CD Skripsi
Analisis Potensi Likuifaksi Berdasarkan Data Cpt Dengan Metode Simulasi Monte Carlo
Liquefaction potential analysis is one of the challenges in the geotechnical field. Generally, liquefaction potential analysis is carried out using deterministic methods because the calculations are relatively simple and fast. However, the uncertainty of soil parameters and earthquake parameters means that analysis of liquefaction potential is more suitable to be carried out using probabilistic methods. In this research, analysis of liquefaction potential was carried out at 2 study locations, namely, in "Padang Utara" due to the 2009 Padang Earthquake and Universitas Riau, carried out using a probabilistic method, namely the Monte Carlo simulation method. At the Universitas Riau study location, the stochastic variables chosen were earthquake magnitude (Mw), Peak Ground Acceleration (PGA), total vertical soil stress (σv), Ground Water Level (GWL), Sleeve Friction (fs) and Cone Resistance (qc). The analysis results show that the Probability of Liquefaction (PL) value is dominant in the range of 15-35%, and also the Probability of Liquefaction (PL) value is relatively stable when the number of iterations ranges from 300,000-600,000. Meanwhile, at the "Padang Utara" study location, the stochastic variables chosen were Peak Ground Acceleration (PGA), Ground Water Level (GWL), Sleeve Friction (fs) and Cone Resistance (qc). The analysis results show that the Probability of Liquefaction (PL) value is dominant in the range of 85-100%. This result is in accordance with the reality/field observations when the Padang earthquake occurred in 2009 with a magnitude of 7.9 Mw. The Probability of Liquefaction (PL) value is relatively stable when the number of iterations ranges from 60,000-80,000. Based on the results of the sensitivity analysis, it was found that the stochastic variable that had the most influence on the fluctuation of the value of the safety factor regarding liquefaction events at the two study locations was Cone Resistance (qc).
Keywords: Uncertainty Factor, Liquefaction, Probability of Liquefaction (PL), Monte Carlo Simulation.
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