Curing of Concrete Spatial and Temporal Randomness Over Multiple Length Scales

1. Curing of ConcreteSpatial and Temporal Randomness Over Multiple Length Scales Jeffrey W. Bullard National Institute of Standards and Technology Gaithersburg, Maryland 20899

2. Inorganic Materials Group at NIST: • Edward Garboczi, Group Leader • composite theory, elasticity, finite element models • Dale Bentz • microstructure models • Clarissa Ferraris • experimental rheology, durability • Nicos Martys • computational rheology, fluid dynamics • Ken Snyder • transport properties • Paul Stutzman • materials characterization, QXRD, SEM

3. Spatial Complexity of Concrete Macro-scale Courtesy Portland Cement Association

4. t = 0.5 h Ettringite C-S-H Gel Microstructure Development in Cement Paste t = 0 Gypsum C3A C2S C3S

5. Microstructure Development in Cement Paste t = 4 h t = 672 h C-S-H C-S-H CH C-S-H C-S-H

6. Structural Complexity of Cement Paste Micro-scale 150 µm 75 µm 250 µm • 3-D solid-pore random composite • Porosity forms 3-D percolating network • Solids may begin as percolating (or not) “soft” clusters; later form stiff percolating network

7. CMS of Cement & Concrete at NIST Objective:Predict microstructure development and its influence on properties (mechanical, transport, rheological) and durability 20 µm Principal: input µ-structure model hydration of µ-structure predict properties compare w/ experiment Digitize Each volume element has properties of the phase at that location in space

8. Ca Si Al K K … X-ray Element Maps … … are used to segment image into phases Building a Representative 3-D Microstructure SEM/BSE Image…

9. Building a Representative 3-D Microstructure • 2D Segmented image is analyzed by constructing autocorrelation functions on the majority phases • Autocorrelation functions are used to distribute these phases statistically in a 3D digitized microstructure 3-D image of model cement paste

10. Cellular Automaton Model of Hydration • Current Approach • Each volume element is an independent agent that can • Dissolve • Diffuse • React Pore solution Stepwise random walk on lattice Collisions between agents, governed by reaction “rules”

11. Illustration of Model Cement Hydration Image courtesy of Dale Bentz, NIST initial/dissolution/diffusion/early/late This example is in 2D, but all our modeling efforts are on 3D microstructures

12. Heat of Hydration

13. Predicted Adiabatic Heat Signature

14. Prediction vs. Experiment

15. Calculated Elastic Properties

16. But … • Rules are incomplete or inaccurate model of mechanisms • Consequences: • No intrinsic time scale (empirical mapping via fitting to experimental data) • Rules are customized to 1-µm length scale; no convergence behavior; model breaks down at any other length scale • Primarily interpolative--- works for those systems upon which the rules were calibrated Status … • Model quantitatively reproduces some phenomena quite well • Digital image format allows 3D spatial complexity • CA algorithm allows rapid evolution of µ-structure and tracking of properties (pixel counting)

17. Modeling the C-S-H Gel is Crucial • For most of hydration, reactions are rate-controlled by ionic diffusion through gel structure • Need to know the transport factor for ionic species in C-S-H gel transport properties hydration conditions C-S-H structure & composition Next Steps … • Place the hydration model on firmer theoretical basis • Implement diffusion, nucleation, growth, etc using CA methods, but using rules with strict ties to diffusion and transition state theories

18. Structural Complexity of C-S-H Gel Nano-scale “IP” “OP” Porosity Micrograph courtesy of I.G. Richardson, University of Leeds 50 nm CaxSiO(2+x)·H2O

19. Structural Complexity of C-S-H Gel Nano-scale C3S Paste, 20°C, 8 yr “IP” “OP” “IP” Micrographs courtesy of I.G. Richardson, University of Leeds “OP” C3S Paste, 80°C, 8 d

20. How to Obtain? • Enlightening experiments are very difficult to design and control • Molecular scale or multiscale models? • Brownian dynamics used to study colloidal gel formation • Molecular dynamics (gel structure, reaction mechanisms) • Kinetic Monte Carlo (nano-scale film growth, etc.) Critical Information Needed to Better Model Hydration and Microstructure Development … • Nanoscale understanding of C-S-H nucleation and growth mechanisms, and structure under different hydration conditions • Function of temperature, aqueous composition • Some exists in literature, needs to be synthesized • Other information needed, too, but lower priority • Composition ranges of hydration products (C-S-H, ettringite, etc.) • Growth morphologies of hydration products

21. Each voxel is a tri-linear finite element Solve elastic state by minimizing 4 E, G obtained by sum over all voxels

22. Individual phase moduli • Some cement minerals in the geology literature, or have been measured (Lafarge) or being worked on • Nanoindentation gives EC-S-H25-30 GPa • Good ultrasonic data for C3S seems to overestimate E slightly • Good ultrasonic data for CH and ettringite • Do C-S-H moduli change with age? Probably yes, but no evidence for how much, so neglect for now

23. Concrete Rheology Model: Dissipative Particle Dynamics Brownian Dynamics+ Momentum Conserving Collision Hydrodynamic Behavior Model developed by N. Martys (NIST) based on an algorithm by Hoogerbrugge and Koelman (1992)

24. Concrete flow: diam. 0.2

25. Coaxial Rheometer

26. What Is TheVirtual Cement and Concrete Testing Laboratory? • Internet-based and menu driven • Predicts properties based on detailed microstructure simulations of well-characterized starting materials • Goal is to reduce number of physical concrete tests, thus expediting the R&D process and enabling optimization in the material design process

27. CURING CONDITIONS adiabatic, isothermal, T-programmed sealed, saturated, saturated/sealed variable evaporation rate PREDICTED PROPERTIES degree of hydration chemical shrinkage pore percolation pore solution pH ion concentrations concrete diffusivity set point adiabatic heat signature strength development interfacial transition zone rheology (yield stress, viscosity) workability elastic moduli hydrated microstructures VIRTUAL CEMENT AND CONCRETE TESTING LABORATORY (VCCTL) http://vcctl.cbt.nist.gov CEMENT PSD phase distribution chemistry alkali content AGGREGATES gradation volume fraction saturation shape SUPPLEMENTARY CEMENTITIOUS MATERIALS PSD, composition silica fume, fly ash slag, kaolin,limestone MIXTURE PROPERTIES w/cm ratio fibers chemical admixtures air content Industrial Participants CEMEX,Dyckerhoff Zement GmbH, HOLCIM INC., International Center for Aggregate Research, Master Builders Technologies, PORTLAND CEMENT ASSOCIATION Verein Deutscher Zementwerke e.V., W.R. Grace & Co.- CT

28. VCCTL Web Interface

29. VCCTL Extensionto Durability PREDICTED PROPERTIES degree of hydration chemical shrinkage pore percolation pore solution pH ion concentrations concrete diffusivity set point adiabatic heat signature strength development interfacial transition zone rheology (yield stress, viscosity) workability elastic moduli hydrated microstructures DEGRADATION MODELS sulfate attack chloride ingress (corrosion) freeze/thaw damage alkali-silica reaction carbonation leaching SERVICE LIFE PREDICTION and LIFE CYCLE COSTING transport reactions stress generation/ cracking ENVIRONMENT temperature relative humidity carbon dioxide sulfates chlorides alkalis stress state

30. Final Remarks • VCCTL is based on years of computational and experimental materials science research • VCCTL is being “made ready for prime time” with the help of companies and industrial groups • These partners cover all the generic materials that make up concrete • The field of cement and concrete materials needs to be, and will be, revolutionized • VCCTL is leading the way • THERE’S ALWAYS ROOM AT THE BOTTOM! (R. Feynman)

31. NIST/ACBM Modeling Workshop • Annual 5-day summer workshop hosted by NIST • Covers key concepts relevant to many areas of computational materials science • Composite/Effective Medium Theory • Percolation Theory • Microstructure modeling • Finite element/Finite Difference methods • And more • Ideal for grad students and/or faculty who are new to computer modeling of composites Visit http://ciks.cbt.nist.gov/~garbocz/let02.html

32. What is Computational Materials Science? K. Beardmore, Loughboroug University, UK J.D. Joannopoulos et al. ab-initio.mit.edu Techniques depend on length and time scales J. Guo and C. Beckermann, U. Iowa J. Ramirez et al, U. Iowa

33. How Can We Construct 3-D Microstructuresfrom 2-D Images? • Autocorrelation functions • provide information on volume fraction and surface area fraction of individual phases • are identical in 2-D and 3-D! • Measure autocorrelation fns. on 2-D images for each clinker phase • Use them to build a 3-D microstructure that is consistent with these functions f -S S f2 r

34. Building a Representative 3-D Microstructure X-ray Microprobe Analysis RGB image: Ca, Si, Al (courtesty of Paul Stutzman)

35. Model Output … • Degree of hydration of all phases • phase fractions vs. time • Heat release • adiabatic heat signature • Chemical shrinkage • Phase percolation properties (set point and capillary porosity) • Elastic moduli (by coupling to FE calculation) • Compressive strength (via Power’s gel-space ratio or differential EMT on a mortar or concrete) • Transport factor (relative diffusivity) • Pore solution pH, ionic concentrations, and conductivity

36. Building a Meaningful 3-D Microstructure • Microstructure Information • Cement particle size distribution • Cement phase composition and statistical distribution • Gypsum content and form (hemihydrate, anhydrite) • Flocculation/Dispersion • Individual Phase Properties • Specific heat, heat of formation, elastic moduli, etc. • Kinetic Information • Model reaction mechanisms (nucleation, • Activation energies (cement and mineral admixtures) • Curing conditions (isothermal/adiabatic, saturated/sealed)

37. Chemical Complexity of Cement Paste c = 10 chemical species (Ca, O, Si, Al, Fe, S, Mg, K, Na, H) Gibbs Phase Rule • Maximum number of phases that can coexist at equilibrium is c + 2 =12 • During curing, we often find twice as many coexisting phases. Many are amorphous or poorly crystalline and finely divided • A hydrating cement paste is a complex chemical system far from equilibrium 75 µm