STRESS CORROSION CRACKING OF AISI 321 STAINLESS STEEL IN ACIDIC SEAWATER

ImooUonONSCCisoneofthemosttwortantcausoffailureofstaiuleSsstalequipmentandfacilitieS.Studiesonunh0refacilitiesshowedthatanaddicchloridesolutionfilmcouldbefo~onthescheeofstalandthatstaiuleSSstalisinaCtivedissolutionstateinaedicchloridesolutionopinetal.,l99O;Gnanamoorthyetal.,l99O).ltisgenerallythoughtxthatSCCcannotoimrwhenthematerialisinaCtiveanodicdissolutionstate,soitsomcewithresultingcasualties(0ldfieldetal.,l99O)arousedattentiont0it.SomeSCCmeCanisrnsproposedpeuang,l988,Newmanctal.,…     

企鹅珍珠贝人工苗生长的初步观察

为了解企鹅珍珠贝生长规律，观察了壳高2.5～5.0mm的出池幼苗，按月测量其生长参数和成活率，以及环境因子。结果表明，企鹅珍珠贝生长最快的月份为7～11月和次年4～6月，壳长，壳高和壳宽月均增加量分别为3.8～13.0mm、4.7～11.2mm、2.3～3.8mm，月成活率97.8%～98.6%。企鹅珍珠贝生长最慢月份是11月至次年3月。     

Neural network prediction of nitrate in groundwater of Harran Plain, Turkey

Monitoring groundwater quality by cost-effective techniques is important as the aquifers are vulnerable to contamination from the uncontrolled discharge of sewage, agricultural and industrial activities. Faulty planning and mismanagement of irrigation schemes are the principle reasons of groundwater quality deterioration. This study presents an artificial neural network (ANN) model predicting concentration of nitrate, the most common pollutant in shallow aquifers, in groundwater of Harran Plain. The samples from 24 observation wells were monthly analysed for 1 year. Nitrate was found in almost all groundwater samples to be significantly above the maximum allowable concentration of 50 mg/L, probably due to the excessive use of artificial fertilizers in intensive agricultural activities. Easily measurable parameters such as temperature, electrical conductivity, groundwater level and pH were used as input parameters in the ANN-based nitrate prediction. The best back-propagation (BP) algorithm and neuron numbers were determined for optimization of the model architecture. The Levenberg–Marquardt algorithm was selected as the best of 12 BP algorithms and optimal neuron number was determined as 25. The model tracked the experimental data very closely (R = 0.93). Hence, it is possible to manage groundwater resources in a more cost-effective and easier way with the proposed model application.     

Spatial Variability of Rock Depth in Bangalore Using Geostatistical, Neural Network and Support Vector Machine Models

Geospatial technology is increasing in demand for many applications in geosciences. Spatial variability of the bed/hard rock is vital for many applications in geotechnical and earthquake engineering problems such as design of deep foundations, site amplification, ground response studies, liquefaction, microzonation etc. In this paper, reduced level of rock at Bangalore, India is arrived from the 652 boreholes data in the area covering 220 km². In the context of prediction of reduced level of rock in the subsurface of Bangalore and to study the spatial variability of the rock depth, Geostatistical model based on Ordinary Kriging technique, Artificial Neural Network (ANN) and Support Vector Machine (SVM) models have been developed. In Ordinary Kriging, the knowledge of the semi-variogram of the reduced level of rock from 652 points in Bangalore is used to predict the reduced level of rock at any point in the subsurface of the Bangalore, where field measurements are not available. A new type of cross-validation analysis developed proves the robustness of the Ordinary Kriging model. ANN model based on multi layer perceptrons (MLPs) that are trained with Levenberg–Marquardt backpropagation algorithm has been adopted to train the model with 90% of the data available. The SVM is a novel type of learning machine based on statistical learning theory, uses regression technique by introducing loss function has been used to predict the reduced level of rock from a large set of data. In this study, a comparative study of three numerical models to predict reduced level of rock has been presented and discussed.     

红海及亚丁湾间之海水交换

分析表观耗氧量、滴定碱度及总二氧化碳量等资料来研判红海及亚丁湾间之海水交换。结果显示,红海深层水的方解石及霰石饱和度均比亚丁湾和阿拉伯海深层水的饱和度高。红海全水柱之方解石和霰石都处於过饱和状态,亚丁湾和阿拉伯海中各深度之方解石亦呈过饱和状态,但霰石的饱和探度则大约在500m左右。分析深层水之生物体无机碳与有机碳的分解比值,可以发现此地区深层水中,大约有25％的总二氧化碳增加量是由无机碳酸钙溶解而来。     

海水中234Th的超低水平液闪谱仪测定

本文提出了利用超低水平液闪谱仪测定海水中234Th的方法.海水经氢氧化铁吸附共沉淀富集后,接着用阴离子交换和TBP/煤油萃取进行Th同位素的分离与纯化.对一系列测定条件进行了详细的研究,提出了测定海水中234Th的适宜程序,即在含有234Th和产额示踪剂230Th的纯化后的5mol/dm3HNO3溶液中加入TBP/煤油进行萃取,然后用0.1mol/dm3HNO3反萃取,后者是先用契伦柯夫计数法测量234Th(通过234mPa),后加入闪烁液Hisafe 3用α/β模式测量α放射体230Th.对于α和β放射体液闪谱仪的计数效率分别为100%和55.7%±2.7%.234Th的化学回收率和总探测效率分别为70%～80%和30%～45%.该法测定海水中的234Th快速、简便和高效.     

Freely floating-body simulation by a 2D fully nonlinear numerical wave tank

Nonlinear interactions between large waves and freely floating bodies are investigated by a 2D fully nonlinear numerical wave tank (NWT). The fully nonlinear 2D NWT is developed based on the potential theory, MEL/material-node time-marching approach, and boundary element method (BEM). A robust and stable 4th-order Runge–Kutta fully updated time-integration scheme is used with regriding (every time step) and smoothing (every five steps). A special φ_n-η type numerical beach on the free surface is developed to minimize wave reflection from end-wall and wave maker. The acceleration-potential formulation and direct mode-decomposition method are used for calculating the time derivative of velocity potential. The indirect mode-decomposition method is also independently developed for cross-checking. The present fully nonlinear simulations for a 2D freely floating barge are compared with the corresponding linear results, Nojiri and Murayama’s (Trans. West-Jpn. Soc. Nav. Archit. 51 (1975)) experimental results, and Tanizawa and Minami’s (Abstract for the 6th Symposium on Nonlinear and Free-surface Flow, 1998) fully nonlinear simulation results. It is shown that the fully nonlinear results converge to the corresponding linear results as incident wave heights decrease. A noticeable discrepancy between linear and fully nonlinear simulations is observed near the resonance area, where the second and third harmonic sway forces are even bigger than the first harmonic component causing highly nonlinear features in sway time series. The surprisingly large second harmonic heave forces in short waves are also successfully reproduced. The fully updated time-marching scheme is found to be much more robust than the frozen-coefficient method in fully nonlinear simulations with floating bodies. To compare the role of free-surface and body-surface nonlinearities, the body-nonlinear-only case with linearized free-surface condition was separately developed and simulated.     

海水叶绿素α浓度遥感测量的实验研究

本文描述了1989年11月在青岛即墨岙山养殖基地所做的海水叶绿素σ浓度遥感测量的基础实验。该实验获得了高浓度叶绿素α含量的海水反射光谱。该反射光谱的特征波段为:波谷在485nm;波峰在450nm 和535nm;“节点”在572nm.根据该实验数据选取了叶绿素α浓度两种双波段估算模式.分析结果表明;两种模式的精度都在50%以上,且双波段反射率的差值法优于双波段反射率比值法.     

沿海城市海水入侵问题研究

近年来，沿海城市的海水入侵问题逐渐成为人们关心的焦点之一。文章通过资料搜集与整理，对沿海城市的海水入侵状况作了全面描述与分析。系统地总结了海水入侵的若干特点及海水入侵的成因分析与规律，较为详细的分析了海水入侵的基本事实、基本矛盾和各发展阶段的发展原因，在此基础上总结了海水入侵的基本理论。为进一步的研究打下良好的基础。     

Distribution of Boron in Some Egyptian Aquatic Environments

Concentrations of boron in seawater (from four regions along the Alexandria coastline, subjected to land disposal), brackish water (Lake Edku) and drains water (e.g. El-Umum Drain) were determined during the period from February to August 2000. Boron was determined spectrophotometrically by a modified curcumin method. For Lake Edku, boron concentration fluctuated between 0.023 and 0.105 mmol/l. There are several factors that affect the concentration of B in the Lake water: (a) effect of the drainage water via El-Khairy and Barsiek Drains, (b) utilization of boron by hydrophytes, and (c) water exchange through the sea-lake connection. It may be concluded that the level of boron in the Lake water cannot be considered a substantial hazard to the Lake organisms. Boron concentration varied from 0.392 to 0.522 mmol/l in seawater samples and from 0.141 to 0.458 mmol/l in the sites where the water from the drains (El-Umum Drain and El-Noubaria Canal) mixed with the seawater. The broader variation of boron (mmol/l)/salinity ratios for seawater samples (0.0106–0.0138) may be due to that the samples were collected from the upper seawater layers, where contributions from land run-off, atmospheric precipitation and differences in the biota affect the concentration. This revised version was published online in July 2006 with corrections to the Cover Date.