Applying Data Mining Technique to Compute LDE for Rutting Through Full Scale Accelerated Pavement Testing

Excessive overloads on trucks are a strong factor in accelerating highway pavement damage. This paper describes a study which developed a model for predicting rutting performance and determining the Load Damage Exponent (LDE) that establishes the relationship between overload and the related damage. Find Laws, which is a data mining technique, was used for establishing the rutting prediction model using different test pavements. The data mining technique was used for developing a rutting prediction equation using wheel load, load repetition, and structural number (SN) (an index indicating total pavement structure capacity) as inputs.

• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/14680629
• Authors:
  • Chen, Tung-Tsan
  • Chang, Jia-Ruey
  • Chen, Dar-Hao
• Publication Date: 2008-4

Language

• English

Media Info

• Media Type: Print
• Features: Bibliography; Figures; Tables;
• Pagination: pp 227-246
• Serial:
  • Road Materials and Pavement Design
  • Volume: 9
  • Issue Number: 2
  • Publisher: Taylor & Francis
  • ISSN: 1468-0629
  • EISSN: 2164-7402
  • Serial URL: http://www.tandfonline.com/loi/trmp20

Subject/Index Terms

• TRT Terms: Accelerated tests; Bearing capacity; Data mining; Load factor; Loads; Mathematical prediction; Pavement performance; Rutting; Testing
• Subject Areas: Data and Information Technology; Design; Highways; Pavements; I22: Design of Pavements, Railways and Guideways;

Filing Info

• Accession Number: 01110078
• Record Type: Publication
• Source Agency: UC Berkeley Transportation Library
• Files: BTRIS, TRIS, ATRI
• Created Date: Aug 31 2008 8:11AM