Aging life prediction system of polymer outdoors constructed by ANN. 1. Lifetime prediction for polycarbonate

By the application of artificial neural network (ANN), the concept of constructing polymers' aging life prediction system has been proposed for the first time in the present work. Such a system can be designed via integrating several independent ANN modules playing different roles: the S module for calculating environmental stress level, the F module for outputting the feature of aging life distribution, the Sa module for computing the accelerated environmental stress level, the aT module for studying the correspondence between life distribution of certain accelerated and natural aging tests, and the structure module for converting polymer structures into structure parameter matrix. Here polycarbonate, as a widely used engineering thermoplastic with complex aging behavior and various aging mechanisms, has been researched to constructing its aging life model with the help of the systematic ANN method above, which well reflects huge potential of ANN's application in the field of polymers' aging life prediction for practical application.

[1]  André Margaillan,et al.  Degradation study of polymer coating: Improvement in coating weatherability testing and coating failure prediction , 2009 .

[2]  J. Gardette,et al.  Characterisation of accelerated ageing devices for prediction of the service life of acrylic-melamine/urethane thermosets , 2011 .

[3]  J. Malík,et al.  Lifetime prediction for HALS-stabilized LDPE and PP , 1995 .

[4]  Grace Tjandraatmadja,et al.  Evaluation of commercial polycarbonate optical properties after QUV-A radiation—the role of humidity in photodegradation , 2002 .

[5]  James Edward Pickett,et al.  Effects of temperature on the weathering lifetime of coated polycarbonate , 2009 .

[6]  A. Davis.  Effect of climate on the weathering of polyacetal , 1981 .

[7]  Hecht-Nielsen.  Theory of the backpropagation neural network , 1989 .

[8]  R. Chitra,et al.  Natural Weathering Studies of Polypropylene , 2009 .

[9]  Michael Unser,et al.  B-spline signal processing. I. Theory , 1993, IEEE Trans. Signal Process..

[10]  K. Gillen,et al.  Accelerated aging and lifetime prediction: Review of non-Arrhenius behaviour due to two competing processes , 2005 .

[11]  André Margaillan,et al.  Natural and artificial weathering characteristics of stabilized acrylic–urethane paints , 2008 .

[12]  Trevor S. Wiens,et al.  Three way k-fold cross-validation of resource selection functions , 2008 .

[13]  David J. Osguthorpe,et al.  Neural network prediction of glass-transition temperatures from monomer structure , 1995 .

[14]  Gernot M. Wallner,et al.  Aging behavior and lifetime modeling for polycarbonate , 2010 .

[15]  S. Kenig,et al.  Life expectation of polycarbonate , 1985 .

[16]  James Edward Pickett,et al.  Reproducibility of Florida weathering data , 2005 .

[17]  Xavier Colin,et al.  Lifetime prediction of polyethylene in nuclear plants , 2007 .

[18]  R. J. May,et al.  The role of oxygen in the photoaging of bisphenol A polycarbonate. 2. GC/GC/high-resolution MS analysis of Florida-weathered polycarbonate , 1987 .

[19]  João Carlos Figueira Pujol,et al.  A neural network approach to fatigue life prediction , 2011 .

[20]  Willem D. van Driel,et al.  Lifetime assessment of Bisphenol-A Polycarbonate (BPA-PC) plastic lens, used in LED-based products , 2014, Microelectron. Reliab..

[21]  Alessio Micheli,et al.  Prediction of the Glass Transition Temperature of (Meth)Acrylic Polymers Containing Phenyl Groups by Recursive Neural Network , 2007 .

[22]  R. P. Brown.  Predictive techniques and models for durability tests , 1995 .

[23]  D. Marquardt.  An Algorithm for Least-Squares Estimation of Nonlinear Parameters , 1963 .

[24]  Mohammad Bagher Menhaj,et al.  Training feedforward networks with the Marquardt algorithm , 1994, IEEE Trans. Neural Networks.

[25]  Brigitte Pinel,et al.  A methodology to predict the life duration of polymers used in nuclear power stations. Industrial needs and their approach , 1999 .

[26]  Yousef Al-Assaf,et al.  Prediction of the fatigue life of unidirectional glass fiber/epoxy composite laminae using different neural network paradigms , 2002 .

[27]  J. Verdu,et al.  Lifetime prediction in the hydrolytic ageing of polyesters , 1995 .

[28]  J. Pickett,et al.  Sample temperatures during outdoor and laboratory weathering exposures , 2009 .

[29]  Hong Tae Kang,et al.  Prediction of fatigue life for spot welds using back-propagation neural networks , 2007 .

[30]  Wolfgang Graf,et al.  Lifetime prediction using accelerated test data and neural networks , 2009 .

[31]  Eric M. Hoàng,et al.  Lifetime prediction of a blue PE100 water pipe , 2008 .

[32]  James Edward Pickett,et al.  Effects of irradiation conditions on the weathering of engineering thermoplastics , 2008 .

[33]  K. Gillen,et al.  The wear-out approach for predicting the remaining lifetime of materials , 2000 .

[34]  Simon Haykin,et al.  Neural Networks: A Comprehensive Foundation , 1998 .

[35]  P. Gijsman,et al.  Outdoor and accelerated weathering studies of bisphenol A polycarbonate , 2011 .

[36]  Brian R Hinderliter,et al.  A framework for predicting the service lifetime of composite polymeric coatings , 2008 .

[37]  B. Hinderliter,et al.  Statistical approaches for predicting weathering degradation and service life , 2006 .

[38]  Robert Bernstein,et al.  Lifetime predictions for semi-crystalline cable insulation materials: I. Mechanical properties and oxygen consumption measurements on EPR materials , 2006 .

[39]  C. S. Shah,et al.  Accelerated aging and life time prediction analysis of polymer composites: a new approach for a realistic prediction using cumulative damage theory , 1994 .

[40]  Teuvo Kohonen,et al.  An introduction to neural computing , 1988, Neural Networks.

[41]  Kevin Swingler,et al.  Applying neural networks - a practical guide , 1996 .

[42]  Minna Hakkarainen,et al.  Indicator products: a new tool for lifetime prediction of polymeric materials. , 2005, Biomacromolecules.

[43]  James Edward Pickett,et al.  Effects of temperature on the weathering of engineering thermoplastics , 2008 .

[44]  Brian R Hinderliter,et al.  Estimating service lifetimes in weathering: an optimistic view , 2007 .

[45]  Christopher M. Bishop,et al.  Neural networks for pattern recognition , 1995 .

[46]  Robert Bernstein,et al.  Lifetime predictions of EPR materials using the Wear-out approach , 2006 .

[47]  Alessio Micheli,et al.  Prediction of chemical-physical properties by neural networks fro structures , 2005 .

[48]  Igor Aleksander,et al.  Introduction to Neural Computing , 1990 .

[49]  Emile Fiesler,et al.  High-order and multilayer perceptron initialization , 1997, IEEE Trans. Neural Networks.

[50]  Xavier Colin,et al.  A simplified approach for the lifetime prediction of PE in nuclear environments , 2005 .

[51]  Alessio Micheli,et al.  Recursive neural networks prediction of glass transition temperature from monomer structure: an application to acrylic and methacrylic polymers , 2009 .

[52]  Alessio Micheli,et al.  Prediction of Polymer Properties from their Structure by Recursive Neural Networks , 2006 .

[53]  D. Kundu,et al.  Theory & Methods: Generalized exponential distributions , 1999 .

[54]  Peter Richner,et al.  Service life prediction for aircraft coatings , 2003 .

[55]  Zhongya Zhang,et al.  Artificial neural networks applied to polymer composites: a review , 2003 .

[56]  Alessio Micheli,et al.  Ionic liquids: prediction of their melting points by a recursive neural network model , 2008 .

[57]  James Edward Pickett,et al.  Hydrolysis kinetics of condensation polymers under humidity aging conditions , 2013 .

[58]  Zhenyu Jiang,et al.  Prediction on wear properties of polymer composites with artificial neural networks , 2007 .

[59]  Laurene V. Fausett,et al.  Fundamentals Of Neural Networks , 1993 .

[60]  Kenneth Levenberg.  A METHOD FOR THE SOLUTION OF CERTAIN NON – LINEAR PROBLEMS IN LEAST SQUARES , 1944 .

[61]  Mark Evans,et al.  A statistical degradation model for the service life prediction of aircraft coatings: With a comparison to an existing methodology , 2012 .

[62]  Mathias Christopher Celina,et al.  Chemiluminescence as a condition monitoring method for thermal aging and lifetime prediction of an HTPB elastomer , 2006 .