DEM Literature Database

Search parameters are cumulative. Keyword search includes the title and abstract fields.

For copyright reasons only abstracts are available here. A link to the publisher’s website is provided, where access to full papers are subject to the respective publishers’ terms and conditions.

Search Results

We found 2244 result(s).

Title Author(s) Year Source Publisher
Numerical simulation of particle flow and segregation during roller spreading process in additive manufacturing M. Ghadiri, M. Pasha, W. Nan 2019 Powder Technology Elsevier
Wireless detector for translational and rotational motion of spherical-particle flow H. Yang, P. Kong, Q. C. Sun, Q. Chen, R. Li, Y.H. Zhu, Y.J. Zhang, Y.S. Hua 2019 Powder Technology Elsevier
Calibration of micro-scaled mechanical parameters of granite based on a bonded-particle model with 2D particle flow code C. Shi, J. Yang, W. Yang, X. Chen 2019 Granular Matter Springer
The effect of polydispersity on the stresses of cylindrical particle flows H. Jin, J. Hao, J. S. Curtis, Y. Guo, Y. Li 2019 Powder Technology Elsevier
Effect of the cross-section shape of rotating chute on particle flow and burden distribution during the charging process of bell-less top blast furnace with two parallel hoppers G. Zhao, Q. Niu, S. Cheng, W. Xu 2019 Ironmaking & Steelmaking Taylor & Francis
Effect of particle flow dynamics on the fabric evolution in spherical granular assemblies filled under gravity A. Vijayan, R.K. Annabattula 2019 Powder Technology Elsevier
Numerical simulation of wet particle flows in an intensive mixer G. Xie, H. Lu, J. Zhang, S. Gonhg, Z. Zuo 2019 Powder Technology Elsevier
Numerical analysis of similarities of particle flow behavior in stirred chambers B. Cao, F. Jia, X. Meng, Y. Han, Y. Xiao, Y. Zeng 2019 Powder Technology Elsevier
Calibration and verification of DEM parameters for dynamic particle flow conditions using a backpropagation neural network B. Chen, C. Wheeler, F. Ye, J. Hu, K. Chen, W. Chen 2019 Advanced Powder Technology Elsevier
Calibration and Verification of Dynamic Particle Flow Parameters by the Back-Propagation Neural Network Based on the Genetic Algorithm: Recycled Polyurethane Powder B. Pan, D. Zhu, J. Liu, P. He, Y. Fan, Y. Zhu 2019 Materials 2019 MDPI