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توسعه مدل ابتکاری هوشمند جهت تخمین خواص مقاومتی مخلوط بیوکامپوزیت کنف با استفاده از ترکیب الگوریتم چرخه آب و روش مارس | ||
| نشریه مهندسی عمران امیرکبیر | ||
| مقاله 4، دوره 56، شماره 12، 1403، صفحه 1557-1582 اصل مقاله (1.86 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22060/ceej.2024.22940.8080 | ||
| نویسندگان | ||
| داود صداقت شایگان* ؛ الهه فضلی خانی؛ علی اصغر امیرکاردوست | ||
| دانشکده فنی و مهندسی، دانشگاه آزاداسلامی واحدرودهن، رودهن، ایران | ||
| چکیده | ||
| با توجه به ویژگی بتن معمولی که یک ماده مرکب با ویژگی‌‌هایی همچون مقاومت و محدوده کرنش کششی پایین است. در اصل دو ضعف اصلی بتن که دربرگیرنده رفتار ترد بتن و ضعف در کشش آن می‌‌باشد، استفاده از سازه‌‌های بتن که از بتن معمولی ساخته شده اند را با مشکلاتی عمده‌‌ای رو‌‌به‌‌رو کرده است. به طور کلی با افزودن الیاف به مخلوط بتن این امکان وجود داشته که بتوان ویژگی مکانیکی بتن را بهتر کرد. در این تحقیق، از رویکرد فرا ابتکاری با استفاده از الگوریتم چرخه آب جهت ترکیب با روش اسپلاین رگرسیونی چند متغیره تطبیقی (مارس) برای مدل‌‌سازی و پیش‌‌بینی مقاومت فشاری و مقاومت کششی بتن حاوی بیوکامپوزیت‌‌های کنف استفاده شده است. برای توسعه هر یک از مدل‌‌های پیشنهادی، 153 طرح اختلاط به همراه نتایج مقاومت فشاری آنها از مقالات معتبر جمع‌‌آوری شد. بعد از تحلیل و ارزیابی پارامترهای اثر گذار توسط ضریب مالو، پارامترهای ورودی به مدل‌‌های هوشمند شامل نسبت آب به مواد پایه سیمانی، نسبت دانه‌‌های کنف به مواد پایه سیمانی، درصد وزن دانه‌‌های کنف ، مواد پایه سیمانی، دانه‌‌های کنف، چگالی مواد پایه سیمانی، چگالی مصالح خشک و مقاومت مواد پایه سیمانی انتخاب شدند. نتایج نشان داد که ضریب همبستگی برای مدل مقاومت فشاری برای مارس بهینه شده با الگوریتم و مارس به ترتیب 0/991و 0/971 و مقاومت کششی به ترتیب 0/928 و 0/911 در مرحله آموزش و آزمایش می‌‌باشد. بررسی‌‌ها نشان می‌‌دهند که مدل پیشنهادی مارس بهینه شده با الگوریتم فرا ابتکاری از عملکرد خوب و دقت بالایی در برای تخمین مقاومت فشاری و مقاومت کششی بتن حاوی بیوکامپوزیت کنف داشته است. نتایج اعتبارسنجی خارجی نیز نشان‌‌گر آن است که رویکرد پیشنهادی می‌‌توانند به عنوان مدل‌‌های پیش‌‌بینی‌‌کننده معرفی گردند و همبستگی میان مقادیر پیش‌‌بینی‌‌شده و مقادیر آزمایشگاهی نمی‌‌تواند تصادفی باشد. | ||
| کلیدواژه‌ها | ||
| بیوکامپوزیت کنف؛ الیاف طبیعی؛ هوش مصنوعی؛ روش مارس؛ الگوریتم چرخه آب | ||
| موضوعات | ||
| تکنولوژی بتن؛ شبکه های عصبی؛ مصالح نوین جهت اصلاح خواص بتن | ||
| عنوان مقاله [English] | ||
| Development of innovative intelligent model to estimate the strength properties of hemp bio composite mixture using the combination of water cycle algorithm and MARS method | ||
| نویسندگان [English] | ||
| Davood Sedaghat Shayegan؛ Elahe Fazlikhani؛ َAli asghar Amirkardoust | ||
| Department of civil engineering, Roudehen Branch, Islamic Azad University, Tehran, Iran | ||
| چکیده [English] | ||
| Considering the characteristics of ordinary concrete, which is a composite material with characteristics such as resistance and low tensile strain range. Basically, the two main weaknesses of concrete, which include the brittle behavior of concrete and the weakness in its elasticity, have made the use of concrete structures made of ordinary concrete face major problems. In general, by adding fibers to the concrete mixture, it is possible to improve the mechanical properties of concrete. In this research, an innovative approach using the water cycle algorithm was used to combine with the adaptive multivariate regression spline method (MARS) to model and predict the compressive strength and tensile strength of concrete containing hemp biocomposites. For the development of each of the proposed models, 153 mixing designs along with their compressive strength results were collected from authoritative articles. After analyzing and evaluating the influencing parameters by the Mallow coefficient, the input parameters to the smart models include the ratio of water to cement base materials, the ratio of hemp seeds to cement base materials, the weight percentage of hemp seeds, cement base materials, seeds hemp, density of cement base material, density of dry material and strength of cement base material were selected. The results showed that the correlation coefficient for the compressive strength model for MARS optimized with the algorithm and Mars is 0.991 and 0.971, respectively, and the tensile strength is 0.928 and 0.911, respectively, in the training and testing phase. Investigations show that the proposed MARS model optimized with a meta-heuristic algorithm has good performance and high accuracy in estimating the compressive strength and tensile strength of concrete containing hemp biocomposite. The external validation results also show that the proposed approach can be introduced as predictive models and the correlation between predicted values and experimental values cannot be random. | ||
| کلیدواژه‌ها [English] | ||
| Hemp Bio Composite, Natural Fibers, Artificial Intelligence, MARS Method, Water Cycle Algorithm | ||
| مراجع | ||
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آمار تعداد مشاهده مقاله: 733 تعداد دریافت فایل اصل مقاله: 432 |
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