Farhad Hosseinlou, Alireza Mojtahedi, Mohammad Ali Lotfollahi3,
Volume 12, Issue 23 (9-2016)
Abstract
One of the most important items in the field of engineering and design of structures is safety assessment. It is usually complicated, due to uncertainty in determining the most important parameters in the final design. This paper describes a new method for updating stiffness matrix structure that is capable of identifying the damage to individual members, when limited modal data is available by using results of the experiment on physical model of the offshore jacket platforms. We evaluated selection procedure inactive degrees of freedom in the process reduced model with a reasonable criterion by using the sensitivity analysis of system response under base excitation. This performance leads to faster convergence of iterative algorithm. Also, in this study, with using the finite element model updating based on the empirical models, it was considered during the process as much as possible to overcome the problem of uncertainty in modeling.
Saeed Ghaffarpour Jahromi, Mohammad Sharafuddin,
Volume 16, Issue 31 (4-2020)
Abstract
In this study, using the results of 100 PDA dynamic loading tests obtained from different projects and using three types of artificial neural networks (ANN), the loading capacity of a single pile is evaluated. Initially, the Perstron multilayer neural network was used as one of the most widely used neural networks. In the following, a combination of neural-fuzzy networks is used from the nephrophysical network, and at the end, the neural network is used as a function of the radial basis of the successful network in nonlinear problems. Unlike conventional behavioral models, neural network-based models do not explain how input parameters affect output. In this research, by performing sensitivity analysis on the optimal structure of the models introduced in each stage, an attempt has been made to examine this ambiguity to some extent. Also, introducing the relationships governing a neural network model can give engineers more confidence in using them to facilitate analysis and design.
Esmaeil Hasanvand, Pedram Edalat,
Volume 16, Issue 32 (11-2020)
Abstract
This paper analyzes CALM terminal sensitivity under various operating parameters such as water depth, chain mass, current velocity, wave period, hawser length as well as terminal displacement in different directions, and the impact of tanker presence on the behavior of the riser (lazy S) during unloading/loading operations. The hydrodynamic response characteristics of the tanker and CALM buoy are calculated using ANSYS-AQWA software and the outputs are imported in OracleFlex software for simulation of the probable operating scenarios considering the terminal, tanker, mooring lines and Environmental conditions. The results indicate that the terminal dynamic response is most sensitive to the current velocity changes. It is also concluded that for the riser, when Near offset, an effective tension and for far offset, the bending moment includes critical states. The bending moment at the hang-off the riser and the effective tension at PLEM receive the most impact from the interactive mode of operation between the tanker and the terminal.
Naser Shabakhty, Mohammad Hossein Kharaghani,
Volume 19, Issue 39 (9-2023)
Abstract
Since various relationships have been presented to calculate the recession in the berm breakwater, the evaluation of these relationships in the form of probabilistic is one of the most basic topics in marine engineering. In this study, the failure probability or in complementary the reliability for recession of Shahid Beheshti port berm breakwater is investigated based on six models of Torum (2007), Moghim et al. (2011), Lykke Andersen et al. (2014), Moghim and Alizadeh (2014), Van Der Meer and Sigurdarson (2016) and Ehsani et al. (2020). Four methods of First-Order Reliability Method (FORM), Second-Order Reliability Method (SORM), Monte Carlo Simulation (MCS) and Importance Sampling (IS) are applied to obtained the failure probability and reliability index for breakwater at the maximum water depth and 100-year wave height. The results of the MCS show the highest failure probability belongs to Moghim et al. (2011) model with a value of about 0.69, and the lowest value possess to the Torum (2007) model with a value of about 0.29. In addition, Van der Meer and Sigurdarson (2016) and Moghim and Alizadeh (2014) models give the failure probabilities of 0.57 and 0.50 respectively and Likke Andersen et al. (2014) and Ehsani et al. (2020) models presented the failure probabilities of 0.42 and 0.38 respectively. According to these results, Ehsani et al. (2020) and Torum (2007) models which developed for Icelandic breakwaters have the lowest probability of failure. Furthermore, Models of Moghim et al. (2011) and Moghim and Alizadeh (2014) which presented for reshaping breakwaters have the highest probability of failure. Next, sensitivity analysis was performed and the impact of different variables on the probability of failure was investigated.
