Dự đoán sức kháng lửa của cột bê tông cốt thép chịu nén sử dụng phương pháp mạng nơ ron nhân tạo=Estimating the fire resistance of reinforced concrete column subjected to compression using an artificial neural network

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Tác giả: Duy Hưng Nguyễn, Duy Liêm Nguyễn, Lưu Uy Nguyễn, Ngọc Thanh Trần, Minh Quang Trịnh

Ngôn ngữ: vie

Ký hiệu phân loại:

Thông tin xuất bản: Tạp chí Xây dựng, 2024

Mô tả vật lý: tr.58

Bộ sưu tập: Metadata

ID: 485168

Thêm vào giỏ

Nghiên cứu này đã phát triển mô hình mạng nơ ron nhân tạo (ANN) để dự đoán sức kháng lửa của cột bê tông cốt thép chịu nén. Tổng cộng 374 kết quả thí nghiệm được thu thập với 12 thông số đầu vào khác nhau bao gồm: cường độ chịu nén, lớp bê tông bảo vệ, chiều dài cột, bề rộng tiết diện cột, chiều cao tiết diện cột, điều kiện biên, tải trọng tác dụng, độ lệch tâm của tải trọng, hàm lượng cốt thép, số cốt thép, đường kính cốt thép, và cường độ chảy của thép. Thêm nữa, một phần mềm được xây dựng để dự đoán sức kháng lửa của cột bê tông cốt thép chịu nén bằng cách tích hợp dữ liệu dự đoán của mô hình. Kết quả nghiên cứu cho thấy, mô hình ANN có khả năng dự đoán tốt sức kháng lửa trong giai đoạn huấn luyện với giá trị hệ số R là 0.94 và giá trị RMSE là 23 phút. Trong giai đoạn kiểm tra, mô hình ANN dự đoán tương đối tốt với giá trị hệ số R khoảng 0.78 và giá trị RMSE khoảng 59 phút. Kết quả phân tích độ nhạy cho thấy chiều cao tiết diện cột có tác động đáng kể nhất đến sức kháng lửa của cột bê tông cốt thép chịu nén. Bên cạnh đó, phần mềm dự đoán sức kháng lửa của cột bê tông cốt thép chịu nén được phát triển có giao diện đơn giản, dễ sử dụng, và thao tác nhanh. Từ khóa: Cột bê tông cốt thép
chịu nén
sức kháng cháy
mạng nơ ron nhân tạo
phân tích độ nhạy.This study aims to develop an artificial neural network (ANN) model for predicting the fire resistance of reinforced concrete columns subjected to compression. A total of 374 experimental test results, incorporating 12 input parameters, were collected. These parameters include compressive strength, concrete cover, column length, crosssection width, cross-section height, boundary conditions, compressive load, load eccentricity, longitudinal reinforcement ratio, number of reinforcements, diameter of reinforcements, and yield strength of reinforcements. Additionally, a software tool was developed to predict the fire resistance of reinforced concrete columns by integrating the ANN model's estimated dataset. The results showed that the ANN model effectively predicted fire resistance in the training set, achieving an R value of 0.94 and an RMSE of 23 minutes. In the testing set, the model demonstrated acceptable accuracy, with an R value of 0.78 and an RMSE of 59 minutes. Sensitivity analysis revealed that the cross-section height was the most important parameter influencing fire resistance. Furthermore, the developed software was found to be simple, userfriendly, and efficient. keywords: Reinforced concrete column
compression
fire resistance
artificial neural network
sensitivity analysis.

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