大洋调查中海山地磁测量的静日变化校正方法

针对大洋调查中海山地磁测量时难以设立静日变化观测站的问题,提出了一种基于多项式拟合最小二乘算法的日变校正方法,即假设静日变化磁场可以用一个关于时间的高阶多项式来拟合,利用主测线和联络测线交点误差的最小二乘估计求得多项式的系数,从而得到静日变化曲线。从调查测得的磁场中减掉静日变化磁场即可得消除静日变化影响后的海山地磁异常。理论模型和实际资料处理都表明,这种方法不仅可以较好地消除静日变化的影响,而且用计算机实现也简单。为了提高静日变化校正结果,讨论了为提高静日变化校正效果,在大洋调查中测量海山地磁时应注意的几个问题。     

基于潮位预测的潮汐校正方法在高分辨率单道地震调查中的应用

单道地震探测技术在海洋勘探各领域应用广泛,潮汐变化对高分辨率单道地震资料的质量有很大影响,尤其是对采集时间跨度较大的资料,在测线交点处存在严重的剖面不闭合现象。利用潮汐预测方法对高分辨率单道地震进行了潮汐校正,经过校正后的资料品质明显得到提升。通过对比不同测线交点处的剖面情况,剖面不闭合现象得到改善,同相轴的对应关系更好。实际应用结果表明,基于潮位预测的潮汐校正方法在高分辨率单道地震调查中的应用有效可靠。     

海洋声传播二维PE算法对海底边界条件的改进处理

运用海洋声传播二维 PE算法对不规则海底边界条件的处理 ,作者提出 1种改进方法 ,即利用抛物方程和界面边界条件 ,对界面附近的抛物方程的差分形式进行修正 ,以考虑复杂海底边界的影响。通过实际的数值计算表明 ,运用该方法计算声场 ,在提高计算精度方面起到有益的作用。     

Soil Plug Effect Prediction and Pile Driveability Analysis for Large-Diameter Steel Piles in Ocean Engineering

Long steel piles with large diameters have been more widely used in the field of ocean engineering.Owing to the pile with a large diameter,soil plug development during pile driving has great influences on pile driveability and beating capacity.The response of soil plug developed inside the open-ended pipe pile during the dynamic condition of pile-driving is different from the response under the static condition of loading during service.This paper addresses the former aspect.A numerical procedure for soil plng effect prediction and pile driveability analysis is proposed and described.By taking into consideration of the pile dimension effect on side and tip resistance,this approach introduces a dimensional coefficient to the conventional static equilibrium equations for the plug differential unit and proposes an improved static equity method for the plug effect prediction.At the same time,this approach introduces a simplified model by use of one-dimensional stress wave equation to simulate the interaction between soft ping and pile inner wall.The proposed approach has been applied in practical engineering analyses.Results show that the calculated plug effect and pile driveability based on the proposed approach agree well with the observed data.