Debugging Cement Hydration Numerical Simulations

using D3.js and a CAVE

Wesley Griffin Danny Catacora Steven Satterfield Jeffrey Bullard Judith Terrill

Abstract

We have created an integrated interactive

visualization and analysis environment that can be

used immersively or on the desktop to study a

simulation of microstructure development during

hydration or degradation of cement pastes and

concrete. Our environment combines traditional 3D

scientific data visualization with 2D information

visualization using D3.js running in a web browser.

Both the data visualization and information

visualization components are interactive and

support bi-directional updates.

Introduction

Concrete provides strength and structure to a large part of our world. The cement binder in

concrete undergoes multiple interacting chemical and structural changes as it transforms

from a liquid suspension to a solid mass. Understanding the nature of these transformations

is important for building a sustainable civil infrastructure. The Inorganic Materials Group

within the Engineering Laboratory at NIST is developing computational models capable of

predicting the flow, hardening, and strength of cement.

To help understand and validate the models, we have developed an integrated interactive

visualization and analysis environment for the model outputs. Our environment provides a

variety of visual modes to enable precise quantitative measurements and visual information.

We also combine 3D scientific data visualization with information visualization using D3.js

running in a web browser.

Implementation

3D Window Web Browser

IRIS D3.js

Control

Queue

Response

Queue

Node.js

Notify

Queue

Our implementation, illustrated on the left, consists of three main pieces: 1) IRIS: the 3D data

visualization component; 2) D3.js: the 2D information visualization component; and 3) Node.js: the

bidirectional communication server. In the figure, processes are illustrated by squares, interprocess

communication queues by cylinders, graphical user interface windows by squares with titlebars, and

data flow by arrows which are colored based on the specific flow: red for data into IRIS and blue for

data into D3.js.

IRIS is the immersive 3D scientific data visualization. This component runs either in a 2D window on

the desktop or in stereo in an immersive virtual environment with tracking. IRIS supports a variety of

visual modes and interactive tools to make precise quantitative measurements. One specific tool is the

probe tool which is used to measure the specific concentrations of each reaction. As the probe tool is

moved, IRIS updates D3.js.

D3.js is the web-browser 2D information visualization. This component is built on top of the D3

visualization library and thus supports any visualization that can be implemented in D3. This specific

visualization is a heat-map of the reaction concentrations. As different layers and reactions are viewed,

D3.js updates IRIS.

Results

The figures

on the right show the 3D

data visualization (IRIS)

and the 2D information

visualization (D3.js)

windows respectively. The

3D visualization shows

the full simulation grid

while the 2D visualization

shows a single z-layer of

the grid. The z-layer of the

grid currently being viewed

in the 2D visualization

is rendered with the

same set of colors in both

windows. The specific cell

that the mouse is hovering over in the 2D visualization is highlighted in gray in the 3D window.

HydratiCA is a parallel simulation of the cement hydration process designed to run on distributed memory machines. The software is parallelized

with a spatial decomposition and the boundary layers between the processors are transferred into ghost layers for the iterative updates. Recent

modifications to the code, however, were yielding questionable results and bugs were also introduced into the checkpointing code. By visualizing the

model output in both 3D and 2D (including the specific spatial decomposition shown as red lines in the figures), our combined visualization

immediately revealed implementation issues in the computation model, specifically the ghost layers. This issue can be see as the dark blue nodes in

the figures, which should be purple. This quickly pinpointed the location in the code that needed to be fixed.

Conclusion

We have presented an integrated interactive visualization

environment that can be used immersively or on the desktop and

combines 3D scientific data visualization and 2D information

visualization. Both visualization components are interactive and

support bi-directional updates. Our combined visualization

revealed implementation issues in the computational model.

These issues were quickly pinpointed by the scientist and the

implementation was corrected.

Future Work & Acknowledgements

We are currently extending this visualization into a more general tool that can

be used on datasets of varying size and spatial decomposition. This version

displays the 2D information visualization directly in our immersive

environment. We plan on incorporating a hand-held tablet to display the 2D

visualization thus leaving more display space for the immersive 3D data

visualization. We also plan on applying this technique to additional data sets.

This work used the Extreme Science and Engineering Discovery Environment

(XSEDE) supported by National Science Foundation grant OCI-1053575.

High Performance Computing and Visualization Group ACMD / ITL / NIST http://www.nist.gov/itl/math/hpcvg

DISCLAIMER: Certain commercial products are identified in this paper in order to specify the experimental procedure adequately. Such identification is not intended to imply recommendation or endorsement by the

National Institute of Standards and Technology, nor is it intended to imply that the products identified are necessarily the best available for the purpose.