Showing 281 - 300 results of 1,366 for search 'fault three analysis (method OR methods)', query time: 0.21s Refine Results
  1. 281

    Effects of Earthquake on Behavior Characteristics of Fault Gouge in Time-History Analysis of Slope by Seong-Woo Moon, Hyeong-Sin Kim, Yong-Seok Seo

    Published 2022-01-01
    “…A time-history analysis, based on the finite element method, was performed to identify the behavior of a slope containing fault gouge during earthquakes. …”
    Get full text
    Article
  2. 282

    Fire risk assessment in DC Tehran metro trains with Fault Tree Analysis by S Daneshvar, SB Mortazavi, S AtrKar Roshan

    Published 2013-11-01
    “…This study aimed to assess the risk of fire in DC trains and subway lines in Tehran. Methods: For performing this research, after identification of fire hazards in metro trains through observation, interview techniques and review the documentation, Fault Tree Analysis (FTA) was used to determine the causes of fires in DC trains at Tehran metro. …”
    Get full text
    Article
  3. 283
  4. 284
  5. 285
  6. 286

    Regularities of crustal faulting and tectonophysical indicators of fault metastability by Yu. L. Rebetsky

    Published 2018-10-01
    “…The stress state in the vicinity of ruptures and faults has different characteristic features. Based on the seismological and tectonophysical data on earthquake focal parameters and discontinuities, it is possible to identify two or three ranks of stresses, which differ in the laws predetermining their mutual relationships. …”
    Get full text
    Article
  7. 287
  8. 288
  9. 289

    Tectonic characteristics and numerical simulation analysis of an arcuate structural belt:A case study of the middle and southern segments of the Red River fault by WANG Chenxu, LI Xi

    Published 2024-11-01
    “…A three-dimensional (3D) geological model tailored to the actual characteristics of the region was established. …”
    Get full text
    Article
  10. 290
  11. 291
  12. 292

    ANALYSIS OF SUBSURFACE STRUCTURE OF BANDAR LAMPUNG CITY BASED ON GRAVITY ANOMALIES by I. Dani, A. Zaenudin, A. I. Hutomo, N. Yuniza

    Published 2024-08-01
    “…This study aims to identify the subsurface structure of Bandar Lampung City based on gravity anomaly modeling, both 2D and 3D models. The research consists of three main stages: data correction, data processing including spectrum analysis, moving average, second vertical derivative analysis, and subsurface structure modeling. …”
    Get full text
    Article
  13. 293

    INTERBLOCK ZONES IN THE CRUST OF THE SOUTHERN REGIONS OF EAST SIBERIA: TECTONOPHYSICAL INTERPRETATION OF GEOLOGICAL AND GEOPHYSICAL DATA by K. Zh. Seminsky, N. O. Kozhevnikov, A. V. Cheremnykh, E. V. Pospeeva, A. A. Bobrov, V. V. Olenchenko, M. A. Tugarina, V. V. Potapov, R. M. Zaripov, A.S. Cheremnykh

    Published 2015-09-01
    “…We used structural geological methods for studying faults and fractures, morphostructural analysis (including interpretation of satellite images), self-potential (SP) and resistivity profiling, magnetotelluric (MT) sounding, radon emanation survey, and hydrogeological studies of water occurrences. …”
    Get full text
    Article
  14. 294

    Incidence Matrix based Method for <tex>$N-1$</tex> Contingency Parallel Analysis of Main Transformers in Distribution Networks by Qiubo Zou, Fengzhang Luo, Tianyu Zhang

    Published 2025-01-01
    “…The existing <tex>$N-1$</tex> contingency analysis methods of distribution networks are primarily based on the unit of components, and the faults of each component are analyzed and verified one by one. …”
    Get full text
    Article
  15. 295
  16. 296

    Fault Diagnosis of Induction Motors Using Recurrence Quantification Analysis and LSTM with Weighted BN by Dengyu Xiao, Yixiang Huang, Chengjin Qin, Haotian Shi, Yanming Li

    Published 2019-01-01
    “…To cover those shortcomings, in this paper, two manual feature learning approaches are embedded into a deep learning algorithm, and thus, a novel fault diagnosis framework is proposed for three-phase induction motors with a hybrid feature learning method, which combines empirical statistical parameters, recurrence quantification analysis (RQA) and long short-term memory (LSTM) neural network. …”
    Get full text
    Article
  17. 297
  18. 298
  19. 299
  20. 300