Abstract
The Reliability in a Sea of Risk project (RiaSoR) addresses the strategic need for the ocean energy industry to focus on the key engineering challenges that underpin the reliability and survivability of this emerging technology. The project will reduce these risks by developing industry approved reliability methodologies and testing practices which will be applied through the leading ocean energy testing houses to ensure consistency and robustness by which reliability is demonstrated across all wave and tidal technologies. This process will be used to de-risk the uncertainty of failures in the structural, electrical and connection elements of wave and tidal devices and allow more accurate predictions on the load variations they encounter. This reliability methodology is ultimately aimed at reducing Health Safety and Environmental (HSE) risks, technological risks, Operations and Maintenance (O&M) costs which will lower the Levelised Cost of Energy (LCoE) for the sector.
In today’s uncertain investment environment, the perception of technical risk is dependent on how confident the investors are that the ocean energy devices will perform reliably and produce the expected output for their devices. As the industry is approaching a pre-commercial stage, in sea testing and demonstration at various scales will be a primary focus for the sector over the next three to five years. This places a key role on the test houses to put in place a rigorous testing programme whereby the reliability of this emerging technology can be tested and independently verified before these systems move onto large scale array deployments.
A methodology is presented for working with reliability and robustness when developing Ocean Energy Devices, based on the Variation Mode and Effect Analysis (VMEA) methodology. For studying reliability regarding mechanical failure, the concept of load-strength interaction is useful. This means that the problem can be separated into studying a) the outer load acting on the structure to be designed and b) the strength, or resistance, of the structure. The aim is to design the structure to assure, with sufficient confidence, that the strength exceeds the load for future usage. Statistical methods provide useful tools for describing and quantifying the variability in load and strength. For this purpose the concept of VMEA will be used, which is a method aimed at guiding engineers to find critical areas in terms of the effects of unwanted variation. The VMEA method can be used as a reliability tool throughout the product development process. In the early design stage when only vague knowledge about the variation is available, the basic VMEA is used to compare different design concepts. Further in the design process, when better judgements of the sources of uncertainties are available, the enhanced VMEA is used, which is further developed into the probabilistic VMEA in the later design stages where more detailed information becomes available, and the goal is to verify the reliability targets and derive safety factors.
When using a life evaluation model, the uncertainty in the calculated life can thus be quantified using the VMEA method. The factors that cause the most uncertainty can be identified, thus guiding the design improvements to reduce the critical uncertainty, which will lead to more robust and optimized products. Further, it also allows proper safety factors to be established with regard to a required service life or strength. In operation of devices, the VMEA can be updated by condition monitoring data and can thus be a tool used in maintenance planning.
This reliability guidance transfers the experience of reliability and application of VMEA from automotive and aerospace industries to the ocean energy sector. The presented reliability methodology is described in view of the design criteria for marine energy converters, and the different phases of the VMEA methodology are explained in great detail. Further, the application of VMEA is detailed for structural, electrical and mooring/foundation elements of devices, each one exemplified by a case study.