An experimental and numerical investigation of particles fluid dynamic flow and energy transfer in a heat exchanger. Part 1. An experimental and numerical granular material flowability study
Waldemar Cieslakiewicz
Samkelo Khumalo
Daniel Madyira
Dewald Scholtz
Jan Sterfontein
Abstract
Flowability is of great importance to a lot of processes especially granular material handling and heat transfer. In the industry achieving the highest heating efficiency of granular material heat exchanger is the most important factor. Heating/cooling area size is one of the critical factors in heat transfer processes and is highly dependent on flowability. The complexity of optimizing flowability can only be solved in two ways, either through experiment or computational modelling. However, the simulation technique is more time efficient and cost effective compared to the experimental analysis technique. Nonetheless, the CFD methodology requires prior validation of the model with the experiment. This study comprises of the experimental and numerical analysis of granular material flowability, and it aims at establishing a balanced flow of spherical silicon particles in a heat exchanger and developing a validated model that can be used for design optimisation. A Discrete Element Method (DEM) is employed in Simcenter STAR CCM+ to analyse the flow behaviour and is validated qualitatively and quantitatively from the experimental data. The results from both the simulation and the experiment exhibit a similar trend, indicating consistency between the two approaches. In both cases, the particle velocities are not uniform within the heat exchanger, as variations are observed across different regions, from 2 mm/s to 9 mm/s. Specifically, particles near the heat exchanger walls experience lower velocities due to higher frictional resistance, while those in the central flow stream, especially close to the outlet, move at relatively higher speeds. Quantitatively, the percentage difference between the simulation and experimental results is 9.53% for particle velocity and 5.61% for mass flow rate, which falls within an acceptable range for computational modelling of granular flow. This level of accuracy indicates that the simulation effectively captures the key flow dynamics within the heat exchanger, making it a reliable tool for further analysis. The study shows convincingly that the model was validated successfully, however investigated heat exchanger is highly inefficient but using the validated model can be optimized.
The study comprises two parts. The first one presents the experimental and numerical particles flow analysis of the fluid (granular material), while the second one focuses on the experimental and numerical energy transfer (heating/cooling) analysis.
Keywords:
DEM, Hertz Mindlin, Lagrangian multiphase, multiphase interactions, rolling resistance, time step, flowabilityReferences
Aela P., Zong L., Esmaeili M., Siahkouhi M., Jing G. 2022. Angle of repose in the numerical modeling of ballast particles focusing on particle-dependent specifications: Parametric study. Particuology, 65: 39-50. https://doi.org/10.1016/j.partic.2021.06.006
Crossref
Google Scholar
Ahmad M., Ismail K.A, MatF. 2016. Impact models and coefficient of restitution: A review. ARPN Journal of Engineering and Applied Sciences, 11(10): 6549-6555. Google Scholar
Balevičius R., Kačianauskas R., MrózR., SielamowiczI.Z. 2011. Analysis and DEM simulation of granular material flow patterns in hopper models of different shapes. Advanced Powder Technology, 22(2): 226-235. https://doi.org/10.1016/j.apt.2010.12.005
Crossref
Google Scholar
Beakawi Al-Hashemi H.M., Baghabra Al-Amoudi O.S. 2018. A review on the angle of repose of granular materials. Powder Technology, 330: 397-417. https://doi.org/10.1016/j. powtec.2018.02.003
Crossref
Google Scholar
Boateng A.A. 1998. Boundary layer modeling of granular flow in the transverse plane of a partially filled rotating cylinder. International Journal of Multiphase Flow, 24(3): 499-521. https://doi. org/10.1016/S0301-9322(97)00065-7
Crossref
Google Scholar
Fernandes A.C.S., Gomes H.C., Campello E.M.B., Pimenta P.M. 2017. A fluid-particle interaction method for the simulation of particle-laden fluid problems. Proceedings of the XXXVIII Iberian Latin American Congress on Computational Methods in Engineering, no. January. https://doi. org/10.20906/cps/cilamce2017-0139
Crossref
Google Scholar
Das S.K., Gautam S.S. 2024. A comprehensive isogeometric analysis of frictional Hertz contact problem. Tribology International, 200: 110078. https://doi.org/10.1016/j.triboint.2024.110078
Crossref
Google Scholar
Grima A.P., Wypych P.W. 2011. Development and validation of calibration methods for discrete element modelling. Granular Matter, 13(2): 127-132. https://doi.org/10.1007/s10035-010-0197-4
Crossref
Google Scholar
Hao T. 2008. Viscosities of liquids, colloidal suspensions, and polymeric systems under zero or non-zero electric field. Advances in Colloid and Interface Science, 142(1-2): 1-19. https://doi. org/10.1016/j.cis.2008.04.002
Crossref
Google Scholar
Jian B., Gao X. 2023. Investigation of spherical and non-spherical binary particles flow characteristics in a discharge hopper. Advanced Powder Technology, 34(5): 104011. https://doi. org/10.1016/j.apt.2023.104011
Crossref
Google Scholar
Jiang H., Nie J., Debanath O.C., Li Y. 2025. Dynamic column collapse of dry granular materials with multi-scale shape characteristics. Computers and Geotechnics, 177(Part A): 106873. https:// doi.org/10.1016/j.compgeo.2024.106873
Crossref
Google Scholar
Kallus Y. 2016. The random packing density of nearly spherical particles. Soft Matter, 12(18): 4123-4128. https://doi.org/10.1039/c6sm00213g
Crossref
Google Scholar
Khan K.U.J., Xu W.J. 2024. The influencing factors and mechanisms of granular flow dynamics. Powder Technology, 449: 120376. https://doi.org/10.1016/j.powtec.2024.120376
Crossref
Google Scholar
Kumar N. 2023. Chapter Eight – Fundamentals of conveyors. In: Transporting operations of food materials within food factories. Eds. S.M. Jafari, N. Malekjani. Woodhead Publishing, Sawston, p. 221-251. https://doi.org/10.1016/B978-0-12-818585-8.00003-9
Crossref
Google Scholar
Li J., Peng F., Li H., Ru Z., Fu J., Zhu W. 2023. Material evaluation and dynamic powder deposition modeling of PEEK/CF composite for laser powder bed fusion process. Polymers, 15(13): 2863. https://doi.org/10.3390/polym15132863
Crossref
Google Scholar
MatWeb. 2024. Silicon, Si. Retrieved from https://www.matweb.com/search/datasheet. aspx?matguid=7d1b56e9e0c54ac5bb9cd433a0991e27&n=1&ckck=1 Google Scholar
McGlinchey D. 2008. Bulk solids handling: equipment selection and operation. Blackwell Publishing, Hoboken. https://doi.org/10.1002/9781444305449
Crossref
Google Scholar
Mindlin R.D., DeresiewiczH. 1953. Elastic spheres in contact under varying oblique forces. Journal of Applied Mechanics, 20(3): 327-344. https://doi.org/10.1115/1.4010702
Crossref
Google Scholar
Qin R., Fang H., Liu F., Xing D., Yang J., Lv N., Chen J., Li J. 2019. Study on physical and contact parameters of limestone by DEM. IOP Conference Series: Earth and Environmental Science, 252(5): 052110. https://doi.org/10.1088/1755-1315/252/5/052110
Crossref
Google Scholar
Santomaso A., Lazzaro P., Canu P. 2003. Powder flowability and density ratios: The impact of granules packing. Chemical Engineering Science, 58(13): 2857-2874. https://doi.org/10.1016/ S0009-2509(03)00137-4
Crossref
Google Scholar
Shi J., Shan Z., Yang H. 2024. Research on the macro- and meso-mechanical properties of frozen sand mold based on Hertz-Mindlin with Bonding model. Particuology, 88: 176-191. https://doi. org/10.1016/j.partic.2023.08.019
Crossref
Google Scholar
Siemens Digital Industries Software. 2023. Simcenter STAR-CCM+ User Guide, version 2302. p. 5184-5218. Retrieved from https://docs.sw.siemens.com/documentation/external/ PL20200805113346338/en-US/userManual/userguide/html/STARCCMP/GUID-28A739CF- 6DE2-4D87-B582-E390B522011C.html# Google Scholar
Stanley-Wood N. 2009. Bulk powder properties: instrumentation and techniques. In: Bulk Solids Handling: Equipment Selection and Operation. Ed. D. McGlinchey. Blackwell Publishing, Hoboken, p. 1-67. https://doi.org/10.1002/9781444305449.ch1
Crossref
Google Scholar
Staron L., Hinch E.J. 2007. The spreading of a granular mass: Role of grain properties and initial conditions. Granular Matter, 9(3-4): 205-217. https://doi.org/10.1007/s10035-006-0033-z
Crossref
Google Scholar
Tahmasebi P. 2023. A state-of-the-art review of experimental and computational studies of granular materials: Properties, advances, challenges, and future directions. Progress in Materials Science, 138: 101157. https://doi.org/10.1016/j.pmatsci.2023.101157
Crossref
Google Scholar
Thornton C., Cummins S.J., Cleary P.W. 2013. An investigation of the comparative behaviour of alternative contact force models during inelastic collisions. Powder Technology, 233: 30-46. https://doi.org/10.1016/j.powtec.2012.08.012
Crossref
Google Scholar
Wang G., Niu Z., Liu Y., Cheng F. 2024. Two novel semi-analytical coefficients of restitution models suited for nonlinear impact behavior in granular systems. Powder Technology, 452: 120501. https://doi.org/10.1016/j.powtec.2024.120501
Crossref
Google Scholar
Wensrich C.M., Katterfeld A. 2012. Rolling friction as a technique for modelling particle shape in DEM. Powder Technology, 217: 409-417. https://doi.org/10.1016/j.powtec.2011.10.057
Crossref
Google Scholar
Zhang P., Bi Z., Yu H., Wang R., Sun G., Zhang S. 2023. Effect of particle surface roughness on the flowability and spreadability of Haynes 230 powder during laser powder bed fusion process. Journal of Materials Research and Technology, 26: 4444-4454. https://doi.org/10.1016/j. jmrt.2023.08.173
Crossref
Google Scholar
Zheng Q.J., Yu A.B. 2015. Modelling the granular flow in a rotating drum by the Eulerian finite element method. Powder Technology, 286: 361-370. https://doi.org/10.1016/j.powtec.2015.08.025
Crossref
Google Scholar
