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Energy Institute Developing DOE RAPID-Funded Education Program on Computer-Aided Process Intensification

Published: August 13, 2020
Rapid Advancement in Process Intensification Deployment (RAPID)
Rapid Advancement in Process Intensification Deployment (RAPID)

As a part of an award from the U.S. Department of Energy’s Rapid Advancement in Process Intensification Deployment (RAPID) Institute, which is overseen by the American Institute of Chemical Engineers, the Texas A&M Energy Institute is developing a comprehensive educational and workforce development training program specifically focusing on computer-aided and process systems engineering-based strategies for modeling and simulation of process intensification systems.

The 12-month project, which is titled, “COmputer-aided, Model-based Process intensification LEarning, Training, and Education” (COMPLETE), is a partnership with Chemstations, Inc., and will be led by Primary Investigator M.M. Faruque Hasan, along with Efstratios N. PistikopoulosMahmoud El-HalwagiDebalina SenguptaValentini Pappa, Jeff Sammons, and Konstantinos Pappas from the Texas A&M Energy Institute, as well as Wendy Young from Chemstations.

The COMPLETE project is developing a comprehensive educational and workforce-development training course in the area of modeling and simulation (M&S) for Process Intensification (PI) and Modular Chemical Process Intensification (MCPI). PI and MCPI are relatively new concepts for many practitioners in the chemical industry. Furthermore, conventional chemical engineering education in the areas of process modeling, design, operation, and control does not often adequately address the unique nature of modular and intensified systems.

Leveraging process systems engineering-based expertise within the Texas A&M Energy Institute, including the RAPID SYNOPSIS and DIAMOND projects, the project aims to provide an integrated set of computer-aided educational and training tools to a broad range of audiences that include graduate students, technicians, process engineers, R&D professionals, and operations engineers. Ideally, this computer-aided, model-based learning will accelerate the transfer of knowledge toward the actual deployment of many MCPI technologies.

A pilot course with materials developed within the COMPLETE project is expected to be offered in 2021, with additional modules and components to follow through the AIChE Academy and at Texas A&M University.