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Abstract: STM design provisions, such as those in Appendix A of ACI318-08, consist of rules for evaluating the capacity of the load-resisting truss that is idealized to carry the forces through the D-Region. These code rules were primarily derived from test data on simple D-Regions such as deep beams and corbels. However, these STM provisions are taken as being sufficiently general and conservative that they can be used for the design of all possible D-Regions, including those regions in which a highly statically indeterminate and complex truss is selected and designed to carry the imposed loadings. Since STM design provisions are only for capacity assessment and given the wide range of applicability of the method, members designed using these STM provision may not necessarily exhibit satisfactory performance under service load levels or during overloads. More particularly, the limitation of current STM design provisions include: (1) no methodology for satisfactorily estimating the complete load-displacement response history, cracking loads, stress and strain states in reinforcement, and failure modes; (2) a lack of guidance for selecting the shape, dimensions, and stress limits of STM components; (3) a lack of guidance for proportioning of forces in statically indeterminate STM designs; and (4) an inability to employ performance-based design concepts. To overcome these limitations, an experimental and computational program was conducted. This research aimed to generate the data needed for evaluating and validating the STM approach, for advancing STM shape selection techniques, and also to develop more reliable computational models for predicting the response of cracked structural concrete. In addition, a design and analysis framework that enables for automated nonlinear FEA design validation is proposed that integrates the current STM design provisions with two additional components: (1) the shape selection technique of STM based on topology optimization and (2) the new automated nonlinear FEA tool that was specialized for modeling and analyzing complex D-Regions.

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