Effect Rate of Strain on In Situ Horizontal Coefficient of Consolidation from Pressuremeter

Alzubaidi, Radhi

doi:10.1007/s10706-019-01122-6

Cited by 3 publications

(1 citation statement)

References 5 publications

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“…In the world, the horizontal coefficient of consolidation of soft soil can be commonly determined by three methods, such as laboratory tests, CPTu dissipation tests, and Asaoka's observational method. Recently, the c h value can be calculated by DMT pressure dissipation tests [7] or pressuremeter [8].…”

Section: Introductionmentioning

confidence: 99%

Research on Horizontal Coefficient of Consolidation of Vietnam’s Soft Soil

Son

Ngoc

2020

Journal of Engineering

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The horizontal coefficient of consolidation is the most important parameter for designing the improvement of soil soft by prefabricated vertical drains (PVDs) combined with surcharge and vacuum preloading. This paper presents the experimental study on the horizontal coefficient of consolidation (ch) of some soft soils distributed in Vietnam. The ch value was determined by the laboratory test and CPTu dissipation test. The laboratory tests included the Rowe consolidation cell test and constant rate of strain consolidation with radial drainage test. Two types of consolidation laboratory tests were performed. The experimental results indicated that the ch value is always larger than the vertical coefficient of consolidation of soil (cv). The ratio of ch/cv depends on the consolidated pressure, type of soil, and the anisotropy of soil. The ratio of ch/cv is different in different types of soft soil in Vietnam. In the normally consolidated state, the ch/cv ratio ranges from 1.35 to 10.59. It was necessary to choose the ch value at the consolidated stress level for calculating the PVD spacing.

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Section: Introductionmentioning

confidence: 99%

Research on Horizontal Coefficient of Consolidation of Vietnam’s Soft Soil

Son

Ngoc

2020

Journal of Engineering

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In-situ Creep Behavior of Expansive Soils Based on Pressuremeter Test

Li,

Kong,

Jin

2023

Geotech Geol Eng

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Prediction of stratified ground consolidation via a physics‐informed neural network utilizing short‐term excess pore water pressure monitoring data

Gong,

Zuo,

et al. 2024

Computer aided Civil Eng

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Predicting stratified ground consolidation effectively remains a challenge in geotechnical engineering, especially when it comes to quickly and dependably determining the coefficient of consolidation () for each soil layer. This difficulty primarily stems from the time‐intensive nature of the consolidation process and the challenges in efficiently simulating this process in laboratory settings and using numerical methods. Nevertheless, the consolidation of stratified ground is crucial because it governs ground settlement, affecting the safety and serviceability of structures situated on or in such ground. In this study, an innovative method utilizing a physics‐informed neural network (PINN) is introduced to predict stratified ground consolidation, relying solely on short‐term excess pore water pressure (PWP) data collected by monitoring sensors. The proposed PINN framework identifies from the limited PWP data set and subsequently utilizes the identified to predict the long‐term consolidation process of stratified ground. The efficacy of the method is demonstrated through its application to a case study involving two‐layer ground consolidation, with comparisons made to an existing PINN method and a laboratory consolidation test. The results of the case study demonstrate the applicability of the proposed PINN method to both forward and inverse consolidation problems. Specifically, the method accurately predicts the long‐term dissipation of excess PWP when is known (i.e., the forward problem). It successfully identifies the unknown with only 0.05‐year monitoring data comprising 10 data points and predicts the dissipation of excess PWP at 1‐year, 10‐year, 15‐year, and even up to 30‐year intervals using the identified (i.e., the inverse problem). Moreover, the investigation into optimal PWP monitoring sensor layouts reveals that installing sensors in areas with significant variations in excess PWP enhances the prediction accuracy of the proposed PINN method. The results underscore the potential of leveraging PINNs in conjunction with PWP monitoring sensors to effectively predict stratified ground consolidation.

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Effect Rate of Strain on In Situ Horizontal Coefficient of Consolidation from Pressuremeter

Cited by 3 publications

References 5 publications

Research on Horizontal Coefficient of Consolidation of Vietnam’s Soft Soil

Research on Horizontal Coefficient of Consolidation of Vietnam’s Soft Soil

In-situ Creep Behavior of Expansive Soils Based on Pressuremeter Test

Prediction of stratified ground consolidation via a physics‐informed neural network utilizing short‐term excess pore water pressure monitoring data

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