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dynamic shear responses of RC circular columns strengthened with recycled FRPs

structures 2025年 78卷

作者： Yan, Zhi-Wei Song, Yanchen Bai, Yu-Lei Liu, Kun Faculty of Civil Engineering and Mechanics Jiangsu University Zhenjiang212013 China State Key Laboratory of Bridge Engineering Safety and Resilience Beijing University of Technology Beijing100124 China Key Lab of Structures Dynamic Behavior and Control of the Ministry of Education Harbin Institute of Technology Harbin150090 China

Increasingly heavy urban traffic exacerbates vehicle impacts on reinforced concrete (RC) bridge columns, possibly leading to shear failure and structural collapse. To enhance the dynamic shear resistance of these columns, fiber reinforced polymers (FRPs) made from recycled polyethylene terephthalate (PET) plastic bottles were used for external strengthening. PET FRPs offer an eco-friendly alternative by repurposing plastic waste, reducing pollution, and promoting circular economy. This study focused on the dynamic shear responses of RC columns strengthened with PET FRPs. The influences of FRP types and number of FRP layers were experimentally revealed in terms of the failure modes, impact force, reaction force, shear force and impact force-displacement relationship. It was found that significant shear damage occurred in RC columns under horizontal impact loads, with carbon FRPs (CFRPs) strengthening unable to alter the failure mode. Nevertheless, the use of PET FRPs transformed the failure mode to a flexural-shear mode, significantly reducing the impact duration, maximum and residual displacements, and energy dissipation. Moreover, a finite element model was validated to describe the impact resistance of PET FRP-strengthened RC columns, as supported by experimental data. A parametric study further investigated the effects of impact velocity, impact mass, number of FRP layers, and reinforcement ratios on the dynamic shear responses. Based on the truss-arch model, a dynamic shear strength model was proposed and can well predict the dynamic shear capacity of FRP-strengthened RC circular columns. © 2025

关键词： Carbon fiber reinforced plastics

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Stacked Ensemble Learning Method for TBM Surrounding Rock Classification Prediction of Surrounding Rock in TBM Excavation

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Science Technology and Engineering 2025年第14期25卷 6016-6022页

作者： Zhu, He-Chao Yao, Chang-Rui Shao, Yong-Ping Tang, Liang Kong, Xiang-Xun Li, Bo-Yu Zhang, Tian-Yu Angang Cornerstone Mining Co. Ltd. Anshan114001 China Key Laboratory of Structures Dynamic Behavior and Control of Ministry of Education HarbinInstitute of Technology Harbin150090 China School of Civil Engineering Harbin Institute of Technology Harbin150090 China China Railway 17th Bureau Group Second Engineering Co. Ltd. Xi'an710000 China

The data-driven approach of machine learning enables the intelligent construction of TBM(tunnel boring machines), which is crucial for optimizing the tunneling process, improving the safety of tunneling and reducing labor costs. In order to solve the problems of excessive noise, redundant parameters and difficult effective feature extraction in TBM operation data, a data-driven machine learning method was used to mine the complex machine-soil interaction contained in the data and realize the classification and prediction of TBM surrounding rock mass. First, for the large amount of operational data generated during TBM tunneling, the KDE (kernel density estimation) method was used to extract features from typical tunneling parameter curves, and the maximum probability of the key operating parameters during stable tunneling stage of TBM is obtained. Then, based on the actual TBM operation data, an integrated learning algorithm for surrounding rock classification stacking was proposed. The algorithm is further optimized through k-fold cross-validation, and the complex relationships in the data are mined by using the two-layer learning framework of base classifier and meta-classifier. Finally, a data set of 5 868 TBM segments was used to verify the effectiveness of the proposed algorithm. The results show that the average F1 of the four-classification problem is 0. 705, and the average F1 of the two-classification problem is 0. 797, which are better than the four selected base classifiers. © 2025 Beijing Kexue Jishu yu Gongcheng Zazhishe. All rights reserved.

关键词： Data reduction

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Artificial flaw design for engineered cementitious composites via sand coating strategy: Optimization and mechanism

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Construction and Building Materials 2025年 489卷

作者： Zhuo Tang Ming Zhang Jing Zhong Key Lab of Structures Dynamic Behavior and Control of the Ministry of Education (Harbin Institute of Technology) Harbin 150090 PR China School of Civil Engineering Harbin Institute of Technology Harbin 150090 PR China China State Construction International Holdings Limited 999077 Hong Kong

The multiple cracking phenomenon of Engineered Cementitious Composites (ECC) is strongly governed by the size and distribution of flaws, which remain challenging to control. Conventional approaches for introducing artificial flaws to induce multiple cracking typically substantially reduce compressive strength. Recently, a strategy was proposed using sands coated with a thin and porous defective coating of polymer nanocomposites to enhance the tensile behaviors of ECC with limited loss of compressive strength. In this study, the ECC performance is further enhanced by controlling the microstructure and interaction with hydrates of the carbon nanotube (CNT) polymer nanocomposite coating and the agglomeration of sands. Relative to the control group, the ductility and compressive strength of the optimized ECC increased by 178 % and 10 %, respectively, with very stable cracking behaviors among all the tested samples. This improvement is mainly because increasing the CNT content in the nanocomposite altered the physicochemical properties and microstructure of coatings, leading to the varied properties of coated sand, which determines the distribution of flaws in the matrix. Interestingly, it was found that the well-separated coated sand ensures high ductility and performance stability of ECC. The formation of diverse sand/matrix interfaces, transitioning from polymer-matrix to CNT-matrix, eventually allows us to overcome the traditional dilemma between ductility and compressive strength.

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Structural Performance of Smart CFRP-FBG Reinforced Steel Beams

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Journal of Architectural Environment & Structural Engineering Research 2020年第4期3卷 9-15页

作者： Huaping Wang Tao Song Hengyang Li Siyuan Feng School of Civil Engineering and Mechanics Lanzhou UniversityLanzhouGansu730000China Key Lab of Structures Dynamic Behavior and Control(Harbin Institute of Technology) Ministry of EducationHarbinHeilongjiang150090China

Many beam structures suffer from gradual performance degradation with the increase of service *** recover the bearing capacity of these beams,carbon fiber reinforced polymer(CFRP)plates are developed to attached on the beam *** check the structural performance of the CFRP reinforced beams,smart CFRP plate with FBGs in series is designed and LVDTs are adopted to measure the *** deflection of the reinforced beam is given based on the elastic conversion cross-section *** experimental results validate the effectiveness of the proposed *** study shows that the CFRP reinforced zone has a larger flexural rigidity than the pure steel beam *** general distribution of the deflection along the span of the CFRP reinforced beam can be described by the proposed *** provides a scientific design guidance for the deflection control of CFRP reinforced structures.

关键词： CFRP reinforced beam Interfacial interaction Smart CFRP-FBG plate Deflection Experimental investigation

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SDIGLM: Leveraging Large Language Models and Multi-Modal Chain of Thought for Structural Damage Identification

arXiv

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arXiv 2025年

作者： Zhang, Yunkai Wei, Shiyin Huang, Yong Su, Yawu Lu, Shanshan Li, Hui Key Lab of Smart Prevention and Mitigation of Civil Engineering Disasters Ministry of Industry and Information Technology School of Civil Engineering Harbin Institute of Technology Harbin150090 China Key Lab of Structures Dynamic Behavior and Control of the Ministry of Education Harbin Institute of Technology Harbin150090 China CSCEC Digital Technology Co. Ltd. Beijing100000 China

Existing computer vision(CV)-based structural damage identification models demonstrate notable accuracy in categorizing and localizing damage. However, these models present several critical limitations that hinder their practical application in civil engineering(CE). Primarily, their ability to recognize damage types remains constrained, preventing comprehensive analysis of the highly varied and complex conditions encountered in real-world CE structures. Second, these models lack linguistic capabilities, rendering them unable to articulate structural damage characteristics through natural language descriptions. With the continuous advancement of artificial intelligence(AI), large multi-modal models(LMMs) have emerged as a transformative solution, enabling the unified encoding and alignment of textual and visual data. These models can autonomously generate detailed descriptive narratives of structural damage while demonstrating robust generalization across diverse scenarios and tasks. This study introduces SDIGLM, an innovative LMM for structural damage identification, developed based on the open-source VisualGLM-6B architecture. To address the challenge of adapting LMMs to the intricate and varied operating conditions in CE, this work integrates a U-Net-based semantic segmentation module to generate defect segmentation maps as visual Chain of Thought(CoT). Additionally, a multi-round dialogue fine-tuning dataset is constructed to enhance logical reasoning, complemented by a language CoT formed through prompt engineering. By leveraging this multi-modal CoT, SDIGLM surpasses general-purpose LMMs in structural damage identification, achieving an accuracy of 95.24% across various infrastructure types. Moreover, the model effectively describes damage characteristics such as hole size, crack direction, and corrosion severity. Copyright © 2025, The Authors. All rights reserved.

关键词： Structural health monitoring

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Interfacial Interaction of CFRP Reinforced Steel Beam structures

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Journal of Architectural Environment & Structural Engineering Research 2020年第4期3卷 2-8页

作者： Huaping Wang Hengyang Li Siyuan Feng Tao Song School of Civil Engineering and Mechanics Lanzhou UniversityLanzhouGansu730000China Key Lab of Structures Dynamic Behavior and Control(Harbin Institute of Technology) Ministry of EducationHarbinHeilongjiang150090China

Due to the increase of service life,the phenomenon of performance degradation of bridge structures becomes more and more *** is important to strengthen the bridge structures so as to restore the resistance level and extend the normal service *** fiber reinforced polymer(CFRP)materials are thus used for the assembly reinforcement of bridges for the advantages of high strength,light weight,corrosion resistance and long-term stability of physical and chemical properties,*** view of this,based on the previous theoretical study and the established formula of the interfacial shear stress of CFRP reinforced steel beam and the normal stress of CFRP plate,this paper discusses the sensitive parameters that affect the interfacial interaction of CFRP strengthened beam *** the analysis,the priority design indicators and suggestions are accordingly given for the design of reinforced beam ***’s modulus of CFRP composite and shear modulus of the adhesive have the greatest influence on the interfacial interaction,which should be carefully *** is suggested that CFRP material with Ec close to 300 GPa and thickness no less than 3 mm,and adhesive material with Ga less than 5 GPa and 3-mm thickness can be adopted in CFRP reinforced steel *** conclusions of this paper can provide guidance for the interfacial damage control of CFRP reinforced steel beam structures.

关键词： CFRP reinforced steel beam Interfacial interaction Shear stress Parametric analysis Design instruction

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Essential Stressing State Features of Laterally Loaded Masonry Wall Panels Revealed from Experimental Displacements

Research Square

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Research Square 2021年

作者： Liu, Bai Li, Rui Zhang, Yu Zhou, Guangchun Key Lab of Structures Dynamic Behavior and Control of China Ministry of Education Key Lab of Smart Prevention and Mitigation of Civil Engineering Disasters of the Ministry of Industry and Information Technology School of Civil Engineering Harbin Institute of Technology Harbin150090 China Urban and Engineering Disaster Prevention Laboratory Institute of Engineering Mechanics China Earthquake Administration Harbin150086 China

This study reveals the essential and general working features of laterally loaded masonry (LLM) wall panels from their experimental displacements by applying structural stressing state theory. Firstly, the generalized work of force is proposed to express the stressing state mode and its characteristic parameter. Then, the Mann-Kendall criterion is applied to detect the mutation point in the curve of the characteristic parameter with the load increase. Correspondingly, it is verified that the evolution of the stressing state mode also embodies the mutation feature. The stressing state mutation feature is inherent and common as the embodiment of the natural law from quantitative change to qualitative change of a system. The stressing state mutation feature reveals the starting point of structural failure process, which could update the existing definition of structural failure load. Further, the elastoplastic branch (EPB) point is revealed referring to the updated failure load, which might be directly taken as the design load with the rational margin of safety. In a sense, this paper presents a new way to address the classic issue of structural load-bearing capacity uncertainty and to update the existing design codes of LLM wall panels. © 2021, CC BY.

关键词： Fracture mechanics

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A Study Using the Combined Method of Scientometric and Manual Analysis on the Present Research of Plant Fibres Reinforced Concrete

SSRN

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SSRN 2022年

作者： Pan, Yunshi Li, Shuangxin Deng, Ling Shi, Youyu Wang, Jiarui Zhang, Faqi School of Civil Engineering Northeast Forestry University Harbin150060 China School of Civil Engineering Harbin Institute of Technology Harbin150090 China Key Lab of Structures Dynamic Behaviour and Control of the Ministry of Education Harbin Institute of Technology Harbin150090 China Anqiu Water Resources Bureau Anqiu262100 China

As one of the most important supporting technologies to economic development and urbanisation, concrete becomes a crucial link to reduce the global carbon emission and confronts with an unprecedented challenge of decarbonation. The reinforcement by plant fibres in concrete is one of promising approaches to decarbonise concrete. This paper combines scientometric and manual analysis to evaluate the research progress on plant fiber reinforced concrete (PFRC), revealing the prevailing research domains and focuses on PFRC and the work performance of PFRC. The main challenges confronted by PFRC are discussed and and future research scope are proposed at the end. © 2022, The Authors. All rights reserved.

关键词： Thermal insulation

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Experimental investigation of shear behavior in precast concrete beams with steel bolted splice connections

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structures 2025年 78卷

作者： Khalil Abualtayef Wei Zhou School of Civil Engineering Harbin Institute of Technology Harbin 150090 China Key Lab of Structures Dynamic Behavior and Control Ministry of Education School of Civil Engineering Harbin Institute of Technology Harbin 150090 China Key Lab of Smart Prevention and Mitigation of Civil Engineering Disasters of the Ministry of Industry and Information Technology School of Civil Engineering Harbin Institute of Technology Harbin 150090 China

Precast concrete structures with bolted connections offer significant advantages, including shorter construction times, improved quality control, and enhanced structural performance. This study investigates the shear behavior of precast concrete beams with steel-bolted splice connections (PCBSBs), which join the discontinuity of two short concrete beam segments, under monotonic loading. Afterwards, the shear performance of PCBSB beams was experimentally and analytically investigated. Six full-scale PCBSB specimens and one control concrete beam were tested to evaluate the effects of key parameters include the shear span ratio and steel plate thickness. The test results show that the failure modes of PCBSB beams are similar to those of reinforcement concrete beams, and the crack propagations can be well controlled by the steel plate thickness. Using a steel bolted connection with a thickness of 3 mm and 5 mm increased the shear crack load by 9 % and 24 %, respectively. After the loading reached 65 % of the peak load, the deflection of steel bolted connection begins to increase more than the shear load deflection till peak load. For beams with long shear span ratio, increase of steel plate thickness led to increase the stiffness, and peak load. Higher a/d ratios increase deflection and shift failure modes from ductile (shear-compression) to brittle (shear-tension). Finally, the experimental shear capacities of the PCBSBs exceeded the predictions of the GB, ACI, EN, and CSA standards for beams with a/d ratios of 1.5 and 2.0. However, discrepancies were observed for beams with a/d of 3.0, where flexural behavior becomes more dominant. Based on these findings, a preliminary design recommendation was proposed. Further studies were recommended to investigate the performance of beams with shorter a/d ratios and varying dimensions to optimize connection efficiency.

关键词： Precast concrete

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Big-data driven building retrofitting: An integrated support vector machines and fuzzy c-means clustering method

Big-data driven building retrofitting: An integrated support...

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World Sustainable Built Environment - Beyond 2020, WSBE 2020

作者： Lu, Weizhuo Feng, Kailun Department of Civil Environmental and Natural Resources Engineering Luleå University of Technology Sweden Department of Construction Management Harbin Institute of Technology Harbin150009 China Key Lab of Structures Dynamic Behavior and Control of the Ministry of Education Harbin Institute of Technology Harbin150090 China Key Lab of Smart Prevention and Mitigation of Civil Engineering Disasters of Ministry of Industry and Information Technology Harbin Institute of Technology Harbin150090 China

It has become a mainstream to use physical models to quantify expected energy savings from alternative retrofit methods and technologies. However, they are not suitable for predicting energy use of buildings when detailed and specified input parameters are unavailable. The overall purpose of the research is to support the stakeholders in taking decisions on refurbishments options when not all of physical information is available, in order to achieve the Swedish Energy Agency's measurements of near-zero energy buildings. The research will transfer big data from Swedish Energy Performance Certificates for building retrofitting. A Support Vector Machines and Fuzzy C-means clustering (SVM-FCM) integrated machine learning algorithm is used directly to extract the case-specific knowledge from EPC big data regarding building characteristics and energy saving of retrofit measures. It enables to prioritize retrofit measures and compute their expected energy savings for buildings. This proposed data driven method is an attempt of taking advantage of big data for practical building retrofit selection. © 2020 Institute of Physics Publishing. All rights reserved.

关键词： Support vector machines

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