In this activity you will learn how to analyze 3D scientific data sets and get experience thinking in three dimensional space (NOT EASY!). This data set is a computed tomography (CT) scan of a turbine fan blade, where gradients in density are observed. The objective of this data is to detect the existence of cracks, voids, and other anomalies in a fan. This technology will help detect errors in turbine fans before they are put into use, making them more safe. Below is a picture, showing how the data is organized.

In this activity you will use the JAVA 3d Slicer to view the three dimensional data set. While "slicing" through the x, y, and z planes you will observe trends in the fuel concentrations. As you move the slice through the data the observed colors will change; red stands for the highest concentration and purple for the lowest concentration.

To perform this activity you will use the first data set in the brown.hdf file . The data set exists in the JAVA 3d Slicer's folder; it is named fan_256_sds.hdf. To access the file you select the drop down menu on the top of the JAVA applet and select "Open URL", then type "fan_256_sds.hdf" (without the quotes). The data set will then load on the screen and you can move the "slice" through the data to observe certain trends and concentration levels.

The colors seen in the 3D Slicer represents the density of the turbine fan. Green colors represent very low density, while red represents very high density. Blue colors represent voids.

Analysis Procedure

• Start on the y-axis and take the scroll bar to 0. As you increase the position to 60, what part of the fan is being viewed?
• At position 145, explain what you see. What part of the fan is being viewed? Is this part of the fan very dense?
• At position 185, what part of the fan do you see? Is this part of the fan very dense?
• Do you see any voids or cracks between 115 and 130? What colors are the voids or cracks?
• Now, switch to the z-axis and position the scroll bar at 0. What do you see?
• As you increase the position to 130, what do you see?
• At position 180, what do you see?
• Now, switch to the x-axis and position the scroll bar at 0. What do you see?
• As you increase the position to 15, what do you see?
• At position 40, what do you see?

Original work provided by Bryan Foster, Shoma Sarkar, and Mike Wojdyla (Class of '00).