ISSN 1008-5548

CN 37-1316/TU

2024年30卷  第1期
<返回第1期

料仓落料过程中不同粒径颗粒的混合均匀性

Mixing uniformity of particles of different particle sizes during blanking condition of silo


褚嘉玮, 胡力群, 韩振强, 邵 威

(长安大学 公路学院, 特殊地区公路工程教育部重点实验室, 陕西 西安 710064)


引用格式:

褚嘉玮, 胡力群, 韩振强, 等. 料仓落料过程中不同粒径颗粒的混合均匀性[J]. 中国粉体技术, 2024, 30(1): 79-89.

CHU J W, HU L Q, HAN Z Q, et al. Mixing uniformity of particles of different particle sizes during blanking condition of silo [J]. China Powder Science and Technology, 2024, 30(1): 79-89.

DOI:10.13732 / j.issn.1008-5548.2024.01.008

收稿日期: 2023-07-04,修回日期:2023-11-10,上线日期:2023-12-16。

基金项目:中央高校基本科研项目,编号:300102211307。

第一作者简介:褚嘉玮(1999—),男,硕士生,研究方向为路面基层材料研发。 E-mail: cjw@chd.edu.cn。

通信作者简介:胡力群(1971—),男,教授,博士,交通部交通科技英才,博士生导师,研究方向为路面结构与材料。 E-mail: hlq123@126.com。


摘要:【目的】研究厂拌法施工过程中料仓落料环节对粒料混合均匀性产生的影响。 【方法】采用离散单元法和多因素Box-Behnken 响应面模型,探讨在落料过程中粒料的混合均匀性;设计网格均匀性指数(grid uniformity index,σg)、 竖向离析指数(vertical segregation index, Sv)、 中心区域比例差值(center percentage difference,Pc)指标,用于评价竖向、水平和网格划分粒料均匀性;研究贮料仓卸料漏斗的倾角、 漏斗开口大小、 颗粒间滚动摩擦系数对落料过程中粒料均匀性的影响。 【结果】在颗粒间滚动摩擦系数为 0. 07 时,选择倾角为 55°、 漏斗出口边长为 400 mm 的贮料仓漏斗,可以获得较为均匀的粒料分布。 【结论】使用 Sv、 Pc 和 σg 指标可以有效地评估落料过程中粒料的分布情况;漏斗倾角、漏斗开口大小、颗粒间滚动摩擦系数对粒料均匀性具有显著影响。

关键词: 料仓; 道路材料; 均匀性; 离散元

Abstract

Objective In order to improve the characteristics of graded gravel materials, the study explores the influence of the material bin discharge phase on the uniformity of granular materials in the plant mixing construction process. The findings offer valuable insights for optimizing the discharge process and achieving superior material mixing.

Methods In this paper, the vertical segregation index Sv, center percentage difference Pc, and grid uniformity index σg metrics were developed to evaluate vertical, horizontal, and grid-generated particle uniformity. The grid uniformity index was defined as quantifying the uniformity of granular material distribution within a defined grid. By calculating the standard deviation of particle counts in each grid, a measure of how evenly granular materials are distributed was obtained. The vertical segregation index measures the extent of vertical segregation within the material, which calculates the difference between the mean Z-coordinate of particles within a single layer. When Sv was equal to 0, vertical uniformity was considered good. When Sv is less than 0, it indicates that particles in this grade tend to be in the lower part of the material. Conversely, when Sv is greater than 0, it suggests that particles in this grade tend to be in the upper part of the material. Center percentage difference assesses the distribution of

granular material in the center region of the container versus the peripheral region. It calculates the difference in the central percentage of two types of particles. A Pc value of 0 indicates perfect material uniformity. A Pc

value greater than 0 indicates that the particles involved in the calculation are more concentrated in the core region of the material, and A Pc value less than 0 suggests that the particles involved in the calculation are distributed around the periphery of the material. Secondly, the discrete element method (DEM) and a multi-factor Box-Behnken response surface model, containingthree continuous factors, were employed to examine the uniformity of granular materials during the discharge process. Thirdly, using particles with radii of 6mm and 10 mm, an initial uniform material distribution was established. By varying the funnel’s inclination angle (α), funnel outlet size ( L), and inter-particle rolling friction coefficient (μ), simulations were conducted to explore different segregation scenarios and identify the most uniform particles. Furthermore, the reliability of the fitted equations obtained from the response surface experiments was conducted through an additional 17 sets of simulation experiments. Finally, according to the results of numerical simulation, the parameters of silo were optimized and conducted via the fitting results.

Results and Discussion Based on the simulations conducted above, an analysis was performed to determine the correlation between the indicator values and the corresponding factors. Regression analysis was then performed using the response surface method, equations were fitted using quadratic functions. Non-significant factors were eliminated to establish a suitable regression equation. For the three indicators corresponding to Sv , Pc, and σG , the R-squared values of the respective equations were 95. 1%, 99. 16%, and 98. 46%, respectively. Fixing two parameters among them allowed the generation of curves that illustrated the relationships between the parameters and the indicators. Additionally, a 95% confidence interval for regression analysis errors was provided. Within the results of the regression equation, the variables Sv and μ exhibited a close correlation, while the variable Pc and σG were more sensitive to L. By computing the indicators from 17 sets of validation experiments and applying them to the error analysis of the regression equation mentioned above, it was evident that all indicator values were obtained from the validation experiments fall within the predicted range. The regression equation accurately predicted the results of discrete element simulation. In conclusion, the relationships between various judgment indicators and influencing factors, with a reliability of 95%, have been obtained. The following results showed that the horizontal homogeneity did not change with the increase of funnel inclination, and the grid partition homogeneity increased and the vertical homogeneity decreased with the funnel outlet size and inter-particle rolling friction coefficient fixed. Upon fixing the funnel inclination angle and inter-particle rolling friction coefficient increasing the funnel outlet size enhanced horizontal and grid partition uniformity, with a temporary decrease and subsequent improvement in vertical uniformity. In addition, upon fixing the funnel outlet size and inclination angle, an increase in inter-particle rolling friction coefficient led to decreased grid partition and vertical uniformity, while improving horizontal uniformity. To optimize discharge parameters for achieving a uniform mixture, the regression equations underwent multifactor response prediction, and recommended values for reliability analysis parameters were provided based on a 95% confidence level. 

Conclusion In this paper, several new segregation assessment criteria and recommendations for the modification of silo funnel shape parameters were reported. These evaluation metrics assessed the uniformity of the mixed material from various perspectives, including the degree of uniformity in the horizontal and vertical directions, as well as the uniformity of grid differentiation. The proposed criteria provided a comprehensive framework for evaluating and enhancing the uniformity of material distribution in material bin discharge phase. Based on the numerical simulations analyzing, it was found that various influencing factors in the simulation experiments had significant correlations with the response indicators, indicating that the metrics had a valuable reference significance. Therefore, to improve the uniformity of graded crushed stone, for particles with an inter-particle rolling friction coefficient of approximately 0. 07, discharge funnel parameters for the batching plant including a funnel’ s inclination angle α = 55° and a funnel outlet length L = 400 mm were recommended. Due to the constraints of the experimental methods for obtaining three-dimensional particle coordinates, the quantitative validation of the discrete element simulation proposed in this study faces challenges when compared to physical experiments. The chosen theoretical models and parameter ranges have limitations in representing real-world situations and need further refinement. In summary, optimizing the discharge phase of material bins during the construction process of a mixing station is crucial for achieving uniform material distribution. The uniformity of graded crushed stone materials is a key factor influencing the quality of road construction. The simulation results obtained in this study provide a basis for improving the design of discharge hoppers in the field of road construction and enhancing construction quality.

Keywords: silo; pavement material; uniformity; discrete element


参考文献(References):

[1]JUNG E A, PARK Y J, KIM J E. Application of continuous manufacturing for solid oral dosage forms [ J]. Journal of Pharmaceutical Investigation, 2023, 53(4): 457-474.

[2]JIMIDAR I S M, SOTTHEWES K, GARDENIERS H, et al. Self-organization of agitated microspheres on various substrates [J]. Soft Matter, 2022, 18(19): 3660-3677.

[3]THAPER R K, FULTON J P, McDONALD T P, et al. Potential of fertilizer segregation during application using spinner disc spreader[J]. Precision Agriculture, 2022, 23(1): 83-100.

[4]WANG L, LI R X, LI H Y. Development of on-line monitoring system for pollution sourse wastewater [ J]. Fresenius Environmental Bulletin, 2022, 31(7): 7448-7454.

[5]CHEN H, PAN Y Y, HAN D D, et al. Evaluating segregation of hot in-place recycled pavement based on surface texture distribution characteristics[J]. International Journal of Pavement Research and Technology, 2023, 16(4): 822-840.

[6]HU T, YUAN J, ZHOU X L, et al. A two-dimensional entropy-based method for detecting the degree of segregation in asphalt mixture[J]. Construction and Building Materials, 2022, 347:128450.

[7] BHARGAVA N, ZAMAN S, SIDDAGANGAIAH A K, et al. Assessment of asphalt mixture performance subjected to production and paving segregation[J]. Journal of Materials in Civil Engineering, 2021, 33(2): 402-467.

[8]中华人民共和国交通运输部. 公路工程名词术语:JTJ 002—1987[S]. 北京: 中国标准出版社, 1988. Ministry of Transport of the People’s Republic of China. Terms of road construction: JTJ 002—1987[ S]. Beijing: Standards Press of China, 1988.

[9]LEE E T, FAN Z, SENCER B. A new approach to detect surface defects from 3D point cloud data with surface normal gabor filter (SNGF)[J]. Journal of Manufacturing Processes, 2023, 92: 196-205.

[10]FAN B H, BOSC F, SMANIOTTO B, et al. Dielectric characterisation of rock aggregates with different grain size distributions[J]. Road Materials and Pavement Design, 2023: 1-14.

[11]CHEN C, CHANDRA S, SEO H. Automatic pavement defect detection and classification using RGB-thermal images based on hierarchical residual attention network[J]. Sensors, 2022, 22(15): 5781.

[12]ZENG S, ZHANG C, ZENG K, et al. Real-time identification of asphalt mixture segregation during paving process using digital imaging technique and four-side static moment[J]. Construction and Building Materials, 2023, 397: 132436.

[13]唐伟, 李宁, 邹晓勇, 等. 基于图像处理技术的厂拌热再生混合料均匀性研究[J]. 重庆交通大学学报(自然科学版), 2023, 42(1): 60-65.

TANG W, LI N, ZOU X Y, et al. Homogeneity of plant-produced RAP mixtures based on DIP technology[J]. Journal of Chongqing Jiaotong University(Natural Science), 2023, 42(1): 60-65.

[14]XIE Y C, YUAN M Y, ZHAO Y L. Analysis of mechanism and evaluation of asphalt mixtures segregation based on DEM simulation[J]. Construction and Building Materials, 2023, 398: 132500.

[15]LIU Y, GONZALEZ M, WASSGREN C. Modeling granular material segregation using a combined finite element method and advection-diffusion-segregation equation model[J]. Powder Technology, 2019, 346: 38-48.

[16]HUANG A N, CHENG T H, HDU W Y, et al. DEM study of particle segregation in a rotating drum with internal diameter variations[J]. Powder Technology, 2021, 378: 430-440.

[17]LI M, AN X, WU Y. Segregation behavior of particles with Gaussian distributions in the rotating drum with rolling regime [J]. Advanced Powder Technology, 2023, 34(2): 103953.

[18]邵威. 基于离散元对混合料卸料和落料过程离析的影响因素研究[D]. 西安: 长安大学, 2022. 

SHAO W. Study on the influencing factors of segregation based on discrete element simulation of falling and discharging process of graded aggregates[D]. Xi’an:Chang’an University, 2022.

[19]CHEN F, JELAGIN D, PARTL M N. Vibration-induced aggregate segregation in asphalt mixtures [ J]. Materials and Structures, 2020, 53(2): 27.

[20]CHIBWE D, EVANS G, DOROODCHI E, et al. Particle near-neighbour separation index for quantification of segregation of granular material[J]. Powder Technology, 2019, 360: 481-492.

[21]BOX G E P, WILSON K B. On the experimental attainment of optimum conditions[ J]. Journal of the Royal Statistical: Society Series B: Methodological, 1951, 13: 1-38.

[22]GUTIERREZ-CH J G, SENENT S, ZENG P, et al. DEM simulation of rock creep in tunnels using rate process theory[J].Computers and Geotechnics, 2022, 142: 104559.

[23]LI J, WANG B, WANG D, et al. A coupled MPM-DEM method for modelling soil-rock mixtures[ J]. Computers and Geotechnics, 2023, 160: 105508.