A new numerical approach to the hyperstatic reaction method for segmental tunnel linings

This paper proposes a numerical approach to the hyperstatic reaction method (HRM) for the analysis of segmental tunnel linings. The influence of segmental joints has been considered directly using a fixity ratio that is determined on the basis of the rotational stiffness. The parameters necessary for the calculation are presented. A specific implementation has been developed using a FEM framework. This code is able to consider the three‐dimensional (3D) effect of segment joints in successive rings on the tunnel lining behaviour. The present HRM allows one to take an arbitrary distribution of segment joints along the tunnel boundary into consideration. In addition, the rotational stiffness of segment joints has been simulated using nonlinear behaviour, as it is closer to the true behaviour of a joint than linear or bilinear behaviour. The numerical results of three hypotheses on ring interaction, which allow the 3D effect of a segmental tunnel lining to be taken into account, have been compared with data obtained from the shield‐driven tunnel of the Bologna–Florence high‐speed railway line project. The numerical results presented in the paper show that the proposed HRM can be used to effectively estimate the behaviour of a segmental tunnel lining. Copyright © 2014 John Wiley & Sons, Ltd.     

Flood-prone area mapping using machine learning techniques: a case study of Quang Binh province,Vietnam

Natural Hazards - Vietnam’s central coastal region is the most vulnerable and always at flood risk, severely affecting people’s livelihoods and socio-economic development. In...     

Predicting rock size distribution in mine blasting using various novel soft computing models based on meta-heuristics and machine learning algorithms

Blasting is well-known as an effective method for fragmenting or moving rock in open-pit mines. To evaluate the quality of blasting, the size of rock distribution is used as a critical criterion in blasting operations. A high percentage of oversized rocks generated by blasting operations can lead to economic and environmental damage. Therefore, this study proposed four novel intelligent models to predict the size of rock distribution in mine blasting in order to optimize blasting parameters, as well as the efficiency of blasting operation in open mines. Accordingly, a nature-inspired algorithm (i.e., firefly algorithm – FFA) and different machine learning algorithms (i.e., gradient boosting machine (GBM), support vector machine (SVM), Gaussian process (GP), and artificial neural network (ANN)) were combined for this aim, abbreviated as FFA-GBM, FFA-SVM, FFA-GP, and FFA-ANN, respectively. Subsequently, predicted results from the abovementioned models were compared with each other using three statistical indicators (e.g., mean absolute error, root-mean-squared error, and correlation coefficient) and color intensity method. For developing and simulating the size of rock in blasting operations, 136 blasting events with their images were collected and analyzed by the Split-Desktop software. In which, 111 events were randomly selected for the development and optimization of the models. Subsequently, the remaining 25 blasting events were applied to confirm the accuracy of the proposed models. Herein, blast design parameters were regarded as input variables to predict the size of rock in blasting operations. Finally, the obtained results revealed that the FFA is a robust optimization algorithm for estimating rock fragmentation in bench blasting. Among the models developed in this study, FFA-GBM provided the highest accuracy in predicting the size of fragmented rocks. The other techniques (i.e., FFA-SVM, FFA-GP, and FFA-ANN) yielded lower computational stability and efficiency. Hence, the FFA-GBM model can be used as a powerful and precise soft computing tool that can be applied to practical engineering cases aiming to improve the quality of blasting and rock fragmentation.     

A study of coral reef resilience and implications of adaptive management and rehabilitation in Khanh Hoa Province, Vietnam

The Province of Khanh Hoa, Vietnam, is located in the western South China Sea and boasts a shoreline of 385 km and many islands. Previous studies have indicated the extreme diversity and abundance of coral reefs in its waters as compared with other coastal provinces of Vietnam. A study on the resilience of coral reefs against increased surface water temperature and anthropogenic impact is conducted at 19 reef sites in 2015. At each site, a series of parameters (e.g., coral covers, genus diversity, and coral recruitment, substratum heterogeneity, depth, water exchange level, and sediment deposit and water temperature) are measured quantitatively or semi-quantitatively. The measured data are rated based on the relationship between the parameter values and coral susceptibility; the consideration that reef health reflects the biological capability to adapt to environmental changes and the recruitment potential if bleached; and positive or negative influences of physical factors in the mitigation of thermal stress and protecting corals from bleaching. A cumulative analysis enables researchers to divide the studied reefs into four categories based on varying levels of reef health to support resilience, recovery, and vulnerability in the case of increased water temperature. Relevant management interventions for each category and other supporting activities are suggested to enhance management effectiveness and to plan the rehabilitation of coral reefs for biodiversity conservation and touristic development, taking into account the involvement of related stakeholders.     

Flash flood susceptibility mapping using a novel deep learning model based on deep belief network,back propagation and genetic algorithm

Flash floods are responsible for loss of life and considerable property damage in many countries.Flood susceptibility maps contribute to flood risk reduction in areas that are prone to this hazard if appropriately used by landuse planners and emergency managers.The main objective of this study is to prepare an accurate flood susceptibility map for the Haraz watershed in Iran using a novel modeling approach(DBPGA) based on Deep Belief Network(DBN) with Back Propagation(BP) algorithm optimized by the Genetic Algorithm(GA).For this task, a database comprising ten conditioning factors and 194 flood locations was created using the One-R Attribute Evaluation(ORAE) technique.Various well-known machine learning and optimization algorithms were used as benchmarks to compare the prediction accuracy of the proposed model.Statistical metrics include sensitivity,specificity accuracy, root mean square error(RMSE), and area under the receiver operatic characteristic curve(AUC) were used to assess the validity of the proposed model.The result shows that the proposed model has the highest goodness-of-fit(AUC = 0.989) and prediction accuracy(AUC = 0.985), and based on the validation dataset it outperforms benchmark models including LR(0.885), LMT(0.934), BLR(0.936), ADT(0.976), NBT(0.974), REPTree(0.811), ANFIS-BAT(0.944), ANFIS-CA(0.921), ANFIS-IWO(0.939), ANFIS-ICA(0.947), and ANFIS-FA(0.917).We conclude that the DBPGA model is an excellent alternative tool for predicting flash flood susceptibility for other regions prone to flash floods.     

Prediction of Rock Size Distribution in Mine Bench Blasting Using a Novel Ant Colony Optimization-Based Boosted Regression Tree Technique

Natural Resources Research - In this paper, we used artificial intelligence (AI) techniques to investigate the relation between the rock size distribution (RSD) and blasting parameters for rock...     

Small-scale marine fisheries policy in Vietnam

Vietnam's marine fisheries are considered to be small scale and are concentrated in coastal near-shore waters. This has resulted in heavy pressure on near-shore fisheries resources. Near-shore fisheries are considered by fishers and the government to be over-exploited, causing hardship for many coastal communities. This paper reviews and analyzes changes in policy towards small-scale fisheries in Vietnam over the last two decades. The primary issues facing the small-scale fisheries in Vietnam are to restructure the near-shore fisheries and to address over-capacity. Recommended actions include improved fisheries statistics, resources for provincial fisheries staff, and a coordinated and integrated approach involving a mixed strategy of resource management; resource restoration; economic and community development; and new governance arrangements.     

An improved SPH method for saturated soils and its application to investigate the mechanisms of embankment failure: Case of hydrostatic pore‐water pressure

The method of smoothed particle hydrodynamics (SPH) has recently been applied to computational geomechanics and has been shown to be a powerful alternative to the standard numerical method, that is, the finite element method, for handling large deformation and post‐failure of geomaterials. However, very few studies apply the SPH method to model saturated or submerged soil problems. Our recent studies of this matter revealed that significant errors may be made if the gradient of the pore‐water pressure is handled using the standard SPH formulation. To overcome this problem and to enhance the SPH applications to computational geomechanics, this article proposes a general SPH formulation, which can be applied straightforwardly to dry and saturated soils. For simplicity, the current work assumes hydrostatic pore‐water pressure. It is shown that the proposed formulation can remove the numerical error mentioned earlier. Moreover, this formulation automatically satisfies the dynamic boundary conditions at a submerged ground surface, thereby saving computational cost. Discussions on the applications of the standard and new SPH formulations are also given through some numerical tests. Furthermore, techniques to obtain the correct SPH solution are also proposed and discussed throughout. As an application of the proposed method, the effect of the dilatancy angle on the failure mechanism of a two‐sided embankment subjected to a high groundwater table is presented and compared with that of other solutions. Finally, the proposed formulation can be considered a basic formulation for further developments of SPH for saturated soils. Copyright © 2011 John Wiley & Sons, Ltd.     

A geochronological and petrological study of anatectic paragneiss and associated granite dykes from the Day Nui Con Voi metamorphic core complex,North Vietnam: constraints on the timing of metamorphism within the Red River shear zone

The Red River shear zone (RRSZ) is a major left‐lateral strike‐slip shear zone, containing a ductilely deformed metamorphic core bounded by brittle strike‐slip and normal faults, which stretches for >1000 km from Tibet through Yunnan and North Vietnam to the South China Sea. The RRSZ exposes four high‐grade metamorphic core complexes along its length. Various lithologies from the southernmost core complex, the Day Nui Con Voi (DNCV), North Vietnam, provide new constraints on the tectonic and metamorphic evolution of this region prior to and following the initial India–Asia collision. Analysis of a weakly deformed anatectic paragneiss using P–T pseudosections constructed in the MnO–Na₂O–CaO–K₂O–FeO–MgO–Al₂O₃–SiO₂–H₂O–TiO₂–O (MnNCKFMASHTO) system provides prograde, peak and retrograde metamorphic conditions, and in situ U–Th–Pb geochronology of metamorphic monazite yields texturally controlled age constraints. Tertiary metamorphism and deformation, overprinting earlier Triassic metamorphism associated with the Indosinian orogeny and possible Cretaceous metamorphism, are characterized by peak metamorphic conditions of ~805 °C and ~8.5 kbar between c. 38 and 34 Ma. Exhumation occurred along a steep retrograde P–T path with final melt crystallizing at the solidus at ≥~5.5 kbar at ~790 °C. Further exhumation at ~640–700 °C and ~4–5 kbar at c. 31 Ma occurred at subsolidus conditions. U–Pb geochronological analysis of monazite from a strongly deformed pre‐kinematic granite dyke from the flank of the DNCV provides further evidence for exhumation at this time. Magmatic grains suggest initial emplacement at 66.0 ± 1.0 Ma prior to the India–Asia collision, whereas grains with metamorphic characteristics indicate later growth at 30.6 ± 0.4 Ma. Monazite grains from a cross‐cutting post‐kinematic dyke within the core of the DNCV antiform provide a minimum age constraint of 25.2 ± 1.4 Ma for the termination of fabric development. A separate and significant episode of monazite growth at c. 83–69 Ma is suggested to be the result of fluid‐assisted recrystallization following the emplacement of magmatic units.