Myung-June Park

Mixed Analog/Digital Gonadotrope Biosynthetic Response to Gonadotropin-releasing Hormone

Mammalian reproduction requires gonadotropin-releasing hormone (GnRH)-mediated signaling from brain neurons to pituitary gonadotropes. Because the pulses of released GnRH vary greatly in amplitude, we studied the biosynthetic response of the gonadotrope to varying GnRH concentrations, focusing on extracellular-regulated kinase (ERK) phosphorylation and egr1 mRNA and protein production. The overall average level of ERK activation in populations of cells increased non-cooperatively with increasing GnRH and did not show evidence of either ultrasensitivity or bistability. However, automated image analysis of single-cell responses showed that whereas individual gonadotropes exhibited two response states, inactive and active, both the probability of activation and the average response in activated cells increased with increasing GnRH concentration. These data indicate a hybrid single-cell response having both digital (switch-like) and analog (graded) features. Mathematical modeling suggests that the hybrid response can be explained by indirect thresholding of ERK activation resulting from the distributed structure of the GnRH-modulated network. The hybrid response mechanism improves the reliability of noisy reproductive signal transmission from the brain to the pituitary.

Fischer–Tropsch synthesis on cobalt/Al2O3-modified SiC catalysts: effect of cobalt–alumina interactions

The effects of Al2O3 modification of the beta-SiC support on Fischer–Tropsch synthesis (FTS) catalysts were investigated in terms of the dispersion of cobalt particles through different metal support interactions for higher CO conversion and stability. The SiC support was previously modified using a alumina precursor with 0–15 wt% in order to increase the surface area and to enhance a dispersion of Co3O4 particles. The alumina-modified SiC support at an optimal amount of Al2O3 showed higher catalytic performance and stability compared with the unmodified Co–SiC catalyst. The optimum concentration of alumina for higher catalytic performance is found to be around 10 wt% Al2O3 on the SiC support. The observed higher CO conversion and stability are mainly attributed to the formation of adjacent cobalt–alumina complexes through an increase of cobalt dispersion and the enhanced interactions between cobalt and alumina particles. The enhanced interactions of cobalt–alumina are also responsible for a lower aggregation of metallic cobalt particles by forming smaller cobalt particles around 13 nm in size, which was confirmed using X-ray photoelectron spectroscopy, temperature-programmed reduction and TEM analyses mainly.

Modelling and analysis of pre-combustion CO2 capture with membranes

A pre-combustion CO2 capture system was modelled with three different membranes. It comprised an amine absorber for the elimination of H2S, high- and low-temperature water gas shift reactors for the conversion of CO to CO2 and a membrane to keep over 90% of the CO2 in the retentate. The absorber and equilibrium reactors were modelled using rigorous models, while the partial least squares model was used for three different types of membranes to predict the experimental results. The effectiveness of the modelling of the reactors and membranes was tested through comparison of simulated results with experimental data. The effects of operating pressure and membrane type are also discussed, and it was found that using a smaller membrane under high pressure lowered the membrane’s cost but also lowered energy recovery.

Kinetics modeling for the mixed reforming of methane over Ni-CeO2/MgAl2O4 catalyst

Abstract Kinetics model was developed for the mixed (steam and dry) reforming of methane, which is useful for the control of H 2 /CO ratio. The equilibrium constants of reaction rate were determined using the experimental equilibrium data at different reaction temperatures, while the forward reaction rate constants were estimated using the experimental data under non-equilibrium (high inert fraction and high space velocity) conditions. The comparison between calculated and experimental data clearly showed that the developed model described satisfactorily, and further analysis using the parametric sensitivity determined the wall temperature and CO 2 fraction in the feed gas as effective parameters for the manipulation of CH 4 conversion and H 2 /CO ratio of synthesis gas under the equilibrium condition. Meanwhile, the inert fraction, rather than the residence time, was selected as additional parameter under non-equilibrium condition.

Property evaluation and control in a semibatch MMA/MA solution copolymerization reactor

This article deals with the property control of polymer product in a semibatch MMA/MA copolymerization reactor by applying the extended Kalman filter (EKF) based nonlinear model predictive control (MPC). In addition to the feeding of the more reactive monomer, the solvent is continuously supplied so as to maintain the viscosity of the reaction mixture within a reasonable range. This measure then provides favorable conditions not only for the on-line estimation with the EKF but also for the performance of the EKF based nonlinear MPC. Indeed, the improved performance of the state estimator is confirmed by experiment under isothermal and nonisothermal conditions over a prolonged reaction time. On the basis of the estimated state, the EKF based nonlinear MPC is implemented to the semibatch reactor to produce copolymers with desired properties. The experimental results clearly demonstrate the superiority of the present control strategy compared to the result of our previous work obtained without having additional feed of solvent.

Kinetic parameter estimation for the MMA/MA copolymerization system

The mathematical model for a batch methyl methacrylate (MMA) and methyl acrylate (MA) copolymerization system was simplified by applying the pseudo-kinetic rate constant method and used for the estimation of parameters for various reaction rate constants. For this, the polymerization experiment was conducted under a variety of reaction conditions and the Levenberg-Marquardt method was employed. The state variables selected for the parameter estimation were the solid content and the number and weight average molecular weights. The validity of the estimated parameters was corroborated by conducting experiments under different reaction conditions and the newly estimated parameter values were found to be superior to the ones reported in the literature. Thus the kinetic parameters estimated in this study may be used to predict the properties of polymer product obtained by solution MMA/MA copolymerization.

Nonlinear Model Order Reduction and Control of Particle Size Distribution in a Semibatch Vinyl Acetate/Butyl Acrylate Emulsion Copolymerization Reactor

This paper addresses the control of the full particle size distribution (PSD) in a semibatch emulsion copolymerization reactor. The numerical approximation of a fundamental population balance model results in a high order system to accurately describe the distribution of particle size; therefore, model order reduction is required. Pseudo random input signals are input to the mechanistic model to generate a data set which covers the reachable region of the system, on the basis of which the transformation matrices are calculated by principal component analysis (PCA). A linear time varying model with reduced order obtained from the transformation matrices is augmented in the prediction equation of linear model predictive control. The performance of the controller is evaluated to drive the particle size distribution at the final time of the batch to the desired distribution in the presence of disturbances.

LMI-based robust model predictive control for a continuous MMA polymerization reactor

Abstract A linear matrix inequality (LMI)-based robust model predictive control (MPC) is applied to a continuous stirred-tank reactor for the polymerization of methyl methacrylate (MMA). The polytopic model is constructed to predict the responses to various control input sequences by using Jacobians of uncertain nonlinear model at several operating points and the controller design is characterized as the problem of minimizing an upper bound on the ‘worst-case’ infinite horizon objective function subject to constraints on the control input and plant output. Simulation studies under different conditions are conducted to validate the feasibility of the optimization problem and evaluate the applicability of such a control scheme. Simulation results show that, despite the model uncertainty, the LMI-based robust model predictive controller performs quite satisfactorily for the property control of the continuous polymerization reactor and guarantees the robust stability.

Polymer property control in a continuous styrene polymerization reactor using model-on-demand predictive controller

The model-on-demand (MoD) framework was extended to the model predictive control (MPC) to design a multiple variable model-on-demand predictive controller (MoD-PC). This control algorithm was applied to the property control of polymer product in a continuous styrene polymerization reactor. For this purpose, a local auto-regressive exogenous input (ARX) model was constructed with a small portion of data located in the region of interest at every sample time. With this model an output prediction equation was formulated to calculate the optimal control input sequence. Jacket inlet temperature and conversion were chosen as the elements of regressor state vector in data searching step. Simulation studies were conducted by applying the MoD-PC to MIMO control problems associated with the continuous styrene polymerization reactor. The control performance of the MoD-PC was then compared with that of a nonlinear MPC based on the polynomial auto-regressive moving average (ARMA) model for disturbance rejection as well as for setpoint-tracking. As a result, the MoD-PC was found to be an effective strategy for the production of polymers with desired properties.

Computational fluid dynamics modeling and analysis of Pd-based membrane module for CO2 capture from H2/CO2 binary gas mixture

A Pd-based membrane module for the capture of CO2 from a H2/CO2 binary gas mixture was considered, and computational fluid dynamics modeling was used to predict the module performance. Detailed models of momentum and mass balances, including local flux as a function of local linear velocity, satisfactorily described CO2 fraction in a retentate tube when compared to the experimental data under various feed flow rates. By using the model, several cases having different geometries, including the location and diameter of feed tube and the number and location of the feed and retentate tubes, were considered. Among tested geometries, the case of two feed tubes with each offset by an angle, θ, of 45° from the center line, and a feed tube diameter of 2.45mm showed the increase of the feed flow rate up to 11.80% compared to the reference case while a CO2 fraction of 90% in the retentate, which was the criterion for effective CO2 capture in the present study, was guaranteed. This would result in a plausible reduction in capital expenditures for the CO2 capture process.