Overview of Past, Present and Future Marine Power Plants

In efforts to overcome an foreseeable energy crisis predicated on limited oil and gas supplies, reserves; economic variations facing the world, and of course the environmental side effects of fossil fuels, an urgent need for energy sources that provide sustainable, safe and economic supplies for the world is imperative. The current fossil fuel energy system must be improved to ensure a better and cleaner transportation future for the world. Despite the fact that the marine transportation sector consumes only 5% of global petroleum production; it is responsible for 15% of the world NOx and SOx emissions. These figures must be the engine that powers the scientific research worldwide to develop new solutions for a very old energy problem. In this paper, the most effective types of marine power plants were discussed. The history of the development of each type was presented first and the technical aspects were discussed second. Also, the fuel ceils as a new type of power plants used in marine sector were briefed to give a complete overview of the past, present and future of the marine power plants development. Based on the increased worldwide concerns regarding harmful emissions, many researchers have introduced solutions to this problem, including the adoption of new cleaner fuels. This paper was guided using the same trend and by implementing the hydrogen as fuel for marine internal combustion engine, gas turbines, and fuel cells.

The Use of Hydrogen as a Fuel for Inland Waterway Units

Escalating apprehension about the harmful effects of widespread use of conventional fossil fuels in the marine field and in internal combustion engines in general, has led to a vast amount of efforts and the directing of large capital investment towards research and development of sustainable alternative energy sources. One of the most promising and abundant of these sources is hydrogen. Firstly, the use of current fossil fuels is. discussed focusing on the emissions and economic sides to emphasize the need for a new, cleaner and renewable fuel with particular reference to hydrogen as a suitable possible alternative. Hydrogen properties, production and storage methods are then reviewed along with its suitability from the economical point of view. Finally, a cost analysis for the use of hydrogen in internal combustion engines is carried out to illustrate the benefits of its use as a replacement for diesel. The outcome of this cost analysis shows that 98% of the capital expenditure is consumed by the equipment, and 68.3% of the total cost of the equipment is spent on the solar photovoltaic cells. The hydrogen plant is classified as a large investment project because of its high initial cost which is about 1 billion US$; but this is justified because hydrogen is produced in a totally green way. When hydrogen is used as a fuel, no harmful emissions are obtained.

Geochemistry of the Rare Earth Elements (REE) Distribution in Terengganu Coastal Waters: A Study Case from Redang Island Marine Sediment

A study on the rare earth elements (REEs) of Redang Island marine sediments was conducted in August 2011 during the premonsoon season. Bottom sediments were collected from 27 sampling stations on board UMT Discovery II vessel using a Smith McIntyre grab and analyzed for rare earth elements (REEs) using inductively coupled plasma mass spectrometry (ICP-MS). Results showed that the REEs patterns in sediments reflected the source rock patterns with an overall order of abundance such as: light rare earth elements (LREE) > middle rare earth element (MREE) > high rare earth elements (HREE). The chondrite normalized patterns of REEs showed enrichment of LREEs over HREEs with La/Yb of 13.6 while the chondrite normalized value showed low (Gd/Yb)N ratios (2.12) which was illustrated in the flat HREE pattern. The chondrite normalized REE patterns of sediments showed the enrichment of LREE and depletion of HREE. From our findings, REEs concentrations in the study area were found to be of geogenic origins and the distributions were not influenced by anthropogenic sources.

Thermodynamic Analysis of Alternative Marine Fuels for Marine Gas Turbine Power Plants

The marine shipping industry faces challenges to reduce engine exhaust emissions and greenhouse gases （GHGs） from ships, and in particular, carbon dioxide. International regulatory bodies such as the International Maritime Organization and National Environmental Agencies of many countries have issued rules and regulations to drastically reduce GHG and emissions emanating from marine sources. This study investigates the possibility of using natural gas and hydrogen as alternative fuels to diesel oil for marine gas turbines and uses a mathematical model to assess the effect of these alternative fuels on gas turbine thermodynamic performance. Results show that since natural gas is categorized as a hydrocarbon fuel, the thermodynamic performance of the gas turbine cycle using natural gas was close to that of the diesel case. However, the gas turbine thermal efficiency was found to be slightly lower for natural gas and hydrogen fuels compared to diesel fuel.

Precise Point Positioning Technique with IGS Real-Time Service (RTS) for Maritime Applications

The maritime navigation accuracy requirements for radionavigation systems such as GPS are specified by the International Maritime Organization (IMO). Maritime navigation usually consists of three major phases identified as Ocean/Coastal/Port approach/Inland waterway, in port navigation and automatic docking with an accuracy requirement that ranges from 10 m to 0.1 m. With the advancement in autonomous GPS positioning techniques such as Precise Point Positioning (PPP) and with the advent of the new IGS-Real-Time-Service (RTS), it is necessary to assess the possibility of a wider role of the PPP-based positioning technique in maritime applications. This paper investigates the performance of an autonomous real-time PPP-positioning solution by using the IGS- RTS service for maritime applications that require an accurate positioning system. To examine the performance of the real-time IGS-RTS PPP-based technique for maritime applications, kinematic data from a dual frequency GPS receiver is investigated. It is shown that the real-time IGS-RTS PPP-based GPS positioning technique fulfills IMO requirements for maritime applications with an accuracy requirement ranges from 10 m for Ocean/Coastal/Port approach/Inland waterways navigation to 1.0 m for in port navigation but cannot fulfill the automatic docking application with an accuracy requirement of 0.10 m. To further investigate the real-time PPP-based GPS positioning technique, a comparison is made between the real-time IGS-RTS PPP-based positioning technique and the real-time PPP-based positioning by using the predicted part of the IGS Ultra-Rapid products and the real-time GPS positioning technique with the Wide Area Differential GPS service (WADGPS). It is shown that the IGS-RTS PPP-based positioning technique is superior to the IGS-Ultra-Rapid PPP-based and WADGPS-based positioning techniques.

Impact of Tropospheric Delay Gradients on Total Tropospheric Delay and Precise Point Positioning

GPS signals are electromagnetic waves that are affected by the Earth’s atmosphere. The Earth’s atmosphere can be categorized, according to its effect on GPS signals, into the ionosphere (ionospheric delay) and neutral atmosphere (tropospheric delay). The first-order ionospheric delay can be eliminated by linear combination of GPS observables on different frequencies. However, tropospheric delay cannot be eliminated because it is frequency-independent. The total tropospheric delay can be divided into three components. The first is the dry component, the second part is the wet component, and the third part is the horizontal gradients which account for the azimuthal dependence of tropospheric delay. In this paper, the effect of modeling tropospheric gradients on the estimation of the total tropospheric delay and station position is investigated. Long session, one month during January 2015, of GPS data is collected from ten randomly selected globally distributed IGS stations. Two cases are studied: the first case, the coordinates of stations are kept fixed to their actual values and the tropospheric delay is estimated twice, with and without tropospheric gradients. In the second case, the station position is estimated along with the total tropospheric delay with and without tropospheric gradients. It is shown that the average bias of the estimated total tropospheric delay when neglecting tropospheric gradients ranges from ?1.72 mm to 2.14 mm while the average bias when estimating gradients are ?0.898 mm to 1.92 mm which means that the bias is reduced by about 30%. In addition, the average standard deviation of the bias is 4.26 mm compared with 4.52 mm which means that the standard deviation is improved by about 6%.

Stochastic Analysis of Low-Cost Single-Frequency GPS Receivers

Typically, dual-frequency geodetic grade GNSS receivers are utilized for positioning applications that require high accuracy. Single-frequency high grade receivers can be used to minimize the expenses of such dual-frequency receivers. However, user has to consider the resultant positioning accuracy. Since the evolution of low-cost single-frequency (LCSF) receivers is typically cheaper than single-frequency high grade receivers, it is possible to obtain comparable positioning accuracy if the corresponding observables are accurately modelled. In this paper, two LCSF GPS receivers are used to form short baseline. Raw GPS measurements are recorded for several consecutive days. The collected data are used to develop the stochastic model of GPS observables from such receivers. Different functions are tested to determine the best fitting model which is found to be 3 parameters exponential decay function. The new developed model is used to process different data sets and the results are compared against the traditional model. Both results from the newly developed and the traditional models are compared with the reference solution obtained from dual-frequency receiver. It is shown that the newly developed model improves the root-mean-square of the estimated horizontal coordinates by about 10% and improves the root-mean-square of the up component by about 39%.

Power Scheduling with Max User Comfort in Smart Home:Performance Analysis and Tradeoffs

The smart grid has enabled users to control their home energy more effectively and efficiently.A home energy management system(HEM)is a challenging task because this requires the most effective scheduling of intelligent home appliances to save energy.Here,we presented a meta-heuristic-based HEM system that integrates the Greywolf Algorithm(GWA)and Harmony Search Algorithms(HSA).Moreover,a fusion initiated on HSA and GWA operators is used to optimize energy intake.Furthermore,many knapsacks are being utilized to ensure that peak-hour load usage for electricity customers does not surpass a certain edge.Hybridization has proven beneficial in achieving numerous objectives simultaneously,decreasing the peak-to-average ratio and power prices.Widespread MATLAB simulations are cast-off to evaluate the routine of the anticipated method,Harmony GWA(HGWA).The simulations are for a multifamily housing complex outfitted with various cool gadgets.The simulation results indicate that GWA functions better regarding cost savings than HSA.In reputes of PAR,HSA is significantly more effective than GWA.The suggested method reduces costs for single and ten-house construction by up to 2200.3 PKR,as opposed to 503.4 in GWA,398.10 in HSA and 640.3 in HGWA.The suggested approach performed better than HSA and GWA in PAR reduction.For single-family homes in HGWA,GWA and HSA,the reduction in PAR is 45.79%,21.92%and 20.54%,respectively.The hybrid approach,however,performs better than the currently used nature-inspired techniques in terms of Cost and PAR.

Classification of Beach Based on Beach-Surf-Zone Morphodynamics—A Case Study

The beach classifications based on theoretical and numerical modelling study are more in literature. The paper discusses a case study regarding the morphological response of sandy beach to the monsoonal waves and its classifications based on the energy conditions. The sediment dynamics associated with morphological changes are functions of incident wave climate, sediment characteristics and other environmental factors. The study establishes quantitative relationships between incident wave energy flux, fall speed parameters, grain size and wave steepness, and classifies beach in accordance with energy conditions using different empirical functions. A criterion for sediment transport direction with different wave climate is also proposed and validated in the field conditions.

Thermo-Mechanical Influence on the Internal Friction of a 51CrV4 Shaft

The influence of simultaneously applied mechanical and thermal treatment is used for producing a geometrically complex shaft from 51CrV4 steel resulting in widely differing formations of microstructures.Materials'properties such as internal friction(IF),hardness and electrical resistivity are affected by this change of microstructure formations.The Snoek–Koster peak is identified and analyzed in the actual steel structure.

Automatic Detection of Outliers in Multi-Channel EMG Signals Using MFCC and SVM

The automatic detection of noisy channels in surface Electromyogram(sEMG)signals,at the time of recording,is very critical in making a noise-free EMG dataset.If an EMG signal contaminated by high-level noise is recorded,then it will be useless and can’t be used for any healthcare application.In this research work,a new machine learning-based paradigm is proposed to automate the detection of low-level and high-level noises occurring in different channels of high density and multi-channel sEMG signals.A modified version of mel fre-quency cepstral coefficients(mMFCC)is proposed for the extraction of features from sEMG channels along with other statistical parameters i-e complexity coef-ficient,hurst exponent,and root mean square.Several state-of-the-art classifiers such as Support Vector Machine(SVM),Ensemble Bagged Trees,Ensemble Sub-space Discriminant,and Logistic Regression are used to automatically identify an EMG channel either bad or good based on these extracted features.Comparison-based analyses of these classifiers have also been considered based on total classi-fication accuracy,prediction speed(observations/sec),and processing time.The proposed method is tested on 320 simulated EMG channels as well as 640 experi-mental EMG channels.SVM is used as our main classifier for the detection of noisy channels which gives a total classification accuracy of 99.4%for simulated EMG channels whereas accuracy of 98.9%is achieved for experimental EMG channels.

Estimation of Travel Times on Signalized Arterials

This paper describes procedure for estimation of travel time on signalized arterial roads based on multiple data sources with application of dimensionality reduction. Travel time estimation approach incorporates forecast of transportation nodes impendence and travel time on network links. Forecasting period is two hours and the estimation is based on historical data and real time data on traffic conditions. Travel time estimation combines multivariate regression, principal component analysis, KNN （k-nearest neighbours）, cross validation and EWMA （exponentially weighted moving average） methods. When comparing estimation methodologies, relevantly better results were achieved by KNN method than with EWMA method. This is true for every time interval considered except for evening time interval when signalized arterial roads were uncongested.

Sedimentology of the Redang Island Coral Reefs Environment

A study on the sedimentology of the Redang Island coral reefs environment was conducted. Sediments were collected on board UNIPERTAMA VII during the pre and post monsoon seasons. Twenty and seven sediments samples were collected using a Smith McIntyre grab on board UNI PERTAMA VII and put in labelled plastic bags then brought back to the laboratory for analysis. The sediments were analyzed for their sedimentological characteristics （mean size, skewness, standard deviation and kurtosis） using dry sieving method. Results showed that the highest mean size value of the sediments during the pre and post monsoons seasons are 2.14 ~ and 2.37 O. respectively and the lowest are -0.40 q~ and -0.10 ~, respectively. Based on the results, sediments can be classified as medium sand （34%）, poorly sorted （67%）, strongly negative skewed （36%） and extremely leptokurtic （56%） during the pre monsoon season, while during the post monsoon season sediments can be classified as medium sand （38%）, poorly sorted （73%）, strongly negative skewed （41%） and very leptokurtic （62%）. Results revealed that the sediments in the whole study area are relatively coarse. No relationship was observed between mean size and other sedimentological characteristics （R2= 0.05 pre-monsoon. R2 =0.0017 post monsoon） with seasons.

Efficient Harmonic Analysis Technique for Prediction of IGS Real-Time Satellite Clock Corrections

Real-time satellite orbit and clock corrections obtained from the broadcast ephemerides can be improved using IGS real-time service (RTS) products. Recent research showed that applying such corrections for broadcast ephemerides can significantly improve the RMS of the estimated coordinates. However, unintentional streaming interruption may happen for many reasons such as software or hardware failure. Streaming interruption, if happened, will cause sudden degradation of the obtained solution if only the broadcast ephemerides are used. A better solution can be obtained in real-time if the predicted part of the ultra-rapid products is used. In this paper, Harmonic analysis technique is used to predict the IGS RTS corrections using historical broadcasted data. It is shown that using the predicted clock corrections improves the RMS of the estimated coordinates by about 72%, 58%, and 72% in latitude, longitude, and height directions, respectively and reduces the 2D and 3D errors by about 80% compared with the predicted part of the IGS ultra-rapid clock corrections.

Optimization of Waterway with Multiple Locks and Canals by Integration of Petri Net and Genetic Algorithm

This paper presents the possibilities of job optimization in waterway with multiple locks and canals, in order to increase the system productivity. Safe navigation in such complex waterway system is very demanding. Some of the problems that need to be solved are： How to control traffic in a way that vessels move in opposite directions; How to resolve possible conflicts in case that more vessels try to acquire particular lock at the same time; How to avoid possible deadlocks; How to ensure the vessel passage in the shortest possible time？ It is necessary to apply adequate control policy to avoid deadlocks and blocks the vessels＇ moving only in the case of dangerous situation. The motion of vessels can be described as the set of discrete events and states. Herein we propose deadlock avoidance algorithm for complex waterway system with multiple key resources and we use multiple re-entrant flowlines class of Petri net （MRF^PN）. The solution represents deadlock prevention supervisor in a sense that vessels are stopped only in a case of immediate dangerous situation in dense traffic. The goal of this paper is to find optimal, conflict and deadlock free job schedule in CWS. In this sense, the authors developed the algorithm which integrates MRF^PN with a genetic algorithm. The algorithm deals with multi-constrained scheduling problem with shared resources. The final goals are minimization the total travel time of vessels through the waterway system.

A Statistical Analysis of the Fuel Tanks＇ Corrosion Loss over Some Aged Bulk Carriers

This paper deals with modeling corrosion wastage over the fuel tanks＇ structures at the exemplar of ten aged bulk carriers. In this paper, employed method might be treated as a long term one, and it is based on Weibull distribution parameters analysis. The purpose of these analyses is optimal assessing of the average corrosion losses for the bulk carriers＇ fuel tanks areas at different points of time during the whole period of the exploitation, due to uprising the structural stability and safety of bulk carriers in operation. Though, the applied approach, among others, might be of particular importance in determining the amounts （percentage/depths） of time-dependent corrosion losses over different areas of aging bulk carriers＇ fuel tanks during the operational circles, with the ultimate goal of keeping stability and safety of these vital vessels＇ structural components.

Analyzing the Corrosion Wastage over Some of the Bulk Carriers＇ Member Locations

In this paper, well-known and structured Monte Carlo simulation technique has been employed in predicting the amounts of the corrosion wastage over some bulk carriers＇ structural elements in different points of time during their exploitation life. As a base for the realization of the simulations, the appropriate statistical data collected over the group of ten bulk carriers have been used. Both longitudinal and transversal ships＇ hull structural elements have been taken into the consideration. Due to some experts＇ knowledge in this domain, the critical hull zones are identified and certain interventions are done in the pre-processing of the input data to the Monte Carlo simulations, all with the aim of achieving better convergence between simulation results and the experts＇ expectations in this field.

Influence of Corrosion on the Reliability of SMA Materials in the Marine Environment

The research of new materials on the basis of memory shape today occupies the special attention of researchers in various industrial fields,such as medicine,traffic,robotics,etc.This paper analyzes the possibility of applying SMAs(shape memory alloys)in the maritime industry in terms of monitoring the behavior of SMAs in different marine environments.The subject of the research is Cu-Al-Ni and Ni-Ti CC alloys processed by CC(continuous casting)in the shape of bars and Ni-Ti as cast processed by casting in the shape of disk.Using the method of EDX(energy dispersion X-ray spectrophotometry),the chemical composition of alloy elements in zones such as in the air,on the surface of the sea and in the sea was determined after six and twelve months of exposure.By applying the theory of reliability,an assessment of the reliability of the alloy elements was obtained.According to the obtained results of the Cu-Al-Ni alloy,nickel is the most reliable in the sea.Aluminum is the least reliable in the sea.The Ni-Ti CC alloy in the marine environment is more reliable than the Ni-Ti as cast alloy.Based on the changes in the chemical composition of alloys in all three considered zones,it is concluded that all three alloys have the lowest reliability in the sea and the highest in the air.

Fuel Saving and Emissions Cut Through Shore-Side Power Concept for High-speed Crafts at the Red Sea in Egypt

The progress of economic globalization,the rapid growth of international trade,and the maritime transportation has played an increasingly significant role in the international supply chain.As a result,worldwide seaports have suffered from a central problem,which appears in the form of massive amounts of fuel consumed and exhaust gas fumes emitted from the ships while berthed.Many ports have taken the necessary precautions to overcome this problem,while others still suffer due to the presence of technical and financial constraints.In this paper,the barriers,interconnection standards,rules,regulations,power sources,and economic and environmental analysis related to ships,shore-side power were studied in efforts to find a solution to overcome his problem.As a case study,this paper investigates the practicability,costs and benefits of switching from onboard ship auxiliary engines to shore-side power connection for high-speed crafts called Alkahera while berthed at the port of Safaga,Egypt.The results provide the national electricity grid concept as the best economical selection with 49.03 percent of annual cost saving.Moreover,environmentally,it could achieve an annual reduction in exhaust gas emissions of CO2,CO,NOx,P.M,and SO2by 276,2.32,18.87,0.825 and 3.84 tons,respectively.

Week Ahead Electricity Power and Price Forecasting Using Improved DenseNet-121 Method

In the Smart Grid(SG)residential environment,consumers change their power consumption routine according to the price and incentives announced by the utility,which causes the prices to deviate from the initial pattern.Thereby,electricity demand and price forecasting play a significant role and can help in terms of reliability and sustainability.Due to the massive amount of data,big data analytics for forecasting becomes a hot topic in the SG domain.In this paper,the changing and non-linearity of consumer consumption pattern complex data is taken as input.To minimize the computational cost and complexity of the data,the average of the feature engineering approaches includes:Recursive Feature Eliminator(RFE),Extreme Gradient Boosting(XGboost),Random Forest(RF),and are upgraded to extract the most relevant and significant features.To this end,we have proposed the DensetNet-121 network and Support Vector Machine(SVM)ensemble with Aquila Optimizer(AO)to ensure adaptability and handle the complexity of data in the classification.Further,the AO method helps to tune the parameters of DensNet(121 layers)and SVM,which achieves less training loss,computational time,minimized overfitting problems and more training/test accuracy.Performance evaluation metrics and statistical analysis validate the proposed model results are better than the benchmark schemes.Our proposed method has achieved a minimal value of the Mean Average Percentage Error(MAPE)rate i.e.,8%by DenseNet-AO and 6%by SVM-AO and the maximum accurateness rate of 92%and 95%,respectively.