Robert Y. Liang

Methods for Deriving p-y Curves from Instrumented Lateral Load Tests

With the developments of new deep foundation systems and construction techniques, such as high capacity micro-piles, large diameter piles or drilled shafts, existing p-y criteria that were developed previously for small diameter piles or shafts may no longer be adequate. Deriving p-y curves from lateral load tests on instrumented deep foundations is critical for further refinement or developing pertinent p-y criteria for these new applications. However, there is a lack of a consistent and well verified method for deducing the p-y curves from lateral load tests measurement data. Four existing methods are evaluated using the measured results of eight full-scale field tests on fully instrumented drilled shafts as well as four hypothetical numerical simulation results. It is found that the p-y curves deduced by the piecewise cubic polynomial curve fitting method, when input into the LPILE (or COM624P) computer program, provides the smallest error on the prediction of deflections of a drilled shaft under the applied lateral loads. A procedure for determining an optimum strain gage spacing for instrumentation in a lateral load test to derive representative p-y curves is recommended. Finally, a parametric study has shown that the errors of the deduced p-y curves are mainly due to inaccurate moment profiles from strain gage readings. Accurate estimate of moment-curvature relationship of a reinforced concrete shaft is therefore essential to the accuracy of the deduced p-y curves from strain data.

A Segmentation Approach for Stochastic Geological Modeling Using Hidden Markov Random Fields

Stochastic modeling methods and uncertainty quantification are important tools for gaining insight into the geological variability of subsurface structures. Previous attempts at geologic inversion and interpretation can be broadly categorized into geostatistics and process-based modeling. The choice of a suitable modeling technique directly depends on the modeling applications and the available input data. Modern geophysical techniques provide us with regional data sets in two- or three-dimensional spaces with high resolution either directly from sensors or indirectly from geophysical inversion. Existing methods suffer certain drawbacks in producing accurate and precise (with quantified uncertainty) geological models using these data sets. In this work, a stochastic modeling framework is proposed to extract the subsurface heterogeneity from multiple and complementary types of data. Subsurface heterogeneity is considered as the “hidden link” between multiple spatial data sets. Hidden Markov random field models are employed to perform three-dimensional segmentation, which is the representation of the “hidden link”. Finite Gaussian mixture models are adopted to characterize the statistical parameters of multiple data sets. The uncertainties are simulated via a Gibbs sampling process within a Bayesian inference framework. The proposed modeling method is validated and is demonstrated using numerical examples. It is shown that the proposed stochastic modeling framework is a promising tool for three-dimensional segmentation in the field of geological modeling and geophysics.

A method for slope stability analysis considering subsurface stratigraphic uncertainty

The accuracy of stability evaluation of a natural slope consisting of multiple soil and rock layers, regardless the adopted analysis methods, can be highly dependent upon a precise description of the subsurface soil/rock stratigraphy. However, in practice, due to the limitation of site investigation techniques and project budget, stratigraphy of the slope cannot be observed completely and directly; therefore, there remains a considerable degree of uncertainty in the interpreted subsurface soil/rock stratification. Therefore, estimating and minimizing the uncertainty of the computed factor of safety (FS) due to the uncertain site stratigraphy is an important issue in gaining confidence on the stability evaluation outcome. Presented in this paper is a practical analysis approach for evaluating the stability of slopes considering uncertain stratigraphic profiles by incorporating a recently developed stochastic stratigraphic modeling technique into a conventional finite element simulation approach. The stochastic modeling techniques employed for simulating the stratigraphic uncertainty will be briefly described. The main efforts are focused on elucidating the additional benefits from the proposed analysis approach, including a more reasonable probabilistic estimation of FS with consideration of stratigraphic uncertainty, as well as an effective approach for finding the optimum location of additional borehole logs to reduce the uncertainty of FS due to uncertain subsurface stratigraphy.

NEW WAVE EQUATION TECHNIQUE FOR HIGH STRAIN IMPACT TESTING OF DRIVEN PILES

The real time records of force and velocity measured at the pile head during each hammer impact constitute the so-called high strain test (HST) data in the modern wave equation technology in connection with pile-driving activities. Currently, the Case method and the CAPWAP match procedure represent the state-of-art in interpreting HST data to obtain useful information, such as bearing capacity of a pile, soil-pile interaction model parameters, and the hammer performance, etc. A new HST data interpretation procedure based on wave equation theories is developed in this paper. For the case where only toe resistance exists, the new method utilizes both force and velocity records to analytically compute the corresponding dynamic soil resistance at the toe of an impact-driven pile. An inverse optimization scheme is developed to use these analytically computed quantities to determine the pertinent soil-pile interaction model parameters. Examples are given to illustrate the use of the new method to determine the pertinent Smith model constants commonly used in modeling the dynamic soil-pile interactions. The developed algorithm is also successfully extended to the case in which both shaft and toe resistances are involved during pile driving.

Solutions for Soil-Pile-Soil Forces in Pile Stabilized Slopes

This paper introduces a mathematical procedure to analyze slope/pile systems. Limiting equilibrium method of slices is extended to account for the pile in the slope. Force and moment equilibrium for each individual slice is satisfied. The proposed procedure allows two separate predefined failure slip surfaces (one in the upslope side and the other in the downslope side) with a unique factor of safety for each slip surface. An illustrative example is presented to elucidate the use of the solution in comprehending the interrelationships among the pile location, the desired factor of safety of the slope/pile system, and the interactive soil/pile forces.

Design of Drilled Shafts for Slope Stabilization

A design method for using the drilled shafts to stabilize an unstable slope is presented in this paper. The method is based on the concept that the presence of drilled shafts in a slope reduces the driving forces on the down slope side of the drilled shafts due to the soil arching by which the earth pressure was transferred to the drilled shafts. The presented design procedure allows for optimization of the drilled shafts size, shaft location, shaft fixity (the necessary rock-socket length), and the spacing between the drilled shafts for a given unstable slope with known slip surface to achieve the desired target FS of the slope/drilled shafts system.