Ocean Flow Field Research Articles

Dynamic event-triggered integrated task and motion planning for process-aware source seeking

The process-aware source seeking (PASS) problem in flow fields aims to find an informative trajectory to reach an unknown source location while taking the energy consumption in the flow fields into consideration. Taking advantage of the dynamic flow field partition technique, this paper formulates this problem as a task and motion planning (TAMP) problem and proposes a bi-level hierarchical planning framework to decouple the planning of inter-region transition and inner-region trajectory by introducing inter-region junctions. An integrated strategy is developed to enable efficient upper-level planning by investigating the optimal solution of the lower-level planner. In order to leverage the information acquisition and computational burden, a dynamic event-triggered mechanism is introduced to enable asynchronized estimation, region partitioning and re-plans. The proposed algorithm provides guaranteed convergence of the trajectory, and achieves automatic trade-offs of both exploration-exploitation and accuracy-efficiency. Simulations in a highly complicated and realistic ocean surface flow field validate the merits of the proposed algorithm, which demonstrates a significant reduction in computational burden without compromising planning optimality.

Visualization Method for Mesoscale Eddies Characteristics in Ocean Flow Fields Based on Variable Particle Systems

Visualization of ocean flow fields is a major area of interest in marine science. Existing visualization methods based on randomly generated particles tend to exhibit a uniform distribution. While this approach effectively represents ocean flow fields, it inadequately conveys the characteristic structures within the flow in an intuitive manner. Ocean eddies, as crucial components of ocean dynamics (Patrizio & Thompson, 2021), are key features in visualizing ocean flow fields. Mesoscale eddies, which contain 90% of the ocean's kinetic energy, play a vital role in transporting this energy. These eddies significantly influence local marine environments and are instrumental in understanding the kinetic energy of ocean flow fields, providing valuable insights for fields such as oceanography, meteorology, and climate research. The aim of this study is to establish a method based on variable particle systems. Initially, a feature set for mesoscale eddies and a parameter set for variable particles are defined. By mapping the feature set to the parameter set, we express the characteristic structure of mesoscale eddies dynamically. Using ocean flow field data, we demonstrate the method's ability to effectively highlight the characteristic structures of mesoscale eddies within the flow field through qualitative and quantitative evaluation metrics. By analyzing and visualizing ocean flow fields, we can gain a deeper understanding of their spatiotemporal evolution, thereby uncovering the patterns and regularities of their movement. This research approach not only facilitates the effective development, utilization, and sustainable management of marine resources but also aligns with the demands of digital ocean technology for visualizing marine spatial information.

Characterization of underwater manipulator based on the fluid-structure interaction under pulsating flow

Abstract Underwater manipulators are taking on an increasingly significant function in marine biological fishing operations. Under the action of the ocean flow field, vortex-induced vibration will be induced, which will cause fatigue damage or even fracture of the underwater manipulator. Based on the Ansys fluid-solid coupling software, this paper simulates the vortex-induced vibration response characterizations of underwater manipulators under pulsating flow conditions. The pulsation flow at the entrance is realized by changing the velocity amplitude and pulsation frequency. The influence laws of pulsating frequency and amplitude on the CL , CD, and wake vortex shedding are investigated. The results showed that the CL and CD of the underwater manipulator increased by 133.33 % and 39.18 %, respectively, with an increase in the pulsation parameter. Additionally, with the increase of pulsating frequency, the banded vortex behind the underwater manipulator is gradually obvious, and the energy in the vortex is also increasing.

Dynamic 3-D Visualization System of Sea Flow Field Based on Virtual Reality Technology in the Environment of Internet of Things

Abstract Ocean 3-D dynamic visualization is a method to analyze the law of ocean motion by processing complex and changeable ocean data by importing and visualizing. Through 3-D visualization design, the ability to analyze and reconstruct 3-D visualization characteristics of sea area flow field can be improved. To improve the 3-D dynamic visualization effect of ocean flow field and reveal the law of ocean motion, this paper designs a 3-D dynamic visualization system of ocean flow field based on virtual reality technology. Firstly, the framework of the dynamic 3-D visualization system of sea area flow field was designed. On the basis of defining the system development environment, the system software was developed and designed from the aspects of information acquisition module, database model, 3-D reconstruction module, visual simulation module, etc. So far, the design of the 3-D dynamic visualization system of sea area flow field was realized. The simulation results show that the output stability of the design system is good, the visualization ability is strong, and it has certain application values.

Scale-to-scale energy flux in the oceanic global circulation models

Lewis Fry Richardson proposed his famous picture of turbulent flows in 1922, where the kinetic energy is transferred from large-scale to small-scale structures until the viscosity converts it into heat. This cascade idea, also known as the forward energy cascade, is now widely accepted and is treated as the cornerstone of not only turbulent modeling, but also global circulation models of the ocean and atmosphere. In this work, the Filter-Space-Technique is applied to the oceanic flow field provided by the CMEMS reanalysis model to quantify the scale-to-scale energy flux. A rich dynamical pattern associated with different scales is observed. More precisely, either positive or negative fluxes are observed, indicating the direction of the energy cascade, where the energy is transferred from large-scale structures to small-scale ones or vice versa. High-intensity energy exchange is found mainly in the Western Boundary Current Systems and Equatorial Counter Currents. For the latter case, a wavelike pattern is observed on the westward travel. Moreover, strong seasonal variation is evident for some scales and regions. These results confirm the existence of forward and inverse cascades and rich regional dynamics.

Research on high sensitivity optical fiber sensing method for simultaneous measurement of seawater velocity and temperature

Aiming at the need of high sensitivity flow velocity and temperature sensor in ocean research, an optical fiber sensor for the simultaneous measurement of seawater velocity and temperature was proposed by coupling a reflective Panda fiber polarization interferometer with a hollow cylindrical cantilever, which combining the stress sensitivity of Panda fiber and optical vernier effect to achieve simultaneous measurement and sensitization of flow velocity and temperature. Firstly, the theoretical formulas of velocity sensitivity and temperature sensitivity were obtained by theoretical derivation and finite element simulation. Secondly, a velocity and temperature measurement system was established experimentally, and the maximum velocity sensitivity was –233.86 nm/(m/s) at 0.42 m/s with the mean relative error compared with the theoretical sensitivity was 3.8 %, the maximum temperature sensitivity was −14.5 nm/(°C) with the mean relative error compared with the theoretical sensitivity was 8 %. Finally, nine different sets of seawater velocity and temperature were measured using the sensitivity matrix and compared with the Acoustic Doppler Velocimetry and Conductivity-Temperature-Depth meter, the mean relative error of velocity and temperature measurement results were 2.8 % and 2 %, respectively. The optical fiber sensor based on the cantilever is expected to play an important role in the field of ocean flow field measurement because of high sensitivity and the ability to measure velocity and temperature simultaneously.

Modelling of tuna around fish aggregating devices: The importance of ocean flow and prey

Catch and distribution of tuna in the ocean are typically investigated with ocean basin-scale models. Due to their large scale, such models must greatly simplify tuna behaviour occurring at a scale below ∼100 km, despite interactions at this level potentially being important to both catch and distribution of tuna. For example, the associative behaviour of tuna with man-made floating objects, that are deployed by fishers to improve their catch rates (Fish Aggregating Devices; FADs), are usually ignored or simplified. Here we present a model that can be used to investigate the influence of tuna dynamics below the ∼100 km scale on larger scales. It is an Individual-Based Model (IBM) of a hypothetical, tuna-like species, that includes their interactions with each other, free-floating FADs and prey. In this IBM, both tuna and FADs are represented by Lagrangian particles that are advected by an ocean flow field, with tuna also exhibiting active swimming based on internal states such as stomach fullness. We apply the IBM in multiple configurations of idealized flow and prey fields, alongside differing interaction strengths between agents. When tuna swimming behaviour is influenced equally by prey and FADs, we find that the model simulations compare well with observations at the ≲100 km scale. For instance, compared to observations, tuna particles have a similar stomach fullness when associated or non-associated to a FAD, tuna colonize at similar timescales at FADs after their deployment and tuna particles exhibit similar variations in continuous residence times. However, we find large differences in emergent dynamics such as residence and catch among different flow configurations, because the flow determines the time scale at which tuna encounter FADs. These findings are discussed in the context of directing future research, and an improved interpretation of tuna catch and other data for the sustainable management of these economically important species.

Narrative In Situ Visual Analysis for Large-Scale Ocean Eddy Evolution.

The rapid development of high-performance computing systems has led to a rapid increase in the speed of flow field simulation calculations. However, large-scale simulation output data lead to storage bottlenecks and inefficient data analysis. In this work, we used in situ visualization to process the simulation analysis of large-scale flow fields. Combined with narrative visual analysis, we designed a large-scale ocean flow field eddy evolution analysis system based on in situ visualization. Our system can generate high-precision eddy streamline structures in real time and supports eddy statistical analysis and tracking analysis at different ocean regional scales. Through the case data analysis of ocean simulation, we demonstrated the efficiency and effectiveness of the system.

Detecting Submesoscale Cold Filaments in a Basin‐Scale Gyre in Large, Deep Lake Geneva (Switzerland/France)

AbstractSubmesoscale filaments are a well‐documented feature of oceanic flow fields. Based on the analysis of high‐resolution 3D numerical simulations, field observations, and remote sensing imagery, this study, carried out in Lake Geneva, Western Europe's largest lake, provides for the first time evidence that submesoscale filaments also exist in a lake. Field observations confirm that submesoscale, cold‐water filaments are formed at the edges and in the center of a counterclockwise rotating large‐scale gyre during summertime above the thermocline, as indicated by 3D numerical simulation results and remote sensing. Cold submesoscale filaments were well‐developed with sharp lateral temperature gradients (∼1–2°C) during summertime. Locally, these filaments can significantly increase the depth of the upper mixed layer when a relatively strong thermocline exists in the near‐surface layers and cause upward and downward vertical velocities comparable to those reported for oceanic filaments.

The Identification and Prediction of Mesoscale Eddy Variation via Memory in Memory With Scheduled Sampling for Sea Level Anomaly

Ocean mesoscale eddies are ubiquitous in world ocean and account for 90% oceanic kinetic energy, which dominate the upper ocean flow field. Accurately predicting the variation of ocean mesoscale eddies is the key to understand the oceanic flow field and circulation system. In this article, we propose to make an initial attempt to explore spatio-temporal predictability of mesoscale eddies, employing deep learning architecture, which primarily establishes Memory In Memory (MIM) for sea level anomaly (SLA) prediction, combined with the existing mesoscale eddy detection. Oriented to the western Pacific ocean (125°−137.5°E and 15°−27.5°N), we quantitatively investigate the historic daily SLA variability at a 0.25° spatial resolution from 2000 to 2018, derived by satellite altimetry. We develop the enhanced MIM prediction strategies, equipped with Gated Recurrent Unit (GRU) and spatial attention module, in a scheduled sampling manner, which overcomes the gradient vanishing and complements to strengthen spatio-temporal features for long-term dependencies. At the early stage, the real value SLA input guides the model training process for initialization, while the scheduled sampling intentionally feeds the newly predicted value, to resolve the distribution inconsistency of inference. It has been demonstrated in our experiment results that our proposed prediction scheme outperformed the state-of-art approaches for SLA time series, with MAPE, RMSE of the 14-day prediction duration, respectively, 5.1%, 0.023 m on average, even up to 4.6%, 0.018 m for the effective sub-regions, compared to 19.8%, 0.086 m in ConvLSTM and 8.3%, 0.040 m in original MIM, which greatly facilitated the mesoscale eddy prediction. This proposed scheme will be beneficial to understand of the underlying dynamical mechanism behind the predictability of mesoscale eddies in the future, and help the deployment of ARGO, glider, AUV and other observational platforms.

Development of the CSOMIO Coupled Ocean-Oil-Sediment- Biology Model

The fate and dispersal of oil in the ocean is dependent upon ocean dynamics, as well as transformations resulting from the interaction with the microbial community and suspended particles. These interaction processes are parameterized in many models limiting their ability to accurately simulate the fate and dispersal of oil for subsurface oil spill events. This paper presents a coupled ocean-oil-biology-sediment modeling system developed by the Consortium for Simulation of Oil-Microbial Interactions in the Ocean (CSOMIO) project. A key objective of the CSOMIO project was to develop and evaluate a modeling framework for simulating oil in the marine environment, including its interaction with microbial food webs and sediments. The modeling system developed is based on the Coupled Ocean-Atmosphere-Wave-Sediment Transport model (COAWST). Central to CSOMIO’s coupled modeling system is an oil plume model coupled to the hydrodynamic model (Regional Ocean Modeling System, ROMS). The oil plume model is based on a Lagrangian approach that describes the oil plume dynamics including advection and diffusion of individual Lagrangian elements, each representing a cluster of oil droplets. The chemical composition of oil is described in terms of three classes of compounds: saturates, aromatics, and heavy oil (resins and asphaltenes). The oil plume model simulates the rise of oil droplets based on ambient ocean flow and density fields, as well as the density and size of the oil droplets. The oil model also includes surface evaporation and surface wind drift. A novel component of the CSOMIO model is two-way Lagrangian-Eulerian mapping of the oil characteristics. This mapping is necessary for implementing interactions between the ocean-oil module and the Eulerian sediment and biogeochemical modules. The sediment module is a modification of the Community Sediment Transport Modeling System. The module simulates formation of oil-particle aggregates in the water column. The biogeochemical module simulates microbial communities adapted to the local environment and to elevated concentrations of oil components in the water column. The sediment and biogeochemical modules both reduce water column oil components. This paper provides an overview of the CSOMIO coupled modeling system components and demonstrates the capabilities of the modeling system in the test experiments.

Learning and detecting abnormal speed of marine robots

This article presents anomaly detection algorithms for marine robots based on their trajectories under the influence of unknown ocean flow. A learning algorithm identifies the flow field and estimates the through-water speed of a marine robot. By comparing the through-water speed with a nominal speed range, the algorithm is able to detect anomalies causing unusual speed changes. The identified ocean flow field is used to eliminate false alarms, where an abnormal trajectory may be caused by unexpected flow. The convergence of the algorithms is justified through the theory of adaptive control. The proposed strategy is robust to speed constraints and inaccurate flow modeling. Experimental results are collected on an indoor testbed formed by the Georgia Tech Miniature Autonomous Blimp and Georgia Tech Wind Measuring Robot, while simulation study is performed for ocean flow field. Data collected in both studies confirm the effectiveness of the algorithms in identifying the through-water speed and the detection of speed anomalies while avoiding false alarms.

Research on Semantic Analysis of Ocean Flow Field Based on Feature Similarity Collaborative Filtering

Ding, L., 2020. Research on semantic analysis of ocean flow field based on feature similarity collaborative filtering. In: Yang, D.F. and Wang, H. (eds.), Recent Advances in Marine Geology and Environmental Oceanography. Journal of Coastal Research, Special Issue No. 108, pp. 53–57. Coconut Creek (Florida), ISSN 0749-0208.In the field of ocean space-time data modeling research, fields and features are usually used to describe and organize ocean current phenomena, which is continuous and dynamic. However, during the process, the semantic analysis and expression of ocean flow field phenomena often produce heterogeneous problems. Because the feature theory can construct and define the conceptual model framework of domain knowledge system, the semantic analysis of the ocean flow field using the feature theory can be regarded as one of the ways to achieve the semantic sharing of the ocean flow field. Moreover, based on the collection and analysis of existing knowledge and concepts in the field of marine science, a quadruple-based organization in the paper is proposed for ocean flow field features, in which by expanding the concept features, attribute features, and relationship features, a basic structure-based approach is formed. The overall characteristic structure of the ocean flow field comprises concept, attribute, and relationship structure. Additionally, collaborative filtering is performed on the similarity of the structural features in the ocean flow field, and a formal grammatical expression system conforming to the characteristics of continuous flow field is also made so that a normative framework system is provided for the ocean flow field knowledge organization. The OWL language is used, which allows for the conduction of the formal expression and description of geostrophic flow, which provides semantic support for the integration and management of spatiotemporal data in the ocean flow fields.

The Numerical Calculation and Laboratory Model Validation Analysis of Mechanical Noise Based on Benchmark Submarine Model

The mechanical noise analysis of ship structure based on finite element method has been an important means of mechanical noise assessment in the initial design stage of ships. This article is based on the Benchmark standard submarine model, carrying out the numerical simulation of the Benchmark submarine scale model, and obtaining the first-order and second-order natural vibration characteristics of the model. At the same time, we establish a laboratory test system of the Benchmark submarine scale model, and test the natural vibration characteristics of the model under laboratory conditions. We compare numerical simulations and experimental laboratory test results, optimize the numerical modeling method and find the reliability of the numerical simulation calculation. Based on the above research, modeling a true-scale Benchmark standard submarine model, calculate the natural vibration characteristics of the Benchmark submarine model in the ocean flow field environment. Then calculate the value of mechanical radiation noise under the excitation of mechanical equipment based on the natural vibration characteristics results.

Multi-Scale Representation of Ocean Flow Fields Based on Feature Analysis

When it comes to feature retention in multi-scale representations of ocean flow fields, not all data points are equal. Therefore, this paper proposes a method of selecting data points based on their importance. First, an autocorrelation analysis is performed on flow speed and the rate of change in flow direction. Then, the magnitude of speed and variation in the rate of change in flow direction are classified. Feature regions are determined according to autocorrelation aggregation and classification analysis. Then, rough set theory and evidence theory are applied, using these results to determine the weights of different points. Finally, these weights are used to construct multi-scale representations of ocean flow fields, which effectively retain flow-field characteristics.

Single super-vortex as a proxy for ocean surface flow fields

Abstract. Empirical flow field data evaluation in a well-studied ocean region along the US west coast revealed a surprisingly strong relationship between the surface integrals of kinetic energy and enstrophy (squared vorticity). This relationship defines a single isolated Gaussian super-vortex, whose fitted size parameter is related to the mean eddy size, and the square of the fitted height parameter is proportional to the sum of the square of all individual eddy amplitudes obtained by standard vortex census. This finding allows very effective coarse-grained eddy statistics with minimal computational efforts. As an illustrative example, the westward drift velocity of eddies is determined from a simple cross-correlation analysis of kinetic energy integrals.

Distributed Traversability Analysis of Flow Field Under Communication Constraints

Traversability analysis, previously developed for ground robots, is extended to be performed by a group of marine vehicles over ocean flow fields. To enable distributed path planning against flow, a systematic method is developed to determine a flow map that is significant for sharing among vehicles. Using traversability analysis, each vehicle finds a set of support vectors to approximate the boundary of flow regions with strong average flow speed. These support vectors, together with the parameters determined by the traversability analysis, are then shared over the communication links. The shared information is used by each vehicle to construct a flow map that supports path planning algorithms running on each vehicle. Underwater communication limits the amount of information contained in a map that can be shared among vehicles. A novel method for information reduction is developed so that only reduced flow maps are shared. The length of the data packets can be adjusted through an optimization process that balance between the fidelity of the approximated boundary and the number of bits that need to be transmitted. Simulation results demonstrate that the flow maps constructed from the shared information can have sufficient quality to allow near-optimal paths to be generated.

Dynamic visual simulation of marine vector field based on LIC—a case study of surface wave field in typhoon condition

Line integral convolution (LIC) is a useful visualization technique for a vector field. However, the output image produced by LIC has many problems in a marine vector field. We focus on the visual quality improvement when LIC is applied in the ocean steady and unsteady flow field in the following aspects. When a white noise is used as the input in a steady flow field, interpolation is used to turn the discrete white noise into continuous white noise to solve the problem of discontinuity. The “cross” high-pass filtering is used to enhance the textures of streamlines to be more concentrated and continuity strengthened for each streamline. When a sparse noise is used as the input in a steady flow field, we change the directions of background sparse noise according to the directions of vector field to make the streamlines clearer and brighter. In addition, we provide a random initial phase for every streamline to avoid the pulsation effect during animation. The velocities of vector field are encoded in the speed of the same length streamlines so that the running speed of streamlines can express flow rate. Meanwhile, to solve the problem of obvious boundaries when stitching image, we change the streamline tracking constraints. When a white noise is used as an input in an unsteady flow field, double value scattering is used to enhance the contrast of streamlines; moreover, the “cross” high-pass filtering is also adopt instead of two-dimensional high-pass filtering. Finally, we apply the above methods to a case of the surface wave field in typhoon condition. Our experimental results show that applying the methods can generate high-quality wave images and animations. Therefore, it is helpful to understand and study waves in typhoon condition to avoid the potential harm of the waves to people’s lives and property.

Evaluation of multi-scale representation of ocean flow fields using the Euler method based on map load

ABSTRACT This paper takes the map load as the evaluation indicator for multi-scale representations of ocean flow fields using Euler method. First, the map load of the ocean flow fields is calculated and the suitable map load interval is analysed in order to obtain the key scale for the multi-scale representation of ocean flow fields. Then, the load is limited by appropriate load intervals to fit the relationship between map load and scale. Finally, a mathematical model for multilevel comprehensive evaluation in fuzzy mathematics is established, and the usability of the resulting ocean flow field map is evaluated using questionnaires.

Helmholtz–Hodge decomposition-based 2D and 3D ocean surface current visualization for mesoscale eddy detection

Ocean surface current (or ocean flow) visualization plays a significant role in the understanding of dynamical processes of ocean. It has been a hot research topic in both computer science and oceanography. Ocean surface current is a turbulent flow field mixing of multi-scale ocean dynamics such as large-scale ocean circulations ( $$100\,\hbox {km}\sim$$ ), mesoscale eddies (10– $$100\,\hbox {km}$$ ), submesoscale processes (1– $$10\,\hbox {km}$$ ). Mesoscale eddies, which are strong but short-life movement relative to the large-scale ocean circulations, have great importance on the transportation of ocean water masses, momentum and energy. However, their detection and recognition, which are treated as the foundation of exploring their dynamical mechanisms, is still a challenging issue. For one thing, in the mixed ocean flow field, different ocean flows depended and influence with each other making existing methods difficult to identify among them. For another, mesoscale eddies are active signals on the ocean. They may change their forms and velocities at any time. This challenges existing works to deal with their boundary ambiguity and unremitting transitions. To solve these problems, this paper proposes a novel 2D and 3D ocean surface current visualization approach based on an amended Helmholtz–Hodge decomposition (HHD), which can be widely used for mesoscale eddy detection. In our method, HHD decomposes each mixed ocean flow field to two components: curl component and divergence component. Different ocean flows can be represented by these two components independently. In addition, to improve the performance of eddy identification and to reveal the 3D structure of ocean flows simultaneously, HHD transforms the 2D ocean flow field to 3D potential surfaces. Finally, comprehensive experiments are performed on both global and local ocean flow field (Black Sea and Mediterranean Sea) calculated from satellite maps of sea level anomaly to verify our method. Experimental results demonstrate the good effectiveness of our method.