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The major component of environmental loadings on offshore structures is the wave-induced loads. The time-domain analysis has been commonly preferred to assess offshore structures because it provides considerable benefits to the practicing engineer without losing accuracy. However, such assessments are high computational demands and time costs due to complex numerical procedures in completing the hydrodynamic loadings on the offshore structures. Moreover, a huge number of simulations is required to increase the accuracy, leading to a long processing time. Hence, a simplified analysis-based time domain is introduced by applying direct calculation procedures to overcome this issue. It refers to an efficient time simulation regression method called the ETS-RegSE model. The result of the Monte Carlo Time Simulation (MCTS) will be used to compare the performance of the ETS-RegSE model's output. Provided with reasonable accuracy, the ETS-RegSE model offered a more efficient approach to optimal and costeffective structural analysis. [ABSTRACT FROM AUTHOR]

For offshore structural design, the load due to wind-generated random waves is usually the most important source of loading. The most accurate method that is commonly used to evaluate the offshore structural response on the subjected load is the Monte Carlo time simulation which can account for all sorts of nonlinearities without introducing any approximations. However, it is computationally very demanding due to its complex procedure. A simple method using finite-memory nonlinear system (FMNS) has been introduced. The method is, however, only applicable based on the linear wave analysis. Hence, by taking advantage on the efficiency of FMNS method, a new model needs to be developed by apply the FMNS method with a nonlinear wave analysis for a more reliable result. The most appropriate model can then be used to determine the probability distribution of response extreme values with great efficiency and accuracy. [ABSTRACT FROM AUTHOR]

An offshore structure is operated in an ocean wave environment that is stochastic in nature. Essential knowledge of ocean wave mechanics is practically important when it comes to the reliability of the structure. This paper summarised the numerical formulation involved in representing the ocean wave which will provide interaction effect in the design load of offshore structural response. Mechanism of wave load involved the formulation of wave spectra, ocean wave theory, water particles kinematics above sea water level, and the evaluation of wave force. Several formulations introduced by previous researchers for each process of wave load mechanism are discussed. At the end of this study, a good understanding of the estimated wave loads-induced responses will be discovered in terms of the selected ocean wave modelling. In application perspective, the calculated offshore structural responses would be utilised as the design load (structural responses) in structural reliability analysis of offshore platforms. [ABSTRACT FROM AUTHOR]

The most reliable technique for predicting the statistical properties of the response of an offshore structure to random wave loading is the conventional time simulation method (CTS). However, this study is concerned to reduce the computational demand of this method due to long simulation needed for stable results. To this end, a more efficient version of the time simulation technique (ETS) has been introduced which divides the simulated response extreme values into several groups based on the magnitude of the extreme values of their associated surface elevation or linear response records. The method has proved to be very efficient for both low and high-intensity sea states. In this study, the 100-year extreme responses from ETS and CTS methods have been compared to examine the accuracy of the ETS technique. Overall, the ETS technique was found to be many times more efficient than the conventional method. [ABSTRACT FROM AUTHOR]

The reliability of offshore structure is dominantly affected by the wind-generated random waves load. Hence, an appropriate technique is required in predicting the extreme response due to the dominant load. Monte Carlo (MC) time simulation is said to be the most accurate technique. However, such analysis leads to a large number of response records which is computationally demanding. Current finding shows that a modified finite-memory nonlinear system offered more efficient technique. Still, the accuracy is getting severe once negative current is considered. Hence, improved version of MFMNS technique is required by modelling the residue between the extreme values from MC and the approximate MFMNS techniques; known as the eMFMNS technique. In advanced, a comprehensive study on eMFMNS technique will be carried out involving a wide range of environmental conditions. From the investigation, it is proven that eMFMNS technique improved the accuracy in predicting extreme values compare to MFMNS technique. [ABSTRACT FROM AUTHOR]

Offshore structures are exposed to random wave loading in the ocean environment. The response is commonly non-Gaussian due to the nonlinearity of the drag component of Morison's wave loading and also the load intermittency on members in the splash zone. The previous study shows that the developed finite-memory nonlinear system (FMNS) model can efficiently simulate the response of an offshore structure to random Morison wave loading. However, the FMNS models minimise the computational effort, and the estimates are not particularly good for lower significant wave height value. To overcome this deficiency, a modified version of FMNS models (MFMNS) is used to compute the extreme response values which increase the accuracy but is computationally less efficient than the current FMNS models. In this study, the probability distributions of extreme responses from both models are compared with corresponding distributions from the conventional time simulation technique to establish their level of accuracy. [ABSTRACT FROM AUTHOR]

Offshore structures are exposed to random wave loading in the ocean environment and hence the probability distribution of the extreme values of their response to wave loading is required for their safe and economical design. To this end, the conventional (Monte Carlo) time simulation technique (CTS) is frequently used for predicting the probability distribution of the extreme values of response. However, this technique suffers from excessive sampling variability and hence a large number of simulated extreme responses (hundreds of simulated response records) are required to reduce the sampling variability to acceptable levels. A more efficient version of the time simulation technique (ETS) was recently introduced which takes advantage of the correlation between the extreme surface elevations and their corresponding extreme responses by dividing the simulated extreme responses into a number of groups based on the magnitude of their associated extreme surface elevations. The probability distribution of response extreme values for each group is then calculated individually based on a relatively small number of simulations, and then the total probability theorem is used to derive the probability distribution of response extreme values. The ETS procedure is found to be many times more efficient than the CTS method. However, its efficiency and accuracy reduces for sea states of lower intensity. In this paper, a more efficient version of the ETS technique is introduced which takes advantage of the correlation between extreme values of the nonlinear response and their corresponding linear response extreme values (both quasi-static and dynamic linear responses are considered)). The three different versions of the ETS technique are compared by exposing a test structure to sea states of different intensity. It is demonstrated that the extreme linear response versions of the ETS technique are more accurate and efficient than the version based on surface elevation extreme values. [ABSTRACT FROM PUBLISHER]

In offshore engineering, the main forces that are loaded onto ocean structures come from wind-generated random waves. The prediction of wave forces that are applied onto slender cylindrical members is usually based on the Morison's equation, in which the wave force at any section of a member is expressed directly in terms of wave kinematics. It is essential to be able to estimate sensible kinematics at all levels of a structure to determine accurate prediction of wave forces and corresponding responses of these structures in a random wave field. Linear random wave theory (LRWT) is the simplest and most often used to simulate water particle kinematics at different nodes of an offshore structure from a reference surface elevation record. However, water particle kinematics calculated from LRWT grossly overpredicts the kinematics above the mean water level (MWL). Methods have been introduced to overcome this problem of high kinematics above the MWL, which consists of using linear wave theory (such as Wheeler, vertical stretching, effective node elevation and effective water depth methods) to provide a more realistic representation of near-surface wave kinematics. This is promising as there is some evidence that the water particle kinematics from the Wheeler method are underestimated and that those from the vertical stretching method are somewhat exaggerated. In this paper, the comparisons of the probability distributions of extreme values from different methods of simulation wave kinematics are investigated by using conventional time simulation procedure. [ABSTRACT FROM AUTHOR]

Offshore structures are exposed to random wave loading in the ocean environment and hence the probability distribution of the extreme values of their response to wave loading is required for their safe and economical design. Wave loading on slender members of bottom-supported jacket structures is frequently calculated by Morison's equation. Due to nonlinearity of the drag component of Morison wave loading and also due to intermittency of wave loading on members in the splash zone, the response is often non-Gaussian; therefore, simple techniques for derivation of their extreme response probability distributions are not available. To this end, the conventional time simulation technique (CTS) is frequently used for predicting the probability distribution of the extreme values of response. However, this technique suffers from excessive sampling variability and hence a large number of simulated response extreme values (hundreds of simulated response records) are required to reduce the sampling variability to acceptable levels. In this paper, a more efficient version of the time simulation technique (ETS) is introduced to derive the probability distribution of response extreme values from a much smaller sample of simulated extreme values. The ETS procedure is found to be many times more efficient than the CTS method. [ABSTRACT FROM PUBLISHER]

Among cereals, oats are unique for their benefiting from high protein as well as lipid content. However, insufficient gluten content creates a big challenge to making breads out of this kind of cereals. Flour made of one type of bread wheat cultivar plus two types of improved oat lines were employed in this study to make composite oat-wheat flour bread. According to the data obtained from farinograph readings, water absorption capacity and the duration of the dough development increased with an increase in the dough's proportion of oat. The data obtained from the extensograph readings showed that the dough energy increased but extensibility property decreased with increase in the proportion of oat in the dough. Breads with 10% oat flour were ranked highest by the panelists. However, from a sensory point of view, the 10% formula was found to be inferior to control (bread baked from 100% wheat flour). Overall, considering the substantial nutritional benefits of oat, a certain level of compromise in the sensory properties can be made by offering breads with 20-30% rate of oat content. [ABSTRACT FROM AUTHOR]