Date Approved
3-3-2026
Embargo Period
3-3-2028
Document Type
Dissertation
Degree Name
Ph.D. Mechanical Engineering
Department
Mechanical Engineering
College
Henry M. Rowan College of Engineering
Advisor
Chen Shen, Ph.D.
Committee Member 1
Behrad Koohbor, Ph.D.
Committee Member 2
Amin Nozariasbmarz, Ph.D.
Committee Member 3
Adriana Trias, Ph.D.
Committee Member 4
Ryan Masoodi, Ph.D.
Abstract
As engineering structures grow in scale and complexity, ensuring structural integrity and long-term performance remains a critical challenge. Wind turbine blades (WTBs), which are essential components of renewable energy infrastructure, operate under harsh conditions that can lead to fatigue, cracking, and eventual failure. Undetected damage may reduce energy efficiency and pose serious safety risks. This dissertation investigates acoustic wave–based non-destructive testing (NDT) techniques for damage detection in WTBs. Simultaneously, the increasing adoption of 3D-printed concrete (3DPC) in construction presents challenges for evaluating material properties during the fresh and early-hardening stages, when the material continuously evolves. Therefore, an acoustic-based monitoring approach is developed to characterize sound velocity, dynamic Young’s modulus, and curing behavior from the fresh state. In parallel, acoustic metasurfaces with subwavelength thickness enable precise manipulation of acoustic wave propagation but are often limited by fixed geometries and single-function operation. To address these limitations, frequency-multiplexed acoustic metasurfaces are developed that allow a single passive structure to operate at multiple frequencies and perform distinct functions. Through theoretical analysis, computational modeling, and experimental validation in the sonic regime, metasurfaces capable of wave splitting and focusing are demonstrated.
Recommended Citation
Zabihi, Ali, "ACOUSTIC WAVE-BASED TECHNIQUES FOR WAVE MANIPULATION AND NON-DESTRUCTIVE EVALUATION IN ENGINEERED MATERIALS AND SYSTEMS" (2026). Theses and Dissertations. 3496.
https://rdw.rowan.edu/etd/3496