پیش بینی شکنندگی سنگ با استفاده از ویژگی های ژئومکانیکی سنگ آهک همه کسی: آنالیز رگرسیون و شبکه عصبی مصنوعی

نوع مقاله : مقاله پژوهشی

نویسنده

دانشگاه بوعلی سینا

چکیده

آب و هوای سرد، پارامتر مناسبی برای توسعه ترک های کششی و کاهش شکنندگی سنگ است. بنابراین در این مقاله سعی بر بررسی سنگ آهک های متخلخل همه کسی و پیش بینی شکنندگی آنها در طی چرخه های انجماد و ذوب شدن شده است. هر چرخه از آزمایش انجماد و ذوب شدن شامل 16 ساعت انجماد و 8 ساعت ذوب شدن است. ویژگی های ژئومکانیکی و شاخص های شکنندگی (B1, B2, B3)  سنگ آهک ها در طی چرخه های انجماد و آب شدن از چرخه (سنگ غیر هوازده) تا چرخه 40 اندازه گیری شده اند. آنالیز آماری شامل رگرسیون ساده و چندمتغیره به منظور شناسایی پارامترهای ژئومکانیکی که نسبت به سایر پارامترها تحت تاثیر پیشرفت چرخه های انجماد و ذوب شدن قرار گرفته و برای پیش بینی شکنندگی مناسبتر هستند، بکار رفته اند. از دیدگاه آنالیز رگرسیون ساده، تمامی پارامترهای ژئومکانیکی شامل مقاومت کششی، مقاومت فشاری تک محوری، سرعت موج p، تخلخل و جذب آب (به استثنای دانسیته خشک) ارتباط خوبی با شاخص شکنندگی نشان داده اند. در این تحقیق؛ پیش بینی یکپارچه شکنندگی به منظور توسعه مدل های چند متغیره (MR) و شبکه عصبی مصنوعی (ANN) با تعدادی پارامتر آماری (R ،  RMSE، VAF و ME) و بر اساس خصوصیات ژئومکانیکی بررسی شده است. بر طبق آماره های بدست آمده، مدل­هایی که بر اساس n، Vp و  می باشند کارایی بیشتری نشان می دهند. علیرغم این حقیقت که Vp در رگرسیون ساده ضریب انطباق خوبی با چرخه های انجماد و آب شدن و B3  (R= 0.74  و R= 0.55) دارد، اما اثر آشکاری بر B3 در مدل های MR ندارد. همچنین پارامترهایی با ضریب تعیین کم در رگرسیون ساده (=0.15) نمی توانند سبب بهبود مدل ها در رگرسیون چند متغیره شوند

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