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A Case Study in Computational Science

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CIS/ME 794Y A Case Study in Computational Science & Engineering ... Many engineering applications and processes ... Automotive engines. Gas Turbine engines. 9 ... – PowerPoint PPT presentation

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Title: A Case Study in Computational Science


1
A Case Study in Computational Science
EngineeringSupersonic flow of ionized gas
through a nozzle
2
Course Objectives
  • To provide insight and understanding of issues
    and difficulties in computational modeling
    through a quarter-long case-study.
  • Evaluate relative merits of various methods using
    programs you have written and pre-developed
    software modules.
  • To understand the differences in performance when
    computations are done serially versus in parallel.

3
Introduction to Case Study
  • Many engineering applications and processes
    involve reacting and plasma flows.
  • Some important examples
  • plasma processes in manufacturing of integrated
    circuits (etching, deposition)
  • manufacturing processes (welding, coatings,
    synthesis of novel materials)
  • space propulsion (positioning and station-keeping
    of satellites)
  • Gas lasers, wind-tunnel test facilities,
    nozzles/shock tubes for studying chemistry

4
Manufacturing of Semiconductor Devices
A trench 0.2 mm wide by 4 mm deep in
single-crystal Si, produced by plasma etching
(from Lieberman Lichtenberg)
5
Plasma welding
6
Diamond deposition using a plasma arcjet
7
Diamond growth on silicon using an oxy-acetylene
flame
8
  • There are numerous examples of reacting flows in
    industrial applications
  • Energy generation conversion combustion
    processes
  • Automotive engines
  • Gas Turbine engines

9
Motivation for modeling
  • Gives detailed insight and basic understanding
    into the problem
  • Helpful for design, control and optimization can
    identify improved geometries for reactors,
    scale-up, etc.
  • Availability of detailed experimental
    measurements enable in-depth understanding of
    cause-effect relationships (important for process
    control).
  • Helpful in interpreting system or sensor response
    (e.g.. Ionization probe), and experimental data

10
Existing modeling tools
  • Canned programs exist
  • Fluent, Fidap, StarCD, Chemkin, etc.
  • Why write ones own code?
  • greater flexibility
  • speed (canned codes trade off speed for
    user-friendliness), and most importantly
  • ability to model additional phenomena

11
  • This quarters case study will focus on an
    illustrative example involving a supersonic flow
    in a nozzle with ionization recombination
    processes.
  • This case study is intended to help bring out
    issues related computational modeling of a
    prototypical engineering problem, using
    high-performance computing methods.

12
OSU supersonic afterglow wind-tunnel
Supersonic afterglow of Nitrogen over a wedge
Supersonic afterglow of Helium over a wedge
13
Case Study Problem
  • Argon gas flows through a converging-diverging
    channel of known cross sectional area
  • Given
  • upstream total pressure, total temperature, and
    channel geometry
  • desire supersonic flow in the diverging portion
    of the channel
  • Find
  • distributions of velocity, density, pressure,
    temperature, Mach number, electron density, and
    ionization fraction throughout the channel, at
    steady state/transient state.

14
Case Study Problem
Adiabatic walls, i.e. no heat flow
Po1 atm To300 K
L 1 m
Argon gas flow
CONVERGING-DIVERGING OR CD NOZZLE
Zone of heat addition
15
Background
  • Flow of a gas at high speeds such as in CD
    nozzles, is characterized by changing density, r.
  • the mass density, r, of a gas can change due to
    temperature changes or pressure changes. When r
    changes because of pressure changes, the flow is
    called a compressible flow.
  • To illustrate some of the basic characteristics
    of such a flow through a varying area channel, we
    begin by with a quasi one-dimensional (quasi 1-D)
    model of steady flow

16
Quasi 1-D steady flow
  • Quasi 1-D ? that flow varies in the streamwise,
    i.e. flow direction only, and transverse
    variations are ignored.
  • Steady ? , i.e., no time variation.
  • Governing equations, i.e. rules that govern such
    a flow are conservation of mass (or continuity),
    conservation of linear momentum, conservation of
    energy and species number density.

17
Governing equations for quasi 1-D flow
r(x) ni(x) P(x) T(x) u(x) A(x)
r(xdx) ni(xdx) P(xdx) T(xdx) u(xdx) A(xdx)
x
dx
xdx
18
Conservation of mass
(1)
At steady state, we have
19
Conservation of momentum
(2)
Conservation of energy
(3)
Species conservation (electrons)
(4)
20
Equation of State
(5)
Definition of Density
(6)
Unknowns r, u, P, T, ne, and nA
21
Governing equations for quasi 1-D steady flow
(1)
(2)
(3)
(4)
(5)
(6)
22
Governing equations for quasi 1-D, steady,
adiabatic, frictionless, compositionally frozen
flow
(1)
(2)
(3)
(4)
(5)
(6)
23
Choking condition
  • The foregoing equations can be combined to yield
  • where Mu/(gRT)1/2 is the Mach number based on
    the isentropic speed of sound
  • Note that when M1, dA/dx must be zero in order
    for there to be smooth acceleration through M1.
  • Further, for Mlt1, du/dxgt0 for dA/dxlt0
  • Similarly, for Mgt1, du/dxgt0 for dA/dxgt0

24
Implications of the choking condition
  • Subsonic nozzles are supersonic diffusers
  • Subsonic diffusers are supersonic nozzles

25
Two-dimensional flow
  • Conservation of mass
  • Conservation of momentum
  • Conservation of energy
  • Species conservation

Navier-Stokes Equations
y
x
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