SEARCH · Engineering Papers

Results for “Diffusion model”

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.

SourceResearch connectionFrom yearThrough year

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

At least 1,063 records · Page 59

All sources NASA NTRS DOE OSTI

DOE OSTI2011

Discrete Event Modeling and Massively Parallel Execution of Epidemic Outbreak Phenomena

In complex phenomena such as epidemiological outbreaks, the intensity of inherent feedback effects and the significant role of transients in the dynamics make simulation the only effective method for proactive, reactive or post-facto analysis. The spatial scale, runtime speed, and behavioral detail needed in detailed simulations of epidemic outbreaks make it necessary to use large-scale parallel processing. Here, an optimistic parallel execution of a new discrete event formulation of a reaction-diffusion simulation model of epidemic propagation is presented to facilitate in dramatically increasing the fidelity and speed by which epidemiological simulations can be performed. Rollback support needed during optimistic parallel execution is achieved by combining reverse computation with a small amount of incremental state saving. Parallel speedup of over 5,500 and other runtime performance metrics of the system are observed with weak-scaling execution on a small (8,192-core) Blue Gene / P system, while scalability with a weak-scaling speedup of over 10,000 is demonstrated on 65,536 cores of a large Cray XT5 system. Scenarios representing large population sizes exceeding several hundreds of millions of individuals in the largest cases are successfully exercised to verify model scalability.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

An Investigation of Thermal Properties of 2D Materials [Dissertation]

Studying the thermal conductivity of 2D materials is important due to the applications of 2D materials in fields such as thermal management, thermoelectricity, renewable energy, and sensors. As such, measurements of the thermal conductivity of these 2D materials become important to measure. Thermal conductivity is often difficult to measure for 2D materials due to their atomically thin nature and many experimental methods for doing so requiring contact with the sample, which can alter the thermal properties. A non-contact method for calculating the thermal conductivity of 2D materials supported on substrates in order to model the thermal conductivity of 2D materials for devices, is proposed and experimentally performed in this dissertation. The optothermal Raman technique is a useful non-contact diagnostic technique useful in determining the thermal conductivity of 2D materials. The optothermal Raman typically does not account for heat losses due to convection or radiation or substrate resistance, which are shown to be important factors to consider when developing an optothermal Raman model. Additionally, the calculation of the interfacial thermal conductance between the bottom surface of the sample and the top surface of the substrate, plays an important role in determining the final value of the thermal conductivity of a supported sample, and will yield differing results based on whether or not the conductance is calculated using an approach such as the Diffuse Mismatch Model (DMM) or calculated directly by varying the laser heating profile (usually done by changing the laser objective). This is shown to be the case for both graphene on Ni, graphene on Cu, and SnSe 2 on Cu. In addition to experimentally calculating the thermal conductivity of a 2D material with the optothermal Raman technique, the thermal conductivity of 2D materials can also be calculated using computational methods. The three-phonon method is a method which can be used to simulate phonon scattering processes and determine the thermal conductivity of semiconductors, wherein phonon scattering is the dominant mechanism which determines the thermal conductivity. The three-phonon method uses relaxation times for phonon scattering with other phonons, electrons, and other material system elements, such as isotopes or material defects, in order to create a single-mode relaxation time approximation (SMRTA), which is used to calculate the final value of the thermal conductivity. An important consideration when determining the thermal conductivity of a 2D material using this method is the device geometry, which is reflected in this work as the phonon-boundary scattering relaxation time. This inclusion is important along with the inclusion of phonon-electron scattering in accurately determining the thermal conductivity of a 2D material. In both the optothermal Raman experiments and the three-phonon method computations, strain is shown to have a demonstrable effect on the thermal conductivity of 2D materials. When a 1.1% strain was applied to the mechanical properties of SnSe, the three-phonon processes yielded a lower thermal conductivity than the no-strain case. For the optothermal Raman experiments, the strain induced in the Cu substrate and transferred to a single-layer graphene (SLG) sample yields a trend where the thermal conductivity of the SLG decreases with respect to strain applied. In the case where the interfacial thermal conductance was calculated directly, the conductance increased with respect to strain applied. This presents strain as a reliable and viable method for tuning the thermal properties of 2D materials for device applications.

36 MATERIALS SCIENCE↗

DOE OSTI2017

A microstructure sensitive grain boundary sliding and slip based constitutive model for machining of $\mathrm{Ti}$-$\mathrm{6Al}$-$\mathrm{4V}$

We report a composite dual phase internal state variable constitutive model was developed for Ti-6Al-4V. The proposed model includes diffusion assisted grain boundary sliding based physics in addition to a traditional slip-based plasticity. Influence of microstructure on the flow stress is introduced via dislocation density and mean grain size internal state variables. The dislocation density evolves according to a physics based law that considers dislocation nucleation and annihilation processes. Grain refinement is driven by dynamic recrystallization, which is modeled phenomenologically. The model is calibrated with uniaxial stress–strain data that ranges between quasi-static and dynamic rates across a wide range of temperatures. Validation against machining data shows that the model predicts chip segmentation frequency, machining forces, and tool temperatures reasonably well. The newly introduced grain boundary sliding physics was found to dominate deformation following sufficient grain refinement. This deformation mode provides softening at the constitutive level without the need for invoking damage based softening mechanisms. This physical interpretation is something that has not previously been explored in the machining literature.

36 MATERIALS SCIENCE↗

DOE OSTI2011

Influence of crystal orientation and ion bombardment on the nitrogen diffusivity in single-crystalline austenitic stainless steel

The nitrogen diffusivity in single-crystalline AISI 316L austenitic stainless steel (ASS) during ion nitriding has been investigated at different crystal orientations ((001), (110), (111)) under variations of ion flux (0.3-0.7 mA cm{sup -2}), ion energy (0.5-1.2 keV), and temperature (370-430 deg. C). The nitrogen depth profiles obtained from nuclear reaction analysis are in excellent agreement with fits using the model of diffusion under the influence of traps, from which diffusion coefficients were extracted. At fixed ion energy and flux, the diffusivity varies by a factor up to 2.5 at different crystal orientations. At (100) orientation, it increases linearly with increasing ion flux or energy. The findings are discussed on the basis of atomistic mechanisms of interstitial diffusion, potential lattice distortions, local decomposition, and ion-induced lattice vibrational excitations.

36 MATERIALS SCIENCE↗

DOE OSTI2011

Discrete event modeling and massively parallel execution of epidemic outbreak phenomena

In complex phenomena such as epidemiological outbreaks, the intensity of inherent feedback effects and the significant role of transients in the dynamics make simulation the only effective method for proactive, reactive or post facto analysis. The spatial scale, runtime speed, and behavioral detail needed in detailed simulations of epidemic outbreaks cannot be supported by sequential or small-scale parallel execution, making it necessary to use large-scale parallel processing. Here, an optimistic parallel execution of a new discrete event formulation of a reaction–diffusion simulation model of epidemic propagation is presented to facilitate a dramatic increase in the fidelity and speed by which epidemiological simulations can be performed. Rollback support needed during optimistic parallel execution is achieved by combining reverse computation with a small amount of incremental state saving. Parallel speedup of over 5,500 and other runtime performance metrics of the system are observed with weak-scaling execution on a small (8,192-core) Blue Gene/P system, while scalability with a weak-scaling speedup of over 10,000 is demonstrated on 65,536 cores of a large Cray XT5 system. Scenarios representing large population sizes, with mobility and detailed state evolution modeled at the level of each individual, exceeding several hundreds of millions of individuals in the largest cases, are successfully exercised to verify model scalability.

Computer Science↗

DOE OSTI2020

Physics-Informed Deep Neural Networks for Learning Parameters and Constitutive Relationships in Subsurface Flow Problems

In this paper, we present a physics informed deep neural network (DNN) method for estimating parameters and unknown physics (constitutive relationships) in partial differential equation (PDE) models. We use PDEs in addition to measurements to train DNNs to approximate unknown parameters and constitutive relationships as well as states. The proposed approach increases the accuracy of DNN approximations of partially known functions when a limited number of measurements is available and allows for training DNNs when no direct measurements of the functions of interest are available. We employ physics informed DNNs to estimate the unknown space-dependent diffusion coefficient in a linear diffusion equation and an unknown constitutive relationship in a non-linear diffusion equation. For the parameter estimation problem, we assume that partial measurements of the coefficient and states are available and demonstrate that under these conditions, the proposed method is more accurate than state-of-the-art methods. For the non-linear diffusion PDE model with a fully unknown constitutive relationship (i.e., no measurements of constitutive relationship are available), the physics informed DNN method can accurately estimate the non-linear constitutive relationship based on state measurements only. Finally, we demonstrate that the proposed method remains accurate in the presence of measurement noise.

42 ENGINEERING↗

DOE OSTI2018

Ensemble Grouping Strategies for Embedded Stochastic Collocation Methods Applied to Anisotropic Diffusion Problems

Previous work has demonstrated that propagating groups of samples, called ensembles, together through forward simulations can dramatically reduce the aggregate cost of sampling-based uncertainty propagation methods [E. Phipps, M. D'Elia, H. C. Edwards, M. Hoemmen, J. Hu, and S. Rajamanickam, SIAM J. Sci. Comput., 39 (2017), pp. C162--C193]. However, critical to the success of this approach when applied to challenging problems of scientific interest is the grouping of samples into ensembles to minimize the total computational work. For example, the total number of linear solver iterations for ensemble systems may be strongly influenced by which samples form the ensemble when applying iterative linear solvers to parameterized and stochastic linear systems. In this paper we explore sample grouping strategies for local adaptive stochastic collocation methods applied to PDEs with uncertain input data, in particular canonical anisotropic diffusion problems where the diffusion coefficient is modeled by truncated Karhunen--Loève expansions. Finally, we demonstrate that a measure of the total anisotropy of the diffusion coefficient is a good surrogate for the number of linear solver iterations for each sample and therefore provides a simple and effective metric for grouping samples.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

Planck 2013 results. XIV. Zodiacal emission

The Planck satellite provides a set of all-sky maps at nine frequencies from 30GHz to 857GHz. Planets, minor bodies, and diffuse interplanetary dust emission (IPD) are all observed. The IPD can be separated from Galactic and other emissions because Planck views a given point on the celestial sphere multiple times, through different columns of IPD. We use the Planck data to investigate the behaviour of zodiacal emission over the whole sky at sub-millimetre and millimetre wavelengths. We fit the Planck data to find the emissivities of the various components of the COBE zodiacal model-a diffuse cloud, three asteroidal dust bands, a circumsolar ring, and an Earth-trailing feature. The emissivity of the diffuse cloud decreases with increasing wavelength, as expected from earlier analyses. The emissivities of the dust bands, however, decrease less rapidly, indicating that the properties of the grains in the bands are different from those in the diffuse cloud. We fit the small amount of Galactic emission seen through the telescope's far sidelobes, and place limits on possible contamination of the cosmic microwave background (CMB) results from both zodiacal and far-sidelobe emission. When necessary, the results are used in the Planck pipeline to make maps with zodiacal emission and far sidelobes removed. We show that the zodiacal correction to the CMB maps is small compared to the Planck CMB temperature power spectrum and give a list of flux densities for small solar system bodies.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2012

Thermal conductivity of ZnO thin film produced by reactive sputtering

ZnO thin films have been produced by reactive sputtering with different oxygen contents in the sputtering gas. As a result of transmission electronic microscopy observation, each film consist of two layers: an interfacial layer close to the substrate, with a thickness of about 200 nm, composed of very fine crystal grains and an upper layer above the interfacial layer, composed of column-shaped grains aligned along the out-plane direction. The grain diameter ranges from 35 to 100 nm depending on the oxygen partial pressure. The in-plane and out-plane thermal conductivity have been measured at room temperature. The out-plane thermal conductivity of the interfacial layer is 2.3 W m{sup -1} K{sup -1}, independent on the oxygen partial pressure. The out-plane thermal conductivity of the upper layer is 5.4, 7.1, and 4.0 W m{sup -1} K{sup -1}, and the in-plane thermal conductivity 4.86, 6.01, and 2.66 W m{sup -1} K{sup -1}, for the O{sub 2} 30%, 60%, and 90% ZnO film, respectively. Both out-plane and in-plane thermal conductivity decrease with the decrease of grain diameter. The thermal conductance of grain boundary has been estimated with the phonon diffusion mismatch model, and the intrinsic thermal conductivity within ZnO grains has been calculated with a cylinder-structured composite model. The result shows that the thermal conductivity of the ZnO thin films is dominated by the intrinsic thermal conductivity, which is a function of grain size.

36 MATERIALS SCIENCE↗

DOE OSTI2015

FermI large area telescope third source catalog

We present the third Fermi Large Area Telescope (LAT) source catalog (3FGL) of sources in the 100 MeV–300 GeV range. Based on the first 4 yr of science data from the Fermi Gamma-ray Space Telescope mission, it is the deepest yet in this energy range. Relative to the Second Fermi LAT catalog, the 3FGL catalog incorporates twice as much data, as well as a number of analysis improvements, including improved calibrations at the event reconstruction level, an updated model for Galactic diffuse γ-ray emission, a refined procedure for source detection, and improved methods for associating LAT sources with potential counterparts at other wavelengths. The 3FGL catalog includes 3033 sources above 4σ significance, with source location regions, spectral properties, and monthly light curves for each. Of these, 78 are flagged as potentially being due to imperfections in the model for Galactic diffuse emission. Twenty-five sources are modeled explicitly as spatially extended, and overall 238 sources are considered as identified based on angular extent or correlated variability (periodic or otherwise) observed at other wavelengths. For 1010 sources we have not found plausible counterparts at other wavelengths. More than 1100 of the identified or associated sources are active galaxies of the blazar class; several other classes of non-blazar active galaxies are also represented in the 3FGL. Pulsars represent the largest Galactic source class. From source counts of Galactic sources we estimate that the contribution of unresolved sources to the Galactic diffuse emission is ∼3% at 1 GeV.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2012

THE ABUNDANCE OF MOLECULAR HYDROGEN AND ITS CORRELATION WITH MIDPLANE PRESSURE IN GALAXIES: NON-EQUILIBRIUM, TURBULENT, CHEMICAL MODELS

Observations of spiral galaxies show a strong linear correlation between the ratio of molecular to atomic hydrogen surface density R{sub mol} and midplane pressure. To explain this, we simulate three-dimensional, magnetized turbulence, including simplified treatments of non-equilibrium chemistry and the propagation of dissociating radiation, to follow the formation of H{sub 2} from cold atomic gas. The formation timescale for H{sub 2} is sufficiently long that equilibrium is not reached within the 20-30 Myr lifetimes of molecular clouds. The equilibrium balance between radiative dissociation and H{sub 2} formation on dust grains fails to predict the time-dependent molecular fractions we find. A simple, time-dependent model of H{sub 2} formation can reproduce the gross behavior, although turbulent density perturbations increase molecular fractions by a factor of few above it. In contradiction to equilibrium models, radiative dissociation of molecules plays little role in our model for diffuse radiation fields with strengths less than 10 times that of the solar neighborhood, because of the effective self-shielding of H{sub 2}. The observed correlation of R{sub mol} with pressure corresponds to a correlation with local gas density if the effective temperature in the cold neutral medium of galactic disks is roughly constant. We indeed find such a correlation of R{sub mol} with density. If we examine the value of R{sub mol} in our local models after a free-fall time at their average density, as expected for models of molecular cloud formation by large-scale gravitational instability, our models reproduce the observed correlation over more than an order-of-magnitude range in density.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

SECONDARY PRODUCTION AS THE ORIGIN OF THE COSMIC-RAY POSITRON EXCESS

The Alpha Magnetic Spectrometer has released high-precision data for cosmic rays, and has verified an excess of positrons relative to expectations from cosmic-ray interactions in the interstellar medium. An exciting and well-known possibility for the excess is production of electron–positron pairs by annihilating dark matter particles in the halo of the Galaxy. We have constructed a new scenario for the propagation of cosmic rays, based on the 2000 SMILI results and various other astrophysical observations and measurements in which the positron excess is due to secondary production. The scenario is studied from a simple heuristic perspective, and also within the constraints of a diffusion-reacceleration model using GALPROP. The conclusions of each approach agree with one another, showing that the scenario agrees well with the observed positron flux, without any need for dark matter or other exotic production mechanisms.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2015

New complex bismuth oxides in the Bi{sub 2}O{sub 3}–NiO–Sb{sub 2}O{sub 5} system and their properties

Phase equilibria in the Bi{sub 2}O{sub 3}–NiO–Sb{sub 2}O{sub 5} system have been investigated. The isothermal section of the system (650°) has been constructed. For the first time the existence of the pyrochlore structure solid solution, (Bi{sub 2−x}Ni{sub x})Ni{sub 2/3−y}Sb{sub 4/3+y}O{sub 7±δ}, x=0.1−0.35, y=0−0.1, and a new compound Bi{sub 3}Ni{sub 2/3}Sb{sub 7/3}O{sub 11} of KSbO{sub 3} structure type have been discovered. The structures and properties of these compounds were studied by XRD, XAFS, diffuse reflection spectroscopy and magnetic methods. Rietveld refinement of synchrotron radiation-based powder XRD data for pyrochlore sample of 38.43Bi{sub 2}O{sub 3}–33.0NiO–28.57Sb{sub 2}O{sub 5} composition and Bi{sub 3}Ni{sub 2/3}Sb{sub 7/3}O{sub 11} compound was performed. The best possible refinement of the positional parameters for both pyrochlore and Bi{sub 3}Ni{sub 2/3}Sb{sub 7/3}O{sub 11} structures was achieved for disordered models. Magnetic, diffuse reflection and an X-ray absorption spectroscopy study confirmed that in both compounds nickel ions are mainly in a 2+ oxidation state. According to magnetic data, Bi{sub 1.84}Ni{sub 0.16}(Ni{sub 0.63}Sb{sub 1.37})O{sub 7} pyrochlore and Bi{sub 3}Ni{sub 2/3}Sb{sub 7/3}O{sub 11} are overall paramagnetic in nature. - Graphical abstract: Isothermal section of the Bi{sub 2}O{sub 3}–NiO–Sb{sub 2}O{sub 5} system at 650 °C in air and variation of magnetic susceptibility and inverse susceptibility with temperature for Bi{sub 1.84}Ni{sub 0.79}Sb{sub 1.37}O{sub 7} pyrochlore. - Highlights: • We have constructed the isothermal section of the system Bi{sub 2}O{sub 3}–NiO–Sb{sub 2}O{sub 5}. • The boundaries of pyrochlore structure solid solution have been determined. • New Bi{sub 3}Ni{sub 2/3}Sb{sub 7/3}O{sub 11} compound of KSbO{sub 3} structure type have been discovered. • The structures were studied by means of synchrotron X-ray diffraction and XAFS. • Magnetic measurements revealed that both compounds are paramagnetic at 2–350 K.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2012

FERMI-LAT OBSERVATIONS OF THE DIFFUSE {gamma}-RAY EMISSION: IMPLICATIONS FOR COSMIC RAYS AND THE INTERSTELLAR MEDIUM

The {gamma}-ray sky >100 MeV is dominated by the diffuse emissions from interactions of cosmic rays with the interstellar gas and radiation fields of the Milky Way. Observations of these diffuse emissions provide a tool to study cosmic-ray origin and propagation, and the interstellar medium. We present measurements from the first 21 months of the Fermi Large Area Telescope (Fermi-LAT) mission and compare with models of the diffuse {gamma}-ray emission generated using the GALPROP code. The models are fitted to cosmic-ray data and incorporate astrophysical input for the distribution of cosmic-ray sources, interstellar gas, and radiation fields. To assess uncertainties associated with the astrophysical input, a grid of models is created by varying within observational limits the distribution of cosmic-ray sources, the size of the cosmic-ray confinement volume (halo), and the distribution of interstellar gas. An all-sky maximum-likelihood fit is used to determine the X{sub CO} factor, the ratio between integrated CO-line intensity and H{sub 2} column density, the fluxes and spectra of the {gamma}-ray point sources from the first Fermi-LAT catalog, and the intensity and spectrum of the isotropic background including residual cosmic rays that were misclassified as {gamma}-rays, all of which have some dependency on the assumed diffuse emission model. The models are compared on the basis of their maximum-likelihood ratios as well as spectra, longitude, and latitude profiles. We also provide residual maps for the data following subtraction of the diffuse emission models. The models are consistent with the data at high and intermediate latitudes but underpredict the data in the inner Galaxy for energies above a few GeV. Possible explanations for this discrepancy are discussed, including the contribution by undetected point-source populations and spectral variations of cosmic rays throughout the Galaxy. In the outer Galaxy, we find that the data prefer models with a flatter distribution of cosmic-ray sources, a larger cosmic-ray halo, or greater gas density than is usually assumed. Our results in the outer Galaxy are consistent with other Fermi-LAT studies of this region that used different analysis methods than employed in this paper.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2013

Cone beam x-ray luminescence computed tomography: A feasibility study

Purpose: The appearance of x-ray luminescence computed tomography (XLCT) opens new possibilities to perform molecular imaging by x ray. In the previous XLCT system, the sample was irradiated by a sequence of narrow x-ray beams and the x-ray luminescence was measured by a highly sensitive charge coupled device (CCD) camera. This resulted in a relatively long sampling time and relatively low utilization of the x-ray beam. In this paper, a novel cone beam x-ray luminescence computed tomography strategy is proposed, which can fully utilize the x-ray dose and shorten the scanning time. The imaging model and reconstruction method are described. The validity of the imaging strategy has been studied in this paper. Methods: In the cone beam XLCT system, the cone beam x ray was adopted to illuminate the sample and a highly sensitive CCD camera was utilized to acquire luminescent photons emitted from the sample. Photons scattering in biological tissues makes it an ill-posed problem to reconstruct the 3D distribution of the x-ray luminescent sample in the cone beam XLCT. In order to overcome this issue, the authors used the diffusion approximation model to describe the photon propagation in tissues, and employed the sparse regularization method for reconstruction. An incomplete variables truncated conjugate gradient method and permissible region strategy were used for reconstruction. Meanwhile, traditional x-ray CT imaging could also be performed in this system. The x-ray attenuation effect has been considered in their imaging model, which is helpful in improving the reconstruction accuracy. Results: First, simulation experiments with cylinder phantoms were carried out to illustrate the validity of the proposed compensated method. The experimental results showed that the location error of the compensated algorithm was smaller than that of the uncompensated method. The permissible region strategy was applied and reduced the reconstruction error to less than 2 mm. The robustness and stability were then evaluated from different view numbers, different regularization parameters, different measurement noise levels, and optical parameters mismatch. The reconstruction results showed that the settings had a small effect on the reconstruction. The nonhomogeneous phantom simulation was also carried out to simulate a more complex experimental situation and evaluated their proposed method. Second, the physical cylinder phantom experiments further showed similar results in their prototype XLCT system. With the discussion of the above experiments, it was shown that the proposed method is feasible to the general case and actual experiments. Conclusions: Utilizing numerical simulation and physical experiments, the authors demonstrated the validity of the new cone beam XLCT method. Furthermore, compared with the previous narrow beam XLCT, the cone beam XLCT could more fully utilize the x-ray dose and the scanning time would be shortened greatly. The study of both simulation experiments and physical phantom experiments indicated that the proposed method was feasible to the general case and actual experiments.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2018

Effects of Electric and Magnetic Fields on the Spin Current in Organic Spintronic Devices

Organic semiconductors are suitable for spin transport because of the extremely long spin-diffusion length, which stems from the weak spin-orbit coupling. In this article, the drift-diffusion transport model to evaluate the spin current in a ferromagnetic/organic semiconductor structure is studied. Effects of the spin-dependent interfacial conductance, temperature and the polarization of the FM bulk on the spin current are discussed in the existence of the electric and magnetic fields. It is obtained that the electric and magnetic fields increase the spin current significantly.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2025

GenAI4UQ: A software for forward and inverse uncertainty quantification using conditional generative AI

We introduce GenAI4UQ, a software package for forward and inverse uncertainty quantification in model calibration, parameter estimation, and ensemble forecasting. GenAI4UQ leverages a generative AI-based conditional modeling framework to address limitations of traditional inverse modeling techniques, such as Markov Chain Monte Carlo (MCMC) methods. By replacing computationally intensive iterative processes with a direct, learned mapping, GenAI4UQ enables efficient calibration of input parameters and generation of predictions directly from observations. The software supports rapid ensemble forecasting with robust uncertainty quantification while maintaining computational and storage efficiency. Built-in auto-tuning of hyperparameters simplifies model training, ensuring accessibility for users with varying expertise. Its versatile conditional generative framework is applicable across diverse scientific domains. While GenAI4UQ offers significant advantages in flexibility and efficiency, users should interpret its uncertainty estimates with caution in data-sparse scenarios, as the model may overestimate uncertainty—an effect common to all surrogate-based approaches including MCMC with surrogate models. Despite this, GenAI4UQ transforms inverse modeling by providing a fast, reliable, and user-friendly solution. It empowers researchers and practitioners to quickly estimate parameter distributions and generate model predictions for new observations, facilitating efficient decision-making and advancing the state of uncertainty quantification in computational modeling.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

A finite difference informed random walker (FDiRW) solver for strongly inhomogeneous diffusion problems

In nature, many complex multi-physics coupling problems exhibit strong diffusivity inhomogeneity. For instance, in the context of radionuclide absorption by porous wasteform materials within a flowing waste stream, the difference of species’ diffusivity in solid and liquid phases spans by 3~8 orders of magnitude. To solve the diffusion equations with strongly inhomogeneous diffusivity, traditional discretization-based methods, such as the Finite Difference Method (FDM), require infinitesimally small time steps (<10 -10 ) as high spatial resolutions are employed in most microstructure evolution processes, leading to prohibitively high computational costs. Here, this work developed an integrated numerical approach (FDiRW: Finite Difference informed Random Walk) to tackle this challenge. The idea is that utilizing the Random Walk concept, the fast diffusion is modeled as a superposition of point source’s solution for a concentration distribution while FDM is used to obtain the point source’s solution at each node. A mesh-coarsening algorithm is developed to generate an exclusive coarse mesh for FDiRW approach to maximize its efficiency. The effectiveness of the coarse mesh-based FDiRW approach is validated by benchmarking Finite Difference solutions. Numerical results demonstrated that FDiRW achieves a remarkable 1000x computational efficiency improvement over FDM while preserving desired accuracy for a medium-sized model of 192 × 192 × 192 grids. Finally, as models scale up, a floating-point operations (PLOPs) analysis of the FDiRW algorithm reveals that its computational complexity grows quadratically in terms of the number of nodes employed in computation.

36 MATERIALS SCIENCE↗