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A timing system comprising an electronic master clock and a subsystem for distributing time signals from the master clock to end users is undergoing development to satisfy anticipated timing requirements of NASA s Deep Space Network (DSN) for the next 20 to 30 years. This system has a modular, flexible, expandable architecture that is easier to operate and maintain than the present frequency and timing subsystem (FTS).
A document discusses the Portable Health Algorithms Test (PHALT) System, which has been designed as a means for evolving the maturity and credibility of algorithms developed to assess the health of aerospace systems. Comprising an integrated hardware-software environment, the PHALT system allows systems health management algorithms to be developed in a graphical programming environment, to be tested and refined using system simulation or test data playback, and to be evaluated in a real-time hardware-in-the-loop mode with a live test article. The integrated hardware and software development environment provides a seamless transition from algorithm development to real-time implementation. The portability of the hardware makes it quick and easy to transport between test facilities. This hard ware/software architecture is flexible enough to support a variety of diagnostic applications and test hardware, and the GUI-based rapid prototyping capability is sufficient to support development execution, and testing of custom diagnostic algorithms. The PHALT operating system supports execution of diagnostic algorithms under real-time constraints. PHALT can perform real-time capture and playback of test rig data with the ability to augment/ modify the data stream (e.g. inject simulated faults). It performs algorithm testing using a variety of data input sources, including real-time data acquisition, test data playback, and system simulations, and also provides system feedback to evaluate closed-loop diagnostic response and mitigation control.
A system of software has been developed to coordinate the operation of an autonomous Earth-observing sensorweb. Sensorwebs are collections of sensor units scattered over large regions to gather data on spatial and temporal patterns of physical, chemical, or biological phenomena in those regions. Each sensor unit is a node in a data-gathering/ data-communication network that spans a region of interest. In this case, the region is the entire Earth, and the sensorweb includes multiple terrestrial and spaceborne sensor units. In addition to acquiring data for scientific study, the sensorweb is required to give timely notice of volcanic eruptions, floods, and other hazardous natural events. In keeping with the inherently modular nature of the sensory, communication, and data-processing hardware, the software features a flexible, modular architecture that facilitates expansion of the network, customization of conditions that trigger alarms of hazardous natural events, and customization of responses to alarms. The soft8 NASA Tech Briefs, July 2006 ware facilitates access to multiple sources of data on an event of scientific interest, enables coordinated use of multiple sensors in rapid reaction to detection of an event, and facilitates the tracking of spacecraft operations, including tracking of the acquisition, processing, and downlinking of requested data.
The MSFC/APL Robotic Lunar Landing Project (RLLDP) team has developed lander concepts encompassing a range of mission types and payloads for science, exploration, and technology demonstration missions: (1) Developed experience and expertise in lander systems, (2) incorporated lessons learned from previous efforts to improve the fidelity of mission concepts, analysis tools, and test beds Mature small and medium lander designs concepts have been developed: (1) Share largely a common design architecture. (2) Flexible for a large number of mission and payload options. High risk development areas have been successfully addressed Landers could be selected for a mission with much of the concept formulation phase work already complete
Phobos Surveyor Mission concept provides an innovative low cost, highly reliable approach to exploring the inner solar system 1/16/2013 3 Dual manifest launch. Use only flight proven, well characterize commercial off-the-shelf components. Flexible mission architecture allows for a slew of unique measurements.
This presentation will discuss the methodology behind Model Class Definition--the use of separate model assemblies of the same product, at different fidelities, driven by the same skeleton files. These fidelities can be used to convey only the detail that the end user needs, by allowing the end user to pick and choose between model classes for assembly creation. The usefulness of MPA for the Windchill Release Process will be demonstrated, along with its usefulness in minimizing CPU resources during design. The presentation will include an overview the ML product, how to structure complex products in a flexible modular architecture, and how to maximize system resources.
A robust and flexible autopilot architecture for NASA's Space Launch System (SLS) family of launch vehicles is presented. As the SLS configurations represent a potentially significant increase in complexity and performance capability of the integrated flight vehicle, it was recognized early in the program that a new, generalized autopilot design should be formulated to fulfill the needs of this new space launch architecture. The present design concept is intended to leverage existing NASA and industry launch vehicle design experience and maintain the extensibility and modularity necessary to accommodate multiple vehicle configurations while relying on proven and flight-tested control design principles for large boost vehicles. The SLS flight control architecture combines a digital three-axis autopilot with traditional bending filters to support robust active or passive stabilization of the vehicle's bending and sloshing dynamics using optimally blended measurements from multiple rate gyros on the vehicle structure. The algorithm also relies on a pseudo-optimal control allocation scheme to maximize the performance capability of multiple vectored engines while accommodating throttling and engine failure contingencies in real time with negligible impact to stability characteristics. The architecture supports active in-flight load relief through the use of a nonlinear observer driven by acceleration measurements, and envelope expansion and robustness enhancement is obtained through the use of a multiplicative forward gain modulation law based upon a simple model reference adaptive control scheme.
A robust and flexible autopilot architecture for NASA's Space Launch System (SLS) family of launch vehicles is presented. The SLS configurations represent a potentially significant increase in complexity and performance capability when compared with other manned launch vehicles. It was recognized early in the program that a new, generalized autopilot design should be formulated to fulfill the needs of this new space launch architecture. The present design concept is intended to leverage existing NASA and industry launch vehicle design experience and maintain the extensibility and modularity necessary to accommodate multiple vehicle configurations while relying on proven and flight-tested control design principles for large boost vehicles. The SLS flight control architecture combines a digital three-axis autopilot with traditional bending filters to support robust active or passive stabilization of the vehicle's bending and sloshing dynamics using optimally blended measurements from multiple rate gyros on the vehicle structure. The algorithm also relies on a pseudo-optimal control allocation scheme to maximize the performance capability of multiple vectored engines while accommodating throttling and engine failure contingencies in real time with negligible impact to stability characteristics. The architecture supports active in-flight disturbance compensation through the use of nonlinear observers driven by acceleration measurements. Envelope expansion and robustness enhancement is obtained through the use of a multiplicative forward gain modulation law based upon a simple model reference adaptive control scheme.
The Bumper code has been the standard in use by NASA and contractors to perform meteoroid/debris risk assessments since 1990. It has undergone extensive revisions and updates [NASA JSC HITF website; Christiansen et al., 1992, 1997]. NASA Johnson Space Center (JSC) has applied BUMPER to risk assessments for Space Station, Shuttle, Mir, Extravehicular Mobility Units (EMU) space suits, and other spacecraft (e.g., LDEF, Iridium, TDRS, and Hubble Space Telescope). Bumper continues to be updated with changes in the ballistic limit equations describing failure threshold of various spacecraft components, as well as changes in the meteoroid and debris environment models. Significant efforts are expended to validate Bumper and benchmark it to other meteoroid/debris risk assessment codes. Bumper 3 is a refactored version of Bumper II. The structure of the code was extensively modified to improve maintenance, performance and flexibility. The architecture was changed to separate the frequently updated ballistic limit equations from the relatively stable common core functions of the program. These updates allow NASA to produce specific editions of the Bumper 3 that are tailored for specific customer requirements. The core consists of common code necessary to process the Micrometeoroid and Orbital Debris (MMOD) environment models, assess shadowing and calculate MMOD risk. The library of target response subroutines includes a board range of different types of MMOD shield ballistic limit equations as well as equations describing damage to various spacecraft subsystems or hardware (thermal protection materials, windows, radiators, solar arrays, cables, etc.). The core and library of ballistic response subroutines are maintained under configuration control. A change in the core will affect all editions of the code, whereas a change in one or more of the response subroutines will affect all editions of the code that contain the particular response subroutines which are modified. Note that the Bumper II program is no longer maintained or distributed by NASA.
The Space Exploration Synthetic Aperture Radar (SESAR) is an advanced P-band beamforming radar instrument concept to enable a new class of observations suitable to meet multiple Decadal Survey science goals for planetary exploration. The radar is capable of providing unprecedented surface and near subsurface measurements at full polarimetry and fine (meter scale) resolution, and achieves beam agility through programmable waveform generation and digital beamforming. The radar’s highly flexible modular architecture employs a novel low power, lightweight design approach to meet stringent planetary instrument requirements, all while minimizing cost and development time.
Hybrid gas-electric aircraft propulsion architectures provide flexibility in the way that power and energy is managed when compared to their traditional pure-gas counterparts. In this paper, investigations are conducted for the impact this added flexibility has on the operability of turbomachinery. Specifically, the Turbine Electrified Energy Management (TEEM) concept is applied. It takes a controls approach to improving operability of the turbomachinery by utilizing electric hardware. In this paper, TEEM is applied to a propulsion system for a 15 passenger vertical lift concept vehicle. This is the first application of TEEM to a turbine engine that generates power. The study establishes TEEM as being applicable to this smaller thrust/power class of air transportation vehicle and explore show power can be otherwise managed in the propulsion system to benefit the aircraft. The simulation study demonstrates significant improvements in transient operability that expands the engine design space to enable a more efficient and lighter-weight engine design. Simulation results also demonstrate tighter regulation of the power turbine and rotor speeds, a slight decrease in bulk fuel burn, and an increase in the maximum thrust of ~7%. This is achieved through the power management control strategy and modestly sized electric machines with re-usable energy storage.
Hybrid gas-electric aircraft propulsion architectures provide flexibility in the way that power and energy is managed when compared to their traditional pure-gas counterparts. In this paper, investigations are conducted for the impact this added flexibility has on the operability of turbomachinery. Specifically, the Turbine Electrified Energy Management (TEEM) concept is applied. It takes a controls approach to improving operability of the turbomachinery by utilizing electric hardware. In this paper, TEEM is applied to a propulsion system for a 15 passenger vertical lift concept vehicle. This is the first application of TEEM to a turbine engine that generates power. The study establishes TEEM as being applicable to this smaller thrust/power class of air transportation vehicle and explores how power can be otherwise managed in the propulsion system to benefit the aircraft. The simulation study demonstrates significant improvements in transient operability that expands the engine design space to enable a more efficient and lighter weight engine design. Simulation results also demonstrate tighter regulation of the power turbine and rotor speeds, a slight decrease in bulk fuel burn, and an increase in the maximum thrust of ~7%. This is achieved through the power management control strategy and modestly sized electric machines with re usable energy storage.
BACKGROUND: While NASA currently uses the Integrated Medical Model (IMM) to model spaceflight medical risk for Low Earth Orbit missions, IMPACT (Informing Mission Planning via Analysis of Complex Tradespaces) was created to improve the fidelity of medical risk analysis for exploration missions involving the Lunar surface and beyond. OVERVIEW: While completion work continues on the initial version of the IMPACT tool, work has already begun to investigate ways to further enhance the fidelity of the model and its utility to stakeholders. DISCUSSION: Future additions leveraging the more robust and flexible IMPACT architecture include analyzing mission segments to account for segment-specific environments (ie. Lunar surface or microgravity), clinically tracible outcomes based on partial treatment of conditions, the ability to model mission outcomes based on provider Knowledge, Skills, and Abilities (KSAs), and the ability to affect the incidence of conditions based on the occurrence of related conditions (e.g. UTI progressing to sepsis). IMPACT also enables the addition of new conditions to its database as required to meet future risk assessment needs. Ultimately, the desire is to broaden IMPACT from a tool that models/trades medical risk to one that does so for all crew health and performance relevant systems (e.g., food, exercise, etc.).
The development of numerical methods and software tools for parallel processors can be aided through the use of a hardware test-bed. The test-bed architecture must be flexible enough to support investigations into architecture-algorithm interactions. One way to implement a test-bed is to use a commercial parallel processor. Unfortunately, most commercial parallel processors are fixed in their interconnection and/or processor architecture. In this paper, we describe a modified n cube architecture, called the hypercluster, which is a superset of many other processor and interconnection architectures. The hypercluster is intended to support research into parallel processing of computational fluid and structural mechanics problems which may require a number of different architectural configurations. An example of how a typical partial differential equation solution algorithm maps on to the hypercluster is given.
The Orion Entry, Descent, and Landing simulation was created over the past two years to serve as the primary Crew Exploration Vehicle guidance, navigation, and control (GN&C) design and analysis tool at the National Aeronautics and Space Administration (NASA). The Advanced NASA Technology Architecture for Exploration Studies (ANTARES) simulation is a six degree-of-freedom tool with a unique design architecture which has a high level of flexibility. This paper describes the decision history and motivations that guided the creation of this simulation tool. The capabilities of the models within ANTARES are presented in detail. Special attention is given to features of the highly flexible GN&C architecture and the details of the implemented GN&C algorithms. ANTARES provides a foundation simulation for the Orion Project that has already been successfully used for requirements analysis, system definition analysis, and preliminary GN&C design analysis. ANTARES will find useful application in engineering analysis, mission operations, crew training, avionics-in-the-loop testing, etc. This paper focuses on the entry simulation aspect of ANTARES, which is part of a bigger simulation package supporting the entire mission profile of the Orion vehicle. The unique aspects of entry GN&C design are covered, including how the simulation is being used for Monte Carlo dispersion analysis and for support of linear stability analysis. Sample simulation output from ANTARES is presented in an appendix.
In this innovation, a digital downconverter has been created that produces a large (16 or greater) number of output channels of smaller bandwidths. Additionally, this design has the flexibility to tune each channel independently to anywhere in the input bandwidth to cover a wide range of output bandwidths (from 32 MHz down to 1 kHz). Both the flexibility in channel frequency selection and the more than four orders of magnitude range in output bandwidths (decimation rates from 32 to 640,000) presented significant challenges to be solved. The solution involved breaking the digital downconversion process into a two-stage process. The first stage is a 2 oversampled filter bank that divides the whole input bandwidth as a real input signal into seven overlapping, contiguous channels represented with complex samples. Using the symmetry of the sine and cosine functions in a similar way to that of an FFT (fast Fourier transform), this downconversion is very efficient and gives seven channels fixed in frequency. An arbitrary number of smaller bandwidth channels can be formed from second-stage downconverters placed after the first stage of downconversion. Because of the overlapping of the first stage, there is no gap in coverage of the entire input bandwidth. The input to any of the second-stage downconverting channels has a multiplexer that chooses one of the seven wideband channels from the first stage. These second-stage downconverters take up fewer resources because they operate at lower bandwidths than doing the entire downconversion process from the input bandwidth for each independent channel. These second-stage downconverters are each independent with fine frequency control tuning, providing extreme flexibility in positioning the center frequency of a downconverted channel. Finally, these second-stage downconverters have flexible decimation factors over four orders of magnitude The algorithm was developed to run in an FPGA (field programmable gate array) at input data sampling rates of up to 1,280 MHz. The current implementation takes a 1,280-MHz real input, and first breaks it up into seven 160-MHz complex channels, each spaced 80 MHz apart. The eighth channel at baseband was not required for this implementation, and led to more optimization. Afterwards, 16 second stage narrow band channels with independently tunable center frequencies and bandwidth settings are implemented A future implementation in a larger Xilinx FPGA will hold up to 32 independent second-stage channels.
The Project Integration Architecture (PIA) implements a flexible, object-oriented, wrapping architecture which encapsulates all of the information associated with engineering applications. The architecture allows the progress of a project to be tracked and documented in its entirety. By being a single, self-revealing architecture, the ability to develop single tools, for example a single graphical user interface, to span all applications is enabled. Additionally, by bringing all of the information sources and sinks of a project into a single architectural space, the ability to transport information between those applications becomes possible, Object-encapsulation further allows information to become in a sense self-aware, knowing things such as its own dimensionality and providing functionality appropriate to its kind.
The Project Integration Architecture (PIA) implements a flexible, object-oriented, wrapping architecture which encapsulates all of the information associated with engineering applications. The architecture allows the progress of a project to be tracked and documented in its entirety. Additionally, by bringing all of the information sources and sinks of a project into a single architectural space, the ability to transport information between those applications is enabled.