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Ignition of a lean hydrogen–oxygen premixture by focused-laser-induced breakdown and subsequent three-dimensional expanding-flame instabilities are simulated in high detail. Both diffusive–thermal and hydrodynamic (Darrieus–Landau) instabilities are active and accelerate the flame expansion. The fluid is a partially-ionized gas in local thermodynamic equilibrium with detailed kinetics and transport models, starting from initial conditions from an auxiliary simulation based on a two-temperature local thermodynamic non-equilibrium model. After the decay of the initial laser-induced plasma, the r ∼ t 1.5 growth in time of the flame radius matches theory and experimental observations. Based on hydrodynamic theory for spherical-flame propagation, a global Karlovitz number is defined as the ratio of the hydrodynamic to flame-distortion time scales. It initially increases during the diffusive–thermal instability stage, then with the onset of significant baroclinic torque, this trend reverses, with vorticity production becoming the dominant mechanism of instability. [ABSTRACT FROM AUTHOR]

Machine learning methods are used to improve the efficiency by which turbulence-resolved simulations predict whether a hydrogen jet in air crossflow will successfully ignite. The flush-mounted jet issues perpendicularly from the wall of a low-speed wind tunnel into a turbulent boundary layer wherein a laser-induced optical breakdown (LIB) hotspot is deposited. A detailed hydrogen chemical mechanism is used to model the radicals and any subsequent chemical reactions. A dielectric-barrier discharge actuator generates body forces and hydrogen radicals near the jet orifice. We focus on the success or not of the ignition based on LIB location. A challenge is that definitive determination of this requires long simulations, up to 440 µs after the LIB deposition. This is particularly expensive since multiple simulations are required to find the threshold. To reduce the computational effort, three short-time (91 µs) criteria are proposed, evaluated, and compared: a constructed criterion based on detailed observations of radicals near the stoichiometric surface and two machine learning approaches, each trained on 38 realizations. The constructed criterion provides a low-cost estimate of the ignition boundary that is unambiguous in 45 of the 50 training and test trials, so only 10% of them would need to be simulated longer. The trained neural networks correctly predict outcomes in all cases evaluated, with the more automated procedure—a convolutional neural network (CNN) trained on two-dimensional images—providing the most definitive outcome prediction. From the CNN, a sensitivity analysis is used to determine which kernel features from the two-dimensional input data, as defined by intermediate-layer network weights, are important for identifying ignition. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to develop a sizing method to decide the best design features of a noise protective unit (NPU). The method of “inverse matrix” was used to assess the local acoustic pressure drop when a wave goes through the multi-layer shell of the NPU. Solutions of the wave equations were used in each of the layers taking into account: 1) the incidence angle of the sound waves and the layer loss factor; 2) the input boundary conditions establishing the equality of the normal components of particle velocity and acoustic pressure at medium borders; 3) the system of algebraic complex equations and corresponding matrix equations. The telemetric information obtained during a real launch was processed by means of specially developed software. A novel method of sizing the best design features for a noise protective unit makes it possible to reduce vibroacoustic loads on spacecraft to acceptable levels. The comparison of the data calculated using this method and the experimental data showed their good agreement. The devised method appears to have considerable promise when developing new launch vehicles able to protect spacecraft from noise and vibration. At critical frequencies the levels of acoustic pressure decreased by half to two thirds. [ABSTRACT FROM AUTHOR]

This work presents large eddy simulation/probability density function (LES/PDF) simulation results for the Sandia/Sydney series of bluff-body stabilized CH 4 / H 2 flames. Results are presented for the flames HM1, HM2 and HM3, using the 19-species ARM2 reduced chemical mechanism, and comparison is made with previous numerical simulations of the same flames. When compared to previous numerical studies of these bluff-body flames, the present simulation shows considerable improvement, particularly in the downstream regions of the flow. The simulations are shown to be sensitive to the treatment of heat transfer to the bluff-body face, with better agreement in the temperature profiles achieved with the addition of a Dirichlet temperature boundary condition. [ABSTRACT FROM AUTHOR]