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 1,207 records · Page 67
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Study of Interfacial Interactions Using Thing Film Surface Modification: Radiation and Oxidation Effects in Materials

Interfaces play a key role in dictating the long-term stability of materials under the influence of radiation and high temperatures. For example, grain boundaries affect corrosion by way of providing kinetically favorable paths for elemental diffusion, but they can also act as sinks for defects and helium generated during irradiation. Likewise, the retention of high-temperature strength in nanostructured, oxide-dispersion strengthened steels depends strongly on the stoichiometric and physical stability of the (Y, Ti)-oxide particles/matrix interface under radiation and high temperatures. An understanding of these interfacial effects at a fundamental level is important for the development of materials for extreme environments of nuclear reactors. The goal of this project is to develop an understanding stability of interfaces by depositing thin films of materials on substrates followed by ion irradiation of the film-substrate system at elevated temperatures followed by post-irradiation oxidation treatments. Specifically, the research will be performed by depositing thin films of yttrium and titanium (~500 nm) on Fe-12%Cr binary alloy substrate. Y and Ti have been selected as thin-film materials because they form highly stable protective oxides layers. The Fe-12%Cr binary alloy has been selected because it is representative of ferritic steels that are widely used in nuclear systems. The absence of other alloying elements in this binary alloy would allow for a clearer examination of structures and compositions that evolve during high-temperature irradiations and oxidation treatments. The research is divided into four specific tasks: (1) sputter deposition of 500 nm thick films of Y and Ti on Fe-12%Cr alloy substrates, (2) ion irradiation of the film-substrate system with 2MeV protons to a dose of 2 dpa at temperatures of 300°C, 500°C, and 700°C, (3) oxidation of as-deposited and ion-irradiated samples in a controlled oxygen environment at 500°C and 700°C, (4) multi-scale computational modeling involving first- principle molecular dynamics (FPMD) and coarse-grained dissipative particle dynamics (DPD) approaches to develop theories underlying the evolution and stability of structures and phases. Samples from Tasks 1 to 3 (above) will be rigorously characterized and analyzed using scanning electron microscopy, Auger electron microscopy, x-ray diffraction, Rutherford back scatter spectroscopy, and transmission electron microscopy. Expected outcomes of the experimental work include a quantitative understanding film-substrate interface mixing, evolution of defects and other phases at the interface, interaction of interfaces with defects, and the ability of the Y and Ti films to mitigate irradiation-assisted oxidation.The aforementioned experimental work will be closely coupled with multi-scale molecular dynamics (MD) modeling to understand the reactions at the surface, the transport of oxidant through the thin film, and the stabilities of the deposited thin films under radiation and oxidation. Simulations of materials property changes under conditions of radiation and oxidation require multiple size domains and a different simulation scheme for each of these domains. This will be achieved by coupling the FPMD and coarse-grained kinetic Monte Carlo (KMC). This will enable the comparison of the results of each simulation approach with the experimental results.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Early diagenetic processes in an iron-dominated marine depositional system

The early diagenetic interplay between reactive iron, sulfur, and organic matter in the bathymetrically isolated Santa Monica Basin (SMB) sediments are investigated in this study. Here, we explore solid-phase and porewater profiles from the basin, supplemented with a transect from 71 to 907 m water depth that includes oxygenated (>60 μM O 2 ) bottom waters near the coast and oxygen-deficient waters (~4 µM O 2 ) in the basin. The geochemical data of the basin sediments are further scrutinized by means of reactive transport modeling. The results show that the basin sediments do not follow the traditional geochemical signatures of oxygen-deficient settings. A lack of dissolved sulfide accumulation and sulfurized iron persists despite the sediments being deposited under reducing conditions (without bioturbation/bioirrigation), strong organic carbon input (TOC up to 5.0 wt%), and active dissimilatory sulfate reduction. Not only did we find an exceptional enrichment in highly reactive Fe in the surface sediments (~45 % of total Fe), but the enrichment of reactive Fe, including ferrihydrite, persists downcore and coexists with high levels of dissolved Fe. The enhanced preservation of Fe oxides and lack of iron-sulfide precipitation is in part explained by detection via Mössbauer spectra of iron oxides bounded to organic matter (Fe[III]-OM coprecipitates). The modeled Fe budget shows that most of the Fe oxides in the surface sediments are internally recycled by upward diffusion and subsequent oxidation of Fe 2+ . Sulfide oxidation coupled to Fe reduction effectively precludes sulfide accumulation while enhancing build-up of dissolved Fe, fueling the Fe cycle within the first 5 cm depth. Continuous reoxidation of Fe 2+ enhances the formation of Fe(III)-OM coprecipitates, limiting the amount of reactive organic matter. In the unavailability of labile organic matter, other than within the uppermost layers, the organic-rich sediment profiles are dominated by Fe cycling that limits the production and preservation of sulfides and enhances the preservation of Fe oxides and organic carbon. Finally, this study highlights key local controls on Fe availability in marginal basins and describes an intricate biogeochemical C-Fe-S cycling in modern and possibly ancient marine systems with important implications for Fe availability in the marine realm.

58 GEOSCIENCES↗
DOE OSTI2013

Thermal stability and lifetime estimates of a high temperature epoxy by T g reduction

Thermal degradation of a high temperature epoxy network is studied in terms glass transition temperature (T g ) reduction over a temperature window encompassing the T g of the network. The T g is shown to decrease as the network is thermally aged at elevated temperatures in air and in argon. The duration of the aging experiments is extended to long time such that the absolute T g reduction approaches a long time reduction plateau. Degradation is dominated by non-oxidative pyrolysis with a small contribution from diffusion limited thermal oxidative degradation at the surface. A time–temperature superposition is constructed from the extent of T g reduction of samples aged in air and the thermal shift factors are shown to have Arrhenius scaling behavior. An activation energy is extracted that agrees with previous activation energy measurements derived from other property measurements of the same network aged under similar conditions. The agreement of the activation energy with past results shows that T g reduction is controlled by the same degradation mechanism and may be used as an observable for lifetime estimates when thermal degradation is pyrolytic in nature. The extent of T g reduction is modeled with an autocatalytic rate expression and compared to previous property measurements to show the difference in sensitivity of observable material properties on degradation.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Tunable Atomic Layer Deposition into Ultra-High-Aspect-Ratio (>60000:1) Aerogel Monoliths Enabled by Transport Modeling

Atomic layer deposition (ALD) modification of ultra-high-aspect-ratio structures (>10,000:1) is a powerful platform with applications in catalysis, filtration, and energy conversion. However, the deposition of conformal and tunable ALD coatings at these aspect ratios remains challenging, resulting in empirical tradeoffs between precursor utilization and reaction time. Here, we demonstrate tunable control of the ALD infiltration depth into an aerogel monolith (AM) and develop a reaction-diffusion model to accurately describe the coating process. Specifically, we investigate the ALD exposure time and precursor dose needed to conformally coat a silica AM with pore sizes of ~20 nm, a monolith thickness of ~2.5 mm, and aspect ratios exceeding 60,000:1. We demonstrate complete infiltration into the AM, which is quantified by elemental mapping. A reaction-diffusion model is developed, which accounts for multiple doses and precursor depletion in the ALD chamber during an exposure step. The experimentally validated model enables the prediction and tuning of infiltration depth into a tortuous, high-aspect-ratio structure such as an AM, allowing for the synthesis of rationally designed material architectures. Additionally, the model allows for co-optimization of the total deposition time and percentage of unreacted precursor, which are important for the manufacturability and sustainability of ALD processing. Lastly, we demonstrate that ultra-thin ALD Al 2 O 3 coatings can be used to stabilize silica AMs against structural degradation under high-temperature annealing conditions (700-800 °C), by limiting changes in surface area and monolith volume. As a result, this improved high-temperature stability has implications for numerous aerogel applications, including catalysis and thermal insulation.

14 SOLAR ENERGY↗
DOE OSTI2019

On benchmarking of simulations of particle transport in ITER

We present results of benchmarking of core particle transport simulations by a collection of codes widely used in transport modelling of tokamak plasmas. Our analysis includes formulation of transport equations, difference between electron and ion solvers, comparison of modules of the pellet and edge gas fuelling on the ITER baseline scenario. During the first phase of benchmarking we address the particle transport effects in the stationary phase. Firstly, simulations are performed with identical sources, sinks, transport coefficients, and boundary conditions prescribed in the flattop H-mode phase. The transformation of ion particle transport equations is introduced so to directly compare their results to electron transport solvers. Moreover, the pellet fuelling models are benchmarked in various conditions to evaluate the dependency of the pellet deposition on the pellet volume, injection side, pedestal and separatrix parameters. Thirdly, edge gas fuelling is benchmarked to assess sensitivities of source profile predictions to uncertainties in plasma conditions and detailed model assumptions. At the second phase, we address particle transport effects in the time-evolving plasma including the current ramp-up to the ramp-down phase. The ion and the electron solvers are benchmarked together. Differences between the simulation results of the solvers are investigated in terms of equilibrium, grid resolution, radial coordinate, radial grid distribution, and plasma volume evolution term. We found that the selection of the radial coordinate can yield prominent differences between the solvers mainly due to differences in the edge grid distribution. The simulations reveal that electron and ion solvers predict noticeably different density peaking for the same diffusion and pinch velocity while with the peaked profile of helium, expected in fusion reactors. The fuelling benchmarking demonstrates that gas puffing is not efficient for core fuelling in H-modes and density control should be done by the high field side pellet injection in contrast to present machines.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Quantification of the Crack Evolution Process by Extracting Relevant Signal Components from Wave Propagation and Diffusive Transport Front Measurements

Wave propagation and diffusive transport phenomena in a geological rock sample undergoing crack evolution process are expected to interact with the mechanical discontinuities in the medium. The measurements of the signals associated with these phenomena can be used to assess and monitor the crack-driven micromechanical alterations in the rock. Different wave/diffusion phenomena, such as sonic propagation, pressure diffusion, and acoustic emission (AE), are sensitive to different elements of the mechanical discontinuities generated during the evolution of the crack clusters from initiation to coalescence. Sonic propagation, AE, and pressure diffusion monitoring have the potential to map the crack evolution because the transmitter-receiver arrays can be designed, arranged and tuned to (1) achieve maximum recovery of the scattered waveforms and travel times, (2) capture the later arrivals and multiple reflections, and (3) illuminate large rock volume. However, the structural/topological complexities of the mechanical discontinuities, complex distribution of the stress fields, complex mechanical alterations in media, and fluid redistribution in the crack system pose serious challenges for the detection and modeling of the crack evolution process (from here on, we will use the term ‘crack evolution process’ to mean that the crack evolution occurred under shallow crustal conditions). For purposes of accurately accounting such complexities and heterogeneities in the absence of reliable physical laws, simulation methods, and signal processing techniques, my early-career research proposal will develop and apply novel data-driven machine learning methods to: (1) extract signal components relevant to the various phases of crack evolution and (2) generate a 2D visual map of the crack evolution process.

58 GEOSCIENCES↗
DOE OSTI2022

Removing numerical pathologies in a turbulence parameterization through convergence testing

Discretized numerical models of the atmosphere are usually intended to faithfully represent an underlying set of continuous equations, but this necessary condition is violated sometimes by subtle pathologies that have crept into the discretized equations. Such pathologies can introduce undesirable artifacts, such as sawtooth noise, into the model solutions. The presence of these pathologies can be detected by numerical convergence testing. This study employs convergence testing to verify the discretization of the Cloud Layers Unified By Binormals (CLUBB) model of clouds and turbulence. That convergence testing identifies two aspects of CLUBB's equation set that contribute to undesirable noise in the solutions. First, numerical limiters (i.e. clipping) used by CLUBB introduce discontinuities or slope discontinuities in model fields. Second, this noise can be amplified by an advective term in CLUBB's background diffusion. Smoothing the limiters and removing the advective component of the background diffusion reduces the noise and restores the expected first-order convergence in CLUBB's solutions. These model reformulations improve the results at coarser, near-operational grid spacing and time step in cumulus cloud and dry turbulence tests. In addition, convergence testing is proved to be a valuable tool for detecting pathologies, including unintended discontinuities and grid dependence, in the model equation set.

Mathematics and Computing, Geosciences↗
DOE OSTI2019

Temperature Dependence of Self-diffusion in Cr2O3 from First Principles

Understanding and predicting the dominant diffusion processes in Cr2O3 is essen- tial to its optimization for anti-corrosion coatings, spintronics, and other applications. Despite significant theoretical effort in modeling defect mediated diffusion in Cr2O3 the correlation with experimentally measured diffusivities remains poor partly due to the insufficient accuracy of the theoretical approaches. Here an attempt to resolve these discrepancies is made through high accuracy density functional theory simulations cou- pled with grand canonical formalism of defect thermochemistry. In this approach, point defect formation energies were computed using hybrid exchange correlation functional. This level of theory proved to be essential for achieving the agreement with experi- mental self-diffusion coefficients. The analysis of the resulting self-diffusion coefficients indicate that chromium has higher mobility at low temperatures and high oxygen partial pressures, in particular at standard temperature and pressure conditions. At high vacuum, high temperature conditions, oxygen diffusion becomes dominant. At Cr/Cr2O3 interfaces O vacancies were found to be more mobile than Cr vacancies at all temperatures. Cr diffuses preferentially along the c-axis at low temperatures but switches to basal plane at higher temperatures. O diffusion is primarily bound to basal plane at all temperatures.

Medasani, Bharat K.↗
DOE OSTI2020

Anomalous Anisotropic Nanoparticle Aggregation in Cu 2 (OH) 3 Br Gels

Aerogels are of interest for their ability to uniformly incorporate nanoscale features into macroscopic assemblies, which enabled applications that require low density, high surface area, and/or bicontinuous networks. The structure of the nanoporous network is intrinsically linked to the macroscopic properties of aerogels. Hence, control of this structure is of paramount importance. Small-angle X-ray scattering (SAXS) is used here to monitor nanoparticle aggregation in situ in Cu 2 (OH) 3 Br aerogels formed via epoxide-assisted gelation. Anomalous anisotropic aggregation is observed in the absence of templating agents and is attributed to the molecular structure of the inorganic nanoparticles themselves. This is a fundamental departure from the models currently used to describe traditional inorganic sol–gel chemistry where nanoparticles are believed to undergo isotropic diffusion- and/or kinetically limited aggregation. Time-resolved SAXS indicates that Cu 2 (OH) 3 Br nanoparticles nucleate rapidly from solution to form unbranched chain-like aggregates rather than branched mass-fractal aggregates. Sizes of primary particles (~1.5 nm) and the chain-like structure of their aggregates are independent of particle concentration (gel density), while rates of particle aggregation, gelation time, and aggregate size are strongly dependent upon particle concentration, which implies that the chemistry of particle formation and the physics of particle aggregation are independent processes. Because the conditions necessary for creating anisotropic structures are not unique to Cu 2 (OH) 3 Br, these results could provide insight into the structure and gelation mechanisms of other inorganic aerogels.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Distributed State Estimation Over Time-Varying Graphs: Exploiting the Age-of-Information

Here, we study the problem of designing a distributed observer for an LTI system over a time-varying communication graph. The limited existing work on this topic imposes various restrictions either on the observation model or on the sequence of communication graphs. In contrast, we propose a single-time-scale distributed observer that works under mild assumptions. Specifically, our communication model only requires strong-connectivity to be preserved over non-overlapping, contiguous intervals that are even allowed to grow unbounded over time. We show that under suitable conditions that bound the growth of such intervals, joint observability is sufficient to track the state of any discrete-time LTI system exponentially fast, at any desired rate. We also develop a variant of our algorithm that is provably robust to worst-case adversarial attacks, provided the sequence of graphs is sufficiently connected over time. The key to our approach is the notion of a "freshness-index" that keeps track of the age-of-information being diffused across the network. Such indices enable nodes to reject stale estimates of the state, and, in turn, contribute to stability of the error dynamics.

42 ENGINEERING↗
DOE OSTI2018

A Novel Multi-scale Simulation Strategy for Turbulent Reacting Flows

In this project, a new methodology was proposed to bridge the gap between Direct Numerical Simulation (DNS) and Large Eddy Simulation (LES). This novel methodology, titled Lattice-Based Multiscale Simulation (LBMS), creates a lattice structure of One-Dimensional Turbulence (ODT) models. This model has been shown to capture turbulent combustion with high fidelity by fully resolving interactions between turbulence and diffusion. By creating a lattice of ODT models, which are then coupled, LBMS overcomes the shortcomings of ODT, which are its inability to capture large scale three dimensional flow structures. However, by spacing these lattices significantly apart, LBMS can avoid the curse of dimensionality that creates untenable computational costs associated with DNS. This project has shown that LBMS is capable of reproducing statistics of isotropic turbulent flows while coarsening the spacing between lines significantly. It also investigates and resolves issues that arise when coupling ODT lines, such as flux reconstruction perpendicular to a given ODT line, preservation of conserved quantities when eddies cross a course cell volume and boundary condition application. Robust parallelization is also investigated.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Assessing the ASME Section III, Division 5, Class A Primary Load Design Rules Against Creep Notch Effects

This report assesses the ASME Section III, Division 5, Subsection HB, Subpart B rules covering the design and construction of high temperature Class A nuclear reactor components for their robustness against creep notch effects. The creep notch effect combines the effect of multiaxial stresses on material creep deformation and damage. This report considers both effects, including the potential for creep mechanism shifts affecting the extrapolation of design data from high stress, short-time experimental data to low stress, long time operating component conditions. The report summarizes the history of and literature on multiaxial creep and surveys the current ASME design rules dealing with multiaxial effects. The report then describes the results of two dedicated numerical studies, one assessing the robustness of the ASME rules against uncertainty in extrapolating from uniaxial creep test data to multiaxial component conditions and a second study examining the potential effects of a mechanism shift from high stress, dislocation-mediated creep to diffusion-dominated creep at lower stresses. The final conclusion of the report is that the ASME rules adequately guard against multiaxial creep failure, though there are several aspects of the Code that could be optimized to provide less over-conservative design predictions or to provide a more consistent design margin as a function of temperature and stress. In a few areas, particularly the potential for mechanism shifts outside the currently-available experimental data, the Code rules should be revaluated as additional experimental data and new modeling and simulation results become available

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2012

Overlapping local/global iteration framework for whole-core transport solution

In current practice of reactor design analysis, whole-core diffusion nodal method is used in which nodal parameters are provided by single-assembly lattice physics calculation with net current zero boundary condition. Thus, the whole-core solution is not transport, because the inter-assembly transport effect is not incorporated. In this paper, the overlapping local/global iteration framework is described that removes the limitation of the current method. It consists of two-level iterative computations: half-node overlapping local problems embedded in a global problem. The local problem can employ fine-group deterministic or continuous-energy stochastic (Monte Carlo) transport methods, while the global problem is an equivalent coarse-group transport model based on p-CMFD methodology. The method is tested on several highly heterogeneous multi-slab problems with encouraging results. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

Modeling soil CO<sub>2</sub> production and transport with dynamic source and diffusion terms: testing the steady-state assumption using DETECT v1.0

Abstract. The flux of CO2 from the soil to the atmosphere (soil respiration, Rsoil) is a major component of the global carbon (C) cycle. Methods to measure and model Rsoil, or partition it into different components, often rely on the assumption that soil CO2 concentrations and fluxes are in steady state, implying that Rsoil is equal to the rate at which CO2 is produced by soil microbial and root respiration. Recent research, however, questions the validity of this assumption. Thus, the aim of this work was two-fold: (1) to describe a non-steady state (NSS) soil CO2 transport and production model, DETECT, and (2) to use this model to evaluate the environmental conditions under which Rsoil and CO2 production are likely in NSS. The backbone of DETECT is a non-homogeneous, partial differential equation (PDE) that describes production and transport of soil CO2, which we solve numerically at fine spatial and temporal resolution (e.g., 0.01 m increments down to 1 m, every 6 h). Production of soil CO2 is simulated for every depth and time increment as the sum of root respiration and microbial decomposition of soil organic matter. Both of these factors can be driven by current and antecedent soil water content and temperature, which can also vary by time and depth. We also analytically solved the ordinary differential equation (ODE) corresponding to the steady-state (SS) solution to the PDE model. We applied the DETECT NSS and SS models to the six-month growing season period representative of a native grassland in Wyoming. Simulation experiments were conducted with both model versions to evaluate factors that could affect departure from SS, such as (1) varying soil texture; (2) shifting the timing or frequency of precipitation; and (3) with and without the environmental antecedent drivers. For a coarse-textured soil, Rsoil from the SS model closely matched that of the NSS model. However, in a fine-textured (clay) soil, growing season Rsoil was ∼ 3 % higher under the assumption of NSS (versus SS). These differences were exaggerated in clay soil at daily time scales whereby Rsoil under the SS assumption deviated from NSS by up to 35 % on average in the 10 days following a major precipitation event. Incorporation of antecedent drivers increased the magnitude of Rsoil by 15 to 37 % for coarse- and fine-textured soils, respectively. However, the responses of Rsoil to the timing of precipitation and antecedent drivers did not differ between SS and NSS assumptions. In summary, the assumption of SS conditions can be violated depending on soil type and soil moisture status, as affected by precipitation inputs. The DETECT model provides a framework for accommodating NSS conditions to better predict Rsoil and associated soil carbon cycling processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Stability of Cu(In x Ga 1− x )Se 2 Solar Cells Utilizing RbF Postdeposition Treatment under a Sulfur Atmosphere

Alkali halide postdeposition treatments (PDTs) have become a key tool to maximize efficiency in Cu(In x Ga 1− x )Se 2 (CIGS) photovoltaics. RbF PDTs have emerged as an alternative to the more common Na‐ and K‐based techniques. This study utilizes temperature‐dependent current–voltage ( JVT ) measurements to study a unique RbF PDT performed in a S atmosphere. The samples are measured before and after 6 months in a desiccator to study device stability. Both samples contain Na and K which diffuse from the soda–lime glass substrate. A reference sample and a RbF + S PDT sample both show the development of a rear contact barrier after aging. The contact barrier is higher for the RbF + S PDT sample, leading to decreased current in forward bias. Series resistance is also higher in the RbF + S PDT device which leads to lower fill factor. However, after aging the reference sample has a larger decrease in open‐circuit voltage ( V OC ). Ideality factor measurements suggest Shockley–Read–Hall recombination dominates both samples. V OC versus temperature and a temperature‐dependent activation energy model are used to calculate diode activation energies for each sample condition. Both techniques produce similar values that indicate recombination primarily occurs within the bulk absorber.

14 SOLAR ENERGY↗
DOE OSTI2022

Experimental validation of the mechanistic scale-up methodology of gas–solid spouted beds using radioactive particle tracking (RPT)

The very high-temperature reactors (VHTRs) are highly ranked among candidates of Generation IV of nuclear reactors due to their high efficiency, safety, the resistance to proliferation, and reliability. The VHTRs are preferentially fueled by Tristructural-isometric (TRISO) coated fuel particles which has fuel kernels of fissile material coated by four coating layers: a porous buffer pyrolysis carbon layer (buffer PyC), an inner dense pyrolysis carbon layer (IPyC), a silicon carbide layer (SiC) and an outer dense pyrolysis carbon layer (OPyC). The heart of the operation and safety of the VHTRs significantly depends on the reliability of the coating layers of TRISO particles to retain metallic and gaseous fission products within the particles. The technique used for coating TRISO particles are gas-solids spouted beds via chemical vapor deposition (CVD). Fabrication of high-quality low-defect TRISO fuel particles fuel at larger scale spouted beds is required to support the commercialization of the VHTRs. In this work, our new developed mechanistic scale-up methodology of gas-solids spouted beds based on matching the radial profile of gas-holdup has been demonstrated and validated using radioactive particle tracking (RPT). Two spouted beds of small and larger scales were used in the study. Three sets of conditions were carried out which include the conditions of the reference case in the large scale, conditions that provide similar gas holdup radial profile to that of the reference case and conditions that provided dissimilar gas holdup radial in the small-scale spouted beds. The results confirm the validation of the scale-up methodology in terms of the dimensionless values of the spout diameter, cumulative probability distribution of the solids particles penetration into the spout, fraction of cycle time in each region of the bed, the radial profiles of the dimensionless values of the root-mean-square particle velocities and solids eddy diffusivity. Finally, the results further advance the knowledge and understanding of the gas-solids spouted beds provide deeper insight into their solids dynamics and presenting important benchmarking data for validating computational fluid dynamics codes and models. At last, procedures are established for the implementation of the new scale-up methodology.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Best of both worlds: Enforcing detailed balance in machine learning models of transition rates

The slow microstructural evolution of materials often plays a key role in determining material properties. When the unit steps of the evolution process are slow, direct simulation approaches such as molecular dynamics become prohibitive and Kinetic Monte-Carlo (kMC) algorithms, where the state-to-state evolution of the system is represented in terms of a continuous-time Markov chain, are instead frequently relied upon to efficiently predict long-time evolution. The accuracy of kMC simulations however relies on the complete and accurate knowledge of reaction pathways and corresponding kinetics. This requirement becomes extremely stringent in complex systems such as concentrated alloys where the astronomical number of local atomic configurations makes the a priori tabulation of all possible transitions impractical. Machine learning models of transition kinetics have been used to mitigate this problem by enabling the efficient on-the-fly prediction of kinetic parameters. While conventional KMC methods based on transition state theory naturally yield reversible dynamics that exactly obey the detailed balance criterion, providing strong guarantees on the properties of the stationary distribution, many recently-proposed ML-based approaches to barrier predictions provide no such guarantees. In this study, we derive conditions under which physics-informed ML architectures exactly enforce the detailed balance condition by construction, even when relying on non-extensive descriptions of states in terms of local environments around mobile defects. In conclusion, using the diffusion of a vacancy in a concentrated alloy as an example, we show that such ML architectures also exhibit superior performance in terms of prediction accuracy, demonstrating that the imposition of physical constraints can facilitate the accurate learning of barriers at no increase in computational cost.

36 MATERIALS SCIENCE↗