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1.
《Advances in Space Research (includes Cospar's Information Bulletin, Space Research Today)》2023,71(7):3060-3075
Mega wildfires are one of the environmental disasters worldwide. This study evaluates the pre-fire species diversity and the indirect effects, including habitat loss for one of the largest wildfires in Manavgat (Antalya-Turkey) in 2021, with a two-step methodology. Here, (1) burnt areas in the Manavgat district (2021) were detected with remote sensing data from Sentinel-2A by delta Normalized Burn Ratio calculation for a selected area in Google Earth Engine, and (2) mammals' habitat vector data of International Union for Conservation of Nature (IUCN) Red List were integrated into Habitat and Biodiversity modelling of Terrset to analyze the alpha, beta, gamma diversity and Range Restriction Index for the wildfire region. In the total 4210 km2 study area, 696 km2 of the area was damaged by different fire severity; also, there were 56 mammal species' habitats here. These species include bats (i.e. Nyctalus leisleri), felids (i.e. Felis chaus), rodents (i.e. Rattus norvegicus) and large mammals (i.e. Ursus arctos). 88 % of these species are in IUCN's Least Concern category. The remaining classes are Near Threatened (3.7 %) and Vulnerable (7.4 %). This study also indicated that the burnt area's species richness does not totally consist of endemic species. Therefore, pre-fire species richness analyses of this study can be a base for further studies about the species' post-fire activity and occupancy.Furthermore, the 2021 mega wildfires show us the necessity of wildfire monitoring and risk studies in the entire Mediterranean ecosystem to evaluate the risks to the Sustainable Development Goals. Therefore, post-fire spatial data, fire migration monitorization, and recording of the species' activities should be performed temporally. In this way, the ability of wildlife's recovering, and the direct and indirect effects of the fire will be examined for ecosystems in the long term. 相似文献
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利用CHAMP卫星数据,对2002-2008年12个不同强度磁暴事件期间的热层大气密度变化特征进行分析,并研究对应磁暴期间大气模式NRLMSISE-00分布特征.结果表明,大磁暴期间日侧大气密度峰值从高纬到低纬的时间延迟为2h,中小磁暴期间的延迟时间为3~4h;春秋季暴时大气密度分布基本呈南北对称分布,而夏冬季大气密度的分布是夏半球大于冬半球,春秋季暴时大气密度大于夏冬季;NRLMSISE-00大气模式得到的热层大气密度很好的体现了半球分布以及季节分布的特征,但模式模拟结果偏小;Dst指数峰值比ap指数峰值更能反应大气密度的变化情况. 相似文献
3.
A new modeling scheme for powered parafoil unmanned aerial vehicle platforms: Theory and experiments
《中国航空学报》2019,32(11):2466-2479
A novel framework is established for accurate modeling of Powered Parafoil Unmanned Aerial Vehicle (PPUAV). The model is developed in the following three steps: obtaining a linear dynamic model, simplifying the model structure, and estimating the model mismatch due to model variance and external disturbance factors. First, a six degree-of-freedom linear model, or the structured model, is obtained through dynamic establishment and linearization. Second, the data correlation analysis is adopted to determine the criterion for proper model complexity and to simplify the structured model. Next, an active model is established, combining the simplified model with the model mismatch estimator. An adapted Kalman filter is utilized for the real-time estimation of states and model mismatch. We finally derive a linear system model while taking into account of model variance and external disturbance. Actual flight tests verify the effectiveness of our active model in different flight scenarios. 相似文献
4.
《中国航空学报》2020,33(2):407-417
Multi-faults detection is a challenge for rolling bearings due to the mode mixture and coupling of multiple fault features, as well as its easy burying in the complex, non-stationary structural vibrations and strong background noises. In this paper, a method based on the flexible analytical wavelet transform (FAWT) possessing fractional scaling and translation factors is proposed to identify multiple faults occurred in different components of rolling bearings. During the route of the proposed method, the proper FAWT bases are constructed via genetic optimization algorithm (GA) based on maximizing the spectral correlated kurtosis (SCK) which is firstly presented and proved to be efficient and effective in indicating interested fault mode. Via using the customized FAWT bases for each interested fault mode, the original vibration measurements are decomposed into fine frequency subbands, and the sensitive subband which enhances the signal-to-noise ratio (SNR) is selected to exhibit the fault signature on its envelope spectrum. The proposed method is tested via simulated signals, and applied to analyze the experimental vibration measurements from the running roller bearings subjected to outrace, inner-race and roller defects. The analysis results validate the effectiveness of the proposed method in identifying multi-faults occurred in different components of rolling bearings. 相似文献
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旋转机构是旋转调制捷联惯导系统的关键部件之一。为了精确模拟旋转机构的动力学特性,研究了支撑旋转轴系的双列球轴承的动力学建模方法,提出了使用Bushing单元来建立同时具有径向移动刚度、轴向移动刚度和径向角刚度的三向刚度轴承动力学模型的方法。利用有限元数值仿真方法计算了三向刚度数值,并利用轴承手册上的经验公式进行了验证。在此基础上,建立了含弹性轴承支撑的旋转调制捷联惯导系统旋转机构的结构动力学有限元模型,分析比较了轴承有无角刚度两种状态下的固有模态。分析结果表明:对于旋转调制捷联惯导系统旋转机构来说,轴承模型角刚度对计算精度的影响较大,角刚度已知的模型更接近真实情况。 相似文献
8.
《中国航空学报》2020,33(2):439-447
Fault diagnosis is vital in manufacturing system. However, the first step of the traditional fault diagnosis method is to process the signal, extract the features and then put the features into a selected classifier for classification. The process of feature extraction depends on the experimenters’ experience, and the classification rate of the shallow diagnostic model does not achieve satisfactory results. In view of these problems, this paper proposes a method of converting raw signals into two-dimensional images. This method can extract the features of the converted two-dimensional images and eliminate the impact of expert’s experience on the feature extraction process. And it follows by proposing an intelligent diagnosis algorithm based on Convolution Neural Network (CNN), which can automatically accomplish the process of the feature extraction and fault diagnosis. The effect of this method is verified by bearing data. The influence of different sample sizes and different load conditions on the diagnostic capability of this method is analyzed. The results show that the proposed method is effective and can meet the timeliness requirements of fault diagnosis. 相似文献
9.
Ti2AlNb intermetallic alloy is a relatively newly developed high-temperature-resistant structural material, which is expected to replace nickel-based super alloys for thermally and mechanically stressed components in aeronautic and automotive engines due to its excellent mechanical properties and high strength retention at elevated temperature. The aim of this work is to present a fast and reliable methodology of inverse identification of constitutive model parameters directly from cutting experiments. FE-machining simulations implemented with a modified Johnson-Cook (TANH) constitutive model are performed to establish the robust link between observables and constitutive parameters. A series of orthogonal cutting experiments with varied cutting parameters is carried out to allow an exact comparison to the 2D FE-simulations. A cooperative particle swarm optimization algorithm is developed and implemented into the Matlab programs to identify the enormous constitutive parameters. Results show that the simulation observables (i.e., cutting forces, chip morphologies, cutting temperature) implemented with the identified optimal material constants have high consistency with those obtained from experiments, which illustrates that the FE-machining models using the identified parameters obtained from the proposed methodology could be predicted in a close agreement to the experiments. Considering the wide range of the applied unknown parameters number, the proposed inverse methodology of identifying constitutive equations shows excellent prospect, and it can be used for other newly developed metal materials. 相似文献
10.
Yeerang Lim Youeyun Jung Hyochoong Bang 《Advances in Space Research (includes Cospar's Information Bulletin, Space Research Today)》2018,61(10):2661-2672
This study presents model predictive formation control based on an eccentricity/inclination vector separation strategy. Alternative collision avoidance can be accomplished by using eccentricity/inclination vectors and adding a simple goal function term for optimization process. Real-time control is also achievable with model predictive controller based on convex formulation. Constraint-tightening approach is address as well improve robustness of the controller, and simulation results are presented to verify performance enhancement for the proposed approach. 相似文献