Faculty Advisor or Committee Member
Leonard D. Albano, Advisor
Faculty Advisor or Committee Member
David A. Lucht, Department Head
Robert W. Fitzgerald, Brian J. Meacham
"Thanks to significant worldwide research directed at understanding and predicting structural behavior at elevated temperatures, analytical methods are available to support a rational, performance-based approach to the structural design of buildings for fire conditions. To utilize these analytical methods effectively, structural engineers need guidance on reliable and appropriate approaches to dealing with a variety of factors, including the effects of fire protection measures, temperature-dependent thermal and structural properties, elastic and inelastic behavior of structural components and assemblies, and thermal and structural response of framing connections. To meet the objective of guiding the structural engineer in appropriate analytical methods and parameter values for performance-based structural fire protection, this thesis proposes a comprehensive way of thinking about the design and analysis of structures for fire conditions. This integration of structural engineering and fire protection engineering into a functional framework is defined herein as Fire-Robust Structural Engineering (FRSE). The FRSE process, which is presented as a series of flowcharts, is designed to guide the structural engineer in executing the functions involved in the design of fire-safe structures and to help identify informational needs critical to these tasks. Currently, mechanisms for identifying possible resources to fulfill fire-related informational needs are generally organized for the convenience of the fire research community. Identification of resources that provide appropriate information for fire-robust structural engineering, such as laboratory fire test results, parametric studies of analytical methods, and other sources of guidance, is often difficult because these resources are rarely organized and presented for the benefit of structural engineers. To begin to resolve this problem, this thesis has developed a prototype information management system (IMS) based on the framework of the FRSE process. The IMS addresses the critical challenge of organizing and presenting the available knowledge and data in a format that is consistent with the perspective and informational needs of the structural engineer. The prototype version of the IMS has been implemented using a Microsoft ExcelÂ® platform. In addition to guidance in utilizing specific analytical methods and choosing appropriate parameter values, the structural engineer also requires an understanding of the input requirements and accuracy of various analytical methods in order to make informed decisions regarding which methods are appropriate for use with different structural configurations. Therefore, this thesis includes a model study as an example of a resource that could aid the structural engineer in making such decisions. The model study compares various analytical methods (simplified spreadsheet applications and advanced finite element techniques) to published laboratory test data and discusses concerns that the structural engineer must keep in mind when using each method. Conclusions are drawn regarding the appropriateness of each analytical method to the analysis of a fully restrained, spray-protected steel beam. Given this type of information, the structural engineer can make decisions regarding the types of analytical methods and the level of analytical sophistication required to solve a given design problem."
Worcester Polytechnic Institute
Fire Protection Engineering
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Johann, Matthew A., "Fire-Robust Structural Engineering: A Framework Approach to Structural Design for Fire Conditions" (2002). Masters Theses (All Theses, All Years). 1127.
structural engineering, fire safety, framework approach, performance-based design, information management, finite element, lumped-parameter, laboratory tests, steel, beam, restrained, plastic analysis, Building, Fireproof, Structural engineering, Fire testing, Data processing