Screw augers are primary grain conveying equipment in the agriculture industry. Quantitative prediction of grain conveyance using screw augers requires better understanding and measurement of bulk particle-particle and particlerigid- body interactions. Discrete element modeling (DEM) has potential to simulate particle dynamics and flow within a screw auger and thus provide simulation-based guidance for auger design and operating parameters. The objective of this study was to develop a DEM corn model calibration methodology and validation for combine-harvested corn flow in a commercial screw auger. The methodology used a virtual design of experiment (DOE) varying DEM corn parameters and calibration to match grain pile formation expressed in a normalized angle of repose (AOR). DEM corn particle shape was approximated using 1-sphere and clumped spheres (2-sphere, 5-sphere, and 13-sphere) matching the measured physical parameters of equivalent geometrical diameter, 2D axial dimensions, 3D axial dimensions, and detailed CAD-approximated corn dimensions, respectively. For each DEM corn shape approximation, a virtual DOE using Latin square hypercube design with four independent DEM Hertz-Mindlin contact model interaction coefficients was developed. The DEM assembly of particles matching the initial conditions of the AOR test was created in EDEM 2.7. From the quasi-static AOR of corn flow in the AOR tests and EDEM simulations, the mean square error (MSE), a sum of square difference in grain heights in the AOR tests and EDEM simulations, was used as a bulk material dependent response for the calibration process. The DEM 2-sphere corn shape model and the material interaction coefficients showed the minimum MSE (5.31 mm) compared to the 1-sphere, 5-sphere, and 13-sphere models. With the best DEM corn shape model (2-sphere) and DEM model parameters with the minimum MSE, validation of the DEM in predicting corn flow in a commercial screw auger in laboratory tests at two rotational speeds (250 and 450 rpm) was performed and showed good prediction (within 5% relative error) in matching the change in mass flow rate with the change in auger rotational speed.