Hasil untuk "Ocean engineering"

A. El-Rabbany

Jun Hu, Tao Ren, Meiyu Sun et al.

Passive chilled beam (PCB) systems have attracted considerable attention for the application in public buildings due to its improving energy efficiency and thermal comfort. The ventilation performance of the PCB is comprehensively evaluated using a validated numerical model in the present study. Three key influencing factors are considered: PCB cooling capacity (qPCB), aspect ratio (AR), and false ceiling configuration. The results indicate that the overall indoor temperature is reduced from 25.2 °C to 22.7 °C with increasing qPCB from 20 to 60 W/m2. However, the vertical temperature difference is increased by 0.2 °C in the seated position and 0.6 °C in the standing position. Comprehensive analysis indicates that an optimal AR within the range of 0.17–0.20 results in the most uniform indoor temperature field, minimizes the extent of overcooled zones, and optimizes the distribution of PMV and PD, achieving a balance between cooling efficiency and thermal comfort. The installation of a false ceiling leads to an increase in indoor temperature by approximately 0.3 °C, compared to the scenario without a false ceiling. Hollow square false ceiling present better overall performance, with a more uniform indoor temperature distribution and a reduced sensation of the cold air.

Zifei Xu

Predictive maintenance for floating offshore wind turbines (FOWTs) presents significant challenges due to the need for flexible integration of structural damage prediction and maintenance decision-making under uncertainty. In particular, it requires accurate estimation of damage progression and adaptive planning of maintenance actions that balance safety, reliability, and cost across the lifecycle. To address these challenges, this study proposes an intelligent predictive maintenance framework that couples a damage magnitude prediction model with a reinforcement learning-based decision-making module. The prediction model estimates damage magnitude, quantifies uncertainty, and evaluates failure probability within inspection intervals, while the decision module selects optimal preventive actions to maintain structural integrity and economic efficiency. The framework is validated using a high-fidelity simulated FOWT dataset. The results demonstrate that prediction uncertainty decreases as damage severity increases, indicating greater model confidence in critical conditions. Furthermore, the reinforcement learning module adaptively balances risk and operational cost, yielding near-optimal maintenance schedules even under cost uncertainty. Overall, proposed framework reduces operation and maintenance costs, enhances safety, and supports sustainable FOWT operation.

Manuela F. Ceron-Viveros, Wolfgang Maass, Jiaojiao Tian

Window segmentation and vectorization remains a significant challenge, particularly in the absence of clean facade images. To extract complete window segments from building fa&#x00E7;ade images with occlusions, this article proposes an occlusion-aware window segmentation <italic>(OA-WinSeg)</italic> network with conditional adversarial training guided by prior structural information. This architecture combines the power of image segmentation and generative capabilities to handle occlusions. First, <italic>OA-WinSeg</italic> automatically detects occlusions and generates a rectangular boundary guidance from a coarse window segmentation, which incorporates structural information about the building layout into the process. Subsequently, the network refines the coarse segmentation and generates window segments in the missing regions by attending to contextual information of the nonoccluded parts of the fa&#x00E7;ade. Finally, our approach generates accurate vector representations, information needed for building modeling systems. Experimental results demonstrate the effectiveness of our model with simulated and occluded real-world datasets. In addition, we evaluate our model on various ablation studies to explore the contribution of the different modules. Finally, we have analyzed the potential applications of the proposed segmentation network and the completed window segments, including building fa&#x00E7;ade inpainting.

Erkang Chen, Zhiqi Lin, Jiancheng Chen et al.

Autonomous underwater cleaning in water pools requires reliable perception, efficient coverage path planning, and robust control. However, existing autonomous underwater vehicle (AUV) cleaning systems often suffer from fragmented software frameworks that limit end-to-end performance. To address these challenges, this paper proposes an integrated vision-based autonomous underwater cleaning system that combines global-camera AprilTag localization, YOLOv8-based dirt detection, and a multi-scale A* coverage path planning algorithm. The perception and planning modules run on a host computer system, while a NanoPi-based controller executes motion commands through a lightweight JSON-RPC protocol over Ethernet. This architecture ensures real-time coordination between visual sensing, planning, and hierarchical control. Experiments conducted in a simulated pool environment demonstrate that the proposed system achieves accurate localization, efficient planning, and reliable cleaning without blind spots. The results highlight the effectiveness of integrating vision, multi-scale planning, and lightweight embedded control for autonomous underwater cleaning tasks.

Lin Yan, Enchuan Qiao, Changyong Dou et al.

In this article, we present a comprehensive evaluation of the on-orbit radiometric performance of the multispectral imager (MSI) onboard the sustainable development goals science satellite 1 (SDGSAT-1). Launched on November 5, 2021, SDGSAT-1 is the first scientific satellite dedicated to supporting the United Nations&#x2019; 2030 agenda for sustainable development. The study systematically assesses key radiometric performance parameters, including signal-to-noise ratio (SNR), radiometric resolution, uniformity, and absolute radiometric calibration accuracy. Results indicate that the B1&#x2013;B3 bands exhibit good performance, with SNR exceeding 150 at high-reflectance sites (e.g., 309.5 for B1 over Gobi) and meeting requirements (<inline-formula><tex-math notation="LaTeX">$\geq$</tex-math></inline-formula>130 for B1, <inline-formula><tex-math notation="LaTeX">$\geq$</tex-math></inline-formula> 150 for B2&#x2013;B7). However, B4&#x2013;B7 bands show reduced SNR in low-reflectance regions (e.g., B5 SNR drops to 75.9 at LCFR Airport). Radiometric resolution remains stable for B1&#x2013;B3 (<inline-formula><tex-math notation="LaTeX">$\approx 1.0\times 10^{-3}$</tex-math></inline-formula>), while B4&#x2013;B7 display higher variability (up to 2.8&#x00D7; 10<inline-formula><tex-math notation="LaTeX">$^{-3}$</tex-math></inline-formula>). Radiometric uniformity is better than 2% for B1-B4 but degrades to 4.3% &#x2013;7.7% for B5&#x2013;B7 due to detector response inconsistencies. Absolute calibration accuracy falls within <inline-formula><tex-math notation="LaTeX">$\pm$</tex-math></inline-formula>7% for most bands, except B6 (7.2% <inline-formula><tex-math notation="LaTeX">$\pm$</tex-math></inline-formula>6.6% ), meeting the design specifications. These findings indicate that SDGSAT-1 MSI has a relatively stable on-orbit status with its radiometric performance well met the requirement, except some saturation bands, i.e., B4, B5, and B7. Further efforts including enhanced calibration algorithms developing, cross radiometric calibration with payloads have good radiometric performance will be conducted. This article provides critical insights into the operational characteristics of the MSI and offers a scientific basis for the long-term stability of satellite payloads and the reliability of data products, thereby supporting the achievement of global sustainable development goals.

Yongjian Li, Song Ji, Danchao Gong et al.

The development of satellite remote sensing technology has made it easier to obtain satellite imagery. Compared to imagery obtained from aerial photography, satellite imagery has the advantages of wide coverage, high acquisition efficiency, and periodic revisits. In photogrammetry, the 3-D reconstruction technology of satellite imagery often requires optimization and adjustment of numerous rational polynomial coefficient parameters, which to some extent limits the speed and accuracy of 3-D reconstruction. At the same time, the progress in 3-D reconstruction technology in the field of computer vision has shown certain advantages in terms of accuracy and speed. However, these methods are specifically designed for pinhole imaging models and cannot be directly applied to the 3-D reconstruction of satellite imagery with row-sampled central projection. The introduction of the equivalent pinhole imaging model enables computer vision methods to perform 3-D reconstruction on satellite imagery. This local approximation introduces reprojection errors when the RPC model is equivalent to the pinhole imaging model, thereby affecting the accuracy of 3-D reconstruction. This article investigates the causes and patterns of reprojection errors in the equivalent pinhole imaging model and proposes a method for generating pseudoimages through iterative resampling, as well as a method for partitioning satellite images to equivalently approximate the pinhole imaging model. Test results on the MVS3D dataset show that both methods can reduce reprojection errors, thereby improving the accuracy of 3-D reconstruction of satellite images using the equivalent pinhole imaging model.

Nicholas A Fackler, B. Heijstra, Blake J. Rasor et al.

Owing to rising levels of greenhouse gases in our atmosphere and oceans, climate change poses significant environmental, economic, and social challenges globally. Technologies that enable carbon capture and conversion of greenhouse gases into useful products will help mitigate climate change by enabling a new circular carbon economy. Gas fermentation using carbon-fixing microorganisms offers an economically viable and scalable solution with unique feedstock and product flexibility that has been commercialized recently. We review the state of the art of gas fermentation and discuss opportunities to accelerate future development and rollout. We discuss the current commercial process for conversion of waste gases to ethanol, including the underlying biology, challenges in process scale-up, and progress on genetic tool development and metabolic engineering to expand the product spectrum. We emphasize key enabling technologies to accelerate strain development for acetogens and other nonmodel organisms. Expected final online publication date for the Annual Review of Chemical and Biomolecular Engineering, Volume 12 is June 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

A. Vergés, Erin McCosker, M. Mayer‐Pinto et al.

1Centre for Marine Science & Innovation and Evolution & Ecology Research Centre, School of Biological, Earth and Environmental Sciences, UNSW Australia, Sydney, New South Wales, Australia; 2Sydney Institute of Marine Science, Mosman, New South Wales, Australia; 3Department of Primary Industries, New South Wales Fisheries, Coffs Harbour, New South Wales, Australia; 4National Marine Science Centre, Southern Cross University, Coffs Harbour, New South Wales, Australia; 5School of Biological Sciences, UWA Oceans Institute, University of Western Australia, Crawley, Western Australia, Australia; 6Department of Science and Environment (DSE), Roskilde University, Roskilde, Denmark and 7Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technical University, Singapore City, Singapore

Zhien Wang, M. Menenti

Laboratory for Atmospheric and Space Physics and Department of Atmospheric and Oceanic Sciences, University of Colorado, Boulder, CO, United States, Department of Geoscience and Remote Sensing, Faculty of Civil Engineering, Delft University of Technology, Delft, Netherlands, State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China

D. Keller, A. Lenton, V. Scott et al.

Abstract. The recent IPCC reports state that continued anthropogenic greenhouse gas emissions are changing the climate, threatening severe, pervasive and irreversible impacts. Slow progress in emissions reduction to mitigate climate change is resulting in increased attention to what is called geoengineering, climate engineering, or climate intervention – deliberate interventions to counter climate change that seek to either modify the Earth's radiation budget or remove greenhouse gases such as CO2 from the atmosphere. When focused on CO2, the latter of these categories is called carbon dioxide removal (CDR). Future emission scenarios that stay well below 2 °C, and all emission scenarios that do not exceed 1.5 °C warming by the year 2100, require some form of CDR. At present, there is little consensus on the climate impacts and atmospheric CO2 reduction efficacy of the different types of proposed CDR. To address this need, the Carbon Dioxide Removal Model Intercomparison Project (or CDRMIP) was initiated. This project brings together models of the Earth system in a common framework to explore the potential, impacts, and challenges of CDR. Here, we describe the first set of CDRMIP experiments, which are formally part of the 6th Coupled Model Intercomparison Project (CMIP6). These experiments are designed to address questions concerning CDR-induced climate reversibility , the response of the Earth system to direct atmospheric CO2 removal (direct air capture and storage), and the CDR potential and impacts of afforestation and reforestation, as well as ocean alkalinization.>

Lei Wang, Feng Zhang, Chongwei Zheng et al.

In this study, the Regional Ocean Modeling System (ROMS) is employed to construct a three-dimensional barotropic ocean model with a monodirectional upper boundary and homogeneous and steady wind covering the entire computation area. Eight perturbation experiments are designed to determine the vertical grid distribution difference with high resolution at the surface and bottom. Two types are considered in the model, including removing the Coriolis force (type 1) and employing a different Coriolis force (type 2). According to the experiments, the velocity of the current in type 1 yields uncertainty, and wind energy could penetrate the upper ocean and reach the abyss. The surface velocity in type 2 is fundamentally compatible with the empirical relationship constructed by Ekman, and the curved lines of the vertical distribution of horizontal currents nearly match. For type 1, the velocity is very strong from the sea surface to the bottom. When comparing type 1 and type 2 cases, the Coriolis force obstructs the wind energy transfer into the deep ocean. In addition, the European Centre for Medium-Range Weather Forecasts (ECMWF)’s global surface wind distribution indicates that the realistic ocean upper wind boundary is similar to the numerical experiment in the Pacific and Atlantic oceans, where the wind direction is along the latitude line at the equator. In order to make the experimental situation as close as possible to the real ocean, validation experiments are conducted in this study to consider the uncertainty in the current profile at the equator. The simulation results of type 1 differ significantly from the data obtained from the real ocean. This uncertainty may transfer the signal to higher latitudes, causing incorrect simulation results, especially in the critical region. Overall, this research not only makes discoveries in physical ocean theory but also guides predictive and forecasting techniques for ocean modeling.

Jinglei Li, Haiyan Wang, Haijie Yu et al.

Thermal damage induced by coal spontaneous combustion (CSC) has a significant impact on its development. In this study, low-rank coals were heat-treated (25–500 °C). Experiments such as nuclear magnetic resonance, scanning electron microscopy, and uniaxial compression were used to visualize and quantify the evolution of pore structure and structural strength during CSC. A multi-component discrete-element model of coal thermal fracture was developed and a sensitivity analysis of the micromechanical behavior of CSC was carried out. The results showed that during CSC, the micropores in coal gradually evolved into mesopores or macropores, and the pore diameter, porosity and permeability can be increased to 5.51 μ m, 21.05 % and 1.51 mD respectively with the temperature. Significant thermal damage occurred in low-rank coal at 100 °C, leading to a sharp decrease in its load-bearing capacity, which made it easier to reach the damage condition and produce more cracks. And then the thermal damage was fluctuating with the increase of temperature. From 100 °C to 500 °C, the micromechanical behavior of low-rank coal is similar, and the variation of the critical value with temperature is small. The study results can serve as a reference for controlling coal fires.

Yongfu Ke, Limei Shi, Weinan Ji et al.

With the widespread application of mobile robotics technology, path planning has increasingly become a research hotspot. In complex environments, planning an efficient, stable, and safe path is an urgent problem that needs to be addressed. To this end, this paper proposes the Improved Walrus Optimization Algorithm (IWaOA) and applies it to path planning. Firstly, the Sine-Tent-Cosine chaotic mapping is used to initialize the walrus population, addressing the issue of insufficient population diversity in the later stages of the algorithm&#x2019;s iteration. Next, two improvement strategies are proposed: optimal value-enhanced random walk and directional evolutionary mutation. These strategies aim to enhance the algorithm&#x2019;s local search capability and precision, optimizing the issues of the original algorithm&#x2019;s proneness to falling into local optima and slow convergence speed. Finally, building on the three stages of the Walrus Optimization Algorithm (WaOA), this paper introduces a fourth stage termed the &#x201C;Hunting Stage&#x201D; to the original algorithm with historical experience positions. It&#x2019;s capable of significantly improving the overall performance of the algorithm. Evaluating the performance of the proposed algorithm, this paper conducts experiments with three distinct sets of benchmark functions and compares the outcomes against various swarm intelligence algorithms. Furthermore, the IWaOA was applied to the path planning problem for mobile robots. The experimental results confirm the efficacy and advantage of the IWaOA compared to the traditional WaOA, demonstrating a decrease in path length by 16.7%, 3.7%, and 6.2% across three different map scenarios.

N. Seltenrich

In recent years plastic pollution in the ocean has become a significant environmental concern for governments, scientists, nongovernmental organizations, and members of the public worldwide. A December 2014 study derived from six years of research by the 5 Gyres Institute estimated that 5.25 trillion plastic particles weighing some 269,000 tons are floating on the surface of the sea.1 At the same time, plastics in consumer products have become subject to increasing scrutiny regarding their potential effects on human health. Bisphenol A (BPA),2 a component of polycarbonate plastics and suspected endocrine disruptor, is one of the most widely known chemicals of interest. But BPA is only one of many monomers, plasticizers, flame retardants, antimicrobials, and other chemicals used in plastics manufacturing3 that are able to migrate into the environment. Investigators are researching whether consumption of plastic debris by marine organisms translates into toxic exposures for people who eat seafood. At the junction of these two lines of inquiry is an emerging third field that is in many ways even more complex and less well understood: investigating human exposures to and potential health effects of plastics that have entered the marine food chain. Studies have demonstrated plastics’ tendency to sorb (take up) persistent, bioaccumulative, and toxic substances, which are present in trace quantities in almost all water bodies.4 The constituents of plastics, as well as the chemicals and metals they sorb, can travel into the bodies of marine organisms upon consumption,5,6,7,8,9 where they may concentrate and climb the food chain, ultimately into humans. This topic has attracted interest and funding from the U.S. Environmental Protection Agency (EPA), the National Oceanic and Atmospheric Administration (NOAA), and the National Academy of Sciences (NAS), as well as researchers, nonprofit groups, and institutions around the world. At this point “there are more questions than answers,” says Richard Thompson, a professor of marine science and engineering at England’s Plymouth University. Thompson coined the term “microplastics” in 200410 and later undertook a three-year study of these particles in the marine environment for the UK’s Department of Environment, Food, and Rural Affairs.11,12,13 “From a human perspective,” he says, “at the moment I think there’s cause for concern rather than cause for alarm.” Viewpoints on the human health risks of marine debris are nearly as complex as the underlying science, as was evident at an inaugural EPA and NAS symposium on the topic held in Washington, DC, in April 2014. In addition to myriad small details, the researchers in attendance considered an overarching question: Within the context of limited oceanographic research funding, the variety of other problems affecting ocean health (including overfishing and acidification), and the extent of humans’ daily and direct exposures to potentially harmful chemicals from consumer plastics and other sources—how concerned should we be about marine plastics as far as human health goes? Researchers don’t yet have an answer, even if they believe they’re asking the right question. As EPA chemist Richard Engler concluded in a 2012 review, “While current research cannot quantify the amount, plastic in the ocean does appear to contribute to [persistent, bioaccumulative, and toxic substances] in the human diet.”14

Hengtong Zhang, Xixi Wu, Liang Quan et al.

Oceans have vast potential to develop high-value bioactive substances and biomaterials. In the past decades, many biomaterials have come from marine organisms, but due to the wide variety of organisms living in the oceans, the great diversity of marine-derived materials remains explored. The marine biomaterials that have been found and studied have excellent biological activity, unique chemical structure, good biocompatibility, low toxicity, and suitable degradation, and can be used as attractive tissue material engineering and regenerative medicine applications. In this review, we give an overview of the extraction and processing methods and chemical and biological characteristics of common marine polysaccharides and proteins. This review also briefly explains their important applications in anticancer, antiviral, drug delivery, tissue engineering, and other fields.

R. More, A. Ardekani

Density stratification due to temperature or salinity variations greatly influences the flow around and the sedimentation of objects such as particles, drops, bubbles, and small organisms in the atmosphere, oceans, and lakes. Density stratification hampers the vertical flow and substantially affects the sedimentation of an isolated object, the hydrodynamic interactions between a pair of objects, and the collective behavior of suspensions in various ways, depending on the relative magnitude of stratification, inertia (advection), and viscous (diffusion) effects. This review discusses these effects and their hydrodynamic mechanisms in some commonly observed fluid–particle transport phenomena in oceans and the atmosphere. Physical understanding of these mechanisms can help us better model these phenomena and, hence, predict their geophysical, engineering, ecological, and environmental implications. Expected final online publication date for the Annual Review of Fluid Mechanics, Volume 55 is January 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

E. Pan

The Green’s function (GF) method, which makes use of GFs, is an important and elegant tool for solving a given boundary-value problem for the differential equation from a real engineering or physical field. Under a concentrated source, the solution of a differential equation is called a GF, which is singular at the source location, yet is very fundamental and powerful. When looking at the GFs from different physical and/or engineering fields, i.e. assigning the involved functions to real physical/engineering quantities, the GFs can be scaled and applied to large-scale problems such as those involved in Earth sciences as well as to nano-scale problems associated with quantum nanostructures. GFs are ubiquitous and everywhere: they can describe heat, water pressure, fluid flow potential, electromagnetic (EM) and gravitational potentials, and the surface tension of soap film. In the undergraduate courses Mechanics of Solids and Structural Analysis, a GF is the simple influence line or singular function. Dropping a pebble in the pond, it is the circular ripple traveling on and on. It is the wave generated by a moving ship in the opening ocean or the atom vibrating on a nanoscale sheet induced by the atomic force microscopy. In Earth science, while various GFs have been derived, a comprehensive review is missing. Thus, this article provides a relatively complete review on GFs for geophysics. In section , the George Green’s potential functions, GF definition, as well as related theorems and basic relations are briefly presented. In section , the boundary-value problems for elastic and viscoelastic materials are provided. Section is on the GFs in full- and half-spaces (planes). The GFs of concentrated forces and dislocations in horizontally layered half-spaces (planes) are derived in section in terms of both Cartesian and cylindrical systems of vector functions. The corresponding GFs in a self-gravitating and layered spherical Earth are presented in section in terms of the spherical system of vector functions. The singularity and infinity associated with GFs in layered systems are analyzed in section along with a brief review of various layer matrix methods. Various associated mathematical preliminaries are listed in appendix, along with the three sets of vector function systems. It should be further emphasized that, while this review is targeted at geophysics, most of the GFs and solution methods can be equally applied to other engineering and science fields. Actually, many GFs and solutions methods reviewed in this article are derived by engineers and scientists from allied fields besides geophysics. As such, the updated approaches of constructing and deriving the GFs reviewed here should be very beneficial to any reader.

Q. Guan, Fei Ji, Yun Liu et al.

With the advance of the Internet of Underwater Things, underwater acoustic sensor network (UASN) has been considered as a promising technology for oceanic engineering to explore and exploit marine resources. Due to the time variability, frequency selectivity, and the very limited available bandwidth, underwater acoustic (UWA) channels are generally known as one of the most challenging communication media in use today. The highly dynamic nature of UWA links calls for adaptive, scalable, and efficient routing schemes for UASNs. Depth-based routing has attracted much attention because it can work efficiently without the need for full-dimensional location information of sensors. However, it suffers from the problems of void region and detouring forwarding. To this end, this paper proposes a distance-vector-based opportunistic routing (DVOR) scheme to address these problems. DVOR uses a query mechanism to establish the distance vectors for UWA nodes, which record the smallest hop counts toward the sink. Then, an opportunistic routing is developed to coordinate the packet forwarding based on the distance vectors. DVOR has a low signaling overhead in opportunistic forwarding, as well as the ability to avoid the problems of void region and long detour. Simulation results show that DVOR outperforms the existing routing protocols in terms of packet delivery ratio, energy-efficiency, and average end-to-end delay.

Rafi Ullah Khan, Jingbo Yin, Siqi Wang et al.

The inherent complexities of Artificial Intelligence (AI) and machine learning (ML) technologies expose autonomous ships to a wide range of multifaceted interconnected risks. However, very few studies have aimed at the holistic risk assessment of autonomous ships. To this end, this study employs an expert-opinion-based integrated machine learning approach amalgamating logistic regression and Bayesian network to conduct risk assessment for autonomous ships. The results reveal human factor interactions and operational issues as the prominent accident causation factors. The findings of this study will contribute significantly to the existing literature on autonomous ships and the complexities involved in their operational systems. By identifying critical factors causing accidents and their impact on autonomous ship safety and resilience, stakeholders such as autonomous ship manufacturers, port authorities, shipping companies, and governments can develop more efficient and effective operational and safety systems.