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The modelling of wave-structure interaction (WSI) has significant applications in understanding natural processes as well as securing the safety and efficiency of marine engineering. Based on the technique of Computational Fluid Dynamics (CFD) and the open-source simulation framework - OpenFOAM, this paper provides a state-of-the-art review of WSI modelling methods. The review categorises WSI scenarios and suggests their suitable computational approaches, concerning a rigid, deformable or porous structure in regular, irregular, non-breaking or breaking waves. Extensions of WSI modelling for wave-structure-seabed interactions and various wave energy converters are also introduced. As a result, the present review aims to help understand the CFD modelling of WSI and guide the use of OpenFOAM for target WSI problems.

Parametric excitation in the pitch/roll degrees of freedom (DoFs) can induce dynamic instability in floating cylinder-type structures such as spar buoys, floating offshore wind or wave energy converters. At certain frequency and amplitude ranges of the input waves, parametric coupling between the heave and pitch/roll DoFs results in undesirable large amplitude rotational motion. One possible remedy to mitigate the existence of parametric resonance is the use of dynamic vibration absorbers. Two prominent types of dynamic vibration absorbers are tuned mass dampers (TMDs) and nonlinear energy sinks (NESs), which have contrasting properties with regard to their amplitude and frequency dependencies when absorbing kinetic energy from oscillating bodies. This paper investigates the suppression of parametric resonance in floating bodies utilizing dynamic vibration absorbers, comparing the performance of TMDs against NESs for a test case considering a floating vertical cylinder. In addition to the type of dynamic vibration absorber utilized, the paper also examines the DoF which it acts on, comparing the benefits between attaching the vibration absorber to the primary (heave) DoF or the secondary (pitch) DoF. The results show that the TMD outperforms the NES and that it is more effective to attach the vibration absorber to the heave DoF when eliminating parametric resonance in the pitch DoF.

This study pertains to analysing the dynamical behaviour of a floating body undergoing parametric resonances. A simple vertical cylinder, representing a classical spar-buoy, is considered, limiting its motion to heave and pitch degrees of freedom. Its geometry and mass distribution are chosen such that a 2:1 ratio of heave to pitch/roll natural frequency makes the spar-buoy prone to parametric resonance. The system is then studied by the shooting method, combined with a pseudo-arclength continuation, and the harmonic balance procedure. Results show that an extensive bistable region exists, where stable parametric resonance coexists with a regular resonance response. The analysis also unveiled the existence of stable quasiperiodic motions existing in correspondence of both pitch and heave resonance. Results are qualitatively validated using a model based on the explicit nonlinear Froude–Krylov force calculation.

International audience; The paper presents results from the Collaborative Computational Project in Wave Structure Interaction (CCP-WSI) Blind Test Series 2. Without prior access to the physical data, participants, with numerical methods ranging from low-fidelity linear models to fully non-linear Navier–Stokes (NS) solvers, simulate the interaction between focused wave events and two separate, taut-moored, floating structures: a hemispherical-bottomed cylinder and a cylinder with a moonpool. The ‘blind’ numerical predictions for heave, surge, pitch and mooring load, are compared against physical measurements. Dynamic time warping is used to quantify the predictive capability of participating methods. In general, NS solvers and hybrid methods give more accurate predictions; however, heave amplitude is predicted reasonably well by all methods; and a WEC-Sim implementation, with CFD-informed viscous terms, demonstrates comparable predictive capability to even the stronger NS solvers. Large variations in the solutions are observed (even among similar methods), highlighting a need for standardisation in the numerical modelling of WSI problems.

The purpose of this study was to determine the effect of adding CIDAA to a subpopulation of an HMO that also had an RPM program. Patients taking insulin for >6 months with A1Cs >8.0% were selected from 3 cohorts, RPM + CIDAA (Group A) , RPM alone (Group B) and usual care (Group C) and followed for 6 months. Glucose readings of Group A patients, given a Bluetooth-enabled glucometer, were analyzed with dose adjustment recommendations sent to their providers (2 MDs, 1 PA) that they could accept or modify. Health educators contacted Group A and B patients for each RPM glucose value of 200 mg/dl and counseled them how to avoid subsequent episodes. Non-insulin drugs were not allowed to be added to Group A and B patients. A1C levels were measured at baseline and 6 months. Patient demographics, their A1C responses and alerts are shown in the Table. There were no differences among baseline A1Cs but significant differences from baseline. Groups A vs. B (P = 0.01) and A vs. C (P = 0.001) were significantly different but not B vs. C. All alerts (P = 0.02) and those >200 mg/dl (P = 0.002) were significantly less in Group A vs. B but alerts Disclosure J.S.Pulicharam: None. J.Davidson: None. M.B.Davidson: Other Relationship; Mellitus Health. Funding Mellitus Health, Inc

Measurement uncertainties are inevitable during physical wave tank tests. Therefore, when validating a numerical wave tank against experiments, knowledge of the uncertainties in the physical experiments, and the sensitivity of the body dynamics to such uncertainties, is crucial. Specifically, the inertial properties, as well as the location of the centre of mass (CoM), which are challenging to measure accurately, can have a significant influence on the system dynamics. On the basis of test cases of the Collaborative Computational Project in Wave Structure Interaction Blind Test Series 2, this paper presents a sensitivity analysis of the agreement between experimental and numerical data sets to the quality of the incident, focused wave, as well as the inertial properties and the location of the CoM. A significant influence on the modelled system dynamics can be observed when changing the system parameters, resulting in a variation of the observed error of up to 80 percentage points for pitch motion.

During the development and optimisation of wave energy converters, numerical wave tanks are useful tools, providing detailed insight into the hydrodynamic performance of devices. Specifically, computational fluid dynamics (CFD)-based numerical wave tanks (CNWTs) can deliver high-fidelity, high-resolution results for a wide range of test conditions. However, CNWTs come at significant computational cost and require more man-hours during model setup, compared to lower-fidelity, frequency domain-based models. The computational costs can only be significantly decreased by improving the numerical solvers or by increasing expenditure on computational power. The required man-hours for the model setup, however, can be reduced by streamlining the setup of CNWTs. To this end, the formulation of best-practice guidelines can expedite this streamlining. A step toward such best-practice guidelines is blind tests. This paper presents the CNWT used for the authors’ contribution to the Collaborative Computational Project in Wave–Structure Interaction (CCP-WSI) Blind Test Series 3. In the employed numerical wave tanks, a self-calibrating impulse source wave maker is implemented for wave generation. In addition to the numerical results, and the comparison with the recently disclosed experimental data, the paper presents the spatial and temporal convergence studies, as well as results for the numerical wave maker calibration. The numerical results show average deviations with the experimental data of less than 10%. Furthermore, a correlation between the accuracy of the numerical replication of the wave and the agreement between numerical and experimental device motion is highlighted.

This paper addresses the issue of hydrodynamic model identification from recorded tank test data, for a prototype wave energy device. The study focusses on nonlinear Kolmogorov–Gabor polynomial models, with linear models also used as a baseline reference. Six different experimental data sets are employed for model identification and validation, all derived from a JONSWAP input sea state. Compared to identification on numerical data, this study shows that the determination of model structure and orders is not so straightforward, but that consistent and useful computationally efficient models can be obtained. For the particular tests undertaken, in which the prototype device generally behaves as a wave follower, the nonlinear models only show very marginal performance improvement over the linear ones.

An active control method, to suppress the onset of pitch/roll parametric resonance on an oscillating water column (OWC) spar buoy, is proposed in this paper, which utilises a pressure relief valve at the top of the OWC air chamber. The paper examines the hypothesis that by opening the relief valve, to reduce the air chamber pressure difference and to decouple the dynamics of the spar buoy and the OWC within, the natural pitch/roll frequencies of the system will be shifted, allowing parametric resonance to be cancelled when its onset is detected. The paper reports on experiments, performed to test the stated hypothesis, with a small-scale model OWC spar buoy in a wave flume. Two configurations are considered and tested in a range of monochromatic waves (1) fully closed air chamber; (2) fully open chamber. The results partially confirm the hypothesis, demonstrating that the occurrence of parametric resonance observed for certain wave frequencies when the chamber is closed does not occur when the chamber is open. However, the change in the natural pitch/roll frequencies between the two configurations is very small, and parametric resonance occurs in both confurations for waves with twice this frequency.

The largest challenge for appropriate adjustment of insulin doses for PCPs is lack of time and for patients is provision of enough blood glucose values. Potential solutions to these two issues are CIDAA for PCPs and CGM for patients. The combination of these two innovations was evaluated in a FQHC serving a poor, mostly minority, medically underserved population. Poorly controlled diabetic patients (A1C levels >9.0%) are referred to a specially trained clinical pharmacist (CP). The pharmacy department supported CGM (Free Style Libre Pro) for 13 patients, 10 on basal insulin alone and 3 on basal/bolus who had ≥2 visits. Their downloaded CGM results were analyzed by FDA-cleared CIDAA and a report containing recommendations for dose adjustments that the CP could modify or accept was provided within 30 seconds. The mean number of reports was 4.8 which covered a period of 97 days. The glycemic responses are shown in the Table. Total insulin doses increased by 42%. Conclusion: Analysis of CGM results by CIDAA addresses the two largest challenges of adjusting insulin doses for PCPs and patients. Using both together has the potential of markedly improving A1C levels in poorly controlled insulin-requiring diabetic patients. Disclosure M.B. Davidson: None. J. Davidson: Employee; Self; Mellitus Health.

Energy maximising controllers (EMCs), for wave energy converters (WECs), based on linear models, are attractive in terms of simplicity and computation. However, such (Cummins equation) models are normally built around the still water level as an equilibrium point and assume small movement, leading to poor model validity for realistic WEC motions, especially for the large amplitude motions obtained by a well controlled WEC. The method proposed here is to use an adaptive algorithm to estimate the control model online, whereby system identification techniques are employed to identify a linear model that is most representative of the actual controlled WEC behaviour. Using exponential forgetting, the linear model can be regularly adapted to remain representative in changing operational conditions. To that end, this paper presents a novel adaptive controller based on a receding horizon pseudospectral formulation. A case study is presented, providing an preliminary evaluation of the adaptive receding horizon pseudospectral control (ARHPC), using simulations based on both linear hydrodynamic modelling and computational fluid dynamics (CFD). The parameter adaptation is shown to behave as expected in both different simulation environments. The ARHPC is observed to perform well in irregular sea states, absorbing more power than its nonadaptive counterpart. The optimal trajectory calculated by the adaptive model is seen to have a smaller motion and power take-off (PTO) forces, compared to those calculated by the nonadaptive linear control model, due to the increased amount of hydrodynamic resistance estimated by the adaptive model, as identified from the nonlinear viscous CFD simulation.

Scaled model tests are an important step during the research and development of wave energy converters (WECs). While such scaled model tests in physical wave tanks are prone to undesired scaling effects due to e.g. mechanical artefacts and/or fluid effects, numerical wave tanks (NWTs) provide excellent tools for the analysis of WECs across a range of scales, overcoming the limitations of the physical test environment. Simultaneous scaling based on the Froude and Reynolds number is achievable in physical wave tanks only with significant effort, whereas NWTs allow the adjustment of fluid properties, such as viscosity, in an easy manner, thereby catering for Froude and Reynolds similarity. This study exploits the capabilities of a high-fidelity, computational fluid dynamics based, NWT and investigates the hydrodynamic scaling effects for the heaving buoy Wavestar WEC. Various test cases, relevant for WEC applications and with progressively increasing complexity, are considered to develop a comprehensive understanding of the scaling effects. Results show that significant scaling effects occur for the viscous component of the hydrodynamic loads on the WEC hull, while the system dynamics and total (viscous + pressure) loads are relatively unaffected by scaling effects.

Parametric resonance is a dynamic instability due to the internal transfer of energy between degrees of freedom. Parametric resonance is known to cause large unstable pitch and/or roll motions in floating bodies, and has been observed in wave energy converters (WECs). The occurrence of parametric resonance can be highly detrimental to the performance of a WEC, since the energy in the primary mode of motion is parasitically transferred into other modes, reducing the available energy for conversion. In addition, the large unstable oscillations produce increased loading on the WEC structure and mooring system, accelerating fatigue and damage to the system. To remedy the negative effects of parametric resonance on WECs, control systems can be designed to mitigate the onset of parametric resonance. A key element of such a control system is a real-time detection system, which can provide an early warning of the likely occurrence of parametric resonance, enabling the control system sufficient time to respond and take action to avert the impending exponential increase in oscillation amplitude. This paper presents the first application of a real-time detection system for the onset of parametric resonance in WECs. The method is based on periodically assessing the stability of a mathematical model for the WEC dynamics, whose parameters are adapted online, via a recursive least squares algorithm, based on online measurements of the WEC motion. The performance of the detection system is demonstrated through a case study, considering a generic cylinder type spar-buoy, a representative of a heaving point absorber WEC, in both monochromatic and polychromatic sea states. The detection system achieved 95% accuracy across nearly 7000 sea states, producing 0.4% false negatives and 4.6% false positives. For the monochromatic waves more than 99% of the detections occurred while the pitch amplitude was less than 1/6 of its maximum amplitude, whereas for the polychromatic waves 63% of the detections occurred while the pitch amplitude was less than 1/6 of its maximum amplitude and 91% while it was less than 1/3 of its maximum amplitude.

Computational Fluid Dynamics (CFD) simulations, based on Reynolds-AveragedNavier&ndash, Stokes (RANS) models, are a useful tool for a wide range of coastal and offshore applications,providing a high fidelity representation of the underlying hydrodynamic processes. Generating inputwaves in the CFD simulation is performed by a Numerical Wavemaker (NWM), with a variety ofdifferent NWM methods existing for this task. While NWMs, based on impulse source methods, havebeen widely applied for wave generation in depth averaged, shallow water models, they have notseen the same level of adoption in the more general RANS-based CFD simulations, due to difficultiesin relating the required impulse source function to the resulting free surface elevation for non-shallowwater cases. This paper presents an implementation of an impulse source wavemaker, which is ableto self-calibrate the impulse source function to produce a desired wave series in deep or shallowwater at a specific point in time and space. Example applications are presented, for a NumericalWave Tank (NWT), based on the open-source CFD software OpenFOAM, for wave packets in deepand shallow water, highlighting the correct calibration of phase and amplitude. Furthermore, thesuitability for cases requiring very low reflection from NWT boundaries is demonstrated. Possibleissues in the use of the method are discussed, and guidance for accurate application is given.

Wave energy conversion is an active field of research, aiming to harness the vast amounts of energy present in ocean waves. An essential development trajectory towards an economically competitive wave energy converter (WEC) requires early device experimentation and refinement using numerical tools. OpenFOAM\(^{\textregistered }\) is proving to be a useful numerical tool for WEC development, having been increasingly employed in recent years to simulate and analyse the performance of WECs. This chapter reviews the latest works employing OpenFOAM\(^{\textregistered }\) in the field of wave energy conversion, and then presents the new application, of evaluating energy maximising control systems (EMCSs) for WECs, in an OpenFOAM\(^{\textregistered }\) numerical wave tank (NWT). The advantages of using OpenFOAM\(^{\textregistered }\) for this application are discussed, and implementation details for simulating a controlled WEC in an OpenFOAM\(^{\textregistered }\) NWT are outlined. An illustrative example is given, and results are presented, highlighting the value of evaluating EMCSs for WECs in an OpenFOAM\(^{\textregistered }\) NWT.

Adjusting insulin doses is very challenging for primary care physicians because of infrequent office visits and time constraints at the visit. For patients, frequent office visits are a barrier. We have used FDA-approved, computerized insulin dose adjustment algorithms and remote glucose monitoring to circumvent both of these issues. Diabetic patients in a safety net clinic who took insulin for at least 6 months with A1C levels ?8.0% were enrolled in a study in which an iHealth glucose meter was attached to a smartphone containing an app downloaded from the Web that transmitted the glucose values to a secure, HIPAA-approved server. There the values were analyzed by the algorithms and a report with recommendations for dose changes was generated and sent to a clinic nurse practitioner every 2-3 weeks who could accept or modify the recommendations. A clinic staff individual contacted the patient with the insulin dose changes. Twenty-eight diabetic patients (one type 1) have reached 3 months. Their mean age (± SD) was 55.9 ± 8.6 years, 15 were females and 13 were males. There were 20 Latinos, 4 African-Americans, 3 Caucasians, and 1 Asian. Their insulin regimens were: basal alone - 11, basal/bolus - 14 and self-mixed/split - 3. Non-insulin drugs were not changed. Their baseline A1C levels (± SD) of 10.0% ± 1.2 decreased by 1.9% ± 0.9 to 8.1% ± 1.1 after 3 months. Their total insulin dose increased by 24%. There were no episodes of severe hypoglycemia (requiring 2nd party assistance) nor emergency room visits for hypoglycemia. Conclusion: Remote glucose monitoring utilizing computerized insulin dose adjustment algorithms to analyze glucose values and generating recommendations for dose changes at more frequent intervals markedly improved A1C levels in poorly controlled diabetic patients in the absence of office visits. Disclosure M.B. Davidson: Employee; Self; Insulin Algorithms, Inc. J. Davidson: Employee; Self; Insulin Algorithms.

Mathematical modelling of wave energy devices has many uses, including power production assessment, simulation of device motion and as a basis for model-based control design. Apart from computationally heavy approaches, such as those based on computational fluid dynamics (CFD) and smooth particle hydrodynamics (SPH), the vast majority of models employed in the simulation and analysis of wave energy converters (WECs) are based on boundary-element methods (BEMs). While BEM models have been shown to be useful, they have the inherent limitation that they are linearised around the still water level, with validity only on the immediate vicinity of this equilibrium point. In this paper, we develop a new modelling methodology, which combines the fidelity of CFD models with the computational attractiveness of BEM-type models. This flexible methodology can give representative linear models, or be extended into the nonlinear domain, as desired.

Background: Asthma-like symptoms are common in those under physical duress. It has been demonstrated that 21% of athletes with presumed asthma had no objective evidence at assessment (1). Military personnel who develop symptoms of asthma are frequently declared unfit for service pending medical review. This has ramifications for the recruit and leads to avoidable healthcare costs. Aims: · To know the percentage of recruits referred with asthma who have objective evidence at assessment. · To understand the effects of treatment on the ability to return to unrestricted duties in military personnel. Methods: A retrospective review of military personal with a presumed diagnosis of asthma (July 2012 to June 2016). Diagnosis based on more than a 12% improvement of forced expiratory volume in one second (FEV1) to inhaled short acting beta agonist (SABA) and/or a positive methacholine challenge test. Asthma treatment was adjusted in line with British Thoracic Society (BTS) guidelines. Results: 40% (48/121) of presumed asthmatics had no objective evidence of asthma. 60% (44/73) of those with asthma were on no treatment or SABA only. Appropriate treatment meant that post-review 46/50 (92%) patients who were temporarily downgraded were subsequently recommended for unrestricted duties. Conclusions: At referral, the majority of recruits were on no medication or inhaled SABA only. Appropriate treatment allowed a return to unrestricted duties in most cases. Prompt referral for investigation and titration of treatment is likely to reduce time out of service. 1) Dickinson JW et al. Impact of changes in the IOC-MC asthma criteria: a British perspective. Thorax. 2005;60(8):629-32.

The modelling approach presented in this chapter is that of system identification, where models are determined from input/output data measured from the system under study. Models identified from recorded wave energy converter (WEC) data can accurately describe WEC behaviour, provided the data is of a sufficiently high quality. The chapter details generating data for the system identification process and outlines the requirements of the data to ensure representative models are obtained. Different parametric model structures are presented, along with identification algorithms to determine the optimum parameter values for the models. A number of case studies illustrating the use of system identification to obtain numerical models of WECs are given.

While linear and nonlinear system identification is a well established field in the control system sciences, it is rarely used in wave energy applications. System identification allows the dynamics of the system to be quantified from measurements of the system inputs and outputs, without significant recourse to first principles modelling. One significant obstacle in using system identification for wave energy devices is the difficulty in accurately quantifying the exact incident wave excitation, in both open ocean and wave tank scenarios. However, the use of numerical wave tanks (NWTs) allow all system variables to be accurately quantified and present some novel system tests not normally available for experimental devices. Considered from a system identification perspective, this paper examines the range of tests available in a NWT from which linear and nonlinear dynamic models can be derived. Recommendations are given as to the optimal configuration of such system identification tests.Copyright © 2015 by ASME

To facilitate commercially relevant numerical design optimization in wave energy conversion accurate and validated simulations of wave body interactions are necessary. Wave energy, more so than almost any other industry, can benefit from such numerical optimization because of the high cost and long period of design iteration in experimental and field testing. For the foreseeable future wave energy device design and optimization will continue to rely heavily on potential flow solvers. Two important prerequisites to successfully using simulations based on these codes are firstly a need to validate the simulation implementation by comparison with experiment and secondly a need to supplement the potential flow solution with experimentally (or CFD) derived coefficients for the forces that are neglected by the potential flow solver. This paper attempts to address both of these prerequisites. A comparison of numerical simulations and physical wave tank experiments on a submerged horizontal cylinder moored in waves is presented. Good agreement between numerical model and experiment is achieved. At operating points where the body response is linear a numerical model based purely on potential flow and linear mooring stiffness achieves excellent results and at operating points where the body response is non-linear a time domain model with frequency independent quadratic damping is shown to give good agreement for a wide range of wave periods and amplitudes.

Size and power requirements of wireless sensor nodes are gradually decreasing and this has allowed data collection across a range of spatial and temporal ranges. These nodes have power requirements that often necessitate batteries as an energy source. As the power requirements decrease for these sensors, alternative energy sources become more attractive. One such technology is thermal energy harvesting. Thermal energy harvesting requires a differential temperature between a heat source and a cool sink. As heat energy flows from source to the sink, energy can be harvested and utilized to power sensor nodes. By exploiting the temperature difference between a sun-warmed plate and a heat sink immersed in water, electrical energy can be harvested. The proposed concept utilizes a thermoelectric device to convert solar energy into electrical power. Initial experiments were carried out at the CSIRO Energy Centre for a variety of winter time intervals in 2009, with peak power outputs in the order of 50mW. Results indicate such a system could power a wireless sensor node continuously at ocean, lake and river water interfaces. We are presently in the process of evaluating the concept by powering a CSIRO FleckTM wireless node to transmit water temperature and battery voltage data.

Over the last decade, wireless computing and mobile devices have decreased in size and power requirements. These devices traditionally had significant power requirements that necessitated the use of batteries as their power source. However, as the power requirements are reducing, with wireless sensor nodes rarely exceeding 75mW, alternative means of power provision become available. One of these alternatives is the use of thermal energy harvesting from waste heat or environmental sources. This report discusses the field of thermal energy harvesting, with a particular focus on those thermal technologies that provide direct electricity as output. There are a number of technologies in this field. The general technologies discussed in this report are thermoelectric devices, such as devices utilising the Seebeck effect, thermocouples and, thermionics. Sources of thermal energy discussed include solar, the human body, vehicle exhaust systems and subsurface heating. Solar has an obvious advantage of being a very large source of energy. Cases studies are presented to show magnitudes and the daily variation of power output from Seebeck style thermoelectric devices. Overall, this report reveals that while present thermal energy harvesting technologies suffer from very low efficiencies, there are a number of promising technologies that are increasing in reliability and efficiency. This, along with a continuing decrease in power requirements on the demand side of the equation, marks thermal energy harvesting as a very promising field of research.

Seventy percent of the Earth's surface is covered by water and all living things are dependent upon this resource. As such there are many applications for monitoring environmental data in and around aquatic environments. Wireless sensor networks are poised to revolutionise this process as the reduction in size and power consumption of electronics are opening up many new possibilities for these networks. Aquatic sensor nodes are usually battery powered, so as sensor networks increase in number and size, replacement of depleted batteries becomes time consuming, wasteful and in some cases unfeasible. Additionally, a battery that is large enough to last the life of a sensor node would dominate the overall size of the node, and thus would not be very attractive or practical. As a result, there is a clear need to explore novel alternatives to power sensor nodes/networks, as existing battery technology hinders the widespread deployment of these networks. By harvesting energy from their local environment, sensor networks can achieve much greater run-times, years not months, with potentially lower cost and weight. A potential renewable energy source in aquatic environments exists via the temperature gradient present between the water layer and ambient air. A body of water will be either a few degrees warmer or colder than the air directly above it dependant on its latitude, time of year and time of day. By incorporating a thermal energy harvesting device into the sensor node deployment which promotes the flow of heat energy across the thermal gradient, a portion of the energy flow can be converted into useable power for the sensor node. To further increase this temperature difference during the day the top section can be heated to temperatures above the ambient air temperature by absorbing the incoming sunlight. As an initial exploration into the potential of this novel power source we have developed a model of the process. By inputting environmental data, the model calculates the power which can be extracted by a thermal energy harvesting device. Initial outputs show a possibility of up to 10W/m2 of power available from measured sites assuming a thermal energy harvester operating with Carnot efficiency.

By scavenging energy from their local environment, portable electronic devices such as mobile phones, radios and wireless sensors can achieve greater run-times with potentially lower weight. Vibration energy harvesting is one such approach where energy from parasitic vibrations can be converted into electrical energy, through the use of piezoelectric and electromagnetic transducers. Parasitic vibrations come from a range of sources such as wind, seismic forces and traffic. Existing approaches to vibration energy harvesting typically utilise a rectifier circuit, which is tuned to the resonant frequency of the harvesting structure and the dominant frequency of vibration. We have developed a novel approach to vibration energy harvesting, including adaption to non-periodic vibrations so as to extract the maximum amount of vibration energy available. Experimental results of an experimental apparatus using off-the-shelf transducer (i.e. speaker coil) show mechanical vibration to electrical energy conversion efficiencies of 27 - 34%. However, simulations of a more electro-mechanical efficient and lightly damped transducer show conversion efficiencies in excess of 80%.

The analysis of wave-current interaction (WCI) in numerical wave tanks (NWTs) requires the simultaneous generation of a current velocity profile and free surface waves. This paper presents a novel approach to simulate the WCI using an impulse-source-based methodology together with a numerical beach implementation. Three additional terms are added to the momentum equation, to incorporate current and wave generation, as well as the numerical beach. The model components, i.e. wave and current generation, and WCI, are verified independently against two sets of reference data. The results show excellent agreement for the wave-only case, while for the current-only and thus WCI, some model weaknesses can be identified.

Computational fluid dynamics (CFD) based numerical wave tanks (NWTs) can provide valuable insight into the hydrodynamic performance of wave energy converters (WECs). Being able to capture hydrodynamic non-linearities, CFD-based NWTs (CNWTs) allow the analysis of WECs over a wide range of test conditions, such as sea states, power take-off control settings and model scale. The capabilities of a CNWT are exploited in this paper, which aims at the analysis of the scaling effects of two moored, point-absorber type WECs, exposed to focused waves. To this end, three different scales are considered: 1:1, 1:10 and 1:10PWT. The latter, 1:10PWT scale, refers to the typical scale used in physical wave tanke (PWTs), complying with Froude similitude, but violating Reynolds similitude. In the 1:10 scale model, fluid viscosity is scaled, inline with the geometrical properties, thereby achieving both Froude and Reynolds similitude. From the results, average differences between the three considered scales of around 5% have been observed, and the overall biggest sensitivity to scale effects can be found in the surge and pitch degree of freedom.

A numerical wave tank (NWT) based on ComputationalFluid Dynamics (CFD) provides a useful tool for the analysis of offshore renewable energy (ORE) systems, such as wave energy converters (WECs). NWT experiments, of WECoperation, rely on accurate wave generation and absorption at the NWT boundaries. To tackle this problem, different methodologies, termed as numerical wave makers (NWMs), are available. The performance of these NWMs are often sensitive to properties of the experiment being performed, such as the frequency spectrum of the input sea state, the CFD solver used and/or the internal settings of the NWM. This paper discusses the desiredNWM capabilities, for effective analysis of marine systems, and then proposes a set of test cases to assess these capabilities for a given NWM. Results are presented for a sample NWM, the OpenFOAM toolbox OLAFOAM, and demonstrate the sensitivity of the NWM to the desired wave conditions and the global solver settings.The assessment methodologies introduced in this paper, and demonstrated for a single type of NWM, lay the groundwork for future evaluation and comparison of different NWM types, enabling appropriate NWM selection for NWT analysis of WECs