An optimization neural network model for bridge cable force identification

T Gai, D Yu, S Zeng, JCW Lin - Engineering Structures, 2023 - Elsevier
Accurate determination of cable force values is the most important technical means to avoid
damage to the cable bridge. In order to avoid the influence of the difficulty in distinguishing …

Shear strength prediction and failure mode identification of beam–column joints using BPNN, RBFNN, and GRNN

J Zhang, X Zhao, Y Gao, W Guo, Y Zhai - Arabian Journal for Science and …, 2023 - Springer
Beam–column joints are critical members of reinforced concrete frames, the failure of which
may induce the collapse of structures under earthquake action. The design equations in …

Corrosion evaluation of carbon steel bars by magnetic non-destructive method

AG Diogenes, EP de Moura… - Nondestructive …, 2022 - Taylor & Francis
Reinforced concrete structures undergo various degradation processes, mainly rebars
corrosion. Recently, magnetic non-destructive tests have been used to study the steel …

Inversion of the fracture toughness of zirconium alloy cladding interface in nuclear fuel using splitting method via general regression neural network

Y Zhou, Y Dong, H Ma, J Lv, Q Li - Journal of Nuclear Materials, 2025 - Elsevier
For nuclear fuel elements, the interface mechanical properties of zirconium alloy cladding is
critical to the safety and reliability of reactors. However, due to the small thickness of the fuel …

Predicting hardness profile of steel specimens subjected to Jominy test using an artificial neural network and electromagnetic nondestructive techniques

I Ahadi Akhlaghi, S Kahrobaee… - Nondestructive …, 2021 - Taylor & Francis
Based on relationships between electromagnetic properties and microstructural changes in
steel, the current paper describes the development of an electromagnetic technique to …

Shadclips: When parameter-efficient fine-tuning with multimodal meets shadow removal

X Zhang, Z Xu, H Tang, C Gu, S Zhu, X Guan - 2024 - researchsquare.com
Abstract Segment Anything Model (SAM), an advanced universal image segmentation
model trained on an expansive visual dataset, has set a new benchmark in image …

Quantitative Prediction of Surface Hardness in Cr12MoV Steel and S136 Steel with Two Magnetic Barkhausen Noise Feature Extraction Methods

X Wang, Y Cai, X Liu, C He - Sensors, 2024 - mdpi.com
The correlation between magnetic Barkhausen noise (MBN) features and the surface
hardness of two types of die steels (Cr12MoV steel and S136 steel in Chinese standards) …

Análise de corrosão em armaduras de concreto armado através de ensaio não destrutivo eletromagnético

AG Diógenes - 2021 - repositorio.ufc.br
As armaduras de aço são amplamente utilizadas em estruturas de concreto armado como
edifícios, pontes, plataformas, viadutos, dentre outros. Embora essas estruturas apresentem …