Modeling of a laboratory cone crusher using the discrete element method
DOI:
https://doi.org/10.29393/ppudec-6btml40006Keywords:
cone crusherResumen
Comminution consists of the progressive reduction of ore size in successive stages. This process is the most energy-consuming in mining, utilizing up to 50% of the total energy used in mineral processing Jeswiet and Szekeres(2016). Among the challenges that this process presents are the inappropriate design of the process control, unwanted segregation and ore variability from Run-of-Mine Asbjörnsson et al. (2022). Therefore, there is growing demand to optimize the performance and profitability of comminution circuits (Bengtsson et al., 2017). This demand has generated a high interest in the modeling and simulation of mining processes, with the aim of achieving the prediction of different operating parameters of different equipment Johansson et al. (2017). The prediction of the behavior of these machines is possible using mathematical models, which can be classified into empirical (Bearman et al., 1991) and mechanistic models (Liu et al., 2018; Evertsson,1999). Some of the latter can be solved numerically, such as those developed using the discrete element method. With the discrete element method, several mining machines have been simulated (Weerasekara et al., 2013).
Citas
J. Jeswiet, A. Szekeres, Energy consumption in mining comminution, Procedia CIRP 48 (2016) 140–145.
G. Asbj¨ornsson, L. M. Tavares, A. Mainza, M. Yahyaei, Different perspectives of dynamics in comminution processes, Minerals Engineering 176 (2022) 107326. doi:10.1016/j.mineng.2021.107326.
M. Bengtsson, G. Asbj¨ornsson, E. Hulth´en, C. Evertsson, Near linear time algorithm to detect community structures in large-scale networks, Minerals Engineering 103-104 (2017) 14–24.
M. Johansson, J. Quist, C. Evertsson, E. Hulth´en, one crusher performance evaluation using dem simulations and laboratory, Phys. Rep.-Rev. Sec. Phys. Lett. 103-104 (2017) 93–101.
R. A. Bearman, R. W. Barley, A. Hitchcock, Prediction of power consumption and product size in cone crushing, Minerals Engineering 4 (1991)1243–1256.
R. Liu, B. Shi, G. Li, H. Yu, Influence of operating conditions and crushing chamber on energy consumption of cone crusher, Energies 11 (2018) 1–16.
C. Evertsson, Modelling of flow in cone crushers, Minerals Engineering 12 (1999) 1479–1499.
N. Weerasekara, M. Powell, P. Cleary, L. Tavares, M. Evertsson, R. Morrison, J. Quist, R. Carvalho, The contribution of dem to the science of comminution, Powder Technology 248 (2013) 3–24.
A. S. Yamashita, A. Thivierge, T. A. Euz´ebio, A review of modeling and control strategies for cone crushers in the mineral processing and quarrying industries, Minerals Engineering 170 (2021) 107036. doi:10.1016/j.mineng.2021.107036.
J. Quist, C. Evertsson, Cone crusher modelling and simulation using dem, Minerals Engineering 85 (2016) 92–105.
K. Bhadani, G. Asbj¨ornsson, M. S. Almefelt, E. Hulth´en, M. Evertsson, Trade-off curves for performance optimization in a crushing plant, Minerals 13 (2023) 1242. doi:10.3390/min13101242.
M. Moncada, P. Toledo, F. Betancourt, C. Rodr´ıguez, Torque analysis of a gyratory crusher with the discrete element method, Minerals 11 (2021) 1–28.
G. Barrios, N. Jim´enez-Herrera, L. Tavares, Simulation of particle bed breakage by slow compression and impact using a dem particle replacement model, Advanced Powder Technology 31 (2020) 2749–2758.
G. Delaney, R. Morrison, M. Sinnott, S. Cummins, P. Cleary, Dem modelling of non-spherical particle breakage and flow in an industrial scale cone crusher, Minerals Engineering 74 (2015) 112–122.
Z. Chen, G. Wang, D. Xue, Q. Bi, Simulation and optimization of gyratory crusher performance based on the discrete element method, Powder Technology 376 (2020) 93–103.
Y. Li, L. Zhao, E. Hu, K. Yang, J. He, H. Jiang, Q. Hou, Laboratory-scale validation of a dem model of a toothed double-roll crusher and numerical studies, Powder Technology 356 (2019) 60–72.
G. Barrios, N. Jim´enez-Herrera, S. Fuentes-Torres, L. Tavares, Dem simulation of laboratory-scale jaw crushing of a gold-bearing ore using a particle replacement model, Minerals 10 (2020) 16.
ESSS, DEM Technical Manual 2022 R1, ESSS Rocky DEM, S.R.L., Florianopolis, Brazil, 2022.
F. André, L. Tavares, Simulating a laboratory-scale cone crusher in dem using polyhedral particles, Powder Technology 372 (2020) 362–371.
M. Lindqvist, C. Evertsson, Improved flow- and pressure model for cone crushers, Minerals Engineering 17 (2004) 1217–1225.
P. Cleary, M. Sinnott, R.Morrison, S. Cummins, G. Delaney, Analysis of cone crusher performance with changes in material properties and operating conditions using dem, Minerals Engineering 100 (2017) 49–70.
L. Tavares, A. Andr´e, F.; Potapov, C. Maliska, Adapting a breakage model to discrete elements using polyhedral particles, Powder Technology 362 (2020) 208–220.
D. Legendre, R. Zevenhoven, Assessing the energy efficiency of a jaw crusher, Energy 74 (2014) 119–130.
N. Jim´enez-Herrera, G. Barrios, L. Tavares, Comparison of breakage models in dem in simulating impact on particle beds, Advanced Powder Technology 29 (2018) 692–706.
O. Walton, R. Braun, Stress calculations for assemblies of inelastic spheres in uniform shear, Acta Mechanica 63 (1986) 73–86.
J. Xie, W. Zhong, Y. Shao, K. Li, Coupling of cfd-dem and reaction model for 3d fluidized beds, Powder Technology 353 (2019) 72–83.
S. Zhang, A. Zs´aki, Effect geometric detail on the outcome of dem simulations with polyhedral particles, Geomechanics and Geoengineering 18 (2022) 426–439.
J. Landauer, M. Kuhn, D. Nasato, P. Foerst, H. Briesen, Particle shape matters – using 3d printed particles to investigate fundamental particle and packing properties, Powder Technology 361 (2020) 711–718.
ASTM E11-20, Specification for Woven Wire Test Sieve Cloth and Test Sieves, Standard, ASTM International, West Conshohocken, 2020. doi:10.1520/E0011-20.
L. M. Tavares, Analysis of particle fracture by repeated stressing as damage accumulation, Powder Technology 190 (2009) 327–339. doi:10.1016/j.powtec.2008.08.011.
L. M. Tavares, Review and Further Validation of a Practical Single-particle Breakage Model, KONA Powder and Particle Journal (2022). doi:10.14356/kona.2022012.
S. C. Angulo, N. V. Silva, D. A. Lange, L. M. Tavares, Probability distributions of mechanical properties of natural aggregates using a simple
method, Construction and Building Materials 233 (2020) 117269. doi:10.1016/j.conbuildmat.2019.117269.
H. Hertz, On the contact of elastic solids, Z. Reine Angew. Mathematik 92 (1881) 156–171.
L. Tavares, R. King, Single-particle fracture under impact loading, International Journal of Mineral Processing 54 (1998) 1–28. doi:10.1016/s0301-7516(98)00005-2.
G. Unland, P. Szczelina, Coarse crushing of brittle rocks by compression, International Journal of Mineral Processing 74 (2004) S209–S217. doi:10.1016/j.minpro.2004.07.030.
C. Wang, Y. Cheng, X. He, M. Yi, Z. Wang, Size effect on uniaxial compressive strength of single coal particle under different failure conditions, Powder Technology 345 (2019) 169–181. doi:10.1016/j.powtec.2019.01.017.
M. Moncada, , F. Betancourt, C. Rodr´ıguez, P. Toledo, Effect of particle shape on parameter calibration for a discrete element model for mining applications, Minerals 13 (2023) 1–17.
A. Forrester, A. Keane, A. S´obester, Engineering design via surrogate modelling: a practical guide (2008).
Descargas
Postado
Categorías
Licencia
Derechos de autor 2026 Fernando Betancourt, Manuel Moncada, Patricio Toledo, Cristian Rodriguez
Esta obra está bajo una licencia internacional Creative Commons Atribución 4.0.
Licencia de uso
El Repositorio distribuye sus contenidos bajo la Licencia Creative Commons Internacional de Atribución (CC BY 4.0), lo que permite que el uso de los documentos depositados en el Repositorio deba regirse de acuerdo a las siguientes condiciones:
- Reconocimiento. Se deben reconocer los créditos de la obra de la manera especificada por el autor o el licenciador.
