Hasil untuk "Ocean engineering"

Spyridon Syntakas, Kostas Vlachos

Autonomous Underwater Vehicles (AUVs) are a highly promising technology for ocean exploration and diverse offshore operations, yet their practical deployment is constrained by energy efficiency and endurance. To address this, we propose Current-Harnessing Stage-Gated MPC, which exploits ocean currents via a per-stage scalar which indicates the "helpfulness" of ocean currents. This scalar is computed along the prediction horizon to gate lightweight cost terms only where the ocean currents truly aids the control goal. The proposed cost terms, that are merged in the objective function, are (i) a Monotone Cost Shaping (MCS) term, a help-gated, non-worsening modification that relaxes along-track position error and provides a bounded translational energy rebate, guaranteeing the shaped objective is never larger than a set baseline, and (ii) a speed-to-fly (STF) cost component that increases the price of thrust and softly matches ground velocity to the ocean current, enabling near zero water-relative "gliding". All terms are C1 and integrate as a plug-and-play in MPC designs. Extensive simulations with the BlueROV2 model under realistic ocean current fields show that the proposed approach achieves substantially lower energy consumption than conventional predictive control while maintaining comparable arrival times and constraint satisfaction.

Tenglong Zheng, Xiaoying Feng, Siyuan Wang et al.

To achieve robust and accurate collaborative 3D measurement under complex noise conditions, a global calibration method for dual-arm hand–eye systems and multi-view 3D imaging is proposed. A multi-view 3D scanning approach based on ICP (M3DHE-ICP) integrates a multi-frequency heterodyne coding phase solution with ICP optimization, effectively correcting stitching errors caused by robotic arm attitude drift. After correction, the average 3D imaging error is 0.082 mm, reduced by 0.330 mm. A global calibration method based on encoded marker points (GCM-DHE) is also introduced. By leveraging spatial geometry constraints and a dynamic tracking model of marker points, the transformation between multi-coordinate systems of the dual arms is robustly solved. This reduces the average imaging error to 0.100 mm, 0.456 mm lower than that of traditional circular calibration plate methods. In actual engineering measurements, the average error for scanning a vehicle’s front mudguard is 0.085 mm, with a standard deviation of 0.018 mm. These methods demonstrate significant value for intelligent manufacturing and multi-robot collaborative measurement.

Peng Qu, Zhiyu Zhang, Yang Wu et al.

The present study aimed to investigate the effects of increasing levels of yellow mealworm Tenebrio molitor (TM) meal as a replacement of dietary fishmeal (FM) and different levels of dietary selenium supplementation on the growth performance, digestive and absorptive enzyme activity, immune response, skin color and muscle quality of large yellow croaker Larimichthys crocea (initial body weight: 189.97 ± 1.01 g). Using a 3 × 2 factorial design, six isonitrogenous (about 47 % of crude protein) and isolipidic (about 10 % of crude lipid) diets were formulated with 3 replacement levels of FM by TM (15 %, 30 % and 45 %) and two supplemented levels of selenium (0.67 mg/kg and 3.78 mg/kg) in the form of sodium selenite. After an 80-day feeding trial, the results showed that 30 % of replacement of dietary FM by TM did not significantly influence the growth performance and feed utilization of large yellow croaker. The supplement level of 1.7 mg/kg Se significantly improved the weight gain and ventral and caudal skin yellow value (P < 0.05). This selenium level led to a decrease in serum triglyceride, malondialdehyde, and 8-hydroxydeoxyguanosine, while increased the activities of intestinal chymotrypsin, γ-glutamyltransferase, acid phosphatase and lysozyme (P < 0.05). The replacement of FM with TM at 15 % and 30 % levels significantly increased the expression of nuclear factor erythroid 2-related factor 2 (P < 0.05). The 1.7 mg/kg dietary selenium reduced the expression of nuclear factor-κb and kelch-like ech-associated protein 1 in both intestine and liver. In conclusion, up to 30 % replacement of dietary FM by TM showed no significant adverse effects on growth and feed utilization of large yellow croaker. Supplementation of 1.7 mg/kg dietary selenium significantly enhanced the growth, feed utilization, anti-oxidative ability, and muscle quality of large yellow croaker. However, there were no interactions between dietary FM replacement level and Se supplement level regarding growth performance, immune response, and muscle quality of large yellow croaker. The Se could mitigate the negative growth effects of over-high dietary TM on large yellow croaker.

Fei Liu, Qiming Cheng, Zijian Zeng et al.

Abstract The employment of Low Impact Development (LID) facilities is an effective means to alleviate urban flood in the context of climate change and urbanization. Existing methods for evaluating the hydrological reduction and control effect of LID facilities are mostly based on hydrological models, which have inherent shortages in accurate flood process simulation. In this study, a fully‐distributed bidirectional‐coupled hydrodynamic model based on the Finite Volume Coastal Ocean Model (FVCOM) and a one‐dimensional drainage pipe model is used to evaluate the effectiveness of LID facilities combining the Coevolutionary Constrained Multi‐objective Optimization (CCMO) algorithm. The proposed method is applied to investigate the responses of LID facilities effectiveness in hydrological reduction and control to rainfall patterns in the Yuelai New City, Chongqing, China. Results show that the overflow volume and peak overflow under unimodal rainfall are larger than those under other rainfall patterns. The time lag between initial and peak overflow under unimodal rainfall is the shortest, and it is shorter under small rainfall return period. The flood reduction and delay effect of LID facilities under unimodal rainfall is lower than that under bimodal rainfall, and it is the best under uniform rainfall. At low costs, the peak flood reduction effect of combined LID facilities may be lower than that of a single LID facility with strong permeability, but as costs continue to increase, combined LID facilities show its superiority. The proposed optimization‐simulation method is of great significance for environmental managers to seek best solutions in urban flood control.

Yuming Wen, Yu Liu, Zhaozhi Liang et al.

Digital images are prone to various forms of noise during acquisition, which can distort structural information and hinder subsequent processing. This work proposes AuroraNet, a denoising framework that extends the dual-branch design of DudeNet and integrates a Gradient-projected Function (GPF) optimizer to enhance training stability and preserve fine-scale image features. We evaluated the model on two real-world noisy image datasets to examine its robustness under different noise conditions. AuroraNet achieved an average PSNR of 35.59 dB on the first dataset and 38.40 dB on the second, together with an SSIM of 0.9633 in the latter. Across both benchmarks, AuroraNet consistently delivered higher reconstruction quality than several established models and the baseline DudeNet. Although R-REDNet produced the highest overall scores on one of the datasets, AuroraNet attained comparable performance while using a much smaller amount of parameters, underscoring its efficiency and practical value. These results indicate that AuroraNet offers a balanced solution for real-world image denoising, providing strong denoising capability without sacrificing computational economy.

Yanshuo Liu, Hongxia Li, Gang Liu et al.

Offshore structures frequently confront complex and variable marine environments, and the frequency-domain approach is often used in engineering to predict the fatigue damage of structures. To bridge the gap between stress spectra and stress range distributions, this paper proposes a novel stress range probability density distribution model comprising two stress range distribution functions, which can be well adapted to the shapes of the stress power spectral density (PSD) in various cases, and provides a more accurate representation of the rain-flow range probability density function (PDF). This study initially analyzes the stress range distributions of bimodal spectra using the rain-flow counting RFC method. Subsequently, and the unknown parameters of the stress range PDF are determined using the 1st-order moment of rain-flow stress amplitudes and polynomial relationships derived from normalized mean frequency and shape parameters. The proposed model is validated through the use of stress time-series data generated from random combinations of normal distribution functions.

Deepak A. Cherian

I take inspiration from the property-testing literature, particularly the work of Prof. John Hughes, and explore how such ideas might be applied to numerical models of the ocean. Specifically, I ask whether geophysical fluid dynamics (GFD) theory, expressed as property tests, might be used to address the oracle problem of testing the correctness of ocean models. I propose that a number of simple idealized GFD problems can be framed as property tests. These examples clearly illustrate how physics naturally lends itself to specifying property tests. Which of these proposed tests might be most feasible and useful, remains to be seen.

Wenshuai Liu

The lunar farside highlands, referred to as the lunar farside thicker crust compared with the nearside crust, presents a challenge to the theory of formation and evolution of the Moon. Here, we show that, after the Moon reached synchronous rotation, Earthshine could induce global circulation in lunar magma ocean due to the imposed surface temperature gradient generated by the hot, post-giant impact Earth. The global circulation, generating downwellings on the farside and a deeper return flow on the nearside, results that magmas flow from the nearside to the farside in the shallow magma ocean while the the direction of flow is opposite in the deep magma ocean. Such flow in the shallow magma ocean would transport anorthositic crystals formed in the nearside to the farside. Furthermore, since the lunar farside is cooler than the nearside, crystallization is much more efficient at the farside, resulting that farside magmas transported from the nearside produce anorthositic crystals rapidly. The theory proposed here may provide a natural way of explaining the origin of the lunar farside highlands and the lunar dichotomy.

Armin Ariamajd, Raquel López-Ríos de Castro, Andrea Volkamer

The increasing importance of Computational Science and Engineering has highlighted the need for high-quality scientific software. However, research software development is often hindered by limited funding, time, staffing, and technical resources. To address these challenges, we introduce PyPackIT, a cloud-based automation tool designed to streamline research software engineering in accordance with FAIR (Findable, Accessible, Interoperable, and Reusable) and Open Science principles. PyPackIT is a user-friendly, ready-to-use software that enables scientists to focus on the scientific aspects of their projects while automating repetitive tasks and enforcing best practices throughout the software development life cycle. Using modern Continuous software engineering and DevOps methodologies, PyPackIT offers a robust project infrastructure including a build-ready Python package skeleton, a fully operational documentation and test suite, and a control center for dynamic project management and customization. PyPackIT integrates seamlessly with GitHub's version control system, issue tracker, and pull-based model to establish a fully-automated software development workflow. Exploiting GitHub Actions, PyPackIT provides a cloud-native Agile development environment using containerization, Configuration-as-Code, and Continuous Integration, Deployment, Testing, Refactoring, and Maintenance pipelines. PyPackIT is an open-source software suite that seamlessly integrates with both new and existing projects via a public GitHub repository template at https://github.com/repodynamics/pypackit.

Leonhard Applis, Yuntong Zhang, Shanchao Liang et al.

The growth of Large Language Model (LLM) technology has raised expectations for automated coding. However, software engineering is more than coding and is concerned with activities including maintenance and evolution of a project. In this context, the concept of LLM agents has gained traction, which utilize LLMs as reasoning engines to invoke external tools autonomously. But is an LLM agent the same as an AI software engineer? In this paper, we seek to understand this question by developing a Unified Software Engineering agent or USEagent. Unlike existing work which builds specialized agents for specific software tasks such as testing, debugging, and repair, our goal is to build a unified agent which can orchestrate and handle multiple capabilities. This gives the agent the promise of handling complex scenarios in software development such as fixing an incomplete patch, adding new features, or taking over code written by others. We envision USEagent as the first draft of a future AI Software Engineer which can be a team member in future software development teams involving both AI and humans. To evaluate the efficacy of USEagent, we build a Unified Software Engineering bench (USEbench) comprising of myriad tasks such as coding, testing, and patching. USEbench is a judicious mixture of tasks from existing benchmarks such as SWE-bench, SWT-bench, and REPOCOD. In an evaluation on USEbench consisting of 1,271 repository-level software engineering tasks, USEagent shows improved efficacy compared to existing general agents such as OpenHands CodeActAgent. There exist gaps in the capabilities of USEagent for certain coding tasks, which provides hints on further developing the AI Software Engineer of the future.

Xiaoshi Zhou, Yanran Dai, Haidong Qin et al.

Achieving precise synchronization is critical for multi-camera systems in various applications. Traditional methods rely on hardware-triggered synchronization, necessitating significant manual effort to connect and adjust synchronization cables, especially with multiple cameras involved. This not only increases labor costs but also restricts scene layout and incurs high setup expenses. To address these challenges, we propose a novel subframe synchronization technique for multi-camera systems that operates without the need for additional hardware triggers. Our approach leverages a time-calibrated video featuring specific markers and a uniformly moving ball to accurately extract the temporal relationship between local and global time systems across cameras. This allows for the calculation of new timestamps and precise frame-level alignment. By employing interpolation algorithms, we further refine synchronization to the subframe level. Experimental results validate the robustness and high temporal precision of our method, demonstrating its adaptability and potential for use in demanding multi-camera setups.

Baohang Wang, Wenhong Li, Chaoying Zhao et al.

Interferometric fringes containing noise with complex distributions significantly contribute to phase unwrapping (PhU) failures in synthetic aperture radar interferometry (InSAR) technology. The study proposes an <italic>L</italic>²-Norm Quasi 3-D PhU-assisted multitemporal InSAR strategy. Initially, the <italic>L</italic>²-norm quasi 3-D PhU (first spatial 2-D and then temporal 1-D PhU) is employed to reduce the phase gradient of interferograms with optimized networks. The advantage of this methodology is that the wrapped residual phase satisfies the phase triangle, thereby making it suitable for existing widely-used 2-D or 3-D PhU techniques. Subsequently, a popular PhU method is applied to the residual phase, which is smooth and continuous, thereby improving the accuracy of subsequent spatial PhU. The deformation rate, time series and number of PhU triplet closures demonstrate the reliability of the proposed method for the Pingtan Straits Rail-cum-Road Bridge and the Hong Kong&#x2013;Zhuhai&#x2013;Macao Bridge in China using the sentinel-1A SAR dataset. The deformation results demonstrate that the bridge deformation is temperature-dependent, with the location of deformation being contingent upon the structural configuration of the bridge.

Liying Chen, Liying Chen, Dai Li et al.

Research on the microbiota associated with marine invertebrates is important for understanding host physiology and the relationship between the host and the environment. In this study, the microbiota of the green mussel Perna viridis was characterized at the tissue scale using 16S rRNA gene high-throughput sequencing and compared with the microbiota of the surrounding environment. Different mussel tissues were sampled, along with two environmental samples (the mussel's attachment substratum and seawater). The results showed that the phyla Proteobacteria, Bacteroidetes, and Spirochaetae were dominant in mussel tissues. The bacterial community composition at the family level varied among the tissues of P. viridis. Although the microbiota of P. viridis clearly differed from that of the surrounding seawater, the composition and diversity of the microbial community of the foot and outer shell surface were similar to those of the substratum, indicating their close relationship with the substratum. KEGG prediction analysis indicated that the bacteria harbored by P. viridis were enriched in the degradation of aromatic compounds, osmoregulation, and carbohydrate oxidation and fermentation, processes that may be important in P. viridis physiology. Our study provides new insights into the tissue-scale characteristics of mussel microbiomes and the intricate connection between mussels and their environment.

Md. Toukir Ahmed, Md Wadud Ahmed, Ocean Monjur et al.

As the demand for food surges and the agricultural sector undergoes a transformative shift towards sustainability and efficiency, the need for precise and proactive measures to ensure the health and welfare of livestock becomes paramount. In the context of the broader agricultural landscape outlined, the application of Hyperspectral Imaging (HSI) takes on profound significance. HSI has emerged as a cutting-edge, non-destructive technique for fast and accurate egg quality analysis, including the detection of chick embryo mortality. However, the high cost and operational complexity compared to conventional RGB imaging are significant bottlenecks in the widespread adoption of HSI technology. To overcome these hurdles and unlock the full potential of HSI, a promising solution is hyperspectral image reconstruction from standard RGB images. This study aims to reconstruct hyperspectral images from RGB images for non-destructive early prediction of chick embryo mortality. Firstly, the performance of different image reconstruction algorithms, such as HRNET, MST++, Restormer, and EDSR were compared to reconstruct the hyperspectral images of the eggs in the early incubation period. Later, the reconstructed spectra were used to differentiate live from dead chick-producing eggs using the XGBoost and Random Forest classification methods. Among the reconstruction methods, HRNET showed impressive reconstruction performance with MRAE of 0.0955, RMSE of 0.0159, and PSNR of 36.79 dB. This study motivated that harnessing imaging technology integrated with smart sensors and data analytics has the potential to improve automation, enhance biosecurity, and optimize resource management towards sustainable agriculture 4.0.

Mitra Ebrahimpoor, Renee Menezes, Ningning Xu et al.

Integrated analysis of multi-omics datasets holds great promise for uncovering complex biological processes. However, the large dimension of omics data poses significant interpretability and multiple testing challenges. Simultaneous Enrichment Analysis (SEA) was introduced to address these issues in single-omics analysis, providing an in-built multiple testing correction and enabling simultaneous feature set testing. In this paper, we introduce OCEAN, an extension of SEA to multi-omics data. OCEAN is a flexible approach to analyze potentially all possible two-way feature sets from any pair of genomics datasets. We also propose two new error rates which are in line with the two-way structure of the data and facilitate interpretation of the results. The power and utility of OCEAN is demonstrated by analyzing copy number and gene expression data for breast and colon cancer.

Junyang Gou, Lara Börger, Michael Schindelegger et al.

The gravimetry measurements from the Gravity Recovery and Climate Experiment (GRACE) and its follow-on (GRACE-FO) satellite mission provide an essential way to monitor changes in ocean bottom pressure ($p_b$), which is a critical variable in understanding ocean circulation. However, the coarse spatial resolution of the GRACE(-FO) fields blurs important spatial details, such as $p_b$ gradients. In this study, we employ a self-supervised deep learning algorithm to downscale global monthly $p_b$ anomalies derived from GRACE(-FO) observations to an equal-angle $0.25^\circ$ grid in the absence of high-resolution ground truth. The optimization process is realized by constraining the outputs to follow the large-scale mass conservation contained in the gravity field estimates while learning the spatial details from two ocean reanalysis products. The downscaled product agrees with GRACE(-FO) solutions over large ocean basins at the millimeter level in terms of equivalent water height and shows signs of outperforming them when evaluating short spatial scale variability. In particular, the downscaled $p_b$ product has more realistic signal content near the coast and exhibits better agreement with tide gauge measurements at around 80% of 465 globally distributed stations. Our method presents a novel way of combining the advantages of satellite measurements and ocean models at the product level, with potential downstream applications for studies of the large-scale ocean circulation, coastal sea level variability, and changes in global geodetic parameters.

Surajit Das Barman, Rakibuzzaman Shah, Syed Islam et al.

This paper demonstrates a 2-D numerical model to represent two conceptual pyrocumulonimbus (pyroCb) thundercloud structures: i) tilted dipole and ii) tripole structure with enhanced lower positive charge layer, which are hypothesized to explain the occurrence of lightning flashes in pyroCb storms created from severe wildfire events. The presented model considers more realistic thundercloud charge structures to investigate the electrical states and determine surface charge density for identifying potential lightning strike areas on Earth. Simulation results on dipole structure-based pyroCb thunderclouds confirm that the wind-shear extension of its upper positive (UP) charge layer by 2&#x2013;8 km reduces the electric field and indicates the initiation of negative surface charge density around the earth periphery underneath the anvil cloud. These corresponding lateral extensions have confined the probable striking zone of &#x2013;CG and +CG lightning within 0&#x2013;23.5 km and 23.5&#x2013;30 km in the simulation domain. In contrast, pyroCb thundercloud possessing the tripole structure with enhanced lower positive charge develops a negative electric field at the cloud&#x0027;s bottom part to block the progression of downward negative leader and cause the surface charge density beneath the thundercloud to become negative, which would lead to the formation of +CG flashes. Later, a parametric study is conducted assuming a positive linear correlation between the charge density and aerosol concentration to examine the effect of high aerosol concentration on surface charge density in both pyroCb thunderclouds. The proposed model can be expanded into 3-D to simulate lightning leader movement, aiding wildfire risk management.

Panagiota Keramea, Nikolaos Kokkos, George Zodiatis et al.

The second-largest oil pollution incident in the Eastern Mediterranean Levantine basin, following the oil pollution crisis in Lebanon in 2006, is considered to be the oil leakage from the Syrian Baniyas power plant (summer 2021), during which 12,000 tons of oil were released. At the operational phase, the everyday predictions of oil drift were provided using the MEDSLIK and MEDSLIK-II models in the framework of an agreement between the Mediterranean Operational Network for Global Ocean Observing System (MONGOOS) and the Regional Marine Pollution Emergency Response Centre for the Mediterranean (REMPEC). In this work, we present a novel post-operational comprehensive model-based analysis, conducting a SAR validation in two model outputs: the MEDSLIK and the OpenDrift models. Each simulation is initiated with the operationally acquired EMSA-CSN and ESA SAR images. Moreover, the high-resolution met-ocean fields (CYCOFOS, SKIRON) are used to force the oil drift and transformation in both models. The spill was developed under the calm-wind conditions that prevailed during the incident. We found that the boundary sea currents developed on the periphery of the Lattakia eddies (anticyclonic and cyclonic) were responsible for the fast westward spreading of the oil spill offshore in the NE Levantine, the north-south pathway bifurcation, and re-landing of oil in the extended coastal area of Lattakia. Model outputs were validated against Synthetic-aperture radar (SAR) images with appropriate performance metrics, used for the first time, to assess the capacity of a reliable representation of oil spill drift. The intercomparison between the two oil spill models indicated that both models produce almost similar results, while their validation against the satellite SAR observations illustrates moderate accuracy.

Antonio Petrizzo, Andrea Barbanti, Giulia Barfucci et al.

Abstract The protection of marine habitats from human-generated underwater noise is an emerging challenge. Baseline information on sound levels, however, is poorly available, especially in the Mediterranean Sea. To bridge this knowledge gap, the SOUNDSCAPE project ran a basin-scale, cross-national, long-term underwater monitoring in the Northern Adriatic Sea. A network of nine monitoring stations, characterized by different natural conditions and anthropogenic pressures, ensured acoustic data collection from March 2020 to June 2021, including the full lockdown period related to the COVID-19 pandemic. Calibrated stationary recorders featured with an omnidirectional Neptune Sonar D60 Hydrophone recorded continuously 24 h a day (48 kHz sampling rate, 16 bit resolution). Data were analysed to Sound Pressure Levels (SPLs) with a specially developed and validated processing app. Here, we release the dataset composed of 20 and 60 seconds averaged SPLs (one-third octave, base 10) output files and a Python script to postprocess them. This dataset represents a benchmark for scientists and policymakers addressing the risk of noise impacts on marine fauna in the Mediterranean Sea and worldwide.

Zhang Baofeng, Zhang Baofeng, Zhang Baofeng et al.

The single pile offshore wind turbine foundation is a typical flexible structure, and the dynamic interac-tion between ice and structure is complex. Ice-induced vibrations can affect the normal operation of the upper motor and the safety of the foundation structure. This paper takes the interaction between ice and offshore platform in the Bohai Sea as the research object and discusses the strategies to mitigate the ice- induced vibrations of offshore wind turbine foundation. Through a simplified mechanical model of a damping vibration isolation system, the relationship between the parameters of the damping isolation layer and the structural damping ratio was analyzed. Based on the numerical simulation results, it was found that the damping isolation layer with a damping ratio of 0.2 can play a better role in controlling structural displacement and acceleration response under the action of steady-state and random ice forces. It provides a reference for the design of ice-resistant and safe operation of the offshore wind turbine.