دورية أكاديمية
أعرض في EDS

Wavelet Packet Method for Locating Critical Slip Surface Using the Strength Reduction Method

التفاصيل البيبلوغرافية
العنوان: Wavelet Packet Method for Locating Critical Slip Surface Using the Strength Reduction Method
المؤلفون: Yongfeng Cheng, Zhibao Nie, Chao Han, Shijun Ding, Kaiyuan Liu
المصدر: Applied Sciences, Vol 11, Iss 21, p 10098 (2021)
بيانات النشر: MDPI AG, 2021.
سنة النشر: 2021
المجموعة: LCC:Technology
LCC:Engineering (General). Civil engineering (General)
LCC:Biology (General)
LCC:Physics
LCC:Chemistry
مصطلحات موضوعية: slope stability analysis, strength reduction method, critical slip surface, wavelet packet analysis, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999
الوصف: When the finite element-strength reduction method is used for two-dimensional slope stability analysis for elastic-perfectly plastic material, the failure criterion usually adopts the criterion of plastic zone penetration. That is, when the slope is in the limit equilibrium state, the plastic zone goes through the slope from the toe to the top. Meanwhile, the critical slip surface is composed of a series of points of maximum equivalent plastic strain along the depth direction. By deploying a set of parallel lines approximately perpendicular to the slope surface and picking out the points of these lines with the maximum equivalent strain points, we obtain a series of points taking on a wave shape, which constitutes a signal function. Subsequently, the wavelet packet analysis is used to smooth these points, i.e., locating the critical slip surface. The analysis of classic examples and comparison with Spencer’s method show that the proposed method in this paper is reasonable and effective.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2076-3417
Relation: https://www.mdpi.com/2076-3417/11/21/10098; https://doaj.org/toc/2076-3417
DOI: 10.3390/app112110098
URL الوصول: https://doaj.org/article/91170e9388c54cef9e5f658c83904442
رقم الأكسشن: edsdoj.91170e9388c54cef9e5f658c83904442
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:20763417
DOI:10.3390/app112110098