Wall to particle bed contact conduction heat transfer in a rotary drum using DEM

  • PDF / 1,195,742 Bytes
  • 11 Pages / 595.276 x 790.866 pts Page_size
  • 78 Downloads / 214 Views

DOWNLOAD

REPORT


Wall to particle bed contact conduction heat transfer in a rotary drum using DEM Manogna Adepu1

· Shaohua Chen1 · Yang Jiao1 · Aytekin Gel2 · Heather Emady1

Received: 25 February 2020 / Revised: 10 August 2020 / Accepted: 26 August 2020 © OWZ 2020

Abstract Contact conduction heat transfer behavior in a rotary drum using the discrete element method (DEM)-based simulation codes MFIX-DEM (open-source) and EDEM (commercial) is investigated. Simulations are performed to compare the performance of open-source and commercial code models with experimental data. This study also aims to investigate the effects of particle size distribution (PSD), rotation speed, and rolling friction on overall wall–bed heat transfer using the validated codes. It is found that the variability in the PSD with same mean, μ, and standard deviation, σ , resulted in different heat transfer coefficients. Monodispersed particle beds exhibit better heat transfer when compared to polydispersed beds, because heat transfer is inhibited as the distribution broadens due to segregation. Rotation speed has minimal impact on conduction heat transfer. At lower values of rolling friction, particle circulation in the bed is enhanced and therefore better heat transfer is achieved. Keywords Particle technology · Heat conduction · Discrete element method · Particle size distribution · Rolling friction

1 Introduction Granular materials undergo processing steps that include transportation, drying, and chemical or physical conversion. In several instances, these materials involve heat transfer during processing. The particle heat transfer characteristics are complex due to the continuous moving bed, moving drum wall, and a wide range of process parameters. The measurement systems in rotary drums remain limited, so it is difficult to extract the temperature of each particle continuously throughout experiments. However, developments in scientific computing have significantly advanced our understanding of the fundamental physics involved in such complex processes. Simulation can provide a means for solving the physics-based mathematical equations, to resolve

B

Heather Emady [email protected] Manogna Adepu [email protected]

1

School for Engineering of Matter, Transport, and Energy, Arizona State University, Tempe, AZ 85287, USA

2

School of Computing, Informatics, Decisions Systems Engineering, Arizona State University, Tempe, AZ 85287, USA

the governing physics both spatially and temporally, and to optimize, design, and troubleshoot specific problems. The discrete element method (DEM), a particle-based simulation tool, has become an important means to study particle heat transfer [39]. It is a tool for simulating flow of particles by solving Newton’s equations of motion for individual particles as well as energy balances for each particle, thereby allowing the user to track the position and temperature of each particle. Previous researchers have focused on developing DEM codes to solve complex problems and handle a diverse range of spatial/temporal scales inv