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At least 379 records · Page 21

Realistic 3D Radiative Modeling of Turbulent Structure of Moderate-Mass Stars and Sun

Understanding the turbulent dynamics of the Sun and stars is a critical element for interpreting observed processes and phenomena on different scales and for predicting extreme events such as flares and super flares. High-­‐resolution observations of the Sun and high-­‐fidelity radiative MHD numerical simulations have substantially advanced our understanding of solar and stellar local dynamics and magnetism from the upper convection zone to the atmosphere and corona. However, global modeling of the Sun with such a high degree of realism is currently not affordable due to the extremely high computational cost of resolving the scales in the convection zone. The physics of the deep solar dynamics can be effectively addressed through modeling more massive solar-­‐type stars where the convection zone is shallower and the convective overturning time is much shorter than those on the Sun. We present recent 3D realistic simulation results of moderate-­‐mass stars and discuss links between solar and stellar dynamics, such as the multiscale structure of granulation, convective overshoot, and others. In particular, these simulations have provided better understanding of the dynamics of the tachocline (the overshoot layer at the bottom of the convection zone) and have explained long-­‐ standing results from helioseismology.

Realistic↗

Multiscale Modeling of Thermoplastics Using Atomistic-informed Micromechanics

A multiscale model was developed for predicting the thermoelastic behavior of semi-crystalline thermoplastic materials for composite aerospace applications. At the highest scale containing the semi-crystalline spherulite in an amorphous matrix, the generalized method of cells, or high fidelity method of cells, was used to perform the homogenization calculations to obtain the effective properties. Models were developed assuming a cubic, or spherical shape, for the spherulite to understand if the morphology of the spherulite affects the effective thermoelastic properties. The generalized method of cells was used to model at the repeating unit cells at the subscales of the microstructure including the lamellae stacks and granular crystal blocks. The scales are integrated using the multiscale micromechanics method in the NASA Multiscale Analysis Tool. Data from molecular dynamics simulations were used as inputs for the amorphous and crystalline constituents. Convergence studies were performed to determine the best level of discretization for the repeating unit cell at the highest scale. Effective Young’s modulus, shear modulus, Poisson’s ratio, coefficient of thermal expansion, and thermal conductivity were predicted for polyether ether ketone and polyether ketone ketone, and very good agreement between the model utilizing the cubic spherulite and the experimental data, where available, was observed for polyether ketone ketone. Normalization of the data for the bulk polyether ketone ketone, against amorphous data, improved the predictions as compared to experimental data. Overall, the high fidelity method of cells predicted a stiffer response then the generalized method of cells as the crystallinity was increased. The shape of the spherulite had a minimal effect on the predicted bulk properties of the polymers.

thermoplastics↗

Evaluation of a nonlinear variational multiscale method for fluid transport problems

Diverse transport problems, especially those based on fluid flow models, are intrinsically multiscale and nonlinear, characteristics that often lead to intricate dynamics such as the development of instabilities and turbulence. Computational simulations that resolve all scales in these problems are often unfeasible, prompting to coarse-grained simulation strategies in which small-scale features are modeled instead of resolved. Variational Multiscale (VMS) methods, and particularly residual-based Large-Eddy Simulation (LES) approaches, have proven effective and robust for the coarse-grained simulation of complex transport problems. VMS methods avoid the assumption of separable nonlinearity and the reliance on empirical small-scale models by using a variational decomposition of scales together with a residual-based approximation of the small-scales. Evaluation of a nonlinear VMS approach, denoted as VMS n , is presented for the coarse-grained simulation of transient-advective-diffusive-reactive (TADR) transport problems arising from fluid flow models. In contrast to classical VMS approaches that neglect the effect of the small scales on the transport operator, VMS n treats the inter-dependence between large- and small-scales upfront. The treatment of inter-scale coupling involves the solution of a local algebraic nonlinear system describing the evolution of the small-scales. The VMS n approach is complemented with two algebraic approximations of the small-scales: one based on the main diagonal of the transport matrices and another that preserves transport fluxes and is suitable for generic TADR systems. The suitability of the VMS n approach for handling general TADR problems and regimes is evaluated with benchmark incompressible, compressible, and magnetohydrodynamic laminar flow problems, the incompressible Taylor-Green vortex flow, the turbulent free jet, and the two-temperature arc in crossflow. Furthermore, simulation results show that VMS n leads to minor improvements in accuracy with respect to the classical VMS for the laminar flow problems, but to significantly greater accuracy for the turbulent flows and the unsteady plasma flow problems, while using the same cohesive numerical formulation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Multiscale, mechanistic modeling of cesium transport in silicon carbide for TRISO fuel performance prediction

Understanding cesium (Cs) transport in TRistructural ISOtropic (TRISO) particle fuel is crucial for predicting fission product release in high-temperature reactors. However, current challenges include significant scatter in diffusivity data and unexplained temperature-dependent diffusion regimes in the silicon carbide layer. This study addresses these challenges by developing a multiscale, mechanistic Cs transport model integrating atomistic simulations and phase field modeling. Our model quantifies temperature and grain size effects on Cs diffusivity, attributing experimentally observed regimes to a transition from bulk-dominated diffusivity at high temperatures to grain boundary-dominated diffusivity at lower temperatures. The model, validated against diffusion measurements and advanced gas reactor (AGR)-1 and AGR-2 post-irradiation fission product release data, enhances the predictive capability of the BISON fuel performance code. This study advances our understanding of Cs release from TRISO particles and its dependence on temperature and silicon carbide grain size, with implications for the safety and efficiency of high-temperature nuclear reactors.

BISON↗

Multiphase computational fluid dynamics modeling of reacting flows in absorption columns for carbon capture

First-principles derived computational fluid dynamics (CFD) simulations have been proposed as a fundamental tool for investigating solvent-based CO 2 absorption in packed columns due to their ability to accurately represent the underlying nonlinear, multiscale dynamics. Numerous studies have previously utilized such CFD simulations to investigate hydrodynamics of columns with structured and random packings by assessing the key hydrodynamic metrics such as the interfacial and wetted areas. While mapping such metrics for different conditions is essential to the optimization of absorption columns, it is not sufficient, as the CO 2 capture rate depends also on the coupled, nonlinear dynamics from the underlying chemical reaction kinetics, thermodynamics, and heat-transfer rates. In this work, we present detailed CFD simulation results augmented by incorporating the effects of interfacial physical mass transfer of CO 2 , heat release from chemical reaction kinetics, and thermophysical property variations from resulting temperature gradients. We demonstrate the applicability of the proposed approach in numerically assessing the performance of packed columns by evaluating key hydrodynamic quantities, CO 2 absorption rates, and temperature rise in a reference column with packings that are structurally similar to the Sulzer Mellapak™ 250.Y packing, for different solvent inflow velocities and temperatures. Predictions from simulation results are found to be consistent with the trends in experimental observations from the literature, suggesting that the predictive capabilities of the simulation framework can be leveraged to guide the future development of absorber-column designs and optimized process flowsheets.

Absorption columns↗

#COVIDisAirborne: AI-enabled multiscale computational microscopy of delta SARS-CoV-2 in a respiratory aerosol

We seek to completely revise current models of airborne transmission of respiratory viruses by providing never-before-seen atomic-level views of the SARS-CoV-2 virus within a respiratory aerosol. Our work dramatically extends the capabilities of multiscale computational microscopy to address the significant gaps that exist in current experimental methods, which are limited in their ability to interrogate aerosols at the atomic/molecular level and thus obscure our understanding of airborne transmission. We demonstrate how our integrated data-driven platform provides a new way of exploring the composition, structure, and dynamics of aerosols and aerosolized viruses, while driving simulation method development along several important axes. We present a series of initial scientific discoveries for the SARS-CoV-2 Delta variant, noting that the full scientific impact of this work has yet to be realized.

60 APPLIED LIFE SCIENCES↗

Interpretation of Ion Irradiation and Neutron Irradiation Damage in Additively Manufactured 316 Stainless Steel using Multiscale Modeling

The accelerated adoption of nuclear energy necessitates advanced manufacturing technologies, such as additive manufacturing, to meet heightened supply chain requirements and support innovative reactor technologies. Due to the unique microstructural characteristics of additively manufactured materials under distinct solidification conditions, comprehensive evaluation of their performance in reactor environments is essential. The Advanced Materials and Manufacturing Technologies program under the Department of Energy's Office of Nuclear Energy focuses on understanding the irradiation performance and damage evolution of laser powder bed fusion 316 stainless steel, with an emphasis on integrating ion and neutron irradiation data to accelerate the development and qualification of materials for advanced nuclear reactor applications. While ion irradiation is a cost- and time-effective method, modeling and simulation are required to interpret the data for the broader range of irradiation conditions encountered in advanced reactors. In fiscal year 2025, integrated multiscale modeling and simulations were conducted to assess irradiation damage in additively manufactured 316 stainless steel. Key outcomes include predictions of chromium enrichment at grain boundaries, nickel enrichment at dislocation cell walls and void surfaces, and heterogeneous void evolution under ion and neutron irradiation conditions. Cluster dynamics simulations revealed the coarsening of voids at high irradiation temperatures and the suppression of void growth by high network dislocation density, while also demonstrating significant growth and coarsening of voids and self-interstitial atom loops at low dose rates. Machine learning-accelerated atomistic simulations highlighted the impact of the local environment and chromium concentration on vacancy diffusivity, providing key insights on the influence of composition on void swelling and radiation-induced segregation. Additionally, molecular dynamics simulations demonstrated the presence of defect production bias and a significant effect of carbon content on defect cluster behavior. These combined efforts aim to predict the performance of additively manufactured materials under various reactor conditions, supporting their qualification for nuclear reactor applications by interpreting ion irradiation data. This report underscores the potential of integrated multiscale modeling to analyze ion irradiation data in the effort to accelerate the qualification of additively manufactured materials for nuclear reactor components.

316 stainless steel↗

Multimodal and multiscale strengthening mechanisms in Al-Ni-Zr-Ti-Mn alloy processed by laser powder bed fusion additive manufacturing

The unique thermokinetics of laser-powder bed fusion additive manufacturing (L-PBFAM) has been exploited for development of a novel high-strength Al-Ni-Ti-Zr-Mn alloy. The addition of 0.5 wt% Mn leads to extraordinary improvement in ultimate tensile strength (502 MPa) and work hardening due to the activation of two Mn-induced strengthening mechanisms. First, by a bimodal particle strengthening effect due to Al 31 Mn 6 Ni 12 nano-quasi-crystal particles rejected in inter-dendritic spaces and fibrous Al 3 Ni eutectic dendritic channels, which predominately contributes to the strength improvement, and second by solid solution strengthening from remaining Mn entrapped in Al. These mechanisms supplement the particle strengthening effect imparted by coherent and incoherent Al 3 (Ti,Zr) co-precipitates present at melt pool boundaries, dislocation strengthening due to solidification induced strain, and Hall-Petch and backstress strengthening effect due to heterogenous grain size distribution occurring at various length scales. In conclusion, the solidification dynamics and hierarchical heat distribution that are associated with L-PBFAM resulted in complex spatial variations in these strengthening phenomena and were investigated via a high-throughput multiscale structure–property correlation that involved thermokinetic simulation, X-ray diffraction, high-resolution nanoindentation mapping, and site-specific transmission electron microscopy of the alloy.

36 MATERIALS SCIENCE↗

Decoupling between Shockley partials and stacking faults strengthens multiprincipal element alloys

We report that mechanical properties are fundamental to structural materials, where dislocations play a decisive role in describing their mechanical behavior. Although the high-yield stresses of multiprincipal element alloys (MPEAs) have received extensive attention in the last decade, the relation between their mechanistic origins remains elusive. Our multiscale study of density functional theory, atomistic simulations, and high-resolution microscopy shows that the excellent mechanical properties of MPEAs have diverse origins. The strengthening effects through Shockley partials and stacking faults can be decoupled in MPEAs, breaking the conventional wisdom that low stacking fault energies are coupled with wide partial dislocations. This study clarifies the mechanistic origins for the strengthening effects, laying the foundation for physics-informed predictive models for materials design.

36 MATERIALS SCIENCE↗

A DG-IMEX Method for Two-moment Neutrino Transport: Nonlinear Solvers for Neutrino–Matter Coupling

Neutrino-matter interactions play an important role in core-collapse supernova (CCSN) explosions as they contribute to both lepton number and/or four-momentum exchange between neutrinos and matter, and thus act as the agent for neutrino-driven explosions. Due to the multiscale nature of neutrino transport in CCSN simulations, an implicit treatment of neutrino-matter interactions is desired, which requires solutions of coupled nonlinear systems in each step of the time integration scheme. In this paper we design and compare nonlinear iterative solvers for implicit systems with energy coupling neutrino-matter interactions commonly used in CCSN simulations. Specifically, we consider electron neutrinos and antineutrinos, which interact with static matter configurations through the Bruenn 85 opacity set. The implicit systems arise from the discretization of a nonrelativistic two-moment model for neutrino transport, which employs the discontinuous Galerkin (DG) method for phase-space discretization and an implicit-explicit (IMEX) time integration scheme. In the context of this DG-IMEX scheme, we propose two approaches to formulate the nonlinear systems — a coupled approach and a nested approach. For each approach, the resulting systems are solved with Anderson-accelerated fixedpoint iteration and Newton’s method. The performance of these four iterative solvers has been compared on relaxation problems with various degree of collisionality, as well as proto-neutron star deleptonization problems with several matter profiles adopted from spherically symmetric CCSN simulations. Here, numerical results suggest that the nested Anderson-accelerated fixed-point solver is more efficient than other tested solvers for solving implicit nonlinear systems with energy coupling neutrino-matter interactions.

79 ASTRONOMY AND ASTROPHYSICS↗

Multiscale Modeling of Thermal Conductivity of Polymer/Carbon Nanocomposites

Molecular dynamics simulation was used to estimate the interfacial thermal (Kapitza) resistance between nanoparticles and amorphous and crystalline polymer matrices. Bulk thermal conductivities of the nanocomposites were then estimated using an established effective medium approach. To study functionalization, oligomeric ethylene-vinyl alcohol copolymers were chemically bonded to a single wall carbon nanotube. The results, in a poly(ethylene-vinyl acetate) matrix, are similar to those obtained previously for grafted linear hydrocarbon chains. To study the effect of noncovalent functionalization, two types of polyethylene matrices. -- aligned (extended-chain crystalline) vs. amorphous (random coils) were modeled. Both matrices produced the same interfacial thermal resistance values. Finally, functionalization of edges and faces of plate-like graphite nanoparticles was found to be only modestly effective in reducing the interfacial thermal resistance and improving the composite thermal conductivity

Clancy, Thomas C.↗

Coupling of Spark Plasma Sintering with Advanced Modeling to Enable Process Scale-Up: LDRD Final Project Poster

Electric-field assisted sintering (EFAS) manufacturing techniques reduce energy usage requirements, fabricate near-net-shape parts, and produce bulk nanostructured materials through rapid heating and cooling rates achievable through Joule heating. Process parameters of pulsed DC voltage and constant pressure are applied through stainless steel rams and graphite tooling to the ceramic yttrium oxide powder to be sintered. Our high-fidelity modeling code application advances manufacturing for extreme environments by enabling process-informed design and improving microstructure consistency through multiphysics multiscale process-structure-property-performance correlation simulations.

36 MATERIALS SCIENCE↗

Multiscale formulation of frictional contact mechanics at the pore scale

Direct numerical simulation (DNS) yields the highest fidelity predictions of mechanical deformation at the pore scale, but is prohibitively expensive for analyzing large or many samples. Discrete element methods (DEM) are an efficient alternative, but are limited to granular media and incapable of estimating or controlling prediction errors. We present a pore-level multiscale method (PLMM) that approximates DNS efficiently and with controllable accuracy. We focus on the linear elastic response of a consolidated geologic porous medium with arbitrary microstructure, heterogeneous mineralogy, containing cracks or defects. PLMM decomposes the solid phase into non-overlapping subdomains, on which local basis functions are constructed. The bases are then coupled with a global interface problem that accounts for slip or stick contact conditions between the subdomains. PLMM produces an initial, but accurate, approximation to DNS that can be iteratively improved. It is amenable to parallelism and allows for different mesh, models, and physics in each subdomain. An algebraic interpretation of PLMM as a preconditioner is also presented to allow non-intrusive implementation into existing solvers. Lastly, this work extends previous developments of PLMM in fluid dynamics to solid mechanics and enables future extensions towards modeling coupled flow and mechanics problems.

42 ENGINEERING↗

Numerical Simulation of Container Breach and Airborne Release of Solids Due to Mechanical Insults

Throughout U.S. Department of Energy (DOE) complexes, safety engineers employ the five-factor formula to calculate the source term (ST) that includes parameters of airborne release fraction (ARF), respirable fraction (RF) and damage ratio (DR). Limited experimental data on fragmentation of solids, such as ceramic pellets (i.e., PuO2), and container breach due to mechanical insults (i.e., drop and forklift impact), can be supplemented by modeling and simulation using high fidelity computational tools to estimate these parameters. This paper presents the use of Sandia National Laboratories' SIERRA solid mechanics (SM) finite element code to investigate the behavior of the widely utilized waste container (such as 7A Drum) subject to a range of free fall impact and puncture scenarios. The resulting behavior of the container is assessed, and the estimates are presented for bounding DRs from calculated breach areas for the various accident conditions considered. This paper also describes a novel multiscale constitutive model recently implemented in SIERRA/SM that simulates the fracture of brittle materials such as PuO 2 and determines ARF during the fracture process. Furthermore, comparisons are made between model predictions and simple bench-top experiments.

61 RADIATION PROTECTION AND DOSIMETRY↗

SO2 over Central China: Measurements, Numerical Simulations and the Tropospheric Sulfur Budget

SO2 in central China was measured in situ from an aircraft and remotely using the Ozone Monitoring Instrument (OMI) from the Aura satellite; results were used to develop a numerical tool for evaluating the tropospheric sulfur budget - sources, sinks, transformation and transport. In April 2008, measured ambient SO2 concentrations decreased from approx.7 ppbv near the surface to approx. 1 ppbv at 1800 m altitude (an effective scale height of approx.800 m), but distinct SO2 plumes were observed between 1800 and 4500 m, the aircraft's ceiling. These free tropospheric plumes play a major role in the export of SO2 and in the accuracy of OMI retrievals. The mean SO2 column contents from aircraft measurements (0.73 DU, Dobson Units) and operational OMI SO2 products (0.63+/-0.26 DU) were close. The OMI retrievals were well correlated with in situ measurements (r = 0.84), but showed low bias (slope = 0.54). A new OMI retrieval algorithm was tested and showed improved agreement and bias (r = 0.87, slope = 0.86). The Community Multiscale Air Quality (CMAQ) model was used to simulate sulfur chemistry, exhibiting reasonable agreement (r = 0.62, slope = 1.33) with in situ SO2 columns. The mean CMAQ SO2 loading over central and eastern China was 54 kT, approx.30% more than the estimate from OMI SO2 products, 42 kT. These numerical simulations, constrained by observations, indicate that ",50% (35 to 61 %) of the anthropogenic sulfur emissions were transported downwind, and the overall lifetime of tropospheric SO2 was 38+/-7 h.

He, Hao↗

Magnetopause Reconnection as Influenced by the Dipole Tilt Under Southward IMF Conditions: Hybrid Simulation and MMS Observation

Abstract Using a three‐dimensional (3‐D) global‐scale hybrid code, the Magnetospheric Multiscale (MMS) reconnection event around 02:13 UT on 18 November 2015, highlighted in the Geospace Environment Modeling (GEM) Dayside Kinetic Challenge, is simulated, in which the interplanetary magnetic field (IMF) points southward and the geomagnetic field has a −27° dipole tilt angle. Strong southward plasma jets are found near the magnetopause as a result of the dayside reconnection. Our results indicate that the subsolar magnetopause reconnection X line shifts from the subsolar point toward the Northern Hemisphere due to the effect of the tilted geomagnetic dipole angle, consistent with the MMS observation. Subsequently, the reconnection X lines or sites and reconnection flux ropes above the equator propagate northward along the magnetopause. The formation and global distribution of the X lines and the structure of the magnetopause reconnection are investigated in detail with the simulation. Mirror mode waves are also found in the middle of the magnetosheath downstream of the quasi‐perpendicular shock where the plasma properties are consistent with the mirror instability condition. As a special outcome of the GEM challenge event, the spatial and temporal variations in reconnection, the electromagnetic power spectra, and the associated D‐shaped ion velocity distributions in the simulated reconnection event are compared with the MMS observation.

Guo, Zhifang↗

Adaptive tau-leaping methods for microscopic-lattice kinetic Monte Carlo simulations

Traditional Kinetic Monte Carlo (KMC) approaches, rooted in Gillespie’s stochastic simulation algorithm, become computationally demanding in systems with a large range of timescales. The goal of this work is to propose and study new adaptive lattice-KMC time integration strategies for spatially non-uniform systems. To that end, two novel adaptive tau-leaping methods and their corresponding time integration strategies are developed based on the idea of the “n-fold” direct KMC method. These strategies allow for the simultaneous execution of multiple reactions, advancing time by adaptively selected coarse increments. We present numerical experiments comparing the proposed methods with existing approaches in a catalytic surface kinetics application involving ammonia decomposition.

Bimolecular reactions↗