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Blades are one of the most important components, in terms of capital and operational costs, of wind turbines. In contrast with some other elements of the turbine, the knowledge regarding the failure modes and processes of the composite materials that form the blade are less known. Therefore, providing a systematic study breaking down the individual components of the blade and analyzing the criticality of each of the failure modes affecting them is the first step toward the implementation of measures reducing operational and maintenance costs. The scarce information that is publicly available regarding wind turbine blade failures and their constant evolution inclines risk analysis toward studies based on expert opinion. In this study, the criticality of the failure modes is determined through a failure mode and effects analysis (FMEA) that examines the severity and likelihood of occurrence of the failure modes identified. In light of the results of criticality, the current and potential maintenance strategies covering the different failure modes will be identified, along with the applicable monitoring techniques found in the literature, to propose risk mitigation strategies. The results of this study may be utilized for further exploration of operation and maintenance analysis toward the development of dynamic decision support systems.

We introduce IMP-MARL, an open-source suite of multi-agent reinforcement learning (MARL) environments for large-scale Infrastructure Management Planning (IMP), offering a platform for benchmarking the scalability of cooperative MARL methods in real-world engineering applications. In IMP, a multi-component engineering system is subject to a risk of failure due to its components' damage condition. Specifically, each agent plans inspections and repairs for a specific system component, aiming to minimise maintenance costs while cooperating to minimise system failure risk. With IMP-MARL, we release several environments including one related to offshore wind structural systems, in an effort to meet today's needs to improve management strategies to support sustainable and reliable energy systems. Supported by IMP practical engineering environments featuring up to 100 agents, we conduct a benchmark campaign, where the scalability and performance of state-of-the-art cooperative MARL methods are compared against expert-based heuristic policies. The results reveal that centralised training with decentralised execution methods scale better with the number of agents than fully centralised or decentralised RL approaches, while also outperforming expert-based heuristic policies in most IMP environments. Based on our findings, we additionally outline remaining cooperation and scalability challenges that future MARL methods should still address. Through IMP-MARL, we encourage the implementation of new environments and the further development of MARL methods.

Rumor has it that all technologies needed to build energy islands are ready. Wind turbines are spinning in many large offshore parks, while combinations of sand and concrete have given birth to several entirely new islands. However, not all rumors are true. Not only has the Danish parliament mandated the largest ever infrastructure project in the history of our country. The first Danish artificial island built for energy production will also become the world’s largest renewable energy project. On top of the technical and logistical challenges associated with building something of an unprecedented scale and nature come new concerns. The energy islands are an extreme version of the power system we know today, and therefore represent a Mars mission for the energy system. More than once have large infrastructure projects been plagued by delays and significant additional costs. Often such problems have been rooted in overly optimistic planning, limited knowledge regarding the complexity and interdependencies involved, and not giving enough attention to the development phase relative to the construction phase. For many reasons, it is highly desirable for the energy island projects to perform well. Therefore, we have teamed up to map the key challenges and suggest R&D initiatives to address them. Importantly, these initiatives are not intended as an inserted step before construction. Given the urgency in green transition and ending the reliance on fossil fuels, research and construction must be conducted in parallel. A solid foundation for energy islands On the following pages we invite you to delve into the complexity of constructing and operating offshore hubs for renewable energy. As you will hopefully agree, we are by no means saying that it cannot be done. It can. But only if decisions are based on a solid foundation of knowledge.

To become more competitive, less dependent on financial support and more attractive for investors, wind energy needs to reduce its final cost of energy. According to Levelized Cost of Energy, there are two ways to achieve this goal, by reducing costs or increasing production. Overall Equipment Effectiveness (OEE) is a widely used metric in manufacturing systems, supporting operators to enhance productivity by reducing operational losses. Therefore, this study aims to perform a qualitative literature review of the main operational losses following the OEE metric, namely availability, performance and quality, adjusting it to wind energy systems. Introduction of this metric can be a valuable tool towards an integrated indicator linking production and losses, allowing comparison between assets deployed in different settings.

Breaking the curse of small datasets in machine learning is but one of the major challenges that cause several real-life prediction problems. In offshore wind application, for instance, this issue presents when monitoring an asset in an attempt to reduce its infant mortality failures. Another challenge could emerge when reducing the number of sensors installed in order to limit the investment in monitoring systems. To tackle these issues, the aim of this article is to investigate the impact of small data-set on conventional machine learning methods, and to outline the improvement achievable by the implementation of transfer learning approach. It provides a solution to mitigate this issue by applying a hard parameter multi-task learning approach to the supervisory control and data acquisition data from an operational wind turbine, allowing for smaller datasets to efficiently predict the status of the gearbox’s vibration data. Two experiments are carried out in this paper. The first is to envisage the possibility of using hard parameter transfer on the operational data from two wind turbines. The second is to compare the results of this model to the findings from a conventional deep neural network model trained on the data from a single turbine.

This paper documents the development of an integrated approach for the development of effective maintenance strategies for offshore wind energy assets, based on a risk-based approach.

Highlights • Co-combustion analysis was investigated using a bench-scale combustor test rig. • Raw human faeces (FC) contained 73.9 ± 4.4 wt% moisture as received basis. • Blending with wood dust (WD) in a 50:50 ratio reduced moisture levels by ∼40%. • Minimum acceptable blend for combustion without prior drying is 30:70 WD:FC. • Fuel burn rates are 3.18–4.49 g/min for all the blends at air flow of 12–18 L/min. • Oxygen, potassium and calcium are the most abundant elements in faecal ash., Fuel blending is a widely used approach in biomass combustion, particularly for feedstocks with low calorific value and high moisture content. In on-site sanitation technologies, fuel blending is proposed as a pre-treatment requirement to reduce moisture levels and improve the physiochemical properties of raw faeces prior to drying. This study investigates the co-combustion performance of wood dust: raw human faeces blends at varying air-to-fuel ratios in a bench-scale combustor test rig. It concludes with ash composition analyses and discusses their potential application and related problems. The study shows that a 50:50 wood dust (WD): raw human faeces (FC) can reduce moisture levels in raw human faeces by ∼40% prior to drying. The minimum acceptable blend for treating moist faeces without prior drying at a combustion air flow rate of 14–18 L/min is 30:70 WD: FC. For self-sustained ignition and flame propagation, the minimum combustion temperature required for conversion of the fuel to ash is ∼400 °C. The most abundant elements in faecal ash are potassium and calcium, while elements such as nickel, aluminium and iron are in trace quantities. This suggests the potential use of faecal ash as a soil conditioner, but increases the tendency for fly ash formation and sintering problems.

Presentation for the ROMEO Symposium organized in the frame of the Wind Energy Science Conference (WESC)

The “Reinvent the Toilet Challenge” set by the Bill & Melinda Gates Foundation aims to bring access to adequate sanitary systems to billions of people. In response to this challenge, on-site sanitation systems are proposed and being developed globally. These systems require in-situ thermal treatment, processes that are not well understood for human faeces (HF). Thermogravimetric analysis has been used to investigate the pyrolysis, gasification and combustion of HF. The results are compared to the thermal behaviour of simulant faeces (SF) and woody biomass (WB), along with the blends of HF and WB. Kinetic analysis was conducted using non-isothermal kinetics model-free methods, and the thermogravimetric data obtained for the combustion of HF, SS and WB. The results show that the devolatilisation of HF requires higher temperatures and rates are slower those of WB. Minimum temperatures of 475 K are required for fuel ignition. HF and SF showed similar thermal behaviour under pyrolysis, but not under combustion conditions. The activation energy for HF is 157.4 kJ/mol, relatively higher than SS and WB. Reaction order for HF is lower (n = 0.4) to WB (n = 0.6). In-situ treatment of HF in on-site sanitary systems can be designed for slow progressive burn.

In many developing countries, including South Africa, water scarcity has resulted in poor sanitation practices. The majority of the sanitation infrastructures in those regions fail to meet basic hygienic standards. This along with the lack of proper sewage/wastewater infrastructure creates significant environmental and public health concerns. A self-sustained, waterless “Nano Membrane Toilet” (NMT) design was proposed as a result of the “Reinvent the Toilet Challenge” funded by the Bill and Melinda Gates Foundation. A “cradle-to-grave” life cycle assessment (LCA) approach was adopted to study the use of NMT in comparison with conventional pour flush toilet (PFT) and urine-diverting dry toilet (UDDT). All three scenarios were applied in the context of South Africa. In addition, a Quantitative Microbial Risk Assessment (QMRA) was used to reflect the impact of the pathogen risk on human health. LCA study showed that UDDT had the best environmental performance, followed by NMT and PFT systems for all impact categories investigated including human health, resource and ecosystem. This was mainly due to the environmental credits associated with the use of urine and compost as fertilizers. However, with the incorporation of the pathogen impact into the human health impact category, the NMT had a significant better performance than the PFT and UDDT systems, which exhibited an impact category value 4E + 04 and 4E + 03 times higher, respectively. Sensitivity analysis identified that the use of ash as fertilizer, electricity generation and the reduction of NOx emissions were the key areas that influenced significantly the environmental performance of the NMT system.

An extensive literature research has been conducted to create an insight into the existing norms and standards regulating the assessment of human exposure to motions in offshore environments. A summary of current threshold values and their specific fields of application is included. The presented literature is analysed with respect to their applicability for assessing low frequency oscillatory motions of floating offshore wind turbines to which technicians are exposed during maintenance tasks. The review identifies the need for a consistent assessment method in combination with threshold values for floating structures.

Highlights • A probabilistic model is developed to assess the performance of an NMT. • Energy and environmental performance uncertainties of the system are qualified. • A realistic prediction of the energy and environmental performance of the system. • Probabilistic approach can be applied in other complex engineering systems., A probabilistic modelling approach was developed and applied to investigate the energy and environmental performance of an innovative sanitation system, the “Nano-membrane Toilet” (NMT). The system treats human excreta via an advanced energy and water recovery island with the aim of addressing current and future sanitation demands. Due to the complex design and inherent characteristics of the system’s input material, there are a number of stochastic variables which may significantly affect the system’s performance. The non-intrusive probabilistic approach adopted in this study combines a finite number of deterministic thermodynamic process simulations with an artificial neural network (ANN) approximation model and Monte Carlo simulations (MCS) to assess the effect of system uncertainties on the predicted performance of the NMT system. The joint probability distributions of the process performance indicators suggest a Stirling Engine (SE) power output in the range of 61.5–73 W with a high confidence interval (CI) of 95%. In addition, there is high probability (with 95% CI) that the NMT system can achieve positive net power output between 15.8 and 35 W. A sensitivity study reveals the system power performance is mostly affected by SE heater temperature. Investigation into the environmental performance of the NMT design, including water recovery and CO2/NOx emissions, suggests significant environmental benefits compared to conventional systems. Results of the probabilistic analysis can better inform future improvements on the system design and operational strategy and this probabilistic assessment framework can also be applied to similar complex engineering systems.

This article describes the design and commissioning of a micro-combustor for energy recovery from human faeces, which can operate both in updraft and downdraft modes. Energy recovery from faecal matter via thermochemical conversion has recently been identified as a feasible solution for sanitation problems in low income countries and locations of high income countries where access to sewage infrastructures is difficult or not possible. This technology can be applied to waterless toilets with the additional outcome of generating heat and power that can be used to pre-treat the faeces before their combustion and to ensure that the entire system is self-sustaining. The work presented here is framed within the Nano Membrane Toilet (NMT) project that is being carried out at Cranfield University, as part of the Reinvent the Toilet Challenge of the Bill and Melinda Gates Foundation. For this study, preliminary trials using simulant faeces pellets were first carried out to find out the optimum values for the main operating variables at the scale required by the process, i.e. a fuel flowrate between 0.4 and 1.2 g/min of dry faeces. Parameters such as ignition temperature, residence time, and maximum temperature reached, were determined and used for the final design of the bench-scale combustor prototype. The prototype was successfully commissioned and the first experimental results, using real human faeces, are discussed in the paper.

Concern for load analysis and structural design of offshore renewable energy devices. Attention shall be given to the interaction between the load and structural response of fixed and floating installations taking due consideration of the stochastic nature of the ocean environment. Aspects related to prototype testing, certification, marine operations and total cost of energy shall be considered. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non- Commercial License 4.0 (CC BY-NC 4.0)

Offshore structures are generally fabricated of welded joints, which are considered as potential spots for crack initiation owing to the degree of stress concentrations imposed by the weld geometry and the effects of residual stresses introduced by welding processes. There are significant numbers of the current and anticipated offshore installations coupled with the use of newer materials and fabrication techniques. It is therefore important to understand the crack growth mechanisms in these structures accompanied with the effects of mean or residual stresses for a safe estimation of their service lives. In this paper, crack growth results of HAZ and weld materials similar to those used for offshore installations are presented. Tests were conducted in air and in simulated free-corrosion conditions at loading frequencies of 0.3 Hz in seawater, 5 Hz in air and at loading ratios of 0.1, 0.5 and 0.7. Results showed that crack growth rates were influenced by mean stresses, materials microstructure accompanied by welding procedure and environment. Crack growth results showed good agreement when compared with those obtained from other steels used for offshore structures.

Offshore wind turbine reliability, one of the industry's biggest sources of uncertainty, is the focus of the present paper. Specifically the impact of uncertain component failure distributions at constant failure rates has been investigated with respect to its implications for wind farm availability. A fully probabilistic offshore wind simulation model has been applied to quantify results; effects shown in this paper underline the significant impact that failure probability distributions have on asset performance evaluation. It was found that wind farm availability numbers may vary in the range up to 20 % just by changing the distributions of failure to a different pattern; in particular those scenarios in which extensive failure accumulation occurred led to significant losses in production. Results are interpreted and discussed mainly from the viewpoint of an offshore wind farm developer, owner and operator, with implications underlined for application in state-of-the-art offshore wind O&M (Operations and Maintenance) models and simulation tools.

Poor sanitation is one of the major hindrances to the global sustainable development goals. The Reinvent the Toilet Challenge of the Bill and Melinda Gates Foundation is set to develop affordable, next-generation sanitary systems that can ensure safe treatment and wide accessibility without compromise on sustainable use of natural resources and the environment. Energy recovery from human excreta is likely to be a cornerstone of future sustainable sanitary systems. Faeces combustion was investigated using a bench-scale downdraft combustor test rig, alongside with wood biomass and simulant faeces. Parameters such as air flow rate, fuel pellet size, bed height, and fuel ignition mode were varied to establish the combustion operating range of the test rig and the optimum conditions for converting the faecal biomass to energy. The experimental results show that the dry human faeces had a higher energy content (∼25MJ/kg) than wood biomass. At equivalence ratio between 0.86 and 1.12, the combustion temperature and fuel burn rate ranged from 431 to 558°C and 1.53 to 2.30g/min respectively. Preliminary results for the simulant faeces show that a minimum combustion bed temperature of 600±10°C can handle faeces up to 60wt.% moisture at optimum air-to-fuel ratio. Further investigation is required to establish the appropriate trade-off limits for drying and energy recovery, considering different stool types, moisture content and drying characteristics. This is important for the design and further development of a self-sustained energy conversion and recovery systems for the NMT and similar sanitary solutions.

With about 2.4 billion people worldwide without access to improved sanitation facilities, there is a strong incentive for development of novel sanitation systems to improve the quality of life and reduce mortality. The Nano Membrane Toilet is expected to provide a unique household-scale system that would produce electricity and recover water from human excrement and urine. This study was undertaken to evaluate the performance of the conceptual energy and water recovery system for the Nano Membrane Toilet designed for a household of ten people and to assess its self-sustainability. A process model of the entire system, including the thermochemical conversion island, a Stirling engine and a water recovery system was developed in Aspen Plus®. The energy and water recovery system for the Nano Membrane Toilet was characterised with the specific net power output of 23.1Wh/kgsettledsolids and water recovery rate of 13.4dm3/day in the nominal operating mode. Additionally, if no supernatant was processed, the specific net power output was increased to 69.2Wh/kgsettledsolids. Such household-scale system would deliver the net power output (1.9–5.8W). This was found to be enough to charge mobile phones or power clock radios, or provide light for the household using low-voltage LED bulbs.

Offshore Wind has become the most profitable renewable energy source due to the remarkable development it has experienced in Europe over the last decade. In this paper, a review of Structural Health Monitoring Systems (SHMS) for offshore wind turbines (OWT) has been carried out considering the topic as a Statistical Pattern Recognition problem. Therefore, each one of the stages of this paradigm has been reviewed focusing on OWT application. These stages are: Operational Evaluation; Data Acquisition, Normalization and Cleansing; Feature Extraction and Information Condensation; and Statistical Model Development. It is expected that optimizing each stage, SHMS can contribute to the development of efficient Condition-Based Maintenance Strategies. Optimizing this strategy will help reduce labor costs of OWTs׳ inspection, avoid unnecessary maintenance, identify design weaknesses before failure, improve the availability of power production while preventing wind turbines׳ overloading, therefore, maximizing the investments׳ return. In the forthcoming years, a growing interest in SHM technologies for OWT is expected, enhancing the potential of offshore wind farm deployments further offshore. Increasing efficiency in operational management will contribute towards achieving UK׳s 2020 and 2050 targets, through ultimately reducing the Levelised Cost of Energy (LCOE).

This paper documents the methodology and presents the results of a comprehensive LCA study of an Airbus A320 commercial airliner to determine the relative environmental impact of its manufacturing phase. The study was conducted in accordance with ISO 14040/44 using SimaPro LCA software, the EcoInvent inventory database and Eco-Indicator 99 weighting method, which allows the analysis to be outputted in a single score representing a number of damage models including damage to human health, ecosystem quality or resource depletion. Results indicate CFRP wings to have the most significant contribution to the overall environmental impact as a proportion to mass.

Currently, cutting tool life for machining operations is correlated to process parameters through the widely applied Taylor functions. The latter are valuable expressions in established practice however their generalised nature does not allow accurate prediction of the tool’s service life or optimization of the manufacturing process due to effects of uncertainties in various input variables. These variables should be treated in a stochastic way in order to avoid employment of safety factors for quantification of uncertainty. This paper documents a procedure that allows derivation of analytical expressions for cutting tools performance employing advanced approximation methods and concepts of reliability analysis. Due to the complexity of manufacturing processes surrogate modelling (SM) methods are applied, starting from a few sample points obtained through lab or soft experiments and extending them to models able to predict/estimate the values of control values/indicators as a function of the key design variables, often referred to as limit states.

As part of the transition to a ‘low carbon economy', renewable technologies are expected toplay an increasing role in reducing dependence on fossil fuels for energy and electricity. Windpower in particular is likely to become a much larger contributor to the UK's energy mix. Thecurrent dominant design for large, grid-connected wind turbines is a three blade rotor with ahorizontal rotating axis. The concept of a vertical axis wind turbine (VAWT) is relatively new, buthas several advantages over horizontal axis alternatives. It is able to capture the wind from anydirection, and the vertical axis is such that the rotor equipment is located at base level, makingit is simpler and less costly to install and maintain. The Energy Technologies Institute (ETI) is a UK-based company formed from global industriesand the UK government. One of three projects looking at new turbine design and concepts foroffshore wind is the Novel Offshore Vertical Axis (NOVA) project, a UK-based consortiumlaunched in January 2009 to look at the feasibility of a NOVA turbine. achieved through the installation of NOVA wind turbines, in comparison to conventionalhorizontal axis wind turbines (HAWTs) for offshore power generation. The increased powerrating of the NOVA turbines compared to current HAWTs is expected to provide considerablereductions in lifetime greenhouse gas emissions. It compared the emissions from 1 GWinstallations over 20 years, based on a life cycle analysis of construction, operation anddisposal. The comparison used the popular Vestas V90 3 MW model and the proposed NOVA10 MW units. The estimated lifetime emissions were 521 kt CO2e for the conventional design and419 kt CO2e for NOVA. Using budget share to attribute the reductions to the project partners,Cranfield's brainprint was 34 kt CO2e. As there are no current NOVA units in operation, there were high uncertainties associated withthe estimates. A Monte-Carlo simulation resulted in a mean difference in emissions betweenthe two installations of 102 kt CO2e, with a standard deviation of 108.

Offshore wind turbines are developing at a rapid pace. By far the most common turbine configuration is the HAWT (Horizontal Axis Wind Turbine) and development of these machines is largely centered about drive train and blade issues with some work concerning foundations/ supporting structures. Several teams around the world are developing floating supporting structures for HAWT, mainly for deep water deployment. This paper describes the development of a floating support structure for Vertical Axis Wind Turbines (VAWT) with particular focus on structural/survival risk and reliability. Unlike Oil & Gas floating support structures, wind turbine floaters need to resist significant dynamic wind and machine loading in addition to wave excitation. Coupling of dynamic response modes can be difficult and consideration of these within a reliability framework presents several challenges. The paper describes a simplified procedure for risk assessment so that potential areas of concern can be quickly identified and uses a VAWT to illustrate the methods and reasoning employed.

Structural Reliability treats uncertainties in structural design systematically, evaluating the levels of safety and serviceability of structures. During the past decades, it has been established as a valuable design tool for the description of the performance of structures, and lately stands as a basis in the background of the most of the modern design standards, aiming to achieve a uniform behaviour within a class of structures. Several methods have been proposed for the estimation of structural reliability, both deterministic (FORM and SORM) and stochastic (Monte Carlo Simulation etc) in nature. Offshore structures should resist complicated and, in most cases, combined environmental phenomena of greatly uncertain magnitude (eg. wind, wave, current, operational loads etc). Failure mechanisms of structural systems and components are expressed through limit state functions, which distinguish a failure and a safe region of operation. For a jacket offshore structure, which comprises of multiple tubular members interconnected in a three dimensional truss configuration, the limit state function should link the actual load or load combination acting on it locally, to the response of each structural member. Cont/d.

Presentation in the framework of WindEurope Offshore 2019 – Session "Digitalization concepts to optimize O&M strategies in Offshore Wind Energy"

Presentation in the framework of WindEurope Offshore 2019 –Session "Digitalization concepts to optimize O&M strategies in Offshore Wind Energy"

Presentation for the ROMEO Symposium organized in the frame of the Wind Energy Science Conference (WESC)

The IEC standard 61400 − 12 − 1 recommends a reliable and repeatable methodology called ‘binning’ for accurate computation of wind turbine power curves that recognise only the mean wind speed at hub height and the air density as relevant input parameters. However, several literature studies have suggested that power production from a wind turbine also depends significantly on several operational variables (such as rotor speed and blade pitch angle) and incorporating these could improve overall accuracy and fault detection capabilities. In this study, a Gaussian Process (GP), a machine learning, data-driven approach, based power curve models that incorporates these operational variables are proposed in order to analyse these variables impact on GP models accuracy as well as uncertainty. This study is significant as it find out key variable that can improve GP based condition monitoring activities (e.g., early failure detection) without additional complexity and computational costs and thus, helps in maintenance decision making process. Historical 10-minute average supervisory control and data acquisition (SCADA) datasets obtained from variable pitch regulated wind turbines, are used to train and validate the proposed research effectiveness. The results suggest that incorporating operational variables can improve the GP model accuracy and reduce uncertainty significantly in predicting a power curve. Furthermore, a comparative study shows that the impact of rotor speed on improving GP model accuracy is significant as compared to the blade pitch angle. Performance error metrics and uncertainty calculations are successfully applied to confirm all these conclusions.

Condition-based maintenance is applied in various industries to monitor and control critical assets and to optimize maintenance efforts. Its applicability to the offshore wind energy industry has been considered for almost 20 years and has resulted in the development and implementation of solutions that have contributed to lower cost of maintenance and increased asset availability. However, there is currently no public domain guidance available that provides the information required to (i) prioritize systems for which condition monitoring would generate highest value and to (ii) understand the parameters that need to be monitored by a specific system from failure cause to failure mode. Both items are addressed in this paper, providing a clearly structured, risk-based assessment methodology and corresponding results for state-of-the-art offshore wind turbines. A total of 337 failure modes have been identified and analysed by experts representing approximately 70% of the European offshore wind market to assess potential benefits of condition monitoring systems. Results may be used to target the development of condition monitoring systems focusing on critical systems and to find optimal O&M strategies by understanding failure paths of main offshore wind turbine systems resulting in a lower cost of energy and a more optimal risk-return balance.

This thesis contributes to the significant portfolio of research on carbon capture and storage (CCS) in general, and the potential for CO₂ storage with impurities within the UK Southern North Sea (UKSNS) to meet the global greenhouse gas emission reduction targets. First, this thesis extensively reviews the current developments in carbon dioxide storage, highlighting major options for CO₂ sequestration, storage site evaluation criteria, behaviour of CO₂ in the reservoir, methodologies for estimating storage capacity, appraisal of the major storage projects, and a projection of the future outlook for CO₂ storage. The review draws attention to the fact that although a high-quality knowledge base has been developed through CCS research, the main hinderance to CO₂ storage deployment is associated with public acceptability of the technology. Second, this thesis involves laboratory experimental investigation of the effect of impure CO₂ on reservoir grain size distributions and permeability using rock samples from the Bunter saline aquifer. The thesis shows that the presence of impurities in the CO₂ stream can affect the grain size distribution and fluid transmissivity. Third, this thesis uses numerical modelling to evaluate the effect of impure CO₂ on reservoir performance with a case study from the Bunter saline aquifer. The results show that depending on the impurities present in the CO₂ stream, the limits of stability during storage operations in saline aquifer varies, however, the variation does not affect reservoir performance negatively during long-term injection and storage.

The wind industry is determined to lower the costs of producing energy in all phases of the offshore wind project. During 2015–2016, projects achieved a levelized cost of energy (LCOE) of £97 and more recently it was announced that Ørsted guaranteed £57.5/MWh. Significant price increases on structural materials directly impact on larger scale wind projects, the overall cost of turbines, establishing effective supply chains, improving the consent procedures for new developments, governmental mechanisms and support, improving grid connections and finally reducing overall uncertainty and costs etc. The most important decisions at the planning stage of new investment are the selection of a profitable, cost-effective suitable offshore location and a support structure type, which greatly impact on the overall Life Cycle Costs (LCC). This research aims to introduce and apply a scalable framework to reveal and select the optimal offshore location deployment and support structure in Round 3 zones in the UK by considering the interplay of LCC aspects at the planning stage of development. This research produced a portfolio of five studies while developing the framework above. First, a comparative Political Economic Social Technological Legal Environmental (PESTLE) analysis on wind energy was performed. The analysis focused on Europe, Germany, the UK and Greece, where the UK was selected in this research as the world leader in offshore wind energy. Second, three state-of-the-art Multi-Objective Optimisation (MOO) algorithms were employed to discover optimum locations for an offshore wind farm. The 7-objective optimisation problem comprises of some of the most important techno-economic LCC factors that are directly linked to the physical aspects of each site. The results of Non-dominated Sorting Genetic Algorithm (NSGA II), NSGA III and SPEA 2 algorithms follow a similar trend, where NSGA III demonstrated its suitability by revealing more uniform and clear optimum non-dominated solutions, also known as Pareto Front (PF), because of its main design compared to the other optimisers. Based on their frequency of appearance in the PF solutions, Seagreen Alpha, Seagreen Bravo, Teesside C, Teesside D, and the Celtic Array South West Potential development Area were discovered as the most appropriate. Since PF includes solutions from all regions, this provides the developer with the flexibility to accordingly assign costs in different development phases, as required, and to choose whether to invest the available budget on the installation or the maintenance stage of the project. Third, in order to reveal optimum locations for UK Round 3 offshore zones and each zone individually, three different wind farm layouts and four types of turbines were considered in an 8-objective formulation, where five LCC factors are directly linked to the physical aspects and restrictions of each location. NSGA II discovered Moray Firth Eastern Development Area 1, Seagreen Alpha, Hornsea Project One, East Anglia One and Norfolk Boreas in the PF solutions. Although layouts 1 and 2 were mainly selected as optimum solutions, the extreme case (layout 3) also appeared in the PF a few times. All this demonstrates the scalability and effectiveness of the framework. Fourth, the effectiveness of coupling MOO and Multi-Criteria Decision Making (MCDM) methods is demonstrated, so as to select the optimum wind farm Round 3 location in order to help stakeholders with investment decisions. A process on the criteria selection is also introduced, and seven conflicting criteria are considered by using the two variations of Technique for the Order of Preference by Similarity to the Ideal Solution (TOPSIS) in order to rank the optimum locationsthat were discovered by NSGA II. From the prioritisation list, Seagreen Alpha was found as the best option, three times more preferable than Moray Firth Eastern Development Area 1. Fifth, experts‘ opinions were employed in an MCDM process to select the support structure type in an offshore wind farm. For comparison, six deterministic MCDM methods and their stochastic expansion were employed; WSM, WPM, TOPSIS, AHP, ELECTRE I and PROMETHEE I in order to account for uncertainties systematically. It was shown that the methods can relate to each other and can deliver similar results. The jacket and monopile support structures were ranked first in most deterministic and stochastic approaches. Overall, the effectiveness of the introduced research framework to meet the aim of the research is demonstrated. The framework combines a) a prototype techno-economic model for offshore wind farm deployment by using the LCC and geospatial analysis, b) MOO by using NSGA II and c) survey data from real-world experts within MCDM by using a deterministic and stochastic version of TOPSIS. EngD in Renewable Energy Marine Structures (REMS)

This study investigates the viability of localising job roles in the oil and gas industry and whether job role localisation can reduce staffing costs. The principal barrier to job role localisation is high standards required by oil and gas companies and immature labour markets that do not meet these standards. A four stage mixed methods approach is taken. The first stage addresses the global level using a survey about local content issues. The second stage focuses on the national level using interviews to investigate how national factors can affect job role localisation. The third stage addresses the company level, using a decision tree methodology on a sample of ten job roles within one oil and gas company operating in Ghana to assess the viability of localising particular job roles. The fourth stage uses training and development investment timelines to model whether the costs of employing expatriates are greater than training, developing and employing Ghanaians to do the same job roles. The findings show that different stakeholders often share opinions about local content issues. At the national level there are many national context specific factors that affect job role localisation including legislations, culture, attitudes and experience within the labour market. The decision tree methodology developed in this study is an effective tool to assess the viability of localising different job roles over time. Training and development investment timelines show that it is more cost-effective to invest in the education, training and development of local people than it is to employ expatriates. This study finds that localisation is becoming increasingly prevalent worldwide. Oil and gas companies must adapt their localisation strategies to the national context where they are operating. Whilst not all job roles should be localised, decision trees can support companies to decide which job roles should be localised. Furthermore, companies can reduce costs if they train, develop and employ local people rather than employing expatriates. MSc by Research in Energy and Power

Research and innovation have considerable, currently unquantified potential to reduce greenhouse gas emissions by, for example, increasing energy efficiency. Furthermore, the process of knowledge transfer in itself can have a significant impact on reducing emissions, by promoting awareness and behavioural change. The concept of the 'carbon brainprint' was proposed to convey the intellectual contribution of higher education institutions to the reduction of greenhouse gas emissions by other parties through research and teaching/training activities. This paper describes an investigation of the feasibility of quantifying the carbon brainprint, through six case studies. The potential brainprint of higher education institutes is shown to be significant: up to 500 kt CO(2)e/year for one project. The most difficult aspect is attributing the brainprint among multiple participants in joint projects. Refereed/Peer-reviewed

The Subsea blowout preventer (BOP) which is latched to a subsea wellhead is one of several barriers in the well to prevent kicks and blowouts and it is the most important and critical equipment, as it becomes the last line of protection against blowout. The BOP system used in Subsea drilling operations is considered a Safety – Critical System, with a high severity consequence following its failure. Following past offshore blowout incidents such as the most recent Macondo in the Gulf of Mexico, there have been investigations, research, and improvements sought for improved understanding of the BOP system and its operation. This informs the need for a systematic re-evaluation of the Subsea BOP system to understand its associated risk and reliability and identify critical areas/aspects/components. Different risk analysis techniques were surveyed and the Failure modes effect and criticality analysis (FMECA) selected to be used to drive the study in this thesis. This is due to it being a simple proven cost effective process that can add value to the understanding of the behaviours and properties of a system, component, software, function or other. The output of the FMECA can be used to inform or support other key engineering tasks such as redesigning, enhanced qualification and testing activity or maintenance for greater inherent reliability and reduced risk potential. This thesis underscores the application of the FMECA technique to critique associated risk of the Subsea BOP system. System Functional diagrams was developed with boundaries defined, a FMECA were carried out and an initial select list of critical component failure modes identified. The limitations surrounding the confidence of the FMECA failure modes ranking outcome based on Risk priority number (RPN) is presented and potential variations in risk interpretation are discussed. The main contribution in this thesis is an innovative framework utilising Multicriteria decision making (MCDA) analysis techniques with consideration of fuzzy interval data is applied to the Subsea BOP system critical failure modes from the FMECA analysis. It utilised nine criticality assessment criteria deduced from expert consultation to obtain a more reliable ranking of failure modes. The MCDA techniques applied includes the technique for order of Preference for similarity to the Ideal Solution (TOPSIS), Fuzzy TOPSIS, TOPSIS with interval data, and Preference Ranking Organization Method for Enrichment of Evaluations (PROMETHEE). The outcome of the Multi-criteria analysis of the BOP system clearly shows failures of the Wellhead connector, LMRP hydraulic connector and Control system related failure as the Top 3 most critical failure with respect to a well control. The critical failure mode and components outcome from the analysis in this thesis is validated using failure data from industry database and a sensitivity analysis carried out. The importance of maintenance, testing and redundancy to the BOP system criticality was established by the sensitivity analysis. The potential for MCDA to be used for more specific analysis of criteria for a technology was demonstrated. Improper maintenance, inspection, testing (functional and pressure) are critical to the BOP system performance and sustenance of a high reliability level. Material selection and performance of components (seals, flanges, packers, bolts, mechanical body housings) relative to use environment and operational conditions is fundamental to avoiding failure mechanisms occurrence. Also worthy of notice is the contribution of personnel and organisations (by way of procedures to robustness and verification structure to ensure standard expected practices/rules are followed) to failures as seen in the root cause discussion. OEMs, operators and drilling contractors to periodically review operation scenarios relative to BOP system product design through the use of a Failure reporting analysis and corrective action system. This can improve design of monitoring systems, informs requirement for re-qualification of technology and/or next generation designs. Operations personnel are to correctly log in failures in these systems, and responsible Authority to ensure root cause analysis is done to uncover underlying issue initiating and driving failures.

Offshore oil and gas exploitation is principally conducted using dry or wet tree systems, otherwise called the subsea Xmas tree system. Due to the shift to deeper waters, subsea production system (SPS) has come to be a preferred technology with attendant economic benefits. At the centre of the SPS is the subsea control module (SCM), responsible for the proper functioning and monitoring of the entire system. With increasing search for hydrocarbons in deep and ultra-deepwaters, the SCM system faces important environmental, safety and reliability challenges and little research has been done in this area. Analysis of the SCM reliability then becomes very fundamental due to the huge cost associated with failure. Several tools are available for this analysis, but the FMECA stands out due to its ability to not only provide failure data, but also showcase the system’s failure modes and mechanisms associated with the subsystems and components being evaluated. However, the technique has been heavily challenged in various literatures for several reasons. To close this gap, a novel multi-criteria approach is developed for the analysis and ranking of the SCM failures modes. This research specifically focusses on subsea tree-mounted electro-hydraulic (E-H) SCM responsible for the underwater control of oil and gas production. A risk identification of the subsea control module is conducted using industry experts. This is followed by a comprehensive component based FMECA analysis of the SCM conducted with the conventional RPN technique, which reveals the most critical failure modes for the SCM. A novel framework is developed using multi-criteria fuzzy TOPSIS methodology and applied to the most critical failure modes obtained from the FMECA evaluation using unconventional parameters. Finally, a validation of these results is performed using a stochastic input evaluation and SCM failure data obtained from the offshore industry standard reliability database, OREDA.

The geotechnical conditions of the soil can fluctuate greatly across the wind farm. This is an issue since geotechnical modelling is the base of the structural design of an offshore wind farm, and the efficient installation of the wind turbines depends on its accuracy. This paper deals with the characterization of the seabed, predicting the soil properties over the total affected area by a wind farm, with the challenge to reduce the required data samples in the site investigation under the number of installed wind turbines, to reduce its cost. It is compared the prediction outcome from two different interpolation methods, kriging and radial basis function, assessing their accuracy by the Mean-Squared Error and the Goodness-of-Prediction Estimate, as well as with a visual examination of their mapping; obtaining higher accuracy for radial basis function and reducing to half the required sample points, from the initial value of installed wind turbines. In a second stage it is studied the soil effect over the foundation, analyzing the results from a FEA, where different geometries of the structure are compared submitted to different load cases to check its limit states. Those results show that the foundation cost can increase four times due to the soil conditions, taking into account only the steel volume, and demonstrating how important is the soil characterization in the foundation design, as it gives the chance to relocate those wind turbines that require more expensive foundations.

In today’s world there are 2.6 billion people that lack basic sanitation (37% of world inhabitants). In August of 2012, Cranfield University was awarded by the Bill & Melinda Gates Foundation with $810,000 to produce a prototype of the Cranfield’s innovative Nano-membrane Toilet (NMT). Finally, the prototype is going to be exhibited at the “Reinvent the Toilet Fair” during 21st and 22nd of March 2014 in the Taj Palace Hotel, New Delhi (India). Cranfield’s NMT demands electricity for its daily performance. Nevertheless, it is targeted to off-grid communities. Consequently, a human-powered generator (HPG) was selected as a backup solution. The current MSc by Research aimed to design and test of a prototype of the aforesaid HPG. Moreover, to promote its usage, a portable power supply unit is designed to store energy and power small-loads like charging mobile phones and electric lighting. To select the most suitable design for our case study, a methodology using the Technique for Order of Preference by Similarity to the Ideal Solution has been developed. As a result the plugged-in bike HPG alternative was selected. Next, prototypes of this generator and the portable power supply unit were developed, tested and shipped for display. While testing of the plugged-in generator and portable power supply unit, 26 Watt-hours (Wh) were harvested over 15 minutes, with its corresponding average charging power of 105 Watts. Nevertheless, the present study concludes 96 Wh as a more accurate energy level to be harvested during one hour of pedalling. Considering 96 Wh of energy, a round-trip battery efficiency of 70% (lead-acid), and a NMT’s demand of 283 Wh; a 10 people household needs to pedal the HPG over 4 hours and 20 minutes. Nevertheless, if considering an 85% inverter efficiency, 57.12 Wh are available to fully charge one mobile phone (5.6 Wh) and provide 4.5 hours of room and desk lighting (11 Watts bulb).

As a consequence of the gradually expanding aviation network, civil aircrafts are occupying an increasingly high proportion of the transport industry. Air transport now dominates the intercity rapid transit, long-distance passenger transport, international passenger and freight transport, and specific regional transport, advantaged as it is by fast, convenient, comfortable and safe options. Nevertheless, the potential adverse impact on the environment of air transport, specifically, in the case of this research, the pollutants generated during aircraft production remain a concern. Using the A319 as the main research object, this thesis will conduct a life cycle assessment research about its environmental impact. Moreover, it will focus on the impact brought by the application of composite materials to the entire life cycle environmental influence of the aircraft, particularly the material production and disposal process. At the same time, a contrast with the B737-800 aircraft will be made due to their different composite material use rate. Firstly, the inventory list is formed by collecting data about the weight and material of every component in the aircraft, the input and output information of the composite material manufacturing process, the disposal situation of the aircraft and the treatment of composite material. Secondly, the impact assessment of the aircraft is conducted to examine their environmental influence. During the assessment, each life stage and the whole life cycle of the aircrafts is assessed, and a comparison between these two aircraft types is made. Finally, according to the impact assessment result, the environment load increase brought by the manufacturing of composite material and the decrease of the environment impact due to the weight reduction character of composite material is calculated and compared. From this research, the conclusion that the use of composite material has a positive effect on decreasing the environmental impact of the whole life cycle of the aircraft is obtained. This will enable aircraft manufacturers to target these reas for improvement, to produce more comfortable, environment friendly and market competitive aircraft.

In the present work, an investigation of the fatigue life benefits emerging from fillet weld geometries optimization has been carried out. At first, an introduction to ageing mechanisms, corrosion and especially fatigue, acting on operating marine structures has been made. Residual stresses at weld toes, stress modes, and types, geometrical factors (weld angle, toe radius, leg length), welding techniques selected, post-welding treatment and plate‟s material are some of the principal factors affecting the fatigue life of a fillet weld joint. Especially, the accuracy of various approaches in fatigue life estimation of specific geometries under pre-set types and levels of stress is studied. It is evident so far that even the notch stress concept is the most accurate method based on S-N curves, the Fracture Mechanics approach can offer more accurate solutions of a crack development through the material. Towards this, a literature review on crack evolution aspects in welded and non-welded plates under bending and tension was performed; substantial parameters were determined and finally implemented in the LEFM model which was used for the simulation purposes of Chapter 6. As far as the crack aspect ratio evolution is concerned, an extensive reference is available in literature since many researchers have investigated its contribution to the determination of geometrical paths, commonly known as “Preferred Propagation Paths”. Their significance is related with our ability to determine accurate SIF solutions leading to precise fatigue life estimations. A typical fillet weld joint 2-D model has been developed in CAE Abaqus software and a Finite Element Analysis of subject T-profile has been carried out. Through this analysis, the fillet weld angle, the weld leg length, the weld toe curvature radio ρ and the carrying load plate thickness are examined for their impacts on the maximum surface stress. Finally, a number of stress mitigating measures are proposed and their effects are analyzed. Undoubtedly, the notch stress concept today is gradually gaining more and more acceptance among other fatigue analysis practices, hence the need for an estimation of the actual surface stresses along fillet weld toes, has become imperative. Towards this, different 2-D geometries are tested against stress concentration factors developed at weld toes, which are calculated on the basis of maximum in-plane principal stresses over nominal stresses in mode I pure bending and pure tension respectively. Moreover, validation with corresponding results from literature is provided. Finally, three different concepts for reducing the maximum surface stresses are presented. The first one proposes grinding of the weld toe area and formulation of an artificial U-notch or a part- circular profile. The second one applies to non-penetrating welds and assumes the existence of a root gap of a specific geometry which is related to the fatigue life and stress concentration factor of the fillet weld joint. Last but not least, the relatively recent concept of the variable radius notch is discussed, even though it is applicable mostly to notched bodies, not weld joints. Afterwards, a Linear Elastic Fracture Mechanics analysis of reference 2D fillet weld model is demonstrated. A number of geometrical parameters considered at previous stage for their impact on surface Stress Concentration levels at the weld toe region, have been correlated to fatigue life benefits in terms of increased number of stress cycles till failure. An extensive analysis of 9 different T-butt weld joint geometries has been provided in order to investigate how positively a possible SCF reduction can affect the fatigue life of a weld joint. Essential geometric variations (weld angle, length, toe radius, root slot) were considered in the 2D model. All calculated benefits both in pure bending and pure tension cases have been reported accordingly. Based on a linear interpolation of the points scatter (SCF, N-cycles) both in banding and tension, it was observed that a surface stress mitigation of 1% could lead to 1,33 up to 2,5% fatigue life benefit in the range of SCF=2 – 2,5. It is evident so far that the geometrical optimization of a weld joint in respect of notch stress mitigation can be a powerful tool both in shipbuilding and maintenance practice in the future. However, technically wise their application may incur high initial costs of improved tools of welding and post welding treatment and robots even though it would consist a cost effective solution in a medium/long term basis. Finally, the above process is followed by a reliability analysis of the most critical geometrical parameters affecting the fatigue life of a fillet weld joint. Reliability assessment results concerning medium, high and low cycle fatigue are provided and a comparative analysis of each factor‟s impact on fatigue life has been carried out.

The aviation industry represents approximately 3% of global greenhouse gas emissions, however with significant growth expected over the coming decades this proportion is expected to increase. Continued governmental and social pressure to reduce global emissions is posing a challenging question to the industry; how to improve environmental efficiency and reduce emissions with increasing industry growth. The environmental impact of aviation globally is discussed, examining the significant emissions and protocols that exist and their relative impacts both environmentally and economically. The viability of alternative biofuels is discussed, determining the life cycle environmental impact of future replacements to kerosene based jet fuel. This thesis therefore aims to provide an understanding of the fundamentals of aviation emissions but also most importantly provide possible solutions to assist the industry in reducing its emissions ‘footprint’. An important factor in determining efficiency improvements is to understand the impact of particular stages of an aircraft life and the impact they have individually. This was achieved using an established methodology called Life Cycle Assessment (LCA), which is an efficient tool for the analytical consideration of the environmental impact of manufacturing, operation and decommissioning. The results of a comprehensive LCA study of an Airbus A320 are documented considering all phases of the service life. The study draws useful conclusions, indicating the significance of special materials such as carbon fibre reinforced plastic (CFRP) on the total manufacturing emissions of the aircraft and indicating its operational phase as the one contributing most in its environmental performance breakdown. The thesis also examines short-term efficiencies for emissions reduction in commercial aviation, focussing on improvements in aircraft routing. The initiation of the EU emissions trading system (ETS) within European aviation willincentivise airlines to reduce their annual CO2 emissions. An alternative routing strategy is proposed for selected long haul routes, which introduces multiple stages into the route utilising two aircraft and is shown to reduce total CO2 emissions by up to 13.7%. Combined with blended biofuel, this reduction was estimated to increase to 16.6% with a reduction in ticket fares estimated to be as high as $19 per passenger per flight.