METHODOLOGY FOR IMPROVEMENT OF OXIDE RESIDUE MODELS FOR ESTIMATION OF AGGREGATE PERFORMANCE USING STOICHIOMETRIC ANALYSIS

A methodology is presented for improving the predictive ability of oxide-based chemical models that predict aggregate material properties using the chemical composition of the coarse aggregate. Because portland cement concrete is composed of 70 to 85% coarse and fine aggregates (by weight), the aggregate material properties have a profound effect on the material properties of the finished concrete and ultimately on pavement performance. An existing computer program, CHEM1, has been used to estimate these concrete properties (compressive and tensile strength, elastic modulus, and drying shrinkage) through stochastic models based on user-input oxide residues. This approach, although adequate for some applications, suffers from the fact that concrete properties are influenced more by the mineralogy of the aggregate than by the oxides formed from their decomposition. Using Stoichiometric analysis, the CHEM2 program backcalculates the original mineral composition from the oxides and thereby improves the accuracy of the models. The CHEM2 program also adds the ability to predict for aggregate blends and a model for thermal coefficient of expansion, both of which were lacking in CHEM1.

Language

  • English

Media Info

  • Features: Figures; References; Tables;
  • Pagination: p. 59-64
  • Monograph Title: Aggregates: waste and recycled materials: new rapid evaluation technology
  • Serial:

Subject/Index Terms

Filing Info

  • Accession Number: 00667646
  • Record Type: Publication
  • ISBN: 0309055156
  • Files: TRIS, TRB
  • Created Date: Oct 11 1994 12:00AM