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Governing Equations
Published in Dalia E. E. Khalil, Essam E. Khalil, Sprinklers and Smoke Management in Enclosures, 2020
Dalia E. E. Khalil, Essam E. Khalil
CFD is applied to a wide range of research and engineering problems in many fields of study and industries, including aerodynamics and aerospace analysis, weather simulation, natural science and environmental engineering, industrial system design and analysis, biological engineering and fluid flows, and engine and combustion analysis. The starting point of any numerical simulation is the governing equations of the physics of the problem to be solved. In the present book, numerical simulations are carried out using FDS version 6.5.3 as a good example of applications. FDS is a CFD model of fire-driven fluid flow. The software numerically solves a form of the Navier–Stokes equations appropriate for low-speed (Ma < 0.3), thermally driven flow, with an emphasis on smoke and heat transport from fires. The formulation of the equations and the numerical algorithm are illustrated in Section 3.2, where the model’s detailed assumptions and governing equations used in the model will be further demonstrated.
Computational Fluid Dynamics (CFD) Simulations in Food Processing
Published in Surajbhan Sevda, Anoop Singh, Mathematical and Statistical Applications in Food Engineering, 2020
Abhishek Dutta, Ferruh Erdoğdu, Fabrizio Sarghini
Therefore, this chapter has first suggested to use CFD approach with a certain knowledge of the mathematical and physical background of the processes, knowing the fundamental governing differential equations. For this purpose, the steps involved in a CFD analysis were explained in sufficient detail. Governing equations using finite volume method as a mathematical approach to solve the CFD problem were explained. Two case studies from food process engineering were demonstrated. In the first one, a rather simple CFD process was chosen and a step-by-step preparation of the model was demonstrated. The second case was from a rather complex process requiring a comprehensive CFD approach and mathematical analysis on the physical interpretation of the results. A future outlook for CFD studies was also presented, where GPUs-based CFD approaches were explained and data-driven CFD-based optimization studies involving AI were mentioned. In addition, the significance of experimental validation or validation on a mathematical basis were also included in the scope of the chapter.
Product Design and Development
Published in Quamrul H. Mazumder, Introduction to Engineering, 2018
Figure 12.9 shows a mesh file and computational fluid dynamics (CFD) analysis output of an S-bend pipe. CFD is a powerful tool for simulation and analysis of different fluid flow patterns and heat transfer to find real life results without even producing the parts. It shows us how any particular part will react in real life with specified conditions and specifically which part of a component needs more precaution. Figure 12.9 shows a location of maximum erosion of a pipe after performing CFD analysis. It can also tell us the magnitude of this erosion and the external conditions. ANSYS Workbench, AutoCAD CFD, OpenFoam, Creo Parametric, SolidWorks CATIA, and Unigraphics (NX) are some of the commonly used FEA and 3D modeling software packages.
Estimating the effect of blast and ventilation parameters on blast fume dilution time in underground development blasting using computational fluid dynamics
Published in CIM Journal, 2023
A. Adhikari, P. Tukkaraja, S. Jayaraman Sridharan
To address the weakness of professional judgment, conventional mathematical models, and mine ventilation software, some researchers have used computational fluid dynamics (CFD). CFD is a mathematical simulation technique used to model a physical phenomenon involving fluid flow. For example, Torno and Toraño (2020) developed CFD models to study the fundamental parameters of dilution and demonstrated that CFD can be a powerful tool to analyze dilution of fumes in development blasting. Adjiski et al. (2019) used CFD to estimate the optimal duct distance from the outlet of the forcing duct to the development heading. Tiile (2019) used CFD to investigate the effects of fresh air duct discharge and blast exclusion zone location and devised equations to conservatively estimate re-entry time. Torno et al. (2011) used CFD to predict airflow velocity and respirable dust movement at the working face. Their models allowed optimization of the auxiliary ventilation system, which would have been impossible using conventional methods. Adhikari et al. (2022) used CFD to show that fumes trapped in the muckpile take longer to dilute and suggest that trapped fumes can pose a serious health risk to miners if they are not properly monitored and controlled, especially during loading and transportation of the muckpile.
Shape Optimization and Flow Analysis of Supersonic Nozzles Using Deep Learning
Published in International Journal of Computational Fluid Dynamics, 2022
Aref Zanjani, Amir Mahdi Tahsini, Kimia Sadafi, Fatemeh Ghavidel Mangodeh
On one hand, CFD is the only tool available for analysing fluid flows in real situations, because analytical approaches are often too simplified for a real engineering use. On the other hand, CFD has many challenges and there is always some error associated with its outcome. The accuracy of CFD simulations is affected by various sources of error and challenges. As highlighted by Spalart and Venkatakrishnan (2016), these sources include the accuracy of geometry representation, which poses a significant challenge in resolving gaps, intersecting surfaces and other complex elements in a clear and unambiguous manner. Achieving accurate numerical solutions is another crucial aspect, necessitating close approximations to continuous solutions of partial differential equations (PDEs) while accounting for errors arising from iteration, convergence, discretisation and solving nonlinear systems in unsteady flows. Furthermore, the inherent inaccuracies of physical models compared to reality become particularly prominent when dealing with turbulence. The representation of scales in computational models is dictated by the underlying physics, while the precision of these scales is influenced by the grid and numerical approach employed (Moin and Mahesh 1998).
A Review of Pellet Injector Technology: Brief History and Recent Key Developments
Published in Fusion Science and Technology, 2020
Shashi Kant Verma, Samiran Shanti Mukherjee, Ranjana Gangradey, R. Srinivasan, Vishal Gupta, Paresh Panchal, Pratik Nayak
The present work reviews the analytical, experimental, and computational aspects of this field of research, with specific focus on the progress made during the previous two decades. In Sec. II, the basic configurations for the pellet injection system are presented, followed by a discussion and illustrated by Tables I, II, and III. Section III describes the basic concept of the extruder and its thermal-hydraulic correlation as well as computational fluid dynamics (CFD) modeling of a twin-screw hydrogen extruder system. CFD is the analysis of systems involving fluid flow, heat transfer, and associated phenomena such as species transport by means of computer-based simulation. Previous research is discussed in Sec. IV. Finally, recent developments in the field of the pellet injector systems in India are described in Sec V. The challenges associated with modeling of a twin-screw extruder (TSE) are discussed before the conclusions in Sec. VI.