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This dissertation explores three different aspects of the Texas Department of Transportation’s Texas Cone Penetration (TCP) test and its associated foundation design charts. The first aspect has to do with the reliability of TCP data. The TCP test hammer efficiency, rod length influence on the hammer efficiency, and effect of overburden pressure on the TCP test blowcounts (NTCP) are explored. Results are compared with published correction factors for the Standard Penetration Test (SPT). The final dataset analyzed for the study, consisted of 293 TCP tests from which 135 tests were instrumented. Analyses showed a statistically significant relationship between the TCP hammer efficiency and the rod length below ground surface. Rod length correction factors (CR-TCP) and overburden correction factors (CN-TCP) were obtained factors for the TCP test. The second topic involves a quantitative and a qualitative evaluation of the predictive validity of the Texas Cone Penetration (TCP) foundation design charts where allowable measured total capacities determined from results of full-scale load tests were compared to allowable predicted total capacities determined from TCP foundation design charts. The final dataset analyzed compiled for this study consisted of 60 full scale load testes comprising 33 driven piles and 27 drilled shafts. Allowable measured capacities were determined using strength-based and serviceability-based models. Results from analyses suggested that it is apparent that different performance assessment criteria leads to different conclusions regarding the predictive validity of the TxDOT TCP method for deep foundation design. The allowable predicted total capacity determined from the TCP foundation design charts could be considered to be reasonable based on a strength-based model, moderately over-conservative, to over-conservative according to serviceability-based models. Further, it was observed that as the level of tolerable settlement is increased, the interpretation of the TCP foundation design charts becomes even more conservative. The third topic identifies resistance factors for the serviceability limit state (SLS) condition used in the load and resistance factor design (LRFD) of deep foundations using the results from the TCP test. The performance function was established based on load corresponding to tolerable displacement and design load. The compiled dataset consisted of a total of 60 full scale load test cases comprising 33 driven piles and 27 drilled shafts. The loads corresponding to tolerable displacements were determined using the load-settlement curves, and these loads were compared with the design load determined using the TCP test method. Resistance factors for SLS conditions were obtained for tolerable displacements using both the Monte Carlo simulation (MCS) and the first order second moment (FOSM) calibration approaches.

This dissertation evaluates the influence of three factors – cover soil depth, demand model sophistication, and live load attenuation method – on the load rating of cast-in-place (CIP), reinforced-concrete (RC) box culverts. Concrete box culvert load rating appears simple but is quite complex. The governing federal policy, analysis principles, challenges, and the disconnect between load rating calculations and field inspection observations are discussed in detail. Cover soil depth above the culvert directly influences culvert load rating results in non-linear ways. A population of Texas Department of Transportation CIP RC culvert standard designs developed between 1930 and 1980 were load rated using AASHTO policy guidance and a direct-stiffness demand model for a full range of cover soil depths. Three typical rating vs. depth relationships are illustrated and described in detail. The distribution of characteristic rating vs. depth relationships based on culvert geometry, design cover soil depth, and design era are explored. Cover soil depth is shown to be a critical parameter that must be explicitly considered for the intelligent load rating and design of reinforced concrete box culverts. Demand model sophistication influences the accuracy and precision of culvert load rating calculations. Two production-simplified culvert load rating demand models were analyzed using live load test data from three instrumented reinforced concrete box culverts under four cover soil depths. The demand models were a structural-frame model and a soil-structure interaction model. As expected, increased sophistication in the soil-structure interaction model as compared to the structural-frame model resulted in higher precision and accuracy for predicted moments. Variations in predicted moment accuracy and precision were not uniform but are a function of the critical section location in the culvert structure. The soil-structure interaction model requires an out-of-plane, live load attenuation method; this method directly affects the accuracy and precision of the culvert load rating calculation. A new method, called the depth-calibrated method, attenuates out-of-plane live load to the critical section depths in a culvert. The depth-calibrated method improves current practice by increasing the accuracy and precision of live load demand predictions, particularly in culvert walls and bottom slabs. Use of the depth-calibrated method helps close the disconnect between calculated load rating and observed structural performance by more accurately predicting both the location of the weakest critical section and the live load magnitude. The effectiveness of the depth-calibrated method was evaluated by comparing predicted live load moments to measured live load moments obtained from published datasets from full-scale culvert load tests. A load rating example shows the improved alignment between load rating and observed performance. Understanding the influence of cover soil depth, modeling sophistication, and live load attenuation allows for more accurate and precise load rating of cast-in-place, reinforced-concrete, box culverts and better correspondence between load rating calculations and field inspection observations. This dissertation advances the state of production-simplified load rating practice and knowledge.