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At least 127 records · Page 7

Multiscale Analysis of Structurally-Graded Microstructures Using Molecular Dynamics, Discrete Dislocation Dynamics and Continuum Crystal Plasticity

A multiscale modeling methodology is developed for structurally-graded material microstructures. Molecular dynamic (MD) simulations are performed at the nanoscale to determine fundamental failure mechanisms and quantify material constitutive parameters. These parameters are used to calibrate material processes at the mesoscale using discrete dislocation dynamics (DD). Different grain boundary interactions with dislocations are analyzed using DD to predict grain-size dependent stress-strain behavior. These relationships are mapped into crystal plasticity (CP) parameters to develop a computationally efficient finite element-based DD/CP model for continuum-level simulations and complete the multiscale analysis by predicting the behavior of macroscopic physical specimens. The present analysis is focused on simulating the behavior of a graded microstructure in which grain sizes are on the order of nanometers in the exterior region and transition to larger, multi-micron size in the interior domain. This microstructural configuration has been shown to offer improved mechanical properties over homogeneous coarse-grained materials by increasing yield stress while maintaining ductility. Various mesoscopic polycrystal models of structurally-graded microstructures are generated, analyzed and used as a benchmark for comparison between multiscale DD/CP model and DD predictions. A final series of simulations utilize the DD/CP analysis method exclusively to study macroscopic models that cannot be analyzed by MD or DD methods alone due to the model size.

Saether, Erik↗

CoarsenConf: Equivariant Coarsening with Aggregated Attention for Molecular Conformer Generation

Molecular conformer generation (MCG) is an important task in cheminformatics and drug discovery. The ability to efficiently generate low-energy 3D structures can avoid expensive quantum mechanical simulations, leading to accelerated virtual screenings and enhanced structural exploration. Several generative models have been developed for MCG, but many struggle to consistently produce high-quality conformers for meaningful downstream applications. To address these issues, we introduce CoarsenConf, which coarse-grains molecular graphs based on torsional angles and integrates them into an SE(3)-equivariant hierarchical variational autoencoder. Through equivariant coarse-graining, we aggregate the fine-grained atomic coordinates of subgraphs connected via rotatable bonds, creating a variable-length coarse-grained latent representation. Our model uses a novel aggregated attention mechanism to restore fine-grained coordinates from the coarse-grained latent representation, enabling efficient generation of accurate conformers. Furthermore, we evaluate the chemical and biochemical quality of our generated conformers on multiple downstream applications, including property prediction and large-scale oracle-based protein docking. Overall, CoarsenConf generates more accurate conformer ensembles compared to prior generative models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Phase-Field Methods for Structure Evolution in Sheared Multiphase Systems

A homogeneous disordered phase separates into ordered structures when quenched into a broken-symmetry phase. The competition of broken-symmetry phases to select an equilibrium state may be studied in terms of coarse-grained order parameters described by a suitable Landau free-energy function. A network of equilibrium-phase domains develops on quenching and coarsens with time with a topology that may be controlled by shear. We use three-dimensional simulations, in which time-dependent models for conserved-order parameters coupled to Navier-Stokes fluid models are solved, to investigate the evolution of such domains, e.g. spinodal decompositions of polymeric materials under shear. The numerical problems are formidable because of the strong nonlinearities inherent in the coupled model, and these are amongst the first 3D calculations undertaken. In linear shear fields we find stable nanostrings, also recently seen in experiments. The affinity of the ordered phases to boundaries plays a role in the form of the structures that develop, with stacked plate-like phase distributions emerging under certain conditions. Such methods appear quite promising for design and analysis of multiphase and complex fluid formulations. The behavior of foams in such conditions is of particular interest in microgravity environments. Additional information can be found in the original extended abstract.

Badalassi, Vittorio↗

Dust Particle Aeroheating Calculations for Mars Entry Hypersonic Flows

The purpose of the current research effort is to predict particle trajectories in a hypersonic flowfield while accounting for all relevant particle-fluid and particle-particle interactions. The resulting particle solver is titled DUst Simulation & Tracking (DUST) and works in conjunction with the US3D CFD flow solver. The key elements underpinning the current work are an efficient mesh-localiztion algorithm, time-driven hard-sphere model, point-to-point MPI framework, coarse-graining using computational parcels, and high-order Adams-Bashforth time stepping. The coupled US3D-DUST framework will be applied to conduct a multi-physics examination of dust-laden flows around the the Schiarparelli capsule.

Dusty Flows↗

Dust Particle Aeroheating Calculations for Mars Entry Hypersonic Flows

The purpose of the current research effort is to predict particle trajectories in a hypersonic flowfield while accounting for all relevant particle-fluid and particle-particle interactions. The resulting particle solver is titled DUst Simulation & Tracking (DUST) and works in conjunction with the US3D CFD flow solver. The key elements underpinning the current work are an efficient mesh-localiztion algorithm, time-driven hard-sphere model, point-to-point MPI framework, coarse-graining using computational parcels, and high-order Adams-Bashforth time stepping. The coupled US3D-DUST framework will be applied to conduct a multi-physics examination of dust-laden flows around the the Mars 2020 capsule.

Dusty Flows↗

Beyond Magic Barrels: Digital manufacturing for crystallization, process development and optimization of explosive materials: Part II Resveratrol Exemplar

This SAND report summarizes work supported by an Engineering Sciences Research Foundation (ESRF) Lab Directed Research and Development (LDRD) project entitled “Beyond Magic Barrels: Digital manufacturing for crystallization, process development and optimization of explosive materials.” This SAND report is written in two parts with Part 1 discusses recrystallization of our explosive exemplar and Part 2 summarizing our work with recrystallization of resveratrol. We have studied resveratrol recrystallization with a multiscale approach combining experiments, modeling and simulation. At the single crystal scale, microscopy experiments illuminate crystal time-dependent growth rates using advanced image analysis. Bench scale experiments were carried out to look at growth of multiple particles in a small reactor creating thousands of particles and analyzing the results with microscopy and μCT. For the modeling we combine kinetic Monte Carlo (kMC) models with subscale information from density functional theory (DFT) or molecular dynamics. This work is discussed in Part 1 and can also be found in a paper from the project discussing a coarse-grained kMC model specifically developed for resveratrol. For well-mixed systems, we have population balance equations (PBE) linked with species mass conservation forming a set of ordinary differential equations that can be solved quickly. For more complicated geometries, such as the vat crystallization used throughout the complex, a coupled computational fluid dynamic (CFD)/PBE method was developed to account for gradients in temperature and concentration and differences in crystallization rates throughout the domain. These simulations are more complex and require high performance computing. We present results for two cases: 5% seed fast cool with parameters fit to the well-mixed case and 5% seed slow cool using the same parameters. We show reasonable agreement with experiments though are particles are significantly larger than the experiments.

36 MATERIALS SCIENCE↗

Complex orders and chirality in the classical Kitaev-Γ model

It is well recognized that the low-energy physics of many Kitaev materials is governed by two dominant energy scales, the Ising-type Kitaev coupling 𝐾 and the symmetric off-diagonal Γ coupling. An understanding of the interplay between these two scales is therefore the natural starting point toward a quantitative description that includes subdominant perturbations that are inevitably present in real materials. This study focuses on the classical 𝐾−Γ model on the honeycomb lattice, with a specific emphasis on the region 𝐾< 0 and Γ > 0 , which is the most relevant for the available materials and which remains enigmatic in both quantum and classical limits, despite much effort. We employ large-scale Monte Carlo simulations on specially designed finite-size clusters and unravel the presence of a complex multisublattice magnetic order in a wide region of the phase diagram, whose structure is characterized in detail. We show that this order can be quantified in terms of a coarse-grained scalar-chirality order, featuring a counterrotating modulation on the two spin sublattices. Here, we also provide a comparison to previous studies and discuss the impact of quantum fluctuations on the phase diagram.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Software Testing and Verification in Climate Model Development

Over the past 30 years most climate models have grown from relatively simple representations of a few atmospheric processes to a complex multi-disciplinary system. Computer infrastructure over that period has gone from punch card mainframes to modem parallel clusters. Model implementations have become complex, brittle, and increasingly difficult to extend and maintain. Existing verification processes for model implementations rely almost exclusively upon some combination of detailed analysis of output from full climate simulations and system-level regression tests. In additional to being quite costly in terms of developer time and computing resources, these testing methodologies are limited in terms of the types of defects that can be detected, isolated and diagnosed. Mitigating these weaknesses of coarse-grained testing with finer-grained "unit" tests has been perceived as cumbersome and counter-productive. In the commercial software sector, recent advances in tools and methodology have led to a renaissance for systematic fine-grained testing. We discuss the availability of analogous tools for scientific software and examine benefits that similar testing methodologies could bring to climate modeling software. We describe the unique challenges faced when testing complex numerical algorithms and suggest techniques to minimize and/or eliminate the difficulties.

Clune, Thomas L.↗

Effects of Mesoscale Eddies in the Active Mixed Layer: Test of the Parametrisation in Eddy Resolving Simulations

In eddy resolving simulations, we test a mixed layer mesoscale parametrisation, developed recently by Canuto and Dubovikov [Ocean Model., 2011, 39, 200-207]. With no adjustable parameters, the parametrisation yields the horizontal and vertical mesoscale fluxes in terms of coarse-resolution fields and eddy kinetic energy (EKE). We compare terms of the parametrisation diagnosed from coarse-grained fields with the eddy mesoscale fluxes diagnosed directly from the high resolution model. An expression for the EKE in terms of mean fields has also been found to get a closed parametrisation in terms of the mean fields only. In 40 numerical experiments we simulated two types of flows: idealised flows driven by baroclinic instabilities only, and more realistic flows, driven by wind and surface fluxes as well as by inflow-outflow. The diagnosed quasi-instantaneous horizontal and vertical mesoscale buoyancy fluxes (averaged over 1-2 degrees and 10 days) demonstrate a strong scatter typical for turbulent flows, however, the fluxes are positively correlated with the parametrisation with higher (0.5-0.74) correlations at the experiments with larger baroclinic radius Rossby. After being averaged over 3-4 months, diffusivities diagnosed from the eddy resolving simulations are consistent with the parametrisation for a broad range of parameters. Diagnosed vertical mesoscale fluxes restratify mixed layer and are in a good agreement with the parametrisation unless vertical turbulent mixing in the upper layer becomes strong enough in comparison with mesoscale advection. In the latter case, numerical simulations demonstrate that the deviation of the fluxes from the parametrisation is controlled by dimensionless parameter estimating the ratio of vertical turbulent mixing term to mesoscale advection. An analysis using a modified omega-equation reveals that the effects of the vertical mixing of vorticity is responsible for the two-three fold amplification of vertical mesoscale flux. Possible physical mechanisms, responsible for the amplification of vertical mesoscale flux are discussed.

simulation↗

An adaptive, data-driven multiscale approach for dense granular flows

The accuracy of coarse-grained continuum models of dense granular flows is limited by the lack of high-fidelity closure models for granular rheology. One approach to addressing this issue, referred to as the hierarchical multiscale method, is to use a high-fidelity fine-grained model to compute the closure terms needed by the coarse-grained model. The difficulty with this approach is that the overall model can become computationally intractable due to the high computational cost of the high-fidelity model. In this work, we describe a multiscale modeling approach for dense granular flows that utilizes neural networks trained using high-fidelity discrete element method (DEM) simulations to approximate the constitutive granular rheology for a continuum incompressible flow model. Our approach leverages an ensemble of neural networks to estimate predictive uncertainty that allows us to determine whether the rheology at a given point is accurately represented by the neural network model. Additional DEM simulations are only performed when needed, minimizing the number of additional DEM simulations required when updating the rheology. This adaptive coupling significantly reduces the overall computational cost of the approach while controlling the error. In addition, the neural networks are customized to learn regularized rheological behavior to ensure well-posedness of the continuum solution. We first validate the approach using two-dimensional steady-state and decelerating inclined flows. We then demonstrate the efficiency of our approach by modeling three-dimensional sub-aerial granular column collapse for varying initial column aspect ratios, where our multiscale method compares well with the computationally expensive computational fluid dynamics (CFD)-DEM simulation.

Dense granular flows↗

VOTCA: multiscale frameworks for quantum and classical simulations in soft matter

Many physical phenomena in liquids and soft matter are multiscale by nature and can involve processes with quantum and classical degrees of freedom occurring over a vast range of length- and timescales. Examples range from structure formation processes of complex polymers or even polymer blends (Svaneborg & Everaers, 2023) on the classical side to charge and energy transport and conversion processes (Lee et al., 2019) involving explicit electronic and, therefore, quantum information. The Versatile Object-oriented Toolkit for Coarse-graining Applications (VOTCA) provides multiscale frameworks built on a comprehensive set of methods for the development of classical coarse-grained potentials (VOTCA-CSG) as well as state-of-the art excited state electronic structure methods based on density-functional and many-body Green’s function theories, coupled in mixed quantum-classical models and used in kinetic network models (VOTCA-XTP).

97 MATHEMATICS AND COMPUTING↗

Quantum real-time evolution using tensor renormalization group methods

We introduce an approach for approximate real-time evolution of quantum systems using tensor renormalization group (TRG) methods originally developed for imaginary time. We use higher-order TRG to generate a coarse-grained time evolution operator for a 1+1⁢D transverse Ising model with a longitudinal field. We show that the standard tensor norm used for the singular value decomposition-based truncation is degenerate and propose an alternate method to discriminate. We show that it is effective and efficient in evolving Gaussian wave packets for one and two particles in the disordered phase, while ordered phase behavior is more challenging to capture. We compare our algorithm with local simulators for universal quantum computers and discuss possible benchmarking in the near future.

lattice gauge theory↗

Can classical DEM simultaneously capture compressibility and flowability of milled biomass?

Accurate prediction of the rheological behavior of biomass is essential for the design and operation of hoppers, feeders, and storage systems in biorefineries. This study examines whether the classical, coarse-grained discrete element method (DEM) formulation can simultaneously reproduce the compressibility and flowability of milled herbaceous biomass, using Miscanthus × giganteus as a representative material. The model represents particles as rigid spheres interacting through Hertz-Mindlin elastic-frictional contacts augmented with an area-dependent cohesion term. Laboratory cyclic compression and wedge-shaped hopper discharge experiments were used as calibration benchmarks. Although the model can independently reproduce each behavior by appropriately tuning particle Young's modulus E and cohesion energy density k, an extensive parametric investigation comprising more than 600 simulations reveals that the optimal parameter regions for compression and hopper flow are distinct and non-overlapping in (E, k) space. Surrogate surface analysis further shows that the corresponding objective-function valleys exhibit similar trends but are approximately parallel and spatially offset, precluding a unified calibration within the explored domain. Sensitivity analysis indicates that compressibility is governed predominantly by stiffness and cohesion, whereas the slope of the mass flow rate-opening relation in hopper discharge is primarily controlled by tangential friction. Extensions incorporating particle size distribution and clumped-sphere representations do not eliminate the incompatibility. These results systematically reveal, for the first time, the structural limitation of simplified DEM formulations in representing biomass rheological behavior, underscoring the necessity for models incorporating additional physical mechanisms, such as particle deformability or enhanced interlocking, to achieve unified predictive capability for biomass handling behavior.

09 BIOMASS FUELS↗

Data-driven modeling of dislocation mobility from atomistics using physics-informed machine learning

Dislocation mobility, which dictates the response of dislocations to an applied stress, is a fundamental property of crystalline materials that governs the evolution of plastic deformation. Traditional approaches for deriving mobility laws rely on phenomenological models of the underlying physics, whose free parameters are in turn fitted to a small number of intuition-driven atomic scale simulations under varying conditions of temperature and stress. This tedious and time-consuming approach becomes particularly cumbersome for materials with complex dependencies on stress, temperature, and local environment, such as body-centered cubic crystals (BCC) metals and alloys. In this paper, we present a novel, uncertainty quantification-driven active learning paradigm for learning dislocation mobility laws from automated high-throughput large-scale molecular dynamics simulations, using Graph Neural Networks (GNN) with a physics-informed architecture. We demonstrate that this Physics-informed Graph Neural Network (PI-GNN) framework captures the underlying physics more accurately compared to existing phenomenological mobility laws in BCC metals.

36 MATERIALS SCIENCE↗

An Assessment of the Axial and Radial Dilation of a DPIMS Tantalum Cartridge for Space Shuttle Flight Experiments

Ground-based heat treatment tests are planned on an argon gas-filled tantalum cartridge developed as pan of a Diffusion Processes in Molten Semiconductors (DPIMS) experiment conducted on NASA's Space Shuttle. The possibility that the cartridge may creep during testing and touch the furnace walls is of real concern in this program. The present paper discusses the results of calculations performed to evaluate this possibility. Deformation mechanism maps were constructed using literature data in order to identify the creep mechanism dominant under the appropriate stresses and temperatures corresponding to the test conditions. These results showed that power-law creep was dominant when the grain size of the material exceeded 55 gm but Coble creep was the important mechanism below this value of grain size. Finite element analysis was used to analyze the heat treatment tWs assuming a furnace run away condition (which is a worst case scenario) using the appropriate creep parameters corresponding to grain sizes of 1 and 100 gm. Calculations were also conducted to simulate the effect of an initial 3 tilt of the cartridge assembly, the maximum possible tilt angle. The von Mises stress and su-ain distributions were calculated assuming that the cartridge was fixed at one end as it was heated from ambient temperature to 1823 K in 1.42 h, maintained at 1823 K for 9.5 h and then further heated to an over temperature condition of 2028 K in 0.3 h. The inelastic axial and radial displacements of the cartridge walls were evaluated by resolving the von Mises strain along the corresponding directions. These calculations reveal that the maximum axial and radial displacements are expected to be about 2.9 and 0.25 mm, respectively, for both fine and coarse-grained materials at 2028 K. It was determined that these displacements occur during heat-up to temperature and creep of the cartridge is likely to be relatively insignificant irrespective of grain size. Furthermore, with a 3' tilt of the cartridge, the deflection is increased by only 0.39 gm which is negligible. Since the gap between the furnace heating elements and the cartridge is about 7.5 mm and less than the maximum radial dilation of 0.25 mm at 2028 K, it is concluded that the cartridge is unlikely to touch the furnace walls during the experiments.

Raj, S.V.↗

Radiation breakage of DNA: a model based on random-walk chromatin structure

Monte Carlo computer software, called DNAbreak, has recently been developed to analyze observed non-random clustering of DNA double strand breaks in chromatin after exposure to densely ionizing radiation. The software models coarse-grained configurations of chromatin and radiation tracks, small-scale details being suppressed in order to obtain statistical results for larger scales, up to the size of a whole chromosome. We here give an analytic counterpart of the numerical model, useful for benchmarks, for elucidating the numerical results, for analyzing the assumptions of a more general but less mechanistic "randomly-located-clusters" formalism, and, potentially, for speeding up the calculations. The equations characterize multi-track DNA fragment-size distributions in terms of one-track action; an important step in extrapolating high-dose laboratory results to the much lower doses of main interest in environmental or occupational risk estimation. The approach can utilize the experimental information on DNA fragment-size distributions to draw inferences about large-scale chromatin geometry during cell-cycle interphase.

Chromatin/radiation effects↗

Optical and TEM study of shock metamorphism from the Sedan test site

Thus far, detailed petrologic studies of shock metamorphism have been performed on samples recovered from laboratory experiments and on a few natural impactites. The loading history of these samples is quite different: In particular, laboratory experiments spend only a short time (less than 1 microsec) at peak pressure, whereas natural impactites may have stress pulses from 0.1 - 1 ms. On the other hand, laboratory experiments have known stress histories; natural impactites do not. Natural samples are also subjected to thousands or millions of years of postshock annealing and/or weathering. A useful intermediate case is that of nuclear detonation. Stress pulses for these events can reach 0.1 ms or higher, and samples are obtained in pristine condition. All three types of loading produce stresses of hundreds of kilobars. Samples studied were taken from the Sedan nulcear test site, and consist of a coarse-grained granodiorite containing quartz, K-feldspar, cordierite, and hornblende. Samples were studied optically in this section, then were thinned with an ion mill and studied by transmission electron microscopy (TEM). Optically, quartz and K-feldspar displayed numerous sets of planar deformation features (PDF's) identical to the nondecorated PDF's seen in laboratory samples and many natural impactites. TEM study showed that the PDF's in quartz and feldspar corresponded to densely packed wide transformation lamellae identical to those described in laboratory studies. The transformation lamellae in both minerals were amorphous, with no sign of high-pressure phases. In the case of K-feldspar only, narrow sublamellae extended outward from some wide lamellae. Quartz, which was more abundant and studied more extensively, contained no shock-induced dislocations. Some planar features were also seen in cordierite, but could not be identified due to rapid beam damage. No shock defects were seen in hornblende in TEM. The shock-induced defects present at the Sedan site are very similar to those seen in shock recovery experiments, and also to those present at certain natural events (e.g., Meteor Crater). This suggests that shock deformation in quartz is not strongly dependent on shock pulse duration, and that laboratory recovery experiments are useful simulations of natural impact events.

Gratz, A. J.↗

Lunar resources: Oxygen from rocks and soil

The first set of hydrogen reduction experiments to use actual lunar material was recently completed. The sample, 70035, is a coarse-grained vesicular basalt containing 18.46 wt. percent FeO and 12.97 wt. percent TiO2. The mineralogy includes pyroxene, ilmenite, plagioclase, and minor olivine. The sample was crushed to a grain size of less than 500 microns. The crushed basalt was reduced with hydrogen in seven tests at temperatures of 900-1050 C and pressures of 1-10 atm for 30-60 minutes. A capacitance probe, measuring the dew point of the gas stream, was used to follow reaction progress. Experiments were also conducted using a terrestrial basalt similar to some lunar mare samples. Minnesota Lunar Simulant (MLS-1) contains 13.29 wt. percent FeO, 2.96 wt. percent Fe2O3, and 6.56 wt. percent TiO2. The major minerals include plagioclase, pyroxene, olivine, ilmenite, and magnetite. The rock was ground and seived, and experiments were run on the less than 74- and 500-1168-micron fractions. Experiments were also conducted on less than 74-micron powders of olivine, pyroxene, synthetic ilmenite, and TiO2. The terrestrial rock and mineral samples were reduced with flowing hydrogen at 1100 C in a microbalance furnace, with reaction progress monitored by weight loss. Experiments were run at atmospheric pressure for durations of 3-4 hr. Solid samples from both sets of experiments were analyzed by Mossbauer spectroscopy, petrographic microscopy, scanning electron microscopy, tunneling electron microscopy, and x-ray diffraction. Apollo 17 soil 78221 was examined for evidence of natural reduction in the lunar environment. This sample was chosen based on its high maturity level (I sub s/FeO = 93.0). The FeO content is 11.68 wt. percent and the TiO2 content is 3.84 wt. percent. A polished thin section of the 90-150 micron size fraction was analyzed by petrographic microscopy and scanning electron microscopy.

Allen, C. C.↗