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DOE OSTI2020

Wildfire‐Smoke Aerosols Lead to Increased Light Use Efficiency Among Agricultural and Restored Wetland Land Uses in California's Central Valley

Abstract There are few observational studies measuring the ecosystem‐scale productivity effects of changes in incident diffuse photosynthetically active radiation (PAR diffuse ), especially related to wildfire smoke. Climate change‐induced increases to the duration and intensity of fire conditions have made smoke a common occurrence across western North America, with largely unquantified ecosystem feedbacks. Under equivalent amounts of radiation, increased atmospheric particulate matter could lead to a boost in productivity as scattering redistributes photons throughout multilayer canopies. In this work, we leverage a meso‐network of eddy covariance measurement sites across a unique array of managed and restored C 3 and C 4 canopy types to understand how recent wildfire smoke affected ecosystem productivity during the summer of 2018, an especially smoky year in the agriculturally productive Central Valley. We find that diffuse PAR diffuse increased by more than a third compared to the previous growing season, while total PAR was only slightly diminished. These conditions caused nearly a doubling of light use efficiency over the range of diffuse fraction observed, with the highest sensitivity to diffuse fraction exhibited by corn and alfalfa crops. We utilized an empirical model to assess the trade‐off between enhanced diffuse fraction and reduced total PAR. Under mean radiation conditions, daily integrated gross ecosystem productivity increased by 1.2–4.2% compared to the previous growing season. Finally, we explore the potential negative effect of heightened ozone, a copollutant often associated with wildfire. In addition to the effects of wildfire smoke, the results of this natural experiment can help validate future predictions of aerosol‐productivity feedbacks.

Hemes, Kyle S.↗

DOE OSTI2025

The rigorous upscaling of advection-dominated transport in heterogeneous porous media via the Method of Finite Averages

Systems involving advection-dominated transport through heterogeneous porous and fractured media are ubiquitous in subsurface engineering applications. However, upscaling such systems continues to challenge rigorous modeling efforts, particularly when advection is stronger than diffusion at fine spatial scales (i.e., when the Péclet number is greater than one at length scales that characterize a system’s unit-cells, representative elementary volumes, or averaging regions). Here, in this work, we propose and validate a strategy for extending the Method of Finite Averages (MoFA), a rigorous upscaling methodology for heterogeneous porous media, to upscale transport systems experiencing stronger advection than diffusion at fine scales (i.e., fine-scale Péclet numbers greater than one). We detail the strategy, the physical conditions under which it can be applied while retaining a priori modeling error guarantees, and implement the strategy to obtain a MoFA model for advective-diffusive transport that accommodates advective physics at fine spatial scales. We then perform two numerical experiments considering systems with system-scale Péclet numbers of 300 and 1000 — which correspond to fine-scale Péclet numbers of 30 and 100, respectively — to verify that the error guarantees are met under the strategy. After, we conduct a numerical study to demonstrate the strategy’s advantages over the original MoFA methodology. The results suggest that rigorously-upscaled transport models for heterogeneous porous media experiencing advective physics at finer spatial scales can be derived through MoFA and resolved orders of magnitude faster than their pore-scale counterparts. The results also suggest that the presented strategy is limited to modeling shallow concentration gradients when there are large differences between the time scales related to advection and a system’s temporally-varying boundary conditions. This limitation hinders the strategy’s practicality in modeling more advective systems, and as such, opportunity exists for developing additional strategies that accommodate rapidly-varying boundary conditions — and consequentially, steeper concentration gradients — while modeling advective systems with MoFA.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Temperature effect on phase state and reactivity controls atmospheric multiphase chemistry and transport of PAHs

Polycyclic aromatic hydrocarbons like benzo(a)pyrene (BaP) in atmospheric particulate matter pose a threat to human health because of their high carcinogenicity. In the atmosphere, BaP is mainly degraded through a multiphase reaction with ozone, but the fate and atmospheric transport of BaP are poorly characterized. Earlier modeling studies used reaction rate coefficients determined in laboratory experiments at room temperature, which may overestimate/underestimate degradation rates when applied under atmospheric conditions. Moreover, the effects of diffusion on the particle bulk are not well constrained, leading to large discrepancies between model results and observations. We show how regional and global distributions and transport of BaP can be explained by a new kinetic scheme that provides a realistic description of the temperature and humidity dependence of phase state, diffusivity, and reactivity of BaP-containing particles. Low temperature and humidity can substantially increase the lifetime of BaP and enhance its atmospheric dispersion through both the planetary boundary layer and the free troposphere. The new scheme greatly improves the performance of multiscale models, leading to better agreement with observed BaP concentrations in both source regions and remote regions (Arctic), which cannot be achieved by less-elaborate degradation schemes (deviations by multiple orders of magnitude). Our results highlight the importance of considering temperature and humidity effects on both the phase state of aerosol particles and the chemical reactivity of particulate air pollutants.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Mass Transport in Membrane Systems: Flow Regime Identification by Fourier Analysis

The numerical calculation of local mass distributions in membrane systems by computational fluid dynamics (CFD) offers indispensable benefits. However, the concept to calculate such distributions in response to separate variations of operation conditions (OCs) makes it difficult to address overall, flow-physics-related questions, which require the consideration of the collective interaction of OCs. It is shown that such understanding-related relationships can be obtained by the analytical solution of the advection–diffusion equation considered. A Fourier series model (FSM) is presented, which provides exact solutions of an advection–diffusion equation for a wide range of OCs. On this basis, a new zeroth-order model is developed, which is very simple and as accurate as the complete FSM for all conditions of practical relevance. Advection-dominated blocked and diffusion-dominated unblocked flow regimes are identified (depending on a Péclet number which compares the flow geometry with a length scale imposed by the flow), which implies relevant requirements for the use of lab results for pilot- and full-scale applications. Analyses reveal the equivalence of variations of OCs, which offers a variety of options to accomplish desired flow regime changes.

Heinz, Stefan (ORCID:0000000248712416)↗

DOE OSTI2020

The influence of boundary and edge-plasma modeling in computations of axisymmetric vertical displacement

A number of previously published studies apply extended-MHD computations to model macroscopic dynamics of tokamak vertical displacement events (VDEs). The characteristic plasma-wall contact and resistive-wall diffusion imply sensitivity to boundary conditions in a general sense, but which conditions have significant influence depends on how the plasma is modeled. This work examines these dependencies by comparing results of axisymmetric extended-MHD computations with different sets of boundary conditions, plasma thermal-conduction models, and wall resistivity values. The geometry and plasma parameters of the computations represent a modest-sized tokamak. The forced-displacement scenario and computational setup are similar to those used in previous 3D computations. The results show that for a given wall resistivity, the VDE time-scale is most sensitive to variations in the boundary and thermal-conduction parameters that affect electron thermal transport. The electrical conductivity depends on electron temperature, and the dependence on thermal transport stems from its influence on the electrical circuit that includes the open-field halo current. Lastly, conditions that lead to hotter, broader halo regions slow the evolution. Significant sensitivity to the boundary condition on plasma flow-velocity exists when electron thermal conduction is restricted and electron energy loss is convective, which is expected for conditions at the entrance of the magnetic presheath.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Recent Progress on Numerical Modeling for Microgravity Electric Field Flames: Preprint

This paper presents the recent progress on the NASA Physical Science Informatics (PSI) project PeleLM CFD of Ion Driven Winds from Diffusion Flames in simulating the E-FIELD Flames microgravity results. The focus of this project is to comprehensively simulate the behavior of a small diffusion flame under the influence of an externally applied electric field in zero-gravity. To date, the capability of accurately simulating electric field flames has eluded researchers because the system exhibits dramatic ranges of coupled temporal and spatial scales. Moreover, in earth gravity the hot combustion products are subject to buoyancy effects that are difficult to isolate from those generated by the electric field. This work is an implementation in an existing powerful simulation framework (PeleLM) for this problem using PeleLMeX in order to validate the model and investigate the complex coupled system. The current effort includes establishing the domain of a diffusion coflow burner, examining the boundary conditions, flame geometry and ignition with gravitational forces and also with an electric field applied. A detailed model is used that includes the chemistry of charged ions and chemiluminescent flame intermediates to capture any feedback between ion-driven convection and combustion behavior, and to allow quantitative comparisons with experimental measurements.

coflow flames↗

DOE OSTI2026

Interpretable Deep Learning for Advancing Field-Enhanced Catalysis

This DOE Early Career project developed a physics-informed, interpretable AI-and-modeling framework to understand and exploit electric-field effects in heterogeneous catalysis, with ammonia cracking and synthesis as a representative pathway. The team built and validated methods to map local electric fields on metal surfaces and nanoparticles, showing that low-coordination features (tips/edges/corners) can concentrate fields by several-fold relative to flat facets. Using DFT-generated datasets, the project created physics-guided machine learning models that rapidly predict local electric fields and field-dependent adsorption energetics with near-DFT accuracy while reducing computational cost by orders of magnitude. These predictions were integrated with microkinetic modeling to quantify how field-dipole interactions reshape reaction energetics and mechanisms, enabling large increases in predicted catalytic rates and substantial reductions in operating temperature under favorable field conditions. To accelerate discovery of earth-abundant catalysts, the project combined interpretable ML screening (with electronic-structure descriptors identified as key drivers) with a generative inverse-design workflow based on diffusion models and physics constraints. The resulting closed-loop approach, linking simulation, mechanistic modeling, and AI, provides reusable tools and datasets for designing catalysts and operating conditions in field-enhanced catalysis, with broad relevance to electrostatic catalysis, plasma catalysis, electrocatalysis, and other energy-related chemical transformations.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2017

Multiscale models and stochastic simulation methods for computing rare but key binding events in cell biology

The main difficulty in simulating diffusion processes at a molecular level in cell microdomains is due to the multiple scales involving nano- to micrometers. Few to many particles have to be simulated and simultaneously tracked while there are exploring a large portion of the space for binding small targets, such as buffers or active sites. Bridging the small and large spatial scales is achieved by rare events representing Brownian particles finding small targets and characterized by long-time distribution. These rare events are the bottleneck of numerical simulations. A naive stochastic simulation requires running many Brownian particles together, which is computationally greedy and inefficient. Solving the associated partial differential equations is also difficult due to the time dependent boundary conditions, narrow passages and mixed boundary conditions at small windows. We present here two reduced modeling approaches for a fast computation of diffusing fluxes in microdomains. The first approach is based on a Markov mass-action law equations coupled to a Markov chain. The second is a Gillespie's method based on the narrow escape theory for coarse-graining the geometry of the domain into Poissonian rates. The main application concerns diffusion in cellular biology, where we compute as an example the distribution of arrival times of calcium ions to small hidden targets to trigger vesicular release.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2019

Simulation of Spent Nuclear Fuel loading into a Final Waste Repository

Previous work towards studying repository loading have used: - spent nuclear fuel (SNF) with an average burnup composition; - a lumped capacitance thermal model for calculating temperature in a Cyclus repository model. The goal of this work is to improve on the repository models and use U.S. historical SNF inventory data in simulations to more accurately study the loading of a waste repository. These goals will be achieved by: - using UNF-ST-and-DARDS Unified Database (UDB) that has historic assembly-specific data (e.g, isotopic composition, heat) in Cyclus simulations; - implementing a more accurate thermal model within a Cyclus repository model. Objectives: - Create a Cyclus spent fuel conditioning model that packages spent fuel bundles into packages which have user-defined properties. - Create a Cyclus medium-fidelity repository model that gives accurate time and spatial dependent temperature values and loads the repository based on a user-selected loading strategy. Cyclus is an agent-based extensible framework for modeling flow of material through user-defined nuclear fuel cycles. In Cyclus, each facility in the fuel cycle is modeled individually and the facilities interact with one another as independent agents. The spent fuel conditioning model accepts spent fuel bundles and puts them into a cylindrical waste package. In the spent fuel conditioning model, the user can define variables: For each layer, radius, thermal conductivity, thermal diffusivity; For each package, Number of spent fuel bundles, Radius and height. The waste repository model accepts waste packages and emplaces them into available positions within the waste repository based on a thermal criteria. The thermal criteria is a temperature limit at the interface between the waste package surface and the host geology, that is set based on the repository's host geology. In the waste repository model, the user can define the variables: Capacity, Distance between waste packages, Distance between drifts, Repository host geology, Loading Strategy. After the addition of new waste packages at each time step, the waste repository model recalculates the temperature at each location in the repository. If the addition of this new package causes its temperature to exceed the thermal limit, it will be placed back into the buffer. A thermal model that relies on a transient 'outside' model and quasi-steady-state 'inside' model is used to accurately determine the temperature in the repository. The 'outside' model assumes a homogenous medium with the Engineered Barrier System (EBS) replaced by the geologic medium. Temperature solutions for the central waste package, adjacent point and line sources are superimposed to calculate the temperature at specific points in the repository. The central drift consists of one finite line source which represents the central waste package. The central drift also consists of point sources that represent neighboring waste packages in the central drift. The neighboring drifts are represented by infinite line sources. The 'inside' model is considered to be at a quasi-steady-state condition because EBS has a relatively low thermal mass compared to the infinite geologic medium. The steady state calculation is performed at each time step with the heat source and interface temperature as boundary conditions. Future Work: Run Cyclus simulations with U.S. historical SNF inventory data, the spent fuel conditioning and repository models to study how waste package acceptance strategies impact repository loading.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS1999

FDNS CFD Code Benchmark for RBCC Ejector Mode Operation

Computational Fluid Dynamics (CFD) analysis results are compared with benchmark quality test data from the Propulsion Engineering Research Center's (PERC) Rocket Based Combined Cycle (RBCC) experiments to verify fluid dynamic code and application procedures. RBCC engine flowpath development will rely on CFD applications to capture the multi-dimensional fluid dynamic interactions and to quantify their effect on the RBCC system performance. Therefore, the accuracy of these CFD codes must be determined through detailed comparisons with test data. The PERC experiments build upon the well-known 1968 rocket-ejector experiments of Odegaard and Stroup by employing advanced optical and laser based diagnostics to evaluate mixing and secondary combustion. The Finite Difference Navier Stokes (FDNS) code was used to model the fluid dynamics of the PERC RBCC ejector mode configuration. Analyses were performed for both Diffusion and Afterburning (DAB) and Simultaneous Mixing and Combustion (SMC) test conditions. Results from both the 2D and the 3D models are presented.

Holt, James B.↗

DOE OSTI2015

Kinetics study of the evolution of oxygen-related defects in mono-crystalline silicon subjected to electron-irradiation and thermal treatment

The diffusion and dissociation mechanisms governing the evolution of oxygen and vacancy-oxygen defects in Czochralski-grown Si samples have been studied. The samples were irradiated at (i) room temperature or (ii) elevated temperature (350 °C) by MeV electrons and then isothermally annealed at 8 different temperatures in the range of 300 °C to 500 °C. The evolution of the concentrations of oxygen complexes (O{sub n}, n ≤ 3) and mono-vacancy-oxygen defects (VO{sub n}, n ≤ 4) have been followed by infrared absorption measurements of local vibrational modes originating from the individual defects. The experimental kinetics data have been compared with simulation results based on the theory for diffusion limited reactions, assuming a model where sequential build-up of the VO{sub n} defects is a key ingredient. A close quantitative agreement is obtained for both sets of samples despite quite different initial conditions prior to the annealing, which adds evidence to the validity of the model. Values for the diffusivity and dissociation rates of VO{sub n} (n ≤ 4) and O{sub n} (n ≤ 3) have been deduced and in general, the mobility and stability of VO{sub n} decrease and increase with n, respectively. For all the defects, partial dissociation appears as a prevailing process during diffusion, while full dissociation of VO{sub n} is limited by an energy barrier identical to that of interstitial oxygen (O{sub i}) diffusion (∼2.55 eV). The oxygen dimer and trimer are fast diffusers but slower than substitutional oxygen, i.e., VO; VO is found to be the most mobile species, whilst O{sub i} is the slowest one with a difference in diffusivity of up to 7 orders of magnitude in the studied temperature range.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

ASCEND: Asymptotically compatible strong form foundations for nonlocal discretization

Nonlocal models naturally handle a range of physics of interest to SNL, but discretization of their underlying integral operators poses mathematical challenges to realize the accuracy and robustness commonplace in discretization of local counterparts. This project focuses on the concept of asymptotic compatibility, namely preservation of the limit of the discrete nonlocal model to a corresponding well-understood local solution. We address challenges that have traditionally troubled nonlocal mechanics models primarily related to consistency guarantees and boundary conditions. For simple problems such as diffusion and linear elasticity we have developed complete error analysis theory providing consistency guarantees. We then take these foundational tools to develop new state-of-the-art capabilities for: lithiation-induced failure in batteries, ductile failure of problems driven by contact, blast-on-structure induced failure, brittle/ductile failure of thin structures. We also summarize ongoing efforts using these frameworks in data-driven modeling contexts. This report provides a high-level summary of all publications which followed from these efforts.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Numerical Study of PAHs and Soot Emissions from Gasoline–Methanol, Gasoline–Ethanol, and Gasoline– n -Butanol Blend Surrogates

Soot formation is an intricate phenomenon, and soot propensity of a fuel is interwoven with the fuel composition, physical and chemical properties, and combustion environment. Here, the present study examines the hypothesis that in addition to the chemical composition of the fuel, the sooting nature of the fuel is closely coupled with its chemical property known as octane sensitivity (S). With this motivation, the present study numerically investigates the effects of gasoline surrogate composition and its property, octane sensitivity (S), on polycyclic aromatic hydrocarbons (PAHs) and soot emissions. Four-component toluene primary reference fuel (TPRF)–alcohol blends, comprising iso-octane, n-heptane, toluene, and one of the three different alcohols- methanol, ethanol, and n-butanol, are used as gasoline surrogates. A total of 320 TPRF–alcohol mixtures, with S in the range of 1–10, are examined under laminar counterflow diffusion flame conditions. A detailed chemical mechanism coupled with a comprehensive soot model, which includes reactions for soot inception, surface growth, PAH condensation, and oxidation, is adopted. The analysis indicates that the toluene content in the fuel mixture has a prominent effect, while the alcohol content and octane sensitivity of the fuel have a weak correlation with the PAHs and soot. Thus, it is not clear if any of these three variables, namely, toluene content in the fuel, alcohol content in the fuel, and S, are individually sufficient to characterize the PAHs and soot across various blends. For this reason, a new variable (X CHO ) based on the elemental composition of the fuel mixture is identified and it is shown that X CHO along with S of the fuel characterize soot emissions satisfactorily. Further, a reaction path analysis indicates that the efficacy of alcohols in reducing soot emissions follows the order: methanol > ethanol > n-butanol.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Structural constraint integration in a generative model for the discovery of quantum materials

Billions of organic molecules have been computationally generated, yet functional inorganic materials remain scarce due to limited data and structural complexity. Here, in this work, we introduce Structural Constraint Integration in a GENerative model (SCIGEN), a framework that enforces geometric constraints, such as honeycomb and kagome lattices, within diffusion-based generative models to discover stable quantum materials candidates. SCIGEN enables conditional sampling from the original distribution, preserving output validity while guiding structural motifs. This approach generates ten million inorganic compounds with Archimedean and Lieb lattices, over 10% of which pass multistage stability screening. High-throughput density functional theory calculations on 26,000 candidates shows over 95% convergence and 53% structural stability. A graph neural network classifier detects magnetic ordering in 41% of relaxed structures. Furthermore, we synthesize and characterize two predicted materials, TiPd 0.22 Bi 0.88 and Ti 0.5 Pd 1.5 Sb, which display paramagnetic and diamagnetic behaviour, respectively. Our results indicate that SCIGEN provides a scalable path for generating quantum materials guided by lattice geometry.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Decomposition of methane diluted with inert gas in an RF discharge cell

Decomposition of methane using non-thermal plasmas is an attractive route for producing hydrogen-rich gases and valuable carbon nanomaterials. Understanding how plasma discharge modes influence methane decomposition in optimizing plasma-assisted chemical conversion remains unexplored. This study explores the coupling between the discharge structure and product selectivity in RF capacitively coupled discharges operating in methane/inert gas mixtures in the pressure range of 2–3 torr. Under our experimental conditions the discharge exhibits mode transitions from uniform to striated in Ar and Kr and from diffuse to contracted in Ar and Kr with <5% CH 4 . The discharges in He and Ne remained uniform under our operating conditions, and their mixtures with CH 4 remained diffuse. A 0-d model for Ar/CH 4 discharge established a threshold for contraction while also asserting the importance of Ar$^{*}_{\textrm{m}}$ in the dissociation and ionization processes. The highest degree of methane decomposition, >99.7% with the main products of acetylene and graphitized solid carbon was achieved in the contracted discharge mode for both Kr or Ar with ⩽5% CH 4 . We demonstrate that contraction can play a crucial role in the effective decomposition of methane with value-added products and that both the electronic and thermal properties of plasma gas are responsible for this effect.

RF plasma↗

NASA NTRSDate not supplied

Characterization of Dendritic Spatially Extended 3D Patterns in Directional Solidification: Microgravity Experiments in DECLIC-DSI onboard ISS and 3D Phase-field Simulations

To clarify and characterize the fundamental physical mechanisms active in the dynamical formation of three-dimensional (3D) arrays of dendrites under diffusive growth conditions, in situ monitoring of series of experiments on transparent model alloy succinonitrile – 0.46 wt% camphor was carried out under low gravity in the DECLIC Directional Solidification Insert onboard the International Space Station. These experiments offer the very unique opportunity to observe in situ and characterize the dynamics of the microstructure formation and evolution in extended 3D patterns under microgravity environment. The analyses of the dendritic patterns for a broad range of growth velocities displaying different levels of sidebranching will be presented. Especially, the time evolution of primary spacing, in case of solidifications at constant pulling rate as well as for experiments with pulling rate jump, will be compared to 3D phase-field simulations, and the results will be discussed in terms of stable spacing range.

Kaihua Ji↗

NASA NTRSDate not supplied

Characterization of Dendritic Spatially Extended 3D Patterns in Directional Solidification: Microgravity Experiments in DECLIC-DSI Onboard ISS and 3D Phase-field Simulations

Kaihua Ji↗

DOE OSTI2017

Diffusive confinement of free radical intermediates in the OH radical oxidation of semisolid aerosols

Multiphase chemical reactions (gas + solid/liquid) involve a complex interplay between bulk and interface chemistry, diffusion, evaporation, and condensation. Reactions of atmospheric aerosols are an important example of this type of chemistry: the rich array of particle phase states and multiphase transformation pathways produce diverse but poorly understood interactions between chemistry and transport. Their chemistry is of intrinsic interest because of their role in controlling climate. Their characteristics also make them useful models for the study of principles of reactivity of condensed materials under confined conditions. Previously, we have reported a computational study of the oxidation chemistry of a liquid aliphatic aerosol. In this study, we extend the calculations to investigate nearly the same reactions at a semisolid gas-aerosol interface. A reaction-diffusion model for heterogeneous oxidation of triacontane by hydroxyl radicals (OH) is described, and its predictions are compared to measurements of aerosol size and composition, which evolve continuously during oxidation. Our results are also explicitly compared to those obtained for the corresponding liquid system, squalane, to pinpoint salient elements controlling reactivity. The diffusive confinement of the free radical intermediates at the interface results in enhanced importance of a few specific chemical processes such as the involvement of aldehydes in fragmentation and evaporation, and a significant role of radical-radical reactions in product formation. The simulations show that under typical laboratory conditions semisolid aerosols have highly oxidized nanometer-scale interfaces that encapsulate an unreacted core and may confer distinct optical properties and enhanced hygroscopicity. This highly oxidized layer dynamically evolves with reaction, which we propose to result in plasticization. The validated model is used to predict chemistry under atmospheric conditions, where the OH radical concentration is much lower. The oxidation reactions are more strongly influenced by diffusion in the particle, resulting in a more liquid-like character.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗