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Thermal runaway has remained a major source of risk to process industry for decades as exothermic reactions can lead to severe consequences such as fire and explosions if not effectively mitigated. Quenching runaway via injection of chemical inhibitors is recognized as a more sustainable and cost-effective response measure compared to the pressure relief system commonly employed in process industry. In the case of free-radical polymerizations, inhibitors as radical scavengers consume the live radicals in the reacting mass to halt the temperature runaway by interrupting the kinetics. While a few experimental tests in both lab and pilot scale have been reported to evaluate the effectiveness of shortstopping, a general and practical design paradigm of inhibition systems remains underexplored. In this work, a multiscale model-based design framework is proposed to unravel the complexity by decoupling the multiphysics at different spatial scales and elucidate the impact of key design factors (e.g., amount of inhibitor, injection timing, and injection locations) on quenching performance to identify the optimal design under conditions of interest. A combined perspective of system design and reaction engineering facilitates both a rapid screening of inhibition recipe, and a detailed investigation of mixing effect during inhibition, which exhibits strong advantages on computational cost than traditional computational fluid dynamics (CFD) models.
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