Doctor of Philosophy, The Ohio State University, 2007, Civil Engineering

Delays in construction projects are inevitable; as a result claims and disputes arise among different construction parties. Different causes of delay can come into play, therefore, there is a need to identify and classify different causes of project delay. Estimation of the likelihood of delay resulting from different factors that contribute to project delay is essential to project success. Different factors that contribute to project delay affect the likelihood of project delay in different effectiveness degrees. There is a pressing need to estimate the likelihood of delay by implementing analysis methods and examining these methods. Probabilistic fault tree analysis and fuzzy fault tree analysis are two methods suggested by this research to estimate the likelihood of delay. Fuzzy fault tree analysis is performed by planners and managers since they select the delay causes that are applicable to a given project and categorize these delay causes into enabling, triggering, and procedural causes. Then, managers assess the degree of effectiveness of each cause of delay to overall project delay. Assessment of the contributing causes of delay and their degree of effectiveness on project delay uses subjective judgment linguistic terms. The result of the fuzzy fault tree analysis is a likelihood of delay membership function that is compared to the predefined fuzzy logic model to assess the degree of severity of the likelihood of delay. Likelihood of delay membership function is further quantified using the weighted average defuzzification method. Different fuzzy logic models are implemented into the fuzzy fault tree analysis, using Visual Basic software, these models are Baldwin's rotational model, the Angular model, the Translational model and the Triangular model. Recommendation of the fuzzy logic model that is best applied to a given scenario needs further sensitivity analysis and is beyond the scope of this research. Validation of the fuzzy fault tree analysis computer (open full item for complete abstract)

Committee: Fabian Tan (Advisor) Subjects: Engineering, Civil

Master of Science, The Ohio State University, 2016, Civil Engineering

Dayanta, also called the Great Wild Goose Pagoda, is a square seven-floor pagoda located in Xi'an, Shaanxi Province, China. This thesis provides a visualized investigation of Dayanta in three aspects: (1) redrawing the four different versions of Dayanta in history; (2) providing a 3-D simulation of the structure and construction sequence of today's Dayanta by using Autodesk 3DS MAX in a step-by-step manner; and (3) evaluating the performance of Dayanta by using Fuzzy Fault Tree Analysis (FFTA) in the form of diagram and fuzzy logic graphics. A graphics pipeline has been proposed as the methodology to accomplish the entire modeling work, and it offers an effective method for the digital reconstruction of ancient buildings and graphical simulation in its structure and construction activities. The significance of the Dayanta modeling work can be reflected in the contributions to preserve ancient architecture, visualize historical data in 3-D graphics, and apply the models in education. The results produced by the two FFTA agree with a real observation of Dayanta, ranging from extremely good to very good, verifying the effectiveness of the use of FFTA to investigate the Dayanta's performance. In conclusion, the visualized investigation of ancient building can be regarded as an exploration of the application of visualization techniques and the employment of fuzzy methods when investigating the performance of the Dayanta.

Committee: Fabian Tan (Advisor); Abdollah Shafieezadeh (Committee Member); Philip Smith (Committee Member); Karen Dannemiller (Committee Member) Subjects: Archaeology; Architecture; Asian Studies; Civil Engineering; Computer Engineering; Design; Education; Engineering; History