SEARCH · Search NASA

Results for “classical 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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 451 records · Page 25

All sources NASA NTRS DOE OSTI

NASA NTRS1981

The 1981 NASA ASEE Summer Faculty Fellowship Program, volume 2

A collection of papers on miscellaneous subjects in aerospace research is presented. Topics discussed are: (1) Langmuir probe theory and the problem of anisotropic collection; (2) anthropometric program analysis of reach and body movement; (3) analysis of IV characteristics of negatively biased panels in a magnetoplasma; (4) analytic solution to classical two body drag problem; (5) fast variable step size integration algorithm for computer simulations of physiological systems; (6) spectroscopic experimental computer assisted empirical model for the production of energetics of excited oxygen molecules formed by atom recombination shuttle tile surfaces; and (7) capillary priming characteristics of dual passage heat pipe in zero-g.

Robertson, N. G.↗

NASA NTRS1988

Expert systems for adaptive control of large space structures

It is expected that space systems for the future will evolve to structures of unprecedented size with associated extreme control requirements. A method is necessary that is sufficiently general to initiate stable control of a vehicle and subsequently learn the true nature of the structure. It is suggested that a suitable constructed expert system (ES) would be capable of learning by appending observations to a knowledge base. To verify that an ES can control a large space structure, numerical simulations of a simple structure subjected to periodic vibrations and the performance of a classical controllers were performed. The ES was then exercised to show its ability to truthfully mimic nominal control and to demonstrate its superiority to the classical controller, given sensor failures. An ES generating software package, The Intelligent Machine Model, was employed. It uses the pattern matching technique. Results of this program are discussed.

Gartrell, Charles F.↗

NASA NTRS1991

Recovery system termination load reduction through the use of a central load core

A study is presented of the development and testing of a parachute central load core, an adaptive device whose primary function is to minimize parachute stored elastic energy while providing adequate rotational stiffness to prevent shroud line fouling from twisting and sufficient resistive torque for any balloon gondola positioning requirements. Empirical relations are given for the uninhibited drag area growth which are derived in the classical nondimensional form. Attention is given to development considerations and design along with model simulations, small and midscale drop test data, full-scale flight data, and instrumentation applications.

Robbins, ED↗

NASA NTRS1995

Analysis of discretization errors in LES

All numerical simulations of turbulence (DNS or LES) involve some discretization errors. The integrity of such simulations therefore depend on our ability to quantify and control such errors. In the classical literature on analysis of errors in partial differential equations, one typically studies simple linear equations (such as the wave equation or Laplace's equation). The qualitative insight gained from studying such simple situations is then used to design numerical methods for more complex problems such as the Navier-Stokes equations. Though such an approach may seem reasonable as a first approximation, it should be recognized that strongly nonlinear problems, such as turbulence, have a feature that is absent in linear problems. This feature is the simultaneous presence of a continuum of space and time scales. Thus, in an analysis of errors in the one dimensional wave equation, one may, without loss of generality, rescale the equations so that the dependent variable is always of order unity. This is not possible in the turbulence problem since the amplitudes of the Fourier modes of the velocity field have a continuous distribution. The objective of the present research is to provide some quantitative measures of numerical errors in such situations. Though the focus of this work is LES, the methods introduced here can be just as easily applied to DNS. Errors due to discretization of the time-variable are neglected for the purpose of this analysis.

Ghosal, Sandip↗

NASA NTRS1998

Comparison of Five System Identification Algorithms for Rotorcraft Higher Harmonic Control

This report presents an analysis and performance comparison of five system identification algorithms. The methods are presented in the context of identifying a frequency-domain transfer matrix for the higher harmonic control (HHC) of helicopter vibration. The five system identification algorithms include three previously proposed methods: (1) the weighted-least- squares-error approach (in moving-block format), (2) the Kalman filter method, and (3) the least-mean-squares (LMS) filter method. In addition there are two new ones: (4) a generalized Kalman filter method and (5) a generalized LMS filter method. The generalized Kalman filter method and the generalized LMS filter method were derived as extensions of the classic methods to permit identification by using more than one measurement per identification cycle. Simulation results are presented for conditions ranging from the ideal case of a stationary transfer matrix and no measurement noise to the more complex cases involving both measurement noise and transfer-matrix variation. Both open-loop identification and closed- loop identification were simulated. Closed-loop mode identification was more challenging than open-loop identification because of the decreasing signal-to-noise ratio as the vibration became reduced. The closed-loop simulation considered both local-model identification, with measured vibration feedback and global-model identification with feedback of the identified uncontrolled vibration. The algorithms were evaluated in terms of their accuracy, stability, convergence properties, computation speeds, and relative ease of implementation.

Jacklin, Stephen A.↗

DOE OSTI2026

Hamiltonian simulation in Zeno subspaces

Here, we investigate the quantum Zeno effect as a framework for designing and analyzing quantum algorithms for Hamiltonian simulation. We show that frequent projective measurements of an ancilla qubit register can be used to simulate quantum dynamics on a target qubit register with a circuit complexity similar to randomized approaches. The classical sampling overhead in the latter approaches is traded for ancilla qubit overhead in Zeno-based approaches. A second-order Zeno sequence is developed to improve scaling and implementations through unitary kicks are discussed. We derive rigorous error bounds that allow for identifying the associated circuit complexities for the first- and second-order Zeno sequences. We show that the circuits over the combined register can be identified as a subroutine commonly used in post-Trotter Hamiltonian simulation methods. We build on this observation to reveal connections between different Hamiltonian simulation algorithms.

Hamiltonian simulation↗

NASA NTRSDate not supplied

Implementing Artificial Thinking Autonomy with Model-Based System Engineering

Complex autonomous systems capable of successfully operating independently under ‘known unknowns’ and harsh conditions require paradigm innovation in modern development strategies. In the field of autonomy, developing a system-of-systems which can ostensibly think for itself in the face of ‘unknown unknowns’ is still a field of ongoing research. Maturing the systems architecting and modeling methodologies for developing henceforth named Thinking Autonomous Systems, which are verified with digital mission simulation, can potentially usher in the next generation of artificial intelligence for space exploration. The concept presented in this paper incorporates multiple Model-Based Systems Engineering and simulation methodologies combined as a new paradigm to design a novel, biomimetic thinking autonomy strategy. Anachronistic concepts from classical Kantian philosophy will be leveraged to inspire architectural designs that could be used for complex distributed systems in deep space. To accomplish this, digital transformation of a document-based implementation plan for Thinking Autonomous Systems, generated by experienced NASA software engineers, is implemented for NASA’s Platform for Autonomous Systems by creating descriptive and executable software models in SysML to prototype real-time operating capabilities. This conceptual implementation has been developed by incorporating model-based digital simulations to theorize how a cyberphysical thinking system would achieve specific strategies without crew reliance, while simultaneously being resilient to all operating conditions and remaining functional when devoid of ground communication. Additionally, ensuring that an autonomous system framework is an ethical Artificial Intelligence requires careful consideration of system behavior and accountability, human factors for teaming with a thinking autonomous system, and comparison to other modern approaches used for implementing true autonomy. This paper presents the first steps in formalizing the metacognition required for instantiating a truly Thinking Autonomous System; the approach described symphonizes autonomy characteristics from classical philosophical into a unified software architecture describing human thought. In the future, the foundational models described in this paper can be further leveraged to help advance research into thinking autonomy requirements for future deep space missions as well as for current near-term applications, i.e., living aboard crewed spacecraft like a NASA Gateway cislunar habitat.

Artificial Thought↗

NASA NTRSDate not supplied

Optimization Algorithms as Quantum Performance Benchmarks

Combinatorial optimization is anticipated to be one of the primary use cases for quantum computation in the coming years. The Quantum Approximate Optimization Algorithm (QAOA) and Quantum Annealing (QA) have the potential to demonstrate significant run-time performance benefits over current state-of-the-art solutions. Using existing methods for characterizing classical optimization algorithms, we analyze solution quality obtained by solving Max-Cut problems using a quantum annealing device and gate-model quantum simulators and devices. This is used to guide the development of an advanced benchmarking framework for quantum computers designed to evaluate the trade-off between run-time execution performance and the solution quality for iterative hybrid quantum-classical applications. The framework generates performance profiles through effective visualizations that show performance progression as a function of time for various problem sizes and illustrates algorithm limitations uncovered by the benchmarking approach. The framework is an enhancement to the existing open-source QED-C Application-Oriented Benchmark suite and can connect to the open-source analysis libraries. The suite can be executed on various quantum simulators and quantum hardware systems.

benchmarking↗

NASA NTRS2021

Reconnection and particle acceleration in 3D current sheet evolution in moderately-magnetized astrophysical pair plasma

Magnetic reconnection, a plasma process converting magnetic energy to particle kinetic energy, is often invoked to explain magnetic energy releases powering high-energy flares in astrophysical sources including pulsar wind nebulae and black hole jets. Reconnection is usually seen as the (essentially 2D) nonlinear evolution of the tearing instability disrupting a thin current sheet. To test how this process operates in 3D, we conduct a comprehensive particle-in-cell simulation study comparing 2D and 3D evolution of long, thin current sheets in moderately-magnetized, collisionless, relativistically-hot electron- positron plasma, and find dramatic differences. We first systematically characterize this process in 2D, where classic, hierarchical plasmoid-chain reconnection determines energy release, and explore a wide range of initial configurations, guide magnetic field strengths, and system sizes. We then show that 3D simulations of similar configurations exhibit a diversity of behaviours, including some where energy release is determined by the nonlinear relativistic drift-kink instability. Thus, 3D current-sheet evolution is not always fundamentally classical reconnection with perturbing 3D effects, but, rather, a complex interplay of multiple linear and nonlinear instabilities whose relative importance depends sensitively on the ambient plasma, minor configuration details, and even stochastic events. It often yields slower but longer-lasting and ultimately greater magnetic energy release than in 2D. Intriguingly, nonthermal particle acceleration is astonishingly robust, depending on the upstream magnetization and guide field, but otherwise yielding similar particle energy spectra in 2D and 3D. Though the variety of underlying current-sheet behaviours is interesting, the similarities in overall energy release and particle spectra may be more remarkable.

Gregory R. Werner↗

NASA NTRS2008

Using Global Simulations to Relate the Three-Part Structure of Coronal Mass Ejections to in Situ Signatures

White-light observations of coronal mass ejections (CMEs) often show the classic "three-part" structure consisting of (1) a bright front; (2) a dark cavity; and (3) a bright, compact core. It has proven difficult to unambiguously associate these features with in situ measurements of interplanetary CMEs (ICMEs), in all but a few cases. In this study we use a global MHD model to simulate the eruption and evolution of a CME out to 0.25 AU, allowing us to continuously track these features from the Sun and through the solar wind. Our results support the generally held view that the interplanetary flux rope corresponds to the dark cavity. We find that the bright front merges with solar wind material swept up by the ICME. Thus, the sheath material found ahead of fast ejecta is in fact composed from both ambient solar wind material, as well the bright front. We also note that, in this simulation, the bright front is formed from the overlying streamer configuration from within which the CME erupted and is not itself coronal material swept up during the early phase of the eruption. The conclusions reached in this study are undoubtedly sensitive to the initial configuration and mechanism used to initiate the CME, and thus care should be taken when using them to interpret specific observations. On the other hand, they provide a unique, unbroken connection between remote solar and interplanetary observations. Ultimately, detailed comparisons between observations and simulation results may be able to constrain or even rule out some mechanisms of CME initiation.

Riley, Pete↗

NASA NTRS2008

Using Global Simulations to Relate the Three-Part Structure of Coronal Mass Ejections to In Situ Signatures

Riley, Pete↗

DOE OSTI2024

Simulation of Nanocrystalline Magnetic Cores using Maxwell ANSYS

Explore the source record for details and available documents.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRSDate not supplied

REACTER: A Heuristic Method for Reactive Molecular Dynamics

REACTER (www.reacter.org) is a heuristic protocol that enables the simulation of complex reactions using atomistic molecular dynamics (MD) with a fixed-valence force field. Incorporating reactions into classical MD with this approach allows modeling of reactive systems over greatly-increased time scales, enabling systems to be modeled with MD that would not otherwise be feasible. One or more competing multi-step reactions or series of reactions can be invoked simultaneously. Special treatment can be applied to neighboring atoms to relax high energy configurations while the simulation progresses. The original version of REACTER, which was implemented in the open-source LAMMPS simulation package as fix bond/react, was only available for serial simulations. This work describes the expansion of fix bond/react for use in parallel simulations, as well as the addition of various new options, including deletion of reaction by-products, reversible reactions, and custom reaction constraints. These new capabilities are demonstrated through large-scale simulations (200,000+ atoms) of the polymerization of polystyrene and nylon 6,6. The morphologies of both polymers are analyzed after reaching >99% extent of polymerization. Finally, the newly-added reversible reactions feature is demonstrated by rupturing these highly-entangled systems under uniaxial strain by defining a chain scission reaction.

polymer simulations, molecular dynamics↗

NASA NTRS1993

Development of a computational testbed for numerical simulation of combustion instability

A synergistic hierarchy of analytical and computational fluid dynamic techniques is used to analyze three-dimensional combustion instabilities in liquid rocket engines. A mixed finite difference/spectral procedure is employed to study the effects of a distributed vaporization zone on standing and spinning instability modes within the chamber. Droplet atomization and vaporization are treated by a variety of classical models found in the literature. A multi-zone, linearized analytical solution is used to validate the accuracy of the numerical simulations at small amplitudes for a distributed vaporization region. This comparison indicates excellent amplitude and phase agreement under both stable and unstable operating conditions when amplitudes are small and proper grid resolution is used. As amplitudes get larger, expected nonlinearities are observed. The effect of liquid droplet temperature fluctuations was found to be of critical importance in driving the instabilities of the combustion chamber.

Grenda, Jeffrey↗

DOE OSTI2024

Quantum computation of stopping power for inertial fusion target design

Stopping power is the rate at which a material absorbs the kinetic energy of a charged particle passing through it—one of many properties needed over a wide range of thermodynamic conditions in modeling inertial fusion implosions. First-principles stopping calculations are classically challenging because they involve the dynamics of large electronic systems far from equilibrium, with accuracies that are particularly difficult to constrain and assess in the warm-dense conditions preceding ignition. Here, we describe a protocol for using a fault-tolerant quantum computer to calculate stopping power from a first-quantized representation of the electrons and projectile. Our approach builds upon the electronic structure block encodings of Su et al. [ PRX Quant. 2 , 040332 (2021)], adapting and optimizing those algorithms to estimate observables of interest from the non-Born–Oppenheimer dynamics of multiple particle species at finite temperature. We also work out the constant factors associated with an implementation of a high-order Trotter approach to simulating a grid representation of these systems. Ultimately, we report logical qubit requirements and leading-order Toffoli costs for computing the stopping power of various projectile/target combinations relevant to interpreting and designing inertial fusion experiments. We estimate that scientifically interesting and classically intractable stopping power calculations can be quantum simulated with roughly the same number of logical qubits and about one hundred times more Toffoli gates than is required for state-of-the-art quantum simulations of industrially relevant molecules such as FeMoco or P450.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Prediction of residual stresses in additively manufactured parts using lumped capacitance and classical lamination theory

Several industries are interested in Laser Powder Bed Fusion (L-PBF) Additively Manufactured (AM) metal parts because their designs can be made arbitrarily complex while retaining bulk-type material properties. However, the residual stresses (RS) and distortions caused by the heat gradients inherent to L-PBF processes are detrimental to the structural integrity of the parts and must be taken into consideration during the part design cycle. Predicting the state of stresses in as-built 3D printed parts is a difficult problem that is typically approached with the use of transient thermomechanical Finite Element Models (FEMs). However, the nonlinearities associated with AM processes are difficult to capture in these FEMs without increasing the computational cost of the simulation, limiting their ability to be incorporated into practical design cycles. This work presents a novel analytical framework that combines lumped capacitance nonlinear heat transfer with time dependent classical lamination theory to efficiently and accurately predict RS in as-built L-PBF parts without the need of FEMs. The simulation was compared to Neutron Diffraction (ND) residual strain measurements taken at Oak Ridge National Laboratories (ORNL) as well as Synchrotron X-ray Diffraction (XRD) strain data published by the National Institute of Standards and Technology (NIST). The simulation predictions and the experimental data showed excellent agreement for the in-plane strain directions, and general agreement for the out of plane strain component, highlighting an area where further development can be implemented.

42 ENGINEERING↗

NASA NTRS2020

Cross-field Streaming Instabilities in the Lower Hybrid Frequency Near the Front Pole Regions of a Magnetically Shielded Hall Thruster

The mechanism that led to the erosion of the inner front pole cover in wear tests of the Hall-effect Rocket with Magnetic Shielding (HERMeS) at 300 V and 12.5 kW has been elusive. Several classical mechanisms have been considered yet none has explained conclusively the source of the discrepancy between wear measurements and simulations. In this article we consider a new mechanism. The electrostatic dispersion relation for an unbounded, homogeneous plasma in a fixed magnetic field is solved numerically in the near-plume region of this thruster. The plasma conditions have been obtained from Hall2De (r-z) multifluid-PIC simulations. We find that the modified two-stream instability can be excited in most regions of the domain, with the fastest growth approaching the fluid-limit value of ωLH/2 near the magnetic poles where ωpe/ωce~1. In this region the relative drift between magnetized electrons and beam ions perpendicular to the magnetic field can exceed 3uTi, while that between counter-streaming beam and cathode ions can exceed 4uTi. The latter suggests that the ion-ion cross-field lower hybrid instability may also be active here. Unlike the classical ion-acoustic instability, lower hybrid instabilities can heat ions to temperatures that are comparable to the electron temperature. Such anomalous heating would enhance the average energy of these ions and, in turn, the erosion of the nearby surfaces they sputter. An idealized model that scales the anomalous ion heating with ωLH has been incorporated in Hall2De and the simulations now yield significantly improved agreement with the measured wear rates and IVDFs, as reported in our companion paper.

Ortega, Alejandro Lopez↗

DOE OSTI2026

Quantum-Inspired Bayesian Sampling for Uncertainty Quantification and Machine Learning (Final Technical Report)

With increasing simulation and measurement data, machine learning and artificial intelligence have been widely used in computational decision-making of complex engineering systems. The resulting tools, such as uncertainty quantification solvers, reinforcement learning, and physics-informed machine learning, have achieved great success in critical DOE tasks such as material discovery and design, energy system modeling and control, and numerical weather and climate prediction. A core topic in scientific machine learning and artificial intelligence is Bayesian inference: given an observed data set, people want to estimate the posterior distribution of a (possibly large) number of hidden parameters. Due to the flexibility and weak assumptions, Bayesian sampling has been the mainstream Bayesian inference solvers despite the rapid progress of approximate Bayesian inference. Classical Bayesian sampling methods such as Markov-chain Monte Carlo suffer from a low-acceptance rate due to the random walk nature, therefore state-of-the-art techniques use Hamiltonian Monte Carlo and its variants to efficiently draw posterior samples in a high dimension. The key idea of Hamiltonian Monte Carlo and its variants is to simulate the Hamiltonian dynamics of a classical particle with a fixed mass, and their performance significantly degrades when the posterior distribution is highly spiky or has multiple modes. Leveraging the idea of quantum physics, this project has investigated new theory, algorithms and applications of Bayesian inference (especially Bayesian sampling). The main results include: (1) novel quantum-inspired Bayesian sampling methods that can lead to better accuracy for challenging multi-modal or spiky distributions, (2) more scalable machine learning framework leveraging tensor-compressed Bayesian inference, and (3) Bayesian and sampling approaches for verifying the robustness of continuous and binary neural networks.

97 MATHEMATICS AND COMPUTING↗