Parameter identification for lined tunnels in a viscoplastic medium

This paper is dedicated to the identification of constitutive parameters of elasto‐viscoplastic constitutive law from measurements performed on deep underground cavities (typically tunnels). This inverse problem is solved by the minimization of a cost functional of least‐squares type. The exact gradient is computed by the direct differentiation method and the descent is done using the Levenberg–Marquardt algorithm. The method is presented for lined or unlined structures and is applied for an elastoviscoplastic constitutive law of the Perzyna class. Several identification problems are presented in one and two dimensions for different tunnel geometries. The used measurements have been obtained by a preliminary numerical simulation and perturbed with a white noise. The identified responses match the measurements. We also discuss the usage of the sensitivity analysis of the system, provided by the direct differentiation method, for the optimization of in situ monitoring. The sensitivity distribution in space and time assess the location of the measurements points as well as the time of observation needed for reliable identification. Copyright © 2002 John Wiley & Sons, Ltd.     

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.     

Meiobenthos in estuary part of ha long bay (gulf of tonkin, south china sea, vietnam)

The distribution of the taxonomical composition and the density of meiobenthos depending on some factors of environment has been studied in bottom sediments of the northern estuary part of Ha Long Bay (Cua Luc estuary). The basic factor of influence on meiobenthic community structure was the granulometric composition of sediment. The greatest taxonomic diversity is noted in the silted sands, lowest — in the silty sediments. The density of meiobenthic community was higher in the silty sediments. Slightly expressed correlation between the density of nematodes and the percentage of silty particles in the sediments is detected (Spearman rank correlation coefficient was 0.49±0.21, p=0.035). The nematodes were dominant at all stations. In total, representatives of 66 species of nematodes belonging to 17 families and 52 genera were identified.     

Integrated Geological–Geophysical and Oceanographic Research in the South China Sea: Cruise 88 of the R/V “Akademik M.A. Lavrentyev”

Oceanology - Abstract—The paper gives brief results of comprehensive studies in the South China Sea obtained from a joint Russian–Vietnamese expedition in November 2019 (cruise 88 of...     

A new portable in situ flume for measuring critical shear stress on river beds

A new portable in situ flume(PISF)for measuring critical bed shear stress(CBSS)was developed in this study.The PISF consists of an open bottom sediment erosion chamber and an electrically-driven pump.Unlike most existing in situ flumes with similar designs,the new PISF does not rely on monitoring the flow conditions or particle density in the sediment erosion chamber;instead,it is a pre-calibrated flume.The calibration was performed by first determining CBSS of various selected sediment samples of known particle size and density(using the law of the wall),based on flow velocity-depth profiles measured in a 6 m straight open-channel flume using a Particle Image Velocimetry(PIV)system.These same particles of known CBSS were then used in the new in-situ flume under controlled lab conditions to obtain a series of calibration curves of CBSS vs.pump electrical power.A wide variety of particle types and sizes(simulated sediments)were used in this two-step calibration procedure to widen CBSS measurement range and simulate cohesive force effects.The size of the PISF is much smaller and more practical than other similar devices as lamellar flow conditions are not required and it can be applied to a wide range of sediment types including cohesive sediments.     

Statistical data fusion of multi-sensor AOD over the Continental United States

This article illustrates two techniques for merging daily aerosol optical depth (AOD) measurements from satellite and ground-based data sources to achieve optimal data quality and spatial coverage. The first technique is a traditional Universal Kriging (UK) approach employed to predict AOD from multi-sensor aerosol products that are aggregated on a reference grid with AERONET as ground truth. The second technique is spatial statistical data fusion (SSDF); a method designed for massive satellite data interpolation. Traditional kriging has computational complexity O(N³), making it impractical for large datasets. Our version of UK accommodates massive data inputs by performing kriging locally, while SSDF accommodates massive data inputs by modelling their covariance structure with a low-rank linear model. In this study, we use aerosol data products from two satellite instruments: the moderate resolution imaging spectrometer and the geostationary operational environmental satellite, covering the Continental United States.     

Slow quasigeostrophic unstable modes of a lens vortex in a continuously stratified flow

This work addresses the linear dynamics underlying the formation of density interfaces at the periphery of energetic vortices, well outside the vortex core, both in the radial and axial directions. We compute numerically the unstable modes of an anticyclonic Gaussian vortex lens in a continuously stratified rotating fluid. The most unstable mode is a slow mode, associated with a critical layer instability located at the vortex periphery. Although the most unstable disturbance has a characteristic vertical scale which is comparable to the vortex height, interestingly, the critical levels of the successively fastest growing modes are closely spaced at intervals along the axial direction that are much smaller than the vortex height.     

Ensemble rainfall forecasting with numerical weather prediction and radar‐based nowcasting models

The overall objective of this study is to improve the forecasting accuracy of the precipitation in the Singapore region by means of both rainfall forecasting and nowcasting. Numerical Weather Predication (NWP) and radar‐based rainfall nowcasting are two important sources for quantitative precipitation forecast. In this paper, an attempt to combine rainfall prediction from a high‐resolution mesoscale weather model and a radar‐based rainfall model was performed. Two rainfall forecasting methods were selected and examined: (i) the weather research and forecasting model (WRF); and (ii) a translation model (TM). The WRF model, at a high spatial resolution, was run over the domain of interest using the Global Forecast System data as initializing fields. Some heavy rainfall events were selected from data record and used to test the forecast capability of WRF and TM. Results obtained from TM and WRF were then combined together to form an ensemble rainfall forecasting model, by assigning weights of 0.7 and 0.3 weights to TM and WRF, respectively. This paper presented results from WRF and TM, and the resulting ensemble rainfall forecasting; comparisons with station data were conducted as well. It was shown that results from WRF are very useful as advisory of anticipated heavy rainfall events, whereas those from TM, which used information of rain cells already appearing on the radar screen, were more accurate for rainfall nowcasting as expected. The ensemble rainfall forecasting compares reasonably well with the station observation data. Copyright © 2012 John Wiley & Sons, Ltd.     

The Potential of Eleocharis acicularis for Phytoremediation: Case Study at an Abandoned Mine Site

Phytoremediation, a plant‐based and cost‐effective technology for the cleanup of contaminated soil and water, is receiving increasing attention. In this study, the aquatic macrophyte Eleocharis acicularis was examined for its ability to take up multiple heavy metals and its potential application for phytoremediation at an abandoned mining area in Hokkaido, Japan. Elemental concentrations were measured in samples of E. acicularis, water, and soil collected from areas of mine tailing and drainage. The results reveal that Pb, Fe, Cr, Cu, Ni, and Mn accumulation in the plants increased over the course of the experiment, exceeding their initial concentrations by factors of 930, 430, 60, 25, 10, and 6, respectively. The highest concentrations of Fe, Pb, Zn, Mn, Cr, Cu, and Ni within the plants were 59500, 1120, 964, 388, 265, 235, and 47.4 mg/kg dry wt., respectively, for plants growing in mine drainage after 11 months of the experiment. These results indicate that E. acicularis is a hyperaccumulator of Pb. We also found high Si concentrations in E. acicularis (2.08%). It is likely that heavy metals exist in opal‐A within cells of the plant. The bioconcentration factors (BCF: ratio of metal concentration in the plant shoots to that in the soil) obtained for Cr, Cu, Zn, Ni, Mn, and Pb were 3.27, 1.65, 1.29, 1.26, 1.11, and 0.82, respectively. The existence of heavy metals as sulphides is thought to have restricted the metal‐uptake efficiency of E. acicularis at the mine site. The results of this study indicate that E. acicularis shows great potential in the phytoremediation of mine tailing and drainage rich in heavy metals.     

Floodplain hydrology of the Mekong Delta,Vietnam

The Mekong Delta is one of the largest and most intensively used estuaries in the world. Each year it witnesses widespread flooding which is both the basis of the livelihood for more than 17 million people but also the major hazard. Therefore, a thorough understanding of the hydrologic and hydraulic features is urgently required for various planning purposes. While the general causes and characteristics of the annual floods are understood, the inundation dynamics in the floodplains in Vietnam which are highly controlled by dikes and other control structures have not been investigated in depth. Especially, quantitative analyses are lacking, mainly due to scarce data about the inundation processes in the floodplains. Therefore, a comprehensive monitoring scheme for channel and floodplain inundation was established in a study area in the Plain of Reeds in the northeastern part of the Vietnamese Delta. This in situ data collection was complemented by a series of high‐resolution inundation maps derived from the TerraSAR‐X satellite for the flood seasons 2008 and 2009. Hence, the inundation dynamics in the channels and floodplains, and the interaction between channels and floodplains, could be quantified for the first time. The study identifies the strong human interference which is governed by flood protection levels, cropping patterns and communal water management. In addition, we examine the tidal influence on the inundation in various parts of the Delta, since it is expected that climate change‐induced sea level rise will increase the tidal contribution to floodplain inundation. Copyright © 2011 John Wiley & Sons, Ltd.