1 STRUCTURAL AND ARCHITECTURAL INTEGRATION IN BUILDING DESIGN

A team of civil engineers, architects and computer scientists is using CaseBased Design (CBD) as an approach for integrating preliminary architectural and structural design. This approach focuses on the adaptation of geometric models of existing buildings in order to find solutions to new design problems. Dimensional and topological adaptation are treated as two distinct processes, each employing different strategies for achieving integration. Conclusions of this work are that cases consisting of a geometrical building model both simplify design knowledge acquisition and provide a valuable integrated preliminary design solution which serves as a useful starting point to the design process. INTRODUCTION Computer Aided Design (CAD) is currently one of the most active fields of research and development in artificial intelligence. Many systems have been developed in order to study human problem solving as well as to test the potential for CAD in design practice. The advantages and shortcomings of the approaches used in many of these systems are discussed in the paragraphs that follow. The Integrated Building Design Environment (IBDE) (Fenves et al 1989) was one of the first integrated building design systems to be implemented. Design knowledge from various building design domains is organised into independent rule bases in separate system modules. Foundation, core and column layout design, for example, are treated as separate design sub-tasks. A control module in a blackboard architecture (Hayes-Roth et al 1980) determines the solution sequence for each sub-task. The IBDE suffers from the problems of conflict and possible looping between modules (Schmitt 1989), caused by decomposing the design process into sub-tasks and subsequently ignoring the full extent of their interdependence upon recomposing to produce an integrated solution. Prototypes (Gero et al 1988) are parametric models of design objects which are adapted to solve new design problems. The prototype approach demonstrates the advantage of starting the design process with examples of solutions. A disadvantage is that parametric models must be formulated by generalising both design and domain knowledge. This is 2 difficult to achieve for complex objects, such as buildings, which are characterised by many thousands of parameters. Mutation (Zhao and Maher 1992) is proposed as a means of increasing the creativity of prototypical design. In this approach analogical reasoning is used to adapt prototypes to include parts of others, thus making solutions more innovative. The paradigm of Case-Based Reasoning (CBR) originates from psychological models of human memory structure (Schank 1982). The underlying concept is that humans use not only heuristic rules to solve problems, but also refer to solutions to previous similar problems. For example, when faced with the task of designing a new warehouse, the case of an existing warehouse is adapted to suit new needs, rather than starting with a set of rules stating, for example, that roofs are supported by beams, beams are supported by columns, and columns must be founded. Cases in some early CBR systems consist of the ’ingredients and steps to follow’, as in CHEF (Hammond 1986) which produces new recipes from existing ones. This type of case is a plan of the design process, formulated at the knowledge acquisition stage. Existing solutions must be evaluated by a human designer and a case formulated to suit the way it will be used during reasoning. A disadvantage of this approach is therefore that knowledge acquisition may be both time-consuming and complicated. CYCLOPS (Navinchandra 1988) is a landscape planning and design system in which a case is both a previous problem and its solution. Analogical reasoning is used to identify cases, not necessarily from the same domain, which match the current design problem. The identification of relevant cases from other domains necessitates a great deal of domain independent knowledge. Furthermore, cases must be formulated so that the useful information is represented explicitly. Due to the belief that a practical CBR system would need many hundreds of cases from which to reason, much research has been concentrated on indexing and retrieving cases (Kolodner 1989). Systems have been developed which find the best case, rather than reason with the case once selected. ARCHIE (Domeshek and Kolodner 1992) indexes and organises decomposed cases (annotated building plans) in memory and provides a case browser for the retrieval of stories, which are defined as ’selective presentations about a case which have a lesson to teach’. The user is left to interpret a story, as ARCHIE does not reason, being a problem sensitive teaching tool rather than a design system. A similar system is being developed by the FABEL joint project group (Bakhtari and Bartsch-Spörl 1993). CADSYN (Zhang and Maher 1993) is a case based building design system which considers architectural space planning, structural design and services design. The system assumes that design problems can be decomposed to nearly independent sub-problems which can be solved independently and then recomposed to provide a complete solution. A 3 drawback of this approach is that the interdependence of sub-problems can lead to conflict or function sharing upon recomposition of sub-solutions. The DDIS system (Wang and Howard 1991) combines case based reasoning with design independent knowledge in a blackboard framework. This system demonstrates the advantages of combining reasoning strategies. Design knowledge is represented by cases consisting of the problem specification, final solution, intermediate propositions, design history, etc. Cases are retrieved by users who decide similarity to the new design problem. The system treats the design of steel columns, and is therefore yet to be tested on complex tasks. INTEGRATION Buildings can be seen from many different points of view. For example, to a civil engineer a building consists of structural elements, whereas an architect may view it as a collection of rooms (Figure 1). These interpretations are referred to as abstractions. Figure 1. Multiple building abstractions. One of the most difficult tasks in design is resolving conflicts which occur when integrating solutions from multiple abstractions or decomposed sub-problems. The conflict between architects and engineers is traditionally one of the greatest problems in building design (Holgate 1986). In practice, designers rely heavily on their experience of conflict resolution in order to make trade-offs. In design practice, as in CAD, integration is the key to good design. This is accepted by many researchers, but current CAD systems provide little support. As mentioned above, blackboard systems may loop between modules, unless the control module contains complete knowledge of all possible conflicts as well as effective 4 strategies to resolve them. The weakness of blackboard systems is found precisely in the representation of knowledge for conflict resolution. An improved model of the design process is therefore needed.