GMT Enclosure Wind and Thermal Study Arash Farahani*ª, Alexy Kolesnikov

b, Leighton Cochran

b, Charles Hullª, Matt Johnsª

ªGMTO Corporation, 251 South Lake Ave., Suite 300, Pasadena, CA 91101, USA bCPP, 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).

*Farahani@gmto.org; 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.

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 pressure-

tapped 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).

(a) (b)

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

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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

approach velocity profile in the form � = ����(�

��)�.�� specified at the inlet, where � is the approach velocity

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 two-

equation 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.

Figure 7. Velocity measurement locations (100% open case).

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.

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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.

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: ����� = 0.1"∆��.�, where, ����� is the Seeing in arcseconds. A

value of ��� = 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

(a) (b)

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.

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.

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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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