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The paper describes the problem of designing screw conveyors in terms of determining their exploitation characteristics. Based on the actual values of mass efficiency and power demand obtained in a laboratory experiment, the theoretical design methods and the numerical discrete element method model results were verified. The obtained results have shown that the currently used theoretical methods underestimate the mass efficiency and power demand compared to experiments when typical values of filling rate coefficient and progress resistance coefficient are used. It was also shown that the results of DEM simulations are in good agreement with the experiments in terms of mass efficiency and power demand. Based on the exploitation characteristics determined in DEM simulations for different constructions of the screw and different rotational speeds, multi-objective optimization of the exploitation parameters of the screw was performed in order to minimize the power demand of a screw conveyor and simultaneously maximize its mass efficiency. The optimization results showed that it is possible to find such construction and the rotational speed that will maximize the mass efficiency of the conveyor and keep the power demand low, reducing the exploitation costs of the device.
Czasopismo
Rocznik
Tom
Strony
285--293
Opis fizyczny
Bibliogr. 29 poz., rys., tab.
Twórcy
autor
- AGH University of Science And Technology, al. Mickiewicza 30, 30-059 Kraków
autor
- AGH University of Science And Technology, al. Mickiewicza 30, 30-059 Kraków
autor
- AGH University of Science And Technology, al. Mickiewicza 30, 30-059 Kraków
Bibliografia
- 1. ANSI/CEMA standard no. 350. Screw Conveyors for Bulk Materials. 5th edition 2019.
- 2. Bates L. Entrainment patterns of screw hopper dischargers, transaction of the ASME, Journal of Engineering for Industry 1969; 91: 295-302, https://doi.org/10.1115/1.3591561.
- 3. Carleton A J, Miles J E P, Valentin F H H. A study of factors affecting the performance of screw conveyors and feeders, Journal of Engineering for Industry 1969; 91: 329-333, https://doi.org/10.1115/1.3591565.
- 4. Chudzik A, Warda B. Fatigue life prediction of a radial cylindrical roller bearing subjected to a combined load using FEM. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2020; 22 (2): 212-220, https://doi.org/10.17531/ein.2020.2.4.
- 5. Coetzee C J. Calibration of the Discrete Element Method and the effect of particle shape, Powder Technology 2016; 297: 50-70, https://doi.org/10.1016/j.powtec.2016.04.003.
- 6. Coetzee C J. Review: Calibration of the discrete element method. Powder Technology 2017; 310: 104-142, https://doi.org/10.1016/j.powtec.2017.01.015.
- 7. Cunha A G, Covas J A. Optimization in Polymer Processing. Nova Science, New York, United States 2011.
- 8. Karwat B, Machnik R, Niedźwiedzki J, Nogaj M, Rubacha P, Stańczyk E. Calibration of bulk material model in discrete element method on example of perlite D18-DN, Eksploatacja i Niezawodnosc - Maintenance and Reliability 2019; 21(2): 351-357, https://doi.org/10.17531/ein.2019.2.20.
- 9. Karwat B, Rubacha P, Stańczyk E. Simulational and experimental determination of the exploitation parameters of a screw conveyor. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2020; 22 (4): 741-747, https://doi.org/10.17531/ein.2020.4.18.
- 10. Kozłowski E, Mazurkiewicz D, Żabiński T, Prucnal S, Sęp J. Machining sensor data management for operation-level predictive model. Expert Systems with Applications 2020; 159: 1-22, https://doi.org/10.1016/j.eswa.2020.113600.
- 11. Kretz D, Callau-Monje S, Hitschler M, Hien ., Raedle M, Hesser J. Discrete element method (DEM) simulation and validation of a screw feeder system, Powder Technology 2016; 287: 131-138, https://doi.org/10.1016/j.powtec.2015.09.038.
- 12. Kulinowski P, Kasza P, Zarzycki J. Identification of the operating parameters of the friction drum drive in industrial conditions. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2021; 23 (1): 94-102, https://doi.org/10.17531/ein.2021.1.10.
- 13. Mazurkiewicz D. A Knowledge Base of the Functional Properties of the Conveyor Belt Adhesive Joint for FEM Simulation of Its Stress and Strain State. Journal of Adhesion Science and Technology 2012; 26 (10-11): 1429-1442, https://doi.org/10.1163/156856111X618308.
- 14. Mazurkiewicz D. Computer-aided maintenance and reliability management systems for conveyor belts. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2014; 16 (3): 377-382.
- 15. McBride W, Cleary P W. An investigation and optimization of the 'OLDS' elevator using Discrete Element Modeling. Powder Technology 2009; 193: 216-234, https://doi.org/10.1016/j.powtec.2009.03.014.
- 16. Minglani D, Sharma A, Pandey H, Dayal R, Joshi J B, Subramaniam S. A review of granular flow in screw feeders and conveyors, Powder Technology 2020; 366: 369-381, https://doi.org/10.1016/j.powtec.2020.02.066.
- 17. Mitura A, Gawryluk J, Teter A. Numerical and experimental studies on the rotating rotor with three active composite blades. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2017; 19 (4): 571-579, https://doi.org/10.17531/ein.2017.4.11.
- 18. O'Callaghan, J R. Some experiments on the intake processing a vertical screw conveyor, Journal of Agricultural Engineering 1962; 7(4): 282-287.
- 19. Oreficea L, Khinast J G. DEM study of granular transport in partially filled horizontal screw conveyors, Powder Technology 2017; 305: 347-356, https://doi.org/10.1016/j.powtec.2016.09.067.
- 20. Owen P J, Cleary P W. Prediction of screw conveyor performance using the Discrete Element Method (DEM). Powder Technology 2009; 193: 274-288, https://doi.org/10.1016/j.powtec.2009.03.012.
- 21. Patinge S, Prasad K. Screw feeder performance prediction using Discrete Element Method (DEM), International Journal of Scientific & Engineering Research 2017; 8(3).
- 22. Roberts A W. Design and performance criteria for screw conveyors in bulk solids operation, Bulk Solids Handling 2002; 22(6): 436-444.
- 23. Uematu T, Nakamura S. A study of the screw conveyor, Bulletin of The Japan Society of Mechanical Engineers 1960; 3: 449-455, https://doi.org/10.1299/jsme1958.3.449.
- 24. Walker P, Doroszuk B, Król R. Analysis of ore flow through longitudinal belt conveyor transfer point. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2020; 22 (3): 536-543, https://doi.org/10.17531/ein.2020.3.17.
- 25. Wang S, Haolong H L, Tian R, Wang R, Xu Wang X, Sun Q, Fan J. 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.
- 26. Wang Y, Li T, Muzzio F J, Glasser B J. Predicting feeder performance based on material flow properties, Powder Technology 2017; 308:135-148, https://doi.org/10.1016/j.powtec.2016.12.010.
- 27. White G M, Schaper L A, Ross I J, Isaacs G W. Performance characteristics of enclosed screw conveyors handling shelled corn and soybeans, Research bulletin - Purdue University Agricultural Experiment Station 1962; 740.
- 28. Wodołażski A. Modelling of slurry hydrodynamics with two-blade impeller in tank reactor. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2014; 16(4): 533-536.
- 29. Zareiforoush H, Komarizadeh M H, Alizadeh M R. Performance evaluation of a 15.5 cm screw conveyor during handling process of rough rice (Oriza Sativa L.) grains, Nature and Science 2010; 8: 66-74.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-42cbe4ab-025b-4063-9599-d0ca90610553