Article
Engineering, Environmental
Zhi-Ping Deng, Min Pan, Jing-Tai Niu, Shui-Hua Jiang, Wu-Wen Qian
Summary: This paper proposes a reliable analysis method for slopes based on the SIR-MARS method, which effectively solves the high dimensionality problem under spatially variable soils. By simulating the spatial variability of soil properties and establishing the relationship between soil shear strength parameters and safety factor, the method obtains accurate reliability results at a low cost.
BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT
(2021)
Article
Engineering, Environmental
Zhiyong Yang, Jiayan Nie, Xing Peng, Dong Tang, Xueyou Li
Summary: This study systematically investigates the influence of RFE size on statistics of factor of safety (FS) and sliding mass (SM) distribution, critical slip surfaces, reliability, and risk of slopes, showing that the RFE sizes have a relatively larger influence on the distribution of SM than that of FS, tending to overestimate slope failure probability and risk with larger RFE sizes.
BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT
(2021)
Article
Geosciences, Multidisciplinary
Longlong Chen, Wengang Zhang, Fuyong Chen, Dongming Gu, Lin Wang, Zhenyu Wang
Summary: Anisotropic spatial variability of soil properties has a significant influence on slope failure probability and failure characteristics. The directional angles of scales of fluctuation and the cross-correlation between soil properties are the key factors. General anisotropic spatial variability has a stronger effect on slope reliability compared to transverse anisotropic spatial variability.
GEOSCIENCE FRONTIERS
(2022)
Article
Engineering, Geological
Longlong Chen, Wengang Zhang, Gustavo Paneiro, Yuwei He, Li Hong
Summary: In this study, an efficient numerical-simulation-based slope reliability analysis (NSB-SRA) method considering spatial variability is proposed. By employing dual dimensionality reduction and response conditioning techniques, the computational time is reduced and the accuracy of slope reliability assessment is improved.
Article
Engineering, Geological
Wengang Zhang, Chongzhi Wu, Yongqin Li, Lin Wang, P. Samui
Summary: This study utilizes machine learning algorithms to construct predictive models for assessing pile drivability, comparing the performance of Random Forest Regression (RFR) and Multivariate Adaptive Regression Splines (MARS) models. The results indicate that the RFR model outperforms MARS in terms of fitting and operational efficiency.
GEORISK-ASSESSMENT AND MANAGEMENT OF RISK FOR ENGINEERED SYSTEMS AND GEOHAZARDS
(2021)
Article
Thermodynamics
Mohammad Ali Sahraei, Hakan Duman, Muhammed Yasin Codur, Ecevit Eyduran
Summary: This research aims to predict transport energy demand in Turkey using the MARS model, with the third MARS model selected as the best predictive model after evaluating multiple factors.
Article
Engineering, Environmental
Tengfei Wang, Qiang Luo, Zhengtao Li, Wensheng Zhang, Weihang Chen, Liyang Wang
Summary: This paper presents a methodology for evaluating the safety of large-scale geotechnical systems and applies it to the reliability analysis of a long railway geotechnical slope system. By incorporating multivariate adaptive regression splines (MARS) into the reliability analysis, the probability of failure for each slope segment can be assessed. Through a reliability-based performance evaluation and exploration of the effect of remediation on system reliability, the safety of the geotechnical slope system can be comprehensively assessed.
BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT
(2022)
Article
Computer Science, Interdisciplinary Applications
Xin Liu, Yu Wang
Summary: This study develops a method based on Monte Carlo simulation to assess the annual slope failure probability (PFA) considering both soil spatial variability and rainfall uncertainty. Results show that the semi-analytical and Monte Carlo simulation-based methods produce consistent PFA. When the variability of soil properties is negligible, PFA is dominated by rainfall uncertainty and converges to a constant failure probability.
COMPUTERS AND GEOTECHNICS
(2023)
Article
Engineering, Environmental
Xueyou Li, Yadong Liu, Zhiyong Yang, Zhenzhu Meng, Limin Zhang
Summary: The paper proposes an efficient slope reliability analysis method based on active learning support vector machine (SVM) and Monte Carlo simulation (MCS), which updates the model by selecting appropriate training samples to improve efficiency and accuracy. The effectiveness of the method is demonstrated using four slope examples and compared with other surrogate models, showing better computational efficiency and similar estimation accuracy.
BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT
(2021)
Article
Computer Science, Artificial Intelligence
Gulsah Altinok, Pinar Karagoz, Inci Batmaz
Summary: Learning to rank is a supervised learning problem that aims to construct a ranking model for a given dataset, with MARS and CMARS being effective techniques for point-wise learning to rank. Experimental results show that MARS and ANN are effective methods for learning to rank problem and provide promising results.
COMPUTATIONAL INTELLIGENCE
(2021)
Article
Environmental Sciences
Guodao Zhang, Sayed M. Bateni, Changhyun Jun, Helaleh Khoshkam, Shahab S. Band, Amir Mosavi
Summary: The feasibility of using random forest (RF) and multivariate adaptive regression splines (MARS) for predicting the long-term mean monthly dew point temperature (T-dew) was evaluated in this study. The results showed that both RF and MARS methods were capable of accurately predicting the long-term mean monthly T-dew.
FRONTIERS IN ENVIRONMENTAL SCIENCE
(2022)
Article
Computer Science, Interdisciplinary Applications
Kang Liao, Yiping Wu, Fasheng Miao, Yutao Pan, Michael Beer
Summary: This study presents a risk assessment for earth dams in spatially variable soils using the random adaptive finite element limit analysis. It introduces the random field theory to describe soil spatial variability, adopts the adaptive finite element limit analysis to obtain the bound solution and consequence, and counts the failure probability and risk assessment through Monte Carlo simulation. The stochastic analysis considering spatial variability can provide statistical characteristics of stability and comprehensively assess the risk of earth dam failure, which is useful for decision-making and mitigation.
ENGINEERING WITH COMPUTERS
(2023)
Article
Computer Science, Interdisciplinary Applications
Yi-li Yuan, Chang-ming Hu, Yuan Mei, Xue-yan Wang, Juan Wang
Summary: This study analyzed the impact of curvilinear local averaging on a 2-D random field by equation derivation, proposing a simple reliability analysis method for natural slopes. Experimental results show that this method is reliable and efficient.
COMPUTERS AND GEOTECHNICS
(2021)
Article
Engineering, Civil
Atin Roy, Subrata Chakraborty
Summary: The dual metamodeling approach is used to address the stochastic nature of earthquakes, while avoiding prior distribution assumption, a direct response approximation approach is attempted here. Furthermore, an adaptive support vector regression-based metamodeling is proposed for selecting new training samples near the failure boundary with consideration to accuracy and efficiency. The effectiveness of the approach is demonstrated by comparing it with direct Monte Carlo simulation technique and an active learning-based Kriging approach.
JOURNAL OF EARTHQUAKE ENGINEERING
(2023)
Article
Computer Science, Interdisciplinary Applications
Guo-Hui Gao, Dian-Qing Li, Zi-Jun Cao
Summary: This paper proposes a design point identification method based on Monte Carlo simulation (MCS) to address the issue of random simulation not being able to obtain design points and parametric sensitivity. The proposed method approximates the design point by selecting the failure sample with the maximum value of probability density function on the limit state surface (LSS) from the random samples generated in MCS. The accuracy of the method depends on the number of failure samples generated in MCS, particularly those close to the LSS, and can be improved with advanced MCS algorithms.
COMPUTERS AND GEOTECHNICS
(2023)
Article
Geosciences, Multidisciplinary
Haifeng Chen, Hao Zou, M. Santosh, Huawen Cao, Franco Pirajno, Changcheng Huang, Mingcai Hou
Summary: Researchers have identified a supervolcano eruption event in the tuff layers from the Early-Middle Triassic boundary in the Yangtze Block. This eruption may have contributed to the delayed biotic recovery after the end-Permian mass extinction.
GEOSCIENCE FRONTIERS
(2024)
Article
Geosciences, Multidisciplinary
Yanjuan Yin, Baohua Zhang, Xinzhuan Guo
Summary: This study determines the Fe-Mn interdiffusion rates in natural Mn-bearing garnet crystals with 750 ppm H2O using an experimental approach. The results show that the Fe-Mn interdiffusion coefficient slightly decreases with increasing Fe content, and water significantly enhances the Fe-Mn interdiffusion in garnet. These findings suggest that the time required for homogenization of the compositional zoning of a garnet is much shorter than previously thought.
GEOSCIENCE FRONTIERS
(2024)
Article
Geosciences, Multidisciplinary
Yirang Jang, Sung Won Kim, Vinod O. Samuel, Sanghoon Kwon, Seung-Ik Park, M. Santosh, Keewook Yi
Summary: Detrital zircon geochronology and Hf isotope analysis are used to infer provenance characteristics and evaluate the tectonic evolution of sedimentary basins. The results of this study show that the Paleozoic sequences of the Okcheon Belt have a diverse provenance linked to different tectonic environments.
GEOSCIENCE FRONTIERS
(2024)
Article
Geosciences, Multidisciplinary
Stephen F. Foley, Isra S. Ezad
Summary: This study investigates the trace element compositions of melts and minerals from hydrous pyroxenites containing K-richterite through high-pressure experiments. The results show that different minerals play different roles in the enrichment of various trace elements. The study also models the isotopic aging process in hydrous pyroxenite source rocks.
GEOSCIENCE FRONTIERS
(2024)
Article
Geosciences, Multidisciplinary
G. Harshitha, C. Manikyamba, M. Santosh, Cheng-Xue Yang, A. Keshav Krishna, V. V. Sesha Sai, I. Panduranga Reddy
Summary: The early Archean oceans underwent significant redox changes that had a lasting impact on the Earth's biosphere. This study investigates the geochemical characteristics of Archean Mnformations in southern India and reveals the importance of these sedimentary deposits in understanding the ancient redox conditions and sedimentation patterns. The findings suggest that the sediments were deposited in shallow to deeper shelf environments in the Archean proto-ocean, and they provide evidence of regional episodes of ocean oxygenation prior to the Great Oxygenation Event.
GEOSCIENCE FRONTIERS
(2024)