Civil and Environmental Engineering Commons^™

Exploring Machine Learning In Deep Foundation And Soil Classification Application, Mohammad Moontakim Shoaib

LSU Master's Theses

The applicability of several Machine Learning (ML) models was explored in this research to predict the ultimate capacity and load-settlement behavior of axially loaded single-driven piles from Cone Penetration Test (CPT) data. Additionally, a common CPT-based soil behavior type (SBT) classification system was reproduced using those ML models. Eighty static pile load tests and corresponding CPT data close to those pile locations were collected from 34 sites in Louisiana for the deep foundation application. On the other hand, 70 CPT soundings were taken in 14 different parishes across Louisiana for the soil classification application. Specifically, tree-based ML models such as …

Investigation Of Sand-Biochar Mixtures As A Potential Roadway Fill Material, Katia J. Lele Lagmago

LSU Master's Theses

Biochar is a sustainable and lightweight carbon-rich material with a high surface area and porosity. Previous studies reported that biochar can reduce soil erosion and cracking, retain contaminants, and enhance soil aggregation. Given these favorable properties, soil-biochar mixtures have the possibility to serve as a multifunctional lightweight fill material for roadway embankment applications. The purpose of this research is to develop sand-biochar mixtures as a sustainable and multifunctional lightweight fill material for roadway embankment applications.

This research investigated the consolidation and hydraulic properties of sand-biochar mixtures by (1) performing 1D consolidation tests, (2) performing permeability tests, and (3) assessing the …

Finite Element Numerical Modeling And Parametric Study Of Geosynthetic Reinforced Pile-Supported Embankments, Abdallah Ikbarieh

LSU Master's Theses

This study directed at investigating the performance of the pile-supported embankment system utilizing a geosynthetic reinforced load transfer platform (GRLTP) using Finite Element numerical modeling. A 2D Finite Element Modeling (FEM) methodology was first developed using PLAXIS 2D 2021 computer software and verified by well-documented case studies in the literature of this system. Second, a performance prediction was made for a field case study of the Amite River Project near French Settlement, which is located along Route LA 16 Livingston Parish in Louisiana State. A comprehensive FEM parametric study was then carried out to evaluate the performance of the system …

Engineering Characteristics Of Nest Building Geomaterials Used By Mud Dauber Species, Noura Saleh

LSU Master's Theses

Mud dauber wasps construct their nests using soil from adjacent areas. Mud dauber nests have been studied from an entomological perspective. However; the properties of the nest material remain unexplored from a soil engineering perspective. This study investigated the physical and mechanical properties of the nest soil for use in future bio-inspired design to improve soil behavior as a construction material. To achieve this goal, nests from three mud dauber species (black and yellow, organ pipe, and steel blue) were collected from locations near Baton Rouge, Louisiana. The shape, weight, moisture content, organic content, and specific gravity of the nests …

Study Of The Effect Of Heating - Cooling Cycles On The Clay - Concrete Pile Interface Characteristics, Abedalqader Ahmad Idries

LSU Master's Theses

This study aimed at investigating the effect of heating-cooling cycles on the interface strength parameters of clay soil-concrete for potential applications to improve the side capacity of piles driven in clayey soil by the heating process, and also to assess the behavior of geothermal piles regarding interface shear strength parameters. A modified large-size direct shear test device with the dimensions 12” x 12” x 8”, was used in this study. A concrete block (12” x 12” x 4”) of similar texture and smoothness to the concrete piles was used to simulate the pile interface. The tested clays are low plasticity …

Evaluation Of Undrained Shear Strength Of Soil, Ultimate Pile Capacity And Pile Set-Up Parameter From Cone Penetration Test (Cpt) Using Artificial Neural Network (Ann), Md Ariful Hassan Mojumder

LSU Master's Theses

Over the years, numerous design methods were developed to evaluate the undrained shear strength, S_u, ultimate pile capacity and pile set-up parameter, A. In recent decades, the emphasis was given to the in-situ cone and piezocone penetration tests (CPT, PCPT) to estimate these parameters since CPT/PCPT has been proven to be fast, reliable and cost-effective soil investigation method. However, because of the paucity of a vivid comprehension of the physical problem, some of the developed methods incorporate correlation assumptions which might compromise the consistent accuracy. In this study, the Artificial Neural Network (ANN) was exerted using CPT data …

Modeling Of Fluid Injection For Hydraulic Fracturing Initiation In Porous Rock Formations, Krishna Adhikari

LSU Master's Theses

Hydraulic fracturing has been widely opted in recent times to simulate the unconventional reservoirs and thus, has become key a subject of interest in petroleum engineering. The stress concentration around the borehole affects the breakdown pressure and fracture reopening pressure during the hydraulic fracturing treatments. Thus, the state of stress around borehole wall and its surrounding rocks due to instantaneous drilling and a fluid injection at borehole surface needs to be determined accurately to initiate the hydraulic fractures. This research intends to derive the analytical stress solution of inclined borehole subjected to time-dependent fluid injection and in-situ stress, verify the …

Evaluation Of Synthetic Cpt And Soil Boring Data By Various Spatial Interpolation Techniques, Md Habibur Rahman

LSU Master's Theses

In order to incorporate the influence of collected in-situ data, the spatial correlation between the data and the foundation needs to be explored. However, risk and uncertainty are the characteristics of the soil that cannot be eliminated. Statistical information of the soil property can be estimated from available field data obtained from testing at discrete locations across the site. In this research, several well-established spatial interpolation methods like ordinary kriging (OK), simple kriging (SK), inverse distance weight (IDW), spline, natural neighbor (NaN) and universal kriging (UK) were incorporated to evaluate the best method. Six CPT (Cone penetration test) (Tip Resistance …

Evaluation Of Undrained Shear Strength And Soil Classification From Cone Penetration Test, Md Imran Hossain

LSU Master's Theses

The in-situ cone and piezocone penetration tests (CPT, PCPT) has been widely used by the geotechnical engineering community for subsurface soil characterization and classification, and for the evaluation of many engineering soil properties, such as undrained shear strength (s_u), unit weight (γ), constrained modulus (M), coefficient of consolidation (c_v), and stress history (OCR). The objective of this research study was to estimate the undrained shear strength of clayey soil using CPT/PCPT data in addition to some soil boring log data. At the same time, soil classification charts/methods based …

Evaluation Of Site Variability And Its Application In Design, Abu Hakim Muhammad Hasan Faisal

LSU Master's Theses

Geotechnical characterization has an important role in engineering geology as well as in implementation of any project. There are several variables and uncertainties involved in characterizing a project site. Four different sources of uncertainties represent the characterization of geotechnical variability, which include spatial variability, measurement error, statistical error and model bias. Spatial variability is expressed in terms of the mean, variance, and scale of fluctuation. Several statistical techniques such as the Gauge R & R, which includes X-Bar/R and ANOVA, and the Second Moment can be applied to compute site variability in terms of the coefficient of variations. Measurement error …