Building Nonstructural Damage

Building Nonstructural Damage#

Description

This analysis computes the non-structural damage to buildings based on a particular hazard. Currently, supported hazard is: earthquake, flood, and hurricane.

The process is similar to evaluating other structural damages. The probabilities for building damage state are obtained using fragility curves and a hazard definition, each building site will have a specific PGA (Peak Ground Acceleration), a measurement of an earthquake hazard for each scenario. Liquefaction effect, which is defined as a change in stress condition, in which material that is ordinarily a solid behaves like a liquid can be considered as well. The LMF (Liquefaction Modification Factor) values are implemented as multiplication factors to the median fragility values and they must be present in the dataset. This analysis can support various types of fragility curves assigned to the building: e.g.acceleration-sensitive (AS) and drift-sensitive (DS).

The code covers Normal and LogNormal fragilities with 3 limit states and creates an output CSV file with corresponding damage states. The second output file is a JSON with information about hazard and fragilities.

Input Parameters

key name	type	name	description
`result_name` ^*	`str`	Result name	Name of the result dataset.
`hazard_type`	`str`	Hazard type	Hazard type (earthquake, flood, hurricane).
`hazard_id`	`str`	Hazard id	ID of the hazard from the Hazard service.
`fragility_key`	`str`	Fragility Key	Fragility key used in mapping dataset.
`use_liquefation`	`bool`	Liquefaction	Use liquefaction, if applicable to the hazard. Default False.
`liq_geology_dataset_id`	`str`	Liquefaction id	A liquefaction susceptibility dataset.
`use_hazard_uncertainty`	`bool`	Uncertainty	Use hazard uncertainty. Default is False.
`num_cpu`	`int`	Number of CPUs	Number of CPUs used for parallel computations. Default 1.

Input Hazards

key name	type	name	description
`hazard`	`earthquake` `flood` `hurricane`	Hazard	Supported hazard object for using local and remote hazards.

Input Datasets

key name	type	name	description
`buildings` ^*	`ergo:buildingInventoryVer4` `ergo:buildingInventoryVer5` `ergo:buildingInventoryVer6` `ergo:buildingInventoryVer7`	Building dataset	A building dataset.
`dfr3_mapping_set` ^*	`incore:dfr3MappingSet`	DFR3 Mapping Set	DFR3 Mapping Set.

Output datasets

key name	type	parent key	name	description
`result` ^*	`ergo:nsBuildingInventoryDamageVer4`	`buildings`	Results	A dataset containing results (format: CSV).
`damage_result` ^*	`incore:nsBuildingInventoryDamageSupplement`	`buildings`	Results	Information about applied hazard value and fragility (format: JSON).

(* required)

Execution

code snippet:

    # Create an instance
    non_structural_building_dmg = NonStructBuildingDamage(client)

    # Load input datasets
    non_structural_building_dmg.load_remote_input_dataset("buildings", building_dataset_id)

    # Load fragility mapping
    fragility_service = FragilityService(client)
    mapping_set = MappingSet(fragility_service.get_mapping(mapping_id))
    non_structural_building_dmg.set_input_dataset('dfr3_mapping_set', mapping_set)

    # Specify the result name
    result_name = "non_structural_building_dmg_result"

    # Set analysis parameters
    non_structural_building_dmg.set_parameter("result_name", result_name)
    non_structural_building_dmg.set_parameter("hazard_type", hazard_type)
    non_structural_building_dmg.set_parameter("hazard_id", hazard_id)
    non_structural_building_dmg.set_parameter("fragility_key", NonStructBuildingUtil.DEFAULT_FRAGILITY_KEY_AS)
    non_structural_building_dmg.set_parameter("num_cpu", 4)

    # Shelby County Liquefaction Susceptibility
    use_liquefaction = True
    liq_geology_dataset_id = "5a284f55c7d30d13bc0824ba"

    non_structural_building_dmg.set_parameter("use_liquefaction", use_liquefaction)
    non_structural_building_dmg.set_parameter("liq_geology_dataset_id", liq_geology_dataset_id)

    non_structural_building_dmg.run_analysis()

full analysis: building_nonstructural_dmg.ipynb