한국주조공학회지 (Journal of Korea Foundry Society)

  • 제34권3호
  • /
  • Pages.107-111
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  • 2014
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  • 1598-706X(pISSN)
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  • 2288-8381(eISSN)
한국주조공학회 (Korea Foundry Society)
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Estimation of Permeability of Green Sand Mould by Performing Sensitivity Analysis on Neural Networks Model

  • Reddy, N. Subba (School of Materials Science and Engineering, Gyeongsang National University) ;
  • Baek, Yong-Hyun (School of Materials Science and Engineering, Gyeongsang National University) ;
  • Kim, Seong-Gyeong (School of Materials Science and Engineering, Gyeongsang National University) ;
  • Hur, Bo Young (School of Materials Science and Engineering, Gyeongsang National University)
  • 투고 : 2014.05.23
  • 심사 : 2014.06.25
  • 발행 : 2014.06.30
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초록

Permeability is the ability of a material to transmit fluid/gases. It is an important material property and it depends on mould parameters such as grain fineness number, clay, moisture, mulling time, and hardness. Modeling the relationships among these variable and interactions by mathematical models is complex. Hence a biologically inspired artificial neural-network technique with a back-propagation-learning algorithm was developed to estimate the permeability of green sand. The developed model was used to perform a sensitivity analysis to estimate permeability. The individual as well as the combined influence of mould parameters on permeability were simulated. The model was able to describe the complex relationships in the system. The optimum process window for maximum permeability was obtained as 8.75-10.5% clay and 3.9-9.5% moisture. The developed model is very useful in understanding various interactions between inputs and their effects on permeability.

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참고문헌

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피인용 문헌

  1. Modeling and optimization of furan molding sand system using design of experiments and particle swarm optimization 2018, https://doi.org/10.1177/0954408917728636
  2. Comprehensive modelling, analysis and optimization of furan resin-based moulding sand system with sawdust as an additive vol.41, pp.4, 2019, https://doi.org/10.1007/s40430-019-1684-0