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A Developed Computational Code to Build a 3D Fracture Network to Reduce the Uncertainty of Fracture Parameter Generation (A Case Study of the Emamzadeh Hashem Tunnel)

Rock masses comprise intact rock and discontinuities, such as fractures, which significantly influence their mechanical and hydraulic properties. Uncertainty in constructing the fracture network can notably affect the outcomes of sensitive analyses, including tunnel stability simulations. Thus, accurately determining specific parameters of rock joints, including orientation and trace length, is essential. A discrete fracture network (DFN) is one technique used to simulate jointed rock. However, engineers often face challenges due to the inherent uncertainty in building a fracture network using statistical distribution functions. This study analyzed the fracture network of the Emamzadeh Hashem tunnel using MATLAB-developed code and 3DEC software. It focused on the impact of statistical distribution functions on the uncertainty of fracture network construction. The results reveal that using a negative exponential distribution can introduce significant errors in constructing the fracture network, especially when generating the dip direction. The parametric study shows that employing statistical distribution functions that account for data variance in the Probability Distribution Function (PDF) can enhance the accuracy of generating fracture parameters, such as dip, dip direction, and trace length, thereby reducing uncertainty in fracture network construction.

Ketersediaan
#
Perpustakaan BIG (Eksternal Harddisk) 550
341
Tersedia
Informasi Detail
Judul Seri
Geosciences
No. Panggil
550
Penerbit
Switzerland : MPDI.,
Deskripsi Fisik
22 hlm PDF, 3.692 KB
Bahasa
Inggris
ISBN/ISSN
2076-3263
Klasifikasi
550
Tipe Isi
text
Tipe Media
other
Tipe Pembawa
online resource
Edisi
Vol.15, Issue 1, January 2025
Subjek
Uncertainty
discrete fracture network
jointed rock
3DEC
statistical distribution
geohazard
Info Detail Spesifik
Geosciences
Pernyataan Tanggungjawab
Versi lain/terkait

Tidak tersedia versi lain

Lampiran Berkas
  • A Developed Computational Code to Build a 3D Fracture Network to Reduce the Uncertainty of Fracture Parameter Generation (A Case Study of the Emamzadeh Hashem Tunnel)
    Rock masses comprise intact rock and discontinuities, such as fractures, which significantly influence their mechanical and hydraulic properties. Uncertainty in constructing the fracture network can notably affect the outcomes of sensitive analyses, including tunnel stability simulations. Thus, accurately determining specific parameters of rock joints, including orientation and trace length, is essential. A discrete fracture network (DFN) is one technique used to simulate jointed rock. However, engineers often face challenges due to the inherent uncertainty in building a fracture network using statistical distribution functions. This study analyzed the fracture network of the Emamzadeh Hashem tunnel using MATLAB-developed code and 3DEC software. It focused on the impact of statistical distribution functions on the uncertainty of fracture network construction. The results reveal that using a negative exponential distribution can introduce significant errors in constructing the fracture network, especially when generating the dip direction. The parametric study shows that employing statistical distribution functions that account for data variance in the Probability Distribution Function (PDF) can enhance the accuracy of generating fracture parameters, such as dip, dip direction, and trace length, thereby reducing uncertainty in fracture network construction.
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