Chapter 1 Governing Equations of Fluid Flow and Heat Transfer
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Aerodynamics Material - Taylor & Francis
CopyrightAerodynamics material - Taylor & Francis ______________________________________________________________________ 257 Aerodynamics Symbol List Symbol Definition Units a speed of sound ⁄ a speed of sound at sea level ⁄ A area aspect ratio ‐‐‐‐‐‐‐‐ b wing span c chord length c Copyrightmean aerodynamic material chord- Taylor & Francis specific heat at constant pressure of air · root chord tip chord specific heat at constant volume of air · / quarter chord total drag coefficient ‐‐‐‐‐‐‐‐ , induced drag coefficient ‐‐‐‐‐‐‐‐ , parasite drag coefficient ‐‐‐‐‐‐‐‐ , wave drag coefficient ‐‐‐‐‐‐‐‐ local skin friction coefficient ‐‐‐‐‐‐‐‐ lift coefficient ‐‐‐‐‐‐‐‐ , compressible lift coefficient ‐‐‐‐‐‐‐‐ compressible moment ‐‐‐‐‐‐‐‐ , coefficient , pitching moment coefficient ‐‐‐‐‐‐‐‐ , rolling moment coefficient ‐‐‐‐‐‐‐‐ , yawing moment coefficient ‐‐‐‐‐‐‐‐ ______________________________________________________________________ 258 Aerodynamics Aerodynamics Symbol List (cont.) Symbol Definition Units pressure coefficient ‐‐‐‐‐‐‐‐ compressible pressure ‐‐‐‐‐‐‐‐ , coefficient , critical pressure coefficient ‐‐‐‐‐‐‐‐ , supersonic pressure coefficient ‐‐‐‐‐‐‐‐ D total drag induced drag Copyright material - Taylor & Francis parasite drag e span efficiency factor ‐‐‐‐‐‐‐‐ L lift pitching moment · rolling moment · yawing moment · M mach number ‐‐‐‐‐‐‐‐ critical mach number ‐‐‐‐‐‐‐‐ free stream mach number ‐‐‐‐‐‐‐‐ P static pressure ⁄ total pressure ⁄ free stream pressure ⁄ q dynamic pressure ⁄ R -
Stall/Surge Dynamics of a Multi-Stage Air Compressor in Response to a Load Transient of a Hybrid Solid Oxide Fuel Cell-Gas Turbine System
Journal of Power Sources 365 (2017) 408e418 Contents lists available at ScienceDirect Journal of Power Sources journal homepage: www.elsevier.com/locate/jpowsour Stall/surge dynamics of a multi-stage air compressor in response to a load transient of a hybrid solid oxide fuel cell-gas turbine system * Mohammad Ali Azizi, Jacob Brouwer Advanced Power and Energy Program, University of California, Irvine, USA highlights Dynamic operation of a hybrid solid oxide fuel cell gas turbine system was explored. Computational fluid dynamic simulations of a multi-stage compressor were accomplished. Stall/surge dynamics in response to a pressure perturbation were evaluated. The multi-stage radial compressor was found robust to the pressure dynamics studied. Air flow was maintained positive without entering into severe deep surge conditions. article info abstract Article history: A better understanding of turbulent unsteady flows in gas turbine systems is necessary to design and Received 14 August 2017 control compressors for hybrid fuel cell-gas turbine systems. Compressor stall/surge analysis for a 4 MW Accepted 4 September 2017 hybrid solid oxide fuel cell-gas turbine system for locomotive applications is performed based upon a 1.7 MW multi-stage air compressor. Control strategies are applied to prevent operation of the hybrid SOFC-GT beyond the stall/surge lines of the compressor. Computational fluid dynamics tools are used to Keywords: simulate the flow distribution and instabilities near the stall/surge line. The results show that a 1.7 MW Solid oxide fuel cell system compressor like that of a Kawasaki gas turbine is an appropriate choice among the industrial Hybrid fuel cell gas turbine Dynamic simulation compressors to be used in a 4 MW locomotive SOFC-GT with topping cycle design. -
CFD Based Design for Ejector Cooling System Using HFOS (1234Ze(E) and 1234Yf)
energies Article CFD Based Design for Ejector Cooling System Using HFOS (1234ze(E) and 1234yf) Anas F A Elbarghthi 1,*, Saleh Mohamed 2, Van Vu Nguyen 1 and Vaclav Dvorak 1 1 Department of Applied Mechanics, Faculty of Mechanical Engineering, Technical University of Liberec, Studentská 1402/2, 46117 Liberec, Czech Republic; [email protected] (V.V.N.); [email protected] (V.D.) 2 Department of Mechanical and Materials Engineering, Masdar Institute, Khalifa University of Science and Technology, Abu Dhabi, UAE; [email protected] * Correspondence: [email protected] Received: 18 February 2020; Accepted: 14 March 2020; Published: 18 March 2020 Abstract: The field of computational fluid dynamics has been rekindled by recent researchers to unleash this powerful tool to predict the ejector design, as well as to analyse and improve its performance. In this paper, CFD simulation was conducted to model a 2-D axisymmetric supersonic ejector using NIST real gas model integrated in ANSYS Fluent to probe the physical insight and consistent with accurate solutions. HFOs (1234ze(E) and 1234yf) were used as working fluids for their promising alternatives, low global warming potential (GWP), and adhering to EU Council regulations. The impact of different operating conditions, performance maps, and the Pareto frontier performance approach were investigated. The expansion ratio of both refrigerants has been accomplished in linear relationship using their critical compression ratio within 0.30% accuracy. The results show that ± R1234yf achieved reasonably better overall performance than R1234ze(E). Generally, by increasing the primary flow inlet saturation temperature and pressure, the entrainment ratio will be lower, and this allows for a higher critical operating back pressure. -
MSME with Depth in Fluid Mechanics
MSME with depth in Fluid Mechanics The primary areas of fluid mechanics research at Michigan State University's Mechanical Engineering program are in developing computational methods for the prediction of complex flows, in devising experimental methods of measurement, and in applying them to improve understanding of fluid-flow phenomena. Theoretical fluid dynamics courses provide a foundation for this research as well as for related studies in areas such as combustion, heat transfer, thermal power engineering, materials processing, bioengineering and in aspects of manufacturing engineering. MS Track for Fluid Mechanics The MSME degree program for fluid mechanics is based around two graduate-level foundation courses offered through the Department of Mechanical Engineering (ME). These courses are ME 830 Fluid Mechanics I Fall ME 840 Computational Fluid Mechanics and Heat Transfer Spring The ME 830 course is the basic graduate level course in the continuum theory of fluid mechanics that all students should take. In the ME 840 course, the theoretical understanding gained in ME 830 is supplemented with material on numerical methods, discretization of equations, and stability constraints appropriate for developing and using computational methods of solution to fluid mechanics and convective heat transfer problems. Students augment these courses with additional courses in fluid mechanics and satisfy breadth requirements by selecting courses in the areas of Thermal Sciences, Mechanical and Dynamical Systems, and Solid and Structural Mechanics. Graduate Course and Research Topics (Profs. Benard, Brereton, Jaberi, Koochesfahani, Naguib) ExperimentalResearch Many fluid flow phenomena are too complicated to be understood fully or predicted accurately by either theory or computational methods. Sometimes the boundary conditions of real-world problems cannot be analyzed accurately. -
Turbulent Boundary Layers 7 - 1 David Apsley 7.2.3 Radiation
7. HEAT TRANSFER SPRING 2009 7.1 Definitions 7.2 Modes of heat transfer 7.3 The Prandtl number 7.4 Dimensionless numbers in free and forced convection 7.5 The energy equation 7.6 Laminar boundary layers with isothermal walls 7.7 Temperature profile in a turbulent boundary layer 7.8 Heat-transfer coefficients 7.9 Temperature integral results 7.10 Engineering heat-transfer calculations 7.11 References Examples 7.1 Definitions Heat transfer is energy in transit due to a temperature difference. The heat flux qh is the rate of heat transfer per unit area. 7.2 Modes of Heat Transfer 7.2.1 Conduction Heat transfer due to molecular activity in the absence of a bulk motion. Fourier ’s Law = − ∇ qh kh T (1) kh is the conductivity of heat . –1 –1 –1 –1 At 20 ºC, kh(water) = 0.604 W m K ; kh(air) = 0.0257 W m K . 7.2.2 Advection Heat transfer due to bulk motion of fluid. = − qh c p (T Te )u (2) cp is the specific heat capacity (at constant pressure). Te is a reference (usually the external or free-stream) temperature. –1 –1 –1 –1 At 20 ºC, cp(water) = 4182 J kg K ; cp(air) = 1007 J kg K . Turbulent Boundary Layers 7 - 1 David Apsley 7.2.3 Radiation Heat transfer by emission of electromagnetic radiation. Stefan-Boltzmann Law = 4 qh Ts (3) (= 5.670 ×10 -8 W m–2 K–4) is the Stefan-Boltzmann constant . is the emissivity ( = 1 for a perfect black body) 7.2.4 Free and Forced Convection For fluids, conduction and advection are usually combined as convection , which may be either: forced convection – flow driven by external means; free (or natural ) convection – flow driven by buoyancy. -
Potential Flow Theory
2.016 Hydrodynamics Reading #4 2.016 Hydrodynamics Prof. A.H. Techet Potential Flow Theory “When a flow is both frictionless and irrotational, pleasant things happen.” –F.M. White, Fluid Mechanics 4th ed. We can treat external flows around bodies as invicid (i.e. frictionless) and irrotational (i.e. the fluid particles are not rotating). This is because the viscous effects are limited to a thin layer next to the body called the boundary layer. In graduate classes like 2.25, you’ll learn how to solve for the invicid flow and then correct this within the boundary layer by considering viscosity. For now, let’s just learn how to solve for the invicid flow. We can define a potential function,!(x, z,t) , as a continuous function that satisfies the basic laws of fluid mechanics: conservation of mass and momentum, assuming incompressible, inviscid and irrotational flow. There is a vector identity (prove it for yourself!) that states for any scalar, ", " # "$ = 0 By definition, for irrotational flow, r ! " #V = 0 Therefore ! r V = "# ! where ! = !(x, y, z,t) is the velocity potential function. Such that the components of velocity in Cartesian coordinates, as functions of space and time, are ! "! "! "! u = , v = and w = (4.1) dx dy dz version 1.0 updated 9/22/2005 -1- ©2005 A. Techet 2.016 Hydrodynamics Reading #4 Laplace Equation The velocity must still satisfy the conservation of mass equation. We can substitute in the relationship between potential and velocity and arrive at the Laplace Equation, which we will revisit in our discussion on linear waves. -
Heat Transfer in Flat-Plate Solar Air-Heating Collectors
Advanced Computational Methods in Heat Transfer VI, C.A. Brebbia & B. Sunden (Editors) © 2000 WIT Press, www.witpress.com, ISBN 1-85312-818-X Heat transfer in flat-plate solar air-heating collectors Y. Nassar & E. Sergievsky Abstract All energy systems involve processes of heat transfer. Solar energy is obviously a field where heat transfer plays crucial role. Solar collector represents a heat exchanger, in which receive solar radiation, transform it to heat and transfer this heat to the working fluid in the collector's channel The radiation and convection heat transfer processes inside the collectors depend on the temperatures of the collector components and on the hydrodynamic characteristics of the working fluid. Economically, solar energy systems are at best marginal in most cases. In order to realize the potential of solar energy, a combination of better design and performance and of environmental considerations would be necessary. This paper describes the thermal behavior of several types of flat-plate solar air-heating collectors. 1 Introduction Nowadays the problem of utilization of solar energy is very important. By economic estimations, for the regions of annual incident solar radiation not less than 4300 MJ/m^ pear a year (i.e. lower 60 latitude), it will be possible to cover - by using an effective flat-plate solar collector- up to 25% energy demand in hot water supply systems and up to 75% in space heating systems. Solar collector is the main element of any thermal solar system. Besides of large number of scientific publications, on the problem of solar energy utilization, for today there is no common satisfactory technique to evaluate the thermal behaviors of solar systems, especially the local characteristics of the solar collector. -
Chapter 5 Dimensional Analysis and Similarity
Chapter 5 Dimensional Analysis and Similarity Motivation. In this chapter we discuss the planning, presentation, and interpretation of experimental data. We shall try to convince you that such data are best presented in dimensionless form. Experiments which might result in tables of output, or even mul- tiple volumes of tables, might be reduced to a single set of curves—or even a single curve—when suitably nondimensionalized. The technique for doing this is dimensional analysis. Chapter 3 presented gross control-volume balances of mass, momentum, and en- ergy which led to estimates of global parameters: mass flow, force, torque, total heat transfer. Chapter 4 presented infinitesimal balances which led to the basic partial dif- ferential equations of fluid flow and some particular solutions. These two chapters cov- ered analytical techniques, which are limited to fairly simple geometries and well- defined boundary conditions. Probably one-third of fluid-flow problems can be attacked in this analytical or theoretical manner. The other two-thirds of all fluid problems are too complex, both geometrically and physically, to be solved analytically. They must be tested by experiment. Their behav- ior is reported as experimental data. Such data are much more useful if they are ex- pressed in compact, economic form. Graphs are especially useful, since tabulated data cannot be absorbed, nor can the trends and rates of change be observed, by most en- gineering eyes. These are the motivations for dimensional analysis. The technique is traditional in fluid mechanics and is useful in all engineering and physical sciences, with notable uses also seen in the biological and social sciences. -
Introduction to Compressible Computational Fluid Dynamics James S
Introduction to Compressible Computational Fluid Dynamics James S. Sochacki Department of Mathematics James Madison University [email protected] Abstract This document is intended as an introduction to computational fluid dynamics at the upper undergraduate level. It is assumed that the student has had courses through three dimensional calculus and some computer programming experience with numer- ical algorithms. A course in differential equations is recommended. This document is intended to be used by undergraduate instructors and students to gain an under- standing of computational fluid dynamics. The document can be used in a classroom or research environment at the undergraduate level. The idea of this work is to have the students use the modules to discover properties of the equations and then relate this to the physics of fluid dynamics. Many issues, such as rarefactions and shocks are left out of the discussion because the intent is to have the students discover these concepts and then study them with the instructor. The document is used in part of the undergraduate MATH 365 - Computation Fluid Dynamics course at James Madi- son University (JMU) and is part of the joint NSF Grant between JMU and North Carolina Central University (NCCU): A Collaborative Computational Sciences Pro- gram. This document introduces the full three-dimensional Navier Stokes equations. As- sumptions to these equations are made to derive equations that are accessible to un- dergraduates with the above prerequisites. These equations are approximated using finite difference methods. The development of the equations and finite difference methods are contained in this document. Software modules and their corresponding documentation in Fortran 90, Maple and Matlab can be downloaded from the web- site: http://www.math.jmu.edu/~jim/compressible.html. -
INCOMPRESSIBLE FLOW AERODYNAMICS 3 0 0 3 Course Category: Programme Core A
COURSE CODE COURSE TITLE L T P C 1151AE107 INCOMPRESSIBLE FLOW AERODYNAMICS 3 0 0 3 Course Category: Programme core a. Preamble : The primary objective of this course is to teach students how to determine aerodynamic lift and drag over an airfoil and wing at incompressible flow regime by analytical methods. b. Prerequisite Courses: Fluid Mechanics c. Related Courses: Airplane Performance Compressible flow Aerodynamics Aero elasticity Flapping wing dynamics Industrial aerodynamics Transonic Aerodynamics d. Course Educational Objectives: To introduce the concepts of mass, momentum and energy conservation relating to aerodynamics. To make the student understand the concept of vorticity, irrotationality, theory of air foils and wing sections. To introduce the basics of viscous flow. e. Course Outcomes: Upon the successful completion of the course, students will be able to: Knowledge Level CO Course Outcomes (Based on revised Nos. Bloom’s Taxonomy) Apply the physical principles to formulate the governing CO1 K3 aerodynamics equations Find the solution for two dimensional incompressible inviscid CO2 K3 flows Apply conformal transformation to find the solution for flow over CO3 airfoils and also find the solutions using classical thin airfoil K3 theory Apply Prandtl’s lifting-line theory to find the aerodynamic CO4 K3 characteristics of finite wing Find the solution for incompressible flow over a flat plate using CO5 K3 viscous flow concepts f. Correlation of COs with POs: COs PO1 PO2 PO3 PO4 PO5 PO6 PO7 PO8 PO9 PO10 PO11 PO12 CO1 H L H L M H H CO2 H L H L M H H CO3 H L H L M H H CO4 H L H L M H H CO5 H L H L M H H H- High; M-Medium; L-Low g. -
Heat Transfer (Heat and Thermodynamics)
Heat Transfer (Heat and Thermodynamics) Wasif Zia, Sohaib Shamim and Muhammad Sabieh Anwar LUMS School of Science and Engineering August 7, 2011 If you put one end of a spoon on the stove and wait for a while, your nger tips start feeling the burn. So how do you explain this simple observation in terms of physics? Heat is generally considered to be thermal energy in transit, owing between two objects that are kept at di erent temperatures. Thermodynamics is mainly con- cerned with objects in a state of equilibrium, while the subject of heat transfer probes matter in a state of disequilibrium. Heat transfer is a beautiful and astound- ingly rich subject. For example, heat transfer is inextricably linked with atomic and molecular vibrations; marrying thermal physics with solid state physics|the study of the structure of matter. We all know that owing matter (such as air) in contact with a heated object can help `carry the heat away'. The motion of the uid, its turbulence, the ow pattern and the shape, size and surface of the object can have a pronounced e ect on how heat is transferred. These heat ow mechanisms are also an essential part of our ventilation and air conditioning mechanisms, adding comfort to our lives. Importantly, without heat exchange in power plants it is impossible to think of any power generation, without heat transfer the internal combustion engine could not drive our automobiles and without it, we would not be able to use our computer for long and do lengthy experiments (like this one!), without overheating and frying our electronics. -
(CFD) Modelling and Application for Sterilization of Foods: a Review
processes Review Computational Fluid Dynamics (CFD) Modelling and Application for Sterilization of Foods: A Review Hyeon Woo Park and Won Byong Yoon * ID Department of Food Science and Biotechnology, College of Agricultural and Life Science, Kangwon National University, Chuncheon 24341, Korea; [email protected] * Correspondence: [email protected]; Tel.: +82-33-250-6459 Received: 30 March 2018; Accepted: 23 May 2018; Published: 24 May 2018 Abstract: Computational fluid dynamics (CFD) is a powerful tool to model fluid flow motions for momentum, mass and energy transfer. CFD has been widely used to simulate the flow pattern and temperature distribution during the thermal processing of foods. This paper discusses the background of the thermal processing of food, and the fundamentals in developing CFD models. The constitution of simulation models is provided to enable the design of effective and efficient CFD modeling. An overview of the current CFD modeling studies of thermal processing in solid, liquid, and liquid-solid mixtures is also provided. Some limitations and unrealistic assumptions faced by CFD modelers are also discussed. Keywords: computational fluid dynamics; CFD; thermal processing; sterilization; computer simulation 1. Introduction In the food industry, thermal processing, including sterilization and pasteurization, is defined as the process by which there is the application of heat to a food product in a container, in an effort to guarantee food safety, and extend the shelf-life of processed foods [1]. Thermal processing is the most widely used preservation technology to safely produce long shelf-lives in many kinds of food, such as fruits, vegetables, milk, fish, meat and poultry, which would otherwise be quite perishable.