Reliability analysis of various modeling techniques for the prediction of axial strain of FRP-confined concrete

纤维增强塑料 有限元法 结构工程 人工神经网络 非线性系统 压缩(物理) 材料科学 计算机科学 复合材料 工程类 机器学习 量子力学 物理
作者
Ahmed Babeker Elhag,Ali Raza,Nabil Ben Kahla,Muhammed Arshad
出处
期刊:Multidiscipline Modeling in Materials and Structures [Brill]
标识
DOI:10.1108/mmms-03-2024-0070
摘要

Purpose The external confinement provided by the fiber-reinforced polymer (FRP) sheets leads to an improvement in the axial compressive strength (CS) and strain of reinforced concrete structural members. Many studies have proposed analytical models to predict the axial CS of concrete structural members, but the predictions for the axial compressive strain still need more investigation because the previous strain models are not accurate enough. Moreover, the previous strain models were proposed using small and noisy databases using simple modeling techniques. Therefore, a rigorous approach is needed to propose a more accurate strain model and compare its predictions with the previous models. Design/methodology/approach The present work has endeavored to propose strain models for FRP-confined concrete members using three different techniques: analytical modeling, artificial neural network (ANN) modeling and finite element analysis (FEA) modeling based on a large database consisting of 570 sample points. Findings The assessment of the previous models using some statistical parameters revealed that the estimates of the newly recommended models were more accurate than the previous models. The estimates of the new models were validated using the experimental outcomes of compressive members confined with carbon-fiber-reinforced polymer (CFRP) wraps. The nonlinear FEA of the tested samples was performed using ABAQUS, and its estimates were equated with the calculations of the analytical and ANN models. The relative investigation of the estimates solidly substantiates the accuracy and applicability of the recommended analytical, ANN and FEA models for predicting the axial strain of CFRP-confined concrete compression members. Originality/value The research introduces innovative methods for understanding FRP confinement in concrete, presenting new models to estimate axial compressive strains. Utilizing a database of 570 experimental samples, the study employs ANNs and regression analysis to develop these models. Existing models for FRP-confined concrete's axial strains are also assessed using this database. Validation involves testing 18 cylindrical specimens confined with CFRP wraps and FE simulations using a concrete-damaged plastic (CDP) model. A comprehensive comparative analysis compares experimental results with estimates from ANNs, analytical and finite element models (FEMs), offering valuable insights and predictive tools for FRP confinement in concrete.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
sammie_9622完成签到,获得积分20
1秒前
1秒前
闪闪冰旋发布了新的文献求助20
1秒前
廉洁发布了新的文献求助10
1秒前
1秒前
iknj完成签到,获得积分10
2秒前
Tough完成签到 ,获得积分10
2秒前
雪白煜城完成签到,获得积分10
2秒前
lcdamoy完成签到,获得积分10
2秒前
汉堡包应助明写春诗采纳,获得10
2秒前
2秒前
旺旺发布了新的文献求助10
2秒前
qqq完成签到,获得积分10
2秒前
标致橘子完成签到,获得积分10
3秒前
屁股大大发布了新的文献求助10
3秒前
wxh_20232110065完成签到,获得积分20
4秒前
ding应助shangchen采纳,获得10
4秒前
严驰发布了新的文献求助10
4秒前
努力的学发布了新的文献求助10
4秒前
直率的鸿发布了新的文献求助10
4秒前
Hello应助无忧采纳,获得10
5秒前
gyy发布了新的文献求助10
5秒前
科研通AI6.1应助sieena采纳,获得10
5秒前
大西瓜发布了新的文献求助10
6秒前
科目三应助开心枣枣采纳,获得10
6秒前
神勇草莓完成签到,获得积分20
6秒前
6秒前
李健的小迷弟应助鹏gg采纳,获得10
6秒前
6秒前
炸茄盒的老头完成签到,获得积分10
6秒前
7秒前
7秒前
酷波er应助浮光采纳,获得30
7秒前
7秒前
7秒前
可爱的函函应助晓晓采纳,获得10
7秒前
8秒前
mindseye完成签到,获得积分20
8秒前
8秒前
8秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Kinesiophobia : a new view of chronic pain behavior 3000
The Social Psychology of Citizenship 1000
Signals, Systems, and Signal Processing 510
Discrete-Time Signals and Systems 510
Le genre Cuphophyllus (Donk) st. nov 500
Brittle Fracture in Welded Ships 500
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5930970
求助须知:如何正确求助?哪些是违规求助? 6990738
关于积分的说明 15847363
捐赠科研通 5059750
什么是DOI,文献DOI怎么找? 2721679
邀请新用户注册赠送积分活动 1678644
关于科研通互助平台的介绍 1610057