This page has only limited features, please log in for full access.

Dr. Jie Yuan
School of Civil Engineering, Guangzhou University, Guangzhou, China

Basic Info

Basic Info is private.

Research Keywords & Expertise

0 particle breakage
0 calcareous sand
0 MICP
0 Liquefaction characteristic
0 Soft clay engineering property

Honors and Awards

The user has no records in this section


Career Timeline

The user has no records in this section.


Short Biography

The user biography is not available.
Following
Followers
Co Authors
The list of users this user is following is empty.
Following: 0 users

Feed

Journal article
Published: 04 May 2021 in Sustainability
Reads 0
Downloads 0

Lane-changing behavior is one of the most common driving behaviors while driving. Due to the complexity of its operation, vehicle collision accidents are prone to occur when changing lanes. Under the environment of vehicle networking, drivers can obtain more accurate traffic information in time, which can be of great help in terms of improving lane-changing safety. This paper analyzes the core factors that affect the safety of vehicles changing lanes, establishes the weight model of influencing factors of lane-changing behavior using the analytic hierarchy process (AHP), and obtains the calculation method of lane-changing behavior factors (LCBFs). Based on the fuzzy reasoning theory, the headway between the lane-changing vehicle and adjacent vehicles in the target lane was examined, and fuzzy logic lane-changing models were established for both situations (i.e., change to the left and change to the right lane). The fuzzy logic lane-changing models were tested via simulation experiments, and the test results showed that the models have a better warning effect on lane changing (LCBF = 1.5), with an accuracy of more than 90%. Thus, the established model in this paper can provide theoretical support for safety warnings when changing lanes and theoretical support for the sustainable development of transportation safety.

ACS Style

Qiang Luo; Xiaodong Zang; Xu Cai; Huawei Gong; Jie Yuan; Junheng Yang. Vehicle Lane-Changing Safety Pre-Warning Model under the Environment of the Vehicle Networking. Sustainability 2021, 13, 5146 .

AMA Style

Qiang Luo, Xiaodong Zang, Xu Cai, Huawei Gong, Jie Yuan, Junheng Yang. Vehicle Lane-Changing Safety Pre-Warning Model under the Environment of the Vehicle Networking. Sustainability. 2021; 13 (9):5146.

Chicago/Turabian Style

Qiang Luo; Xiaodong Zang; Xu Cai; Huawei Gong; Jie Yuan; Junheng Yang. 2021. "Vehicle Lane-Changing Safety Pre-Warning Model under the Environment of the Vehicle Networking." Sustainability 13, no. 9: 5146.

Journal article
Published: 07 January 2021 in Materials
Reads 0
Downloads 0

Microbial-induced calcite precipitation (MICP) has been a promising method to improve geotechnical engineering properties through the precipitation of calcium carbonate (CaCO3) on the contact and surface of soil particles in recent years. In the present experiment, water absorption and unconfined compressive strength (UCS) tests were carried out to investigate the effects of three different fiber types (glass fiber, polyester fiber, and hemp fiber) on the physical and mechanical properties of MICP-treated calcareous sand. The fibers used were at 0%, 0.10%, 0.15%, 0.20%, 0.25%, 0.30%, 0.35%, and 0.40% relative to the weight of the sand. The results showed that the failure strain and ductility of the samples could be improved by adding fibers. Compared to biocemented sand (BS), the water absorption of these three fiber-reinforced biocemented sands were, respectively, decreased by 11.60%, 21.18%, and 7.29%. UCS was, respectively, increased by 24.20%, 60.76%, and 6.40%. Polyester fiber produced the best effect, followed by glass fiber and hemp fiber. The optimum contents of glass fiber and polyester fiber were 0.20% and 0.25%, respectively. The optimum content of hemp fiber was within the range of 0.20–0.25%. Light-emitting diode (LED) microscope and scanning electron microscope (SEM) images lead to the conclusion that only a little calcite precipitation had occurred around the hemp fiber, leading to a poor bonding effect compared to the glass and polyester fibers. It was therefore suggested that polyester fiber should be used to improve the properties of biocemented sand.

ACS Style

Jitong Zhao; Huawei Tong; Yi Shan; Jie Yuan; Qiuwang Peng; Junling Liang. Effects of Different Types of Fibers on the Physical and Mechanical Properties of MICP-Treated Calcareous Sand. Materials 2021, 14, 268 .

AMA Style

Jitong Zhao, Huawei Tong, Yi Shan, Jie Yuan, Qiuwang Peng, Junling Liang. Effects of Different Types of Fibers on the Physical and Mechanical Properties of MICP-Treated Calcareous Sand. Materials. 2021; 14 (2):268.

Chicago/Turabian Style

Jitong Zhao; Huawei Tong; Yi Shan; Jie Yuan; Qiuwang Peng; Junling Liang. 2021. "Effects of Different Types of Fibers on the Physical and Mechanical Properties of MICP-Treated Calcareous Sand." Materials 14, no. 2: 268.

Journal article
Published: 10 April 2020 in Mathematical Problems in Engineering
Reads 0
Downloads 0

The accuracy of the rear-end collision models is crucial for the early warning of potential traffic accident identification, and thus analyzes of the main factors influencing the rear-end collision relevant models is an active topic in the field. The previous studies have tried to determine the single factor influence on the rear-end collision model performance. Less attention was paid to exploit mutual influences on the model performance. To bridge the gap, we proposed an improved vehicle rear-end collision model by integrating varied factors which influence two parameters (i.e., response time and road adhesion coefficient). The two parameters were solved with the integrated weighting and neural network models, respectively. After that we analyzed the relationship between varied factors and the minimum car-following distance. The research findings support both the theoretical and practical guidance for transportation regulations to release more reasonable minimum headway distance to enhance the roadway traffic safety.

ACS Style

Qiang Luo; Xiaodong Zang; Jie Yuan; Xinqiang Chen; Junheng Yang; Shubo Wu. Research of Vehicle Rear-End Collision Model considering Multiple Factors. Mathematical Problems in Engineering 2020, 2020, 1 -11.

AMA Style

Qiang Luo, Xiaodong Zang, Jie Yuan, Xinqiang Chen, Junheng Yang, Shubo Wu. Research of Vehicle Rear-End Collision Model considering Multiple Factors. Mathematical Problems in Engineering. 2020; 2020 ():1-11.

Chicago/Turabian Style

Qiang Luo; Xiaodong Zang; Jie Yuan; Xinqiang Chen; Junheng Yang; Shubo Wu. 2020. "Research of Vehicle Rear-End Collision Model considering Multiple Factors." Mathematical Problems in Engineering 2020, no. : 1-11.

Research article
Published: 23 January 2020 in Journal of Advanced Transportation
Reads 0
Downloads 0

The reasonable distance between adjacent cars is very crucial for roadway traffic safety. For different types of drivers or different driving environments, the required safety distance is different. However, most of the existing rear-end collision models do not fully consider the subjective factor such as the driver. Firstly, the factors affecting driving drivers’ characteristics, such as driver age, gender, and driving experience are analyzed. Then, on the basis of this, drivers are classified according to reaction time. Secondly, three main factors affecting driving safety are analyzed by using fuzzy theory, and the new calculation method of the reaction time is obtained. Finally, the improved car-following safety model is established based on different reaction time. The experimental results have shown that our proposed model obtained more accurate vehicle safety distance with varied traffic kinematic conditions (i.e., different traffic states, varied driver types, etc.). The findings can help traffic regulation departments issue early warnings to avoid potential traffic accidents on roads.

ACS Style

Qiang Luo; Xinqiang Chen; Jie Yuan; Xiaodong Zang; Junheng Yang; Jing Chen. Study and Simulation Analysis of Vehicle Rear-End Collision Model considering Driver Types. Journal of Advanced Transportation 2020, 2020, 1 -11.

AMA Style

Qiang Luo, Xinqiang Chen, Jie Yuan, Xiaodong Zang, Junheng Yang, Jing Chen. Study and Simulation Analysis of Vehicle Rear-End Collision Model considering Driver Types. Journal of Advanced Transportation. 2020; 2020 ():1-11.

Chicago/Turabian Style

Qiang Luo; Xinqiang Chen; Jie Yuan; Xiaodong Zang; Junheng Yang; Jing Chen. 2020. "Study and Simulation Analysis of Vehicle Rear-End Collision Model considering Driver Types." Journal of Advanced Transportation 2020, no. : 1-11.

Journal article
Published: 26 June 2019 in Materials
Reads 0
Downloads 0

In this paper, an image-based micromechanical model for an asphalt mixture's rheological mechanical response is introduced. Detailed information on finite element (FE) modeling based on X-ray computed tomography (X-ray CT) is presented. An improved morphological multiscale algorithm was developed to segment the adhesive coarse aggregate images. A classification method to recognize the different classifications of the elemental area for a confining pressure purpose is proposed in this study. Then, the numerical viscoelastic constitutive formulation of asphalt mortar in an FE code was implemented using the simulation software ABAQUS user material subroutine (UMAT). To avoid complex experiments in determining the time-dependent Poisson's ratio directly, numerous attempts were made to indirectly obtain all material properties in the viscoelastic constitutive model. Finally, the image-based FE model incorporated with the viscoelastic asphalt mortar phase and elastic aggregates was used for triaxial compressive test simulations, and a triaxial creep experiment under different working conditions was conducted to identify and validate the proposed finite element approach. The numerical simulation and experimental results indicate that the three-dimensional microstructural numerical model established can effectively analyze the material's rheological mechanical response under the effect of triaxial load within the linear viscoelastic range.

ACS Style

Wenke Huang; Hao Wang; Yingmei Yin; Xiaoning Zhang; Jie Yuan. Microstructural Modeling of Rheological Mechanical Response for Asphalt Mixture Using an Image-Based Finite Element Approach. Materials 2019, 12, 2041 .

AMA Style

Wenke Huang, Hao Wang, Yingmei Yin, Xiaoning Zhang, Jie Yuan. Microstructural Modeling of Rheological Mechanical Response for Asphalt Mixture Using an Image-Based Finite Element Approach. Materials. 2019; 12 (13):2041.

Chicago/Turabian Style

Wenke Huang; Hao Wang; Yingmei Yin; Xiaoning Zhang; Jie Yuan. 2019. "Microstructural Modeling of Rheological Mechanical Response for Asphalt Mixture Using an Image-Based Finite Element Approach." Materials 12, no. 13: 2041.

Journal article
Published: 12 January 2019 in Computers and Geotechnics
Reads 0
Downloads 0

The design of soil nail walls in China is dictated by two national technical specifications, namely, Technical Specification for Retaining and Protection of Building Foundation Excavations by China Academy of Building Research (CABR) and Specifications for Soil Nailing in Foundation Excavations by China Association for Engineering Construction Standardization (CECS). Each specification proposes a method for computation of maximum nail loads while the prediction accuracy of the method is still not yet fully assessed. To fill the gap, this study evaluates the accuracies of the two methods using 144 measured nail loads collected from fully instrumented soil nail walls in China. The influences of three wall working conditions on the prediction accuracy of the methods are also examined. The results show that the two default methods overestimate the maximum nail loads by about 40% on-average and the spread in prediction generally ranges from 70% to 100%. However, the prediction accuracy is not significantly influenced by wall working conditions. Simple calibrations with two or three empirical constants are introduced to the two methods to achieve great improvements in prediction accuracy. The calibrated CABR and CECS methods are demonstrated to be unbiased on average and the prediction dispersions are reduced to about 50%.

ACS Style

Jie Yuan; Peiyuan Lin; Rui Huang; Yun Que. Statistical evaluation and calibration of two methods for predicting nail loads of soil nail walls in China. Computers and Geotechnics 2019, 108, 269 -279.

AMA Style

Jie Yuan, Peiyuan Lin, Rui Huang, Yun Que. Statistical evaluation and calibration of two methods for predicting nail loads of soil nail walls in China. Computers and Geotechnics. 2019; 108 ():269-279.

Chicago/Turabian Style

Jie Yuan; Peiyuan Lin; Rui Huang; Yun Que. 2019. "Statistical evaluation and calibration of two methods for predicting nail loads of soil nail walls in China." Computers and Geotechnics 108, no. : 269-279.