1 / 68

Ancona , Italy Prasanth Tanikella and Jan Olek Purdue University

Incorporating Physical and Chemical Characteristics of Fly Ash in Statistical Modeling of Binder Properties. Ancona , Italy Prasanth Tanikella and Jan Olek Purdue University. June 30 th , 2010. Objectives and Hypothesis. The goal of this research was to :

mairi
Télécharger la présentation

Ancona , Italy Prasanth Tanikella and Jan Olek Purdue University

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Incorporating Physical and Chemical Characteristics of Fly Ash in Statistical Modeling of Binder Properties Ancona, Italy PrasanthTanikella and Jan Olek Purdue University June 30th, 2010 Jan Olek- Purdue University

  2. Objectives and Hypothesis • The goal of this research was to: • Characterize two sets of fly ashes (Class C and Class F) • Statistically verify the importance of their physical and chemical properties on the performance of binary paste systems • Scope of the Project (2 Phases) • Phase 1 – Characterization of Fly Ashes • Phase 2 – Effect of Fly Ashes on the Properties of Binary Paste Systems (cement + fly ash) Jan Olek - Purdue University

  3. Phase 1 Phase 1 – Characterization of Fly Ashes • Collected 20 different fly ashes (13 Class C and 7 Class F) • 15 of them ( 9 Class C ashes and 6 Class F ashes) are currently on the INDOT’s list of approved pozzolanic materials • A database summarizing the physical and chemical characteristics of the collected fly ashes and the impact of these properties on the behavior of binders would benefit the engineers, contractors and concrete producers Test Methods Jan Olek - Purdue University

  4. Phase 1 ResultsRange of chemical compositions Jan Olek - Purdue University * INDOT list of approved fly ashes

  5. Phase 1 ResultsRange of physical characteristics Jan Olek - Purdue University * INDOT list of approved fly ashes

  6. Phase 1 ResultsXRD – Typical Class F Fly Ash XRD pattern for Elmer Smith fly ash • Typical X-ray patterns for Class F fly ashes • Includes 1. Quartz – SiO2 2.Mullite – Al6Si2O13 3. Anhydrite – CaSO4 4. Hematite – Fe2O3 5. Magnetite – Fe3O4 6. Lime – CaO • Measured magnetic content is generally very high (with two exceptions) • A hump, representing a silica-type glass with a maximum at 2θ=~25° is visible • Glass “hump” is generally higher than that observed for Class C ashes XRD pattern for Miami 7 fly ash Jan Olek - Purdue University

  7. Phase 1 ResultsXRD - Typical Class C Fly Ash • X-ray pattern for a typical Class C fly ash • Includes 1. Quartz – SiO2 2. Anhydrite – CaSO4 3. Merwinite – Ca3Mg(SiO4)2 4. Periclase – MgO 5. Lime – CaO • Glass peak is similar for all the ashes of this type • Magnetite might be present in the fly ash, either in crystalline form or in the glass • A hump, representing a calcium-aluminate type of glass with a maximum at 2θ=~30° is visible XRD pattern for Hennepin fly ash Jan Olek - Purdue University

  8. Phase 1 ResultsXRD – Glass Content Estimation • Glass content was empirically estimated by calculating the area under the glass hump • Three softwares were used for the purpose • xyExtract – To extract points from the XRD pattern • LabFit – To fit the curve very precisely through the extracted points • Sicyon Calculator – To integrate the fitted curve Jan Olek - Purdue University

  9. Phase 1 ResultsParticle Size Distributions • Class F and Class C ashes form two different bands of PSDs • The band of Class C ashes is shifted towards the left of the band of Class F ashes Class C Class F Jan Olek - Purdue University

  10. Phase 1 ResultsDiscrepancies in PSD • Discrepancies observed in PSD • The pipette analysis seems to work well for particles larger than 5 micron • The results below 5 microns seem to diverge from either of the curves • Even though the sedimentation technique does not work well for particles smaller than 5 microns, based on the data it is reasonable to assume that the PSD based on Lab 1 (Purdue) data is accurate Jan Olek - Purdue University

  11. ResultsMorphology of class F (Type I) ashes • There is a large variation in the sizes and shapes of the particles • Particles with rugged surface are generally magnetic, contrary to the class C fly ashes • Many hollow particles present • Relatively smaller number of unburnt carbon particles, but bigger particles have been observed, which is consistent with the higher LOIsvalues observed in Class F ashes Zimmer Elmer Smith Petersburg Mill Creek Jan Olek - Purdue University

  12. ResultsMorphology of class C ashes • Wide range of sizes of spherical particles • Many hollow particles with shell generally composed of silica and alumina • Frequent irregularly-shaped particles (often with rugged surfaces) predominantly composed of sulfates or magnesium, or rarely sodium Labadie Kenosha Will County Rush Island Jan Olek - Purdue University

  13. Phase 1 Summary – Phase 1Characterization of fly ashes • Significant variations in the chemical and physical characteristics of fly ashes observed • The strength activity index of Class C ashes was higher than Class F ashes • The glass content for all the Class C ashes was higher than the glass content for all but two Class F ashes, thus indicating that although Class C fly ashes have less glass than these two Class F ashes, the glass in Class C ashes is more reactive • The morphology of the ashes was similar irrespective of the class, with a few exceptions • The particle size distributions of class C and class F ashes were significantly different • All mean particle sizes in class F were larger than mean particle sizes in class C ashes, resulting in a lower surface area of class F ashes • The LOI values of all class F ashes were higher than that of the C ashes Jan Olek - Purdue University

  14. Phase 2 - Evaluation of the hydration characteristics of cement-fly ash binder systems • Binder systems consisted of portland cement with 20% (by weight) replaced by fly ash • Pastes with constant water/binder ratio (0.41) were tested for various properties including, • Initial Time of Set – Vicat needle (ASTM C 191) • Heat of Hydration – Isothermal Calorimetry (at a constant temperature of 21 oC) • Amount of Calcium Hydroxide at ages 1, 3, 7 and 28 days - TGA • Non-evaporable water content at 1,3 7 and 28 days – TGA • Rate of strength gain at 1, 3, 7 and 28 days – Strength activity index (ASTM C 311) Jan Olek - Purdue University

  15. Phase 2 Initial Setting Time - Results Flash Set • Range of set time for Class C ashes – (1 hour to 4.5 hours) • Range of set time for Class F ashes – ( 2.5 hours to 3.5 hours) Jan Olek - Purdue University

  16. Phase 2 A Typical Calorimeter Curve Time of Peak Heat • Data acquired from the calorimeter curve • Peak heat of hydration (W/kg) • Time of peak heat of hydration (minutes) • Total heat of hydration (J/kg) – ( Area under the curve from 60 minutes to 3 days) Total Heat Jan Olek - Purdue University

  17. Phase 2 Peak Heat of Hydration - Results • Most ashes tend to reduce the peak heat of hydration compared to cement • Class F ashes in general have a higher peak heat of hydration than Class C ashes • Kenosha, the fly ash with the lowest peak heat of hydration had a flash set Jan Olek - Purdue University

  18. Phase 2 Time of Peak Heat of Hydration - Results • Most ashes tend to delay the occurrence peak heat of hydration compared to cement • Class C ashes in general have a higher time of peak heat than Class C ashes • Kenosha, the fly ash with the lowest peak heat of hydration had longest time of peak heat Jan Olek - Purdue University

  19. Phase 2 Thermo-gravimetric Analysis (TGA) • Calcium hydroxide content and non-evaporable water content were estimated using TGA at various ages (1, 3, 7 and 28 days) • Calcium Hydroxide content between 480oC and 550oC (carbonation taken in to account) • Non-evaporable water content calculated according to Barneyback, 1983. Jan Olek - Purdue University

  20. Phase 2 Calcium Hydroxide Content at 1 day - Results • Most ashes tend to reduce the amount of calcium hydroxide at 1 day compared to plain cement paste (with some exception) • Class F ashes have a slightly higher CH content than Class C ashes at early ages Jan Olek - Purdue University

  21. Phase 2 Calcium Hydroxide Content at 28 days - Results • Most of the ashes show a higher amount of calcium hydroxide at 28 day compared to plain cement paste • Difference in the rates of reactions in the fly ashes Jan Olek - Purdue University

  22. Phase 2 Strength Activity Index at 28 days - Results • All of the Class C ashes show a higher strength at 28 days compared to plain cement paste while Class F ashes show a lower strength comparatively Jan Olek - Purdue University

  23. Phase 2 Statistical Modeling of Binary Binders Jan Olek- Purdue University

  24. Phase 2 Statistical Modeling of Binary Binders Jan Olek - Purdue University

  25. Dependent Variables Jan Olek - Purdue University

  26. Phase 2 Ten Models with the highest Adj-R2 – Set Time Jan Olek - Purdue University

  27. Phase 2 ANOVA Table (Class C Ashes) – Set Time Jan Olek - Purdue University

  28. Phase 2 Observed Vs Predicted (Class C Ashes) – Set Time Jan Olek - Purdue University

  29. Phase 2 ANOVA Table (Class F Ashes) – Set Time Jan Olek - Purdue University

  30. Phase 2 Observed Vs Predicted (Class F Ashes) – Set Time Jan Olek - Purdue University

  31. Phase 2 ANOVA Table (Class C Ashes) – (SAI) at 28 days Jan Olek - Purdue University

  32. Phase 2 ANOVA Table (Class F Ashes) – (SAI) at 28 days Jan Olek - Purdue University

  33. Phase 2 Observed Vs Predicted (Class F Ashes) – Set Time Jan Olek - Purdue University

  34. Phase 2 Summary- Phase 2Binary Binder Systems • Physical characteristics of fly ash had a higher effect than chemical characteristics of fly ash • Surface area was found to be the most influencing variable affecting most of the properties of the binder system at both early and later ages • Variables including SAI (at later ages) and time of peak heat of hydration can be predicted accurately using the respective statistical models Jan Olek - Purdue University

  35. Conclusions • Class C and F ashes were significantly different in both their physical characteristics and chemical composition • There was significant difference in the effect of the two classes on binder properties • Both physical and chemical characteristics of fly ash had an effect on the binder systems • The sets of variables affecting each of the properties were unique • The signs of the coefficients in the models indeed pointed out the type of effect on the property • The statistical analysis of the properties of binary binders allowed us to draw inferences about the characteristics of fly ash which held the highest importance Jan Olek - Purdue University

  36. Conclusions • Some of the properties could not be accurately predicted by the statistical models with good significant as there were errors introduced by the limited number of variables chosen for modeling • Specific surface area of the fly ash had the highest impact on all the properties of binder systems Jan Olek - Purdue University

  37. THANK YOU Jan Olek - Purdue University

  38. Phase 2 Total Heat of Hydration - Results • Most ashes tend to reduce the total heat of hydration compared to cement • Most Class C ashes have a similar total heat of hydration • Quite a few of the Class F ashes have a similar total heat of hydration as that of most Class C ashes Jan Olek - Purdue University

  39. Phase 2 Non-evaporable Water Content at 1 day - Results • Most ashes tend to lower the amount of non-evaporable water content at 1 day compared to plain cement paste • Plain cement has a higher degree of hydration than most of the fly ash pastes Jan Olek - Purdue University

  40. Phase 2 Non-evaporable Water Content at 28 days - Results • Most of the Class C ashes show a higher amount of non-evaporable water at 28 day compared to Class F ashes • Difference in the rates of reactions in the fly ashes PrasanthTanikella - Purdue University

  41. Phase 3 – Ternary Binder Systems • Ternary Binder System – Cement + 2 different fly ashes • Total 20 % of the cement replaced with the mixture of fly ashes at specific percentages • Water/binder ratio was 0.41 (unless specified in the standard) OBJECTIVES • To ascertain the applicability of the weighted sum of the models chosen for the binary paste systems to predict the properties of ternary binder systems. • The analysis of which of the chosen independent variables (from binary binder models) have the highest effect on the properties of ternary systems PrasanthTanikella - Purdue University

  42. Phase 3 Ternary Binder Systems Experimental Design • Full factorial design consists of 180 experiments when the ratio of the two fly ashes is fixed • Fractional factorial design – Orthogonal Array Technique (Taguchi Method) Requirements of a Fractional Factorial Design • Reduction in the number of experiments • The data should be a representative data set of the full factorial design • The quality of the inferences obtained should be similar to the inferences from the full factorial design PrasanthTanikella - Purdue University

  43. Phase 3 Orthogonal Array Technique – Taguchi Method • A special test matrix is prepared • Columns – Factors (Dependent Variables) • Rows – Each row is an experiment (Mix design) • Values in the table – Factors levels, levels at which the three factors are varied PrasanthTanikella - Purdue University

  44. Phase 3 Test Matrix for Set Time • Columns – Factors (Sulfate, Alumina, Glass) • Rows – Each row is an experiment (Mix design) • Factor Levels – 33.33 , 50 and 66.67 percentile of the available data set PrasanthTanikella - Purdue University

  45. Phase 3 Scaled Standard Deviation - SSD • It is practically not possible to choose two ashes (in any proportions) having a target combination of three different factors Standardizing the Error in the Fly Ash Combinations • Scaled Standard Deviation (SSD) to evaluate the error of the combination SSD = • SSD values up to 0.3 were found to give a good approximation of the target values PrasanthTanikella - Purdue University

  46. Phase 3 Analysis of the Data - Additivity Model 1 – The two models obtained for Class C and Class F ashes from the binary binder, with the chosen independent variables (factors) were used to predict the properties (dependent variables) for both the Classes of ashes separately. The two predicted values were then added in the proportions of the added fly ashes to obtain the final value of prediction for the ternary binder system. This value was compared with the experimentally observed values. • Model 2 – The best models obtained for Class C, Class F ashes individually were used to predict the properties of the ashes in the mixture separately, and the predicted values of the properties were added in the proportion of the ashes to obtain the final value of the predicted properties of the ternary binder systems. • Model 3 – The model obtained for the entire set of Class C and Class F ashes together using all the 20 data points, containing the best three chosen independent variables was used to predict the properties of Class C and Class F ashes separately. PrasanthTanikella - Purdue University

  47. Phase 3 Analysis(Objective 2) – Influencing Variables • Analysis of Variance (ANOVA) – Factor level ANOVA • Total Sum of Squares , ST = • Variation caused by a single factor A, SA = - • where, NA1 = total number of experiments in which level 1 of factor A is present • A1 = the sum of the results of level 1 of factor A (Xi) • Mean squares (Variance): VA = • Pure sum of squares: SA’ = SA – (Ve x fA) • Percent Influence: PA = • where, fA is the degrees of freedom for factor A • Ve is the variance for the error term, which is calculated as • Se = error sum of squares • fe = error degrees of freedom • T = sum of the results (Xi) and N is total number of results PrasanthTanikella - Purdue University

  48. Phase 3 Test for Additivity – SAI 28 days (%) • Observed Strength higher than most predicted for all the combinations of the fly ash PrasanthTanikella - Purdue University

  49. Phase 3 Percent Influence • Observed Strength higher than most predicted for all the combinations of the fly ash PrasanthTanikella - Purdue University

  50. Phase 3 Summary - Phase 3Ternary Binder Systems • None of the properties were found linearly additive Reasons could be: • Variables chosen in the binary binder systems can not explain a significant variation in the dependent variables • A few of the binary binder models were not significant and the error carried into the analysis of the ternary binder systems • The chosen variables might not be “linearly” related to the properties of the binary binder systems • Weighted linear combinations of strength activity index at 28 days suggest a synergistic effect in the addition of two ashes to the binder system • Physical properties of the fly ashes were more influencing than the chemical composition in most of the properties • Surface area of fly ashes has the highest effect on the properties • The most influencing variables on ternary binder systems were similar to the ones for binary binder systems PrasanthTanikella - Purdue University

More Related