A methodological framework for the development of feasible CO₂ conversion processes

Roh, Kosan,Lee, Jay H.,Gani, Rafiqul Elsevier 2016 INTERNATIONAL JOURNAL OF GREENHOUSE GAS CONTROL Vol.47 No.-

<P><B>Abstract</B></P> <P>Converting captured CO<SUB>2</SUB> feedstock into valuable chemical products is viewed as one of the potential ways to reduce atmospheric CO<SUB>2</SUB> emission. To this end, a methodological framework is suggested to support the development of feasible CO<SUB>2</SUB> conversion processes that can contribute to the CO<SUB>2</SUB> reduction by replacing non-CO<SUB>2</SUB> utilizing processes or non CO<SUB>2</SUB>-based products. The framework encompasses several execution and decision steps and uses three main criteria, which are the demand availability, CO<SUB>2</SUB> reduction feasibility, and economic feasibility. As an illustrative example, a methanol plant employing combined reforming (CR) of methane reaction is developed. To supply the CO<SUB>2</SUB> feedstock, the aMDEA-based CO<SUB>2</SUB> capture applied to a SMR-based H<SUB>2</SUB> plant is considered. A baseline process is developed and is compared with a non-CO<SUB>2</SUB> utilizing conventional methanol plant (process substitution) and a gasoline production process (product substitution) in terms of the established criteria. For the former, it is verified that the methanol production via combined reforming leads to cheaper unit production cost as well as lower net CO<SUB>2</SUB> emission compared to the conventional methanol plant. For the latter, it is shown that the feasibility of the CO<SUB>2</SUB>-based methanol as an alternative fuel to gasoline highly depends on the type and price of the raw materials. To improve the developed baseline CO<SUB>2</SUB> conversion process further, (1) some of the combined reforming reaction related design variables are fine-tuned using a sensitivity analysis and an equilibrated syngas plot, and (2) utilization of various renewable energy resources for the internal electricity demand is examined.</P> <P><B>Highlights</B></P> <P> <UL> <LI> A methodological framework for feasible CO<SUB>2</SUB> conversion process development. </LI> <LI> Replacement of a conventional methanol plant by the CO<SUB>2</SUB> conversion process. </LI> <LI> Replacement of gasoline by the CO<SUB>2</SUB>-based methanol. </LI> <LI> Reduction of net CO<SUB>2</SUB> emission of the developed process through a graphical approach. </LI> <LI> Utilization of various renewable energy resources for internal electricity demand. </LI> </UL> </P>

Progress and Challenges in Control of Chemical Processes

Lee, Jay H.,Lee, Jong Min Annual Reviews 2014 Annual review of chemical and biomolecular enginee Vol.5 No.-

Approximate dynamic programming approach for process control

Jay H. Lee 제어로봇시스템학회 2010 제어로봇시스템학회 국제학술대회 논문집 Vol.2010 No.10

Many process control and scheduling problems can be formulated as Markov Decision Process (MDP), which represents a multi-stage decision problem under uncertainty. For the past two decades, the Artificial Intelligence (AI) research community has seen significant activities in Approximate Dynamic Programming (ADP), which is developed into an effective method for solving Markov Decision Process (MDP). In this paper, we explore the use of ADP for process control and scheduling applicaitons and examine different design options within ADP, such as the pre-decision state vs. post-decision state value function, parametric vs. nonparametric value function approximator, etc. We show that ADP can be tailored into an effective method to solve stochastic constrained control problems.

Techno-economic and environmental evaluation of CO₂ mineralization technology based on bench-scale experiments

Lee, Ji Hyun,Lee, Jay H.,Park, In Kee,Lee, Chang Hyun Elsevier 2018 Journal of CO₂ utilization Vol.26 No.-

<P><B>Abstract</B></P> <P>This work presents a techno-economic & environmental analysis of a CO<SUB>2</SUB> mineralization process, intended to examine its potential for CO<SUB>2</SUB> reduction and economic feasibility. The CO<SUB>2</SUB> mineralization technology of this study is composed of the CO<SUB>2</SUB> carbonation process and the brine electrolysis process, producing various chemical compounds such as sodium bicarbonate, hydrogen, and chlorine. Notably, the CO<SUB>2</SUB> mineralization process is able to utilize flue gas with a low concentration of CO<SUB>2</SUB> that has not been subjected to CO<SUB>2</SUB> capture processes. For the technical feasibility analysis of the CO<SUB>2</SUB> mineralization process examined in the study, performance evaluation is conducted for a bench-scale CO<SUB>2</SUB> mineralization test unit (2 kg/day CO<SUB>2</SUB> utilization capacity), yielding sodium bicarbonate of over 97% purity. It is also estimated that the CO<SUB>2</SUB> utilization process of this study produces 0.65 tons of CO<SUB>2</SUB> emissions per ton of sodium bicarbonate produced, which indicates a 2.09 ton CO<SUB>2</SUB> reduction compared to the conventional processes which produce 2.74 tons of CO<SUB>2</SUB> emissions for the same amount of sodium bicarbonate production. With these results as a basis, an economic evaluation is conducted for a commercial-scale CO<SUB>2</SUB> utilization plant (sodium bicarbonate production capacity: approximately 5000 tons/year) which utilizes CO<SUB>2</SUB> in flue gas produced from thermal power plants. The evaluation supports the economic feasibility of the process with a benefit/cost ratio (B/C ratio) of 1.12 and internal rate of return (IRR) of 10.4%.</P> <P><B>Highlights</B></P> <P> <UL> <LI> CO<SUB>2</SUB> mineralization test unit yields NaHCO<SUB>3</SUB> of over 97% purity. </LI> <LI> The CO<SUB>2</SUB> utilization process produces 0.65 tons of CO<SUB>2</SUB> emissions per ton of NaHCO<SUB>3</SUB> produced. </LI> <LI> Economic feasibility with a B/C ratio of 1.12 and internal rate of return of 10.4%. </LI> </UL> </P>

Machine learning: Overview of the recent progresses and implications for the process systems engineering field

Lee, Jay H.,Shin, Joohyun,Realff, Matthew J. Elsevier 2018 Computers & chemical engineering Vol.114 No.-

<P><B>Abstract</B></P> <P>Machine learning (ML) has recently gained in popularity, spurred by well-publicized advances like deep learning and widespread commercial interest in big data analytics. Despite the enthusiasm, some renowned experts of the field have expressed skepticism, which is justifiable given the disappointment with the previous wave of neural networks and other AI techniques. On the other hand, new fundamental advances like the ability to train neural networks with a large number of layers for hierarchical feature learning may present significant new technological and commercial opportunities. This paper critically examines the main advances in deep learning. In addition, connections with another ML branch of reinforcement learning are elucidated and its role in control and decision problems is discussed. Implications of these advances for the fields of process and energy systems engineering are also discussed.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Recent advances in deep learning and reinforcement learning (RL) are reviewed. </LI> <LI> Motivation, early problems and recent resolutions of deep learning are discussed. </LI> <LI> The idea of RL and its success in the Go game (<I>a la</I> AlphaGo) are introduced. </LI> <LI> Applicability of RL to multi-stage decision problems in industries is discussed. </LI> <LI> Potential applications and research directions of ML in the PSE domains are given. </LI> </UL> </P>

Control-Relevant Experiment Design for Multivariable Systems

Jay H. Lee 제어로봇시스템학회 1997 제어로봇시스템학회 국내학술대회 논문집 Vol.1997 No.10

Model Predictive Control and Dynamic Programming

Jay H. Lee 제어로봇시스템학회 2011 제어로봇시스템학회 국제학술대회 논문집 Vol.2011 No.10

Control-Relevant Experiment Design for Multivariable Systems

Jay H. Lee 제어로봇시스템학회 1997 제어로봇시스템학회 국내학술대회 논문집 Vol.1 No.10

Implementation of Digital Image Processing for Coastline Extraction from Synthetic Aperture Radar Imagery

Lee, Dong-Cheon,Seo, Su-Young,Lee, Im-Pyeong,Kwon, Jay-Hyoun,Tuell, Grady H. Korean Society of Surveying 2007 한국측량학회지 Vol.25 No.6

Extraction of the coastal boundary is important because the boundary serves as a reference in the demarcation of maritime zones such as territorial sea, contiguous zone, and exclusive economic zone. Accurate nautical charts also depend on well established, accurate, consistent, and current coastline delineation. However, to identify the precise location of the coastal boundary is a difficult task due to tidal and wave motions. This paper presents an efficient way to extract coastlines by applying digital image processing techniques to Synthetic Aperture Radar (SAR) imagery. Over the past few years, satellite-based SAR and high resolution airborne SAR images have become available, and SAR has been evaluated as a new mapping technology. Using remotely sensed data gives benefits in several aspects, especially SAR is largely unaffected by weather constraints, is operational at night time over a large area, and provides high contrast between water and land areas. Various image processing techniques including region growing, texture-based image segmentation, local entropy method, and refinement with image pyramid were implemented to extract the coastline in this study. Finally, the results were compared with existing coastline data derived from aerial photographs.

Sub-Bandgap Optical GIDL Current Method for Extracting the Interface States in the Gate-to-Drain Overlapped Region of MOSFETs

Jay Bok Choi,김동명,이충현,김대환,김대정,D.W. Kang,G.C. Kang,H. T. Kim,이진구,J.U. Lee,K. S. Roh,K. Y. Kim,민경식,S. W. Kim,이순영,S.H. Seo 한국물리학회 2006 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.49 No.4

In this paper, a novel characterization technique is presented to quantitatively extract the energy distribution of interface states in the gate-to-drain overlapped region of MOSFETs. Optical excitation with a sub-bandgap optical power (Eph = 0.95 eV < Eg,Si = 1.12 eV) is applied over the MOSFETs and the gate-induced drain leakage (GIDL) current, named the optically-induced GIDL, and the energy distribution of interface states in the gate-to-drain overlapped region of MOSFETs can be extracted. The increased drain leakage current under sub-bandgap optical illumination is expected to be predominantly caused by optical trap-assisted tunneling (optical GIDL current, IOTAT = IGIDL = ID,opt . ID,dark). Combining analytical models for the GIDL current, which is increased only by trap-assisted tunneling under sub-bandgap photonic excitation, we extracted interface-state density in the gate-to-drain overlapped region, excluding the band-to-band tunneling current in the off-state drain leakages in MOSFETs. Our optical GIDL current measurement is shown to be in good agreement with the results of the charge pumping and photonic gated diode method (PGDM) results for interface states in MOSFETs. In this paper, a novel characterization technique is presented to quantitatively extract the energy distribution of interface states in the gate-to-drain overlapped region of MOSFETs. Optical excitation with a sub-bandgap optical power (Eph = 0.95 eV < Eg,Si = 1.12 eV) is applied over the MOSFETs and the gate-induced drain leakage (GIDL) current, named the optically-induced GIDL, and the energy distribution of interface states in the gate-to-drain overlapped region of MOSFETs can be extracted. The increased drain leakage current under sub-bandgap optical illumination is expected to be predominantly caused by optical trap-assisted tunneling (optical GIDL current, IOTAT = IGIDL = ID,opt . ID,dark). Combining analytical models for the GIDL current, which is increased only by trap-assisted tunneling under sub-bandgap photonic excitation, we extracted interface-state density in the gate-to-drain overlapped region, excluding the band-to-band tunneling current in the off-state drain leakages in MOSFETs. Our optical GIDL current measurement is shown to be in good agreement with the results of the charge pumping and photonic gated diode method (PGDM) results for interface states in MOSFETs.