This thesis implemented a prototype of an expert system shell for support of engineering design activities in the way of logic programming. The development of the system is based on the theoretical framework for knowledge-based system design and the formal modeling concepts. Under the above methodologies, two knowledge representations, production rule system and system entity structure, are incorporated into the knowledge base for figuring design structures. Here the production system scheme is employed for synthesis of design models represented in the system entity structure. The whole system is coded in Turbo Prolog and a specific domain knowledge, namely a local area network, is currently used as a testbed environment.

Thesis (Ph.D)--Mechanical Engineering, Georgia Institute of Technology, 2009. / Committee Co-Chair: Dr. Christiaan J. J. Paredis; Committee Co-Chair: Dr. Russell S. Peak; Committee Member: Dr. Charles Eastman; Committee Member: Dr. David McDowell; Committee Member: Dr. David Rosen; Committee Member: Dr. Steven J. Fenves. Part of the SMARTech Electronic Thesis and Dissertation Collection.

In simulation-based design, a key challenge is to formulate and solve analysis problems efficiently to evaluate a large variety of design alternatives. The solution of analysis problems has benefited from advancements in commercial off-the-shelf math solvers and computational capabilities. However, the formulation of analysis problems is often a costly and laborious process. Traditional simulation templates used for representing analysis problems are typically brittle with respect to variations in artifact topology and the idealization decisions taken by analysts. These templates often require manual updates and "re-wiring" of the analysis knowledge embodied in them. This makes the use of traditional simulation templates ineffective for multi-disciplinary design and optimization problems. Based on these issues, this dissertation defines a special class of problems known as variable topology multi-body (VTMB) problems that characterizes the types of variations seen in design-analysis interoperability. This research thus primarily answers the following question: How can we improve the effectiveness of the analysis problem formulation process for VTMB problems? The knowledge composition methodology (KCM) presented in this dissertation answers this question by addressing the following research gaps: (1) the lack of formalization of the knowledge used by analysts in formulating simulation templates, and (2) the inability to leverage this knowledge to define model composition methods for formulating simulation templates. KCM overcomes these gaps by providing: (1) formal representation of analysis knowledge as modular, reusable, analyst-intelligible building blocks, (2) graph transformation-based methods to automatically compose simulation templates from these building blocks based on analyst idealization decisions, and (3) meta-models for representing advanced simulation templates VTMB design models, analysis models, and the idealization relationships between them. Applications of the KCM to thermo-mechanical analysis of multi-stratum printed wiring boards and multi-component chip packages demonstrate its effectiveness handling VTMB and idealization variations with significantly enhanced formulation efficiency (from several hours in existing methods to few minutes). In addition to enhancing the effectiveness of analysis problem formulation, KCM is envisioned to provide a foundational approach to model formulation for generalized variable topology problems.

The complexity in multiscale systems design is significantly greater than in conventional systems because in addition to interactions between components, couplings between physical phenomena and scales are also important. This complexity amplifies two design challenges: a) complexity of coupled simulation models prohibits design space exploration, and b) unavailability of complete simulation models that capture all the interactions. Hence, the challenge in design of multiscale systems lies in managing this complexity and utilizing the available simulation models and information in an efficient manner to support effective decision-making. In order to address this challenge, our primary hypothesis is that the information and computational resources can be utilized in an efficient manner by designing design-processes (meta-design) along with the products. The primary hypothesis is embodied in this dissertation as a framework for integrated design of products and design processes. The framework consists of three components 1) a Robust Multiscale Design Exploration Method (RMS-DEM), 2) information-economics based metrics and methods for simplification of complex design processes and refinement of simulation models, and 3) an information modeling strategy for implementation of the theoretical framework into a computational environment. The framework is validated using the validation-square approach that consists of theoretical and empirical validation. Empirical validation of the framework is carried out using various examples including: pressure vessel design, datacenter cooling system design, linear cellular alloy design, and multifunctional energetic structural materials design. The contributions from this dissertation are categorized in three research domains: a) multiscale design methodology, b) materials design, and c) computer-based support for collaborative, simulation-based multiscale design. In the domain of design methodology, new methods and metrics are developed for integrating the design of products and design processes. The methods and metrics are applied in the field of materials design to develop design-processes and specifications for Multifunctional Energetic Structural Materials. In the domain of computer-based support for design, an information modeling strategy is developed to provide computational support for meta-design. Although the framework is developed in the context of multiscale systems it is equally applicable to design of any other complex system.

Problem: Engineering design decisions require the integration of information from multiple and disparate sources. However, this information is often independently created, limited to a single perspective, and not formally represented, thus making it difficult to formulate decisions. Hence, the primary challenge is the development of computational representations that facilitate the exchange of information for decision support. Approach: First, the scope of this research is limited to representing design decisions as compromise decision support problems (cDSP). To address this challenge, the primary hypothesis is that a formal language will enable the semantics of cDSP to be captured, thus providing a digital interface through which design information can be exchanged. The primary hypothesis is answered through the development of a description logic (DL) based formal language. The primary research question is addressed in four sub-questions. The first two research questions relate to the development of a vocabulary for representing the semantics of the cDSP. The first hypothesis used to answer this question is that formal information modeling techniques can be used to explicitly capture the semantics and structure of the cDSP. The second research question is focused on the realization of a computer-processible representation. The hypothesis used to answer this question is that DL can be used for developing computational-based representations. The third research question is related to the organization and retrieval of decision information. The hypothesis used to answer this question is DL reasoning algorithms can be used to support organization and retrieval. Validation: The formal language developed in this dissertation is theoretically and empirically validated using the validation square approach. Validation of the hypotheses is achieved by systematically building confidence through example problems. Examples include the cDSP construct, analysis support models, the design of a cantilever beam, and design of a structural fin array heat sink. Contributions: The primary contribution from this dissertation is a formal language for capturing the semantics of cDSPs and analysis support models comprised of: (1) a systematic methodology for decision formulation, (2) a cDSP vocabulary, (3) a graphical information model, and (4) a DL-based representation. The components, collectively, provide a means for exchanging cDSP information.