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Information Journal Paper

Title

DETERMINING THE COMPRESSIVE STRENGTH OF GREEN SAND MOULDS WITH DIFFERENT MOISTURE CONTENTS, USING ARTIFICIAL NEURAL NETWORKS

Pages

  47-56

Abstract

 The quality of parts in green sand mold casting mostly depends on the green sand properties such as compressive strength, permeability, mould hardness, etc. These parameters depend on input parameters like water, size and shape of the sand, percentage of bentonite and so on. The compressive strength of sand of different moisture contents which is required for modeling, obtained by experimental tests, and a research method, based on Artificial Neural Network (ANN). The predicted values of the compressive strength obtained by the ANN and new experiments found to be in good agreement with each other and showed that by using ARTIFICIAL NEURAL NETWORKS one can estimate the compressive strength of green sand precisely before molding.

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    Cite

    APA: Copy

    MESHKABADI, R., MARAMI, GH.R., & JAHANI, K.. (2013). DETERMINING THE COMPRESSIVE STRENGTH OF GREEN SAND MOULDS WITH DIFFERENT MOISTURE CONTENTS, USING ARTIFICIAL NEURAL NETWORKS. JOURNAL OF NEW MATERIALS, 4(1 (13)), 47-56. SID. https://sid.ir/paper/169737/en

    Vancouver: Copy

    MESHKABADI R., MARAMI GH.R., JAHANI K.. DETERMINING THE COMPRESSIVE STRENGTH OF GREEN SAND MOULDS WITH DIFFERENT MOISTURE CONTENTS, USING ARTIFICIAL NEURAL NETWORKS. JOURNAL OF NEW MATERIALS[Internet]. 2013;4(1 (13)):47-56. Available from: https://sid.ir/paper/169737/en

    IEEE: Copy

    R. MESHKABADI, GH.R. MARAMI, and K. JAHANI, “DETERMINING THE COMPRESSIVE STRENGTH OF GREEN SAND MOULDS WITH DIFFERENT MOISTURE CONTENTS, USING ARTIFICIAL NEURAL NETWORKS,” JOURNAL OF NEW MATERIALS, vol. 4, no. 1 (13), pp. 47–56, 2013, [Online]. Available: https://sid.ir/paper/169737/en

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