Root-inspired ground anchors are an emergent bio-inspired geotechnical ground anchoring technology leveraging the pullout resistance efficiency of fibrous plant root systems. These anchors are a technologically feasible means to construct root-like anchor geometries in-situ using conventional ground anchor construction techniques and equipment: a ferrous linkage mechanism alters its configuration in-situ from cylindrical to root-like and remains fixed in the latter configuration by cured cement grout. This technology currently lacks a means to estimate forces on the linkage mechanism during in-situ actuation, and thus, mechanism design and size limitations are poorly understood. A reliability-based design procedure and Monte-Carlo simulation software are presented which implement an analytical estimate of the forces on root-inspired ground anchors during actuation in-situ and an analytical pullout capacity prediction method. Design examples are presented along with software outputs and discussion of the assumptions and limitations of the methodology.
The versatile, Effective Stress Beta Method can be applied to driven pile design across various soil profiles. However, it is not widely practiced, potentially due to unreliable FHWA guidance for selecting pile design coefficients (β & Nt). This study addresses this issue by evaluating FHWA design coefficients against measured data from the Deep Foundation Load Test Database (DFLTD) V.2. The investigation reveals significant disparities between measured load-carrying capacities (Qm) and capacities calculated using FHWA design coefficients (Qc). The design coefficients, β & Nt, were then systematically back-calculated from load test data and were found to differ from the FHWA design coefficients, as hypothesized. In order to improve the design coefficients selection guidance, a neural network (NN) and machine learning (ML) based approach is proposed. The models BetaSPTNet (Artificial-NN for β) and NtSPTNet (Dense-NN for Nt) outperformed other models in predicting β & Nt. The study showcases NN’s adaptability in handling ambiguous correlations such as the one between geotechnical engineering properties of soil and β & Nt design coefficients. The proposed NN architecture improves precision and reduces uncertainty in determining β and Nt using geotechnical properties derived from SPT and CPT soil exploration data. Finally, we propose a modified approach integrating the traditional Beta design method with NN-predicted design coefficients. This integration significantly enhances the accuracy of calculated pile load-carrying capacities.
In a paper in the ASCE Journal, Vesic (1970), presented a case history on static loading tests on strain-gage instrumented pipe-piles that gained a wide national and international attention. The paper evaluated the case records and derived a concept later called “critical depth” that became generally accepted as basis for the design of piled foundations. That concept stated that, down to the “critical depth”, starting at a depth of about to 10 pile diameters, the ultimate unit shaft and toe resistance of a pile would develop in conformity with the effective overburden stress. Below this depth, the unit resistances would cease to correlate directly to the effective stress and become constant with increasing depth below 20 pile diameters. The concept was oblivious to the presence of residual force, which, had it been considered, would have removed the appearance of a critical depth.
Liquefaction-induced settlement poses significant challenges to the stability and performance of structures constructed on liquefiable soils during seismic events. To mitigate the adverse effects of liquefaction-induced foundation settlements, sheet piles are utilized to provide lateral confinement to the soil, thereby enhancing its stability. The performance of sheet piles is contingent upon their installation location. Therefore, identifying the optimal installation location for sheet piles remains a topic of interest. This research aims to evaluate the optimal installation location of sheet piles to mitigate liquefaction-induced foundation settlements. The experimental study employs a moderate scale 1g shaking table to replicate seismic events and investigate the behavior of sandy soil under liquefaction conditions. Multiple configurations of sheet piles, varying in terms of distance from the foundation, depth within the dense layer, and effect of thickness are examined. The excess pore water pressure generation and dissipation, and foundation movement (settlement and tilting) are used to determine the optimal location of sheet piles that minimize liquefaction-induced foundation settlements. The results indicate that the liquefaction-induced foundation settlement increased with increasing the distance between the sheet piles and the foundation. Adversely, the settlement decreased with increasing the embedment depth of sheet piles. Additionally, although this was not the focus of this study, the installation of thinner sheet piles surrounding the foundation appeared to be a more effective measure than thicker sheet piles in mitigating liquefaction-induced foundation settlements based on this experiment.
Determining the bearing capacity of driven steel piles is a critical concern in geotechnical engineering particularly when constructing major structures in oil and gas and infrastructure projects in Alberta. To verify pile capacity, the pile driving analyzer (PDA) and static load tests (SLTs) are widely used. In recent years, PDA testing has become a regular part of pile quality assurance programs on projects and increasingly used as full-scale load tests. Several studies have shown that geotechnical resistance factor (GRF) values can be calibrated with the aim of PDA testing results which can help designers to potentially reduce the number and length of piles. Nevertheless, uncertainty remains regarding the extent to which the GRF value can be optimized following the implementation of the PDA. In this paper, a database of PDA tests and SLTs are compiled from several projects in Alberta, Canada. The primary objective of this study is to assess the impact of time on the recommended GRFs by several codes. To achieve this, the study employs a well-established probabilistic technique known as Monte Carlo Simulation (MCS) to quantify the influence of time, referred to as “setup time”. To enhance the assessment of setup time’s effect, the recorded bearing capacities are collected during two distinct time points: after the completion of pile installation or the end of drive (EOD) condition, and after a specific setup time at the Beginning-of-Restrike (BOR) condition. The results suggest that by taking into account the time impact, GRF values can be optimized, leading to an increase in factored pile resistance and ultimately resulting in a more cost-effective design process for steel-driven piles.
