Noninvasive Tracking of Solidification Using Ultrasound

Restricted (Penn State Only)
- Author:
- Smith, Caeden
- Graduate Program:
- Engineering Science and Mechanics
- Degree:
- Master of Science
- Document Type:
- Master Thesis
- Date of Defense:
- March 16, 2023
- Committee Members:
- Andrea P. Arguelles, Thesis Advisor/Co-Advisor
Christopher Kube, Committee Member
Albert Segall, Program Head/Chair
Julianna Simon, Committee Member - Keywords:
- Ultrasound
Mushy Zone
Reflection
Matching Layer
Acoustic
Casting
Solidification
Wax
Metal
Front Tracking - Abstract:
- Casting is a common manufacturing technique in industries ranging from automotive manufacturing to healthcare. The technique is advantageous as it is inexpensive and effective at producing parts in high quantities. However, many material defects may form when a liquid solidifies in a cast, including cracks, voids, and porosity which can lead the cast to fail. Therefore, much research has been devoted to defect detection and prediction in casting. This thesis explores two aspects of noninvasive ultrasonic monitoring of solidification. First, ultrasonic sensors are used in through-transmission mode on either side of a paraffin wax cast to monitor the response over the solidification period. The difference in speed of sound between the wax’s liquid and solid phases allows for the time of complete solidification to be identified. Second, an acoustic wave model is used to determine the reflection and transmission properties of a region at the liquid-solid interface of a cast known as the mushy zone. Numerical casting simulations show a strong dependence on the properties of the mushy zone in defect formation. An acoustic model for ultrasonic reflections from a continuous matching layer is applied to the mushy zone. The model was successfully validated using an elastic wave propagation simulation in Abaqus. However, further experimental work is required to verify these results. This thesis makes progress towards enabling in situ noninvasive tracking of solidification and characterization of the mushy zone using ultrasound with the goal of real-time defect detection and prediction.