JOURNAL OF CHEMICAL ENGINEERING OF JAPAN
Online ISSN : 1881-1299
Print ISSN : 0021-9592
Volume 55, Issue 10
Displaying 1-3 of 3 articles from this issue
Editorial Note
Physical Properties and Physical Chemistry
  • Qian Zhang, Jie Liu
    Article type: Research Paper
    2022Volume 55Issue 10 Pages 317-325
    Published: October 20, 2022
    Released on J-STAGE: October 20, 2022
    JOURNAL FREE ACCESS
    Supplementary material

    Phase diagrams of aqueous saline systems constitute the cornerstone of the brine purification industry. Although ternary phase diagrams may be studied using many experimental methods, the developed isothermal titration microcalorimetry (ITC) approach is simple, generic, and can be extended to the investigation of phase diagrams of multi-salt aqueous solutions and other related systems. In this study, the phase equilibrium of one complex ternary system, Na2CO3+Na2SO4+H2O, with several hydrated salts and a double salt, was determined using ITC with the aid of X-ray diffraction, differential scanning calorimetry, and thermogravimetry. The isobaric and isothermal titration methods can not only determine the boundaries of different phase regions by changes in the slope of the heat evolved vs. time plot or in the slope of the observed heat vs. solvent concentration plot, but also provide additional information regarding the hydration heat of ions and hydrates, dissolution heat, and dilution heat. The use of ITC can be extended to complex systems after optimization of data processing.

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Process Systems Engineering and Safety
  • Zhong Zhao, Yanglihong Chen, Junqiu Pang
    Article type: Research Paper
    2022Volume 55Issue 10 Pages 326-335
    Published: October 20, 2022
    Released on J-STAGE: October 20, 2022
    JOURNAL FREE ACCESS

    When acoustic emission detection technology is applied to detect the agglomeration in fluidized bed reactors (FBRs), the collected acoustic emission samples are usually non-stationarity and unbalanced, making it difficult to extract stable and separable classification features. In this study, the voiceprint features of collected acoustic emission signals were extracted with the Mel Frequency Cepstrum Coefficients (MFCC) and Linear Prediction Cepstrum Coefficients (LPCC). Extracted voiceprint features of LPCC and MFCC were fused with RelieF algorithm to form the stable R-LPMFCC feature, which were then compressed with principal components analysis (PCA) as input data for classification. The cost factor and GINI index-based decision-making calculation were introduced to the Adaboost algorithm to significantly improve its accuracy and F-score when classifying unbalanced samples. The comparative experimental results in a fluidized-bed pilot plant verify the effectiveness and feasibility of the proposed method.

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