Fixed-wing aircraft cannot maintain optimal aerodynamic performance at different flight speeds. As a type of morphing aircraft, the shear variable-sweep wing(SVSW) can dramatically improve its aerodynamic performance ...
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Fixed-wing aircraft cannot maintain optimal aerodynamic performance at different flight speeds. As a type of morphing aircraft, the shear variable-sweep wing(SVSW) can dramatically improve its aerodynamic performance by altering its shape to adapt to various flight *** order to achieve smooth continuous shear deformation, SVSW's skin adopts a flexible composite skin design instead of traditional aluminum alloy materials. However, this also brings about the non-linear difficulty in stiffness modeling and calculation. In this research, a new SVSW design and efficient stiffness modeling method are proposed. Based on shear deformation theory, the flexible composite skin is equivalently modeled as diagonally arranged nonlinear springs, simulating the elastic force interaction between the skin and the mechanism. By shear loading tests of flexible composite skin, the accuracy of this flexible composite skin modeling method is verified. The SVSW stiffness model was established, and its accuracy was verified through static loading tests. The effects of root connection, sweep angles, and flexible composite skin on the SVSW stiffness are analyzed. Finally, considering three typical flight conditions of SVSW: low-speed flow(Ma = 0.3,Re = 5.82 × 10^(6)), transonic flow(Ma = 0.9, Re = 3.44 × 10^(6)), and supersonic flow(Ma = 3,Re = 7.51 × 10^(6)), the stiffness characteristics of SVSW under flight conditions were *** calculated results guide the application of SVSW.
Aimed at the demand of contingency return at any time during the near-moon phase in the manned lunar landing missions,a fast calculation method for three-impulse contingency return trajectories is ***,a three-impulse ...
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Aimed at the demand of contingency return at any time during the near-moon phase in the manned lunar landing missions,a fast calculation method for three-impulse contingency return trajectories is ***,a three-impulse contingency return trajectory scheme is presented by combining the Lambert transfer and maneuver at the special ***,a calculation model of three-impulse contingency return trajectories is ***,fast calculation methods are proposed by adopting the high-order Taylor expansion of differential algebra in the twobody trajectory dynamics model and perturbed trajectory dynamics ***,the performance of the proposed methods is verified by numerical *** results indicate that the fast calculation method of two-body trajectory has higher calculation efficiency compared to the semi-analytical calculation method under a certain accuracy *** to its high efficiency,the characteristics of the three-impulse contingency return trajectories under different contingency scenarios are further analyzed *** findings can be used for the design of contingency return trajectories in future manned lunar landing missions.
Herein,the successful preparation of a singleatom catalyst V-N-C using vanadium-doped zeolitic imidazolate framework(ZIF)-8 as a precursor is *** experimental results showed that the V-N-C had a good promoting effect ...
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Herein,the successful preparation of a singleatom catalyst V-N-C using vanadium-doped zeolitic imidazolate framework(ZIF)-8 as a precursor is *** experimental results showed that the V-N-C had a good promoting effect on the hydrogen storage performance of MgH_(2),and the optimal addition amount of V-N-C was 10wt%.The hydrogenation and dehydrogenation apparent activation energies of 10 wt%V-N-C-catalyzed MgH_(2)were reduced by 44.9 and 53.5 kJ·mol^(-1),respectively,compared to those of additive-free MgH_(2).The 10 wt%V-N-C-catalyzed MgH_(2)could reabsorb 5.92 wt%of hydrogen in 50 min at 150℃,with a capacity retention rate of 99.1%after 30 cycles of hydrogen absorption and *** analysis showed that V-N-C was partially transformed into VN and metallic V when it was milled with MgH_(2);the in-situ-formed VN and metallic V played an important role in improving the hydrogen storage performance of MgH_(2).This approach provides a potential solution for obtaining high-performance Mg-based hydrogen storage materials through synergistic interactions between V,N and C.
The flourish of deep learning frameworks and hardware platforms has been demanding an efficient compiler that can shield the diversity in both software and hardware in order to provide application *** the existing dee...
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The flourish of deep learning frameworks and hardware platforms has been demanding an efficient compiler that can shield the diversity in both software and hardware in order to provide application *** the existing deep learning compilers,TVM is well known for its efficiency in code generation and optimization across diverse hardware *** the meanwhile,the Sunway many-core processor renders itself as a competitive candidate for its attractive computational power in both scientific computing and deep learning *** paper combines the trends in these two ***,we propose swTVM that extends the original TVM to support ahead-of-time compilation for architecture requiring cross-compilation such as *** addition,we leverage the architecture features during the compilation such as core group for massive parallelism,DMA for high bandwidth memory transfer and local device memory for data locality,in order to generate efficient codes for deep learning workloads on *** experiment results show that the codes generated by swTVM achieve 1.79x improvement of inference latency on average compared to the state-of-the-art deep learning framework on Sunway,across eight representative *** work is the first attempt from the compiler perspective to bridge the gap of deep learning and Sunway processor particularly with productivity and efficiency in *** believe this work will encourage more people to embrace the power of deep learning and Sunwaymany-coreprocessor.
After the integration of large-scale DistributedGeneration(DG)into the distribution network,the randomness and volatility of its output result in a reduction of spatiotemporal alignment between power generation and de...
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After the integration of large-scale DistributedGeneration(DG)into the distribution network,the randomness and volatility of its output result in a reduction of spatiotemporal alignment between power generation and demand in the distribution network,exacerbating the phenomenon of wind and solar power *** a novel power system model,the fundamental concept of Regional Autonomous Power Grids(RAPGs)is to achieve localized management and energy autonomy,thereby facilitating the effective consumption of ***,this paper proposes a distributed resource planning strategy that enhances the autonomy capabilities of regional power grids by considering multiple evaluation indexes for ***,a regional Energy Storage(ES)configuration strategy is *** strategy can select a suitable reference value for the upper limit of ES configuration based on the regional load andDGoutput to maximize the elimination of source load deviations in the region as the upper limit constraint of ES ***,a control strategy for regional ES is proposed,the charging and discharging reference line of ES is set,and multiple autonomy and economic indexes are used as objective functions to select different proportions of ES to control the distributed resources of the regional power grid and establish evaluation indexes of the internal regional generation and load power ratio,the proportion of power supply matching hours,new energy consumption rate and tie line power imbalance outside the region to evaluate changes in the regional autonomy *** final simulation results showthat in the real regional grid example,the planning method in the planning year in the region of the overall power supply matching hour ratio and new energy consumption rate increased by 3.9%and 4.8%on average,and the power imbalance of the tie line decreased by 7.8%on *** proposed planning approach enables the maximization of regional autonomy while effectively smoothing the fluct
Multi-UAV cooperative path planning is a key problem in the research filed on UAV swarm, which is usually a complex nonlinear NP-hard optimization problem. In this paper, the grey wolf optimization (GWO) algorithm is ...
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To validate the alternative simulation models and select the most credible one when the models have multivariate and correlated outputs, an intelligent ranking evaluation method of simulation models based on Graph Neu...
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To enhance the convergence capability of grey wolf optimizer (GWO), this research investigates an evolved GWO using weighted-leader strategy (WLS), namely WLSGWO. The key issue of WLS is realizing the adaptive adjustm...
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For the study on the multi-UAV cooperative execution of complex tasks, this paper divides multi-UAV cooperative tasks planning into three parts: task allocation, path planning and trajectory tracking. Firstly, the spe...
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With increasing restrictions on ship carbon emis-sions,it has become a trend for ships to use zero-carbon energy such as solar to replace traditional fossil ***,uncer-tainties of solar energy and load affect safe and ...
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With increasing restrictions on ship carbon emis-sions,it has become a trend for ships to use zero-carbon energy such as solar to replace traditional fossil ***,uncer-tainties of solar energy and load affect safe and stable operation of the ship *** order to deal with uncertainties and real-time requirements and promote application of ship zero-carbon energy,we propose a real-time energy management strategy based on data-driven stochastic model predictive ***,we establish a ship photovoltaic and load scenario set consid-ering time-sequential correlation of prediction error through three *** steps include probability prediction,equal probability inverse transformation scenario set generation,and simultaneous backward method scenario set ***,combined with scenario prediction information and rolling op-timization feedback correction,we propose a stochastic model predictive control energy management *** each scenario,the proposed strategy has the lowest expected operational cost of control ***,we train the random forest machine learn-ing regression algorithm to carry out multivariable regression on samples generated by running the stochastic model predictive ***,a low-carbon ship microgrid with photovoltaic is *** results demonstrate the proposed strategy can achieve both real-time application of the strategy,as well as operational cost and carbon emission optimization performance close to stochastic model predictive *** Terms-Data-driven stochastic model predictive control,low-carbon ship microgrid,machine learning,real-time energy management,time-sequential correlation.
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