Ph.D.

• This dissertation deals with the development of a model that aim to assist engineers in the conceptual phase of the structural design of tall buildings by providing him/her with organized and reliable information. This preliminary conceptual design involves selecting preliminary materials, selecting the overall structural form of the building, producing a rough dimensional layout, and considering technological possibilities. Decisions are made on the basis of such information as height of the building, building use, typical live load, wind velocity, earthquake loading, design fundamental period, design acceleration, maximum lateral deflection, spans, story height, and other clients requirements. The model objective is to provide designers with adapted past design solutions with the help of a distributed multi-reasoning mechanism creating a support system to enhance creativity, engineering knowledge and experience of designers. To prove the feasibility of the proposed model I developed a distributed artificial intelligence computer system that works as a decision support tool for the preliminary design of tall buildings structures. This system applies an agent like approach developing competence modules, which is an expert at a particular small task oriented competence. The Internet is being used as a communication backbone among the different systems that implement the reasoning mechanisms being employed. The current implementation was developed with three modules: The classification module implemented by a C4.5 agent, the past cases/experience module implemented by a Case Based Reasoning agent, and the adaptation module implemented by the Genetic Algorithm agent.

Degree of S.M. Civil Engineering

Specialist in Advanced Construction Technology

B.S. Civil Engineering