Probabilistic Site Response Analysis and Soil-Structure Interaction: A Data Science and Statistical Investigation Utilizing a Comprehensive Dataset in Japan and the US
Site response analysis (SRA) plays a crucial role in the performance-based design ofstructures subjected to earthquakes. It allows for the prediction of ground motion and the subsequent effects on structures. While the accuracy of current SRA methodologies has been the focus of much research, there are several sources of uncertainty in soil media that should be accounted for in design practice. These include variations in soil properties, which can affect the response of the ground to earthquakes. In addition to ground motion, the effects of soil-structure interaction (SSI) must also be taken into consideration, as they can significantly influence the response of a structure to an earthquake. Therefore, the incorporation of these factors is essential in the design process to ensure the safe and efficient performance of structures during earthquakes. There has been recent progress in developing methods to understand how uncertainties in soil parameters can affect the results of nonlinear (NL) SRA. However, it is not yet clear how reliable these methods are, and further testing using real-life data is needed to determine their strengths and weaknesses. Additionally, soil-structure interaction (SSI) analysis using the "direct" method, which involves analyzing the entire soil-structure system at the same time under strong shaking scenarios, is becoming more common in engineering practice. However, the accuracy of this method is uncertain due to the complex nonlinear behavior of soil, structures, and foundations. Similarly, further testing using real-life data is needed to understand the strengths and weaknesses of this approach. Proposing new methodologies, and validating those against actual recordings for a large inventory of sites this report provides some recommendations for design purposes. The work done is presented in three parts. In the first part, a new methodology is proposed for quantifying the effects of epistemic uncertainty in soil parameters on NL SRA results. The methodology is validated using data from a well-instrumented geotechnical downhole array located in Japan, and the results of 46,200 NL finite element (FE) analyses are presented. The findings demonstrate that increasing the number of soft realizations and implementing higher levels of earthquake intensity leads to higher dispersion in ground motion. In contrast to previous studies, the proposed methodology has no significant effect on the predicted median surface response spectra and amplification factors for this case study. The findings of this part were published in the Earthquake Spectra in 2022. The second part aims to benchmark a three-dimensional (3D) Nonlinear (NL) SoilStructure Interaction (SSI) analysis methodology in the time-domain code LS-DYNA for a mid-rise well-instrumented building in Japan. The findings of this study indicate that the response of a structure is significantly influenced by the accuracy of the predicted free-field ground surface response, particularly at the structural fundamental period rather than the site period. Additionally, the results show that the responses of fixed-base and flexible-base structural models are significantly different, with the main contributing factor being SSI effects that cannot be accounted for in the fixed-base model. A discussion on the minimum amount of data needed to accurately capture nonlinear structural response using the proposed SSI methodology is also included in the study. The findings of this part were submitted to Soil Dynamics and Earthquake Engineering. The third part utilizes data from 14 well-instrumented downhole arrays in the United States and Japan to evaluate the reliability of the proposed methodology presented in part 1 to examine the individual and combined effects of uncertainties in soil parameters, such as the shear-wave velocity profile and shear strength, on NL SRA results for sites with different characteristics to provide some recommendations for design purposes. Results from 182,400 NL FE analyses are presented. The results of this study demonstrate that the applied methodology effectively quantifies the effects of soil parameter uncertainty on the response, without resulting in any undesired reductions in the predicted median surface response spectra, unlike some previous studies. Additionally, the results indicate that the impact of soil parameter uncertainty on the response strongly depends on the site conditions and the intensity of the seismic motion. The manuscript for this portion of the study is currently in preparation and will be submitted to a peer-reviewed journal in the near future.
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