Influence of Geometrical Factors on Performance of Thermoelectric Material Using Numerical Methods

DEREBAŞI N., Eltez M., Guldiken F., Sever A., Kallis K., Kilic H.

JOURNAL OF ELECTRONIC MATERIALS, cilt.44, sa.6, ss.2068-2073, 2015 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 44 Sayı: 6
  • Basım Tarihi: 2015
  • Doi Numarası: 10.1007/s11664-015-3657-0
  • Dergi Adı: JOURNAL OF ELECTRONIC MATERIALS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.2068-2073
  • Bursa Uludağ Üniversitesi Adresli: Evet

Özet

Prediction of the performance of thermoelectric cooling material (figure of merit, ZT) was carried out by simulated results obtained from the finite element method (FEM) as a training dataset with an artificial neural network. A total of 87 input vectors for the ZT obtained from the four thermoelectric cooling (TEC) modules modeled using the FEM analysis were available in the training set to a back-propagation artificial neural network. An average correlation and maximum prediction error were found to be 100% and 0.01%, respectively, for the ZT after training. The standard deviation of the values was 0.05%. A set of test data, different from the training dataset was used to investigate the network performance. The average correlation and maximum prediction error were found to be 99.92% and 0.07%, respectively, for the tested TEC module. A thermoelectric module produced based on the numerical results was shown to be a promising device for use in cooling systems.