SlideShare a Scribd company logo
Convection Heat Transfer
Reading
12-1 → 12-8
13-1 → 13-6
14-1 → 14-4

Problems
12-41, 12-46, 12-53, 12-57, 12-76, 12-81
13-39, 13-47, 13-59
14-24, 14-29, 14-47, 14-60

Introduction
• convection heat transfer is the transport mechanism made possible through the motion of
fluid

• the controlling equation for convection is Newton’s Law of Cooling
˙
Qconv =

∆T
Rconv

= hA(Tw − T∞ )

⇒

where
A = total convective area, m2
h = heat transfer coefficient, W/(m2 · K)
1

Rconv =

1
hA
Tw = surface temperature, ◦ C
T∞ = fluid temperature, ◦ C

Factors Affecting Convective Heat Transfer
Geometry: flat plate, circular cylinder, sphere, spheroids plus many other shapes. In addition to the general shape, size, aspect ratio (thin or thick) and orientation (vertical or
horizontal) play a significant role in convective heat transfer.
Type of flow: forced, natural, mixed convection as well as laminar, turbulent and transitional flows. These flows can also be considered as developing, fully developed, steady
or transient.
Boundary condition: (i) isothermal wall (Tw = constant) or
(ii) isoflux wall (qw = constant)
˙
Type of fluid: viscous oil, water, gases (air) or liquid metals.
Fluid properties: symbols and units
mass density
specific heat capacity
dynamic viscosity
kinematic viscosity
thermal conductivity
thermal diffusivity
Prandtl number
volumetric compressibility

:
:
:
:
:
:
:
:

ρ, (kg/m3 )
Cp , (J/kg · K)
µ, (N · s/m2 )
ν, ≡ µ/ρ (m2 /s)
k, (W/m · K)
α, ≡ k/(ρ · Cp ) (m2 /s)
P r, ≡ ν/α (−−)
β, (1/K)

All properties are temperature dependent and are usually determined at the film temperature, Tf = (Tw + T∞ )/2

External Flow: the flow engulfs the body with which it interacts thermally
Internal Flow: the heat transfer surface surrounds and guides the convective stream
Forced Convection: flow is induced by an external source such as a pump, compressor, fan, etc.

2
Natural Convection: flow is induced by natural means without the assistance of an external
mechanism. The flow is initiated by a change in the density of fluids incurred as a result
of heating.
Mixed Convection: combined forced and natural convection

Dimensionless Groups
In the study and analysis of convection processes it is common practice to reduce the total number
of functional variables by forming dimensionless groups consisting of relevant thermophysical
properties, geometry, boundary and flow conditions.
Prandtl number: P r = ν/α where 0 < P r < ∞ (P r → 0 for liquid metals and P r →
∞ for viscous oils). A measure of ratio between the diffusion of momentum to the diffusion
of heat.
Reynolds number: Re = ρU L/µ ≡ U L/ν (forced convection). A measure of the balance
between the inertial forces and the viscous forces.
Peclet number: P e = U L/α ≡ ReP r
Grashof number: Gr = gβ(Tw − Tf )L3 /ν 2 (natural convection)
Rayleigh number: Ra = gβ(Tw − Tf )L3 /(α · ν) ≡ GrP r
Nusselt number: N u = hL/kf This can be considered as the dimensionless heat transfer
coefficient.
Stanton number: St = h/(U ρCp ) ≡ N u/(ReP r)

Forced Convection
The simplest forced convection configuration to consider is the flow of mass and heat near a flat
plate as shown below.

• as Reynolds number increases the flow has a tendency to become more chaotic resulting in
disordered motion known as turbulent flow
– transition from laminar to turbulent is called the critical Reynolds number, Recr
Recr =

U∞ xcr
ν

3
– for flow over a flat plate Recr ≈ 500, 000
• the thin layer immediately adjacent to the wall where viscous effects dominate is known as
the laminar sublayer

Boundary Layers

Velocity Boundary Layer
• the region of fluid flow over the plate where viscous effects dominate is called the velocity
or hydrodynamic boundary layer
Thermal Boundary Layer
• the thermal boundary layer is arbitrarily selected as the locus of points where
T − Tw
T∞ − Tw

= 0.99

4
Flow Over Plates

1. Laminar Boundary Layer Flow, Isothermal (UWT)
The local values of the skin friction and the Nusselt number are given as
Cf,x =

0.664
Re1/2
x

N ux = 0.332 Re1/2 P r 1/3
x
N uL =

hL L
kf

⇒ local, laminar, UWT, P r ≥ 0.6

1/2

= 0.664 ReL Pr1/3

⇒ average, laminar, UWT, P r ≥ 0.6

For low Prandtl numbers, i.e. liquid metals
N ux = 0.565 Re1/2 P r 1/2
x

⇒ local, laminar, UWT, P r ≤ 0.6

2. Turbulent Boundary Layer Flow, Isothermal (UWT)
Cf,x =

τw
2
(1/2)ρU∞

N ux = 0.0296

=

Re0.8
x

0.0592
Re0.2
x

Pr

1/3

⇒ local, turbulent, UWT, P r ≥ 0.6
local, turbulent, UWT,
⇒ 0.6 < P r < 100, Rex > 500, 000

5
N uL = 0.037

Re0.8
L

Pr

1/3

average, turbulent, UWT,
⇒ 0.6 < P r < 100, Rex > 500, 000

3. Combined Laminar and Turbulent Boundary Layer Flow, Isothermal (UWT)

N uL =

hL L
k

= (0.037 Re0.8 − 871) P r 1/3
L

average, combined, UWT,
0.6 < P r < 60,
⇒ 500, 000 ≤ ReL > 107

4. Laminar Boundary Layer Flow, Isoflux (UWF)

N ux = 0.453 Re1/2 P r 1/3
x

⇒ local, laminar, UWF, P r ≥ 0.6

5. Turbulent Boundary Layer Flow, Isoflux (UWF)

N ux = 0.0308 Re4/5 P r 1/3
x

⇒ local, turbulent, UWF, P r ≥ 0.6

Flow Over Cylinders and Spheres
1. Boundary Layer Flow Over Circular Cylinders, Isothermal (UWT)
The Churchill-Berstein (1977) correlation for the average Nusselt number for long (L/D > 100)
cylinders is


∗
N uD = SD + f (P r)

1/2
ReD

1

+

ReD
282, 000


5/8 4/5


average, UWT, Re < 107
⇒ 0 ≤ P r ≤ ∞, Re · P r > 0.2

∗
where SD is the diffusive term associated with ReD → 0 and is given as
∗
SD = 0.3

and the Prandtl number function is
f (P r) =

0.62 P r 1/3
[1 + (0.4/P r)2/3 ]1/4
6
All fluid properties are evaluated at Tf = (Tw + T∞ )/2.

2. Boundary Layer Flow Over Non-Circular Cylinders, Isothermal (UWT)
The empirical formulations of Zhukauskas and Jakob given in Table 12-3 are commonly used,
where

N uD ≈

hD
k

= C Rem P r 1/3
D

⇒ see Table 12-3 for conditions

3. Boundary Layer Flow Over a Sphere, Isothermal (UWT)
For flow over an isothermal sphere of diameter D

N uD =

∗
SD

+ 0.4

1/2
ReD

+ 0.06

2/3
ReD

Pr

0.4

µ∞
µw

1/4

average, UWT,
0.7 ≤ P r ≤ 380
⇒ 3.5 < ReD < 80, 000

where the diffusive term at ReD → 0 is
∗
SD = 2

and the dynamic viscosity of the fluid in the bulk flow, µ∞ is based on T∞ and the dynamic
viscosity of the fluid at the surface, µw , is based on Tw . All other properties are based on T∞ .

7
Internal Flow

The Reynolds number is given as

ReD =

Um D
ν

For flow in a tube:
ReD < 2300

laminar flow

2300 < ReD < 4000

transition to turbulent flow

ReD > 4000

turbulent flow

Hydrodynamic (Velocity) Boundary Layer
• the hydrodynamic boundary layer thickness can be approximated as

δ(x) ≈ 5x

Um x
ν

−1/2

5x
= √
Rex

• the hydrodynamic entry length can be approximated as
Lh ≈ 0.05ReD D

(laminar flow)

8
Thermal Boundary Layer

• the thermal entry length can be approximated as
Lt ≈ 0.05ReD P rD

(laminar flow)

• for turbulent flow Lh ≈ Lt ≈ 10D

Wall Boundary Conditions
1. Uniform Wall Heat Flux: Since the wall flux qw is uniform, the local mean temperature de˙
noted as
Tm,x = Tm,i +

qw A
˙
mCp
˙

will increase in a linear manner with respect to x.
The surface temperature can be determined from
Tw = Tm +

qw
˙
h

9
2. Isothermal Wall: The outlet temperature of the tube is
Tout = Tw − (Tw − Tin ) exp[−hA/(mCp )]
˙
Because of the exponential temperature decay within the tube, it is common to present the
mean temperature from inlet to outlet as a log mean temperature difference where

˙
Q = hA∆Tln
∆Tln =
ln

Tout − Tin
Tw − Tout

=

Tout − Tin
ln(∆Tout /∆Tin )

Tw − Tin

10
1. Laminar Flow in Circular Tubes, Isothermal (UWT) and Isoflux (UWF)
For laminar flow where ReD ≤ 2300
N uD = 3.66

⇒ fully developed, laminar, UWT, L > Lt & Lh

N uD = 4.36

⇒ fully developed, laminar, UWF, L > Lt & Lh

N uD = 1.86

ReD P rD
L

1/3

µb
µw

0.14

developing laminar flow, UWT,
P r > 0.5
⇒ L < Lh or L < Lt

In all cases the fluid properties are evaluated at the mean fluid temperature given as

Tmean =

1
2

(Tm,in + Tm,out )

except for µw which is evaluated at the wall temperature, Tw .
2. Turbulent Flow in Circular Tubes, Isothermal (UWT) and Isoflux (UWF)
For turbulent flow where ReD ≥ 2300 the Dittus-Bouler equation (Eq. 13-68) can be used

N uD = 0.023 Re0.8 P r n
D

turbulent flow, UWT or UWF,
0.7 ≤ P r ≤ 160
ReD > 2, 300
n = 0.4 heating
⇒ n = 0.3 cooling

For non-circular tubes, again we can use the hydraulic diameter, Dh = 4Ac /P to determine both
the Reynolds and the Nusselt numbers.
In all cases the fluid properties are evaluated at the mean fluid temperature given as

Tmean =

1
2

(Tm,in + Tm,out )

11
Natural Convection
What Drives Natural Convection?
• fluid flow is driven by the effects of buoyancy
• fluids tend to expand when heated and contract when cooled at constant pressure
• therefore a fluid layer adjacent to a surface will become lighter if heated and heavier if cooled
by the surface

Recall from forced convection that the flow behavior is determined by the Reynolds number. In
natural convection, we do not have a Reynolds number but we have an analogous dimensionless
group called the Grashof number

Gr =

buouancy force
viscous force

=

gβ(Tw − T∞ )L3
ν2

where
g = gravitational acceleration, m/s2
12
β = volumetric expansion coefficient, β ≡ 1/T
Tw = wall temperature, K
T∞ = ambient temperature, K
L = characteristic length, m
ν = kinematic viscosity, m2 /s

The volumetric expansion coefficient, β, is used to express the variation of density of the fluid with
respect to temperature and is given as

β=−

1

∂ρ

ρ

∂T

P

Natural Convection Over Surfaces
• the velocity and temperature profiles within a boundary layer formed on a vertical plate in a
stationary fluid looks as follows:

13
• note that unlike forced convection, the velocity at the edge of the boundary layer goes to zero

Natural Convection Heat Transfer Correlations
The general form of the Nusselt number for natural convection is as follows:
N u = f (Gr, P r) ≡ CGr m P r n

where Ra = Gr · P r

1. Laminar Flow Over a Vertical Plate, Isothermal (UWT)
The general form of the Nusselt number is given as
1/4 



N uL =

hL
kf

=C

 gβ(Tw




− T∞ )L3 

ν2




≡Gr






1/4

ν 

α




1/4

= C GrL P r 1/4

≡P r

Ra1/4

where
gβ(Tw − T∞ )L3

RaL = GrL P r =

αν

2. Laminar Flow Over a Long Horizontal Circular Cylinder, Isothermal (UWT)
The general boundary layer correlation is
1/4 



N uD =

hD
kf

 gβ(Tw



=C

− T∞ )D 3 

ν2




≡Gr






1/4

ν 

α
≡P r




1/4

= C GrD P r 1/4
1/4

RaD

where

RaD = GrD P r =

gβ(Tw − T∞ )L3
αν

All fluid properties are evaluated at the film temperature, Tf = (Tw + T∞ )/2.
14
Natural Convection From Plate Fin Heat Sinks
Plate fin heat sinks are often used in natural convection to increase the heat transfer surface area
and in turn reduce the boundary layer resistance

R ↓=

1
hA ↑

For a given baseplate area, W × L, two factors must be considered in the selection of the number
of fins
• more fins results in added surface area and reduced boundary layer resistance,
1
R ↓=
hA ↑
• more fins results in a decrease fin spacing, S and in turn a decrease in the heat transfer
coefficient
1
R ↑=
h↓A
A basic optimization of the fin spacing can be obtained as follows:
˙
Q = hA(Tw − T∞ )
15
where the fins are assumed to be isothermal and the surface area is 2nHL, with the area of the fin
edges ignored.
For isothermal fins with t < S

Sopt = 2.714

S3L

1/4

RaS

= 2.714

L
1/4

RaL

with

RaL =

gβ(Tw − T∞ )L3
ν2

Pr

The corresponding value of the heat transfer coefficient is
h = 1.307k/Sopt
All fluid properties are evaluated at the film temperature.

16

More Related Content

What's hot

Fluid mechanics ( 2019 2020)
Fluid mechanics ( 2019 2020)Fluid mechanics ( 2019 2020)
Fluid mechanics ( 2019 2020)
Yuri Melliza
 
Heat Convection by Latif M. Jiji - solutions
Heat Convection by Latif M. Jiji - solutionsHeat Convection by Latif M. Jiji - solutions
Fluid intro
Fluid  introFluid  intro
Fluid intro
Yasir Hashmi
 
Lecture Ch 10
Lecture Ch 10Lecture Ch 10
Lecture Ch 10rtrujill
 
Compressible flow basics
Compressible flow basicsCompressible flow basics
Compressible flow basics
George Mathew Thekkekara
 
Mechanical engineer's manual(by. engr. yuri g. melliza)
Mechanical engineer's manual(by. engr. yuri g. melliza)Mechanical engineer's manual(by. engr. yuri g. melliza)
Mechanical engineer's manual(by. engr. yuri g. melliza)
Yuri Melliza
 
Solutions manual for fluid mechanics 1st edition by hibbeler ibsn 9780133770001
Solutions manual for fluid mechanics 1st edition by hibbeler ibsn 9780133770001Solutions manual for fluid mechanics 1st edition by hibbeler ibsn 9780133770001
Solutions manual for fluid mechanics 1st edition by hibbeler ibsn 9780133770001
Beckham000
 
Heat and mass transfer equation; continuity equation; momentum equation;
Heat and mass transfer equation; continuity equation; momentum equation;Heat and mass transfer equation; continuity equation; momentum equation;
Heat and mass transfer equation; continuity equation; momentum equation;
Chandan
 
Chap 02
Chap 02Chap 02
Fox and McDonalds Introduction to Fluid Mechanics 9th Edition Pritchard Solut...
Fox and McDonalds Introduction to Fluid Mechanics 9th Edition Pritchard Solut...Fox and McDonalds Introduction to Fluid Mechanics 9th Edition Pritchard Solut...
Fox and McDonalds Introduction to Fluid Mechanics 9th Edition Pritchard Solut...
KirkMcdowells
 
Qpedia apr07 understanding_heat_transfer_coefficient
Qpedia apr07 understanding_heat_transfer_coefficientQpedia apr07 understanding_heat_transfer_coefficient
Qpedia apr07 understanding_heat_transfer_coefficient
Teguh Apriy
 
HOW TO PREDICT HEAT AND MASS TRANSFER FROM FLUID FRICTION
HOW TO PREDICT HEAT AND MASS TRANSFER FROM FLUID FRICTIONHOW TO PREDICT HEAT AND MASS TRANSFER FROM FLUID FRICTION
HOW TO PREDICT HEAT AND MASS TRANSFER FROM FLUID FRICTION
balupost
 
5
55
Liza anna jj309 fluid mechanics (buku kerja
Liza anna   jj309 fluid mechanics (buku kerjaLiza anna   jj309 fluid mechanics (buku kerja
Liza anna jj309 fluid mechanics (buku kerja
lizaannaseri
 
Fluid fundamentals
Fluid  fundamentalsFluid  fundamentals
Fluid fundamentals
Yasir Hashmi
 
Solution Manual for Heat Convection second edition by Latif M. Jiji
Solution Manual for Heat Convection second edition by Latif M. JijiSolution Manual for Heat Convection second edition by Latif M. Jiji
Solution Manual for Heat Convection second edition by Latif M. Jiji
physicsbook
 
Answers assignment 2 fluid statics-fluid mechanics
Answers assignment 2 fluid statics-fluid mechanicsAnswers assignment 2 fluid statics-fluid mechanics
Answers assignment 2 fluid statics-fluid mechanicsasghar123456
 
Thermodynamics (2013 new edition) copy
Thermodynamics (2013 new edition)   copyThermodynamics (2013 new edition)   copy
Thermodynamics (2013 new edition) copyYuri Melliza
 
Boiling and Condensation heat transfer -- EES Functions and Procedures
Boiling and Condensation heat transfer -- EES Functions and ProceduresBoiling and Condensation heat transfer -- EES Functions and Procedures
Boiling and Condensation heat transfer -- EES Functions and Procedures
tmuliya
 

What's hot (20)

Fluid mechanics ( 2019 2020)
Fluid mechanics ( 2019 2020)Fluid mechanics ( 2019 2020)
Fluid mechanics ( 2019 2020)
 
Heat Convection by Latif M. Jiji - solutions
Heat Convection by Latif M. Jiji - solutionsHeat Convection by Latif M. Jiji - solutions
Heat Convection by Latif M. Jiji - solutions
 
Fluid intro
Fluid  introFluid  intro
Fluid intro
 
Lecture Ch 10
Lecture Ch 10Lecture Ch 10
Lecture Ch 10
 
Compressible flow basics
Compressible flow basicsCompressible flow basics
Compressible flow basics
 
Mechanical engineer's manual(by. engr. yuri g. melliza)
Mechanical engineer's manual(by. engr. yuri g. melliza)Mechanical engineer's manual(by. engr. yuri g. melliza)
Mechanical engineer's manual(by. engr. yuri g. melliza)
 
Solutions manual for fluid mechanics 1st edition by hibbeler ibsn 9780133770001
Solutions manual for fluid mechanics 1st edition by hibbeler ibsn 9780133770001Solutions manual for fluid mechanics 1st edition by hibbeler ibsn 9780133770001
Solutions manual for fluid mechanics 1st edition by hibbeler ibsn 9780133770001
 
Heat and mass transfer equation; continuity equation; momentum equation;
Heat and mass transfer equation; continuity equation; momentum equation;Heat and mass transfer equation; continuity equation; momentum equation;
Heat and mass transfer equation; continuity equation; momentum equation;
 
Chap 02
Chap 02Chap 02
Chap 02
 
Fox and McDonalds Introduction to Fluid Mechanics 9th Edition Pritchard Solut...
Fox and McDonalds Introduction to Fluid Mechanics 9th Edition Pritchard Solut...Fox and McDonalds Introduction to Fluid Mechanics 9th Edition Pritchard Solut...
Fox and McDonalds Introduction to Fluid Mechanics 9th Edition Pritchard Solut...
 
Qpedia apr07 understanding_heat_transfer_coefficient
Qpedia apr07 understanding_heat_transfer_coefficientQpedia apr07 understanding_heat_transfer_coefficient
Qpedia apr07 understanding_heat_transfer_coefficient
 
HOW TO PREDICT HEAT AND MASS TRANSFER FROM FLUID FRICTION
HOW TO PREDICT HEAT AND MASS TRANSFER FROM FLUID FRICTIONHOW TO PREDICT HEAT AND MASS TRANSFER FROM FLUID FRICTION
HOW TO PREDICT HEAT AND MASS TRANSFER FROM FLUID FRICTION
 
5
55
5
 
Liza anna jj309 fluid mechanics (buku kerja
Liza anna   jj309 fluid mechanics (buku kerjaLiza anna   jj309 fluid mechanics (buku kerja
Liza anna jj309 fluid mechanics (buku kerja
 
Fluid fundamentals
Fluid  fundamentalsFluid  fundamentals
Fluid fundamentals
 
Solution Manual for Heat Convection second edition by Latif M. Jiji
Solution Manual for Heat Convection second edition by Latif M. JijiSolution Manual for Heat Convection second edition by Latif M. Jiji
Solution Manual for Heat Convection second edition by Latif M. Jiji
 
Answers assignment 2 fluid statics-fluid mechanics
Answers assignment 2 fluid statics-fluid mechanicsAnswers assignment 2 fluid statics-fluid mechanics
Answers assignment 2 fluid statics-fluid mechanics
 
Synopsis
SynopsisSynopsis
Synopsis
 
Thermodynamics (2013 new edition) copy
Thermodynamics (2013 new edition)   copyThermodynamics (2013 new edition)   copy
Thermodynamics (2013 new edition) copy
 
Boiling and Condensation heat transfer -- EES Functions and Procedures
Boiling and Condensation heat transfer -- EES Functions and ProceduresBoiling and Condensation heat transfer -- EES Functions and Procedures
Boiling and Condensation heat transfer -- EES Functions and Procedures
 

Similar to S08 chap6 web

INTRODUCTION TO CONVECTION FOR MECH.pptx
INTRODUCTION TO CONVECTION FOR MECH.pptxINTRODUCTION TO CONVECTION FOR MECH.pptx
INTRODUCTION TO CONVECTION FOR MECH.pptx
HarishPanjagala1
 
HMT CONVhdhdhdhdhdhdh hv vhvh vECTION 1.pdf
HMT CONVhdhdhdhdhdhdh hv vhvh vECTION 1.pdfHMT CONVhdhdhdhdhdhdh hv vhvh vECTION 1.pdf
HMT CONVhdhdhdhdhdhdh hv vhvh vECTION 1.pdf
RaviShankar269655
 
Fm ppt unit 5
Fm ppt unit 5Fm ppt unit 5
Fm ppt unit 5
MD ATEEQUE KHAN
 
heat
 heat heat
heat
farowk
 
convection-1.ppt
convection-1.pptconvection-1.ppt
convection-1.ppt
OISTMEHOD
 
M6TeacherSlides.pdf
M6TeacherSlides.pdfM6TeacherSlides.pdf
M6TeacherSlides.pdf
ssusercf6d0e
 
UNIT-1 CONDUCTION
UNIT-1 CONDUCTIONUNIT-1 CONDUCTION
UNIT-1 CONDUCTION
Ramesh Thiagarajan
 
kuliah-3-fundamental-of-convection3(0).ppt
kuliah-3-fundamental-of-convection3(0).pptkuliah-3-fundamental-of-convection3(0).ppt
kuliah-3-fundamental-of-convection3(0).ppt
ssuser355c2a
 
thermal considerations in pipe flows.ppt
thermal considerations in pipe flows.pptthermal considerations in pipe flows.ppt
thermal considerations in pipe flows.ppt
trialaccountforme
 
Free convection
Free convectionFree convection
Free convection
selvakumar948
 
Dimension less quantities
Dimension less quantitiesDimension less quantities
Dimension less quantities
SALONI AGARWAL
 
Heat transfer modes
Heat transfer modesHeat transfer modes
Heat transfer modes
arivazhaganrajangam
 
Mit2 092 f09_lec12
Mit2 092 f09_lec12Mit2 092 f09_lec12
Mit2 092 f09_lec12
Rahman Hakim
 
convection heat transfer convection heat
convection heat transfer convection heatconvection heat transfer convection heat
convection heat transfer convection heat
Lalerz
 
mel242-24.ppt
mel242-24.pptmel242-24.ppt
mel242-24.ppt
AvadheshSharma32
 
Chilton Colburn Analogy - Overall Concept
Chilton Colburn Analogy - Overall ConceptChilton Colburn Analogy - Overall Concept
Chilton Colburn Analogy - Overall Concept
SyedHameedAnwarSahib
 
Effects of radiation on an unsteady natural convective flow of a eg nimonic 8...
Effects of radiation on an unsteady natural convective flow of a eg nimonic 8...Effects of radiation on an unsteady natural convective flow of a eg nimonic 8...
Effects of radiation on an unsteady natural convective flow of a eg nimonic 8...
Alexander Decker
 
Fluid dynamics 1
Fluid dynamics 1Fluid dynamics 1
Fluid dynamics 1
guest7b51c7
 
Fluid dynamics 1
Fluid dynamics 1Fluid dynamics 1
Fluid dynamics 1
guest7b51c7
 

Similar to S08 chap6 web (20)

INTRODUCTION TO CONVECTION FOR MECH.pptx
INTRODUCTION TO CONVECTION FOR MECH.pptxINTRODUCTION TO CONVECTION FOR MECH.pptx
INTRODUCTION TO CONVECTION FOR MECH.pptx
 
HMT CONVhdhdhdhdhdhdh hv vhvh vECTION 1.pdf
HMT CONVhdhdhdhdhdhdh hv vhvh vECTION 1.pdfHMT CONVhdhdhdhdhdhdh hv vhvh vECTION 1.pdf
HMT CONVhdhdhdhdhdhdh hv vhvh vECTION 1.pdf
 
Fm ppt unit 5
Fm ppt unit 5Fm ppt unit 5
Fm ppt unit 5
 
heat
 heat heat
heat
 
convection-1.ppt
convection-1.pptconvection-1.ppt
convection-1.ppt
 
M6TeacherSlides.pdf
M6TeacherSlides.pdfM6TeacherSlides.pdf
M6TeacherSlides.pdf
 
UNIT-1 CONDUCTION
UNIT-1 CONDUCTIONUNIT-1 CONDUCTION
UNIT-1 CONDUCTION
 
kuliah-3-fundamental-of-convection3(0).ppt
kuliah-3-fundamental-of-convection3(0).pptkuliah-3-fundamental-of-convection3(0).ppt
kuliah-3-fundamental-of-convection3(0).ppt
 
thermal considerations in pipe flows.ppt
thermal considerations in pipe flows.pptthermal considerations in pipe flows.ppt
thermal considerations in pipe flows.ppt
 
Free convection
Free convectionFree convection
Free convection
 
Dimension less quantities
Dimension less quantitiesDimension less quantities
Dimension less quantities
 
Heat transfer modes
Heat transfer modesHeat transfer modes
Heat transfer modes
 
Mit2 092 f09_lec12
Mit2 092 f09_lec12Mit2 092 f09_lec12
Mit2 092 f09_lec12
 
convection heat transfer convection heat
convection heat transfer convection heatconvection heat transfer convection heat
convection heat transfer convection heat
 
mel242-24.ppt
mel242-24.pptmel242-24.ppt
mel242-24.ppt
 
Chilton Colburn Analogy - Overall Concept
Chilton Colburn Analogy - Overall ConceptChilton Colburn Analogy - Overall Concept
Chilton Colburn Analogy - Overall Concept
 
MET 214 Module 3
MET 214 Module 3 MET 214 Module 3
MET 214 Module 3
 
Effects of radiation on an unsteady natural convective flow of a eg nimonic 8...
Effects of radiation on an unsteady natural convective flow of a eg nimonic 8...Effects of radiation on an unsteady natural convective flow of a eg nimonic 8...
Effects of radiation on an unsteady natural convective flow of a eg nimonic 8...
 
Fluid dynamics 1
Fluid dynamics 1Fluid dynamics 1
Fluid dynamics 1
 
Fluid dynamics 1
Fluid dynamics 1Fluid dynamics 1
Fluid dynamics 1
 

Recently uploaded

UiPath Test Automation using UiPath Test Suite series, part 3
UiPath Test Automation using UiPath Test Suite series, part 3UiPath Test Automation using UiPath Test Suite series, part 3
UiPath Test Automation using UiPath Test Suite series, part 3
DianaGray10
 
JMeter webinar - integration with InfluxDB and Grafana
JMeter webinar - integration with InfluxDB and GrafanaJMeter webinar - integration with InfluxDB and Grafana
JMeter webinar - integration with InfluxDB and Grafana
RTTS
 
FIDO Alliance Osaka Seminar: Passkeys at Amazon.pdf
FIDO Alliance Osaka Seminar: Passkeys at Amazon.pdfFIDO Alliance Osaka Seminar: Passkeys at Amazon.pdf
FIDO Alliance Osaka Seminar: Passkeys at Amazon.pdf
FIDO Alliance
 
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024
Tobias Schneck
 
UiPath Test Automation using UiPath Test Suite series, part 4
UiPath Test Automation using UiPath Test Suite series, part 4UiPath Test Automation using UiPath Test Suite series, part 4
UiPath Test Automation using UiPath Test Suite series, part 4
DianaGray10
 
IOS-PENTESTING-BEGINNERS-PRACTICAL-GUIDE-.pptx
IOS-PENTESTING-BEGINNERS-PRACTICAL-GUIDE-.pptxIOS-PENTESTING-BEGINNERS-PRACTICAL-GUIDE-.pptx
IOS-PENTESTING-BEGINNERS-PRACTICAL-GUIDE-.pptx
Abida Shariff
 
How world-class product teams are winning in the AI era by CEO and Founder, P...
How world-class product teams are winning in the AI era by CEO and Founder, P...How world-class product teams are winning in the AI era by CEO and Founder, P...
How world-class product teams are winning in the AI era by CEO and Founder, P...
Product School
 
Transcript: Selling digital books in 2024: Insights from industry leaders - T...
Transcript: Selling digital books in 2024: Insights from industry leaders - T...Transcript: Selling digital books in 2024: Insights from industry leaders - T...
Transcript: Selling digital books in 2024: Insights from industry leaders - T...
BookNet Canada
 
Bits & Pixels using AI for Good.........
Bits & Pixels using AI for Good.........Bits & Pixels using AI for Good.........
Bits & Pixels using AI for Good.........
Alison B. Lowndes
 
Connector Corner: Automate dynamic content and events by pushing a button
Connector Corner: Automate dynamic content and events by pushing a buttonConnector Corner: Automate dynamic content and events by pushing a button
Connector Corner: Automate dynamic content and events by pushing a button
DianaGray10
 
"Impact of front-end architecture on development cost", Viktor Turskyi
"Impact of front-end architecture on development cost", Viktor Turskyi"Impact of front-end architecture on development cost", Viktor Turskyi
"Impact of front-end architecture on development cost", Viktor Turskyi
Fwdays
 
Epistemic Interaction - tuning interfaces to provide information for AI support
Epistemic Interaction - tuning interfaces to provide information for AI supportEpistemic Interaction - tuning interfaces to provide information for AI support
Epistemic Interaction - tuning interfaces to provide information for AI support
Alan Dix
 
FIDO Alliance Osaka Seminar: FIDO Security Aspects.pdf
FIDO Alliance Osaka Seminar: FIDO Security Aspects.pdfFIDO Alliance Osaka Seminar: FIDO Security Aspects.pdf
FIDO Alliance Osaka Seminar: FIDO Security Aspects.pdf
FIDO Alliance
 
GraphRAG is All You need? LLM & Knowledge Graph
GraphRAG is All You need? LLM & Knowledge GraphGraphRAG is All You need? LLM & Knowledge Graph
GraphRAG is All You need? LLM & Knowledge Graph
Guy Korland
 
Unsubscribed: Combat Subscription Fatigue With a Membership Mentality by Head...
Unsubscribed: Combat Subscription Fatigue With a Membership Mentality by Head...Unsubscribed: Combat Subscription Fatigue With a Membership Mentality by Head...
Unsubscribed: Combat Subscription Fatigue With a Membership Mentality by Head...
Product School
 
Essentials of Automations: Optimizing FME Workflows with Parameters
Essentials of Automations: Optimizing FME Workflows with ParametersEssentials of Automations: Optimizing FME Workflows with Parameters
Essentials of Automations: Optimizing FME Workflows with Parameters
Safe Software
 
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...
Ramesh Iyer
 
Designing Great Products: The Power of Design and Leadership by Chief Designe...
Designing Great Products: The Power of Design and Leadership by Chief Designe...Designing Great Products: The Power of Design and Leadership by Chief Designe...
Designing Great Products: The Power of Design and Leadership by Chief Designe...
Product School
 
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered Quality
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualitySoftware Delivery At the Speed of AI: Inflectra Invests In AI-Powered Quality
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered Quality
Inflectra
 
Assuring Contact Center Experiences for Your Customers With ThousandEyes
Assuring Contact Center Experiences for Your Customers With ThousandEyesAssuring Contact Center Experiences for Your Customers With ThousandEyes
Assuring Contact Center Experiences for Your Customers With ThousandEyes
ThousandEyes
 

Recently uploaded (20)

UiPath Test Automation using UiPath Test Suite series, part 3
UiPath Test Automation using UiPath Test Suite series, part 3UiPath Test Automation using UiPath Test Suite series, part 3
UiPath Test Automation using UiPath Test Suite series, part 3
 
JMeter webinar - integration with InfluxDB and Grafana
JMeter webinar - integration with InfluxDB and GrafanaJMeter webinar - integration with InfluxDB and Grafana
JMeter webinar - integration with InfluxDB and Grafana
 
FIDO Alliance Osaka Seminar: Passkeys at Amazon.pdf
FIDO Alliance Osaka Seminar: Passkeys at Amazon.pdfFIDO Alliance Osaka Seminar: Passkeys at Amazon.pdf
FIDO Alliance Osaka Seminar: Passkeys at Amazon.pdf
 
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024
 
UiPath Test Automation using UiPath Test Suite series, part 4
UiPath Test Automation using UiPath Test Suite series, part 4UiPath Test Automation using UiPath Test Suite series, part 4
UiPath Test Automation using UiPath Test Suite series, part 4
 
IOS-PENTESTING-BEGINNERS-PRACTICAL-GUIDE-.pptx
IOS-PENTESTING-BEGINNERS-PRACTICAL-GUIDE-.pptxIOS-PENTESTING-BEGINNERS-PRACTICAL-GUIDE-.pptx
IOS-PENTESTING-BEGINNERS-PRACTICAL-GUIDE-.pptx
 
How world-class product teams are winning in the AI era by CEO and Founder, P...
How world-class product teams are winning in the AI era by CEO and Founder, P...How world-class product teams are winning in the AI era by CEO and Founder, P...
How world-class product teams are winning in the AI era by CEO and Founder, P...
 
Transcript: Selling digital books in 2024: Insights from industry leaders - T...
Transcript: Selling digital books in 2024: Insights from industry leaders - T...Transcript: Selling digital books in 2024: Insights from industry leaders - T...
Transcript: Selling digital books in 2024: Insights from industry leaders - T...
 
Bits & Pixels using AI for Good.........
Bits & Pixels using AI for Good.........Bits & Pixels using AI for Good.........
Bits & Pixels using AI for Good.........
 
Connector Corner: Automate dynamic content and events by pushing a button
Connector Corner: Automate dynamic content and events by pushing a buttonConnector Corner: Automate dynamic content and events by pushing a button
Connector Corner: Automate dynamic content and events by pushing a button
 
"Impact of front-end architecture on development cost", Viktor Turskyi
"Impact of front-end architecture on development cost", Viktor Turskyi"Impact of front-end architecture on development cost", Viktor Turskyi
"Impact of front-end architecture on development cost", Viktor Turskyi
 
Epistemic Interaction - tuning interfaces to provide information for AI support
Epistemic Interaction - tuning interfaces to provide information for AI supportEpistemic Interaction - tuning interfaces to provide information for AI support
Epistemic Interaction - tuning interfaces to provide information for AI support
 
FIDO Alliance Osaka Seminar: FIDO Security Aspects.pdf
FIDO Alliance Osaka Seminar: FIDO Security Aspects.pdfFIDO Alliance Osaka Seminar: FIDO Security Aspects.pdf
FIDO Alliance Osaka Seminar: FIDO Security Aspects.pdf
 
GraphRAG is All You need? LLM & Knowledge Graph
GraphRAG is All You need? LLM & Knowledge GraphGraphRAG is All You need? LLM & Knowledge Graph
GraphRAG is All You need? LLM & Knowledge Graph
 
Unsubscribed: Combat Subscription Fatigue With a Membership Mentality by Head...
Unsubscribed: Combat Subscription Fatigue With a Membership Mentality by Head...Unsubscribed: Combat Subscription Fatigue With a Membership Mentality by Head...
Unsubscribed: Combat Subscription Fatigue With a Membership Mentality by Head...
 
Essentials of Automations: Optimizing FME Workflows with Parameters
Essentials of Automations: Optimizing FME Workflows with ParametersEssentials of Automations: Optimizing FME Workflows with Parameters
Essentials of Automations: Optimizing FME Workflows with Parameters
 
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...
 
Designing Great Products: The Power of Design and Leadership by Chief Designe...
Designing Great Products: The Power of Design and Leadership by Chief Designe...Designing Great Products: The Power of Design and Leadership by Chief Designe...
Designing Great Products: The Power of Design and Leadership by Chief Designe...
 
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered Quality
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualitySoftware Delivery At the Speed of AI: Inflectra Invests In AI-Powered Quality
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered Quality
 
Assuring Contact Center Experiences for Your Customers With ThousandEyes
Assuring Contact Center Experiences for Your Customers With ThousandEyesAssuring Contact Center Experiences for Your Customers With ThousandEyes
Assuring Contact Center Experiences for Your Customers With ThousandEyes
 

S08 chap6 web

  • 1. Convection Heat Transfer Reading 12-1 → 12-8 13-1 → 13-6 14-1 → 14-4 Problems 12-41, 12-46, 12-53, 12-57, 12-76, 12-81 13-39, 13-47, 13-59 14-24, 14-29, 14-47, 14-60 Introduction • convection heat transfer is the transport mechanism made possible through the motion of fluid • the controlling equation for convection is Newton’s Law of Cooling ˙ Qconv = ∆T Rconv = hA(Tw − T∞ ) ⇒ where A = total convective area, m2 h = heat transfer coefficient, W/(m2 · K) 1 Rconv = 1 hA
  • 2. Tw = surface temperature, ◦ C T∞ = fluid temperature, ◦ C Factors Affecting Convective Heat Transfer Geometry: flat plate, circular cylinder, sphere, spheroids plus many other shapes. In addition to the general shape, size, aspect ratio (thin or thick) and orientation (vertical or horizontal) play a significant role in convective heat transfer. Type of flow: forced, natural, mixed convection as well as laminar, turbulent and transitional flows. These flows can also be considered as developing, fully developed, steady or transient. Boundary condition: (i) isothermal wall (Tw = constant) or (ii) isoflux wall (qw = constant) ˙ Type of fluid: viscous oil, water, gases (air) or liquid metals. Fluid properties: symbols and units mass density specific heat capacity dynamic viscosity kinematic viscosity thermal conductivity thermal diffusivity Prandtl number volumetric compressibility : : : : : : : : ρ, (kg/m3 ) Cp , (J/kg · K) µ, (N · s/m2 ) ν, ≡ µ/ρ (m2 /s) k, (W/m · K) α, ≡ k/(ρ · Cp ) (m2 /s) P r, ≡ ν/α (−−) β, (1/K) All properties are temperature dependent and are usually determined at the film temperature, Tf = (Tw + T∞ )/2 External Flow: the flow engulfs the body with which it interacts thermally Internal Flow: the heat transfer surface surrounds and guides the convective stream Forced Convection: flow is induced by an external source such as a pump, compressor, fan, etc. 2
  • 3. Natural Convection: flow is induced by natural means without the assistance of an external mechanism. The flow is initiated by a change in the density of fluids incurred as a result of heating. Mixed Convection: combined forced and natural convection Dimensionless Groups In the study and analysis of convection processes it is common practice to reduce the total number of functional variables by forming dimensionless groups consisting of relevant thermophysical properties, geometry, boundary and flow conditions. Prandtl number: P r = ν/α where 0 < P r < ∞ (P r → 0 for liquid metals and P r → ∞ for viscous oils). A measure of ratio between the diffusion of momentum to the diffusion of heat. Reynolds number: Re = ρU L/µ ≡ U L/ν (forced convection). A measure of the balance between the inertial forces and the viscous forces. Peclet number: P e = U L/α ≡ ReP r Grashof number: Gr = gβ(Tw − Tf )L3 /ν 2 (natural convection) Rayleigh number: Ra = gβ(Tw − Tf )L3 /(α · ν) ≡ GrP r Nusselt number: N u = hL/kf This can be considered as the dimensionless heat transfer coefficient. Stanton number: St = h/(U ρCp ) ≡ N u/(ReP r) Forced Convection The simplest forced convection configuration to consider is the flow of mass and heat near a flat plate as shown below. • as Reynolds number increases the flow has a tendency to become more chaotic resulting in disordered motion known as turbulent flow – transition from laminar to turbulent is called the critical Reynolds number, Recr Recr = U∞ xcr ν 3
  • 4. – for flow over a flat plate Recr ≈ 500, 000 • the thin layer immediately adjacent to the wall where viscous effects dominate is known as the laminar sublayer Boundary Layers Velocity Boundary Layer • the region of fluid flow over the plate where viscous effects dominate is called the velocity or hydrodynamic boundary layer Thermal Boundary Layer • the thermal boundary layer is arbitrarily selected as the locus of points where T − Tw T∞ − Tw = 0.99 4
  • 5. Flow Over Plates 1. Laminar Boundary Layer Flow, Isothermal (UWT) The local values of the skin friction and the Nusselt number are given as Cf,x = 0.664 Re1/2 x N ux = 0.332 Re1/2 P r 1/3 x N uL = hL L kf ⇒ local, laminar, UWT, P r ≥ 0.6 1/2 = 0.664 ReL Pr1/3 ⇒ average, laminar, UWT, P r ≥ 0.6 For low Prandtl numbers, i.e. liquid metals N ux = 0.565 Re1/2 P r 1/2 x ⇒ local, laminar, UWT, P r ≤ 0.6 2. Turbulent Boundary Layer Flow, Isothermal (UWT) Cf,x = τw 2 (1/2)ρU∞ N ux = 0.0296 = Re0.8 x 0.0592 Re0.2 x Pr 1/3 ⇒ local, turbulent, UWT, P r ≥ 0.6 local, turbulent, UWT, ⇒ 0.6 < P r < 100, Rex > 500, 000 5
  • 6. N uL = 0.037 Re0.8 L Pr 1/3 average, turbulent, UWT, ⇒ 0.6 < P r < 100, Rex > 500, 000 3. Combined Laminar and Turbulent Boundary Layer Flow, Isothermal (UWT) N uL = hL L k = (0.037 Re0.8 − 871) P r 1/3 L average, combined, UWT, 0.6 < P r < 60, ⇒ 500, 000 ≤ ReL > 107 4. Laminar Boundary Layer Flow, Isoflux (UWF) N ux = 0.453 Re1/2 P r 1/3 x ⇒ local, laminar, UWF, P r ≥ 0.6 5. Turbulent Boundary Layer Flow, Isoflux (UWF) N ux = 0.0308 Re4/5 P r 1/3 x ⇒ local, turbulent, UWF, P r ≥ 0.6 Flow Over Cylinders and Spheres 1. Boundary Layer Flow Over Circular Cylinders, Isothermal (UWT) The Churchill-Berstein (1977) correlation for the average Nusselt number for long (L/D > 100) cylinders is  ∗ N uD = SD + f (P r) 1/2 ReD 1 + ReD 282, 000  5/8 4/5  average, UWT, Re < 107 ⇒ 0 ≤ P r ≤ ∞, Re · P r > 0.2 ∗ where SD is the diffusive term associated with ReD → 0 and is given as ∗ SD = 0.3 and the Prandtl number function is f (P r) = 0.62 P r 1/3 [1 + (0.4/P r)2/3 ]1/4 6
  • 7. All fluid properties are evaluated at Tf = (Tw + T∞ )/2. 2. Boundary Layer Flow Over Non-Circular Cylinders, Isothermal (UWT) The empirical formulations of Zhukauskas and Jakob given in Table 12-3 are commonly used, where N uD ≈ hD k = C Rem P r 1/3 D ⇒ see Table 12-3 for conditions 3. Boundary Layer Flow Over a Sphere, Isothermal (UWT) For flow over an isothermal sphere of diameter D N uD = ∗ SD + 0.4 1/2 ReD + 0.06 2/3 ReD Pr 0.4 µ∞ µw 1/4 average, UWT, 0.7 ≤ P r ≤ 380 ⇒ 3.5 < ReD < 80, 000 where the diffusive term at ReD → 0 is ∗ SD = 2 and the dynamic viscosity of the fluid in the bulk flow, µ∞ is based on T∞ and the dynamic viscosity of the fluid at the surface, µw , is based on Tw . All other properties are based on T∞ . 7
  • 8. Internal Flow The Reynolds number is given as ReD = Um D ν For flow in a tube: ReD < 2300 laminar flow 2300 < ReD < 4000 transition to turbulent flow ReD > 4000 turbulent flow Hydrodynamic (Velocity) Boundary Layer • the hydrodynamic boundary layer thickness can be approximated as δ(x) ≈ 5x Um x ν −1/2 5x = √ Rex • the hydrodynamic entry length can be approximated as Lh ≈ 0.05ReD D (laminar flow) 8
  • 9. Thermal Boundary Layer • the thermal entry length can be approximated as Lt ≈ 0.05ReD P rD (laminar flow) • for turbulent flow Lh ≈ Lt ≈ 10D Wall Boundary Conditions 1. Uniform Wall Heat Flux: Since the wall flux qw is uniform, the local mean temperature de˙ noted as Tm,x = Tm,i + qw A ˙ mCp ˙ will increase in a linear manner with respect to x. The surface temperature can be determined from Tw = Tm + qw ˙ h 9
  • 10. 2. Isothermal Wall: The outlet temperature of the tube is Tout = Tw − (Tw − Tin ) exp[−hA/(mCp )] ˙ Because of the exponential temperature decay within the tube, it is common to present the mean temperature from inlet to outlet as a log mean temperature difference where ˙ Q = hA∆Tln ∆Tln = ln Tout − Tin Tw − Tout = Tout − Tin ln(∆Tout /∆Tin ) Tw − Tin 10
  • 11. 1. Laminar Flow in Circular Tubes, Isothermal (UWT) and Isoflux (UWF) For laminar flow where ReD ≤ 2300 N uD = 3.66 ⇒ fully developed, laminar, UWT, L > Lt & Lh N uD = 4.36 ⇒ fully developed, laminar, UWF, L > Lt & Lh N uD = 1.86 ReD P rD L 1/3 µb µw 0.14 developing laminar flow, UWT, P r > 0.5 ⇒ L < Lh or L < Lt In all cases the fluid properties are evaluated at the mean fluid temperature given as Tmean = 1 2 (Tm,in + Tm,out ) except for µw which is evaluated at the wall temperature, Tw . 2. Turbulent Flow in Circular Tubes, Isothermal (UWT) and Isoflux (UWF) For turbulent flow where ReD ≥ 2300 the Dittus-Bouler equation (Eq. 13-68) can be used N uD = 0.023 Re0.8 P r n D turbulent flow, UWT or UWF, 0.7 ≤ P r ≤ 160 ReD > 2, 300 n = 0.4 heating ⇒ n = 0.3 cooling For non-circular tubes, again we can use the hydraulic diameter, Dh = 4Ac /P to determine both the Reynolds and the Nusselt numbers. In all cases the fluid properties are evaluated at the mean fluid temperature given as Tmean = 1 2 (Tm,in + Tm,out ) 11
  • 12. Natural Convection What Drives Natural Convection? • fluid flow is driven by the effects of buoyancy • fluids tend to expand when heated and contract when cooled at constant pressure • therefore a fluid layer adjacent to a surface will become lighter if heated and heavier if cooled by the surface Recall from forced convection that the flow behavior is determined by the Reynolds number. In natural convection, we do not have a Reynolds number but we have an analogous dimensionless group called the Grashof number Gr = buouancy force viscous force = gβ(Tw − T∞ )L3 ν2 where g = gravitational acceleration, m/s2 12
  • 13. β = volumetric expansion coefficient, β ≡ 1/T Tw = wall temperature, K T∞ = ambient temperature, K L = characteristic length, m ν = kinematic viscosity, m2 /s The volumetric expansion coefficient, β, is used to express the variation of density of the fluid with respect to temperature and is given as β=− 1 ∂ρ ρ ∂T P Natural Convection Over Surfaces • the velocity and temperature profiles within a boundary layer formed on a vertical plate in a stationary fluid looks as follows: 13
  • 14. • note that unlike forced convection, the velocity at the edge of the boundary layer goes to zero Natural Convection Heat Transfer Correlations The general form of the Nusselt number for natural convection is as follows: N u = f (Gr, P r) ≡ CGr m P r n where Ra = Gr · P r 1. Laminar Flow Over a Vertical Plate, Isothermal (UWT) The general form of the Nusselt number is given as 1/4   N uL = hL kf =C  gβ(Tw    − T∞ )L3   ν2   ≡Gr     1/4 ν   α   1/4 = C GrL P r 1/4 ≡P r Ra1/4 where gβ(Tw − T∞ )L3 RaL = GrL P r = αν 2. Laminar Flow Over a Long Horizontal Circular Cylinder, Isothermal (UWT) The general boundary layer correlation is 1/4   N uD = hD kf  gβ(Tw   =C − T∞ )D 3   ν2   ≡Gr     1/4 ν   α ≡P r   1/4 = C GrD P r 1/4 1/4 RaD where RaD = GrD P r = gβ(Tw − T∞ )L3 αν All fluid properties are evaluated at the film temperature, Tf = (Tw + T∞ )/2. 14
  • 15. Natural Convection From Plate Fin Heat Sinks Plate fin heat sinks are often used in natural convection to increase the heat transfer surface area and in turn reduce the boundary layer resistance R ↓= 1 hA ↑ For a given baseplate area, W × L, two factors must be considered in the selection of the number of fins • more fins results in added surface area and reduced boundary layer resistance, 1 R ↓= hA ↑ • more fins results in a decrease fin spacing, S and in turn a decrease in the heat transfer coefficient 1 R ↑= h↓A A basic optimization of the fin spacing can be obtained as follows: ˙ Q = hA(Tw − T∞ ) 15
  • 16. where the fins are assumed to be isothermal and the surface area is 2nHL, with the area of the fin edges ignored. For isothermal fins with t < S Sopt = 2.714 S3L 1/4 RaS = 2.714 L 1/4 RaL with RaL = gβ(Tw − T∞ )L3 ν2 Pr The corresponding value of the heat transfer coefficient is h = 1.307k/Sopt All fluid properties are evaluated at the film temperature. 16