Search Results (2,085)

Underwater communication is essential for marine research, yet saline environments pose significant challenges as electromagnetic waves suffer from severe attenuation and optical systems face scattering. Consequently, acoustic transmission remains the most practical method for medium- to long-range communication. This study investigates the impact of salinity, transmission frequency, and propagation distance on signal integrity, specifically focusing on the feasibility of using a square-wave carrier with On-Off Keying (OOK) modulation as a simpler, low-cost alternative to traditional sinusoidal frequency-shift keying (FSK). Experiments were conducted in a custom glass tank and analyzed via MATLAB. The results reveal that increased salinity and higher frequencies led to greater signal distortion and attenuation, which complicates reliable binary recovery. However, despite these environmental hurdles, the study demonstrates that square-wave OOK allows for successful binary data recovery over short distances. The findings suggest that simplified modulation schemes could potentially be used for short-range underwater communication in controlled environments, particularly where minimizing system complexity is of concern. Ultimately, the work provides valuable insights into how environmental factors influence acoustic signal integrity, offering a preliminary basis for future development of accessible and efficient underwater communication platforms targeted to shallow water communication. Full article

Liquid storage tanks are widely used in sectors such as water treatment, oil and gas, food processing, and chemical manufacturing. Knowing the exact amount of liquid in a tank is essential for ensuring safety, preventing spills, and optimizing process control; therefore, the liquid level in a tank must be maintained at a precise reference point. This is where liquid level control for tanks becomes crucial and constitutes a fundamental problem in the industrial sector due to nonlinearities, multivariable coupling, and stochastic disturbances. Given the drawbacks of available control methods, such as classical Model Predictive Control (MPC), which are highly dependent on model accuracy and struggle to reject complex stochastic noise, predicting random disturbances represents a major technological challenge. A new approach is proposed to specifically address the problem and challenge of the four-tank system, where water levels in two lower tanks must be controlled by two pumps, often with varying delays and significant parameter disturbances. To establish a relationship between expected performance and MPC parameters, this approach uses a novel hybrid nonlinear MPC, Extended State Observer, and Physics-Informed Neural State Estimation (NMPC-ESO-PINSE) architecture. A Physics-Informed Neural State Estimation (PINSE) layer, chosen for its learning capacity, is designed to filter sensor noise by applying Bernoulli’s physical laws, while an Extended State Observer (ESO) is integrated to capture and compensate for unmodeled uncertainties in the process. Finally, a proposed hybrid (NMPC-ESO-PINSE) strategy leverages these clean, physically consistent state estimations to solve a non-convex optimization problem via Sequential Quadratic Programming (SQP), computing optimal pump voltages. Extensive numerical simulations demonstrate the superior resilience of this decoupled framework against parametric drifts and continuous noise sequences, yielding a $+27.36\%$ reduction in global Root Mean Square Error (RMSE) compared to standard NMPC, accelerating the closed-loop settling time to $15.2 \mathrm{s}$, and restricting transient overshoot to just $0.18\%$. Full article

Ammonia is a promising zero-carbon energy carrier for maritime decarbonisation, but its deployment is limited by safety risks that are not adequately addressed by conventional marine fuel safety frameworks. This study critically reviews safety assessment, risk management and control strategies for ammonia storage and handling in maritime applications using a PRISMA-informed literature synthesis. Evidence is analysed across hazard characterisation, storage configurations, transfer operations, risk assessment methods, mitigation barriers and regulatory frameworks. The review shows that ammonia safety is governed by coupled release–exposure–barrier interactions shaped by storage condition, tank configuration, pressure–temperature behaviour, material compatibility, transfer mode, ventilation, ship geometry and human intervention. Existing methods, including HAZID, HAZOP, risk matrices and QRA, support hazard screening and prioritisation, but remain limited in representing flashing two-phase releases, dense gas dispersion, confined-space accumulation, exposure duration, ventilation effectiveness and safeguard timing under maritime conditions. CFD, FTA, Bayesian approaches and Monte Carlo analysis offer higher analytical resolution, but their reliability is constrained by limited validation data, uncertain leak-frequency inputs and simplified assumptions for human exposure and emergency response. Effective risk control therefore requires a toxicity-centred barrier strategy linking containment integrity, ammonia-compatible materials, gas and process monitoring, emergency shutdown, ventilation, water-based mitigation, PPE, competency-based training and emergency planning. Current regulatory and classification guidance provides an essential foundation but remains fragmented and insufficiently aligned with ammonia-specific requirements for exposure modelling, safety-zone definition and approval pathways. This review contributes a maritime-specific synthesis of ammonia storage and handling safety by connecting hazard behaviour, storage design, transfer operations, risk assessment limitations, control-barrier logic and regulatory approval needs. The findings highlight the need for validated source-term models, full-scale release and dispersion data, exposure-based safety criteria and harmonised regulatory pathways to support the safe and scalable use of ammonia in maritime decarbonisation. Full article

Introduction: Sharks are key species in marine ecosystems, and their conservation is a priority across European waters. However, several fisheries unintentionally capture sharks as bycatch, raising concerns about their post-capture survival. In the Gulf of Cadiz, demersal trawl fisheries frequently capture the catsharks Galeus atlanticus and G. melastomus. Objective: This study aimed to assess the short-term survival rates of these two species following trawl capture and to identify potential blood biochemical markers predictive of survival. Methodology: Fieldwork was conducted aboard an oceanographic research vessel over two spring seasons. Standarized demersal trawl hauls of 1-h duration were performed. Immediately after capture, individuals were transferred to onboard seawater tanks, where their recovery was monitored for 24 h. Blood samples were collected at two time points: immediately after capture and after the 24-h recovery period. Biochemical parameters associated with secondary stress responses were analyzed. Results: Survival rates were high for both species, reaching 88 ± 8% for G. atlanticus and 90 ± 4% for G. melastomus. Blood analyses indicated a clear physiological recovery in all surviving individuals after 24 h, evidenced by the normalization of stress-related parameters. Notably, interspecific differences were observed in certain biochemical markers after capture, including amino acids and lactate concentrations, suggesting species-specific responses to capture stress. Conclusions: These findings provide valuable insights into the resilience of demersal catsharks to trawl-induced stress and highlight the potential of blood biomarkers as a tool for predicting post-capture survival. The results support the development of evidence-based onboard handling protocols aimed at maximizing the survival of incidentally captured sharks. Such measures can contribute to more sustainable fisheries management and the conservation of vulnerable elasmobranch species in European waters. Full article

Introduction: The Atlantic bluefin tuna Thunnus thynnus (ABFT) is a large pelagic apex predator with adaptations for a life of ceaseless swimming during long-distance oceanic migrations. The environmental physiology and energetics of tunas have interested researchers for many decades, but they are notoriously challenging to study because they are so difficult to keep in captivity. Adult ABFT are, however, now fattened in cages at various sites in the Mediterranean, while juveniles are reared from hatching every year at the Unique Scientific and Technological Infrastructure for ABFT aquaculture (ICAR-IEO), near Cartagena in Spain. These facilities provide access to animals, but the fish remain very problematic to study because of their highly active but physiologically delicate nature and, for adults, their very large sizes. Objective: To study the in vivo physiology and behaviour of ABFT. Methodology: We used heart rate biologging and high residency acoustic tracking to follow cardiac and swimming activity over a year in n = 24 adult ABFT (mass range 25 to 200 kg) held in a cage off the coast of Malta (Malta Fish Farming). We then performed swim tunnel respirometry on young of the year juveniles (500g) at ICRA-IEO, but subsequently took a ‘hands-off’ approach, using video analyses and group respirometry on free-swimming animals. Results: The descriptive approach on the caged adults provided understanding of how seasonal water temperatures (15 to 28 °C) affect tuna physiology and behaviour. The swimming respirometry on juveniles revealed that their performance was constrained by confinement in the tunnel, compared to when they were swimming at their spontaneous preferred speed in their rearing tank. Video analyses provided insights into the effects of size (25 to 200 cm bodylength) on spontaneous swimming speeds and coupled with tank respirometry, revealed how progressive hypoxia affects the metabolic rate and schooling behaviour of juveniles. Conclusions: These opportunistic and disparate pieces of information are nonetheless valuable for such a fascinating but data-deficient species, and can be useful in mechanistic models for management of an extremely valuable fishery in a context of global change. Full article

Limited access to clean water and reliable electricity infrastructure remains a major challenge in many remote regions of Indonesia, particularly for building-scale domestic use. Conventional water treatment systems are often constrained by high operational costs and dependence on grid power, highlighting the need for sustainable and autonomous infrastructure solutions. This study presents the design, development, and performance evaluation of an integrated solar-powered clean water treatment system for smart building applications in remote areas using a Research and Development (R&D) approach. The proposed system combines off-grid polycrystalline photovoltaic panels with a multi-stage water treatment process consisting of a floss (mud) filter, activated carbon filter, water hyacinth cellulose bio-filter, ultraviolet (UV) sterilization unit, storage tank, and an IoT-based real-time water quality monitoring system. System performance was evaluated through microbiological, physical, and chemical water quality testing, with monitoring conducted via Wi-Fi-enabled sensors connected to the Blynk platform. The results demonstrate substantial improvements in treated water quality. Escherichia coli and total coliform bacteria were eliminated (100% reduction). Total dissolved solids (TDSs) decreased from 450 mg/L to 218 mg/L (51.6%), and dissolved manganese was reduced from 30 mg/L to 0.01 mg/L (99.97%), while nitrate levels decreased by 50%. Water pH and temperature remained stable and within regulatory limits. All treated water parameters complied with national clean water standards for hygiene and sanitation. The system operated independently using solar energy and achieved a clean water production capacity of 1000–1500 L/day. These findings indicate that the proposed system is a feasible, cost-effective, and sustainable civil engineering solution for clean water infrastructure in remote building environments. Full article

Ensuring safe and palatable drinking water is critical for long-duration space travel and part of NASA’s 2022 strategic goals. This study investigated whether the formation of iodoform occurred when iodine reacts with trace levels of dissolved organic carbon (DOC) leaching from spacecraft water system components. A simplified model of the International Space Station’s Environmental Control and Life Support System was constructed, focusing on disinfection. The system included water storage in low-density polyethylene (LDPE) bags followed by activated carbon block filtration. Three scenarios were tested: iodine treatment in the storage tank, iodine treatment in-line after storage, and a control with no iodine. Preliminary results showed I₂ concentrations of 0.1–5.42 mg/L prior to filtration, which decreased below detection after filtration. DOC concentrations ranged from below detection to 1.1 mg/L. Concentrations of iodoform, determined by gas chromatography–mass spectrometry, were assessed to observe potential risks to spacecraft drinking water quality. Iodine-based disinfection did result in significant iodoform formation or increased leaching of DOC. This study supports that long-term water storage can be achieved using iodine disinfection and LDPE storage. These results also inform the use of iodine disinfection in emergency situations by drinking water managers when water supply is interrupted in disaster situations. Full article

This paper presents a full-scale case study on real-time corrosion monitoring in an underground reinforced-concrete potable water tank built in 1968. The study aims to demonstrate how continuous electrochemical monitoring can support durability assessment and predictive maintenance in ageing water-retaining infrastructure, where direct inspection is often limited and exposure conditions are spatially variable. Fourteen monitoring points were installed in beams, columns and domes subjected to different exposure conditions. Corrosion potential, concrete resistivity, corrosion current density and temperature were recorded every 3 h and used to assess the corrosion state of the reinforcement. The monitored durability indicators were reinforcement section loss, estimated from corrosion current density using Faraday’s law, and corrosion-induced crack-width evolution, used as a serviceability-related indicator for maintenance planning. The results show that beams remained predominantly passive, with corrosion current densities below 0.1 µA/cm² and incremental sectional losses below approximately 2 µm during the monitoring period. Columns showed the highest vulnerability, particularly at lower elevations subjected to prolonged immersion, with estimated incremental section losses reaching approximately 4–6 µm and a clear correlation between submerged time and corrosion progression. Domes exhibited intermediate behaviour, with occasional activation events associated with environmental fluctuations. A multivariable model combining resistivity and temperature was used to interpret corrosion kinetics, while Faraday-based section-loss estimates were coupled with empirical crack-width models to forecast serviceability indicators up to 2045. These forecasts are presented as scenario-based maintenance-support indicators rather than deterministic predictions of future damage, since corrosion propagation and crack development may evolve nonlinearly under changing exposure conditions. The proposed approach demonstrates how continuous corrosion monitoring can be linked to durability limit-state assessment, enabling risk-informed and performance-based maintenance of critical water infrastructure. Full article

In the practical operation of air-source heat pump heating systems coupled with phase-change energy storage tanks, wide fluctuations in outdoor temperatures often cause issues such as excessive heating, frequent unit start–stops, and low operational efficiency. Traditional start–stop control strategies struggle to balance heating quality with system energy savings. To enhance the system’s energy efficiency across all operating conditions and improve the stability of indoor temperatures, this study introduces a straightforward and easy-to-implement return water temperature zone control strategy. Using physical reference points, a three-zone control approach for return water temperature was created, which integrates outdoor temperature feedback along with combined indoor temperature adjustments. The proposed strategy’s effectiveness was confirmed through comparative experiments that split the heating season into two parts: one employing traditional control and the other using the zone control method. The results show that, compared to empirical start–stop control, the segmented control strategy increased the system’s average coefficient of performance (COP) from 3.06 to 3.11, representing a 1.63% improvement; reduced indoor temperature deviation from 1.4 °C to 1.2 °C, a 14.2% decrease; and narrowed the amplitude of extreme temperature deviations from 7.9 °C to 3.9 °C, a 50.6% reduction. Total electricity consumption for the entire heating season was approximately 4191 kWh. These findings indicate that the proposed control strategy effectively improves system energy efficiency and indoor temperature stability while meeting heating demands. It significantly suppresses excessive heating during transitional seasons and enhances heating reliability under extreme low-temperature conditions. This study involves low retrofitting costs and balances both energy-saving and comfort objectives, providing a practical, engineering-ready solution for the intelligent control of air-source heat pump heating systems. Full article

Accurate prediction of nonlinear wave–structure interaction is essential for the safe design of coastal structures. In this study, a fully nonlinear high-order spectral numerical wave tank is developed to investigate nonlinear wave interaction with a vertical wall. The incident-wave boundary is introduced through an additional velocity potential, with the incident-wave kinematics prescribed from corresponding nonlinear analytical wave solutions. The model is validated against the Fourier solution, demonstrating good accuracy in predicting free-surface elevation, pressure distribution, and resultant wave force. Numerical results show that wave nonlinearity significantly modifies both the standing-wave field and the wall loading. Under strongly nonlinear conditions, negative pressure develops near the lower part of the wall during the crest phase, giving rise to a characteristic saddle-shaped force history. Water depth further modulates this nonlinear mechanism by altering both the force magnitude and the pressure distribution along the wall. For focused wave groups, the force response is strongly affected by the focusing type, wave steepness, and spectral bandwidth. A narrower bandwidth maintains stronger phase coherence over a longer portion of the wave group, leading to slightly larger focused extrema and more pronounced amplification of adjacent wave and force cycles. These findings highlight the importance of nonlinear pressure effects and spectral characteristics in predicting extreme wave loads on vertical-wall coastal structures. Full article

As critical air-dropped acoustic sensors for underwater target detection, sonobuoys are frequently compromised by severe hydrodynamic self-noise induced by sea-surface wave excitation, which masks target signals and degrades detection performance. While structural optimizations have traditionally been employed, effective signal-processing-based noise suppression remains challenging because the noise is non-stationary and physically coupled with buoy motion. To address the limited physical interpretability of conventional decomposition methods, this study proposes a physically guided self-noise suppression framework: VMD Constrained by DCCA Correlation (VMD-DCCA). The main contribution is the incorporation of the Detrended Cross-Correlation Analysis (DCCA) coefficient between the sonobuoy’s vertical velocity and the acoustic data as a correlation-dependent constraint within the Variational Mode Decomposition (VMD) optimization process. This motion prior allows more targeted isolation of motion-induced components than standard data-driven decomposition. Simulation and controlled water-tank results show that VMD-DCCA outperforms EEMD and standard VMD, achieving an SNR improvement of approximately 15 dB at an input SNR of −9 dB. The reconstructed signal also preserves visible narrowband spectral lines in the time-frequency representation. These results demonstrate the potential of the proposed method for controlled or post-processing sonobuoy self-noise reduction, while validation under irregular open-ocean conditions remains necessary. Full article

Potassium sodium niobate (KNN) lead-free piezoelectric ceramics feature eco-friendliness and low density, coupled with superior high-frequency driving efficiency, albeit with inferior low-frequency performance. Conversely, Terfenol-D exhibits outstanding low-frequency driving capability but suffers from high density and poor high-frequency efficiency. This work proposes a ternary symmetric driving structure that integrates the complementary advantages of KNN and Terfenol-D, developing an underwater acoustic transducer with excellent lightweight design, low-frequency response, and broadband performance. The ternary symmetrically excited transducer maintains stable nodal planes across different operating frequencies and exhibits two distinct resonant frequencies. The vibration equation is analytically solved, and modal analysis is performed to clarify the evolution of the dual-resonance frequencies. A prototype transducer weighing 2.8 kg is fabricated and tested in an anechoic water tank. It delivers a maximum transmitting voltage response of 145 dB at 1.7 kHz with a broad operating bandwidth of 1–6 kHz. Compared with previously reported transducers, its weight is reduced by 26% to 93%. Benefiting from the double-ended radiation structure, the transducer yields a nearly omnidirectional radiation pattern. This ternary symmetrically excited transducer holds promising application prospects for underwater acoustic detection, communication, and navigation systems on unmanned underwater vehicle platforms. Full article

We conducted experiments to assess the importance of the effects of interactions between individuals of co-occurring species, the Common Gudgeon Gobio gobio, native to Europe, and the invasive Monkey Goby Neogobius fluviatilis. We examined the influence of the size of the competitor and the temperature of the water on competition for food between these two species. To investigate whether this food competition is dependent on the size of invasive competitors, we used three size classes of the invasive N. fluviatilis and a single size class of the native G. gobio in a tank-based experiment. To reflect the possible impact of temperature, we used two different water temperatures: 16 °C preferred by the G. gobio and 22 °C preferred by the N. fluviatilis. Based on the number of prey consumed, time to start feeding, and the total time spent hunting prey, we provided direct confirmation that the invasive N. fluviatilis in Europe is the superior competitor for food at both tested temperatures, eating twice as much prey, feeding 2–4 times faster, and spending up to three times more time on hunting. Food competition was size-dependent: the greater threat for native species is invasive fish, which are smaller or similar to them in size. Warmer temperatures (22 °C) gave more than twice as much advantage to the invaders under all tested feeding parameters. Therefore, we concluded that populations of invasive N. fluviatilis present a serious threat to native European benthic fish species (i.e., G. gobio). Increasing temperatures, better tolerated by invasive species, compound this problem. Full article

Providing optimal temperatures in greenhouses is essential for cultivating high-temperature-demand crops in winter. Therefore, this study aimed to investigate the feasibility of utilizing a flat plate solar collector (FPC) for heating greenhouses. A field experiment was conducted, complemented by simulations using the PolySun V2023.11 software. The FPC system comprised two collectors, each with an aperture area of 2.24 m², connected to a 300 L hot water tank. The water tank had an internal electric backup heater (2 kW) and a thermostat to regulate the hot water temperature. The experiment consisted of two greenhouses, each with an area of 50 m². The first unheated greenhouse (UHGH) was used as the control, while the second heated greenhouse (HGH) was heated by a closed-loop system comprising copper pipes installed along the internal perimeter. Results revealed that the FPC significantly increased air temperature by 2.7 °C, and reduced relative humidity by 9.7% in the HGH compared to the UHGH. Simulated results showed that the annual generated energy of the FPC was 4830 kWh with a reduction of CO₂ emission by ≈2.9 tones. The average thermal efficiency of the FPC was 44%, with a payback period of 8.5 years. In conclusion, the FPC could protect plants from low temperatures in winter. Full article

The increasing expansion of ubiquitous sensing systems has created large streams of time-series data that are difficult for non-technical users to interpret. Large Language Models (LLMs) offer a promising interface for transforming sensor data into natural language insights, particularly in distributed environments where users may lack familiarity with data analysis. However, models optimized for text generation often struggle to interpret raw time-series signals, producing responses that are generic, inaccurate, or poorly grounded in the data. This study evaluates a prompt structure based on the Retrieval-Augmented Generation (RAG) framework for interpreting sensor-derived time-series data from water-consumption monitoring systems installed in household storage tanks. The prompt integrates statistical summaries, sensor metadata, and contextual information about household water-use practices. Performance is evaluated using synthetic datasets representing a year of tank water-consumption measurements and a rubric-based evaluation framework applied by three independent language-model evaluators. Results show that augmenting prompts with structured contextual information improves the clarity and grounding of language model responses to sensor time-series data, increasing evaluation scores and reducing failure modes such as hallucination, contradiction with the data, and misuse of contextual information, as assessed by independent evaluator models. These findings highlight the potential of structured contextual prompting to support locally deployed language models that produce reliable and actionable interpretations of sensor time-series data. Full article