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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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Spacecraft control systems with computer command redundant jets for linear and angular pulses, relating configuration design to level-of- redundancy and task dimension
Space shuttle electronics requirements, considering systems in Mercury and Gemini spacecraft and Apollo lunar and command service modules
Design, development, and operation of communications system for command and control of unmanned spacecraft during exploration of deep space
The Apollo range instrumentation aircraft (ARIA) fleet which consists of four EC-135N aircraft used for Apollo communication support is discussed. The ARIA aircraft are used to provide coverage of lunar missions, earth orbit missions, command module/service module separation to spacecraft landing, and assist in recovery operations. Descriptions of ARIA aircraft, capabilities, and instrumentation are included.
Deep Space Network support is detailed for Viking spacecraft activities and the Viking command and tracking system. Viking DSN Mark 3 data subsystem implementation related testing is also discussed.
NASA presently maintains a worldwide system of ground tracking stations to provide communication support (tracking, telemetry and command) to all authorized user spacecraft missions. The set of ground stations supporting earth orbiting missions, and their supporting communication links (called NASCOM) to various NASA centers, is designated as the Spaceflight Tracking and Data Network (STDN). Major users of the STDN in the 1980's include LANDSAT-D, SEASAT-B and the Shuttle, all of which are capable of generating data at rates that cannot be handled by the present STDN ground stations. The expanded capabilities of the STDN in the 1980's to provide support to these missions and other users is addressed. The newest asset of the STDN, the Tracking and Data Relay Satellite System (TDRSS) is described, as are the remaining STDN ground stations (called the GSTDN). The Shuttle communications support is not only for the Shuttle itself, but also for the Spacelab, attached payloads (within the Shuttle bay), and detached payloads being either deployed or retrieved by Shuttle. The specific communications support being provided by STDN (both by TDRSS and by the GSTDN) to the Shuttle is also described.
The Apollo II Second Generation Lunar Exploration System includes the direct landing spacecraft which consists of cargo command module, service module, and landing module. The landing module is also capable of being used as the Lunar Landing Vehicle (LLV) for landing unmanned cargos consisting of shelter modules such as the Lunar Occupancy Payload and other cargo in support of lunar surface operations. High energy cryogenic propellants are utilized to permit direct landing, manned, or logistic missions with use of a single Saturn V class booster. In last year's studies, the LLV was configured for maximum payload and with consideration for the direct three-man landing and return mission. Light weight and low vehicle height above the lunar surface at touchdown were major objectives. Logistic cargos of more than 27,000 pounds landed on the Moon were achieved within the single Saturn V boost capability. For the manned mission, the lunar take-off weight was determined to be 28,000 pounds ready for the return-to-Earth portion of the mission. The command module utilized was an advanced light-weight design weighing 10,000 pounds including supporting subsystems. Cryogenic oxygen/hydrogen propulsion was again used for maximum propulsion efficiency. Study of the Lunar Occupancy Payload was also accomplished last year. This module was configured to serve as an early lunar shelter or outpost station or as a basic module of an integrated base module complex. Single and dual compartment versions, as well as special mission versions, were studied.
The communications and data handling system of the HST are described in detail. Consideration is given to observation scheduling, commanding, telemetry, scientific data collection, spacecraft data handling systems, and the use of the TDRSS and NASCOM data network. The science instruments control and data handling subsystem is presented in schematic form.
In the coming decade, several lander missions to Mars are planned (e.g., MESUR Pathfinder, MESUR). One of the dangers facing planners of these missions is the rough topography observed at both Viking Lander sites. Both landing sites are ubiquitously covered with meter-scale boulders. Objects of this size pose obvious threats to soft landers, especially at Mars where the distance from Earth causes prohibitive time lags between the transmission of commands and feedback from the spacecraft. An obvious solution is to scout for a 'smooth' site prior to the landing. However, the best resolutions realizable on current and future missions (i.e., Mars Observer) are on the order of several meters. Even at this scale, boulders of 1-2 meters in size are unresolvable. Additionally, the amount of time and spacecraft resources required to search even a small area of the planet are unrealistic given other mission objectives. An alternative is to determine the 'roughness' of the surface at a subpixel scale using bidirectional reflectance observations. Much larger areas of the planet can be searched, and much of the search can easily be automated. The morphology of the martian plains observed by the Viking Landers is physically simple. The surface is covered with a layer (approximately flat lying) of aeolian sediment from which numerous outcrops of bedrock and boulders protrude. This morphology, while simple, will be difficult to characterize from orbit using traditional bidirectional reflectance models for two reasons. First, modeling the surface as facets with Gaussian or exponential slope distributions is not realistic given the morphology described above. Second, the roughness parameter is an 'average' of the roughness at scales ranging from the wavelength of light being scattered to the pixel size of the observation. Thus, there is no definite scale of roughness that can be extracted from the Hapke roughness parameter. Using the concepts of geometric and boolean models developed by several workers, we have developed a model for the bidirectional reflectance of a surface morphology comparable to that observed at the Viking Lander sites.
A spacecraft Attitude Control and Determination Subsystem (ACDS) is heavily dependent upon simulation throughout its entire development, implementation and ground test cycle. Engineering simulation tools are typically developed to design and analyze control systems to validate the design and software simulation tools are required to qualify the flight software. However, the need for simulation does not end here. Operating the ACDS of a spacecraft on the ground requires the simulation of spacecraft dynamics, disturbance modeling and celestial body motion. Sensor data must also be simulated and substituted for actual sensor data on the ground so that the spacecraft will respond by sending commands to the actuators as they will on orbit. And finally, the simulators is the primary training tool and test-bed for the Flight Operations Team. In this paper various ACDS simulation, developed for or used by the Landsat 7 project will be described. The paper will include a description of each tool, its unique attributes, and its role in the overall development and testing of the ACDS. Finally, a section is included which discusses how the coordinated use of these simulation tools can maximize the probability of uncovering software, hardware and operations errors during the ground test process.
Annapolis, Maryland-based designAmerica Inc., a small aerospace company specializing in the development and delivery of ground control systems for satellites and instrumentation, assisted Goddard Space Flight Center in the development of the ASIST software, a real-time command and control system for spacecraft development, integration, and operations. It was designed to be fully functional across a broad spectrum of satellites and instrumentation, while also being user friendly. The company now has rights to commercial use of the program and is offering it to government and industry satellite designers.
A system was developed to provide a new mechanism for members of the mission community to create and contribute new science data to the rest of the community. Mission tools have allowed members of the mission community to share first order data (data that is created by the mission s process in command and control of the spacecraft or the data that is captured by the craft itself, like images, science results, etc.). However, second and higher order data (data that is created after the fact by scientists and other members of the mission) was previously not widely disseminated, nor did it make its way into the mission planning process.
It is possible to use a Delay Tolerant Network (DTN) to transport data and/or commanding from one end-point to another end-point where DTN is not used. This implies that at least one or the other end-point is sending and receiving as a non-DTN node. It also implies that at least one intermediate node prior to the non-DTN node has a Convergence Layer Adapter (CLA) or application which supports appropriate protocols. This is the basic concept of Rationale, Scenarios, and Requirements for DTN in Space, section 4.2.2.6.3: An application on the last hop relay node may extract TeleCommands(TCs) from an immediate or delayed TC file and radiate them as TCs to their destination (typically orbiter to lander); Rationale: Such an application could be used to support low-level commanding in case the destination spacecraft’s network layer is not functioning properly.
Artificial Intelligence (AI) is an integral part of today’s process of conducting science and technology development. At NASA, AI has become an integral and important tool for researchers, engineers, data scientists, and technologists in pursuing the ground-breaking discoveries that we are known for, including the command and controlling of our spacecraft and other supporting infrastructures. Consequently, research and engineering efforts incorporating AI have permeated almost every area of our work. It is contributing to NASA’s drive toward the future, not just of space science, but for society here at home. We are dedicated to continuing the use of AI in a safe and fully transparent approach so that the public can have high confidence in the outcomes and benefits. We believe that the plan outlined here will be responsive and contribute to the call for openness across the federal government. NASA is committed to responsible use of AI in all of its activities and in all phases of development and deployment of its space and terrestrial programs missions. NASA does not deliberately focus on “AI Research” as a separate field (we have no single “AI office” or “AI program”), rather NASA uses AI to build tools for its programs. This plan, being put forward, adheres to the Responsible AI (RAI) principles set and laid down by the White House in its Presidential Executive Order 13960. Our research, engineering and technical communities have been made aware of these guidelines and we are committed to an on-going process of educating and monitoring its implementation to ensure adherence to those principles. The vast majority of NASA’s use cases, which number almost 75 today, are geared toward analyzing the petabytes of data that NASA collects from its fleet of spacecraft across all disciplines, in human space exploration, and in aeronautics, etc.
Livingstone2 is a reusable, artificial intelligence (AI) software system designed to assist spacecraft, life support systems, chemical plants, or other complex systems by operating with minimal human supervision, even in the face of hardware failures or unexpected events. The software diagnoses the current state of the spacecraft or other system, and recommends commands or repair actions that will allow the system to continue operation. Livingstone2 is an enhancement of the Livingstone diagnosis system that was flight-tested onboard the Deep Space One spacecraft in 1999. This version tracks multiple diagnostic hypotheses, rather than just a single hypothesis as in the previous version. It is also able to revise diagnostic decisions made in the past when additional observations become available. In such cases, Livingstone might arrive at an incorrect hypothesis. Re-architecting and re-implementing the system in C++ has increased performance. Usability has been improved by creating a set of development tools that is closely integrated with the Livingstone2 engine. In addition to the core diagnosis engine, Livingstone2 includes a compiler that translates diagnostic models written in a Java-like language into Livingstone2's language, and a broad set of graphical tools for model development.
Three documents provide information on a digital processing unit (DPU) for the planned Aquarius mission, in which a radiometer aboard a spacecraft orbiting Earth is to measure radiometric temperatures from which data on sea-surface salinity are to be deduced. The DPU is the interface between the radiometer and an instrument-command-and-data system aboard the spacecraft. The DPU cycles the radiometer through a programmable sequence of states, collects and processes all radiometric data, and collects all housekeeping data pertaining to operation of the radiometer. The documents summarize the DPU design, with emphasis on innovative aspects that include mainly the following: a) In the radiometer and the DPU, conversion from analog voltages to digital data is effected by means of asynchronous voltage-to-frequency converters in combination with a frequency-measurement scheme implemented in field-programmable gate arrays (FPGAs). b) A scheme to compensate for aging and changes in the temperature of the DPU in order to provide an overall temperature-measurement accuracy within 0.01 K includes a high-precision, inexpensive DC temperature measurement scheme and a drift-compensation scheme that was used on the Cassini radar system. c) An interface among multiple FPGAs in the DPU guarantees setup and hold times.
A method, apparatus, article of manufacture, and a memory structure for compensating for instrument induced spacecraft jitter is disclosed. The apparatus comprises a spacecraft control processor for producing an actuator command signal, a signal generator, for producing a cancellation signal having at least one harmonic having a frequency and an amplitude substantially equal to that of a disturbance harmonic interacting with a spacecraft structural resonance and a phase substantially out of phase with the disturbance harmonic interacting with the spacecraft structural resonance, and at least one spacecraft control actuator, communicatively coupled to the spacecraft control processor and the signal generator for inducing satellite motion according to the actuator command signal and the cancellation signal. The method comprises the steps of generating a cancellation signal having at least one harmonic having a frequency and an amplitude substantially equal to that of a disturbance harmonic interacting with a spacecraft structural resonance and a phase substantially out of phase with the disturbance harmonic interacting with the spacecraft structural resonance, and providing the cancellation signal to a spacecraft control actuator. The apparatus comprises a storage device tangibly embodying the method steps described above.
Full-scale-model and actual spacecraft were impact tested to define the emergency land-landing capability of the Apollo command module. Structural accelerations and strains were recorded on analog instrumentation, and a summary to these data is included. The landing kinematics were obtained from high-speed photography. Photographs of the structural damage caused during the tests are included. Even though extensive damage can be expected, the crew will receive nothing more than minor injuries during the majority of the probable landing conditions.