Currently, the primary method for controlling red tides in the ocean involves spraying water solutions with special chemicals as solutes. High-pressure spraying results in the formation of typical jet structures. In this study, numerical simulation methods are employed to investigate the velocity variations, turbulent characteristics, and gas content distribution of jet flow fields under different initial jet flow pressures, cone angles, and nozzle diameters. Based on practical application scenarios, cluster analysis is used to explore the similarities and differences in jet equivalent diameters under different parameter conditions. The research findings indicate the following. (1) The difference of jet velocity distribution at the far field exit will be enlarged with the increase in the nozzle cone angle. When the nozzle cone angle is 4 mm, the velocity uniformity at the outlet is the best. (2) The TKE of the flow field has no consistent change law along the central axis. At the jet exit, the TKE shows an obvious multi-peak structure. (3) The gas content demonstrates a typical “double-valley” feature at the jet outlet cross-section. Increasing the initial pressure leads to a decrease in the gas content within the jet due to reduced entrainment, while the entrainment range remains largely constant. (4) Cluster analysis reveals that the similarity of jet flow width when it reaches the water surface is minimal compared to other operating conditions when the initial pressure is 0.36 MPa, the cone angle is 115°, and the nozzle diameter is 2 mm. All conditions can be categorized into two or three groups to ensure jet effectiveness. The study results provide scientific guidance for selecting spray devices for controlling red tides in the ocean.

Resistance serves as a critical performance metric for ships. Swift and accurate resistance prediction can enhance ship design efficiency. Currently, methods for determining ship resistance encompass model tests, estimation techniques, and computational fluid dynamics (CFDs) simulations. There is a need to improve the prediction speed or accuracy of these methods. Machine learning is gradually emerging as a method applied in the field of ship research. This study aims to investigate ship resistance prediction methods utilizing machine learning across various datasets. This study proposes two methods: employing stacking ensemble learning to enhance resistance prediction accuracy with identical ship samples and utilizing various ship resistance prediction models for accurate resistance prediction through transfer learning. Initially focusing on container ships as the research subject, the stacking ensemble learning model outperforms the basic machine learning model, the Holtrop and Mennen method, and the updated Guldhammer and Harvald method based on comparative prediction results. Subsequently, the container ship resistance prediction model achieves precise resistance prediction for bulk carriers. This study offers dependable guidance for applying machine learning in predicting ship hydrodynamic performance.

The hazard of highly combustible marine oil leakage greatly increases fishing vessel operation risks. This research integrates an experiment to explore the coupling mechanism of a typical heated surface of an engine room as a source to ignite marine oil. A numerical model is established that depicts the dynamic process of and variations in the combined effects regarding multiple factors of oil ignition under actual experiment. The leaked marine oil is ignited with a heated surface, relevant models are applied to reproduce the results, and the influences of specific parameters of a fishing vessel’s engine room are analyzed. The results indicate that the leaked oil boils violently on the heated surface, and a vapor film forms on the oil surface. Increased heated-surface temperatures lead to a significant difference in the initial ignition occurrences of marine oil, and the distance between the ignition height and oil is closely related to the engine room environment. The ignition probability of marine oil shows a gradually increasing trend with elevated heated-surface temperatures. The ignition height presents a downward trend with the increase in the heated-surface temperature, while the engine room’s humidity in air inhibits the upward transfer of heat; however, the degree of inhibition is limited accordingly. The results evidence that this comparative work can be an effective approach to reveal the impacts of marine oil, heat source, ventilation velocity, and humidity on initial ignition characteristics. Additionally, this work provides a basis for setting up emergency planning with appropriate monitoring equipment and further preventing vessel fires due to oil–thermal ignition.

Ship resistance has a very important value in the determination of ship power and the design of emission standards. In this paper, a ship resistance model with different displacement, speed, and attachment under the condition of a fixed scale ratio is tested by means of experimental research, which is used to analyze the change law of ship resistance under the condition of a single factor. The coupling effects of multiple factors on the actual ship power are studied after the establishment of a mathematical relationship between the actual ship power and resistance on the basis of the response surface method. The research results show that: (1) there is an obvious positive correlation between ship resistance and speed, which matches the change law of the exponential equation. Compared with ship appendages, displacement and speed have the greatest influence on resistance. (2) According to the correlation analysis, the maximum correlation coefficient between ship speed/resistance and power is 0.99, and the correlation coefficients between displacement/resistance and power are 0.93 and 0.88, respectively. However, the correlation coefficients between ship appendages and resistance and power are only 0.23 and 0.14, respectively. (3) The actual ship power and speed, displacement, and appendages form a quadratic polynomial relationship. The multi-factor interaction analysis results show that speed and displacement have the greatest influence on the actual ship power. The research results have a certain guiding significance for ship design.

针对传统调制识别算法在低信噪比下识别率不高的情况,提出双路卷积神经网络级联双向长短时记忆(two way convolutional neural network cascaded bidirectional long short term memory,TCNN BiLSTM)网络的调制识别算法.首先,该算法并联不同尺度卷积核的卷积层,提取调制信号不同维度的特征.然后,级联BiLSTM层,对多维特征构建LSTM时间模型.最后,使用softmax分类器完成识别.仿真实验表明,所提算法结构在加性高斯白噪声和特定信道参数的瑞利衰落信道下,性能要优于基于传统特征和其他网络结构的识别算法.在特定信道参数的瑞利衰落信道下信噪比低至6 dB时,该算法对6种数字调制信号的识别率仍可达到92％以上.

Lhasa is a crucial agricultural region of the Tibetan plateau for local grain and vegetable supplies. Therefore, to sustain soil productivity, it is important to understand how agricultural management practices can cause changes in soil properties. Based on the information from the soil survey conducted in the late 1980s, we selected and sampled the following sites in the summer of 2007: 17 sites of the tillage (A) layer soils and 13 sites of soil profiles, including the tillage and subsoil layers from three types of arable land soils in Lhasa (alluvial soil, steppe soil, and meadow soil). At the same time, another 55 composite samples and core samples were taken from the grain-crop land, open vegetable land and greenhouse vegetable land of the alluvial soil. The selected soil properties were measured and compared to the soil survey data from the 1980s. The results showed that because of wind erosion and irrigation, the arable soils in the investigated area have become significantly more sandy (P<0.05) since the late 1980s. Moreover, because of fertiliser application and acid precipitation, the soil pH and cation exchange capacity of the study soils are significantly lower (P<0.05) than in the late 1980s, thus leading to soil acidification and lower soil fertility. Soil organic matter and the total nitrogen contents in the cultivated steppe soils and meadow soils increased, possibly because of manure addition and fertiliser use in the region. The soil organic matter and the total nitrogen content decreased in the alluvial soils, possibly due to an intensified cultivation; however, the available nitrogen and phosphorus increased significantly (P<0.01), whereas potassium decreased significantly (P<0.05). These changes were mainly attributed to the heavy use of nitrogen and phosphorus fertilisers and the infrequent use of potassium fertiliser. The changes in the A layer (tillage layer) were more apparent than in the other layers. This finding was especially evident in the vegetable land, where the changes are attributed to the agricultural management activities that often occur in this layer. The soil organic matter in the B layer increased significantly (P<0.05) due to the accumulation of plant roots and the deposition of organic matter from the A horizon. For the same soil under different land use, the rank of the soil fertility was cropland<open vegetable land<greenhouse vegetable land, which further suggests that the changes in the soil properties were mainly due to the application of manure and the intensity of cultivation.