SlideShare a Scribd company logo
Stochastic ApS
Quick and dirty
First principles modelling
Scaling, Energy and Symmetry Methods
Stochastic ApS
Buckingham P theorem
Given M variables in N fundamental dimensions (m, s, kg, etc.),
there are (usually) M-N independent dimensionless combinations
of these variables (dimensionless numbers)
Drag on a sphere
Buckingham’s theorem says every one of these dimensionless
variables is a function of the others and nothing else
Drag D kgms-2
Flow speed U ms-1
Radius a m
Viscosity m kgm-1s-1
Density r kgm-3
2 2
D
U ar
5 variables, 3 dimensions
2 dimensionless parameters
Re
Uar
m
=
( )2 2
Re
D
U a

r
=
Stochastic ApS
Silencing the whistling boiler
Hot air
Water / steam
pipes
Vortex shedding or
shear layer instability
Unsteady flow forcing
Resonant
acoustic
response
Acoustic response
synchronizes flow
unsteadiness to
resonance
Stochastic ApS
Silencing the whistling boiler
Hot air
Water / steam
pipes
Vortex shedding or
shear layer instability
Unsteady flow forcing
Damped
acoustic
response
Micro-perforated plate
Stochastic ApS
Silencing the whistling boiler
Hot air
Water / steam
pipes
Vortex shedding or
shear layer instability
Unsteady flow forcing
Damped
acoustic
response
Micro-perforated plate
acoustic
velocity
acoustic
pressure
Viscous laminar
flow gives pressure
differential and loss
Stochastic ApS
Silencing the whistling boiler
Resistivity:
• Too large, pressure waves reflect and cavity just splits into two
• Too small and no loss
• Just right when
Hot boiler
How does R change with temperature and frequency?
acoustic
velocity
acoustic
pressure
Viscous laminar
flow gives pressure
differential and loss
p
u
R p u= 
R cr
d
2a
Stochastic ApS
Silencing the whistling boiler
Resistivity:
• Too large, pressure waves reflect and cavity just splits into two
• Too small and no loss
• Just right when
Hot boiler
How does R change with temperature and frequency?
acoustic
velocity
acoustic
pressure
Viscous laminar
flow gives pressure
differential and loss
p
u
R p u= 
R cr
Pressure
difference
p kgm-1s-2
velocity w ms-1
hole size a m
plate
thickness
d m
density r kgm-3
viscosity n m2s-1
frequency w s-1
7 variables, 3 dimensions
4 dimensionless parameters
a
d
( ) 2
p d a
wnr

( ) 2
2
p d a
wr

2
a
v
w
Stochastic ApS
Assume
• Small Reynolds number
• Thickness only enters in pressure drop, not in pressure gradient
• Note that p is actually a Fourier amplitude and so is even in its
real part (doesn’t care if frequency is positive or negative) and
odd in its imaginary part (has to be real when transformed back)
Silencing the whistling boiler
Resistivity:
• Too large, pressure waves reflect and cavity just splits into two
• Too small and no loss
• Just right when
Hot boiler
How does R change with temperature and frequency?
R p u= 
R cr
Pressure
difference
p kgm-1s-2
velocity w ms-1
hole size a m
plate
thickness
d m
density r kgm-3
viscosity n m2s-1
frequency w s-1
7 variables, 3 dimensions
4 dimensionless parameters
a
d
( ) 2
p d a
wnr

( ) 2
2
p d a
wr

2
a
v
w
( ) 2 2
,
p d a a a
w d
w

nr n
  
=  
 
( ) 2 2
p d a a
w
w

nr n
  
=  
 
( )
22 2 2
0 1 2
p d a a a
k ik k
w v v
w w
nr
  
= + + + 
 
Stochastic ApS
Energy methods
Statics
Potential energy in a deflection = work done making deflection
Need an expression for the potential energy in terms of the
deflection shape (bit tedious)
Approximate the deflection shape (satisfy boundary conditions) –
usually polynomials or sometimes trig functions
Differentiate the potential energy with respect to deflection to get
the force. Equate to get the deflection
Dynamics
Average kinetic energy = average potential energy
Can use to find resonant frequencies by approximating the
deflection shape
Much more useful for looking at modified systems
M


Stochastic ApS
Energy methods
Without added mass.
Kinetic energy
On average
Average potential energy is the same by Virial theorem
With added mass
Kinetic energy
On average
Average potential energy is unchanged. Apply virial theorem once more
Dynamics
Average kinetic energy = average potential energy
Can use to find resonant frequencies by approximating the
deflection shape
Much more useful for looking at modified systems
M
2 2 2
2
0
1
d sin
2 2
L u mL
T m x C t
t
w
w
  
= = 
 

( ) ( ), cosu x t y x tw= 

2 2
4
mL
T C
w
=
2 2
2 2 2 21
sin sin
2 2
M
M M M
mL
T C t M t
w
w w w

= + 
( )
2 2
4
M
T CmL M
w
= +
2
M CmL
CmL M
w
w
 
= 
+ 
Stochastic ApS
Symmetry methods
Symmetries are transformations that leave mathematical objects
unchanged (invariant)
Finding critical points using symmetry
The curve is unchanged by the reflection
Moreover, the minimum is a fixed point of this transformation
( )2y x x= −
' 2x x= −
( )( ) ( )2 ' 2 ' 2 ' ' 2y x x x x= − − − = −
min min min min min2 1x x x x x =  = −  =
Stochastic ApS
Symmetry methods
Multistaging
Reduce flow noise by staging pressure drop over several stages
Flow accelerated (isentropically) to high speed in the valve.
Non-dimensionalize sound power with stream power
Power law relation to Mach number
Compressible form of Bernoulli’s equation gives
and
so
0p 1p
2
maxQu
2 0
max
1
1
m
p
u
p
  
  − 
   
0 0
1 1
1
m m
p p
M
p p
    
 −    
     
2
max
n
aW Qu M=
1
2 2
0 0
1 1
1
n mn
m
a
p p
W
p p
+
    
 −    
     
Stochastic ApS
Symmetry methods
Multistaging
Reduce flow noise by staging pressure drop over several stages
Flow accelerated (isentropically) to high speed in the valve.
Non-dimensionalize sound power with stream power
Power law relation to Mach number
Compressible form of Bernoulli’s equation gives
and
so
0p 1p
2
maxQu
2 0
max
1
1
m
p
u
p
  
  − 
   
0 0
1 1
1
m m
p p
M
p p
    
 −    
     
2
max
n
aW Qu M=
1
2 2
0 0
1 1
1
n mn
m
a
p p
W
p p
+
    
 −    
     
0p 1p 2p 1Np − Np
We want to minimize
but we have to keep the total pressure drop fixed
Can solve by multivariate calculus with Lagrange multipliers
Or you can notice that both the sound power and the constraint are
invariant under permutations of qi.
For example, let and for all the other i.
The order of the sum and product change, but not the result.
The minimum is a fixed point so
for all possible permutations, which is only possible if all the
pressure ratios are equal.
1
1
22
0
1
mnnN
m
a i i
i
W q q
−
+
=
  − 
1
0
0
N
i
iN
p
p
q
−
=
= 
1 Nq q = 1i iq q −
 =
   1 2 1 2min min
, , , , , ,N Nq q q q q q   =

More Related Content

PDF
CMB Likelihood Part 2
PDF
Development of advanced Modal methods camarda
PPT
Admission in india 2014
PDF
Electromagnetic oscillation
PDF
Mit2 092 f09_lec11
PDF
Rhodes solutions-ch4
PPTX
W2 Example 2 Answers
CMB Likelihood Part 2
Development of advanced Modal methods camarda
Admission in india 2014
Electromagnetic oscillation
Mit2 092 f09_lec11
Rhodes solutions-ch4
W2 Example 2 Answers

What's hot (19)

PDF
Solving heat conduction equation (parabolic pde)
PPTX
Fanno Flow
PPTX
Compressible flow basics
PDF
Solucionario de fluidos_white
PDF
185817220 7e chapter5sm-final-newfrank-white-fluid-mechanics-7th-ed-ch-5-solu...
PPTX
Applications of Differential Equations of First order and First Degree
PPTX
The wkb approximation..
PDF
Notes mech v
PDF
Differential equations final -mams
PPTX
Dsp class 2
PDF
Fundamentals of Transport Phenomena ChE 715
PDF
applications of second order differential equations
PPTX
Differential Equation_Half Life
DOCX
Ch.1 fluid dynamic
PPTX
Transient analysis
PPTX
W2 Example 4 Answers
PDF
Solucionario serway cap 27
PDF
Laminar flow over a backward
DOCX
1 d heat equation
Solving heat conduction equation (parabolic pde)
Fanno Flow
Compressible flow basics
Solucionario de fluidos_white
185817220 7e chapter5sm-final-newfrank-white-fluid-mechanics-7th-ed-ch-5-solu...
Applications of Differential Equations of First order and First Degree
The wkb approximation..
Notes mech v
Differential equations final -mams
Dsp class 2
Fundamentals of Transport Phenomena ChE 715
applications of second order differential equations
Differential Equation_Half Life
Ch.1 fluid dynamic
Transient analysis
W2 Example 4 Answers
Solucionario serway cap 27
Laminar flow over a backward
1 d heat equation
Ad

Similar to Quick and dirty first principles modelling (20)

PPTX
FM CHAPTER 5.pptx
PDF
The kinetic theory of gases- physical chemistry
DOCX
Methods to determine pressure drop in an evaporator or a condenser
PDF
009a (PPT) Viscous Flow-1 New.pdf .
PDF
Gate 2017 mechanical engineering evening session
PPTX
POWER SYSTEM STABILITY for power systems.pptx
PPT
1.0 Physical Quantities and Measurement
PDF
Measurements and Dimensional Analysis.pdf
PPTX
unit-3.pptx hydraulic simil tude powerpoint
PPT
2. Fluids 2.ppt
PPTX
CL208_324_Week4 Lecture Slides Chemical Reaction Engineering.pptx
PPT
UNIT - III.ppt
PPT
volumetric properties.ppt
PDF
Momentum equation.pdf
PDF
Ejercicio 2. analisis dimensional
PDF
Lectures on Cosmological Correlations
PDF
FluidMechanicsBooklet.pdf
PPT
HUST-talk-1.pptof uncertainty quantification. Volume 6. Springer, 2017. SFK08...
PPT
2. fluids 2
PDF
PART VII.3 - Quantum Electrodynamics
FM CHAPTER 5.pptx
The kinetic theory of gases- physical chemistry
Methods to determine pressure drop in an evaporator or a condenser
009a (PPT) Viscous Flow-1 New.pdf .
Gate 2017 mechanical engineering evening session
POWER SYSTEM STABILITY for power systems.pptx
1.0 Physical Quantities and Measurement
Measurements and Dimensional Analysis.pdf
unit-3.pptx hydraulic simil tude powerpoint
2. Fluids 2.ppt
CL208_324_Week4 Lecture Slides Chemical Reaction Engineering.pptx
UNIT - III.ppt
volumetric properties.ppt
Momentum equation.pdf
Ejercicio 2. analisis dimensional
Lectures on Cosmological Correlations
FluidMechanicsBooklet.pdf
HUST-talk-1.pptof uncertainty quantification. Volume 6. Springer, 2017. SFK08...
2. fluids 2
PART VII.3 - Quantum Electrodynamics
Ad

More from Graeme Keith (9)

PDF
Look back presentation Pangloss Oil & Gas
PDF
Model Lookback Presentation
PDF
Oil and Gas exploration services - Stochastic ApS
PDF
Quantitative strategic risk management
PDF
Decision decision decision
PDF
Bayesian updating using saam data
PDF
What it costs to be rubbish at risking
PDF
The fundamental unity of strategy and risk
PDF
Bias and overconfidence in oil and gas exploration
Look back presentation Pangloss Oil & Gas
Model Lookback Presentation
Oil and Gas exploration services - Stochastic ApS
Quantitative strategic risk management
Decision decision decision
Bayesian updating using saam data
What it costs to be rubbish at risking
The fundamental unity of strategy and risk
Bias and overconfidence in oil and gas exploration

Recently uploaded (20)

PPTX
M Tech Sem 1 Civil Engineering Environmental Sciences.pptx
PDF
SM_6th-Sem__Cse_Internet-of-Things.pdf IOT
PDF
Mitigating Risks through Effective Management for Enhancing Organizational Pe...
PPTX
IOT PPTs Week 10 Lecture Material.pptx of NPTEL Smart Cities contd
PDF
The CXO Playbook 2025 – Future-Ready Strategies for C-Suite Leaders Cerebrai...
PPTX
Lecture Notes Electrical Wiring System Components
PPTX
UNIT 4 Total Quality Management .pptx
PPTX
Recipes for Real Time Voice AI WebRTC, SLMs and Open Source Software.pptx
PDF
PPT on Performance Review to get promotions
PDF
July 2025 - Top 10 Read Articles in International Journal of Software Enginee...
PDF
Enhancing Cyber Defense Against Zero-Day Attacks using Ensemble Neural Networks
PPTX
web development for engineering and engineering
PDF
Embodied AI: Ushering in the Next Era of Intelligent Systems
PDF
Mohammad Mahdi Farshadian CV - Prospective PhD Student 2026
PPT
Mechanical Engineering MATERIALS Selection
PDF
BMEC211 - INTRODUCTION TO MECHATRONICS-1.pdf
PPTX
CARTOGRAPHY AND GEOINFORMATION VISUALIZATION chapter1 NPTE (2).pptx
PPTX
UNIT-1 - COAL BASED THERMAL POWER PLANTS
PPTX
Engineering Ethics, Safety and Environment [Autosaved] (1).pptx
PPTX
Sustainable Sites - Green Building Construction
M Tech Sem 1 Civil Engineering Environmental Sciences.pptx
SM_6th-Sem__Cse_Internet-of-Things.pdf IOT
Mitigating Risks through Effective Management for Enhancing Organizational Pe...
IOT PPTs Week 10 Lecture Material.pptx of NPTEL Smart Cities contd
The CXO Playbook 2025 – Future-Ready Strategies for C-Suite Leaders Cerebrai...
Lecture Notes Electrical Wiring System Components
UNIT 4 Total Quality Management .pptx
Recipes for Real Time Voice AI WebRTC, SLMs and Open Source Software.pptx
PPT on Performance Review to get promotions
July 2025 - Top 10 Read Articles in International Journal of Software Enginee...
Enhancing Cyber Defense Against Zero-Day Attacks using Ensemble Neural Networks
web development for engineering and engineering
Embodied AI: Ushering in the Next Era of Intelligent Systems
Mohammad Mahdi Farshadian CV - Prospective PhD Student 2026
Mechanical Engineering MATERIALS Selection
BMEC211 - INTRODUCTION TO MECHATRONICS-1.pdf
CARTOGRAPHY AND GEOINFORMATION VISUALIZATION chapter1 NPTE (2).pptx
UNIT-1 - COAL BASED THERMAL POWER PLANTS
Engineering Ethics, Safety and Environment [Autosaved] (1).pptx
Sustainable Sites - Green Building Construction

Quick and dirty first principles modelling

  • 1. Stochastic ApS Quick and dirty First principles modelling Scaling, Energy and Symmetry Methods
  • 2. Stochastic ApS Buckingham P theorem Given M variables in N fundamental dimensions (m, s, kg, etc.), there are (usually) M-N independent dimensionless combinations of these variables (dimensionless numbers) Drag on a sphere Buckingham’s theorem says every one of these dimensionless variables is a function of the others and nothing else Drag D kgms-2 Flow speed U ms-1 Radius a m Viscosity m kgm-1s-1 Density r kgm-3 2 2 D U ar 5 variables, 3 dimensions 2 dimensionless parameters Re Uar m = ( )2 2 Re D U a  r =
  • 3. Stochastic ApS Silencing the whistling boiler Hot air Water / steam pipes Vortex shedding or shear layer instability Unsteady flow forcing Resonant acoustic response Acoustic response synchronizes flow unsteadiness to resonance
  • 4. Stochastic ApS Silencing the whistling boiler Hot air Water / steam pipes Vortex shedding or shear layer instability Unsteady flow forcing Damped acoustic response Micro-perforated plate
  • 5. Stochastic ApS Silencing the whistling boiler Hot air Water / steam pipes Vortex shedding or shear layer instability Unsteady flow forcing Damped acoustic response Micro-perforated plate acoustic velocity acoustic pressure Viscous laminar flow gives pressure differential and loss
  • 6. Stochastic ApS Silencing the whistling boiler Resistivity: • Too large, pressure waves reflect and cavity just splits into two • Too small and no loss • Just right when Hot boiler How does R change with temperature and frequency? acoustic velocity acoustic pressure Viscous laminar flow gives pressure differential and loss p u R p u=  R cr d 2a
  • 7. Stochastic ApS Silencing the whistling boiler Resistivity: • Too large, pressure waves reflect and cavity just splits into two • Too small and no loss • Just right when Hot boiler How does R change with temperature and frequency? acoustic velocity acoustic pressure Viscous laminar flow gives pressure differential and loss p u R p u=  R cr Pressure difference p kgm-1s-2 velocity w ms-1 hole size a m plate thickness d m density r kgm-3 viscosity n m2s-1 frequency w s-1 7 variables, 3 dimensions 4 dimensionless parameters a d ( ) 2 p d a wnr  ( ) 2 2 p d a wr  2 a v w
  • 8. Stochastic ApS Assume • Small Reynolds number • Thickness only enters in pressure drop, not in pressure gradient • Note that p is actually a Fourier amplitude and so is even in its real part (doesn’t care if frequency is positive or negative) and odd in its imaginary part (has to be real when transformed back) Silencing the whistling boiler Resistivity: • Too large, pressure waves reflect and cavity just splits into two • Too small and no loss • Just right when Hot boiler How does R change with temperature and frequency? R p u=  R cr Pressure difference p kgm-1s-2 velocity w ms-1 hole size a m plate thickness d m density r kgm-3 viscosity n m2s-1 frequency w s-1 7 variables, 3 dimensions 4 dimensionless parameters a d ( ) 2 p d a wnr  ( ) 2 2 p d a wr  2 a v w ( ) 2 2 , p d a a a w d w  nr n    =     ( ) 2 2 p d a a w w  nr n    =     ( ) 22 2 2 0 1 2 p d a a a k ik k w v v w w nr    = + + +   
  • 9. Stochastic ApS Energy methods Statics Potential energy in a deflection = work done making deflection Need an expression for the potential energy in terms of the deflection shape (bit tedious) Approximate the deflection shape (satisfy boundary conditions) – usually polynomials or sometimes trig functions Differentiate the potential energy with respect to deflection to get the force. Equate to get the deflection Dynamics Average kinetic energy = average potential energy Can use to find resonant frequencies by approximating the deflection shape Much more useful for looking at modified systems M  
  • 10. Stochastic ApS Energy methods Without added mass. Kinetic energy On average Average potential energy is the same by Virial theorem With added mass Kinetic energy On average Average potential energy is unchanged. Apply virial theorem once more Dynamics Average kinetic energy = average potential energy Can use to find resonant frequencies by approximating the deflection shape Much more useful for looking at modified systems M 2 2 2 2 0 1 d sin 2 2 L u mL T m x C t t w w    = =     ( ) ( ), cosu x t y x tw=   2 2 4 mL T C w = 2 2 2 2 2 21 sin sin 2 2 M M M M mL T C t M t w w w w  = +  ( ) 2 2 4 M T CmL M w = + 2 M CmL CmL M w w   =  + 
  • 11. Stochastic ApS Symmetry methods Symmetries are transformations that leave mathematical objects unchanged (invariant) Finding critical points using symmetry The curve is unchanged by the reflection Moreover, the minimum is a fixed point of this transformation ( )2y x x= − ' 2x x= − ( )( ) ( )2 ' 2 ' 2 ' ' 2y x x x x= − − − = − min min min min min2 1x x x x x =  = −  =
  • 12. Stochastic ApS Symmetry methods Multistaging Reduce flow noise by staging pressure drop over several stages Flow accelerated (isentropically) to high speed in the valve. Non-dimensionalize sound power with stream power Power law relation to Mach number Compressible form of Bernoulli’s equation gives and so 0p 1p 2 maxQu 2 0 max 1 1 m p u p      −      0 0 1 1 1 m m p p M p p       −           2 max n aW Qu M= 1 2 2 0 0 1 1 1 n mn m a p p W p p +       −          
  • 13. Stochastic ApS Symmetry methods Multistaging Reduce flow noise by staging pressure drop over several stages Flow accelerated (isentropically) to high speed in the valve. Non-dimensionalize sound power with stream power Power law relation to Mach number Compressible form of Bernoulli’s equation gives and so 0p 1p 2 maxQu 2 0 max 1 1 m p u p      −      0 0 1 1 1 m m p p M p p       −           2 max n aW Qu M= 1 2 2 0 0 1 1 1 n mn m a p p W p p +       −           0p 1p 2p 1Np − Np We want to minimize but we have to keep the total pressure drop fixed Can solve by multivariate calculus with Lagrange multipliers Or you can notice that both the sound power and the constraint are invariant under permutations of qi. For example, let and for all the other i. The order of the sum and product change, but not the result. The minimum is a fixed point so for all possible permutations, which is only possible if all the pressure ratios are equal. 1 1 22 0 1 mnnN m a i i i W q q − + =   −  1 0 0 N i iN p p q − = =  1 Nq q = 1i iq q −  =    1 2 1 2min min , , , , , ,N Nq q q q q q   =