaction strength. Despite its polynomial computational cost, our method outperforms coupled-cluster and provides energies that are in excellent agreement with the numerically-exact full configuration interaction values.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2007

Risk Assessment of Bone Fracture During Space Exploration Missions to the Moon and Mars

The possibility of a traumatic bone fracture in space is a concern due to the observed decrease in astronaut bone mineral density (BMD) during spaceflight and because of the physical demands of the mission. The Bone Fracture Risk Module (BFxRM) was developed to quantify the probability of fracture at the femoral neck and lumbar spine during space exploration missions. The BFxRM is scenario-based, providing predictions for specific activities or events during a particular space mission. The key elements of the BFxRM are the mission parameters, the biomechanical loading models, the bone loss and fracture models and the incidence rate of the activity or event. Uncertainties in the model parameters arise due to variations within the population and unknowns associated with the effects of the space environment. Consequently, parameter distributions were used in Monte Carlo simulations to obtain an estimate of fracture probability under real mission scenarios. The model predicts an increase in the probability of fracture as the mission length increases and fracture is more likely in the higher gravitational field of Mars than on the moon. The resulting probability predictions and sensitivity analyses of the BFxRM can be used as an engineering tool for mission operation and resource planning in order to mitigate the risk of bone fracture in space.

Lewandowski, Beth E.↗
NASA NTRS2008

Risk Assessment of Bone Fracture During Space Exploration Missions to the Moon and Mars

The possibility of a traumatic bone fracture in space is a concern due to the observed decrease in astronaut bone mineral density (BMD) during spaceflight and because of the physical demands of the mission. The Bone Fracture Risk Module (BFxRM) was developed to quantify the probability of fracture at the femoral neck and lumbar spine during space exploration missions. The BFxRM is scenario-based, providing predictions for specific activities or events during a particular space mission. The key elements of the BFxRM are the mission parameters, the biomechanical loading models, the bone loss and fracture models and the incidence rate of the activity or event. Uncertainties in the model parameters arise due to variations within the population and unknowns associated with the effects of the space environment. Consequently, parameter distributions were used in Monte Carlo simulations to obtain an estimate of fracture probability under real mission scenarios. The model predicts an increase in the probability of fracture as the mission length increases and fracture is more likely in the higher gravitational field of Mars than on the moon. The resulting probability predictions and sensitivity analyses of the BFxRM can be used as an engineering tool for mission operation and resource planning in order to mitigate the risk of bone fracture in space.

Lewandowski, Beth E.↗
NASA NTRS1999

Envelope structure of deeply embedded young stellar objects in the Serpens Molecular Cloud

Aperture-synthesis and single-dish (sub-) millimeter molecular-line and continuum observations reveal in great detail the envelope structure of deeply embedded young stellar objects (SMM 1 = FIRS 1, SMM 2, SMM 3, SMM 4) in the densely star-forming Serpens Molecular Cloud. SMM 1, 3, and 4 show partially resolved (>2" = 800 AU) continuum emission in the beam of the Owens Valley Millimeter Array at lambda = 3.4-1.4 mm. The continuum visibilities accurately constrain the density structure in the envelopes, which can be described by a radial power law with slope -2.0 +/- 0.5 on scales of 300 to 8000 AU. Inferred envelope masses within a radius of 8000 AU are 8.7, 3.0, and 5.3 Msolar for SMM 1, 3, and 4, respectively. A point source with 20%-30% of the total flux at 1.1 mm is required to fit the observations on long baselines, corresponding to warm envelope material within approximately 100 AU or a circumstellar disk. No continuum emission is detected interferometrically toward SMM 2, corresponding to an upper limit of 0.2 Msolar assuming Td = 24 K. The lack of any compact dust emission suggests that the SMM 2 core does not contain a central protostar. Aperture-synthesis observations of the 13CO, C18O, HCO+, H13CO+, HCN, H13CN, N2H+ 1-0, SiO 2-1, and SO 2(2)-1(1) transitions reveal compact emission toward SMM 1, 3, and 4. SMM 2 shows only a number of clumps scattered throughout the primary field of view, supporting the conclusion that this core does not contain a central star. The compact molecular emission around SMM 1, 3, and 4 traces 5"-10" (2000-4000 AU) diameter cores that correspond to the densest regions of the envelopes, as well as material directly associated with the molecular outflow. Especially prominent are the optically thick HCN and HCO+ lines that show up brightly along the walls of the outflow cavities. SO and SiO trace shocked material, where their abundances may be enhanced by 1-2 orders of magnitude over dark-cloud values. A total of 31 molecular transitions have been observed with the James Clerk Maxwell and Caltech Submillimeter telescopes in the 230, 345, 490, and 690 GHz atmospheric windows toward all four sources, containing, among others, lines of CO, HCO+, HCN, H2CO, SiO, SO, and their isotopomers. These lines show 20-30 km s-1 wide line wings, deep and narrow (1-2 km s-1) self-absorption, and 2-3 km s-1 FWHM line cores. The presence of highly excited lines like 12CO 4-3 and 6-5, 13CO 6-5, and several H2CO transitions indicates the presence of material with temperatures > or approximately 100 K. Monte Carlo calculations of the molecular excitation and line transfer show that the envelope model derived from the dust emission can successfully reproduce the observed line intensities. The depletion of CO in the cold gas is modest compared to values inferred in objects like NGC 1333 IRAS 4, suggesting that the phase of large depletions through the entire envelope is short lived and may be influenced by the local star formation density. Emission in high-excitation lines of CO and H2CO requires the presence of a small amount of approximately 100 K material, comprising less than 1% of the total envelope mass and probably associated with the outflow or the innermost region of the envelope. The derived molecular abundances in the warm (Tkin > 20 K) envelope are similar to those found toward other class 0 YSOs like IRAS 16293-2422, though some species appear enhanced toward SMM 1. Taken together, the presented observations and analysis provide the first comprehensive view of the physical and chemical structure of the envelopes of deeply embedded young stellar objects in a clustered environment on scales between 1000 and 10,000 AU.

NASA Discipline Exobiology↗
DOE OSTI2023

Multi-fidelity microstructure-induced uncertainty quantification by advanced Monte Carlo methods

Quantifying uncertainty associated with the microstructure variation of a material can be a computationally daunting task, especially when dealing with advanced constitutive models and fine mesh resolutions in the crystal plasticity finite element method (CPFEM). Numerous studies have been conducted regarding the sensitivity of material properties and performance to the mesh resolution and choice of constitutive model. However, a unified approach that accounts for various fidelity parameters, such as mesh resolutions, integration time-steps and constitutive models simultaneously is currently lacking. Further, this paper proposes a novel uncertainty quantification (UQ) approach for computing the properties and performance of homogenized materials using CPFEM, that exploits a hierarchy of approximations with different levels of fidelity. In particular, we illustrate how multi-level sampling methods, such as multi-level Monte Carlo (MLMC) and multi-index Monte Carlo (MIMC), can be applied to assess the impact of variations in the microstructure of polycrystalline materials on the predictions of homogenized materials properties. We show that by adaptively exploiting the fidelity hierarchy, we can significantly reduce the number of microstructures required to reach a certain prescribed accuracy. Finally, we show how our approach can be extended to a multi-fidelity framework, where we allow the underlying constitutive model to be chosen from either a phenomenological plasticity model or a dislocation-density-based model.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Search for leptonic charge asymmetry in $t\overline{t}W$ production in final states with three leptons at $\sqrt{s}$ = 13 TeV

A search for the leptonic charge asymmetry (${A}_{c}^{\ell}$) of top-quark-antiquark pair production in association with a $W$ boson ($t\overline{t}W$) is presented. The search is performed using final states with exactly three charged light leptons (electrons or muons) and is based on $\sqrt{s}$= 13 TeV proton-proton collision data collected with the ATLAS detector at the Large Hadron Collider at CERN during the years 2015–2018, corresponding to an integrated luminosity of 139 fb –1 . A profile-likelihood fit to the event yields in multiple regions corresponding to positive and negative differences between the pseudorapidities of the charged leptons from top-quark and top-antiquark decays is used to extract the charge asymmetry. At reconstruction level, the asymmetry is found to be –0.12 ± 0.14 (stat.) ± 0.05 (syst.). An unfolding procedure is applied to convert the result at reconstruction level into a charge-asymmetry value in a fiducial volume at particle level with the result of –0.11 ± 0.17 (stat.) ± 0.05 (syst.). The Standard Model expectations for these two observables are calculated using Monte Carlo simulations with next-to-leading-order plus parton shower precision in quantum chromodynamics and including next-to-leading-order electroweak corrections. They are ${–0.084}_{–0.003}^{+0.005}$ (scale) ± 0.006 (MC stat.) and ${–0.063}_{–0.004}^{+0.007}$ (scale) ± 0.004 (MC stat.) respectively, and in agreement with the measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Nematic order driven by superconducting correlations

The interplay of nematicity and superconductivity has been observed in a wide variety of quantum materials. To explore this interplay, we consider a two-dimensional (2D) array of nematogens, local droplets with Z 3 nematicity, coupled to a network of Josephson junction wires. Using finite temperature classical Monte Carlo simulations, we elucidate the phase diagram of this model and show that the development of superconducting correlations and the directional delocalization of Cooper pairs can promote nematogen ordering, resulting in long-range nematic order. We obtain the transport properties of our model within an effective resistor network picture. We discuss these ideas in the context of the 2D electron gas at the (111) KTaO 3 interface and the doped topological insulators Nb x Bi 2 Se 3 and Cu x Bi 2 Se 3 . Overall, our work makes contact with Phil Anderson’s numerous contributions to broken symmetries driven by the saving of kinetic energy, including double exchange ferromagnetism and the interlayer tunneling theory of high Tc csuperconductivity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Pathway for decarbonizing residential building operations in the US and China beyond the mid-century

With global carbon budget targets looming, residential buildings in top economies must become carbon neutral as soon as possible to reserve more emission space for emerging carbon-emitting economies. This study is the first to compare the operational decarbonization process of China’s and the United States (US) residential buildings from 2000 to 2060 by combining the end-use emission model with the decomposing structural decomposition (DSD) method and Monte Carlo simulation. The results show that from 2001 to 2020 China decarbonized 1544 mega-tons of carbon dioxide (MtCO 2 ) and the US decarbonized 1848 MtCO 2 . In the business-as-usual scenario, China will hit its emission peak in 2031 (±3) with 934 (±61) MtCO 2 , while the US will maintain a lock-in level of 736 (±133) MtCO 2 since the 2030s. In the decarbonization scenario, operational carbon neutrality for residential buildings in 2060 is promoted by an increase in clean power generation proportion, building-integrated power generation level, building electrification level, and a reduction in end-use energy intensity, which will contribute 34.4 %, 21.4 %, 14.3 %, and 29.9 % in China and 32.9 %, 33.1 %, 8.2 %, and 25.8 % in the US, respectively. Especially, building-integrated power generation in China only costs about 40 % of what it costs in the US. Besides, high-decarbonization strategies for residential building operations are proposed as references for governments to formulate targeted climate policies. Overall, this study offers data benchmarks for buildings’ carbon neutrality of top economies to further promote synergistic carbon neutrality with the buildings of emerging economies in the age of Post COP27.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Feasibility of DEIM for retrieving the initial field via dimensionality reduction

When parameter estimation is solved in a high-dimensional space, the dimensionality reduction strategy becomes the primary consideration for alleviating the tremendous computational cost. Here, the discrete empirical interpolation method (DEIM) is explored to retrieve the initial condition (IC) by combining the polynomial chaos (PC) based ensemble Kalman filter (i.e. PC-EnKF), where a non-intrusive PC expansion is considered as a surrogate model in place of the forward model in the prediction step of the ensemble Kalman filter, resulting in fewer forward model integrations but with a comparable accuracy as Monte Carlo-based approaches. The DEIM acts as a hyper-reduction tool to provide the low-dimensional input for the high-dimensional initial field, which can be reconstructed using the information on the sparse interpolation grid points that is adaptively obtained through PC-EnKF data assimilation method. Thus an innovative framework to reconstruct the IC is developed. The detailed procedure at each assimilation iteration includes: the determination of the spatial interpolation points, the estimation of the initial values on the interpolation locations using the optimal observations, and the reconstruction of IC in the full space. The current study uses the reconstruction field of initial conditions of the Navier-Stokes equations as an example to illustrate the efficacy of our method. The experimental results demonstrate the proposed algorithm achieves a satisfactory reconstruction for the initial field. The proposed method helps to extend the applicable area of DEIM in solving inverse problems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Initial validation of ALFRED: A Monte Carlo code built on Geant4 for TREAT energy deposition

Predicting the energy deposited in the specimen during an experiment in the Transient Reactor Test (TREAT) Facility is a complex problem due to the nature of the transients occurring in the reactor. In addition, the many particles contributing to energy deposition have different behavior in time and space. ALFRED, a new Geant4 based code, is developed to transport and simulate each particle generated in the core. This code is verified against OpenMC (Open Monte Carlo) on the Godiva benchmark and a simple TREAT model. Next, the energy deposition in TREAT is calculated: 181.05 ± 0.01 MeV for the “instantaneous” energy deposition (which accounts for the energy deposited within 1 s after neutron emission) in fuel and 189.90 ± 0.01 MeV for the total energy deposition in fuel. We discuss these results in this paper with previous calculations and experimental evaluations. This work demonstrates ALFRED’s potential as a high-fidelity tool for computing the spatial and temporal energy deposition in TREAT paving the way for a better understanding of the energy coupling factors in TREAT.

73 - NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

A Comprehensive Monte Carlo Framework for Jet-Quenching

This article presents the motivation for developing a comprehensive modeling framework in which different models and parameter inputs can be compared and evaluated for a large range of jet-quenching observables measured in relativistic heavy-ion collisions at RHIC and the LHC. Here, the concept of a framework is discussed within the context of recent efforts by the JET Collaboration, the authors of JEWEL, and the JETSCAPE collaborations. The framework ingredients for each of these approaches is presented with a sample of important results from each. The role of advanced statistical tools in comparing models to data is also discussed, along with the need for a more detailed accounting of correlated errors in experimental results.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Revealing Intermetallic Active Sites of PtNi Nanocatalysts for Reverse Water Gas Shift Reaction

Bimetallic nanoparticles have gained great interest due to their potential applications in catalysis. By combining Lattice Boltzmann Modeling (LBM), Density Functional Theory (DFT) calculations, and kinetic Monte Carlo (KMC) simulation, here we rationalize the superior performance of supported Pt-Ni alloy nanostructures over Pt and Ni alone during the reverse Water Gas Shift (rWGS) reaction, which was observed previously. The LBM simulation including the diffusion and flow of the reacting gas molecules within the supporting nanoporous channels in SBA-15 indicates that the simple combination of contributions from Ni and Pt alone is not enough to result in the observed promotion in rWGS activity and selectivity of the Pt-Ni alloy. Instead, the synergy between Pt and Ni via a unique intermetallic motif is responsible according to the DFT and KMC simulation. In conclusion, compared to the monometallic counterparts, the intermetallic-introduced ensemble effect at the low-coordinated Pt-Ni hybrid site of Pt-Ni alloy nanocatalysts enables the enhanced activation of CO 2 and promoted removal of CO/H 2 O as gas phase product.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗