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A novel approach for robust damage detection of linear and nonlinear systems using recursive canonical correlation analysis (RCCA) is proposed in this paper. The method generates proper orthogonal modes (POMs) at each time stamp that are recursively tracked to provide iterative eigenspace updates, using first order eigen perturbation (FOEP) method. The transformed responses obtained are subsequently fit using time varying auto regressive (TVAR) models, in order to aid as damage sensitive features (DSFs) for identifying temporal and spatial patterns of damage. As most of the past work utilize offline algorithms that gather data in windows and operate in batch mode, recursive algorithms that provide iterative eigenspace updates at each instant of time, are missing in the context of structural health monitoring (SHM). This greatly motivates the development of the present work, where the both uni and multi directional structural responses are considered to be available in real time. The transformed responses are obtained by using the proposed algorithm that utilizes FOEP for multi-directional block covariance structure to solve the recursive generalized eigenvalue problem. The TVAR coefficients modeled on the transformed responses obtained in real time using FOEP, and residual error examined in a recursive framework, act as efficient real time DSFs for detecting damage online. Numerical simulations carried out on nonlinear systems and backed by experimental setups devised in controlled laboratory conditions, demonstrate the efficacy of the RCCA algorithm. Application of the proposed algorithm on the combined ambient and earthquake responses obtained from the UCLA Factor Building, demonstrates the robustness of the proposed methodology as an ideal candidate for real time SHM.

This paper presents an experimental study on the development of masonry block with Palm Oil Fuel Ash (POFA) as a partial replacement to cement whilst maintaining satisfactory properties of masonry block. The dosages of POFA are limited to 0%, 20%, 40% and 60% by mass of the total cementitious material in the masonry block. The experiments on masonry block investigate the compressive strength and the breaking load for mechanical properties and water absorption and efflorescence for its durability. The compressive strength and the breaking load of the masonry blocks reduce with increasing percentage of POFA replacement. However, it satisfies the requirements of Class 1 and Class 2 load-bearing masonry block according to Malaysian Standard MS76:1972. In terms of durability of the masonry block, water absorption for all the masonry blocks satisfies the requirement of ASTM C55-11 and there is no any sign of efflorescence on all the masonry blocks. POFA based masonry block are also found to be cheaper than the cement sand masonry blocks. The experimental studies indicate that POFA based masonry block has a significant potential for application in the construction industry.

The possibility of employing bridge deck surface roughness for Structural Health Monitoring (SHM) under operational conditions is proposed in this paper. A bilinear breathing crack in a damaged Euler-Bernoulli beam traversed by a moving oscillator is considered in this regard. The Road Surface Roughness (RSR) of the beam is classified as per ISO 8606:1995(E). The interaction of the moving oscillator with surface roughness is exploited to define simple, consistent, easy to implement and robust statistical descriptors to detect and calibrate the existence, the location and the extent of damage. The effects of vehicle speed and variable RSR profiles for such detection are investigated and preferable conditions for detection are identified. The proposed method is also suitable for experimental analysis where a theoretical model is not available or is not credibly ascertained. Irish Research Council

This article presents quantile autoregressive modeling (QAR), a new tool in relation to structural health monitoring addressing the problems associated with sudden changes in linear stiffness, transitions from linear to non-linear structural states and contiguous non-linear changes of states. Acceleration data is modeled using QAR process which involves fitting autoregressive (AR) coefficients at various pre-selected quantiles. The necessity of such a modeling stems from the inability of traditional AR models to account for non-stationary variance and the presence of non-linearity. Percentage changes in the QAR coefficients at different quantiles is proposed as a conditional indicator to detect changes in state of the structural systems. Numerical simulations on a hysteretic system subjected to El-Centro ground motion and a laboratory-scale experiment on a two-storied shear building model undergoing real time mass-loss demonstrate the robustness of the proposed methodology.

Understanding the dynamic behaviour of offshore wind and wave energy devices is extremely important in relation to the maintenance and management of these marine assets. Since experimentation in sea may often be difficult, expensive or unnecessary at a conceptual or at pre-commercial stage, scaled experimentation in wave tanks can be central to the understanding and assessment of their dynamic responses. This paper presents scaled dynamic testing in a wave tank of a tension leg platform for supporting a wind turbine for different regular wave conditions and sea states characterised by the Bretschneider spectra. The dynamic response of the device was monitored at different locations on the device using load cells and with a camera based motion recognition system. For the analysis, a frequency response function based approach was considered to illustrate the response of the device under varied wave loading conditions. The experimentation does not assume any underlying theoretical model, apart from the consideration of Froude scaling conditions to attempt to link experimentation conditions with actual conditions. The results are important for characterisation of theoretical models and fitting parameters of such theoretical models, while identifying the limits and potential challenges of applying linear dynamic analysis in these situations. The findings are also important for establishing system identification and control strategies for undesirable levels of dynamic response. The fitted models based on physical modelling, when combined with scaled experimental responses, can also be helpful in better estimating extreme responses of the devices.

This paper investigates the potential use of PolyVinyliDene Fluoride (PVDF) for the purposes of damage detection for infrastructural elements, primarily for bridge elements. PVDF based sensors have been created and characterised in the laboratory in this regard. Finite element analysis of vehicle-bridge interactions with varying damage are carried out. The energy harvesting signatures of realistic trains are assessed and quantified for the modelled bridge. The effect of localized damage on the finite element model and its subsequent relationship with energy harvesting from the calibrated PVDF based sensors are investigated using the harvesting signatures of realistic trains. This approach is useful in terms of designing new generation smart bridge structures and for possible retrofit of existing structures. The use of train-bridge interaction ensures that the damage detection is carried out while the bridge is under operational conditions. Consequently, there is minimal to no impact on the existing operation of the bridge or the transport network during damage detection. The paper is expected to be useful for practicing engineers and researchers in the field of application of new materials in the next generation of bridge structures.

Rapid assessment of large, short-period structures is extremely important for establishing structural integrity. This paper demonstrates experimental non-contact detection of consistent frequency peaks from the ambient vibration of a range of large buildings. Long distance, remote Laser Doppler Vibrometry is employed to estimate the dominant response frequencies of these large building structures from their ambient vibration. These dominant frequencies were reproducible in the frequency domain. The results demonstrate potential field applications of this method in a number of important applications. Such applications include model-free and rapid assessment or monitoring of historical structures, strategically important structures, lifelines, assessment and monitoring of structures such as nuclear facilities and rapid evaluation of large scale structures following disasters. Empirical formulas specified in codes do not cover such special structures and experimental determination of periods employing the method proposed may thus become essential.

This paper presents Hurst exponent footprints from pseudo-dynamic measurements of significantly varied activities on a damaged bridge structure during rehabilitation through continuous monitoring. The system is interesting due to associated uncertainty in large-scale structures and significant presence of human intervention arising from fundamentally different processes. Investigations into the variation of computed Hurst exponents on time series of limited lengths are carried out in this regard. The Hurst exponents are compared with respect to specific events during the rehabilitation, as well as with the data collection locations. The variations of local Hurst exponents about the values computed for each activity are presented. The scaling of Hurst exponents for different activities is also investigated; these are representative of the extent of multifractality for each event. The extent of multifractality is assessed along with its source and time dependency. The National Roads Authority, Maudlins, Naas, Kildare, Ireland South Dublin County Council, Tallaght, Dublin, Ireland Coastway, Naas, Kildare, Ireland Datum Monitoring Services Limited, Moira, Armagh, Northern Ireland Structural Concrete Bonding Services Limited, Newbridge, Kildare, Ireland Complete Highway Maintenance Group, Walkinstown, Dublin, Ireland Testconsult Ireland Limited, Portlaoise, Laoise, Ireland

This paper details the monitoring and repair of an impact damaged prestressed concrete bridge. The repair was required following an impact from a low-loader carrying an excavator while passing underneath the bridge. The repair was carried out by preloading the bridge in the vicinity of the damage to relieve some prestressing. This preload was removed following the hardening and considerable strength gain of the repair material. The true behaviour of damaged prestressed concrete bridges during repair is difficult to estimate theoretically due to a lack of benchmarking and inadequacy of assumed damage models. A network of strain gauges at locations of interest was thus installed during the entire period of repair. Effects of various activities were qualitatively and quantitatively observed. The interaction and rapid, model-free calibration of damaged and undamaged beams, including identification of damaged gauges, were also probed. This full-scale experiment is expected to be of interest and benefit to the practising engineer and the researcher alike.

The use of bridge management systems (BMS) by infrastructure stakeholders has led to the collection and retention of large quantities of data concerning the condition states of bridges throughout national and regional networks. The database for the BMS is often populated by the results of routine visual inspections, based on a prescribed scale for defining the condition state of the bridge’s individual elements, and of the bridge structure as a whole. The populating of the database also leads to the storage of large quantities of so-called metadata; which can describe the physical parameters of the bridge. The availability of this data allows the assessment of the BMS using multivariate techniques to enhance the life-cycle assessment of bridge networks, through advanced descriptive and predictive techniques applied to deteriorating network assets. Multivariate techniques such as principal component analysis have been demonstrated by the authors to be effectively applied as a descriptive tool to an existing BMS, and the results of a case study of a large dataset of bridges indicate its viability to be integrated into data-based approaches to infrastructural asset management., This work was supported by European Cooperation in Science and Technology TU1406 Quality specifications for roadway bridges, standardization at a European level (BridgeSpec), a COST Action supported by EU Framework Programme Horizon 2020, as well as the financial support of the Irish Research Council Government of Ireland Postgraduate Scholarship Scheme., info:eu-repo/semantics/publishedVersion

IABMAS: 8th International Conference on Bridge Maintenance, Safety and Management, Foz do Iguacu, Parana, Brazil, 26-30 June, 2016

Renew 2016: 2nd International Conference on Renewable Energies Offshore, Lisbon, Portugal, 24-26 October 2016

For water depths greater than 60m floating wind turbines will become the most economical option for generating offshore wind energy. Tension mooring stabilised units are one type of platform being considered by the offshore wind energy industry. The complex mooring arrangement used by this type of platform means that the dynamics are greatly effected by offsets in the positioning of the anchors. This paper examines the issue of tendon anchor position tolerances. The dynamic effects of three positional tolerances are analysed in survival state using the time domain FASTLink. The severe impact of worst case anchor positional offsets on platform and turbine survivability is shown. The worst anchor misposition combinations are highlighted and should be strongly avoided. Novel methods to mitigate this issue are presented. Science Foundation Ireland Centre MaREI - Centre for Marine and Renewable Energy

The process of Nuclei detection in high-grade breast cancer images is quite challenging in the case of image processing techniques due to certain heterogeneous characteristics of cancer nuclei such as enlarged and irregularly shaped nuclei, highly coarse chromatin marginalized to the nuclei periphery and visible nucleoli. Recent reviews state that existing techniques show appreciable segmentation accuracy on breast histopathology images whose nuclei are dispersed and regular in texture and shape; however, typical cancer nuclei are often clustered and have irregular texture and shape properties. This paper proposes a novel segmentation algorithm for detecting individual nuclei from Hematoxylin and Eosin (H&E) stained breast histopathology images. This detection framework estimates a nuclei saliency map using tensor voting followed by boundary extraction of the nuclei on the saliency map using a Loopy Back Propagation (LBP) algorithm on a Markov Random Field (MRF). The method was tested on both whole-slide images and frames of breast cancer histopathology images. Experimental results demonstrate high segmentation performance with efficient precision, recall and dice-coefficient rates, upon testing high-grade breast cancer images containing several thousand nuclei. In addition to the optimal performance on the highly complex images presented in this paper, this method also gave appreciable results in comparison with two recently published methods-Wienert et al. (2012) and Veta et al. (2013), which were tested using their own datasets. Science Foundation Ireland SFI-ISCA (Science Foundation Ireland - International Strategic Cooperation Award) program

Extensive research on bender element tests has been carried out by many researchers, but precise guidelines for carrying out such tests have not yet been established. It is often recommended that, when using a particular bender element test for the first time on a particular soil to determine its small strain dynamic properties, several methods should be tried and the results compared in order to improve confidence in the results obtained. Demonstrated use of relatively easy analytical models for investigating different scenarios of bender element testing is another aspect that should be further looked into. This paper presents laboratory experiments and dynamic finite element analyses to determine a suitable wave for use in bender element tests in the laboratory to measure small strain shear stiffness (Gmax). The suitability of a distorted sine wave over a continuous sine wave for tests is observed from laboratory experiments and dynamic finite element analyses. The use of simple finite element models for assessing a number of aspects in relation to bender element testing is demonstrated. Department of Civil Engineering, University of Dublin, Trinity College Nishimatsu Construction Co., Ltd The Geotechnical Trust Fund of the Institution of Engineers of Ireland

Wireless sensor nodes have a limited power budget, though they are often expected to be functional in the field once deployed for extended periods of time. Therefore, minimization of energy consumption and energy harvesting technology in Wireless Sensor Networks (WSN) are key tools for maximizing network lifetime, and achieving self-sustainability. This paper proposes an energy aware Adaptive Sampling Algorithm (ASA) for WSN with power hungry sensors and harvesting capabilities, an energy management technique that can be implemented on any WSN platform with enough processing power to execute the proposed algorithm. An existing state-of-the-art ASA developed for wireless sensor networks with power hungry sensors is optimized and enhanced to adapt the sampling frequency according to the available energy of the node. The proposed algorithm is evaluated using two in-field testbeds that are supplied by two different energy harvesting sources (solar and wind). Simulation and comparison between the state-of-the-art ASA and the proposed energy aware ASA (EASA) in terms of energy durability are carried out using in-field measured harvested energy (using both wind and solar sources) and power hungry sensors (ultrasonic wind sensor and gas sensors). The simulation results demonstrate that using ASA in combination with an energy aware function on the nodes can drastically increase the lifetime of a WSN node and enable self-sustainability. In fact, the proposed EASA in conjunction with energy harvesting capability can lead towards perpetual WSN operation and significantly outperform the state-of-the-art ASA. Science Foundation Ireland Analog Devices

This paper presents the reliability analysis of a network of six bridges in Ireland, with a focus on the sensitivity analysis and the analysis of parameter importance measures. The basis of the analysis stems from the possibility of investigating similarities in various parameters, leading to the establishment of network-level indicators based on fully probabilistic assessments. Initially, deterministic assessments are carried out on these bridges to verify the limit states, and a detailed probabilistic analysis is conducted, taking uncertainty in relation to the available information into account. Parametric importance measures are established across the network, and patterns identified from these studies suggest the potential for reliability-based network calibrations of bridge structures. This paper is expected to encourage a greater sharing of network-level information of the owners and managers of bridges. John Sisk Postgraduate Research Scholarship in Civil Engineering, University College Cork

The tower is an essential component of a wind turbine assembly with its cost amounting to approximately 30% of the overall turbine costs for onshore installations. This paper investigates the relative performance of steel and concrete tower solutions for a selection of heights and wind speeds by means of a flapwise numerical model. For each case, elements of a baseline 5. MW wind turbine are used to model the components supported by the tower. The Lagrangian approach is used to establish the equations of motion of the dynamic system, allowing for the coupling of the tower and the system of blades. The analysis is performed for a range of typical tower heights from 88 to 120. m. Comparison of the relative performance of the two tower solutions is presented using fragility curves. This illustrates the probabilistic characteristics of limit state exceedance as a function of wind loading. Irish Research Council for Science, Engineering and Technology Banagher Precast Concrete Ltd under the IRCSET (Irish Research Council for Science, Engineering & Technology) Enterprise Partnership Scheme

This article presents an experimental monitoring of the evolution of a crack in a beam using beam-vehicle interaction response signals for identification of progressively increasing crack-depth ratios. The beam is traversed by a two-axle model vehicle providing excitation in the time domain for the various extents of damage. The response of the beam in the time domain during the period of forced vibration is measured using strain gages. A consistent evolution of damage has been demonstrated in terms of the maxima values of the measured responses. The corresponding distortions of wavelet coefficients of the measured strain data due to the presence of various levels of damage have been identified. The evolution of the phase space and the wavelet transformed phase spaces have been evaluated with damage evolution. The wavelet transformed phase spaces for the undamaged and the damaged cases are observed to be distinctly different at high scales. The importance of denoising of the acquired data and the importance of vehicle configuration has been illustrated. This study presents a basis for a general model free damage assessment and structural health monitoring framework. The study presented is particularly useful in the context of continuous online bridge health monitoring, since the data necessary for analysis can be obtained from the operating condition of the bridge and the structure does not need be closed down.

Analysis of the variability in the responses of large structural systems and quantification of their linearity or nonlinearity as a potential non-invasive means of structural system assessment from output-only condition remains a challenging problem. In this study, the Delay Vector Variance (DVV) method is used for full scale testing of both pseudo-dynamic and dynamic responses of two bridges, in order to study the degree of nonlinearity of their measured response signals. The DVV detects the presence of determinism and nonlinearity in a time series and is based upon the examination of local predictability of a signal. The pseudo-dynamic data is obtained from a concrete bridge during repair while the dynamic data is obtained from a steel railway bridge traversed by a train. We show that DVV is promising as a marker in establishing the degree to which a change in the signal nonlinearity reflects the change in the real behaviour of a structure. It is also useful in establishing the sensitivity of instruments or sensors deployed to monitor such changes. Irish Research Council for Science, Engineering and Technology Science Foundation Ireland International Strategic Cooperation Award (ISCA), Ireland–India ISCA Programme India Study Centre, University College Cork, Ireland

Although vibration monitoring is a popular method to monitor and assess dynamic structures, quantification of linearity or nonlinearity of the dynamic responses remains a challenging problem. We investigate the delay vector variance (DVV) method in this regard in a comprehensive manner to establish the degree to which a change in signal nonlinearity can be related to system nonlinearity and how a change in system parameters affects the nonlinearity in the dynamic response of the system. A wide range of theoretical situations are considered in this regard using a single degree of freedom (SDOF) system to obtain numerical benchmarks. A number of experiments are then carried out using a physical SDOF model in the laboratory. Finally, a composite wind turbine blade is tested for different excitations and the dynamic responses are measured at a number of points to extend the investigation to continuum structures. The dynamic responses were measured using accelerometers, strain gauges and a Laser Doppler vibrometer. This comprehensive study creates a numerical and experimental benchmark for structurally dynamical systems where output-only information is typically available, especially in the context of DVV. The study also allows for comparative analysis between different systems driven by the similar input. Irish Research Council for Science, Engineering and Technology Science Foundation Ireland Marine Research Energy Ireland (MaREI)

Although aspects of power generation of many offshore renewable devices are well understood, their dynamic responses under high wind and wave conditions are still to be investigated to a great detail. Output only statistical markers are important for these offshore devices, since access to the device is limited and information about the exposure conditions and the true behaviour of the devices are generally partial, limited, and vague or even absent. The markers can summarise and characterise the behaviour of these devices from their dynamic response available as time series data. The behaviour may be linear or nonlinear and consequently a marker that can track the changes in structural situations can be quite important. These markers can then be helpful in assessing the current condition of the structure and can indicate possible intervention, monitoring or assessment. This paper considers a Delay Vector Variance based marker for changes in a tension leg platform tested in an ocean wave basin for structural changes brought about by single column dampers. The approach is based on dynamic outputs of the device alone and is based on the estimation of the nonlinearity of the output signal. The advantages of the selected marker and its response with changing structural properties are discussed. The marker is observed to be important for monitoring the as- deployed structural condition and is sensitive to changes in such conditions. Influence of exposure conditions of wave loading is also discussed in this study based only on experimental data. Science Foundation Ireland Marine Research Energy Ireland (MaREI)

While the potential of offshore wind and wave energy devices is well established and accepted, operations and maintenance issues are still not very well researched or understood. In this regard, scaled model testing has gained popularity over time for such devices at various technological readiness levels. The dynamic response of these devices are typically measured by different instruments during such scaled tests but agreed sensor choice, measurement and placement guidelines are still not in place. This paper compared the dynamic responses of some of these sensors from a scaled ocean wave testing to highlight the importance of sensor measurement strategies. The possibility of using multiple, cheaper sensors of seemingly inferior performance as opposed to the deployment of a small number of expensive and accurate sensors are also explored. An energy aware adaptive sampling theory is applied to highlight the possibility of more efficient computing when large volumes of data are available from the tested structures. Efficient sensor measurement strategies are expected to have a positive impact on the development of an device at different technological readiness levels while it is expected to be helpful in reducing operation and maintenance costs if such an approach is considered for the devices when they are in operation. Science Foundation Ireland Marine Research Energy Ireland (MaREI)

With the importance of renewable energy well-established worldwide, and targets of such energy quantified in many cases, there exists a considerable interest in the assessment of wind and wave devices. While the individual components of these devices are often relatively well understood and the aspects of energy generation well researched, there seems to be a gap in the understanding of these devices as a whole and especially in the field of their dynamic responses under operational conditions. The mathematical modelling and estimation of their dynamic responses are more evolved but research directed towards testing of these devices still requires significant attention. Model-free indicators of the dynamic responses of these devices are important since it reflects the as-deployed behaviour of the devices when the exposure conditions are scaled reasonably correctly, along with the structural dimensions. This paper demonstrates how the Hurst exponent of the dynamic responses of a monopile exposed to different exposure conditions in an ocean wave basin can be used as a model-free indicator of various responses. The scaled model is exposed to Froude scaled waves and tested under different exposure conditions. The analysis and interpretation is carried out in a model-free and output-only environment, with only some preliminary ideas regarding the input of the system. The analysis indicates how the Hurst exponent can be an interesting descriptor to compare and contrast various scenarios of dynamic response conditions. Science Foundation Ireland Marine Research Energy Ireland (MaREI)

Tuned liquid column dampers have been proved to be successful in mitigating the dynamic responses of civil infrastructure. There have been some recent applications of this concept on wind turbines and this passive control system can help to mitigate responses of offshore floating platforms and wave devices. The control of dynamic responses of these devices is important for reducing loads on structural elements and facilitating operations and maintenance (O&M) activities. This paper outlines the use of a tuned single liquid column damper for the control of a tension leg platform supported wind turbine. Theoretical studies were carried out and a scaled model was tested in a wave basin to assess the performance of the damper. The tests on the model presented in this paper correspond to a platform with a very low natural frequency for surge, sway and yaw motions. For practical purposes, it was not possible to tune the liquid damper exactly to this frequency. The consequent approach taken and the efficiency of such approach are presented in this paper. Responses to waves of a single frequency are investigated along with responses obtained from wave spectra characterising typical sea states. The extent of control is quantified using peak and root mean squared dynamic responses respectively. The tests present some guidelines and challenges for testing scaled devices in relation to including response control mechanisms. Additionally, the results provide a basis for dictating future research on tuned liquid column damper based control on floating platforms.

Wireless sensor nodes have a limited power budget, while they are often expected to be functional for a very long period of time once deployed in the field. Therefore, the minimization of energy consumption and energy harvesting technology are key tools for maximization of network lifetime and achieving self sustainability in Wireless Sensor Networks (WSN). This paper proposes an energy aware Adaptive Sampling Algorithm (ASA) for WSN with power hungry sensors and harvesting capabilities. An existing ASA developed for wireless sensor networks with power hungry sensors is optimized and enhanced to adapt the sampling frequency according to the available energy of the node. The proposed algorithm is evaluated using an in-field testbed with a sensor node which incorporates a wind harvester and a power hungry wind speed/direction sensor. Simulation and comparison between an existing ASA and the energy aware ASA in terms of energy durability are carried out using the measured wind energy and the wind speed over a period of a month. The simulation results have shown that using ASA in combination with energy aware function on the nodes can drastically increase the lifetime of a WSN node. Moreover, the energy aware ASA in conjunction with the node energy harvesting capability can lead towards a perpetual operation of WSN and significantly outperform state-of-the-art ASA.

Understanding of dynamic behaviour of offshore wind floating substructures is extremely important in relation to design, operation, maintenance and management of floating wind farms. This paper presents assessment of nonlinear signatures of dynamic responses of a scaled tension-leg platform (TLP) in a wave tank exposed to different regular wave conditions and sea states characterized by the Bretschneider, the Pierson–Moskowitz and the JONSWAP spectra. Dynamic responses of the TLP were monitored at different locations using load cells, a camera-based motion recognition system and a laser Doppler vibrometer. The analysis of variability of the TLP responses and statistical quantification of their linearity or nonlinearity, as non-destructive means of structural monitoring from the output-only condition, remains a challenging problem. In this study, the delay vector variance (DVV) method is used to statistically study the degree of nonlinearity of measured response signals from a TLP. DVV is observed to create a marker estimating the degree to which a change in signal nonlinearity reflects real-time behaviour of the structure and also to establish the sensitivity of the instruments employed to these changes. The findings can be helpful in establishing monitoring strategies and control strategies for undesirable levels or types of dynamic response and can help to better estimate changes in system characteristics over the life cycle of the structure.

Extreme wave parameters are used for engineering design in our seas and oceans, yet the methods used to determine them are non-standardized and can give highly variable output. With increased commercial activity in the marine sector, the importance of accurate extreme wave parameter determination has become increasingly apparent. This is particularly the case for marine renewable structures where even small over-predictions in design parameters can affect the whole feasibility of the project. This paper addresses the methods of extreme wave prediction currently in use, with a view to selecting the optimal method for the prediction of extreme wave conditions (Hs, Hmax and Tz) in coastal Irish waters. The paper identifies pitfalls and drawbacks of current extreme prediction methods, with particular attention given to the use of limited in time buoy data from coastal locations where development is to take place. In addition a new methodology of determining extreme wave periods, that is the wave periods occurring coincidentally with the most extreme wave heights, is established. This is important as the destructive energy of a wave is dependent on the wave period. By estimating the extreme wave energy and significant wave height, it is possible to formulate a method of reliably approximating the likely coincident wave period.

Cycling as a mode of travel provides an opportunity for many people to increase their levels of regular physical activity and contribute to their mental and physical health. Heart rate is often used as a means of measuring the intensity and energy expenditure of physical activity. However, heart rate is also linked to emotional factors such as anxiety and fear. Perceptions of risk due to external factors such as other road users and infrastructure may arouse such emotions in urban cyclists. The present study set out to investigate whether or not perceptions of risk among urban cyclists may lead to increased heart rates. Cyclists completed a test route in normal traffic conditions in Cork, Ireland and heart rates and self-reported risk ratings were recorded in real time. Evidence was found of a link between perceptions of risk and heart rates. This raises questions regarding the use of heart rate to estimate exercise intensity and energy expenditure during urban cycling. The perceptions of cyclists of their safety in relation to various road elements on familiar routes were also assessed, as well as specific events which they perceive to be high in risk. The results indicate that incidents involving car traffic and busy roads which offer no protection from interaction with car traffic are associated with greatest perceptions of risk. Environmental Protection Agency

Control of dynamic responses of renewable energy device platforms is important for their performance, safe operation and efficiency over their lifetime under regular and extreme wave conditions. Tuned Liquid Column Dampers (TLCDs) have been recently considered as a viable passive control mechanism in this regard but limited information is available in relation to their experimental performance. This paper compares scaled experiments conducted in two different ocean wave basins where floating offshore platforms were retrofitted with multiple TLCDs (MTLCDs). Performance of such MTLCDs in these scaled ocean wave basins are evaluated and compared considering control of dynamic responses for a specific objective. This paper shows the potential of MTLCDs to reduce motions in offshore platforms for different designs and platforms of MTLCDs and provides a comparison of the levels of reduction of dynamic responses achieved. The performance of MTLCDs in different wave basins create an experimental evidence base behind the potential use of such solutions, the objectives of such use and highlight related challenges and limitations.

This paper presents an experimental study on the development of normal strength Self compacting concrete (SCC) from uncontrolled burning of rice husk ash (RHA) as a partial replacement to cement and blended fine aggregate whilst maintaining satisfactory properties of SCC. Experiments on the fresh and hardened state properties have been carried out on RHA based SCC from uncontrolled burning. The dosages of RHA are limited to 0%, 20%, 30% and 40% by mass of the total cementitious material in the concrete. The experiments on fresh state properties investigate the filling ability, the passing ability and the segregation resistance of concrete. The experiments on hardened state properties investigate the compressive and the splitting tensile strengths. The water absorption level of the concrete with changing RHA levels has also been monitored. The experimental studies indicate that RHA based SCC developed from uncontrolled burning has a significant potential for use when normal strength is desired. R&D Department, Curtin University Sarawak under CSRF scheme

There has been focus in recent times in the creation of smart, wireless sensor networks for the purposes of Structural Health Monitoring of large scale civil infrastructure. However, the power requirements of such networks are dependent on finite batteries, which limit the effectiveness of such a system. The use of energy harvesters, however, offers a viable and attractive solution to this problem. This paper investigates the use of such energy harvesters not only to power wireless sensor nodes, but to also act in the process as a damage detection tool. The properties and creation of such energy harvesters is detailed in full. The effects of damage on a simply supported reinforced concrete beam are investigated through finite element analysis. The use of the energy harvesters for damage detection is subsequently investigated and the feasibility of using such harvesters is experimentally validated. The simultaneous power of wireless sensor nodes by the harvesters is determined and an energy harvesting circuit is examined in this regard. This paper establishes the basis and viability of using an energy harvesting system for use in this dual role.

This paper investigates the horizontal effect of fresh concrete on precast arches. A number of different models of horizontal pressure of fresh concrete are considered in this regard. The effects of fresh concrete on a precast arch are represented as a ratio of maximum normal stress from horizontal action of fresh concrete to the normal stress induced by the self-weight of the precast concrete arch. A parameter study on a number of geometric and operational variables was carried out. The implications of this horizontal loading from fresh concrete are discussed within the context of the potential financial effects.

In recent years, cycling has been recognized and is being promoted as a sustainable mode of travel. The perception of cycling as an unsafe mode of travel is a significant obstacle in increasing the mode share of bicycles in a city. Hence, it is important to identify and analyze the factors which influence the safety experiences of the cyclists in an urban signalized multi-modal transportation network. Previous researches in the area of perceived safety of cyclists primarily considered the influence of network infrastructure and operation specific variables and are often limited to specific locations within the network. This study explores the factors that are expected to be important in influencing the perception of safety among cyclists but were never studied in the past. These factors include the safety behavior of existing cyclists, the users of other travel modes and their attitude toward cyclists, facilities and network infrastructures applicable to cycling as well as to other modes in all parts of an urban transportation network. A survey of existing cyclists in Dublin City was conducted to gain an insight into the different aspects related to the safety experience of cyclists. Ordered Logistic Regression (OLR) and Principal Component Analysis (PCA) were used in the analysis of survey responses. This study has revealed that respondents perceive cycling as less safe than driving in Dublin City. The new findings have shown that the compliance of cyclists with the rules of the road increase their safety experience, while the reckless and careless attitudes of drivers are exceptionally detrimental to their perceived safety. The policy implications of the results of analysis are discussed with the intention of building on the reputation of cycling as a viable mode of transportation among all network users.

This paper investigates the potential for the harvesting of energy from the interaction between a train and a bridge through the use of piezoelectric materials. Two piezoelectric materials are considered in this regard, Lead Zirconate Titanate (PZT) and PolyVinyliDene Fluoride (PVDF). A finite element analysis of train bridge interaction is carried out. The friendliness of the different trains in terms of energy harvesting potential is assessed and quantified. The speed zones conducive to maximum harvested energy are identified. The use of train-bridge interaction ensures that the energy harvesting is carried out while the bridge is under operational conditions, with minimal to no impact on the existing operation of the bridge or the rail network during energy harvesting operations. The approach is useful in terms of designing a new generation of smart bridge infrastructures and potential retrofitting of existing structures.

Redistribution of stresses can be difficult to predict following damage in bridge structures. Such uncertainty is particularly important for designing, monitoring and decision making in relation to repair works. When continuous monitoring is deemed feasible on a damaged bridge, on-site rapid calibrations can be of significant importance in addressing these uncertainties and help in the decision making process. This paper presents a full scale example of a bridge structure damaged by impact loading and subsequently repaired in the presence of a monitoring sensor network. A site- based, rapid calibration of the damaged and undamaged beams in the bridge is presented based on full-scale experimentation and the relationship between the calibrations between the damaged and undamaged beams are investigated.

International audience; This paper presents a texture analysis based approach for the detection of damaged regions on the surface of infrastructural elements. A k-means clustering algorithm was used to partition regions with similar textural properties. Four texture measures were derived from a Grey Level Cooccurrence Matrix (GLCM) namely; contrast, homogeneity, entropy and Angular Second Moment (ASM). The approach is validated successfully on an image of a damaged concrete bridge beam. The performance of this Non-Destructive Testing (NDT) technique is evaluated for various values of k through the use of performance points in the Receiver Operating Characteristic (ROC) space. The technique may be deployed as a Structural Health Monitoring (SHM) tool to track the extent of surface damage, and can used in a Bridge Management System (BMS) to aid structured decision making and scheduling of repair work.

This paper proposes High Dynamic Range (HDR) imaging as a protocol for nondestructive-testing for the first time. HDR imaging protocol has been experimentally validated on images of pitting corrosion in this paper and has been further applied to isolate a range of image backgrounds that arise out of a number of environmental conditions. The superiority of HDR imaging over a standard imaging process has been demonstrated. The results indicate that the proposed protocol is not limited by the examples considered in this paper and can readily be applied to a number of infrastructure maintenance management related applications. The protocol complements and improves standard visual inspection techniques and expert opinions. This approach immediately lends itself to further mathematical and statistical analyses, both qualitative and quantitative. European Commission - European Regional Development Fund DURATINET (Durable Transport Infrastructures in the Atlantic Area Network) project, approved by the “Atlantic Area Transnational Program 2007-2013”

The European Union has expanded significantly in recent years. Sustainable trade within the Union leading to economic growth to the benefit of the 'old' and 'new' member states is thus extremely important. The road infrastructure is strategic and vital to such development since an uneven transport infrastructure, in terms of capacity and condition, has the potential to reinforce uneven development trends and hinder economic convergence of old and new member states. Significantly, in the decades since their design and construction, loading conditions have significantly changed for many major highway infrastructure elements/networks due primarily to increased freight volumes and vehicle sizes. This coupled with the gradual deterioration of a significant number of highway structures, due to their age, and the absence of a pan-European assessment framework can be expected to affect the smooth functioning of the infrastructure in its as-built condition, through increased periods of reduced flow due to planned and unplanned interventions for repair/rehabilitation. This paper reports the findings of a survey regarding the current status of the highway infrastructure elements in six countries within the European Union as reported by the owners/operators. The countries surveyed include a cross section of ‘existing’ older countries and ‘new’ accession countries. The current situations for bridges, culverts, tunnels and retaining walls are reported along with their potential replacement costs. The findings act as a departure point for further studies in support of a Centralized and/or Synchronised EU approach to Infrastructure Maintenance Management. Information in the form presented in this paper is central to any future decision making frameworks in terms of trade route choice and operations, monetary investment, optimized maintenance, management and rehabilitation of the built infrastructure and the economic integration of the newly joined member states. Deposited by bulk import

International audience; This paper presents an edge detection technique used in conjunction with preliminary image modification in order to identify and quantify regions of interest on a surface. In particular, this paper shall focus on applying this technique to examine the surface features of harbours facilities and offshore infrastructural elements affected by corrosion to determine the extent of damage present. The use of image processing compliments and enhances standard visual inspection techniques. It allows for a greater surface region to be inspected in less time, and in a more methodical manner, as well as having minimal prerequisites. The performance of this Non Destructive Testing (NDT) technique is assessed by probabilistic means through the use of receiver operating characteristic (ROC) curves. NDT techniques can provide useful information which on the condition of a structure, which can be fed directly into an Infrastructure Management System (IMS).

Marine Institute (Networking and Technology Transfer Initiative), Submitted Version, The increased size and flexibility of modern multi-Megawatt wind turbines has resulted in the dynamic behaviour of these structures becoming an important design consideration. The aim of this paper is to study the variation in natural frequency of wind turbine blades due to centrifugal stiffening and the potential use of semi-active tuned mass dampers (STMDs) in reducing vibrations in the flapwise direction with changing parameters in the turbine. The parameters considered were the rotational speed of the blades and the stiffness of the blades and nacelle. Two techniques have been employed to determine the natural frequency of a rotating blade. The first employs the Frobenius method to a rotating Bernoulli-Euler beam. These results are compared with the natural frequencies determined from an eigenvalue analysis of the dynamic model of the turbine including nacelle motion, which is developed in this paper. The model derived considers the structural dynamics of the turbine and includes the dynamic coupling between the blades and tower. The semi-active control system developed employs a frequency-tracking algorithm based on the short-time Fourier transform technique. This is used to continually tune the dampers to the dominant frequencies of the system. Numerical simulations have been carried out to study the effectiveness of the STMDs in reducing flapwise vibrations in the system when variations occur in certain parameters ofthe turbine. Steady and turbulent wind loading has been considered.

This paper presents an image processing based detection method for detecting pitting corrosion in steel structures. High Dynamic Range (HDR) imaging has been carried out in this regard to demonstrate the effectiveness of such relatively inexpensive techniques that are of immense benefit to Non – Destructive – Tesing (NDT) community. The pitting corrosion of a steel sample in marine environment is successfully detected in this paper using the proposed methodology. It is observed, that the proposed method has a definite potential to be applied to a wider range of applications.

This work isolates cases of nondetection, false alarm, and insensitivity for a general class of problems dealing with the detection and characterization of existence, location, and extent of singularities embedded in signals or in their derivatives when employing kurtosis- and pseudofractal-based methods for the detection and characterization process. The nondetection, false alarm, and insensitivity for these methods are illustrated on an example problem of damage identification and calibration in beams where the singularity to be identified lies in the derivative of the measured signal. The findings are general, not constrained to linear systems, and are potentially applicable to a wide range of fields including engineering system identification, fault detection, health monitoring of mechanical and civil structures, sensor failure, aerospace engineering, and biomedical engineering.