This study provides an assessment of possible changes in the general circulation and residence time in the Persian Gulf under potential future sea-level rise and changes in the wind field due to the ...climate change. To determine the climate-change-induced impacts, Mike 3 Flow Model FM was used to simulate hydrodynamic and transport processes in the Persian Gulf in both historical (1998–2014) and future periods (2081–2100). Historical simulation was driven by ERA-Interim data. A statistical approach was employed to modify the values and directions of the future wind field obtained from the Representative Concentration Pathway 4.5 and 8.5 (RCP4.5 and RCP8.5, respectively) scenarios derived from CMCC-CM model of the fifth phase of the Coupled Model Intercomparison Project (CMIP5). The numerical model was calibrated and validated using measured data. Results indicated that in the historical period, residence time ranged between values of less than a month in the Strait of Hormuz and 10 years in the semi-enclosed area close to the south of Bahrain. The changes in wind field based on RCP 8.5 scenario were found to be the most disadvantageous for the Persian Gulf's capacity to flush dissolved pollutants out. Under this scenario, residence time would be 17% longer than that of historical one. This is mainly because the change in the wind field is large enough to overwhelm general circulation, showing a relationship between the residence time and the residual circulation. Impact of change in the wind field according to RCP 4.5 scenario on the modeled residence time is negligible. The numerical outputs also showed that the sea-level rise would slightly decrease the current velocity, resulting in a negligible increase in residence time. The findings of this study are intended to support establishing climate-adaptation management plans for coastal zones of the studied area in line with sustainable development goals.
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•Climate change effects on the physical processes in the Persian Gulf were assessed.•A numerical model was used to determine the residence time and general circulation.•Sea-level rise is projected to have a negligible impact on the residence time.•Changes in wind speed and direction are likely to increase the residence time.•Wind changes would have a greater effect on the circulation than sea-level rise.
Estimation of the variability in the electrical power production and performance over the life-time of wave energy converters (WEC) is paramount for the economic viability of potential wave farm ...projects. In this research, the significance of the inter-annual variability in the potential production performance (PPP) is demonstrated, using power conversion matrices of ten pre-commercial WEC devices and an existing 31-year wave hindcast case study from the central shelf of New South Wales, Australia. The variability in the PPP over the intra- and inter-annual time scales is found to be comparable, hence indicating that making predictions merely based on annual and monthly averages could be misleading and that inter-annual fluctuations should be considered in future analysis. The results also show that inter-annual variations in WEC production performance can be significantly higher than that of the wave energy resource (WER) owing to the efficiency of different WECs relative to the local sea state conditions. We also demonstrate that optimization of WEC performance for the local sea state cannot only potentially lead to improved power yields but also a decrease in the intra- and inter-annual variability in PPP.
This study aims to evaluate the wave energy potential and its spatial and temporal variations in the southern Caspian Sea. For this purpose, SWAN model was used to hindcast wave characteristics for ...11 years. The wave energy assessment was conducted in four nearshore stations in order to assess the feasibility of wave energy harvesting and locate the most appropriate station. Assessment of seasonal and monthly variations of the mean and maximum wave powers showed that the central station contains the highest values, especially in November; while the north-eastern station has the lowest values with the highest variation of directional distribution of the wave power. Moreover, the seasonal and monthly variability indices indicate a relatively stable wave condition in all stations. The total and exploitable storages of wave energy were also higher in the central station. Therefore, it was concluded that the central station is the most appropriate location for wave energy harvesting. Furthermore, the inter-annual variations of the mean wave power illustrate no significant long-term change in wave power in the southern Caspian Sea. Therefore, considering the relatively stable condition and comparable exploitable storage of wave energy, this area can be a suitable location for developers.
•Wave energy was assessed in the Southern Caspian Sea using numerical modeling.•Spatial and temporal variation of the wave power was investigated.•Seasonal and monthly variations of wave power were assessed in nearshore stations.•Total and exploitable storages of wave energy were obtained in selected stations.•Inter-annual variations in wave power showed no significant change in all stations.
Growing energy demand worldwide and onshore limitations have increased interest in offshore renewable energy exploitation. A combination of offshore renewable energy resources such as wind and wave ...energy can produce stable power output at a lower cost compared to a single energy source. Consequently, identifying the best locations for constructing combined offshore renewable energy farms is crucial. This paper investigates the technical, economic, social, and environmental aspects of Combined Offshore Wind and Wave Energy Farm (COWWEF) site selection. Past literature was evaluated using a systematic review method to synthesize, criticize, and categorize study regions, dataset characteristics, constraints, evaluation criteria, and methods used for the site selection procedure. The results showed that most studied regions belong to European countries, and numerical model outputs were mainly used in the literature as met-ocean data due to the limited coverage and low spatiotemporal resolution of buoy and satellite observations. Environmental and marine usage are the main constraints in the site selection process. Among all constraints, shipping lanes, marine protected areas, and military exercise areas were predominately considered to be excluded from the potential sites for COWWEF development. The technical viability and economic feasibility of project deployment are emphasized in the literature. Resource assessment and distance to infrastructures were mostly evaluated among techno-economic criteria. Wind and wave energy power are the most important criteria for evaluating feasibility, followed by water depth, indicators of variability and correlation of the energy resources, and distance to the nearest port. Multi-Criteria Decision-Making (MCDM) methods and resource-based analysis were the most-used evaluation frameworks. Resource-based studies mainly used met-ocean datasets to determine site technical and operational performance (i.e., resource availability, variability, and correlation), while MCDM methods were applied when a broader set of criteria were evaluated. Based on the conducted review, it was found that the literature lacks evaluation of seabed conditions (seabed type and slope) and consideration of uncertainty involved in the COWWEF site selection process. In addition, the market analysis and evaluation of environmental impacts of COWWEF development, as well as impacts of climate change on combined exploitation of offshore wind and wave energy, have rarely been investigated and need to be considered in future studies. Finally, by providing a comprehensive repository of synthesized and categorized information and research gaps, this study represents a road map for decision-makers to determine the most suitable locations for COWWEF developments.
This study aims to assess the wave energy at five coastal stations in the Gulf of Oman using the time series of locally generated wind waves obtained by numerical modeling for 11 years. For this ...purpose, the spatial, seasonal, monthly, directional, inter-annual of wave energy and power were investigated. The spatial distribution shows that the wave power increases towards the Indian Ocean and the highest mean wave power is located at the eastern station in all seasons. In addition, monthly mean wave power is highest during July and August while the monthly maximum wave power is highest during February at all stations. The ratio of monthly maximum to mean wave power is also the lowest during May to August. Moreover, Monthly Variability Index is the highest in west of the domain where there is no significant wave power potential. In addition, annual wave power as well as total and exploitable wave energies increases from west to east, where the dominant waves propagate from the south, and the exploitable wave energy is approximately 20 times greater than of the central stations.
•The wave energy was assessed at five coastal stations in the Gulf of Oman.•The spatial, temporal, directional and storage of wave energy were investigated.•The ratio of monthly maximum to mean wave power is the lowest during May to August.•The highest annual wave power exists in the eastern station almost in all years.•Both the total and exploitable wave energies increase from west to east.
An important issue in application of fuzzy inference systems (FISs) to a class of system identification problems such as prediction of wave parameters is to extract the structure and type of fuzzy ...if–then rules from an available input–output data set. In this paper, a hybrid genetic algorithm–adaptive network-based FIS (GA–ANFIS) model has been developed in which both clustering and rule base parameters are simultaneously optimized using GAs and artificial neural nets (ANNs). The parameters of a subtractive clustering method, by which the number and structure of fuzzy rules are controlled, are optimized by GAs within which ANFIS is called for tuning the parameters of rule base generated by GAs. The model has been applied in the prediction of wave parameters, i.e. wave significant height and peak spectral period, in a duration-limited condition in Lake Michigan. The data set of year 2001 has been used as training set and that of year 2004 as testing data. The results obtained by the proposed model are presented and analyzed. Results indicate that GA–ANFIS model is superior to ANFIS and Shore Protection Manual (SPM) methods in terms of their prediction accuracy.
Abstract
The accurate prediction of the mean wave overtopping rate at breakwaters is vital for a safe design. Hence, providing a robust tool as a preliminary estimator can be useful for ...practitioners. Recently, soft computing tools such as artificial neural networks (ANN) have been developed as alternatives to traditional overtopping formulae. The goal of this paper is to assess the capabilities of two kernel-based methods, namely Gaussian process regression (GPR) and support vector regression for the prediction of mean wave overtopping rate at sloped breakwaters. An extensive dataset taken from the EurOtop database, including rubble mound structures with permeable core, straight slopes, without berm, and crown wall, was employed to develop the models. Different combinations of the important dimensionless parameters representing structural features and wave conditions were tested based on the sensitivity analysis for developing the models. The obtained results were compared with those of the ANN model and the existing empirical formulae. The modified Taylor diagram was used to compare the models graphically. The results showed the superiority of kernel-based models, especially the GPR model over the ANN model and empirical formulae. In addition, the optimal input combination was introduced based on accuracy and the number of input parameters criteria. Finally, the physical consistencies of developed models were investigated, the results of which demonstrated the reliability of kernel-based models in terms of delivering physics of overtopping phenomenon.
With the merit on representing traffic conflict through examining the crash mechanism and causality proactively, crash surrogate measures have long been proposed and applied to evaluate the traffic ...safety. However, the driver's Perception-Reaction Time (PRT), an important variable in crash mechanism, has not been considered widely into surrogate measures. In this regard, it is important to know how the PRT affects the performances of surrogate indicators. To this end, three widely used surrogate measures are firstly modified by involving the PRT into their crash mechanisms. Then, in order to examine the difference caused by the PRT, a comparative study is carried out on a freeway section of the Pacific Motorway, Australia. This result suggests that the surrogate indicators' performances in representing rear-end crash risks are improved with the incorporating of the PRT for the investigated section.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Wave energy converters (WECs) can play a significant role in the transition towards a more renewable-based energy mix as stable and unlimited energy resources. Financial analysis of these projects ...requires WECs cost and WEC capital expenditure (CapEx) information. However, (i) cost information is often limited due to confidentiality and (ii) the wave energy field lacks flexible methods for cost breakdown and parameterisation, whereas they are needed for rapid and optimised WEC configuration and worldwide site pairing. This study takes advantage of the information provided by Wavepiston to compare different costing methods. The work assesses the Froude-Law-similarities-based “Similitude method” for cost-scaling and introduces the more flexible and generic “CapEx method” divided into three steps: (1) distinguishing WEC’s elements from the wave energy farm (WEF)’s; (2) defining the parameters characterising the WECs, WEFs, and site locations; and (3) estimating elements that affect WEC and WEF elements’ cost and translate them into factors using the parameters defined in step (2). After validation from Wavepiston manual estimations, the CapEx method showed that the factors could represent up to 30% of the cost. The Similitude method provided slight cost-overestimations compared to the CapEx method for low WEC up-scaling, increasing exponentially with the scaling.
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