Probabilistic framework for assessing liquefaction hazard at a given site in a specified exposure time using standard penetration testing

2010 ◽  
Vol 47 (6) ◽  
pp. 674-687 ◽  
Author(s):  
C. Hsein Juang ◽  
Chang-Yu Ou ◽  
Chih-Chieh Lu ◽  
Zhe Luo
Keyword(s):  
Exposure Time ◽  
Soil Column ◽  
Standard Penetration Test ◽  
Probabilistic Framework ◽  
Liquefaction Potential ◽  
Potential Index ◽  
Liquefaction Hazard ◽  
The Usa ◽  
Standard Penetration Testing ◽  
Surface Manifestation

This paper presents a probabilistic framework for assessing the liquefaction hazard at a given site in a given exposure time. Ten sites from different seismic-prone regions of the USA are studied to validate the developed probabilistic framework. Additionally, this framework is extended from the focus of liquefaction potential at a given soil element (or finite layer) to the concern of the whole soil column based on the concept of liquefaction potential index (LPI) proposed by Iwasaki and his co-workers. In this extended framework, the probability of surface manifestation of liquefaction at a given site subjected to all ground motions at all hazard levels in a given exposure time is determined. As an example to illustrate this probabilistic framework, the widely used, standard penetration test (SPT)-based method by Youd et al. is adopted as a building block in the framework. This framework is illustrated with examples and its versatility is demonstrated. Finally, the procedure for extending the developed framework to the evaluation of ground settlement is outlined.

scholarly journals LPI Based Earthquake Induced Soil Liquefaction Susceptibility Assessment at Probashi Palli Abasan Project Area, Tongi, Gazipur, Bangladesh

2018 ◽  
Vol 10 (2) ◽  
pp. 105-116
Author(s):  
A. H. Farazi ◽  
N. Ferdous ◽  
A. S. M. M. Kamal
Keyword(s):  
Threshold Value ◽  
Flood Plain ◽  
Standard Penetration Test ◽  
Soil Liquefaction ◽  
Cumulative Frequency ◽  
Liquefaction Potential ◽  
Project Area ◽  
Potential Index ◽  
Liquefaction Hazard ◽  
Simplified Procedure

This study aims at evaluation of seismic soil liquefaction hazard potential at Probashi Palli Abasan Project area of Tongi, Gazipur, exploiting standard penetration test (SPT) data of 15 boreholes, following Simplified Procedure. Liquefaction potential index (LPI) of each borehole was determined and then cumulative frequency distribution of clustered LPI values of each surface geology unit was determined assuming cumulative frequency at LPI = 5 as the threshold value for liquefaction initiation. By means of geotechnical investigation two surface geological units—Holocene flood plain deposits, and Pleistocene terrace deposits were identified in the study area. We predicted that 14% and 24% area of zones topped by Pleistocene terrace deposits and zones topped by Holocene flood plain deposits, respectively, would exhibit surface manifestation of liquefaction as a result of 7 magnitude earthquake. The engendered hazard map also depicts site specific liquefaction intensity through LPI values of respective boreholes, and color index, which was delineated by mapping with ArcGIS software. Very low to low, and low to high liquefaction potential, respectively, was found in the areas covered by Pleistocene terrace deposits and Holocene flood plain deposits. LPI values of both units are such that sand boils could be generated where LPI > 5.

scholarly journals Liquefaction Resistance Evaluation of Soils using Artificial Neural Network for Dhaka City, Bangladesh

2021 ◽  
Author(s):  
Abul Kashem Faruki Fahim ◽  
Md. Zillur Rahman ◽  
Md. Shakhawat Hossain ◽  
A S M Maksud Kamal
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Cumulative Frequency ◽  
Dhaka City ◽  
Liquefaction Resistance ◽  
Liquefaction Potential ◽  
Resistance Evaluation ◽  
Potential Index ◽  
Liquefaction Hazard ◽  
Artificial Neural

Abstract Soil liquefaction resistance evaluation is an important site investigation for seismically active areas. To minimize the loss of life and property, liquefaction hazard analysis is a prerequisite for seismic risk management and development of an area. Liquefaction potential index (LPI) is widely used to determine the severity of liquefaction quantitatively and spatially. LPI is estimated from the factor of safety (FS) of liquefaction that is the ratio of cyclic resistance ratio (CRR) to cyclic stress ratio (CSR) calculated applying simplified procedure. Artificial neural network (ANN) algorithm has been used in the present study to predict CRR directly from the normalized standard penetration test blow count (SPT-N) and near-surface shear wave velocity (Vs) data of Dhaka City. It is observed that ANN model have generated accurate CRR data. Three liquefaction hazard zones are identified in Dhaka City on the basis of the cumulative frequency (CF) distribution of the LPI of each geological unit. The liquefaction hazard maps have been prepared for the city using the liquefaction potential index (LPI) and its cumulative frequency (CF) distribution of each liquefaction hazard zone. The CF distribution of the SPT-N based LPI indicates that 15%, 53%, and 69% of areas, whereas the CF distribution of the Vs based LPI indicates that 11%, 48%, and 62% of areas of Zone 1, 2, and 3, respectively, show surface manifestation of liquefaction for a scenario earthquake of moment magnitude, Mw 7.5 with a peak horizontal ground acceleration (PGA) of 0.15 g.

scholarly journals Liquefaction Hazard Mapping Based on LPI (Liquefaction Potential Index) At Jepara, Indonesia

2020 ◽  
Vol 9 (4) ◽  
pp. 1611-1617
Keyword(s):  
Soil Analysis ◽  
Empirical Method ◽  
Earthquake Magnitude ◽  
Hazard Mapping ◽  
Penetration Test ◽  
Liquefaction Potential ◽  
Liquefaction Potential Index ◽  
Potential Index ◽  
Liquefaction Hazard ◽  
Potential Level

Liquefaction is a phenomenon of loss of strength of the soil layers caused by earthquake vibration. Liquefaction causes the soil to be in a liquid – like state, especially on sandy soil. Analysis of liquefaction potential was performed by using the semi-empirical method by calculating the Safety Factor (SF) based on Standard penetration Test (SPT) and Cone Penetration test (CPT) data. After the SF value was obtained, then the Liquefaction Potential Index (LPI) was calculated to determine the level of potential liquefaction in the study area to further produce a liquefaction potential map based on the liquefaction potential index. Based on the results of the calculation of the LPI, the level of liquefaction potential in the study area was very low when the earthquake magnitude is 5 Mw because the Liquefaction Potential Index (LPI) = 0. When the earthquake magnitude is 6 Mw, 7 Mw, 8 Mw, and 9 Mw, most of the investigation area has low potential level and there are some points that a high potential level.

scholarly journals Brief Communication: A case study of risk assessment for facilities associated with earthquake-induced liquefaction potential in Kimhae City, South Korea 

2021 ◽  
Author(s):  
Sang-Soo Jeon ◽  
Daeyang Heo ◽  
Sang-Seung Lee
Keyword(s):  
Geographical Information Systems ◽  
Standard Penetration Test ◽  
Geographical Information ◽  
Liquefaction Potential ◽  
Risk Levels ◽  
Potential Index ◽  
Secondary Damage ◽  
Yangsan Fault ◽  
The Nakdong River ◽  
High Level

Abstract. Liquefaction causes secondary damage after earthquakes; however, liquefaction related phenomena were rarely reported until after the Mw = 5.4 November 15, 2017 Pohang earthquake in Korea. Both the Mw = 5.8 September 12, 2016 Gyeongju earthquake and Mw = 5.4 November 15, 2017 Pohang earthquake occurred in the fault zone of Yangsan City (located in the south-eastern part of Korea), and both of these earthquakes induced liquefaction. Moreover, they demonstrated that Korea is not safe against the liquefaction induced by earthquakes. In this study, estimations and calculations were performed based on the distances between the centroids of administrative districts and an epicenter located at the Yangsan Fault, the peak ground accelerations (PGAs) induced by Mw = 5.0 and 6.5 earthquakes, and a liquefaction potential index (LPI) calculated based on groundwater level and standard penetration test results from 274 locations in Kimhae City (adjacent to the Nakdong river and across the Yangsan Fault). Then, a kriging method using geographical information systems was used to evaluate the liquefaction effects on the risk levels of facilities. The results indicate that a Mw = 5.0 earthquake induces a small and low level of liquefaction, resulting in slight risk for facilities, but a Mw = 6.5 earthquake induces a large and high level of liquefaction, resulting in a severe risk for facilities.

Liquefaction Hazard Scenario of Imphal City for 1869 Cachar and a Hypothetical Earthquake

2012 ◽  
Vol 3 (1) ◽  
pp. 34-56 ◽  
Author(s):  
Kumar Pallav ◽  
S. T. G. Raghukanth ◽  
Konjengbam Darunkumar Singh
Keyword(s):  
Severity Index ◽  
Great Earthquake ◽  
Potential Hazard ◽  
Large Area ◽  
Liquefaction Potential ◽  
Contour Maps ◽  
Potential Index ◽  
Liquefaction Hazard ◽  
Hazard Scenario ◽  
Liquefaction Failure

In the present article liquefaction potential of Imphal city is reported in the form of two indices, i.e., LPI (Liquefaction Potential Index) and LSI (Liquefaction Severity Index), for 1869 Cachar earthquake (Mw 7.5) along the Kopili fault and probable future great earthquake (Mw 8.1) in the Indo-Burma subduction zone. The Factor of Safety (FS) against liquefaction has been computed by using modified procedure given by Idriss and Boulanger (2006) for all depths of 122 boreholes. The computed FS have been used as input parameters for evaluating LPI and LSI indices for Imphal City. Based on these LPI and LSI indices, liquefaction potential hazard contour maps of Imphal city is prepared. It is observed that over a large area of Imphal city is highly vulnerable to liquefaction failure in the events of the selected earthquake. The liquefaction hazard obtained at each site exhibits a good agreement with the damages documented for 1869 Cachar earthquake. This contour map can be served as a guideline for engineer and planner in site selection for upcoming projects and helps city administration in mitigating the city from future hazards.

scholarly journals Liquefaction potential analysis in Palu Bay area

2021 ◽  
Vol 930 (1) ◽  
pp. 012077
Author(s):  
F Patriaman ◽  
T F Fathani ◽  
W Wilopo
Keyword(s):  
Soil Condition ◽  
Standard Penetration Test ◽  
Command Area ◽  
Eastern Region ◽  
Liquefaction Potential ◽  
Potential Analysis ◽  
Eastern Area ◽  
Bay Area ◽  
Liquefaction Potential Index ◽  
Potential Index

Abstract Sulawesi Island has a Palu Koro Fault that actively moves with a high displacement magnitude but low seismicity. On 28 September 2018, at 18:02 local time, an earthquake occurred in Palu Koro Shear Fault. The field investigations along the Palu coast revealed new evidence regarding the extensive liquefaction in these areas, both inland and coastal land. The research command area was located in the Palu Bay coastal area, the Province of Central Sulawesi. The data used was in the form of the Standard Penetration Test of the area, and the potential liquefaction analysis was carried out using the simplified procedure method. Furthermore, to determine the level of liquefaction potential, Liquefaction Potential Index was applied. Geological observations showed that the soil condition in the Palu Bay area was dominated by non-cohesive soil (sand). Based on the liquefaction potential analysis, it was indicated that most of the eastern region of the Palu Bay area showed no liquefaction potential. On the contrary, the western and southern parts were indicated to have liquefaction potentials. The Liquefaction Potential Index analysis results showed that the western and southern areas were dominated with extremely high liquefaction potentials. Meanwhile, in the eastern area, it was extremely low.

Assessment of Liquefaction Potential Index Using Deterministic and Probabilistic Approaches

2012 ◽  
Vol 3 (2) ◽  
pp. 60-76 ◽  
Author(s):  
Naveen James ◽  
T. G. Sitharam ◽  
K. S. Vipin
Keyword(s):  
Nuclear Power ◽  
Pore Water Pressure ◽  
Water Pressure ◽  
Liquefaction Potential ◽  
Liquefaction Susceptibility ◽  
Liquefaction Potential Index ◽  
Potential Index ◽  
Liquefaction Hazard ◽  
Sudden Decrease ◽  
Deterministic And Probabilistic Approaches

Liquefaction is a devastating effect of earthquakes resulting in sudden decrease in shear strength due to excess pore water pressure generation, resulting in differential settlement of structure, inducing severe damages. Assessment of liquefaction hazard for a given site is important for planning out mitigation works. In this paper the liquefaction susceptibility using deterministic and probabilistic methodologies was assessed and results are presented in terms of liquefaction potential index (LPI) for a nuclear power plant site. The results of this study are explored further in the article.

Evaluation of the Liquefaction Potential Index for Assessing Liquefaction Hazard in Christchurch, New Zealand

2014 ◽  
Vol 140 (7) ◽  
pp. 04014032 ◽  
Author(s):  
Brett W. Maurer ◽  
Russell A. Green ◽  
Misko Cubrinovski ◽  
Brendon A. Bradley
Keyword(s):  
New Zealand ◽  
Liquefaction Potential ◽  
Liquefaction Potential Index ◽  
Potential Index ◽  
Liquefaction Hazard

scholarly journals Probabilistic Analysis of Local Liquefaction Potential Based on Spatial Variability of SPT Data

2020 ◽  
Keyword(s):  
Random Field ◽  
Conditional Random Field ◽  
Site Investigation ◽  
Standard Penetration Test ◽  
Layer By Layer ◽  
Liquefaction Potential ◽  
In Situ Data ◽  
Potential Index ◽  
Liquefiable Soil ◽  
Spt Data

In this paper, the spatial distribution of liquefaction potential is estimated using in-situ data from the Standard Penetration Test (SPT). For this purpose, a case study of a liquefiable soil at the Azad University of Qeshm is selected in the numerical modeling. After conducting the site investigation and determining SPT results at four boreholes, two distinct modeling approaches are implemented to evaluate the Liquefaction Potential Index (LPI) at the considered site; In the first method, the conditional random field for SPT data is generated in a layer-by-layer strategy and then, the LPI is obtained using a SPT-based empirical relations at each elemental column. On the other hand, in the second method, the LPI is first determined at each borehole location and then, this parameter is adopted as a stochastic variable in the construction of surficial conditional random field. It can be concluded that both approaches are able to capture the varying severity levels of liquefaction at most locations across the area of study. However, the comparison shows that using the first approach results in a more fluctuated LPI results with almost the same extremum values.

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