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At least 649 records · Page 36

Rescue and Preservation of Sample Data from the Apollo Missions to the Moon

Six Apollo missions landed on the Moon from 1969-72, returning to Earth 382 kg of lunar rock, soil, and core samples. These samples are among the best documented and preserved samples on Earth that have supported a robust research program for 45 years. From mission planning through sample collection, preliminary examination, and subsequent research, strict protocols and procedures are followed for handling and allocating Apollo subsamples, resulting in the production of vast amounts of documentation. Even today, hundreds of samples are allocated for research each year, building on the science foundation laid down by the early Apollo sample studies and combining new data from today's instrumentation, lunar remote sensing missions and lunar meteorites. Much sample information is available to researchers at curator.jsc.nasa.gov. Decades of analyses on lunar samples are published in LPSC proceedings volumes and other peer-reviewed journals, and tabulated in lunar sample compendia entries. However, for much of the 1969-1995 period, the processing documentation, individual and consortia analyses, and unpublished results exist only in analog forms or primitive digital formats that are either inaccessible or at risk of being lost forever because critical data from early investigators remain unpublished.

Todd, Nancy S.↗

The Cassini Solstice Mission: Streamlining Operations by Sequencing with PIEs

The Cassini Solstice Mission (CSM) is the second extended mission phase of the highly successful Cassini/Huygens mission to Saturn. Conducted at a much-reduced funding level, operations for the CSM have been streamlined and simplified significantly. Integration of the science timeline, which involves allocating observation time in a balanced manner to each of the five different science disciplines (with representatives from the twelve different science instruments), has long been a labor-intensive endeavor. Lessons learned from the prime mission (2004-2008) and first extended mission (Equinox mission, 2008-2010) were utilized to design a new process involving PIEs (Pre-Integrated Events) to ensure the highest priority observations for each discipline could be accomplished despite reduced work force and overall simplification of processes. Discipline-level PIE lists were managed by the Science Planning team and graphically mapped to aid timeline deconfliction meetings prior to assigning discrete segments of time to the various disciplines. Periapse segments are generally discipline-focused, with the exception of a handful of PIEs. In addition to all PIEs being documented in a spreadsheet, allocated out-of-discipline PIEs were entered into the Cassini Information Management System (CIMS) well in advance of timeline integration. The disciplines were then free to work the rest of the timeline internally, without the need for frequent interaction, debate, and negotiation with representatives from other disciplines. As a result, the number of integration meetings has been cut back extensively, freeing up workforce. The sequence implementation process was streamlined as well, combining two previous processes (and teams) into one. The new Sequence Implementation Process (SIP) schedules 22 weeks to build each 10-week-long sequence, and only 3 sequence processes overlap. This differs significantly from prime mission during which 5-week-long sequences were built in 24 weeks, with 6 overlapping processes.

Vandermey, Nancy↗

UAS CNPC Satellite Link Performance - Sharing Spectrum with Terrestrial Systems

In order to provide for the safe integration of unmanned aircraft systems into the National Airspace System, the control and non-payload communications (CNPC) link connecting the ground-based pilot with the unmanned aircraft must be highly reliable. A specific requirement is that it must operate using aviation safety radiofrequency spectrum. The 2012 World Radiocommunication Conference (WRC-12) provided a potentially suitable allocation for radio line-of-sight (LOS), terrestrial based CNPC link at 5030-5091 MHz. For a beyond radio line-of-sight (BLOS), satellite-based CNPC link, aviation safety spectrum allocations are currently inadequate. Therefore, the 2015 WRC will consider the use of Fixed Satellite Service (FSS) bands to provide BLOS CNPC under Agenda Item 1.5. This agenda item requires studies to be conducted to allow for the consideration of how unmanned aircraft can employ FSS for BLOS CNPC while maintaining existing systems. Since there are terrestrial Fixed Service systems also using the same frequency bands under consideration in Agenda Item 1.5 one of the studies required considered spectrum sharing between earth stations on-board unmanned aircraft and Fixed Service station receivers. Studies carried out by NASA have concluded that such sharing is possible under parameters previously established by the International Telecommunications Union. As the preparation for WRC-15 has progressed, additional study parameters Agenda Item 1.5 have been proposed, and some studies using these parameters have been added. This paper examines the study results for the original parameters as well as results considering some of the more recently proposed parameters to provide insight into the complicated process of resolving WRC-15 Agenda Item 1.5 and achieving a solution for BLOS CNPC for unmanned aircraft.

Pilotless aircraft↗

Analysis of Terrestrial Interference Protection from UAS CNPC Satellite Transmitters

Unmanned aircraft (UA) are projected to have a major impact on future aviation. Larger UA operating at altitudes above 3000 feet will require at least occasional access to non-segregated, that is, controlled airspace. In order for unmanned aircraft to be integrated into the airspace and operate with other commercial aircraft, a very reliable command and control (a. k. a. control and non-payload communications, (CNPC)) link is required. For operations covering large distances or over remote locations, a beyond-line-of-sight (BLOS) CNPC link implemented through a satellite will almost always be required. Protected aviation spectrum (aeronautical mobile satellite (route) service, or AMS(R)S) would normally be used for such a safety-critical link, however studies have shown that currently available aviation safety satellite spectrum is inadequate to support the projected BLOS CNPC link bandwidth requirements. To address this inadequacy, the 2015 World Radio communication Conference studied the possible use of the Fixed Satellite Service (FSS) to provide CNPC, including possible allocations in Ku-Band and Ka-Band, under Agenda Item (AI) 1.5. Although UA CNPC satellite links in these bands were shown to meet operational availability and continuity requirements, a serious complication exists in that there are also terrestrial service allocations in these bands, in particular, Fixed Service (FS) point-to-point and point-to-multipoint microwave digital links. During the WRC-15 study cycle, much opposition to AI 1.5 was generated based on fears that UA CNPC satellite transmitters in these bands would impose unacceptable levels of interference to the FS receivers. NASA analyzed the possible interference from the UA transmitters based on probable UA transmission and FS receiver characteristics, and UA traffic distributions and densities to determine conditions under which UA could operate without imposing unacceptable interference levels to the FS. Ultimately, UA power flux density transmission limits were proposed as a way to insure protection of FS receivers and further studies were prepared on the various proposals. This paper presents the results of these studies and discusses possible implications on future UA BLOS operations.

aircraft communications↗

Outcomes of the 2015 World Radiocommunication Conference for Aeronautical Spectrum and Applications

At the conclusion of a nearly four year study cycle following the closing of the 2012 World Radiocommunication Conference (WRC-12), the 2015 WRC in November of 2015 considered a number of agenda items and issues relevant to systems and spectrum allocations supporting communications, navigation and surveillance for the operation of civil aviation. Among a number of WRC-15 agenda items and issues, the key agenda items affecting civil aviation included: unmanned aircraft systems use of the Fixed Satellite Service for command and control communications; global flight tracking; new allocations to International Mobile Telecommunications (IMT); and protection of the Fixed Satellite Service to support safe operation of aircraft. A number of other agenda items affecting or potentially affecting civil aviation were also addressed by WRC-15. In this paper we describe the outcomes of WRC-15 for these civil aeronautical-relevant issues. We then outline the civil aviation-related agenda items and issues that will be considered at the upcoming 2019 WRC.

air traffic control↗

Integrating Communication and Navigation: Next Generation Broadcast Service (NGBS)

NASA Goddard has been investing in technology demonstrations of a beacon service, now called Next Generation Broadcast Services (NGBS). NGBS is a global, space-based, communications and navigation service for users of Global Navigation Satellite Systems (GNSS) and the Tracking and Data Relay Satellite System (TDRSS). NGBS will provide an S-band beacon messaging source and radio navigation available to users at orbital altitudes 1400 km and below, increasing the autonomy and resiliency of onboard communication and navigation. NGBS will deliver both one-way radiometric (Doppler and pseudorange) and fast forward data transport services to users. Portions of the overall forward data volume will be allocated for fixed message types while the remaining data volume will be left for user forward command data. The NGBS signal will reside within the 2106.43 MHz spectrum currently allocated for the Space Networks multiple access forward (MAF) service and a live service demonstration is currently being planned via the 2nd and 3rd generation TDRS satellites.

Navigation↗

Micropulsed Plasma Thrusters for Attitude Control of a Low-Earth-Orbiting CubeSat

This study presents a 3-Unit CubeSat design with commercial-off-the-shelf hardware, Teflon-fueled micropulsed plasma thrusters, and an attitude determination and control approach. The micropulsed plasma thruster is sized by the impulse bit and pulse frequency required for continuous compensation of expected maximum disturbance torques at altitudes between 400 and 1000 km, as well as to perform stabilization of up to 20 deg /s and slew maneuvers of up to 180 deg. The study involves realistic power constraints anticipated on the 3-Unit CubeSat. Attitude estimation is implemented using the q method for static attitude determination of the quaternion using pairs of the spacecraft-sun and magnetic-field vectors. The quaternion estimate and the gyroscope measurements are used with an extended Kalman filter to obtain the attitude estimates. Proportional-derivative control algorithms use the static attitude estimates in order to calculate the torque required to compensate for the disturbance torques and to achieve specified stabilization and slewing maneuvers or combinations. The controller includes a thruster-allocation method, which determines the optimal utilization of the available thrusters and introduces redundancy in case of failure. Simulation results are presented for a 3-Unit CubeSat under detumbling, pointing, and pointing and spinning scenarios, as well as comparisons between the thruster-allocation and the paired-firing methods under thruster failure.

Gatsonis, Nikolaos A.↗

Spaceport Command and Control System Software Development

During the course of this internship, software was developed to ensure the efficient management and allocation of an employee to an area of their expertise or experience that may otherwise have gone unnoticed. This directly affects any future missions prescribed to the SLS by allowing management to easily see where employees can be re-allocated to different mission specific projects or assist a project that may be lacking in a specific field. This software is intended to provide proof of NASA's diligence and deliberation in hiring new employees and in providing training and guidance to employees who may have fallen short of expectations. Allowing management to more easily statistically track and monitor the supply and demand of employees with specific experience will help introduce a beneficial culture where employees are given the ability to grow and hone skills which might otherwise atrophy over time. With this new system in place, NASA can prove the employees they hire and already have are exemplary and will remain exemplary to serve the nation as a whole.

Kessluk, Jonathan↗

Expanded Guidance for NASA Systems Engineering. Volume 2: Crosscutting Topics, Special Topics, and Appendices

Historically, most successful NASA projects have depended on effectively blending project management, systems engineering, and technical expertise among NASA, contractors, and third parties. Underlying these successes are a variety of agreements (e.g., contract, memorandum of understanding, grant, cooperative agreement) between NASA organizations or between NASA and other Government agencies, Government organizations, companies, universities, research laboratories, and so on. To simplify the discussions, the term "contract" is used to encompass these agreements. This section focuses on the NASA systems engineering activities pertinent to awarding a contract, managing contract performance, and completing a contract. In particular, NASA systems engineering interfaces to the procurement process are covered, since the NASA engineering technical team plays a key role in the development and evaluation of contract documentation. Contractors and third parties perform activities that supplement (or substitute for) the NASA project technical team accomplishment of the NASA common systems engineering technical process activities and requirements outlined in this guide. Since contractors might be involved in any part of the systems engineering life cycle, the NASA project technical team needs to know how to prepare for, allocate or perform, and implement surveillance of technical activities that are allocated to contractors.

Steven R Hirshorn↗

Human-Automation Cooperation for Separation Assurance in Future NextGen Environments

A 2012 Human-In-The-Loop air traffic control simulation investigated a gradual paradigm-shift in the allocation of functions between operators and automation. Air traffic controllers staffed five adjacent high-altitude en route sectors, and during the course of a two-week experiment, worked traffic under different function-allocation approaches aligned with four increasingly mature NextGen operational environments. These NextGen time-frames ranged from near current-day operations to nearly fully-automated control, in which the ground systems automation was responsible for detecting conflicts, issuing strategic and tactical resolutions, and alerting the controller to exceptional circumstances. Results indicate that overall performance was best in the most automated NextGen environment. Safe operations were achieved in this environment for twice todays peak airspace capacity, while being rated by the controllers as highly acceptable. However, results show that sector operations were not always safe; separation violations did in fact occur. This paper will describe in detail the simulation conducted, as well discuss important results and their implications.

air traffic control↗

The Radio Frequency Environment at 240-270 MHz with Application to Signal-of-Opportunity Remote Sensing

Low frequency observations are desired for soil moisture and biomass remote sensing. Long wavelengths are needed to penetrate vegetation and Earths land surface. In addition to the technical challenges of developing Earth observing spaceflight instruments operating at low frequencies, the radio frequency spectrum allocated to remote sensing is limited. Signal-of-opportunity remote sensing offers the chance to use existing signals exploiting their allocated spectrum to make Earth science measurements. We have made observations of the radio frequency environment around 240-270 MHz and discuss properties of desired and undesired signals.

Soil Moisture↗

Multi-Objective Reinforcement Learning-Based Deep Neural Networks for Cognitive Space Communications

Future communication subsystems of space exploration missions can potentially benefit from software-defined radios (SDRs) controlled by machine learning algorithms. In this paper, we propose a novel hybrid radio resource allocation management control algorithm that integrates multi-objective reinforcement learning and deep artificial neural networks. The objective is to efficiently manage communications system resources by monitoring performance functions with common dependent variables that result in conflicting goals. The uncertainty in the performance of thousands of different possible combinations of radio parameters makes the trade-off between exploration and exploitation in reinforcement learning (RL) much more challenging for future critical space-based missions. Thus, the system should spend as little time as possible on exploring actions, and whenever it explores an action, it should perform at acceptable levels most of the time. The proposed approach enables on-line learning by interactions with the environment and restricts poor resource allocation performance through virtual environment exploration. Improvements in the multiobjective performance can be achieved via transmitter parameter adaptation on a packet-basis, with poorly predicted performance promptly resulting in rejected decisions. Simulations presented in this work considered the DVB-S2 standard adaptive transmitter parameters and additional ones expected to be present in future adaptive radio systems. Performance results are provided by analysis of the proposed hybrid algorithm when operating across a satellite communication channel from Earth to GEO orbit during clear sky conditions. The proposed approach constitutes part of the core cognitive engine proof-of-concept to be delivered to the NASA Glenn Research Center SCaN Testbed located onboard the International Space Station.

space archtiecture↗

Implementation of a Space Communications Cognitive Engine

Although communications-based cognitive engines have been proposed, very few have been implemented in a full system, especially in a space communications system. In this paper, we detail the implementation of a multi-objective reinforcement-learning algorithm and deep artificial neural networks for the use as a radio-resource-allocation controller. The modular software architecture presented encourages re-use and easy modification for trying different algorithms. Various trade studies involved with the system implementation and integration are discussed. These include the choice of software libraries that provide platform flexibility and promote reusability, choices regarding the deployment of this cognitive engine within a system architecture using the DVB-S2 standard and commercial hardware, and constraints placed on the cognitive engine caused by real-world radio constraints. The implemented radio-resource allocation-management controller was then integrated with the larger spaceground system developed by NASA Glenn Research Center (GRC).

reinforcement learning↗

Internal Acoustics of the ISS and Other Spacecraft

It is important to control the acoustic environment inside spacecraft and space habitats to protect for astronaut communications, alarm audibility, and habitability, and to reduce astronauts' risk for sleep disturbance, and hear-ing loss. But this is not an easy task, given the various design trade-offs, and it has been difficult, historically, to achieve. Over time it has been found that successful control of spacecraft acoustic levels is achieved by levying firm requirements at the system-level, using a systems engineering approach for design and development, and then validating these requirements with acoustic testing. In the systems engineering method, the system-level requirements must be flowed down to sub-systems and component noise sources, using acoustic analysis and acoustic modelling to develop allocated requirements for the sub-systems and components. Noise controls must also be developed, tested, and implemented so the sub-systems and components can achieve their allocated limits. It is also important to have management support for acoustics efforts to maintain their priority against the various trade-offs, including mass, volume, power, cost, and schedule. In this extended abstract and companion presentation, the requirements, approach, and results for controlling acoustic levels in most US spacecraft since Apollo will be briefly discussed. The approach for controlling acoustic levels in the future US space vehicle, Orion Multipurpose Crew Vehicle (MPCV), will also be briefly discussed. These discussions will be limited to the control of continuous noise inside the space vehicles. Other types of noise, such as launch, landing, and abort noise, intermittent noise, Extra-Vehicular Activity (EVA) noise, emergency operations/off-nominal noise, noise exposure, and impulse noise are important, but will not be discussed because of time limitations.

Allen, Christopher S.↗

Multi-Objective Reinforcement Learning-based Deep Neural Networks for Cognitive Space Communications

Future communication subsystems of space exploration missions can potentially benefit from software-defined radios (SDRs) controlled by machine learning algorithms. In this paper, we propose a novel hybrid radio resource allocation management control algorithm that integrates multi-objective reinforcement learning and deep artificial neural networks. The objective is to efficiently manage communications system resources by monitoring performance functions with common dependent variables that result in conflicting goals. The uncertainty in the performance of thousands of different possible combinations of radio parameters makes the trade-off between exploration and exploitation in reinforcement learning (RL) much more challenging for future critical space-based missions. Thus, the system should spend as little time as possible on exploring actions, and whenever it explores an action, it should perform at acceptable levels most of the time. The proposed approach enables on-line learning by interactions with the environment and restricts poor resource allocation performance through virtual environment exploration. Improvements in the multiobjective performance can be achieved via transmitter parameter adaptation on a packet-basis, with poorly predicted performance promptly resulting in rejected decisions. Simulations presented in this work considered the DVB-S2 standard adaptive transmitter parameters and additional ones expected to be present in future adaptive radio systems. Performance results are provided by analysis of the proposed hybrid algorithm when operating across a satellite communication channel from Earth to GEO orbit during clear sky conditions. The proposed approach constitutes part of the core cognitive engine proof-of-concept to be delivered to the NASA Glenn Research Center SCaN Testbed located onboard the International Space Station.

space archtiecture↗

Thermal Protection for Mars Sample Return Earth Entry Vehicle: A Grand Challenge for Design Methodology and Reliability Verification

Mars Sample Return is our Grand Challenge for the coming decade. TPS (Thermal Protection System) nominal performance is not the key challenge. The main difficulty for designers is the need to verify unprecedented reliability for the entry system: current guidelines for prevention of backward contamination require that the probability of spores larger than 1 micron diameter escaping into the Earth environment be lower than 1 million for the entire system, and the allocation to TPS would be more stringent than that. For reference, the reliability allocation for Orion TPS is closer to 11000, and the demonstrated reliability for previous human Earth return systems was closer to 1100. Improving reliability by more than 3 orders of magnitude is a grand challenge indeed. The TPS community must embrace the possibility of new architectures that are focused on reliability above thermal performance and mass efficiency. MSR (Mars Sample Return) EEV (Earth Entry Vehicle) will be hit with MMOD (Micrometeoroid and Orbital Debris) prior to reentry. A chute-less aero-shell design which allows for self-righting shape was baselined in prior MSR studies, with the assumption that a passive system will maximize EEV robustness. Hence the aero-shell along with the TPS has to take ground impact and not break apart. System verification will require testing to establish ablative performance and thermal failure but also testing of damage from MMOD, and structural performance at ground impact. Mission requirements will demand analysis, testing and verification that are focused on establishing reliability of the design. In this proposed talk, we will focus on the grand challenge of MSR EEV TPS and the need for innovative approaches to address challenges in modeling, testing, manufacturing and verification.

Design and Verification for Reliability↗

Assessment and Verification of SLS Block 1-B Exploration Upper Stage and Stage Disposal Performance

Delta-v allocation to correct for insertion errors caused by state uncertainty is one of the key performance requirements imposed on the SLS Navigation System. Additionally, SLS mission requirements include the need for the Exploration Up-per Stage (EUS) to be disposed of successfully. To assess these requirements, the SLS navigation team has developed and implemented a series of analysis methods. Here the authors detail the Delta-Delta-V approach to assessing delta-v allocation as well as the EUS disposal optimization approach.

Patrick, Sean↗

Implementation of a Space Communications Cognitive Engine

Although communications-based cognitive engines have been proposed, very few have been implemented in a full system, especially in a space communications system. In this paper, we detail the implementation of a multi-objective reinforcement-learning algorithm and deep artificial neural networks for the use as a radio-resource-allocation controller. The modular software architecture presented encourages re-use and easy modification for trying different algorithms. Various trade studies involved with the system implementation and integration are discussed. These include the choice of software libraries that provide platform flexibility and promote reusability, choices regarding the deployment of this cognitive engine within a system architecture using the DVB-S2 standard and commercial hardware, and constraints placed on the cognitive engine caused by real-world radio constraints. The implemented radio-resource allocation-management controller was then integrated with the larger spaceground system developed by NASA Glenn Research Center (GRC).

reinforcement learning↗