Experimental evaluation of a mass-spring-damper suspension system to identify the configuration that minimizes displacement transmissibility across a 1–6 Hz frequency range. The system was tested across combinations of damping and mass settings with calibrated force and displacement transducers. Testing revealed that the damper does not behave linearly while the spring component followed a linear model well. The low-mass, high-damping configuration produced the best performance, achieving a minimum peak gain of 5.28 dB at a natural frequency of 2.76 Hz. MATLAB was used for sinusoidal curve fitting, Bode plot generation, and uncertainty analysis. 

Calibration and validation of a custom tensile testing rig for measuring force and displacement in structural materials. This project involved correcting transducer offsets, applying linear and quadratic curve fits to account for rig deformation, and establishing an overall force uncertainty to keep measurements within the required 10% uncertainty threshold. The calibrated rig was validated through destructive tensile testing of a climbing sling, five steel bolts, and an aluminum dog bone. Experimental results for yield, ultimate, and fracture properties consistently matched theoretical values within 6% error. MATLAB was used for data processing, regression modeling, and uncertainty analysis. 

Development and validation of a signal processing pipeline to improve the accuracy and precision of a digital SONAR target-tracking system. This project involved characterizing systematic and random noise sources in raw acoustic signals and implementing a baseline subtraction and signal averaging method to improve the signal-to-noise ratio. Prior to processing, the system had an average tracking deviation of 13.91 cm. After processing, the average deviation dropped to 0.585 cm across distances up to 1.15 m, meeting the target specification. MATLAB was used for signal processing, noise analysis, and distance calculation.