This paper develops a Monte Carlo simulation (MCS)-based reliability analysis approach for slope stability problems and utilizes an advanced MCS method called “subset simulation” improving efficiency resolution of the at relatively small probability levels. Reliability is operationally decoupled from deterministic implemented using commonly available spreadsheet software, Microsoft Excel. The package validated through comparison with other methods commercial software. then used to explore...

In geotechnical engineering, the number of measurement data obtained from in situ or laboratory tests is usually sparse, especially for projects small medium size. Interpretation such sparse challenging and may result significant statistical uncertainty, which refers to inaccuracy inference results caused by a limited used inferences. Consider, example, soil property profile (i.e. variation with depths), interpreted unavoidably contains uncertainty. Geotechnical design analysis are greatly...

This paper develops a Bayesian approach for probabilistic site characterization (i.e., on both stratigraphy and soil properties) using cone penetration tests (CPTs). The available information prior to the project (e.g., existing geological maps, geotechnical reports, local experience) is used in as knowledge, it integrated systematically with results of CPTs that are performed deliberately project. inherent spatial variability modeled explicitly by random field theory. proposed contains two...

In this paper, we analyze the convergence of alternating direction method multipliers (ADMM) for minimizing a nonconvex and possibly nonsmooth objective function, $\phi(x_0,\ldots,x_p,y)$, subject to coupled linear equality constraints. Our ADMM updates each primal variables $x_0,\ldots,x_p,y$, followed by updating dual variable. We separate variable $y$ from $x_i$'s as it has special role in our analysis. The developed guarantee covers variety functions such piecewise functions, $\ell_q$...

This paper develops Bayesian approaches for facilitating the determination of characteristic (or nominal) values geomaterial properties in geotechnical analysis and design when extensive testing cannot be performed, which is case a majority projects, particularly those small or medium size. These aim to characterize probabilistically undrained shear strength, Su, clay using limited amount liquidity index (LI) test data, provide logical route determine design, probability-based codes. The...

The underground space in urban areas is frequently congested with utilities, including pipelines and conduits, that are affected by construction, e.g., tunneling. This paper carries out finite element (FE) analyses to investigate the effects of tunneling-induced ground movement on pipelines, special attention different soil responses uplift downward pipe–soil relative movements. A series numerical parametric studies 900 FE simulation runs total performed encompass various combinations...

This paper develops Bayesian approaches for underground soil stratum identification and classification using cone penetration tests (CPTs). The uncertainty in the CPT-based Robertson chart is modeled explicitly approaches, probability that belongs to one of nine types based on a set CPT data formulated maximum entropy principle. proposed contain two major components: model class selection approach identify most probable number layers system simultaneously estimate layer thicknesses classify...

Random field theory has been increasingly used in probabilistic geotechnical analyses over the past few decades, where a random generator with parameters is needed to simulate samples (RFSs) of interest. Estimation parameters, particularly correlation functions or length, generally requires extensive measurements. However, data gathered from site characterizations are usually sparse, for small medium sized projects. Therefore, it difficult provide an accurate estimation on and estimated...

The delineation of vertical geological cross-sections is an essential task in geotechnical site characterization and has a profound impact on subsequent designs analyses. It long-lasting challenge, particularly for complex settings, to properly produce subsurface cross-section from limited boreholes that are usually encountered engineering practice. Emerging machine learning methods, such as the convolutional neural network (CNN), provide fresh perspective this challenge effective...

Variation of soil properties with depth, i.e., the property profile, is a key input in geotechnical design and analysis, it determined during site characterization. Determination such profile requires extensive measurement data points from However, number characterization usually sparse limited. As such, determining limited remains challenge to engineers. In engineering practice, frequently assistance experience judgment or statistical methods when only are available. Because both inevitably...