The Use of Poisson's Ratio and HVSR Analysis for Clustering Liquefaction Hazard Potential (Case Study: Mandalika Special Economic Zone Buffer Zone)
DOI:
https://doi.org/10.11113/mjfas.v21n4.4372Keywords:
Class potential, HVSR, liquefaction, buffer village of Mandalika, influential factorsAbstract
Liquefaction is a geotechnical phenomenon resulting from decreased strength and stability of water-saturated soil due to vibrations or dynamic loads caused by earthquakes. This phenomenon can potentially cause substantial damage to infrastructure and buildings and threaten the safety of humans. The area has never experienced liquefaction, but the Mandalika is a special economic zone (SEZ) that faces directly onto the earthquake source Megatrust of the Indian Ocean, which has the potential to cause an earthquake of 9.0 Mw. The surrounding villages, namely Kuta, Mertak, Sukadana, and Sengkol, support this area. The rapid development of this area as a tourism and infrastructure destination has resulted in the need to understand and mitigate the risk of liquefaction that could impact the safety and sustainability of development in the area. This study aims to cluster the liquefaction potential of the Madalika area and its surroundings based on Poisson's ratio data supported by the results of horizontal to vertical spectrum ratio (HVSR) analysis and groundwater depth data. Microseismic data were measured at around 60 points spread throughout the research area. Poisson's ratio was calculated from the primary and secondary wave velocities of ground profiling microseismic data and groundwater level data measured in dug wells owned by residents. The value of the Poisson's ratio in the study area is about 0.1 to 0.5. Observing high or low Poisson's ratio values can help determine the potential for liquefaction moments caused by vibration and estimate the level of liquefaction risk in the Mandalika area. Poisson's ratio data was supported with data on sediment thickness, about (4 – 129) meters, (1 – 5) meters of groundwater level, and (64 – 918) ms-1 of Vs-30 to determine class potential liquefaction. The ranking or class liquefaction is based on factors influencing a row occupied by Kuta Village, Sengkol Village, Sukadana Village, and Mertak Village.
References
Estriani, H. N. (2019). Prodi Ilmu Hubungan Internasional FISIP UPN “Veteran” Jakarta Kawasan Ekonomi Khusus (KEK) Mandalika dalam implementasi konsep pariwisata berbasis ecotourism: Peluang dan tantangan.
Maharani, Y. N., Septiadhi, A., & Algary, T. A. (2022). Pemetaan jalur evakuasi sebagai upaya pengurangan risiko bahaya tsunami di wilayah Kuta Mandalika, Provinsi Nusa Tenggara Barat, Indonesia.
Alaydrus, A. T., Susilo, A., Naba, A., & Minardi, S. (2021). Identification of the constraints of physical properties on fluid flow rate (as a preliminary study for analysis of changes in subsurface conditions in the KEK Mandalika Lombok). Journal of Physics: Conference Series, 1816(1), 012100. https://doi.org/10.1088/1742-6596/1816/1/012100
Alaydrus, A. T., Susilo, A., Naba, A., Minardi, S., & Azhari, A. P. (2024). Investigation of seawater intrusion in Mandalika, Lombok, Indonesia using time-lapse geoelectrical resistivity survey. International Journal of Design and Nature and Ecodynamics, 19(1), 1–11. https://doi.org/10.18280/ijdne.190101
Alaydrus, A. T., Susilo, A., Minardi, S., Naba, A., & Abraham, T. P. (2023). 3D inversion modelling of gravity and geomagnetic in the coastal aquifer of the Mandalika Lombok. IOP Conference Series: Earth and Environmental Science, 1175(1), 012018. https://doi.org/10.1088/1755-1315/1175/1/012018
Minardi, S., Ardianto, T., Alaydrus, A. T., Tawakal, M. I., & Martha, A. A. (2023). Investigation of sediment thickness beneath the Mandalika circuit and its surroundings based on microtremor data. International Journal of GEOMATE, 25(112), 40–47. https://doi.org/10.21660/2023.112.4108
Wafid, M., Sugianto, Tulus, P., & Sarwondo. (2014). Resume hasil kegiatan pemetaan geologi teknik Pulau Lombok skala 1:250.000.
Agustian, Y. (2021). Likuefaksi. Jurnal Ilmiah Teknologi Informasi Terapan, 8(1), 209–215. https://doi.org/10.33197/jitter.vol8.iss1.2021.749
Irsyam, M., et al. (2015). Development of seismic risk microzonation maps of Jakarta city. In Geotechnics for catastrophic flooding events (pp. 35–47). Taylor and Francis. https://doi.org/10.1201/b17438-6
Housner, G. W. (1985). Liquefaction of soils during earthquakes.
Musa Sjahrain, U., Rondonuwu, S. G., & Riogilang, H. (2021). Analisis potensi likuifaksi dengan menggunakan parameter kuat geser tanah lempung.
Deo, P., Prayitno, & Artati, H. K. (2021). Analisis potensi likuifaksi berdasarkan distribusi ukuran butir tanah dan data cone penetration test (CPT).
Seed, B. H., & Idriss, I. M. (1970). National Technical Information Service: A simplified procedure for evaluating soil liquefaction potential.
Day, R. W. (2002). Geotechnical earthquake engineering handbook. McGraw-Hill.
Dong, L., Xu, H., Fan, P., & Wu, Z. (2021). On the experimental determination of Poisson’s ratio for intact rocks and its variation as deformation develops. Advances in Civil Engineering, 2021, 8843056. https://doi.org/10.1155/2021/8843056
Narimani, S., Davarpanah, S. M., & Vásárhelyi, B. (2024). Estimation of the Poisson’s ratio of the rock mass. Budapest University of Technology and Economics. https://doi.org/10.3311/PPci.22689
Raharjo, W., Palupi, I. R., Nurdian, S. W., Giamboro, W. S., & Soesilo, J. (2016). Poisson’s ratio analysis (Vp/Vs) on volcanoes and geothermal potential areas in Central Java using tomography travel time method of grid search relocation hypocenter. Journal of Physics: Conference Series, 776(1), 012114. https://doi.org/10.1088/1742-6596/776/1/012114
Wang, Q., & Ji, S. (2009). Poisson’s ratios of crystalline rocks as a function of hydrostatic confining pressure. Journal of Geophysical Research: Solid Earth, 114(9). https://doi.org/10.1029/2008JB006167
Arns, C. H., Knackstedt, M. A., & Pinczewski, W. V. (2002). Accurate Vp:Vs relationship for dry consolidated sandstones. Geophysical Research Letters, 29(8). https://doi.org/10.1029/2001GL013788
Lógó, B. A., & Vásárhelyi, B. (2020). Parametric study on the connection between Poisson’s Ratio, GSI and environmental stress. Computer Assisted Methods in Engineering and Science, 27(2–3), 205–217. https://doi.org/10.24423/cames.287
Garia, S., Pal, A. K., Nair, A. M., & Ravi, K. (2020). Elastic wave velocities as indicators of lithology-based geomechanical behaviour of sedimentary rocks: An overview. Springer Nature. https://doi.org/10.1007/s42452-020-03300-1
Bukowska, M., Kasza, P., Moska, R., & Jureczka, J. (2022). The Young’s modulus and Poisson’s ratio of hard coals in laboratory tests. Energies, 15(7). https://doi.org/10.3390/en15072477
Essien, U. E., Akankpo, A. O., & Igboekwe, M. U. (2014). Poisson’s ratio of surface soils and shallow sediments determined from seismic compressional and shear wave velocities. International Journal of Geosciences, 5(12), 1540–1546. https://doi.org/10.4236/ijg.2014.512125
Zhang, J. J., & Bentley, L. R. (2005). Factors determining Poisson’s ratio.
Poulos, H. G. (2021). Use of shear wave velocity for foundation design. https://doi.org/10.21203/rs.3.rs-493427/v1
Yan, K., Wang, Y., Lai, X., Wang, Y., & Yang, Z. (2023). Experimental study on Poisson’s ratio of silty-fine sand with saturation. Journal of Marine Science and Engineering, 11(2). https://doi.org/10.3390/jmse11020427
Bowles, J. E. (1997). Foundation analysis and design. Irwin/McGraw-Hill.
Mandasari, S., Asrillah, & Rusydy, I. (2017). Studi likuifaksi menggunakan nilai Poisson’s ratio di Kecamatan Meurah Dua, Pidie Jaya.
Gorstein, M., & Ezersky, M. (2015). Combination of HVSR and MASW methods to obtain shear wave velocity model of subsurface in Israel. International Journal of Geohazard and Environment, 20–41.
Mirzaoglu, M., & Dýkmen, Ü. (2003). Application of microtremors to seismic microzoning procedure.
Moustafa, S. S. R., Mohamed, A., Abdelhafiez, H. E., El-Faragawy, K., & Ali, S. (2023). A fusion approach for evaluating ground conditions for seismic microzoning at the Egyptian Solar Park in Benban, Aswan. Environmental Earth Sciences, 82(12). https://doi.org/10.1007/s12665-023-10968-2
Nakamura, Y. (1989). Clear identification of fundamental idea of Nakamura’s technique and its applications. https://www.researchgate.net/publication/228603691
Hamimu, L. H., Juarzan, L. I., & Pathiasari, N. I. (2023). Analisis ketebalan lapisan sedimen menggunakan metode horizontal to vertical spectral ratio (HVSR) di daerah perbukitan Kecamatan Moramo. Jurnal Rekayasa Geofisika Indonesia, 6(01), 1–15. https://doi.org/10.56099/jrgi.v6i01.29
Nakamura, Y. (2008). On the H/V spectrum.
Sambridge, M. (1999). Geophysical inversion with a neighbourhood algorithm – I. Searching a parameter space. Geophysical Journal International, 138(2), 479–494. https://doi.org/10.1046/j.1365-246X.1999.00876.x
Sunardi, B., Susilanto, P., & Putri, E. N. (2017). Penerapan metode inversi HVSR untuk pencitraan 3-D kecepatan gelombang geser (Vs) di Kulon Progo bagian selatan. Jurnal Riset Geofisika Indonesia, 1(2), 53–59. https://www.researchgate.net/publication/322695502
Badan Standardisasi Nasional. (2012). Tata cara perencanaan ketahanan gempa untuk struktur bangunan gedung dan non gedung. www.bsn.go.id
Tian, B., Du, Y., You, Z., & Zhang, R. (2019). Measuring the sediment thickness in urban areas using revised H/V spectral ratio method. Engineering Geology, 260. https://doi.org/10.1016/j.enggeo.2019.105223
Semesta. (2024). SRI seismometer technical specification.
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