Generation of capacity curves using DBELA

This notebook enables the user to generate capacity curves (in terms of spectral acceleration vs. spectral displacement) using the Displacement-based Earthquake Loss Assessment (DBELA) approach. The DBELA methodology permits the calculation of the displacement capacity of a collection of structures at a number of limit states (which could be structural or non-structural). These displacements are derived based on the capacity of an equivalent SDOF structure, following the principles of structural mechanics (Crowley et al., 2004; Bal et al., 2010; Silva et al., 2013). The figure below illustrates various capacity curves generated using this approach.

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from rmtk.vulnerability.model_generator.DBELA_approach import DBELA
from rmtk.vulnerability.common import utils
%matplotlib inline

Load geometric and material properties

In order to use this methodology it is necessary to define a building model, which specifies the probabilistic distribution of the geometrical and material properties. These models need to be defined according to the format described in the RMTK manual. Please specify below the paths for the input files containing the building model and damage model:



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building_model_file = "../../../../../rmtk_data/DBELA/bare_frames.csv"
damage_model_file = "../../../../../rmtk_data/DBELA/damage_model_dbela_low_code.csv"

Number of samples

The parameter no_assets below controls the number of synthetic structural models or assets (each one with unique geometrical and material properties) that will be generated using a Monte Carlo sampling process:



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no_assets = 100

Generate the capacity curves



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building_class_model = DBELA.read_building_class_model(building_model_file)
assets = DBELA.generate_assets(building_class_model, no_assets)
damage_model = utils.read_damage_model(damage_model_file)
capacity_curves = DBELA.generate_capacity_curves(assets, damage_model)

Plot the capacity curves



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utils.plot_capacity_curves(capacity_curves)

Include additional information

Additional information can be added to the capacity curves generated using the above method. For instance, by setting appropriate values for the parameters gamma and yielding_point_index in the cell below, the add_information function can be used to include this data in the previously generated capacity curves.



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gamma = 1.2
yielding_point_index = 1.0



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capacity_curves = utils.add_information(capacity_curves, "gamma", "value", gamma)
capacity_curves = utils.add_information(capacity_curves, "yielding point", "point", yielding_point_index)

Save capacity curves

Please specify below the path for the output file to save the capacity curves:



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output_file = "../../../../../rmtk_data/capacity_curves_dbela.csv"



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utils.save_SdSa_capacity_curves(capacity_curves, output_file)