The number of Tall buildings is growing rapidly in metropolitan areas in the US and around the world. These buildings, designed to meet certain performance goal, will sustain damage during a large magnitude earthquake. The incurred damage can be light, moderate or severe. While the severe damage is easier to be visually identified, the light and moderate damages require a detailed damage survey after an earthquake. Furthermore, conventional visual inspection of an affected tall building can take several weeks. Alternatively, monitoring the integrity of these structures using sensory data and detecting structural damage during or shortly after an earthquake can significantly help prevent or reduce monetary loss due to unnecessary closure of a safe building, and subsequently, help build smarter and more resilient cities.
Wave method for structural identification and health monitoring of buildings has received increasing attention in the past two decades. In this method, the structure is viewed as a wave-guide through which motion waves propagate. It has been shown for buildings that the velocity of vertically propagating waves, through the structure, can be used as a damage sensitive parameter in the monitoring of the structural health. The method models the building as a layered shear beam whose impulse response functions (IRFs) are fitted, in the least square sense, into the IRFs of the recorded data at the floors where sensors are placed.
This study is a companion to a research work performed by Rahmani and Todorovska. They used the wave method to identify a 54-story steel moment resisting frame building located in downtown Los Angeles. The building is instrumented at 6 levels and was subjected to 6 major earthquakes. As part of the identification algorithm, a 4-layer shear beam model was fit into the recorded data. Rahmani and Todorovska found that the identified vertical wave velocities are sensitive to small changes in the structure. Their results revealed that reductions in the identified velocities during one event was recovered during a subsequent smaller event indicating that the building’s response was predominantly elastic during the 6 analyzed earthquakes. Another important observation was the variability (coefficient of variation) of identified velocities which were as large as 5%. While these variabilities were related to several reasons, the root sources causing most contribution to these variabilities and their extents were unknown. The main goal of this thesis is to determine the extent of variability in the identified velocities and their root causes.
In this project, the identification variability was investigated using a detailed finite element model (FEM) of the building (i.e., the 54-Story Steel-MRF). We have acquired the structural drawings of the building and created an as-built FE model of the building in ETABS-18. Extensive rounds of model-updating were carried out to identify an FEM that best matches the recorded response of the structure as well the its modal characteristics. Chapter 3 presents details of this updating process and our findings. The updated FEM was then subjected to 9 major earthquake accelerations at its base. The biaxial input accelerations were taken from the recorded response at the ground level of the actual building. Linear time-history analysis of building was carried out and acceleration response at levels of interest were collected.
Wave method was then employed to inversely identify the finite element model of the building. Observed variabilities of the identified shear wave velocities for the FE model were compared to the actual building. Chapter 4 presents these results and comparisons. The identification results for our FE model revealed that there is a variability (coefficient of variation) between 0.7% to 2.2%. This variability is about half the one in the actual building. In chapter 4, a list of all plausible physical phenomena that could contribute to the observed variability for the actual building and/or the FE model are discussed. It was concluded that among all phenomena, wave dispersion due to soil structure interaction, manmade change in floors’ occupancy and usage, and thermal effects (environmental effects) are the main factors for the observed additional variability in the actual building.
|Commitee:||Calabrese, Andrea, Terzic, Vesna|
|School:||California State University, Long Beach|
|Department:||Civil Engineering & Construction Engineering Management|
|School Location:||United States -- California|
|Source:||MAI 82/4(E), Masters Abstracts International|
|Subjects:||Civil engineering, Engineering, Architectural engineering|
|Keywords:||Tall Steel Frame Building, Wave Method, Estimated Wave Velocities|
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