Bin Li

Dr. Bin Li


Research Focus & Metrics

Academic Career Length

2Years (2025-Present)

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

Representative Publications

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22 May 2025 in Agriengineering
Verified
Journal Article
Open access
PDF file
BLBin Li
Bin Li
CLChuandong Liu
Chuandong Liu
ZLZebao Li
Zebao Li
YLYuelang Liu
Yuelang Liu
HZHaoping Zhang
Haoping Zhang
ZZZhiheng Zeng
Zhiheng Zeng
Porosity is the key factor affecting a medium’s tortuosity, effective evaporation area coefficient, and ventilation resistance, and further affects the drying efficiency, energy consumption, and drying uniformity in the drying process. To reveal the dynamic variation characteristics of porosity in paddy flow layer, an air convection drying apparatus was established and a mathematical porosity model was established based on response surface methodology. The reliability of the model was verified through EDEM–Fluent coupled digital simulation and experiments. The research results show that under different paddy flow rates vd (0.01 m/s, 0.03 m/s, 0.05 m/s), different moisture contents Mc (14% w.b., 23% w.b., 32% w.b.), different wind speeds vw (0.4 m/s, 0.6 m/s, 0.8 m/s), and different layer thicknesses L (100 mm, 150 mm, 200 mm), the porosity values obtained by the porosity measurement device range from 39.562% to 46.006%. The relative errors between the actual values (εr), the simulation values (εs), and the predicted values (εp) are all within ±1%. Moreover, the obtained mathematical porosity model has high reliability (R2 = 0.968). The Conclusions provide an analysis method for dynamic change characteristic parameters and basic data for the dynamic change of porosity to reduce drying energy consumption, improve the drying power coefficient, and enhance drying quality.

13 March 2025 in Processes
Verified
Journal Article
Open access
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SSShumin Song
Shumin Song
LZLei Zhang
Lei Zhang
YWYu Wu
Yu Wu
WSWeixing Shao
Weixing Shao
WLWenshu Liu
Wenshu Liu
YPYoulun Pang
Youlun Pang
The high damage rate of mechanical cutting and low harvesting efficiency of stem mustard is a major constraint to the sustainable development of its industry. In this study, a reciprocating cutter device tailored for stem mustard was designed for stem mustard under special growing conditions in southwest China. A reciprocating cutter model was developed based on ANSYS/LS-DYNA. Parameters considered include cutting height (X1), angle of incision (X2), forward speed (X3) and single run displacement (X4). Cutting force (F) and cutting power (P) were identified as evaluation metrics. A multifactor quadratic regression model was developed for the orthogonal combinatorial testing procedure using the Box–Behnken design methodology. Cutting force and cutting power obtained by applied derivation of regression equations were 41.4 N and 36.756 W, respectively. Response surface methodology and analysis of variance (ANOVA) were used to determine the optimum operating parameters of the cutting tools used for machining, which were determined to be X1 = 1.45 mm, X2 = 12°, X3 = 0.5 m/s and X4 = 93 mm. The maximum cutting success rate of 94% and the minimum damage rate of 6% on stemmed mustard under the optimum combination of cutting parameters were verified through several field trials. The results of this study provide valuable technical insights into the optimal design of harvesting equipment for stem and leaf mustard to improve the success rate and reduce the damage rate.

1 August 2025 in Agronomy
Verified
Journal Article
Open access
PDF file
CLChuandong Liu
Chuandong Liu
HZHaoping Zhang
Haoping Zhang
ZLZebao Li
Zebao Li
ZZZhiheng Zeng
Zhiheng Zeng
XZXuefeng Zhang
Xuefeng Zhang
BLBin Li
Bin Li
In this study, we aimed to address the lack of systematic research on key collision dynamics parameters (elastic restitution coefficient) in the full mechanization of rapeseed operations, which hinders the development of precision agriculture. In this present work, the restitution coefficient of rapeseed was systematically investigated, and a predictive model (R2 = 0.959) was also established by using Box–Behnken design response surface methodology (BBD-RSM). The results show that the collision restitution coefficient varies in the range of 0.539–0.649, with the key influencing factors ranked as follows: moisture content (Mc) > material layer thickness (L) > drop height (H). The EDEM simulation methodology was adopted to validate the experimental results, and the results show that there is a minimal relative error (−1% < δ < 1%) between the measured and simulated rebound heights, indicating that the established model shows a reliable prediction performance. Moreover, by comprehensively analyzing stress, strain, and energy during the collision process between rapeseed and Q235 steel, it can be concluded that the process can be divided into five stages—free fall, collision compression, collision recovery, rebound oscillation, and rebound stabilization. The maximum stress (1.19 × 10−2 MPa) and strain (6.43 × 10−6 mm) were observed at the beginning of the collision recovery stage, which can provide some theoretical and practical basis for optimizing and designing rapeseed machines, thus achieving the goals of precise control, harvest loss reduction, and increased yields.