Shiwei Zhao^1,*, Hao Chen², Jidong Zhao¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.2, pp. 1-1, 2023, DOI:10.32604/icces.2023.09965

Abstract With global warming, thaw-induced landslides occur more frequently in permafrost, which not only threaten the safety of infrastructures as general geohazards but also worsen global warming due to carbon release. This work presents a novel computational framework to model thaw-induced landslides from a multiscale perspective. The proposed approach can capture the thermal-mechanical (TM) response of frozen soils at the particulate scale by using discrete element method (DEM). The micromechanics-based TM model is superior to capturing the sudden crash of soil skeletons caused by thaw-induced cementation loss between soil grains. The DEM-simulated TM response is then homogenized and directly fed into… More >

Can Huang^1,*, Xiaoliang Wang¹, Qingquan Liu¹, Huaning Wang²

The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.1, pp. 1-1, 2023, DOI:10.32604/icces.2023.09824

Abstract Soil‒water coupling is an important process in landslide-generated impulse waves (LGIW) problems, accompanied by large deformation of soil, strong interface coupling and three-dimensional effect. A meshless particle method, smooth particle hydrodynamics (SPH) has great advantages in dealing with complex interface and multiphase coupling problems. This study presents an improved soil‒water coupled model to simulate LGIW problems based on an open source code DualSPHysics (v4.0). Aiming to solve the low efficiency problem in modeling real large-scale LGIW problems, graphics processing unit (GPU) acceleration technology is implemented into this code. An experimental example, subaerial landslidegenerated water waves, is simulated to validate this… More >

G. Bhargavi^*, J. Arunnehru

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1257-1272, 2023, DOI:10.32604/iasc.2023.034335

Abstract Landslides are a natural hazard that is unpredictable, but we can prevent them. The Landslide Susceptibility Index reduces the uncertainty of living with landslides significantly. Planning and managing landslide-prone areas is critical. Using the most optimistic deep neural network techniques, the proposed work classifies and analyses the severity of the landslide. The selected experimental study area is Kerala’s Idukki district. A total of 3363 points were considered for this experiment using historic landslide points, field surveys, and literature searches. The primary triggering factors slope degree, slope aspect, elevation (altitude), normalized difference vegetation index (NDVI), and distance from road, lithology, and… More >

Shaojie Feng^*, Leipeng Liu, Chen Gao, Hang Hu

FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.5, pp. 1189-1201, 2023, DOI:10.32604/fdmp.2023.023637

Abstract The present study considers the damage mechanisms and the rainfall infiltration process responsible for landslide phenomena which originate from accumulation slopes. Accordingly, a physical test model is developed for different slopes and different rainfall conditions. Moreover, a three-dimensional laser scanner and a camera are used to monitor the slope erosion and the landslide dynamic evolution. Using this approach, the time variation curves of volumetric water content, pore water pressure, soil pressure, slope deformation, and damage are determined. The results show that under similar conditions, similar trends of the pore water pressure are achieved for different slopes and rainfall intensities. More > Graphic Abstract

Binghui Cui^1,*, Liaojun Zhang²

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.1, pp. 357-376, 2023, DOI:10.32604/cmes.2022.022309

Abstract Flow-type landslide is one type of landslide that generally exhibits characteristics of high flow velocities, long jump distances, and poor predictability. Simulation of its propagation process can provide solutions for risk assessment and mitigation design. The smoothed particle hydrodynamics (SPH) method has been successfully applied to the simulation of two-dimensional (2D) and three-dimensional (3D) flow-like landslides. However, the influence of boundary resistance on the whole process of landslide failure is rarely discussed. In this study, a boundary condition considering friction is proposed and integrated into the SPH method, and its accuracy is verified. Moreover, the Navier-Stokes equation combined with the… More > Graphic Abstract

Saman Riaz¹, Ali Arshad², Shahab S. Band^3,*, Amir Mosavi⁴

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4303-4321, 2022, DOI:10.32604/cmc.2022.024819

Abstract The way towards generating a website front end involves a designer settling on an idea for what kind of layout they want the website to have, then proceeding to plan and implement each aspect one by one until they have converted what they initially laid out into its Html front end form, this process can take a considerable time, especially considering the first draft of the design is traditionally never the final one. This process can take up a large amount of resource real estate, and as we have laid out in this paper, by using a Model consisting of… More >

N. B. Ghazali¹, F. C. Seman^1,*, K. Isa¹, K. N. Ramli¹, Z. Z. Abidin¹, S. M. Mustam¹, M. A. Haek², A. N. Z. Abidin², A. Asrokin²

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5427-5440, 2022, DOI:10.32604/cmc.2022.023211

Abstract Applying the fault diagnosis techniques to twisted pair copper cable is beneficial to improve the stability and reliability of internet access in Digital Subscriber Line (DSL) Access Network System. The network performance depends on the occurrence of cable fault along the copper cable. Currently, most of the telecommunication providers monitor the network performance degradation hence troubleshoot the present of the fault by using commercial test gear on-site, which may be resolved using data analytics and machine learning algorithm. This paper presents a fault diagnosis method for twisted pair cable fault detection based on knowledge-based and data-driven machine learning methods. The… More >

Meng Song^1,*, Yuncai Liu², Zhen Wang¹

FDMP-Fluid Dynamics & Materials Processing, Vol.18, No.2, pp. 313-327, 2022, DOI:10.32604/fdmp.2022.017737

Abstract The purpose of the study is to implement a new model based on the Navier-Stokes equations for the characterization of landslide sediments interacting with a moving fluid. The model is implemented by combining Hypermesh, the LS-DYNA software and MATLAB. The results show that the main factors affecting the permeability of landslide sediments are the genetic mechanism, the structure and composition of materials, material lithology, and stress. The characteristics and mechanism of permeability changes are determined by adjusting the water levels of fluids. It is found that the permeability of landslide sediments increases at the front and decreases in the middle… More >

Sanghyo Lee¹, Yonghan Ahn², Ha Young Kim^{3, *}

CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 1-17, 2020, DOI:10.32604/cmc.2020.011104

Abstract In this study, we examined the efficacy of a deep convolutional neural network (DCNN) in recognizing concrete surface images and predicting the compressive strength of concrete. A digital single-lens reflex (DSLR) camera and microscope were simultaneously used to obtain concrete surface images used as the input data for the DCNN. Thereafter, training, validation, and testing of the DCNNs were performed based on the DSLR camera and microscope image data. Results of the analysis indicated that the DCNN employing DSLR image data achieved a relatively higher accuracy. The accuracy of the DSLR-derived image data was attributed to the relatively wider range… More >

Jin Yeon Cho¹, Yun Hyuk Choi², You Me Song³, Chang Sik Kim⁴

The International Conference on Computational & Experimental Engineering and Sciences, Vol.4, No.3, pp. 151-158, 2007, DOI:10.3970/icces.2007.004.151

Abstract In this work, PDSL(pre-detection sort last) and SDSL(strip-wise decomposition sort last) parallel visualization algorithms are proposed for efficient visualization of massive data generated from large-scale parallel finite element analysis through investigating the characteristics of distributed parallel finite element analysis procedure. The proposed parallel visualization algorithms are based on the sort last approach, and designed to be highly compatible with the characteristics of domain-wise computation in parallel finite element analysis. To investigate the performances of proposed algorithms, in-house software is developed by applying the binary tree network communication pattern along with the proposed sorting algorithms, and benchmarking test for parallel visualization… More >