- Author
-
Bentz, D. P.
|
Feng, X.
|
Haecker, C. J.
|
Stutzman, P. E.
- Title
- Analysis of CCRL Proficiency Cements 135 and 136 Using CEMHYD3D.
- Coporate
- National Institute of Standards and Technology, Gaithersburg, MD
- Report
-
NISTIR 6545,
August 2000,
23 p.
- Distribution
- For more information contact: Website: http://ciks.cbt.nist.gov/bentz/cem135a136/cem135a136.html AVAILABLE FROM National Technical Information Service (NTIS), Technology Administration, U.S. Department of Commerce, Springfield, VA 22161. Telephone: 1-800-553-6847 or 703-605-6000; Fax: 703-605-6900. Website: http://www.ntis.gov
- Keywords
-
cements
|
computer models
|
heat of hydration
|
hydration kinetics
|
particle size distribution
|
SEM imaging
|
strength development
- Abstract
- This NISTIR provides experimental and computer modeling results for cements 135 and 136 issued by the Cement and Concrete Reference Laboratory at NIST in January of 2000. The purposes of this report are to characterize these cements via scanning electron microscopy (SEM) analysis and to document the ability of the NIST computer model, CEMHYD3D, to predict the hydration kinetics, heat of hydration, and mortar strength development of Portland cements evaluated in the CCRL proficiency sample program. The general procedure to evaluate a new cement is as follows: 1) two-dimensional SEM backscattered electron and X-ray microanalysis images of the cement of interest are obtained, along with a measured particle size distribution (PSD), 2) based on analysis of these images and the measured PSD, three-dimensional microstructures of various water-to-cement ratios are created and hydrated using CEMHYD3D, and 3) the model predictions for degree of hydration under saturated and sealed conditions, heat of hydration (ASTM C186), and strength development of mortar cubes (ASTM C1O9) are compared to experimental measurements either performed at NIST or at the participating CCRL proficiency sample evaluation laboratories. For both cements, generally good agreement is observed between the model predictions and the experimental data, demonstrating the predictive capabilities of CEMHYD3D.