Date of Award
5-2026
Document Type
Thesis
Degree Name
Master of Science (MS)
Department
Civil Engineering
Committee Chair/Advisor
Brandon E. Ross
Committee Member
Brunela P. Rodrigues
Committee Member
Weichiang Pang
Abstract
South Carolina has about 2,600 bridges that are supported by nearly 75,000 timber piles. They are increasingly vulnerable to biological decay, cracking and impact damages after decades of service. Current inspection methods used by the South Carolina Department of Transportation (SCDOT), such as hammer sounding and awl probing, are labor-intensive and expensive. This study investigated non-destructive evaluation (NDE) methods, including micro-resistance drilling and stress wave timing, as alternatives for assessing timber pile condition.
Ten timber piles were collected from two South Carolina bridges, and their above-grade portions were cut into 40 specimens approximately 13 to 15 inches long. Specimens were classified as good, medium, or bad based on visible voids and cracks. Each specimen underwent geometric measurements, NDE tests, and compression testing to determine parallel-to-grain compressive strength and stiffness.
Results showed that mean compressive strength was similar for good (2478 psi) and medium (2466 psi) specimens, but lower for bad specimens (1981 psi). Transverse stress wave transmission times varied clearly across damage levels. Regression models were developed to estimate mechanical properties from NDE data. Linear regression showed weak predictive ability, while random forest models performed better for compressive strength (R² = 0.675) and stiffness (R² = 0.839). Transverse and longitudinal stress wave times were the strongest predictors of compressive strength and stiffness, respectively. Two Excel-based random forest tools were developed for practical use by SCDOT engineers, demonstrating that NDE methods can support more efficient inspection and decision-making for timber pile assessment.
Recommended Citation
Sapkota, Aashish, "Estimation of the Mechanical Properties of South Carolina Timber Piles Using Non-Destructive Evaluation Methods And Experimentally-Informed Models" (2026). All Theses. 4725.
https://open.clemson.edu/all_theses/4725