نشریه علمی سازه و فولاد

نشریه علمی سازه و فولاد

برآورد خیز حداکثر حد الاستیک ورق دیوار برشی فولادی نیمه‌مقید در لبه‌ها با استفاده از الگوریتم‌های یادگیری ماشین و استخراج فرمول‌ تحلیلی

نوع مقاله : مقاله پژوهشی

نویسندگان
1 استادیار، گروه مهندسی عمران، مجتمع آموزش عالی تربت جام، تربت جام، ایران
2 استادیار، گروه مهندسی کامپیوتر، مجتمع آموزش عالی تربت جام، تربت جام، ایران
چکیده
زمینۀ پژوهش: دیوار برشی فولادی نیمه‌مقید در لبه‌ها (SSSW) به‌عنوان یک سیستم نوظهور برای تحمل بارهای جانبی در سازه‌ها به‌کار گرفته شده است. در این سیستم، ورق‌های دیوار به ستون‌های فرعی متصل بوده و تحت بارهای جانبی کوچک دچار کمانش می‌شوند. این کمانش موجب ایجاد خیز (تغییرشکل خارج از صفحه) در ورق می‌شود. به‌دلیل شروع کمانش ورق در بارهای جانبی کوچک، ناحیۀ وسیعی از ورق دارای رفتار پس‌کمانشی الاستیک است. یکی از روش‌های به‌دست‌آوردن خیز ورق‌ها، حل دستگاه معادلات فون‌کارمن است که در پژوهش‌های پیشین، خیز ورق دیوار در ناحیۀ پس‌کمانشی الاستیک از حل این معادلات با استفاده از روش گالرکین به‌دست آمده است. حل معادلات فون‎کارمن بسیار پیچیده بوده و تاکنون راه حل صریح برای آن ارائه نشده است. هدف این پژوهش، پیش‌بینی خیز حداکثر حد الاستیک ورق با استفاده از الگوریتم‌های یادگیری ماشین و ارائۀ یک فرمول صریح ریاضی است.
روش پژوهش: پنج الگوریتم یادگیری ماشین شامل رگرسیون خطی، رگرسیون چندجمله‌ای، جنگل تصادفی، تقویت گرادیان و XGBoost برای پیش‌بینی خیز حداکثر حد الاستیک ورق‌های دیوار برشی فولادی نیمه‌مقید در لبه‌ها ارزیابی و با هم مقایسه شدند. داده‌های مورد استفاده از نتایج حل معادلات فون‌کارمن به روش گالرکین استخراج شده‌اند.
یافته‌ها: در میان الگوریتم‌های بررسی‌شده، رگرسیون چندجمله‌ای بهترین تعادل را میان دقت و قابلیت تفسیر نشان داد. بر این اساس، یک فرمول ریاضی صریح برای تخمین خیز حداکثر حد الاستیک استخراج شد که میانگین خطای آن کم‌تر از دو درصد است.
نتیجه‌گیری: فرمول پیشنهادی این پژوهش به طراحان امکان می‌دهد بدون نیاز به حل معادلات پیچیده یا انجام مدل‌سازی‌های پرهزینه، خیز حداکثر حد الاستیک ورق دیوار برشی فولادی نیمه‌مقید را به‌سرعت و با دقت مناسب تخمین بزنند.
کلیدواژه‌ها
موضوعات

عنوان مقاله English

Estimation of the Maximum Deflection at the Elastic Limit of a Semi-Supported Steel Plate Shear Wall Using Machine Learning Algorithms and Derivation of an Analytical Formula

نویسندگان English

Seyed Ebrahim Sadat Kholerdi 1
Marieh Jahannia 2
1 Assistant professor, Department of Civil Engineering, University of Torbat-e Jam, Torbat-e Jam, Iran
2 Assistant Professor, Department of Computer Engineering, University of Torbat-e Jam, Torbat-e Jam, Iran
چکیده English

Background: The Semi-Supported Steel Plate Shear Wall (SSSW) is an emerging lateral load-resisting system in which wall plates connect to secondary columns rather than the main boundary frame. Under small lateral loads, these plates buckle and develop out-of-plane deflection. Since buckling initiates at low load levels, a large portion of the plate operates in the elastic post-buckling range. Calculating this deflection requires solving the Von-Kármán equations via the Galerkin method, a procedure that is mathematically complex and has no known closed-form solution. This study aims to predict the maximum elastic limit deflection of SSSW wall plates using machine learning algorithms and to derive an explicit mathematical formula for practical design use.
Methods: Five machine learning algorithms, Linear Regression, Polynomial Regression, Random Forest, Gradient Boosting and XGBoost were evaluated for predicting the maximum elastic limit deflection of SSSW wall plates.
Results: Among the algorithms evaluated, Polynomial Regression achieved the best balance between accuracy and interpretability. An explicit mathematical formula for estimating the maximum elastic limit deflection was derived, with a mean prediction error below 2%.
Conclusion: The proposed formula allows designers to estimate the maximum elastic limit deflection of SSSW wall plates quickly and reliably, without solving the Von-Kármán equations or performing costly numerical modeling.

کلیدواژه‌ها English

Semi-Supported
Steel Plate Shear Wall
Deflection
Elastic Limit
Machine Learning Algorithms
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  • تاریخ دریافت 03 اسفند 1404
  • تاریخ پذیرش 17 تیر 1405
  • تاریخ اولین انتشار 17 تیر 1405
  • تاریخ انتشار 01 فروردین 1405