Macroscopic analysis of design processes based on a scheme for coding designers' cognitive actions

We have devised a new scheme for coding designers' cognitive actions from video/audio design protocols. Designers' actions are coded into four cognitive levels; physical, perceptual, functional and conceptual. Relations between actions belonging to different levels, such as dependencies and triggering relations, are also coded. The present scheme has two benefits. First, we found that design actions are definable in a systematic way using the vocabulary of the scheme, and thus a designer's cognitive behaviours in each of local design stages is represented as a structure composed of defined primitive actions. This is expected to lay the foundation for microscopic analyses of how particular types of actions contribute to the formation of key design ideas. Second, this scheme is suitable for macroscopic analyses of how designers cognitively interact with their own sketches. We examined, for a practising architect, the ways in which drawing, inspection of drawings, perception, and functional thoughts correlated with one another in his design process. The findings suggest that design sketches serve not only as external memory or as a provider of visual cues for association of non-visual information, but also as a physical setting in which design thoughts are constructed on the fly.     

Design optimization of 3D steel structures: Genetic algorithms vs. classical techniques

In this paper an elitist genetic algorithm (GA) developed by the authors is compared with common commercial solutions for complex structural optimization. After its prior validation on two-dimensional (2D) structures, the GA was tuned and improved in order to obtain structural elements with minimum weights that satisfy the ultimate limit states of the applicable building code. Subsequently, the same spatial structures were optimized using a commercial structural analysis program. Finally, the cost and weight improvements obtained using the GA, although at a higher computational cost, are discussed.     

A qualitative energy-based unified representation for buildings

This paper presents the development of energy-based unified representations for buildings called Archi Bond Graphs and then specialises them as qualitative Archi Bond Graphs that combine graphical representations and qualitative equations. They can be applied to simulations of people behaviour and people-energy behaviour in space-people systems, building energy flows and building energy variations in different building energy systems, and energy interactions between these building subsystems. The applicability of qualitative Archi Bond Graphs is demonstrated through a building simulation for the dynamic energy interactions between the space-people system and building energy systems, including lighting system, and hydraulic system in a town-house design.     

Uncertainty and the design of building subsystems—A dynamic programming approach

This paper discusses the general problem of designing building subsystems which include probabilistic demands thus producing a stochastic problem. This class of problem, if linear, can be readily solved using classical stochastic linear programming. It is shown that the problem may be formulated as a stochastic dynamic program. A problem of designing the HVAC subsystem is formulated and solved as a dynamic program. Comparisons are made between the two methods. It is shown that dynamic programming is the more powerful method both in terms of obtaining the solution and in its post-optimality analysis. It is suggested that dynamic programming is a suitable technique for a wide range of building and architectural design problems.     

A genetic engineering approach to genetic algorithms

We present an extension to the standard genetic algorithm (GA), which is based on concepts of genetic engineering. The motivation is to discover useful and harmful genetic materials and then execute an evolutionary process in such a way that the population becomes increasingly composed of useful genetic material and increasingly free of the harmful genetic material. Compared to the standard GA, it provides some computational advantages as well as a tool for automatic generation of hierarchical genetic representations specifically tailored to suit certain classes of problems.