Prediction of effective moment of inertia for hybrid FRP-steel reinforced concrete beams  using the genetic algorithm

Kheyroddin, Ali; Maleki, Fahimeh

doi:10.29252/nmce.2.1.15

Cited by 10 publications

(10 citation statements)

References 27 publications

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“…Issal et al [14] recommended modifying Branson's formula based on flexural tests on the tension reinforcement ratio and load pattern. Kheyroddin and Maleki [15] proposed a new equation of the effective moment of inertia of FRP-steel RC beams using Branson's formula. Bertero and Bertero [16] evaluated the accuracy of Branson and Bischoff equations for the minimum deflection of two-way slabs.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Shear Effect on Deflection of RC Beams

2021

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This study evaluates the effect of shear on the deflection of reinforced concrete (RC) beams subjected to combined bending and shear. A total of nine simply supported beams were manufactured with the shear span-to-depth ratio, tension steel ratio, and shear capacity ratio as test variables. The experimental results were used to evaluate the effect of shear on the deflection by separating them into flexural and shear deformations. The theoretical deflection of the specimens was calculated using the effective moment of inertia equation recommended by ACI 318-19 based on the curvature relationships and experimental results of the flexure critical beams. By comparing the experimental and analytical results, it was revealed that the deflection obtained using the ACI equation underestimated the experimental results by up to about 1.6 times when the shear effect was large.

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Section: Introductionmentioning

confidence: 99%

Evaluation of Shear Effect on Deflection of RC Beams

2021

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“…They said that the model is better than existing models. Kheyroddin and Maleki 13 used the genetic algorithm to estimate the deflection of concrete beams containing hybrid fiber. The used model predicted the deflection with a low error.…”

Section: Prediction Results Of the Selected Modelsmentioning

confidence: 99%

“…11 There have been articles in the literature about estimating the strength of concrete containing fiber. [12][13][14] In these articles, deep-learning (DL) model was not used to estimate the mechanical properties of SCC having single fiber and binary, ternary, and quaternary fiber hybridization. The DL has been generally used in crack detection in civil engineering in recent years.…”

mentioning

confidence: 99%

Estimation of strengths of hybrid FR‐SCC by using deep‐learning and support vector regression models

Kına

Türk

Tanyıldızı

2022

Structural Concrete

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In this work, to estimate the compressive, splitting tensile, and flexural strength of self‐compacting concrete (SCC) having single fiber and binary, ternary, and quaternary fiber hybridization, the deep‐learning (DL) and support vector regression (SVR) models were devised. The fiber content and coarse aggregate/total aggregate ratio (CA/TA) were the variables for 24 designed mixtures. Four different fibers, which were a macro steel fiber, two types of micro steel fibers with different aspect ratio, and polyvinyl alcohol (PVA) fiber, were used in SCC mixtures. The specimens of each mixture were tested to measure the engineering properties for 7, 28, and 90 days. The amount of cement, fly ash, fine aggregate, CA, high‐range water‐reducing admixture, water, macro steel fiber, PVA fiber, two types of micro steel fibers, and curing time were selected as input layers while the output layers were strength results. The experimental results were compared with the estimation results. The engineering properties were estimated using the SVR model with 95.25%, 87.81%, and 93.89% accuracy, respectively. Furthermore, the DL model estimated compressive strength, tensile strength, and flexural strength with 99.27%, 98.59%, and 99.15% accuracy, respectively. It was found that the DL estimated the engineering properties of hybrid fiber–reinforced SCC with higher accuracy than SVR.

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“…[9] năm 2015, Pang và cs. [10] năm 2015 và Kheyrodin & Maleki [11] năm 2017. Các nghiên cứu này đều dựa trên công thức đề xuất trong tiêu chuẩn ACI 440.1R-06 [2] của Branson để chính xác hóa công thức tính độ võng dầm bê tông cốt hỗn hợp qua giá trị mô men quán tính hiệu quả I e theo tiêu chuẩn Hoa Kỳ.…”

Section: Giới Thiệuunclassified

Nghiên cứu tính toán độ võng ngắn hạn dầm bê tông cốt hỗn hợp thép và polyme cốt sợi thủy tinh theo TCVN 5574:2018

Tuấn¹,

Tâm²

2022

TCKHCNXD

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Thanh cốt sợi thủy tinh (GFRP) có cường độ cao nhưng mô đun đàn hồi thấp, khiến dầm bê tông cốt GFRP thuần túy thường có độ võng lớn. Việc sử dụng kết hợp cốt thép và cốt GFRP sẽ giúp cải thiện vấn đề này. Tuy nhiên, việc xác định độ võng dầm bê tông cốt hỗn hợp thép và GFRP (cốt SGFRP) hiện chưa có tiêu chuẩn hướng dẫn. Dựa theo các quan hệ ứng suất-biến dạng của vật liệu theo tiêu chuẩn TCVN 5574:2018, bài báo trình bày một phương pháp xác định độ võng ngắn hạn bằng các nghiên cứu lý thuyết. Qua đó nghiên cứu đã khảo sát độ võng ngắn hạn dầm bê tông cốt SGFRP với các thông số thay đổi, đã so sánh độ võng ngắn hạn dầm bê tông cốt SGFRP với độ võng dầm bê tông cốt thép và dầm bê tông cốt sợi thủy tinh thuần túy.

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Prediction of effective moment of inertia for hybrid FRP-steel reinforced concrete beams using the genetic algorithm

Cited by 10 publications

References 27 publications

Evaluation of Shear Effect on Deflection of RC Beams

Evaluation of Shear Effect on Deflection of RC Beams

Estimation of strengths of hybrid FR‐SCC by using deep‐learning and support vector regression models

Nghiên cứu tính toán độ võng ngắn hạn dầm bê tông cốt hỗn hợp thép và polyme cốt sợi thủy tinh theo TCVN 5574:2018

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