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131.
Liu Baohua Wu Jinlong Xin Baisen Peng Chao . First Institute of Oceanography State Oceanic Administration Qingdao China . Ocean University of Qingdao Qingdao China 《海洋学报(英文版)》1999,(2)
INTRODUCTIONTo study the compensation model of sea topography and isostatic states by using toPOgraphicand gravity data, is an imPOrtant mean for further researching deep structures as elastic structure,stress state of lithosphere, and so on. Since Airy and Pratt proPOsed local isostatic model in the1850' s, greater development on the theoretical study has been attained. Veining Meinesz (1941 )introduced regional compensation mechanism by considering it as floating crust in elastic fie… 相似文献
132.
南海大眼金枪鱼和黄鳍金枪鱼生物学特性及其分布 总被引:1,自引:0,他引:1
利用2010年3月—2013年2月南海金枪鱼延绳钓探捕与渔业生产监测取得的生物学数据和生产数据,对南海的大眼金枪鱼(Thunnus obesus)和黄鳍金枪鱼(Thunnus albacres)的生物学特性和渔场分布进行了研究。结果表明:(1)南海大眼金枪鱼叉长范围50—169cm,平均为111.8cm,体重范围2.45—87kg,平均为33.2kg,叉长(FL)体重(W)关系:W=1.74×10–5FL3.01,性腺成熟度Ⅱ期居多,占总尾数的45.27%。绝对怀卵量109.46—456.95万粒,摄食强度以0—2级为主。大眼金枪鱼延绳钓渔场春夏季分布于南沙西北部和南沙中西部海域;秋冬季分布于西、中沙和南沙西北部海域。渔获水深90%集中在150—400m。(2)南海黄鳍金枪鱼叉长范围41—180cm,平均为107.9cm,体重范围1.2—77.5kg,平均为27.9kg,叉长体重关系:W=2.19×10–5FL2.94,性腺成熟度以Ⅱ—Ⅳ期居多,占总尾数的89.01%,绝对怀卵量15—154万粒,摄食强度以1—2级为主。黄鳍金枪鱼延绳钓渔场春夏季分布于南沙西北部和南沙中西部海域;秋冬季分布于西、中沙、南沙西北部、南沙中西部海域。渔获水深93.75%集中在50—350m。西沙西部和南沙西北部海域是灯光围网和灯光罩网捕捞金枪鱼的重要渔场。研究认为:(1)在南海可发展小型冷海水延绳钓船,在每年10月末—次年5月初在西沙东北海域开展浅水延绳钓作业;(2)在南海的岛礁附近设置PAYAO群,开展金枪鱼灯光罩网或围网捕捞。(3)目前取得的资料仍然有限,未来仍需进一步调查,以掌握南海金枪鱼种群动态,为渔业开发和养护提供建议。 相似文献
133.
四川盆地上三叠统须家河组油气勘探开始于20世纪40年代,其中须二段、须四段是主要探目的层段,也是盆地周边地区寻找新气源最有利层位之一。依据地震地层学方法和理论,结合钻井与测井资料,将大川中地区须家河组划分成7个地震层序边界,分别为SB1—SB7,与之对应6个最大湖泛面,分别为MFS1—MFS6,并对层序界面的地震反射特征进行了总结。利用地震反射内部结构、外部形态和反射波终止类型,在大川中地区须家河组须二段与四段内共识别出平行—亚平行、前积、丘状、透镜状及发散状地震反射特征等5种地震相,并对18条二维地震测线进行了剖面地震相的综合解释,编制了须二段与四段的地震相平面分布图。通过地震相与沉积相的转换,分别划分出冲积扇、扇三角洲、辫状河三角洲以及湖泊等沉积体系,编制了大川中地区须家河组二段与四段沉积相平面图,对大川中地区须家河组构造格局的演化规律进行了分析。 相似文献
134.
135.
In coastal sea areas with the bimodal Ochi-Hubble wave spectrum, such as parts of the China Sea and Indian Ocean,wave energy is the superposition of wind wave and swell. Traditional heaving buoy wave energy converters developed with narrowband wave spectrums suffer from big energy loss in these areas, leading to lower power absorption efficiency and higher generating costs. In contrast, multi-freedom buoy has different resonant frequencies and maximal power capture wave frequencies in different ... 相似文献
136.
It is well known that pitting corrosion occurring on surface of hull structural plate will surely result in a significant degradation of the ultimate strength of the hull structural plate. This report aims at development of an assessing formula for ultimate strength of hull plate with pitting corrosion damage under the biaxial in-plane compression loading. The ultimate strength assessment model that is in terms of the corroded volume loss was deduced in theory, and which was then completed through numerical experiment by employing nonlinear finite element analyses for series of corroded plate models. Meanwhile, pitting corrosion in actual ship hull was analyzed and simulated, which ensured that all the assumptions for the finite element model parameters were in accord with the actual hull plate with pitting corrosion damage. Furthermore, the effects of plate slenderness, the linear factors at the plate edges and the ratio between the transverse and the longitudinal in-plane stresses on the ultimate strength reduction related to the corroded volume loss were discussed. The ultimate strength assessment formula being in terms of corroded volume loss developed in this research is expected to be applicable to assess the ultimate strength of the hull structural plate with pitting corrosion damage. 相似文献
137.
海岸侵蚀是沿海各国面临的共同问题,海滩养护是当前砂质海岸保护的最佳手段,在全球范围内得到广泛应用。本文回顾了海滩养护技术的发展历程,总结了世界范围的海滩养护实践,分析各国海滩养护理念上存在的差异。以研究文献为基础,总结归纳了平面和横向剖面的补砂方式、辅助工程技术和海滩模型预测等方面的海滩养护技术研究进展,并在此基础上提出了海滩养护的未来发展趋势:①针对复杂海岸的海滩养护应用拓展;②基于沉积物管理的海滩养护修复;③从地貌系统到生态系统全面考虑的海滩养护技术;④全球砂源赤字条件下的海滩保护和修复思路。 相似文献
138.
Juan Chen Fei-Hua Wu Qiang Xiao Zhang-Hua Yang Sheng-Kai Huang Jian Wang Yu-Guang Wu Xue-Jun Dong Zhen-Ming Pei Hai-Lei Zheng 《Estuarine, Coastal and Shelf Science》2010
The diurnal variation of nitric oxide (NO) emission fluxes from a Kandelia obovata and Avicennia marina mangrove wetland were studied in the Zhangjiang River Estuary Mangrove National Nature Reserve using a dynamic chamber-based technique and a chemiluminescent analyzer. Results from field experiments show that NO emission from K. obovata and A. marina sampling sites reached maximal values of 1.07 ng N m−2 s−1 and 1.23 ng N m−2 s−1, respectively after the night tide. Meanwhile NO emission maintained at a steady lower level in daytime for both wetland sites. In laboratory experiments, NO emission from the mangrove wetland soil samples treated with simulated tides in the darkness exhibited higher values than those in the light, therefore it seems that tides and darkness could increase NO emission from mangrove wetlands, while intensive light, high temperature, and dryness in the daytime decreased NO emission. Compared with K. obovata soil samples, the diurnal average NO emission rate of the A. marina site was significantly higher, which was closely related to relatively higher diurnal average CO2 emission rate, soil available nitrogen content and soil net nitrification rate of the A. marina site. Moreover, soil samples of the A. marina site were more responsive to simulated tides and the addition of nitrogen than those of the K. obovata site. 相似文献
139.
Storm surges pose significant danger and havoc to the coastal residents' safety, property, and lives, particularly at offshore locations with shallow water levels. Predictions of storm surges with hours of warning time are important for evacuation measures in low-lying regions and coastal management plans. In addition to experienced predictions and numerical models, artificial intelligence (AI) techniques are also being used widely for short-term storm surge prediction owing to their merits in good level of prediction accuracy and rapid computations. Convolutional neural network (CNN) and long short-term memory (LSTM) are two of the most important models among AI techniques. However, they have been scarcely utilised for surge level (SL) forecasting, and combinations of the two models are even rarer. This study applied CNN and LSTM both individually and in combination towards multi-step ahead short-term storm surge level prediction using observed SL and wind information. The architectures of the CNN, LSTM, and two sequential techniques of combining the models (LSTM–CNN and CNN–LSTM) were constructed via a trial-and-error approach and knowledge obtained from previous studies. As a case study, 11 a of hourly observed SL and wind data of the Xiuying Station, Hainan Province, China, were organised as inputs for training to verify the feasibility and superiority of the proposed models. The results show that CNN and LSTM had evident advantages over support vector regression (SVR) and multilayer perceptron (MLP), and the combined models outperformed the individual models (CNN and LSTM), mostly by 4%–6%. However, on comparing the model computed predictions during two severe typhoons that resulted in extreme storm surges, the accuracy was found to improve by over 10% at all forecasting steps. 相似文献
140.