The problem of white pollution caused by waste agricultural mulch film (WAMF) has a long history and has brought great damage to the soil and ecological environment. The recycled WAMF has no ...processing performance because it is doped with a large amount of cotton straw and soil inorganic particles. In this study, it was reported for the first time that high‐quality and efficient recovery of WAMF was carried out by means of solid‐state shear milling (S3M) technology. After the pretreatment of S3M, the recycled WAMF is transformed into an active composite powder with a particle size of microns, which regains certain processing performance. Then we prepared a composite material similar to WPC (wood‐plastic composite) by using the composite powder. It was found that under the action of strong three‐dimensional shear force, the phase domain size of the composite decreased significantly, and the compatibility of each component improved. The macroscopic performance was that the tensile strength was increased by 65% and the bending strength was increased by 74%, reaching 8.30 and 17 MPa, respectively. The 24‐h water absorption of this composite decreased by 13%. More importantly, the thermal stability was not significantly reduced during the milling process. This process does not require sorting, cleaning, or other operations, which can greatly simplify the process flow and improve recovery efficiency. It provides an effective solution to the problem of white pollution caused by WAMF.
Preparation of WPC/SIP composite by S3M technology and the effect of milling times on the mechanical properties of composites.
•A Dynamic Bayesian Network availability model is developed for ship machinery systems.•The dynamic availability model accounts for ship maintenance.•The proposed model is used to evaluate the ...machinery systems safety of conventional ship.•The machinery systems safety of Maritime Autonomous Surface Ships (MASS) is discussed.•A framework is presented to develop a redundancy and planned maintenance strategy for MASS.
With their complex structure, multiple failure modes and lack of maintenance crew, the safety problem of Maritime Autonomous Surface Ships’ (MASS) machinery systems are becoming an important research topic. The present study presents an availability model for ship machinery systems incorporating a maintenance strategy based on Dynamic Bayesian Networks (DBN). First, the availability of conventional ship machinery systems is evaluated and used as a benchmark based on the configuration and planned maintenance strategy. Secondly, the availability of MASS machinery systems is compared to the benchmark, before the introduction of any changes to the ship’s configuration and planned maintenance strategy. Finally, the availability improvement strategies, including redundant designs and planned maintenance strategies at port, are proposed based on sensitivity analysis and planned maintenance cost minimization. To exemplify the model's application, a case study of a cooling water system is explored. Based on a sensitivity analysis using the model, it is possible to decide which components need to be redundant. Different redundancy designs and corresponding planned maintenance strategies can be adopted to meet the availability demand. It is also shown that redundancy and enhanced detection capabilities reduce much of the planned maintenance cost. This framework can be used in the early design stages to determine whether the MASS machinery systems’ availability is at least equivalent to that of conventional ships, and has certain reference significance for redundant configuration designs and MASS planned maintenance strategy schedule.
•A transparent and generic framework is proposed to design a risk matrix.•Weights of probability and consequence indices represent their importance on given risk level.•Experts judgements are ...quantified using fuzzy Analytic Hierarchy Process.•A risk matrix is designed for Maritime Surface Autonomous Ships.
Risk matrix, a tool for visualizing risk assessment results, is essential to facilitate the risk communication and risk management in risk-based decision-making processes related to new and unexplored socio-technical systems. The use of an appropriate risk matrix is discussed in the literature, but it is overlooked for emerging technologies such as Maritime Autonomous Surface Ships (MASS). In this study, a comprehensive framework for developing a risk matrix based on fuzzy Analytic Hierarchy Process (AHP) is proposed. In this framework, a linear function is defined where the risk index is treated as a response variable, while the probability and consequence indices are explanatory variables, with weights of these two indices representing their importance on given risk level. This significance is assessed by experts and quantified using AHP in interval type 2 fuzzy environment. A continuous risk diagram is then created and converted into a risk matrix that can be improved. To verify the feasibility of the proposed framework, a risk matrix is designed in the context of MASS grounding. The results show that the proposed approach is feasible. Our discussion results can provide new insights for the design of risk matrices and promote the management of MASS navigational risks.
Recently, the safety issue of maritime autonomous surface ships (MASS) has become a hot topic. Preliminary hazard analysis of MASS can assist autonomous ship design and ensure safe and reliable ...operation. However, since MASS technology is still at its early stage, there are not enough data for comprehensive hazard analysis. Hence, this paper attempts to combine conventional ship data and MASS experiments to conduct a preliminary hazard analysis for autonomy level III MASS using the hybrid causal logic (HCL) method. Firstly, the hazardous scenario of autonomy level III MASS is developed using the event sequence diagram (ESD). Furthermore, the fault tree (FT) method is utilized to analyze mechanical events in ESD. The events involving human factors and related to MASS in the ESD are analyzed using Bayesian Belief Network (BBN). Finally, the accident probability of autonomy level III MASS is calculated in practice through historical data and a test ship with both an autonomous and a remote navigation mode in Wuhan and Nanjing, China. Moreover, the key influence factors are found, and the accident-causing event chains are identified, thus providing a reference for MASS design and safety assessment process. This process is applied to the preliminary hazard analysis of the test ship.
Lacking of appropriate learning facilities, the traditional approach to learn high-performance computing (HPC) is commonly theory-oriented without sufficient hands-on programming experiences. To ...improve the hands-on experiences of HPC learners, we design and implement a flexible and adaptive online HPC learning platform in this paper, called EasyHPC. This platform contains various online course modules such as quiz bank, interactive community, and virtual laboratory. In our system, various HPC theoretical and experimental learning activities can be conducted online, such as assigning HPC parallel programming tasks, and creating HPC questions and collecting students' submissions. It is convenient for students to study HPC-related courses in our platform, submit course assignments, exchange ideas, and complete HPC programming tasks. Our preliminary learning trials have shown that our system can effectively improve the hands-on experience of our students by providing an integrated HPC learning and programming environment. Our students are able to achieve various HPC capstone projects in our platform to develop their system capability.
The 2nd Workshop on Maritime Computer Vision (MaCVi) 2024 addresses maritime computer vision for Unmanned Aerial Vehicles (UAV) and Unmanned Surface Vehicles (USV). Three challenges categories are ...considered: (i) UAV-based Maritime Object Tracking with Re-identification, (ii) USV-based Maritime Obstacle Segmentation and Detection, (iii) USV-based Maritime Boat Tracking. The USV-based Maritime Obstacle Segmentation and Detection features three sub-challenges, including a new embedded challenge addressing efficicent inference on real-world embedded devices. This report offers a comprehensive overview of the findings from the challenges. We provide both statistical and qualitative analyses, evaluating trends from over 195 submissions. All datasets, evaluation code, and the leaderboard are available to the public at https://macvi.org/workshop/macvi24.
The 2 nd Workshop on Maritime Computer Vision (MaCVi) 2024 addresses maritime computer vision for Unmanned Aerial Vehicles (UAV) and Unmanned Surface Vehicles (USV). Three challenges categories are ...considered: (i) UAV-based Maritime Object Tracking with Re-ideruification, (ii) USV-based Maritime Obstacle Segmentation and Detection, (iii) USV-based Maritime Boat Tracking. The USV-based Maritime Obstacle Segmentation and Detection features three sub-challenges, including a new embedded challenge addressing efficicent inference on real-world embedded devices. This report offers a comprehensive overview of the findings from the challenges. We provide both statistical and qualitative analyses, evaluating trends from over 195 submissions. All datasets, evaluation code, and the leaderboard are available to the public at https://macvi.org/workshop/macvi24.
