Research on empathy has been surging in popularity in the engineering design community since empathy is known to help designers develop a deeper understanding of the users’ needs. Because of this, the design community has become more invested in devising and assessing empathic design activities. However, research on empathy has been primarily limited to individuals, meaning we do not know how it impacts team performance, particularly in the concept generation and selection stages of the design process. Specifically, it is unknown how the empathic composition of teams, defined here as the average (elevation) and standard deviation (diversity) of team members’ empathy, would impact design outcomes during nominal group concept generation and early concept screening. Therefore, the goal of the current study is to investigate the impact of team empathy on nominal group concept generation and early concept screening in an engineering design student project. This was accomplished through a computational simulation of 13,482 teams of non-interacting brainstorming individuals generated by a statistical bootstrapping technique. This simulation drew upon a design repository of 806 ideas generated by first-year engineering students. The main findings from the study indicated that the impact of the elevation and diversity of different components of team empathy varied depending upon the specific design outcome (number of ideas, overall creativity, elegance, usefulness, uniqueness) and design stage (concept generation and concept screening). The results from this study can be used to guide team formation in engineering design.

I present an implementation of shape grammars that is aimed at supporting designers. It has two parts: a grammar editor and a stand-alone interpreter. The editor is the modeling application Rhinoceros3d using Python scripts. The interpreter is general, is three-dimensional, and supports subshape detection. A grammar is a Rhinoceros3d model; thus users can manipulate all its parts directly and immediately. That is, they can modify any shape without selecting or invoking an editor, and they can lay out the parts of the grammar in any way they find meaningful. Using this approach, which I call a whole-grammar approach, users are shielded from most subdomain tasks, like typing text files or specifying transformations. Informal observations suggest that users of this implementation can work effectively.

Architects use sketching and diagramming in their design process to perform functional reasoning, formal arrangements, analogy transfer, structure mapping, and knowledge acquisition. This paper describes a research framework of the author's efforts in the studies of design drawings and the building of computational sketching tools to support the early conceptual design process in architecture. The first part of the paper discusses empirical studies conducted to determine or guess a designer's thought process from sketches and thus identifies domain-specific graphical symbols. It proposes a reasoning process framework of drawing marks, acts, and reacts. The second part of the paper illustrates how design support tools could be developed based on these concepts and describes the various applications of the study, such as indexing and retrieving of design drawings or images based on the recognition of geometric shapes and the spatial relationships among them.

In designing a state space of possible designs is implied by the representation used and the computational processes that operate on that representation. GAs are a means of effectively searching that state space which is defined by the length of the genotype's bit string. Of particular interest in design computing are processes that enlarge that state space to change the set of possible designs. This paper presents one such process based on the generalization of the genetic crossover operation. A crossover operation of genetic algorithms is reinterpreted as a random sampling of interpolating phenotypes, produced by a particular case of phenotypic interpolation. Its generalization is constructed by using a more general version of interpolation and/or by adding extrapolation to interpolation. This generalized crossover has a potential to move the current population outside of the original state space. An adaptive strategy for state space enlargement, which is based on this generalization, is designed. This strategy can be used for computational support of creative designing. An example is given.