# Presentation: 153670

## Edward J. Garboczi and Jeffrey W. Bullard 
Building and Fire Research Laboratory, NIST
September 16, 2002

- Edward J. Garboczi and Jeffrey W. Bullard
- Building and Fire Research Laboratory, NIST
- September 16, 2002

- VCCTL: A Web-Based Virtual Cement and Concrete Testing Laboratory

## Vision of VCCTL

- Can you imagine designing a complicated, expensive building empirically, without the use of finite element computational tools?
- ...yet we design concrete materials empirically
**VISION: *****Computer-design construction materials just like engineers computer-design structures***

## What is NIST?

- NIST = National Institute of Standards and Technology
- Department of Commerce laboratory
- 100 years of doing basic measurement technology research for the aid of  scientifically-based industrial standardization
- Cement research at NIST began in 1917
- Long history of cooperation between PCA and NIST, since the 1920’s (Bogue and Blaine)

## NIST: The HYPERCON Program

**Tool 1**:  *High-tech materials science experiments* including scanning electron microscopy; X-ray diffraction, absorption, and tomography; rheometry; and ion chromatography
**Tool 2**:  *World-leading advanced computational materials science*, using parallel processing, to predict concrete microstructure and properties
**Main output**:  Collaboration with industry in the Virtual Cement and Concrete Testing Laboratory

- Bringing basic experimental and computational
- materials science tools to bear on the prediction
- and optimization of real-world concrete properties

## Why Develop a VirtualTesting Lab?

- Current testing
- physical based
- manpower intensive
- materials intensive
- weeks/months
- high disposal costs

- Virtual testing
- computer based
- computation intensive
- small material needs
- days
- low disposal costs

## But characterization is the key

- To enable virtual testing requires characterization of raw materials (cement, aggregates, mineral admixtures) far beyond what has been systematically done before
-  BUT:  will enable modeling to be used profitably

## What Is TheVirtual 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

## History of the research behind the VCCTL

- 1982 – Development at NIST, under Geoff Frohnsdorff’s leadership, by Hamlin Jennings of first simple cement hydration model (continuum based)
- 1989
- NIST starts developing first (primitive) pixel-based simulation of cement hydration
- NIST starts developing finite difference methods for computing properties of pixel-based systems
- January 1, 2001 – Start of VCCTL
- So VCCTL is organization and further development, for industry benefit, of ~20 years of NIST research
- Collaboration between three NIST laboratories – Building and Fire Research, Information Technology, and Materials Science and Engineering

## VIRTUAL CEMENT

- 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**

_**CURING CONDITIONS**_
- adiabatic, isothermal, T-programmed
- sealed, saturated,  saturated/sealed
- variable evaporation rate

_**SUPPLEMENTARY CEMENTITIOUS**_
_**MATERIALS**_
- PSD, composition
- silica fume, fly ash
- slag*, kaolin,*limestone

_**AGGREGATES**_
- gradation
- volume fraction
- saturation
*shape*

_**MIXTURE PROPERTIES**_
- w/cm ratio
- fibers
- chemical admixtures
- air content

** **_**CEMENT**_
- PSD
- phase distribution
- chemistry
- alkali content

***Industrial Participants***
**CEMEX,**** ****Dyckerhoff Zement GmbH****, ****HOLCIM**** INC.,**
**International Center for Aggregate Research, **
**Master Builders Technologies, PCA,**
**Verein Deutscher Zementwerke e.V., W.R. Grace & Co.- CT**

## VCCTL Consortium:Industry Relevance and Leveraging

- Eight companies at present (Cemex, Holcim, Portland Cement Association, W.R. Grace, Master Builders, Dyckerhoff, VDZ, ICAR) at $40K/year plus research collaboration
- Well over 100% match by NIST funds
- All generic concrete raw material groups are represented in VCCTL – cement (portland and blended), chemical admixtures, and aggregates

## VCCTL Interface

- Web-based
- http://vcctl.cbt.nist.gov (Version 1.0)
- advanced versions at member sites
- Javascript, Perl, and cgi code to accept and validate user inputs and return results
- Gnuplot to create graphs of model (and experimental) results
- Interface launches to C modeling engines

**Notes:**
A variety of WEB authoring and programming tools are utilized in the VCCTL.  The system uses HTML forms to provide a familiar interface for the users.

## VCCTL Web Interface

**VCCTL Web Interface**

## Modeling Approach

- of the phase at that location in space

**Modeling Approach**

- Microstructure-Based
- Spatial resolution at the sub-particle level using small volume elements (1 m3)

- Each volume element has properties
- of the phase at that location in space

**Notes:**
A variety of WEB authoring and programming tools are utilized in the VCCTL.  The system uses HTML forms to provide a familiar interface for the users.

## What Input is Needed for Microstructure-Based Models?

- Individual Phase Properties
- Specific heat, heat of formation, elastic moduli, etc.
- Microstructure Information
- Cement (mineral admixture) particle size distribution
- Cement phase composition and distribution
- Gypsum content and form (hemihydrate, anhydrite)
- Flocculation/Dispersion
- Volume fraction of aggregates
- Kinetic Information
- Model reaction mechanisms
- Activation energies (cement and admixtures)
- Curing conditions (isothermal/adiabatic, saturated/sealed)

**Notes:**
To have any chance of simulating microstructure development and predicting performance, quantitative and extensive characterization of the raw materials (particularly the cement) is critical.

Only when we have characterized the starting materials can we have any hope of predicting what will happen when water is added to the system.

## What Kind of Problems Can the VCCTL Address?

- 3-D microstructures
- Degree of hydration of all phases
- phase fractions vs. time
- Heat release
- adiabatic heat signature
- Chemical shrinkage
- Compressive strength (via Power’s gel-space ratio)
- Elastic moduli
- Phase percolation properties (set point and capillary porosity)
- Diffusivity coefficient predictions (conductivities)
- Pore solution pH, ionic concentrations, and conductivity

**Notes:**
A variety of properties can be predicted using the VCCTL.  Each property can be graphed and experimental data can be included in the graph to compare the model and experiment.

As enhancements continue to be made to the VCCTL, more properties will be predictable (rheology, elastic modulus, etc.)

## How to Obtain Microstructure Input Data?Characterize Real Cement Microstructures!

**Notes:**
To have any chance of simulating microstructure development and predicting performance, quantitative and extensive characterization of the raw materials (particularly the cement) is critical.

Only when we have characterized the starting materials can we have any hope of predicting what will happen when water is added to the system.

## SEM backscattered electron image

**SEM backscattered electron image**
**of Portland cement**
**	****	****	****(courtesy of Paul Stutzman)**

**SEM backscattered electron image**
**of Portland cement**
**	****	****	****(courtesy of ****Paul Stutzman****)**

## RGB image: Ca, Si, Al

**RGB image: Ca, Si, Al**
**	****(courtesty of Paul Stutzman)**

**RGB image: ****Ca****, ****Si****, ****Al**
**	****(courtesty of ****Paul Stutzman****)**

## C3S, C2S, C3A, C4AF, gypum, CaO

**C****3****S, C****2****S, C****3****A, C****4****AF, gypum, CaO**

**C****3****S****, ****C****2****S****, ****C****3****A****, ****C****4****AF****, ****gypsum****, ****CaO**

## SEM/X-ray Characterization of Fly Ash (Municipal Waste Fly Ash from France)

**SEM/X-ray Characterization of Fly Ash (Municipal Waste Fly Ash from France)**

**Red- S**
**Blue- AS**
**Green- CAS****2**
**Orange- CaCl****2**
**Aqua- CaSO****4**
**White- inert**

**Red- S**
**Blue- AS**
**Green- CAS****2**
**Orange- CaCl****2**
**Aqua- CaSO****4**
**White- inert**

## How Can We Construct 3-D Microstructures from 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 functions on 2-D images for each clinker phase
- Use them to build a 3-D microstructure that is consistent with these functions

**Notes:**
To have any chance of simulating microstructure development and predicting performance, quantitative and extensive characterization of the raw materials (particularly the cement) is critical.

Only when we have characterized the starting materials can we have any hope of predicting what will happen when water is added to the system.

## 3-D image 

**3-D image **
**of model **
**cement**
**particles**

**3-D image **
**of model **
**cement**
**particles**

## Cement Image & PSD Database

- Internet accessible database at http://ciks.cbt.nist.gov/phpct/database/images
- Contains processed image, particle size distribution (PSD), and phase composition for each cement (links to ftp site to download correlation and related files)
- Version 1.0 contains data for 26 cements from 7 countries
- Versions at member sites can be customized for IP purposes

**Notes:**
One of the advantages of an Internet-based system is the worldwide accessibility it provides.  The cement images database can be accessed anywhere worldwide using a Web browser (Netscape, Internet Explorer, etc.)  The files can also be downloaded from an anonymous ftp site maintained at NIST.  The site is at ftp.nist.gov  and the files are in subdirectories under the pub/bfrl/bentz/CEMHYD3D/images directory.

## VCCTL:Better Understanding  Improved Models

- Extension of hydration model
- alkali species (pore solution composition) influence on hydration kinetics (NIST, Cemex, Dyckerhoff, W.R. Grace, VDZ)
- realistic cement particle shapes (NIST)
- more accurate modeling of slag hydration (NIST, Dyckerhoff)
- Standardization of PSD measurement (All, ASTM)
- Rheological properties (yield stress and viscosity)
- interactions between air entrainment and rheology (NIST, Grace, and Master Builders)
- Elastic and visco-elastic properties
- model validation (NIST, Dyckerhoff, Holcim)
- Aggregate shape effects on concrete properties (NIST, ICAR, all)

**Notes:**
The VCCTL is an evolutionary product and version 2.0 will feature more capabilities......

## Module forCement Paste Hydration

**Notes:**
To have any chance of simulating microstructure development and predicting performance, quantitative and extensive characterization of the raw materials (particularly the cement) is critical.

Only when we have characterized the starting materials can we have any hope of predicting what will happen when water is added to the system.

## How is Hydration Modeled?

- Cellular automaton 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”**

**Notes:**
One of the advantages of an Internet-based system is the worldwide accessibility it provides.  The cement images database can be accessed anywhere worldwide using a Web browser (Netscape, Internet Explorer, etc.)  The files can also be downloaded from an anonymous ftp site maintained at NIST.  The site is at ftp.nist.gov  and the files are in subdirectories under the pub/bfrl/bentz/CEMHYD3D/images directory.

## Illustration of Model Cement Hydration

**initial/dissolution/diffusion/early/late**

## Heat of Hydration

**Notes:**
Some examples of model predictions vs. experimental data.  The first shows isothermal calorimetry results compared to model predicted heat release for one cement at two different w/c ratios.  After the induction period (> 7 h), the agreement between model and experiment is excellent.

## Predicted Adiabatic Heat Signature

**Notes:**
The predicted heat release, in combination with knowledge of the mixture proportions (aggregate volume fraction), allows one to predict the adiabatic heat signature (temperature vs. time under adiabatic curing) for a given concrete.  Results shown here for a concrete with a 10 % silica fume addition once again illustrate a good agreement between model (solid line) and experiment (data points).

## Prediction of Compressive Strength

- Use gel-space ratio theory of Powers and Brownyard
- X = (0.68 * α)/(0.32 * α + w/c)= gel/space
- directly count gel and space in 3-D microstructure
- σc = A * Xn        (n=2.6 to 3.0)
- Calibrate A via measured 3-day compressive strength (assume n=2.6)
- Use hydration model to predict X vs. time and calculate 7-day and 28-day compressive strengths to compare to experiment

**Notes:**
To predict compressive strength, the gel-space ratio theory developed by Powers and Brownyard is employed.  As the cement hydrates, the model automatically keeps track of the amounts of gel and “space” within the 3-D microstructural volume element.  

Because the hydration products of each cement have a different intrinsic strength, one measured early-age compressive strength is used to calibrate the model predictions.  The model can then be used to predict later-age strengths.  For example, the model should be able to predict 28 d strength based on a 3 d or 7 d measurement, expediting the quality assurance and construction processes.

## Prediction vs. Experiment

**Notes:**
Here, the model has been applied to predict the compressive strength of ASTM C109 mortar cubes.  The circles indicate the measured compressive strengths at 3 d, 7 d, and 28 d (within the Cement and Concrete Reference Laboratory (CCRL) proficiency sample program).  The +s indicate the measured standard deviations.  The solid line is the model prediction, which in this case, falls well within the measurement error.

## Example #1Replacement of coarse cement particles by inert fillers in high-performance concrete

- In low (< 0.38) w/c concretes, there is insufficient space for all of the cement to hydrate
- Thus, in HPCs we are often using expensive cement as a reinforcing filler
- Can we replace a portion of the (coarse) cement by an inert filler without a significant loss in strength in these HPCs?
- Reference: Bentz, D.P., and Conway, J.T., Cement and Concrete Research, Vol. **31**, 503-506, 2001.

**Notes:**
The VCCTL is ideal for what-if type simulations.  Here, first, we examine the possibility of reducing cement usage by replacing the coarser cement particles by inert fillers in low w/c ratio high performance concretes.  This would reduce carbon dioxide emissions, etc. and result in cost savings for all parties involved.  This is applicable only in low w/c ratio concretes, since in these systems, all of the cement will not be able to hydrate anyway.

## Main Details

- CCRL Cement 135 (68 % C3S, 17 % C2S, 7 % C3A and 8 % C4AF - 394 m2/kg Blaine)
- w/s of 0.25 and 0.30
- 0.30: replace coarsest 14.5 % and 22.3 % of particles (mass basis; particles larger than 20 μm to 27 μm in diameter)
- 0.25: replace coarsest 20.5 % and 30.8 %
- hydrate for about 200 d of real time using VCCTL
- compare degrees of hydration and predicted compressive strengths (assume unhydrated cement and inert filler contribute equally to strength)

**Notes:**
To proceed, we chose a typical cement from the database and constructed starting 3-D microstructures with different percentages of the coarsest cement particles replaced by “inert” fillers.  We hydrated these microstructures using the VCCTL and looked at the predictions for degree of hydration and compressive strength.

## Initial Microstructures: w/s=0.25       No filler                     30.8 % filler

**Initial Microstructures: w/s=0.25****       ****No filler                     30.8 % filler**

- C3S, C2S, C4AF, C3A, Gypsum, Inert

- C3S, C2S, C4AF, C3A, Gypsum, Inert

**Notes:**
These are 2-D images from the initial 3-D microstructures.  One can clearly observe the larger inert filler particles in the image on the right.  Of course, the effective w/c ratio is larger in the system with the inert fillers.  This should allow a more complete hydration of the cement.

## Predicted Degree of Hydration and Strength Development(w/s=0.25 20.5 % replacement: dashed line)

**Notes:**
Here, we see that for the system with the inert filler, the predicted degree of hydration is indeed larger.  However, in terms of strength, there is a slight reduction (since we have reduced the overall cement content of the mix and increased the effective w/c ratio).

## Difference in Compressive Strength

- 20.5 % replacement

- 30.8 % replacement

**w/s=0.25**

**Notes:**
This graph summarizes the strength reductions to be expected when replacing the coarser cement particles with inert fillers.  A 20.5 % replacement level might be quite acceptable, since it only reduces the compressive strength by about 6 Mpa (or 7 %).

## How important is “coarse” particle replacement?

## Are these predictions supported by experiment?

- Obtained limestone from OMYA, Inc. and classified it along with CCRL Cement 135 (at 30 μm)
- Prepared high-performance mortars (w/s=0.30) with and without 15 % coarse cement replacement by limestone
- Observed about a 10 % loss in compressive strength at 7 d, but equivalent strengths at 56 d (99 MPa)

## Implications from VCCTL

- Appears that one can replace 15 % -20 % of coarse cement particles by inert fillers in low w/s ratio HPCs with only about a 5 MPa reduction in 28 d strength
- VCCTL useful for
- exploring “what if” scenarios
- optimizing material systems

**Notes:**
These two examples hopefully illustrate the power of using the VCCTL for what-if type questions.  The models do a very good job of predicting the influence of cement particle size distribution, composition, w/c ratio, and mineral admixture additions on performance of cement-based materials.

## Addition of limestone reactions

Addition of slag reactions (some fly ash reactions, silica fume already in model)

Modelling of pore solution concentration during hydration (K+, Na+, pH, etc.) (relates strongly to ASR behavior)

- Addition of slag reactions (some fly ash reactions, silica fume already in model)
- Modelling of pore solution concentration during hydration (K+, Na+, pH, etc.) (relates strongly to ASR behavior)

**Recent extensions****Better understanding ******** Improved models**

## Example: Influence of Alkali Species

- Goal: Link pH (ion concentrations) to hydration kinetics in VCCTL model
- Approach: Add known quantities of alkalis to cement pastes and assess changes in hydration kinetics as measured by          non-evaporable water content (wn)
- at NIST, Cemex, and Dyckerhoff Zement

## Coordinated Modeling with Experimental Validation

- NIST experimental effort
- Pore fluid expression studies for various cements at various degrees of hydration to assess concentrations of potassium and sodium and pH
- NIST modeling effort
- Partition alkalis into readily soluble and slowly released components (assume release of the latter  )
- Account for decrease in **capillary pore** and increase in **gel water** during hydration
- Account for incorporation of alkali ions by C-S-H and AFm phases (Taylor, H.F.W., *Cement Chemistry*, Thomas Telford, 1997.)

## drying 

**drying **
**effects**

**Total K+ adjusted**

**Notes:**
Materials: CCRL Cem. 141 + added alkalis 
sodium sulfate and potassium sulfate added on an equivalent molar basis 
0.93 % K2SO4 and 0.76 % Na2SO4 by mass of cement
Measurements:
pore solution concentrations by filtering pastes (w/c=0.4) with subsequent analysis by ion chromatography
(1, 2, and 3) h
non-evaporable water content (VCCTL Tech Note #1)
8 h, (1, 3, 7, 28, and 91) d
curing at 20 oC in constant temperature water bath

## Modeling Efforts

**Modeling Efforts**

- Approach: make the probabilities for dissolution depend on pore solution concentration.  For each phase *i*

- P’i  =

- Pi(pH=13.25)

- 1  +  niX(pH,[SO42-])

- ,   ni = 0 or 1

**Notes:**
ni determines whether pH affects phase i (= 1) or not (= 0)

X is a function that depends on pH.  It generally decreases as the pH increases.  Currently is just an empirically determined function for best fit to available data.

## What is X?

- Function of solution pH and concentration of sulfate ions
- Empirically based, calibrated to data
-                                                 _ __pH_
-     X   =    [SO42-]  + 1.5         < 12.5
-                                  + 1.0         > 12.5
-                                  + 0.667     > 12.75
-                                  + 0.333     > 13.0
-                                  + 0.0         > 13.25
-                                  + -0.25      > 13.75

## Experimental and Model Results ...

**Notes:**
Materials: CCRL Cem. 140 + added alkalis  (LOW ALKALI CEMENT)
0.186 % K2O and 0.093 % Na2O by mass of cement in CCRL 140 (low in alkalis)
Measurements:
pore solution concentrations (w/c=0.4)
(1, 2, and 3) h
non-evaporable water content
8 h, (1, 3, 7, 28, and 91) d

BASICALLY ALL ADDED ALKALIS WENT INTO SOLUTION!!

POOR MIXING IN LOW-SHEAR MIXER WHEN ALKALIS ARE ADDED --->  USE HIGH-SHEAR MIXER

Watch out for syngenite in high-alkali cements!!!

## ... But Poor Agreement witha Dyckerhoff Cement

**Notes:**
Experimental data obtained from Dyckerhoff Zement:

Disagreement could be due to:
	(1) Measurement method for determining DOH
	(2) Curing conditions (sealed vs. saturated).

But we checked these obvious things and they were not the culprit.

Low-T calorimetry may give clues to the late-age behavior. 

## Clues from Low-T Calorimetery?

**Capillary pore**
**water signal**

**Gel space**
**water signal**

**Gel space**
**water signal**

**Capillary pore**
**water signal**

**Notes:**
Experimental data obtained from Dyckerhoff Zement:

Disagreement could be due to:
	(1) Measurement method for determining DOH
	(2) Curing conditions (sealed vs. saturated).

But we checked these obvious things and they were not the culprit.

Low-T calorimetry may give clues to the late-age behavior. 

## Alkalis in VCCTL Version 3.0

- pH (and pore solution concentration) influences hydration kinetics
- user selection to turn on or off
- Pore solution conductivity
- equations added to pHpred.c module
- procedure based on recent paper by Snyder et al:
- Snyder, K.A., Feng, X., Keen, B., and Mason, T.O., “Estimating the Electrical Conductivity of Cement Paste Pore Solutions from K+ and Na+ Concentrations,” submitted to *Cem. Conc. Res.,* 2002.

## Ongoing Validation

- Evaluate experimental results generated at Dyckerhoff Zement and Cemex.
- Quantitative XRD analysis of C3A and C3S hydration
- Study systems with pozzolans (slag, fly ash, silica fume)
- good data available from VDZ on absorption of alkalis in blended cement systems
- pozzolanic C-S-H known to absorb more alkalis than primary (conventional) C-S-H

## Module forRheological Properties ofFresh Concrete

**Notes:**
To have any chance of simulating microstructure development and predicting performance, quantitative and extensive characterization of the raw materials (particularly the cement) is critical.

Only when we have characterized the starting materials can we have any hope of predicting what will happen when water is added to the system.

## What Do We Wish To Accomplish?

- Ultimately
- Prediction of concrete rheological properties based on fundamental material variables:
- cement PSD, w/c, admixtures, paste flocculation, aggregate PSD, etc
- But this is a very difficult problem, so ...
- Currently in VCCTL
- Prediction of fresh concrete viscosity relative to that of the mortar

## Virtual Concrete Rheology

**Concrete composition**
- Aggregates gradation and shape
- Mineral and chemical admixtures
- Cement type

**Rheology**
**Mortar measurements**
**Computer simulation**

**Fresh concrete**
- Workability
- Placement
- Finishability

***Prediction***

## Project Objective 

**      ****Prediction of fresh concrete rheology**
_**Multi-scale approach**_
- Micro:  cement in water	            (Cement Paste)
- Milli:    sand in cement paste            (Mortar)
- Macro: coarse aggregates in mortar  (Concrete)

## Bingham model concept

**Stress**

**Shear strain rate**

- Yield stress

**Stress**

**Shear strain rate**

- Same yield stress
- BUT
- different plastic viscosity

- Same plastic viscosity
- BUT
- different yield stress

## Relative viscosity

- Relative viscosity = plastic viscosity of concrete divided by plastic viscosity of mortar matrix
- Seems to normalize out rheometer-to-rheometer differences, also normalizes for different mortar matrices
- Relative viscosity is then a material parameter, dependent only on volume fraction, shape, and sieve analysis of aggregates

## Relative viscosity

## From gradation to viscosity:a database

**Output**

**Coarse aggregates size distribution**

**Input: search by**

## Brownian Dynamics + Momentum Conserving Collision
		                  Hydrodynamic Behavior

- 		                  **Hydrodynamic Behavior**

**Concrete Rheology Model: ****Dissipative Particle Dynamics**

- Model developed by N. Martys (NIST) based on
- an algorithm by Hoogerbrugge and Koelman (1992)

## Parallel Plate rheometer

## Coaxial Rheometer

## Concrete Flow: diam. 0.5

**Notes:**
Prenons comme cas d’étude un béton autoplaçant, qui par définition s’écoule à travers les obstacles sans aucune vibration. Le béton est simulé dans un premier temps par une suspension concentrée de granulats sphériques monodisperses dans un mortier. Le mortier est considéré comme un fluide newtonien homogène et est caractérisé par sa viscosité plastique. La distance entre les armatures est fixe mais la viscosité du médium (mortier), la dimension des granulats et la concentration en granulats sont variables.
Les mécanismes de blocage peuvent ainsi être étudiés. Les informations qui peuvent être alors être déduites de cette simulation sont: 1) la vitesse d’écoulement; 2) la granulométrie optimale des granulats (gravillons); 3) la viscosité idéale du mortier; 4) la concentration idéale en granulats; et 5) l’influence de la forme des granulats (sphériques, concassés...). L’opérateur peut ainsi étudier numériquement différents scénarios (sans avoir à gâcher de béton). 
Cette figure et la suivante montre deux exemples de résultats obtenus. Un film captant les images successives du flux fut produit  et on peut voir le flux de particules
Differents points de vue peuvent être visualisés soit en représentation 2-D soit en 3-D sur un écran RAVE (Reconfigurable Advanced Visualization Environment) au NIST. 

## Concrete flow: diam. 0.2

**Notes:**
Dans l’exemple présenté, (la diapo precedente et celle-ci)  seule la dimension des granulats a varié. Les granulats étaient sphériques et leurs diamètre maximal representait soit 1/5 ème soit la moitié de la distance libre entre les armatures. La concentration des granulats est,  dans cet exemple,  de 45% du volume (environ 1200 kg/m3).  La seule force appliquée est la gravité terrestre. Il n’y pas de force d’interaction entre les granulats. L’interaction entre les particules peut être simulée mais ceci n’est pas nécessaire pour des granulats. Elle le serait par contre pour la simulation de la pâte de ciment où se produisent des phénomènes d’agglomération et de répulsion dus à la présence d’adjuvants, par exemple, ou à l’hydratation.
Dans notre exemple de béton autoplaçant, nous avons calculé la vitesse des granulats. Les petits granulats (1/5 ème) coulent 40% plus vite que les gros granulats (1/2). On peut aussi remarquer que le mélange présente une porosité plus importante en aval des armatures et moins importante en amont. Cela est dû à l’effet de paroi et d’emcombrement des armatures.  On peut également remarquer que la distribution des granulats semble plus homogène dans le cas des petits granulats ( B).
Note: Les  particules semblent sautes (apparaitre et disparaitre) car on ne voit qu ’une partie (un cube) de un systeme infini et periodique.  Dans le film diam 0.5, on peut remarquer que les numeros dans le coins continue a augementer mais les particules ne bougent plus. Cela indique que la simulation continue mais qu ’il y a blocage.

## Pretty Simulations, ButAre They Any Good?

- We require experimental methods to measure the rheological properties (yield stress, viscosity) of fresh mortars and concretes
- Must be reliable and reproducible to provide model validation.

## Mortar rheometer

## Viscosity as function of air

**Viscosity as function of air**

**Mortar**

**Concrete**

## Where rheology work is heading

- Method to **measure in mortar** the influence of air, chemical, mineral admixtures
**Simulation** of various geometries of rheometers or flow between rebars
**Possible quantitative link** between all rheometers and mortar through the relative viscosity

## Elastic Properties ofCement Paste

**Notes:**
To have any chance of simulating microstructure development and predicting performance, quantitative and extensive characterization of the raw materials (particularly the cement) is critical.

Only when we have characterized the starting materials can we have any hope of predicting what will happen when water is added to the system.

## Elastic properties of cement paste

- Combine:
- measurements of the elastic properties of individual phases and cement paste at various degrees of  hydration
- digital-image-based modelling of cement paste microstructure
- finite element computation of cement paste elastic moduli
- To result in a predictive tool for cement paste and concrete as part of the VCCTL
- First version is in VCCTL 2.0
- Working with S. Shah of Northwestern (ACBM) to link with compressive strength

## Each voxel is  a tri-linear finite element

- sum over all voxels

- 4

## Individual phase moduli

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

## Slide 72

## Data comparison (w/c=0.5)

- Unmodified model
- microstructure

- Experiment

## Digital Resolution

- Most early-age problems apparently due to digital resolution.
- Solution - go to higher resolution (i.e., 2003, 3003, etc. - we are adding the option of higher resolution to the VCCTL code)
- Scalar code can do systems above 1003, but longer run-times and memory-intensive requirements restrict size of feasible systems
- Solution:  Parallel code, using MPI protocols and extensive re-design of FORTRAN
- Runs on distributed memory (Linux) computers, excellent speed-up and accuracy
- Allows higher resolution cement paste systems to be studied elastically

## Higher resolution allows artificial connections to be 

- Higher resolution allows artificial connections to be
- easily “broken” without disturbing microstructure
- as much as in 1003 case

- 3003

- 1003

## Aggregate shape analysis

- (in collaboration with International Center for Aggregates Research)

## Model aggregate shapes

## Realistic aggregate shapes

- X-ray tomography (FHWA)

## Aggregate shape: Does it matter?

- Composites are affected by the shape and topology of their phases and the property contrast between phases
- Property contrast means, for example, E2/E1 (Young moduli ratio)
- If property contrast is small (_<_ 1-2), then composite properties do not depend much on shape of inclusions
- If property contrast is high (> 5-10), then composite properties do depend sensitively on shape of inclusions

## Concrete properties and aggregate shape

- Concrete is a composite = cement paste + aggregate, or mortar + coarse aggregate
- Diffusivity not affected much by aggregate shape at usual property contrast levels (~10%)
- Potential for elasticity to be affected quite a bit by aggregate shape (~50 % or more), especially at early ages, where elastic property contrast is high
- Potential for rheology to be greatly affected (~100%) by aggregate shape, since large property contrast
- So yes, it matters!

## “Extract” aggregate shapes,

**“****Extract” aggregate shapes,**
**then mathematically analyze **
**and store them**

## Slide 82

## 195726

## Slide 84

## Asteroid Eros

## ICAR/NIST collaboration

- UT-Austin supplies research collaboration requirement of VCCTL consortium membership - partnership between NIST and UT-Austin
- 2-way technology transfer, graduate students at NIST
- Build aggregate shape/properties/psd database, samples from ICAR members
- Statistical analysis of shape/psd information, relation of shape parameters to performance properties
- Quantitative addition of real-shape aggregates to models predicting elastic moduli, compressive strength, rheology/workability, and chloride penetrability

## Requirements for Building Models with Particles

- When placing model particles in a model volume, need to:
- Be able to tell if they overlap any existing particles
- Place them at arbitrary positions and orientations
- Easy to do for spheres – just use center-center distance compared to sum of radii, no orientation
- Easy to do for any particle by eye/brain, hard for dumb computer to do
- Only possible for real-shaped particles by using spherical harmonic expansion

## Slide 88

## VCCTL Extension to 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

_**ENVIRONMENT**_
**temperature**
**relative humidity**
**carbon dioxide**
**sulfates**
**chlorides**
**alkalis**
**stress state**

_**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**

## 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
- Thanks to PCA for being one of the industrial groups that are helping to make VCCTL a reality