Search Results (5)

Hydrogen is regarded as a promising energy source for the future due to its clean combustion products, remarkable efficiency and renewability. However, its characteristics of low-ignition energy, a wide flammable range from 4% to 75%, and a rapid flame speed may bring significant explosion risks. Typically, accidental release of hydrogen into confined enclosures can result in a flammable hydrogen–air mixture with concentration gradients, possibly leading to flame acceleration (FA) and deflagration-to-detonation transition (DDT). The current study focused on the evolutions of the FA and DDT of homogenous/inhomogeneous hydrogen–air mixtures, based on the open-source computational fluid dynamics (CFD) platform OpenFOAM and the modified Weller et al.’s combustion model, taking into account the Darrieus–Landau (DL) and Rayleigh–Taylor (RT) instabilities, the turbulence and the non-unity Lewis number. Numerical simulations were carried out for both homogeneous and inhomogeneous mixtures in an enclosed channel 5.4 m in length and 0.06 m in height. The predictions demonstrate good quantitative agreement with the experimental measurements in flame-tip position, speed and pressure profiles by Boeck et al. The characteristics of flame structure, wave evolution and vortex were also discussed. Full article

Recent advancements in the integration of artificial intelligence (AI) and machine learning (ML) with physical sciences have led to significant progress in addressing complex phenomena governed by nonlinear partial differential equations (PDEs). This paper explores the application of novel operator learning methodologies to unravel the intricate dynamics of flame instability, particularly focusing on hybrid instabilities arising from the coexistence of Darrieus–Landau (DL) and Diffusive–Thermal (DT) mechanisms. Training datasets encompass a wide range of parameter configurations, enabling the learning of parametric solution advancement operators using techniques such as parametric Fourier Neural Operator (pFNO) and parametric convolutional neural networks (pCNNs). Results demonstrate the efficacy of these methods in accurately predicting short-term and long-term flame evolution across diverse parameter regimes, capturing the characteristic behaviors of pure and blended instabilities. Comparative analyses reveal pFNO as the most accurate model for learning short-term solutions, while all models exhibit robust performance in capturing the nuanced dynamics of flame evolution. This research contributes to the development of robust modeling frameworks for understanding and controlling complex physical processes governed by nonlinear PDEs. Full article

An experimental study of ignition and flame front propagation during spark initiation in a hydrogen–air mixture in a semi-open channel with a porous coating is reported. The bottom surface of the channel was covered with a porous layer made of porous polyurethane or steel wool. The measurements were carried out for a stoichiometric mixture (equivalence ratio ER = 1.0) and for a lean mixture (ER = 0.4) of hydrogen with air, where ER is the molar excess of hydrogen. The flame front was recorded with a high-speed camera using the shadow method. Depending on the pore size, the velocity of the flame front and the sizes of disturbances generated on the surface of the flame front were determined. Qualitative features of the deflagration flame front at ER = 0.4, consisting of disturbances resembling small balls of flame, were discovered. The sizes of these disturbances significantly exceed the analytical values for the Darrieus–Landau instability. The effect of coatings made of porous polyurethane or steel wool is compared with the results obtained for an empty smooth channel. Depending on the hydrogen concentration in the hydrogen–air mixture, the velocity of the flame front compared to a smooth channel was three times higher when the channel was covered with steel wool and five times higher when the channel was covered with porous polyurethane. Full article

Convective velocity perturbations (CVPs) are known to play an important role in the response of flames to acoustic perturbations and in thermoacoustic combustion instabilities. In order to elucidate the flow-physical origin of CVPs, the present study models the response of laminar premixed slit flames to low amplitude perturbations of the upstream flow velocity with a reduced order flow decomposition approach: A linearized G-equation represents the shape and heat release rate of the perturbed flame, while the velocity perturbation field is decomposed into irrotational and solenoidal contributions. The former are determined with a conformal mapping from geometry and boundary conditions, whereas the latter are governed by flame front curvature and flow expansion across the flame, which generates baroclinic vorticity. High-resolution CFD analysis provides values of model parameters and confirms the plausibility of model results. This flow decomposition approach makes it possible to explicitly evaluate and analyze the respective contributions of irrotational and solenoidal flows to the flame response, and conversely the effect of flame perturbations on the flow. The use of the popular ad hoc hypothesis of convected velocity perturbation is avoided. It is found that convected velocity perturbations do not result from immediate acoustic-to-hydrodynamic mode conversion, but are generated by flame-flow feedback. In this sense, models for flame dynamics that rely on ad-hoc models for CVPs do not respect causality. Furthermore, analysis of the flame impulse response reveals that for the configuration investigated, flame-flow feedback is also responsible for “excess gain” of the flame response, that is, the magnitude of the flame frequency response above unity. Full article

A general method for solving a linear stability problem of an interface with a continuous internal structure is described. Such interfaces or fronts are commonly found in various branches of physics, such as combustion and plasma physics. It extends simplified analysis of an infinitely thin discontinuous front by means of numerical integration along the steady-state solution. Two examples are presented to demonstrate the application of the method for 1D pulsating instability in magnetic deflagration and 2D Darrieus–Landau instability in a laser ablation wave. Full article