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...     

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.     

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.     

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.     

Seismic stability analysis of piled embankments: A multiphase approach

The seismic stability analysis of an embankment lying over a soft foundation soil reinforced by a group of vertical piles is performed within the framework of the upper bound kinematic approach of yield design. The analysis is based on a previously developed ‘multiphase’ model of the reinforced ground, which explicitly accounts for the shear and bending resistances of the piles. Making use of appropriate failure mechanisms involving shear zones across which the reinforcements are continuously deforming, along with ‘plastic hinge’ surfaces, upper bound estimates to the critical seismic coefficient of the structure are derived. The results, which are confirmed by the simulations obtained from a finite element elastoplastic code, give clear evidence of the key role played by the bending strength capacities of the piles in ensuring the stability of the pile reinforced embankment. Copyright © 2009 John Wiley & Sons, Ltd.     

Monthly suspended sediment load prediction using artificial intelligence: testing of a new random subspace method

ABSTRACT

The predictive capability of a new artificial intelligence method, random subspace (RS), for the prediction of suspended sediment load in rivers was compared with commonly used methods: random forest (RF) and two support vector machine (SVM) models using a radial basis function kernel (SVM-RBF) and a normalized polynomial kernel (SVM-NPK). Using river discharge, rainfall and river stage data from the Haraz River, Iran, the results revealed: (a) the RS model provided a superior predictive accuracy (NSE = 0.83) to SVM-RBF (NSE = 0.80), SVM-NPK (NSE = 0.78) and RF (NSE = 0.68), corresponding to very good, good, satisfactory and unsatisfactory accuracies in load prediction; (b) the RBF kernel outperformed the NPK kernel; (c) the predictive capability was most sensitive to gamma and epsilon in SVM models, maximum depth of a tree and the number of features in RF models, classifier type, number of trees and subspace size in RS models; and (d) suspended sediment loads were most closely correlated with river discharge (PCC = 0.76). Overall, the results show that RS models have great potential in data poor watersheds, such as that studied here, to produce strong predictions of suspended load based on monthly records of river discharge, rainfall depth and river stage alone.     

Improving Indigenous Technologies for Sustainable Land Use in Northern Mountainous Areas of Vietnam

More than 30 ethnic groups are now living in northern mountainous regions, Vietnam, mainly relying on shifting cultivation with the fallow period being shortened from time to time. Naturally, soil fertility reduces from cycle to cycle, entailing the reduction of productivity. Large areas of moderately sloping lands suitable for upland agriculture have become bare after many cultivation-fallow cycles. The soils there have been severely degraded with more toxicity, low porosity, low water retention capacity and poor floral diversity. Normally, these lands cannot be used for food crop cultivation. So farmers in uplands have to rely on slash-and-burn practices for their livelihood. As there is no more forest with good soil in medium slopes, farmers go to cut forests in watershed, high slope lands and old forests up to the mountains‘ top. There are ecologically and environmentally very sensitive areas, so their destruction will inevitably cause hazardous consequences in the whole basin. Meanwhile,cultivation in these areas has low economic efficiency and sustainability because the crop yield may decrease very fast due to severe erosion as the higher the slope, the more serious erosion. Consequently living standards of highland farmers remain low and unstable. Sustainable farming on these lands in the perspective of a seriously deteriorated ecology and environmental is not an easy task. There have been many projects trying to help mountainous farmers get out of their vicious circle. However, due to different reasons, the results gained are low, and in some cases,things ceased to move after the projects phased out. During past few years, based on the farmer experiences, the Vietnam Agricultural Science Institute has cooperated with local and international partners to implement different projects in order to solve the problems by developing simple, easy and cheap cultivation technologies, which can be accepted and applied by local poor farmers for sustainable agricultural production. The first results of our activities offered good opportunities for sustain food production, improve soil health, recharge of aquifers,and enhanced household income for better rural lively hoods in the upland eco-regions of northern Vietnam.