ABSTRACT 1. INTRODUCTION

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1 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 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). *Farahani@gmto.org; Phone (+1) ; Fax (+1) ;

2 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. 2.1 Terrain Study 2. WIND 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.

3 (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: 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).

4 (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 M x and M y acting about the x and y axes, respectively; the base shears along the x and y axes are V x and V y ; the base torque about the vertical axis is M z. 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).

5 NORTH 0 wind Y Z up X 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

6 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.

7 3.1 Objectives and General Methodology 3. CFD STUDY 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 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

8 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 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.

9 EQ EQ Figure 7. Velocity measurement locations (100% open case). Ratio (U/Uref) [Normal component] (a) Velocity Measurement Locations Wind Tunnel CFD Ratio (W/Uref) [Vertical component] (b) Velocity Measurement Locations Wind Tunnel CFD Ratio (Vmag/Uref) [Velocity magnitude] (c) Velocity Measurement Locations Wind Tunnel CFD 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.

10 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.

11 (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 (0.017 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 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

12 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) Temperature Difference vs Time [Wind speed (around the members): 1.5 m/s] (b) Temperature Difference vs Time [Wind speed (around the members): 3.0 m/s] T [Temp Difference (K)] mm Thick 4 mm Thick 6 mm Thick 8 mm Thick 10 mm Thick 12 mm Thick 14 mm Thick 16 mm Thick 18 mm Thick 20 mm Thick T [Temp Difference (K)] mm Thick 4 mm Thick 6 mm Thick 8 mm Thick 10 mm Thick 12 mm Thick 14 mm Thick 16 mm Thick 18 mm Thick 20 mm Thick t [Time (min)] 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. (c)

13 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 submitted by AURA. REFERENCES [1] Cermak, J.E., Application of Fluid Mechanics to Wind Engineering, A Freeman Scholar Lecture, Journal of Fluids Engineering, American Society of Mechanical Engineers, Volume 97, No. 1, March [2] American Society of Civil Engineers, "Minimum Design Loads for Buildings and Other Structures", ASCE 7-05, 330 pages, [3] Cochran, L.S., Contemporary Architectural Aerodynamics and the Future of Wind Engineering, Proceedings of The International Workshop on Wind Engineering Research and Practice, Chapel Hill, North Carolina, 23 pages, May [4] Meroney, R.N., Wind-Tunnel Simulation of the Flow Over Hills and Complex Terrain, Journal of Wind Engineering and Industrial Aerodynamics, Volume 5, pages , [5] Baker, A.J. (1983). Finite Element Computational Fluid Mechanics, Washington, DC: Taylor & Francis. [6] Chen, Q. (1995). Comparison of different k-e models for indoor airflow computations, Numerical Heat Transfer, Part B, 28, [7] Chen, Q. (1996). Prediction of room air motion by Reynolds-Stress models, Building and Environment, 3, [8] Kolesnikov, A. (2006). Use of computational fluid dynamics to predict airflow and contamination concentration profiles within laboratory floor plan environment, Applied Buisafety, 11(4), [9] Piomelly, U. (1999). Large Eddy Simulation: Achievements and challenges, Progress in Aerospace Sciences, 35, [10] STAR-CD User Guide. Version 4.00, 2006, CD-adapco. [11] Su, M., Chen, Q., & Chiang, C. (2001). Comparison of different subgrid scale models of Large Eddy Simulation for indoor airflow modeling, ASME Transactions, 132(3), [12] Zhang, Z. Zhai, J.Z. and Chen, Q. (2007). Evaluation of different CFD models in predicting room airflow and turbulence, Roomvent 2007, Proceedings.