A multiscale approach to tackle water, energy, and infrastructure challenges for a sustainable future

Shifting toward a circular economy for a sustainable future requires developing, optimizing, and diffusing water and resource recovery technologies. Transitioning these technologies from laboratory to commercial scale is a process that often spans years, if not decades. The conventional approach for biological resource recovery processes involves performing lab-scale experiments in parallel for different designs and conditions. However, such an approach is costly and limited by the number of reactors that can be operated concurrently. In this talk, I will demonstrate an alternative hybrid (computational and experimental) framework that addresses two fundamental challenges in upscaling water and resource recovery technologies: 1) Understanding the processes at each relevant scale and 2) transferring information and understanding across scales. First, I will use an energy-positive wastewater recovery process, the Staged Anaerobic Fluidized-bed Membrane Bioreactor (SAF-MBR), to demonstrate how high-fidelity computational fluid dynamics simulations can be leveraged to improve our understanding of the processes at relevant scales and better constrain the design and operating parameter spaces for the bioreactor. Second, I will present the development of an adaptive hybrid modeling method that enables the transfer of information and understanding across scales. The hybrid approach combines expensive fine-scale and coarse upscaled models to understand and predict the transport of chemicals and precipitation/dissolution reactions in porous media. The proposed hybrid framework has the potential to address challenges in upscaling water and resource recovery technologies from laboratory to commercial scales and accelerate the transition to a circular economy for a sustainable future.

Speaker: Yinuo Yao, Texas A & M University