Doctor of Philosophy, The Ohio State University, 2018, Civil Engineering

This research focuses on the wall and the towers of the Great Wall of China in Jinshanling, located in Luanping County, approximately 153 km northeast of Beijing, China. The study reveals that the main construction methods used to create the wall were rammed earth and rubble construction, foundation stone masonry installation, and mostly Flemish configuration brick masonry installation. These methods were implemented in a bottom-up construction. In some areas, especially in the eastern area of Jinshanling, foundation stones and bricks were integrated with existing stone masonry (large stones and mortar) from an earlier construction period at the beginning of the Ming Dynasty. The main construction method used to construct the towers was also rammed earth and rubble construction for the base of the tower's inner core of the base. Similarly, to the wall, the towers were completed with an outer layer at the base composed of fire kiln bricks and foundation stones. The installation of fire kiln brick masonry and foundation stone masonry were implemented on the outer layer of the towers' base. The main difference between the towers is the support system on the first floor. One design used timber columns on the first floor to support the second floor of the towers, while a second design used interior brick walls, arches, and vaults on the first floor to support the second floor. There is a statistical correlation showing that the bricks and arches supporting the towers were more likely to be implemented at a higher elevation in sampled towers. The findings from literature searches, site visits, and interviews of experts on the Great Wall were used as the inputs for the fuzzy sets and logic assessments. The fuzzy models used in the evaluations were the fuzzy sets angular model and the fuzzy sets rotational model. The outputs of the fuzzy evaluations (i.e., the main construction method, the sequence implemented at the time of construction, and the current performance of t (open full item for complete abstract)

Committee: Fabian Hadipriono Tan (Advisor) Subjects: Civil Engineering; History

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