Self-induced sloshing is an oscillatory phenomenon of a free liquid surface due to the flow of a fluid. This phenomenon has been reported in some gas–liquid reactors, and it is important to predict and prevent its occurrence for the safe operation of the reactors. However, the fundamental knowledge on the self-induced sloshing by bubble flow, such as the frequency and amplitude, is insufficient, and the occurrence condition has not been clarified. The purpose of this study is to investigate the characteristics of self-induced sloshing by bubble flow experimentally. We attempt to reproduce self-induced sloshing by using computational fluid dynamics (CFD) and establish a CFD model for the prediction of the occurrence of self-induced sloshing. In the experiments, air bubbles were dispersed into a liquid from the bottom of a rectangular vessel. The effects of the air flow rate and static liquid height on the characteristics of self-induced sloshing were investigated experimentally by image analysis. The occurrence of self-induced sloshing was confirmed by increasing the airflow rate at a specific static liquid height. The amplitude reached a maximum at the static liquid height, where self-induced sloshing was most likely to occur, and the frequency decreased with increasing static liquid height. Next, in order to reproduce the self-induced sloshing through CFD, an appropriate drag model of the bubbles was selected. Although the amplitude was overestimated due to the absence of the foam layer, the predicted frequency agreed well with the experimental value. Finally, the movement of the circulation flow was analyzed, and its correlation with the self-induced sloshing was clarified.

The CO hydrogenation activity of a Ru/Fe/TiO₂ catalyst with reactant gases containing H₂O was investigated for application in the production of substitute natural gas containing CH₄ as the major component and C₂–C₄ hydrocarbons as the minor components. The total higher heating value (HHV) of the C₁–C₄ hydrocarbon products in the complete CO conversion was higher than 45 MJ/m³(Normal) for the CO hydrogenation using reactant gases containing H₂O. Moreover, the HHV of the C₁–C₄ hydrocarbon products in the complete CO conversion was higher than 45 MJ/m³(N) over a wider temperature range when the H₂/CO molar ratio in the reactant gas was 2.5 rather than when it was 3.0.

The time-varying and multi-dimensional characteristics are major causes of the low performance of soft sensors in chemical processes. To solve the problem, an improved adaptive soft sensor modeling method is proposed. This method obtains predicted deviation by modular steps of moving window and evaluates deterioration of soft sensors via ttest adaptively. Besides, this paper combines the moving window-autoassociative neural network (AANN) method to update both the modeling auxiliary variable and the auxiliary variable data. Data simulation and result analysis obtained via a continuous stirred tank reactor (CSTR) and a debutanizer column process (DCP) show that the improved adaptive soft sensor modeling method proposed in this paper can evaluate the deterioration of soft sensors and update the soft sensor model adaptively, and improve the predicted performance of soft sensors for time-varying and multi-dimensional chemical processes.

Removing the mother liquor from crystalline agglomerated particles is important to improve crystal quality. Reslurry is one of the operation methods for replacing the mother liquor and recovering purity. The properties of agglomerated crystalline particles are modified by crystallization, which affect the reslurry rate. There are no reported studies on the design of the crystallization process for improving the reslurry rate. The effects of the properties of crystalline agglomerates exerted by the anti-solvent crystallization process on the reslurry rate are discussed. The reslurry was performed using particles of various sizes prepared by controlling the agitation speed during crystallization. The removal ratio was calculated to evaluate the relationship between the properties of the crystalline agglomerates and the reslurry rate. Kinetic studies revealed that the reslurry rate was dependent on the particle size. Thus, a design strategy involving the modification of particle properties in crystallization for improving the reslurry rate is proposed.