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

• Published in: PloS one Vol. 19; no. 10; p. e0308019
• Main Authors: Chen, Lintao, Chen, Rui, Mou, Xiangwei, Liu, Zhaoxiang, Ma, Xu, Wu, Xifeng, Deng, Xiangwu
• Format: Journal Article
• Language: English
• Published: San Francisco Public Library of Science 22.10.2024
• Subjects: Algorithms; Angle of repose; Back propagation networks; Bamboo; Biology and Life Sciences; Biomass energy; Calibration; Compression; Compression ratio; Computer and Information Sciences; Computer simulation; Computers; Contact angle; Dimensional analysis; Discrete element method; Expected values; Flour; Fluidity; Heat treating; Information processing; Market positioning; Methods; Neural networks; Parameters; Particle size; Physical Sciences; Prediction models; Predictions; Pressure molding; R&D; Raw materials; Research & development; Research and Analysis Methods; Shear strength; Simulation; Technology assessment

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...