Assessment of offshore platforms under extreme waves by probabilistic incremental wave analysis

In this study, a novel probabilistic framework named Probabilistic Incremental Wave Analysis (PIWA) is established in order to assess the performance of jacket offshore platforms under extreme waves. The PIWA can take into account the uncertainties in three main elements consisting of sea state parameters, structural response and collapse capacity. The main advantage of the PIWA approach is reflected in decoupling of the wave hazard and structural analyses via an intermediate variable known as the wave height intensity measure. Despite the fact that most of the uncertainties associated with structural response are concentrated in wave hazard, this will enable the PIWA to estimate the probability of failure accurately. Moreover, both static and dynamic wave analyses can be utilized in the PIWA procedure. In this approach, multiple incremental wave analyses are employed to estimate the distribution of structural demand for a wide range of wave height intensities. Subsequently, the mean annual frequency of exceeding a structural limit state is calculated for which this research addresses two different methodologies including demand-based and wave height-based approaches. Furthermore, a new probabilistic-based Reserve Strength Ratio (RSR) is proposed and the probability of exceeding various levels of RSR is provided. To reduce the large number of simulations and hence improving the computational effort in the PIWA procedure, a combination of Latin Hypercube Sampling and Simulated Annealing optimization technique is utilized as an efficient sampling scheme. The PIWA procedure is employed in probabilistic assessment of an existing jacket offshore platform located in the Persian Gulf as well.     

考虑极值风速方向性的围护结构设计风荷载概率估计方法研究

对于围护结构的设计风荷载（一定重现期的极值风压）,目前工程上普遍采用最不利值方法进行估算,这类方法不符合概率统计意义。只有统筹考虑极值风速和极值风压系数的随机性、方向性及相关性才能给出较为准确的设计风荷载。为此,提出一种全面考虑极值风速和极值风压系数随机性和方向性的围护结构设计风荷载概率估计方法。首先,提出了极值风压计算所需的三个要素,即各风向的极值风速分布、Cook-Mayne极值风压系数和风向相关性;然后,通过极值风压的概率分布理论分析,给出一个以上述三要素为输入的计算过程简便实用的围护结构风荷载估算公式;最后,以上海地区一栋高层建筑为例,通过与工程上常用最不利值方法相比,验证了本文方法的精确性和实用性。     

Sensitivity analysis of jacket-type offshore platforms under extreme waves

Jacket-type offshore platforms play an important role in oil and gas industries in shallow and intermediate water depths such as Persian Gulf region. Such important structures need accurate considerations in analysis, design and assessment procedures. In this paper, nonlinear response of jacket-type platforms against extreme waves is examined utilizing sensitivity analyses. Results of this paper can reduce the number of random variables and consequently the computational effort in reliability analysis of jacket platforms, noticeably. Effects of foundation modeling have been neglected in majority of researches on the response of jacket platforms against wave loads. As nonlinear response of the pile foundation is one of the most important sources of potential nonlinearity in the response of offshore platforms, in this study, a powerful model which is able to consider Pile–Soil–Structure Interaction (PSSI) is employed. Therefore, PSSI parameters as well as other parameters such as uncertainties in the prediction of the wave force on jacket structure and uncertainties in structural model are utilized in sensitivity analyses. In this research, pushover methods as well as an advanced approach named “Incremental Wave Analysis (IWA)” are employed. Consequently, collapse prevention limit state of jacket platforms is investigated through different outcomes of pushover and IWA methods including Reserve Strength Ratio, ultimate capacity, collapse displacement and Collapse Wave Height indicators. In order to consider the effects of correlation between random variables, a robust method of sensitivity analysis named correlation coefficient approach is also employed.     

Some recent results on probabilistic models of extreme wind speeds

This paper deals with the determination of the relationship between probability of occurrence and wind speed at a given site, on the basis of maximum annual wind speed series.Previous contributions in the area are reviewed. The arguments in favour of each of the extreme-value distributions in use, as well as methods of parameter and confidence limit estimation are discussed.The difficulties inherent in the approach are pointed out and the effects of several factors, such as type of storm, wind averaging time and ground surface roughness are discussed in detail. Finally, a two-parameter model for mixed populations of winds due to extratropical and thunderstorms is suggested.     

Dynamic response of offshore platforms to extreme waves including fluid-structure interaction

Basic considerations for dynamic response analyses of offshore platforms under extreme wave loadings are discussed and the main difficulties of the problem are pointed out. These difficulties arise from the random nature of the loading, the nonlinearity of the drag dominated wave forces and the dependence of such forces on the response of the structure. A time domain solution is recommended, using kinematics of a random sea state for the wave force model along with a relative velocity formulation to account for fluid-structure interaction. The proposed solution is based on approximating structural velocities in Morison's equation with their values at the previous time step. This simplification linearizes the equations of motion and permits analyses of detailed structural models by modal techniques. A limited comparison with results from a more accurate solution appears to justify this approximation. As an example, a structure with 1428 degrees of freedom is subjected to a random wave segment and its responses with and without relative velocities are compared. It is shown that relative velocity effects can be well approximated with an appropriate increase in modal damping and therefore analyses neglecting relative motion are justified, provided that the correct increase of viscous damping is specified. The method of solution proposed here can be utilized to establish this increase in the early stages of design.     

A probabilistic occupant response model for fire emergencies

The present paper describes a probabilistic occupant response model for fire emergencies, which is integrated into a fire risk analysis model called CUrisk. Based on the PIA process, i.e., Perception, Interpretation and Action, the occupant response model predicts the probabilities of occupants perceiving fire signals due to direct perception, receiving fire alarms due to the activation of local alarms, sprinklers, the central alarm and the voice alarm, being warned by the other occupants and fire department, and taking actions including pulling the fire alarm, warning other occupants, calling the fire department, and commencing evacuation. The occupant response model is applied to predict the probabilities of evacuation initiation for a number of scenarios that consider combinations of fire detection and alarm systems for a mid-rise building. The results of the model show that asleep occupants need much longer response time to start evacuating and have lower probabilities of starting evacuation than awake occupants, which are consistent with what is observed in reality. Additionally, fire protection systems with only local alarms and only sprinklers connected to the central alarm can be improved significantly with systems with smoke detectors alone or combined with sprinklers connected to a central alarm, which result in higher probabilities of evacuation initiation with shorter delay times.     

Calibrating partial factors for Danish railway embankments using probabilistic analyses

High costs are connected with upgrading railway embankments throughout Denmark using the partial factors for geotechnical design calibrated for general application. One way to reduce the costs is reliability-based calibration of the partial factors to a reasonable safety level taking into account the specific design situations and uncertainties relevant to railway embankments. A reliability-based design has been investigated, resulting in an optimal partial factor for the considered subsoil. With a stochastic soil model to simulate the undrained shear strength of soft soil deposits, the partial factor is calibrated using asymptotic sampling for the reliability assessment. The calibration shows that the partial factor can be reduced significantly compared to the value specified in the Danish National Annex to DS/EN 1997-1 （2007）, Eurocode 7.     

A probabilistic model of bathing beach safety

An improved mathematical model for bathing beach safety is proposed. It is derived by joining the probability of infection from a given dose (Poisson distribution and the probability of acquiring such a dose (lognormal distribution).Even in the absence of better clinical and epidemiological data, the model permits an assessment of relative risk from certain hazards and the design of more meaningful bacteriological standards for individual beaches.     

A probabilistic fatigue strength model for brick masonry under compression

The paper presents the development of a model for the fatigue resistance of brick masonry under compression. The model takes into account the random nature of the fatigue strength phenomena and, as a consequence, proposes different model parameters as a function of the desired probability level. The model, based on a Weibull distribution, has been calibrated with the still limited experimental data on brick masonry under high cycle compression loading. Very good correlation is obtained. The results show that there is a clear trend of the experimental data to follow the Weibull distribution. It is also shown how the fatigue resistance of brick masonry is not only dependent on the magnitude of the stress cycles, but also on the magnitude of the minimum stress level. The paper also shows how the proposed model can be used in the reliability-based assessment of the fatigue performance of existing masonry arch bridges. Either the nominal probability of failure (reliability index) to fatigue or the remaining service life with a predefined probability level for an existing bridge can be predicted with the proposed method.     

Spatial probabilistic evaluation of offshore/nearshore sea bottom soils based on cone penetration tests

The inherent variability of soil has a crucial role in reliability-based design, especially for offshore foundations where the variability and uncertainty are more critical due to high costs as compared to the onshore counterparts. In this study, spatial probabilistic evaluation of the characteristics of offshore/nearshore sea bottom soils is performed based on data of 65 cone penetration tests (CPTs), reaching to 200-m depths in seabed soils, in up to 64 m of water. The types and typical characteristics of sea bottom soils are reported, together with statistical evaluation. A key parameter for random field theory, the spatial correlation length, based on CPT data is obtained for different soil types, using four different autocovariance functions (exponential, squared exponential, cosine exponential and second-order autoregressive). For these purposes, a MATLAB code is developed to take the CPT data, identify individual soil layers, carry out statistical evaluation of the properties of soils and report the vertical spatial correlation length of each layer using four different autocovariance functions. The undrained shear strength of clays in nearshore and offshore soils increases with depth, at rates of 1 to 3 kPa/m. Sands nearshore and offshore have similar relative density that is generally less than 50% (i.e. in loose to medium-dense state). The vertical spatial correlation length based on CPT of all soils is in the range of 0.11 m to 0.27 m, for all four different autocovariance functions, for all CPT cone tip resistances, sleeve friction and friction ratio, and for all shallow- and deep-water soils. The vertical spatial correlation length of nearshore soils is slightly larger than offshore soils. The results add to the scarce data on the spatial correlation length of offshore soils and can be useful for future studies on reliability and risk assessment of nearshore/offshore foundations.