The uplift capacity of single-plate helical pile in shallow dense sand including the influence of installation

The helical pile has been used to resist the tension for a long time. However, the prediction of the uplift capacity of helical piles including the influence of installation is still a challenge in design. Based on the change in stress according to Mohr-Coulomb failure criterion, a simple theoretical method has been developed, which can calculate the uplift capacity of shallow pre-embedded circular plate anchors and the uplift capacity of helical piles installed by torque and compression. In order to analyse the influence of installation process of a single-plate helical pile on its uplift capacity and verify the theoretical model, a series of model tests have been conducted in dense saturated sand. The single-plate helical piles with different out diameters of helixes have been installed with different installation speeds, and then, the single-plate helical piles have been moved up monotonically. The test results show that the installation speed and the size of the out diameter of the helix have significant influence on the uplift capacity of the helical piles, and the results of the theoretical method have a good fit with the test results. Using this simple theoretical method, the designer can easily predict the uplift capacities of helical piles, which includes the influence of installation.     

A signal decomposition method based on repeated extraction of maximum energy component for offshore structures

Contrary to most signal decomposition methods that usually decompose an original signal into a series of components simultaneously, a novel approach based on repeated extraction of Maximum Energy Component (MEC) is proposed. The approach starts from determination of the MEC referring to the estimated Power Spectral Density (PSD) function, and then represents the MEC by employing an exponential function to fit the original signal. By defining a stopping criterion based on two adjacent estimated PSDs, each MEC can be accurately extracted with an improved performance throughout the entire signal decomposition. To verify the proposed method, a single degree-of-freedom system subject to harmonic loads has been examined. Numerical results show that the analytical response can not only be decomposed into four MECs corresponding to the excitation and the system, respectively, but also provide an accurate estimation of natural frequency and damping ratio of the system. Meanwhile, by observing results from the Ensemble Empirical Mode Decomposition (EEMD), Variational Mode Decomposition (VMD) and Prony based on state-space model (Prony-SS), an improved decomposition accuracy has been achieved from the proposed approach. Furthermore, experimental data from the Norwegian Deepwater Programme and two sets of field-test data from one fixed offshore platform and an offshore wind turbine have been used to demonstrate the correctness of the developed signal decomposition method. It is noted that divergence in results by Prony-SS can be observed when a very large model order is used, while the proposed method provides the better decomposition and reconstruction of signals.     

浅谈船舶如何顺利通过外部机构的检查

介绍了外部机构检查的特点,提出了船舶顺利通过外部机构检查应采取的措施和做法。     

航运市场中的牛鞭效应研究

揭示了航运市场中存在的牛鞭效应。结合航运产品的特点及H.L.Lee对牛鞭效应的研究,分析了对航运产品需求的预测、船舶建造周期、批量运输及运输的不平衡性、运输价格的波动、定量供应与短缺博弈是产生航运市场牛鞭效应的主要原因,并由此提出了相应的对策框架。     

数字滤波检漏仪检测实用技术

通过对几种检测管道漏泄方法的优缺点比较,得出目前铁路供水管网检漏设备最为实用的设备是数字滤波检漏仪。根据多年的检漏实践,归纳出检测管道泄漏点综合操作程序。     

交流功率电源在直流电动系仪表检定中的应用

针对直流电动系仪表功耗较大,对检测电源负载能力要求高的情况,提出将负载能力较强的交流功率电源加装整流装置,应用于直流电动系仪表检定工作,满足实际检定工作要求。     

供需链环境下提高企业订单执行效率分析

在企业的生产、管理过程中,如何提高订单执行力的研究仍是一个空白。此文针对当前制造业生产环境存在的主要问题,即生产面临复杂的环境、市场变化的不确定性导致激烈的市场竞争、订单执行过程的协调性较差,进行分析与探讨,提出提高企业订单执行力的方法和可采取的4个方面的措施,从而建立起一套在供需链管理模式下的高效订单执行力体系,使企业快速拓展市场,实现增值和稳步发展。     

Extreme hawser tension assessment for FPSO vessel during offloading operation in Bohai bay

The Floating Production Storage and Offloading Unit (FPSO) is an offshore vessel that produces and stores crude oil prior to tanker transport.Robust prediction of extreme hawser tensions during Floating Production Storage and Offloading (FPSO) operation is an important safety concern. Excessive hawser tension may occur during offloading operations, posing an operational risk. In this paper, AQWA has been used to analyze vessel response due to hydrodynamic wave loads, acting on a specific FPSO vessel under actual sea conditions. Experimental validation of numerical results has been discussed as well.This paper advocates methodology for estimating extreme response statistics, based on simulations (or measurements). The modified ACER (averaged conditional exceedance rate) method is presented in brief detail. Proposed methodology provides an accurate extreme value prediction, utilizing all available data efficiently. In this study the estimated return level values, obtained by ACER method, are compared to the corresponding return level values obtained by Gumbel method. Based on the overall performance of the proposed method, it is concluded that the improved ACER method can provide more robust and accurate prediction of the extreme hawser tension.Data declustering issue has been addressed. Paper highlights ability of ACER method to account for a set of varying sea state probabilities, as required in engineering long term statistical analysis.Described approach may be well used at the vessel design stage, while defining optimal vessel parameters that would minimize potential FPSO hawser tension.     

Determination of limiting cavity depths for offshore spudcan foundations in a spatially varying seabed

The importance of accurate prediction of limiting cavity depths during offshore spudcan foundations installation has been variously highlighted in the literature. Nonetheless, most of the previous research is deterministic in nature and confined to homogenous soils. Since offshore clayey soils can be highly spatially variable, there is a practical need to take proper account of the spatial variability in the prediction of limiting cavity depths. In a bid to remedy this situation, large deformation finite element calculations combined with three-dimensional random fields were repeatedly conducted in this study within a Monte-Carlo framework. The continuous penetration of a spudcan initiated from surface was explicitly modeled until a full-localized flow-around mechanism was observed. Spatial variability was found to clearly affect the soil back-flow and thereby the limiting cavity depth, the latter of which takes a range of values that can be approximately modeled as a log-normal distribution. Characteristic limiting cavity depths at various probability levels were ascertained. An algebraic expression was proposed to explicitly predict the characteristic limiting cavity depths in random soils from the fractile. Particular attention was paid to the lower and upper 5% characteristic values, which are likely to be useful for reliability-based design.     

Strain prediction for critical positions of FPSO under different loading of stored oil using GAIFOA-BP neural network

FPSO (floating, production, storage and offloading) units are widely used in the offshore oil and gas industry. Generally, FPSOs have excellent oil storage capacity owing to their huge oil cargo holds. The volume and distribution of stored oil in the cargo holds influence the strain level of hull girder, especially at critical positions of FPSO. However, strain prediction using structural analysis tools is computationally expensive and time consuming. In this study, a prediction tool based on back-propagation (BP) neural network called GAIFOA-BP is proposed to predict the strain values of concerned positions of an FPSO model under different oil storage conditions. The GAIFOA-BP combines BP model and GAIFOA which is a combination of genetic algorithm (GA) and an improved fruit fly optimization algorithm (IFOA). Results from three benchmark tests show that the GAIFOA-BP model has a remarkable performance. Subsequently, a total of 81 sets of training data and 25 sets of testing data are obtained from experiment using fiber Bragg grating (FBG) sensors installed on the surface of an FPSO model. The numerical results show that the GAIFOA-BP is capable of predicting the strain values with higher accuracy as compared with other BP models. Finally, the reserved GAIFOA-BP model is utilized to predict the strain values under the inputs of a 10-day time series of volume and distribution of stored oil. The predicted strain results are further used to calculate the fatigue consumption of measurement points.