Danyang Di
- (2024): Interface bonding characteristics of the Cured-in-Place Pipe lined steel plates and parameter sensitivity analysis. In: Structures, v. 69 (November 2024).
- (2024): Prediction model of maximum stress for concrete pipes based on XGBoost-PSO algorithm. In: Structures, v. 68 (Oktober 2024).
- (2024): A CFD-DEM investigation into hydraulic transport and retardation response characteristics of drainage pipeline siltation using intelligent model. In: Tunnelling and Underground Space Technology, v. 152 (Oktober 2024).
- (2024): Mechanical behavior and parameter sensitivity analysis of water supply steel pipes under complex service load combinations. In: Structures, v. 67 (September 2024).
- (2024): Intelligent prediction model of a polymer fracture grouting effect based on a genetic algorithm-optimized back propagation neural network. In: Tunnelling and Underground Space Technology, v. 148 (Juni 2024).
- (2024): Mechanical characteristics of concrete pipes under the coupled effects of the pressure, seepage, and flow fields. In: Structures, v. 61 (März 2024).
- (2024): Shear behavior of a two-component non-water reactive foamed polyurethane (TNFPU) grouting material under different stress levels. In: Construction and Building Materials, v. 411 (Januar 2024).
- (2024): Using EPS and CFRP liner to strengthen prestressed concrete cylinder pipe. In: Construction and Building Materials, v. 412 (Januar 2024).
- (2024): An automatic defect classification and segmentation method on three-dimensional point clouds for sewer pipes. In: Tunnelling and Underground Space Technology, v. 143 (Januar 2024).
- (2023): Integrating fluid–solid coupling domain knowledge with deep learning models: An automatic and interpretable diagnostic system for the silting disease of drainage pipelines. In: Tunnelling and Underground Space Technology, v. 142 (Dezember 2023).
- (2023): Defects identification and location of underground space for ground penetrating radar based on deep learning. In: Tunnelling and Underground Space Technology, v. 140 (Oktober 2023).
- (2023): An automatic and integrated self-diagnosing system for the silting disease of drainage pipelines based on SSAE-TSNE and MS-LSTM. In: Tunnelling and Underground Space Technology, v. 136 (Juni 2023).
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