Rapid Estimation of Vs30 Through Elitist Genetic Algorithm HVSR Inversion and Refraction Microtremor Data Analysis in the Greater Metro Manila Area and Leyte Province, Philippines
Vs30, the average shear wave velocity in the uppermost 30 m, is a critical parameter in seismic hazard analysis. In the Philippines, the Refraction Microtremor (ReMi) survey is the standard method for Vs30 Estimation. This study evaluates the efficiency of using an elitist Genetic Algorithm (GA) to...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-02-01
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| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/15/5/2447 |
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| Summary: | Vs30, the average shear wave velocity in the uppermost 30 m, is a critical parameter in seismic hazard analysis. In the Philippines, the Refraction Microtremor (ReMi) survey is the standard method for Vs30 Estimation. This study evaluates the efficiency of using an elitist Genetic Algorithm (GA) to invert Horizontal-to-Vertical Spectral Ratio (HVSR) data as an alternative approach. Unlike ReMi surveys, which require geophone arrays, HVSR surveys use a single-unit three-component microtremor seismograph, enabling faster and broader data collection. Analysis of 174 HVSR and 52 ReMi datasets from the Greater Metro Manila Area (GMMA) and Leyte Province revealed strong correlations between estimated and measured Vs30 values. The overall match rates for soil profile classification under the National Structural Code of the Philippines (NSCP 2015) were 76% in GMMA and 81% in Leyte, with R-squared values of 0.885 and 0.806, respectively. Additionally, the relationship between the fundamental site period and estimated Vs30 values was explored. The R-squared values of 0.772 for GMMA and 0.707 for Leyte indicate a strong correlation and demonstrate the expected inverse relationship between the two variables. Given the Philippines’ high seismic activity, this method provides an efficient means to enhance seismic hazard mapping, improving earthquake preparedness and mitigation. |
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| ISSN: | 2076-3417 |