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To improve the wear resistance of CoCrFeNi high-entropy alloys (HEAs) for a wider range of industrial applications, the alloying strategy was applied to CoCrFeNi HEA by doping Mo element in various ratios, and CoCrFeNiMox (x = 0, 0.2, 0.5, and 1.0) HEA deposits were fabricated by cold spray. The microstructure evolution, mechanical properties, and tribological properties of cold-sprayed CoCrFeNiMox HEA deposits were systematically investigated. The results showed that Mo0, Mo0.2, and Mo0.5 deposits have a face-centered-cubic (FCC) single structure, while Mo1.0 deposit was composed of FCC matrix and hard brittle phases. The doping of Mo element into CoCrFeNi HEA deposits significantly increased the hardness due to the enhanced solid solution strengthening and precipitation strengthening. As a result, the anti-wear properties of Mo-doped CoCrFeNi HEA deposits were gradually improved with the increase in Mo ratios. To be specific, the Mo1.0 deposit exhibited the lowest specific wear rate of 5.1 × 10−5 mm3/N·m, which was reduced by 94.9% in comparison to the Mo0 deposit. Overall, the current study proposes a new strategy to manipulate the mechanical properties of cold-sprayed HEA deposits by alloying.

Solid-state cold spray additive manufacturing has the potential to fabricate high-strength bulk high-entropy alloys (HEAs). Through systematic experiments, this study examined the microstructure and mechanical properties of cold spray fabricated bulk HEAs with mixed CoCrFeNi and Ti powders and explored the effects of Ti content in 4 and 7 at% and post-heat treatment at 800 °C/6 h and 1000 °C/6 h. It is found that the bulk HEAs are highly densified and remain nearly defect-free after the post-heat treatment. The addition of Ti serves as an mixing powder effect to further densify the alloys. Moreover, the addition of Ti and post-heat treatment promote the formation of fine precipitates, including Fe2Ti, Co2Ti, CrFe, CoTi2, and Ni3Ti, which contributes to the strengthening of the alloys. Furthermore, post-heat treatment improves the cohesion of the alloys and yields fine and relatively uniform grains by stimulating static recovery and recrystallization. These synergistic effects improve the hardness, elastic modulus, strength, and ductility properties. The average hardness and elastic modulus of the bulk alloys are as high as 377.6 HV and 94.8 GPa, respectively; the best ultimate tensile strength and elongation to failure are 626.7 MPa and 22.1 %, respectively. Synchrotron X-ray diffraction validates the complex precipitates formed and confirms that there is no phase change during tension. The study offers insights into the microstructure and mechanical properties of cold spray additive manufactured HEAs and the effects of mixed powders and post-heat treatment on tuning microstructure and properties.

In an effort to enhance the efficiency and accuracy of deep-sea manganese nodule grasping behavior by a manipulator, a novel approach employing an improved YOLOv5 algorithm is proposed for the extraction of the shortest paths to manganese nodules targeted by the manipulator. The loss function of YOLOv5s has been improved by integrating a dual loss function that combines IoU and NWD, resulting in better accuracy for loss calculations across different target sizes. Additionally, substituting the initial C3 module in the network backbone with a C2f module is intended to improve the flow of gradient information while reducing computational demands. Once the geometric center of the manganese nodules is identified with the improved YOLOv5 algorithm, the next step involves planning the most efficient route for the manipulator to pick up the nodules using an upgraded elite strategy ant colony algorithm. Enhancements to the ACO algorithm consist of implementing an elite strategy and progressively decreasing the number of ants in each round. This method reduces both the number of iterations and the time required for each iteration, while also preventing the occurrence of local optimal solutions. The experimental findings indicate that the improved YOLOv5s detection algorithm boosts detection accuracy by 2.3%. Furthermore, when there are fewer than 30 target planning points, the improved algorithm requires, on average, 24% fewer iterations than the ACO algorithm to determine the shortest path. Additionally, the speed of calculation for each iteration is quicker while still providing the optimal solution.

1060Al/Al–Al2O3 laminated particle-reinforced aluminum matrix composites (LPRAMCs) were successfully prepared using a combination of cold spraying (CS) and accumulative roll bonding (ARB) techniques, exhibiting a synergistic improvement in strength and plasticity. The effects of Al2O3 particle content on the microstructure, tensile properties and fracture morphology of LPRAMCs were studied. The results showed that compared with the 1# composites with higher Al2O3 particle content (20.1 vol%), the 2# composites with lower Al2O3 particle content (8.4 vol%) exhibited delayed necking fracture during the ARB process, with greater elongation (El) but lower ultimate tensile strength (UTS). After 5 passes of ARB, the UTS and El of the 1# and 2# composites were 345 MPa, 16.1%, and 293 MPa, 22.2%, respectively. This suggests that the mechanical properties of the Al–Al2O3 deposited layer have a significant impact on the mechanical properties of LPRAMCs. With an increase in ARB passes, the fracture mode of the LPRAMCs shifted from brittle to ductile fracture, displayed by equiaxed and shear dimples. These findings can provide novel insights and theoretical foundations for optimizing the mechanical properties of Al matrix composites.

Deep-sea manganese nodules are abundant in the ocean, with high exploitation potential and commercial value, and have become mineral resources that coastal countries compete to develop. The pipeline-lifting mining system is the most promising deep-sea mining system at present. A deep-sea mining vehicle is the core equipment of this system. Mining quality and efficiency rely on mining vehicles to a great extent. According to the topographic and geomorphic environmental characteristics of deep-sea manganese nodules at the bottom of the ocean, a new deep-sea mining system based on an autonomous manganese nodule mining vehicle is proposed in this paper. According to the operating environment and functional requirements of the seabed, a new mining method is proposed, and the global traverse path planning research of the autonomous manganese nodule mining vehicle based on this mining method is carried out. The arc round-trip acquisition path planning method is put forward, and the simulation verification shows that the method effectively solves the problems of low efficiency of mining vehicle traversing acquisition and obstacle avoidance.

The development of the additive manufacturing (AM) technology proffers challenging requirements for forming accuracy and efficiency. In this paper, a hybrid additive manufacturing technology combining fusion-based selective laser melting (SLM) and solid-state cold spraying (CS) was proposed in order to enable the fast production of near-net-shape metal parts. The idea is to fabricate a bulk deposit with a rough contour first via the “fast” CS process and then add fine structures and complex features through “slow” SLM. The experimental results show that it is feasible to deposit an SLM part onto a CS part with good interfacial bonding. However, the CS parts must be subject to heat treatment to improve their cohesion strength before being sending for SLM processing. Otherwise, the high tensile residual stress generated during the SLM process will cause fractures and cracks in the CS part. After heat treatment, pure copper deposited by CS undergoes grain growth and recrystallization, resulting in improved cohesive strength and the release of the residual stress in the CS parts. The tensile test on the SLM/CS interfacial region indicates that the bonding strength increased by 38% from 45 ± 7 MPa to 62 ± 1 MPa after the CS part is subject to heat treatment, and the SLM/CS interfacial bonding strength is higher than the CS parts. This study demonstrates that the proposed hybrid AM process is feasible and promising for manufacturing free-standing SLM-CS components.

Two-phase flow (flow of water in both liquid and gas phase, containing a non-condensable gas such as CO2) in the wellbore is one of the most important processes in the production performance and wellbore scaling evaluations of high temperature geothermal wells. This paper first describes the discharge tests in the Yangbajing geothermal field, Tibet. Next, a simple model for governing the two-phase flow in the presence of CO2 in the wellbore is constructed and a robust calculation method is presented. The model is applied to three production wells in the Yangbajing geothermal field. The results show that the velocity difference between the gas and liquid phase should be included in the model. Ignoring this difference (i.e., homogeneous model) would result in a significant deviation between measurements and calculations. A drift flux model (DFM) describes the velocity difference, where the specifics of the particular model can have significant effects on the results for the pressure and temperature profiles in the wellbore. Three commonly used DFMs are compared to estimate their performance. The calculated wellhead pressure and temperature are in the range of 2,3 bar and 125°C–135°C for all three wells at a production rate of about 20 kg/s. The estimated wellhead gas mass fraction is between 3% and 8%. Considering CO2 content, three different scenarios were evaluated, although the effect on the pressure and temperature profiles were limited. However, CO2 content has a much more significant effect on the flash depth, which is an important parameter for the estimation of calcite scaling.

A multiple processing technique that combines cold spraying (CS) and accumulative roll bonding (ARB) was designed to prepare multilayered 1060Al/Al–Al2O3 composites with improved ductility. Microstructural evolution during processing was characterized using scanning electron microscopy (SEM) and electron backscattered diffraction (EBSD). The deposited Al–Al2O3 complex layer was well bonded to the 1060Al matrix, and during ARB processing, the deposited layers were highly squeezed to eliminate voids, Al2O3 particles were split to reduced size and dispersed to a homogeneous distribution within the deposited layers. The tensile test results revealed that the best combination of strength and ductility was achieved in the sample with optimized 3-pass ARB processing, with an increase of ∼41.66% in ultimate tensile strength (153 MPa) and an increase of ∼95.73% in tensile elongation (7.34%) compared to the initial As-Annealed sample. Fracture behavior of the prepared composite was also analyzed. The analysis of microstructural features provided insight into the underlying mechanisms explaining the high strength and great ductility.

Cold spray is a solid-state deposition technology that can achieve deposition of pure metal, alloys, and composites with high efficiency. By taking the advantage of cold spray method, in this work, Ta and Ag were successfully used to fabricate Ta-Ag composite deposits for the first time, despite their significantly different properties. It was found that mechanical bonding was the major deposition mechanism between Ta and Ag. The Ag volume in the mechanically mixed powder influence the deposition between Ag and Ta particles. Deposition of Ta-Ag powder was same as pure Ta powder when Ag volume was low, and the small volume of deposited Ag inhibit the deposition of Ta particles. Higher Ag volume in powder promoted the deposition of Ta particles via mechanical interlocking due to the formation of large Ag agglomerates.

This paper proposes an approach to predicting fatigue crack growth under mixed-mode loading based on improved Gaussian process. In terms of analyzing the theoretical background for fatigue crack growth, a corresponding finite element model is built to generate sufficient simulation data, which is utilized to obtain the key parameters (e.g., stress intensity factor) for the fatigue crack growth process. And then, a Gaussian process model is achieved to meet the condition that the stress intensity factor is a nonlinear continuous change in crack growth, especially for mixed-mode loading. Following, an idea of local sample densification method is implemented to improve Gaussian sample generation process according to the simplified model of the crack growth path. Based on the above investigation, a fatigue crack growth prediction model using the improved Gaussian process is finished, which is subsequently verified through the test data of lower bainite steel (SCM435) material. The results show that the proposed approach has better computational accuracy and efficiency than the traditional finite element method in predicting fatigue crack growth under mixed-mode loading.

Objective To establish a method for determination of 6 kinds of carbamate pesticides and 3 kinds of chloronicotinyl pesticides in Chinese Kushui rose by ultra high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) coupled with QuEChERS. Methods After extracted by acetonitrile, the Chinese Kushui rose was cleaned by QuEChERS. The target compounds were separated by C18 column (2.1 mm×100 mm, 1.7 μm) using 10 mmol/L ammonium acetate solution (0.1% formic acid) with acetonrtrile as mobile phase for gradient elution, and analyzed by MS/MS system with electrospray ionization (ESI+) under muti-reaction monitoring mode and quantified by external standard method. Results All the 9 kinds of pesticides showed good linear relationships in range of 0.01-0.50 μg/mL, and the correlation coefficients were above 0.990, the recoveries at different spiked levels for all target compounds in blank matrices were 76.3%-102%, and the relative standard deviation (RSD) were 1.3%-9.0% (n=6). The limits of detection and quantification of the method were 0.001 6-0.003 2 and 0.005 4-0.010 mg/kg. Conclusion The method was suitable for rapid screening and analysis of 9 pesticide residues in Chinese Kushui rose with the advantage of accuracy, rapidity, simplicity and high sensitivity.

In this study, ethylene glycol diglycidyl ether (EGDE) and melamine (ME) were used to prepare a spherical composite material CMC-LTO-EGDE-ME through the strategy of cross-linking reaction of biodegradable sodium carboxymethyl cellulose (CMC) with Li2TiO3 (LTO) to improve the cycle stability of the adsorption-desorption for lithium recovery. In the geothermal water at 333.15°K, the adsorption capacity of the spherical composite adsorbent for lithium-ion is 12.02 mg/g, and the adsorption equilibrium time is 8 h. There is a good selectivity of Li+ (Kd = 3.7 × 103) and high separation factors between Li+ and Na+, K+, Cs+ and Ca2+ (between 39.17 and 181.97). Studies on adsorption kinetics and adsorption isotherm showed that composite material’s adsorption process was obtained from the pseudosecond-order kinetics and the molecular diffusion model. It was found that the composite material has broad applications in lithium recovery from geothermal water.

In recent years, the acceleration of urbanization processes coupled with more frequent extreme weather including more severe flood events, have led to an increase in the complexity of managing community flood resilience. This research presents an empirical study to explore the factors influencing community flood resilience in six communities located in the Hubei Province of China. The study presents the development of a flood resilience evaluation index system, comprising the use of the decision-making trial and evaluation laboratory (DEMATEL) and interpretative structural modeling method (ISM) methods. The results show that the three most important factors affecting the flood resilience capacity of the community are (i) the investment in disaster prevention, (ii) disaster relief capacity and (iii) flood control and drainage capacity. The differences between the six communities were analyzed across four dimensions to reveal the strengths and weaknesses of the communities across these dimensions and in terms of their overall resilience. By analyzing the causal hierarchical relationship that affects community flood resilience, this study helps to enhance community resilience to flood disasters and reduce disaster risk. These findings are conducive to enhancing the sustainable development of urban communities and are expected to provide scientific guidance for community risk management and strategic decision-making.

Friction stir welding (FSW) is regarded as an important joining process for the next generation of aerospace aluminum alloys. However, the performance of the FSW process often suffers from low precision and a long test cycle. In order to overcome these problems, a machine learning model based on a backpropagation neural network (BPNN) was developed to optimize the FSW of 2195 aluminum alloys. A four-dimensional mapping relationship between welding parameters and mechanical properties of joints was established through the analysis and mining of FSW data. The intelligent optimization of the welding process and the prediction of joint properties were realized. The weld formation characteristics at different welding parameters were analyzed to reveal the metallurgical mechanism behind the mapping relationship of the process-property obtained by the BPNN model. The results showed that the prediction accuracy of the method proposed could reach 92%. The welding parameters optimized by the BPNN model were 1810 rpm, 105 mm/min, and 3 kN for the rotational speed, welding speed, and welding pressure, respectively. Under these conditions, the tensile strength of the joint was found to be 415 MPa, which deviated from the experimental value by 3.71%.

Low ductility of metallic deposits manufactured by cold spraying (CS) impedes potential mechanical performances in industrial applications. Through appropriate annealing treatment, the amount of both, non-bonded interfaces and work hardening promoted dislocations during CS can be significantly reduced. Consequently, the annealed samples exhibit higher strength and fracture strain than the as-deposited ones. Cu was selected as a reliable material for CS. To correlate Cu deposit strength with primary process parameters and material properties, the Cu powder strength was assessed. Crack characterization of Cu deposits was performed by in-situ microscopic observations during tensile testing. The direct observation of crack initiation, growth and final fracture allows revealing failure mechanisms. The in-situ tests allow distinguishing the effects of reduced initial defect sizes due to annealing and improved ductility in the vicinity of initial defects on possible crack growth and part failure. Considering the necessary compromise between strength, uniform elongation, ductility and microhardness, a post-spraying annealing process is desirable for CSed Cu deposits. The identification of macroscopic and micro-mechanical properties attained under respective process parameters and influences of annealing processes therefore allow identifying solutions for improvements of CSed deposits for load-carrying applications, which is a prerequisite for using CS as additive manufacturing technique.

A fully dense carbon nanotubes (CNTs) reinforced AlSi matrix composite with the multiscale nacre-like architecture was designed and successfully realized by flake powder metallurgy followed by cold spraying (CS). The nanolaminated and ultrafine-grained structure initially created in the CNT/AlSi flaky powder was perfectly conserved, due to the typical ‘cold’ feature of CS. As discussed based on finite element analysis and single splat observation, self-alignment behavior of the flaky powders during impact also allowed the formation of the microlaminated structure. Hence, the scalable CS technique opens a new avenue for bioinspired material design and fabrication with complex shape. Keywords: Additive manufacturing, Cold spray, Metal matrix composites, Nanolaminated structure, Carbon nanotubes

Experimental investigation was conducted to explore the formation conditions and provide new insights into the formation mechanisms of the unexplained intermixing phenomenon observed at the substrate-coatings interface of cold sprayed materials. The results indicate that the formation of intermixing interface significantly depends on the extent of plastic deformation at the coating-substrate interface, with severe deformation creating favorable conditions for the intermixing interface. Two factors have been identified to be critical for inducing the severe interfacial plastic deformation: low deposition efficiency and material properties. During low deposition efficiency cold spraying, most of the accelerated particles rebound after impact while inducing accumulative plastic deformation and thus intermixing at the coating-substrate interface. Considering the material properties, the coating materials must have sufficiently high density to attain enough kinetic energy for creating substantial plastic deformation of the first coating layer and the substrate upon their impact. Also, the substrate materials cannot be too hard so that plastic deformation can be induced. Based on the experimental analyses, the hypothesis of the intermixing interface formation mechanism is proposed in this paper.

In nature, fish not only have extraordinary ability of underwater movement but also have high mobility and flexibility. The low energy consumption and high efficiency of fish propulsive method provide a new idea for the research of bionic underwater robot and bionic propulsive technology. In this paper, the swordfish was taken as the research object, and the mechanism of the caudal fin propulsion was preliminarily explored by analyzing the flow field structure generated by the swing of caudal fin. Subsequently, the influence of the phase difference of the heaving and pitching movement, the swing amplitude of caudal fin, and Strouhal number (St number) on the propulsion performance of fish was discussed. The results demonstrated that the fish can obtain a greater propulsion force by optimizing the motion parameters of the caudal fin in a certain range. Lastly, through the mathematical model analysis of the tail of the swordfish, the producing propulsive force principle of the caudal fin and the caudal peduncle was obtained. Hence, the proposed method provided a theoretical basis for the design of a high-efficiency bionic propulsion system.

The low retainability of reinforcing particles in functional composite coatings fabricated by cold spray (CS) is a major problem in maximizing coating properties. In this work, the Ni-coated FeSiAl composite powders were used to fabricate soft magnetic composite (SMC) coatings via CS. The feedstock particles were preheated prior to the entrance of nozzle to improve the retainability of FeSiAl particles and the coating properties. Our results showed that the dense Ni/FeSiAl coatings containing the uniformly-dispersed and crack-free FeSiAl particles were produced. The thermal softening effect of Ni layer, as a result of particle preheating, can effectively increase the volumetric content of FeSiAl particle (from 24.3% to 46.2%) in the composite coating. Particle preheating also conducted to the significant improvement of coating thickness due to enhanced deposition efficiency. Dry-sliding test showed that the tribological performance of SMC coating with particle preheating weakens, owing to lowered microhardness. Enhanced magnetic property was achieved with higher soft ferromagnetic characteristic and decreasing coercivity value at higher particle preheating temperatures. The study on coating formation mechanism highlighted that thermal softening effect can give rise to adiabatic shear instability of Ni layer. This results in the significantly improved retainability of FeSiAl particles and soft magnetic performance. Keywords: Cold spray, Soft magnetic composites, Composite powder, Finite element analysis, Tribological performance

Detection technology of underwater pipeline leakage plays an important role in the subsea production system. In this paper, a new method based on the acoustic leak signal collected by a hydrophone is proposed to detect pipeline leakage in the subsea production system. Through the pipeline leakage test, it is found that the radiation noise is a continuous spectrum of the medium and high-frequency noise. Both the increase in pipe pressure and the diameter of the leak hole will narrow the spectral structure and shift the spectrum center towards the low frequencies. Under the same condition, the pipe pressure has a greater impact on the noise; every 0.05 MPa increase in the pressure, the radiation sound pressure level increases by 6-7 dB. The time-frequency images were obtained by processing the acoustic signals using the Ensemble Empirical Mode Decomposition (EEMD) and Hilbert–Huang transform (HHT), and fed into a two-layer Convolutional Neural Network (CNN) for leakage detection. The results show that CNN can correctly identify the degree of pipeline leakage. Hence, the proposed method provides a new approach for the detection of pipeline leakage in underwater engineering applications.

This work aims to measure the thermodynamics of a main cabin ventilation system in a JU-2000E jack-up offshore platform. A three-dimensional (3D) physical model of the ventilation system was established, and the computational fluid dynamics (CFD) software (ANSYS FLUENT) was used to calculate the model thermodynamics. Numerical analysis was performed to investigate the influence mechanisms of the ventilation factors such as ventilation temperature and volume on the ventilation performance. The analysis results demonstrate that (1) top-setting of the exhaust vents is more effective than the side-setting in terms of high temperature reduction, (2) small ventilation temperature and volume can improve the ventilation efficiency, and (3) proper shutdown selection of the backup diesel engine can enhance the ventilation performance. Furthermore, the effect of humidity for the ventilation air was investigated. Lastly, an experimental platform was developed based on the simulation model. Experimental tests were carried out to evaluate the shutdown selection of the backup engine and have shown consistent results to that of the simulation model. The findings of this study provide valuable guidance in designing the ventilation system in the JU-2000E jack-up offshore platform.

With the development of science and technology, traffic perception, communication, information processing, artificial intelligence and the shipping information system have become important in supporting the realization of intelligent shipping transportation. Against this background, the Internet of Vessels (IoV) is proposed to integrate all these advanced technologies into a platform to meet the requirements of international and regional transportations. The purpose of this paper is to analyze how to benefit from the Internet of Vessels to improve the efficiency and safety of shipping, and promote the development of world transportation. In this paper, the IoV is introduced and its main architectures are outlined. Furthermore, the characteristics of the Internet of Vessels are described. Several important applications that illustrate the interaction of the Internet of Vessels’ components are proposed. Due to the development of the Internet of Vessels still being in its primary stage, challenges and prospects are identified and addressed. Finally, the main conclusions are drawn and future research priorities are provided for reference and as professional suggestions for future researchers in this field.