Authors : Roger Rumbu; Reggie-John Rumbu

Volume/Issue : Volume 11 - 2026, Issue 8 - August

Google Scholar : https://tinyurl.com/25nhwz7x

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DOI : https://doi.org/10.38124/ijisrt/26aug400

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Abstract : Metallurgical bubbling fluidized-bed roasters couple dense gas–solid hydrodynamics, strongly exothermic sulfide oxidation, interphase heat and mass transfer, solids residence-time distributions, and gas-cleaning constraints. These interactions create a demanding application for digital-twin technology. This perspective proposes a digital-twin framework for such roasters. Zinc-sulfide roasting provides the reference chemistry because it exposes the control conflict among rapid oxidation to ZnO, sulfate formation, thermal uniformity, oxygen availability, zinc-ferrite formation, and agglomeration risk. The framework separates the physical asset, measurement and data-quality layer, high-fidelity multiphysics models, reduced-order online models, state and parameter estimation, diagnostic services, and constrained decision support. A thesis-derived start-up case is integrated as the first operating mode of the twin. In the reported simulations, continuous blowing raised the inert-bed temperature from approximately 298 to 800 K in 1,200 s, while complete-interruption sequences remained within approximately 298–308 K over the first 400 s. These unequal-duration simulations support continuous or near-continuous fluidization as the reference start-up strategy, but they do not establish fuel savings or readiness for concentrate admission. A staged verification and validation programme uses pressure drop, bed expansion, temperature fields, off-gas composition, calcine sulfur speciation, mineralogy, and transient plant tests. The resulting contribution consists of a metallurgically grounded architecture, a cold start-up module supported by preliminary CFD evidence, and testable criteria for progression from numerical comparison to instrumented plant validation.

Keywords : Bubbling Fluidized Bed; Digital Twin; Zinc-Sulfide Roasting; CFD; Reduced-Order Model; Data Assimilation; ModelPredictive Control; Cold Start-Up; Verification and Validation.

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