Correlation of Electrical Resistivity and SPT-N Value from Standard Penetration Test (SPT) of Sandy Soil

2015 ◽  
Vol 785 ◽  
pp. 702-706 ◽  
Author(s):  
Khairul Anwar Hatta ◽  
Syed Baharom Azahar Syed Osman

In general practice, soil investigation (SI) incorporating bore hole sampling produced the most reliable value of the relevant soil parameters for the purpose of actual calculation on factor of safety (FOS) in slopes even tough time consuming and very expensive. Assessments of slope stability using electrical parameters have least been research by many scholars due to non-destructive and very sensitive and it is attractive tool for describing the subsurface properties of the slope without disturbing the physical characteristic of the soil. The method has been applied in various contexts like groundwater exploration, agronomical management by identifying areas of excessive or soil horizon thickness and bedrock depth. This paper investigates the relationship between electrical resistivity and SPT-N values of sandy soils. The research work consists of field resistivity surveys, soil boring and soil characterization tests. Field survey included 1D vertical electrical sounding (VES) and SPT method in obtaining SPT-N value. The test being conducted on 3 different areas and 11 sandy soil sample with electrical, physical soil characterization data which being used for least-squares regression method. In this part of the study, correlations of electrical resistivity with SPT values of soil were assessed. The findings showed good correlation between the resistivity and soil properties. The obtained results demonstrate the possibility usage of electrical resistivity survey as an alternative to standard penetration test SPT is possible.

Author(s):  
A. Burak Göktepe ◽  
Selim Altun ◽  
Alper Sezer

AbstractThe standard penetration test (SPT) is the most common test conducted in the field, and it is used to determine in situ properties of different soils. Although it is a matter of debate, these tests are also used for the determination of the consistency of fine-grained soils, whereby the test results can also be utilized to establish numerous empirical correlations to predict the strength of soils in the field. In this study, unsupervised clustering algorithms were employed to classify the SPT standard penetration resistance value (SPT-N) in the field. In this scope, shear strength and liquidity index parameters were used to classify the SPT-N values by taking the classification system of Terzaghi and Peck (1967) into consideration. The results showed that the input parameters were successful for classifying the SPT-N value to an acceptable degree of strength attribute. Therefore, in cases where the SPT tests are unreliable or could not be performed, laboratory tests on undisturbed specimens can give valuable information regarding the consistency and SPT-N value of the soil specimen under investigation. Data in this study is based on several tests that were conducted in a region; nevertheless, it is advised that the results of this study should be evaluated using global data.


2005 ◽  
Vol 42 (3) ◽  
pp. 856-875 ◽  
Author(s):  
Sheng-Yao Lai ◽  
Ping-Sien Lin ◽  
Ming-Jyh Hsieh ◽  
Hoi-Fung Jim

Discriminant models are developed for evaluating soil liquefaction potential, using standard penetration test (SPT) data for 592 occurrences of liquefaction and nonliquefaction. The discriminant model used is a multivariate statistical method. The square root of the SPT N value, (N1)601/2, and the logarithm of the cyclic stress ratio, ln CSR7.5, are adopted as the major parameters for analyses. Two models measuring liquefaction resistance through the SPT N value are also established in this study, which allows calculated results to be compared with the empirical curves. Key words: liquefaction, discriminant analysis, misclassified probability.


2017 ◽  
Vol 8 (3) ◽  
pp. 143
Author(s):  
Rifki Asrul Sani

ABSTRAKSeiring dengan terjadinya longsoran di beberapa titik wilayah di bukit Hambalang, maka diperlukan kajian data kondisi geologi teknik berupa sifat fisik dan mekanik tanah serta batuan bawah permukaan, terutama mengenai daya dukung tanah dalam menahan beban bangunan di atasnya agar tidak terjadi penurunan. Metode yang digunakan dalam penelitian ini dibagi menjadi tiga, yaitu metode penelitian studio dengan memanfaatkan data-data sekunder yang telah ada, metode penelitian di lapangan melalui pemetaan geologi untuk mendapatkan data litologi yang tersingkap di permukaan, zonasi longsoran yang terjadi, dan identifikasi kekuatan tanah hasil pemboran geoteknik dengan Standard Penetration Test (SPT), serta metode penelitian di laboratorium untuk mendapatkan parameter sifat fisik dan mekanik tanah sebagai penunjang data daya dukung tanah serta geologi teknik daerah penelitian. Hasil perhitungan fondasi dangkal untuk general soil shear condition dan local soil shear condition dapat disimpulkan bahwa daya dukung tanah yang diizinkan (qa) untuk setiap kedalaman yang paling tinggi pada fondasi bujur sangkar (square footing) dan nilai tertinggi yang terdapat pada kedalaman 2 m, yaitu 57,32 ton/m2 dan 36,11 ton/m2. Fondasi yang paling rendah untuk semua kedalaman pada fondasi menerus (continuous footing) untuk kedalaman 2 m memiliki nilai 34,49 ton/m2 dan 21,25 ton/m2. Berdasarkan data SPT, nilai daya dukung yang diizinkan (qa) pada masing-masing titik bor berkisar pada rentang 2,85 ton/m2 sampai 16,85 ton/m2. Kata kunci: longsoran, daya dukung, Standard Penetration Test (SPT). ABSTRACTAlong with the landslide in some areas on the Hambalang Hill, it needs data of engineering geological study such as mechanical and physical properties of soil also subsurface rocks. Especially regarding the soil bearing capacity in order to restrain the building from settlement. There are three methods which used in this research, those are studio research by using secondary data, fieldwork research that is geological mapping conducted to obtain data on lithological rocks at surface, landslide zone and soil strength identification from geotechnical drilling with Standard Penetration Test (SPT) and laboratory research to obtain the soil parameters of physical and mechanical properties, which used to support soil bearing capacity data and engineering geology in research area. The calculation results of the shallow foundation for general soil shear condition and the local soil shear condition it could be concluded that the allowable bearing capacity for all depth which is highest at the square footing and the highest value found to a depth of 2 m, that is 57.32 ton/m2 and 36.11 ton/m2. The lowest foundation for all the depth of the continuous footing to a depth of 2 m had value 34.49 ton/m2 and 21.25 ton/m2. Based on data from SPT, the allowable bearing capacity on each of borehole ranging from 2.85 ton/m2 to 16.85 ton/m2. Keywords: landslide, bearing capacity, Standard Penetration Test (SPT).


2014 ◽  
Vol 2 (4) ◽  
pp. 2443-2461 ◽  
Author(s):  
I. Shooshpasha ◽  
A. Kordnaeij ◽  
U. Dikmen ◽  
H. MolaAbasi ◽  
I. Amir

Abstract. Shear wave velocity (VS) is a basic engineering property implemented in evaluating the soil shear modulus. In many instances it may be preferable to determine VS indirectly by common in-situ tests, such as the Standard Penetration Test (SPT). In this paper, the relationship between VS and geotechnical soil parameters such as standard penetration test blow counts (N160), effective stress and fines content, as well as overburden stress ratio (σvo/σ′vo), is investigated. A new mode based on support vector machine (SVM) approach is proposed to correlate geotechnical parameters and VS, predicated on a total of 620 data sets, including field investigation records for the Kocaeli (Turkey, 1999) and Chi-Chi (Taiwan, 1999) earthquakes. This study addresses the question of whether Support Vector Machine (SVM) approach should be used to estimate VS based on the specified geotechnical variables, and assessing the influence of each variable on VS. Results revealed that SVM, in comparison to previous statistical relations, provides an effective means of efficiently recognizing the patterns in data and accurately predicting the VS.


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