Download or read book Analytical Modeling of Wood-frame Shear Walls and Diaphragms written by Johnn Paul Judd and published by . This book was released on 2005 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt: Analytical models of wood-frame shear walls and diaphragms for use in monotonic, quasi-static (cyclic), and dynamic analyses are developed in this thesis. A new analytical model is developed to accurately represent connections between sheathing panels and wood framing members (sheathing-to-framing connections) in structural analysis computer programs. This new model represents sheathing-to-framing connections using an oriented pair of nonlinear springs. Unlike previous models, the new analytical model for sheathing-to-framing connections is suitable for both monotonic, cyclic, or dynamic analyses. Moreover, the new model does not need to be scaled or adjusted. The new analytical model may be implemented in a general purpose finite element program, such as ABAQUS, or in a specialized structural analysis program, such as CASHEW. The analytical responses of several shear walls and diaphragms employing this new model are validated against measured data from experimental testing. A less complex analytical model of shear walls and diaphragms, QUICK, is developed for routine use and for dynamic analysis. QUICK utilizes an equivalent single degree of freedom system that has been determined using either calibrated parameters from experimental or analytical data, or estimated sheathing-to-framing connection data. Application of the new analytical models is illustrated in two applications. In the first application, the advantages of diaphragms using glass fiber reinforced polymer (GFRP) panels in conjunction with plywood panels as sheathing (hybrid diaphragms) are presented. In the second application, the response of shear walls with improperly driven (overdriven)nails is determined along with a method to estimate strength reduction due to both the depth and the percentage of total nails overdriven.