RepDNet:A re-parameterization despeckling network for autonomous underwater side-scan sonar imaging with prior-knowledge customized convolution

Side-scan sonar(SSS)is now a prevalent instrument for large-scale seafloor topography measurements,deployable on an autonomous underwater vehicle(AUV)to execute fully automated underwater acoustic scanning imaging along a predetermined trajectory.However,SSS images often suffer from speckle noise caused by mutual interference between echoes,and limited AUV computational resources further hinder noise suppression.Existing approaches for SSS image processing and speckle noise reduction rely heavily on complex network structures and fail to combine the benefits of deep learning and domain knowledge.To address the problem,Rep DNet,a novel and effective despeckling convolutional neural network is proposed.Rep DNet introduces two re-parameterized blocks:the Pixel Smoothing Block(PSB)and Edge Enhancement Block(EEB),preserving edge information while attenuating speckle noise.During training,PSB and EEB manifest as double-layered multi-branch structures,integrating first-order and secondorder derivatives and smoothing functions.During inference,the branches are re-parameterized into a 3×3 convolution,enabling efficient inference without sacrificing accuracy.Rep DNet comprises three computational operations:3×3 convolution,element-wise summation and Rectified Linear Unit activation.Evaluations on benchmark datasets,a real SSS dataset and Data collected at Lake Mulan aestablish Rep DNet as a well-balanced network,meeting the AUV computational constraints in terms of performance and latency.

Review of the evolution and prevention of friction,wear,and noise for water-lubricated bearings used in ships

With the development of green tribology in the shipping industry,the application of water lubrication gradually replaces oil lubrication in stern bearings and thrust bearings.In terms of large-scale and high-speed ships,water-lubricated bearings with high performance are more strictly required.However,due to the lubricating medium,water-lubricated bearings have many problems such as friction,wear,vibration,noise,etc.This review focuses on the performance of marine water-lubricated bearings and their failure prevention mechanism.Furthermore,the research of marine water-lubricated bearings is reviewed by discussing its lubrication principle,test technology,friction and wear mechanism,and friction noise generation mechanism.The performance enhancement methods have been overviewed from structure optimization and material modification.Finally,the potential problems and the perspective of water-lubricated bearings are given in detail.

Experimental Study on Wear Performance and Oil Film Characteristics of Surface Textured Cylinder Liner in Marine Diesel Engine

It is of a vital importance to reduce the frictional losses in marine diesel engines. Advanced surface textures have provided an e ective solution to friction performance of rubbing pairs due to the rapid development of surface engineering techniques. However,the mechanisms through which textured patterns and texturing methods prove beneficial remains unclear. To address this issue,the tribological system of the cylinder liner?piston ring(CLPR) is investigated in this work. Two types of surface textures(Micro concave,Micro V?groove) are processed on the cylinder specimen using di erent processing methods. Comparative study on the friction coe cients,worn surface texture features and oil film characteristics are performed. The results demonstrate that the processing method of surface texture a ect the performance of the CLPR pairs under the specific testing conditions. In addition the micro V?groove processed by CNCPM is more favorable for improving the wear performances at the low load,while the micro?con?cave processed by CE is more favorable for improving the wear performances at the high load. These findings are in helping to understand the e ect of surface texture on wear performance of CLPR.

Insight into the Lubrication Performance of Biomimetic Porous Structure Material for Water-lubricated Bearings

Water-lubricated bearings have great advantages in the application of ship tail bearings due to the characteristics of green,pollution-free,and sustainable.However,the poor wettability of water-lubricated materials,as well as the low viscosity and poor load-carrying capacity of water,resulting in poor lubricating film integrity and short material service life under low-speed,heavy-load,start-stop conditions,which limits its application.To study the relationship between wettability and lubrication state and improve the lubrication performance of Si_(3)N_(4) under water lubrication conditions,the characteristic parameters that determine the hydrophilicity of Sphagnum were detected and extracted,and the bionic Si_(3)N_(4) model was established using Material Studio.Then,the molecular dynamic behavior and tribological properties of different Si_(3)N_(4) models were simulated and analyzed.Pore structure affects the spreading and storage of water on the material surface and changes the wettability of the material.Under the condition of water lubrication,better wettability and water storage promote the formation of water film,effectively improve the lubrication state of the material,and improve its bearing performance.

Marine antifouling behavior of the surfaces modified by dopamine and antibacterial peptide

Marine biofouling causes serious harms to surfaces of marine devices in transportation,aquaculture,and offshore construction.Traditional antifouling methods pollute the environment.A novel and green antifouling strategy was developed to prevent effectively the adhe sion of bacteria and microalgae.An antifouling surface was fabricated via coating Turgencin BMox2(TB)onto dopamine-modified 304stainless steel(304 SS).The surface physical and chemical properties before and after modification were characterized by Fourier transform infrared spectrometer(FTIR),X-ray photoelectron spectrometer(XPS),contact angle measurement(CA),3D optical profilometer,ellipsometer,and atomic force microscope(AFM).Antimicrobial peptide was coated onto the surface of 304 SS successfully,and the surface morphology and wettability of the modified sample were modified.Moreover,cytocompatibility of the peptide was evaluated by co-culture of peptide and cells,indicating promising cell biocompatibility at the modified sample surface.At last,antifouling performance and electrochemical corrosion were tested.Results show that the adhesion rates of Vibrio natriegens and Phaeodactylum tricornutum on the antifouling surface were reduced by 99.85% and 67.93%,respectively from those of untreated samples.Therefore,the modified samples retained superior corrosion resistance.The study provide a simply and green way against biofouling on ship hulls and marine equipment.

Online interactive identification method based on ESO disturbance estimation for motion model of double propeller propulsion unmanned surface vehicle

In this paper, the online parameter identification problem of the mathematical model of an unmanned surface vehicle (USV) considering the characteristics of the actuator is studied. A data-driven mathematical model of motion is very meaningful to realize trajectory prediction and adaptive motion control of the USV. An interactive identification algorithm (ESO–MILS, extended state observer–multi-innovation least squares) based on ESO is proposed. The robustness of online identification is improved by expanding the state observer to estimate the current disturbance without making artificial assumptions. Specifically, the three-degree-of-freedom dynamic equation of the double propeller propulsion USV is constructed. A linear model for online identification is derived by parameterization. Based on the least square criterion function, it is proved that the interactive identification method with disturbance estimation can improve the identification accuracy from the perspective of mathematical expectation. The extended state observer is designed to estimate the unknown disturbance in the model. The online interactive update improves the disturbance immunity of the identification algorithm. Finally, the effectiveness of the interactive identification algorithm is verified by simulation experiment and real ship experiment.

Modeling mechanism of a novel fractional grey mode based on matrix analysis

To fully display the modeling mechanism of the novelfractional order grey model （FGM （q,1））, this paper decomposesthe data matrix of the model into the mean generation matrix, theaccumulative generation matrix and the raw data matrix, whichare consistent with the fractional order accumulative grey model（FAGM （1,1））. Following this, this paper decomposes the accumulativedata difference matrix into the accumulative generationmatrix, the q-order reductive accumulative matrix and the rawdata matrix, and then combines the least square method, findingthat the differential order affects the model parameters only byaffecting the formation of differential sequences. This paper thensummarizes matrix decomposition of some special sequences,such as the sequence generated by the strengthening and weakeningoperators, the jumping sequence, and the non-equidistancesequence. Finally, this paper expresses the influences of the rawdata transformation, the accumulation sequence transformation,and the differential matrix transformation on the model parametersas matrices, and takes the non-equidistance sequence as an exampleto show the modeling mechanism.

Wear monitoring method of water-lubricated polymer thrust bearing based on ultrasonic reflection coefficient amplitude spectrum

The water-lubricated thrust bearings of the marine rim-driven thruster(RDT)are usually composed of polymer composites,which are prone to serious wear under harsh working conditions.Ultrasonic is an excellent non-destructive monitoring technology,but polymer materials are characterized by viscoelasticity,heterogeneity,and large acoustic attenuation,making it challenging to extract ultrasonic echo signals.Therefore,this paper proposes a wear monitoring method based on the amplitude spectrum of the ultrasonic reflection coefficient.The effects of bearing parameters,objective function,and algorithm parameters on the identification results are simulated and analyzed.Taking the correlation coefficient and root mean square error as the matching parameters,the thickness,sound velocity,density,and attenuation factor of the bearing are inversed simultaneously by utilizing the differential evolution algorithm(DEA),and the wear measurement system is constructed.In order to verify the identification accuracy of this method,an accelerated wear test under heavy load was executed on a multi-functional vertical water lubrication test rig with poly-ether-etherketone(PEEK)fixed pad and stainless-steel thrust collar as the object.The thickness of pad was measured using the high-precision spiral micrometer and ultrasonic testing system,respectively.Ultimately,the results demonstrate that the thickness identification error of this method is approximately 1%,and in-situ monitoring ability will be realized in the future,which is of great significance to the life prediction of bearings.

Modelling medium-and long-term purchasing plans for environment-orientated container trucks:a case study of Yangtze River port

The transportation sector is the most significant contributor to anthropogenic greenhouse gas(GHG)emissions.Particularly,maritime transportation,which is predominantly powered by fossil-fuel engines,accounts for more than 90%of world freight movement and emits 3%of global carbon dioxide(CO_(2))emissions.China is the world’s largest emitter of CO_(2 )and plays a key role in mitigating global climate change.In order to tackle this pressing concern,this study analyses the port’s throughput,the current number of trucks and their emissions during the container truck purchasing process.Previous studies about container truck purchasing plans mostly focused on the trucks’price and port needs.The objective of this study is to minimize the total cost of a port’s inland transportation using optimization technique such as the interval uncertainty planning model to convert container truck emissions into social costs.The study considers the port of Yangtze as a case study.The study has designed two scenarios.(i)The base scenario(business-asusual,BAU)is used to quantify the relationship between pollutant emissions and system cost.In the base scenario,no environmental control facilities are used during the planning period,and there is no need to purchase new energy container trucks.(ii)The expected scenario(Scenario A)is for three planning periods.In Scenario A,the emissions levels are required to remain at the same level as the first planning period during the whole planning period.By solving the above model,the number of all truck types,system cost,container throughput and truck emissions in the port area were analysed.The results showed that if no emission reduction control measures are implemented in the next 9 years,the growth rate of pollutants in the port area could reach 20%.In addition,the findings showed clearly that truck emissions are reduced by purchasing new energy trucks and restricting the number of fossil-fuel(diesel)trucks.This study could also help to minimize system costs associated with port planning and management.

Insight into tribological problems of green ship and corresponding research progresses

The so-called "green ship" is being regarded as a potential solution to the problems that the shipping industry faces, such as energy conservation and environmental protection. Some new features, such as integrated renewable energy application, biomimetic materials, and antifriction and wear resistant coating have been accepted as the typical characteristics of a green ship, but the tribology problems involved in these domains have not been precisely redefined yet. Further, the related research work is generally focused on the technology or material itself, but not on the integration of the applicable object or green ship, marine environment, and tribological systematical analysis from the viewpoint of the energy efficiency design index(EEDI) and ship energy efficiency management plan(SEEMP) improvements. Aiming at the tribology problems of the green ship, this paper reviews the research status of this issue from three specific domains, which are the tribology problems of the renewable energy system, tribological research for hull resistance reduction, and energy efficiency enhancement. Some typical tribological problems in the sail-auxiliary system are discussed, along with the solar photovoltaic system and hull drag reduction in traditional marine mechanical equipment. Correspondingly, four domains that should be further considered for the future development target of the green ship are prospected.

Application of Bionic Tribology in Water-Lubricated Bearing:A Review

Water-lubricated bearing has become the development trend in the future because of its economy and environmental friendliness.The poor friction performance under low speed and heavy load seriously limits the popularization and application of water-lubricated bearings.Learning from nature,the phenomenon of low friction and wear in nature has aroused great interest of scientists,and a lot of research has been carried out from mechanism analysis to bionic application.In this review,our purpose is to provide guiding methods and analysis basis for the bionic design and theoretical research of anti-friction and anti-wear of water-lubricated bearings.The development of water-lubricated bearing materials are described.Some typical examples of natural friction reduction and drag reduction are introduced in detail,and several representative preparation methods are listed.Finally,the application status of bionic tribology in water-lubricated bearings is summarized,and the future development direction of water-lubricated bearings is prospected.

Structural Assessment of Printed Circuit Heat Exchangers in Supercritical CO_(2) Waste Heat Recovery Systems for Ship Applications

Printed circuit heat exchangers(PCHEs)are considered as the most promising heat exchangers for use of the supercritical carbon dioxide(S-CO_(2))Brayton cycle.As crucial components operating at high pressure and thermal load at the same time,PCHE structural integrity evaluations are essential.In this study,to assess the structural strength of PCHEs serving as recuperators and precoolers in the S-CO_(2) Brayton cycle as a waste heat recovery system for marine engines,the finite element method(FEM)is used and compared with a currently used method from ASME codes.The effects of temperature and pressure on the hot and cold sides are studied in terms of the temperature and pressure differences between the two sides and the main factors affecting its strength discussed.Then,detailed stress intensities of a PCHE under design conditions are investigated,and the results indicate that the highest stress appears at the middle of the semicircular arc of the channel,except for a concentration near the channel tip regions.Stresses of the PCHE are mainly caused by both pressure and temperature differences,with the minimum effect from temperature.The synthesis of the temperature and pressure fields exhibits a complicated action on the total stress under the design conditions.FEM was a more comprehensive means for structural assessment than the method from ASME codes.Further structural optimization of PCHE is conducted to ensure a maximum life span.This research work can provide theoretical guidance for structural integrity assessment of PCHE for the S-CO_(2) Brayton cycle.

Review of condition monitoring and fault diagnosis for marine power systems

The use of condition monitoring and fault diagnosis(CMFD)in marine power systems significantly influences ship safety.This study divides the development of CMFD for marine power systems into three periods and reviews the content,state and limitations of CMFD research for each period.According to the research achievements and engineering experience of the authors’team,typical application cases are introduced for CMFD in ships,including CMFD platforms on engineering ships,salvage ships,container ships and ro-ro ships powered by solar photovoltaic systems.Finally,prospective research directions are proposed for CMFD in marine power systems,considering the research status of CMFD and the trend toward intelligent and eco-friendly ships.

Introduction to special issue on maritime safety and smart shipping

Shipping is perhaps themost international of all the world’s great industries and one of the most dangerous.It is essential to study maritime safety and take reasonable measurements to ensure the security of life and property.With the rapid development of Artificial Intelligence,industrial upgrading is undergoing a change in the maritime industry,where many techniques have been developed to enhance maritime safety and improve the automation and intelligence of ships,equipment,and infrastructure.

Stable oral lubrication enhancer obtained from thiolated polyethylene glycol and mucin

Mucins are vital components contributing to the unique lubrication properties of human whole saliva.For patients receiving medication and or treatment such as diabetes or radiotherapy,xerostomia(dry mouth)is a common with numerous and deleterious side effects.Although products exist on the market to relive the symptoms of Xerostomia there remains a drive to formulate a biocompatible lubricant that replicate the functionality offered by the natural biological environment.Herein,a combination of mucin and thiolated polyethylene glycol(PEG-SH)was proposed as a new saliva substitute.Mucin and PEG-SH molecules could form hydrated layers immediately by chemisorption.Meanwhile,the chemical interactions between mucin and PEG-SH molecules also promoted the formation of a mixed layer.All the pre-formed layers could decrease friction and had the potential to decrease wear,especially mucin and PEG-SH mixed layer when compared to mucin only solutions.Further investigations of tribological mechanism implied that the excellent lubrication performance of mixed layer with long effectiveness was contributed to the frictionreducing effect of PEG/mucin molecules and the mucoadhesive property of mucin.The study provides a guide for using mucin as a mucoadhesive agent to stable lubricative polymers with low molecular weight as novel salivary substitutes for lubrication.

Load and velocity boundaries of oil-based superlubricity using 1,3-diketone

The clarification of the critical operating conditions and the failure mechanism of superlubricity systems is of great significance for seeking appropriate applications in industry.In this work,the superlubricity region of 1,3-diketone oil EPND(1-(4-ethyl phenyl)nonane-1,3-dione)on steel surfaces was identified by performing a series of ball-on-disk rotation friction tests under various normal loads(3.5–64 N)and sliding velocities(100–600 mm/s).The result shows that beyond certain loads or velocities superlubricity failed to be reached due to the following negative effects:(1)Under low load(≤3.5 N),insufficient running-in could not ensure good asperity level conformity between the upper and lower surfaces;(2)the high load(≥64 N)produced excessive wear and big debris;(3)at low velocity(≤100 mm/s),the weak hydrodynamic effect and the generated debris deteriorated the lubrication performance;(4)at high velocity(≥500 mm/s),oil migration occurred and resulted in oil starvation.In order to expand the load and velocity boundaries of the superlubricity region,an optimized running-in method was proposed to avoid the above negative effects.By initially operating a running-in process under a suitable combination of load and velocity(e.g.16 N and 300 mm/s)and then switching to the target certain higher or lower load/velocity(e.g.100 N),the superlubricity region could break through its original boundaries.The result of this work suggests that oil-based superlubricity of 1,3-diketone is a promising solution to friction reduction under suitable operating conditions especially using a well-designed running-in strategy.

Tribological behavior of co-textured cylinder liner-piston ring during running-in

The running-in of cylinder liner-piston rings(CLPRs)is the most important process that must be performed before a marine diesel engine can be operated.The quality of running-in directly affects the reliability of a CLPR.The surface texture of a CLPR has been proven to significantly affect its lubrication performance.In this study,the tribological behavior of a CLPR during running-in is investigated.Three types of surface textures are generated on the CLPR via laser processing:dimple texture on piston rings,groove texture on cylinder liners,and co-texture on both sides.Subsequently,a series of tests are performed on a slice tester.A load of 300 N(1.64 MPa) is applied,and two speeds(50 and 100 rpm)are adopted.The CLPR running-in quality is characterized based on three parameters,i.e.,the friction coefficient,contact resistance,and wear topography.Experimental results show that,compared with a non-textured surface,the three types of surface textures mentioned above improved the friction performance during running-in.The lubricant supply capacity of the dimple texture on the piston ring,as a mobile oil reservoir,is stronger than that of the groove texture on the cylinder liner serving as a static oil reservoir.By contrast,the wear resistance of the dimple texture,as a movable debris trap on the piston ring,is weaker than that of the groove texture on the cylinder liner,which serves as a static debris trap.It is demonstrated that the co-texture combines the advantages of dimples and groove textures.Compared with non-textured surfaces,the friction coefficient decreased the most at 100 rpm(44.5%),and the contact resistance improved the most at 50 rpm(352.9%).The coupling effect provides the surface with improved running-in quality by optimizing the tribological performance,particularly at the dead center.This study provides guidance for the tribological design and manufacturing of CLPR in marine diesel engines.

ANALYSIS OF THE IMPACT OF SAMPLE SIZE, ATTRIBUTE VARIANCE AND WITHIN-SAMPLE CHOICE DISTRIBUTION ON THE ESTIMATION ACCURACY OF MULTINOMIAL LOGIT MODELS USING SIMULATED DATA

Literature review indicates that sample size, attribute variance and within-sample choice distribution of alternatives are important considerations in the estimation of multinomial logit （MNL） models, but their impacts on the estimation accuracy have not been systematically studied. Therefore, the objective of this paper is to provide an empirical examination to the above issues through a set of simulated discrete choice preference and rank ordered preference datasets. In this paper, the utility coefficients, alternative specific constants （ASCs）, and the mean and standard deviation of the four attributes for a set of seven hypothetical alternatives are specified as a priori. Then, synthetic datasets, with varying sample size, attribute variance and within-sample choice distribution are simulated. Based on these datasets, the utility coefficients and ASCs of the specified MNLs are re-estimated and compared with the original values specified as the priori. It is found that （1） the estimation accuracy of utility parameters increases as the sample size increases; （2） the utility coefficients can be re-estimated with reasonable accuracy, but the estimates of the ASCs are confronted with much larger errors; （3） as the variances of the alternative attributes increase, the estimation accuracy improves significantly; and （4） as the distribution of chosen choices becomes more balanced across alternatives within sample datasets, the hit-ratio decreases. The results indicate that （a） under a similar setting presented in this paper, a large sample consisting of a few thousand observations （3000 - 4000） may be needed in order to provide reasonable estimates for utility coefficients, particularly for ASCs; （b） a larger, but realistic attribute space is preferred in the stated preference survey design; and （c） choice datasets with unbalanced ＂chosen＂ choice frequency distribution is preferred, in order to better capture the elasticity between the ＂perceived utility＂ associated with alternative＇s attributes.

Using naturalistic driving data to identify driving style based on longitudinal driving operation conditions

Purpose–An individual’s driving style significantly affects overall traffic safety.However,driving style is difficult to identify due to temporal and spatial differences and scene heterogeneity of driving behavior data.As such,the study of real-time driving-style identification methods is of great significance for formulating personalized driving strategies,improving traffic safety and reducing fuel consumption.This study aims to establish a driving style recognition framework based on longitudinal driving operation conditions(DOCs)using a machine learning model and natural driving data collected by a vehicle equipped with an advanced driving assistance system(ADAS).Design/methodology/approach–Specifically,a driving style recognition framework based on longitudinal DOCs was established.To train the model,a real-world driving experiment was conducted.First,the driving styles of 44 drivers were preliminarily identified through natural driving data and video data;drivers were categorized through a subjective evaluation as conservative,moderate or aggressive.Then,based on the ADAS driving data,a criterion for extracting longitudinal DOCs was developed.Third,taking the ADAS data from 47 Kms of the two test expressways as the research object,six DOCs were calibrated and the characteristic data sets of the different DOCs were extracted and constructed.Finally,four machine learning classification(MLC)models were used to classify and predict driving style based on the natural driving data.Findings–The results showed that six longitudinal DOCs were calibrated according to the proposed calibration criterion.Cautious drivers undertook the largest proportion of the free cruise condition(FCC),while aggressive drivers primarily undertook the FCC,following steady condition and relative approximation condition.Compared with cautious and moderate drivers,aggressive drivers adopted a smaller time headway(THW)and distance headway(DHW).THW,time-to-collision(TTC)and DHW showed highly significant differences in driving style identification,while longitudinal acceleration(LA)showed no significant difference in driving style identification.Speed and TTC showed no significant difference between moderate and aggressive drivers.In consideration of the cross-validation results and model prediction results,the overall hierarchical prediction performance ranking of the four studied machine learning models under the current sample data set was extreme gradient boosting>multi-layer perceptron>logistic regression>support vector machine.Originality/value–The contribution of this research is to propose a criterion and solution for using longitudinal driving behavior data to label longitudinal DOCs and rapidly identify driving styles based on those DOCs and MLC models.This study provides a reference for real-time online driving style identification in vehicles equipped with onboard data acquisition equipment,such as ADAS.

Hypo-toxicity and prominent passivation characteristics of 316 L stainless steel fabricated by direct metal laser sintering in a simulated inflammation environment

3D-printing is an emerging technology that challenged wrought counterparts by one-step manufacturing for complicated biological devices.However,the material properties and surface features due to manufacturing parameters play an important role on the corrosion behaviour and influence the toxicity of the material as an implant.In this paper,the improvement of pitting potential was observed by electrochemical experiments as the result of grain refinement of DMLS 316 L at 200 W laser power.The ICP results verified the supressed release of toxic cations after the formation of the passive film with enhanced characteristics.However,the pores from DMLS 316 L have the potential to develop into pits when polarised above pitting potential,promoting the risk of using 3D-printed 316 L as implant materials.