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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.

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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

ezAlign: A Tool for Converting Coarse-Grained Molecular Dynamics Structures to Atomistic Resolution for Multiscale Modeling

Soft condensed matter is challenging to study due to the vast time and length scales that are necessary to accurately represent complex systems and capture their underlying physics. Multiscale simulations are necessary to study processes that have disparate time and/or length scales, which abound throughout biology and other complex systems. Herein we present ezAlign, an open-source software for converting coarse-grained molecular dynamics structures to atomistic representation, allowing multiscale modeling of biomolecular systems. The ezAlign v1.1 software package is publicly available for download at github.com/LLNL/ezAlign. Its underlying methodology is based on a simple alignment of an atomistic template molecule, followed by position-restraint energy minimization, which forces the atomistic molecule to adopt a conformation consistent with the coarse-grained molecule. The molecules are then combined, solvated, minimized, and equilibrated with position restraints. Validation of the process was conducted on a pure POPC membrane and compared with other popular methods to construct atomistic membranes. Additional examples, including surfactant self-assembly, membrane proteins, and more complex bacterial and human plasma membrane models, are also presented. By providing these examples, parameter files, code, and an easy-to-follow recipe to add new molecules, this work will aid future multiscale modeling efforts.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

A coarse-grained model of clay colloidal aggregation and consolidation with explicit representation of the electrical double layer

The aggregation of clay minerals in liquid water exemplifies colloidal self-assembly in nature. These negatively charged aluminosilicate platelets interact through multiple mechanisms with different sensitivities to particle shape, surface charge, aqueous chemistry, and interparticle distance and exhibit complex aggregation structures. Experiments have difficulty resolving the associated colloidal assemblages at the scale of individual particles. Conversely, all-atom molecular dynamics (MD) simulations provide detailed insight on clay colloidal interaction mechanisms, but they are limited to systems containing a few particles. We develop a new coarse-grained (CG) model capable of representing assemblages of hundreds of clay particles with accuracy approaching that of MD simulations, at a fraction of the computational cost. Our CG model is parameterized based on MD simulations of a pair of smectite clay particles in liquid water. A distinctive feature of our model is that it explicitly represents the electrical double layer (EDL), i.e., the cloud of charge-compensating cations that surrounds the clay particles. Our model captures the simultaneous importance of long-range colloidal interactions (i.e., interactions consistent with simplified analytical models, already included in extant clay CG models) and short-range interactions such as ion correlation and surface and ion hydration effects. The resulting simulations correctly predict, at low solid-water ratios, the existence of ordered arrangements of parallel particles separated by water films with a thickness up to ~10 nm and, at high solid-water ratios, the coexistence of crystalline and osmotic swelling states, in agreement with experimental observations.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2003

Versatile Turbine Disk Alloy Designed and Processed for Higher Temperature Applications

Advanced turbine engine configurations using higher temperature combustor and airfoil concepts require compressor and turbine disks that can withstand temperatures higher than the 650 C typical of current engines. This requires disk alloy and processing improvements. A versatile disk alloy was needed that could be given either fine grain heat treatments for high strength and fatigue and creep resistance up to 704 C or given coarse grain heat treatments for high strength and creep and dwell crack-growth resistance at higher temperatures. This alloy could produce disks with uniform microstructures and properties, as well as with varied, optimized microstructures at disk bore and rim sections. A series of experimental disk alloys were designed and processed to give subscale disks about 13 cm in diameter and 4 cm thick. These alloys had varying levels of key elements to affect mechanical properties and change the "solvus" solution heat-treatment temperature necessary to produce coarse grain microstructures. Disks were given coarse grain heat treatments followed by rapid oil quenching and slower fan air quenching. These heat treatments were intended to simulate the cooling paths of rapidly cooled full-scale disks at the outermost rim and interior bore locations, respectively. Preliminary quench tests of tensile specimens and coin-size minidisks had indicated that alloys having high solvus temperatures were more prone to cracking during rapid quenching from coarse grain heat treatments. These findings were confirmed in the subscale disks, where such alloys did form undesirable quench cracks. Mechanical tests were performed on specimens from subscale disks given these coarse grain heat treatments, as well as on specimens given a fine grain heat treatment. Tensile, creep, and crack growth tests were performed at 704 C and higher temperatures. A versatile alloy was identified that had a low solvus temperature for resistance to quench cracking as well as an optimal combination of high levels of strengthening refractory elements that produced balanced high mechanical properties for both fine grain and coarse grain microstructures. This low-solvus, high-refractory (LSHR) alloy has been scaled-up to produce prototype full-scale turbine disks typical of regional jet turbofan engines. Disks were successfully heat treated to give uniform coarse grain and uniform fine grain microstructures. Additional disks were given a NASA dual microstructure heat treatment (DMHT) that intentionally varied the solution heat-treatment temperatures between the disk rim and bore (re f. 1). The disk rim was heated to a high enough temperature to produce a coarse grain microstructure, while the bore was maintained at a lower temperature to produce a fine grain microstructure (see the figure). This DMHT can produce optimal high strength, fatigue, and creep resistance up to 704 C in the cooler running disk bore, and high strength, creep resistance, and dwell crack growth resistance at higher temperatures for the hotter disk rim. Extensive mechanical testing is being initiated to compare the mechanical properties of the uniform and DMHT disks.

Gabb, TImothy P.↗
DOE OSTI2024

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↗
DOE OSTI2025

Advancing material modeling in hydrocodes using a concurrent finite-element and molecular dynamics multiscale framework

We present a multiscale simulation framework that couples the finite-element method with molecular dynamics. Bypassing traditional equations of state (EOS) by using in-line atomistic simulations, the method offers the advantage of incorporating detailed microscale physics not easily represented with coarse-grained models. Coupling consistency with the continuum code is ensured through the use of lifting and restriction operators, in line with heterogeneous multiscale methods. The concurrent continuum-atomistic framework is validated through comparison with experimental results and conventional EOS models, and demonstrated in a shock-driven hydrodynamic flow simulation under extreme conditions. We further evaluate the framework's usability by comparing it to state-of-the-art EOS models of deuterium. A computational performance study reveals that the atomistic EOS evaluation is a feasible alternative to conventional approaches, and demonstrates a weak scaling of 99% efficiency. These results highlight the framework's potential for large-scale multiscale modeling across a broad range of materials and conditions.

Computer science↗
DOE OSTI2024

Development of a coarse-grained molecular dynamics model for poly(dimethyl- co -diphenyl)siloxane

Polydimethylsiloxane is an important polymeric material with a wide range of applications. However, environmental effects like low temperature can induce crystallization in this material with resulting changes in its structural and dynamic properties. The incorporation of phenyl-siloxane components, e.g., as in a poly(dimethyl-co-diphenyl)siloxane random copolymer, is known to suppress such crystallization. Molecular dynamics (MD) simulations can be a powerful tool to understand such effects in atomistic detail. Unfortunately, all-atomistic molecular dynamics (AAMD) is limited in both spatial dimensions and simulation times it can probe. Here, to overcome such constraints and to extend to more useful length- and time-scales, we systematically develop a coarse-grained molecular dynamics (CGMD) model for the poly(dimethyl-co-diphenyl)siloxane system with bonded and non-bonded interactions determined from all-atomistic simulations by the iterative Boltzmann inversion (IBI) method. Additionally, we propose a lever rule that can be useful to generate non-bonded potentials for such systems without reference to the all-atomistic ground truth. Our model captures the structural and dynamic properties of the copolymer material with quantitative accuracy and is useful to study long-time dynamics of highly-entangled systems, sequence-dependent properties, phase behaviour, etc.

36 MATERIALS SCIENCE↗
NASA NTRS2013

Coarse-Grain Bandwidth Estimation Techniques for Large-Scale Space Network

In this paper, we describe a top-down analysis and simulation approach to size the bandwidths of a store-andforward network for a given network topology, a mission traffic scenario, and a set of data types with different latency requirements. We use these techniques to estimate the wide area network (WAN) bandwidths of the ground links for different architecture options of the proposed Integrated Space Communication and Navigation (SCaN) Network.

Cheung, Kar-Ming↗
DOE OSTI2025

Equation-Free Coarse Control of Distributed Parameter Systems via Local Neural Operators

The control of high-dimensional distributed parameter systems (DPS) remains a challenge when explicit coarse-grained equations are unavailable. Classical equation-free (EF) approaches rely on fine-scale simulators treated as black-box timesteppers. However, repeated simulations for steady-state computation, linearization, and control design are often computationally prohibitive, or the microscopic timestepper may not even be available, leaving us with data as the only resource. We propose a data-driven alternative that uses local neural operators, trained on spatiotemporal microscopic/mesoscopic data, to obtain efficient short-time solution operators. These surrogates are employed within Krylov subspace methods to compute coarse steady and unsteady-states, while also providing Jacobian information in a matrix-free manner. Krylov-Arnoldi iterations then approximate the dominant eigenspectrum, yielding reduced models that capture the open-loop slow dynamics without explicit Jacobian assembly. Both discrete-time Linear Quadratic Regulator (dLQR) and pole-placement (PP) controllers are based on this reduced system and lifted back to the full nonlinear dynamics, thereby closing the feedback loop.

93B52, 93C20, 47N70, 65J15, 65M32, 68T07, 68T20, 6↗
DOE OSTI2025

Onset of cavitation and vapor bubble development over hydrophilic and hydrophobic surfaces

Cavitation, the formation of vapor bubbles as the liquid pressure is reduced below the saturated vapor pressure, often requires a substantial negative relative pressure in a pure liquid. Classical nucleation theory (CNT) provides an estimate for the rate of cavitation but there is often a disconnect between the predictions at the molecular scale compared to observations at the macroscale. We report on mesoscale simulations of cavitation based on many-body dissipative particle dynamics (mDPD), a coarse-grained molecular dynamics (MD), which bridges the two scales. A liquid layer is confined between smooth planar walls at a constant temperature, while the pressure is reduced slowly by expanding the wall-bounded domain. The wetting properties of the liquid are determined by the parameters of the interaction potentials. With hydrophilic walls, homogeneous nucleation is observed in the liquid bulk. As a bubble forms and grows, it creates a strong pressure pulse and oscillations that cause other bubbles that may have formed slightly later to collapse. For a nearly neutral wall with a contact angle close to 90 ° , heterogeneous nucleation occurs at the walls at a smaller negative pressure and generates weaker pressure oscillations. With hydrophobic walls or seed particles, heterogeneous nucleation readily occurs, where fluctuations and the merger of transient surface bubbles are significant.

Science & Technology - Other Topics↗
DOE OSTI2025

Coarse Graining Discrete Element Method Information in Particle-in-Cell Length Scales Using a Machine Learning Approach

This report details the development of a machine learning (ML)-driven framework to coarse-grain inter-particle collision dynamics from high-fidelity Discrete Element Method (DEM) simulations to Particle-in-Cell (PIC) scales for gas-solid systems. Traditional PIC models, while computationally efficient, rely on empirical granular stress formulations that fail to capture the full complexity of collision physics, particularly the heterogeneity in particle dynamics. This study adopts a bottom-up approach, integrating insights from DEM simulations to improve the physical fidelity and interpretability of PIC-scale models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Molecular dynamics study of hydrogen Cottrell atmosphere in aluminum: Influence of solute-solute interactions in the dislocation core

Cottrell atmospheres form when solute atoms segregate to dislocations, and is one of the most basic processes by which solutes alter mechanical properties of materials. In the case of hydrogen, Cottrell atmospheres are believed to contribute to hydrogen embrittlement. Here, in this study, we use direct molecular dynamics simulations to study the formation of hydrogen Cottrell atmospheres around edge dislocations in aluminum. Using coarse-graining techniques, we resolve the temporal and spatial evolution of the hydrogen concentration field. By comparing our results with theories of Cottrell atmosphere formation and thermodynamics, we show that a repulsive, concentration-dependent H-H interaction reduces the peak atmosphere concentration at the dislocation core. Furthermore, this interaction differs significantly from the H-H interaction that is experienced in the bulk away from a dislocation.

Aluminum↗
NASA NTRS1982

Origin of desert loess from some experimental observations

The aeolian attrition of angular quartz grains previously produced by weathering in deserts has been simulated, yielding abrasion products which show that both coarse and fine silt sizes are produced by this process. These results suggest that desert aeolian processes can produce loess, and it is speculated that while much of this material from many deserts has been deposited in the sea, the Chinese loess could have been produced in the Gobi desert. The finest of the particles produced by such attrition may serve as a source of silica for silcrete formation.

Whalley, W. B.↗
NASA NTRS2020

Molecular Simulations of Ultrafast Radiation Induced Melting at Metal-Semiconductor Interfaces

Understanding radiation induced ultrafast melting at material interfaces is essential in designing robust electronic devices for aviation/space applications and in laser machining. While it is difficult to achieve the spatial and temporal resolution required to quantify the phenomenon experimentally, simulations can provide the detailed mechanisms of the structural changes that happen during phase transition. In this work, we use molecular simulations to study the effect of radiation damage on silicon carbide (SiC) - tungsten (W) interfaces which is of interest in high power electronics. A multi-scale approach is involved wherein the reactions at the interfaces are quantified using ab-initio molecular dynamics (MD) simulations and classical MD simulations are employed to understand the structural and diffusional changes across the material interface. Finally, coarse-grained Lennard-Jones type models are used to study the larger scale mechanisms and structures obtained due to the induced damages. We show that the response of the material to radiation damage depends on factors such as energy of the incident radiation, thermal properties, and molecular structure of the material.

Ravichandran, Ashwin↗
DOE OSTI2026

Seamlessly joining length scales: From atomistic thermal graphs to anisotropic continuum conductivity

Thermal transport in complex solids is governed by local structure, defects, and anisotropy, yet most continuum models still rely on oversimplified and homogenized conductivities. Here, we bridge atomistic and continuum descriptions by building finite element (FE) models directly from the site-projected thermal conductivity (SPTC), an atomic-level decomposition of the Green–Kubo thermal conductivity. We introduce a toolkit, the “Simulator Collection for Atomic-to-Continuum Scales (SCACS)”, which uses a graph neural network to predict SPTC on large atomic structures, coarse-grains these fields into anisotropic conductivity tensors, and embeds them into the heat-flow FE equation with a customized, anisotropy-aware adaptive mesh refinement scheme. Applied to silicon nanostructures, the resulting FE models act as representative volume elements, reproduce bulk conductivities, and capture interfacial and defect-driven anisotropy while maintaining thermodynamic consistency. Additionally, SCACS predicts experimental conductance trends and fields. This work demonstrates a general route for transferring atomistic transport information into device-scale thermal simulations with physics-based approximations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Equipping Neural Network Surrogates with Uncertainty for Propagation in Physical Systems

Coarse-grained or filtered models typically rely on closure models to account for unresolved scales. For instance, large eddy simulation for modeling turbulent fluid flows explicitly resolves the largest scales, but requires modeling closure terms to account for the sub-filter scales. With the vast amount of data available from high-fidelity simulations, there are unique opportunities to leverage data-driven modeling techniques to formulate expressive and flexible closure models. Despite their flexibility, data-driven models struggle in domain shift settings, i.e. when deployed in configurations not captured in the training dataset. In particular, the efficacy of neural network surrogates is difficult to assess a priori due to the deterministic, point-estimate nature of predictions. In high-consequence applications, such models require reliable uncertainty estimates in the data-informed and out-of-distribution regimes. To quantify uncertainties in both regimes, we employ Bayesian neural networks which are able to capture both epistemic and aleatoric uncertainties. We will discuss challenges associated with the training and evaluation of these networks. Furthermore, we will discuss uncertainty embedding strategies to enable efficient sampling and propagation of uncertainty through high-fidelity simulations.

Bayesian neural networks↗
NASA NTRS1987

Simulations of transition and turbulence on the Navier-Stokes computer

The Navier-Stokes Computer (NSC) consists of multiple local memory parallel processors interconnected in a hypercube network. Efficient implementation of algorithms on the NSC thus requires the effective utilization of both the coarse and fine grain paralelism inherent in the architectural design. The basic approach to implementing an algorithm on the NSC is presented herein. The particular finite-difference algorithm considered was developed for performing transition and turbulence simulations by direct solution of the time-dependent incompressible Navier-Stokes equations. The suitability of this algorithm for performing simulations of the isotropic turbulence problem is verified from computations performed on a Cray 2. Projected timing results for the algorithm on the NSC itself are presented for both the isotropic turbulence and laminar turbulent transition problems.

Krist, S. E.↗
NASA NTRS2006

Development of Standardized Lunar Regolith Simulant Materials

Lunar exploration requires scientific and engineering studies using standardized testing procedures that ultimately support flight certification of technologies and hardware. It is necessary to anticipate the range of source materials and environmental constraints that are expected on the Moon and Mars, and to evaluate in-situ resource utilization (ISRU) coupled with testing and development. We describe here the development of standardized lunar regolith simulant (SLRS) materials that are traceable inter-laboratory standards for testing and technology development. These SLRS materials must simulate the lunar regolith in terms of physical, chemical, and mineralogical properties. A summary of these issues is contained in the 2005 Workshop on Lunar Regolith Simulant Materials [l]. Lunar mare basalt simulants MLS-1 and JSC-1 were developed in the late 1980s. MLS-1 approximates an Apollo 11 high-Ti basalt, and was produced by milling of a holocrystalline, coarse-grained intrusive gabbro (Fig. 1). JSC-1 approximates an Apollo 14 basalt with a relatively low-Ti content, and was obtained from a glassy volcanic ash (Fig. 2). Supplies of MLS-1 and JSC-1 have been exhausted and these materials are no longer available. No highland anorthosite simulant was previously developed. Upcoming lunar polar missions thus require the identification, assessment, and development of both mare and highland simulants. A lunar regolith simulant is manufactured from terrestrial components for the purpose of simulating the physical and chemical properties of the lunar regolith. Significant challenges exist in the identification of appropriate terrestrial source materials. Lunar materials formed under comparatively reducing conditions in the absence of water, and were modified by meteorite impact events. Terrestrial materials formed under more oxidizing conditions with significantly greater access to water, and were modified by a wide range of weathering processes. The composition space of lunar materials can be modeled by mixing programs utilizing a low-Ti basalt, ilmenite, KREEP component, high-Ca anorthosite, and meteoritic components. This approach has been used for genetic studies of lunar samples via chemical and modal analysis. A reduced composition space may be appropriate for simulant development, but it is necessary to determine the controlling properties that affect the physical, chemical and mineralogical components of the simulant.

Carpenter, P.↗