Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Conditional diffusion models”

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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Analytical-based simulation approach for an anion exchange membrane fuel cell

An analytical and empirical-based 1-D, non-isothermal, steady-state model for anion exchange membrane fuel cell capable of capturing two-phase phenomena is presented in this study. Coupled multi-physics including mass and charge transport, electrochemical reactions, heat transfer, and two-phase water transport are considered in the model and the simulated results are compared to experimental data. To better represent actual material properties and localized conditions, the model applies multilayer discretization in the gas diffusion electrode to enhance prediction accuracy. The model successfully predicts the baseline performance at 70 °C, 131 kPa abs., 92% RH with pure H 2 /O 2 gas as well as the limiting current at 10% H 2 . The robust simulation approach allows for simplistic and accurate estimation of cell performance without the complications of applying two-phase parameters and expensive computational need for numerical models. In addition, the results from the sensitivity studies of material properties and operating conditions provide valuable insights on water management strategies and optimal component design for advancing anion exchange membrane fuel cell technology.

1-D model↗
DOE OSTI2025

Field-level reconstruction from foreground-contaminated 21-cm maps

Current and upcoming 21-cm experiments will soon be able to map 21-cm spatial fluctuations in three dimensions for a wide range of redshifts. However, bright foreground contamination and the nature of radio interferometry create significant challenges, making it difficult to access rich cosmological information from the Fourier modes that lie within the “foreground wedge”. Here, in this work, we introduce two approaches aiming to reconstruct the full 21-cm density field, including the missing modes in the wedge: (a) a field-level inference under an effective field theory (EFT) framework; (b) a diffusion-based deep generative model trained on simulations. Under the EFT framework, we implement a fully differentiable forward model that maps the initial conditions of matter fluctuations to the observed, foreground-filtered 21-cm maps. This enables a gradient-based sampler to simultaneously sample the initial conditions and bias parameters, allowing a physically motivated mode reconstruction. Alternatively, we apply a variational diffusion model to perform 21-cm density reconstruction at the map level. Our model is trained on semi-numerical simulations over a wide range of astrophysical parameters. Our results from both approaches should provide improved cosmological constraints from the field level and also enable cross-correlation between experiments that have little or no overlapping modes.

cosmological perturbation theory↗
DOE OSTI2022

Defining the scope for altering rice leaf anatomy to improve photosynthesis: a modelling approach

Summary Leaf structure plays an important role in photosynthesis. However, the causal relationship and the quantitative importance of any single structural parameter to the overall photosynthetic performance of a leaf remains open to debate. In this paper, we report on a mechanistic model, eLeaf, which successfully captures rice leaf photosynthetic performance under varying environmental conditions of light and CO 2 . We developed a 3D reaction‐diffusion model for leaf photosynthesis parameterised using a range of imaging data and biochemical measurements from plants grown under ambient and elevated CO 2 and then interrogated the model to quantify the importance of these elements. The model successfully captured leaf‐level photosynthetic performance in rice. Photosynthetic metabolism underpinned the majority of the increased carbon assimilation rate observed under elevated CO 2 levels, with a range of structural elements making positive and negative contributions. Mesophyll porosity could be varied without any major outcome on photosynthetic performance, providing a theoretical underpinning for experimental data. eLeaf allows quantitative analysis of the influence of morphological and biochemical properties on leaf photosynthesis. The analysis highlights a degree of leaf structural plasticity with respect to photosynthesis of significance in the context of attempts to improve crop photosynthesis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Phase field simulation of anode microstructure evolution of solid oxide fuel cell through Ni(OH) 2 diffusion

Microstructure evolution in a solid oxide fuel cell anode is strongly affected by operating condition. The detailed mesoscale evolution mechanism under operating condition is still under debate. Here we develop a phase-field model to simulate microstructure evolution through formation and diffusion of gaseous Ni(OH)2. We studied the coarsening kinetics and redistribution of Ni under different steam distributions and compare it to that under pure hydrogen condition. Overall, the results suggest that although the presence of a steady gradient of steam leads to redistribution of Ni, Ni(OH) 2 formation and diffusion do not significantly change the Ni coarsening rate under strictly humid conditions, contrary to commonly reported hypotheses. It is concluded that competing mechanisms other than Ni(OH) 2 diffusion must be responsible for the experimentally observed Ni redistribution and enhanced coarsening under humid conditions.

25 ENERGY STORAGE↗
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 OSTI2019

Atomistic modeling of out-of-pile xenon diffusion by vacancy clusters in UO 2

We report that diffusion of Xe atoms in UO 2 fuel is important for nuclear fuel performance, and is enabled by interaction with U and O vacancies. Previous work using atomistic calculations based on density functional theory (DFT) and empirical potentials (EP) focused on the role of small vacancy clusters (Xe U2Oy , y = 0, 1, 2) for Xe transport, but the model predictions failed to reproduce the experimental observations by consistently underestimating Xe diffusivity. In this work, where we focused on out-of-pile conditions (i.e. in the absence of irradiation), we have explored two of the uncertainties associated with the model: the DFT methodology and the types of clusters considered. Additionally, we found that using the energy barriers obtained with GGA + U DFT allows to reconcile simulation results and experimental observations in the intrinsic regime (i.e. out-of-pile conditions). The Xe UO cluster is the preferred configuration at high temperature, while the mobile Xe U2O cluster takes over below 1720 K. The latter cluster is also the main contributor to Xe diffusion and good agreement is obtained with current models empirically fitted to experiments for diffusion at high temperature. A simple expression that captures most of Xe diffusivity is proposed, relying on Xe UO and Xe U2O clusters only. We also determined the out-of-pile concentration and diffusivity of extended clusters Xe U z O y , 3 ≤ x ≤ 9, and determined that these do not contribute significantly to the overall diffusivity under intrinsic conditions. However, we speculate that the Xe U 4 O 3 and Xe U 8 O 9 clusters, which have relatively low migration barrier, may play a role under irradiation conditions, because the radiation-induced enhanced vacancy concentration would rapidly increase the fraction of large Xe-vacancy clusters.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2014

Atomistic modeling of intrinsic and radiation-enhanced fission gas (Xe) diffusion in UO2 +/- x: Implications for nuclear fuel performance modeling

Based on density functional theory (DFT) and empirical potential calculations, the diffusivity of fission gas atoms (Xe) in UO2 nuclear fuel has been calculated for a range of non-stoichiometry (i.e. UO2x), under both out-of-pile (no irradiation) and in-pile (irradiation) conditions. This was achieved by first deriving expressions for the activation energy that account for the type of trap site that the fission gas atoms occupy, which includes the corresponding type of mobile cluster, the charge state of these defects and the chemistry acting as boundary condition. In the next step DFT calculations were used to estimate migration barriers and internal energy contributions to the thermodynamic properties and calculations based on empirical potentials were used to estimate defect formation and migration entropies (i.e. pre-exponentials). The diffusivities calculated for out-of-pile conditions as function of the UO2x nonstoichiometrywere used to validate the accuracy of the diffusion models and the DFT calculations against available experimental data. The Xe diffusivity is predicted to depend strongly on the UO2x non-stoichiometry due to a combination of changes in the preferred Xe trap site and in the concentration of uranium vacancies enabling Xe diffusion, which is consistent with experiments. After establishing the validity of the modeling approach, it was used for studying Xe diffusion under in-pile conditions, for which experimental data is very scarce. The radiation-enhanced Xe diffusivity is compared to existing empirical models. Finally, the predicted fission gas diffusion rates were implemented in the BISON fuel performance code and fission gas release from a Risø fuel rod irradiation experiment was simulated. 2014 Elsevier B.V. All rights

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

Conditional deep generative models for simultaneous simulation and reconstruction of entire events

We extend the particle-flow neural assisted simulations (arnassus) framework of fast simulation and reconstruction to entire collider events. In particular, we use two generative artificial intelligence tools, continuous normalizing flows and diffusion models, to create a set of reconstructed particle-flow objects conditioned on truth-level particles from CMS Open Simulations. While previous work focused on jets, our updated methods now can accommodate all particle-flow objects in an event along with particle-level attributes like particle type and production vertex coordinates. This approach is fully automated, entirely written in Python, and GPU-compatible. Using a variety of physics processes at the LHC, we show that the extended arnassus is able to generalize beyond the training dataset and outperforms the standard, public tool elphes.

Dreyer, Etienne [Weizmann Institute of Science, Re↗
DOE OSTI2019

Hybrid model with dynamical sources for heavy-ion collisions at BES energies

We develop a (3+1)-dimensional hybrid evolution model for heavy-ion collisions with dynamical sources for the energy-momentum tensor and baryon current. During an initial pre-equilibrium stage based on UrQMD, the four-momenta and baryon numbers carried by secondary particles created within UrQMD are fed continuously, after a short thermalization time, into a (3+1)-dimensional viscous hydrodynamic evolution module including baryon transport. The sensitivity of the initial conditions to model parameters and the effect of baryon diffusion on the hydrodynamic evolution are studied.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2014

Magnonic band gaps in two-dimension magnonic crystals with diffuse interfaces

In this paper, the plane wave method is extended to include the diffuse interface in the calculation of the dispersion of spin waves in two-dimension magnonic crystals. The diffuse interfaces with linear and sinusoidal profiles of variation in the spontaneous magnetization and exchange constant are considered and the effects of the thicknesses and profiles of diffuse interfaces on the magnonic band gaps are investigated. The results show that the thicknesses and profiles of diffuse interfaces are clearly seen to play a significant role in determining the size and position of the magnonic band gaps in the both square and triangular lattices in the exchange interaction regime. The smooth (linear or sinusoidal) interface does not lead to disappearance of the band gaps, instead it may lead to larger band gaps than those in the model with sharp (infinitely thin) diffuse interface under certain conditions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

Diffusion-induced periodic transition between oscillatory modes in amplitude-modulated patterns

We study amplitude-modulated waves, e.g., wave packets in one dimension, overtarget spirals and superspirals in two dimensions, under mixed-mode oscillatory conditions in a three-variable reaction-diffusion model. New transition zones, not seen in the homogeneous system, are found, in which periodic transitions occur between local 1{sup N−1} and 1{sup N} oscillations. Amplitude-modulated complex patterns result from periodic transition between (N − 1)-armed and N-armed waves. Spatial recurrence rates provide a useful guide to the stability of these modulated patterns.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Flame acceleration and transition to detonation in a pre-/main-chamber combustion system

Numerical simulations are performed to study the mechanism of deflagration to detonation transition (DDT) in a pre-/main-chamber combustion system with a stoichiometric ethylene–oxygen mixture. A Godunov algorithm, fifth-order in space, and third-order in time, is used to solve the fully compressible Navier–Stokes equations on a dynamically adapting mesh. A single-step, calibrated chemical diffusive model described by Arrhenius kinetics is used for energy release and conservation between the fuel and the product. The two-dimensional simulation shows that a laminar flame grows in the pre-chamber and then develops into a jet flame as it passes through the orifice. A strong shock forms immediately ahead of the flame, reflecting off the walls and interacting with the flame front. The shock–flame interactions are crucial for the development of flame instabilities, which trigger the subsequent flame development. The DDT arises due to a shock-focusing mechanism, where multiple shocks collide at the flame front. A chemical explosive mode analysis (CEMA) criterion is developed to study the DDT ignition mode. Preliminary one-dimensional computations for a laminar propagating flame, a fast flame deflagration, and a Chapman–Jouguet detonation are conducted to demonstrate the validity of CEMA on the chemical-diffusive model, as well as to determine the proper conditioning value for CEMA diagnostic. The two-dimensional analysis with CEMA indicates that the DDT initiated by the shock-focusing mechanism can form a strong thermal expansion region at the flame front that features large positive eigenvalues for the chemical explosive mode and dominance of the local autoignition mode. Thus, the CEMA criterion proposed in this study provides a robust diagnostic for identifying autoignition-supported DDT, of which the emergence of excessive local autoignition mode is found to be a precursor. The effect of grid size, initial temperature, and orifice size are then evaluated, and results show that although the close-chamber DDT is highly stochastic, the detonation initiation mechanism remains robust.

42 ENGINEERING↗
DOE OSTI2022

Catalytic resonance of ammonia synthesis by simulated dynamic ruthenium crystal strain

Ammonia affords dense storage for renewable energy as a fungible liquid fuel, provided it can be efficiently synthesized from hydrogen and nitrogen. In this work, the catalysis of ammonia synthesis was computationally explored beyond the Sabatier limit by dynamically straining a ruthenium crystal (±4%) at the resonant frequencies (10 2 to 10 5+ Hz) of N 2 surface dissociation and hydrogenation. Density functional theory calculations at different strain conditions indicated that the energies of NH x surface intermediates and transition states scale linearly, allowing the description of ammonia synthesis at a continuum of strain conditions. A microkinetic model including multiple sites and surface diffusion between step and Ru(0001) terrace sites of varying ratios for nanoparticles of differing size revealed that dynamic strain yields catalytic ammonia synthesis conversion and turnover frequency comparable to industrial reactors (400°C, 200 atm) but at lower temperature (320°C) and an order of magnitude lower pressure (20 atm).

10 SYNTHETIC FUELS↗
DOE OSTI2018

Calculation of the Influence of the Ion Current Density and Temperature on the Accumulation Kinetics of Point Defects under the Irradiation of Si with Light Ions

Numerical calculations of the accumulation kinetics of point defects—vacancies and divacancies—under the irradiation of Si with ions having masses of M{sub 1} ≤ 31 amu and energies of E ≤ 100 keV under various irradiation conditions are performed. The previously proposed diffusion-coagulation model is used without application of the “weak diffusion” approximation, which was performed during its analytical implementation. The main peculiarities of the dependences of the concentrations of vacancies and divacancies on the dose, ion-current density, and temperature under irradiation are analyzed. A physical interpretation of these results is given. The developed computing complex is rather flexible and makes it possible to analyze the influence of model input parameters by means of their variation and include additional processes into consideration if necessary.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Transport and Loss of Ring Current Electrons Inside Geosynchronous Orbit During the 17 March 2013 Storm

Ring current electrons (1–100 keV) have received significant attention in recent decades, but many questions regarding their major transport and loss mechanisms remain open. In this study, we use the four-dimensional Versatile Electron Radiation Belt code to model the enhancement of phase space density that occurred during the 17 March 2013 storm. Our model includes global convection, radial diffusion, and scattering into the Earth's atmosphere driven by whistler-mode hiss and chorus waves. We study the sensitivity of the model to the boundary conditions, global electric field, the electric field associated with subauroral polarization streams, electron loss rates, and radial diffusion coefficients. The results of the code are almost insensitive to the model parameters above 4.5 R E R E , which indicates that the general dynamics of the electrons between 4.5 R E and the geostationary orbit can be explained by global convection. We found that the major discrepancies between the model and data can stem from the inaccurate electric field model and uncertainties in lifetimes. We show that additional mechanisms that are responsible for radial transport are required to explain the dynamics of ≥40-keV electrons, and the inclusion of the radial diffusion rates that are typically assumed in radiation belt studies leads to a better agreement with the data. The overall effect of subauroral polarization streams on the electron phase space density profiles seems to be smaller than the uncertainties in other input parameters. This study is an initial step toward understanding the dynamics of these particles inside the geostationary orbit.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

The accuracy of multi-group models for nonlocal electron transport in magnetized plasmas

In the extreme conditions of inertial confinement fusion experiments, heat flow plays a vital role, but local diffusive models frequently break down and overestimate the heat flow. The situation becomes more complicated again in the significant magnetic fields generated during laser–plasma interactions or in magnetized fusion schemes. Accurate non-local and magnetized heat flow computations can be carried out using Vlasov–Fokker–Planck (VFP) simulations, but these are computationally expensive. There is, therefore, significant interest in using faster multi-group models to accurately calculate the non-local heat flow in magnetized plasmas. We benchmark two such multi-group models for calculating the heat flow, M1 and hybrid-AWBS-BGK, against diffusive models and full VFP simulations, before applying the models to realistic example test cases, both magnetized and unmagnetized. We find that the multi-group models generally perform very well for moderate non-localities up to kλmfp∼0.01, but the computational cost increases dramatically. hybrid-AWBS-BGK performs more effectively than M1 at high non-localities, up to kλmfp∼1, due to its adaptive solver and robust P1 closure, but tends to fail in very strong magnetic fields. Both codes are much faster than VFP simulations but are still slow in steep temperature gradients.

Arran, C. (ORCID:0000000286448118)↗
DOE OSTI2016

Experimental Studies and Model Analysis of Noble Gas Fractionation in Porous Media

Core Ideas Ambient noble gases in porous media fractionate from through‐flow of other gases. CO 2 fluxes and noble‐gas fractionation are measured in simple sandbox experiments. Modeled fractionation provides indirect proxy, e.g., of steady CO 2 leakage fluxes. The noble gases, which are chemically inert under normal terrestrial conditions but vary systematically across a wide range of atomic mass and diffusivity, offer a multicomponent approach to investigating gas dynamics in unsaturated soil horizons, including transfer of gas between saturated zones, unsaturated zones, and the atmosphere. To evaluate the degree to which fractionation of noble gases in the presence of an advective–diffusive flux agrees with existing theory, a simple laboratory sand column experiment was conducted. Pure CO 2 was injected at the base of the column, providing a series of constant CO 2 fluxes through the column. At five fixed sampling depths within the system, samples were collected for CO 2 and noble gas analyses, and ambient pressures were measured. Both the advection–diffusion and dusty gas models were used to simulate the behavior of CO 2 and noble gases under the experimental conditions, and the simulations were compared with the measured depth‐dependent concentration profiles of the gases. Given the relatively high permeability of the sand column (5 × 10 −11 m 2 ), Knudsen diffusion terms were small, and both the dusty gas model and the advection–diffusion model accurately predicted the concentration profiles of the CO 2 and atmospheric noble gases across a range of CO 2 flux from ∼700 to 10,000 g m −2 d −1 . The agreement between predicted and measured gas concentrations demonstrated that, when applied to natural systems, the multi‐component capability provided by the noble gases can be exploited to constrain component and total gas fluxes of non‐conserved (CO 2 ) and conserved (noble gas) species or attributes of the soil column relevant to gas transport, such as porosity, tortuosity, and gas saturation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Quantum Transmission Conditions for Diffusive Transport in Graphene with Steep Potentials

We present a formal derivation of a drift-diffusion model for stationary electron transport in graphene, in presence of sharp potential profiles, such as barriers and steps. Assuming the electric potential to have steep variations within a strip of vanishing width on a macroscopic scale, such strip is viewed as a quantum interface that couples the classical regions at its left and right sides. In the two classical regions, where the potential is assumed to be smooth, electron and hole transport is described in terms of semiclassical kinetic equations. The diffusive limit of the kinetic model is derived by means of a Hilbert expansion and a boundary layer analysis, and consists of drift-diffusion equations in the classical regions, coupled by quantum diffusive transmission conditions through the interface. The boundary layer analysis leads to the discussion of a four-fold Milne (half-space, half-range) transport problem.

77 NANOSCIENCE AND NANOTECHNOLOGY↗