Thermal Properties Of Sediments From Middle Valley

DOI: 10.4236/jmmce.2005.41002   PDF   HTML     3,788 Downloads   4,568 Views  


A neural network model was used to treat thermal conductivity data obtained from Middle Valley. This technique was able to separate the effects of different parameters such as porosity, grain density, bulk density and water content on the thermal conductivity. Predicted curves showed good agreement with the experimental results.

Share and Cite:

A. Hafaiedh and K. Hassine, "Thermal Properties Of Sediments From Middle Valley," Journal of Minerals and Materials Characterization and Engineering, Vol. 4 No. 1, 2005, pp. 11-19. doi: 10.4236/jmmce.2005.41002.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] Rona. P.A., Davis, E.E., and Ludwig, R.J., "Thermal properties of TAG hydrothermal precipitates, Mid-Atlantic Ridge: a comparison with Middle Valley, Juan de Fuca Ridge". In Herzig, P.M., Humphris, S.E., Miller, D. J., and Zierenberg, R.A. editors, 1998, Proc. ODP, Sci. Results, 158: College Station, TX (Ocean Drilling Program), 329-335.
[2] Davis, E.E., and Villinger, H., "Tectonic and thermal structure of the Middle Valley sedimented rift, northern Juan de Fuca Ridge". In Davis, E.E., Mottl, M.J., Fisher, A.T., et al., editors, 1992, Proc. ODP, Init. Repts., 139, College Station, TX (Ocean Drilling Program), 9-41.
[3] Gr?schel-Becker, H.M., Davis, E.E., and Franklin, J.M., 1994. Data Report: Physical properties of massive sulfide from Site 856, Middle Valley, northern Juan de Fuca Ridge. In Mottl, M.J., Davis, E.E., Fisher, A.T., and Slack, J.F. (Eds.), Proc. ODP, Sci. Results, 139: College Station, TX (Ocean Drilling Program), 721-724.
[4] M. Y. El-Bakry, K. A. El-Metwally, 2003, "Neural network model for proton-proton collision at high energy." Chaos, Solitons and Fractals, No. 16, pp. 279-285.
[5] M. Lee, S. Hwang, and J. Chen, 1994, ”Density and Viscosity Calculations for Polar Solutions via Neural Networks.” J. Chem. Eng. of Japan, Vol. 27, No. 6, pp. 749754.
[6] Y. Baram and Z. Roth, 1994 "Density shaping by neural networks with application to classification, estimation and forecasting" Center for Intelligent Systems," Israel Institute for Technology, Haifa, Israel, Tech. Rep. CIS-94-20.
[7] Y. Sun, Y. Pengand, A. Shukla, 2003, “Application of Artificial Neural Networks in the Design of Controlled Release Drug Delivery Systems.” Advanced Drug Delivery Reviews No. 55, pp. 1201-1215.
[8] J. Bourquin, H. Schmidli, P. Van Hoogevest, and H. Leuenberger, 1997, "Application of Artificial Neural Networks (ANN) in the Development of Solid Dosage Forms.” Pharm. Dev. Technol., No. 2, pp.111-121
[9] M.T. Hagan and M.B. Menhaj, 1994, Training feed-forward networks with the Marquardt algorithm." IEEE Transactions on Neural Networks, No. 6, pp. 861-867.

comments powered by Disqus

Copyright © 2020 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.