An innovative option contract for allocating water in Inter-Basin Transfers: the case of the Tagus-Segura Transfer in Spain

The Tagus-Segura Transfer (TST), the largest water infrastructure in Spain, connects the Tagus basin’s headwaters and the Segura basin, one of the most water-stressed areas in Europe. The need to increase the minimum environmental flows in the Tagus River and to meet new urban demands has lead to the redefinition of the TST’s management rules, what will cause a reduction of transferable volumes to the Segura basin. After evaluating the effects of this change in the whole Tagus-Segura system, focusing on the availability of irrigation water in the Segura, the environmental flows in the Tagus and the economic impacts on both basins; we propose an innovative two-tranche option contract that could reduce the negative impacts of the modification of the Transfer’s management rule, and represents an institutional innovation with respect to previous inter-basin water trading. We evaluate this contract with respect to spot and non-market scenarios. Results show that the proposed contract would reduce the impact of a change in the transfer’s management rule on water availability in the recipient area

Optimal Burn-in Time and Imperfect Maintenance Strategy for a Warranted Product with Bathtub Shaped Failure Rate

‘Burn-in/preventive maintenance’ programme is an efficient approach used to minimise the warranty servicing cost of a product with bathtub shaped failure rate. Burn-in is a widely used method to improve the quality of product during its ‘infant mortality’ period and preventive maintenance is a scheduled necessary activity carried out during its ‘wear-out’ period. In this paper, an optimisation model is developed to determine the optimal burn-in time and optimal imperfect preventive maintenance strategy that minimises the total mean servicing cost of a warranted product with an age-dependent repair cost. We provide a numerical study to illustrate our results

Structural Health Monitoring (SHM) and Determination of Surface Defects in Large Metallic Structures using Ultrasonic Guided Waves

Ultrasonic guided wave (UGW) is one of the most commonly used technologies for non-destructive evaluation (NDE) and structural health monitoring (SHM) of structural components. Because of its excellent long-range diagnostic capability, this method is effective in detecting cracks, material loss, and fatigue-based defects in isotropic and anisotropic structures. The shape and orientation of structural defects are critical parameters during the investigation of crack propagation, assessment of damage severity, and prediction of remaining useful life (RUL) of structures. These parameters become even more important in cases where the crack intensity is associated with the safety of men, environment, and material, such as ship’s hull, aero-structures, rail tracks and subsea pipelines. This paper reviews the research literature on UGWs and their application in defect diagnosis and health monitoring of metallic structures. It has been observed that no significant research work has been convened to identify the shape and orientation of defects in plate-like structures. We also propose an experimental research work assisted by numerical simulations to investigate the response of UGWs upon interaction with cracks in different shapes and orientations. A framework for an empirical model may be considered to determine these structural flaws

Evaluation of Wind Resources and the Effect of Market Price Components on Wind-Farm Income: A Case Study of Ørland in Norway

This paper aims to present a detailed analysis of the performance of a wind-farm using the wind turbine power measurement standard IEC61400-12-1 (2017). Ten minutes averaged wind data are obtained from LIDAR over the period of twelve months and it is compared with the 38 years’ data from weather station with the objective of determining the wind resources at the wind-farm. The performance of one of the wind turbines located in the wind-farm is assessed by comparing the wind power potential of the wind turbine with its actual power production. Our analysis shows that the wind farm under study is rated as ‘good’ in terms of wind power production and has wind power density of 479 W/m2. The annual wind-farm’s income is estimated based on the real-data collected from the wind turbines. The effect of price of electricity and the spot prices of Norwegian-Swedish green certificate on the income will be illustrated by means of a Monte-Carlo Simulation (MCS) approach. Our study provides a different perspective of wind resource evaluation by analyzing LIDAR measurements using Windographer and combines it with the lesser explored effects of price components on the income using statistical tools

Wind Energy Development Site Selection Using an Integrated Fuzzy ANP-TOPSIS Decision Model

The identification of appropriate locations for wind energy development is a complex problem that involves several factors, ranging from technical to socio-economic and environmental aspects. Wind energy site selection is generally associated with high degrees of uncertainty due to the long planning, design, construction, and operational timescales. Thus, there is a crucial need to develop efficient methods that are capable of capturing uncertainties in subjective assessments provided by different stakeholders with diverse views. This paper proposes a novel multi-criteria decision model integrating the fuzzy analytic network process (FANP) and the fuzzy technique for order performance by similarity to ideal solution (TOPSIS) to evaluate and prioritize the potential sites for wind power development. Four major criteria, namely economic, social, technical, and geographical, with nine sub-criteria are identified based on consultation with wind farm investors, regulatory bodies, landowners and residents, developers and operators, component suppliers, ecologists, and GIS analysts. The stakeholders’ preferences regarding the relative importance of criteria are measured using a logarithmic least squares method, and then the alternative sites are prioritized based on their relative closeness to the positive ideal solution. The proposed model is applied to determine the most appropriate site for constructing an onshore wind power plant consisting of 10 wind turbines of 2.5 MW. Finally, the results are discussed and compared with those obtained using the traditional AHP, ANP and ANP-TOPSIS decision-making approaches

Corrosion Behaviour of Cupronickel 90/10 Alloys in Arabian Sea Conditions and its Effect on Maintenance of Marine Structures

The composition of seawater plays a very significant role in determining the severity of corrosion process in marine assets. The influential contributors to the general and pitting corrosions in marine structures include temperature, dissolved oxygen (DO), salinity, PH, chlorides, pollutants, nutrients, and microbiological activities in seawater. The Cu-Ni (90/10) alloy is increasingly used in marine applications such as heat exchangers and marine pipelines because of its excellent corrosion resistant properties. Despite the significant advancements in corrosion shielding procedures, complete stoppage of corrosion induced metal loss, especially under rugged marine environments, is practically impossible. The selection of appropriate metal thickness is merely a multifaceted decision because of the high variability in operating conditions and associated corrosion rate in various seawater bodies across the globe. The present research study aims to analyze the early phase of corrosion behavior of Cu-Ni (90/10) alloy in open-sea conditions as well as in pollutant-rich coastal waters of the Arabian Sea. Test samples were placed under natural climatic conditions of selected sites, followed by the mass loss and corrosion rate evaluation. The corrosion rate in the pollutant-rich coastal waters was around five times higher than in the natural seawater. A case study on marine condenser (fitted with of Cu-Ni 90/10 alloy tubes) is presented, and a risk-based inspection (RBI) plan is developed to facilitate equipment designers, operators, and maintainers to consider the implications of warm and polluted seawater on equipment reliability, service life, and subsequent health inspection/ maintenance

Joint Determination of Price and Upgrade Level for a Warranted Second-hand Product

An upgrade action is a pre-sale procedure that brings the second-hand item to an improved functional state and effectively reduces its age. This action is usually costly and adds directly to the sale price of the second-hand product, but it improves the product reliability and can reduce the warranty servicing cost. In the present paper, we propose a decision model to determine the optimal price and upgrade strategy of a warranted second-hand product to maximize the dealer's expected profit. The objective function includes both demand and cost functions, where purchase price from an end user, upgrade cost, and warranty cost are involved. We illustrate our finding using real data on second-hand electric device. Also, a sensitivity analysis is conducted to evaluate the effect of model parameters on the optimal solution

Developing a Trade-off between Upgrade Action Time and Warranty Length for Second-hand Electrical Components

One way of improving the reliability and reducing the warranty servicing cost for second-hand items is through actions such as overhaul and upgrade which are carried out by the dealer or a third party. For second-hand electrical components, the improvement involves testing of items for a short time, called upgrade action time, before their release to the market. The items that fail during the test are scrapped or repaired; only items that survive the test are considered to be of good quality and released to the market. In this paper, a cost model is developed to achieve a trade-off between reducing the warranty servicing cost and increasing the upgrade action cost for a second-hand electrical component sold under various warranty policies

Data Management for Structural Integrity Assessment of Offshore Wind Turbine Support Structures: Data Cleansing and Missing Data Imputation

Structural Health Monitoring (SHM) and Condition Monitoring (CM) Systems are currently utilised to collect data from offshore wind turbines (OWTs), to enhance the accurate estimation of their operational performance. However, industry accepted practices for effectively managing the information that these systems provide have not been widely established yet. This paper presents a four-step methodological framework for the effective data management of SHM systems of OWTs and illustrates its applicability in real-time continuous data collected from three operational units, with the aim of utilising more complete and accurate datasets for fatigue life assessment of support structures. Firstly, a time-efficient synchronisation method that enables the continuous monitoring of these systems is presented, followed by a novel approach to noise cleansing and the posterior missing data imputation (MDI). By the implementation of these techniques those data-points containing excessive noise are removed from the dataset (Step 2), advanced numerical tools are employed to regenerate missing data (Step 3) and fatigue is estimated for the results of these two methodologies (Step 4). Results show that after cleansing, missing data can be imputed with an average absolute error of 2.1%, while this error is kept within the [+ 15.2%−11.0%] range in 95% of cases. Furthermore, only 0.15% of the imputed data fell outside the noise thresholds. Fatigue is found to be underestimated both, when data cleansing does not take place and when it takes place but MDI does not. This makes this novel methodology an enhancement to conventional structural integrity assessment techniques that do not employ continuous datasets in their analyses