Dae Ryook Yang

Development and Current Status of the Korea Thermophysical Properties Databank (KDB)

Physical property data, phase equilibrium data, and predictive models are essential parts of process design and operation. With the support of the Ministry of Commerce, Industry and Energy (MOCIE) of Korea, four universities collaborated to develop a thermophysical property databank and to obtain experimental data. In this paper topics related to the development and use of the thermophysical properties and phase equilibrium database are discussed. The databank contains about 4000 pure components and 5000 phase equilibrium data sets. Most of the data were collected along with the experimental uncertainties. Various estimation methods and thermodynamic models were included to calculate properties and phase equilibria. Data can be searched for with a stand-alone program or using an Internet web site. The current status and future prospects of the KDB (Korean Thermophysical Properties Databank) are discussed.

Modeling and Parameter Identification of the Simultaneous Saccharification-Fermentation Process for Ethanol Production

Despite many environmental advantages of using alcohol as a fuel, there are still serious questions about its economical feasibility when compared with oil‐based fuels. The bioethanol industry needs to be more competitive, and therefore, all stages of its production process must be simple, inexpensive, efficient, and “easy” to control. In recent years, there have been significant improvements in process design, such as in the purification technologies for ethanol dehydration (molecular sieves, pressure swing adsorption, pervaporation, etc.) and in genetic modifications of microbial strains. However, a lot of research effort is still required in optimization and control, where the first step is the development of suitable models of the process, which can be used as a simulated plant, as a soft sensor or as part of the control algorithm. Thus, toward developing good, reliable, and simple but highly predictive models that can be used in the future for optimization and process control applications, in this paper an unstructured and a cybernetic model are proposed and compared for the simultaneous saccharification‐fermentation process (SSF) for the production of ethanol from starch by a recombinant Saccharomyces cerevisiae strain. The cybernetic model proposed is a new one that considers the degradation of starch not only into glucose but also into dextrins (reducing sugars) and takes into account the intracellular reactions occurring inside the cells, giving a more detailed description of the process. Furthermore, an identification procedure based on the Metropolis Monte Carlo optimization method coupled with a sensitivity analysis is proposed for the identification of the modelapos;s parameters, employing experimental data reported in the literature.

Experimental simultaneous state and parameter identification of a pH neutralization process based on an extended Kalman Filter

The pH neutralization process is a representative nonlinear process. If a change in feed or buffer streams is introduced, the characteristics of the titration curve are altered and the way of change in titration curve is highly nonlinear. Moreover, if the changes are introduced in the middle of operation, then the nature of the process becomes nonlinear and time-varying. This is the one of the reason why conventional PID controller may fail. Even though the use of buffer solution may alleviate the nonlinearity, the improvement may be limited. A better way to tackle this type of process is to use nonlinear model-based control techniques with online parameter estimation. However, in most cases, the measurements of the process are not adequate enough so that the full state feedback control techniques can be utilized. If the states and crucial parameters are estimated online simultaneously, the effectiveness of the nonlinear state feedback control can be greatly enhanced. Thus, in this study, the capability of simultaneous estimation of states and parameters using Extended Kalman Filter (EKF) are experimentally investigated for a pH neutralization process. The process is modelled using reaction invariants and the concentrations of reaction invariants of the effluent stream (states) and the feed concentrations (parameters) are estimated online. From the comparison of experiments and simulations, it is found that the states and parameters can efficiently be identified simultaneously with EKF so that the estimated information can be exploited by state-feedback control techniques

An explicit solution of the mathematical model for osmotic desalination process

Membrane processes such as reverse osmosis and forward osmosis for seawater desalination have gained attention in recent years. Mathematical models have been used to interpret the mechanism of membrane processes. The membrane process model, consisting of flux and concentration polarization (CP) models, is coupled with balance equations and solved simultaneously. This set of model equations is, however, implicit and nonlinear; consequently, the model must be solved iteratively and numerically, which is time- and cost-intensive. We suggest a method to transform implicit equations to their explicit form, in order to avoid an iterative procedure. In addition, the performance of five solving methods, including the method that we suggest, is tested and compared for accuracy, computation time, and robustness based on input conditions. Our proposed method shows the best performance based on the robustness of various simulation conditions, accuracy, and a cost-effective computation time.

Quantitative estimation of internal concentration polarization in a spiral wound forward osmosis membrane module compared to a flat sheet membrane module

Internal concentration polarization (ICP) within the forward osmosis (FO) membrane affects the reduction of driving force. The magnitude of ICP in the FO membrane was investigated experimentally by measuring water flux in both spiral wound (SW) and flat-sheet (FS) modules with different draw solutions (sodium chloride, sodium sulfate, and disodium phosphate). The FO SW module always shows inferior water flux performance to the FO FS module. The water flux in the FO SW module can be easily estimated by just changing structure parameter. The estimated structure parameter in the FO SW module is 9.1325×10−4 m, which is quite higher than 4.2×10−4 m in the FO FS module. The increase of the structure parameter is attributed to the bending of the FO membrane in the SW module. It can be concluded that a module design such like SW type is not suitable for the FO process.

Cost-based analysis about a newly designed two-staged reverse osmosis process with draw solute

Abstract Draw solution assisted reverse osmosis (DSARO) process is suggested and mathematically modelled in this study. The main concept of the process is osmotic pressure reduction in the RO process by utilizing draw solution which has lower concentration than seawater. Since the pressure requirement of the DSARO process is in the range of BWRO process, the plant capital cost data in BWRO process can be used for cost estimation model. The cost estimation results shows that the specific water cost in DSARO process is more than 10% lower than that of conventional RO process. So the DSARO process can be economically feasible.

Operation strategy of industrial crystallization for the production of 2,3,4,4′-tetrahydroxybenzophenon

To improve the filterability of hydroxybenzophenone crystal, a cooling strategy for the cooling crystallization process is investigated by examining the solubility and growth kinetics of hydroxybenzophenone. The operating strategy is divided into two steps. The first step is to generate the seed by dissolving the raw material and by changing operating conditions. The second step is to grow seeds to the product with desired crystal size distribution. For each part, an operating strategy has been proposed based on the solid-liquid phase equilibrium data in a ternary system and growth kinetic experimental results. The strategy for the first step is experimentally determined under various operating conditions, and the second one is determined by theoretical modeling and model-based optimization. The average crystal size resulting from the proposed strategy has been improved and the filterability has been enhanced compared to an existing strategy used in the industry.

Economic analysis of waste recycle process in perhydropolysiloxazane synthesis

The perhydropolysiloxazane (PHPS) solution has been widely used in the spin-on-dielectric (SOD) process to form silicon oxide layer on a wafer in semiconductor industries. To reduce the whole semiconductor manufacturing cost, the process of PHPS solution production requires high productivity as well as low production cost. A large portion of the PHPS solution production cost is attributed to the large usage of solvents (pyridine and xylene), because more than 20 times of solvents in mass are required to produce a unit mass of high purity PHPS solution. Therefore, we suggest several plausible solvent regeneration processes of organic solvent waste from the PHPS solution production, and their economics is evaluated for comparison.

Optimization of temperature swing strategy for selective cooling crystallization of α-form l-glutamic acid crystals

Abstractl-glutamic acid can be crystallized as metastable α-form and stable β-form crystal. The α-form is desired because of its prismatic shape. Production of α-form of l-glutamic acid by cooling crystallization is not well-defined and α-form solid is commercially not available. In this study, an optimal cooling strategy to selectively produce large and narrowly distributed α-crystals is found by modeling and optimizing the crystallization and polymorphic transformation of l-glutamic acid. The optimal temperature profile is found to be cooling-heating-cooling concept where short nucleation period is followed by growth period in metastable zone. The obtained α-form of L-glutamic acid by optimal strategy had improved mean size, distribution, and purity compared to constant cooling.

Effects of sweating time and cooling strategy on purification of N-vinyl-2-pyrrolidinone using a melt crystallizer

A melt crystallization process is proposed to produce high-purity n-vinyl-2-pyrrolidinone (NVP). To produce high purity products, operation strategy plays key role in the melt crystallizer. We investigated the cooling strategy and optimal sweating time using a batch-type melt crystallizer. A slow cooling followed by a slow heating was found to be an effective temperature profile to produce high purity of NVP. The optimal sweating time was found to be about 20 minutes. For industrial application, a cascade melt crystallizer which consists of four stages was constructed and the proposed crystallization/sweating scheme was applied. Using the new melt crystallizer, NVP more than 99.99% purity can be produced in semi-continuous mode.