A survey of Mars mission trajectory characteristics.
Trajectory characteristics of high-thrust Mars missions and effect on other aspects of mission planning
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Trajectory characteristics of high-thrust Mars missions and effect on other aspects of mission planning
Space mission trajectory optimization by iterative minimizing of residual vector, using linear correction
Computer program for parametric analysis and trajectory simulation for axisymmetric planetary entry vehicles
Use of Jupiter gravity turns for tailoring trajectories to Saturn with consideration of launch opportunities
Two-variable asymptotic solution for three-dimensional solar powered low thrust trajectories in vicinity of ecliptic plane
Necessary conditions for optimal lunar trajectories with discontinuous state variables and intermediate point constraints
Ballistic reentry trajectories at hypersonic speed
Combination numerical-analytical approach to ascent trajectory optimization
Mariner IV trajectory analysis and importance of flight-path selection in construction of basic mission profile
Trajectory measurement errors for powered spacecraft using matrix analysis
Combination numerical-analytical approach to ascent trajectory optimization
Optimal payload lifting and nonlifting trajectories of winged boost-launch vehicle
Reentry trajectory optimization by repetitive computations of impulse response functions and state equations solution
A new method is described for design of an Earth-Moon transfer trajectory with substantial savings of propellant over classical methods.
This paper documents the current design reference mission planned for the first two elements of NASA’s Gateway. When launched together, the Power and Pro-pulsion Element and Habitation and Logistics Outpost comprise the Co-Manifested Vehicle (CMV).1The low-thrust transfer between the initial parking orbit and the final insertion into the operational Near Rectilinear Halo Orbit is described. While each specific trajectory depends on launch date, trends are identified in the dynamics and orientation of the CMV as it traverses its spiral orbit. This paper describes the interplay between various assumptions and constraints on the development of the low thrust lunar transfer.
To enable the airspace integration of autonomous operations, such as uncrewed aircraft conducting cargo deliveries, there is a need to forecast the positions of the surrounding traffic with which they may interact. This paper focuses on forecasting Visual Flight Rules traffic, a significant source of uncertainty and risk in the airspace, especially around small regional airports, due to the unplanned and often untracked nature of such flights. A deep generative model is developed, trained on historical traffic data at example towered and non-towered airports, and used to predict flight trajectories. Experimental results are presented comparing the performance of variational autoencoder and classical machine learning forecasting when applied to both the towered and non-towered airports over varying time horizons. The results show the advantages of the variational autoencoder in producing accurate probabilistic forecasts over varying time horizons.
To enable the airspace integration of autonomous operations, such as uncrewed aircraft conducting cargo deliveries, there is a need to forecast the positions of the surrounding traffic with which they may interact. This paper focuses on forecasting Visual Flight Rules traffic, a significant source of uncertainty and risk in the airspace, especially around small regional airports, due to the unplanned and often untracked nature of such flights. A deep generative model is developed, trained on historical traffic data at example towered and non-towered airports, and used to predict flight trajectories. Experimental results are presented comparing the performance of variational autoencoder and classical machine learning forecasting when applied to both the towered and non-towered airports over varying time horizons. The results show the advantages of the variational autoencoder in producing accurate probabilistic forecasts over varying time horizons.
Renewable natural gas (RNG) is a clean alternative to fossil natural gas, which can be used as transportation fuel, among other applications. This study projects the development trajectory of RNG and evaluates its impacts on the future U.S. transportation market using a hybrid computable general equilibrium model. This analysis considers various factors and uncertainties affecting RNG production, such as technology development, market conditions, competition with other advanced biofuels, and national and state policies. In 2050, RNG production will grow to 2.7 billion gallons (10 billion liters), mostly from swine manure, under current policy provisions. This will lead to a reduction in greenhouse gas (GHG) emissions by 58.56 million metric tonne of CO 2e in 2050. Analysis of different technology cases finds RNG from animal manure to be predominant, while RNG from corn stover and cellulosic ethanol are less competitive. Furthermore, a high mandatory target of 1 billion gallons will drive RNG production higher by 8–18 %, while an extended 2 nd -generation biofuel production tax credit will mostly increase cellulosic ethanol production. The model also finds RNG production being affected by uncertainties in market conditions, such as GDP growth, fossil fuel prices, and oil and gas supply.