SlideShare a Scribd company logo
Intro to Forced Convection
Forced Convection in External Flows – Lesson 1
Intro to Forced Convection
• In general, convection is the process of thermal energy transfer that occurs due to fluid motion.
‐ For example, if air is blown across a heated plate, the downstream air is hotter – thermal energy has been transferred into
the fluid and carried by it to another location.
‐ How does the heat enter the fluid? How much thermal energy can be transferred? How does the nature of the fluid flow
affect the rate of heat transfer? These questions are addressed by the science of convective heat transfer.
• Convection is classified into forced and natural (free) convection based on the mechanism responsible for
creating the fluid flow:
‐ In forced convection, the flow is generated by external means, e. g., wind or a fan, or by the object’s motion through a fluid.
‐ In natural convection, the heat transfer itself is the primary mechanism behind the fluid motion, which is generated by the
buoyancy force due to temperature gradients.
• In this course, we will focus our discussion on forced convection.
Air Flow
Temperature distribution in the air as it flows over a hot heat
sink to extract heat through the process of forced convection
Newton’s Law of Cooling/Heating Revisited
• Consider Newton’s Law of cooling/heating at a point on our heated plate. Let the local convection
heat flux be represented using the heat transfer coefficient ℎ, the incoming fluid temperature 𝑇∞ and
wall temperature 𝑇𝑤.
• At the wall, there is no motion due to the no-slip condition and the conduction heat flux in the fluid is
described by Fourier’s Law.
• These two fluxes must be equal at the wall (neglecting radiation), thus:
𝑞𝑊
′′
= ℎ 𝑇𝑤 − 𝑇∞ = −𝑘𝑓
𝜕𝑇
𝜕𝑦
ቚ𝑤
Conduction
Convection
𝑇∞
𝑇𝑤
fluid
solid
Local and Average Heat Transfer Coefficients
• In general, heat transfer is a function of space, so the heat transfer coefficient will vary (sometimes substantially)
over a surface.
• Accordingly, a local heat transfer coefficient can be defined based on the local heat flux 𝑞𝑤
′′
and wall temperature,
𝑇𝑤, as shown on the previous slide.
• For engineering purposes, an average heat transfer coefficient value for a surface is often needed in order to
estimate the heat transfer. Therefore, the local value can be area-averaged (denoted by the overbar) as follows:
ℎ = ඵ
𝐴
𝑞𝑊
′′
𝑇𝑤 − 𝑇∞
𝑑𝐴
• Note that the sign of the local heat flux 𝑞𝑤
′′
should be consistent with the local temperature difference 𝑇𝑤 − 𝑇∞
such that ℎ is always a positive number.
• The essence of the problem of convection is determining the local and averaged heat transfer coefficients, which
can subsequently be used to calculate the local flux or the total heat transfer rate.
• It is common to abbreviate the terms “heat transfer coefficient” as HTC, and we will be using this abbreviation
throughout this course.
Then, the total heat transfer rate is: 𝑞 = ℎ𝐴 𝑇𝑤 − 𝑇∞
The Nusselt Number
• Let us now non-dimensionalize the wall heat flux balance equation using 𝐿 (reference length) and 𝑇∞
(reference temperature). All the parameters (𝑇𝑊, 𝑇∞, ℎ, 𝑘𝑓) are assumed to be constant. Denoting
non-dimensional quantities with *, the heat flux balance can be rewritten as:
• The term on the left is known as the Nusselt number (𝑁𝑢). We will use the Nusselt number as a non-
dimensional measure of convective heat transfer relative to heat transfer that would occur by
conduction into the fluid.
• As defined, the Nusselt number is local if the heat transfer coefficient is local. If we employ the average
heat transfer coefficient, we obtain the average Nusselt number:
ℎ𝐿
𝑘𝑓
= −
𝑇∞
𝑇𝑊 − 𝑇∞
𝜕𝑇∗
𝜕𝑦∗ ቚ𝑤 ≡ 𝑁𝑢
𝑁𝑢 =
ത
ℎ𝐿
𝑘𝑓
The Reynolds and Prandtl Numbers
• The Nusselt number is found to correlate with two dimensionless parameters associated with the
momentum and energy equations, namely:
‐ The Reynolds Number 𝑅𝑒 =
𝜌 𝑉𝐿
𝜇
‐ The Prandtl Number 𝑃𝑟 =
𝐶𝑝𝜇
𝑘
=
𝜈
𝛼
• The Reynolds number represents the ratio of inertial forces (represented by 𝜌𝑉𝐿) in a flowing fluid to
the viscous forces (represented by 𝜇).
• The Prandtl number represents the ratio of viscous diffusion of momentum (represented by 𝜈 = 𝜇/𝜌) to
thermal diffusion in the fluid (represented by 𝛼 = 𝑘/𝜌𝐶𝑝).
The Reynolds and Prandtl Numbers (cont.)
• One of the central themes in convection heat transfer is determining the heat transfer coefficient for
specific flow configurations, e. g., flow over a heated cylinder, flow in a pipe, etc.
• This can be accomplished in two ways:
‐ Run a series of experiments in which key geometric and thermal parameters are varied and measured carefully.
For example, we can measure the heat flux from a cylinder of diameter 𝐷 which is maintained at a specific
surface temperature and exposed to a fluid flow at a given freestream temperature and velocity.
‐ Run simulations wherein the governing equations are solved using CFD techniques for specific geometries and
flow/thermal boundary conditions. This is akin to doing an “experiment,” except now we are simulating the
flow field numerically.
• It is impractical to perform experiments or run simulations for every conceivable geometry and
flow/thermal condition. Is there a way to generalize the physics? The answer is yes! We can use
Similarity Methods and Dimensionless Groups to develop correlations for common geometries and flow
configurations.
Geometric and Dynamic Similarity
• Consider a flow over two objects, where the smaller object
represents a physical model of the larger.
• Geometric similarity refers to the requirement that the ratio
of all corresponding lengths of the two objects (L1/L2,
W1/W2) are the same.
‐ Another way of saying this is that the two objects are
perfectly scaled geometrically.
• Dynamic similarity is the requirement that if the two objects
are geometrically similar, then they also have similar flow
patterns, i.e., the velocities and velocity gradients, fluid forces
and streamlines all scale with the geometry.
• For heat transfer problems, we will also require that the
temperatures, temperature gradients and heat fluxes scale
with the geometry.
L1
L2
W1
W2
Geometric and Dynamic Similarity (cont.)
• As in fluid dynamics, formal methods can be used to determine the relevant dimensionless groups for
convection heat transfer.
‐ The Nusselt number is a non-dimensional representation of heat transfer.
‐ The Prandtl number represents the relative sizes of the thermal and velocity gradients.
‐ The Reynolds Number is a non-dimensional representation of the fluid dynamics (ratio of inertial to viscous
forces).
• The requirement for similarity then is that the dimensionless groups (both flow and thermal) are
the same for a geometrically similar system.
• For the case of forced convection, two geometrically similar systems are dynamically similar if their
Nusselt, Reynolds and Prandtl Numbers are the same.
‐ Therefore, if an experiment is run with a model geometry at given Reynolds and Prandtl numbers to
determine a Nusselt number, then the Nusselt number results can be applied to a scaled-up version of the
model provided the Reynolds and Prandtl numbers are the same.
Heat Transfer Correlations
• Let’s consider a convection scenario, such as flow over a heated object of size 𝐿, with the objective to
experimentally determine how the heat transfer varies with the geometry size and flow conditions.
• From the similarity discussion, a test matrix would be set up where the Reynolds and Prandtl numbers
are systematically varied and the Nusselt number is calculated from the data obtained from the tests.
• Could a relationship between the Nusselt number and Reynolds and Prandtl numbers be found? That
is:
• It turns out, the results for a given fluid (i.e., fixed 𝑃𝑟) fall close to a straight line on a log − log scale,
and the expression for a global Nusselt number can be represented by an empirical correlation:
𝑁𝑢 = 𝐹(𝑅𝑒, 𝑃𝑟)
𝑁𝑢𝐿 = 𝐶𝑅𝑒𝑚𝑃𝑟𝑛
• Specific values of 𝐶 , 𝑚 and 𝑛 often are independent of the fluid, but they depend on the geometry of
the surface and flow type.
Heat Transfer Correlations (cont.)
Non-dimensional empirical correlation of heat transfer measurements
𝑃𝑟1
𝑃𝑟2
𝑃𝑟3
log 𝑅𝑒𝐿
log 𝑁𝑢𝐿
log 𝑅𝑒𝐿
log
𝑁𝑢𝐿
𝑃𝑟𝑛
Summary
• Convection heat transfer represents the bulk motion of heat by a flowing fluid.
• Naturally, there is an intimate connection between convection and the fluid mechanics of the flow.
• The main goal of convection analysis is to determine the heat transfer (represented by the heat
transfer coefficient) for a given geometry and flow field.
• In the next lesson, we will begin our study of the thermal boundary layer and its relation to the
velocity boundary layer. This will give us insight into the general nature of convection physics.
ansys forced convection flow powerpoints

More Related Content

PPT
Forced Convection analysis in heat transer.ppt
PPTX
forced convec.pptx
PDF
heat
PPTX
convection heat transfer convection heat
PPT
kuliah-3-fundamental-of-convection3(0).ppt
PPT
Heat transfer modes
PPTX
2014.10.28 pres cae_finale
PPTX
Heat Trans temperatures - Lecture 6.pptx
Forced Convection analysis in heat transer.ppt
forced convec.pptx
heat
convection heat transfer convection heat
kuliah-3-fundamental-of-convection3(0).ppt
Heat transfer modes
2014.10.28 pres cae_finale
Heat Trans temperatures - Lecture 6.pptx

Similar to ansys forced convection flow powerpoints (20)

PDF
Qpedia apr07 understanding_heat_transfer_coefficient
PDF
HMT CONVhdhdhdhdhdhdh hv vhvh vECTION 1.pdf
DOCX
Fundamentals of Heat and Mass Transfer, Theodore L. Bergman,.docx
PPT
convection-1.ppt
PDF
IRJET- Computational Fluid Dymamic Analysis Natural Convection Flow through S...
PPT
Mo phong CFD lien quan den truyen nhiet II
PPT
Chapter 7 EXTERNAL FORCED CONVECTION
PDF
S08 chap6 web
PPTX
Heat transfer by convection
PDF
Chapter 6 Fundamentals of convection.pdf
PPTX
Fundamentals of Convection
PPTX
Forced Convection.pptx
PPTX
Heat transfer
PPTX
Forced convection
PPTX
Basic heat transfer
PPT
F convection.ppt
PDF
Air conditioning, thermal comfort, thermodynamics
PPTX
Heat transfer
PPT
Forced convection
PPTX
MET 214 Module 3
Qpedia apr07 understanding_heat_transfer_coefficient
HMT CONVhdhdhdhdhdhdh hv vhvh vECTION 1.pdf
Fundamentals of Heat and Mass Transfer, Theodore L. Bergman,.docx
convection-1.ppt
IRJET- Computational Fluid Dymamic Analysis Natural Convection Flow through S...
Mo phong CFD lien quan den truyen nhiet II
Chapter 7 EXTERNAL FORCED CONVECTION
S08 chap6 web
Heat transfer by convection
Chapter 6 Fundamentals of convection.pdf
Fundamentals of Convection
Forced Convection.pptx
Heat transfer
Forced convection
Basic heat transfer
F convection.ppt
Air conditioning, thermal comfort, thermodynamics
Heat transfer
Forced convection
MET 214 Module 3
Ad

Recently uploaded (20)

PPTX
UNIT-1 - COAL BASED THERMAL POWER PLANTS
PDF
keyrequirementskkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkk
PDF
A SYSTEMATIC REVIEW OF APPLICATIONS IN FRAUD DETECTION
PPT
introduction to datamining and warehousing
PDF
Mohammad Mahdi Farshadian CV - Prospective PhD Student 2026
PPTX
Sustainable Sites - Green Building Construction
PDF
PPT on Performance Review to get promotions
PDF
BIO-INSPIRED HORMONAL MODULATION AND ADAPTIVE ORCHESTRATION IN S-AI-GPT
PDF
The CXO Playbook 2025 – Future-Ready Strategies for C-Suite Leaders Cerebrai...
PPTX
UNIT 4 Total Quality Management .pptx
PPTX
CYBER-CRIMES AND SECURITY A guide to understanding
PPTX
Artificial Intelligence
DOCX
ASol_English-Language-Literature-Set-1-27-02-2023-converted.docx
PPTX
Geodesy 1.pptx...............................................
PPT
Total quality management ppt for engineering students
PDF
Well-logging-methods_new................
PPTX
6ME3A-Unit-II-Sensors and Actuators_Handouts.pptx
PPTX
MET 305 2019 SCHEME MODULE 2 COMPLETE.pptx
PDF
Automation-in-Manufacturing-Chapter-Introduction.pdf
PPTX
M Tech Sem 1 Civil Engineering Environmental Sciences.pptx
UNIT-1 - COAL BASED THERMAL POWER PLANTS
keyrequirementskkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkk
A SYSTEMATIC REVIEW OF APPLICATIONS IN FRAUD DETECTION
introduction to datamining and warehousing
Mohammad Mahdi Farshadian CV - Prospective PhD Student 2026
Sustainable Sites - Green Building Construction
PPT on Performance Review to get promotions
BIO-INSPIRED HORMONAL MODULATION AND ADAPTIVE ORCHESTRATION IN S-AI-GPT
The CXO Playbook 2025 – Future-Ready Strategies for C-Suite Leaders Cerebrai...
UNIT 4 Total Quality Management .pptx
CYBER-CRIMES AND SECURITY A guide to understanding
Artificial Intelligence
ASol_English-Language-Literature-Set-1-27-02-2023-converted.docx
Geodesy 1.pptx...............................................
Total quality management ppt for engineering students
Well-logging-methods_new................
6ME3A-Unit-II-Sensors and Actuators_Handouts.pptx
MET 305 2019 SCHEME MODULE 2 COMPLETE.pptx
Automation-in-Manufacturing-Chapter-Introduction.pdf
M Tech Sem 1 Civil Engineering Environmental Sciences.pptx
Ad

ansys forced convection flow powerpoints

  • 1. Intro to Forced Convection Forced Convection in External Flows – Lesson 1
  • 2. Intro to Forced Convection • In general, convection is the process of thermal energy transfer that occurs due to fluid motion. ‐ For example, if air is blown across a heated plate, the downstream air is hotter – thermal energy has been transferred into the fluid and carried by it to another location. ‐ How does the heat enter the fluid? How much thermal energy can be transferred? How does the nature of the fluid flow affect the rate of heat transfer? These questions are addressed by the science of convective heat transfer. • Convection is classified into forced and natural (free) convection based on the mechanism responsible for creating the fluid flow: ‐ In forced convection, the flow is generated by external means, e. g., wind or a fan, or by the object’s motion through a fluid. ‐ In natural convection, the heat transfer itself is the primary mechanism behind the fluid motion, which is generated by the buoyancy force due to temperature gradients. • In this course, we will focus our discussion on forced convection. Air Flow Temperature distribution in the air as it flows over a hot heat sink to extract heat through the process of forced convection
  • 3. Newton’s Law of Cooling/Heating Revisited • Consider Newton’s Law of cooling/heating at a point on our heated plate. Let the local convection heat flux be represented using the heat transfer coefficient ℎ, the incoming fluid temperature 𝑇∞ and wall temperature 𝑇𝑤. • At the wall, there is no motion due to the no-slip condition and the conduction heat flux in the fluid is described by Fourier’s Law. • These two fluxes must be equal at the wall (neglecting radiation), thus: 𝑞𝑊 ′′ = ℎ 𝑇𝑤 − 𝑇∞ = −𝑘𝑓 𝜕𝑇 𝜕𝑦 ቚ𝑤 Conduction Convection 𝑇∞ 𝑇𝑤 fluid solid
  • 4. Local and Average Heat Transfer Coefficients • In general, heat transfer is a function of space, so the heat transfer coefficient will vary (sometimes substantially) over a surface. • Accordingly, a local heat transfer coefficient can be defined based on the local heat flux 𝑞𝑤 ′′ and wall temperature, 𝑇𝑤, as shown on the previous slide. • For engineering purposes, an average heat transfer coefficient value for a surface is often needed in order to estimate the heat transfer. Therefore, the local value can be area-averaged (denoted by the overbar) as follows: ℎ = ඵ 𝐴 𝑞𝑊 ′′ 𝑇𝑤 − 𝑇∞ 𝑑𝐴 • Note that the sign of the local heat flux 𝑞𝑤 ′′ should be consistent with the local temperature difference 𝑇𝑤 − 𝑇∞ such that ℎ is always a positive number. • The essence of the problem of convection is determining the local and averaged heat transfer coefficients, which can subsequently be used to calculate the local flux or the total heat transfer rate. • It is common to abbreviate the terms “heat transfer coefficient” as HTC, and we will be using this abbreviation throughout this course. Then, the total heat transfer rate is: 𝑞 = ℎ𝐴 𝑇𝑤 − 𝑇∞
  • 5. The Nusselt Number • Let us now non-dimensionalize the wall heat flux balance equation using 𝐿 (reference length) and 𝑇∞ (reference temperature). All the parameters (𝑇𝑊, 𝑇∞, ℎ, 𝑘𝑓) are assumed to be constant. Denoting non-dimensional quantities with *, the heat flux balance can be rewritten as: • The term on the left is known as the Nusselt number (𝑁𝑢). We will use the Nusselt number as a non- dimensional measure of convective heat transfer relative to heat transfer that would occur by conduction into the fluid. • As defined, the Nusselt number is local if the heat transfer coefficient is local. If we employ the average heat transfer coefficient, we obtain the average Nusselt number: ℎ𝐿 𝑘𝑓 = − 𝑇∞ 𝑇𝑊 − 𝑇∞ 𝜕𝑇∗ 𝜕𝑦∗ ቚ𝑤 ≡ 𝑁𝑢 𝑁𝑢 = ത ℎ𝐿 𝑘𝑓
  • 6. The Reynolds and Prandtl Numbers • The Nusselt number is found to correlate with two dimensionless parameters associated with the momentum and energy equations, namely: ‐ The Reynolds Number 𝑅𝑒 = 𝜌 𝑉𝐿 𝜇 ‐ The Prandtl Number 𝑃𝑟 = 𝐶𝑝𝜇 𝑘 = 𝜈 𝛼 • The Reynolds number represents the ratio of inertial forces (represented by 𝜌𝑉𝐿) in a flowing fluid to the viscous forces (represented by 𝜇). • The Prandtl number represents the ratio of viscous diffusion of momentum (represented by 𝜈 = 𝜇/𝜌) to thermal diffusion in the fluid (represented by 𝛼 = 𝑘/𝜌𝐶𝑝).
  • 7. The Reynolds and Prandtl Numbers (cont.) • One of the central themes in convection heat transfer is determining the heat transfer coefficient for specific flow configurations, e. g., flow over a heated cylinder, flow in a pipe, etc. • This can be accomplished in two ways: ‐ Run a series of experiments in which key geometric and thermal parameters are varied and measured carefully. For example, we can measure the heat flux from a cylinder of diameter 𝐷 which is maintained at a specific surface temperature and exposed to a fluid flow at a given freestream temperature and velocity. ‐ Run simulations wherein the governing equations are solved using CFD techniques for specific geometries and flow/thermal boundary conditions. This is akin to doing an “experiment,” except now we are simulating the flow field numerically. • It is impractical to perform experiments or run simulations for every conceivable geometry and flow/thermal condition. Is there a way to generalize the physics? The answer is yes! We can use Similarity Methods and Dimensionless Groups to develop correlations for common geometries and flow configurations.
  • 8. Geometric and Dynamic Similarity • Consider a flow over two objects, where the smaller object represents a physical model of the larger. • Geometric similarity refers to the requirement that the ratio of all corresponding lengths of the two objects (L1/L2, W1/W2) are the same. ‐ Another way of saying this is that the two objects are perfectly scaled geometrically. • Dynamic similarity is the requirement that if the two objects are geometrically similar, then they also have similar flow patterns, i.e., the velocities and velocity gradients, fluid forces and streamlines all scale with the geometry. • For heat transfer problems, we will also require that the temperatures, temperature gradients and heat fluxes scale with the geometry. L1 L2 W1 W2
  • 9. Geometric and Dynamic Similarity (cont.) • As in fluid dynamics, formal methods can be used to determine the relevant dimensionless groups for convection heat transfer. ‐ The Nusselt number is a non-dimensional representation of heat transfer. ‐ The Prandtl number represents the relative sizes of the thermal and velocity gradients. ‐ The Reynolds Number is a non-dimensional representation of the fluid dynamics (ratio of inertial to viscous forces). • The requirement for similarity then is that the dimensionless groups (both flow and thermal) are the same for a geometrically similar system. • For the case of forced convection, two geometrically similar systems are dynamically similar if their Nusselt, Reynolds and Prandtl Numbers are the same. ‐ Therefore, if an experiment is run with a model geometry at given Reynolds and Prandtl numbers to determine a Nusselt number, then the Nusselt number results can be applied to a scaled-up version of the model provided the Reynolds and Prandtl numbers are the same.
  • 10. Heat Transfer Correlations • Let’s consider a convection scenario, such as flow over a heated object of size 𝐿, with the objective to experimentally determine how the heat transfer varies with the geometry size and flow conditions. • From the similarity discussion, a test matrix would be set up where the Reynolds and Prandtl numbers are systematically varied and the Nusselt number is calculated from the data obtained from the tests. • Could a relationship between the Nusselt number and Reynolds and Prandtl numbers be found? That is: • It turns out, the results for a given fluid (i.e., fixed 𝑃𝑟) fall close to a straight line on a log − log scale, and the expression for a global Nusselt number can be represented by an empirical correlation: 𝑁𝑢 = 𝐹(𝑅𝑒, 𝑃𝑟) 𝑁𝑢𝐿 = 𝐶𝑅𝑒𝑚𝑃𝑟𝑛 • Specific values of 𝐶 , 𝑚 and 𝑛 often are independent of the fluid, but they depend on the geometry of the surface and flow type.
  • 11. Heat Transfer Correlations (cont.) Non-dimensional empirical correlation of heat transfer measurements 𝑃𝑟1 𝑃𝑟2 𝑃𝑟3 log 𝑅𝑒𝐿 log 𝑁𝑢𝐿 log 𝑅𝑒𝐿 log 𝑁𝑢𝐿 𝑃𝑟𝑛
  • 12. Summary • Convection heat transfer represents the bulk motion of heat by a flowing fluid. • Naturally, there is an intimate connection between convection and the fluid mechanics of the flow. • The main goal of convection analysis is to determine the heat transfer (represented by the heat transfer coefficient) for a given geometry and flow field. • In the next lesson, we will begin our study of the thermal boundary layer and its relation to the velocity boundary layer. This will give us insight into the general nature of convection physics.