DOI QR코드

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Polynomial model controlling the physical properties of a gypsum-sand mixture (GSM)

  • Seunghwan Seo (Department of Geotechnical Engineering Research, Korea Institute of Civil Engineering and Building Technology (KICT)) ;
  • Moonkyung Chung (Department of Geotechnical Engineering Research, Korea Institute of Civil Engineering and Building Technology (KICT))
  • 투고 : 2022.04.06
  • 심사 : 2023.11.06
  • 발행 : 2023.11.25

초록

An effective tool for researching actual problems in geotechnical and mining engineering is to conduct physical modeling tests using similar materials. A reliable geometric scaled model test requires selecting similar materials and conducting tests to determine physical properties such as the mixing ratio of the mixed materials. In this paper, a method is proposed to determine similar materials that can reproduce target properties using a polynomial model based on experimental results on modeling materials using a gypsum-sand mixture (GSM) to simulate rocks. To that end, a database is prepared using the unconfined compressive strength, elastic modulus, and density of 459 GSM samples as output parameters and the weight ratio of the mixing materials as input parameters. Further, a model that can predict the physical properties of the GSM using this database and a polynomial approach is proposed. The performance of the developed method is evaluated by comparing the predicted and observed values; the results demonstrate that the proposed polynomial model can predict the physical properties of the GSM with high accuracy. Sensitivity analysis results indicated that the gypsum-water ratio significantly affects the prediction of the physical properties of the GSM. The proposed polynomial model is used as a powerful tool to simplify the process of determining similar materials for rocks and conduct highly reliable experiments in a physical modeling test.

키워드

과제정보

This research was supported by a grant from the project "Development of Smart Complex Solution for Large-Deep Underground Space Using Artificial Intelligence (20230105-001)", which was funded by the Korea Institute of Civil Engineering and Building Technology.

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