Abstract

Sinkholes are a major geohazard with life-threatening consequences when not properly detected and mitigated. Geologic conditions comprised of soluble bedrock (e.g., limestone or other carbonate-based lithologies) overlain by fine-grained sandy and clayey soils, are known internationally as "karst topography" and is generally characterized by such sinkholes, caves, sinking streams, and highly variable groundwater flow conditions. Karst sinkholes, however, are complex geohazards and are difficult to precisely characterize through geotechnical considerations alone. Deterministic methods (e.g., analytical and numerical solutions) may provide for a more robust analysis of internal soil erosion (known as soil raveling) but have limitations for the practical use by engineers and CPT-operators, and often require additional testing to accurately model the subsurface conditions. Often times when investigating in karst for sinkhole activity, time is a limiting factor and decisions on mitigation efforts or lane closures must be made in a timely manner. Therefore, this study presents a comprehensive investigation into the use of the cone penetration tests (CPT) for the identification and assessment of the internally eroded soils associated with sinkhole formation through field and statistically based solutions. Several CPTs can quickly be performed at any suspected sinkhole site, and results can then be analyzed in real time to aid in decision making. Assessment techniques developed in this study include: 1) CPT-based raveling chart for the identification and evaluation of internally eroded soil in a karst landscape and, 2) a quantifiable vulnerability index, the sinkhole resistance ratio (SRR), used to compare the variation of subsurface conditions within a project site and correlate the potential for future sinkhole collapse. These deliverables were developed through an extensive data collection program of CPTs performed in karst landscapes for sinkhole investigation and repair purposes in central Florida over a 20-year period, and the methodology for the chart and index employed mathematical and statistical methods. The outputs of this research provide engineers with an empirically proven evaluation tool when investigating and designing in a known karst landscape, ultimately enabling a safer and more economical geotechnical design.

Notes

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Graduation Date

2020

Semester

Summer

Advisor

Nam, Boo Hyun

Degree

Doctor of Philosophy (Ph.D.)

College

College of Engineering and Computer Science

Department

Civil, Environmental, and Construction Engineering

Degree Program

Civil Engineering

Format

application/pdf

Identifier

CFE0008239; DP0023593

URL

https://purls.library.ucf.edu/go/DP0023593

Language

English

Release Date

August 2023

Length of Campus-only Access

3 years

Access Status

Doctoral Dissertation (Open Access)

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