interactive structural analysis -...

CAAD Futures 2011 : Designing Together, ULg, 2011 © P. Leclercq, A. Heylighen and G. Martin (eds)

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Interactive Structural Analysis

GEORGIOU Odysseas University of Bath, Great Britain & Northern Ireland [email protected]

Abstract. This paper re-approaches structural engineering through an interactive perspective by introducing a series of tools that concatenate parametric design with structural analysis, thus achieving interoperability between form and its structural performance. Parametric Design is linked to Structural Analysis using computer programming to establish a common interactive framework that leads to performance based designs that respond to structural constrains and conditions in an interactive manner. A series of examples illustrate the synergy between form and structure by interactively modelling, analysing and visualizing its response.

1. Introduction

The digital age has introduced new ways of approaching architectural design. Modern digital tools (CAD), allow geometric freedom that in turn enables designers to overcome traditional design boundaries and transform almost any form into a constructible building. The development of complex forms in architecture led to the transition from the traditional, static design approach, to a "dynamic" process [1, 3] and forced computers to become "design generators" [2] and CAD tools to move away from their conventional drafting role. The development of generative design methods, or commonly parametric design, enables the designer to describe mathematically complex forms and explore new ones while understanding their conceptual functions.

Since building forms are becoming more complex, the engineering input is becoming essential from the concept stages and the role of the engineer in a design collaboration is enhanced. Despite that, there seems to be a gap between the ways the two disciplines interact. While a concept form can be shaped, understood and altered quickly by the architect, an engineer cannot assess the data given in analogous speed. For a given free form shape, developed with ease

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inside a Parametric CAD environment, extensive analysis needs to take place on the engineering side for it to be structurally assessed. Most of the times, the full behaviour is not fully understood due to the time chasm between modelling, analysis and assessment and just static performance feedback is returned for the shape analysed. Structural constraints, such as performance of structural members or materials and boundary conditions for example, are not controlled equally by Structural Analysis software as opposed to the way geometrical constraints are treated by Parametric Design software. Conceptual structural engineering of complex shapes cannot follow the rapid and constantly shifting architectural object that it is summoned to support. The digital design process needs to be enhanced and be able to stimulate solutions which respond to structural performance and conditions. There are a few examples that implement the notion of structural performance models applied on specific projects as Phaeno Science Center [4] and Lansdowne Road Stadium [5]. A more global example of performance based design of roof trusses can be found in Ref [2]. Moreover, there are cases that implement other types of data as lighting or thermal information to generate performance based models [6].

2. Interoperability in design

Since the Renaissance, engineering and architecture have been forced to diverge to different disciplines due to a demand of more rigorous design and in order to serve a sustainable and structurally safe built environment. Following the initial split, this chasm has become larger as each discipline tends to specialise more in their new "dedicated" fields of expertise hindering the communication between them. As design projects are becoming more complex, the need to reorganise the design process and the communication between the involved disciplines is becoming crucial. This communication is described by the exchange of data and it often involves the translation of one form of model into another. One of the most difficult tasks that modern engineering practices are summoned to confront is the transfer of geometry from the architect’s model to one that can be used for structural assessment. According to Koster, "Transfer of geometry generated in the architects design tool into structural engineering analysis was problematic and often resulted in simple geometric data without relational or dimensional information" [7].

A case study on an existing building project has been carried out by the author [8], in order to distinguish the issues arising from the collaboration between the disciplines that are involved in the design and construction of a complex building. The case study described the process followed from design to fabrication of the grid-structured roof of MediaCite in Liege (Ron Arad Architects - Buro Happold

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Engineers) and focused on the collaboration between the members of the design team and the data-exchange methods used to realise the project.

Fig. 1. The three different software platforms used by the design team.

The aforementioned project reflected a major challenge in designing and fabricating modern complex structures and at the same time outlined some common collaboration problems that are encountered in practice. The use of distinct design models and different software platforms by the design team members is something common (see Figure 5). However, when it comes to non-conventional shapes, translating and exchanging information that can be universally understood and implemented is an arduous process that can often limit the possibilities of an optimum result. This study outlined the process of translating each information model for use by each different discipline from concept to fabrication and it marked the difficulties that emerged, the data loss and the time spent to resolve arising technical queries. The diagram below illustrates the data exchange flow between the design disciplines and the way data translation took place in order for the initial architectural concept to be shaped to a real structure.

In an attempt to overcome this laborious process this paper presents an alternative process of generating a direct synergy between the architectural shape and its structural performance through an interactive link between a Parametric Design tool, Grasshopper 3d [9], and a Structural Analysis Software, Autodesk’s Robot Structural Analysis [10]. Furthermore it demonstrates how performance can be incorporated into the design process in order to firstly generate an analytical model of the given shape and secondly iterate between a set of efficient structural solutions that apply to that shape.

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Fig. 2. Design data exchange flow diagram.

3. Methodology

To illustrate an overview of a performance based structural design, a series of definitions were assembled by linking together McNeal’s Grasshopper 3D and Autodesk’s Robot Structural Analysis using C# programming language. Grasshopper 3d is a plugin built in .NET framework to access McNeal’s core software, Rhinoceros 3d in order to control and manipulate geometry in a generative manner. The functionality of Grasshopper 3D (GH) can be extended by writing code in C# or VB .NET programming language to create custom components. In parallel, Robot Structural Analysis (RSA) allows the interaction with other software and the use of its Calculation Engine through an Application Programming Interface (API).


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At first, a distinction should be made between the way that CAD software and FEM software understand and control geometry : when modelling a structure, a set of additional parameters should be taken into account in order to facilitate the process of analysing its performance. These parameters are acknowledged as structural modelling entities and include nodes, bars and panels and match real building elements as foundations, beams, slabs and so on. Some of these entities also exist in the pure geometric model, sometimes with different naming, and in fact determine a similar notion. For example, two points can describe a line and in the same way, two connected nodes describe a structural bar. What makes a significant difference in the representation of a structural model is the need to attach structural attributes to each of its elements, while the geometric model can be purely described by its topology. In addition, the numbering of each element and its global orientation in relation to its local axis definition are crucial points in the definition of a structural model (Figure 1). A simple bar element for example, is labelled with a number and is defined by its two interconnected nodes i and j, each one numbered individually in the global system. The accurate definition of nodes is important in structural analysis since that is where all the calculations occur.

Thus, each node that defines geometry in GH needs to be modified accordingly to be read by RSA. For example in order to translate a line to a structural bar, the line’s start and end point coordinates are extracted from GH and are used to define two new nodes for RSA. Those nodes are then used to define a structural bar since there does not exist an implicit way of translating a geometric line to a bar. Each structural member in RSA is defined or controlled using an appropriate interface, which is included in the API library, called Robot Object Model [11]. An interface is a software structure comprising a set of data, defined as attributes or members, and operations that can be performed which are called functions. These interfaces and their functions match the operations that a user follows to model and analyse a structure in the actual software environment. A node for example can be represented by the RobotNode interface, which among others includes three real numbers for x, y and z global coordinates. Each node can be managed using the RobotNodeServer interface, which for example includes the Create function for creating a new node.

3.1. Example 1 : Parametric truss

The following example shows the procedure followed to model a 2-diamensional definition of a Truss where its performance responds to each change of a parameter inside Grasshopper 3d’s visual environment.

The truss’s geometry was first defined parametrically so that all of its attributes could be controlled in an interactive manner. The geometric attributes included

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the truss’ overall span, depth and number of bays. The coordinates of the points comprising its geometric connectivity were stored in x, y and z programming lists and were then used in sequence by the RobotNodeServer interface for structural nodes to be created. Using the interface, each new structural node is created by inputting its global number value and its x,y,z coordinates. Each subsequent node is then connected to form structural bars using the RobotBarServer following the same connectivity sequence used in defining the geometric model. Relatively, the inputs needed by the RobotBarServer interface are each bar’s global number value and its start and end node number values.

The GH geometry is then fully associated with RSA geometry and properties, consequently geometrical parameters imply structural modelling parameters. At this stage, structural constraints such as supports, bar sections, material properties and loads need to be included in the model. This is done by using RSA’s relevant interfaces and members in a similar way, as the user would define them using the software’s Graphical User Interface (GUI). When a structural model includes all the information needed to be analysed, the calculation engine interface (RobotCalcEngine) can be called and the desired results can be generated and returned inside the GH custom component. The results are returned by utilizing the appropriate interface, depending on the type of the results and the reference to the structural entity. For example as shown in Figures 2 and 3, nodal deflection and bar force data was returned from the analysis. These results can now be used as parametric outputs to enable structural analysis visualisation in Rhinoceros 3D environment.

Fig. 3. Visualisation of deflection under self-weight in Rhino3D.

Fig. 4. Visualisation of the distribution of forces in each element

under self-weight in Rhino3D.

Furthermore, as a means to increase the functionality of the performance based model, parametric control to additional structural variables was added. An addition to the algorithm enables any line of load or any curve drawn in Rhinoceros‘s environment to be used to apply a distributed load case on the truss’


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top chord which can be controlled in real time by curve control points. In a similar manner, the truss’ support points can be moved by using a GH numerical slider in respect to the original edge supports (see Figure 4).

Fig. 5. Any arbitrary load case curve can be drawn in Rhino 3D and the

support position can be changed using a numerical slider in Grasshopper 3D.

A wide range of parameters is possible to be added and controlled within GH’s custom component for the truss and in the current context, such control is given by selecting multiple load cases or load case combinations, different truss types (Brown truss, Pratt truss and Vierendeel truss), section type selection from RSA steel section library and truss length (see Figure 5).

Fig. 6. Defining the truss’ parameters in Grasshopper’s sketchpad.

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3.2. Example 2: 3D grillage

As the previous example illustrated the generation of a parametric structural design model, it did not show the possibility for a commonly shared geometric model among the two disciplines. In this example a 3-dimensional structural grillage is linked to a free-form surface that is modelled parametrically in Grasshopper 3d. By this means, any complex architectural skin can acquire a structure where its performance attributes are visualised interactively responding to the change of geometry.

Fig. 7. Free-form surface. Fig. 8. Division in regions.

In this case the parametric surface is split into regions according to the user’s selection and is then transformed to structural data to be read by the analysis software. These regions also form the loading strips of the structure, according to the load-cases set by the user (Figure 8). The edges of the generated regions are subdivided into the desired grillage spacing bays generating structural nodes. The nodes are then offset normal to the surface according to a controllable parameter which defines the height of the grillage. The set of nodes are then connected with structural bars in space, to generate the 3-dimensional grillage. The surface loading is translated to nodal loading to be applied to the structural nodes. The constrain conditions, section types and material properties are also parameters that can be defined in a generative manner by the user, either using numerical sliders or text components. It is the user’s choice to compute the analytical model inside the Structural Analysis software, in order to perform more rigorous analytical tasks (as this tools’ capabilities are limited to conceptual analysis), or to visualise the current results in Grasshopper. The following images illustrate the analytical model in RSA including the point loads assigned on to structural nodes and the constrain conditions (Figure 9) and the visualisation of the stress distribution along the bars of the grillage in Grasshopper’s envorment.


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Fig. 9. Analytical model in Robot Structural Analysis.

Fig. 10. Visualisation of stress ratios in Grasshopper 3d.

3.3. Example 3: Interactive analysis of a free form surface

A more complex case is investigated in this section, which relates to translating any free-form surface (Figure 11) to a structural shell which is able to withstand the external loading conditions itself without an alternate supporting system as

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was the case of the 2nd example. It is anticipated that such models demand a larger effort to be generated, analysed and assessed and thus being able to control geometry changes with instant result feedback would generate an efficient tool for the designer.

Fig. 11. Free-form surface control-point handling.

For the surface to be analysed as a shell structure it needs to be transformed to a Finite Element mesh with analytical information for its structural assessment. Therefore, as a first step to the process, the free-form surface needs to be converted into a triangular mesh. A standard GH component is used to mesh any surface that is either drawn in Rhino 3D or described parametrically in GH. The mesh settings are controlled by the component to shape more a uniform discretisation of the surface. GH’s mesh output is a connectivity matrix of vertices, edges and faces. This information needs to be decomposed in elements that can be read by the structural analysis component. The mesh vertices are translated in a list of points in 3D space, which are then translated in structural nodes inside the analysis component. Up to this point, no relation between the nodes exists only an unreferenced point cloud is drawn in RSA. The connectivity of each face is then used to create arrays of nodes by selecting the three points that comprise each face out of the list. Finite elements can then be created by utilizing the arrays created using the FiniteElems interface in RSA. Structural


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properties need to then be applied, which are treated in a way that allows them to be controlled parametrically by the user through the GH graphical interface. The properties that are essential for the analytical process are: the type of the elements, which are set to planar 3-node elements with constant thickness, the material that either is pre-set from RSA’s library or can manually be defined by its properties and the element’s thickness. The model’s supports are initialised to the edges by selecting all the nodes that lie on the mesh’s outline. The border of the mesh is isolated by utilizing the topological information of the mesh by accessing Rhino.NET SDK [12]. A routine is formed to run through all the edges that form the mesh’s topology and select the ones that are "naked", which means that they are only connected to one face. The vertices that belong to those edges are output to the analysis component and are selected as nodes that contain support information. The option of adding supports on points that did not necessarily coincided with the mesh vertices was also implemented by subdividing the mesh around the area to be supported. The topological information is lost when the mesh is translated to FE for the structural modelling and therefore the index of each support vertex needs to be found from the list of nodes that are already drawn in the model. After the structural information database is complete, the calculation interface can be called and results can be output for each finite element.

For the purpose of graphical representation of the FEA results, each face was translated into a triangulated surface while keeping the topological information of the mesh. Consequently, the analysis results are mapped with each surface facet and their values can be tagged accordingly or coloured using a GH Gradient component. This results to the interactive representation of the impact of change on the geometry or the constraints of the initial NURBS surface in Rhino’s Viewport (see Figure 11).

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Fig. 12. Graphical representation of surface stress ratios in Grasshopper 3D.

4. Conclusions

An integration between the form and its structural performance was illustrated through the synergy between Parametric Design and Structural Analysis software. This combination enabled an interactive approach to structural design, a function which currently is sparingly applied for solving engineering problems. As mentioned in the introduction, tools that aid fast and associative design are readily available to architects. These allow them to generate, analyse and manipulate models quickly, while being able to visualise results in a real-time manner. This process often leads to architecturally elegant design solutions. The involvement of a structural engineer in the early stages of design is essential in modern architecture and particularly in regards to complex forms. This offers a quick


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insight to the structural performance of the form and aids increasing efficiency in the whole design process. However, without the use of compatible tools, an engineer not only fails to support architectural design but also moves away from efficient solutions. The generation of structurally responsive parametric models enables the iteration between ranges of efficient solutions while being able to react to each change of the architectural geometry rapidly.

This paper demonstrated the application of the method through three examples: a simply supported truss, a 3D grillage and a shell structure of a free-form surface. The possibility for all three models to adapt to multiple variations of shape and the continuous user interaction was persistent in all cases. This also illustrates the methods’ applicability to a range of architectural and structural engineering problems.

5. Future work

Future extensions to the performance based parametric components include : • The initialisation of Robot Structural Analysis member design engine would

allow designing and checking structural members while ensuring their structural efficiency.

• The implementation of improved subdivision algorithms for the generation of mesh emitters around the support points to improve the distribution of stresses related to the interactive analysis of a shell structures.

• Including a greater range of structural elements in a single model would allow the generation of performance models which contain largest amounts of assessable information which would enable a more holistic approach to the problem.

References

1. Aish, R. & Woodbury, R., Multi-Level Interaction in Parametric Design. Bentley Systems Incorporated.

2. Shea, K., Aish, R. & Gourtovaia, M. (2005). Towards integrated performance-driven generative design tools. Automation in Construction. March 2005, 14(2), pp. 253-264.

3. Papalexopoulos, D., Stavridou A. & Papadopoulos D. (2007). Conceptual determination of parametric attributes of architectural construction elements and materials (free translation). NTUA.

4. Littlefield, D. (ed.). (2008). Space Craft-Developments in Architectural Computing- Geometry form and complexity. London : RIBA Publishing.

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5. Shepherd, P. & Hudson, R. (2007). Parametric Definition of the Lansdowne Road Stadium. International Association of Shell and Spatial Structures. Venice, Italy.

6. Caldas, L. (2006). GENE_ARCH : An Evolution-Based Generative Design System for Sustainable Architecture. Intelligent Computing in Engineering and Architecture. Lecture Notes in Computer Science, Vol 4200/2006, 109-11.

7. Veltkamp, M. (2007). Freeform Structural Design. Thesis (PhD). TU Delft. 8. Georgiou, O. (2009). MediaCite - Design to Fabrication. Research Report, University

of Bath. 9. Grasshopper - Generative modelling for Rhino (online). Available from : http://www.

grasshopper3D.com. (Accessed 22 Dec 2010). 10. Autodesk - Autodesk Robot Structural Analysis Professional (online). Available from

: http://usa.autodesk.com/adsk/servlet/pc/index?siteID=123112&id=11818169. (Accessed on 20 Dec 2010).

11. Autodesk Inc. (2009). Autodesk Robot Structural Analysis 2010 – Robot Object Model.

12. Developer : dotnetplugins- McNeel Wiki (online). Available from : http://wiki. mcneel.com/developer/dotnetplugins. (Accessed 20 July 2010).

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