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The purpose of this paper is to solve the problem of low conveying efficiency and serious blade wear during vertical screw conveying of cohesive particles. Firstly, the reliability of DEM simulation was verified by comparing the simulated and theoretical values and the influence regularity of different design parameters (rotational speed, pitch, and clearance) on screw conveying characteristics were analyzed based on DEM. In addition, the effect of design parameters on the screw conveying characteristics is identified by ANOVA. Then, the multi-objective optimization model with the both of maximizing the average mass flow rate and minimizing the maximum wear depth of the blade was established using the polynomial fitting regression, which was solved by the non-dominated sorting genetic algorithm (NSGA-II). Finally, the comprehensive evaluation was used to determine the best design parameters. The above research results provide a certain reference for the study of cohesive particle’s vertical screw conveying characteristics and equipment optimization design.
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Tom
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art. no. 13
Opis fizyczny
Bibliogr. 27 poz., rys., tab., wykr.
Twórcy
autor
- School of Mechanical and Energy Engineering, Zhejiang University of Science and Technology, Hangzhou, 310023,China
autor
- School of Mechanical and Energy Engineering, Zhejiang University of Science and Technology, Hangzhou, 310023,China
autor
- School of Mechanical and Energy Engineering, Zhejiang University of Science and Technology, Hangzhou, 310023,China
autor
- Hangzhou Huaxin Mechanical and Electrical Engineering Corporation, Ltd, Hangzhou, 310012,China
autor
- Hangzhou Huaxin Mechanical and Electrical Engineering Corporation, Ltd, Hangzhou, 310012,China
Bibliografia
- 1. Feng Y, Fanghui Y, Li C. Improved Entropy Weighting Model in Water Quality Evaluation. Water Resources Management 2019; 33(6): 2049–2056, https://doi.org/10.1007/s11269-019-02227-6.
- 2. Govender N, Cleary P W, Wilke D N, Khinast J. The influence of faceted particle shapes on material dynamics in screw conveying. Chemical Engineering Science 2021; 243: 116654, https://doi.org/10.1016/j.ces.2021.116654.
- 3. Guo Y. Numerical simulation study of the flow characteristics of gas-solid two-phase flow in vertical screw conveyor. 2015.
- 4. Hærvig J, Kleinhans U, Wieland C et al. On the adhesive JKR contact and rolling models for reduced particle stiffness discrete element simulations. Powder Technology 2017; 319: 472–482, https://doi.org/10.1016/j.powtec.2017.07.006.
- 5. Hou Q F, Dong K J, Yu A B. DEM study of the flow of cohesive particles in a screw feeder. Powder Technology 2014; 256: 529–539, https://doi.org/10.1016/j.powtec.2014.01.062.
- 6. Hu C, Hou Y, Tie Y et al. Influence of Different Bonding Parameters on the Strength of CFRP Laminates with Single Lap Bonding Structure and Optimization. JOURNAL OF MECHANICAL ENGINEERING 2021; 57: 154–165.
- 7. Huang Y J, Nydal O J, Yao B. Time step criterions for nonlinear dense packed granular materials in time-driven method simulations. Powder Technology 2014; 253: 80–88, https://doi.org/10.1016/j.powtec.2013.10.010.
- 8. Karwat B, Rubacha P, Stańczyk E. Optimization of a screw conveyor ’ s exploitation parameters. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2021; 23(2): 285–293. https://doi.org/10.17531/ein.2021.2.8
- 9. Li Z, Liu Y, Wang H et al. Optimization of Ultrasonic Induced Germination of Saposhnikovia divaricate Seeds Based on Plackett-Burman and Box-Behnken Design. Forest engineering 2022; 38: 76–85.
- 10. McBride W, Cleary P W. An investigation and optimization of the “OLDS” elevator using Discrete Element Modeling. Powder Technology 2009; 193(3): 216–234, https://doi.org/10.1016/j.powtec.2009.03.014.
- 11. Mei L, Cheng C, Fan Z. The Mechanical Research of Vertical Screw Conveyor Particle Group Based on the Radial Change of Material Speed. Journal of Physics: Conference Series 2021. doi:10.1088/1742-6596/1952/3/032026, https://doi.org/10.1088/1742-6596/1952/3/032026.
- 12. Minglani D, Sharma A, Pandey H et al. Analysis of flow behavior of size distributed spherical particles in screw feeder. Powder Technology 2021; 382: 1–22, https://doi.org/10.1016/j.powtec.2020.12.041.
- 13. Minglani D, Sharma A, Pandey H, Joshi J B. Analysis of flow behavior of cohesive monosized spherical and non-spherical particles in screw feeder. Powder Technology 2022; 398: 117049, https://doi.org/10.1016/j.powtec.2021.117049.
- 14. Owen P J, Cleary P W. Prediction of screw conveyor performance using the Discrete Element Method (DEM). Powder Technology 2009; 193(3): 274–288, https://doi.org/10.1016/j.powtec.2009.03.012.
- 15. Owen P J, Cleary P W. Screw conveyor performance: Comparison of discrete element modelling with laboratory experiments. Progress in Computational Fluid Dynamics 2010; 10(5–6): 327–333, https://doi.org/10.1504/PCFD.2010.035366.
- 16. Rackl M, Günthner W A. Experimental investigation on the influence of different grades of wood chips on screw feeding performance. Biomass and Bioenergy 2016; 88: 106–115, https://doi.org/10.1016/j.biombioe.2016.03.011.
- 17. Sun H, Ma H, Zhao Y. DEM investigation on conveying of non-spherical particles in a screw conveyor. Particuology 2022; 65: 17–31, https://doi.org/10.1016/j.partic.2021.06.009.
- 18. Tsunazawa Y, Fujihashi D, Fukui S et al. Contact force model including the liquid-bridge force for wet-particle simulation using the discrete element method. Advanced Powder Technology 2016; 27(2): 652–660, https://doi.org/10.1016/j.apt.2016.02.021.
- 19. Tzeng C J, Lin Y H, Yang Y K, Jeng M C. Optimization of turning operations with multiple performance characteristics using the Taguchi method and Grey relational analysis. Journal of Materials Processing Technology 2009; 209(6): 2753–2759, https://doi.org/10.1016/j.jmatprotec.2008.06.046.
- 20. Wang S, Li H, Tian R et al. Numerical simulation of particle flow behavior in a screw conveyor using the discrete element method. Particuology 2019; 43: 137–148, https://doi.org/10.1016/j.partic.2018.01.016.
- 21. Yan H, Liu Y, Li J et al. Simulation and experiment of screening performance of pulverized coal sample device based on EDEM. Engineering Journal of Wuhan University 2021; 54: 658–667.
- 22. Yan H, Li Y, Yuan F et al. Analysis of the screening accuracy of a linear vibrating screen with a multi-layer screen mesh. Strojniski Vestnik/Journal of Mechanical Engineering 2020; 66(5): 289–299, https://doi.org/10.5545/sv-jme.2019.6523.
- 23. Yang W, Meng W, Dai X et al. Continuous medium hypothesis-based study on the screw flight wear model and wear regularity in a screw ship unloader. Transactions of the Canadian Society for Mechanical Engineering 2021; 45(4): 584–593, https://doi.org/10.1139/tcsme-2020-0239.
- 24. Yang W, Meng W, Gao L et al. Analysis of the Screw Flight Wear Model and Wear Regularity of the Bulk Transport in Screw Ship Unloader. Iranian Journal of Science and Technology - Transactions of Mechanical Engineering 2022; 46(1): 15–29, https://doi.org/10.1007/s40997-021-00422-8.
- 25. Yang Z, Xiaoxia S, Wenjun M. Research on the axial velocity of the raw coal particles in vertical screw conveyor by using the discrete element method. Journal of Mechanical Science and Technology 2021; 35(6): 2551–2560, https://doi.org/10.1007/s12206-021-0526-z.
- 26. Yuan J, Li M, Ye F, Zhou Z. Dynamic characteristic analysis of vertical screw conveyor in variable screw section condition. Science Progress 2020; 103(3): 1–16, https://doi.org/10.1177/0036850420951056.
- 27. Zhao R, Guo L, Gao W et al. Structure Optimization Design of Screw Conveyor based on EDEM. Journal of Physics: Conference Series 2022. doi:10.1088/1742-6596/2200/1/012002, https://doi.org/10.1088/1742-6596/2200/1/012002.
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-21818e2b-3b87-433d-8f16-a4c4b8d88a45