X. Wang, K. Wang, J. Han, P. Taylor Image Analysis Applications on Assessing Static Stability and Flowability of Self-Consolidating Concrete by X. Wang, K. Wang, J. Han, P. Taylor June, 2014
Objective Use digital image process and analysis (DIP) to evaluate the static stability of SCC Develop statistical models for predicting flowability from hardened SCC Investigate/calibrate the relationship between parameters derived from DIP method and existing theoretical frame, i.e., excessive paste theory and paste-to-voids volume concept
Background Excess paste/mortar theory The “lubricating” layer of paste around aggregates needs to be Thin enough: prevent coarse aggregate from sinking down and segregating Thick enough: achieve good workability Two main parameters: Dss: average spacing between aggregate particle surfaces Dav: average aggregate diameter Assumptions: Aggregate particles are spherical Particles are packed in a cubic lattice
Background Vpaste/Vvoids concept Provide a quantitative means to consider the interaction between paste and aggregate system Take into account differences between aggregate systems Coat the aggregate particles Fill the voids between the combined aggregate system Disperse the aggregate particles to provide workability
Background Digital image process (DIP) Features: Steps: Rapid, evaluate large number at one time, free from subjectivity, and easy to characterize aggregate features Steps: Image acquisition, pre-processing, segmentation, representation and description, and recognition and interpretation Applications in concrete research: Algorithm development to provide optimum threshold and aggregate size distribution Crack length and fracture properties Fractured aggregate area ratio Aggregate shape and strength Aggregate shape parameters and concrete rheology Air-void system in hardened concrete
Materials Coarse aggregate types: crushed limestone (LS) and river gravel (G); Coarse aggregate sizes: 19 mm (a), 12.5 mm (b), and 9.5 mm (c); SCMs: Class C and F fly ashes (C and F) with 25% replacement level, slag cement (S) 30% replacement level; Limestone dust (LD) amounts: 0 and 15% cement replacement. w/cm: 0.36 to 0.42 Fine-to-total aggregate volume: 0.45 for 19 mm NMSA; 0.47 for 12.5 mm; 0.50 for 9.5 mm
Materials and Mix Proportioning 40 SCC mixtures Low slump flow range between 550 and 650 mm or high flow range between 650 and 750 mm Visual stability index, (VSI)≤1 J-ring ≤ 75 mm
Research Plan
DIP Method
DIP Method Aggregate system used in excessive paste theory (left) and defined in this research
DIP Method a b c d
Results
Results Static stability
Results Probability density vs. HVSI
Results Rheological models Response surface models SF = 657.21 + 36.44 × MTI – 1.56 × τ – 114.07 × (MTI – 1.89) × (ŋ – 0.99) – 93.74 × (ŋ –0.99)2 + 0.04 × (τ – 33.41)2 => SF= 397 + 0.04τ×(τ –106) – 94ŋ×(ŋ – 4.27) +149×(1 – 0.77ŋ) × MTI For a given paste, SF∝MTI Critical viscosity of 1.3 Pa-s
Results
Results Relationship between results from DIP method and existing theoretical frames
Results Average inter-particle spacing from DIP method vs. Dss calculated from excessive paste theory
Conclusions Proposed DIP method and algorithm works Potentially overcomes the limitations of existing theory frames Quantitatively assess stability and workability Probability density of 60% from histogram analysis as a threshold for indicating a uniformly distributed SCC mixtures Viscosity of 1.30 Pa-s tends to be a critical point
Questions?
Appendix Fresh properties and DIP results of limestone SCC mixtures
Appendix Fresh properties and DIP results of gravel SCC mixtures