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方薇, 周志刚. 落砂成型过程及模型孔隙率影响因素研究[J]. 岩土工程学报, 2019, 41(11): 2086-2093. DOI: 10.11779/CJGE201911014
引用本文: 方薇, 周志刚. 落砂成型过程及模型孔隙率影响因素研究[J]. 岩土工程学报, 2019, 41(11): 2086-2093. DOI: 10.11779/CJGE201911014
FANG Wei, ZHOU Zhi-gang. Sand-fall molding process and influencing factors of model porosity[J]. Chinese Journal of Geotechnical Engineering, 2019, 41(11): 2086-2093. DOI: 10.11779/CJGE201911014
Citation: FANG Wei, ZHOU Zhi-gang. Sand-fall molding process and influencing factors of model porosity[J]. Chinese Journal of Geotechnical Engineering, 2019, 41(11): 2086-2093. DOI: 10.11779/CJGE201911014

落砂成型过程及模型孔隙率影响因素研究

Sand-fall molding process and influencing factors of model porosity

  • 摘要: 以颗粒流程序PFC3D为研究工具,结合室内试验,对于落砂成型过程及成型孔隙率的变化规律进行了研究。首先,对落砂过程及结拱现象进行了分析,提出了一种带底孔筒仓流动模型,设计了优化的方形出砂头方案并将其应用于落砂成型试验;然后,利用PFC3D对落高、出砂头孔径、移动速度等因素对成型孔隙率的影响规律进行了模拟和验证。研究表明:当孔径增大时,一次出漏的颗粒数增多,成型时颗粒与颗粒之间的位置尚来不及调整,粒间孔隙较大。随着出砂头移动速度的增大,堆积层次与冲击次数增加,颗粒间的孔隙将会减小。落高增大导致冲击时的动能增大,密实度因而也随之增大。对于所考察的3种试验因素,物理试验与数值模拟均呈现出相同的影响规律。此外,提出的落砂成型孔隙率多因素相关模型具有很好的适应性。

     

    Abstract: Using the PFC3D as the research tool, accompanied with the laboratory tests, the sand-fall molding process and porosity variation of model are analyzed. Firstly, the falling order and arching phenomenon are studied. Thus, the flow model for the straight hopper with a central bottom hole is suggested, and an optimized square outlet is adopted in the laboratory tests. Subsequently, the PFC3D is utilized to simulate and to verify the influences of height, aperture and velocity of outlet on the model porosity. The research results show that the particles leak densely when the aperture increases, thus, the particles of model can not adjust their positions in time, and the porosity remains large. With the increase of the velocity of outlet, the times of stacking and colliding both increase, and the porosity decreases. When the falling height increases, the kinetic energy is amplified in collision, and the porosity decreases. For the above mentioned factors, both the physical and the numerical tests show the same rules, and the suggested multivariate correlation model has a good adaptability.

     

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