George Angeli 26 November, 2001

What Do We Need to Know about Wind for GSMT?

Introduction

Wind information needed

Known (perceived) inconsistencies between models and experiments

GSMT modeling environment

What to expect from wind simulations?

Design process

Concurrent engineering (structural, optical and control)

Design verification through simulation

Feedback to reiterate and improve the design

Our approach

Structuraldesign

FEA

Realization

Opticaldesign

Ray tracing

Realization

HW/SWdesign

Controldesign

Realization

Designverification(Simulation)

MATLABSIMULINK

IDEAS

ZEMAX

Modal DE

Lin.trans.

FB DE

Lin.trans.

Our approach

Advantages Highly improved simulation speed

Significantly reduced computer requirements

Potential for more complex model

Affordable price

Each discipline (mechanical, optical, control) keeps its preferred “native” tools and environment (unlike IMOS but like IODA)

Our approach

Potential drawbacks Difficult to handle nonlinear effects in structure or

optics

Limits of the linear optical approach should be explored and established

Structural model

mΦqq

uBΦMΩqqZΩq 0T12 mmm

uBΦM

0x

ZΩΩ

I0x

q

qx

0

T12 2

m

m

Modal description:

State-Space description:

Optical model

Modal description:

Pqp OPD P - optical sensitivity

Zernike expansion:

pwrrr j

aperture

nj

aperture

jj npnZpZa d

mqWPΦWpa

Small deformations!

Ray tracing

Integrated model

K(s)

A

C1

Br1(s)

y1(s)xu(s)

G(s)

C2

r2(s)

y2(s)

Edge detector feedback

Wavefront sensor feedback

Structural dynamics

Sky motion,atmosphere

Wind, gravity,heatNoise Noise

What to expect?

Optimizing the shape and surface of structural elements to minimize the wind-to-force efficiency

Optimizing the geometry of structure to minimize the coupling of wind power into higher order modes

Recognize the need and location of additional damping and stiffening

Improve the design of the structure to make it less sensitive to wind load by

What to expect?

Optimizing the shape and surface of the dome

Aid the enclosure design to optimize its effect on the wind by

Optimizing the vents and opening on the dome to achieve the required filtering effect

What to expect?

Estimating the amplitude and bandwidth for wind induced deformation of telescope structure and primary mirror

Determining the necessary range and speed of actuators and sensors

Recognizing the need and location of actuators and sensors

Verify the control architecture by

What to expect?

Providing well defined disturbance signals to reject

Aid the design of the various feedback loops by

Help to estimate the optical performance of the telescope

Need to know…

Time evolution of wind forces on structural nodes

Velocity distribution in the vicinity of the structure with spatial sampling rate of node distances

Pressure distribution on the primary mirror with at least 3 samples per segments (to resolve torque)

Wind characteristics

Need to know… Wind-to-force conversion

Drag and lift:

Validity of first order approximation

Vortex shedding (buffeting with Strouhal frequency at low Reynolds number)

Aerodynamic attenuation of large structures

Effect of enclosure generated turbulence

U

tuUACtD D 21

2

1 2ρ

U

twUAC

U

tuUBCtL DL

22

2

121

2

1ρρ

23

4

1

if

f

Experimental wind data

0 50 100 150 200 250 300-4

-2

0

2

4

6

8

10Wind velocity at the Secondary Mirror in Series c00030oo

Time (seconds)

Win

d v

elo

city

(m

/s)

; Win

d A

zim

uth

(ra

d)

; Win

d E

leva

tion

(ra

d)

velocityazimuthelevation

Use of experimental wind data

Problems

Using Gemini South wind measurements

Limited feedback to design (no understanding of process)

Current approach

Real amplitude and direction time functions, no “assumptions”

Limited relevance (different place, different size) No simulation flexibility (given sampling rate,

sample length, amplitude, etc.) Limited environment control (vent gates, direction,

elevation, etc.)

Use of simulated wind data

CFD output

Amplitude and direction time functions

Flexible environmental and simulation parameters

Problems

Limited understanding of the process

Time and resource consuming

Off-line calculations and data transfer

Use of calculated wind data Wind generated in Matlab

Problems

Process understanding applicable to design optimization

Calculation based on mathematical wind model (mean velocity and direction, velocity, pressure and direction PSDs, cross-correlations) – filtered random variable

On-line data generation

Significant research effort

Flexible environmental and simulation parameters

Probably: simplifying assumptions

Atmospheric model

Kolmogorov’s isotropic turbulence theory

Energy cascade: large eddies ⇒ small eddies

Outer scale L0: turbulence not isotropic

Inner scale l0: turbulence disappears, energy dissipated through viscosity

Inertial subrange00

22

lL

πκ

π

3

5

,

κκ κ zFzvΦ Spatial PSD

Atmospheric model

Taylor’s frozen flow hypothesis Atmospheric “dispersion”

zU

f

TzU

πκ

λ

2

3

5

,

fzFfz fvΦ

Temporal PSD

Atmospheric model Problem

Infinite energy @ κ=0 (outside of outer scale)

Von Karman spectrum

3

42

10

2

10

1

1,

U

fc

U

fc

fzFz

m

m

DD κΦ Davenport spectrum

Solution 6

52

0

1

1,

ff

zFz vKvK κΦ

HOWEVER, inside the enclosure and around the structure the turbulence is NOT isotropic and homogenous

Basic questions How are the statistics of the random

process of wind changing due to:

How is the interaction between the wind and telescope structure changing due to:

the mountain top environment; the enclosure; the telescope itself

the enclosure; the telescope itself

Basic questions

How to scale our existing measurements to the GSMT?

What kind of additional measurements we need (if any)?

Pressure/Force PSD on primary mirror

10-2

10-1

100

101

10-2

10-1

100

101

102

103

Modified PSD of Pressure on Primary Mirror

Frequency [Hz]

PS

D o

f pre

ssu

re [P

a/H

z]

fit 0.6/f5/3

data