Doctor of Philosophy (Ph.D.)
Degree Granting Department
Civil and Environmental Engineering
Austin Gray Mullins, Ph.D.
Michael Stokes, Ph.D.
Abla Zayed, Ph.D.
Frank Pyrtle, Ph.D.
Sarah Kruse, Ph.D.
effective radius, temperature prediction modeling, hyperbolic corrections, T-R relationship, drilled shaft
Thermal Integrity Profiling (TIP) is a relatively new non-destructive test method for evaluating the post-construction quality of drilled shafts. Therein anomalies in a shaft are indicated by variations in its thermal profile when measured during the curing stages of the concrete. A considerable benefit with this method is in the ability to detect anomalies both inside and outside the reinforcement cage, as well as provide a measure of lateral cage alignment. Similarly remarkable, early developments showed that the shape of a temperature profile (with depth) matched closely with the shape of the shaft, thus allowing for a straightforward interpretation of data. As with any test method, however, the quality of the results depends largely on the level of analysis and the way in which test data is interpreted, which was the focus of this study. This dissertation presents the findings from both field data and computer models to address and improve TIP analysis methods, specifically focusing on: (1) the analysis of non-uniform temperature distributions caused by external boundary conditions, (2) proper selection of temperature-radius relationships, and (3) understanding the effects of time on analysis.
Numerical modeling was performed to identify trends in the temperature distributions in drilled shafts during concrete hydration. Specifically, computer generated model data was used to identify the patterns of the non-linear temperature distributions that occur at the ends of a shaft caused by the added heat loss boundary in the longitudinal direction. Similar patterns are observed at locations in a shaft where drastic changes in external boundary conditions exist (e.g. shafts that transition from soil to water or air). Numerical modeling data was also generated to examine the relationship between measured temperatures and shaft size/shape which is a fundamental concept of traditional TIP analysis.
A case study involving a shaft from which 24hrs of internal temperature data was investigated and compared to results from a computer generated model made to mimic the field conditions of the shaft. Analysis of field collected and model predicted data was performed to examine the treatment of non-linear temperature distributions at the ends of the shaft and where a mid-shaft change in boundary was encountered. Additionally, the analysis was repeated for data over a wide range of concrete ages to examine the effects of time on the results of analysis.
Finally, data from over 200 field tested shafts was collected and analyzed to perform a statistical evaluation of the parameters used for interpretation of the non-linear distributions at the top and bottom of each shaft. This investigation incorporated an iterative algorithm which determined the parameters required to provide a best-fit solution for the top and bottom of each shaft. A collective statistical evaluation of the resulting parameters was then used to better define the proper methods for analyzing end effects.
Findings revealed that the effects of non-uniform temperature distributions in drilled shaft thermal profiles can be offset with a curve-fitting algorithm defined by a hyperbolic tangent function that closely matches the observed thermal distribution. Numerical models and statistical evaluations provided a rationale for proper selection of the function defining parameters. Additionally, numerical modeling showed that the true temperature-to-radius relationship in drilled shafts is non-linear, but in most cases a linear approximation is well suited. Finally, analysis of both model and field data showed that concrete age has virtually no effect on the final results of thermal profile analysis, as long as temperature measurements are taken within the dominate stages of concrete hydration.
Scholar Commons Citation
Johnson, Kevin Russell, "Advancements in Thermal Integrity Profiling Data Analysis" (2016). Graduate Theses and Dissertations.