Physical systems can be modelled at many levels of approximation. The right model depends on the problem to be solved. In many cases, a combination of models will be more effective than a single model. Our research investigates this idea in the context of engineering design optimization. We present a family of strategies that use multiple models for unconstrained optimization of engineering designs. The strategies are useful when multiple approximations of an objective function can be implemented by compositional modelling techniques. We show how a compositional modelling library can be used to construct a variety of locally calibratable approximation schemes that can be incorporated into the optimization strategies. We analyze the optimization strategies and approximation schemes to formulate and prove sufficient conditions for correctness and convergence. We also report experimental tests of our methods in the domain of sailing yacht design. Our results demonstrate dramatic reductions in the CPU time required for optimization, on the problems we tested, with no significant loss in design quality.

Published research on design rationale (DR) goes back at least 25 years. Judging by the number of publications and the variety of application domains, there has been a significant increase in related research activities in recent years. For example, there have been other special issues on design rationale (e.g., Carrol & Moran, 1991), workshops in international conferences (e.g., Lee, 1992; Chung & Bañares–Alcántara, 1994), and the first book on design rationale has just appeared (Carrol & Moran, 1996).

In a construction project, resource leveling techniques are necessary as a primary schedule-improvement tool to reduce overall project cost by decreasing day-to-day fluctuation in resource usage and resource idleness. There are, however, some limitations in traditional resource leveling techniques. Conventional heuristic approaches cannot guarantee a near-optimum solution for every construction project; a given heuristic may perform well on one project and poorly on another. The existing optimization approaches, such as linear programming and enumeration methods, are best applicable only to small size problems. Recently, there has been success in the use of Artificial Neural Networks (ANNs) for solving some optimization problems. The paper discusses how state-of-the-art ANNs can be a functional alternative to traditional resource leveling techniques. It then investigates the application of different ANN models (such as backpropagation networks, Hopfield networks, Boltzmann machines, and competition ANNs) to resource leveling problems. Because the development of ANNs involves not only science but also experience, the paper presents various intuitive yet effective ways of mapping resource leveling problems on different applicable ANN architectures. To demonstrate the application of ANNs to resource leveling, a simple ANN model is developed using a Hopfield network. The conclusion highlights the usefulness and the limitations of ANNs when applied to resource leveling problems.

The spatial synthesis problem addressed in this paper is the configuration of rectangles in 2D space, where the sides of the rectangles are parallel to an orthogonal coordinate system. Variables are the locations of the edges of the rectangles and their orientations. Algebraic constraints on these variables define a layout and constitute a constraint satisfaction problem. We give a new O(n2) algorithm for incremental path-consistency, which is applied after adding each algebraic constraint. Problem requirements are formulated as spatial relations between the rectangles, for example, adjacency, minimum distance, and nonoverlap. Spatial relations are expressed by Boolean combinations of the algebraic constraints; called disjunctive constraints. Solutions are generated by backtracking search, which selects a disjunctive constraint and instantiates its disjuncts. The selected disjuncts describe an equivalence class of configurations that is a significantly different solution. This method generates the set of significantly different solutions that satisfy all the requirements. The order of instantiating disjunctive constraints is critical for search efficiency. It is determined dynamically at each search state, using functions of heuristic measures called textures. Textures implement fail-first and prune-early strategies. Extensions to the model, that is, 3D configurations, configurations of nonrectangular shapes, constraint relaxation, optimization, and adding new rectangles during search are discussed.

Shape annealing, a computational design method applied to structural design, has been extended to the design of traditional and innovative three-dimensional domes that incorporate the design goals of efficiency, economy, utility, and elegance. In contrast to deterministic structural optimization methods, shape annealing, a stochastic method, uses lateral exploration to generate multiple designs of similar quality that form a structural language of solutions. Structural languages can serve to enhance designer creativity by presenting multiple, spatially innovative, yet functional design solutions while also providing insight into the interaction between structural form and the trade-offs involved in multi-objective design. The style of the structures within a language is a product of the shape grammar that defines the allowable structural forms and the optimization model that provides a functional measure of the generated forms to determine the desirable designs. This paper presents an application of geodesic dome patterns that have been embodied in a shape grammar to define a structural language of domes. Within this language of domes, different dome styles are generated by changing the optimization model for dome design to include the design goals of maximum enclosure space, minimum surface area, minimum number of distinct cross-sectional areas, and visual uniformity. The strengths of the method that will be shown are 1) the generation of both conventional domes similar to shape optimization results and spatially innovative domes, 2) the generation of design alternatives within a defined design style, and 3) the generation of different design styles by modifying the language semantics provided by the optimization model.

Present-day software applications are increasingly required to be “reuse-conscious” in terms of the operating platforms, topology, and evolutionary requirements. Traditionally, there has been much difficulty in communicating specialized knowledge like design intents, design recommendations, and design justifications in the discipline of software engineering. This paper presents a methodology based on the combination of design rationale and design patterns to design reusable software systems. Design rationale is the representation of the reasoning behind the design of an artifact. Design patterns are descriptions of communicating objects and classes that are customized to solve a general design problem in a particular context. The paper details the use of an explicit software development process to capture and disseminate the specialized knowledge (i.e., intents, recommendations, and justifications) that augments the description of the cases in a library (i.e., design patterns) during the development of software applications by heterogeneous groups. The importance of preserving and using this specialized knowledge has become apparent with the growing trend of combining the software development process with the product (i.e., software code). The importance of codifying corporate memory in this regard is also important considering the changing nature of the workplace, where more people are on contract. The information on how and why a software code was developed becomes essential for efficient and smooth continuity of the present software project as well as for reusing the code in future projects. It has become essential to capture the design rationale to develop and design software systems efficiently and reliably. The software prototype developed using the combined methodology will be used as a part of an integrated design environment for reusable software design. This environment supports collaborative development of software applications by a group of software specialists from a library of building block cases represented by design patterns.

Class-centered data models, such as the object-oriented data model, are inadequate for supporting engineering design product models because of their lack of support for object evolution, schema evolution, and semantic and user-defined relationships. Description logic overcomes these limitations by providing constructs for intentional description of classes, relationships, and objects. By combining description logic with object-oriented modelling concepts, design product schemas and data can be uniformly represented and modified throughout the design process.

Gradient-based numerical optimization of complex engineering designs offers the promise of rapidly producing better designs. However, such methods generally assume that the objective function and constraint functions are continuous, smooth, and defined everywhere. Unfortunately, realistic simulators tend to violate these assumptions. We present a rule-based technique for intelligently computing gradients in the presence of such pathologies in the simulators, and show how this gradient computation method can be used as part of a gradient-based numerical optimization system. We tested the resulting system in the domain of conceptual design of supersonic transport aircraft, and found that using rule-based gradients can decrease the cost of design space search by one or more orders of magnitude.

Constraint-based reasoning is a problem-solving approach based on deductive reasoning. In this approach, a problem is modeled in terms of hypotheses and conclusion constraints, and it is solved via constraint satisfaction. The ability to handle linear and nonlinear algebraic constraints is essential for successful application of constraint-based reasoning in engineering. Due to the scarcity of algebraic techniques for satisfying nonlinear constraints, little attention has been paid to the use of constraint-based reasoning for solving nonlinear problems. This paper examines the use of the Grobner Bases method for satisfying nonlinear constraints in the context of constraint-based reasoning. After a brief introduction to the Grobner Bases method and its role in constraint-based reasoning, two examples are presented. The first example illustrates the use of Grobner bases, in the context of constraint-based reasoning, for reasoning about the behavior of beams. The second example illustrates the geometry configuration of truss structures via constraint-based reasoning.

This paper is concerned with presenting guidelines to aide in the selection of the appropriate network architecture for back-propagation neural networks used as approximators. In particular, its goal is to indicate under what circumstances neural networks should have two hidden layers and under what circumstances they should have one hidden layer. Networks with one and with two hidden layers were used to approximate numerous test functions. Guidelines were developed from the results of these investigations.

A design is a plan containing guidelines to build and understand an artifact. Generally, this plan is constructed by a team of designers with different tasks, but sharing a common objective, that is, to create a high-quality, low-cost integrated artifact. Active Design Documents (ADDs) are powerful tools for cooperative design because they account for revealing the rationale among design participants while assisting each of them in their own. Design rationale capture and retrieval are critical issues on building documentation assistant tools. In this paper, we propose to achieve more efficient and effective delivery of design and designers intent by resorting to rhetorical means. The wealth of knowledge kept in ADD’s knowledge bases is organized into high-level Rhetorical Structure Theory (RST) schema and mapped onto input and output screen configurations that gear the interaction between systems and users. We illustrate the effects of such an organization with evidences from an implemented version of ADD for the domain of offshore platform.

Because mechanical operations are performed only up to a certain precision, the geometry of parts involved in real-life products is never known precisely. But if tolerance models for specifying acceptable variations have received a substantial attention, operations on toleranced objects have not been studied extensively. That is the reason why we address in this paper the computation of the union and the intersection of toleranced simple polygons, under a simple and already known tolerance model. First, we provide a practical and efficient algorithm that stores in an implicit data structure the information necessary to answer a request for specific values of the tolerances without performing a computation from scratch. If the polygons are of sizes m and n, and s is the number of intersections between edges occurring for all the combinations of tolerance values, the preprocessed data structure takes O(s) space and the algorithm that computes a union/intersection from it takes O((n + m)log s + k' + k log k) time, where k is the number of vertices of the union/intersection and k ≤ k' ≤ s. Although the algorithm is not output sensitive, we show that the expectations of k and k' remain within a constant factor τ, a function of the input geometry. Second, we define and study the stability of union or intersection features. Third, we list interesting applications of the algorithms related to feasibility of assembly and assembly sequencing of real assemblies.

Design support systems need to be developed on the basis of an understanding of the human design process to be useful during design. The explicit representation of design history and rationale are of particular importance for explanation and reuse. Within the DESIRE framework for compositional modelling, a generic task model of design has been developed that clearly specifies the role of design history and design rationale within the design process. The model provides a structure to distinguish different types of design rationale, according to the functional role they play in the design process. It has been used to structure the modelling process of an example aircraft design task, which illustrates the various instances of design rationale that can be generated.

This paper defines a number of general operations that accept arbitrary sets of values for two variables and general relations among three variables and generate a variety of third sets that are useful in design. Although the operations are defined without respect to mathematical or engineering domain, computing these operations depends on the specific mathematical domain, and algorithms are available for only a few domains. Appropriate software could make this complexity transparent to the designer, allowing the same conceptual operations to be used in many contexts. The paper proves a number of useful characteristics of the operations and offers examples of their potential use in design.

This paper describes the development of models to simulate the process of Concept Design Evaluation. The models are an amalgam of a number of statistically based methods and approaches taken from the probability, reliability, and quality domains. They assume that designers use decomposition of design to undertake evaluation at design characteristic level with the total design evaluation being achieved, in some way, via recomposition. The models described in this paper attempt to describe how designers may perform recomposition and hence total design evaluation. It is argued that the ability to model this human activity is important for the future development of knowledge-based design tools.

Case-based design (CBD) systems aim to solve a design problem by tailoring previously solved design problems to the current problem. Designers' specifications are used for indexing the knowledge base of the CBD system to retrieve an appropriate design case. Menu-based systems fail to capture designers' specifications effectively due to lack of expressiveness, while natural language systems are too immature to satisfy the goal. This paper presents the development of a graphical user interface (GUI) to implement a mechanical design specification language (MDSL) (Stelling, 1994) used to facilitate indexing in case-based mechanical design. The specification language is context-free and hence computable. It represents mechanical design knowledge in a (feature):(attribute) format suitable for indexing. An augmented transition network (ATN) parser is built using the grammar of the specification language. The parser provides syntactic as well as semantic checks. It also has capabilities to expand grammar and to adapt to a specific user domain. A graphical front end to the parser assists and guides the user through the specification language syntax in entering the design specifications. Provisions have been made to expand or edit the language grammar and vocabulary. The ATN parser was implemented in Common Lisp and the graphical user interface was written using the Gold Hill Windows Toolkit. Sample user interactions with the interface and screen dumps of the GUI are included.

The combination of the paradigms of shape algebras and predicate logic representations, used in a new method for describing designs, is presented. First-order predicate logic provides a natural, intuitive way of representing shapes and spatial relations in the development of complete computer systems for reasoning about designs. Shape algebraic formalisms have advantages over more traditional representations of geometric objects. Here we illustrate the definition of a large set of high-level design relations from a small set of simple structures and spatial relations, with examples from the domains of geographic information systems and architecture.