Stanford CEE 214 - Conceptual Design Of High Rise with Parametric methods

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1 Conceptual design of high-rises with parametric methods Victor Gane, Stanford University, USA John Haymaker, Stanford University, USA Abstract. This paper describes the use of parametric methods in generating conceptual designs of high-rise buildings. We first assess current conceptual design practice at a leading AE firm and illustrate the challenge of satisfying a complex set of requirements with the tools currently used by the AEC industry. Few design options are generally developed and analyzed; better design solutions are most likely being overlooked. Parametric tools can potentially help address this problem by allowing designers to formalize and generate solution spaces that can be explored. But few case studies exist to document the construction and impact of these models. We present such a case study. We describe the variables, constraints, components, and rules in the model. We discuss the costs and benefits, and conclude with recommendations for expanding the use of parametric methods. Keywords. Conceptual, rule-based, parametric design. 1. Introduction Conceptual design is a challenging part of the design process as it requires reconciling the design with a complex set of goals and constraints such as program requirements, construction cost, environmental performance, and more abstract notions such as aesthetics and usability. When faced with such complexity, designers are taught to generate and test a large number of options. However, faced with time and budget constraints, Architecture Engineering and Construction (AEC) project teams today often generate and test relatively few options for a design problem. Analyses of these options are limited, and tend to favour space programming and aesthetics over other criteria. Two possible causes of these problems lie in the tools the AEC industry is using. First, these tools were designed to support generating single, static solutions, they do not efficiently support exploring and managing many potential design alternatives. Second, these tools do not yet integrate well with many analysis tools, therefore discouraging multidisciplinary analysis. Potentially better building solutions are neglected by the current inability of design teams to rapidly generate and analyse a wider range of design options. This paper deals principally with the first issue: generating design options. Parametric modelling promises to revolutionize the way we design buildings. To design parametrically means to design a system that sets up a design space which can be explored through the variations of the parameters. In this paper we explore the use of parametric methodology as a potential solution medium for high-rise design and test the extent to which it helps address the above described limitations. We first describe our observations of current high-rise design practice in the United States. We then introduce parametric methodology. Next, we describe a case study in conceptual high-rise building design where parametric design is used to model and manage changes. We conclude with a discussion of the strengths and weaknesses of this method. 2. Benchmark Current Practice When designing high-rises, architects rely on multiple sets of rules (Stiny, 1980, Alexander et al, 1977). Among these are reusable building typology rules that help2 generate the optimal lease-spans (residential – 30’, office – 40’), or meet minimum building efficiency requirements (65% Æ net sellable area = gross area - core area). There are also explicit, project-dependent high-level rules such as the local building codes (i.e. setback from property line) or stakeholders’ requirements (i.e. min. floor plate area) used by designers as general guidelines for generating the building’s volume. Designers rationalize these rules in more implicit, low-level geometric rules that determine geometric element dimensions and relationships. The concurrent implementation of such rules in traditional CAD is challenging and time consuming, especially when multiple goals are tracked simultaneously. Limited, rudimentary analyses are performed by engineers at this point because of schedule constraints and incompatibility of architect-generated design information for use in discipline-specific tools. In a two-week timeframe designers normally develop as few as 1-3 options. Figure 1 describes this process. Explicit analyses are normally performed after the conceptual design phase, which often leads to major changes to the original concept, or unsatisfactory design results. Figure 1 - Narrative of the current SOM conceptual design process Our research investigates whether parametric tools can help formalize the complex rules that describe a high-rise and how might this improve the current design process. 3. Parametric Design - Concepts Originating in the field of mechanical design, parametric methods are gaining popularity in the AEC industry. A few practitioners (Whitehead et al, 2003, Shelden et al, 2002, Hesselgren et al, 2006) and academics (Burry, 2003, Woodbury, 2006, Killian, 2006) are actively implementing parametric and/or performance-based design on AEC projects but industry wide adoption is hindered by the lack of knowledge about how to apply parametric thinking to different building types and among multiple disciplines. More formal case studies and metrics are needed to help establish the benefits and drawbacks of parametric methods in the AEC industry. In this paper, we describe our parametric methodology around six main concepts: variables, constraints, dependencies, components, PowerCopies, and rules. Variables are the primary drivers of geometric variations. We distinguish between two types of variables: independent and dependent. An independent variable is a user-defined numeric input whose value can actively be controlled and changed (i.e. triangle height, etc.) while the dependent variable is the output whose value changes as a result (i.e. triangle area). Variables can also be global or local depending on how these have been attributed to geometric elements. For example, by attributing a variable to the radii of all columns in a building one would establish a global variable, since modifying its value will propagate globally to all the columns. In contrast, a local variable will always affect only a single geometric element to which it is attributed. Constraints help delineate the range of variations that a parametric model can sustain. The extent of


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