Formation of RAPID Center for Process Modeling

RAPID aims to improve energy efficiency, reduce feedstock waste, and improve productivity by promoting modular chemical process intensification (PI) for processing industries in the U.S. manufacturing sector. To facilitate consistent and objective evaluation of performance metrics of various PI projects, RAPID has established this program to support and/or perform first principles-based process modeling for both baseline and intensified processes.

Investigators

Chau-Chyun Chen
Professor

Date approved

July 01, 2017

Modular Catalytic Desulfurization Units for Sour Gas Sweetening

This project focuses on overcoming manufacturing and supply chain issues associated with a much needed modular technology solution in the gas processing sector. The team will look to take an existing technology for sour gas cleanup (processing scale on order of 1T/day sulfur or 1MMSCFD gas processed) and look to improve benefit vs cost through pilot testing to improve performance and manufacturing design/analysis to determine highest leverage cost reduction steps. The resulting technology will be piloted in a field test to confirm economic assessments.

Investigators

Paul Dimick
General Manager

Focus Areas

Date approved

November 01, 2017
Current TRL
5

Development and Demonstration of Novel Thermal Technologies for Enhanced Air-Side and Two-Phase Performance of CPI-Relevant Heat Exchangers

Almost every process in the chemical and processing industries (CPI) involves heat transfer. Integrated functioning of a variety of heat exchangers with gas, liquid, and vapor/liquid flows of single- and multi-component working fluids, is critical in any processing plant. Improving air and/or process-side performance can significantly reduce energy consumption and capital costs. This project is looking at the novel geometries and mechanical actuation to enhance heat exchanger performance.

Investigators

Ari Glezer

Focus Areas

Current TRL
3

An Experimentally Verified Physical Properties Database for Sorbent Selection and Simulation

This project works to close the gap seen in the intensified process fundamentals area around how to enabling modeling tools through the presentation of useful data for phenomena such as adsorption in complex systems. It looks to use meta-analysis of available databases to determine what data can currently be used with statistical confidence in its accuracy.

Investigators

David S. Sholl
Current TRL
3

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