ارزیابی پتانسیل وقوع روانگرایی برمبنای ارائه یک مدل احتمالاتی و انجام تحلیل‌های قابلیت‌اعتماد همراه با بررسی اهمیت نسبی عدم قطعیت پارامترهای مدل

نوع مقاله : علمی - پژوهشی

نویسندگان

1 استادیار دانشگاه رازی

2 دانشجوی کارشناسی ارشدمهندسی عمران_ژئوتکنیک، گروه مهندسی عمران، دانشگاه رازی، کرمانشاه، ایران

چکیده

بررسی پتانسیل روانگرایی خاک نقش مهمی در کاهش خسارات زمین‌لرزه‌ها دارد که به‎دلیل پیچیدگی ماهیت خاک و زلزله امری دشوار است. مطالعات پیشین متفاوتی برای بررسی این پدیده انجام شده، اما این روش‌ها عمدتا به‎دلیل نادقیق بودن مدل‌سازی، درنظر نگرفتن عدم‌قطعیت‌های ناشی از پیچیدگی‌های خاک و زلزله، و یا استفاده از پایگاه داده‌های ناکافی با خطاهای زیادی روبرو هستند. در این مطالعه از روش استنباط بیژین به‌عنوان یک روش مدل‌سازی احتمالاتی با قابلیت به‌روز شدن و درنظرگرفتن عدم‌قطعیت‌ پارامترهای مقاومتی و دینامیکی، با استفاده از یک پایگاه داده جامع از مشاهدات آزمایش نفوذ استاندارد مهمترین رخدادهای روانگرایی دنیا، برای توسعه تابع حالت حدی و ضریب‌اطمینان روانگرایی استفاده شد. برای نخستین‌بار با استفاده از روش قابلیت‌اعتماد مرتبه اول و مونت‌کارلو از روش نمونه‌گیری اهمیت و پیشینه‌نما در برآورد احتمال شکست و شاخص قابلیت‌اعتماد تابع‌حالت‌حدی روانگرایی خاک‌ها استفاده شد، سپس با کمک روش قابلیت‌اعتماد نمونه‌گیری پیشینه‌نما تابع چگالی احتمال (PDF) و تابع تجمعی احتمال (CDF) برای بررسی احتمال فراگذشت از مقادیر مورد نظر بدست آمد. آنالیزحساسیت مدل نیز برای برآورد اثرگذارترین عدم‌قطعیت صورت گرفت. درنتیجه‌ی این مطالعه، یک مدل احتمالاتی قدرتمند و کارا برای ارزیابی پتانسیل روانگرایی خاک‌ها توسعه داده شد. مقایسه نتایج حاصل از این مدل احتمالاتی با مدل‌های متعین و احتمالاتی متداول دیگر، کاهش قابل توجه در عدم قطعیت و انحراف معیار مدل، افزایش دقت، پیش‌بینی بهینه و درک کامل‌تری از رابطه‌ی بین احتمال شکست و ضریب اطمینان روانگرایی را نشان داد. روش‌های نمونه‌گیری مونت کارلو، نمونه‌گیری پیشینه‌نما و نمونه‌گیری‌اهمیت نیزتطابق بسیار خوبی در نتایج داشتند. در آنالیز حساسیت مدل پیشنهادی، عدم‌قطعیت پارامتر بزرگای زلزله به‌عنوان مهمترین عدم‌قطعیت مدل مشخص شد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Assessment of Liquefaction Potential Based on a Probabilistic Model and Performing Reliability Analysis with Evaluation the Relative Importance of Model Parameters Uncertainty

نویسندگان [English]

  • hassan sharafi 1
  • Seyedeh Faezeh Hassanzadeh 2
1 Assistant Professor of Civil Engineering, Faculty of Engineering, Razi University of Kermanshah, Iran
2 M.Sc. Student of Geotechnical Engineering, Department of Civil Engineering, Faculty of Engineering, Razi University, Kermanshah, Iran
چکیده [English]

Investigating the potential of soil liquefaction plays an important role in reducing earthquake damages. Prediction of this phenomenon is difficult due to the complexity of the nature of soil and earthquakes. Previous studies had many errors that include inaccurate modeling, inadequate databases and disregarding the uncertainties that are caused by soil and earthquake complexity. In this research Bayesian inference method is used as a probabilistic modeling method. This method used a comprehensive database of standard penetration test (SPT). For the first time, first-order reliability method (FORM) and importance sampling method were used to estimate the probability of failure and the reliability index of the limit state function of liquefaction. Then with the help histogram sampling, probability density function (PDF) and cumulative probability function (CDF) were obtained to investigate the probability of transgression. A sensitivity analysis of the model was also performed to estimate the most effective parameters. As a result of this study, a robust and efficient probabilistic model was developed to evaluate the liquefaction potential of soils. Comparing the results of this probabilistic model with other deterministic and probabilistic models showed a significant reduction in model uncertainty and standard deviation, increased accuracy and a better understanding of the relationship between failure probability and safety factor of liquefaction. Monte Carlo sampling and importance sampling methods were closed to each other. In the sensitivity analysis of the proposed model, the uncertainty of the magnitude of the earthquake parameter was identified as the most important uncertainty of the model.

کلیدواژه‌ها [English]

  • Liquefaction potential
  • Standard penetration test
  • Bayesian inference
  • Histogram sampling
  • Importance sampling
  • Sensitivity analysis
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