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Pre-Earthquake Damage Assessment Using Artificial Intelligence Algorithms

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DESCRIPTION

Assessment and damage level evaluation for building inventories (minor, moderate, major, collapse) based on pre-earthquake collected data.

BUILDING AI

Step 1. Ground Motion Input

Ground Motion Input Parameters

Direction 1 - Acceleration Time History Record

Direction 2 - Acceleration Time History Record

Please upload direction 1 & direction 2 accelerogram files.

Direction 1 - Acceleration/Time Graph

Direction 1 - Acceleration/Time Graph

Direction 2 - Acceleration/Time Graph

Direction 2 - Acceleration/Time Graph

Seismic Properties

PGA = gPGV = cm/sPGD = cmPGV/PGA = sarms = g
vrms = cm/sdrms = cmIa = m/sIc = SED = cm2/s
CAV = cm/sASI = g*sVSI = cmHI = cmEPA = g
SMA = gPP = sTUD = sBRD = sSMD_TB = s

Response Spectrums

Response Spectrum
Response Spectrum
Response Spectrum

Step 2. ANN Structural Properties

Technical Data

Input Features

ANN Structure Image 1
ANN Structure Image 2
ANN Spectrums

Vulnerability Results

ANN Damage Classification Using Max- Interstorey Drift Ration (MIDR)

NULL-SLIGHT (0 ≤ MIDR < 0.5)
MODERATE (0.5 ≤ MIDR < 1.0)
NEAR COLLAPSE (MIDR ≥ 1.0)

Damage Level:

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