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In the present study, soot formation in the turbulent lifted diffusion flame, consisting of ethylene-air is numerically investigated using three different soot modeling approaches and is comprehensively reported. For turbulence-chemistry…

Fluid Dynamics · Physics 2021-03-03 Rohit Saini , Ashoke De

Transported probability density function (PDF) methods are widely used to model turbulent flames characterized by strong turbulence-chemistry interactions. Numerical methods directly resolving the PDF are commonly used, such as the…

Fluid Dynamics · Physics 2022-10-20 Martin Pollack , Federica Ferraro , Johannes Janicka , Christian Hasse

NO$_{\rm x}$ formation in lean premixed and highly-strained pure hydrogen-air flamelets is investigated numerically. Lean conditions are established at an equivalence ratio of 0.7. Detailed-chemistry, one-dimensional simulations are…

Fluid Dynamics · Physics 2025-09-05 Alessandro Porcarelli , Boris Kruljevic , Ivan Langella

High-frequency combustion instabilities can lead to significant fluctuations in chamber pressure, affecting the structural integrity and performance of solid rocket motors. Since these instabilities manifest as acoustic oscillations during…

Computational Physics · Physics 2024-11-14 Juan M. Tizón , Antoni M. Barredo

Joint probability density function (PDF)-based models in turbulent combustion provide direct closure for turbulence-chemistry interactions. The joint PDFs capture the turbulent flame dynamics at different spatial locations and hence it is…

Fluid Dynamics · Physics 2021-04-06 Rishikesh Ranade , Kevin Gitushi , Tarek Echekki

In this work, we demonstrate a framework for developing closure models in turbulent combustion using experimental multi-scalar measurements. The framework is based on the construction of conditional means and joint scalar PDFs from…

Fluid Dynamics · Physics 2019-09-10 Rishikesh Ranade , Tarek Echekki

Burnback analysis is a geometric exercise, whose correct solution leads to obtaining the thrust curve of solid propellant rockets. Traditionally, Piobert statement, which introduces a certain amount of intuition, is used as an argument to…

Computational Engineering, Finance, and Science · Computer Science 2023-03-06 Juan M. Tizón

The mixing process of multiple jets of liquefied petroleum gas and air in a diffusion flame is numerically analysed. The case study considers a four-port array burner where the fuel is injected by four peripheral nozzles and mixed with the…

The last years saw a renewal of interest for hypersonic research in general and regenerative cooling specifically, with a large increase of the number of dedicated facilities and technical studies. In order to quantify the heat transfer in…

Under rocket-relevant conditions, real-gas effects and thermodynamic non-idealities are prominent features of the flow field. Experimental investigations indicate that phase separation can occur depending on the operating conditions and on…

Fluid Dynamics · Physics 2018-07-16 Christoph Traxinger , Julian Zips , Michael Pfitzner

The present work reports on LES of turbulent reacting flow of the Delft-Jet-in-Hot-Coflow (DJHC) burner, emulating MILD combustion, with transported PDF based combustion models using ANSYS FLUENT 13.0. Two different eddy viscosity models…

Fluid Dynamics · Physics 2021-01-25 Rohit Bhaya , Ashoke De , Rakesh Yadav

Aims. The main goal of the present paper is to provide the first systematic numerical study of the propagation of astrophysical relativistic jets, in the context of high-resolution shock-capturing resistive relativistic magnetohydrodynamics…

High Energy Astrophysical Phenomena · Physics 2023-11-03 Giancarlo Mattia , Luca Del Zanna , Matteo Bugli , Andrea Pavan , Riccardo Ciolfi , Gianluigi Bodo , Andrea Mignone

Understanding the coolant thermal hydraulics in rod bundles is essential to the design of nuclear reactors. However, flows with low Reynolds numbers present serious modeling challenges, especially in heat transfer and natural convection.…

Fluid Dynamics · Physics 2023-08-31 Carolina Bourdot Dutra , Elia Merzari

Our work is motivated by the analysis of ash plume dynamics, arising in the study of volcanic eruptions. Such phenomena are characterized by large Reynolds number (exceeding $10^7$) and a large number of polydispersed particles~[1]. Thus,…

Large eddy simulation of propane/air jet flame in the wrinkled flamelets regime of the Borghi diagram is used to assess the performance of a recently developed consumption speed correction model in premixed combustion. The combustion is…

Fluid Dynamics · Physics 2021-12-03 Ivan Langella , Nguyen Anh Khoa Doan

In the present work we compare reliability of several most widely used reduced detailed chemical kinetic schemes for hydrogen-air and hydrogen-oxygen combustible mixtures. The validation of the schemes includes detailed analysis of 0D and…

Fluid Dynamics · Physics 2013-12-13 M. F. Ivanov , A. D. Kiverin , M. A. Liberman , A. E Smygalina

Direct numerical simulations of free round jets at a Reynolds number ($Re_{D}$) of $5000$, based on jet diameter ($D$) and jet-exit bulk velocity ($U_{e}$), are performed to study jet turbulence characteristics at supercritical pressures.…

Fluid Dynamics · Physics 2021-08-04 Nek Sharan , Josette Bellan

In the present paper, an aerodynamic investigation of a high-speed train is performed. In the first section of this article, a generic high-speed train against a turbulent flow is simulated, numerically. The Reynolds-Averaged Navier-Stokes…

Tabulated chemistry methods are a well-known strategy to efficiently store the flows thermochemical properties. In particular, the Flamelet-Generated Manifold (FGM) is a widely used technique that generates the database with a small number…

Fluid Dynamics · Physics 2024-11-21 Alessandro Ballatore , Diego Quan Reyes , Hesheng Bao , Jeroen van Oijen

Modeling of turbulent combustion system requires modeling the underlying chemistry and the turbulent flow. Solving both systems simultaneously is computationally prohibitive. Instead, given the difference in scales at which the two…

Machine Learning · Computer Science 2022-11-14 Amol Salunkhe , Dwyer Deighan , Paul Desjardin , Varun Chandola