Yongjun Zhang 
- : Intelligent design of shear wall structures based on BIM and multi-objective genetic algorithm. In: Journal of Building Engineering.
- (2025): Effect of electrolytic manganese residue and phosphoric acid on the properties of magnesium oxychloride cement: Strength and water resistance. In: Construction and Building Materials, v. 463 (Februar 2025).
- (2024): Influence of calcium oxide and sodium silicate on the setting, hardening and shrinkage properties of alkali-activated slag/fly ash mortars. In: Construction and Building Materials, v. 453 (November 2024).
- (2024): Displacement-based dynamic stability determination and assessment of single-layer reticulated dome structures under seismic actions. In: Journal of Building Engineering, v. 98 (Dezember 2024).
- (2025): Effect of electrolytic manganese residue with different calcination temperatures on the properties of magnesium oxychloride cement. In: Journal of Building Engineering, v. 100 ( 2025).
- : Seismic Stability Assessment of Single-Layer Reticulated Dome Structures by the Development of Deep Learning Action Recognition Network. In: International Journal of Structural Stability and Dynamics.
- (2023): Influences and mechanisms of mixing process on properties of the fresh and hardened Type II cement asphalt (CA) mortar. In: Materials and Structures, v. 56, n. 9 (11 Oktober 2023).
- (2020): In-situ monitoring and analysis of tunnel floor heave process. In: Engineering Failure Analysis, v. 109 (Januar 2020).
- (2022): Observed performance of a deep excavation of Qingdao Metro Line 4 in China. In: Tunnelling and Underground Space Technology, v. 123 (Mai 2022).
- (2016): Procedure and Model of Antidisaster Differentiated Planning for a Power Distribution System. In: Journal of Energy Engineering, v. 142, n. 1 (März 2016).
- (2020): Multiobjective Coordinated Control Strategy for Grid-Connected Inverter under Unbalanced Voltage Conditions. In: Journal of Energy Engineering, v. 146, n. 3 (Juni 2020).
- (2020): Optimized Energy-Storage Method Based on Deep-Learning Adaptive-Dynamic Programming. In: Journal of Energy Engineering, v. 146, n. 3 (Juni 2020).
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