The multiple stripe analysis (MSA) (Jalayer, 2003) is one state-of-the-art method to conduct site-specific seismic performance assessments that is recommended by FEMA P-58 (FEMA, 2012). As illustrated in the Figure below, engineers first build the structural model and obtain the fundamental period T1, then select different ground motion suites for different intensity levels to match the correponding earthquake scenarios (e.g., Goulet et al., 2007) or conditional intensity measure targets (e.g., Bradley, 2010; Chandramohan et al., 2016). For different sites, the ground motion selection and structural analysis need to be repeated. When being applied to the regional assessment, the MSA can be time-consuming due to re-selecting records and re-analyzing structures. Similarly, the MSA is not flexible for dealing with the time-dependent seismic events (e.g., aftershocks and induced earthquakes).
The incremental dynamic analysis (IDA) (Vamvatsikos and Cornell, 2002) is another method commonly used to assess structural performances. In the IDA, one typically only need analyze the structure using a generic ground motion suite (e.g., FEMA, 2009). The advantage is the IDA does not require users to conduct site-specific hazard analysis or to select ground motion records. But, one major limitation is the results only reflect the ground motion characteristics of the used record suite but not the hazard of any unique site. Preceeding with pioneer studies (e.g., FEMA, 2009; Lin and Baker, 2013, Chandramohan, 2016), the Site-specific Adjustment Framework for Incremental Dynamic Analysis (SAF-IDA) is developed for efficiently using IDA data to estimate site-specific structural performance, e.g., esitmating probabilistic distributions of engineering demand parameters (EDP), evalutating fragilities of damage measures (DM), and assessing collapse risks.
As indicated in the right branch of the figure above, the SHAF-IDA has extra pre- and post-processing modules for the IDA, namely Nested Ground Motion Set and Hazard-Consistent Adjustment. The figure below lists their flowcharts. Please find more details and examples in the two packages: pyngms and pyhca.