Systematic DEM parameter calibration and validation for co-processed pharmaceutical granules: A polyhedral particle and multi-response optimization approach--颗粒学报PARTICUOLOGY

Systematic DEM parameter calibration and validation for co-processed pharmaceutical granules: A polyhedral particle and multi-response optimization approach

Marcos I. Díaz Muñoz^a, Jacquelina C. Lobos de Ponga^{a b}, Ivana M. Cotabarren^{a b 1 *}, Juliana Piña^{a b 1}

a Planta Piloto de Ingeniería Química (PLAPIQUI, UNS-CONICET), Bahía Blanca, Buenos Aires, Argentina
b Departamento de Ingeniería Química (DIQ), Universidad Nacional del Sur (UNS), Bahía Blanca, Buenos Aires, Argentina

10.1016/j.partic.2026.07.019

Volume 117, October 2026, Pages 315-328

Received 15 May 2026, Revised 1 July 2026, Accepted 24 July 2026, Available online 4 August 2026, Version of Record 12 August 2026.

E-mail: icotabarren@plapiqui.edu.ar

Highlights

• A novel DEM calibration method using polyhedral particles is proposed.

• Multi-response optimization ensures accurate bulk flow properties prediction.

• Simulated AOR and bulk density matched experiments with <3.6% error.

• Drawdown test validation showed <10.8% angles error and 6.9% mass error.

• The approach offers a robust framework for DEM in pharmaceutical modeling.

Abstract

Accurate calibration of input parameters is essential for reliable Discrete Element Method (DEM) simulations of pharmaceutical granular materials. This study presents a systematic approach for the calibration and validation of DEM parameters using co-processed lactose-PEG 6000 granules, represented as polyhedral particles. A Box–Behnken experimental design was employed to evaluate the effects and interactions of key parameters—particle-particle and particle-wall friction, and restitution coefficients—on bulk density and angle of repose. Response surface methodology and multi-objective optimization using desirability functions were applied to identify the optimal parameter set that minimizes deviation from experimental measurements. DEM simulations using the optimized parameters reproduced the bulk behavior of the material with errors below 3.6% in angle of repose and bulk density. Model validation via the Drawdown Test confirmed a good predictive agreement, with errors under 10.8% for flow-related angles and 6.9% for discharged mass. The novelty of this work lies in the calibration of DEM parameters for small-sized pharmaceutical excipients using polyhedral particle representations, offering a more realistic alternative to conventional spherical models, particularly considering the strong influence of particle shape on the flow behavior and DEM calibration of fine powders reported in previous studies (Diviš et al., 2025). The proposed methodology provides a promising calibration framework for DEM parameter calibration in pharmaceutical applications, with the potential to support advanced modeling of powder-based processes such as mixing, milling, and tableting.

Graphical abstract

Keywords

Discrete element method; Pharmaceutical granules; Co-processed excipients; Response surface methodology; Parameter calibration; Polyhedral particles

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