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
. 0002-7820
5.
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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