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.     

对建设铁路集装箱物流公共信息平台的探讨

从铁路集装箱物流运输与电子商务应用二者结合的角度出发,阐述铁路集装箱物流公共信息平台建设的意义,分析了目前国内物流公共信息平台的运营情况,提出将铁路集装箱物流中各种环节信息资源纳入统一平台;把海铁联运信息服务、物流SaaS服务、订舱中心服务等作为信息服务的创新产品;在铁路集装箱物流公共平台建设上分步推进等具体策略。     

Definition of wind blowers for vehicles testing at chassis-dyno facilities using a CFD approach

The need to increase measurement accuracy of fuel consumption and pollutant emissions in vehicles is forcing the market to develop chassis-dyno test cells that reproduce on-road conditions realistically.Air-cooling is key to vehicle performance. It is therefore critical that the design of a test cell guarantees realistic cooling of all vehicle components, as important errors in fuel consumption and emissions measurements may otherwise arise. In a test-room, a blower placed in front of the vehicle supplies the cooling air. While there are some guidelines in the literature for the selection of fans required for emissions measurements for standard driving cycles, the information for designing the air supply system for specific tests in other areas is scarce.New Real Driving Emissions (RDE) legislation will force manufacturers to perform on-road measurements of pollutants. This represents a significant challenge due to the variability of conditions coming from non-controlled parameters. In order to optimize vehicles, different tests are performed in cells equipped with a chassis-dyno where the on-road flow field around the vehicle is reproduced as closely as possible.This work provides some guidelines for the definition of the airflow supply system of chassis-dyno facilities for vehicle optimization tests, based on a CFD analysis of the flow characteristics around the vehicle. By comparison with the solution obtained for a vehicle in real road driving conditions, the exit section of the blower and the distance between the blower exit and the car that best reproduce realistic on-road flow conditions in a test room are determined.     

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.     

The influence of fully nonlinear wave forces on aero-hydro-elastic calculations of monopile wind turbines

The response of an offshore wind turbine tower and its monopile foundation has been investigated when exposed to linear and fully nonlinear irregular waves on four different water depths. The investigation focuses on the consequences of including full nonlinearity in the wave kinematics. The linear and nonlinear irregular wave realizations are calculated using the fully nonlinear potential flow wave model OceanWave3D [1]. The linear and nonlinear wave realizations are compared using both a static analysis on a fixed monopile and dynamic calculations with the aeroelastic code Flex5 [2]. The conclusion from this analysis is that linear wave theory is generally sufficient for estimating the fatigue loading, but wave nonlinearity is important in determining the ultimate design loads.     

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.     

Time domain analysis procedures for fatigue assessment of a semi-submersible wind turbine

Long term time domain analysis of the nominal stress for fatigue assessment of the tower and platform members of a three-column semi-submersible was performed by fully coupled time domain analyses in Simo-Riflex-AeroDyn. By combining the nominal stress ranges with stress concentration factors, hot spot stresses for fatigue damage calculation can be obtained. The aim of the study was to investigate the necessary simulation duration, number of random realisations and bin sizes for the discretisation of the joint wind and wave distribution. A total of 2316 3-h time domain simulations, were performed.In mild sea states with wind speeds between 7 and 9 m/s, the tower and pontoon experienced high fatigue damage due to resonance in the first bending frequency of the tower from the tower wake blade passing frequency (3P).Important fatigue effects seemed to be captured by 1 h simulations, and the sensitivity to number of random realisations was low when running simulations of more than 1 h. Fatigue damage for the tower base converged faster with simulation duration and number of random realisations than it did for the platform members.Bin sizes of 2 m/s for wind, 1 s for wave periods and 1 m for wave heights seemed to give acceptable estimates of total fatigue damage. It is, however, important that wind speeds that give coinciding 3P and tower resonance are included and that wave periods that give the largest pitch motion are included in the analysis.     

Detection of nonlinearity effects in structural integrity monitoring methods for offshore jacket-type structures based on principal component analysis

The detection of changes in the dynamic behavior of structures is an important issue in structural safety assessment. The development of detection methods assumes greater significance in the case of offshore platforms because the inherent problems are compounded by the harsh environment. Here, we describe an instrumented physical model for the structural health monitoring of an offshore jacket-type structure and the results of tests in several different damage scenarios. In a comparative investigation of two different methods, we discuss the difficulties of implementing damage detection techniques for complex structures, such as offshore platforms. The combined algorithm of a fuzzy logic system and a model updating method are briefly discussed, and a method based on stochastic autoregressive moving average with exogenous input is adopted for the structure. The consideration of uncertainties and the effects of nonlinearity were major objectives. So, the methods were also investigated based on the test scenarios consisting of the physical model with a geometric nonlinearity. The principal component analysis method was utilized for the detection of nonlinearity in the recorded data. The results show that the developed methods are suitable for damage classification, but the quality of the acquired signals must be considered an important factor influencing successful classification. The development of these methods may be extremely useful, as such technologies could be applied for offshore platforms in service, enabling damage detection with fewer false alarms.