Research

Energy System Modeling and Optimization

We are modeling and optimizing complex energy systems to identify optimal decisions and quantify their economic, environmental, and societal impacts. 

Selected Publications

1. Geissler CH*, Ryu J*, Maravelias CT. The Future of Biofuels in the United States Transportation Sector. Renewable and Sustainable Energy Reviews, 192, 114276, 2024. (DOI: https://doi.org/10.1016/j.rser.2023.114276). 

2. Restrepo-Florez JM, Ryu J, Witkowski D, Rothamer D, Maravelias CT. A Systems Level Analysis of Ethanol Upgrading Strategies to Middle Distillates. Energy & Environmental Science, 15, 4376-4388, 2022. (DOI: https://doi.org/10.1039/D2EE02202H).

Process Synthesis, Design, and Optimization

We are developing mathematical programming models for systematic decision makings in process synthesis, process design, and process optimization. 

Selected Publications

1. Ryu J*, Kong L, Pastore de Lima AE, Maravelias CT. A Generalized Superstructure-based Framework for Process Synthesis. Computers & Chemical Engineering, 133, 106653, 2020. (DOI: https://doi.org/10.1016/j.compchemeng.2019.106653).

2. Ryu J*, Maravelias CT. A Generalized Distillation Network Synthesis Model. Chemical Engineering Science, 244, 116766, 2021. (DOI: https://doi.org/10.1016/j.ces.2021.116766).

3. Ryu J*, Maravelias CT. Computationally Efficient Optimization Models for Preliminary Distillation Column Design and Separation Energy Targeting. Computers & Chemical Engineering, 143, 107072, 2020. (DOI: https://doi.org/10.1016/j.compchemeng.2020.107072).

4. Ryu J*, Maravelias CT. Simultaneous Process and Heat Exchanger Network Synthesis Using a Discrete Temperature Grid. Industrial & Engineering Chemistry Research, 58, 6002-6016, 2019. (DOI: https://doi.org/10.1021/acs.iecr.8b04083).

System-level Analysis and Optimization of Chemical Recycling of Waste Platics

We are developing a comprehensive framework to systematically analyze the recycling of waste plastics using diverse chemical recycling technologies. 

Surrogate Model-based Optimization

We are integrating machine learning models into mathematical programming models, opening new ways of modeling and optimizing complex systems. We are also interested in automating lab experiments using Bayesian optimization.