Data Driven Digital Twin Applications Towards Green Ship Operations

Abstract

Due to the growing rate of energy consumption and its consequent emissions, the International Maritime Organization (IMO) has devised strict rules for an extensive reduction in Greenhouse Emissions (GHG), which forces the shipping industry to search for more energy-efficient solutions. Therefore, alongside with the Energy Efficiency Design Index (EEDI), improving the energy efficiency of existing ships under the Energy Efficiency Existing Ship Index (EEXI) is of considerable importance. This paper address this issue by proposing a digital twin framework supported by big data analytics for ship performance monitoring. The proposed framework is developed by the respective data sets from a selected vessel. For this purpose, a cluster analysis is implemented using the Gaussian Mixture Models (GMMs) with the Expectation Maximization (EM) algorithm. By this approach, the most frequent operating regions of the engine is detected, the shapes of these frequent operating regions are captured, and the relationships between different navigation and performance parameters of the engine are determined. That will make the basis for a digital twin application in shipping. The main objective of this research study is to develop a digital twin of a marine engine by considering the engine operational conditions that can be utilized toward green ship operations. The contribution of this paper and the outcomes can facilitate the shipping industry to meet the IMO requirements enforced by its regulations.

Multiple Model Adaptive Estimation Coupled With Nonlinear Function Approximation and Gaussian Mixture Models for Predicting Fuel Consumption in Marine Engines

“…The detailed implementation and results of the proposed clustering algorithm for a dataset of one month of the selected vessel are presented in [19]. Based on these results, 4 clusters or operating regions are identified for this vessel using the selected operating parameters of the marine engine.…”

Investigation of the mechanical properties and propagation of cracks in prosthetic teeth composed of porcelain and dental ceramics using cohesive meshing under quasi-static loading conditions

“…The tooth has specific mechanical characteristics associated with its role in concentrating internal stresses on the tooth surface [33][34][35][36][37]. Numerous research has been undertaken to examine the mechanical characteristics of human teeth [38,39]. Nevertheless, the processes by which teeth get deformed are still not well understood.…”

Estimation of the mean effective pressure of a spark ignition internal combustion engine using a neural network, considering the wall-wetting dynamics

“…In recent years, excessive consumption of fossil fuels and greenhouse gas emissions has been a significant global challenge. Consequently, renewable sources of energy are widely used [1][2][3][4][5]. A large percentage of fuel consumption and pollutant generation are related to internal combustion engines.…”

“…This has led to efforts to achieve cleaner and more intrusive internal combustion engines. Before the oil crisis of the 1970s, significant people were only mindful of the easy use of cars and convenience, and no one thought about pollution and fuel consumption [2,3,[6][7][8][9]. In recent years, air pollution has become one of the significant problems in the world, causing the pollution of cars to be limited and making its control a significant issue in the policy of car manufacturers [10][11][12][13].…”