Practical Knowledge Based Systems In Conceptual Design

Conceptual Design is one of the few areas of Engineering Design where computers have yet to make an impact. With the development of Knowledge Based Systems it is now possible to rectify this situation. This publication deals with the use of Knowledge Based Systems (KBS) as tools for conceptual design. Included are neglected aspects such as evaluation and user needs. Practical Knowledge Based Systems in Conceptual Design is based on the authors' experience of developing KBS for use in civil engineering, an area of industrial application which is recognised as being one of great potential. The methodology has been tried and tested by designers. Examples of systems which have been developed to solve specific design problems are included.

Ann Macintosh Napier University, UK The papers in this volume are the refereed application papers presented at ES2001, the Twenty-fIrst SGES International Conference on Knowledge Based Systems and Applied ArtifIcial Intelligence, held in Cambridge in December 200 I. The scope of the application papers has expanded over recent years to cover not just innovative applications using traditional knowledge based systems, but also to include applications demonstrating the whole range of AI technologies. These papers continue to illustrate the maturity of AI as a commercially viable technology to solve real world problems. The papers were subject to refereeing by at least two expert referees. All papers that were in any way controversial were discussed in depth by the Application Programme Committee. For the ES2001 Application Stream, a paper is acceptable even if it describes a system that has not yet been installed, provided the application is original and the paper discusses the kind of things that would help others needing to solve a similar problem. Papers have been selected to highlight critical areas of success - and failure - and to present the benefIts and lessons learnt to other developers. This volume contains sixteen papers describing deployed or emerging applications in a range of diverse areas: business and commerce, engineering, manufacturing, knowledge and information management, and music.

Concerned with a design practice for knowledge-based systems, this book describes a method for managing the design of large-scale database systems. These can be used for problems which may involve techniques derived from artificial intelligence.

Knowledge-based systems are increasingly found in a wide variety of settings and this handbook has been written to meet a specific need in their widening use. While there have been many successful applications of knowledge-based systems, some applications have failed because they never received the corrective feedback that evaluation provides for keeping development focused on the users' needs in their actual working environment. This handbook provides a conceptual framework and compendium of methods for performing evaluations of knowledge-based systems during their development. Its focus is on the users' and subject matter experts' evaluation of the usefulness of the system, and not on the developers' testing of the adequacy of the programming code. The handbook permits evaluators to systematically answer the following kinds of questions: Does the knowledge-based system meet the users' task requirements? Is the system easy to use? Is the knowledge base logically consistent? Does it meet the required level of expertise? Does the system improve performance? The authors have produced a handbook that will serve two audiences: a tool that can be used to create knowledge-based systems (practitioners, developers, and evaluators) and a framework that will stimulate more research in the area (academic researchers and students). To accomplish this, the handbook is built around a conceptual framework that integrates the different types of evaluations into the system of development process. The kinds of questions that can be answered, and the methods available for answering them, will change throughout the system development life cycle. And throughout this process, one needs to know what can be done, and what can't. It is this dichotomy that addresses needs in both the practitioner and academic research audiences.

This book introduces a stability and control methodology named AeroMech, capable of sizing the primary control effectors of fixed wing subsonic to hypersonic designs of conventional and unconventional configuration layout. Control power demands are harmonized with static-, dynamic-, and maneuver stability requirements, while taking the six-degree-of-freedom trim state into account. The stability and control analysis solves the static- and dynamic equations of motion combined with non-linear vortex lattice aerodynamics for analysis. The true complexity of addressing subsonic to hypersonic vehicle stability and control during the conceptual design phase is hidden in the objective to develop a generic (vehicle configuration independent) methodology concept. The inclusion of geometrically asymmetric aircraft layouts, in addition to the reasonably well-known symmetric aircraft types, contributes significantly to the overall technical complexity and level of abstraction. The first three chapters describe the preparatory work invested along with the research strategy devised, thereby placing strong emphasis on systematic and thorough knowledge utilization. The engineering-scientific method itself is derived throughout the second half of the book. This book offers a unique aerospace vehicle configuration independent (generic) methodology and mathematical algorithm. The approach satisfies the initial technical quest: How to develop a ‘configuration stability & control’ methodology module for an advanced multi-disciplinary aerospace vehicle design synthesis environment that permits consistent aerospace vehicle design evaluations?

Computer technology has revolutionized many aspects of building design, such as drafting, management, construction - even building with robots. This revolution has expanded into the field of design creativity. Presented in this book is an up-to-date, comprehensive picture of research advances in the fast-growing field of informatics applied to conceptual stages in the generation of artifacts - in particular, buildings. It addresses the question how far and in what ways creative design can be intelligently automated. Among the topics covered are: the use of precedents; the relations between case-based, rule-based, and principle-based architectural design reasoning; product typology; artifact thesauruses; the inputting and retrieval of architectural knowledge; the visual representation and understanding of existing or projected built forms; empirical and analytical models of the design process and the design product; desktop design toolkits; grammars of shape and of function; multiple-perspective building data structures; design as a multi-agent collaborative process; the integration of heterogeneous engineering information; and foundations for a systematic approach to the development of knowledge-based design systems. The papers provide a link between basic and practical issues: - fundamental questions in the theory of artifact design, artifical intelligence, and the cognitive science of imagination and reasoning; - problems in the computerization of building data and design facilities; - the practical tasks of building conception, construction and evaluation. The automation of creative design is itself considered as an engineering design problem. The implications of current and future work for architectural education and research in architectural history, as well as for computer-integrated construction and the management of engineering projects are considered.

This book presents the state of the art of artificial intelligence techniques applied to structural engineering. The 28 revised full papers by leading scientists were solicited for presentation at a meeting held in Ascona, Switzerland, in July 1998. The recent advances in information technology, in particular decreasing hardware cost, Internet communication, faster computation, increased bandwidth, etc., allow for the application of new AI techniques to structural engineering. The papers presented deal with new aspects of information technology support for the design, analysis, monitoring, control and diagnosis of various structural engineering systems.