ظرفیت برشی تیرهای لاغر بتن آرمه با بتن مقاومت بالا و بدون خاموت

نوع مقاله : مقاله پژوهشی

نویسندگان

1 استادیار، دانشکده فنی و مهندسی، دانشگاه آیت ا... بروجردی، بروجرد، ایران

2 استادیار، دانشکده فنی و مهندسی، دانشگاه دامغان، دامغان، ایران

چکیده

در این مطالعه مدلی جدید برای پیش بینی مقاومت برشی تیرهای لاغر بتن آرمه با بتن مقاومت بالا و بدون آرماتور عرضی با استفاده از ترکیب سیستم استنتاج تطبیقی فازی-عصبی و الگوریتم بهینه سازی ازدحام ذرات بر اساس تعداد قابل توجهی نمونه آزمایشگاهی ارائه شده است. پارامترهای موثر در مدل ارائه شده شامل: عمق موثر تیر، مقاومت فشاری بتن، درصد آرماتور طولی، نسبت دهانه برشی بـه ارتفـاع موثر و بزرگ‌ترین بعد سنگ‌دانه مصرفی در بتن می‌باشند. نتایج آزمایشگاهی مورد استفاده در این مطالعه به صورت تصادفی به دو بخش تقسیم شده که بخش اول برای فرآیند آموزش و مابقی برای ارزیابی صحت عملکرد مدل استفاده شده است. پس از ایجاد مدل، آنالیز حساسیت برای بررسی سهم پارامترهای موثر و به صورت تعیین حساسیت خروجی سیستم با توجه به تغییرات دو پارامتر ورودی انجام گرفته است. برای کنترل بیشتر دقت مدل پیشنهادی، نتایج آن با آئین نامه های ACI 318-14، Eurocode-2، CEB-FIP Model Code، AS 3600-2009 و JSCE Guidelines به صورت گرافیکی و همچنین با استفاده از شاخص‌های آماری R2، RMSE و MAPE مقایسه شده است. نتایج نشان داده که مدل ارائه شده در محدوده پایگاه داده ایجاد شده، دقت بیشتری از مدل‌های موجود در آئین نامه‌ها داشته و می‌تواند به عنوان ابزاری مناسب در تخمین ظرفیت برشی تیرهای لاغر مورد استفاده قرار گیرد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Shear Capacity of High-Strength Concrete Slender Beams without Transverse Reinforcement

نویسندگان [English]

  • Masoud Ahmadi 1
  • Mehdi Ebadi Jamkhaneh 2
1 Department of Civil Engineering, Ayatollah Boroujerdi University, Boroujerd, Iran.
2 Department of Civil Engineering, Damghan University, Damghan, Iran
چکیده [English]

In the present study, a new model is derived to estimate the shear capacity of high-strength concrete slender beams without transverse reinforcement using a hybrid adaptive neuro-fuzzy inference system (ANFIS) and particle swarm optimization (PSO) based on the wide range of experimental results. The proposed model relates the shear capacity of the beam to effective depth, the compressive strength of concrete, percent of longitudinal reinforcement, the ratio of shear span to effective depth, and the nominal maximum size of coarse aggregate. The experimental data are randomly categorized into two subsets of the training set and test set. After establishing the proposed model, a sensitivity analysis was carried out to assess the validity of the proposed ANFIS-PSO model. For this purpose, the results of the proposed model are calculated by considering the variation of the two selected input parameters, whereas the values of other parameters are fixed at the corresponding median values. To check the reliability of the proposed model more accurately, the predicted values are compared with the codes and standards such as ACI 318-14, Eurocode-2, CEB-FIP Model Code, AS 3600-2009, and JSCE Guidelines against the whole experimental specimens based on the three well-known statistical measures; correlation coefficient (R2), root mean squared error (RMSE), and mean absolute percentage error (MAPE). It can be found that the proposed ANFIS-PSO model passed desired conditions and could estimate the shear capacity of the high-strength concrete slender beams without transverse reinforcement with a good degree of accuracy.

کلیدواژه‌ها [English]

  • Slender beam
  • Shear Capacity
  • High-strength concrete
  • Adaptive neuro-fuzzy
  • Particle Swarm Optimization
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