• Clean Technology
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• v.28 no.1
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• pp.32-37
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• 2022

Food waste is produced from food factories, food services, and home kitchens. The generated mass reached 5.4 million tons/year in 2020. The basic management technology for such waste has been biological degradation under an anaerobic environment. However, the whole process is intrinsically slow and considerably affected by the inner physicochemical properties of the waste and other surrounding conditions, which makes optimization of the process difficult. The most promising options to counter this massive generation of waste are eco-friendly treatments or recycling. As a preliminary step for these options, attempts were made to evaluate the feasibility and usability of three simulative models based on reaction kinetics. Model (A) predicted relative changes over reaction time for reactant, intermediate, and product. Overall, an increased reaction rate produced less intermediate and more product, thereby leading to a shorter total reaction time. Particle diminishing model (B) predicted reduction of the total waste mass. The smaller particles diminished faster along with the dominant effect of microbial reaction. In Model (C), long-chain cellulose was predicted to transform into reducing sugar. At a standard condition, 48% of cellulose molecules having 10⁵ repeating units turned into reducing sugar after 100 h. Also it was found that the optimal enzyme concentration where the highest amount of remnant sugar was harvested was 1 mg L^-1.

• Membrane Journal
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• v.13 no.4
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• pp.268-282
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• 2003

Pervaporation-facilitated esterification with slow reaction regime was characterized by using a practical model based on non-perfect separation through membrane. A non-perfect separation in which the membrane is not perfectly permselective to water was applied to the model. Thus, membrane selectivity and membrane capability to remove water were included in the simulation model to explain how they influence the membrane-facilitated reaction process and improve the reactor performance. It was shown by simulation that in the reaction systems with non-perfect separation, reaction completion can hardly be achievable when any reactant at initial molar ratio=1 or the less abundant reactant at initial molar ratio>1 permeates through membrane, and the permeation of ester accelerates the forward reaction md increase reaction conversion at any instant through removal of product species like water. The volume change causes concentrating both reactants and products that affect the reaction with time in opposite ways; reactant-concentrating effect is dominant during the initial stage of reaction, increasing the reaction rate, and then concentrating product influences more reaction by decreasing the reaction rate.

• Bulletin of the Korean Chemical Society
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• v.26 no.1
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• pp.139-145
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• 2005

Artificial neural networks (ANNs), for a first time, were successfully developed for the modeling and prediction of solvent effects on rate constant of [2+2] cycloaddition reaction of diethyl azodicarboxylate with ethyl vinyl ether in various solvents with diverse chemical structures using quantitative structure-activity relationship. The most positive charge of hydrogen atom (q$^+$), dipole moment ($\mu$), the Hildebrand solubility parameter (${\delta}_H^2$) and total charges in molecule (q$_t$) are inputs and output of ANN is log k$_2$ . For evaluation of the predictive power of the generated ANN, the optimized network with 68 various solvents as training set was used to predict log k$_2$ of the reaction in 16 solvents in the prediction set. The results obtained using ANN was compared with the experimental values as well as with those obtained using multi-parameter linear regression (MLR) model and showed superiority of the ANN model over the regression model. Mean square error (MSE) of 0.0806 for the prediction set by MLR model should be compared with the value of 0.0275 for ANN model. These improvements are due to the fact that the reaction rate constant shows non-linear correlations with the descriptors.

• Journal of the Korean Mathematical Society
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• v.57 no.1
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• pp.249-281
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• 2020

A reaction-diffusion model with spatiotemporal delay modeling the dynamical behavior of a single species is investigated. The parameter regions for the local stability, global stability and instability of the unique positive constant steady state solution are derived. The conditions of the occurrence of Turing (diffusion-driven) instability are obtained. The existence of time-periodic solutions, the existence and nonexistence of nonconstant positive steady state solutions are proved by bifurcation method and energy method. Numerical simulations are presented to verify and illustrate the theoretical results.

• Journal of the Ergonomics Society of Korea
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• v.11 no.2
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• pp.47-56
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• 1992

In this paper, a mathematical model of learning curve is proposed to study the fi- nger's reaction time. The model is a logarithmic linear type which represents a lear- ning curve appropriately, and parameters are estimated by the linear. The learning coefficient and percentage of a reaction time can easily computed in the mathematical model. This quantitative approach provieds an important information to be used fot the working capqbility qualification of re-employment as well as the adaptability estimation of aged workers.

• Proceedings of the ESK Conference
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• 1992.10a
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• pp.113-120
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• 1992

In this paper, a mathematical model of learning curve is proposed to study the finger's reaction time. The model is a logarithmic linear type which represents a learning curve appropriately, and parameters are estimated by the linear. The learning coefficient and percentage of a reaction time can be easily computed in the mathematical model. This quantitative approach provides an important information to be used for the working capability qualification for re-employment as well as for the adaptability estimation of aged workers.

• International Journal of Concrete Structures and Materials
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• v.6 no.3
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• pp.155-163
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• 2012

In order to predict the neutralization of concrete which is the reaction of carbonation dioxide from the outside and cement hydration product, such as calcium hydroxide and C-S-H, it was studied the numerical analysis method considering change of the pore structure and relative humidity during the neutralization reaction. Diffusion-reaction neutralization model was developed to predict the neutralization depth of concrete with coating finishing material. In order to build numerical analysis models considering outdoor environment and finishing materials, the adaption of proposed model was shown the results of existing outdoor exposure test results and accelerated carbonation test.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.26 no.5
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• pp.209-214
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• 2016

Foam reaction injection molding (FRIM) is a widely used process for manufacturing polyurethane foam with complex shapes. Numerical model for polyurethane foam forming reaction during FRIM process has been intensively investigated by a number of researchers to precisely predict final shapes of polyurethane foams. In this study, we have identified a problem related with a previous theoretical model for polyurethane foam forming reaction. Thus, previous theoretical model was modified based on experimental and computational results.

• Proceedings of the KSME Conference
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• 2007.05b
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• pp.1997-2002
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• 2007

The reformer is one of the most important chemical processes for the production of high purity hydrogen from fossil fuel. This study compares zero-dimensional model with CFD models for reaction analysis of methane-steam reformer. The zero-dimensional model is an empirical equation, however CFD model uses reactions of Arrhenius type. Because the reaction coefficients of the steam-methane catalytic reforming have not been reported before in the form of Arrhenius type, the present study aims to find the appropriate reaction coefficients. The used CFD code is Fluent 6.2 version. Several models are compared for the case of various operating temperature, mass of catalyst and steam to methane ratio.

• Computers and Concrete
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• v.16 no.1
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• pp.37-48
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• 2015

Alkali aggregate reaction affects numerous civil engineering structures and causes irreversible expansion and cracking. This work aims at developing model to predict the potential expansion of concrete containing alkali-reactive aggregates. First, the paper presents the experimental results concerning the influence of particle size of an alkali-reactive aggregate on mortar expansion studied at 0.15-0.80 mm, 1.25-2.50 mm and 2.5-5.0 mm size fractions and gives data necessary for model development. Results show that no expansion was measured on the mortars using small particles (0.15-0.80 mm) while the particles (1.25-2.50 mm) gave the largest expansions. Finally, model is proposed to simulate the experimental results by studying correlations between the measured expansions and the size of aggregates and to calculate the thickness of the porous zone necessary to take again all the volume of the gel created by this chemical reaction.