Calibration of discrete meta-parameters of bamboo flour based on magnitude analysis and BP neural network.

ABSTRACT: In the research and development of technology and equipment for bamboo products deep processing, such as filling, drying, and medicinal use of bamboo flour (BF), the poor compaction and fluidity of BF materials entails the need for accurate discrete element model (DEM) and BF parameters to provide a reference for the simulation of BF processing operationsand the development of related equipment. The average particle size of the 5 types of BFs ranges from 0.136 mm to 0.293 mm, and the small particle size of BF particles causes to the number of BF particles in bamboo processing equipment to reach tens of millions or even billions. When conventional methods are used for simulation, ordinary computers cannot provide the required computing power. To address the aforementioned challenges, this p

SUBMITTER: Chen L 

PROVIDER: S-EPMC11495593 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature