Jili Feng
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Jili Feng has a total of 27 co-authors. Here are the top co-authors by number of shared publications:
Hongze Li
State Key laboratory of Tunnel Engineering, China University of Mining and Technology Beijing, Beijing, China
4 shared publicationsChao Wang
3 shared publications- Chunhui Cao
School of Civil Engineering and Architecture, Zhejiang University of Science and Technology, Hangzhou, China
3 shared publications - Zhigang Tao
School of Mechanics and Civil Engineering, China University of Mining and Technology, Beijing, China
3 shared publications - Chao Wang
China Coal Mine Construction Group Co., Ltd., No. 898, Xiyou Road, Hefei 230071, Zhengwu District, Anhui, P. R. China
2 shared publications - Chun Feng
Institute of Mechanics, Chinese Academy of Sciences, Beijing 100190, China
2 shared publications
Latest Publications
- Open Access
The Double-K Fracture Toughness of Concrete with Different Coarse Aggregate Volume Fractions
This study examines how coarse aggregate volume fraction (Va) affects the double-K fracture toughness and fundamental mechanical properties of concrete. Wedge-splitting tests were conducted on specimens with six different Va values: 19%, 25%, 31%, 37%, 43%, and 50%. The results indicate that compressive strength (fc) and elastic modulus (E) consistently increase with Va, reaching 59.8 MPa and 37.9 GPa at Va = 50%, respectively. Conversely, tensile strength (ft), double-K fracture toughness (including initiation toughness and unstable toughness ), and fracture energy (GIF) initially increase before decreasing, peaking at an optimal Va of 37%. Specifically, , , and GIF reached their maximum values of 0.54 MPa·m1/2, 1.20 MPa·m1/2, and 225.0 N/m at Va = 37%. The tortuosity of crack paths follows a similar trend, becoming more pronounced up to Va = 37% before diminishing. Furthermore, quantitative exponential relationships were established between ft and , , and GIF. A safety warning parameter (δ), derived from the double-K fracture toughness, was proposed to quantitatively assess the pre-peak ductility, with values ranging from 0.88 to 0.72 in this study. The findings offer valuable guidance for optimizing concrete mix design, suggesting that a Va range of 25% to 31% provides an optimal balance between high crack initiation resistance and adequate safety warning capacity for critical engineering structures.Open AccessThe Double-K Fracture Toughness of Concrete with Different Coarse Aggregate Volume Fractions
This study examines how coarse aggregate volume fraction (Va) affects the double-K fracture toughness and fundamental mechanical properties of concrete. Wedge-splitting tests were conducted on specimens with six different Va values: 19%, 25%, 31%, 37%, 43%, and 50%. The results indicate that compressive strength (fc) and elastic modulus (E) consistently increase with Va, reaching 59.8 MPa and 37.9 GPa at Va = 50%, respectively. Conversely, tensile strength (ft), double-K fracture toughness (including initiation toughness and unstable toughness ), and fracture energy (GIF) initially increase before decreasing, peaking at an optimal Va of 37%. Specifically, , , and GIF reached their maximum values of 0.54 MPa·m1/2, 1.20 MPa·m1/2, and 225.0 N/m at Va = 37%. The tortuosity of crack paths follows a similar trend, becoming more pronounced up to Va = 37% before diminishing. Furthermore, quantitative exponential relationships were established between ft and , , and GIF. A safety warning parameter (δ), derived from the double-K fracture toughness, was proposed to quantitatively assess the pre-peak ductility, with values ranging from 0.88 to 0.72 in this study. The findings offer valuable guidance for optimizing concrete mix design, suggesting that a Va range of 25% to 31% provides an optimal balance between high crack initiation resistance and adequate safety warning capacity for critical engineering structures. - 27 September 2025
- Published by Elsevier in Particuology
- Vol. 107, 1-10
An improved particle neighbor search algorithm with multi-level cache optimization strategy for discrete element method using GPU
- 27 September 2025
- Published by Elsevier in Particuology
- Vol. 107, 1-10
An improved particle neighbor search algorithm with multi-level cache optimization strategy for discrete element method using GPU
- 23 September 2025
- Published by Elsevier in Computers and Geotechnics
- Vol. 189
A novel flexible membrane boundary method based on color function in DEM simulations for triaxial tests of granular materials
- 23 September 2025
- Published by Elsevier in Computers and Geotechnics
- Vol. 189
A novel flexible membrane boundary method based on color function in DEM simulations for triaxial tests of granular materials
- Open Access
A Model Based on Neural Network to Predict Surface Settlement During Subway Station Construction: A Case Study of the Dongba-Zhongjie Station in Beijing, China
Surface settlement prediction is crucial to assess the safety of subway station construction. To overcome challenges such as missing on-site settlement data and a limited number of monitoring points, this study proposes a composite prediction model that integrates finite element analysis, a time-series interval GA-BP neural network, and variational mode decomposition (VMD) techniques. Using the Dongba-zhongjie Station in Beijing Subway Line 3 as a case study, surface settlement predictions were made for both typical monitoring points and randomly selected feature points throughout the construction period, followed by validation. The experimental results show that the root mean square error (RMSE) of the finite element model is 15.77%, confirming the model’s effectiveness. As excavation progressed through the second underground floor and bottom plate, the settlement at the maximum settlement point began to rebound, and the structure tended to stabilize. At this stage, construction of the comprehensive utility tunnel above the station can proceed concurrently.
Open AccessA Model Based on Neural Network to Predict Surface Settlement During Subway Station Construction: A Case Study of the Dongba-Zhongjie Station in Beijing, China
Surface settlement prediction is crucial to assess the safety of subway station construction. To overcome challenges such as missing on-site settlement data and a limited number of monitoring points, this study proposes a composite prediction model that integrates finite element analysis, a time-series interval GA-BP neural network, and variational mode decomposition (VMD) techniques. Using the Dongba-zhongjie Station in Beijing Subway Line 3 as a case study, surface settlement predictions were made for both typical monitoring points and randomly selected feature points throughout the construction period, followed by validation. The experimental results show that the root mean square error (RMSE) of the finite element model is 15.77%, confirming the model’s effectiveness. As excavation progressed through the second underground floor and bottom plate, the settlement at the maximum settlement point began to rebound, and the structure tended to stabilize. At this stage, construction of the comprehensive utility tunnel above the station can proceed concurrently.
- 27 March 2025
- Published by Elsevier in Theoretical and Applied Fracture Mechanics
- Vol. 138
Fracture process zone of dynamic cracks in brittle materials based on material configurational mechanics
- 27 March 2025
- Published by Elsevier in Theoretical and Applied Fracture Mechanics
- Vol. 138
Fracture process zone of dynamic cracks in brittle materials based on material configurational mechanics
- 1 March 2025
- Published by Elsevier in Engineering Fracture Mechanics
- Vol. 319
A configurational stress-based model to predict mixed-mode fracture of rock under different environments
- 1 March 2025
- Published by Elsevier in Engineering Fracture Mechanics
- Vol. 319
A configurational stress-based model to predict mixed-mode fracture of rock under different environments
- 24 July 2024
- Published by Elsevier in Theoretical and Applied Fracture Mechanics
- Vol. 133
Modeling of the fracture behaviors of concrete using 3D discrete element method with softening effect
- 24 July 2024
- Published by Elsevier in Theoretical and Applied Fracture Mechanics
- Vol. 133
Modeling of the fracture behaviors of concrete using 3D discrete element method with softening effect
- 25 May 2024
- Published by Elsevier in Theoretical and Applied Fracture Mechanics
- Vol. 132
Crack-tip plastic zone and initiation mechanism of rock based on Eshelby stress
- 25 May 2024
- Published by Elsevier in Theoretical and Applied Fracture Mechanics
- Vol. 132
Crack-tip plastic zone and initiation mechanism of rock based on Eshelby stress