Development of a Roadmap for Dynamic Process Intensification by Using a Dynamic, Data-Driven Optimization Approach

Publication date: Available online 1 May 2019Source: Chemical Engineering and Processing - Process IntensificationAuthor(s): Seyed Mostafa Safdarnejad, Jake F. Tuttle, Kody M. PowellAbstractThe concept of process intensification involves any improvement in the process or equipment that leads to reduced cost and emissions, increased efficiency, or improved productivity. This paper proposes a novel dynamic process intensification approach that results in similar benefits as the traditional process intensification. The proposed approach utilizes a dynamic optimization approach in improving the operation of a plant. The main contribution of this work includes the development of a dynamic particle swarm optimization algorithm and a data-driven model of the plant while the operational and economical metrics of the plant are compared to the same system when steady-state optimization is practiced. Additionally, a roadmap is developed that enables the practitioners to apply the proposed dynamic process intensification concept to any similar systems. A CSTR reactor is used as the case study to demonstrate the benefits of dynamic process intensification over a static approach. The results demonstrate that a dynamic, data-driven optimization algorithm can achieve similar profit as gradient-based optimization approaches. Additionally, a 59.9% increase in profitability of the plant is observed when a dynamic approach is used for optimization, as opposed to a steady-state approach. This is ...

Source: Chemical Engineering and Processing: Process Intensification - May 2, 2019 Category: Chemistry Source Type: research