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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 163 records · Page 9
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NASA NTRS2017

The MSFC Solar Activity Future Estimation (MSAFE) Model

The Natural Environments Branch of the Engineering Directorate at Marshall Space Flight Center (MSFC) provides solar cycle forecasts for NASA space flight programs and the aerospace community. These forecasts provide future statistical estimates of sunspot number, solar radio 10.7 cm flux (F10.7), and the geomagnetic planetary index, Ap, for input to various space environment models. For example, many thermosphere density computer models used in spacecraft operations, orbital lifetime analysis, and the planning of future spacecraft missions require as inputs the F10.7 and Ap. The solar forecast is updated each month by executing MSAFE using historical and the latest month's observed solar indices to provide estimates for the balance of the current solar cycle. The forecasted solar indices represent the 13-month smoothed values consisting of a best estimate value stated as a 50 percentile value along with approximate +/- 2 sigma values stated as 95 and 5 percentile statistical values. This presentation will give an overview of the MSAFE model and the forecast for the current solar cycle.

Suggs, Ron↗
NASA NTRS2017

The MSFC Solar Activity Future Estimation (MSAFE) Model

The Natural Environments Branch of the Engineering Directorate at Marshall Space Flight Center (MSFC) provides solar cycle forecasts for NASA space flight programs and the aerospace community. These forecasts provide future statistical estimates of sunspot number, solar radio 10.7 cm flux (F10.7), and the geomagnetic planetary index, Ap, for input to various space environment models. For example, many thermosphere density computer models used in spacecraft operations, orbital lifetime analysis, and the planning of future spacecraft missions require as inputs the F10.7 and Ap. The solar forecast is updated each month by executing MSAFE using historical and the latest month's observed solar indices to provide estimates for the balance of the current solar cycle. The forecasted solar indices represent the 13-month smoothed values consisting of a best estimate value stated as a 50 percentile value along with approximate +/- 2 sigma values stated as 95 and 5 percentile statistical values. This presentation will give an overview of the MSAFE model and the forecast for the current solar cycle.

Suggs, Ron↗
NASA NTRS2017

The MSFC Solar Activity Future Estimation (MSAFE) Model

The Natural Environments Branch of the Engineering Directorate at Marshall Space Flight Center (MSFC) provides solar cycle forecasts for NASA space flight programs and the aerospace community. These forecasts provide future statistical estimates of sunspot number, solar radio 10.7 cm flux (F10.7), and the geomagnetic planetary index, Ap, for input to various space environment models. For example, many thermosphere density computer models used in spacecraft operations, orbital lifetime analysis, and the planning of future spacecraft missions require as inputs the F10.7 and Ap. The solar forecast is updated each month by executing MSAFE using historical and the latest month's observed solar indices to provide estimates for the balance of the current solar cycle. The forecasted solar indices represent the 13-month smoothed values consisting of a best estimate value stated as a 50 percentile value along with approximate +/- 2 sigma values stated as 95 and 5 percentile statistical values. This presentation will give an overview of the MSAFE model and the forecast for the current solar cycle.

Suggs, Ron↗
NASA NTRS2018

Green Propulsion Advancement and Infusion

All space missions benefit from increased propulsion system performance allowing lower spacecraft launch mass, larger scientific payloads, or extended on-orbit lifetimes. Likewise, propellant candidates that offer significant reduction in personnel hazards and shorter payload processing present a more attractive propulsion subsystem solution. Aiming to reduce risk to potential infusion missions and fully comprehend the alternative propellant performance, the work presented herein represents many years of development and collaborative efforts to successfully align higher performance, low toxicity hydrazine alternatives into NASA Goddard Space Flight Center (GSFC) missions. The High Performance Green Propulsion (HPGP) technology is being considered for Science Mission Directorate (SMD) missions.

Spacecraft Propulsion and Power↗
NASA NTRS2018

A Concept for Civil Space Traffic Management

As technology has improved, operators have sought to use cubesats, as well as smallsats more generally, to perform increasingly more ambitious and sophisticated functions. Despite this, practical concerns associated with cubesat infant mortality, conjunctions, limited maneuverability, and debris generation have been relatively muted because most cubesats have been launched to lower orbits that limit both their orbital lifetime and consequences should a collision occur. NASA ARC has developed a concept for a highly-automated and distributed space traffic management (STM) architecture, drawing on similar work done to provide traffic management for small unmanned aerial systems (UAS) operating at low altitudes. The system proposes a strategy to accommodate growing space traffic volume safely, as well as pave the way for a transition of civil STM authority to a civilian governmental entity. The architecture envisions an open-access software platform architecture of data and service suppliers, consumers, and regulators, connected via a set of application programming interfaces (APIs). The platform would build on, rather than replicate existing integration and coordination efforts within the space situational awareness ecosystem, using existing standards for data message formats from organizations like the Consultative Committee for Space Data Systems and wrapping, rather than replacing existing integrations. We will present an initial STM architecture in this presentation, with a few examples showing how stakeholders can interact structurally, but flexibly, within this architecture.

Space Situational Awareness↗
NASA NTRS2022

Low-Earth Orbit Trajectory Optimization in the Presence of Atmospheric Uncertainty

The previous 20 to 25 years have seen a tremendous increase in space exploration, and with that an increase in the level of logistics planning needed to ensure mission success. For spacecraft that are designed to be periodically re-supplied, a key logistics consumable is propellant, as it constitutes the greatest up-mass on re-supply vehicles. A trajectory design strategy is therefore desired that minimizes propellant usage in order to ease the demand for propellant re-supply missions. This thesis develops such a strategy in three stages, and uses the International Space Station (ISS) as its testbed, as no other LEO spacecraft is more challenging from a space logistics standpoint. First, the ISS trajectory planning problem is formulated as a constrained burn optimization problem assuming a deterministic atmosphere. The cost function is total ∆v, with constraints imposed on longitude of ascending viii node (LAN) and semi-major axis (SMA) altitude. Analytic derivatives are constructed for both the cost and constraints, which are necessary given the 6-week to 2-year time frames being considered. A gradient-based optimizer is then utilized to find locally-optimal solutions to real-world ISS trajectory planning problems. Second, atmospheric uncertainty is addressed by constructing a probabilistic model of space weather data using Gaussian Processes (GPs). Bayesian inference is performed using the GP model to generate mean and covariance estimates for space weather predictions, whose pedigree is assessed against test data. The predictions are then mapped into atmospheric density via the analytic Jacchia-Roberts density model, and the effect of space weather uncertainty on orbital lifetime is examined. Third, an ISS burn execution uncertainty model is developed. This model, along with the space weather uncertainty model, are deployed in a linear covariance analysis to ascertain their combined effect on LAN and SMA altitude dispersions. The deterministic constraints from the original problem are re-formulated as stochastic constraints, where now the constraint uncertainty interval is required to fall within specified bounds. An updated optimization framework is constructed using the original ∆v cost function along with the stochastic constraints to solve the trajectory optimization problem under atmospheric uncertainty. Finally, the complete architecture is summarized for deployment in an operational setting.

Trajectory Optimization↗
NASA NTRSDate not supplied

Revisiting the Effectiveness of Debris Mitigation by Back-Dating Fragmentation Event

Since 1961, more than 250 satellites have fragmented while in orbit about the Earth, from very low Earth orbit out to the geostationary belt. The problem of orbital debris has been recognized since at least the late 1970s, with the institution of the NASA Orbital Debris Program Office (ODPO) in 1979 at the Johnson Space Center. Efforts to mitigate the growth of the orbital debris environment have mainly focused in two areas: the reduction and elimination of accidental explosions of spacecraft and rocket upper stages and the timely removal of spacecraft and rocket upper stages from orbit after completion of their missions. The ODPO continues to analyze the orbital population in orbit based on object type, mass, and other parameters of interest for characterizing the overall growth of objects in Earth’s orbit. Of the 268 known fragmentation events, 46 have occurred more than ten years after the affected satellites’ launch. These long-delayed breakups increase the population of orbital debris on the date of fragmentation, but we can also consider that the debris generated during that event could be attributed to the launch date of that satellite. We will present here an analysis of the historical growth of the low-Earth orbit debris environment, removing intentional fragmentation events, and examine the effectiveness of mitigation measures (such as passivation and reducing post-mission orbital lifetime).

Chris Ostrom↗
NASA NTRS2023

Revisiting the Effectiveness of Debris Mitigation by Back-Dating Fragmentation Events

Since 1961, more than 250 satellites have fragmented while in orbit about the Earth, from very low Earth orbit out to the geostationary belt. The problem of orbital debris has been recognized since at least the late 1970s, with the institution of the NASA Orbital Debris Program Office (ODPO) in 1979 at the Johnson Space Center. Efforts to mitigate the growth of the orbital debris environment have mainly focused in two areas: the reduction and elimination of accidental explosions of spacecraft and rocket upper stages and the timely removal of spacecraft and rocket upper stages from orbit after completion of their missions. The ODPO continues to analyze the orbital population in orbit based on object type, mass, and other parameters of interest for characterizing the overall growth of objects in Earth’s orbit. Of the 268 known fragmentation events, 46 have occurred more than ten years after the affected satellites’ launch. These long-delayed breakups increase the population of orbital debris on the date of fragmentation, but we can also consider that the debris generated during that event could be attributed to the launch date of that satellite. We will present here an analysis of the historical growth of the low-Earth orbit debris environment, removing intentional fragmentation events, and examine the effectiveness of mitigation measures (such as passivation and reducing post-mission orbital lifetime).

Chris Ostrom↗
NASA NTRS1981

Derivation of the collision probability between orbiting objects The lifetimes of Jupiter's outer moons

A general form is derived for Opik's equations relating to the probability of collision between two orbiting objects to their orbital elements, and used to determine the collisional lifetime of the eight outer moons of Jupiter. The derivation is based on a concept of spatial density, or average number of objects found in a unit volume, and results in a set of equations that are easily applied to a variety of orbital collision problems. When applied to the outer satellites, which are all in irregular orbits, the equations predict a relatively long collisional lifetime for the four retrograde moons (about 270 billon years on the average) and a shorter time for the four posigrade moons (0.9 billion years). This short time is suggestive of a past collision history, and may account for the orbiting dust detected by Pioneers 10 and 11.

Kessler, D. J.↗
NASA NTRS1969

Models of Earth's Atmosphere (120 to 1000 Km)

Atmospheric conditions encountered by a spacecraft in orbit about the Earth are important factors in space vehicle design, mission planning, and mission operations. Density is the primary atmospheric property that affects the spacecraft's orbital altitude, lifetime, and motion in the altitude range of 120 to 1000 kilometers. Near the lower limit of this range where density is greatest, a spacecraft will generally remain in orbit for a very short time; near the upper limit, the density effect on orbital lifetime is almost negligible. Density directly affects the torques which result from aerodynamic interaction between the space vehicle and the atmosphere; such torques must be considered in design of spacecraft attitude control systems. Density scale height is required in heating calculations for space vehicles re-entering the Earth's upper atmosphere. Density as well as chemical composition and temperature are needed in calculating a spacecraft's drag coefficient. Chemical composition and temperature also are required in the design of experiment sensors to be flown in this altitude range. Because of variability of atmospheric conditions with spatial location and solar condition, invariant models of the Earth's atmosphere (120 to 1000 kilometers) would not be useful for most engineering applications. Therefore, this monograph presents a computerized version of Jacchia's prediction method to provide models of the Earth's atmosphere which vary with solar condition and location. The resulting atmospheric models, which are predicted for particular times and locations, provide atmospheric density, chemical composition, temperature, molecular mass, and density scale height between 120 and 1000 kilometers altitude. In addition to the computerized method, a quick-look prediction method is given that may be used to obtain an estimate of atmospheric density for any time and spatial location without the use of a computer. A sample problem illustrates this method. Both methods provide models of mean density and models having reasonable upper extremes for density. The analytical approaches in both methods are considered to be the best available, but they could be refined considerably by additional data and study. Information contained in this monograph applies to altitudes between 120 and 1000 kilometers; other design criteria monographs in this series will provide atmospheric information below this altitude region.

Weidner, D. K.↗
NASA NTRS1987

Computing Long-Term Orbital Motions

Drifts and lifetimes predicted. Long-term Orbit Predictor (LOP) is trajectory-propagation computer program used as analysis tool for studies of lifetimes of orbiting spacecraft. Used for any planetary orbiting missions. LOP written in FORTRAN 77.

Kwok, J. H.↗
NASA NTRS2006

On the design of a science orbit about Europa

A science mission about Europa requires high-inclination low-altitude orbits. However, perturbations of Jupiter on the orbiter result in instability. Previous approaches to maximize the lifetime of the orbiter use the doubly averaged problem. We work with the unaveraged equations and find unstable periodic orbits with long lifetimes. These low-altitude repeat ground track solutions exist at all inclinations, making them suitable for mapping missions. The governing dynamics include Hill's model and a Europa gravity field based on synchronous moon theory. Inclusion of additional gravity terms is trivial to the solution method, and for the case of J3, we find a marginal impact on orbit lifetime. The science orbits are found to last on the order of 1 year when the initial conditions are achieved to 11 significant digits and 4 months when only 3 significant digits are achieved. Finally, we demonstrate that the solutions are robust in a realistic ephemeris model, finding average lifetimes of 3 to 4 months for wide range of initial conditions with peak lifetimes of up to 6 months.

unstable↗
NASA NTRS2016

MODIS On-Orbit Thermal Emissive Bands Lifetime Performance

MODerate resolution Imaging Spectroradiometer (MODIS), a leading heritage sensor in the fleet of Earth Observing System for the National Aeronautics and Space Administration (NASA) is in space orbit on two spacecrafts. They are the Terra (T) and Aqua (A) platforms. Both instruments have successfully continued to operate beyond the 6 year design life time, with the T-MODIS currently functional beyond 15 years and the A-MODIS operating beyond 13 years respectively. The MODIS sensor characteristics include a spectral coverage from 0.41 micron 14.4 micron, of which wavelengths ranging from 3.7 micron 14. 4 micron cover the thermal infrared region also referred to as the Thermal Emissive Bands (TEBs). The TEBs is calibrated using a v-grooved BlackBody (BB) whose temperature measurements are traceable to the National Institute of Standards and Technology temperature scales. The TEBs calibration based on the onboard BB is extremely important for its high radiometric fidelity. In this paper, we provide a complete characterization of the lifetime instrument performance of both MODIS instruments in terms of the sensor gain, the Noise Equivalent difference Temperature, key instrument telemetry such as the BB lifetime trends, the instrument temperature trends, the Cold Focal Plane telemetry and finally, the total assessed calibration uncertainty of the TEBs.

Madhavan, Sriharsha↗