Research

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Photocatalytic Conversion of CO2

photo-reactor-co2-monitoring.pngDr. Benson's project takes waste carbon dioxide from large point sources was converted to saleable medium chain alcohols using low-temperature, light activated catalyst powders. These powders were synthesized, characterized, and tested for their ability to convert CO2 and steam to synthesis gas (CO and H2), an intermediate used for Fischer - Tropsch Synthesis.

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Flare Modeling and Optimization

john zink flare tests in tulsa oklahoma

Dr. Chen's project is currently funded by TARC and Lamar Visionary Initiative. Response surface and neural network models were developed to predict the combustion efficiency (CE), opacity, and soot emission of industrial flare operations based on controlled flare test data.

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Abnormal Situation Management and Big Data

head exchanger flow processDr. Chen's project uses process data from wireless sensors and Distributed Control System (DCS) to detect equipment malfunctions early on to facilitate preventive maintenance and to avoid incidents or costly shut-downs. Acoustic and electromagnetic (in addition to density, temperature, and flow) sensors will be explored in the associated experiments.

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Dynamic Modeling and Simulation for Natural Gas Processing, LNG Production, BOG Recovery and Minimization

This research project consists of several broad studies that have been performed at Dr. Xu’s research group for over 10 years, which include research works covering natural gas preprocessing (sweetening, dehydration, NGL recovery, and compression), LNG liquefaction, BOG recovery and minimization, as well as LNG regasification.  our expertise is based on thermodynamic fundamentals and employs both large-scale steady-state and dynamic modeling and simulation techniques to virtually study potential optimization opportunities during the manufacturing process, such as cost minimization, energy saving, emission reduction, as well as control performance improvements.  

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Turnarounds Flare Minimization through Plant-Wide Dynamic Simulation and Optimization

This research has been performed at Dr. Xu’s research group for over 15 years, which has been well recognized and supported by funding agencies from multiple countries. The target of this study is to reduce industrial flare emission sources, energy consumption, as well as downtime of turnaround productions.  The study could also enhance plant safety and operability under abnormal operating conditions.  The project is a triple-win thrust that benefits industrial, environmental, and societal sustainability development.  

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Air-quality Conscious and Cost-effective Emission Control

Emissions from petroleum and chemical process industries (PCPI) is still one of the root causes of transient and localized high-ozone issues in several Texas industrial regions such as Houston-Galveston-Brazoria (HGB), Beaumont-Port Arthur (BPA), and Corpus Christi areas. However, emission reductions at PCPI plants generally need additional facilities and extra operating steps with more energy and material consumptions than before. This will result in substantial capital and operating costs that would impose a heavy economic burden to PCPI plants. Therefore, emission reduction and control in PCPI plants must be both environmentally and economically effective. This project consists of multiple research studies is trying to identify both air-quality conscious and cost-effective emission control strategies to not only improve the air quality in general PCPI regions, but also pursue the minimum cost for industrial emission controls, or even possible to award PCPI plants with more profits.  

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Comprehensive Optimization for Supply Chain Management

This research project consists of three broad studies that have been performed at Dr. Xu’s research group for over 15 years, which  include: (i) port-related supply chain management (PSCM) related to refineries/chemical/ petrochemical industries; (ii) optimal scheduling for decoking operation of ethylene cracking furnace system; and (iii) hoist scheduling for multi-recipe and multi-stage material handling processes.  

 

 

 

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DYNAMIC SIMULATION AND CONTROL OF A NATURAL GAS DEHYDRATION PLANT UNDER UPSET CONDITIONS

This research utilizes modeling, simulation and control tools for improving the operation of a gas dehydration plant. In particular, realistic process conditions are utilized in conjunction with the process simulator ASPENPlus in both steady-state as well as dynamic mode to determine conditions that lead to minimization of product loss under upset conditions.  

 

 

 

 

 

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Establishing an Experimental Method for Measuring Solid-Liquid Work of Adhesion

Dr. Rafael Tadmor's project is funded by National Science Foundation, an experimental method was developed to measure the adhesion between a solid and a liquid. The method was tested on several systems and a comparison with theoretical understanding and literature estimates showed that this is indeed the work of adhesion, measured directly for the first time.

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Faculty Labs and Research Groups

The following Chemical Engineering faculty are currently conducting research with graduate and undergraduate students in research labs and groups:

Dr. Daniel Chen (Carbon Capture, CO2 transport, & sCO2 Power Cycle Modeling, Flare Modeling, Optimization, and Control, Fault Detection and Preventative Maintenance)

Dr. Helen Lou (Sustainable Engineering Technology Lab)

Dr. Peyton Richmond (Process Systems Engineering/ Safety and Reliability Lab)

Dr. Qiang Xu (The Laboratory of Integrated Systems Engineering covering process dynamic modeling, simulation, optimization, process synthesis, production scheduling, process safety, and regional air-quality analysis)