reactingFoam-SCI: An open source CFD platform for reacting flow simulation

Yang, Qi; Zhao, Peng; Ge, Haiwen

doi:10.1016/j.compfluid.2019.06.008

Cited by 45 publications

(14 citation statements)

References 50 publications

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“…In this study, the governing equations are solved using the open-source software platform OpenFOAM [ 12 , 25 , 40 – 42 ]. Time-dependent term is discretized using the first-order implicit Euler scheme.…”

Section: Methodsmentioning

confidence: 99%

LES study on the impact of airway deformation on the airflow structures in the idealized mouth–throat model

Wang

Liang

et al. 2021

J Braz. Soc. Mech. Sci. Eng.

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To investigate the impacts of upper airway deformation on the airflow structures, the airflow fields in the trachea are simulated using three geometrical models considering three different levels of airway deformations. Structured grids are used to create the high-quality grids. Large eddy simulation with the Smagorinsky sub-grid model is adopted to solve the three-dimensional in-compressible Navier–Stokes equations using the solver pisoFoam in the open-source CFD software OpenFOAM. The numerical results demonstrate that the airway deformation influences the main airflow structures depending on the deformation level. Particularly, it slightly impacts on the laryngeal jet such as the profile and the strength of laryngeal jet. The strength of the laryngeal jet increases slightly for the heavy deformation. In contrast, it impacts on the recirculation zone, secondary vortices, and turbulent kinetic energy more obviously. The increasing airway deformation will produce stronger secondary flow, smaller recirculation zone, and weaker turbulent kinetic energy. The turbulence intensity distribution varies as well. The obviously impacted flow region is mainly within the region of one to six tracheal diameters downstream the glottis.

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Section: Methodsmentioning

confidence: 99%

LES study on the impact of airway deformation on the airflow structures in the idealized mouth–throat model

Wang

Liang

et al. 2021

J Braz. Soc. Mech. Sci. Eng.

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“…The numerical simulation of ignition in mixture with thermal and concentration stratification is conducted using a novel inhouse reacting flow CFD code reactingFOAM-SCT based on OpenFOAM 6.0 (Yang et al, 2019). The new features of this open-source platform include an advanced accurate mid-point Splitting scheme (Lu et al, 2017), a fast and accurate stiff Chemistry solver (Imren and Haworth, 2016) and a detailed transport property evaluation package (Dasgupta et al, 2019).…”

Section: Methodsmentioning

confidence: 99%

“…The performance of these advanced features has been extensively validated against either DNS results or analytical solutions in different configurations, including those from a diffusionconvection problem, homogeneous ignition delay, laminar premixed flame, shock wave, 1D spherical flame initiation and propagation, 2D premixed flame instabilities, 1D non-premixed counterflow flame and 2D non-premixed co-flow flame. More details of the governing equation, numerical scheme, spatial and temporal accuracy, and validation results are available in Yang et al (2019). More recently, this code has been utilized to demonstrate the minimum ignition energy, regimes, and propagation dynamics of direct cool flame initiation (Yang and Zhao, 2020).…”

Section: Methodsmentioning

confidence: 99%

Auto-Ignition and Reaction Front Dynamics in Mixtures With Temperature and Concentration Stratification

et al. 2020

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In-cylinder thermal and concentration stratification is omnipresent in the operation of internal combustion engines, especially for various types of direct injection engines. Meanwhile, mixture stratification and φ-sensitivity is frequently adopted in advanced compression ignition strategies to modulate heat release profile and control combustion phasing, such as homogeneous charge compression ignition (HCCI) with partial fuel stratification (PFS), and premixed charge compression ignition (PCCI). Hence, ignition and combustion mode evolution in a stratified charge is of substantial significance in the understanding and prediction of combustion in advanced compression ignition engines. To probe complex combustion in a stratified charge, we have performed one-dimensional direct numerical simulations with detailed chemistry and transport, using a recently developed open source reacting flow CFD platform based on OpenFOAM 6.0. N-heptane is adopted in this work as a typical fuel exhibiting low temperature chemistry. Temperature and equivalence ratio gradient are varied among the simulations to observe ignition and the subsequent combustion development. Three stages of heat release are identified, including the low temperature chemistry chain branching, H 2 O 2 chain branching and CO oxidation, consistent with the recent ignition experiment for lean n-heptane air mixture in a rapid compression machine (RCM). Reaction fronts induced by these oxidation stages are found to be unaffected by diffusion process and exhibit unique propagation features. The results provide useful guidance to the understanding of combustion in a stratified charge and shed light on the development of novel low temperature combustion strategy for advanced compression ignition engines.

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“…After calculating fluxes and gradients according to equations (6) and 7, equation 5can be numerically integrated between time t n and t n+1 � t n + Δt using multistage Runge-Kutta scheme. Denoting by N s the number of stages, this yields…”

Section: Time Integrationmentioning

confidence: 99%

“…erefore, there is a growing interest in the CFD community to develop and implement higher-order methods in OpenFOAM for transient flow calculations. ese include, for example, numerical algorithms for DNS/ LES of incompressible flows [2], compressible flows [3][4][5], and reacting flows [6].…”

Section: Introductionmentioning

confidence: 99%

Scalability of OpenFOAM Density-Based Solver with Runge–Kutta Temporal Discretization Scheme

Paoli

D‘Mello

2020

Scientific Programming

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Compressible density-based solvers are widely used in OpenFOAM, and the parallel scalability of these solvers is crucial for large-scale simulations. In this paper, we report our experiences with the scalability of OpenFOAM’s native rhoCentralFoam solver, and by making a small number of modifications to it, we show the degree to which the scalability of the solver can be improved. The main modification made is to replace the first-order accurate Euler scheme in rhoCentralFoam with a third-order accurate, four-stage Runge-Kutta or RK4 scheme for the time integration. The scaling test we used is the transonic flow over the ONERA M6 wing. This is a common validation test for compressible flows solvers in aerospace and other engineering applications. Numerical experiments show that our modified solver, referred to as rhoCentralRK4Foam, for the same spatial discretization, achieves as much as a 123.2% improvement in scalability over the rhoCentralFoam solver. As expected, the better time resolution of the Runge–Kutta scheme makes it more suitable for unsteady problems such as the Taylor–Green vortex decay where the new solver showed a 50% decrease in the overall time-to-solution compared to rhoCentralFoam to get to the final solution with the same numerical accuracy. Finally, the improved scalability can be traced to the improvement of the computation to communication ratio obtained by substituting the RK4 scheme in place of the Euler scheme. All numerical tests were conducted on a Cray XC40 parallel system, Theta, at Argonne National Laboratory.

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reactingFoam-SCI: An open source CFD platform for reacting flow simulation

Cited by 45 publications

References 50 publications

LES study on the impact of airway deformation on the airflow structures in the idealized mouth–throat model

LES study on the impact of airway deformation on the airflow structures in the idealized mouth–throat model

Auto-Ignition and Reaction Front Dynamics in Mixtures With Temperature and Concentration Stratification

Scalability of OpenFOAM Density-Based Solver with Runge–Kutta Temporal Discretization Scheme

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