Predicting the Friction Angle of Bangkok Sand Using State Parameter and Neural Network
บทความในวารสาร
ผู้เขียน/บรรณาธิการ
กลุ่มสาขาการวิจัยเชิงกลยุทธ์
รายละเอียดสำหรับงานพิมพ์
รายชื่อผู้แต่ง: Youwai S., Wongsala K.
ผู้เผยแพร่: Springer
ปีที่เผยแพร่ (ค.ศ.): 2024
Volume number: 42
หน้าแรก: 5947
หน้าสุดท้าย: 5965
จำนวนหน้า: 19
นอก: 0960-3182
eISSN: 1573-1529
ภาษา: English-Great Britain (EN-GB)
บทคัดย่อ
Accurate determination of the friction angle of sand is crucial for foundation design. Existing research lacks a comprehensive method to ascertain the friction angle specifically for Bangkok Sand based on the Standard Penetration Test (SPT). This study introduces an innovative technique leveraging the concept of the state parameter, a dimensionless metric characterizing the sand’s state relative to its critical condition. The method establishes a correlation between the friction angle and data obtained from triaxial tests and the SPT. The relationship between the friction angle and state parameters of Bangkok Sand is derived from triaxial testing. Additionally, a calibration chamber study involving 17 tests explores the connection between SPT values and the state parameter. To predict the state parameter, a fully connected neural network was developed, incorporating the SPT-N value and the prevailing confining stresses. This parameter is subsequently used to estimate the friction angle from triaxial test data. The validity of this approach is confirmed by a high coefficient of determination (R2 = 0.98), demonstrating its precision. Furthermore, the friction angle deduced through this novel approach is compared with those obtained using traditional methods. This study contributes to the field by providing an effective and accurate method for determining the friction angle of Bangkok Sand, essential for geotechnical engineering applications. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.
คำสำคัญ
Standard penetration test, State parameters
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