Probabilistic corrosion rate estimation model for longitudinal strength members of bulk carriers

Many bulk carrier losses have been reported of late, and one of the possible causes of such casualties is thought to be the structural failure of aging hulls in rough weather. Clearly, in such cases, vessels that start out being adequate somehow become marginal later in life. Fatigue and corrosion-related potential problems may be the most important factors affecting such age related vessel damage. With respect to fatigue, extensive studies have been done worldwide both experimentally and theoretically, and the results have been applied to some extent. However, in the case of corrosion effects, additional research is still needed to better understand, clarify and address the various strength uncertainties and their effects on structural behaviour. This paper develops a probabilistic corrosion rate estimation model for the longitudinal strength members of bulk carriers. The model is based on available statistical data for corrosion of existing bulk carriers. The corrosion data collected are documented for future use.     

大气中粘性效应对三维地形波及其波动阻力的影响

采用两层大气模式, 通过引入瑞利摩擦系数来定性描述大气中粘性机制, 讨论了粘性效应对三维简单地形波及其波动阻力的影响。结果表明,无论低层大气为稳定层结还是不稳定层结, 大气中粘性的存在将减弱地形波的强度, 减小其产生的波动阻力     

Bivariate Gaussian mixture–based equivalent linearization method for stochastic seismic analysis of nonlinear structures

To address challenges in stochastic seismic analysis of nonlinear structures, this paper further develops a recently proposed Gaussian mixture–based equivalent linearization method (GM‐ELM). The GM‐ELM uses a Gaussian mixture distribution model to approximate the probabilistic distribution of a nonlinear system response. Using properties of the Gaussian mixture model, GM‐ELM can decompose the non‐Gaussian response of a nonlinear system into multiple Gaussian responses of linear single–degree of freedom oscillators. With the set of the equivalent linear systems identified by GM‐ELM, response statistics as crossing rate and first‐passage probability can be computed conveniently using theories of linear random vibration analysis. However, the original version of GM‐ELM may lead to an inaccurate estimate because of the heuristic parameters of the linear system introduced to supplement insufficient information. To overcome this limitation and define unique equivalent linear systems, this paper proposes a further developed version of GM‐ELM, which uses a mixture of bivariate Gaussian densities instead of univariate models. Moreover, to facilitate the use of elastic response spectra for estimating the mean peak responses of a nonlinear structure, a new response spectrum combination rule is proposed for GM‐ELM. Two numerical examples of hysteretic structural systems are presented in this paper to illustrate the application of the bivariate GM‐ELM to nonlinear stochastic seismic analysis. The analysis results obtained by the bivariate GM‐ELM are compared with those obtained by the univariate GM‐ELM, the conventional equivalent linearization method, the tail equivalent linearization method, and Monte Carlo simulation. The supporting source code and data are available for download at https://github.com/yisangri/GitHub‐bGM‐ELM‐code.git     

Measurement of local and volumetric deformation in geotechnical triaxial testing using 3D-digital image correlation and a subpixel edge detection algorithm

Based on the three-dimensional digital image correlation (3D-DIC) technique, the stereovision system has been applied to the improved triaxial apparatus to obtain 3D full-field deformation of the specimen during triaxial testing. Through the calibration process, the 3D-DIC technique can obtain the accurate specimen’s spatial displacement deformation. Meanwhile, a subpixel edge detection algorithm has been combined with 3D-DIC technique to calculate the radial strain and the volume strain of the specimen directly. Furthermore, a series of consolidated drained and undrained triaxial tests were carried out on Hainan (China) sand specimens and measured by the conventional and the image measurement methods. Compared to the results measured by the conventional method, the image measurement technique can obtain the more experimental data, such as the 3D displacement field of the whole specimen, the local strain distribution, and so on. The measurement results also show the conventional method would be disturbed by the end constraints in triaxial tests so that the strength of the soil would be overestimated. Meanwhile, the middle of the specimen would be selected to calculate the stress–strain relationship without the influence of the end constraints in the proposed method. Based on the image measurement results, the proposed method has the potential to be used in geotechnical tests for exploring the soil’s progressive failure behaviors, inhomogeneous deformation and mechanical characteristics.

     

Features in REE and Methane Anomalies Distribution in the East China Sea Water Column: a Comparison with the South China Sea

Water Resources - This paper presents review of dissolved Rare Earth Elements (REE) and methane anomalies distribution in the East China Sea water column. In general, the REE concentrations of the...     

A comparative study of sequential minimal optimization-based support vector machines,vote feature intervals,and logistic regression in landslide susceptibility assessment using GIS

Landslide susceptibility assessment using GIS has been done for part of Uttarakhand region of Himalaya (India) with the objective of comparing the predictive capability of three different machine learning methods, namely sequential minimal optimization-based support vector machines (SMOSVM), vote feature intervals (VFI), and logistic regression (LR) for spatial prediction of landslide occurrence. Out of these three methods, the SMOSVM and VFI are state-of-the-art methods for binary classification problems but have not been applied for landslide prediction, whereas the LR is known as a popular method for landslide susceptibility assessment. In the study, a total of 430 historical landslide polygons and 11 landslide affecting factors such as slope angle, slope aspect, elevation, curvature, lithology, soil, land cover, distance to roads, distance to rivers, distance to lineaments, and rainfall were selected for landslide analysis. For validation and comparison, statistical index-based methods and the receiver operating characteristic curve have been used. Analysis results show that all these models have good performance for landslide spatial prediction but the SMOSVM model has the highest predictive capability, followed by the VFI model, and the LR model, respectively. Thus, SMOSVM is a better model for landslide prediction and can be used for landslide susceptibility mapping of landslide-prone areas.     

Phylogenetic diversity of planktonic bacteria in the Chukchi Borderland region in summer

Planktonic bacteria are abundant in the Chukchi Borderland region. However, little is known about their diversity and the roles of various bacteria in the ocean. Seawater samples were collected from two stations K2S and K4S where sea ice was melting obviously. The analysis of water samples with fluorescence in situ hybridization (FISH) showed that DMSP-degrading bacteria accounted for 13% of the total bacteria at the station K2S. No aerobic anoxygenic phototrophic (AAP) bacteria were detected in both samples. The bacterial communities were characterized by two 16S rRNA gene clone libraries. Sequences fell into four major lineages of the domain Bacteria, including Proteobacteria (Alpha, Beta and Gamma subclasses), Bacteroidetes, Actinobacteria and Firmicutes. No significant difference was found between the two clone libraries. SAR11 and Rhodobacteraceae clades of Alphaproteobacteria and Pseudoalteromonas of Gammapro-teobacteria constituted three dominant fractions in the clone libraries. A total of 191 heterotrophic bacterial strains were isolated and 76% showed extracellular proteolytic activity. Phylogenetic analysis reveals that the isolates fell into Gammaproteobacteria, Bacteroidetes, Actinobacteria and Firmicutes. The most common genus in both the bacterial isolates and protease-producing bacteria was Pseudoalteromonas. UniFrac data showed suggestive differences in bacterial communities between the Chukchi Borderland and the northern Bering Sea.     

Nitrogen budget of the eelgrass, Zostera marina in a bay system on the south coast of Korea

Above- and below-ground productivities and tissue N content were measured monthly to quantify N incorporation to sustain eelgrass growth in Koje Bay on the south coast of Korea from January to December 2002. N acquisition was also estimated through measurements of N uptake kinetics, tissue biomass, and in situ inorganic N concentrations in water column and sediments. Above- and below-ground productivities were highest in summer and lowest in late fall and winter. Leaf tissue N content was highest in December and lowest in July, while rhizome tissue N content was highest in October and lowest in April. Estimated monthly N incorporation by leaf tissues based on the leaf productivity and N content ranged from 0.4 g N m^?2 month^?1 in November to 2.0 g N m^?2 month^?1 in May. N incorporation by below-ground tissues ranged from 0.1 g N m^?2 month^?1 in February to 0.2 g N m^?2 month^?1 in October. Annual whole plant N incorporation was 14.5 g N m^?2 y^?1, and N incorporation by leaf tissues accounted for about 87 % of total N incorporation. Maximum uptake rate (V _max ) and half saturation constant (K _m ) of leaf NH₄ ⁺ uptake were significantly lower than those of root NH₄ ⁺ uptake. Above- and below-ground biomass ranged from 20.8 g DW m^?2 and 8.6 g DW m^?2 in winter to 350.0 g DW m^?2 and 81.3 g DW m^?2 in spring, respectively. NH₄ ⁺ concentrations varied from 0.2 to 4.3 mM in water column and from 93.0 to 551.7 mM in sediment pore water. Based on these measurements, annual N acquisition by root tissues contributed slightly higher than that by leaf tissues to total plant N acquisition. During winter, monthly leaf N acquisition was lower than monthly leaf N incorporation. This implies that Z. marina has internal nitrogen retention system to offset the shortage and excess of nitrogen.     

Estimation of non-CO2 GHGs emissions by analyzing burn severity in the Samcheok fire, South Korea

This study was performed to estimate the emission of non-CO 2 greenhouse gases(GHGs) from biomass burning at a large fire area.The extended methodology adopted the IPCC Guidelines(2003) equation for use on data from the Samcheok forest fire gathered using 30 m resolution Landsat TM satellite imagery,digital forest type maps,and growing stock information per hectare by forest type in 1999.Normalized burn ratio(NBR) technique was employed to analyze the area and severity of the Samcheok forest fire that occurred in 2000.The differences between NBR from pre-and post-fire datasets are examined to determine the extent and degree of change detected from burning.The results of burn severity analysis by dNBR of the Samcheok forest fire area revealed that a total of 16,200 ha of forest were burned.The proportion of the area characterized by a ’Low’ burn severity(dNBR below 152) was 35%,with ’Moderate’(dNBR 153-190) and ’High’(dNBR 191-255) areas were at 33% and 32%,respectively.The combustion efficiency for burn severity was calculated as 0.43 for crown fire where burn severity was ’High’,as 0.40 for ’Moderate’ severity,and 0.15 for ’Low’ severity surface fire.The emission factors for estimating non-CO 2 GHGs were separately applied to CO 130,CH 4 9,NO x 0.7 and N 2 O 0.11.Non-CO 2 GHGs emissions from biomass burning in the Samcheok forest fire area were estimated to be CO 44.100,CH 4 3.053,NO x 0.238 and N 2 O 0.038 Gg.