Machine Learning for Accelerating Direct-Simulation Monte-Carlo Collision Operators.
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Time-accurate FUN3D simulations are utilized to estimate buffet-induced unsteady forces experienced by the Space Launch System during the Artemis I (AR01) flight. A set of FUN3D simulations was developed that employed time-accurate mesh translations to simulate the changing velocity and attitude based on the AR01 best estimated trajectory. In these simulations, referred to as accelerating-flow simulations, the freestream Mach number increased from 0.80 to 1.92. Additional time-accurate simulations were obtained at constant freestream Mach number equal to 0.95, 1.18, 1.70, thereby simulating stationary conditions experienced by the flow in a wind-tunnel. On the grounds of favorable comparisons between simulated and flight-measured environments, the FUN3D-based surface pressures were utilized to develop a buffet forcing function (BFF) database. This BFF database was analyzed to characterize the spatial distribution and frequency content of the buffet forces during transonic and supersonic portions of the AR01 flight. The region of interest is located downstream of the forward attachment (FA) hardware between the core stage and the solid rocket boosters where vortex shedding off the FA protuberance produces significant unsteadiness. The analysis reveals that, at transonic and supersonic conditions, buffet forces that are based on constant freestream Mach number data are a good approximation of those based on accelerating-flow simulations.
Time-accurate FUN3D simulations are utilized to estimate buffet-induced unsteady forces experienced by the Space Launch System during the Artemis I (AR01) flight. A set of FUN3D simulations was developed that employed time-accurate mesh translations to simulate the changing velocity and attitude based on the AR01 best estimated trajectory. In these simulations, referred to as accelerating-flow simulations, the freestream Mach number increased from 0.80 to 1.92. Additional time-accurate simulations were obtained at constant freestream Mach number equal to 0.95, 1.18, 1.70, thereby simulating stationary conditions experienced by the flow in a wind-tunnel. On the grounds of favorable comparisons between simulated and flight-measured environments, the FUN3D-based surface pressures were utilized to develop a buffet forcing function (BFF) database. This BFF database was analyzed to characterize the spatial distribution and frequency content of the buffet forces during transonic and supersonic portions of the AR01 flight. The region of interest is located downstream of the forward attachment (FA) hardware between the core stage and the solid rocket boosters where vortex shedding off the FA protuberance produces significant unsteadiness. The analysis reveals that, at transonic and supersonic conditions, buffet forces that are based on constant freestream Mach number data are a good approximation of those based on accelerating-flow simulations.
Human response to angular acceleration, discussing implications for motion capability in flight simulator
Purpose: To quantify the dosimetric variations of misaligned beams for a linear accelerator by using Monte Carlo (MC) simulations. Method and Materials: Misaligned beams of a Varian 21EX Clinac were simulated to estimate the dosimetric effects. All the linac head components for a 6 MV photon beam were implemented in BEAMnrc/EGSnrc system. For incident electron beam parameters, 6 MeV with 0.1 cm full-width-half-max Gaussian beam was used. A phase space file was obtained below the jaw per each misalignment condition of the incident electron beam: (1) The incident electron beams were tilted by 0.5, 1.0 and 1.5 degrees on the x-axis from the central axis. (2) The center of the incident electron beam was off-axially moved toward +x-axis by 0.1, 0.2, and 0.3 cm away from the central axis. Lateral profiles for each misaligned beam condition were acquired at dmax = 1.5 cm and 10 cm depth in a rectangular water phantom. Beam flatness and symmetry were calculated by using the lateral profile data. Results: The lateral profiles were found to be skewed opposite to the angle of the incident beam for the tilted beams. For the displaced beams, similar skewed lateral profiles were obtained with small shifts of penumbra on the +x-axis. The variations of beam flatness were 3.89–11.18% and 4.12–42.57% for the tilted beam and the translated beam, respectively. The beam symmetry was separately found to be 2.95 −9.93% and 2.55–38.06% separately. It was found that the percent increase of the flatness and the symmetry values are approximated 2 to 3% per 0.5 degree tilt or per 1 mm displacement. Conclusion: This study quantified the dosimetric effects of misaligned beams using MC simulations. The results would be useful to understand the magnitude of the dosimetric deviations for the misaligned beams.
A new configuration of a coaxial plasma accelerator with self-energized magnetic compressor coil attached is described. It is shown that the circuit may be treated theoretically by analyzing an equivalent circuit mesh. The results obtained from the theoretical analysis are shown to compare favorably with the results measured experimentally. Using this accelerator configuration, glass beads of 125-micron diameter were accelerated to velocities as high as 11 km/sec, while 700-micron-diam glass beads were accelerated to velocities as high as 5 km/sec. The velocities are within the hypervelocity regime of meteroids.
A new configuration of a coaxial plasma accelerator with self-energized magnetic compressor coil attached is described. It is shown that the circuit may be treated theoretically by analyzing an equivalent circuit mesh. The results obtained from the theoretical analysis compare favorably with the results measured experimentally. Using this accelerator configuration, glass beads of 125 micron diameter were accelerated to velocities as high as 11 kilometers per second, while 700 micron diameter glass beads were accelerated to velocities as high as 5 kilometers per second. The velocities are within the hypervelocity regime of meteoroids.
Nonthermal radiation observed from astrophysical systems containing (relativistic) jets and shocks, e.g., supernova remnants, active galactic nuclei (AGNs), gamma-ray bursts (GRBs), and Galactic microquasar systems usually have power-law emission spectra. Fermi acceleration is the mechanism usually assumed for the acceleration of particles in astrophysical environments. Recent PIC simulations using injected relativistic electron-ion (electro-positron) jets show that acceleration occurs within the downstream jet, rather than by the scattering of particles back and forth across the shock as in Fermi acceleration. Shock acceleration is a ubiquitous phenomenon in astrophysical plasmas. Plasma waves and their associated instabilities (e.g., the Buneman instability, other two-streaming instability, and the Weibel instability) created in the .shocks are responsible for particle (electron, positron, and ion) acceleration. The simulation results show that the Weibel instability is responsible for generating and amplifying highly nonuniform, small-scale magnetic fields. These magnetic fields contribute to the electron's transverse deflection behind the jet head. The "jitter" radiation from deflected electrons has different properties than synchrotron radiation which is calculated in a uniform magnetic field. This jitter radiation may be important to understanding the complex time evolution and/or spectral structure in gamma-ray bursts, relativistic jets, and supernova remnants. We will review recent PIC simulations which show particle acceleration in jets.
The very intensive calculations necessary to define a performance map requiring evaluation of over a hundred individual operating points can be efficiently conducted with accelerated multizone for engine cycle simulation, leading to a definition of regions of acceptable and optimum homogeneous charge compression ignition operation. Accelerated multizone for engine cycle simulation has the virtue of enabling accurate evaluation of many operating conditions based on thermal stratification data from a single fluid mechanics run at motored conditions. This is possible because thermal stratification is more sensitive to engine geometry than to operating conditions. In this article, accuracy of accelerated multizone for engine cycle simulation is demonstrated by comparison with experimental data for iso-octane homogeneous charge compression ignition operation over a broad range of lean equivalence ratios (0.14–0.28). The validated accelerated multizone for engine cycle simulation model is then applied to generating a performance map for an engine controlled by appropriately adjusting equivalence ratio and internal exhaust gas recirculation. Regions of acceptable and optimum combustion are identified. It is finally demonstrated that while indicated mean effective pressure remains low for optimum homogeneous charge compression ignition operation (1–4 bar), this is sufficient for a large fraction of typical driving in light-duty vehicles. Much driving including idle can therefore be done in homogeneous charge compression ignition mode at high efficiency and low (essentially zero) NOx and particulate matter emissions.
The work deals with the construction of strategy for finding optimal control of systems for spatially distributed systems on an example of problems in physics beams. The suggested approach is based on use of exact and approximate invariants as a controlling mechanism for control of modelling process of beam lines. The classical problem of optimal control of similar systems as an optimal control problem is formulated in a functional space. This approach is based on algebraic methods Lie and the corresponding matrix formalism that allows you to build not only the formal procedures for finding optimal solutions, but also provide the necessary constructive computational procedures.
A 2.5-dimensional fully relativistic EM, particle-in-cell code (PIC) is used to investigate a potential electron acceleration mechanism in solar flares. The free energy is provided by ions which have a ring velocity distribution about the magnetic-field direction. Ion rings may be produced by perpendicular shocks, which could in turn be generated by the super-Alfvenic motion of magnetic flux tubes emerging from the photosphere or by coronal mass ejections. Such ion distributions are known to be unstable to the generation of lower hybrid waves, which have phase velocities in excess of the electron thermal speed parallel to the field and can, therefore, resonantly accelerate electrons in that direction. The simulations show the transfer of perpendicular ion energy to energetic electrons via lower hybrid wave turbulence. With plausible ion ring velocities, the process can account for the observationally inferred fluxes and energies of non-thermal electrons during the impulsive phase of flares.
During carbonation, the microstructure of a cement paste is strongly modified, which induces a dynamic feedback loop impacting the global advancement of the reaction. In this study, we investigate the effect of the microstructure model on simulations of accelerated carbonation of cement pastes. A variable-porosity reactive transport model with a new microstructure model is used. To match the chemical layers created by the carbonation front, we use a layered microstructure model. We demonstrate that qualitative prediction for a large range of conditions and formulations can only be obtained if the macroscopic parameters of the carbonated layer can be modelled accurately. In particular, the saturation dependent parameters, such as the capillary pressure or the relative diffusion coefficients, control the rate of advancement of the reaction front since a high saturation inhibits the carbon dioxide diffusion.
Stochastic simulation of large biochemical reaction networks is often computationally expensive due to the disparate reaction rates and high variability of population of chemical species. An approach to accelerate the simulation is to allow multiple reaction firings before performing update by assuming that reaction propensities are changing of a negligible amount during a time interval. Species with small population in the firings of fast reactions significantly affect both performance and accuracy of this simulation approach. It is even worse when these small population species are involved in a large number of reactions. We present in this paper a new approximate algorithm to cope with this problem. It is based on bounding the acceptance probability of a reaction selected by the exact rejection-based simulation algorithm, which employs propensity bounds of reactions and the rejection-based mechanism to select next reaction firings. The reaction is ensured to be selected to fire with an acceptance rate greater than a predefined probability in which the selection becomes exact if the probability is set to one. Our new algorithm improves the computational cost for selecting the next reaction firing and reduces the updating the propensities of reactions.
Discrete dislocation dynamics (DDD) is a widely employed computational method to study plasticity at the mesoscale that connects the motion of dislocation lines to the macroscopic response of crystalline materials. However, the computational cost of DDD simulations remains a bottleneck that limits its range of applicability. Here, we introduce a new DDD-GNN framework in which the expensive time-integration of dislocation motion is entirely substituted by a graph neural network (GNN) model trained on DDD trajectories. As a first application, we demonstrate the feasibility and potential of our method on a simple yet relevant model of a dislocation line gliding through an array of obstacles. We show that the DDD-GNN model is stable and reproduces very well unseen ground-truth DDD simulation responses for a range of straining rates and obstacle densities, without the need to explicitly compute nodal forces or dislocation mobilities during time-integration. Our approach opens new promising avenues to accelerate DDD simulations and to incorporate more complex dislocation motion behaviors.
Highlights: • Two numerical methods are presented to accelerate DMD simulations. • The methods greatly reduce the computation time without much loss of accuracy. • The accelerated DMD model is capable of simulating long-term mass transport at atomistic length scales. • Demonstrated for the propagation of an atomically sharp phase boundary over 30 seconds. - Abstract: Diffusive Molecular Dynamics (DMD) is a class of recently developed computational models for the simulation of long-term diffusive mass transport at atomistic length scales. Compared to previous atomistic models, e.g., transition state theory based accelerated molecular dynamics, DMD allows the use of larger time-step sizes, but has a higher computational complexity at each time-step due to the need to solve a nonlinear optimization problem at every time-step. This paper presents two numerical methods to accelerate DMD based simulations. First, we show that when a many-body potential function, e.g., embedded atom method (EAM), is employed, the cost of DMD is dominated by the computation of the mean of the potential function and its derivatives, which are high-dimensional random variables. To reduce the cost, we explore both first- and second-order mean field approximations. Specifically, we show that the first-order approximation, which uses a point estimate to calculate the mean, can reduce the cost by two to three orders of magnitude, but may introduce relatively large error in the solution. We show that adding an approximate second-order correction term can significantly reduce the error without much increase in computational cost. Second, we show that DMD can be significantly accelerated through subcycling time integration, as the cost of integrating the empirical diffusion equation is much lower than that of the optimization solver. To assess the DMD model and the numerical approximation methods, we present two groups of numerical experiments that simulate the diffusion of hydrogen in palladium nanoparticles. In particular, we show that the computational framework is capable of capturing the propagation of an atomically sharp phase boundary over a time window of more than 30 seconds. The effects of the proposed numerical methods on solution accuracy and computation time are also assessed quantitatively.
In this study, we demonstrate the application of data-driven linear operator construction for time advance with a goal of accelerating plasma physics simulation. We apply dynamic mode decomposition (DMD) to data produced by the nonlinear SOLPS-ITER (Scrape-off Layer Plasma Simulator - International Thermonuclear Experimental Reactor) plasma boundary code suite in order to estimate a series of linear operators and monitor their predictive accuracy via online error analysis. We find that this approach defines when these dynamics can be represented by a sequence of approximate linear operators and is essential for providing consistent projections when compared to an unconstrained application. For linear diffusion and advection–diffusion fluid test problems, we construct and apply operators within explicit and implicit time advance schemes, demonstrating that stability can be robustly guaranteed in each case. We further investigate the use of the linear time advance operators within several integration methods including forward Euler, backward Euler, and the matrix exponential. The application of this method to simulation data from SOLPS-ITER, with varying levels of Markov chain Monte Carlo numerical noise, shows that constrained DMD operators yield a capability to identify, extract, and integrate a (slow) subset of the present timescales. Example applications show that for projected speedup factors of [Formula: see text], and [Formula: see text], a mean relative error of 3%, 5%, and 8% and maximum relative error less than 20% are achievable, which appears acceptable for typical SOLPS-ITER steady-state simulations.
The results of a series of particle-in-cell simulations of stochastic wave-particle interaction are presented. The threshold for stochasticity was confirmed. The simulations demonstrate that in a strong magnetic field plasma waves with quiver velocities much less than the speed of light but above a certain threshold can stochastically accelerate electrons to energies far greater than 1 MeV. Moreover, self-consistency effects drive return currents and produce energetic runaway electrons that violate an invariant of motion.