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AbstractThis paper tracks the use of a Knowledge Engineering in the design, fabrication and installation of a complex wood ceiling in the Burj Khalifa office lobby in Dubai, UAE. Knowledge Engineering is here understood as the use of parametric design tools to capture and reuse design and fabrication know-how, seeking not to supplant the designer or fabricator's skills, but to extend this sensibility to all the participants in the design team, creat-ing a shared platform for material innovation. By treating the production and detailing of this case study project as a system instead of a discreet design object, the authors seek to illustrate the changing role of computational design tools and the implications for the practices of detail design and fabrication.

Case studies are given on the usage of the CATIA/Digital Project Knowledgeware environment to capture design intent and fabrication details in a system that allows them to adapt to new geometric configurations given differ-ent inputs; material bending limits and systems used to describe and map their physical constraints; automated tools built around the sorting and managing of wood veneers; and rationalization strategies related to wood bending and fabrication.

1 IntroductionBehind schedule and with the finish date of the building fast approaching, Gehry Technologies was presented with a unique problem. A complex, double-curved wood ceiling for one of the main entrance to the Burj Khalifa (then Burj Dubai) was under construction and it was becoming apparent that the proposed system would not work as designed. Instead of delaying the schedule or scrapping the design, an integrated team was quickly mobilized. This team was based in different design and fabrication domains, with all participants working toward the shared goals of redesign, fabrication, delivery and installation of the new ceiling, all within a tight timeframe and construction site. Partners included Skidmore Owings and Merrill (SOM), Imperial Woodworking Company (IWA), ICON Integrated Construction and Gehry Technologies/New York (GT). Working through the design is-sues, the new team developed a strategy to strip the design back down to essential geometry and redesign the system from the ground-up, satisfying design intent and a host of fabrication and constructability constraints through a shared parametric model.

The previous system—a stick-built plank system wrapped over a series of ribs—worked within the constraints of a small physical mock-up but did not scale up properly to the required geometries for the finished ceiling. A new system was developed using a pre-fabricated unitized panel approach. Although more risky in terms of on-site adaptability, building the panels offsite in IWA’s Chicago woodshop and then shipping them to Dubai in stages gave the added benefits of quality and speed. Now not only did the panels need to arrive on-time within a very aggressive schedule, but they needed to be built perfectly, arrive undamaged through shipping, and be pre-coor-dinated for installation and all surrounding building elements (structural, mechanical ductwork, interior finishes, lighting, etc.).

Knowledge Engineering: The Capture and Reuse of Design and Fabrication Intelligence on the Burj Khalifa Office Ceiling

Neil Meredith, Gehry TechnologiesJames Kotronis, Gehry Technologies

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2 Knowledge Engineering Approach

Figure 1. Project Process Diagram.

From the beginning the focus was on a high quality digital fabrication process so the panels could be manu-factured and installed correctly on the first attempt. As is often the case, high-pressure deadlines become the driving force for a more innovative fabrication and delivery process. Within this new project structure, traditional drawing and submittal processes were adapted to work with digital model files as contract deliverables and fabri-cation information, not out of an abstract desire for an “integrated delivery process” but out of a very real concern for what was best for the project in terms of speed, quality and cost.

A priority for the team at Gehry Technologies was developing a systems approach to the design problem at hand. Parametric design tools and automation are nothing new either in fabrication or architectural design. The pres-ence of these tools guarantees simply that: their presence. An emerging digital craft culture, directly engaging the people making and shaping the materials and processes through the crafting of these tools to new ends, points to a new and more considered process which we refer to as Knowledge Engineering (KE).

Fundamental to Knowledge Engineering is the idea of reuse. Given the iterative nature of working with an involved design and complex set of fabrication constraints, the system evolved along two lines. The first was a set of drivers, or parametric geometric rigs. Typically made from simple surface and wireframe geometry, they form the adaptable geometric core of the design model. The second system, building on the parametric driver core, is a set of modules related to panel fabrication. By modularizing the technology and explicitly managing the relationship to the driver geometry, these modules (built in the Digital Project Knowledgeware environ-

DESIGN INTENT

COMPLETION

PANELIZATION

MATERIAL BENDING LIMITS

SURVEY DATAAS-BUILT

COORDINATIONDRAWINGS

ON-SITEASSEMBLY

CNCTOOLPATHS

VENEERINVENTORY

COORDINATION

SHIPPING

FABRICATION

PLANKING

DETAILING

SYSTEM DESIGN

VENEER MAPPING

SHIPPING & SEQUENCING

KE DESIGN SURFACE

COORDINATIONMODEL

FABRICATIONMODEL

SURFACE &PLANK MODEL

KE PANELIZATION

KE PLANKING

KE PANELASSEMBLY

KE VENEERMAPPING

ment) depart from a typical scripted or automated approach to model design, and focuses instead on organizing models around specific design and fabrication goals. A script-based approach would typically build in complexity linearly from the base wireframe geometry out to resolved 3D geometry, folding in constraints as you go, grow-ing in complexity. This can often result in a “house of cards” model by where simple changes anywhere can cause things to break or become overly complicated to the point where only one person can control or adapt the script (typically the scripts author). By explicitly managing inputs and outputs and taking a system approach to the design of the model, multiple parties can work in parallel on the same rig, advancing complex modules with relatively simple links to the core driver geometry.

3 DriversThese drivers form the flexible geometric core of the system, comprised of simple surface and line geometries, and built in a way that is fully adaptable. Inputs and parameters can be adjusted or swapped for other inputs, and the outputs from these modules can form the basis for other, more sophisticated downstream processes, as we will see later in this paper. At any point the system can respond to updates or changes, but through modu-larization, this process becomes more controlled.

3.1 Physical TestingThe first step in developing the drivers was map-ping the physical constraints of the desired materi-als. Before we even approached the computer, IWA performed some quick bending studies with a series of plank samples (MDF cores with veneers on each outside plank face) over different radii circles. Though quick and simple, these tests formed the basis of an understanding of maximum bending stresses allow-able within the surface design. These were the first of many “physical computers” that guided and shaped the work being done behind the screen.

3.2 Surface RationalizationThe original design surface was then rationalized to maximize geometric simplicity while still meeting the design criteria and minimum bending radii of tested plank materials. As with any project, a certain vo-cabulary developed around some of the more abstract geometries to allow for quick reference. Moving from the North to South on the design surface we have the beach area, so called for the way that it flattens out from a vertical to horizontal surface. The south-ern end, or the boat consists of two swept profiles trimmed about a central intersecting plane. Connect-ing these two halves are the arms, two bridge-like geometries linking the disparate halves.

Figure 2. Wood Bending.

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Figure 3. Surface Drivers

The first general move was to flatten out the underside profile of the beach. This simple change created a whole zone of like panel types while not compromising the overall feel of the design surface as you approach it from the escalators. Another key step was substituting blended or lofted surfaces with more rational surface types in both the beach and the boat areas. Panels made from torus sections and swept surfaces (as opposed to more free-form surfaces) have the key benefit of being able to use the same repeated unit while still allowing for double curvature within the panelized surface (Peters 2008 and Pottman 2007). The arm surfaces created the greatest challenge in the driver surface design. A series of free-form surfaces were eventually developed that maintained surface tangency to the beach and the boat, while still falling within the various bending constraints for fabrication.

Figure 4. Planking/Panel Driver

3.3 Planking/Panel DriversWith a controlling surface in place, countless iterations of planking and panelization options were then tested. From the underside of the ceiling, the surface is a continuous field of planks. The panel joints are made to disappear on the outward facing surface. Visible from the back surface, rectangular panel divisions simply follow the same divisions as the planking, picking up lines as necessary. Having a parametric rig for the development of both the planking and the paneling was key as this was not a simple linear process, but instead an iterative back-and-forth conversation between maximum panel sizes, constructability, changing planking widths, and various design options for the planking itself. Prosaic constraints such as the size of the freight elevator available on site were worked along side more design-oriented issues such as the typical width of the plank.

PRIMARY DRIVERS

BL END WIREFRAME

BLEND SURFACES

DRIVER SURFACE

COMPLETED SURFACE DRIVER

M AJOR PLANKING DIVISIONS

M AJOR PANEL DIVISIONS

COMPOSITE PLANKING/PANELS

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Figure 5. Geodesic Lines on Double-Curved Surface

Due to the varied topology of the design surface, geodesic curves—or curves that follows the shortest distance along a surface between two points—were used to simulate the natural bending properties of wood planks as they are laid upon a double-curved surface (Pottman 2007). Other geometric techniques such as projecting curves on a surface or intersecting multiple planes to produce curves have the problem of geometric overdetermi-nancy. When you project a line or do any other geometric transformations to produce a curve, you introduce an orientation or a visible geometric approach. The curve reads as something applied to surface, revealing the hand of a strict geometric system. Alternately when the lines resolve along a surface as with geodesic lines, the result-ing curves maintain a natural relationship to that underlying surface (Pottman 2010).

4 Fabrication Modules

4.1 Wood Plank SystemTaking the wireframe planking curves and surfaces as inputs, a series of flexible components were designed to parametrically reconfigure themselves to adapt to various detail conditions. The first module to use this approach was the three-dimensional wood planks forming the exterior of the panel. Due to the desire for variegated ve-neers across the surface, individual planks with different veneers needed to be laid-up on the panels. Compli-cating this arrangement, many of the panels had a anticlastic surface topology, requiring individually cut and finished planks for many of the panels.

DOUBLE-CURVED SURFACE

GEODESIC LINE

FLAT PLANK LAID-UP ON SURFACE

UNFOLDED PLANK (STRAIGHT EDGES)

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Figure 6. Planking System

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In places where the panels had one degree of curvature across the design surface (aided by the rationalization of the input surface in toroids and swept surfaces with evenly distributed geodesic plank lines) a single plank pro-file could be used for the entire panel. In panels with compound curvature, individual profiles would need to be modeled in three-dimensional space, unfolded and then individually CNC cut for placement back on the panel. Therefore these planks were not true planks, but were instead unfolded developable surfaces (Pottman 2008).Automating the modeling and unfolding of these surfaces accurately was a complex challenge, especially when factoring in material thickness, the topology of the input curvature (concave vs. convex surfaces produce slightly different unfolded surfaces when factoring in the thickness of the board) and the true fabrication and bend-ing limits of the materials (Kensek 2000). A Knowledge Pattern aided the quick prototyping of the geometrical solution, providing a framework for future geometry development without having to recode or rescript the entire automation routine. Utilizing a catalog-based approach, different plank configurations could be swapped in to the Knowledge Pattern without having to alter any of the instantiation scripts or input driver geometry (sample scripts are available at sheetd.com).

Figure 7. Veneer Mapping

4.2 Veneer MappingAnother challenge with prefabricated units was predicting the distribution of wood grain across the entire ceiling surface. In a typical plank based design such as a floor, veneers are sorted for aesthetic criteria and then se-lected by craftsman to ensure the even distribution across the surface, avoiding dark and light patches or clus-tered areas. This ceiling was built as a unitized system of panels, fabricated offsite and out of sequence. (Due to the schedule, some panels were still being built in Chicago while the initial grouping was being installed in the UAE.) Often called veneer “randomization” the eventual solution was hardly random, but instead sorted and mapped veneers to discreet planks in an automated system. The tool also allowing for multiple mappings to oc-

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cur in an iterative digital design environment, giving the craftsman a tool to visually asses the veneer placement while still allowing for a new level of control during fabrication. In the end, every veneer for the entire project was tagged and managed across the entire ceiling surface through this method.

In building the veneer tool, we looked at the existing technologies that they worked with. The shop would pur-chase logs of veneers. These would then be hand-sorted by various aesthetic categories down to parts, bundles and leafs. So the fabricator sorts the veneers by the same craft-based visual characteristics that they are accus-tomed too, but GT introduced a new way of managing and applying the sorted veneers on to the actual ceiling project. The craft remains, but a new automated system extends this knowledge to a new scale and level of control.

Given a database of veneers and a plank geometry target model, the automated software routine maps the ve-neers on to the geometry, filtered through a set of rules that govern the adjacencies of the various veneers. Again the idea was to extend the craft-based approach to veneer sorting, but capture this intelligence in a set of rules or system that can be applied on future projects. So using the adjacency matrix—or a diagram indicating what veneers can or cannot be next to each other—the automated routine randomly grabs a veneer from the data-base, checks that it fits geometrically, and if it has a match, color codes the plank model and removes the plank from the database. This randomly executes across the entire design surface till all the planks have a correspond-ing veneer. Each time the tool is run a new pattern emerges. Once completed, all the veneers are accounted for both visually and within the database.

One unanticipated outcome of the tool was the addition of another log of veneers for the project. Initial trials of the planking module did not produce random enough variation across the surface. After adding another log to the database, the distribution loosened and visual randomness increased across the surface, revealing a gap in the initial rule-of-thumb calculations for veneers. Only after taking the step to capture the design intent and fabrication means-and-methods in to a collaborative design model, did a coordinated result emerge. Although developed as a specific tool for the use in this project, it has some general portability and usefulness outside the confines of this single use, extending the system as a technology and the reach of the fabricators design intelligence on to other veneer sorting applications (Speaks 2003).

4.3 Panel TypesWhile the field of computational design has opened up new possibilities for the infinite variation of parts in an assembly, a very real-world constraint that is of-ten ignored amongst the technological exuberance is the actual desire for standardization. A hybrid form of standardization was pursued along two tracks in the Burj ceiling, through creating reusable panels, and the capture and reuse of details within the panels themselves.

Figure 8. Panel Types

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Maximizing the reusability of panel types ultimately allowed for a simplified approach to fabrication without sac-rificing the design intent. In addition to cost and time savings, quality also increases when you reduce the num-ber unique detail conditions. Standardization was obviously not the first project concern given the complex and variegated nature of the design, but within the framework of the design intent, certain panels could be repeated without affecting the outward visual nature of the finished ceiling. The fabrication modeling sought to capture this approach, making subtle tweaks to the driving surface and the planking/paneling scheme to produce like panels in certain areas, all the while maintaining a smooth and continuous curved ceiling surface. In total, 76 unique panel types were developed that were able to work for all 195 panels across the entire ceiling. Several factors contributed to this. Because all the pieces were fabricated using 3-axis CNC manufacturing for both the backing frame and the finished plank pieces, panels that were three-dimensional mirrors of other panels could be fabricated by simply mirroring the CNC profiles. Additionally, due to some of the early stage surface rational-ization there were more panels built on flat, swept, or toroid geometry, allowing for additional panel reuse within these zones.

4.4 Detail ReusabilityA second type of efficiency, standardizing typical details and material configurations within the panels them-selves, was pursued through another Knowledgeware technology called Document Templates. Within a Docu-ment Template, a set of input geometries and parameters create the foundation for a parametric rig. This rig can adapt to a new geometric context while still maintaining internal relationships and rules. This is similar to the planking Knowledge Pattern described above, but Document Templates depart from more typical automated ap-proaches in that in addition to creating unique parts, they can also contain standard parts gathered in an assem-bly model. Furthermore all the geometry in this assembly can be linked to automated drawing outputs. Though not simple to set-up and debug, these Document Templates can accelerate a design process through rule driven self-detailing and self-documenting assemblies.

Figure 9. Panel Build Geometry

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Our general approach was to use the templates to establish the general topology of the panel (number of planks, rough placement and divisions of frame members, etc.), which could then be individually detailed and tweaked right up until release for fabrication. A typical workflow was to instantiate a panel assembly, asses how the parts worked together, make dimensional adjustments (such as the spacing of the backing frame), and then run an update to sync all the elements in the assembly and update the drawing outputs. Although technically pos-sible to create a template that utilized a series of rules to completely detail an entire assembly, we took a softer approach by where the template creates all the necessary parts and relationships, but the actual detailing and final positioning of pieces was adjusted visually within the parametric framework. This provided a nice balance, by where we automated the repetitive geometry creation but still allowed for enough slack to make sure details actually worked or there were not any strange or fussy panel configurations.

Figure 10: Panel Assembly

Developed in concert with the fabrication team, the Document Template evolved to support direct panel fabri-cation. Using the surface and plank lines as inputs, this template produced a number of outputs for both vi-sualization and fabrication. Each of the separate material layers in the panel assembly was either unfolded or laid flat for eventual cutting on a CNC mill. Moving from the finish face of the panel to the interior, the panel is composed of: planks made of an MDF core with a layer of veneer on both faces of the plank, two layers of bend-ing plywood in alternate orientations, and then a plywood “waffle frame” system. The entire assembly is either compressed under pressure with various glues to create composite strength (in the case of the thin bending ply layers) or is mechanically attached (in the case of the frame). Once all the pieces are sanded and assembled, the entire panel is sealed as a unit to create a water resistant finish.

PLANKS

BENDING PLY 1

BENDING PLY 2

FRAME BORDER

FRAME INFILL HORIZONTAL

FRAME INFILL VERTICAL

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Figure 11. 2D Output

Remarkably the entire panel fabrication was done with 2D cutting profiles. That is not to say that the fabricator was not working in 3D, but the understanding of 3D had more to do with assembly and fabrication of actual materials in space instead of digital models. GT produced a 3D solid model, but the Document Template CAM outputs were completely 2D in nature. Instead of relying on robotic fabrication or multi-axis machining, a se-ries of registration elements were output from the model for use during assembly. Looking at one piece of the assembly, the “waffle frame” is a well known and fairly easy-to-assemble construction given the prevalence of CNC fabrication, but to ensure the larger project goals such as continuity between adjacent panels, the edges of the frame were projected on to a single plane to create a “tabling” jig at 1:1 scale and CNC out of ¼” MDF. In addition to the direct-to-fabrication cutting of the plank and frame pieces, various other jigs and templates aided panel continuity and assembly.

Figure 12. Detail Design.

After gathering all the pieces together in to a “master model” (Shelden 2002) details were then refined and expanded in the 3D environment with all the appropriate links to the upstream driver geometry and the down-stream panel fabrication models. While representing an investment in time, effort and infrastructure, the flex-

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ibility of the system allowed for rapid update cycles late in the design pro-cess. To take one example, 3D sur-vey data of as-built conditions was continually cross-checked against the developing fabrication model. Fairly late in the design process it was discovered that some of the steel interfacing with the boat section was not within the assumed design toler-ances and needed to be updated. In-stead of remodeling these parts, the input surface geometry was slightly tweaked, producing a ripple effect of changes though the design surface. These panels were simply updated to the new surface and reissued just prior to the actual panel fabrication.

5 ConclusionsThrough the analysis and iterative design environment enabled by the mapping of actual material constraints on to a parametric model, the Burj ceiling was conceived more as an approach to wood and the bending of wood in complex architectural de-sign, as opposed to the execution of a singular hermetic design. This system relied on a controlled set of geometric drivers and reusable modules, allowing for multiple design studies and mod-els within a shared parametric design environment. Future research looks to extend this driver based approach to other project types as well as general-ize and reuse the design intelligence developed within certain modules.

Figure 13. Panel During Assembly.

Figure 14. Completed Ceiling.

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Pottman, Helmut and Andreas Asperl, Michael Hofer, and Axel Kilian. (2007). Architectural Geometry. Exton, PA: Bentley Institute Press, 289-304.

Ibid, p558.

Pottman, Helmut and Qixing Huang, Bailin Deng, Alexander Schiftner, Martin Kilian, Leonidas Guibas, and Johannes Wallner. (2010). Geodesic Patterns, ACM Trans\Graphics.

Pottman, Helmut and Alexander Schiftner, Pengbo Bo, Heinz Schmiedhofer, Wenping Wang, Niccolo Baldas-sini, and Johannes Wallner. (2008). Freeform Surfaces From Single Curved Panels, SIGGRAPH ’08 [ACM SIGGRAPH 2008 papers]

Kensek, K., Leuppi, J. and Noble, D. (2000) Plank Lines of Ribbed Timber Shell Structures, Eternity, Infinity and Virtuality in Architecture [Proceedings of the 22nd Annual Conference of the Association for Computer-Aided Design in Architecture / 1-880250-09-8], 261-266.

Speaks, Michael. (2003). Design Intelligence. Hunch: The Berlage Institute Report, 416-421.

Shelden, D. R. (2002). Digital Surface Representation and the Constructibility of Gehry’s Architecture. Ph.D thesis in Department of Architecture, Massachusetts Institute of Technology, Cambridge MA.