ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
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Description
The computation of the fundamental mode in structural moment frames provides valuable insight into the physical response of the frame to dynamic or time-varying loads. In standard practice, it is not necessary to solve for all n mode shapes in a structural system; it is therefore practical to limit the system to some determined number of r significant mode shapes. Current building codes, such as the American Society of Civil Engineers (ASCE), require certain class of structures to obtain 90% effective mass participation as a way to estimate the accuracy of a solution for base shear motion. A parametric study was performed from the collected data obtained by the analysis of a large number of framed structures. The purpose of this study was the development of rules for the required number of r significant modes to meet the ASCE code requirements. The study was based on the implementation of an algorithm and a computer program developed in the past. The algorithm is based on Householders Transformations, QR Factorization, and Inverse Iteration and it extracts a requested s (s<< n) number of predominate mode shapes and periods. Only the first r (r < s) of these modes are accurate. To verify the accuracy of the algorithm a variety of building frames have been analyzed using the commercially available structural software (RISA 3D) as a benchmark. The salient features of the algorithm are presented briefly in this study.
ContributorsGrantham, Jonathan (Author) / Fafitis, Apostolos (Thesis advisor) / Attard, Thomas (Committee member) / Houston, Sandra (Committee member) / Hjelmstad, Keith (Committee member) / Arizona State University (Publisher)
Created2014
Description
Most engineers may agree that an optimum design of a particular structure is a proposal that minimizes costs without compromising resistance, serviceability and aesthetics. Additionally to these conditions, the theory and application of the method that produces such an efficient design must be easy and fast to apply at the structural engineering offices.
A considerable amount of studies have been conducted for the past four decades. Most researchers have used constraints and tried to minimize the cost of the structure by reducing the weight of it [8]. Although this approach may be true for steel structures, it is not accurate for composite structures such as reinforced and prestressed concrete. Maximizing the amount of reinforcing steel to minimize the weight of the overall structure can produce an increase of the cost if the price of steel is too high compared to concrete [8]. A better approach is to reduce the total cost of the structure instead of weight. However, some structures such as Prestressed Concrete AASHTO Girders have been standardized with the purpose of simplifying production, design and construction. Optimizing a bridge girder requires good judgment at an early stage of the design and some studies have provided guides for preliminary design that will generate a final economical solution [17] [18]. Therefore, no calculations or optimization procedure is required to select the appropriate Standard AASHTO Girder. This simplifies the optimization problem of a bridge girder to reducing the amount of prestressing and mild steel only. This study will address the problem of optimizing the prestressing force of a PC AASHTO girder by using linear programming and feasibility domain of working stresses. A computer program will be presented to apply the optimization technique effectively.
A considerable amount of studies have been conducted for the past four decades. Most researchers have used constraints and tried to minimize the cost of the structure by reducing the weight of it [8]. Although this approach may be true for steel structures, it is not accurate for composite structures such as reinforced and prestressed concrete. Maximizing the amount of reinforcing steel to minimize the weight of the overall structure can produce an increase of the cost if the price of steel is too high compared to concrete [8]. A better approach is to reduce the total cost of the structure instead of weight. However, some structures such as Prestressed Concrete AASHTO Girders have been standardized with the purpose of simplifying production, design and construction. Optimizing a bridge girder requires good judgment at an early stage of the design and some studies have provided guides for preliminary design that will generate a final economical solution [17] [18]. Therefore, no calculations or optimization procedure is required to select the appropriate Standard AASHTO Girder. This simplifies the optimization problem of a bridge girder to reducing the amount of prestressing and mild steel only. This study will address the problem of optimizing the prestressing force of a PC AASHTO girder by using linear programming and feasibility domain of working stresses. A computer program will be presented to apply the optimization technique effectively.
ContributorsRaudales Valladares, Eduardo Rene (Author) / Fafitis, Apostolos (Thesis advisor) / Zapata, Claudia (Committee member) / Hjelmstad, Keith (Committee member) / Arizona State University (Publisher)
Created2016
Description
Civil infrastructures undergo frequent spatial changes such as deviations between as-designed model and as-is condition, rigid body motions of the structure, and deformations of individual elements of the structure, etc. These spatial changes can occur during the design phase, the construction phase, or during the service life of a structure. Inability to accurately detect and analyze the impact of such changes may miss opportunities for early detections of pending structural integrity and stability issues. Commercial Building Information Modeling (BIM) tools could hardly track differences between as-designed and as-built conditions as they mainly focus on design changes and rely on project managers to manually update and analyze the impact of field changes on the project performance. Structural engineers collect detailed onsite data of a civil infrastructure to perform manual updates of the model for structural analysis, but such approach tends to become tedious and complicated while handling large civil infrastructures.
Previous studies started collecting detailed geometric data generated by 3D laser scanners for defect detection and geometric change analysis of structures. However, previous studies have not yet systematically examined methods for exploring the correlation between the detected geometric changes and their relation to the behaviors of the structural system. Manually checking every possible loading combination leading to the observed geometric change is tedious and sometimes error-prone. The work presented in this dissertation develops a spatial change analysis framework that utilizes spatiotemporal data collected using 3D laser scanning technology and the as-designed models of the structures to automatically detect, classify, and correlate the spatial changes of a structure. The change detection part of the developed framework is computationally efficient and can automatically detect spatial changes between as-designed model and as-built data or between two sets of as-built data collected using 3D laser scanning technology. Then a spatial change classification algorithm automatically classifies the detected spatial changes as global (rigid body motion) and local deformations (tension, compression). Finally, a change correlation technique utilizes a qualitative shape-based reasoning approach for identifying correlated deformations of structure elements connected at joints that contradicts the joint equilibrium. Those contradicting deformations can help to eliminate improbable loading combinations therefore guiding the loading path analysis of the structure.
Previous studies started collecting detailed geometric data generated by 3D laser scanners for defect detection and geometric change analysis of structures. However, previous studies have not yet systematically examined methods for exploring the correlation between the detected geometric changes and their relation to the behaviors of the structural system. Manually checking every possible loading combination leading to the observed geometric change is tedious and sometimes error-prone. The work presented in this dissertation develops a spatial change analysis framework that utilizes spatiotemporal data collected using 3D laser scanning technology and the as-designed models of the structures to automatically detect, classify, and correlate the spatial changes of a structure. The change detection part of the developed framework is computationally efficient and can automatically detect spatial changes between as-designed model and as-built data or between two sets of as-built data collected using 3D laser scanning technology. Then a spatial change classification algorithm automatically classifies the detected spatial changes as global (rigid body motion) and local deformations (tension, compression). Finally, a change correlation technique utilizes a qualitative shape-based reasoning approach for identifying correlated deformations of structure elements connected at joints that contradicts the joint equilibrium. Those contradicting deformations can help to eliminate improbable loading combinations therefore guiding the loading path analysis of the structure.
ContributorsKalasapudi, Vamsi Sai (Author) / Tang, Pingbo (Thesis advisor) / Chong, Oswald (Committee member) / Hjelmstad, Keith (Committee member) / Arizona State University (Publisher)
Created2017