Durability of clay roofing tiles: assessing the reliability of prediction models

Transcription

1 11-14 May 2008, Istanbul Durability of clay roofing tiles: assessing the reliability of prediction models M. Raimondo, M. Dondi, C. Ceroni*, G. Guarini ISTEC-CNR Institute of Science and Technology for Ceramics, Faenza (Italy) *DICASM, University of Bologna, Bologna (Italy)

2 Water-solid interactions.. depend on several variables: expansion of water in freezing freezing rates saturation of bodies variation of Young modulus solid pore amount solid pore size distribution, etc Freezing resistance has to be thought to be influenced by a combination of such variables Blachere and Young, JACS 57, [5], 1974

3 Experimental approach Study of the tile microstructure MIP, BET OP, BD, WA (ASTM C67, C373) SEM, XRPD (Rietveld refinement) Water-solid interaction Capillary rise (UNI EN , UNI 10859) Surface wettability Microstructural variables Porosity related behaviour Durability indices Target Clay roofing tiles with improved frost/thaw resistance Experimental test UNI EN Part 2

4 Models to calculate durability factors Pore amount (MIP, WA) Pore size (MIP) Saturation Coefficient Cs Kinetics of WA (WA 5h /WA 24h ) Maage 3.2/PV 2.4 P3(%) - - Arnott 424 (WA 5h /WA vac ) P3(%) 100 K 4 C s K s Vincenzini - Ф Franke/ Bentrup - Ф Koroth 451/( WA 5h ) (0.97 C s ) - Robinson (WA 24h -10) - 1/(1-C s ) 0.1 K s

5 M dbmc 7 Roofing tile typologies 1 G Sampling A H F 5 D I C K B L E J Coppo Over and under tile Marseillaise Portuguese

6 UNI EN Part 2: Test for frost resistance Climatic cell Freeze/thaw cycles Tests were carried out in the climatic cell from - 15 C to +15 C performing 400 freeze/thaw cycles; this number of cycles - much higher than those (150) scheduled by the reference standard - was chosen in order to simulate very extreme conditions.

7 B 375 cycles 250 Loss of interlocking rib 200 Results of UNI EN 539-2: Number of cycles and defect typology G 100 cycles Breack 400 cycles: 3 samples 375: 1 sample 250 cycles: 2 samples < 100 cycles: 4 samples < 50 cycles: 3 samples J 100 cycles Delamination, Exfoliation K 100 cycles I 75 cycles M 50 cycles 50 0 A B C D E F G H I J K L M Structural crack Peeling Chip, Surface cracks, Delamination

8 A dbmc Coarser grains, big pores and a quite regular smooth microstructure Frost resistance and products microstructure C 0 A B C D E F G H I J K L M BET = 0.7 m 2 /g BET = 1.8 m 2 /g Small and oriented grains, finer matrix and very few big pores

9 1. Freeze/thaw resistance vs Open porosity C OP = 28% Sample C Open porosity (%) M I J K F G L B H D A E Number of cycles OP = 13% Sample E

10 2. Freeze/thaw resistance vs Specific surface area 2,4 2,2 M SS = 2.2 m 2 /g Sample M Specific surface (m 2 /g) 2,0 1,8 1,6 1,4 1,2 C I J G F K L E B D H 1,0 0,8 A 0, Number of cycles SS = 0.7 m 2 /g Sample A

11 UNI vs Maage index Role of pore size DF 3.2 PV P3 MAAGE DF > 70 Resistant 55 < DF < 70 Doubtful behaviour DF < 55 Non resistant 160 P3 (%) A DF G E M I B J F L D H C K A B C D E F G H I J K L M Cycles GELO

12 UNI EN vs Ф 90 Role of pore size 5 DIAMETRO CRITICO A Critical diameter DCR C M I G K J F E Φ μm Frost resistant B H L D Φ μm Not frost resistant Cycles GELO

13 UNI EN vs Arnott index 9.2 P3 0.5 K s (WA 5h /WA) -100 K s C s Arnott's durability factor C M r 2 = 0,129 I G FK J E L A B C D E F G H I J K L M Freeze/thaw cycles B A H D The model proposed by Arnott present a good agreement with the P3 (%) experimental performances of scarcely (<100 cycles) and high resistant (>250 cycles) products; the main exceptions are always represented by samples L, B, H and D having excellent durability. The insertion into the multiple regression analysis of different physical and technological parameters, provides a model where the role of each variable is quantified by a statistical different weight: the amount of greater pores (P3) seems to be the most influent so that, accordingly, index values increases as the percentage of P3 increases.

14 ROB R 2 = C M I K J F G UNI EN vs Robinson index ROBINSON L E Ks Y 101 C Low Y = high frost resistance High Y = low resistance B H A D S E 24H Cycles GELO

15 Frost resistance and phase composition Quartz 6 42 % Plagioclase 0 44 % K-feldspar 1 13 % Pyroxene 0 32 % Melilite 0 6 % Illite 0 13 % Glassy phase 8 58 % Ca-silicates D C L H Unreacted phases: Quartz, K-feldspar New-formed crystalline phases: Ca-silicates New formed or residual phases: Amorphous, Illite A E F J K I G B Qz+Felds M Amorphous+Illite

16 Frost resistance and phase composition High amount of amorphous and residual phases Underfired product from a mineralogical point of view Amorphous + Illite (%) K B M I F J G E L H D C A Number of cycles

17 Frost resistance and phase composition Ca-silicates/amorphous + illite 4,5 4,0 3,5 3,0 2,5 2,0 1,5 1,0 0,5 0,0 C D A L H E J F I K G B M -0, Number of cycles High ratio between Ca-silicates amorphous and residual phases Higher sintering degree

18 1. Statistical analysis: extraction of the main components A. Extraction of the main components (StatSoft software 6.0) Inserted variables microstructural: BD, TP, Φ 50, Φ 90, P3, BET compositional: amount of Ca-silicates, Quartz and amorphous Number of cycles Factor 1 1,0 0,8 0,6 0,4 0,2 0,0-0,2-0,4-0,6 BD Qz F90 P3 F50 Freeze/thaw cycles Am Ca-sil TP -0,8 BET -1,0-1,0-0,8-0,6-0,4-0,2 0,0 0,2 0,4 0,6 0,8 1,0 Factor 2

19 Multiple regression analysis (Statsoft Statistica 6.0) Dependent variable: Number of freeze/thaw cycles Independent variables: Φ 50, Φ 90, BET, BD, TP, P3, Quartz, Amorphous and Ca-silicates Stepwise multiple regression analysis. R = ; R 2 = ; p < N=13 ß Std. Err. B Std. Err. p-level Intercept BET Amorphous BD Quartz Ca-silicates Φ

20 Multiple regression analysis : observed vs predicted values of freeze/thaw durability R 2 = B HA D E L Observed values C K M F I G J 4,0 3,0 2,0 1,0 Ca-silicates/Amorphous -50 0, A B C D E F G H I J K L M Predicted values Confidenza 95%

21 Conclusions Pore amount and pore size/morphology: Expected general trend only for samples with medium performances; Controversial informations about the excellent behaviour of the others samples Durability indices Maage: all samples are no frost resistant, but A according with its greater pore dimensions; Vincenzini: critical diameter is nor statistical significant for our sample; Arnott: good correlations are provided but just for samples having medium peformances; presence of many exceptions. Robinson: very scattered data. Behaviour of the most resistant products A deep understanding of their performances needs also the analysis of the production process and suggests the possible role played by the relative amount of mineralogical phases

22 Conclusions Designing of high performance roofing tiles: is it possible? Microstructural properties Open and total porosity Amount of pores >3 μm Pore dimensions Evaluation of structural properties, i.e body elasticity Sintering process and conditions Sintering degree Amount of new formed crystalline phases Ratio between amorphous, residual and new crystalline phases Highly frost resistant bricks

23 Process and product design Process variables: Firing temperature ( 900 C ) Increased amount of new formed phases; Optimum for frost resistance: Amorphous + Illite 25%; Crystalline/amorphous + Illite 1.5; Product variables Modulation of microstructure in terms of pore dimensions (Φ 50 and pores >3 μm) Increasing CaO content of the starting formulations Attention to the microstructure in order to obtain higher porosity but controlling the pore dimensions (BET should be lower)

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