# Application of EDEM Simulation for Calculating and Optimizing a Closed Coal Fly Ash Screw Conveyor
## 1 Introduction  
The calculation of screw conveyors is approached through various methods [1]. A comprehensive grasp of screw conveyor performance based on continuum mechanical principles is currently lacking. This is primarily due to the intricate nature of flow geometry and the fact that robust continuum models for dense particulate materials are still in the developmental stage. The conveyed materials exhibit a wide range of forms and physical properties, spanning from dry grains to liquid-saturated pastes, and from fine powders to coarse granules [2]. The research employs the methodology proposed by [PERSON] to examine the impact of granular motion on volumetric efficiency concerning theoretical throughput [3]. The outcomes indicate a direct correlation between feeder efficiency, screw rotation speed, and the helix angle of particle motion. This relationship holds true across various speed ranges and incline angles in closed screw conveyors, as evidenced byboth predictive modeling and experimental validation. The study meticulously outlines the parameters and includes detailed analysis diagrams depicting material movement characteristics. These findings reveal intricate interconnections among key dimensions within the screw conveyor, such as screw diameter, screw shaft diameter, screw pitch, rotation speed, incline angle, etc. The properties of the conveyed material, including density, angle of repose, and coefficient of friction, play pivotal roles in the calculation and design of screw conveyors [4]. Several material parameters are particularly noteworthy for screw conveyors. The angle of repose denotes the steepest angle of an unconfined material heap measured from the horizontal plane, indicating the material's heap stability [5]. Additionally, it offers insights into the cohesiveness of granular materials. Material density refers to its mass per unit volume, a crucial factor in determining the conveyor's carrying capacity. The coefficient of friction represents the force that opposes relative motion between two contacting surfaces and is instrumental in assessing the power required to drive the screw conveyor, etc. The DEM (discrete element method) simulation technique hinges on modeling the interactions among material particles themselves, as well as between the material and the screw-conveying apparatus. It operates by simulating the micro-level motion of these particles, adhering to fundamental mechanical principles such as Newton's laws. The DEM simulation software version 8.2.0, Altair EDEM (Engineering Data EDEM), is widely recognized and a product of Altair Engineering, a global leader in computer-aided engineering (CAE) software and technology. Additionally, this software boasts an extensive library encompassing a range of industrial materials, from powders to granules and pellets. Notably, the material properties within the Altair EDEM library closely mirror real-world attributes, rendering them highly applicable in the design and operation of equipment for handling loose materials. The default model within Altair EDEM Software version 8.2.0, as outlined in the Altair EDEM Software manual, is the Hertz-Mindlin (no slip) model, which utilizes Hertzian contact theory to determine the normal force component [6]. Another frequently employed approach is the Mindlin-Dresiewicz model [7], which incorporates damping components for both normal and tangential forces. The damping coefficient is correlated with the coefficient of restitution. The tangential friction force is governed by the Coulomb law of friction. Rolling friction is implemented through a contact-independent model involving constant torque in a specific direction. The DEM method is extensively employed and analyzed from various perspectives. Research [8] delved into the capacity of closed screws across a range of climbing angles. The simulation results were influenced by alterations in capacity at different speeds and angles of the screw conveyor [9]. A study by [PERSON] et al.