Search

Coverage analysis is an essential process when designing a satellite constellation, and the variations of global revisit characteristics are usually elusive in discontinuous coverage problems. In dealing with this, a general method for analyzing the global revisit characteristics of constellations with repeating ground track orbits is proposed in this paper. Firstly, a two-dimensional map based analytical model for the point coverage of constellations is introduced. Then, the variations of revisit characteristics along both the parallel and meridian are analyzed based on the presented analytical model. Finally, numerical examples are carried out. On the one hand, the proposed analytical model for point coverage is demonstrated to be of high precision. On the other hand, all possible positions where the discontinuous changes of revisit characteristics occur can be analytically obtained, which can reveal the discontinuous variations of revisit characteristics along both the parallel and meridian, and can also ensure that all possible global or regional revisit characteristics are counted for a given constellation. The proposed method can contribute to constellation design and coverage performance analysis. • An analytical model for the coverage calculation of satellite constellations is developed. • Conditions for the appearance of the discontinuous changes of global revisit characteristics are deduced analytically. • Variations of the revisit characteristics of satellite constellations along both the parallel and meridian are revealed. [ABSTRACT FROM AUTHOR]

• A design model of hybrid constellations for Earth discontinuous coverage is established. • An analytical method for coverage analysis of hybrid constellations is proposed. • The superiority of hybrid constellations is demonstrated. This paper mainly deals with the configuration design of hybrid constellations for Earth discontinuous coverage. Firstly, a general design model of the hybrid constellation with synchronous orbital precession and multiple repeating ground tracks is developed. Then, to cope with the massive coverage calculation during the constellation design process, an analytical method for rapid coverage analysis of hybrid constellations is proposed. Finally, numerical examples are carried out, and several hybrid constellation design cases are proposed. Results indicate that the proposed coverage analysis method is demonstrated to be of high precision, and the designed hybrid constellations can achieve superior coverage performance compared with conventional Walker constellations. This research can be conducive to hybrid constellations design and Earth discontinuous coverage analysis. [ABSTRACT FROM AUTHOR]

The return multi-flight-phase trajectory optimization of reusable launch vehicle is the key problem of vertical takeoff and vertical landing (VTVL) technologies. In order to solve the problem of ac-curate pinpoint soft landing in the high-dimensional parameter space composed of complex multi-variables and multi-constraints, this paper proposes a strategy of automatic parameter identification and classification and adaptive allocation of optimization algorithms based on clustering analysis. Firstly, state transition matrix of the terminal constraint variables relative to the design variables in the high-dimensional parameter space is obtained, which describes the sensitivity of the terminal constraint variables to the perturbation of the design variables. Then, K-means clustering algorithm is used to classify the sensitivity of the data elements in the state transition matrix, and the linear and nonlinear constraint variables and design variables together with linear state transition matrix are obtained according to the given linearity criterion. Finally, different optimization algorithms are allocated adaptively according to the linear and nonlinear characteristics of different parameter variables. Numerical simulation shows that the proposed algorithm can effectively deal with complex landing constraints, which has well accuracy, convergence and computational efficiency, and reduces the dimension and complexity of parameter space for the return trajectory optimization problem. Besides, the proposed algorithm is suitable for different return missions and has good adaptability and high expansibility. • A new VTVL reusable launch vehicle is studied. • A novel trajectory optimization strategy is presented for return multi-flight-phase. • A new method for parameter characteristics analysis is proposed to reduce dimension. • An adaptive allocation strategy is proposed to enhance adaptability and robustness. • The proposed algorithm has sufficient adaptability to handle VTVL return missions. [ABSTRACT FROM AUTHOR]

Data collection by satellites during and after a natural disaster is of great significance. In this work, a reconfigurable satellite constellation is designed for disaster monitoring, and satellites in the constellation are made to fly directly overhead of the disaster site through orbital transfer. By analyzing the space geometry relations between satellite orbit and an arbitrary disaster site, a mathematical model for orbital transfer and overhead monitoring is established. Due to the unpredictability of disasters, target sites evenly spaced on the Earth are considered as all possible disaster scenarios, and the optimal reconfigurable constellation is designed with the intention to minimize total velocity increment, maximum and mean reconfiguration time, and standard deviation of reconfiguration times for all target sites. To deal with this multiobjective optimization, a physical programming method together with a genetic algorithm is employed. Numerical results are obtained through the optimization, and different observation modes of the reconfigurable constellation are analyzed by a specific case. Superiority of our design is demonstrated by comparing with the existing literature, and excellent observation performance of the reconfigurable constellation is demonstrated. [ABSTRACT FROM AUTHOR]

Despite the common application in pregnancy at clinical practice, it remains ambiguous whether dexamethasone (Dex) exposure can affect embryonic myogenesis. In this study, firstly we showed that 10-6 M Dex (Cheng et al., 2016 ; 2017) treatment resulted in abnormal myogenesis in chicken embryos. Secondly, we demonstrated that 10-6 M Dex-induced abnormality of myogenesis resulted from aberrant cell proliferation, as well as from alteration of the differentiation process from the early stage of somitogenesis up to the late stage of myogenesis. The above-mentioned results caused by Dex exposure might be due to the aberrant gene expressions of somite formation (Raldh2 , Fgf8 , Wnt3a , β-catenin , Slug , Paraxis , N-cadherin) and differentiation (Pax3 , MyoD , Wnt3a , Msx1 , Shh). Thirdly, RNA sequencing implied the statistically significant differential gene expressions in regulating the myofibril and systemic development, as well as a dramatical alteration of retinoic acid (RA) signaling during somite development in the chicken embryos exposed to Dex. The subsequent validation experiments verified that Dex treatment indeed led to a metabolic change of RA signaling, which was up-regulated and principally mediated by FGF-ERK signaling revealed by means of the combination of chicken embryos and in vitro C2C12 cells. These findings highlight that 10-6 M Dex exposure enhances the risk of abnormal myogenesis through interfering with RA signaling during development. [ABSTRACT FROM AUTHOR]

The uncertainties during the return trajectory of vertical takeoff and vertical landing reusable launch vehicle weaken the ability of precision landing and make the return process more challenging. This paper is devoted to quantifying the probability uncertainty of return trajectory with uncertain parameters. The uncertainty model of return multi-flight-phase under the uncertainties of initial flight path angle, axial aerodynamic coefficient, and atmospheric density is established using the generalized polynomial chaos expansion method. By parameterizing random uncertainties and introducing random parameters into the uncertainty model, the uncertainty analysis problem of return trajectory is transformed into stochastic trajectory approximation problem. The coefficients of the polynomial basis function are solved by the stochastic collocation method. Then state solutions, statistical properties, and global sensitivity with Sobol index are established based on coefficients. The simulation results show the efficiency and accuracy of this method compared with the Monte Carlo method, the evolution process of main output parameters under random parameters, and relative importance for random parameters. Through the uncertainty analysis of the return trajectory, the robustness of return trajectory can be quantified, which is contributed to improving the safety, reliability, and robustness of recovery and landing mission. [ABSTRACT FROM AUTHOR]

The epistemic uncertainties caused by insufficient knowledge of the atmosphere, aerodynamic coefficient, and entry state render the entry process challenging, as they not only result in the deviation of the preplanned trajectory, but also may lead to the nonsatisfaction of path constraints. Herein, a robust epistemic uncertainty optimization (REUO) method based on evidence is proposed to solve the Mars entry trajectory optimization problem under epistemic uncertainty. A two-loop nested robust optimization (RO) model is formulated, in which the outer-loop optimization searches the optimal control while the inner-loop optimization calculates the extremal trajectory performances within each focal element (FE) to evaluate the evidence level. To solve the path constraint violation problem under uncertainties, the constraint design based on limitation bounds is considered in the RO model. The polynomial chaos expansion (PCE) is employed to obtain the approximate analytic function of the trajectory performance under uncertainties. Thereafter, the optimization based on ordinary stochastic entry dynamics in the inner loop is replaced by a simple parameter optimization of the analytic functions, which can be readily and rapidly solved. The REUO method is tested in a specific Mars entry mission. The simulation results show that the proposed method can identify the most robust solutions with the optimal trajectory performance under epistemic uncertainties. • Robust trajectory optimization model under epistemic uncertainty is formulated. • A robust epistemic uncertainty optimization method based on evidence is proposed. • Employment of nonintrusive PCE technique improves the optimization efficiency. [ABSTRACT FROM AUTHOR]