Jiale Wang

Mr. Jiale Wang


Research Focus & Metrics

Academic Career Length

4Years (2023-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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9 August 2023 in Materials
Verified
Journal Article
Open access
PDF file
CCChenghao Cui
Chenghao Cui
BABaifu An
Baifu An
HCHeng Cui
Heng Cui
QYQiaomei Yi
Qiaomei Yi
JWJiale Wang
Jiale Wang
To study the flow and strength characteristics of loess-based backfill materials, orthogonal tests were used to design a cemented backfill material combining loess, high-water content materials, cement, and fly ash. By using the range, analysis of variance, and multi-variate regression analysis, influences of four key factors on the initial setting time, diffusivity, compressive strength, and shear strength of the backfill material were investigated. These four factors included the mass concentration of loess water (A), the content of high-water content materials (B), cement content (C), and content of fly ash (D). The results showed that the initial setting time, diffusivity, compressive strength, and shear strength of the backfill material were 13~33 min, 400~580 mm, 0.917–3.605 MPa, and 0.360–0.722 MPa, respectively, all distributed in wide ranges. For the initial setting time, the four factors were listed in descending order as A > D > B > C according to their influences; for diffusivity, the four factors were listed as A > B > C > D; for the compressive strength, the four factors were ranked as A > C > D > B; for the shear strength, the four factors were ranked such that A > C > D > B. With regard to the comprehensive index, the four factors were such that A > B > D > C. That is, the factors were listed in descending order as the mass concentration of loess water, cement content, the content of fly ash, and content of high-water content materials according to their significance in influencing characteristics of the loess-based backfill material. Comprehensive analysis indicated that the fluidity of the material was mainly influenced by the mass concentration of loess water, and the two were negatively correlated. The hydro-consolidation effect of materials with high-water contents accelerated material solidification. The strength of the backfill material was mainly influenced by the cement content while only slightly affected by contents of other materials. In this way, a prediction model for characteristic parameters, namely, fluidity and strength, of the loess-based backfill material under the action of various factors was established.

7 October 2023 in Applied Sciences
Verified
Journal Article
Open access
PDF file
BABaifu An
Baifu An
CCChenghao Cui
Chenghao Cui
JRJinfang Ren
Jinfang Ren
DWDongda Wang
Dongda Wang
JWJiale Wang
Jiale Wang
QYQiaomei Yi
Qiaomei Yi
To study the influences of different mix proportions of materials on the ultrasonic p-wave velocity of coal slime based backfill materials, influences of four factors on the p-wave velocity of specimens were investigated by designing orthogonal tests and taking coal slime as the principal raw material. The four factors included the following: (A) the mass concentration of coal slime, (B) the content of high-water-content material, (C) cement content, (D) and content of fly ash. Test results revealed the following: (1) the ultrasonic p-wave velocity is in the range of 3.916 to 8.319 km/s and various factors are listed in a descending order as A, D, B, and C according to their influences on the ultrasonic p-wave velocity; (2) the ultrasonic p-wave velocity is positively correlated with the compressive strength and shear strength, with correlation coefficients separately of 0.87 and 0.65; (3) the equations for variations in the ultrasonic p-wave velocity under influences of different factors are fitted. The ultrasonic p-wave velocity has a quadratic polynomial relationship with factor A, while following exponential relationships with factors B, C, and D. A predictive model for characteristic parameters of the ultrasonic p-wave velocity of coal slime based backfill materials jointly influenced by the four factors was established based on the fitting equation for variations of single factors and ultrasonic p-wave velocity. The predictive model was then verified.

25 April 2024 in Applied Sciences
Verified
Journal Article
Open access
PDF file
BABaifu An
Baifu An
JSJie Song
Jie Song
JRJinfang Ren
Jinfang Ren
Junmeng LiJunmeng Li
Junmeng Li
CCChenghao Cui
Chenghao Cui
WBWenting Bai
Wenting Bai
This research is designed to investigate the variations in ultrasonic p-wave velocity in various coal based paste fill materials used for recovering standing pillars in closed/closing coal mines, with consideration given to the effects of numerous material-related factors. For this purpose, orthogonal tests were designed. The evaluation was performed on the effects of four variables on the ultrasonic p-wave velocities in samples, using coal grains as the primary material. These variables consisted of the coal grains’ particle size (PA), high-water material content (PB), cement content (PC), and water content (PD). The experimental results show the following: (1) Ultrasonic p-wave velocity of coal based paste fill materials are measured within the range of 1.596 to 2.357 km/s, and these are classified (in descending order) as PD, PB, PC, and then PA, based on their effects on ultrasonic p-wave velocity. (2) Ultrasonic p-wave velocity is positively correlated with compressive strength and shear strength; the correlation coefficients are 0.82 and 0.69, respectively. (3) Changes in the ultrasonic p-wave velocity of coal based paste fill materials, when exposed to various factors, have been characterized by fitted formulae. It was observed that the velocity maintained a quadratic polynomial correlation with factor PB and exponential correlations with factors PA, PC, and PD. The comprehensive predictive model, reflecting the characteristics of the ultrasonic p-wave velocity in response to the combined influence of these four factors, was developed through the utilization of fitted equations pertaining to individual factor variations. Subsequently, this model underwent verification.