Introduction to the China-Vietnam Cooperation Project: A Comparative Study of the Holocene Sedimentary Evolution of the Yangtze and Red River Deltas     

Ping Yin  Van Phach Phung  Dinh Lan Tran  Huy Cuong Do  Van Vuong Bui  Xiaoyong Duan 《中国海洋大学学报(英文版)》2018,17(6):1269-1271

Both China and Vietnam confront the challenges of natural geohazards and environmental changes in their deltas and coastal zones due to rapid urbanization, economic development, and the impacts of global climate change. China and Vietnam initiated a comparative study of the Holocene sedimentary evolution of the Yangtze River Delta(YRD) and Red River Delta(RRD) for the period 2015–2018 in order to improve the understanding of the two delta evolution histories in the Holocene. Previous investigative data of the two rivers, onshore delta plains, and offshore subaqueous deltas have been explored and reinterpreted. New data gleaned from boreholes, piston cores, shallow seismic and hydrodynamic sources have been collected from the offshore YRD and the East China Sea inner shelf, and surface sediments and short cores have been collected from the RRD near-shore areas. Six focal areas of the joint project have been defined for comparative studies of the two deltas, including morphological development, sequential stratigraphy, coastline shifting, sedimentary characteristics, sedimentary dynamics, and correlation with anthropogenic global climate change. The results of these study areas are presented herein. The joint project also includes cooperative capacity building; exchanges of young scientists have been organized during the project period, and hands-on training in laboratory geochemical analysis, numerical modeling, and seismic data processing and interpretation have been provided by China and its Vietnamese geoscientist partners. Joint field excursions were organized to the upstream of the Yangtze and Red Rivers in Yunan Province, China, all the way downstream along the Vietnamese portion of the Red River. These joint studies have, over the past three years, improved understanding of the evolutionary history of these two major rivers and their mechanisms of source to sink. Joint project results of these two major deltas are not limited to the geosciences; the cooperative mechanical and operational experiences have been helpful for future cooperation in the field of marine geoscience between China and Vietnam, as well for cooperative activities with other ASEAN member countries.  相似文献   

A generic approach to modelling flexible confined boundary conditions in SPH and its application     

Shaohan Zhao  Ha H. Bui  Vincent Lemiale  Giang D. Nguyen  Felix Darve 《国际地质力学数值与分析法杂志》2019,43(5):1005-1031

In this paper, a new approach to applying confining stress to flexible boundaries in the smoothed particle hydrodynamics (SPH) method is developed to facilitate its applications in geomechanics. Unlike the conventional SPH methods that impose confining boundary conditions by creating extra boundary particles, the proposed approach makes use of kernel truncation properties of SPH approximations that occur naturally at free-surface boundaries. Therefore, it does not require extra boundary particles and, as a consequence, can be utilised to apply confining stresses onto any boundary with arbitrary geometry without the need for tracking the curvature change during the computation. This enables more complicated problems that involve moving confining boundaries, such as confining triaxial tests, to be simulated in SPH without difficulties. To further enhance SPH applications in elasto-plastic computations of geomaterials, a robust numerical procedure to implement Mohr-Coulomb plasticity model in SPH is presented for the first time to avoid difficulties associated with corner singularities in Mohr-Coulomb model. The proposed approach was first validated against two-dimensional finite element (FE) solutions for confining biaxial compression tests to demonstrate its predictive capability at small deformation range when FE solutions are still valid. It is then further extended to three-dimensional conditions and utilised to simulate triaxial compression experiments. Simulation results predicted by SPH show good agreement with experiments, FE solutions, and other numerical results available in the literature. This suggests that the proposed approach of imposing confining stress boundaries is promising and can handle complex problems that involve moving confining boundary conditions.  相似文献   

A coupled poroplastic damage model accounting for cracking effects on both hydraulic and mechanical properties of unsaturated media          下载免费PDF全文

Tuan Anh Bui  Henry Wong  Frederic Deleruyelle  Annan Zhou  Xiaoqin Lei 《国际地质力学数值与分析法杂志》2016,40(5):625-650

Damage induced by microcracking affects not only the mechanical behaviour of geomaterials but also their hydraulic properties. Evaluating these impacts is important for many engineering applications, such as the safety assessment of radioactive waste disposal facilities. This paper presents a new constitutive model accounting simultaneously for the impact of damage on hydraulic and mechanical properties of unsaturated poroplastic geomaterials. The hydro‐mechanical coupling is formulated by means of the thermodynamic framework for partially saturated media, extended by taking into account isotropic damage and plasticity. State and complementary laws are governed by the so‐called plastic effective stress and equivalent pore pressure. Assuming a bimodal pore size distribution for cracked porous media, the hydraulic part (water retention curve and hydraulic conductivity) is modelled using phenomenological functions of damage variable. The participation of damage on both mechanical and hydraulic part enables this model to describe bilateral couplings between them. This coupled model is then validated against a number of experimental data obtained from Callovo‐Oxfordian argillite, which is the possible host rock for a radioactive waste disposal in France. Parametric studies are also carried out to check the consistency and to better demonstrate the bilateral couplings in the model. Copyright © 2015 John Wiley & Sons, Ltd.  相似文献   

Landslide susceptibility analysis in the Hoa Binh province of Vietnam using statistical index and logistic regression   总被引：12，自引：2，他引：10  

Dieu Tien Bui  Owe Lofman  Inge Revhaug  Oystein Dick 《Natural Hazards》2011,59(3):1413-1444

The purpose of this study is to evaluate and compare the results of applying the statistical index and the logistic regression methods for estimating landslide susceptibility in the Hoa Binh province of Vietnam. In order to do this, first, a landslide inventory map was constructed mainly based on investigated landslide locations from three projects conducted over the last 10 years. In addition, some recent landslide locations were identified from SPOT satellite images, fieldwork, and literature. Secondly, ten influencing factors for landslide occurrence were utilized. The slope gradient map, the slope curvature map, and the slope aspect map were derived from a digital elevation model (DEM) with resolution 20 × 20 m. The DEM was generated from topographic maps at a scale of 1:25,000. The lithology map and the distance to faults map were extracted from Geological and Mineral Resources maps. The soil type and the land use maps were extracted from National Pedology maps and National Land Use Status maps, respectively. Distance to rivers and distance to roads were computed based on river and road networks from topographic maps. In addition, a rainfall map was included in the models. Actual landslide locations were used to verify and to compare the results of landslide susceptibility maps. The accuracy of the results was evaluated by ROC analysis. The area under the curve (AUC) for the statistical index model was 0.946 and for the logistic regression model, 0.950, indicating an almost equal predicting capacity.  相似文献   

An Improved Method Based on Shallow Ice Approximation to Calculate Ice Thickness along Flow-Line and Volume of Mountain Glaciers     

李慧林  李忠勤  张明军  李汶峰 《中国地质大学学报(英文版)》2011,(4)

To evaluate the water storage and project the future evolution of glaciers, the ice-thickness of glaciers is an essential input. However, direct measurements of ice thickness are labo-rious, not feasible everywhere, and necessarily restricted to a small number of glaciers. In this article, we develop a simple method to estimate the ice-thickness along flow-line of mountain glaciers. Different from the traditional method based on shallow ice approximation (SIA), which gives a relationship be-tween ice thickn...  相似文献   

Determination of importance for comprehensive topographic factors on landslide hazard mapping using artificial neural network   总被引：1，自引：0，他引：1  

Mutasem Sh. Alkhasawneh  Umi Kalthum Ngah  Lea Tien Tay  Nor Ashidi Mat Isa 《Environmental Earth Sciences》2014,72(3):787-799

A landslide is one of the natural disasters that occur in Malaysia. In addition to the geological factor and the rain as triggering factor, topographic factors such as elevation, slope angle, slope aspect, and curvature are considered as the main causes of landslides. The study in this paper was conducted in three stages. The first stage involved the extraction of extra topographic factors. Previous landslide studies had identified only four of the topographic factors. However, eight new additional factors have also been identified in this study. They are general curvature, longitudinal curvature, tangential curvature, cross-section curvature, surface area, diagonal line length, surface roughness, and rugosity. At this stage, 13 factors were extracted from the digital elevation model. The second stage involved specifying the importance of each factor. The multilayer perceptron network and backpropagation algorithm were used to specify the weight of each factor. Results were verified using the receiver operating characteristics based on the area under the curve method in the third stage. The results indicated 76.07 % accuracy in predicting of landslides, with slope angle as the most important factor while the tangential curvature has the least importance.  相似文献   

Determining Soil Thermal Conductivity Through Numerical Simulation of a Heating Test on a Heat Exchanger Pile     

K. L. Yu  R. M. Singh  A. Bouazza  H. H. Bui 《Geotechnical and Geological Engineering》2015,33(2):239-252

  相似文献   

Biomass estimation of Sonneratia caseolaris (l.) Engler at a coastal area of Hai Phong city (Vietnam) using ALOS-2 PALSAR imagery and GIS-based multi-layer perceptron neural networks     

Tien Dat Pham  Kunihiko Yoshino  Dieu Tien Bui 《地理信息系统科学与遥感》2017,54(3):329-353

This study tested the use of machine learning techniques for the estimation of above-ground biomass (AGB) of Sonneratia caseolaris in a coastal area of Hai Phong city, Vietnam. We employed a GIS database and multi-layer perceptron neural networks (MLPNN) to build and verify an AGB model, drawing upon data from a survey of 1508 mangrove trees in 18 sampling plots and ALOS-2 PALSAR imagery. We assessed the model’s performance using root-mean-square error, mean absolute error, coefficient of determination (R²), and leave-one-out cross-validation. We also compared the model’s usability with four machine learning techniques: support vector regression, radial basis function neural networks, Gaussian process, and random forest. The MLPNN model performed well and outperformed the machine learning techniques. The MLPNN model-estimated AGB ranged between 2.78 and 298.95 Mg ha^?1 (average = 55.8 Mg ha^?1); below-ground biomass ranged between 4.06 and 436.47 Mg ha^?1 (average = 81.47 Mg ha^?1), and total carbon stock ranged between 3.22 and 345.65 Mg C ha^?1 (average = 64.52 Mg C ha^?1). We conclude that ALOS-2 PALSAR data can be accurately used with MLPNN models for estimating mangrove forest biomass in tropical areas.  相似文献   

Landslide Hazard Assessment Using Random SubSpace Fuzzy Rules Based Classifier Ensemble and Probability Analysis of Rainfall Data: A Case Study at Mu Cang Chai District,Yen Bai Province (Viet Nam)     

Binh Thai Pham  Dieu Tien Bui  Ha Viet Pham  Hung Quoc Le  Indra Prakash  M. B. Dholakia 《Journal of the Indian Society of Remote Sensing》2017,45(4):673-683

Landslide hazard assessment at the Mu Cang Chai district; Yen Bai province (Viet Nam) has been done using Random SubSpace fuzzy rules based Classifier Ensemble (RSSCE) method and probability analysis of rainfall data. RSSCE which is a novel classifier ensemble method has been applied to predict spatially landslide occurrences in the area. Prediction of temporally landslide occurrences in the present study has been done using rainfall data for the period 2008–2013. A total of fifteen landslide influencing factors namely slope, aspect, curvature, plan curvature, profile curvature, elevation, land use, lithology, rainfall, distance to faults, fault density, distance to roads, road density, distance to rivers, and river density have been utilized. The result of the analysis shows that RSSCE and probability analysis of rainfall data are promising methods for landslide hazard assessment. Finally, landslide hazard map has been generated by integrating spatial prediction and temporal probability analysis of landslides for the land use planning and landslide hazard management.  相似文献   

Landslide susceptibility assesssment in the Uttarakhand area (India) using GIS: a comparison study of prediction capability of naïve bayes,multilayer perceptron neural networks,and functional trees methods     

Binh?Thai?PhamEmail author  Dieu?Tien Bui  Hamid?Reza?Pourghasemi  Prakash?Indra  M.?B.?Dholakia 《Theoretical and Applied Climatology》2017,128(1-2):255-273

The objective of this study is to make a comparison of the prediction performance of three techniques, Functional Trees (FT), Multilayer Perceptron Neural Networks (MLP Neural Nets), and Naïve Bayes (NB) for landslide susceptibility assessment at the Uttarakhand Area (India). Firstly, a landslide inventory map with 430 landslide locations in the study area was constructed from various sources. Landslide locations were then randomly split into two parts (i) 70 % landslide locations being used for training models (ii) 30 % landslide locations being employed for validation process. Secondly, a total of eleven landslide conditioning factors including slope angle, slope aspect, elevation, curvature, lithology, soil, land cover, distance to roads, distance to lineaments, distance to rivers, and rainfall were used in the analysis to elucidate the spatial relationship between these factors and landslide occurrences. Feature selection of Linear Support Vector Machine (LSVM) algorithm was employed to assess the prediction capability of these conditioning factors on landslide models. Subsequently, the NB, MLP Neural Nets, and FT models were constructed using training dataset. Finally, success rate and predictive rate curves were employed to validate and compare the predictive capability of three used models. Overall, all the three models performed very well for landslide susceptibility assessment. Out of these models, the MLP Neural Nets and the FT models had almost the same predictive capability whereas the MLP Neural Nets (AUC = 0.850) was slightly better than the FT model (AUC = 0.849). The NB model (AUC = 0.838) had the lowest predictive capability compared to other models. Landslide susceptibility maps were final developed using these three models. These maps would be helpful to planners and engineers for the development activities and land-use planning.  相似文献