Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (3)
  • Open Access


    Analysis and Optimization of Flow-Guided Structure Based on Fluid-Structure Interaction

    Yue Cui1,*, Liyuan Wang2, Jixing Ru3, Jian Wu1

    FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.6, pp. 1573-1584, 2023, DOI:10.32604/fdmp.2023.024873

    Abstract Gases containing sulfur oxides can cause corrosion and failure of bellows used as furnace blowers in high-temperature environments. In order to mitigate this issue, the behavior of an effective blast furnace blower has been examined in detail. Firstly, the Sereda corrosion model has been introduced to simulate the corrosion rate of the related bellows taking into account the effects of temperature and SO2 gas; such results have been compared with effective measurements; then, the average gas velocity in the pipeline and the von Mises stress distribution of the inner draft tube have been analyzed using a Fluid-Structure Interaction model. Finally,… More >

  • Open Access


    Metal Corrosion Rate Prediction of Small Samples Using an Ensemble Technique

    Yang Yang1,2,*, Pengfei Zheng3,4, Fanru Zeng5, Peng Xin6, Guoxi He1, Kexi Liao1

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.1, pp. 267-291, 2023, DOI:10.32604/cmes.2022.020220

    Abstract Accurate prediction of the internal corrosion rates of oil and gas pipelines could be an effective way to prevent pipeline leaks. In this study, a proposed framework for predicting corrosion rates under a small sample of metal corrosion data in the laboratory was developed to provide a new perspective on how to solve the problem of pipeline corrosion under the condition of insufficient real samples. This approach employed the bagging algorithm to construct a strong learner by integrating several KNN learners. A total of 99 data were collected and split into training and test set with a 9:1 ratio. The… More >

  • Open Access


    Prediction of the Corrosion Rate of Al–Si Alloys Using Optimal Regression Methods

    D. Saber1,*, Ibrahim B. M. Taha2, Kh. Abd El-Aziz3

    Intelligent Automation & Soft Computing, Vol.29, No.3, pp. 757-769, 2021, DOI:10.32604/iasc.2021.018516

    Abstract In this study, optimal regression learner methods were used to predict the corrosion behavior of aluminum–silicon alloys (Al–Si) with various Si ratios in different media. Al–Si alloys with 0, 1%, 8%, 11.2%, and 15% Si were tested in different media with different pH values at different stirring speeds (0, 300, 600, 750, 900, 1050, and 1200 rpm). Corrosion behavior was evaluated via electrochemical potentiodynamic test. The corrosion rates (CRs) obtained from the corrosion tests were utilized in the formation of datasets of various machine regression learner optimization (MRLO) methods, namely, decision tree, support vector machine, Gaussian process regression, and ensemble… More >

Displaying 1-10 on page 1 of 3. Per Page