During the past decades, with the increasing demands in lightweight structural materials, Mg alloys with low density and high performance have been extensively investigated and partly applied in some ...industries. Especially when rare earth (RE) elements are added as major alloying elements to Mg alloys, the alloy strength and creep resistance are greatly improved, which have promoted several series of Mg-RE alloys. This paper reviews the progress and developments of high-performance Mg-RE alloys in recent years with emphasis on cast alloys. The main contents include the alloy design, melt purification, grain refinement, castability, novel liquid casting and semisolid forming approaches, and the industrial applications or trials made of Mg-RE alloys. The review will provide insights for future developments of new alloys, techniques and applications of Mg alloys.
In the application of WE43, it is found that Y2O3 inclusion formed in the process of casting seriously reduced the mechanical properties of the products. The reduction of the mechanical properties is ...even more distinct when it comes to the application in the thin walled complex-precision castings. In order to decrease the Y2O3 inclusions, Gd element was used to replace part of the Y element in Mg-Y-RE series alloys. The effect of Y content (Mg-xY-1Gd-2Nd-0.5Zn-0.5Zr) and Y/Gd ratio (Mg-xY-(5-x)Gd-2Nd-0.5Zn-0.5Zr) on the microstructure and mechanical properties of Mg–Y–RE alloys were investigated in this paper. With decreasing Y content, the grain size of the alloys increased, both ultimate tensile strength (UTS) and yield strength (YS) of alloys decreased monotonically. Replacing part of Y content with Gd and keeping the total rare earth content unchanged, the low Y content Mg-2Y-3Gd-2Nd-0.5Zn-0.5Zr alloy showed the same mechanical properties as the high Y content Mg-4Y-1Gd-2Nd-0.5Zn-0.5Zr alloy at both room and elevated temperatures. After solution treatment at 525 °C for 8 h and aging treatment at 225 °C for 10 h, the UTS, YS and elongation (ε) of Mg-2Y-3Gd-2Nd-0.5Zn-0.5Zr alloy reached 281.7 MPa, 198 MPa and 11.1% at room temperature, and 216.7 MPa, 171.6 MPa and 16.1% at 250 °C. The new low Y content Mg-2Y-2Nd-3Gd-0.5Zn-0.5Zr alloy is expected to replace the high Y content WE43 alloys, which can be used in the complex thin-walled parts of aviation products.
The unmanned aerial vehicle (UAV) has drawn increasing attention in recent years, especially in executing tasks such as natural disaster rescue and detection, and battlefield cooperative operations. ...Task assignment and path planning for multiple UAVs in the above scenarios are essential for successful mission execution. But, effectively balancing tasks to better excavate the potential of UAVs remains a challenge, as well as efficiently generating feasible solutions from the current one in constrained explosive solution spaces with the increase in the scale of optimization problems. This paper proposes an efficient approach for task assignment and path planning with the objective of balancing the tasks among UAVs and achieving satisfactory temporal resolutions. To be specific, we add virtual nodes according to the number of UAVs to the original model of the vehicle routing problem (VRP), thus make it easier to form a solution suitable for heuristic algorithms. Besides, the concept of the universal distance matrix is proposed to transform the temporal constraints to spatial constraints and simplify the programming model. Then, a Swap-and-Judge Simulated Annealing (SJSA) algorithm is therefore proposed to improve the efficiency of generating feasible neighboring solutions. Extensive experimental and comparative studies on different scenarios demonstrate the efficiency of the proposed algorithm compared with the exact algorithm and meta-heuristic algorithms. The results also inspire us about the characteristics of a population-based algorithm in solving combinatorial discrete optimization problems.
Satellite observation scheduling plays a significant role in improving the efficiency of satellite observation systems. Although extensive scheduling algorithms have been proposed for the satellite ...observation scheduling problem (SOSP), the task clustering strategy has not been taken into account up to now. This paper presents a novel two-phase based scheduling method with the consideration of task clustering for solving SOSP. This method comprises two phases: a task clustering phase and a task scheduling phase. In the task clustering phase, we construct a task clustering graph model and use an improved minimum clique partition algorithm to obtain cluster-tasks. In the task scheduling phase, based on overall tasks and obtained cluster-tasks, we construct an acyclic directed graph model and utilize a hybrid ant colony optimization coming with a mechanism of local search, called ACO–LS, to produce optimal or near optimal schedules. Extensive experimental simulations demonstrate the efficiency of the proposed scheduling method.
Influences of Sn and Y on the microstructure, mechanical properties, and corrosion behavior of as-cast Mg-5Li-3Al-2Zn (LAZ532) alloy were investigated. The addition of Sn and Y refines grains and ...results in the formation of Mg2Sn and Al2Y phases, thus improving the mechanical properties of alloy by second phase strengthening and grain refinement strengthening. As-cast LAZ532 alloy shows typical filiform corrosion morphology, and the addition of Sn and Y does not change the corrosion mode of alloy. As-cast LAZ532−0.8Sn-1.2Y alloy shows excellent mechanical properties with yield strength of 166.2 MPa, ultimate tensile strength of 228.6 MPa and elongation of 14.8 %, and exhibits the best corrosion resistance with the smallest corrosion current density and the lowest anodic dissolution rate.
Unmanned aerial vehicles are becoming promising platforms for disaster relief, such as providing emergency communication services in wireless sensor networks, delivering some living supplies, and ...mapping for disaster recovery. Dynamic task scheduling plays a very critical role in coping with emergent tasks. To solve the multi-UAV dynamic task scheduling, this paper constructs a multi-constraint mathematical model for multi-UAV dynamic task scheduling, involving task demands and platform capabilities. Three objectives are considered, which are to maximize the total profit of scheduled tasks, to minimize the time consumption, and to balance the number of scheduled tasks for multiple UAVs. The multi-objective problem is converted into single-objective optimization via the weighted sum method. Then, a novel dynamic task scheduling method based on a hybrid contract net protocol is proposed, including a buy-sell contract, swap contract, and replacement contract. Finally, extensive simulations are conducted under three scenarios with emergency tasks, pop-up obstacles, and platform failure to verify the superiority of the proposed method.
Unmanned Aerial Vehicles, commonly known as drones, have been widely used in transmission line inspection and traffic patrolling due to their flexibility and environmental adaptability. To take ...advantage of drones and overcome their limited endurance, the patrolling tasks are parallelized by concurrently dispatching the drones from a truck which travels on the road network to the nearby task arc. The road network considered in previous research is undirected; however, in reality, the road network usually contains unidirectional arcs, i.e., the road network is asymmetric. Hence, we propose an asymmetric coordinated vehicle-drones arc routing mode for traffic patrolling. In this mode, a truck travelling on an asymmetric road network with multiple drones needs to patrol multiple task arcs, and the drones can be launched and recovered at certain nodes on the truck route, making it possible for drones and the truck to patrol the task in parallel. The total patrol time is the objective function that needs to be minimized given the time limit constraints of drones. The whole problem can be considered as an asymmetric arc routing problem of coordinating a truck and multiple drones. To solve this problem, a large-scale neighborhood search with simulated annealing algorithm (LNS-SA) is proposed. Finally, extensive computation experiments and a real case are carried out. The experimental results show the efficiency of the proposed algorithm. Moreover, a detailed sensitivity analysis is performed on several drone-parameters of interest.
With the development of drone technology, drones have been deployed in civilian and military fields for target surveillance. As the endurance of drones is limited, large-scale target surveillance ...missions encounter some challenges. Based on this motivation, we proposed a new target surveillance mode via the cooperation of a truck and multiple drones, which enlarges the range of surveillance. This new mode aims to rationally plan the routes of trucks and drones and minimize the total cost. In this mode, the truck, which carries multiple drones, departs from its base, launches small drones along the way, surveils multiple targets, recycles all drones and returns to the base. When a drone is launched from the truck, it surveils multiple targets and flies back to the truck for recycling, and the energy consumption model of the drone is taken into account. To assist the new problem-solving, we developed a new heuristic method, namely, adaptive simulated annealing with large-scale neighborhoods, to optimize truck and drone routes, where a scoring strategy is designed to dynamically adjust the selection weight of destroy operators and repair operators. Additionally, extensive experiments are conducted on several synthetic cases and one real case. The experimental results show that the proposed algorithm can effectively solve the large-scale target surveillance problem. Furthermore, the proposed cooperation of truck and drone mode brings new ideas and solutions to targets surveillance problems.
Through urban traffic patrols, problems such as traffic congestion and accidents can be found and dealt with in time to maintain the stability of the urban traffic system. The most common way to ...patrol is using ground vehicles, which may be inflexible and inefficient. The vehicle-drone coordination maximizes utilizing the flexibility of drones and addresses their limited battery capacity issue. This paper studied a vehicle-drone arc routing problem (VD-ARP), consisting of one vehicle and multiple drones. Considering the coordination mode and constraints of the vehicle-drone system, a mathematical model of VD-ARP that minimized the total patrol time was constructed. To solve this problem, an improved, adaptive, large neighborhood search algorithm (IALNS) was proposed. First, the initial route planning scheme was generated by the heuristic rule of "Drone-First, Vehicle-Then". Then, several problem-based neighborhood search strategies were embedded into the improved, adaptive, large neighborhood search framework to improve the quality of the solution. The superiority of IALNS is verified by numerical experiments on instances with different scales. Several critical factors were tested to determine the effects of coordinated traffic patrol; an example based on a real road network verifies the feasibility and applicability of the algorithm.
Clinic Named Entity Recognition (CNER) aims to recognize named entities such as body part, disease and symptom from Electronic Health Records (EHRs), which can benefit many intelligent biomedical ...systems. In recent years, more and more attention has been paid to the end-to-end CNER with recurrent neural networks (RNNs), especially for long short-term memory networks (LSTMs). However, it remains a great challenge for RNNs to capture long range dependencies. Moreover, Chinese presents additional challenges, since it uses logograms instead of alphabets, the ambiguities of Chinese word and has no word boundaries. In this work, we present a BiLSTM-CRF with self-attention mechanism (Att-BiLSTM-CRF) model for Chinese CNER task, which aims to address these problems. Self-attention mechanism can learn long range dependencies by establishing a direct connection between each character. In order to learn more semantic information about Chinese characters, we propose a novel fine-grained character-level representation method. We also introduce part-of-speech (POS) labeling information about our model to capture the semantic information in input sentence. We conduct the experiment by using CCKS-2017 Shared Task 2 dataset to evaluate performance, and the experimental results indicated that our model outperforms other state-of-the-art methods.
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