Search NASA⌕ Search

SEARCH · Search NASA

Results for “Structural simulation”

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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Computing virtual dark-field X-ray microscopy images of complex discrete dislocation structures from large-scale molecular dynamics simulations

Dark-field X-ray microscopy (DFXM) is a novel diffraction-based imaging technique that non-destructively maps the local deformation from crystalline defects in bulk materials. While studies have demonstrated that DFXM can spatially map 3D defect geometries, it is still challenging to interpret DFXM images of the high-dislocation-density systems relevant to macroscopic crystal plasticity. This work develops a scalable forward model to calculate virtual DFXM images for complex discrete dislocation structure(s) (DDS) obtained from atomistic simulations. Our new DDS-DFXM model integrates a non-singular formulation for calculating the local strain from the DDS and an efficient geometrical optics algorithm for computing the DFXM image from the strain field. We apply the model to complex DDS obtained from a large-scale mol­ecular dynamics simulation of compressive loading on single-crystal silicon. Simulated DFXM images exhibit prominent contrast for dislocation features between the multiple slip systems, demonstrating the potential of DFXM to resolve features from dislocation multiplication. In conclusion, the integrated DDS-DFXM model provides a toolbox for DFXM experimental design and image interpretation in the context of bulk crystal plasticity for a range of measurements across shock plasticity and the broader materials science community.

X-ray imaging↗
DOE OSTI2018

Structure–Property of Lithium–Sulfur Nanoparticles via Molecular Dynamics Simulation

Lithium-sulfur (Li-S) batteries offer higher energy densities than most reported lithium-ion batteries. However, our understanding of Li-S battery is still largely unknown at the level of the nanoscale. Here, the structural properties of Li-S materials were investigated via molecular dynamics (MD) simulations using the ReaxFF force field. everal Li-S nanoparticles with different Li:S composition ratios (2:1 and 2:8) and various structures are studied. Our MD simulations show that, among the four structures we constructed for Li 2 S 8 nanoparticles, the core-shell structure is the most thermodynamically stable one during the charging (delithiation) process. In contrast to bulk crystal Li 2 S, we find the presence of mixed lithium sulfide and polysulfide species are common features for these Li-S (Li 2 S, Li 2 S 8 ) nanoparticles. The complex distribution of these sulfide and polysulfide speciation are dictated by both stoichiometry and local atomic structures in the nanoparticle. Finally, these findings will provide insight into further development of functionalized lithium-sulfur cathodes.

25 ENERGY STORAGE↗
DOE OSTI2019

The Outer Rim Simulation: A Path to Many-core Supercomputers

Herein we describe the Outer Rim cosmological simulation, one of the largest high-resolution N-body simulations performed to date, aimed at promoting science to be carried out with large-scale structure surveys. The simulation covers a volume of (4.225 Gpc) 3 and evolves more than one trillion particles. It was executed on Mira, a BlueGene/Q system at the Argonne Leadership Computing Facility. We discuss some of the computational challenges posed by a system such as Mira, a many-core supercomputer, and how the simulation code, Hardware/Hybrid Accelerated Cosmology Code, has been designed to overcome these challenges. We have carried out a large range of analyses on the simulation data and we report on the results as well as the data products that have been generated. The full data set generated by the simulation totals more than 5 PB of data, making curation and handling of the data a large challenge in itself. The simulation results have been used to generate synthetic catalogs for large-scale structure surveys, including Dark Energy Spectroscopic Instrument and eBOSS, as well as experiments on the cosmic microwave background. A detailed catalog for the data challenges of the Large Synoptic Survey Telescope Dark Energy Science Collaboration has been created as well. We publicly release some of the Outer Rim halo catalogs, downsampled particle information, and lightcone data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Short-Range Order Tunes Optical Properties in Long-Range Disordered ZnSnN2-ZnO Alloy

Local site ordering offers a new paradigm for property control in functional materials. However, systems that exhibit a propensity for local order and global disorder are often challenging to characterize, and demonstrations of ordering-induced property tuning are few and far between. Here, we demonstrate that short-range ordering tunes the optical absorption edge in the long-range disordered alloy system (ZnSnN2)1-x(ZnO)2x at x = 0.25. We use combinatorial cosputtering to synthesize a set of thin-film samples spanning this alloy space. X-ray diffraction demonstrates lattice contraction as a function of alloy composition, confirming that a mixed-anion and -cation alloy has been synthesized. Using N and O K-edge X-ray absorption near-edge structure in conjunction with simulations of cation-disordered supercell structures, we find that samples exhibit octet-rule-breaking motifs around both anions. Upon annealing at an alloy composition of x = 0.25, X-ray absorption analysis suggests that local motif structure shifts toward octet-rule-conserving while long-range disorder is maintained. Spectroscopic ellipsometry reveals that local ordering increases the absorption edge energy at constant composition. Additionally, alloy-induced optical absorption edge tuning is demonstrated. This work paves the way toward property tuning with short-range ordering in (ZnSnN2)1-x(ZnO)2x and beyond.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Phase field modeling of recrystallization phenomena

In this work, we studied the recrystallization phenomena in copper using phase field modeling technique. EBSD information is successfully translated on to MOOSE and quantitative phase field simulations for Copper are performed on MOOSE. DREAM 3D software is utilized to transform EBSD data into a format which is then used to conduct phase field simulations, with initial grain structure obtained from EBSD data. Several simulations are performed and a comparison is made against various cases: isotropic grain growth without any deformed grains, deformed grains with constant dislocation density, and deformed grains with orientation dependent dislocation density.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Coupling of Charge Regulation and Geometry in Soft Ionizable Molecular Assemblies

The size, shape, and charge of structures, such as proteins and amphiphile assemblies, respond in an interconnected manner to solution ionic conditions. Here, we analyze assemblies of an amphiphile (C 16 K 2 ), with two ionizable amino acids [lysine (K)] coupled to a 16-carbon alkyl tail, via small-angle X-ray scattering (SAXS), nonlinear Poisson–Boltzmann theory (nl-PB), and hybrid Monte Carlo-molecular dynamics (MC-MD) simulations. SAXS revealed structural transitions from spherical micelles to cylindrical micelles to bilayers with increasing pH. By combining SAXS-determined structural information and nl-PB, we derived the molecular degree of ionization as a function of pH. The back-calculated titration curves matched the experimental data over an extended pH range, without adjustable parameters. Similarly, the SAXS data on the evolution of spherical micelle structure with ionic strength were combined with nl-PB and MC-MD to derive the bare and effective charges. MC-MD, which considered finite ion sizes, showed that bare and effective charges saturate quickly with increasing salt concentration. Furthermore, the calculated effective charges closely matched results from Zeta-potential measurements. The presented approach has advantages over customary methods for charge regulation, such as the Henderson–Hasselbalch (HH) or Hill models, where molecular ionization/deionization in assemblies is described by effective pKs that are distinct from the pK for isolated molecules. However, these models lack a physical explanation for these pK shifts. By contrast, our approach of combining structural details with an electrostatic model and simulations provides a more intuitive understanding of structure-charge coupling and a framework for understanding charge regulation in many synthetic and biological systems.

ionization↗
DOE OSTI2023

Solution Structure and Scaling Laws of Cylindrical and Tapered Bottlebrush Polymers

Bottlebrush polymers are a unique class of macromolecular architectures with a plethora of potential industrial and pharmaceutical applications that critically depend on the bottlebrush shape and dimensions. Here, a systematic series of 12 cylindrical and 12 cone-shaped (tapered) bottlebrush polymers with poly(tert-butyl acrylate) (PtBA) or polystyrene (PS) side chains were synthesized using the sequential addition of macromonomers ring-opening metathesis polymerization (SAM-ROMP) grafting-through method. Small-angle neutron scattering (SANS) studies on dilute solutions of the two types of bottlebrush polymers provided noninvasive characterization of their structural dimensions and chain conformations. Simulated SANS traces, generated using coarse-grained molecular dynamics simulations, reproduced the distinctive features observed in the experimental SANS signals and provided necessary validation for data modeling. The combined analysis of experimental and simulated SANS signals yielded key structural and conformational parameters, including the bottlebrush radius, length, and Kuhn length as well as the excluded volume parameter and the correlation length of the polymer side chains. Importantly, the obtained structural parameters followed well-defined scaling laws as a function of the backbone and side chain degrees of polymerization, as predicted by mean field theories. In conclusion, these findings provide clear experimental and computational evidence of the interdependence of structural and conformational properties in an important class of polymer architectures.

36 MATERIALS SCIENCE↗
DOE OSTI2024

DECA: Discrete Event inspired Cellular Automata for grain structure prediction in additive manufacturing

Microstructure largely dictates macroscopic material properties and is strongly affected by processing. Therefore, the simulation of microstructure evolution in response to thermal fields during processing is of significant interest within the computational materials science community. Additive manufacturing (AM) has emerged as a technique for producing complex geometries and unique microstructures. Yet, complex and rapid thermal cycles in AM pose computational challenges for existing microstructure models. This work proposes a discrete event inspired cellular automata (CA) approach, titled DECA, to accelerate simulation of grain structure evolution in AM. In contrast to conventional time-stepped CA models, this model directly solves the times capture events would take place allowing for stepping in events rather than time (a technique also found in the field of discrete-event simulation). In comparison to purely serial discrete-event models, DECA allows for temporary violation of the causality constraint, but detects and corrects these violations, leading to an emergent phenomenon dubbed causality rippling, in which previously calculated capture events are overwritten. The amount of repeated calculations, defined by the capture ratio, is taken as a measure of computational inefficiency, and the model parameters that affect this ratio are evaluated. The new DECA approach was found to be more computationally efficient than conventional time-stepped CA models while guaranteeing an accurate solution, which can only be achieved in the conventional models for vanishingly small time steps. Finally, opportunities for parallelization and scaling of the new approach are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Assessment of Airfoil Property Sensitivity on Wind Turbine Extreme and Fatigue Loads: Preprint

Wind turbines are designed using a set of simulations to determine the structural loads that the turbine could experience. These structural loads can be significant influenced by physical turbine parameters. While significant research and effort has been put into measuring and defining such parameters, limited work has been done to quantify the sensitivity of structural loads to uncertainty in the physical turbine parameters. This paper therefore seeks to assess the sensitivity of different turbine aerodynamic parameters on the resulting ultimate and fatigue loads of the turbine during normal operational conditions. Eighteen different turbine parameters are screened using an Elementary Effects approach with radial points. The results show a high sensitivity of the loads to the blade twist and lift coefficient distributions. To a lesser extent, other turbine parameters that drive loads include the maximum lift coefficient location, blade chord length, and drag coefficient distributions.

17 WIND ENERGY↗
DOE OSTI2024

Molecular simulation using transfer-learned potentials for the disordered nanoscale structure of nitrogen-doped nanoporous carbons

Machine learning (ML)-based molecular dynamics (MD) simulations of the formation of a class of N-doped nanoporous carbons are performed to assess their disordered partially graphitized nanoscale structure. The study is motivated by the effectiveness of so-called nitrogen assembly carbons (NACs) for catalysis applications. Benchmark simulations for pure-C disordered graphitic systems reveal the importance of reliably capturing the vdW component of the potentials in order to accurately describe the tendency for layering of disordered graphene-like sheets. In our modeling, this is achieved by a transfer learning strategy incorporating features of the energetics from the optB88-vdW DFT functional into potentials initially trained with a less expensive functional, thereby providing a superior description of the pure-C systems. Generation from MD simulations of realistic partially graphitized structures is significantly more challenging for N-doped versus for pure C systems. However, such structures are achieved by a tailored MD simulation protocol mimicking the experimental synthesis process and in particular incorporating an annealing and subsequent quenching stages. Simulated PXRD patterns effectively reproduce the features of experimental observations for NACs, including the appearance of a prominent but broad (002) peak at around 25, and the development of another weaker feature associated with in-layer ordering of mixed C-N graphene-like sheets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Molecular Structure and Electron Affinity of Metal-Solvent Complexes: Insights from Density Functional Theory Simulations

A molecular level understanding of the structure and energetics of the monovalent and divalent metal ion complexes is of great importance for development of next-generation batteries. Here, Density Functional Theory (DFT) simulations at the ωb97xD/6-31 + G(d,p) level of theory are performed to investigate the interaction of metal ions (Li + , Na + , K + , Mg 2+ , Ca 2+ , Zn 2+ ) with 26 organic solvent molecules. The reduction energetics (electron affinity and reduction potential) and structural responses of the solvent molecules and the molecular complexes are discussed. The DFT calculations are carried out to investigate the structure, energetics and electron affinities of chelated complexes of water (H 2 O), tetrahydrofuran (THF) and di-methoxy ethane (DME) solvent molecules. Additionally, ab initio dynamic simulations (AIMD) at 298 K using atom centered density matrix propagation (ADMP) formalism are performed to understand the spontaneous structure formation upon electron attachment of the metal ion-solvent complexes. The ADMP simulations indicate the decomposition of Mg + -(DME) 3 complex via cleavage of C–O bond of one of the three DME molecules indicating irreversible decomposition of DME in the presence of the Mg + radical. We believe that the data collected as part of this investigation serves as a library of fundamental knowledge towards a deeper understanding of the electrode-electrolyte interfacial reactions.

25 ENERGY STORAGE↗