Methods of predicting aggregate voids : [technical summary].

Details

• Creators:
  Smyl, Danny
• Corporate Creators:
  Kansas. Dept. of Transportation. Bureau of Materials & Research
• Subject/TRT Terms:
  Aggregate Gradation Aggregate Tests Mathematical Prediction Methodology Void Ratios
• Publication/ Report Number:
  FHWA-KS-12-8
• Resource Type:
  Tech Report
• Geographical Coverage:
  Kansas
• Corporate Publisher:
  Kansas. Dept. of Transportation. Bureau of Materials & Research
• NTL Classification:
  NTL-HIGHWAY/ROAD TRANSPORTATION-HIGHWAY/ROAD TRANSPORTATION
• Abstract:
  Percent voids in combined aggregates vary significantly. Simplified methods of predicting aggregate voids were studied to determine the feasibility of a range of gradations using aggregates available in Kansas.
  
  The 0.45 Power Curve Void Prediction Method was developed at KDOT as an experimental method of predicting combined aggregate voids. The Coarseness Factor is another option for analyzing aggregate gradation. Rather than analyzing all sieve sizes, the coarseness factor chart looks at aggregate as a whole. The Coarseness Factor separates aggregates into three categories: coarse, fine and intermediate. The Coarseness Factor Void Prediction Method was created at KDOT as a simplified method of predicting percent voids in combined aggregate. The coarseness factor is the dependent variable in the void prediction method; it is easily computed and conveys the overall gradation of combined aggregates with a number.
  
  
• Format:
  PDF
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha-512:5f08596d9764bd877a2a32010db493f06cc1f572139216e99471f9fc537fcce807a3cdeb659dec322af88a8ee030ab88d3cae451681562540021b38caa22f5ab
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/25821/dot_25821_DS1.pdf
• File Type:
  [PDF - 185.51 KB ]