Jing Yuan
- (2024): Fluid Flow Modeling and Experimental Investigation on a Shear Thickening Fluid Damper. In: Buildings, v. 14, n. 11 (22 Oktober 2024).
- Research on dynamic performance and mechanical model of a novel magnetorheological shear thickening damper with adaptive variable damping gap. In: Smart Materials and Structures, v. 33, n. 10 (18 September 2024). (2024):
- In-situ detection on near-infrared spectra fingerprints of asphalt mixture after laboratory short_ and long-term aging. In: Construction and Building Materials, v. 421 (März 2024). (2024):
- Experimental studies on flexural behavior of full iron tailings concrete beams. In: Structural Concrete, v. 24, n. 6 (2 November 2023). (2023):
- Research on rheological properties and phenomenological theory-based constitutive model of magnetorheological shear thickening fluids. In: Smart Materials and Structures, v. 32, n. 10 (30 August 2023). (2023):
- Experimental studies and analyses on axial compressive properties of full iron tailings concrete columns. In: Case Studies in Construction Materials, v. 18 (Juli 2023). (2023):
- Influences of interlock-dense gradation designed by discrete element method on properties of cement-stabilized recycled brick-concrete aggregates. In: Construction and Building Materials, v. 368 (März 2023). (2023):
- A two-dimensional entropy-based method for detecting the degree of segregation in asphalt mixture. In: Construction and Building Materials, v. 347 (September 2022). (2022):
- Observing bamboo dimensional change caused by humidity. In: Construction and Building Materials, v. 309 (November 2021). (2021):
- Dynamic response analysis of dual-rotor system with rubbing fault by dimension reduction incremental harmonic balance method. In: International Journal of Structural Stability and Dynamics, v. 22, n. 13 (Mai 2022). (2022):
- Indoor air quality management based on fuzzy risk assessment and its case study. In: Sustainable Cities and Society, v. 50 (Oktober 2019). (2019):
- Customized lifting multiwavelet packet information entropy for equipment condition identification. In: Smart Materials and Structures, v. 22, n. 9 (September 2013). (2013):