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NASA NTRS2024

Modeling Dynamic Crush Behavior of Carbon Fiber Reinforced Polymer Composite Structures Using MAT213

Modeling crushing of carbon fiber reinforced polymer (CFRP) composites is challenging, and current simulation methodologies involve tuning of non-physical parameters. MAT213, a next-generation material model, has advanced functionality to better simulate dynamic impact loading. The objective of the present investigation is to evaluate the potential for using MAT213 to simulate dynamic crushing of CFRPs. Two sets of simulations were performed: one for calibration based on a set of coupon-level experiments and another for prediction of the response of structural elements. Simulations involving dynamic crushing of flat specimens were iteratively run to calibrate model parameters. The calibration demonstrated that MAT213 could produce a simulated force-displacement response within experimental scatter. The simulated failure morphology was also comparable to the experiments. After successful calibration, predictive simulations of dynamic crushing of C-channel shaped specimens were completed using a simulated crash sled test rig and two pairs of impactor mass/velocity conditions. The simulated force-displacement curve in the crash sled simulations for the lower-velocity condition fell within the experimental scatter, but the stable crush force was underpredicted by 27% in the higher-velocity simulations. Better correlation in the lower-velocity test condition likely results from the calibration condition being a similar velocity to the lower-velocity crash sled condition.

Dynamic Crush↗

NASA NTRSDate not supplied

Multi-Convertor Configurable Simulator for Dynamic Radioisotope Power Systems

This paper presents the multi-convertor configurable simulator (MCCS) that can emulate piston/displacer dynamics and power outputs of various types of free-piston Stirling convertors developed at NASA GRC, including Technical Demonstration Convertor (TDC), Advanced Stirling Convertor (ASC), Flexure Isotope Stirling Convertor (FISC), Sunpower Robust Stirling Convertor (SRSC), and P2A. The MCCS can emulate up to four convertors, instead of two convertors in state-of-the-art Stirling simulators, and the maximum power output for each convertor is 1kW. Furthermore, hardware and software changes required to switch between convertors are minimized for easy conversion. A hardware-in-loop (HIL) system is used to easily switch between convertors by updating linearized modeling parameters in software. Also, switched-mode AC power supplies are used to generate wide ranges of voltage and current to emulate different types of Stirling convertors without replacing AC power supplies. Finally, the inductors emulating the linear alternator, which is the only hardware change needed for conversion, are modularized in alternator boxes to enable easy replacement of the inductors. These two features—easy conversion and capability of emulating up to four 1kW-convertors—will enable the validation tests of multi-convertor controller (MCC) concepts that are being developed by APL, the Dynamic Radioisotope Power System (DRPS) generator, and other controller developments for current and future DRPS flight projects. Finally, the MCCS is configured to demonstrate emulation of four FISCs and the outputs of the MCCS are compared with experimental data from the actual FISC.

Free-Piston Stirling Convertor Controller↗

DOE OSTI2015

Characterization of swift heavy ion irradiation damage in ceria

We have examined microstructural evolution in irradiated ceria (CeO2) using swift heavy ion irradiation, electron microscopy, and atomistic simulation. CeO2, a UO2 fuel surrogate, was irradiated with gold ions at an energy of 1 GeV to fluences up to 1x1014 ions/cm2. Transmission electron microscopy accompanied by electron energy loss spectroscopy showed that the ion tracks were of similar size at all fluences, and that there was no chemical change in the ion track core. Classical molecular dynamics simulations of thermal spikes in CeO2 with energy deposition of 12 and 36 keV/nm show damage consisting of isolated point defects at the lower energy and defect clusters at 36 keV/nm, with no amorphization at either energy. Inferences are drawn from modeling about density changes in the ion track and the formation of interstitial loops that shed light on features observed by electron microscopy of swift heavy ion irradiated ceria.

Yablinsky, Clarissa↗

NASA NTRS1996

Research of TREETOPS Structural Dynamics Controls Simulation Upgrade

Under the provisions of contract number NAS8-40194, which was entitled 'TREETOPS Structural Dynamics and Controls Simulation System Upgrade', Oakwood College contracted to produce an upgrade to the existing TREETOPS suite of analysis tools. This suite includes the main simulation program, TREETOPS, two interactive preprocessors, TREESET and TREEFLX, an interactive post processor, TREEPLOT, and an adjunct program, TREESEL. A 'Software Design Document', which provides descriptions of the argument lists and internal variables for each subroutine in the TREETOPS suite, was established. Additionally, installation guides for both DOS and UNIX platforms were developed. Finally, updated User's Manuals, as well as a Theory Manual, were generated.

Yates, Rose M.↗

DOE OSTI2021

pnnl/mol_dgnn

Molecular dynamics simulations often rely on parameterized atomistic potentials, which can be inaccurate compared to ab initio simulation methods. However, dynamic ab initio simulations come with high computational cost. Deep learning techniques offer a method to obtain both high accuracy and low cost predictions of dynamics. Our method gives a prediction of the structural dynamics of a molecule accounting for the prior dynamics, giving high-accuracy predictions at low computational cost

Ashby, Michael↗

DOE OSTI2018

Advanced EMT and Phasor-Domain Hybrid Simulation With Simulation Mode Switching Capability for Transmission and Distribution Systems

Conventional electromagnetic transient (EMT) and phasor do-main hybrid simulation approaches presently exist for transmission system level studies and their simulation efficiency is generally constrained by the EMT simulation. With an increasing number of distributed energy resources and non-conventional loads being installed in the distribution systems, it is imperative to ex-tend the hybrid simulation application to include distribution systems and integrated transmission and distribution systems. Meanwhile, it is equally important to improve the simulation efficiency as the modeling scope and complexity of the detailed system in the EMT simulation increases. To meet both requirements, this paper introduces an advanced electromagnetic transient (EMT) and phasor domain hybrid simulation approach. This approach has two outstanding features: 1) a comprehensive phasor domain modeling framework which supports positive-sequence, three-sequence, three-phase and mixed three-sequence/three-phase representations; 2) a robust and flexible simulation mode switching scheme which enables simulation switching from hybrid simulation mode back to pure phasor domain dynamic simulation mode to achieve significantly improved simulation efficiency. The proposed method has been tested on integrated transmission and distribution systems, and the results show that with the developed simulation switching feature, the total computational time is significantly reduced compared to running the hybrid simulation for the whole simulation period, while good accuracy is maintained.

Huang, Qiuhua (ORCID:0000000184577429)↗

NASA NTRSDate not supplied

Quantum Hardware-Enabled Molecular Dynamics via Transfer Learning

The ability to perform ab initio molecular dynamics simulations using potential energy surfaces provided by quantum computers would open the door to virtually exact dynamics for a variety of chemical and biochemical systems, with impacts on catalysis and biophysics. Nonetheless, performing molecular dynamics on surfaces produced by quantum hardware has been hampered by the noisy energies typically produced by quantum computers and challenges associated with computing gradients and scaling to large systems interest. A recent set of advances in machine learning, known as transfer learning, provides a new path forward for molecular dynamics simulations on quantum hardware. Transfer learning offers a workaround, where one first trains models on larger, less accurate classical datasets and then refines them on smaller, more accurate quantum datasets. We explore this approach by training machine learning models to predict a molecule's potential energy based on its geometric structure using Behler-Parrinello neural networks. When successfully trained, the model enables energy gradient predictions necessary for dynamic simulations. To reduce the quantum resources needed, the model is initially trained with data derived from classical density functional theory and subsequently refined with a smaller dataset obtained from a variational quantum eigensolver optimization of the unitary coupled cluster ansatz. We show that this approach significantly reduces the size of the needed quantum training dataset while capturing the high accuracies needed within quantum chemistry simulations. The success of this two-step training method opens more opportunities to apply machine learning models on quantum data, a significant stride towards efficient quantum-classical hybrid computational models.

quantum computing↗

DOE OSTI2025

Thermally induced mimicry of quantum cluster excitations and implications for the magnetic transition in FePSe 3

In two dimensional magnets, the interplay of thermal fluctuations and spin anisotropy control the existence of long-range magnetic order. In the van der Waals antiferromagnets FePX 3 , orbital degeneracy in the 𝑡 2⁢𝑔 levels of the Fe 2+ ions in octahedral coordination yields strong uniaxial anisotropy, which stabilizes magnetic order up to 𝑇 ≈ 100 K. Recent inelastic neutron scattering measurements around the magnetic ordering transition have shown the existence of a broad spectrum of magnetic fluctuations with nontrivial momentum dependence, which has been interpreted as evidence for localized entangled cluster excitations. In this paper, we offer an alternative interpretation using classical nonlinear spin dynamics simulations. We present stochastic Landau Lifshitz dynamics simulations that reproduce the neutron scattering measurements of Chen et al. [npj Quantum Mater. 9, 40 (2024)] on FePSe 3 . These calculations faithfully explain the dynamical structure factor's momentum and energy dependence and point to a classical origin for the excitations observed in neutron spectroscopy and that the order-disorder transition can be understood in terms of thermal fluctuations overcoming the anisotropy energy.

Landau-Lifschitz-Gilbert equation↗

DOE OSTI2026

Scientific Data Compression for Large Scale Computational Fluid Dynamics (CFD) Simulations

This Cooperative Research and Development Agreement (CRADA) between Oak Ridge National Laboratory (ORNL) and General Electric (GE) investigated methods for reducing the size of large computational fluid dynamics (CFD) simulation datasets using scientific data compression techniques. The work focused on adapting the MultiGrid Adaptive Reduction of Data (MGARD) compression framework and integrating it with high-performance I/O and visualization tools used in CFD workflows. MGARD uses hierarchical multilevel decomposition to enable error-controlled compression of floating-point scientific data while preserving quantities of interest. During the project, MGARD compression was integrated with the ADIOS I/O framework and visualization tools such as ParaView to enable efficient storage, transfer, and analysis of simulation data. The collaboration also explored approaches for improving compression performance for CFD data defined on unstructured meshes. Results demonstrate that scientific data compression can significantly reduce storage requirements and improve data management for large-scale CFD simulations.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1972

Dynamic load simulator

Concepts and techniques for identifying and simulating both the steady state and dynamic characteristics of electrical loads for use during integrated system test and evaluation are discussed. The investigations showed that it is feasible to design and develop interrogation and simulation equipment to perform the desired functions. During the evaluation, actual spacecraft loads were interrogated by stimulating the loads with their normal input voltage and measuring the resultant voltage and current time histories. Elements of the circuits were optimized by an iterative process of selecting element values and comparing the time-domain response of the model with those obtained from the real equipment during interrogation.

Joncas, K. P.↗

DOE OSTI2014

Coarse-grained computer simulation of dynamics in thylakoid membranes: methods and opportunities

Coarse-grained simulation is a powerful and well-established suite of computational methods for studying structure and dynamics in nanoscale biophysical systems. As our understanding of the plant photosynthetic apparatus has become increasingly nuanced, opportunities have arisen for coarse-grained simulation to complement experiment by testing hypotheses and making predictions. Here, we give an overview of best practices in coarse-grained simulation, with a focus on techniques and results that are applicable to the plant thylakoid membrane–protein system. We also discuss current research topics for which coarse-grained simulation has the potential to play a key role in advancing the field.

Brownian dynamics↗

DOE OSTI2021

Nuclear Materials Process Modeling at the Y-12 National Security Complex

The Y-12 National Security Complex (Y-12) has implemented process modeling for various accountable nuclear materials operations that are performed throughout the plant. Using a discrete, event-based dynamic simulation program, key nuclear material streams are modeled, allowing Y-12 to effectively manage numerous points of interest within the plant’s production operations. Integration of the various material processes into a single, interdependent supply and demand model is one of the ongoing focuses within Y-12’s process modeling effort. The primary purpose of using dynamic simulation modeling is to allow for analysis of the nuclear materials inventories and forecasted supplies based on future demands. Analysis of these inventories includes capacity evaluation, bottleneck mitigation, and assessments of individual pieces of equipment to inform future facility investment decisions and associated project schedules. Modeling of the nuclear materials processes throughout the complex also allows for incorporation of changes relevant to production capabilities such as the upcoming transition of specific operations to the new Uranium Processing Facility. Prior to implementation of process modeling, Y-12 forecasted supply and demand of accountable nuclear materials streams using Microsoft Excel. With deterministic models such as Microsoft Excel, the annual forecasts, generated within data input condition parameters, can only provide a fixed point of data. Fixed data cannot simulate integrated material streams and account for the possibility of occurrences and other changes that dynamic simulations take into consideration. Y-12’s dynamic process modeling allows integrated simulations of multiple accountable nuclear materials processes, including supply and demand forecasting and analysis, and is a coordinated effort involving many steps of verification and validation (V&V), site briefings, testing, reporting, data mining, planning, and documentation that spans various programs throughout the Y-12 complex.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS1979

Numerical simulation of dynamics of brushless dc motors for aerospace and other applications. Volume 2: User's guide to computer EMA model

A description and user's guide of the computer program developed to simulate the dynamics of an electromechanical actuator for aerospace applications are presented. The effects of the stator phase currents on the permanent magnets of the rotor are examined. The voltage and current waveforms present in the power conditioner network during the motoring, regenerative braking, and plugging modes of operation are presented and discussed.

Demerdash, N. A. O.↗

NASA NTRS2005

Mars Tumbleweed Simulation Using Singular Perturbation Theory

The Mars Tumbleweed is a new surface rover concept that utilizes Martian winds as the primary source of mobility. Several designs have been proposed for the Mars Tumbleweed, all using aerodynamic drag to generate force for traveling about the surface. The Mars Tumbleweed, in its deployed configuration, must be large and lightweight to provide the ratio of drag force to rolling resistance necessary to initiate motion from the Martian surface. This paper discusses the dynamic simulation details of a candidate Tumbleweed design. The dynamic simulation model must properly evaluate and characterize the motion of the tumbleweed rover to support proper selection of system design parameters. Several factors, such as model flexibility, simulation run times, and model accuracy needed to be considered in modeling assumptions. The simulation was required to address the flexibility of the rover and its interaction with the ground, and properly evaluate its mobility. Proper assumptions needed to be made such that the simulated dynamic motion is accurate and realistic while not overly burdened by long simulation run times. This paper also shows results that provided reasonable correlation between the simulation and a drop/roll test of a tumbleweed prototype.

Raiszadeh, Behzad↗

DOE OSTI2021

Simulation of dynamic crystal plasticity with a Lagrangian discontinuous Galerkin hydrodynamic method

Here we present a new Lagrangian modal discontinuous Galerkin (DG) hydrodynamic method that supports a dynamic dislocation based crystal plasticity model for simulating the mechanical behavior of crystallographic materials, both single crystal and polycrystalline, under dynamic conditions. A modal DG approach is used to evolve fields relevant to conservation laws. These fields are approximated by Taylor series polynomials of varying degree. These polynomials describe macro-scale hydrodynamic behavior while their evolution is determined by evaluating the dynamic crystal plasticity model at material points within the element. The dynamic crystal plasticity model is sensitive to the time increment size, with too large of time increments leading to instability in the model. To mitigate this, the temporal evolution of the dynamic crystal plasticity model is achieved with the combination of a sub-incrementing scheme with Heun’s third-order time integration scheme, which is also used to temporally evolve the governing equations. The implementation of the dynamic crystal plasticity model within the DG framework is tested using a 2D approximation of the Taylor impact test with a single crystal material, using quadratic elements that have faces that can bend. In addition to the standard continuous material modeling, we propose a new simulation method that would represent the heterogeneous behavior of polycrystalline microstructures within an element by varying the position and material properties of the material points within the element. This method is demonstrated using random orientation distributions on materials points that are arranged in both structured and random configurations.

42 ENGINEERING↗

DOE OSTI2013

Temperature-dependent mechanical properties of single-layer molybdenum disulphide: Molecular dynamics nanoindentation simulations

The temperature-dependent mechanical properties of single-layer molybdenum disulphide (MoS{sub 2}) are obtained using molecular dynamics (MD) nanoindentation simulations. The Young's moduli, maximum load stress, and maximum loading strain decrease with increasing temperature from 4.2 K to 500 K. The obtained Young's moduli are in good agreement with those using our MD uniaxial tension simulations and the available experimental results. The tendency of maximum loading strain with different temperature is opposite with that of metal materials due to the short range Stillinger-Weber potentials in MoS{sub 2}. Furthermore, the indenter tip radius and fitting strain effect on the mechanical properties are also discussed.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2016

Ultrafast terahertz-field-driven ionic response in ferroelectric BaTiO 3

The dynamical processes associated with electric field manipulation of the polarization in a ferroelectric remain largely unknown but fundamentally determine the speed and functionality of ferroelectric materials and devices. Here in this paper we apply subpicosecond duration, single-cycle terahertz pulses as an ultrafast electric field bias to prototypical BaTiO 3 ferroelectric thin films with the atomic-scale response probed by femtosecond x-ray-scattering techniques. We show that electric fields applied perpendicular to the ferroelectric polarization drive large-amplitude displacements of the titanium atoms along the ferroelectric polarization axis, comparable to that of the built-in displacements associated with the intrinsic polarization and incoherent across unit cells. This effect is associated with a dynamic rotation of the ferroelectric polarization switching on and then off on picosecond time scales. These transient polarization modulations are followed by long-lived vibrational heating effects driven by resonant excitation of the ferroelectric soft mode, as reflected in changes in the c-axis tetragonality. The ultrafast structural characterization described here enables a direct comparison with first-principles-based molecular-dynamics simulations, with good agreement obtained.

36 MATERIALS SCIENCE↗

DOE OSTI2024

A data-driven multiscale model for reactive wetting simulations

Here, we describe a data-driven, multiscale technique to model reactive wetting of a silver–aluminum alloy on a Kovar™ (Fe-Ni-Co alloy) surface. We employ molecular dynamics simulations to elucidate the dependence of surface tension and wetting angle on the drop’s composition and temperature. A design of computational experiments is used to efficiently generate training data of surface tension and wetting angle from a limited number of molecular dynamics simulations. The simulation results are used to parameterize models of the material’s wetting properties and compute the uncertainty in the models due to limited data. The data-driven models are incorporated into an engineering-scale (continuum) model of a silver–aluminum sessile drop on a Kovar™ substrate. Model predictions of the wetting angle are compared with experiments of pure silver spreading on Kovar™ to quantify the model-form errors introduced by the limited training data versus the simplifications inherent in the molecular dynamics simulations. The paper presents innovations in the determination of “convergence” of noisy MD simulations before they are used to extract the wetting angle and surface tension, and the construction of their models which approximate physio-chemical processes that are left unresolved by the engineering-scale model. Together, these constitute a multiscale approach that integrates molecular-scale information into continuum scale models.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗