Study on Durability Damage Rules and Aging Prediction Method of Geosynthetics

Ze Liu; Guo Lin Yang

doi:10.4028/www.scientific.net/AMR.163-167.3242

Paper Titles

Durability of E-Glass Fiber Reinforced Polymer Subjected to Freeze-Thaw Cycle and Sustained Load
p.3219

Probability Evaluation Method for Cable Safety of Long Span Suspension Bridges under Extreme Wind Load
p.3223

Durability of Ancient Earthen Architecture under Wind Erosion in the Milan Ancient City along the Silk Road of China
p.3230

Analysis on Fatigue of Natural Corrosion Steel Bars
p.3237

Study on Durability Damage Rules and Aging Prediction Method of Geosynthetics
p.3242

Study on Shrinkage of Concrete Based on BP Neural Network
p.3249

Residual Life Predication of Reinforced Concrete Elements Based on Time-Varying Reliability
p.3258

Seismic Assessment of RC Structures in Service Affected by Reinforcement Corrosion
p.3263

Reliability Analysis of Hydraulic Tunnel Lining Structure with Stochastic Finite Elements Method
p.3267

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 163-167Study on Durability Damage Rules and Aging...

Study on Durability Damage Rules and Aging Prediction Method of Geosynthetics

Abstract:

As geosynthetics is made from polymer, its durability is one of the most important issues people have been concerning. Based on the analysis of data gotten from laboratory, field tests and engineering samplings, the reasons for geosynthetics durability damage are summarized, the injury rules and main factors in various applications are analyzed; after studied the existing durability prediction methods, Support Vector Machine (SVM) theory is applied to predict the durability, and an example is analyzed in which temperature, humidity, UV radiation intensity and the aging time were set as input parameters, residual tensile strength and elongation rate were set as output parameters.

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Periodical:

Advanced Materials Research (Volumes 163-167)

Pages:

3242-3248

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.163-167.3242

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Online since:

December 2010

Authors:

Ze Liu, Guo Lin Yang

Keywords:

Aging, Durability, Geosynthetic, Life Prediction, Support Vector Machine (SVM)

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