Editors Ryuichi Egashira (Tokyo Institute of Technology) Jun Fukai (Kyushu University) Choji Fukuhara (Shizuoka University) Toshitaka Funazukuri (Chuo University) Takayuki Hirai (Osaka University) Jun-ichi Horiuchi (Kitami Institute of Technology) Eiji Iritani (Nagoya University) Yoshinori Itaya (Gifu University) Noriho Kamiya (Kyushu University) In-Beum Lee (Pohang University of Science and Technology (POSTEC)) Kouji Maeda (University of Hyogo) Hideyuki Matsumoto (Tokyo Institute of Technology) Nobuyoshi Nakagawa (Gunma University) Masaru Noda (Fukuoka University) Hiroyasu Ogino (Osaka Prefecture University) Mitsuhiro Ohta (The University of Tokushima) Eika W. Qian (Tokyo University of Agriculture and Technology) Yuji Sakai (Kogakuin University) Noriaki Sano (Kyoto University) Naomi Shibasaki-Kitakawa (Tohoku University) Ken-Ichiro Sotowa (The University of Tokushima) Hiroshi Suzuki (Kobe University) Nobuhide Takahashi (Shinshu University) Shigeki Takishima (Hiroshima University) Yoshifumi Tsuge (Kyushu University) Tomoya Tsuji (Nihon University) Da-Ming Wang (National Taiwan University) Takuji Yamamoto (University of Hyogo) Yoshiyuki Yamashita (Tokyo University of Agriculture and Technology) Miki Yoshimune (National Institute of Advanced Industrial Science and Technology (AIST))
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AIMS AND SCOPE:
Journal of Chemical Engineering of Japan, an official publication of the Society of Chemical Engineers, Japan, is dedicated to providing timely original research results in the broad field of chemical engineering ranging from fundamental principles to practical applications. Subject areas of this journal are listed below. Research works presented in the journal are considered to have significant and lasting value in chemical engineering.
Physical Properties and Physical Chemistry Transport Phenomena and Fluid Engineering Particle Engineering Separation Engineering Thermal Engineering Chemical Reaction Engineering Process Systems Engineering and Safety Biochemical Food and Medical Engineering Micro and Nano Systems Materials Engineering and Interfacial Phenomena Energy Environment Engineering Education
The present study describes a low-temperature metal–metal bonding process using leaf-like CuO aggregates. A CuO nanoparticle colloid solution was prepared at 20°C with a salt-base reaction. Leaf-like CuO aggregates with a longitudinal size of ca. 990 nm and a lateral size of ca. 440 nm composed of CuO nanoparticles with a size of ca. 10 nm were fabricated by aging the CuO particle colloid solution at 80°C. The metal–metal bonding ability of the leaf-like CuO aggregates was examined by pressurizing metallic discs sandwiching the CuO particles as a filler at 1.2 MPa for 5 min under annealing in H2 gas. The metal–metal bonding could be performed even for an annealing temperature as low as 250°C. A shear strength of 17.0 MPa was recorded for the annealing temperature of 250°C.
A soft-sensor model is proposed with the aim of predicting the finished pellet quality indicators (chemical composition, physical properties, and metallurgical properties) of the rotary kiln pellet sintering process. The model is based on the radial basis function (RBF) neural network that is optimized by the biogeography-based optimization (BBO) algorithm. Six variables that are associated with the reaction mechanism of the rotary kiln pellet sintering process and that are closely related to the quality indices of the finished pellets—the material thickness of the chain grate, the velocity of chain grate, the temperature of the kiln head, the temperature of the kiln tail, the rotary kiln speed, and the quantity of the fed coal—are selected as inputs to the proposed soft-sensor model, and the finished pellet quality indices form the outputs. Accordingly, a multiple-input-single-output (MISO) RBF neural network (RBFNN) soft-sensor model is established. The structural parameters of the RBFNN model are optimized by the BBO algorithm. The simulation results showed that the model yields better generalization results and has a higher prediction accuracy, and therefore, it is capable of meeting the requirements of real-time control as well as those of an online soft-sensor in the rotary kiln sintering process.
With the aim of utilizing Jatropha oil as fuel for thermal power generation, we have developed a technique for the selective extraction of triglycerides from Jatropha seeds, which contain glycerides, free fatty acids, phosphorus, and water, using supercritical CO2 extraction. The effects of particle size, moisture content of Jatropha seeds, and entrainers, were examined. We found that using tetrahydrofuran (THF) as an entrainer led to reduce extraction times. Specifically, the extraction time was significantly decreased with the use of 7.5 wt% THF and a CO2 flow rate of 5.8 g/min. Supercritical CO2 extraction technology with the addition of THF represents an inexpensive selective extraction process from feedstocks containing oil.
In conventional entrained coal gasification, coal ash is usually discharged from the bottom as molten slag. Therefore, comparatively low ash fusion temperature coal is preferred. However, high ash fusion temperature coal contributes 30% of total world coal production, so a new gasification process has been proposed. We conducted a dry ash removal gasification experiment in an entrained down-flow gasifier using different ash fusion temperature coal. We measured gasification temperature and composition and volume of produced gas to evaluate the gasification behavior. Recovered ash was analysed to evaluate ash behavior. The performance and trend among gasification conditions were similar regardless of coal type, but ash behavior significantly varied depending on ash fusion temperature. Even when gasification temperature was similar, fly ash predominated if high ash fusion temperature coal was used, but ash adhered to the entrained gasifier wall as fouling when low ash fusion temperature coal was used.
Activated-carbon-supported phosphotungstic acid (HPW/C) catalysts were prepared and characterized by FT-IR spectroscopy, X-ray diffraction (XRD), scanning electron microscopy (SEM), and the Brunauer–Emmett–Teller (BET) method. The catalytic performance of HPW/C for β-pinene polymerization was also investigated. The characterization results show that the Keggin structure of HPW does not change after being supported on the activated carbon. The tiny particles of HPW are distributed amorphously and uniformly on the surface of the activated carbon. HPW can interact strongly with surface oxygen-containing groups on the activated carbon. The immobilization of HPW leads to a decrease in the specific surface area and total porous volume of the activated carbon. The polymerization conditions were optimized as follows: loading amount 34.2 wt%; dosage of catalysts 0.6 g; reaction temperature 0–10°C; β-pinene 3 mL; solvent 7 mL; reaction time 2 h. Under these conditions, the polymer yield was up to 73.0%, and the number-average molecular weight was about 860.
In order to deal with the nonlinear varying behavior of NOx emissions for long term predictions, a real-time recursively updating model is indispensable. In this paper, new recursively updating models are proposed to predict NOx emissions. The proposed real-time models are equipped with an initial LSSVM model and subsequent updating methods to adapt the models with recent changes to process data. The updating methods include solo Least Squares Support Vector Machines (LSSVM) update, solo output bias update, and the combination of these two termed as the LSSVM-Scheme. These models are applied to NOx emission process data from a coal combustion power plant in Korea. Prediction results obtained from the proposed real-time LSSVM models are compared with their counterpart real-time PLS models, which reveal that real-time LSSVM models outperform their counterpart real-time PLS models. Among other models developed in this work, LSSVM-Scheme and solo output bias update based on LSSVM predicts NOx emissions robustly for a long passage of time with the highest accuracy.
Various multivariate statistical methods based on pattern recognitions for the Tennessee Eastman (TE) process have been developed to identify and diagnose the root cause of assumed faults. However, even if the same fault occurs, its patterns or traces generated from such conventional approaches can be different according to fault magnitudes. Thus, the fault magnitude should be considered. In this study, a signed digraph (SDG) based on process knowledge is used to identify the relationships between process variables and conceivable faults. A support vector regression (SVR) and dynamic independent component analysis (DICA) are then applied to construct empirical models as a function of process variables associated with assumed faults and their fault magnitudes for isolating a fault and handling non-Gaussian information. In addition, empirical models for predicting fault magnitudes are constructed. The efficacy of the proposed approach is illustrated by comparing it with the previous studies applied for the benchmark process.
The present study reports on ultrasound-assisted hydrolysis of total isoflavones in Radix puerariae using hydrochloric acid as catalyst and the influence of different hydrolysis parameters on the yield of puerarin. Based on the single factor test, response surface methodology (RSM, Box–Behnken Design) was used to develop predictive models for simulation and optimization of the hydrolysis conditions in order to increase the yield of puerarin. The optimum hydrolysis conditions were as follows: hydrolysis time of 48 min, hydrolysis temperature of 78°C, ultrasonic power of 180 W and the concentration of hydrochloric acid of 4.6% (v/v). Under these optimal conditions, the concentration of puerarin was increased to 15.92%, which is 19.5% higher than that in the original crude extract. At the same time, compared with the traditional acid hydrolysis, the time needed in ultrasound-assisted hydrolysis is only 45 min, which is 120 min shorter than traditional hydrolysis.
Vertical photobioreactors (PBR) with cylindrical cross section, namely air-lift reactors (ALR) and bubble column reactors (BCR), are often chosen both for bench-scale and industrial scale microalgal cultivation. It was common belief that ALR was the most favorable configuration in terms of light conversion efficiency (LCE) and/or photosynthetic productivity than BCR because of the regular cyclic flow pattern achieved inside the PBR. In the present study, we simulated the flow patterns in both ALR and BCR by means of computational fluid dynamics (CFD) and clarified the effects of such flow pattern on the LCE and productivity. Simulation results, obtained from the open-source CFD suite OpenFOAM, showed good agreement both for the flow velocity and the mixing time observed in the actual PBR using high-speed photography and conductivity pulse response, respectively. Subsequently, Lagrangian particle tracking was conducted on the simulation results to highlight the main fluid-flow patterns and to calculate the local flashing-light frequency, which was necessary in order to estimate the overall light conversion efficiency of the PBR. The BCR was characterized by a highly random fluid pattern with macroscopic, low-frequency circular loops while the ALR was characterized by numerous swirling flows localized inside the draft tube in addition to the main recirculation between the inner and outer portions of the tube. Finally, image analysis was used to correlate the numerical calculations with the light conversion efficiencies attained in a Haematococcus pluvialis culture that had been illuminated with flashing light.
The micromixing efficiency of viscous media in a rotating packed bed (RPB) was evaluated by using the Dushman-Villermaux reaction system and was quantitatively analyzed based on the segregation index. The effects of the fluid viscosity, diameter of the packing wire, reactant concentration, rotational speed, and liquid flow rate on the mixing efficiency were evaluated. The results show that the segregation index decreases with an increase in the rotational speed, liquid flow rate, and Reynold number. Moreover, the segregation index declines with a decrease in the fluid viscosity, diameter of the packing wire, and reactant concentration. Furthermore, the micromixing time was calculated to be within 5.3×10−5–6×10−4 s (for the viscosity range 1.01–219.18 mPa·s) based on the incorporation model. The micromixing efficiency in a Tee mixer with the same mesh packing was also evaluated. Compared with the Tee mixer and some other reactors, the RPB is superior for enhancing the micromixing efficiency, especially for higher-viscosity systems.
The ion-dependency of oscillatory wetting under a DC voltage, which had been reported previously, was studied in detail. The oil and water phases contained anionic and cationic surfactants, respectively. The contact line of the oil/water interface and the glass surface exhibited a successive pulsation under a DC voltage. This oscillatory wetting occurred for a Ba2+-containing system and was suppressed by Ca2+. The mechanism for the ion dependency was examined in detail. The frequency of the pulsation showed a sudden change at a threshold molar ratio of [Ca2+]/([Ca2+]+[Ba2+]). When water containing Ca2+ was injected into the Ba2+-containing interface, a significant time was required to stop the pulsation. The addition of Ba2+ into the Ca2+-containing interface instantaneously activated the pulsation even when Ca2+ had been dissolved in the water phase. The dynamic behavior was explained in terms of an interfacial chemical reaction with complex formation between the cations and the anionic surfactant.
We have investigated the drying process of latex dispersion coating from the perspective of particle packing process. The behavior of particle aggregates in latex dispersions under shear flow was evaluated based on rheological measurement: particle aggregation under steady shear is related to apparent viscosities and time variation of elastic moduli shows reconstruction of aggregates. The effect of applied shear strain in coating on the thinning behavior of the latex dispersion coatings has been investigated. We found that the packing fraction of particles at the end of a constant film thinning rate period or concentration intricately changed with applied shear strain and glass transition temperature, Tg, of latex particle. If particles are completely dispersed, deformable particles having lower Tg are packed up to a maximum packing density, showing a very short falling drying rate period. In the case of insufficient shear strain application, however, aggregates formed a loosely packed layer, resulting in the emergence of a clearly decreasing thinning rate period. In contrast, hard spheres having the highest Tg formed a loosely packing particle layer similar to aggregated lower Tg particles.
In the sea water desalination process, brine is produced as a byproduct. Brine contains several resources which are various valuable ion materials in high concentration. If the sea water desalination process is integrated with a resource recovery process, a reduction in environmental load and production of valuable resources can be achieved. Mg2+ ion is the second most abundant ion in sea water. However, the development of a Mg2+ ion recovery method is not sufficient. The Mg2+ recovering method in magnesium hydroxide (MH) form from brine has been studied. Brine and bittern are produced when the sea water desalination process is integrated with the resource recovery process. When MH is recovered from concentrated sea water, two kinds of raw resource materials, i.e. brine and bittern, can be considered. However, the MH recovery process using brine as a raw resource material is not compared with the recovery process using bittern. This is because there is almost no fundamental data of MH crystals for process comparison, and MH crystals are produced as ultra-fine particles. Therefore, the purpose of this present study is to obtain the fundamental data for development of the MH recovery process in an integrated process. In particular, the prevention method of ultra-fine MH crystal deposition is investigated, and the yield and crystallinity of MH crystals are compared. It is clear that the yield and crystallinity of MH crystals are strongly dependent on temperature and the kind of raw resource material. These results show a strategy for improvement in process efficiency when MH crystals are recovered from the sea water desalination process.