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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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NASA NTRSDate not supplied

BioSentinel: Mission Summary and Lessons Learned From the First Deep Space Biology CubeSat Mission

Launched on Artemis-1, BioSentinel carries a biology experiment into deep space for the first time in 50 years. A 6U CubeSat form factor was utilized for the spacecraft which included technologies newly developed or adapted for operations beyond Earth orbit. The spacecraft carries onboard budding yeast, Saccharomyces cerevisiae, as an analog to human cells to test the biological response to deep space radiation. This was the maiden deep-space voyage for many of the subsystems, and the first time to evaluate their performance in flight operation. Flying a CubeSat beyond LEO comes with unique challenges with respect to trajectory uncertainty and mission operations planning. The nominal plan was a lunar fly-by, followed by an insertion into Heliocentric orbit. However, some possible scenarios included lunar eclipses that could have severely impacted the power budget during that phase of the mission, while others could have resulted in a “Retrograde” hyperbola at swing-by resulting in the spacecraft traveling inward toward Earth or even towards a collision with the lunar surface. The commissioning phase of the mission was successful and completed a week ahead of schedule. It did not come without its exciting moments and challenges. First contact with the spacecraft uncovered that the vehicle was unexpectedly tumbling after deployment, a situation that needed to be corrected urgently. The mission operations team executed a contingency plan to stabilize the spacecraft, with just moments to spare before the battery ran out of power. The BioSensor payload onboard the spacecraft is a complex instrument that includes microfluidics, fluid systems, sensor control electronics, as well at the living yeast cells. BioSentinel also included a TimePix radiation sensor implemented by JSC’s RadWorks group. Dose and Linear Energy Transfer (LET) data is compared directly to the rate of DSB-and repair events measured by the S. cerevisiae cells. BioSentinel mature nanosatellite technologies included: deep space communications and navigation, autonomous attitude control and momentum management, and micro-propulsion systems, to provide an adaptable nanosatellite platform for deep space uses. This paper discusses the performance of the BioSentinel spacecraft through the mission phase, and includes lessons learned from challenges and anomalies. BioSentinel had many successes and will be a pathfinder for future deep space CubeSats and biology missions.

BioSentinel↗
NASA NTRSDate not supplied

Biosentinel: Mission Summary and Lessons Learned From the First Deep Space Biology CubeSat Mission

Launched on Artemis-1, BioSentinel carries a biology experiment into deep space for the first time in 50 years. A 6U CubeSat form factor was utilized for the spacecraft which included technologies newly developed or adapted for operations beyond Earth orbit. The spacecraft carries onboard budding yeast, Saccharomyces cerevisiae, as an analog to human cells to test the biological response to deep space radiation. This was the maiden deep-space voyage for many of the subsystems, and the first time to evaluate their performance in flight operation. Flying a CubeSat beyond LEO comes with unique challenges with respect to trajectory uncertainty and mission operations planning. The nominal plan was a lunar fly-by, followed by an insertion into Heliocentric orbit. However, some possible scenarios included lunar eclipses that could have severely impacted the power budget during that phase of the mission, while others could have resulted in a “Retrograde” hyperbola at swing-by resulting in the spacecraft traveling inward toward Earth or even towards a collision with the lunar surface. The commissioning phase of the mission was successful and completed a week ahead of schedule. It did not come without its exciting moments and challenges. First contact with the spacecraft uncovered that the vehicle was unexpectedly tumbling after deployment, a situation that needed to be corrected urgently. The mission operations team executed a contingency plan to stabilize the spacecraft, with just moments to spare before the battery ran out of power. The BioSensor payload onboard the spacecraft is a complex instrument that includes microfluidics, fluid systems, sensor control electronics, as well at the living yeast cells. BioSentinel also included a TimePix radiation sensor implemented by JSC’s RadWorks group. Dose and Linear Energy Transfer (LET) data is compared directly to the rate of DSB-and repair events measured by the S. cerevisiae cells. BioSentinel mature nanosatellite technologies included: deep space communications and navigation, autonomous attitude control and momentum management, and micro-propulsion systems, to provide an adaptable nanosatellite platform for deep space uses. This paper discusses the performance of the BioSentinel spacecraft through the mission phase, and includes lessons learned from challenges and anomalies. BioSentinel had many successes and will be a pathfinder for future deep space CubeSats and biology missions.

BioSentinel↗
NASA NTRS2002

Statistical porcess control in Deep Space Network operation

This report describes how the Deep Space Mission System (DSMS) Operations Program Office at the Jet Propulsion Laboratory's (EL) uses Statistical Process Control (SPC) to monitor performance and evaluate initiatives for improving processes on the National Aeronautics and Space Administration's (NASA) Deep Space Network (DSN).

Deep Space Network operations statistical process ↗
NASA NTRS2012

Three-Dimensional Analysis of Deep Space Network Antenna Coverage

There is a need to understand NASA s Deep Space Network (DSN) coverage gaps and any limitations to provide redundant communication coverage for future deep space missions, especially for manned missions to Moon and Mars. The DSN antennas are required to provide continuous communication coverage for deep space flights, interplanetary missions, and deep space scientific observations. The DSN consists of ground antennas located at three sites: Goldstone in USA, Canberra in Australia, and Madrid in Spain. These locations are not separated by the exactly 120 degrees and some DSN antennas are located in the bowl-shaped mountainous terrain to shield against radiofrequency interference resulting in a coverage gap in the southern hemisphere for the current DSN architecture. To analyze the extent of this gap and other coverage limitations, simulations of the DSN architecture were performed. In addition to the physical properties of the DSN assets, the simulation incorporated communication forward link calculations and azimuth/elevation masks that constrain the effects of terrain for each DSN antenna. Analysis of the simulation data was performed to create coverage profiles with the receiver settings at a deep space altitudes ranging from 2 million to 10 million km and a spherical grid resolution of 0.25 degrees with respect to longitude and latitude. With the results of these simulations, two- and three-dimensional representations of the area without communication coverage and area with coverage were developed, showing the size and shape of the communication coverage gap projected in space. Also, the significance of this communication coverage gap is analyzed from the simulation data.

Kegege, Obadiah↗
NASA NTRS2016

Deep Space Network: the Next 50 Years

In 2014, NASA’s Deep Space Network (DSN) celebrated its 50th year of enabling exploration of the Moon, Solar System planets, and beyond. During those 50 years, the DSN has grown along with the associated spacecraft flight systems, providing some 13 orders of magnitude communications systems improvement. It has also contributed to many of the world’s most important scientific discoveries and provided substantial technological spinoffs that have become part of everyday life on Earth. Studies of the next 25 years indicate that deep space missions will need an order of magnitude increased communications performance per decade - and this is likely to continue beyond that time. As exhibited by this meeting, another major change happening right now is the emergence of a standardized international community for tracking deep space missions. The future definitely involves increased international cooperation. This paper explains the near term plans already underway for the DSN. We also consider the plans and possibilities for deep space optical communications. Finally, we will discuss opportunities for international participation in the next 50 years of deep space exploration.

Deutsch, Leslie J.↗
NASA NTRS2016

Deep Space Network: The Next 50 Years

In 2014, NASA’s Deep Space Network (DSN) celebrated its 50th year of enabling exploration of the Moon, Solar System planets, and beyond. During those 50 years, the DSN has grown along with the associated spacecraft flight systems, providing some 13 orders of magnitude communications systems improvement. It has also contributed to many of the world’s most important scientific discoveries and provided substantial technological spinoffs that have become part of everyday life on Earth. Studies of the next 25 years indicate that deep space missions will need an order of magnitude increased communications performance per decade – and this is likely to continue beyond that time. As exhibited by this meeting, another major change happening right now is the emergence of a standardized international community for tracking deep space missions. The future definitely involves increased inter-national cooperation. This paper explains the near term plans already underway for the DSN. We also consider the plans and possibilities for deep space optical communications. Finally, we will discuss opportunities for international participation in the next 50 years of deep space exploration.

Deutsch, Leslie J.↗
NASA NTRSDate not supplied

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge and support human space missions. Through artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in space biosciences and engineered astronaut health systems, to enable Earth-independence and mission operations autonomy. We describe current AI/ML methods to support 1) fundamental biology, 2) in situ analytics, 3) high performance computing, 4) automated science, 5) self-driving labs, 6) remote data management, 7) integrated mission biomonitoring, and 8) a Precision Space Health system. AI/ML approaches that can be integrated to support these domains include active learning, explainable AI, adaptive learning, causal inference, knowledge graphs, federated learning, transfer learning, and large language models. Finally, we present results from several current ML projects that are underway in the space biology field to address key challenges of small sample n, high feature count, heterogeneity, and sparse data. These include 1) connecting omics to phenotypic data using an ensemble model to infer causality of rodent liver health disruption, 2) usage of explainable ML to interrogate muscular underpinnings of muscle atrophy, 3) ML models analyzing and determining directed acyclic graphs of human health risk leveraging rodent bone datasets, 4) usage of large pre-trained models connecting biomedical knowledgebases with small spaceflight datasets to understand gene-to-gene interactions, and 5) a suite of benchmarked open science datasets enabling programmers to identify best algorithms to answer space biology questions.

space biology↗
NASA NTRS1993

Trajectory design for the Deep Space Program Science Experiment (DSPSE) mission

In 1994, the Deep Space Program Science Experiment (DSPSE) spacecraft will become the first spacecraft to perform, in succession, both a lunar orbiting mission and a deep-space asteroid encounter mission. The primary mission objective is to perform a long-duration flight-test of various new-technology lightweight components, such as sensors, in a deep-space environment. The mission has two secondary science objectives: to provide high-resolution imaging of the entire lunar surface for mapping purposes and flyby imaging of the asteroid 1620 Geographos. The DSPSE mission is sponsored by the Strategic Defense Initiative Organization (SDIO). As prime contractor, the Naval Research Laboratory (NRL) is building the spacecraft and will conduct mission operations. The Goddard Space Flight Center's (GSFC) Flight Dynamics Division is supporting NRL in the areas of The Deep Space Network (DSN) will provide tracking support. The DSPSE mission will begin with a launch from the Western Test Range in late January 1994. Following a minimum 1.5-day stay in a low-Earth parking orbit, a solid kick motor burn will boost DSPSE into an 18-day, 2.5-revolution phasing orbit transfer trajectory to the Moon. Two burns to insert DSPSE into a lunar polar orbit suitable for the mapping mission will be followed by mapping orbit maintenance and adjustment operations over a period of 2 sidereal months. In May 1994, a lunar orbit departure maneuver, in conjunction with a lunar swingby 26 days later, will propel DSPSE onto a heliocentric transfer that will intercept Geographos on September 1, 1994. This paper presents the characteristics, deterministic delta-Vs, and design details of each trajectory phase of this unique mission, together with the requirements, constraints, and design considerations to which each phase is subject. Numerous trajectory plots and tables of significant trajectory events are included. Following a discussion of the results of a preliminary launch window analysis, a summary of the deterministic impulsive delta-V budget required to establish the baseline mission trajectory design is presented.

Carrington, D.↗
NASA NTRS1989

Deep space communications, weather effects, and error control

Deep space telemetry is and will remain signal-to-noise limited and vulnerable to interference. A need exists to increase received signal power and decrease noise. This includes going to Ka-band in the mid-1990's to increase directivity. The effects of a wet atmosphere can increase the noise temperature by a factor of 5 or more, even at X-band, but the order of magnitude increase in average data rate obtainable at Ka-band relative to X-band makes the increased uncertainty a good trade. Lowbit error probabilities required by data compression are available both theoretically and practically with coding, at an infinitesimal power penalty rather than the 10 to 15 dB more power required to reduce error probabilities without coding. Advances are coming rapidly in coding, as with the new constraint-length 15 rate 1/4 convolutional code concatenated with the already existing Reed-Solomon code to be demonstrated on Galileo. In addition, high density spacecraft data storage will allow selective retransmissions, even from the edge of the Solar System, to overcome weather effects. In general, deep space communication was able to operate, and will continue to operate, closer to theoretical limits than any other form of communication. These include limits in antenna area and directivity, system noise temperature, coding efficiency, and everything else. The deep space communication links of the mid-90's and beyond will be compatible with new instruments and compression algorithms and represent a sensible investment in an overall end-to-end information system design.

Posner, Edward C.↗
NASA NTRS2012

GMSK Modulation for Deep Space Applications

Due to scarcity of spectrum at 8.42 GHz deep space Xband allocation, many deep space missions are now considering the use of higher order modulation schemes instead of the traditional binary phase shift keying (BPSK). One such scheme is pre-coded Gaussian minimum shift keying (GMSK). GMSK is an excellent candidate for deep space missions. GMSK is a constant envelope, bandwidth efficien modulation whose frame error rate (FER) performance with perfect carrier tracking and proper receiver structure is nearly identical to that of BPSK. There are several issues that need to be addressed with GMSK however. Specificall, we are interested in the combined effects of spectrum limitations and receiver structure on the coded performance of the X-band link using GMSK. The receivers that are typically used for GMSK demodulations are variations on offset quadrature phase shift keying (OQPSK) receivers. In this paper we consider three receivers: the standard DSN OQPSK receiver, DSN OQPSK receiver with filte ed input, and an optimum OQPSK receiver with filte ed input. For the DSN OQPSK receiver we show experimental results with (8920, 1/2), (8920, 1/3) and (8920, 1/6) turbo codes in terms of their error rate performance. We also consider the tracking performance of this receiver as a function of data rate, channel code and the carrier loop signal-to-noise ratio (SNR). For the other two receivers we derive theoretical results that will show that for a given loop bandwidth, a receiver structure, and a channel code, there is a lower data rate limit on the GMSK below which a higher SNR than what is required to achieve the required FER on the link is needed. These limits stem from the minimum loop signal-to-noise ratio requirements on the receivers for achieving lock. As a result of this, for a given channel code and a given FER, there could be a gap between the maximum data rate that BPSK can support without violating the spectrum limits and the minimum data rate that GMSK can support with the required FER depending on the type of GMSK receiver that is used.

Communications↗
NASA NTRS1985

A methodology for the selection of frequencies for deep space telecommunications

For each new deep-space mission it is necessary to select the radio frequencies that will be used for uplink and downlink communication. The frequency selection has the objective of avoiding or minimizing the possibility of radio interference between existing and planned missions. This paper presents a comprehensive procedure for the selection of frequencies for deep-space communications. The procedure includes the possible effects of several existing missions on a new mission. This is shown through an example of frequency selection of a new National Aeronautics and Space Administration (NASA) deep-spce mission using actual mission data.

Mathur, A.↗
NASA NTRS2021

Autonomy for Deep Space Communications and Navigation

In more than 50 years of deep space exploration, the number and complexity of the world’s space missions have continued to increase. This has placed increasing demands on deep space communication and navigation. However, these demands have been met in spite of an essentially level overall budget. One of the reasons for this this has been the continual application of autonomy in various forms. The NASA Deep Space Network’s implementation of “Fol-low the Sun Operations” is a recent example – but certainly not the only one. During this same period, the end-to-end information system has been increasingly automated through the application of packet telemetry and virtual channels. Fully autonomous spacecraft navigation has been demonstrated, and more limited autonomy has been applied to the operational navigation process. This paper will show how autonomy and automation capabilities have been infused into operational deep space mission communication and navigation in both flight and ground systems as appropriate. It will further discuss ongoing work aimed at increasing the level of autonomy in the future, leverag-ing recent research and application of autonomy in everyday life.

Chang, Susan↗
NASA NTRSDate not supplied

Power Optimization of Cryogenic CO2 Deposition Capture in Deep Space

An extremely reliable cabin air revitalization system is needed for human deep space exploration missions. Deep space offers an environmental temperature close to 4 Kelvin. This low environmental temperature enables heat rejection for systems that are thermally power-intensive, i.e. CO2 cold surface deposition (CDep). The CDep system relies on phase change temperatures of air components to deposit CO2 onto a cold surface. The cold surface can be generated utilizing cryocoolers, including Stirling and Reverse Brayton, or deep space environmental temperature. This paper presents a numerical study on a power optimization of cold surface generation via a cryocooler or thermal radiator. An example system for each type is presented. However, a hybrid system would not only reduce power required to remove CO2, but also increase redundancy and reliability of the air revitalization system.

Pranav Jagtap↗
NASA NTRS1987

Deep space optical communications

Preliminary concepts and designs of a deep space optical link for planetary and deep space science are described. As a mission application, attention is given to a spacecraft optical transceiver package (OPTRANSDAC) attached to a Mars rover vehicle. Also considered are a preliminary concept for a 1000-AU mission, and to a tentative long-range plan for NASA's deep space optical communications program.

Sokoloski, Martin M.↗