tcra.vulnerability package

Submodules

tcra.vulnerability.Vulnearbility module

The tcra vulnerability module contains function to estimate damage states to buildings/structures through stochastic simulation.

class FragilityAnalysis[source]

Bases: object

This is FragilityAnalysis class. This class estimates probabilities of various damage states and assign damage states.

Parameters:

  • fragility_curves – fragility curves defined for building structural archetypes

  • mu – median value of lognormal distribution

  • sigma – standard deviation of lognormal distribution

Returns:

damage state

Return type:

damage_state

__init__(fragility_curves)[source]
estimate_damage(building_data)[source]

Estimate damage probabilities for all buildings.

Parameters:

  • building_data – building inventory

  • mph – wind speed

  • type – structural archetype defined in HAZUS

  • mu – median value of lognormal distribution

  • sigma – standard deviation of lognormal distribution

  • id – ids

  • x – longitude

  • y – latitude

  • Occupancy – building occupancy type

Returns:

dataframe inventory with probability of failure

Return type:

pd.DataFrame

estimate_epn_damage_state(epn_data)[source]

Estimate damage probabilities for all electrical poles. :param epn_data: electrical system inventory :param mph: wind speed :param type: structural archetype defined in HAZUS :param mu: median value of lognormal distribution :param sigma: standard deviation of lognormal distribution :param id: ids :param x: longitude :param y: latitude :param Occupancy: building occupancy type

Returns:

dataframe inventory with probability of failure

Return type:

pd.DataFrame

generate_fragility_curve(mu, sigma, intensity)[source]

Generate the fragility curve using log-normal distribution.

Parameters:

  • fragility_curves – fragility curves defined for building structural archetypes

  • mu – median value of lognormal distribution

  • sigma – standard deviation of lognormal distribution

Returns:

lognormal cumulative distribution function

Return type:

lognorm.cdf

sample_damage_state(Pr, DStates, seed=None)[source]

Generate damage states.

Parameters:

  • Pr – building invetory with damage state probabilities

  • DStates – damage states

Returns:

damage state

Return type:

damage_state

tcra.vulnerability.Fragility module

rehab_fragility_curves(rr)[source]

Revise fragility curves based on rehab option

Parameters:

rr – % of rehab or performance improve by rehabilitation

type_R :

Building xxxx_R represents that building type is rehabbed

Returns:

fragility

Return type:

functionality functions

tcra.vulnerability.DR module

damage_ratio(data)[source]

This function estimates damage ratio based on assigned damage states.

Parameters:

  • data – building inventory with damage state

  • Occupancy – building occupancy class as per HAZUS class

  • dmg – damage state

Returns:

DRatio

Return type:

damage ratio in terms of total building percetage to be repaired

Module contents