Orbital Transfer Research Articles

Synthesis and Unexpected Optical Properties of Ionic Phosphorus Heterocycles with P-Regulated Noncovalent Interactions.

Optoelectronic properties of organic chromophores (OCPs) are to a large extent dictated by the chemical structures. Herein, we synthesized a new series of ionic phosphorus(P)-heteropines via the methylation of the P(III) center. Our studies revealed that methylation is highly dependent on the P(III) environments (NPN, NPC, and CPC), in which adjacent nitrogen atoms greatly withdraw electron density of the P(III) center. The observation of noncovalent interactions between solvent molecules and the molecular backbones of the related P-heterocycle in the single crystal structure implied tunable molecular conformations. Different from the red-shifted absorption and emission spectra of ionic P-OCPs induced by either decreased lowest unoccupied molecular orbital (LUMO) or intramolecular charge transfer (ICT) state in previous studies, current ionic P-heterocycles exhibit blue-shifted absorption and emission spectra compared to the nonionic counterparts. Our experimental and theoretical studies suggest that the unexpected photophysical characters are probably due to the counter-anion induced structure twisting via intermolecular noncovalent interactions between NH-indole and O(OTf), and/or strong intermolecular O···F bonding between O(MI) and F(OTf). Our studies also revealed that the P-environments (NPN, NPC, and CPC) conjunctly impact the photophysical properties of the ionic P-heteropines. Overall, the fact that the P-environment-regulated noncovalent interactions induce the rich structure dynamics and photophysics offers us with a new and effective strategy to fine-tune the optical properties of OCPs.

Approximations for Secular Variation Maxima of Classical Orbital Elements under Low Thrust

The reachability assessment of low-thrust spacecraft is of great significance for orbital transfer, because it can give a priori criteria for the challenging low-thrust trajectory design and optimization. This paper proposes an approximation method to obtain the variation maximum of each orbital element. Specifically, two steps organize the contribution of this study. First, combined with functional approximations, a set of analytical expressions for the variation maxima of orbital elements over one orbital revolution are derived. Second, the secular approximations for the variation maxima of the inclination and the right ascension of the ascending node are derived and expressed explicitly. An iterative algorithm is given to obtain the secular variation maxima of the other orbital elements the orbital elements other than the inclination and right ascension of the ascending node. Numerical simulations for approximating the variation maxima and a preliminary application in estimation of the velocity increment are given to demonstrate the efficiency and accuracy of the proposed method. Compared with the indirect method used alone for low-thrust trajectory optimization, the computation burden of the proposed method is reduced by over five orders of magnitude, and the computational accuracy is still high.

A multi-platform active debris removal mission planning method based on DCOP with chain topology

In this work, a distributed multi-platform active debris removal mission planning task is formulated as a distributed constrained optimization problem (DCOP), and a novel Synchronous Incomplete Searching Algorithm under Chain Topology (SISACT) is proposed. We envision a distributive cooperative mission planning scenario where multiple debris removal platforms generate individual mission sub-plans on how to remove a subset of assigned debris subject to constraints on mission duration and orbit transfer cost. The overall goal is to maximize the aggregate reward for debris removal while avoiding conflicts among sub-plans. To resolve the potential conflicts, multiple platforms must communicate each other intensively. The proposed SISACT algorithm can reduce the inter-platform communication burdens by inducing a fully connected constraint graph into a chain graph with domain assignment. SISACT is designed to focus on global collaboration among the platforms for mission plan partitioning while leveraging existing single platform mission planning algorithms to provide details of the sub-plans. Simulation with a realistic active debris removal scenario has been carried out. It is shown that the proposed SISACT algorithm can optimize the overall reward of the mission while satisfying all the constraints. This validates the effectiveness of SISACT. • A new multi-platform ADR mission planning is proposed based on DCOP. • A new DCOP model with fully-connected all-hard constraint graph is presented. • Proposed method can satisfy all constraints without changing solution frequently. • Tests on Iridium33 debris set with 4 platforms verify its efficiency.

Indirect Optimization of Fuel-Optimal Many-Revolution Low-Thrust Transfers With Eclipses

An efficient indirect method is presented to determine fuel-optimal many-revolution low-thrust transfers in the presence of Earth-shadow eclipses. Specifically, the events of shadow entrance and exit are modeled as interior-point constraints. Following the observation that an ill-conditioned state transition matrix may occur when the spacecraft flies over the edge of the shadow, a two-level continuation scheme is introduced to generate many-revolution trajectories. The established computational framework integrates analytic derivatives, switching detection, and continuation with an augmented flowchart, which yields discontinuous bang-bang solutions and their gradients. Transfers from a geostationary transfer orbit to a geostationary orbit are simulated to illustrate the effectiveness and efficiency of the method developed.

Engine startup with a reduced level of cryogenic propellants under microgravity conditions

For missions that involve launching satellites into sun-synchronous orbits, the load-carrying capacity can be improved by regulating the time distribution of different flight phases if a transfer orbit is planned. However, this will shorten the last burn time of the engines. This paper introduces the technologies to ensure a reliable engine restart after coasting when only a reduced level of propellants is left. The influence mechanism of different flight profiles on the carrying capacity is analyzed first. Then a joint simulation method integrating the attitude control and fluid dynamics is proposed that can accurately analyze the sloshing features of the cryogenic propellants and their influences under microgravity conditions. Finally, a guidance method is studied that eliminates the attitude deviations at the shutdown time of the first burn to suppress additional propellant sloshing during the follow-up coasting phase. The high-fidelity simulation system reveals the feasibility of a low level scenario, and with the action of the updated guidance method, the pressure drop can be controlled as needed and the sloshing can be well restrained, matching the existing pressurization ability and requirements for re-ignitions of engines. These technologies are applied in the successful launch of the LM-8/Y2 mission, in which the performance improvement is verified.

A mesh refinement method for low‐thrust orbit transfer problems

AbstractThis paper researches the fuel‐optimal geocentric orbit transfer problem using a low‐thrust, electric propulsion. First, the transfer trajectory is divided into N burn‐coast arcs via introducing (N−1) intermediate orbits between the initial and the target orbits. By restricting the time duration of each burn, the changes in orbital states caused by one time of ignition can be represented by a discrete velocity impulse; therefore, a considerable large N, a great many optimization variables, and a months and revolutions long trajectory will be calculated to solve the optimization problem. By proposing a new transfer coordinate system, the performance index is analytically calculated, and strict constraints derived from the continuous condition between adjacent orbits are removed from the mathematical optimization model. Meanwhile, an improved particle swarm optimization (PSO) method and a mesh refinement method are proposed to address the optimization problem. The mesh refinement algorithm begins with a simple bi‐impulse transfer problem, automatically increases/decreases N, and finally converges to the optimal solution. Numerical simulation shows the efficiency of the method with some classical and representative scenarios.

Orbital Interception Pursuit Strategy for Random Evasion Using Deep Reinforcement Learning

Aiming at the interception problem of noncooperative evader spacecraft adopting random maneuver strategy in one-to-one orbital pursuit–evasion problem, an interception strategy with decision-making training mechanism for the pursuer based on deep reinforcement learning is proposed. Its core purpose is to improve the success rate of interception in the environment with high uncertainty. First of all, a multi-impulse orbit transfer model of pursuer and evader is established, and a modular deep reinforcement learning training method is built. Second, an effective reward mechanism is proposed to train the pursuer to choose the impulse direction and impulse interval of the orbit transfer and to learn the successful interception strategy with the optimal fuel and time. Finally, with the evader taking a random maneuver decision in each episode of training, the trained decision-making strategy is applied to the pursuer, the corresponding interception success rate of which is further analyzed. The results show that the pursuer trained can obtain universal and variable interception strategy. In each round of pursuit–evasion, with random maneuver strategy of the evader, the pursuer can adopt similar optimal decisions to deal with high-dimensional environments and thoroughly random state space, maintaining high interception success rate.

Uncovering the origin of the anomalously high capacity of a 3d anode via in situ magnetometry.

Transition metals can deliver high lithium storage capacity, but the reason behind this remains elusive. Herein, the origin of this anomalous phenomenon is uncovered by in situ magnetometry taking metallic Co as a model system. It is revealed that the lithium storage in metallic Co undergoes a two-stage mechanism involving a spin-polarized electron injection to the 3d orbital of Co and subsequent electron transfer to the surrounding solid electrolyte interphase (SEI) at lower potentials. These effects create space charge zones for fast lithium storage on the electrode interface and boundaries with capacitive behavior. Therefore, the transition metal anode can enhance common intercalation or pseudocapacitive electrodes at high capacity while showing superior stability to existing conversion-type or alloying anodes. These findings pave the way for not only understanding the unusual lithium storage behavior of transition metals but also for engineering high-performance anodes with overall enhancement in capacity and long-term durability.

Simultaneous Observations of the June 23, 2015, Intense Storm at Low Earth Orbit and Geostationary Transfer Orbit

Simultaneous Observations of the June 23, 2015, Intense Storm at Low Earth Orbit and Geostationary Transfer Orbit

SEQUOIA: A sequential algorithm providing feasibility guarantees for constrained optimization*

Real-time optimal control applications rely on quickly solving nonlinear programs (NLPs) with many constraints. It is usually challenging to design a safe controller that guarantees feasibility of the returned points even in the case of early termination. We present a novel algorithm called SEQUOIA that allows users to choose the maximum optimality gap tolerated and implement sub-optimal, feasible decisions faster in time-critical scenarios. Typical constrained optimization methods approach the feasible set from its exterior, hence the point returned in the case of early termination is not guaranteed to be fit for purpose because critical constraints might be violated. Our algorithm guarantees a feasible point is returned after any iteration and an incrementally better point can be easily constructed. Additionally, we developed the theoretical framework behind our algorithm and show some key mathematical properties. The core idea is to store exact upper and lower bounds for the optimal cost and iteratively solve feasibility problems in order to tighten these bounds. To solve the feasibility problems we use a residual-based approach and we can provide an infeasibility detection feature during the first iteration. We illustrate our implementation on a constrained optimization benchmark as well as a maximum radius orbit transfer optimal control problem. Solving this type of dynamic optimization problems is difficult because of the high number of equality constraints generated from the discretization of dynamic and algebraic path constraints. The numerical experiments show that one can reduce the computational time by more than 40% if the allowed optimality gap is increased from 10−15 to 10−10 and the overall solve time can be decreased by up to two orders of magnitude when compared to a quadratic penalty method (QPM).

Paste Propulsion of Space Transportation Vehicles for Orbital Transfer Applications

Paste Propulsion of Space Transportation Vehicles for Orbital Transfer Applications

Overview of Earth-Moon Transfer Trajectory Modeling and Design

The Moon is the only celestial body that human beings have visited. The design of the Earth-Moon transfer orbits is a critical issue in lunar exploration missions. In the 21st century, new lunar missions including the construction of the lunar space station, the permanent lunar base, and the Earth-Moon transportation network have been proposed, requiring low-cost, expansive launch windows and a fixed arrival epoch for any launch date within the launch window. The low-energy and low-thrust transfers are promising strategies to satisfy the demands. This review provides a detailed landscape of Earth-Moon transfer trajectory design processes, from the traditional patched conic to the state-of-the-art low-energy and low-thrust methods. Essential mechanisms of the various utilized dynamic models and the characteristics of the different design methods are discussed in hopes of helping readers grasp the basic overview of the current Earth-Moon transfer orbit design methods and a deep academic background is unnecessary for the context understanding.

Study on geosynchronous satellite launch vehicle propellants and combustion mechanism of each stage

GSLV is a “geosynchronous satellite launch vehicle” which aims at launching space objects into GTO- Geosynchronous transfer orbit. This paper provides a brief idea of the chemistry of propellants used in all three stages and strap-on motors of geosynchronous satellite launch vehicles and their combustion mechanism. It includes all series of GSLVs launched till now and a description of criteria for choosing fuel. This paper also includes a brief description on hydrazine which is a basic part of so many propellant combinations. Furthermore, it includes basic reasons which result in unsuccessful ignition especially at cryogenic. It also emphasizes on reasons for modification in fuels over time and advancement in efficiency obtained due to respective modified fuels, further, giving an overview of future ideas in the development of propellants.

Low-Energy Transfer Design of Heliocentric Formation Using Lunar Swingby on the Example of LISA

Space-based gravitational wave (GW) detection at low frequencies is of great scientific significance and has received extensive attention in recent years. This work designs and optimizes the low-energy transfer of the heliocentric formation of GW detectors, which starts from a geosynchronous transfer orbit and targets an Earth-like orbit. Based on the example of the Laser Interferometer Space Antenna (LISA), the transfer is first designed in two-body dynamical models and then refined in simplified high-fidelity dynamical models that only consider the major orbital perturbations evaluated here. The main contributions of this work are to present an adaptive model continuation technique and to exploit the lunar swingby technique to reduce the problem-solving difficulty and velocity increment of orbital transfer, respectively. The adaptive model continuation technique fully reveals the effect of perturbations and rapidly iterates the solutions to the simplified models. The simulation results show that the lunar swingby does reduce the energy needed to escape the Earth’s sphere of influence. It is found that the gravitation of the Earth–Moon system has a significant contribution to reducing the velocity increment. The solution of low-energy transfer in the simplified models is that the duration is 360.6615 days and the total velocity increment is 0.8468 km/s.

Solution space exploration of low-thrust minimum-time trajectory optimization by combining two homotopies

Solving the low-thrust trajectory optimization problem with indirect methods has two main challenges including initial guessing and global optimum searching. To overcome these difficulties, two homotopies, including the thrust-homotopy and the longitude-homotopy, are combined to investigate the solution space of the low-thrust minimum-time trajectory optimization problem. The thrust-homotopy can be interpreted as a continuation on the maximum thrust magnitude, and the longitude-homotopy is proposed via a continuation on the final cumulative true longitude. Afterwards, the structure of the solution space is revealed by simulating a transfer scenario from the geostationary transfer orbit to the geostationary orbit. A bounded and smooth solution surface, where each point represents a solution with specific thrust and final cumulative true longitude, is formed by intersecting longitude-homotopy paths and thrust-homotopy paths. Based on the solution surface, the thrust-longitude-combined homotopic approach and a new hybrid homotopy are proposed to obtain local solutions by tracking homotopy paths from a solution of an easy problem, avoiding initial guessing. Finally, the longitude-homotopy is applied to search the global minimum-time solution from an obtained local solution.

Assessment of in-house algorithms on re-entry time prediction of uncontrolled space objects

Accurate prediction of re-entry time and location of an uncontrolled re-entering space object is crucial but challenging. This paper presents in-house re-entry prediction algorithms: RSMGA, STKOptim, STKLTOptim, and ABPro. Case studies on re-entry prediction of Starlink-26 (COSPAR ID 2019-029F or NORAD ID 44240) and CZ-5B (COSPAR ID 2021-035B or NORAD ID 48275) during the IADC re-entry test campaigns 2021/1 and 2021/2, respectively are presented. Simultaneous application of these re-entry prediction algorithms facilitates decision-making on automation of switching between these algorithms during various phases (short term or long-term) of the re-entry campaign. The effectiveness and applicability of these algorithms are studied based on percentage error. The study focuses on the overall and time-based performance of the four methods. Six more re-entered objects are selected (three Geosynchronous transfer orbit (GTO) objects and 3 Low-Earth orbit (LEO) objects), and their re-entry time prediction has been carried out using the four methods for different time instances before re-entry. Prediction estimates are compared among the methods for all the time instances in terms of percentage error. Also, the study helps in fixing the suitability of the re-entry time prediction algorithm for objects from GTO and LEO.

Planetary Mapping Using Deep Learning: A Method to Evaluate Feature Identification Confidence Applied to Habitats in Mars-Analog Terrain.

The goals of Mars exploration are evolving beyond describing environmental habitability at global and regional scales to targeting specific locations for biosignature detection, sample return, and eventual human exploration. An increase in the specificity of scientific goals-from follow the water to find the biosignatures-requires parallel developments in strategies that translate terrestrial Mars-analog research into confident identification of rover-explorable targets on Mars. Precisely how to integrate terrestrial, ground-based analyses with orbital data sets and transfer those lessons into rover-relevant search strategies for biosignatures on Mars remains an open challenge. Here, leveraging small Unmanned Aerial System (sUAS) technology and state-of-the-art fully convolutional neural networks for pixel-wise classification, we present an end-to-end methodology that applies Deep Learning to map geomorphologic units and quantify feature identification confidence. We used this method to assess the identification confidence of rover-explorable habitats in the Mars-analog Salar de Pajonales over a range of spatial resolutions and found that spatial resolutions two times better than are available from Mars would be necessary to identify habitats in this study at the 1-σ (85%) confidence level. The approach we present could be used to compare the identifiability of habitats across Mars-analog environments and focus Mars exploration from the scale of regional habitability to the scale of specific habitats. Our methods could also be adapted to map dome- and ridge-like features on the surface of Mars to further understand their origin and astrobiological potential.

Ridesharing Options from Geosynchronous Transfer Orbits to the Sun–Earth Region

Ridesharing options for secondary payloads to be delivered to regions beyond geostationary altitude are increasingly available with propulsive evolved expendable launch vehicle secondary payload adapter rings. The preliminary mission design for secondary payloads must consider the variability of the dropoff orbit orientation: a factor that is a function of the primary mission. In this analysis, assume that the dropoff orbit is an Earth-centered geosynchronous transfer orbit (GTO). Then, propellant-efficient transfers to periodic and quasi-periodic orbits near the Sun–Earth Lagrange point are constructed from a range of GTO orientations. Dynamical structures (such as hyperbolic invariant manifolds) associated with orbits near Sun–Earth Lagrange point are leveraged to identify and summarize various types of transfer opportunities.

Multi-objective low-thrust spacecraft trajectory design using reachability analysis

One of the fundamental problems in spacecraft trajectory design is finding the optimal transfer trajectory that minimizes the propellant consumption and transfer time simultaneously. We formulate this as a multi-objective optimal control (MOC) problem that involves optimizing over the initial or final state, subject to state constraints. Drawing on recent developments in reachability analysis subject to state constraints, we show that the proposed MOC problem can be stated as an optimization problem subject to a constraint that involves the sub-level set of the viscosity solution of a quasi-variational inequality. We then generalize this approach to account for more general optimal control problems in Bolza form. We relate these problems to the Pareto front of the developed multi-objective programs. The proposed approach is demonstrated on two low-thrust orbital transfer problems around a rotating asteroid.

Approximate time-optimal low-thrust rendezvous solutions between circular orbits

Traditional planetocentric low-thrust solutions mainly focus on orbital rephasing or transfer maneuvers, while the rendezvous maneuver is more challenging to obtain and cannot be approximated by existing solutions in some mission scenarios. In this paper, approximate solutions to the time-optimal rendezvous problem between two close circular orbits are presented. First, the optimal control problem is established in terms of the true longitude by using the Sundman transformation, and a set of unified linearized equations of motion is derived to reduce the number of key parameters characterizing this problem. Then, we show that two key parameters can characterize the rendezvous problem, and that the rephasing (or transfer) corresponds to the case when one of the key parameters equals zero. Thus, a set of piecewise functions is developed to approximate the rephasing and transfer solutions. The rendezvous solutions are finally obtained by a traversal method and summarized in a set of contour maps. Numerical simulations demonstrate that the proposed solutions provide good initial guesses for solving the problem with nonlinear dynamics and accurately approximate the performance index for the preliminary mission design.