This thesis investigates the feasibility and effectiveness of Acoustic Emission (AE) methods for monitoring fatigue crack growth in metallic materials, with the aim of enhancing predictive capabilities and understanding of crack propagation under cyclic loading. The research specifically examines the correlation between various AE parameters—such as amplitude, count rate, energy rate, and entropy—and fatigue crack growth rates, using a multi-parametric approach.

Experiments were conducted on multiple specimens under different loading conditions, and both time-domain and frequency-domain AE parameters were analyzed. The study found that parameters like energy rate and rise angle were particularly effective in detecting specific stages of fatigue crack growth, while count rate and amplitude provided consistent indicators of crack initiation and progression. However, the study also highlighted limitations in the use of filtering techniques, such as SNR and amplitude filters, which can inadvertently remove crucial AE signals.

The findings suggest that while AE methods have potential for accurately monitoring fatigue crack growth, their effectiveness is influenced by the choice of AE parameters and the management of noise. To improve accuracy, the study recommends further research that includes a broader range of specimens, explores additional AE parameters, integrates complementary techniques such as Digital Image Correlation (DIC), and applies advanced analytical methods like machine learning. Future research should also consider the impact of environmental factors, such as corrosion fatigue, particularly in marine environments where realistic AE data is critical.

Overall, this study contributes to the broader understanding of AE monitoring for fatigue damage, laying a foundation for future research and practical applications, while acknowledging the need for further refinement and validation of AE techniques across diverse materials and conditions.

This thesis presents the design and experimental evaluation of an in-line, active ultrasound, condition monitoring setup for the detection of contamination in offshore bearing grease. This process is divided into three distinct research steps. First of all, the influences that affect ultrasound propagation through a bearing grease sample have been investigated through various laboratory experiments. Next, a practical, real-world experiment using a linear bearing has been designed and conducted with the aim of determining the applicability of such an in-line condition monitoring setup. Lastly, the performance of the in-line active ultrasound setup has been evaluated, improvements have been proposed and an overall condition monitoring strategy has been devised.

During the laboratory experiments, various influences on ultrasound wave propagation have been investigated. First of all, design-specific parameters, such as the distance between the sensors, the test-setup material, and the scalability of the measured output voltage have been investigated. Next, the effects of temperature fluctuations, air bubble fluctuations, water contamination and iron particle contamination on the attenuation and velocity of waves for active ultrasound spectroscopy were investigated. It has been shown that air bubble concentration and temperature fluctuations influence the attenuation of the ultrasound in the grease sample. Therefore, the temperature should be kept constant throughout the other experiments. Additionally, the air bubble concentration should be managed through a constant resting time throughout the other experiments. Moreover, it has been shown that a condition monitoring setup employing active ultrasound spectroscopy is able to determine water contamination and iron particle contamination. The highest sensitivity of this contamination detection is located in the first percentage of contamination concentration, showing an amplitude drop of about 0.5dB/mm to 1dB/mm and a change in speed of sound of about 5\% to 15\%. It is however, difficult to differentiate between the different types of contamination using only the attenuation and velocity spectroscopy methods.

The practical, real-world experiment using an operational Huisman linear bearing has illustrated the applicability of using an in-line grease condition monitoring setup in such an environment, by evaluating obstacles such as spatial constraints, location constraints, flowability of the grease and surrounding noise. It has been shown that these obstacles pose minimal challenges for the successful implementation of an in-line grease monitoring setup for effective condition monitoring of offshore bearing grease.

The evaluation of the improved in-line active ultrasound condition monitoring setup has highlighted the strengths and weaknesses of implementing such a setup for offshore applications. A possible combination of the proposed grease condition monitoring method with Acoustic Emission monitoring offers

Governments are looking more and more to invest in renewable energy sources due to the energy transition that is currently taking place. One of the many renewable energy sources is wind energy which is increasingly positioned at sea. Wind turbines in deep parts of the ocean can be placed on floating structures which are often moored to the sea bottom by mooring ropes. For deep sea, the only viable option is a synthetic mooring line due to its almost neutral buoyancy.
Mooring ropes have a vital role in the offshore floating structure as it is keeping the structure in place. When a mooring line breaks, the consequences may be big, leading to serious damage or dangerous situations. Therefore, the structural integrity of mooring ropes should be evaluated regularly. For synthetic mooring ropes, the only method at this point in time is visual inspection. This can be done by divers or by Remotely Operated Vehicles (ROVs). This method is expensive, time consuming and in case it is done by divers, it is potentially dangerous. Furthermore, synthetic mooring ropes are susceptible to external damage which means inspection would have to be executed without direct contact with the mooring ropes. Therefore, it is necessary to assess the feasibility of a non-contact, non-destructive testing method in order to assess the structural integrity of a synthetic mooring line. The combination of non-destructive material property assessment and tension assessment is believed to produce a structural health monitoring instrument for synthetic mooring ropes.
In this thesis, a methodology is proposed which uses two independent non-contact, non-destructive measurements to assess the structural integrity of a high modulus polyethylene (HMPE) rope specimen. The measurements involved are ultrasonic guided wave (UGW) measurements and vibration measurements. The UGW measurements are performed to assess the stiffness of the test specimen according to the principle of attenuation of ultrasonic waves propagating through a specimen. The vibration measurements are performed to assess the natural frequencies of a manually excited test specimen. The assessed natural frequencies and the determined stiffness of the test specimen can be used to calculate the load acting on the test specimen.
The methodology is tested by conducting experiments in a laboratory environment where in-situ conditions are recreated by performing the tests underwater. It was concluded that the loads can be recalculated with varying accuracy of approximately 10% with respect to the actual values, with increasing accuracy for higher load values. It is concluded that the proposed methodology has the potential to determine load on a synthetic mooring line in a non-contact, non-destructive manner.

Highly-loaded low-speed roller bearings are commonly used in the offshore machinery, for example in turret moorings systems of Floating Production Storage and Offloading (FPSO) units and in slew bearings in heavy-lifting cranes. Safe and reliable operation and structural integrity can be ensured by monitoring the condition of the bearing. Condition monitoring based on acoustic emission (AE) has shown good potential for monitoring the health of highly-loaded low-speed bearings. With the increase in potential and proven condition monitoring methods, the need for lifetime predicting methods is increasing.
In this thesis, the feasibility of a digital twin (DT) concept is tested to make lifetime predictions of a highly-loaded low-speed roller bearing. The developed DT uses a combination of the Paris model and an AE-based model presenting the current state of the bearing. In the remaining useful life (RUL) prediction, the final crack size and total number of load cycles are determined based on an integrated form of the Paris model. Three different forms were tested for the RUL prediction.
The Paris model and the AE-based model showed good agreement in a benchmark case, based on which the two models were combined. The AE-based prediction was tested for hits and counts, with the counts yielding into better results due to a better fitting of the model constants. The linear RUL based on the number of load cycles resulted in the best prediction. The developed DT showed good potential in making lifetime predictions of highly-loaded low-speed roller bearings and enrichment of future DTs with prognostic information.

Floating Offshore Wind Turbines (FOWTs) have emerged as a promising technology for generating clean energy in deep water locations. Bluewater Energy Services proposes a Tension Leg Platform (TLP) as the floating support structure. An effective Structural Health Monitoring (SHM) system (of which there are various types) can facilitate timely interventions and optimize inspection and maintenance activities by providing continuous insights into their structural condition. Fatigue damage is especially critical for the support structures of FOWTs, as they are subject to cyclic loads that can cause structural damage.

This research proposes a fatigue monitoring system for a TLP supporting FOWTs. The methodology used is Modal Decomposition and Expansion (MDE). Due to the complexity of the studied structure in terms of structural dynamics, MDE is selected for its ability to capture dynamic behaviour. The main objective of the fatigue monitoring system is to perform the full-field strain estimation based on a limited number of sensors. This could also allow for the verification of the design considerations. With the presented response reconstruction approach, the stress in the locations prone to fatigue of the platform can be monitored and therefore, enabling estimation of the remaining lifetime of the structure and optimize maintenance planning.

Different analytical and numerical models are used in this investigation. The application of MDE in a simple structure (i.e. a cantilever beam) is first assessed to verify the performance and to gain insights of the methodology. Later, MDE is applied to a simplified TLP model to validate the response reconstruction approach and demonstrate its applicability for TLP-like structures.

Finally, a FOWT numerical model is used to design the fatigue monitoring system. The proposed system consists of two layouts of two strain gauges in the upper column of the TLP, and two layouts of two strain gauges on each pontoon. This system can provide full-field strain estimations with over 88.9% accuracy and predict fatigue damage accumulation with errors of less than 0.01%. Also, the system presented in this thesis only predicts global responses. However, the fatigue of the structure is also influenced by local structural responses due to sea pressures. Therefore, future research to include local effects in the predictions is recommended.

Fiber reinforced composites have been increasingly used in the aerospace and automotive industry, due to their potential advantages for designing flexible, strong and lightweight structures. More recently they are also being considered for the manufacturing of marine propellers. Since they have the potential to lower the weight, lower the maintenance costs, increase the efficiency at off-design conditions, improve cavitation inception speed and minimize acoustic signatures. Exploiting the full potential of composite propellers however requires that they need to be cost-effective and to do so it is required that the lifetime of the blade is sufficient. To determine the lifetime of the blade it is
crucial to determine how the composite blade will respond to a wide variety of environmental and loading conditions that it will experience over its life. Basically one needs to determine what effects fatigue will have on the material properties of the blade. The main objective of this thesis is to estimate the fatigue lifetime of composite marine propellers subjected to a pressure distribution determined by a Fluid-Structure Interaction
(FSI)model with the use of a progressive damage model integrated into a Finite
Element Model (FEM). The fluid structure interaction model to determine the pressure distribution has already been created Maljaars (2019). Currently the mostly used and most reliable approach is to use an experimental approach in order to estimate the fatigue life. However, for custom designs such as marine propellers this is a long and costly process. Modelling fatigue the fatigue performance in an earlier stage of the design cycle will result in significant cost and time savings.

The expected fatigue lifetime of the composite marine propeller is concluded to be at least 1012 cycles under the considered loading condition. If the propeller would rotate at 600 rpm for 24 hours per day this would translate to over 3000 years. The reason behind this large number is that the combination of the applied pressure load and the strength of the carbon fiber propeller is such that the stresses in each ply are very low. These low stresses create almost no damage throughout the propeller blade even for ultra high cycles.

One of the key challenges for offshore pipeline installation are free spans, which are sections not supported by the seabed. Within these sections the stress in the pipeline is increased due to local buckling which is caused by high bending moments at free span shoulders and midspan. Additionally, hydrodynamic loading due to currents and waves, and vortex induced vibrations increase fatigue damage.

There are many solutions to mitigate free spans and their negative effects, like building supports underneath the pipeline, or reducing the span length by burying a section of the pipeline in the seabed at the shoulder. From a deficiency analysis it is concluded that there is a need for a new system concept especially for steep slopes. This new free span mitigation shall be suitable to be performed by Allseas, an offshore construction company, during pipeline installation with the S-lay method, without the need for subcontractors like dredging companies.

Oil and Gas pipelines which are installed onshore do not create free spans as they follow the topography by being bent. This makes route intervention less extensive as it is done offshore.

The standard DNV-ST-F101 which contains requirements, principles and acceptance criteria for submarine pipeline systems, allows for cold field bends for submarine pipelines as long as certain requirements are met. There are many ideas published to bend the submarine pipeline such that it follows the seabed topography like it is the case for onshore pipelines. These approaches have been either patented or presented as case studies but have not been used in projects, so far.

It has been estimated in some of these previous case studies that the bending moments at the shoulders are reduced and stresses in the bend are within an acceptable range. From the presented opportunities and the described need, it is concluded that it is reasonable to develop a feasible new system concept which satisfies the operational and functional requirements defined in this thesis.

From combining different solutions of common subfunctions a number of concepts have been found which have been analysed and narrowed down to one possible most promising design. Using this new tool which is used in combination with an AUXROV it is possible to bend one 12m joint of the size of 32’’ by 18.5°. With the given parameters of this design the free span length and height are narrowed down and the pipeline follows the topography when bent. It is verified that the bending moment at the free span shoulder is indeed reduced as presented in the literature.

The concept design, presented in this thesis, is at an early development stage but can serve as basis for detailed engineering, the next step in concept development. With a tool like this a new opportunity as standard solution for free span mitigation at steep slopes is introduced.

Floating offshore production units are typically anchored to the seabed with mooring chains. Structural degradation of mooring chain steel can lead to premature failure with large environmental and financial consequences. In the oceanic environment, corrosion and fatigue are the dominant failure modes for mooring chains. These damage mechanisms are hard to predict and even harder to identify at early stages of damage evolution. Continuous research to develop improved monitoring techniques is performed to increase the safety and reliability of these structures. However, inspection techniques that can accurately and quantitatively diagnose these damage mechanisms in the submerged steel parts are yet insufficient.

Acoustic emission (AE) monitoring is a non-destructive evaluation technique that can identify structural degradation in solid materials. The technique consists of recording and processing the ultrasonic waves generated by irreversible changes in the material matrix due to damage growth. This research is focused on the global parametric analysis of the primary features of AE signals recorded during corrosion-fatigue experiments performed with submerged steel and non-contact sensors. Three experiments have been analysed to assess which of the AE primary features can most accurately correlate to the fatigue damage evolution.

Signal characterization based on their energy and duration was performed to distinguish three levels of severity. Based on a global parametric analysis the hit-rate and energy-rate have the highest potential and show good correlation to the corrosion-fatigue damage evolution. However, the global features seem to differ notably between different samples and several moments with absence of recorded activity precede final failure. Performing assessment only based on the global features is not considered sufficient. Thus, local analysis methods for AE signals is suggested to extract further information on the source of the emitting damage mechanisms.

Fiber Reinforced Composite (FRC) materials are gaining great popularity in marine structures because of their excellent strength-to-weight ratio, low density, and provided freedom in the design process. However, the use of FRC materials comes along with relatively large uncertainties in material properties and structural integrity after manufacturing and during its use. In this research a new in-situ non-destructive stiffness assessment methodology is proposed. This methodology is based on a coupling principle between the laminate structural stiffness properties and the ultrasonic guided wave characteristics of FRC materials. In the methodology, a range of possible stiffness properties is defined based on the structural information available for a structure of interest. The average relation between this stiffness range of interest and corresponding wave characteristics is described using a set of coupling coefficients which are determined using numerical simulations. For this, a batch of reference laminates is constructed that covers the entire stiffness range of interest. Input for the system are the group velocities of the zeroth-order symmetric and antisymmetric guided wave modes, measured on the structure of interest. The potential of the proposed methodology is evaluated using a numerical feasibility study based on numerical simulations. Good results were obtained for different test scenarios, varying in the amount of structural information available on the structure of interest. Thereafter, the in-situ application of the methodology has been examined in an experimental setup. Good measurement and analysis times were achieved by using a compact measuring device that is capable of recording the wave signal in five directions simultaneously. A reliable accuracy assessment of the in-situ application of the methodology was, however, difficult to obtain due to the lack of reliable reference studies. Therefore, in future research reliable reference information should be gathered. Additionally, a next step for future research should focus on decreasing the amount of information available on the structure of interest.

Fiber-reinforced composite (FRC) marine propellers potentially outperform metallic propellers in terms of efficiency and underwater radiated noise (URN) by hydro-elastic tailoring of the blades. Several methods can assess the extent of these potentials. Research shows that embedded sensing methods can be used in dynamic measurements of composites. This thesis studies a full-scale application of a network of embedded piezoelectric sensors in an FRC marine propeller blade. The study prefers using piezoelectric sensors because of their ability to operate in a relatively wide frequency range. The focus of the thesis starts with designing the full-scale network of embedded piezoelectric sensors. Since no literature includes this application on FRC blades, this study holds a pioneering role in embedding piezoelectric sensors in an FRC marine propeller blade. Detailed analysis of material dimensions - including sensors, wiring, and fiber plies - leads to a successful sensor network design. Considerations regarding the location of 24 sensors included both the in-plane and the in-depth position within the FRC laminate. Fabrication of an FRC blade has been done using a resin transfer moulding (RTM) process. For the first time, an FRC marine propeller blade is embedded with piezoelectric sensors. Demoulding of the blade caused damage to some of the sensor wires. An amount of 54% of the embedded sensors survived the process with full connectivity. The performance of the intact sensors after fabrication is assessed. These sensors are exposed to free vibration tests of the FRC blade. An excitation is imposed on the blade with an impact hammer. A data acquisition (DAQ) system is used to capture the responses of the embedded piezo-sensors. The frequency response functions (FRFs) of multiple locations on the blade are computed. These FRFs provide more insight into the dynamic behavior of the blade. A frequency range of 1-1000Hz is used in the modal analysis. The first five natural frequencies are found between 240Hz and 840Hz. Natural frequencies measured by the embedded piezo-sensors and surface-mounted strain gauges differ up until 25% from natural frequencies computed by a finite element model (FEM) of the blade. The mode shape of the blade at the natural frequencies is computed for by the FEM and embedded piezo-sensors. Some difference in mode shapes is demonstrated between measurements computed by FEM and those measured by the embedded piezo-sensors and surface-mounted strain gauges. The piezo-sensors and strain gauges are in agreement regarding the measured natural frequencies. Therefore, it is expected that discrepancies exist between the physical blade and FEM. Several points for improvement of the results have been found. The study provides the first-time feasibility of dynamic measurements from embedded piezo-sensors in an FRC marine propeller blade. Additionally, a framework for reconstructing the full-field vibration response is provided, which can provide more accurate results when the agreement between piezo-sensor and FEM measurements has improved.

For floating photovoltaic systems, an uncommon type of offshore structure is considered, which is very flexible and deforms with the motion of the waves. In this research, the bending characteristics of a drop-stitch floater is analysed, which is an inflatable panel. By inflating the drop-stitch floater to a low air pressure, it obtains a flattened shape and the ability to support the flexible solar panels, while still retaining flexibility to deform with the motion of the waves. The bending characteristics of a drop-stitch floater are more complex than common offshore structures due to different non-linearities: wrinkling, hyperelastic material behaviour and internal pressure-volume work. Getting a better understanding in the bending response is important to eventually determine the response and limit states in offshore conditions. A finite element and experimental analysis has been performed of the response in a three point bending load case. Also, an experimental uniaxial tensile test has been performed to evaluate the hyperelastic anisotropic material behaviour. Different yarns spacings, internal air pressures and face sheet thicknesses are evaluated. This showed that there are two types of failure modes with distinct behaviour for an uniaxial pure bending load case: a global wrinkling and folding failure mode.

Highly-loaded low-speed roller bearings are frequently used in equipment offshore e.g. slew bearings in crane, sheave bearings and FPSO turret bearings. Reducing maintenance costs, increasing productivity, ensuring safety of people and structural integrity and longevity assurance of equipment can be achieved by the condition monitoring of highly-loaded low-speed roller bearings.

Currently, very limited research is performed in the field of condition monitoring with acoustic emission (AE) monitoring for highly-loaded low-speed (<10 rpm) bearings with naturally developed damage. Acoustic emission monitoring has shown promising results in early stage and real time identification of defects according to literature. Furthermore, contamination of wear particles in lubricant shows an increase in AE activity according to literature.

In this research, the applicability of AE monitoring for damage assessment of highly-loaded low-speed roller bearings is investigated in a full scale duration test. Furthermore, the influence of contaminated lubricant with steel particles is investigated in the contamination test to study the feasibility of real-time detection of contaminated lubricant during operations and as a supporting technique for wear debris analysis in lubricant.

From the results, an increase in AE activity expressed in hit-rates is observed for a wide frequency band of 40 - 580 kHz during the duration test where the basic rating lifetime (L10) is consumed from 40% to 50%. Wear development in the bearing is observed during visual inspection and has been quantified with lubrication analysis.
A safety limit and a limit if the bearing is at risk for the AE activity has been defined with the results of the baseline and duration test. This research suggests that AE monitoring can be applied on highly-loaded low-speed bearings to assess the damage for representative operational conditions.

From the results of the lubricant contamination test, an increased AE activity with respect to higher lubricant contamination levels were observed. Furthermore, with a proper choice of the SNR-level, there is no masking effect of acoustic emission signals due to contaminated lubricant. The results of the contamination tests, indicates the possibility of detecting contaminated lubricant with AE monitoring.

Currently, as the utilization of offshore wind energy continues to increase, floating wind turbines are expected to be widely used. As the fixed system of the turbine, the safety of the mooring chain has gradually attracted the attention of researchers. Mooring chains immersed in seawater are mainly subjected to various mechanical loads and corrosion. Therefore, premature failure and frequent replacement are the main problems of mooring chain systems. In order to avoid huge losses of safety caused by structural failure, it is urgent to establish mooring integrity management, accurately identify hazards, and evaluate the service life of the mooring system. Considering the requirements of sufficient mechanical properties and economic benefits, high-strength low-alloy steel has gradually replaced low-carbon steel as the main material for mooring chains. However, there are few studies on the detailed corrosion process of mooring chain steel.
This research aims to explore the corrosion process of mooring chain steel and the influence of marine environmental factors on the corrosion process. Traditional electrochemical techniques, morphology observation and new in-situ non-destructive technique acoustic emission are used to investigate the corrosion process. The experiment includes the exploration of the corrosion process of steel under natural and accelerated conditions. Experiments on the influence of flow velocity and temperature are also included. The corrosion process of mooring chain steel is successfully explored during the monitoring process. Acoustic emission signals related to corrosion are separated. Their sources are reasonably identified. The effects of water flow velocity and temperature of the corrosion process are summarized.

Structural health monitoring of maritime and offshore structures can contribute to the reduction of the amount of uncertainty in assessment of the operational loads and the structural integrity. Such a survey can also reduce the large safety margins during the design and optimize the conservative inspection and maintenance schedules. One of the emerging variants of structural health monitoring are the so-called digital twin systems that not only allow the monitoring of the structures, but can also simulate the past or the future state of the structural integrity. In the context of this thesis, the feasibility of a digital twin system for the structural health assessment of marine structures based on machine learning algorithms and utilization of big data is examined. The main research question is if the digital twin technology can be enhanced with machine learning to accurately monitor the structural health of marine structures in terms of loading and fatigue damage accumulation. In order to answer this question four modules have been developed and tested. The first module uses artificial neural networks trained on operational data to predict the fatigue damage accumulation and the frequency that corresponds to the maximum stress power density. The error of the developed networks turned out to be negligible in the investigated cases, with standard deviation of less than 4% in the predictions. The peak frequency of the stress power density is predicted using a random forest regression algorithm. The optimized version of the algorithm has led to an accuracy of 93% with standard deviation of less than 1% in the predictions.
The second module is used to recalibrate the design response amplitude operators of the structure using the predictions of the first module or the operational data, if available. The design response amplitude operators are scaled and shifted in order to minimize the deviation between the spectral fatigue calculations and the predicted (or measured) data.The third module is a static/quasi-static load-reconstruction module. Using on-board strain measurements it is able to calibrate the loading of the structure based on a reformulation of the conventional finite element problem for static and quasi-static loading. A sensitivity analysis of the algorithm effectiveness have been performed using multiple load cases in which the reconstruction error turned out negligible. The fourth and final module relates to structural reliability analysis. This module is based on the estimation of the Hansofer-Lind reliability index as a minimization problem. The employed optimization engine is a variation of the particle swarm optimization algorithm using chaotic system behaviour to iteratively calculate the user-defined parameters. The limit state equation is formulated in a way that it takes the uncertainties related to the fatigue damage accumulation prediction model and Miner's Rule into consideration. Uncertainties related to the material and the fabrication process are not taken into account. The developed modules have been tested on structural details of a vessel monitored in the scope of Monitas Joint Industry Project (JIP). About a year's worth of data has been used to train the machine learning algorithms.

Variations in the production process of fiber-reinforced composite (FRC)materials often influence the material properties of the end product more substantially than their metallic counterparts. It can be valuable for the structural performance and reliability to have a better estimation of the properties of the FRC after production. Detecting these material properties is often performed by intrusive or destructive testing, which are not desirable for in-situ applications. Samples are commonly taken from the material for mechanical testing and material characterization in the laboratory. Feasibility of a non-destructive in-situ assessment method based on ultrasonic guided waves for estimation of the material properties of FRCs, e.g. stiffness in different directions, is investigated in this research. A portable and easy-to- apply measurement system is proposed that can also be less sensitive to the environmental conditions. Point-contact transducers containing a piezoelectric material are utilized for measuring guided waves that propagate through the material. The dispersion characteristics, i.e. phase speed and group speed, of these guided waves are dependent on the layup of the fibers, thickness, and ply properties. Information about the group speed from multiple directions are extracted and compared with the group speeds obtained using a semi-analytical method. A genetic algorithm (GA) is implemented to minimize the difference between the measured and modeled group speeds and obtain the ply properties. The methodology was applied to five glass FRC laminates with different layups. In the numerically simulated case, the error in the estimated material properties turned out to be less than 12%. The coefficient of variation in the experimental results of stiffness values was also less than 20%. The results suggest that the proposed combination of point contact transducers, analysis of group speeds, and GA optimization procedure can potentially form a viable approach for in-situ assessment of material properties of FRCs.

Low-speed roller bearings are generally in the sheave bearings and turret bearings which are used in the offshore industry under heavy loads. One of the challenges to the integrity of these bearings is the presence of subsurface cracking in the raceways. Downtime cost, which is caused by the failure of
these bearings is significant. Based on the potential of the recently-developed monitoring methods for detection of damage in low-speed bearings, this research is focused on the feasibility of the remaining lifetime prediction for roller bearings with existing subsurface cracking in the raceways.
The main approach of this thesis comprises a locally-coupled elasto-plastic damage model for low-cycle fatigue. In the numerical simulations, models with and without crack have been implemented and subjected to heavy loading condition. To avoid the crack singularity in the FEM, and reduce the
mesh sensitivity, a non-local method has been applied to determine the strain data around the crack tip. In a post-processing part, the nonlinear damage accumulation is implemented with a multi-yield surfaces algorithm.
To assess and validate the computational accuracy, the implemented locally-coupled elasto-plastic damage model has been compared with other (published) results. The numerical simulations suggest that the number of cycles to failure is about two times higher when the detectable crack size decreases from 20mm to 5mm. From these results, it is recommended to improve the monitoring system for the detection of smaller cracks. Moreover, further experimental assessment is required to validate and update the estimations in the thesis.

The safety of offshore assets such as wind turbines, offshore cranes, and turret mooring systems partly relies on the integrity of heavy-duty bolted joints. These critical connections can be of different dimensions and exposed to monotonic and cyclic loading. Despite being small components of a structure, bolts need to be maintained appropriately to ensure structural safety and reliability. The integrity of bolted joints can be assured by checking for adequate preload. In addition, fatigue failure resulting from preload loss is of primary concern, as it can occur suddenly without any visible changes. Hence, bolts should be re-tightened periodically to ensure sufficient preload. However, in offshore conditions, this countermeasure leads to high maintenance costs while exposing the crew to unfavourable conditions and risks.

This research focuses on the feasibility of condition-based maintenance of bolts using ultrasonic waves. An energy attenuation method has been implemented for this feasibility research. The main objective is to establish a proper methodology and hypotheses for preload detection. Furthermore, along with preload detection, the feasibility of crack detection was investigated. Finally, the proposed methodology and hypotheses were validated by performing experiments and numerical simulations.

The experimental and numerical results verify the proposed methodology by showing an increasing trend in the energy and the power of the transmitted ultrasonic wave for increasing preload. Also, the feasibility of crack detection using the same setup has been positively evaluated.

The obtained results suggest that the ultrasonic waves can be employed to monitor bolts for condition-based maintenance. Additionally, a number of relevant research activities are recommended based on this study.

Mooring chains are subject to dynamic loads and corrosion. A challenging aspect in assessing the integrity of mooring chains is the presence of marine growth. Marine growth removal is expensive, environmentally damaging, and includes the risk of restarting corrosion process. The focus of this research is on the feasibility of mooring chains assessment in the presence of marine growth using active and passive ultrasound techniques. The approach includes experimental and numerical investigations for fatigue and corrosion damage. In the experimental part, specimens with and without marine growth have been designed, manufactured, and subjected to a series of experiments to determine the transmission characteristics of ultrasound waves through marine growth and its interaction with damage. Fatigue crack signals were simulated on the specimens using Hus-Nelson source. For the investigated compositions, the signal amplitude drop due to the presence of marine growth. Accelerated corrosion experiments were conducted to reproduce corrosion-induced acoustic emissions. Corrosion-induced signals were successfully detected and localized. Active ultrasound experiments were conducted using guided waves. These waves were successfully excited and measured in the test sample with naturally-cultured marine growth. The investigation suggests that guided waves can have a high potential for identification of fatigue cracks in the mooring chains. These experiments were complemented with numerical simulation of the setup. For the sake of computational efficiency and accuracy, a higher-order spectral finite element method was used. Simulations were further extended to investigate and confirm the possibility of detection of surfacebreaking cracks in the test sample.

Fibre-reinforced composites are increasingly being used in maritime structures. Piezoelectric sensors can be used to monitor both loads acting on a fibre-reinforced composite structure and elastic waves emitted from damage initiation within the structure. In certain marine applications, due to a harsh environment or for hydrodynamic reasons, piezoelectric sensors cannot be placed on the surfaces of the structure. Fortunately fibre-reinforced composite materials allow piezoelectric sensors to be embedded inside the structure. The focus in this research is on embedded piezoelectric sensor design, performance and behaviour. Carbon fibre beam specimens with embedded piezoelectric sensors have been manufactured and subject to low-frequency bending, high-frequency elastic wave emission, electrical excitation and monotonic bending to failure. The low-frequency bending test has given insight in the effects of sensor discharge, that is, decreasing and distorting the sensor response. Also it has been used to check consistency between different specimens. The effect of electrical discharge is practically absent around 1.8Hz but becomes apparent at lower frequencies. The test was simulated numerically. The simulation captures the effects of electrical discharge but underestimated sensor response amplitude by 40% to 65% for the small and large sensor respectively. High-frequency elastic wave emissions, originating from fibre-reinforced composite failure during monotonic bending, have been measured by an embedded piezoelectric sensor. The signals measured by the embedded piezoelectric sensor have a median signal-to-noise-ratio of 17dB. Using the spectral element method, a parameter study has been performed for a similar, two-dimensional setup. Embedded piezoelectric sensor length and embedment location in the plate thickness has been varied. Both a symmetric and antisymmetric elastic wave have been excited. It has been found that increasing sensor size has a negative effect on the sensitivity of the sensor. The antisymmetric elastic wave is better captured by the sensor response than the symmetric elastic wave. Effects of electromechanical resonance were not noticeable. Monotonic four-point bending failure tests were performed to compare structural integrity of a carbon fibre-reinforced beam specimen with an embedded piezoelectric sensor to a specimen without sensor. With embedded specimens, an average stiffness drop from 3 to 8% is noted. Specimens with small sensors on the tension side of the composite had a decrease lower than 4% in ultimate strain and at maximum 8% reduction in ultimate load and failure toughness. For specimens with embedded sensors on the compression side, the decline was larger, with the larger sensor outperforming the smaller sensor.