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To achieve persistent systems in the future, autonomous underwater vehicles (AUVs) will need to autonomously dock onto a charging station. Here, reinforcement learning strategies were applied for the first time to control the docking of an AUV onto a fixed platform in a simulation environment. Two reinforcement learning schemes were investigated: one with continuous state and action spaces, deep deterministic policy gradient (DDPG), and one with continuous state but discrete action spaces, deep Q network (DQN). For DQN, the discrete actions were selected as step changes in the control input signals. The performance of the reinforcement learning strategies was compared with classical and optimal control techniques. The control actions selected by DDPG suffer from chattering effects due to a hyperbolic tangent layer in the actor. Conversely, DQN presents the best compromise between short docking time and low control effort, whilst meeting the docking requirements. Whereas the reinforcement learning algorithms present a very high computational cost at training time, they are five orders of magnitude faster than optimal control at deployment time, thus enabling an on-line implementation. Therefore, reinforcement learning achieves a performance similar to optimal control at a much lower computational cost at deployment, whilst also presenting a more general framework.

This study concerns how the Online Coins of the Roman Empire (OCRE) database of imperial coins can support Year 12 students to learn about Roman imperial image on coins for their Classical Civilisation Imperial Image paper. In observations of lessons, the author noted that pupils struggled to remember and identify coins which were prescribed sources for their examinations and appeared disengaged in other teaching methods. The author taught pupils how to use the OCRE database. When using the database, all pupils seemed more interested and engaged in the study of coins. Indeed, pupils’ classwork and written essays showed that, after using the database, their use of coin-related terminology and metalanguage increased, they wrote more detailed descriptions of coins, and considered how coins contributed to Augustus’ imperial image. The author recommends that teachers allow an extended period for students to become familiar with the software before formal activities. He suggests engaging activities for students such as finding and presenting coins to the class, curating displays of coins, or finding coins depicting various animals in the quickest time. Teachers could vary the time on each activity depending on the lesson time available.

This paper presents a numerical performance evaluation of the leading edge tubercles hydrofoil with particular focus on a fully turbulent flow regime. Efforts were focused on the setting up of an appropriate numerical approach required for an in-depth analysis of this phenomenon, being able to predict the main flow features and the hydrodynamic performance of the foil when operating at high Reynolds numbers. The numerical analysis was conducted using an improved delayed detached eddy simulation for Reynolds numbers corresponding to the transitional and fully turbulent flow regimes at different angles of attack for the pre-stall and post-stall regimes. The results show that tubercles operating in turbulent flow improve the hydrodynamic performance of the foil when compared to a transitional flow regime. Flow separation was identified behind the tubercle troughs, but was significantly reduced when operating in a turbulent regime and for which we have identified the main flow mechanisms. This finding confirms that the tubercle effect identified in a transitional regime is not lost in a turbulent flow. Furthermore, when the hydrofoil operates in the turbulent flow regime, the transition to a turbulent regime takes place further upstream. This phenomenon suppresses a formation of a laminar separation bubble and therefore the hydrofoil exhibits a superior hydrodynamic performance when compared to the same foil in the transitional regime.

Aging ships and offshore structures face harsh environmental and operational conditions in remote areas, leading to age-related damages such as corrosion wastage, fatigue cracking, and mechanical denting. These deteriorations, if left unattended, can escalate into catastrophic failures, causing casualties, property damage, and marine pollution. Hence, ensuring the safety and integrity of aging ships and offshore structures is paramount and achievable through innovative healthcare schemes. One such paradigm, digital healthcare engineering (DHE), initially introduced by the final coauthor, aims at providing lifetime healthcare for engineered structures, infrastructure, and individuals (e.g., seafarers) by harnessing advancements in digitalization and communication technologies. The DHE framework comprises five interconnected modules: on-site health parameter monitoring, data transmission to analytics centers, data analytics, simulation and visualization via digital twins, artificial intelligence-driven diagnosis and remedial planning using machine and deep learning, and predictive health condition analysis for future maintenance. This article surveys recent technological advancements pertinent to each DHE module, with a focus on its application to aging ships and offshore structures. The primary objectives include identifying cost-effective and accurate techniques to establish a DHE system for lifetime healthcare of aging ships and offshore structures—a project currently in progress by the authors.

The levellised cost of energy of wave energy converters (WECs) is not competitive with fossil fuel-powered stations yet. To improve the feasibility of wave energy, it is necessary to develop effective control strategies that maximise energy absorption in mild sea states, whilst limiting motions in high waves. Due to their model-based nature, state-of-the-art control schemes struggle to deal with model uncertainties, adapt to changes in the system dynamics with time, and provide real-time centralised control for large arrays of WECs. Here, an alternative solution is introduced to address these challenges, applying deep reinforcement learning (DRL) to the control of WECs for the first time. A DRL agent is initialised from data collected in multiple sea states under linear model predictive control in a linear simulation environment. The agent outperforms model predictive control for high wave heights and periods, but suffers close to the resonant period of the WEC. The computational cost at deployment time of DRL is also much lower by diverting the computational effort from deployment time to training. This provides confidence in the application of DRL to large arrays of WECs, enabling economies of scale. Additionally, model-free reinforcement learning can autonomously adapt to changes in the system dynamics, enabling fault-tolerant control.

The fixed-dose combination of any two antihypertensive drugs from different drug classes is typically more effective in reducing blood pressure than a dose increase of component monotherapy. We assessed the efficacy and safety of a fixed-dose combination of a vasodilating β blocker (nebivolol) and an angiotensin II receptor blocker (valsartan) in adults with hypertension. We did an 8-week, phase 3, multicentre, randomised, double-blind, placebo-controlled, parallel-group trial at 401 US sites. Participants (age ≥18 years) with hypertension but with blood pressure less than 180/110 mm Hg were randomly assigned (2:2:2:2:2:2:2:1) by a 24-h interactive web response system in blocks of 15 to 4 weeks of double-blind treatment with nebivolol and valsartan fixed-dose combination (5 and 80 mg/day, 5 and 160 mg/day, or 10 and 160 mg/day), nebivolol (5 mg/day or 20 mg/day), valsartan (80 mg/day or 160 mg/day), or placebo. Doses were doubled in weeks 5–8; results are reported according to the final dose. Participants and research staff were masked to treatment allocation. The primary and key secondary endpoints were changes from baseline to week 8 in diastolic and systolic blood pressure, respectively. The primary statistical comparison was between the highest fixed-dose combination dose and the highest monotherapy doses; lower doses were then compared if this comparison was positive (Hochberg method for multiple testing). Efficacy analyses were by intention to treat. Safety assessments included monitoring of adverse events. Continuous efficacy parameters were analysed using an ANCOVA model; binary outcomes were analysed using a logistic regression model. This study is registered with ClinicalTrials.gov, NCT01508026. Between Jan 6, 2012, and March 15, 2013, 4161 patients were randomly assigned (277 to placebo and 554–555 to each active comparator group), 4118 of whom were included in the primary analysis. At week 8, the fixed-dose combination 20 and 320 mg/day group had significantly greater reductions in diastolic blood pressure from baseline than both nebivolol 40 mg/day (least-squares mean difference −1·2 mm Hg, 95% CI −2·3 to −0·1; p=0·030) and valsartan 320 mg/day (−4·4 mm Hg, −5·4 to −3·3; p<0·0001); all other comparisons were also significant, favouring the fixed-dose combinations (all p<0·0001). All systolic blood pressure comparisons were also significant (all p<0·01). At least one treatment-emergent adverse event was experienced by 30–36% of participants in each group. Nebivolol and valsartan fixed-dose combination is an effective and well-tolerated treatment option for patients with hypertension. Forest Research Institute.

Underwater transportation is an essential approach for scientific exploration, maritime construction and military operations. Determining the hydrodynamic coefficients for a complex underwater transportation system comprising multiple vehicles is challenging. Here, the suitability of a quick and less costly semi-empirical approach to obtain the hydrodynamic coefficients for a complex transportation system comprising two Unmanned Underwater Vehicles (UUVs) is investigated, where the interaction effects between UUVs are assumed to be negligible. The drag results were verified by Computational Fluid Dynamics (CFD) analysis at the steady state. The semi-empirical results agree with CFD in heave and sway; however, they were overpredicted in surge due to ignoring the wake effects. Furthermore, experiments were performed for the validation of the time-domain motion simulations with semi-empirical and CFD results. The simulations which were performed with the CFD drags were close to the experiments. The semi-empirical approach could be relied on once a correction parameter is included to account for the interactive effect between multiple UUVs. Overall, this work makes a contribution by deriving a semi-empirical approach for the dynamic and controlling system of dual UUVs, with CFD and experiments applied to ascertain its accuracy and potential improvement.

To estimate the response of wave energy converters to different sea environments accurately is an ongoing challenge for researchers and industry, considering that there has to be a balance between guaranteeing their integrity whilst extracting the wave energy efficiently. For oscillating wave surge converters, the incident wave field is changed due to the pitching motion of the flap structure. A key component influencing this motion response is the Power Take-Off system used. Based on OpenFOAM, this paper includes the Power Take-off to establish a realistic model to simulate the operation of a three-dimensional oscillating wave surge converter by solving Reynolds Averaged Navier-Stokes equations. It examines the relationship between incident waves and the perturbed fluid field near the flap, which is of great importance when performing in arrays as neighbouring devices may influence each other. Furthermore, it investigates the influence of different control strategy systems (active and passive) in the energy extracted from regular waves related to the performance of the device. This system is estimated for each wave frequency considered and the results show the efficiency of the energy extracted from the waves is related to high amplitude pitching motions of the device in short periods of time.

T-foil and stern tabs were installed on a wave-piercing catamaran (Incat Tasmania Hull 061) to improve ship motions and passenger comfort. More than 40 total effective hours of sea trials were conducted by the US Navy in 2004, encountering sea states 4–5 in the Atlantic Ocean near the United Kingdom. In this paper the influence of a ride-control system (RCS) on the heave and pitch response amplitude operator (RAO) of the full-scale high-speed catamaran was investigated using the sea trial data. The reduction in motion sickness incidence (MSI) was estimated in order to examine the effectiveness of the RCS in improving passenger comfort. With the existing control algorithm, the vertical accelerations were found to be best controlled by the active T-foil working together with the active stern tabs, while the pitch RAO was mainly mitigated by deploying only the stern tabs. About a 23% reduction was observed in the peak heave RAO with deployment of an active T-foil. The MSI can be reduced by up to 23% with respect to the cases with stern tabs only, depending on the encountered wave conditions, based on ISO recommendation for MSI calculation of a 2-h seaway passage.