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Urbanization increases regional impervious surface area, which generally reduces hydrologic response time and therefore increases flood risk. The objective of this work is to investigate the sensitivities of urban flooding to urban land growth through simulation of flood flows under different urbanization conditions and during different flooding stages. A sub-watershed in Toronto, Canada, with urban land conversion was selected as a test site for this study. In order to investigate the effects of urbanization on changes in urban flood risk, land use maps from six different years (1966, 1971, 1976, 1981, 1986, and 2000) and of six simulated land use scenarios (0%, 20%, 40%, 60, 80%, and 100% impervious surface area percentages) were input into coupled hydrologic and hydraulic models. The results show that urbanization creates higher surface runoff and river discharge rates and shortened times to achieve the peak runoff and discharge. Areas influenced by flash flood and floodplain increases due to urbanization are related not only to overall impervious surface area percentage but also to the spatial distribution of impervious surface coverage. With similar average impervious surface area percentage, land use with spatial variation may aggravate flash flood conditions more intensely compared to spatially uniform land use distribution.

Obstacle avoidance path planning is considered an essential requirement for unmanned aerial vehicle (UAV) to reach its designated mission area and perform its tasks. This study established a motion model and obstacle threat model for UAVs, and defined the cost coefficients for evading and crossing threat areas. To solve the problem of obstacle avoidance path planning with full coverage of threats, the cost coefficients were incorporated into the objective optimization function and solved by a combination of Sequential Quadratic Programming and Nonlinear Programming Solver. The problem of path planning under threat full coverage with no solution was resolved by improving the Bézier curve algorithm. By introducing the dynamic threat velocity obstacle model and calculating the relative and absolute collision cones, a path planning algorithm under multiple dynamic threats was proposed to solve the difficulties of dynamic obstacle prediction and avoidance. Simulation results revealed that the proposed Through-out method was more effective in handling full threat coverage and dynamic threats than traditional path planning methods namely, Detour or Cross Gaps. Our study offers valuable insights into autonomous path planning for UAVs that operate under complex threat conditions. This work is anticipated to contribute to the future development of more advanced and intelligent UAV systems.

Urban flooding is a reoccurring disaster, and its frequency and intensity are likely to increase in the future due to the increasing frequency of storm events. Up-to-date monitoring on the distribution of flood hazards in cities is necessary and valuable for urban planning. This research combines two common urban flooding approaches, namely hydraulic and GIS models, in a case study of London, Ontario, Canada. The hydraulic–GIS combined model employs the hydraulic concept in a simplified GIS frame, hence avoiding heavy computation in the hydraulic model and arbitrary coefficients in a GIS model. We used a binary logistic regression model to integrate the hydraulic concept in a GIS model. The multi-criteria GIS model built by binary logistic regression was able to simulate the results from the hydraulic model with good consistency. Such a strategy serves as a promising prototype for addressing similar geographical modelling issues, where the time-consuming physical model can be potentially replaced by a simplified GIS model. Furthermore, the impervious surface percentage is an important input in the hydraulic model. This research experimented different impervious surface percentages as input to the hydraulic model and found that a spatially variable impervious surface percentage achieves better agreement with hydraulic modelling than that of uniform (25% and 42%) impervious surface percentages.

Accurately and rapidly detecting damage to wind turbine blades is critical for ensuring the safe operation of wind turbines. Current deep learning-based detection methods predominantly employ the gathered blade images directly for damage detection. However, due to the slender geometry of wind turbine blades, non-blade background information accounts for a considerable proportion of the captured images with complex background features, affecting the detection of blade damage. To address this challenge, we propose a novel edge cropping method combined with an enhanced YOLOv5s network for detecting damage in wind turbine blades, termed Edge Crop and Enhanced YOLOv5 (EC–EY). The edge cropping method adaptively modifies the cropping stride by the edge features of both sides of the blade, thereby procuring image content that predominantly encompasses the blade region. This procedure effectively mitigates the interference from complex background features and augments the utilization of image pixels. Furthermore, the enhanced YOLOv5 network incorporates the global attention mechanism into the head section of the network and substitutes the original SPPF module with an attention-based intra-scale feature interaction module. The EC–EY aims to improve the detection accuracy for small and variable-shape damages in wind turbine blades. EC–EY achieved excellent performance on a dataset of wind turbine blade damage collected in western Inner Mongolia. Notably, the edge cropping method significantly improves the accuracy of wind turbine blade damage detection.

Caused by the platform movement, slowly moving targets on the ground will be hidden by the stationary clutter in the Doppler domain for an airborne passive radar system. In this paper, the signal model of airborne passive radar used for ground moving target indication purpose is established at first. Then, the space–time adaptive processing technique is adopted to suppress the strong clutter. Because of the poorer range resolution than active radar, independently and identically distributed training range cells are more difficult to obtain for passive radar. To address this problem, the sparsity of clutter in the space–time domain is exploited and a jointly sparse matrix recovery model is introduced. Furthermore, a parameter-searched two-dimensional multiple measurement vectors based orthogonal matching pursuit (MOMP) algorithm is proposed to solve the off-grid (basis mismatch) problem and reduce the computational complexity at the same time, and thus to more accurately and effectively estimate the clutter covariance matrix. Simulation results with digital TV signal as the illuminator source are shown to demonstrate the effectiveness of the proposed algorithm to determine the Doppler frequency, spatial frequency, and relative bistatic range of the moving targets on the ground.

The ability to transport materials under emergency conditions is one of the important capabilities of the country to respond to crises. In order to study the ability of the emergency material transportation system to resist external damage, this paper builds a three-layer interdependent network model based on capacity-load under the analysis of the basic characteristics of the system, and conducts random attacks on the network, studies the relationship between overall robustness and transportation flow of this three-layer network . In addition, the robustness of the three sub-networks is studied, which provides a theoretical basis for constructing a reasonable and robust emergency material transportation system.

As an important new force in information warfare, the UAV swarm has attracted more and more attention from militarists and scholars of various countries. At present, large-scale and low-cost UAV swarms have been gradually applied to reconnaissance operations. The invulnerability and elasticity of its communication network are the key factors that determine whether the swarm can successfully complete the reconnaissance mission. The research object of this study is the UAV swarm communication network, which performs reconnaissance missions. The swarm network is extracted as a three-layer interdependent network model. We apply scale-free network theory and the new connection probability equation to establish three subnetworks. Then, a three-layer interdependent network is constructed by using the interlayer connection rules of the nodes with the largest degree. The classical M-L model is extended to an interdependent network. An interlayer load redistribution rule is proposed to simulate the cascading failure process of swarm networks. Then, we attack network nodes randomly and observe the invulnerability and elasticity of this network. The simulation results show that the performance of the interdependent network is better than that of the single-layer network due to the effect of the interdependent links. By analyzing the experimental results, some feasible suggestions are put forward to improve the invulnerability and elasticity of reconnaissance UAV swarm communication network.

Based on the GLORY reanalysis data, the simulation results of the two versions of MaCOM volume conservation and mass conservation in the Northwest Pacific Ocean for 8 years (1993-2000) are tested. In this paper, the sea surface height, sea surface flow field, sea surface temperature, salinity, vertical profile structures of sea temperature, sea salinity are evaluated respectively. The results show that the average absolute deviation of sea surface temperature is about 0.3 °C, the average absolute deviation of sea surface salinity is about 0.5 psu, the average absolute deviation of sea surface height is about 0.06 m, and the average absolute deviation of see surface current velocity is about 0.08 m/s. Among them, the difference between volume conservation and mass conservation is not large, about from percentile to thousandth percentile. In the vertical direction, the temperature profiles of the two versions are generally consistent, and The maximum deviation from GLORY data is about 0.5°C at depths of 100-400m. In terms of salinity profile, the deviation between the two versions and GLORY mainly exists in the depth range of 200-800 meters, and the deviation is 0.1-0.3 psu. On the whole, MaCOM runs stably and the results are good. It can well reproduce the temperature and salinity characteristics, ocean current field and dynamic environment of the ocean, and is consistent with the internationally recognized high-precision reanalysis data. It is suitable as another powerful tool for studying the ocean.

In order to solve the imminent problem in that the traditional protection strategy cannot meet time requirements, together with the fact that the rotational inertia of a DC microgrid is small and short-circuit fault develops rapidly, a bidirectional short-circuit current blocker (BSCCB) based on solid-state circuit breaker for a DC microgrid is proposed. Firstly, the bidirectional current blocking circuit structure is proposed based on the analysis of key components. Then, a top-level differential protection strategy is developed based on the aforementioned proposal. Finally, the performance of the blocking circuit is simulated and verified by experiments. The results show that the proposed method can block short-circuit current within 4 ms, and the response speed of the protection strategy is very fast compared with previous approaches. BSCCB also has reclosing, bidirectional blocking and energy releasing functions. The current blocker proposed in this paper can be reused multiple times and has a promising future in low-voltage DC microgrid application.

Reasonable air-to-air refueling planning (AARP) is essential for the successful completion of remote flight missions. A comprehensive task model for air refueling planning is proposed, and the key constraints are determined. The multi-objective optimization algorithm NSGA-II is improved from three distinct perspectives. The performance of the improved NSGA-II was evaluated by selecting test functions from the ZDT series for comparison against the original version. Simulation experiments demonstrate that the improved NSGA-II yields an increase in the average hypervolume index by approximately 10% to 18%, a decrease in the average spacing index by about 22% to 57%, and a reduction in the standard deviation of hypervolume by 27% to 76%. The obtained findings demonstrate that the improved NSGA-II variant exhibits superior convergence, uniformity, and universality. The airspace of the Americas was selected as the mission area to generate 50 AARP schemes for application. Five representative schemes with fuel consumption from 47,083 kg to 104,735 kg, corresponding to time consumption coefficient from 1.27 to 1.07, were chosen as alternatives. This research can enhance the efficiency and stability of air-to-air refueling planning, thereby serving as a valuable theoretical reference for selecting appropriate remote multi-point air refueling schemes.