Wave Conditions Research Articles

Joint probabilistic modeling of extreme wind-wave conditions under typhoon impact and applications to extreme response analysis of floating offshore wind turbines

The joint probabilistic modeling of extreme wind and wave conditions under typhoon impact is a critical task for extreme response analysis of floating offshore wind turbines (FOWTs) deployed in typhoon-prone areas. However, wind and wave observations under typhoon impact are quite limited, which poses great challenges to the probabilistic modeling task. Although some sophisticated programs can be employed to simulate typhoon-induced wave fields, they suffer from unbearable computational burdens. To improve the accuracy and efficiency of joint probabilistic modeling of extreme wind and wave conditions under typhoon impact, an approach that synthesizes the typhoon hazard analysis method and copula-based conditional modeling method is proposed in the present study. The proposed joint distribution model is expressed as the product of the distribution of extreme wind speed and the conditional distribution of significant wave height. The distribution of extreme wind speed is estimated through the typhoon hazard analysis method, and the conditional distribution of significant wave height is modeled by the copula-based method. The effectiveness of the proposed method is verified by comparing with observation data. Applications of the proposed method to extreme response analysis of FOWTs are illustrated as well.

Global stability coefficient of large underground caverns under static loading and earthquake wave condition

Global stability coefficient of large underground caverns under static loading and earthquake wave condition

Enhancing Wave Energy Converters: Dynamic Inertia Strategies for Efficiency Improvement

Wave energy conversion is a promising field of renewable energy, but it still faces several technological and economic challenges. One of these challenges is to improve the energy efficiency and adaptability of Wave Energy Converters to varying wave conditions. A technological approach to solve this efficiency challenge is the negative spring mechanisms illustrated in recent studies. This paper proposes and analyzes a novel negative spring technological concept that dynamically modifies the mass and inertia of a Wave Energy Converter by transferring seawater between its compartments. The added value of the presented technology relies on interoperability, ease of manufacturing and operating, and increased energy efficiency for heterogeneous sea states. The concept is presented in two analyzed alternatives: a passive one, which requires no electrical consumption and is purely based on the relative motion of the bodies, and an active one, which uses a controlled pump system to force the water transfer. The system is evaluated numerically using widely accepted simulation tools, such as WECSIM, and validated by physical testing in a wave flume using decay and regular test scenarios. Key findings include a relevant discussion about system limitations and a demonstrated increase in the extracted energy efficiency up to 12.7% while limiting the maximum power extraction for a singular wave frequency to 3.41%, indicating an increased adaptability to different wave frequencies because of the amplified range of near-resonance operation of the WEC up to 0.21 rad/s.

The possible KK¯* and DD¯* bound and resonance states by solving the Schrodinger equation

The Schrodinger equation with a Yukawa type of potential is solved analytically. When different boundary conditions are taken into account, a series of solutions are indicated as a Bessel function, the first kind of Hankel function and the second kind of Hankel function, respectively. Subsequently, the scattering processes of KK¯* and DD¯* are investigated. In the KK¯* sector, the f 1(1285) particle is treated as a KK¯* bound state, therefore, the coupling constant in the KK¯* Yukawa potential can be fixed according to the binding energy of the f 1(1285) particle. Consequently, a KK¯* resonance state is generated by solving the Schrodinger equation with the outgoing wave condition, which lies at 1417 − i18 MeV on the complex energy plane. It is reasonable to assume that the KK¯* resonance state at 1417 − i18 MeV might correspond to the f 1(1420) particle in the review of the Particle Data Group. In the DD¯* sector, since the X(3872) particle is almost located at the DD¯* threshold, its binding energy is approximately equal to zero. Therefore, the coupling constant in the DD¯* Yukawa potential is determined, which is related to the first zero point of the zero-order Bessel function. Similarly to the KK¯* case, four resonance states are produced as solutions of the Schrodinger equation with the outgoing wave condition. It is assumed that the resonance states at 3885 − i1 MeV, 4029 − i108 MeV, 4328 − i191 MeV and 4772 − i267 MeV might be associated with the Zc(3900), the X(3940), the χ c1(4274) and χ c1(4685) particles, respectively. It is noted that all solutions are isospin degenerate.

Studi Motion Sickness Incidence (MSI) Pada Kapal Patroli (KAL-28) Katamaran

Motion sickness or seasickness is a condition caused by the movement of a ship that results in dizziness, nausea, and vomiting. The Motion Sickness Incidence (MSI) Study on the Patrol Catamaran (KAL-28) aims to evaluate the comfort level of passengers and the safety of the ship's crew during operations, following the ISO 2631/1997 standards. The evaluation is conducted on the vertical acceleration response of the ship under various wave conditions, speeds, and wave directions. Mapping is performed in various areas of the ship, including the deck, navigation room, and engine room, considering wave heights of 0.875 meters and 2 meters at speeds of 15 knots, 22.5 knots, and 30 knots. The research results indicate that at a speed of 15 knots, the deck area, navigation room, and engine room meet the criteria from comfortable to somewhat uncomfortable. However, at speeds of 22.5 knots and 30 knots, these areas are rated as somewhat uncomfortable to very uncomfortable. This study emphasizes the need for ship design that considers both passenger comfort and safety, especially for patrol catamarans

Self-powered wireless sensor node enabled by ultra-high-output swinging hybrid generator toward real-time and in-situ marine meteorological observations

With the intensification of global ocean exploration, there is an increasing need for extensive and dispersed wireless sensor networks (WSNs) to meet the requirements of real-time, in-situ, and high-spatial-temporal-density marine meteorological observations. Nevertheless, providing a reliable power source and ensuring the ongoing maintenance of these WSNs pose significant challenges. Here, an innovative self-powered wireless sensor node is developed to address these challenges, featuring an ultra-high-output triboelectric-electromagnetic hybrid generator (T-EHG) with a swinging mechanism. The T-EHG, which combines triboelectric (TENG) and electromagnetic (EMG) generation, assisted by a universal power management system (UPMS), efficiently converts wave energy into a consistent voltage output between 1.5 V to 3.3 V. Additionally, the self-powered WSNs integrated with T-EHG, UPMS circuits, meteorological sensors, and microcontroller units (MCUs) with LoRa wireless transmission functionality are capable of executing data collection and transmission operations every 10 s under simulated wave conditions. These systems can achieve a maximum wireless transmission range of 1.5 km. Notably, a marine meteorological monitoring system utilizes these autonomous sensor nodes, along with base stations, cloud servers, and terminal devices to effectively implement real-time, on-site measurements of temperature, humidity, and air pressure within the monitored zone. This research underscores the substantial practical utility and extensive application prospects of these advanced self-powered WSNs for marine meteorological surveillance.

Numerical study on efficiency and robustness of wave energy converter-power take-off system for compressed air energy storage

The unpredictable fluctuations of wave lead to an imbalance between energy supply and demand. This article proposes a wave-driven compressed air energy storage system, which uses wave mechanical energy instead of electrical energy as the direct driving force for the compressors. Compressed air energy storage solves the problem of stability of wave energy output by accumulating and storing wave energy and then releasing it in a centralized manner. Due to the significant change in load damping compared to the generator, the damping force of the power take-off with compressed air energy storage load is analyzed. And a robust strategy with adjustable buoy draft and load compressor number is proposed, and the highest capture width ratio of 26.71 % and wave energy to compressed air energy conversion efficiency of 13.00 % are achieved under regular wave conditions. Surface seawater is used for heat supplementation in the expansion phase, and a closed-loop system is designed to avoid the damage of low-temperature condensation, the round-trip efficiency of the system is 11.26 %. This research provides a potential power generation path for wave energy and surface seawater heat. And it may beneficial to provide stable and relatively cheap power supply for coastal and offshore users.

The Formation of Deflation Ridges

The deposition of both pumice and shell is common on beaches during calm and storm wave conditions. This paper describes an investigation of pumice and shell ridges at two sites in Australia, Dark Point in NSW, and in the Younghusband Peninsula in SE South Australia. The formation of lines of wave formed shelly and pumice rich deposits on, and above the backshore is described. The deposits are buried by dune development, but then later exhumed by aeolian deflation as deflation plains and basins evolve. Aeolian erosion of the finer sandy sediments leads to the creation of a ridge form, herein termed a deflation ridge. A new schematic model of ridge formation is also detailed whereby deflation ridges are formed by the aeolian erosion and deflation of shell or pumice concentrations and lag deposits.

Research on Photovoltaic Power Generation Characteristics of Small Ocean Observation Unmanned Surface Vehicles

Under the action of waves, a small unmanned surface vehicle (USV) will experience continuous oscillation, significantly impacting its photovoltaic power generation system. This paper proposes a USV photovoltaic power generation simulation model, and the efficiency of photovoltaic MPPT control under wave action is studied. A simulation model for solar irradiance on solar panels of USV under wave action is established based on CFD and solar irradiation models. The dynamic changes in irradiance of USV solar panels under typical wave conditions are analyzed. The MPPT efficiency of USV photovoltaic power generation devices under continuously changing irradiance conditions is studied on this basis. The simulation research results indicate that waves and solar altitude angles significantly impact the instantaneous irradiation energy of USV photovoltaic devices. However, the impact of waves on the average irradiance is relatively tiny. The sustained oscillation of irradiance poses certain requirements for the Maximum Power Point Tracking (MPPT) control frequency of USV photovoltaic systems; a disturbance control frequency of no less than 50 Hz is proposed.

Enhancing tsunami resilience for coastal bridge piers through seawall-integrated breakwaters: An experimental study

In ocean engineering, breakwater plays a crucial role in protecting coastal structures such as bridge pier from the impact of extreme sea waves. However, enhancing the existing breakwaters' ability to withstand extreme wave remains an urgent issue to address. This study explores the reinforcement strategy of breakwater against extreme sea waves by installing seawalls on the breakwater. Utilizing dam-break wave generation techniques to simulate tsunamis, the study experimentally evaluates the effectiveness of seawalls in reducing the tsunami forces exerted on bridge pier model and numerically investigates the tsunami forces on the seawalls. The focus of this research is to analyze the pressure distribution on seawalls and the impact of different seawall configurations on the reduction of tsunami forces on bridge pier model. Results show that: Under the tested wave condition (a) The height of the seawall on the breakwater is a critical parameter, as increasing wall height reduces the tsunami forces exerted on the bridge pier behind it. The taller seawalls are subjected to greater tsunami forces in tested cases; (b) The trend of extreme pressure values for different seawalls starts increasing at the bottom and then decreases; (c) There is a critical distance that the breakwater being most effective at reducing tsunami impact forces between the bridge pier model and the breakwater. This study not only deepens the understanding of the interaction between tsunami waves and seawalls but also offers practical guidance for designing structures with disaster resilience, significantly influencing the future design and construction of tsunami-resistant coastal infrastructure.

Hydroelastic modelling of a deformable wave energy converter including power take-off

Given the advantages of flexible wave energy converters (FlexWECs), such as deformation-led energy harnessing and structural loading compliance, there has been a significant interest in FlexWECs in both academia and industries. To simulate the FlexWEC interaction with ocean surface waves, a 3D computational fluid-structure interaction approach is developed in this study. The fluid and solid governing equations are discretized using finite difference and finite element methods, respectively. An immersed boundary method is used to couple the two independent grid systems. A novel numerical technique is introduced to model the dielectric elastomer generator (DEG) as the power take-off (PTO). The wave energy capture performance is analysed for different PTO configurations and at various wave conditions. Based on the obtained results, the PTO damping coefficient and the relative wavelength range that maximizes the capture width ratio (CWR) are determined. The wavefield results also reveal the presence of wave-height enhancement and attenuation points around a single FlexWEC, providing potential site selection references when deploying multiple FlexWECs in an array.

Numerical Simulation Method of Hydraulic Power Take-Off of Point-Absorbing Wave Energy Device Based on Simulink

Wave energy has a high energy density and strong predictability, presenting encouraging prospects for development. So far, there are dozens of different wave energy devices (WECs), but the mechanism that ultimately converts wave energy into electrical energy in these devices has always been the focus of research by scholars from various countries. The energy conversion mechanism in wave energy devices is called PTO (power take-off). According to different working principles, PTOs can be classified into the linear motor type, hydraulic type, and mechanical type. Hydraulic PTOs are characterized by their high efficiency, low cost, and simple installation. They are widely used in the energy conversion links of various wave energy devices. However, apart from experimental methods, there is currently almost no concise numerical method to predict and evaluate the power generation performance of hydraulic PTO. Therefore, based on the working principle of hydraulic PTO, this paper proposes a numerical method to simulate the performance of a hydraulic PTO using MATLAB(2018b) Simulink®. Using a point-absorption wave energy device as a carrier, a float hydraulic system power-generation numerical model is built. The method is validated by comparison with previous experimental results. The predicted power generation and conversion efficiency of the point-absorption wave energy device under different regular and irregular wave conditions are compared. Key factors affecting the power generation performance of the device were investigated, providing insight for the subsequent optimal design of the device, which is of great significance to the development and utilization of wave energy resources.

Directional effects on the nonlinear response of vehicle-bridge system under correlated wind and waves

Long-span railway sea-crossing bridges are subjected to strong winds and high waves. Due to variations in structural features, including stiffness and size across diverse orientations, the dynamic response of vehicles and bridges can exhibit significant differences under distinct wind and wave directions. Consequently, a novel approach for analyzing bridge and vehicle dynamic performance called the directional wind-wave-vehicle-bridge (DWWVB) model has been developed. To acquire the statistical characterization of the correlation between wind and wave conditions, a three-dimensional joint probability distribution of wind and wave characteristics derived from collected data at the bridge site is established. The wind loads are derived from wind tunnel tests and computational fluid dynamics simulations. The nonlinear wave loads are solved utilizing the hydrodynamic solver ANSYS-AQWA. Based on the finite element bridge model and a 23-degree-of-freedom mass-spring-damper vehicle model, the aerodynamic nonlinearity and initial geometric nonlinearity are considered during the iteration process. The Newmark-β method is employed to solve the dynamic response of bridges and vehicles. The calculation results reveal that the most unfavorable response occurs when the wind direction is 45° and the wave direction is 90°. The directional analysis provides valuable insights for selecting optimal bridge locations and reasonable design environmental parameters.

Projections of the Adriatic wave conditions under climate changes

Assessing the impact of climate change on wave conditions, including average and extreme waves, is vital for numerous marine-related activities, industries, coastal vulnerability, and marine habitats. Previous research, primarily on a large scale, has investigated this topic, but its relevance for marginal basins like the Adriatic Sea is limited due to the low resolution of the wave models used and atmospheric forcing. To contribute to filling in the gap, here we implemented a high-resolution model (about 2 km) for the period 1992–2050. The future wave climate is simulated for the RCP8.5 emission scenario. This model, developed within the AdriaClim project, comprises, among others, a high-resolution atmospheric downscaling, a circulation Limited Area Model and a spectral wave model. A comparison of our simulation's results with Copernicus Marine Service wave reanalysis on the historical baseline, confirms its accuracy in reproducing both average wave parameters and 95th percentile values, as well as the seasonal cycle, showing the AdriaClim model's suitability as a source to predict future wave climates in the Adriatic Sea. The projected changes suggest a slight increase in average significant wave height and mean wave period, and a more significant decrease at the 95th percentile, with a relevant variability by location and season, partially aligning with previous studies. This study highlights the potential effect of local climate change in coastal areas and the importance of developing long-term simulation with a downscaled modeling system for regional areas.

Heat waves induce milkweed resistance to a specialist herbivore via increased toxicity and reduced nutrient content.

Over the last decade, a large effort has been made to understand how extreme climate events disrupt species interactions. Yet, it is unclear how these events affect plants and herbivores directly, via metabolic changes, and indirectly, via their subsequent altered interaction. We exposed common milkweed (Asclepias syriaca) and monarch caterpillars (Danaus plexippus) to control (26:14°C, day:night) or heat wave (HW) conditions (36:24°C, day:night) for 4 days and then moved each organism to a new control or HW partner to disentangle the direct and indirect effects of heat exposure on each organism. We found that the HW directly benefited plants in terms of growth and defence expression (increased latex exudation and total cardenolides) and insect her'bivores through faster larval development. Conversely, indirect HW effects caused both plant latex and total cardenolides to decrease after subsequent herbivory. Nonetheless, increasing trends of more toxic cardenolides and lower leaf nutritional quality after herbivory by HW caterpillars likely led to reduced plant damage compared to controls. Our findings reveal that indirect impacts of HWs may play a greater role in shaping plant-herbivore interactions via changes in key physiological traits, providing valuable understanding of how ecological interactions may proceed in a changing world.

Celebrification through Media Spectacles: Emerging Forms of Performativity in Indian Politics

We live at a time when new forms of mediatisation are conditioning the political landscape of India, especially in the context of the 2024 Lok Sabha elections in the country. As heat wave conditions prevailed in many parts of the country, the quantity of time spent by politicians for on-ground campaigning was lesser in comparison with earlier elections. The hostile climatic conditions together with the intensity of digital empowerment, access to smartphones and availability of cheap data facilitated the formation of a thriving ecosystem of digital campaigning. The country witnessed political parties using digital spaces to an unprecedented level to inform, influence and even mislead the prospective voters. The focus of the paper will be on the strategic use of social media networks for the current elections in India to transform politicians into celebrities and the acts of performativity choreographed to entice the citizens with media spectacles.

Theoretical and experimental study of the high-frequency nonlinear dynamic response of a 10 MW semi-submersible floating offshore wind turbine

To further investigate the hydrodynamic performance of a novel 10 MW semi-submersible floating offshore wind turbine (FOWT) OUCwind and the dynamic response of the FOWT, especially the high-frequency dynamic response induced by the high-order high-frequency hydrodynamic loads, an experimental study for OUCwind is carried out. A novel regular wave condition design method is proposed, i.e., making incidence wave periods that exactly meet an integer multiple of the natural period of the wind turbine, to stimulate the structural resonance of the tower. To determine the natural period of the wind turbine with an elastic boundary, an irregular wave test is carried out and the natural period of the wind turbine with the elastic boundary is proved to be 3 s. Different parts of the FOWT model are verified to satisfy the corresponding scale similarity through a series of validation tests. The hydrodynamic performance of OUCwind is investigated. Linear response is obtained by applying the band-pass filter to the total response. The pitch motions have apparent high-frequency components aligned with the natural frequency of the wind turbine under the environmental conditions with a wave periods of 6 s. For surge and heave motion, the linear component dominates these two responses and the effect of the high-frequency component on these two responses is negligible. The second-order doubling and third-order tripling wave effects have a tremendous impact on the tower-top shear force and mooring line tension. The experimental data providing high-frequency dynamic responses up to the quadruple order can be used for the validation and correction of mid-fidelity and high-fidelity numerical models. Finally, the mechanisms of the generation of the high-frequency dynamic response of the FOWT are also concluded in an illustrative form.

ANN-assisted prediction of wave run-up around a tension leg platform under irregular wave conditions

This study proposes a novel prediction method for nonlinear wave run-ups around a TLP by combining the linear diffraction method with deep learning techniques. Initially, the linear diffraction method evaluates relative wave motion around the platform based on measured incident waves and frequency domain analysis. Subsequently, an artificial neural network (ANN) predicts the peak values of nonlinear wave run-ups, utilizing incident wave data and linear calculation results as inputs. Two different ANN models were proposed, each tailored to specific output variables. The first, the ζ-based ANN model, predicts the peak value of wave run-ups, while the second, the α-based ANN model, predicts the nonlinear amplification factor. The incorporation of a neural network significantly enhances the prediction accuracy for the peak values of wave run-ups. Moreover, the α-based ANN model demonstrates superior accuracy in predicting high run-up events and better generalization ability across various wave conditions compared to the ζ-based ANN model. The study also investigates the effect of various preprocessing methods on prediction performance. The over-sampling method improves accuracy for high run-up events but degrades predictions for low run-up regions, while the polynomial feature transformation reduces prediction errors for high run-up in the ζ-based ANN model.

A reconstruction method of stress fields, bending moments and wave parameters for floating nuclear power plants through regular wave identification

Floating nuclear power plants (FNPPs) have the potential to supply abundant electricity, hot water, and freshwater resources for offshore islands and offshore oil and gas extraction platforms. However, the consequences of a nuclear reactor accident can be extremely serious. In addition, there may be many uncertain factors in the actual operation of FNPPs. These factors lead to higher structural safety requirements. So， developing more scientific structural monitoring methods is an effective way to enhance the structural safety of FNPP. Traditional hull monitoring schemes can only track bending and torsional forces on specific cross-sections, failing to identify the overall stress field of the entire vessel structure. The paper proposes a reconstruction method for the stress field, bending moment distribution, and wave parameters of FNPP using regular wave identification. Initially, irregular waves are decomposed into a linear combination of multiple regular waves with different amplitudes and frequencies. Subsequently, the strains induced by these regular waves on the FNPP are utilized as basic functions to establish a mathematical model for reconstructing the stress field. The stress field, bending moment distribution, and wave parameters of the FNPP can be reconstructed by identifying the combination coefficients of the regular wave loads. The ill-posedness of the mathematical model for stress field reconstruction has the potential to significantly impact the accuracy of the stress field reconstruction, which was addressed by optimizing the sensor installation position in this study. Meanwhile, the optimization of the sensor installation position greatly reduces the dimensionality of mathematical models. Finally, a numerical study, i.e. FNPP being designed by China, was used to validate the accuracy of the proposed stress field reconstruction algorithm. The reconstructed stress field of the FNPP closely matched the original stress distribution under various irregular wave conditions.

Optimal design of an inclined barrier for performance improvement of an oscillating water column device with an artificial neural network model

An oscillating water column (OWC) device with a surface-piercing inclined barrier has been studied in irregular waves. This study is to determine the optimal shape of an inclined barrier utilizing an Artificial Neural Network (ANN) model for the performance enhancement of the conventional OWC system. We employed the dual boundary element method (DBEM) as our numerical approach, which resolves two separate boundary integral equations (singular and hyper-singular) formulated at the coincident source points situated on either side of the degenerate barrier boundary. The design parameters affecting the performance of the OWC system have been optimized to maximize the power extraction using the trained ANN model. The training dataset was prepared using the DBEM, which is then used to train and validate the ANN model. Subsequently, the trained model was employed to make predictions using a broader dataset to identify the optimal combination of design parameters that maximize the conversion efficiency. The findings reveal that the well-trained ANN model can learn complex nonlinear relationships, make good predictions with high accuracy using a larger dataset of input conditions, and offer the optimal values of an inclined barrier appropriate for the wave conditions at the sea installation site.