出版者・発行元：Structures  

This study investigates the joint between the steel wall plate and the concrete pylon wall in the cable-pylon anchorage zone of cable-stayed bridges, utilizing perfobond rib (PBL) connectors. Finite element analysis (FEM) was conducted on the steel wall plate-concrete joint under various conditions, including cable force, concrete shrinkage, overall warming, and overall cooling, with PBL connectors modeled as spring elements. The results indicate that vertical shear force in the PBL connectors peaks in the steel bracket web plates, with cable force and concrete shrinkage having the most significant impact on stress. Scaled-down local model tests and corresponding solid element FEM analysis were performed to evaluate the load performance of these joints. During tests, deformation between the steel plate and concrete wall remained minimal, and no cracks appeared under loads up to 1.7 times the design load. The ultimate load capacity was 2.9 times the design load, with failure occurring through pullout damage. FEM analysis showed good agreement with test results, and overall stress levels remained low, meeting design requirements. Material yielding only occurred in joint areas under large loads, confirming the feasibility of PBL connectors in composite cable-pylon anchorage zones.

DOI： 10.1016/j.istruc.2024.106973

Web of Science

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記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：Engineering Structures  

With advancements in material properties and reduced costs, carbon fibre reinforced polymer (CFRP) cables are gaining popularity in engineering applications due to their superior strength-to-mass ratio and durability. However, the tensile strength of large-scale parallel CFRP cables remains a critical issue, warranting further research and engineering expertise. To address this issue, this paper proposes a method to rapidly predict and adaptively correct the tensile strength of large-scale parallel CFRP cables using multi-source experimental data and an integrated approach that incorporates Monte Carlo simulations, Neural Network algorithms, and Genetic algorithms. This comprehensive method takes into account the influence of various factors including small-scale material strength and its coefficient of variation, cable length, the number of parallel wires, installation errors, and anchorage errors. Validated by reported experimental data, the method demonstrates its effectiveness in accurately predicting the tensile strength of parallel CFRP cables. Moreover, a design method for large-scale parallel CFRP cables is proposed based on the reliability theory. Lastly, the efficiency and effectiveness of the proposed method are validated through the design and optimization of a cable-stayed bridge featuring a main span of 1984 m, utilising both parallel steel and CFRP cables.

DOI： 10.1016/j.engstruct.2024.117771

Web of Science

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記述言語：日本語   掲載種別：研究論文（学術雑誌）   出版者・発行元：公益社団法人 土木学会  

DOI： 10.11532/structcivil.70A.114

CiNii Research

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記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：Nondestructive Testing and Evaluation  

In the past, diagnoses of the internal defects of ageing concrete members by sound tests have relied on the ability and experience of the inspector. However, with the development of deep neural networks, building diagnosis tools without the subjective judgements of humans is feasible. In this study, sound samples are collected from a tapping sound test on concrete slab specimens with internally embedded artificial defects. Spectrograms are generated from the sound samples and used to train a light-weighted convolutional neural network (CNN). Thereafter, the performance of the proposed CNN models at diagnosing the defects of the concrete slabs are examined and compared with convolutional autoencoder (CAE) and support vector regression (SVR). All the models performed well at distinguishing between healthy and defective concrete. Whereas noise can impair the performance of CAE and SVR, CNN is less affected, particularly when classifying sound samples with distinctive features. CNN also has other advantages: the physical area of the artificial defect can be output directly from CNN, and CNN performance is also less affected by the depth of the artificial defect and the rebar embedded in the concrete. At increased depths, the CNN is still able to identify the defect area.

DOI： 10.1080/10589759.2023.2301032

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記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：Applied Sciences (Switzerland)  

In this study, continuous fiber composite (CFC) panels were used as a strengthening material to improve the impact resistance of reinforced concrete (RC). Both experimental tests and numerical analyses were carried out to investigate the impact resistance of RC beams strengthened with CFC panels. The experiments involved repeated drop-weight impact tests at constant speed. The experimental results confirm that the strengthening of RC beams with CFC panels improves the impact resistance, thereby increasing the number of repeated impacts that can be allowed before a specified residual displacement is reached. In addition, a virtual particle model based on the conventional smoothed particle hydrodynamics (SPH) method, which takes into account the mechanical properties of the adhesive, was introduced as an analytical method to simulate the impact fracture behavior of RC beams strengthened with CFC panels. The analysis results show that the improved SPH method proposed in this study can accurately reproduce the impact behavior of RC beams strengthened with CFC panels and predict the allowable number of repeated impacts. Furthermore, a parametric study was carried out using a validated analytical approach to compare the load-bearing capacity and discuss the impact performance of RC beams with three types of CFC panel reinforcement.

DOI： 10.3390/app131910625

Web of Science

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開催年月日： 2024年4月

記述言語：日本語   会議種別：口頭発表（一般）  

開催地：東京工業大学大岡山キャンパス(東京都)   国名：日本国  

開催年月日： 2024年4月

記述言語：日本語   会議種別：シンポジウム・ワークショップ パネル（公募）  

開催地：東京工業大学大岡山キャンパス(東京都)   国名：日本国  

開催年月日： 2024年4月

記述言語：日本語  

開催地：東京工業大学大岡山キャンパス(東京都)   国名：日本国  

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開催年月日： 2024年3月

記述言語：日本語   会議種別：口頭発表（一般）  

開催地：福岡大学 福岡市   国名：日本国  

開催年月日： 2024年3月

記述言語：日本語  

開催地：福岡大学 福岡市   国名：日本国  

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種別：大会・シンポジウム等 

種別：大会・シンポジウム等 

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