CONDITIONAL ASSESSMENT SYSTEM FOR REINFORCED CONCRETE MARINE STRUCTURES – A CASE STUDY

Current study mainly focusses on the development of a conditional assessment system for reinforced concrete structures present in marine environment demonstrating with a case study of cargo berths (CB) at Deendayal Port Trust, Kandla, Gujarat, India. The maximum tidal range at the study area is nearly 8m, making the field non-destructive tests (NDT) challenging. The proposed assessment system is based on the damage level classification (DLC) of structure, evaluated by a set of widely used NDTs. The study further investigates the usage of DLC system in comparison with the Condition Rating (CR) method developed by Verma et al. NDTs were conducted at 182 locations between CB 7-10 and observed that the condition of the marine structure, indicated by CR system and DLC system is similar irrespective of their different test approaches. The proposed DLC assessment system is reliable, quick, efficient and requires relatively lesser efforts compared to the CR system.

Noise analysis in a model experiment for measuring ice loads using ice free water run

Модельный эксперимент в ледовом бассейне позволяет выяснить ледовые качества проектируемого ледостойкого морского сооружения, в том числе – получить представление о возможных ледовых нагрузках путем измерений глобальных нагрузок многокомпонентным динамометром. Чувствительность применяемого оборудования приводит к появлению шумовых помех в измеренном сигнале, вызванных действиями людей, обслуживающих эксперимент, работой машин и механизмов, гидродинамическими эффектами, а также явлениями в электросети. Отделение шумовых помех от полезного сигнала на этапе обработки данных является важной задачей, успешное решение которой позволит повысить достоверность результатов испытаний в ледовом бассейне. В настоящей работе изложен подход к очистке от шума результатов измерений многокомпонентного динамометра, применяемого в ледовом бассейне Крыловского государственного научного центра (Санкт-Петербург), с использованием амплитудно-частотного анализа участков пробега модели по чистой воде в пределах технологического окна во льду. Предложенный метод показал свою эффективность, в особенности – для экспериментов с моделью больших размеров. A model experiment in an ice tank allows to examine ice qualities of a designed ice-resistant marine structure, namely possible ice loads by measuring global loads with a multicomponent dynamometer. The sensitivity of the equipment leads to the noise interference in the measured signal caused by people's actions carrying out the experiment, by the operation of machines and mechanisms, hydrodynamic effects, as well as the phenomenae in the electrical power grid. It is important to separate noise interference from the relevant signal at the data processing stage, which will increase the reliability of ice tank experiments. This paper describes a method for denoising measurement results of a multicomponent dynamometer used in the ice tank of the Krylov State Scientific Center (St. Petersburg); the approach implies an amplitude-frequency analysis of model run areas in ice-free water within the technological window in the ice. The proposed method has demonstrated its effectiveness, especially for experiments with large models.

APPLIED DEEP LEARNING FOR SLENDER MARINE STRUCTURE DYNAMIC ANALYSIS

Non-linear finite element models (FEM) are commonly used to perform analysis in the time domain to simulate a limited number of stochastic loading scenarios that a slender marine structure may undergo, requiring a high computational time effort. Analytical equations and frequency domain analysis can be used to speed up these simulations, but they are not a convenient choice when high non-linearities are present in the dynamic system. Alternative models can be developed to reduce the simulation time while maintaining a good accuracy level of the system's response. This work proposes different strategies to develop artificial neural networks (ANN) architectures, based on deep learning algorithms, which can predict multiple structural node responses at once, in time and space, significantly reducing the total training time when a great number of structural nodes are considered. A novel classification concept of ANN-based models is introduced for this application: the NodeNet and the LengthNet class types. In the first approach, the model predictor focuses on a single structural node, while in the latter the model focuses on a length (segment) comprising many structural nodes. The work also extends the response predictions of such marine structures from the top region down to the Touchdown Zone (TDZ).

Vibration control of network-based offshore structures subject to earthquakes

Marine structures are inevitably influenced by parametric perturbations as well as multiple external loadings. Among these loadings, earthquake is generally more destructive and unpredictable than others. It is significant to develop effective active control schemes to guarantee the safety, stability, and integrity of marine structures subject to earthquakes and parametric perturbations. In this paper, the problem of networked [Formula: see text] robust damping control is addressed to stabilize a marine structure subject to earthquakes. First, in consideration of perturbations of the structure parameters, an uncertain model of the networked marine structure under earthquakes is presented. Second, a robust networked [Formula: see text] control scheme is presented to suppress seismic responses of the structure. By using stability theory of time-delay systems, several sufficient conditions on robust stability of the networked marine structure system are obtained, and the linear matrix inequality methods are utilized to solve the gain matrix of the controller. Finally, simulation indicates that compared with the traditional robust [Formula: see text] control and the proposed networked [Formula: see text] control, the seismic responses amplitudes of the marine structure under the two controllers are almost the same, while the latter is more economic than the former.

Conditional Assessment System for Reinforced Concrete Marine Structures – A Case Study

Current study mainly focusses on the development of a conditional assessment system for reinforced concrete structures present in marine environment demonstrating with a case study of cargo berths (CB) at Deendayal Port Trust, Kandla, Gujarat, India. The maximum tidal range at the study area is nearly 8m, making the field non-destructive tests (NDT) challenging. The proposed assessment system is based on the damage level classification (DLC) of structure, evaluated by a set of widely used NDTs. The study further investigates the usage of DLC system in comparison with the Condition Rating (CR) method developed by Verma et al. NDTs were conducted at 182 locations between CB 7-10 and observed that the condition of the marine structure, indicated by CR system and DLC system is similar irrespective of their different test approaches. The proposed DLC assessment system is reliable, quick, efficient and requires relatively lesser efforts compared to the CR system.

Application of data analysis methods to the results of operation of the marine structure health monitoring system

В работе представлены результаты, анализа и обработки больших массивов данных, получаемых с системы мониторинга состояния МЛСП. Проанализированы зафиксированные внешние воздействия и отклики конструкции с привязкой к временной шкале. Получены коэффициенты корреляции между внешними воздействиями. Построены фазовые портреты внешних воздействий с выраженными аттракторами. Получены коэффициенты корреляции между откликами конструкции. Построены фазовые портреты откликов. Установлены корреляционные зависимости между зафиксированными внешними воздействиями и зарегистрированными откликами конструкции. Проведен кластерный анализ. Установлены связи между кластерами, позволяющие сформулировать гипотезы о более ожидаемых и менее ожидаемых переходах. Определены основные положения для повышения прогнозных характеристик системы мониторинга. In the paper the results of analysis and processing of large data sets obtained from structures of offshore ice-resistant fixed platform health monitoring system are presented. The fixed external influences and responses of the structure are analyzed with reference to the timeline. Coefficients of correlation between external influences are obtained. Phase portraits of external influences with pronounced attractors are constructed. The coefficients of correlation between the responses of the structure are obtained. Phase portraits of responses were constructed. Correlations between the recorded external influences and the registered responses of the structure have been established. Cluster analysis was carried out. The connections between the clusters have been established, which make it possible to formulate hypotheses about more expected and less expected transitions. The main provisions for improving the predictive characteristics of the monitoring system are determined.

On some fundamental issues about the safety of marine structures

Safety analysis and prediction of a marine structure is a very important field which has received attention from many scientists. Prof. R. Ajit Shenoi has made significant contributions in investigating various issues in this field. In this invited paper of recollection nature, a philosophical attitude is taken to re-examine some fundamental issues about the safety of marine structures with a purpose to identify the key issues to be solved in the future. It is intended to help young generations of scientists how to focus on more important problems related to the safety of marine structures.