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Overview of LaRC's Comprehensive Digital Transformation strategy. Includes foundational items such as modeling & simulation, big data analytics, high performance computing, and advanced information technology. Builds upon the foundation to recommend advanced "virtual capabilities," such as a virtual flight test capability to complement flight testing and wind tunnels.
The purpose of this document was originally to be a working document summarizing Space Station Freedom (SSF) Data Management System (DMS) hardware and software design, configuration, performance and estimated loading data from a myriad of source documents such that the parameters provided could be used to build a dynamic performance model of the DMS. The document is published at this time as a close-out of the DMS performance modeling effort resulting from the Clinton Administration mandated Space Station Redesign. The DMS as documented in this report is no longer a part of the redesigned Space Station. The performance modeling effort was a joint undertaking between the National Aeronautics and Space Administration (NASA) Johnson Space Center (JSC) Flight Data Systems Division (FDSD) and the NASA Ames Research Center (ARC) Spacecraft Data Systems Research Branch. The scope of this document is limited to the DMS core network through the Man Tended Configuration (MTC) as it existed prior to the 1993 Clinton Administration mandated Space Station Redesign. Data is provided for the Standard Data Processors (SDP's), Multiplexer/Demultiplexers (MDM's) and Mass Storage Units (MSU's). Planned future releases would have added the additional hardware and software descriptions needed to describe the complete DMS. Performance and loading data through the Permanent Manned Configuration (PMC) was to have been included as it became available. No future releases of this document are presently planned pending completion of the present Space Station Redesign activities and task reassessment.
NASA Glenn Research Center (GRC) has been supporting development of the Advanced Stirling Radioisotope Generator (ASRG) since 2006. A key element of the ASRG project is providing life, reliability, and performance testing of the Advanced Stirling Convertor (ASC). For this purpose, the Thermal Energy Conversion branch at GRC has been conducting extended operation of a multitude of free-piston Stirling convertors. The goal of this effort is to generate long-term performance data (tens of thousands of hours) simultaneously on multiple units to build a life and reliability database. The test hardware for operation of these convertors was designed to permit in-air investigative testing, such as performance mapping over a range of environmental conditions. With this, there was no requirement to accurately emulate the flight hardware. For the upcoming ASC-E3 units, the decision has been made to assemble the convertors into a flight-like configuration. This means the convertors will be arranged in the dual-opposed configuration in a housing that represents the fit, form, and thermal function of the ASRG. The goal of this effort is to enable system level tests that could not be performed with the traditional test hardware at GRC. This offers the opportunity to perform these system-level tests much earlier in the ASRG flight development, as they would normally not be performed until fabrication of the qualification unit. This paper discusses the requirements, process, and results of this flight-like hardware design activity.
NASA Glenn Research Center (GRC) has been supporting development of the Advanced Stirling Radioisotope Generator (ASRG) since 2006. A key element of the ASRG project is providing life, reliability, and performance testing of the Advanced Stirling Convertor (ASC). For this purpose, the Thermal Energy Conversion branch at GRC has been conducting extended operation of a multitude of free-piston Stirling convertors. The goal of this effort is to generate long-term performance data (tens of thousands of hours) simultaneously on multiple units to build a life and reliability database. The test hardware for operation of these convertors was designed to permit in-air investigative testing, such as performance mapping over a range of environmental conditions. With this, there was no requirement to accurately emulate the flight hardware. For the upcoming ASC-E3 units, the decision has been made to assemble the convertors into a flight-like configuration. This means the convertors will be arranged in the dual-opposed configuration in a housing that represents the fit, form, and thermal function of the ASRG. The goal of this effort is to enable system level tests that could not be performed with the traditional test hardware at GRC. This offers the opportunity to perform these system-level tests much earlier in the ASRG flight development, as they would normally not be performed until fabrication of the qualification unit. This paper discusses the requirements, process, and results of this flight-like hardware design activity.
NASA Glenn Research Center (GRC) has been supporting development of free-piston Stirling conversion technology for spaceflight electrical power generation since 1999. GRC has also been supporting the development of the Advanced Stirling Radioisotope Generator (ASRG) since 2006. A key element of the ASRG project is providing life, reliability, and performance data for the Advanced Stirling Convertor (ASC). The Thermal Energy Conversion branch at GRC is conducting extended operation of several free-piston Stirling convertors. The goal of this effort is to generate long-term performance data (tens of thousands of hours) on multiple units to build a life and reliability database. Currently, GRC is operating 18 convertors. This hardware set includes Technology Demonstration Convertors (TDCs) from Infinia Corporation, of which one pair (TDCs #13 and #14) has accumulated over 60,000 hr (6.8 years) of operation. Also under test are various Sunpower, Inc. convertors that were fabricated during the ASC development activity, including ASC-0, ASC-E (including those in the ASRG engineering unit), and ASC-E2. The ASC-E2s also completed, or are in progress of completing workmanship vibration testing, performance mapping, and extended operation. Two ASC-E2 units will also be used for durability testing, during which components will be stressed to levels above nominal mission usage. Extended operation data analyses from these tests are covered in this paper.
The Enabling Technology Development and Demonstration (ETDD) Program High Efficiency Space Power Systems (HESPS) Project, formerly the Exploration Technology Development Program (ETDP) Energy Storage Project is tasked with developing advanced lithium-ion cells for future NASA Exploration missions. Under this project, components under development via various in-house and contracted efforts are delivered to Saft America for scale-up and integration into cells. Progress toward meeting project goals will be measured by comparing the performance to these cells with cells of a similar format with Saft s state-of-the-art aerospace chemistry. This report discusses the results of testing performed on the first set of baseline cells delivered by Saft to the NASA Glenn Research Center. This build is a cylindrical "DD" geometry with a 10 Ah nameplate capacity. Testing is being performed to establish baseline cell performance at conditions relevant to ETDD HESPS Battery Key Performance Parameter (KPP) goals including various temperatures, rates, and cycle life conditions. Data obtained from these cells will serve as a performance baseline for future cell builds containing optimized ETDD HESPSdeveloped materials. A test plan for these cells was developed to measure cell performance against the high energy cell KPP goals. The goal for cell-level specific energy of the high energy technology is 180 Wh/kg at a C/10 discharge rate and 0 C. The cells should operate for at least 2000 cycles at 100 percent DOD with 80 percent capacity retention. Baseline DD cells delivered 152 Wh/kg at 20 C. This number decreased to 143.9 Wh/kg with a 0 C discharge. This report provides performance data and summarizes results of the testing performed on the DD cells.
The key heating, ventilation, and air-conditioning (HVAC) modifications implemented at the Mars Deep Space Station's Operation Support Building at Jet Propulsion Laboratories (JPL) in order to reduce energy consumption and decrease operating costs are described. An energy analysis comparison between the computer simulated model for the building and the actual meter data was presented. The measurement performance data showed that the cumulative energy savings was about 21% for the period 1979 to 1981. The deviation from simulated data to measurement performance data was only about 3%.
As modern transport environments become increasingly complex, issues such as crew communication, interaction with automation, and workload management have become crucial. Much research is being focused on holistic aspects of social and cognitive behavior, such as the strategies used to handle workload, the flow of information, the scheduling of tasks, the verbal and non-verbal interactions between crew members. Traditional laboratory performance measures no longer sufficiently meet the needs of researchers addressing these issues. However observational techniques are better equipped to capture the type of data needed and to build models of the requisite level of sophistication. Presented here is SHAPA, an interactive software tool for performing both verbal and non-verbal protocol analysis. It has been developed with the idea of affording the researchers the closest possible degree of engagement with protocol data. The researcher can configure SHAPA to encode protocols using any theoretical framework or encoding vocabulary that is desired. SHAPA allows protocol analysis to be performed at any level of analysis, and it supplies a wide variety of tools for data aggregation, manipulation. The output generated by SHAPA can be used alone or in combination with other performance variables to get a rich picture of the influences on sequences of verbal or nonverbal behavior.
Exponential growth in microelectronics technology such as field-programmable gate arrays (FPGAs) has enabled high-performance spaceborne instruments with increasing onboard data processing capabilities. As a commonly used digital signal processing (DSP) building block, fast Fourier transform (FFT) has been of great interest in onboard data processing applications, which needs to strike a reasonable balance between high-performance (throughput, block size, etc.) and low resource usage (power, silicon footprint, etc.). It is also desirable to be designed so that a single design can be reused and adapted into instruments with different requirements. The Multi-Pass Wide Kernel FFT (MPWK-FFT) architecture was developed, in which the high-throughput benefits of the parallel FFT structure and the low resource usage of Singleton s single butterfly method is exploited. The result is a wide-kernel, multipass, adaptive FFT architecture. The 32K-point MPWK-FFT architecture includes 32 radix-2 butterflies, 64 FIFOs to store the real inputs, 64 FIFOs to store the imaginary inputs, complex twiddle factor storage, and FIFO logic to route the outputs to the correct FIFO. The inputs are stored in sequential fashion into the FIFOs, and the outputs of each butterfly are sequentially written first into the even FIFO, then the odd FIFO. Because of the order of the outputs written into the FIFOs, the depth of the even FIFOs, which are 768 each, are 1.5 times larger than the odd FIFOs, which are 512 each. The total memory needed for data storage, assuming that each sample is 36 bits, is 2.95 Mbits. The twiddle factors are stored in internal ROM inside the FPGA for fast access time. The total memory size to store the twiddle factors is 589.9Kbits. This FFT structure combines the benefits of high throughput from the parallel FFT kernels and low resource usage from the multi-pass FFT kernels with desired adaptability. Space instrument missions that need onboard FFT capabilities such as the proposed DESDynl, SWOT (Surface Water Ocean Topography), and Europa sounding radar missions would greatly benefit from this technology with significant reductions in non-recurring cost and risk.
The Propulsion IVHM Technology Experiment (PITEX) successfully demonstrated real-time fault detection and isolation of a virtual reusable launch vehicle (RLV) main propulsion system (MPS). Specifically, the PITEX research project developed and applied a model-based diagnostic system for the MPS of the X-34 RLV, a space-launch technology demonstrator. The demonstration was simulation-based using detailed models of the propulsion subsystem to generate nominal and failure scenarios during captive carry, which is the most safety-critical portion of the X-34 flight. Since no system-level testing of the X-34 Main Propulsion System (MPS) was performed, these simulated data were used to verify and validate the software system. Advanced diagnostic and signal processing algorithms were developed and tested in real time on flight-like hardware. In an attempt to expose potential performance problems, the PITEX diagnostic system was subjected to numerous realistic effects in the simulated data including noise, sensor resolution, command/valve talkback information, and nominal build variations. In all cases, the PITEX system performed as required. The research demonstrated potential benefits of model-based diagnostics, defined performance metrics required to evaluate the diagnostic system, and studied the impact of real-world challenges encountered when monitoring propulsion subsystems.
The Biomass Production Chamber (BPC) at the Kennedy Space Center is part of the Controlled Ecological Life Support System (CELSS) Breadboard Project. Plants are grown in a closed environment in an effort to quantify their contributions to the requirements for life support. Performance of this system is described. Also, in building this system, data from component and subsystem failures are being recorded. These data are used to identify problem areas in the design and implementation. The techniques used to measure the reliability will be useful in the design and construction of future CELSS. Possible methods for determining the reliability of a green plant, the primary component of CELSS, are discussed.
The Biomass Production Chamber (BPC) at the Kennedy Space Center is part of the Controlled Ecological Life Support System (CELSS) Breadboard Project. Plants are grown in a closed environment in an effort to quantify their contributions to the requirements for life support. Performance of this system is described. Also, in building this system, data from component and subsystem failures are being recorded. These data are used to identify problem areas in the design and implementation. The techniques used to measure the reliability will be useful in the design and construction of future CELSS. Possible methods for determining the reliability of a green plant, the primary component of a CELSS, are discussed.
By integrating the attitude determination and control system (ACS) analysis and design, flight software development, and flight software testing processes, it is possible to improve the overall spacecraft development cycle, as well as allow for more thorough software testing. One of the ways to achieve this integration is to use code-generation tools to automatically generate components of the ACS flight software directly from a high-fidelity (HiFi) simulation. In the development of the Microwave Anisotropy Probe (MAP) spacecraft, currently underway at the NASA Goddard Space Flight Center, approximately 1/3 of the ACS flight software was automatically generated. In this paper, we will examine each phase of the ACS subsystem and flight software design life cycle: analysis, design, and testing. In the analysis phase, we scoped how much software we would automatically generate and created the initial interface. The design phase included parallel development of the HiFi simulation and the hand-coded flight software components. Everything came together in the test phase, in which the flight software was tested, using results from the HiFi simulation as one of the bases of comparison for testing. Because parts of the spacecraft HiFi simulation were converted into flight software, more care needed to be put into its development and configuration control to support both the HiFi simulation and flight software. The components of the HiFi simulation from which code was generated needed to be designed based on the fact that they would become flight software. This process involved such considerations as protecting against mathematical exceptions, using acceptable module and parameter naming conventions, and using an input/output interface compatible with the rest of the flight software. Maintaining good configuration control was an issue for the HiFi simulation and the flight software, and a way to track the two systems was devised. Finally, an integrated test approach was devised to support flight software testing at both the unit- and build-test levels using the HiFi simulation to generate data for performance verification. Another benefit of the simulation and code-generation application used on the MAP project is that it supported bringing flight software and test data into the HiFi simulation environment. It was possible to integrate parts of the hand-coded flight software into the HiFi simulation, and also possible to import flight software test data for comparison and performance verification. This capability was used to incorporate the flight software Kalman filter into the HiFi simulation. This enabled us to greatly increase the amount of testing that could be done on the filter, because we could exert a greater degree of control over the software-only simulation than over the flight software test environment. Also, since the simulation could be used to run the Kalman filter faster than real time, our testing efficiency was greatly increased. We will conclude our discussion with a summary of the lessons learned thus far using automatically- generated code for the MAP project, and the spacecraft status as we work towards our scheduled launch in the year 2000.
The Sensors 2000! Program, in support of the Space Life Sciences Payloads Office at NASA Ames Research Center developed a suite of bioinstrumentation hardware for use on the Joint US/Russian Bion I I Biosatellite Mission (December 24, 1996 - January 7, 1997). This spaceflight included 20 separate experiments that were organized into a complimentary and interrelated whole, and performed by teams of US, Russian, and French investigators. Over 40 separate parameters were recorded in-flight on both analog and digital recording media for later analysis. These parameters included; Electromyogram (7 ch), Electrogastrogram, Electrooculogram (2 ch), ECG/EKG, Electroencephlogram (2 ch), single fiber firing of Neurovestibular afferent nerves (7 ch), Tendon Force, Head Motion Velocity (pitch & yaw), P02 (in vivo & ambient), temperature (deep body, skin, & ambient), and multiple animal and spacecraft performance parameters for a total of 45 channels of recorded data. Building on the close cooperation of previous missions, US and Russian engineers jointly developed, integrated, and tested the physiologic instrumentation and data recording system. For the first time US developed hardware replaced elements of the Russian systems resulting in a US/Russian hybrid instrumentation and data system that functioned flawlessly during the 14 day mission.
We develop a case breach model for the on-board fault diagnostics and prognostics system for subscale solid-rocket boosters (SRBs). The model development was motivated by recent ground firing tests, in which a deviation of measured time-traces from the predicted time-series was observed. A modified model takes into account the nozzle ablation, including the effect of roughness of the nozzle surface, the geometry of the fault, and erosion and burning of the walls of the hole in the metal case. The derived low-dimensional performance model (LDPM) of the fault can reproduce the observed time-series data very well. To verify the performance of the LDPM we build a FLUENT model of the case breach fault and demonstrate a good agreement between theoretical predictions based on the analytical solution of the model equations and the results of the FLUENT simulations. We then incorporate the derived LDPM into an inferential Bayesian framework and verify performance of the Bayesian algorithm for the diagnostics and prognostics of the case breach fault. It is shown that the obtained LDPM allows one to track parameters of the SRB during the flight in real time, to diagnose case breach fault, and to predict its values in the future. The application of the method to fault diagnostics and prognostics (FD&P) of other SRB faults modes is discussed.
The approach of this task was to apply leading parallel computing research to a number of existing techniques for assimilation, and extract parameters indicating where and how input/output limits computational performance. The following was used for detailed knowledge of the application problems: 1. Developing a parallel input/output system specifically for this application 2. Extracting the important input/output characteristics of data assimilation problems; and 3. Building these characteristics s parameters into our runtime library (Fortran D/High Performance Fortran) for parallel input/output support.
The objective of the research was to develop a method to predict the weight of paper engines, i.e., engines that are in the early stages of development. The impetus for the project was the Single Stage To Orbit (SSTO) project, where engineers need to evaluate alternative engine designs. Since the SSTO is a performance driven project the performance models for alternative designs were well understood. The next tradeoff is weight. Since it is known that engine weight varies with thrust levels, a model is required that would allow discrimination between engines that produce the same thrust. Above all, the model had to be rooted in data with assumptions that could be justified based on the data. The general approach was to collect data on as many existing engines as possible and build a statistical model of the engines weight as a function of various component performance parameters. This was considered a reasonable level to begin the project because the data would be readily available, and it would be at the level of most paper engines, prior to detailed component design.
An automated image registration system such as that developed for LANDSAT-4 can produce all of the information needed to verify and calibrate the software and to evaluate system performance. The on-line MSS archive generation process which upgrades systematic correction data to geodetic correction data is described as well as the control point library build subsystem which generates control point chips and support data for on-line upgrade of correction data. The system performance was evaluated for both temporal and geodetic registration. For temporal registration, 90% errors were computed to be .36 IFOV (instantaneous field of view) = 82.7 meters) cross track, and .29 IFOV along track. Also, for actual production runs monitored, the 90% errors were .29 IFOV cross track and .25 IFOV along track. The system specification is .3 IFOV, 90% of the time, both cross and along track. For geodetic registration performance, the model bias was measured by designating control points in the geodetically corrected imagery.