Provision of Building Codes in the Context of Seismicsite Characterization and Liquefaction Susceptibility Assessment

Islam, Samiul

doi:10.21660/2023.108.3795

Cited by 5 publications

(1 citation statement)

References 24 publications

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“…Zaman et al (2016) [26] developed a correlation between consolidation properties of soil with liquid limit, in situ water content, void ratio, and plasticity index. Statistical models were also developed to predict the liquefaction and seismic hazard from SPT data [27] [28]. Moreover, several statistical approaches were used to develop models to conduct slope stability assessment of clayey sand hill tracts [29] [30] [31] and also the deformation of soil due to tunneling [32] [33] [34].…”

Section: Introductionmentioning

confidence: 99%

Prediction of Strength Properties of Soft Soil Considering Simple Soil Parameters

Hoque,

Bayezid,

Sharan

et al. 2023

OJCE

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Cohesion is an important soil strength parameter for the overall structure and quality of building foundations as well as slope stability. For a civil engineering project, cohesion (c) can be determined directly from mainly unconfined compression tests, direct shear tests, and triaxial tests of soil. However, it's quite challenging to collect soil samples as there are time and cost constraints, as well as a diversity of soil deposits. Hence, this research aims to demonstrate a simplified method in order to determine the strength parameter of cohesive soil. Here, we propose an alternative solution adopting statistical correlations and machine learning techniques to establish correlations between the liquid limit, plastic limit, moisture content and %fine of soil with the strength parameter. In laboratory testing, these parameters can be obtained easily and these tests are relatively simple, quick to perform and also comparatively inexpensive. Hence, several test results were used from 100 boreholes which were soft soil or silty clay-type soil. Using the collected in-situ and lab test results of soil samples, a Multiple Linear Regression (MLR), Random Forest Regression (RFR) and Machine Learning (ML) model will be developed to establish a relationship between cohesion and the available test results. In order to assess the performances of both models, several performance indicators like: correlation coefficient (R 2 ), mean squared error (MSE), root mean square error (RMSE), and mean average error (MAE) will be used. These correlation coefficients will be used to demonstrate the prediction capacity and accuracy of both models. It should be noted that this approach will substitute the conventional testing required for strength parameters, which is both expensive and time-consuming.

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Section: Introductionmentioning

confidence: 99%

Prediction of Strength Properties of Soft Soil Considering Simple Soil Parameters

Hoque,

Bayezid,

Sharan

et al. 2023

OJCE

View full text Add to dashboard Cite

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Influence of Salt-Lime Stabilization on Soil Strength for Construction on Soft Clay

Islam,

Zahid,

Umama

et al. 2023

OJCE

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Construction on soft soil is one of the most challenging situations faced by geotechnical engineers. The heterogeneous and complex nature of soil, especially those containing organic clay, often makes it impossible for the construction specification to be addressed properly. Generally, clay exhibits low strength, high compressibility, and strength reduction when subjected to mechanical disturbance. This means that construction on clay soil is vulnerable to bearing capacity failure induced by low inherent shear strength. All these properties can be improved by the effective stabilization of soil. This study analyzed the effectiveness of incorporating salt-lime mixtures at various dosages in improving the strength increment of the soil. The results indicate that among different combinations of salt and lime, the best performance in terms of strength increase was achieved by adding 10% NaCl with 3% lime in the soil. The outcome of this study focuses on enhancing the ultimate strength of soil and its implementation in the field of foundation engineering.

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Vehicle-Bridge Interaction Simulation and Damage Identification of a Bridge Using Responses Measured in a Passing Vehicle by Empirical Mode Decomposition Method

Rana,

Zaman,

Ifty

et al. 2023

OJCE

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To prevent early bridge failures, effective Structural Health Monitoring (SHM) is vital. Vibration-based damage assessment is a powerful tool in this regard, as it relies on changes in a structure's dynamic characteristics as it degrades. By measuring the vibration response of a bridge due to passing vehicles, this approach can identify potential structural damage. This dissertation introduces a novel technique grounded in Vehicle-Bridge Interaction (VBI) to evaluate bridge health. It aims to detect damage by analyzing the response of passing vehicles, taking into account VBI. The theoretical foundation of this method begins with representing the bridge's superstructure using a Finite Element Model and employing a half-car dynamic model to simulate the vehicle with suspension. Two sets of motion equations, one for the bridge and one for the vehicle are generated using the Finite Element Method, mode superposition, and D'Alembert's principle. The combined dynamics are solved using the Newmark-beta method, accounting for road surface roughness. A new approach for damage identification based on the response of passing vehicles is proposed. The response is theoretically composed of vehicle frequency, bridge natural frequency, and a pseudo-frequency component related to vehicle speed. The Empirical Mode Decomposition (EMD) method is applied to decompose the signal into its constituent parts, and damage detection relies on the Intrinsic Mode Functions

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Provision of Building Codes in the Context of Seismicsite Characterization and Liquefaction Susceptibility Assessment

Cited by 5 publications

References 24 publications

Prediction of Strength Properties of Soft Soil Considering Simple Soil Parameters

Prediction of Strength Properties of Soft Soil Considering Simple Soil Parameters

Influence of Salt-Lime Stabilization on Soil Strength for Construction on Soft Clay

Vehicle-Bridge Interaction Simulation and Damage Identification of a Bridge Using Responses Measured in a Passing Vehicle by Empirical Mode Decomposition Method

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