Download GMT Enclosure Wind and Thermal Study

GMT Enclosure Wind and Thermal Study
Arash Farahani*ª, Alexy Kolesnikovb, Leighton Cochranb, Charles Hullª, Matt Johnsª
ªGMTO Corporation, 251 South Lake Ave., Suite 300, Pasadena, CA 91101, USA
b
CPP, 1415 Blue Spruce Drive, Fort Collins, CO 80524, USA
ABSTRACT
The GMT (Giant Magellan Telescope) is a large ground-based telescope for astronomical research at optical and infrared
wavelengths. The telescope is enclosed inside an Enclosure that rotates to follow the tracking of the telescope. The
Enclosure is equipped with adjustable shutters and vents to provide maximum ventilation for thermal control while
protecting the telescope from high wind loads, stray light, and severe weather conditions. The project will be built at Las
Campanas Observatory in Chile on Cerro Las Campanas. The first part of this paper presents the wind tunnel test data as
well as CFD (Computational Fluid Dynamics) study results for the GMT Enclosure. The wind tunnel tests include
simulations for: a) Topography, b) Open Enclosure (all the shutters and vents open), and c) Closed Enclosure (all the
vents and shutters closed). The CFD modeling was carried out for a wide range of conditions such as low and high wind
speeds at various wind directions, and for the fully open and partially open Enclosure. The second part of this paper
concerns the thermal effects of the Enclosure steel members. The wind speed and member sizes have been studied in
relation to the required time to reach a defined temperature inside the Enclosure. This is one of the key performance
characteristics of the Enclosure that can affect “Dome Seeing” significantly. The experimental data and theoretical
predications have been used to identify the areas inside the Enclosure that need to be ventilated. The Enclosure thermal
control strategy has been determined and an optimized system has been designed based on the final results.
Keywords: Giant Magellan Telescope (GMT), Enclosure, Wind Study, Computational Fluid Dynamics (CFD)
Modeling, Thermal Study, Dome Seeing.
1. INTRODUCTION
GMTO Corporation is the designated organization to lead the GMT (Giant Magellan Telescope) project that concerns
the design of the largest segmented ground-based telescope in the world. GMT will produce images 10 times sharper
than those from Hubble Space Telescope. The GMT telescope is enclosed inside a rotating Enclosure that allows for
maximum thermal ventilation while protecting the telescope during severe weather conditions and providing shelter
from wind loads and dust during operations. The Enclosure building is about 65 m high and 55 m in diameter. The
Enclosure rotates on an azimuth track that is supported by a static structure, the Enclosure Support Structure. The
rotating Enclosure weighs approximately 2200 metric tonnes. The Enclosure has horizontal and vertical shutters on
tracks that open up to provide the telescope with a view of the sky. The sides of the Enclosure include many wind vents
that open to modulate the flow of air through the Enclosure in order to control the inside thermal environment. The
Enclosure has a 75-tonne capacity overhead crane for maintenance operations, and provides the lifting capacity to
remove the primary mirrors in their cells for recoating. The Enclosure and its sub-systems will be controlled through
Programmable Logic Controllers (PLCs) that will interface with the observatory’s main control and software systems.
Inside the Enclosure base will be a facility with control consoles, electronics equipment, elevators and lifts. The project
will be built at Las Campanas Observatory in Chile on Cerro Las Campanas, elevation 2525 m. The Enclosure building
is shown in Figure 1.
It has been shown that the performance of the telescope is closely linked to the Enclosure thermal characteristics.
Generally, accurate prediction of the thermal behavior of the Enclosure in observatories prior to the project completion
has been one of the design challenges. This is due to a number of influential factors such as environmental conditions
(e.g. wind speed/direction, air temperature, humidity), steel member sizes, openings and ventilation systems, heat
sources, etc. The purpose of this paper is to summarize the effort that has been taken to predict the flow behavior around
and inside the Enclosure, and subsequently estimate the total effects on the GMT design and operation (e.g. HVAC
system requirements, or cooling-down time required prior to observing in order to minimize the Dome Seeing effects on
the telescope performance).
*[email protected]; Phone (+1) 626-204-0521; Fax (+1) 626-204-0504; www.gmto.org
The Enclosure wind study was conducted by carrying out a series of wind tunnel tests using various scaled models of the
Enclosure. The Enclosure CFD study was undertaken by generating the 3D model of the Enclosure for various Enclosure
configurations and wind directions. The thermal behavior of the Enclosure was studied for a wide range of conditions.
The wind and CFD results are given in the following sections.
Figure 1. Enclosure with open (left) and closed (right) shutters and vents.
2. WIND STUDY
2.1 Terrain Study
A wind-tunnel study of the topography around the GMT site was conducted to assess the impact of terrain on winds at
the top of the mountain. A model of the GMT site shown in Figure 2a was fabricated to a 1:5000 scale and placed on a
turntable in the wind tunnel (Meroney 1980). A traverse with a five-hole pressure probe, as presented in Figure 2b, was
used to measure the vertical profiles of the mean velocity and turbulence intensity for the wind azimuths influenced by
the undulating topography. These data were then used to modify the approach flow for the 1:200 pressure study of the
GMT project and to assist in establishing reasonable boundary conditions for the computational wind engineering work.
(a)
(b)
Figure 2. a) The 1:5000 terrain model used to assess the wind profiles at the mountaintop site; b) The five-hole probe used to measure
the mean velocity and turbulence intensity profiles at the site. The white circle represents the 1:200 turntable at a scale of 1:5000.
2.2 Cladding Study
A wind-tunnel study of the sealed Enclosure and Auxiliary Building was conducted to determine structural loads and
peak cladding pressures due to design-level winds. A scale model of the project was centered on a turntable in the wind
tunnel. The local terrain was constructed as part of the turntable, as shown in Figure 3a. Pressure taps were integrated
into the model to measure exterior pressures exerted by the wind. For determination of structural system loads,
fluctuating pressures were measured simultaneously at a large number of tap locations (660 taps) and spatially integrated
over the surface of the sealed Enclosure. The wind-tunnel testing was performed in the neutral boundary-layer wind
tunnel of CPP Inc., Fort Collins, Colorado (Cermak 1975). Approach boundary layers with appropriate mean profiles
and turbulence characteristics were established in the test section of the wind tunnel from the data collected from the
model shown in Figure 2b.
Measurements of external pressures were made for each pressure tap location for 36 wind directions (10 deg intervals).
The measurements were combined with directional wind statistics to produce external pressures. The external pressures
were combined with an internal pressure resulting from infiltration and air-handling systems, to obtain total cladding
pressures. Zones of total cladding pressures on the roof are presented in Figure 3b. The zones with the highest net
pressure were small areas on the roof of the sealed Enclosure. The pressures measured in the wind tunnel were converted
into non-dimensional coefficients by dividing by the wind-tunnel, mean, reference pressure. They were then combined
with a full-scale reference pressure from local wind statistics to produce a full-scale pressure. Facade pressures are based
on the extreme wind data and the choice to largely accept the peak gust of 70 m/s presented by the design team.
For the sealed Enclosure, the vents were assumed to be closed. Accordingly, an internal pressure was assumed due to
infiltration and HVAC equipment based on ASCE 7-05, was considered at all locations. For the sealed Enclosure the
internal pressure was ±0.7 kPa. Figure 3b shows some design wind pressure zones. The zones represent a simplification
of the external pressures with internal pressures as described above. For the sealed Enclosure, the most severe negative
pressure zone is -14 kPa in small regions on the roof. Zones of negative pressures over -9 kPa occur at several areas.
Positive pressure zones of +4 kPa are quite common on the walls. The minimum zone values are +3 and –3 kPa, in
recognition of the lower limits suggested in the commentary to ASCE 7-05 (Section C6.6).
(a)
(b)
Figure 3. a) The 1:200 pressure models of the sealed Enclosure and the Auxiliary Building. The Enclosure was rotated and locked in
the “stow” position for the extreme wind event; b) Cladding zones on the sealed Enclosure roof.
2.3 Structural Load Study
Forces and moments applicable to design of the structural system for the sealed Enclosure were determined from the
pressure model test. The type of model test used for this project is known as the Synchronous Pressure Method (Cochran
2010) in which the overall aerodynamic loads are synthesized from pressures measured at 660 locations on the pressuretapped model. Since the full-scale building can rotate, an agreed “stow” position (facing the Auxiliary Buildings) was
used for the extreme wind event. All loads were analyzed with respect to the building coordinate system shown in Figure
4. Base moments in a sway mode are represented as Mx and My acting about the x and y axes, respectively; the base
shears along the x and y axes are Vx and Vy; the base torque about the vertical axis is Mz. The basic dynamic properties
of the structure used for this study were the mode shapes, mass distribution, and natural frequencies provided by the
structural engineer. The damping ratio was assumed to be 0.01, a nominal value generally used for steel structures. Some
responses were evaluated with parametric values (natural frequencies and/or damping ratios) in addition to these base
values. Static-equivalent shears at the base of the building for the extreme wind event are shown in Figure 5. These
results include the effect of the dynamic response in the fundamental modes of vibration (corresponding nominally to
rotation about the x, y, and z axes respectively). Mean values are plotted using a continuous line, while peak values are
plotted using box symbols. Peak values should be used for design purposes. The primary intent of the figure is to show
the relative effect of wind directions and dynamic building properties.
The response indicated by the ‘base’ natural frequencies provided by the structural engineer will be used to examine the
structural behavior under wind in the following paragraphs. Figure 5 also shows the peak response base shears for two
additional sets of natural frequencies, which bound the base values by ±25 percent. There are two reasons for this. First,
should it become necessary or desirable to modify the structure’s properties due to the magnitude of the design loads, the
variations shown serve as a guide illustrating how the loads will change for a given change in natural frequency (note
that linear interpolation among the values shown should be reasonably accurate, and that loads are affected by natural
frequency alone, rather than mass or stiffness independently). Second, the prediction of natural frequency in a structure
can have significant uncertainties, because of assumptions which must be made regarding joint fixity, ground stiffness,
dead loads, nonlinear behavior, unintended load paths, etc., while response loads may be quite sensitive to this
parameter. The Enclosure design is quite stiff (fundamental natural frequency is about 1.3 Hz) and so the influence of
resonance is quite small (see Figure 5 – not much separation of the peak data).
NORTH
90°
0° wind
5.6
180°
5.6
34°
270°
Y
18.1
X
Z
up
18.1
Figure 4. Enclosure coordinate system.
The mean base shears along the x and y axes vary smoothly with wind direction in a near-sinusoidal fashion, completing
one cycle of variation in 360 degrees, as shown in Figure 5. Referring to the coordinate system shown in Figure 4, the x
shear is expected to be largest (in absolute value) at roughly 120 or 300 degrees, when the approach wind is along the x
axis. This is consistent with a so-called along-wind response, i.e., the primary loading is in the direction of the wind.
Similarly, the y shear is expected to be large at directions 30 and 210 degrees, when the approach wind is along the y
axis.
The along-wind-response behavior varies from this ideal sinusoidal mean action response, however, because of the
asymmetric shape of the building, because of the upwind local terrain and Auxiliary Building, and because of the
variation of design speed with direction. The variation of peak shears with wind direction follows approximately the
same pattern as mean shears, with the fluctuating portion (peak minus mean) being roughly constant at all wind
directions. At those directions where the mean load is large, this is indicative of along-wind response due to buffeting by
longitudinal turbulence in the approach wind. At wind directions where the mean load is near zero, the peak shears are in
a direction roughly perpendicular to the approach wind and are mainly due to buffeting by the lateral component of
turbulence in the approach wind and/or organized cyclical vortices generated by the building itself. This effect is of no
consequence in this building, in part due to its internal stiffness. For many buildings, however, this crosswind response
can be larger than the along-wind response. This effect is usually caused by lateral turbulence, or organized cyclical
vortices, in the wake flow generated by the building itself.
The dynamic response is due partly to resonance (i.e., response at a natural frequency due to excitation by turbulent
energy at that frequency) and partly by quasi-static response to turbulent energy at lower frequencies. At one key wind
direction of 20 degrees, the x shear is 34 percent resonant, while the y shear and z moments are 5 and 73 percent
resonant. The resonant contribution is significant because it is subject to modification by control of the dynamic
properties of the structure: this portion of the dynamic response can be reduced by increasing the natural frequency or
damping. These properties have no effect on the mean load or on the quasi-static background response.
Although the peak load in two or more components may be largest at the same wind direction, these loads will probably
not occur simultaneously due to lack of correlation in the response of different modes of vibration. In general, it is
recommended to design the structure for the simultaneous action of peak loads in the x and z directions, or y and z
directions (due to the increased likelihood of correlation between sway and torsional components), but only the mean
value of either sway component need be considered simultaneously with the peak value of the other sway component.
However, in this study the degree of correlation between calculated base shear responses was used to generate more
accurate design wind loads. A summary of the base moments and shears, with this correlation analysis included, for 10
load cases of interest were presented to the design team as floor-by-floor concentrated quasi-static loads, which were
then applied to the structural system in the structural model.
Figure 5. Design wind loads (Enclosure base shear and toque values) on the sealed Enclosure for various wind directions.
3. CFD STUDY
3.1 Objectives and General Methodology
The objective of the CFD airflow study was to provide qualitative evaluation of the airflow patterns inside the Enclosure
in order to assess natural ventilation efficiency by identifying recirculation (stagnant) zones within the space that could
negatively impact optic performance. The time frames required to flush the Enclosure with outside air, essential for
establishing efficient natural ventilation strategy, were evaluated for each of the considered configurations.
CFD is the science of utilizing advanced computer modeling techniques to solve the Navier-Stokes equations governing
fluid/gas flows. The Navier-Stokes system is derived by applying the principles of conservation of mass, momentum and
energy to a control volume of fluid (Baker, 1983). The resultant equations are extremely complex and possess no known
analytical (exact) solution. Instead, their approximate computer-simulated solutions are considered, with additional
assumptions related to turbulence modeling and properties of the flow field being made based on the physics of the
specific process. The solution is obtained using discretization techniques transforming the original, continuous partial
differential equation forms into their discrete algebraic counterparts. The resulting algebraic system is then solved
utilizing modern computer resources. The result is detailed velocity, pressure, and temperature distributions inside of a
given solution domain.
Interior airflows (the focus of the present work) are often turbulent and characterized by velocity fluctuations with a
number of irregular turbulent eddies forming within a flow structure as opposed to laminar stratified flows.
Mathematically, the ability to accurately resolve these turbulent fluctuations within the “bulk” airflow pattern combined
with appropriate physical discretization density (mesh size) during a computer simulation ultimately determine the
accuracy of the overall solution. Generally, progressively finer mesh will result in improved solution accuracy at a
greater computational cost by reducing numerical diffusion and often mitigating numerical dispersion errors associated
with numerical discretization and gradient capturing. Since mesh refinement studies are impractical for industrial scale
applications due to the exponential cost increase, it is important to combine engineering judgment and expertise with
physical data benchmarking to establish numerical solution adequacy for a given engineering design goal. Benchmarking
results are presented in the following section. Turbulence modeling and its application to the interior and exterior airflow
prediction has been a subject of numerous research studies focused on benchmarking CFD-generated results against
available experimental data. For application of various Reynolds-Averaged closure models see Chen 1995, 1996, and
Kolesnikov 2006. It is shown that major turbulence closure models with minor variations are capable of generating
accurate representation of mean airflow characteristics and are widely used in industrial scale engineering applications.
Application of Large Eddy Simulation (LES) modeling has been discussed among others by Zhang (2007) and was
shown to provide superior resolution results. Unlike Reynolds Averaging, which relies on ensemble-averaging in its
mathematical formulation and calculates mean characteristics of the flow, LES models divide the overall flow structure
into large-scale and small-scale motions (Su et al., 2001; Piomelli 1999). The large-scale motion is directly calculated,
while small-scale motion is modeled during the simulation. This approach provides instantaneous flow information as
well as mean properties of the flow, but is inherently orders of magnitude more computationally expensive, since
significantly finer grids are required to directly resolve physically meaningful smaller-scale motions.
In the present work, fully three-dimensional CFD analysis was used to predict velocities and temperatures inside the
Enclosure. Computations were performed using a commercially available software package, STAR-CD (version 4.14)
developed by CD-adapco. Full scale CFD models of various Enclosure configurations were built following geometric
details of the space. Approximate model size (depending on configuration) was 2.8 million fluid cells, with a uniform
extrusion layer of 10 mm, core mesh size of 1.6 m refined to 0.2 m at the telescope and 0.4 m at the walls. The model of
the Enclosure was placed inside a virtual wind tunnel, as shown in Figure 6. The boundary conditions consisted of the
௓ ଴.ଵଷ
approach velocity profile in the form ܷ = ܷ௥௘௙ (
)
specified at the inlet, where ܷ is the approach velocity
௓ೝ೐೑
magnitude at height above the ground ܼ (with ܼ ranging from 0 m to 500 m at the top of the computational domain), the
outlet boundary was specified at the virtual wind tunnel outlet and a symmetry plane (slip wall) was specified at the top
of the domain to avoid boundary layer formation. ܷ௥௘௙ was set at 3 m/s or 10 m/s as appropriate for a specific case under
consideration, ܼ௥௘௙ was set at 10 m and the mean wind speed profile power law exponent was set at 0.13 corresponding
to open country approach. Effects of the local terrain were neglected due to the varying viewing angle of the Enclosure
and the floor of the virtual wind tunnel was modeled as flat. Since the night-time viewing conditions were the focus of
the model, the outside air temperature was set at 12.7 C, while inside air temperature at time equal 0 seconds was set at
20 C.
The numerical solution was obtained by solving a Reynolds-Averaged Navier-Stokes equation system using the twoequation Low-Reynolds number k-ε model with hybrid wall functions to model turbulence. MARS high order spatial
discretization was used to promote solution accuracy and monotonicity. Numerical simulations were run in transient
mode with a time step varying between 0.0025 and 0.25 seconds to ensure stability and a SIMPLE based transient solver
was used in the simulations. Simulations were run until steady-state airflow conditions were established inside the
Enclosure.
Three Enclosure configurations (100%, 50%, 25% open, referred to as Configurations B, C and D respectively) were
evaluated in the study. Note that Configuration D (25% open) is simply Configuration C (50% open) with the vents all
closed. Two wind directions, namely 0-degree wind approach (normal to the main viewing opening of the Enclosure)
and 50-degree wind approach as well as two reference wind speeds (3m/s and 10 m/s) were simulated for each of the
configurations (12 simulations total).
Figure 6. Enclosure CFD model (50% open case) boundary conditions.
3.2 Wind Tunnel Data Benchmarking
Ability of the constructed CFD models to qualitatively predict the airflow velocities inside the Enclosure were
benchmarked for the 100% open Enclosure case with 0-degree wind approach and wind approach speed of 10 m/s.
Towards this goal a corresponding physical wind tunnel test was conducted utilizing five-hole pressure probes collecting
velocity data at 5 locations along the Enclosure envelope and one additional location inside the Enclosure (6 total
measurement points). Measurement locations are shown in Figure 7. The mean normal (to the viewing opening) and
vertical velocity components as well as mean velocity magnitudes measured in the experiment were normalized by the
reference wind speed at the full scale height of 150 m above the telescope site computed at 14.2 m/s according to the
specified wind approach profile. While horizontal transverse velocity component in this case is negligible and is not
directly included in benchmark evaluation, its effect is included in the velocity magnitude dataset. Identical data was
collected in the corresponding CFD simulation and the results are presented in Figure 8. Both physical wind tunnel and
CFD simulation data show identical trends in directionality and magnitude velocity distributions. The observed
difference between physical wind tunnel and CFD-predicted results ranges from 1 to 12 percent for the normal
component, 17 to 50 percent for the vertical component and between 4 to 20 percent for the overall velocity magnitude.
EQ
EQ
1
2
60.4
3
48.8
6
4
38.8
5
28.8
Ratio (U/Uref)
[Normal component]
Figure 7. Velocity measurement locations (100% open case).
0.9
0.8
0.7
Wind Tunnel
0.6
CFD
0.5
1
2
Ratio (W/Uref)
[Vertical component]
5
6
0.5
0.4
0.3
Wind Tunnel
0.2
CFD
0.1
0
1
2
(b)
Ratio (Vmag/Uref)
[Velocity magnitude]
4
Velocity Measurement Locations
(a)
3
4
Velocity Measurement Locations
5
6
0.9
0.8
0.7
Wind Tunnel
0.6
CFD
0.5
1
(c)
3
2
3
4
5
6
Velocity Measurement Locations
Figure 8. Mean normalized velocity comparison for 100% open Enclosure, 10 m/s wind speed, 0-degree wind approach. a) Normal
component; b) Vertical component; c) Velocity magnitude.
As expected largest differences are observed for vertical velocity components at locations susceptible to vertical airflow
pitch generated by terrain effects at measurement locations closest to the base of the Enclosure (locations 3, 4 and 5;
vertical component). The vertical mean velocity discrepancy is likely to come from the positive terrain slope in the 1:200
physical model versus the flat approach in the CFD model. The difference diminishes at higher measurement locations
for all observed datasets. It is noted that the observed difference in the normal velocity component, which is not expected
to be significantly affected by the local terrain does not exceed 12 percent and that the observed difference in overall
velocity magnitudes does not exceed 20 percent. Hence, with overall directional trends predicted correctly by the
simulations, the CFD predicted times necessary to flush the Enclosure with outside air provide a conservative estimate.
In that, with velocity magnitudes being under-predicted by 20 percent, the actual flush times could be lower by perhaps
as much as 20 percent consistently across the models. While progressively finer model mesh, local terrain effects via
fixed viewing location as well as a more sophisticated LES solution implementation will result in more accurate
predictions at a progressively greater cost, the obtained results provide a dataset which complements the physical wind
tunnel data, hence, the natural ventilation strategies can be made based on the CFD results.
3.3 CFD Results
Simulations performed for the 100% open Enclosure case indicate that it takes 55 seconds to flush the Enclosure with
outside air for the [10 m/s & 0-degree] wind approach case, 70 seconds for the [10 m/s & 50-degree] wind approach
case, 110 seconds for the [3 m/s & 0-degree] wind approach case and 200 seconds for the [3 m/s & 50-degree] wind
approach case. Similar data for the 50% open Enclosure case show 80, 105, 260 and 320 seconds for the wind direction
and wind speed combinations given above. The data for the 25% open case (shutters 50% open, vents closed) indicate
400, 250, 1200 and 800 seconds respectively. While it is clear that reducing the overall area open to the outside increases
the time required to flush the Enclosure, the most valuable observation perhaps relates to the fact that re-orienting the
Enclosure at an angle to the incoming wind for the 25% open case reduces the required flush time as compared to the
normal-direction wind approach case. This is due to the fact that for the 50-degree wind approach case most of the
Enclosure is dominated by the circular air movement region along the inside Enclosure walls. This air movement pattern
results in locally higher velocities inside the Enclosure and therefore reduces required flush times. Representative
horizontal vector sections depicting airflow inside the Enclosure for various considered configurations are shown in
Figures 9 and 10. The CFD results also included the Heat Transfer Coefficient estimate for the Enclosure, the data was
used to calculate the Enclosure cooling-down time as explained in the following section.
(a)
(b)
Figure 9. a) Velocity vectors, 100% open Enclosure, 3 m/s approach wind speed, 0-deg wind approach direction; b) Velocity vectors,
100% open Enclosure, 3 m/s approach wind speed, 50-deg wind approach direction.
(a)
(b)
Figure 10. a) Velocity vectors, 25% open Enclosure, 3 m/s approach wind speed, 0-deg wind approach direction; b) Velocity vectors,
25% open Enclosure, 3 m/s approach wind speed, 50-deg wind approach direction.
4. THERMAL ANALYSIS
The thermal environment inside the telescope chamber can degrade the imaging performance of the telescope if not
carefully controlled. This effect, “Dome Seeing”, is caused by turbulent mixing of air at different temperatures in the
telescope beam.
The empirical relation between Seeing and the difference in air temperature between inside and outside the Enclosure
was derived from the equation [Racine et. al. (1991)] showing the relationship between the image quality and Enclosure
air temperature relative to outside air temperature: ߠ௙௪௛௠ = 0.1"∆ܶ ଵ.ଶ , where, ߠ௙௪௛௠ is the Seeing in arcseconds. A
value of ߠ଼଴ = 0.025" is assumed for the contribution of Dome Seeing which implies a maximum temperature
difference of 0.22 K. This indicates that the air inside the Enclosure during observing should never be warmer than the
outside air by more than 0.22 K in order to satisfy the 80% encircled energy image budget of 0.025″ (0.017″ FWHM) for
this source of error.
The wind tunnel and CFD results have been used in conjunction with theoretical estimation of the key data such as heat
transfer coefficient, wind speeds, etc. A series of calculations have been generated in MathCAD format to determine the
thermal design criteria for the Enclosure. The Enclosure flushing rate range of up to 5 minutes, for most conditions such
as low wind speeds (3 m/s) and Enclosure partially open (50%), has been considered acceptable. The maximum
thickness of the Enclosure structural members (20 mm) was determined by considering the desired maximum cooling
time of about 2-2.5 hours after opening the shutters and vents. The acceptable temperature difference between the steel
and the ambient temperature is defined as 1 K. The desired cooling time is defined as the maximum time needed prior to
start of the night’s observations for the Enclosure to cool down and reach the desired temperature. The graphs,
temperature difference versus time, in Figures 11a and 11b show that the required cooling-down period will be achieved
for the low wind condition, and as a result for all the wind conditions. It should be noted that the results presented in
Figures 11a and 11b are conservative due to reasons such as: a) a higher heat transfer coefficient is expected under
operating weather conditions on site, b) a lower day and night temperature difference is expected, and c) not all the
Enclosure steel members will have the maximum thickness.
After studying the results, it was apparent that due to the design of the Enclosure openings and also the site weather
conditions, the Air Handling Units (AHUs), as specified in Conceptual Design Review (CoDR), would not be required
to control the air temperature inside the Enclosure. Hence, the Enclosure design was modified and the AHUs were
removed, resulting in two major benefits: 1) Cost saving, and 2) Telescope performance improvement. Originally, the
AHUs were located above the telescope at a level close to the horizontal shutters, by removing the AHUs the thermal
mass above the telescope was decreased and subsequently the Dome Seeing effects are expected to reduce.
It was decided to force ventilate the Enclosure in order to remove heat from the heat sources such as drive systems. The
air intakes will be located at top of the Enclosure four main columns (super-columns). The air will be sucked into the
columns using high capacity exhaust fans installed at the Enclosure exhaust tunnel below ground level. The air from the
columns will enter the Bogies Corridor that is an enclosed area around the Enclosure that rotates with the Enclosure and
contains large heat sources such as bogies, drive motors, vertical shutters drive systems, etc. The air will be directed to
the Mezzanine area and from there to the outside and then inside of the Telescope Pier. The air temperature increases as
it flows around the active heat sources and the steel members with greater temperature than that of air. Finally, the air
with the extracted waste heat will be pulled into the exhaust tunnel located at the bottom of the Telescope Pier and the
warm air will be exhausted via ducts to the outside area away from the Enclosure and at right angles to the prevailing
wind directions. The ventilation systems will be designed in a way to prevent the warm air inside the Enclosure rising
into the telescope beam and degrading the image quality.
(a)
(b)
Temperature Difference vs Time
[Wind speed (around the members): 1.5 m/s]
10.0
10.0
2 mm Thick
4 mm Thick
8.0
6 mm Thick
8 mm Thick
7.0
10 mm Thick
12 mm Thick
14 mm Thick
6.0
5.0
4.0
16 mm Thick
18 mm Thick
3.0
20 mm Thick
8.0
6 mm Thick
8 mm Thick
7.0
10 mm Thick
12 mm Thick
14 mm Thick
6.0
5.0
4.0
16 mm Thick
18 mm Thick
3.0
20 mm Thick
2.0
2.0
1.0
1.0
0.0
2 mm Thick
4 mm Thick
9.0
∆T [Temp Difference (K)]
9.0
∆T [Temp Difference (K)]
Temperature Difference vs Time
[Wind speed (around the members): 3.0 m/s]
0.0
0
15
30
45
60
75
90
105 120 135 150 165 180 195 210 225
0
t [Time (min)]
Figure 11. a) Temperature difference (between the members and
the ambient temperature) vs. Time for the Enclosure steel
members cooling from both sides for the local 1.5 m/s wind speed;
b) Temperature difference (between the members and the ambient
temperature) vs. Time for the Enclosure steel members cooling
from both sides for the local 3 m/s wind speed; c) Heat transfer
coefficient estimates (CFD results, Enclosure 100% open, 3 m/s
wind, and 0-deg wind approach direction.
15
30
45
60
75
90
105 120 135 150 165 180 195 210 225
t [Time (min)]
(c)
5. SUMMARY
The Enclosure wind study and CFD results presented in this paper provided the essential data required to design the
Enclosure and improve the telescope performance. The GMT wind study included the terrain study, cladding study, and
structural load study. The findings from the wind tunnel tests have been used to identify the areas with the high loads
and modify the structure to address the issues associated with wind. In addition, the wind effects on the design of the
shutters and bogies drive systems have been investigated based on the wind tunnel test final results. A better
understanding of the thermal behavior of the Enclosure has been obtained by studying the validated CFD results showing
the flow around and inside the Enclosure for various settings. The key parameters such as velocity, temperature, flushing
rate, heat transfer coefficient, and flow patterns have been monitored and used to optimize the design that includes
shutters, vents, and the Enclosure HVAC system. The hand calculations demonstrated that the air temperature inside the
Enclosure can be kept within the desired range in the telescope beam by controlling the structure thermal effects, for
example by limiting the steel member thickness. Hence, Dome Seeing will be minimized and as a result the telescope
performance will improve.
ACKNOWLEDGMENTS
This material is based in part upon work supported by AURA through the National Science Foundation under Scientific
Program Order No. 10 as issued for support of the Giant Segmented Mirror Telescope for the United States
Astronomical Community, in accordance with Proposal No. AST-0443999 submitted by AURA.
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