Skip to content Skip to navigation

Design Scenarios: Enabling Requirements-Driven Parametric Design Spaces

TitleDesign Scenarios: Enabling Requirements-Driven Parametric Design Spaces
Publication TypeTechnical Report
Year of Publication2010
AuthorsGane, V, Haymaker, J
Date Published08/2010
Publication Languageeng
KeywordsCenter for Integrated Facility Engineering, CIFE, Conceptual Design, design spaces, Ontology, Parametric Modeling, Process Mapping, Requirements Modeling, Stanford University
AbstractThis paper presents a novel methodology called Design Scenarios (DS) intended for use in conceptual design of buildings. DS enables multidisciplinary design teams to streamline the requirements definition, alternative generation, analysis, and decision-making processes by providing a methodology for building and managing requirements driven design spaces with parametric Computer Aided Design (CAD) tools. DS consists of four interdependent models: (1) Requirements Model – stakeholders and designers explicitly define and prioritize context specific design requirements; (2) Scenarios Model (SM) – designers formally transform these requirements into actions necessary to achieve them, and determine the geometric and material parameters, interrelationships, and potential conflicts; (3) Parametric Process Model (PPM) – CAD experts build and represent the technical implementation of a SM in a parametric model to enable design teams to manage and communicate its CAD models; (4) Alternative Analysis Model – analyze and visually report performance back to the designers and stakeholders. This paper motivates the need for the DS methodology thorough industry case studies, and establishes points of departure for the methodology through literature review. Next, the paper details the elements and methods in the methodology, describes its implementation into a software prototype, and provides an example to illustrate how DS can potentially enable multidisciplinary teams to generate and communicate larger and better performing design spaces more efficiently than with traditional methods.
PDF Link
Citation Key742