Assessment of histopathological and hematological changes in mice treated with the aqueous extract of origanum (Driganum majorana.L)in algabal Alakhder libya

the aim of this work is to Making a survey to determine the Origanum used in Algabal Alakhder Investigation the histological physiological and hematological alterations resulted from Origanum administration in mice. Studying the rohe of Origanum in decreasing the adverse changes caused by some toxic substanc

Development of a multi-scheme energy management strategy for a hybrid fuel cell driven passenger ship

Hybrid fuel cell propulsion systems for marine applications are attracting widespread interest due to the need to reduce ship emissions. In order to increase the potential of these systems, the design of an efficient energy management strategy (EMS) is essential to distribute the required power properly between different components of the hybrid system. For a hybrid fuel cell/battery passenger ship, a multi-scheme energy managements strategy is proposed. This strategy is developed using four schemes which are: state-based EMS, equivalent fuel consumption minimization strategy (ECMS), charge-depleting charge-sustaining (CDCS) EMS, the classical proportional-integral (PI) controller based EMS, in addition to a code that chooses the suitable scheme according to the simulation inputs. The main objective of the proposed multi-scheme EMS is to minimize the total consumed energy of the hybrid system in order to increase the energy efficiency of the ship. The world's first fuel cell passenger ship FCS Alsterwasser is considered and its hybrid propulsion system is modelled in MATLAB/Simulink environment. The performance of the developed multi-scheme EMS is compared to the four studied strategies in terms of total consumed energy, hydrogen consumption, total cost and the stresses seen by the hybrid fuel cell/battery system components considering a daily ship operation of 8 h. Results indicate that a maximum energy and hydrogen consumption savings of 8% and 16.7% respectively can be achieved using the proposed multi-scheme strategy

Ship speed prediction based on machine learning for efficient shipping operation

Optimizing ship operational performance has generated considerable research interest recently to reduce fuel consumption and its associated cost and emissions. One of the key factors to optimize ship design and operation is an accurate prediction of ship speed due to its significant influence on the ship operational efficiency. Traditional methods of ship speed estimation include theoretical calculations, numerical modeling, simulation, or experimental work which can be expensive, time-consuming, have limitations and uncertainties, or it cannot be applied to ships under different operational conditions. Therefore, in this study, a data-driven machine learning approach is investigated for ship speed prediction through regression utilizing a high-quality publicly-accessible ship operational dataset of the ‘M/S Smyril’ ferry. Employed regression algorithms include linear regression, regression trees with different sizes, regression trees ensembles, Gaussian process regression, and support vector machines using different covariance functions implemented in MATLAB and compared in terms of speed prediction accuracy. A comprehensive data preprocessing pipeline of operational features selection, extraction, engineering and scaling is also proposed. Moreover, cross validation, sensitivity analyses, correlation analyses, and numerical simulations are performed. It has been demonstrated that the proposed approach can provide accurate prediction of ship speed under real operational conditions and help in optimizing ship operational parameters

An improved energy management strategy for a hybrid fuel cell/battery passenger vessel

The combination of a fuel cell and an energy storage system for the reduction of fuel consumption and improving the dynamics of hybrid power systems has successfully been used in transportation applications. In order to realise the benefits of hybrid fuel cell power systems, an energy management strategy is essential for distributing the required power properly between the fuel cell and the energy storage system. For a hybrid fuel cell/battery passenger vessel, an improvement to the classical proportional-integral (PI) controller based energy management strategy is presented. This takes fuel cell efficiency into consideration as an input to maintain higher efficiency of fuel cell and reduce stresses on it and hence reduce its fuel consumption

Experimental testing and simulations of an autonomous, self-propulsion and self-measuring tanker ship model

Improving the energy efficiency of ships has generated significant research interest due to the need to reduce operational costs and mitigate negative environmental impacts. Numerous hydrodynamic energy saving technologies have been proposed. Their overall performance needs to be assessed prior to implementation. A new approach to this evaluation is investigated at model scale which applies an approach comparable to that applied for the performance monitoring of a full scale ship. That is long duration testing that measures power consumption for given environmental and ship operating conditions and can use statistical analysis of the resultant large amount of data to identify performance gains. As a demonstration of the approach, an autonomous, self-propelled and self-measuring free running ship model of an Ice Class tanker is developed. A series of lake based and towing tank tests experiments have been conducted which included bollard pull, shaft efficiency, naked-hull, self-propulsion, and manoeuvrability tests. These investigated the efficiency improvement resulting from changing the ship operational trim and testing different bow designs. An associated mathematical model for the time domain simulation of the autonomous ship model provides an effective tool for data analysis. It has been demonstrated that the use of a suitably instrumented self-propelled autonomous ship model can provide long duration tests that incorporates the influence of varying environmental conditions and thereby identify marginal gains in ship energy efficiency

Ship voyage energy efficiency assessment using ship simulators

The increase in global trade is driving growth in both the size and number of ships. However, this increased demand is leading to greater contributions from shipping to air pollution. This is leading designers and operators to propose and adopt novel powering and propulsion systems. However, there is a challenge with assessing the actual benefit from using a certain retrofit technology or changing the operating conditions of their ships, this may be addressed using numerical simulations. This paper presents a time-domain one-degree of freedom ship simulator implemented in MATLAB/Simulink to enable designers to predict the performance of ship propulsion system during voyages.The proposed simulator is used to assess the effectiveness of three different EEDI and SEEMP measures suggested by IMO to increase ship's propulsion system efficiency which are: voyage execution, slow steaming, and hybrid electric power and propulsion concepts using fuel cells. The developed simulator can be used for further studies and more elements are planned to be added to the ship simulators to make it more generic and capable of testing more propulsion configurations options

Artificial neural network based prediction of ship speed under operating conditions for operational optimization

Ship speed is one of the most fundamental parameters which influences ship design, the energy efficiency of its operation, and safety. Therefore, ship speed selection and prediction under various environmental and operational conditions are of great concern recently for optimizing ship design and operational performance. Among the different approaches that address the ship speed topic, data-driven methodologies and Artificial Neural Network (ANN) techniques are attracting widespread interest due to its efficiency, accuracy, robustness, flexibility, and fault tolerance. Consequently, this study investigates multiple ANN model sizes and architectures to determine the suitable network parameters for ship speed prediction. Thus, we have a good balance between the model’s prediction accuracy and computational complexity. For this study, a publicly-available high-quality operational dataset suitable for benchmarking the results is utilized. This analysis also includes the effect of the data quantity and sampling duration on the data correlation and the ANN performance. The results indicate that the proposed ANN model can accurately predict ship speed under real operational conditions with an error of less than 1 knot. Furthermore, it has been shown that the proposed model can help with the decision-making and optimization processes of voyages planning and execution

Sizing optimization of a fuel cell/battery hybrid system for a domestic ferry using a whole ship system simulator

A power source sizing methodology for a hybrid fuel cell/battery powered domestic ferry is presented in this paper. The sizing objective in this study is to minimize both the system first and operational costs, taking into consideration maintenance and replacement costs of the fuel cell and battery systems. According to the ferry power requirement, different combinations of fuel cell and battery blocks are modelled in order to select the optimal combination according to the sizing objective. Power requirement of the ferry is calculated using a validated time-domain three-degree of freedom total ship system simulator implemented in the MATLAB/Simulink environment

A solar energy-based shore side power system for a ferry service across the Suez Canal

For more sustainable shipping operation in coastal areas and port cities, shore side power (SSP) systems are attracting widespread interest as a solution to reduce ship auxiliary engine emissions, noise and vibration. The potential of these systems can be further improved by integrating renewable energy into the electricity grid. However, the majority of prior research has focused on investigating SSP systems for large ports in large shipping hub countries. Therefore, in this study, SSP technology is investigated for an inland waterway in Egypt on the Suez Canal utilising real ferries operational data. Green electricity from solar sunshade structures is generated for the SSP system utilising the Egyptian excellent solar energy potential. For this study, the ferry diesel generator, battery and solar systems are modelled in MATLAB/Simulink environment to investigate the proposed SSP system. Results indicate that the proposed SSP system could eliminate annually 1420 tonnes of emissions as well reduce the grid CO2 emissions by 1204 tonnes through the green electricity supplied to the grid. Moreover, the cash flow and net present value analyses have shown good profitability with a payback period between 7.4 and 12 years