In this work, an extensive experimental data of Nansulate coating from NanoTechInc were applied to develop an artificial neural network (ANN) model. The Levenberg–Marquart algorithm has been used in network training to predict and calculate the energy gain and energy saving of Nansulate coating. By comparing the obtained results from ANN model with experimental data, it was observed that there is more qualitative and quantitative agreement between ANN model values and experimental data results. Furthermore, the developed ANN model shows more accurate prediction over a wide range of operating conditions. Also, maximum relative error of 3% was observed by comparison of experimental and ANN simulation results.
1.
Khor
, K. A.
, Dong
, Z. L.
, and Gu
, Y. W.
, 1999, “Plasma Sprayed Functionally Graded Thermal Barrier Coatings
,” Mater. Lett.
0167-577X, 38
, pp. 437
–444
.2.
Brindley
, W. J.
, 1996, “Thermal Barrier Coatings
,” J. Therm. Spray Technol.
1059-9630, 5
(4
), pp. 379
–380
.3.
Nicholls
, J. R.
, Deakin
, J. J.
, and Rickerby
, D. S.
, 1999, “A Comparison Between the Erosion Behaviour of Thermal Spray and Electron Beam Physical Vapor Deposition Thermal Barrier Coatings
,” Wear
0043-1648, 233–235
, pp. 352
–361
.4.
Miller
, R. A.
, 1987, “Current Status of Thermal Barrier Coatings—An Overview
,” Surface and Coatings Tecnology
, 30
(1
), pp. 1
–11
. 0002-78205.
Thornton
, J. A.
, 1975, “Influence of Substrate Temperature and Deposition Rate on Structure of Thick Sputtered Cu Coatings
,” J. Vac. Sci. Technol.
0022-5355, 12
, pp. 830
–835
.6.
Schulz
, U.
, Fritscher
, K.
, Rätzer-Scheibe
, H. -J.
, Kaysser
, W. A.
, and Peters
, M.
, 1997, “Thermocylic Behaviour of Microstructurally Modified EB-PVB Thermal Barrier Coatings
,” Mater. Sci. Forum
0255-5476, 251–254
, pp. 957
–964
.7.
Dongming
, Z.
, and Miller
, R. A.
, 2002, “Thermal Conductivity and Sintering Behavior of Advanced Thermal Barrier Coatings
,” Report No. NASA/TM-211481.8.
2009, Project “Nansulate,” Saving Electricity by Coating With Air Conditioning Nansulate Compared With a Local Match Without Coating, Federal Electricity Commission.
9.
Singh
, V.
, Gupta
, I.
, and Gupta
, H. O.
, 2007, “ANN-Based Estimator for Distillation Using Levenberg–Marquardt Approach
,” Eng. Applic. Artif. Intell.
0952-1976, 20
, pp. 249
–259
.10.
Hagen
, M. T.
, Demuth
, H. B.
, and Beale
, M. H.
, 1996, Neural Network Design
, PWS
, Boston, MA
.11.
Jimenez-Marquez
, S. A.
, Lacroix
, C.
, and Thibault
, J.
, 2003, “Impact of Modeling Parameters on the Prediction of Cheese Moisture Using Neural Networks
,” Comput. Chem. Eng.
0098-1354, 27
, pp. 631
–646
.12.
Roj
, E.
, and Wilk
, M.
, 1998, “Simulation of an Absorption Column Performance Using Feed-Forward Neural Networks in Nitric Acid Production
,” Comput. Chem. Eng.
0098-1354, 22
(178
), pp. 909
–912
.13.
Saghatoleslami
, N.
, Sargolzaei
, J.
, Mosavi
, M.
, and Khoshnoodi
, M.
, 2006, “Comparative Study of Artificial Neural Nets (ANN) and Statistical Methods for Predicting the Performance of Ultra Filtration Process in the Milk Industry
,” Iranian Journal of Chemistry and Chemical Engineering
, 25
(2
), pp. 67
–76
.14.
Chau
, K. W.
, 2006, “Particle Swarm Optimization Training Algorithm for ANNs in Stage Prediction of Shing Mun River
,” J. Hydrol.
0022-1694, 329
(3–4
), pp. 363
–367
.15.
Zupan
, J.
, and Gasteir
, J.
, 1999, Neural Networks in Chemistry and Drug Design
, Wiley-VCH
, New York
.16.
Maciej
, L. C.
, 2010, “Training of Neural Models for Predictive Control
,” Neurocomputing
0925-2312, 73
(7–9
), pp. 1332
–1343
.17.
Singh
, V.
, Gupta
, I.
, and Gupta
, H. O.
, 2005, “ANN Based Estimator for Distillation—Inferential Control
,” Chem. Eng. Process.
0255-2701, 44
, pp. 785
–795
.18.
Vafaei
, M. T.
, Eslamloueyan
, R.
, and Ayatollahi
, Sh.
, 2009, “Simulation of Steam Distillation Process Using Neural Networks
,” Chem. Eng. Res. Des.
0263-8762, 87
, pp. 997
–1002
.19.
Mujtaba
, I. M.
, Aziz
, N.
, and Hussain
, M. A.
, 2006, “Neural Network Based Modelling and Control in Batch Reactor
,” Chem. Eng. Res. Des.
0263-8762, 84
(8
), pp. 635
–644
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