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The goal of the Formal Inspection Program at the Jet Propulsion Laboratory (JPL) is to support projects wishing to use Formal Inspections to improve the quality of software and system level engineering products.
A thermal model of the Space Environments Complex (SEC) vacuum chamber and cryoshroud has been developed in support of upcoming thermal vacuum/thermal balance testing for Orion EM-1. The model was developed in Thermal Desktop and includes the vacuum chamber itself, a fluid model of the gaseous nitrogen flowing through the cryoshroud and the chamber piping, the Heat Flux System (HFS) within the cryoshroud, and the mechanical ground support equipment (MGSE) that interfaces with the vehicle. It has been correlated with steady state data from three tests. Two tests ran the cryoshroud in hot mode at 170 °F, and one test ran the cryoshroud in cold mode at -263 °F. Correlation was done using an optimization algorithm to find values of unknown contact conductances that minimized the RMS error between the model predictions and the test data. Overall, model quality was very good with a total RMS error of 2.6 °F.
Flight mission operations systems place human operators in demanding, high risk environments. The objective of Mission Operations and Command Assurance (MO&CA) is to help improve the operational reliability of flight projects by reducing error -- Pareto Analysis shows that the human is the largest error category. MO&CA is a system level task reporting to project flight management and JPL Systems Assurance Division. MO&CA provides direct transfer of knowledge, continuous process improvement, and communication facilitation.
A long-term program is in progress at JPL to reduce cost and risk of mission operations through defect prevention and error management. A major element of this program, Mission Operations and Command Assurance (MO&QA), provides a system level function on flight projects to instill quality in mission operations. MO&CA embodies the Total Quality Management (TQM) principle of Continuous Process Inprovement (CPI) and uses CPI in applying automation to mission operations to reduce risk and costs. MO&CA has led efforts to apply and has implemented automation in areas that impact the daily flight project environment including Incident Surprise Anomoly tracking and reporting; command data verification, tracking, and reporting; and command support data usage. MO&CA's future work in automation will take into account that future missions systems must be designed to avoid increasing error through the introduction of automation, while adapting to the demands of smaller flight teams.
Mission Operations and Command Assurance (MO&CA) is a Total Quality Management (TQM) task on JPL projects to instill quality in flight mission operations. From a system engineering view, MO&CA facilitates communication and problem-solving among flight teams and provides continuous process improvement to reduce risk in mission operations by addressing human factors. The MO&CA task has evolved from participating as a member of the spacecraft team to an independent team reporting directly to project management and providing system level assurance. JPL flight projects have benefited significantly from MO&CA's effort to contain risk and prevent rather than rework errors. MO&CA's ability to provide direct transfer of knowledge allows new projects to benefit from previous and ongoing flight experience.
A long-term program is in progress at JPL to reduce cost and risk of flight mission operations through a defect prevention/error management program. The main thrust of this program is to create an environment in which the performance of the total system, both the human operator and the computer system, is optimized. To this end, 1580 Incident Surprise Anomaly reports (ISA's) from 1977-1991 were analyzed from the Voyager and Magellan projects. A Pareto analysis revealed that 38 percent of the errors were classified as human errors. A preliminary cluster analysis based on the Magellan human errors (204 ISA's) is presented here. The resulting clusters described the underlying relationships among the ISA's. Initial models of human error in flight mission operations are presented. Next, the Voyager ISA's will be scored and included in the analysis. Eventually, these relationships will be used to derive a theoretically motivated and empirically validated model of human error in flight mission operations. Ultimately, this analysis will be used to make continuous process improvements continuous process improvements to end-user applications and training requirements. This Total Quality Management approach will enable the management and prevention of errors in the future.
An account is given of an updated AGK3 with improved proper motions derived from the Palomar 'Quick V' survey. It is judged that the astrometric potential of large-scale Schmidt plates can be realized via the subplate technique, followed by integration with the results of classical photographic astrometry. The new proper motions have a total 2D mean error of 0.82 arcsec/cy. Extensive quality-assurance double-checking has been performed at each stage of this work.
Mission Operations and Command Assurance (MO&CA), a recent addition to flight operations teams at JPL. provides a system level function to instill quality in mission operations. MO&CA's primary goal at JPL is to help improve the operational reliability for projects during flight. MO&CA tasks include early detection and correction of process design and procedural deficiencies within projects. Early detection and correction are essential during development of operational procedures and training of operational teams. MO&CA's effort focuses directly on reducing the probability of radiating incorrect commands to a spacecraft. Over the last seven years at JPL, MO&CA has become a valuable asset to JPL flight projects. JPL flight projects have benefited significantly from MO&CA's efforts to contain risk and prevent rather than rework errors. MO&CA's ability to provide direct transfer of knowledge allows new projects to benefit directly from previous and ongoing experience. Since MO&CA, like Total Quality Management (TQM), focuses on continuous improvement of processes and elimination of rework, we recommend that this effort be continued on NASA flight projects.
The Network Control Center (NCC) Project introduced the concept of total quality management (TQM) in mid-1990. The CSC project team established a program which focused on continuous process improvement in software development methodology and consistent deliveries of high quality software products for the NCC. The vision of the TQM program was to produce error free software. Specific goals were established to allow continuing assessment of the progress toward meeting the overall quality objectives. The total quality environment, now a part of the NCC Project culture, has become the foundation for continuous process improvement and has resulted in the consistent delivery of quality software products over the last three years.
Ways for determining optimum satellite and terrestrial system architectures and parameters for providing the most economical telephone service to remote areas of the U.S. are explored. Several configurations for an isolated rural telephone system, covering all the states plus Alaska, employing satellites is considered. Both direct-to-the-user and community-type of systems are evaluated using UHF and Ku-band RF equipment for the rural/satellite links. The effect of multiple spot beams, outage, signal quality, modulation method, satellite accessing, forward error correction, and the number of users are also evaluated. The total cost for a 5-minute call from an isolated rural user to a TELCO user was shown to be as low as $1.30 for a system with 1.8 X 10 to the sixth rural users.
This paper discusses two cross section interpolation methods commonly found in popular nodal codes; the partial derivatives and multiple tables models. The motivation for choosing a model, and thus a case matrix structure, is a trade off between accuracy and computational cost. Due to decades of experience, there are default structures that are sufficient for current light water reactor analysis. However, this is not necessarily the case for advanced reactor designs. Therefore, it is advantageous to understand the sources of error in cross section interpolation models so that the quality of a case matrix may be improved. A mathematical framework for these models is presented in this work that provides a more rigorous connection between the nuclear engineering field's cross section interpolation methods and the broader mathematical field of function approximation. The two cross section models examined in this paper were found to utilize Lagrange interpolation and are a subset of Lagrange tensor products. Classical results of Lagrange polynomial error analysis were then applied to the partial derivative and multiple tables models to derive expressions for the total point-wise error. The analytical results classify the total error into two parts: the model form error and interpolation error. Finally, based on our observations, a better foundation for improving the quality of a case matrix is proposed. (authors)
We use the full duration of collocated pixel-level MODIS-Terra and MISR aerosol optical thickness (AOT) retrievals and level 2 cloud-screened quality-assured AERONET measurements to evaluate the likely individual MODIS and MISR retrieval accuracies globally over oceans and land. We show that the use of quality-assured MODIS AOTs as opposed to the use of all MODIS AOTs has little effect on the resulting accuracy. The MODIS and MISR relative standard deviations (RSTDs) with respect to AERONET are remarkably stable over the entire measurement record and reveal nearly identical overall AOT performances of MODIS and MISR over the entire suite of AERONET sites. This result is used to evaluate the likely pixel-level MODIS and MISR performances on the global basis with respect to the (unknown) actual AOTs. For this purpose, we use only fully compatible MISR and MODIS aerosol pixels. We conclude that the likely RSTDs for this subset of MODIS and MISR AOTs are 73% over land and 30% over oceans. The average RSTDs for the combined [AOT(MODIS)+AOT(MISR)]/2 pixel-level product are close to 66% and 27%, respectively, which allows us to recommend this simple blend as a better alternative to the original MODIS and MISR data. These accuracy estimates still do not represent the totality of MISR and quality-assured MODIS pixel-level AOTs since an unaccounted for and potentially significant source of errors is imperfect cloud screening. Furthermore, many collocated pixels for which one of the datasets reports a retrieval, whereas the other one does not may also be problematic.
The Global Modeling and Assimilation Office (GMAO) observing system simulation experiment (OSSE) framework is used to explore the response of analysis error and forecast skill to observation quality. In an OSSE, synthetic observations may be created that have much smaller error than real observations, and precisely quantified error may be applied to these synthetic observations. Three experiments are performed in which synthetic observations with magnitudes of applied observation error that vary from zero to twice the estimated realistic error are ingested into the Goddard Earth Observing System Model (GEOS-5) with Gridpoint Statistical Interpolation (GSI) data assimilation for a one-month period representing July. The analysis increment and observation innovation are strongly impacted by observation error, with much larger variances for increased observation error. The analysis quality is degraded by increased observation error, but the change in root-mean-square error of the analysis state is small relative to the total analysis error. Surprisingly, in the 120 hour forecast increased observation error only yields a slight decline in forecast skill in the extratropics, and no discernable degradation of forecast skill in the tropics.
A long-term program is in progress at JPL to reduce cost and risk of mission operations through defect prevention and error management. A major element of this program, Mission Operations and Command Assurance (MO&CA), provides a system level function on flight projects to instill quality in mission operations. MO&CA embodies the total quality management TQM principle of continuous process improvement (CPI) and uses CPI in applying automation to mission operations to reduce risk and costs. MO&CA has led efforts to apply and has implemented automation in areas that impact the daily flight project work environment including Incident Surprise Anomaly tracking and reporting; command data verification, tracking and reporting; and command support data usage. MO&CA's future work in automation will take into account that future mission operations systems must be designed to avoid increasing error through the introduction of automation, while adapting to the demands of smaller flight teams.
A set of compressed, then reconstructed, test images submitted to the Comet Rendezvous Asteroid Flyby (CRAF)/Cassini project is presented as part of its evaluation of near lossless high compression algorithms for representing image data. A total of seven test image files were provided by the project. The seven test images were compressed, then reconstructed with high quality (root mean square error of approximately one or two gray levels on an 8 bit gray scale), using discrete cosine transforms or Hadamard transforms and efficient entropy coders. The resulting compression ratios varied from about 2:1 to about 10:1, depending on the activity or randomness in the source image. This was accomplished without any special effort to optimize the quantizer or to introduce special postprocessing to filter the reconstruction errors. A more complete set of measurements, showing the relative performance of the compression algorithms over a wide range of compression ratios and reconstruction errors, shows that additional compression is possible at a small sacrifice in fidelity.
Solid rocket motors (SRMs) typically use nozzle materials which are required to maintain their shape as well as insulate the underlying support structure during the motor operation. In addition, SRMs need internal insulation materials to protect the motor case from the harsh environment resulting from the combustion of solid propellant. In the nozzle, typical materials consist of high density graphite, carbon-carbon composites and carbon phenolic composites. Internal insulation of the motor cases is typically a composite material with carbon, asbestos, Kevlar, or silica fibers in an ablative matrix such as EPDM or NBR. For both nozzle and internal insulation materials, the charring process occurs when the hot combustion products heat the material intensely. The pyrolysis of the matrix material takes away a portion of the thermal energy near the wall surface and leaves behind a char layer. The fiber reinforcement retains the porous char layer which provides continued thermal protection from the hot combustion products. It is of great interest to characterize both the total erosion rates of the material and the char layer thickness. By better understanding of the erosion process for a particular ablative material in a specific flow environment, the required insulation material thickness can be properly selected. The recession rates of internal insulation and nozzle materials of SRMs are typically determined by testing in some sort of simulated environment; either arc-jet testing, flame torch testing, or subscale SRMs of different size. Material recession rates are deduced by comparison of pre- and post-test measurements and then averaging over the duration of the test. However, these averaging techniques cannot be used to determine the instantaneous recession rates of the material. Knowledge of the variation in recession rates in response to the instantaneous flow conditions during the motor operation is of great importance. For example, in many SRM configurations the recession of the solid propellant grain can drastically alter the flow-field and effect the recession of internal insulation and nozzle materials. Simultaneous measurement of the overall erosion rate, the development of the char layer, and the recession of the char-virgin interface during the motor operation can be rather difficult. While invasive techniques have been used with limited success, they have serious drawbacks. Break wires or make wire sensors can be installed into a sufficient number of locations in the charring material from which a time history of the charring surface can be deduced. These sensors fundamentally alter the local structure of the material in which they are imbedded. Also, the location of these sensors within the material is not known precisely without the use of an X-ray. To determine instantaneous recession rates, real-time X-ray radiography (X-ray RTR) has been utilized in several SRM experiments at PSU. The X-ray RTR system discussed in this paper consists of an X-ray source, X-ray image intensifier, and CCD camera connected to a capture computer. The system has been used to examine the ablation process of internal insulation as well as nozzle material erosion in a subscale SRM. The X-ray source is rated to 320 kV at 10 mA and has both a large (5.5 mm) and small (3.0 mm) focal spot. The lead-lined cesium iodide X-ray image intensifier produces an image which is captured by a CCD camera with a 1,000 x 1,000 pixel resolution. To produce accurate imagery of the object of interest, the alignment of the X-ray source to the X-ray image intensifier is crucial. The image sequences captured during the operation of an SRM are then processed to enhance the quality of the images. This procedure allows for computer software to extract data on the total erosion rate and the char layer thickness. Figure 1 Error! Reference source not found.shows a sequence of images captured during the operation the subscale SRM with the X-ray RTR system. The X-rayTR system, alignment procedure, uncertainty determination, and image analysis process will be discussed in detail in the full manuscript.
An improved 2.4-m photorefractor ocular screening system was tested and evaluated. The photorefractor system works on the principal of obtaining a colored photograph of both human eyes; and, by analysis of the retinal reflex images, certain ocular defects can be detected such a refractive error, strabismus, and lens obstructions. The 2.4-m photorefractory system uses a 35-mm camera with a telephoto lens and an electronic flash attachment. Retinal reflex images obtained from the new 2.4-m system are significantly improved over earlier systems in image quality. Other features were also improved, notably portability and reduction in mass. A total of 706 school age children were photorefracted, 211 learning disabled and 495 middle school students. The total students having abnormal retinal reflexes were 156 or 22 percent, and 133 or 85 percent of the abnormal had refractive error indicated. Ophthalmological examination was performed on 60 of these students and refractive error was verified in 57 or 95 percent of those examined. The new 2.4-m system has a NASA patent pending and is authorized by the FDA. It provides a reliable means of rapidly screening the eyes of children and young adults for vision problems. It is especially useful for infants and other non-communicative children who cannot be screened by the more conventional methods such as the familiar E chart.
Satellite measurements during the COVID-19 lockdowns that began in 2020 revealed unprecedented reductions in NO 2 tropospheric vertical column densities (VCD). These reductions have largely been attributed to reduced anthropogenic emissions associated with abrupt decreases in road traffic and other power consuming business activities. Although decreased emissions tended to be the main contributor to the observed NO 2 VCD reduction, meteorological variability also played a role. Whereas the observed VCD changes were predominantly negative in places where public health policies were strictly enforced, meteorology had both positive and negative effects over short time intervals. Here, we present results from a global study of the NO 2 reductions aimed at disentangling the meteorological and natural emission variability from the anthropogenic emissions over the world’s most populated megacities. For this study, NASA’s TROPOMI NO 2 algorithm was used in conjunction with the Global Modeling Initiative (GMI) chemical transport model to separate the contributions due emissions and meteorology. A priori NO 2 profiles were generated from two GMI simulations performed for 2020 at a resolution of 0.25° longitude x 0.25° latitude. The first simulation used updated, COVID-impacted NOX emissions based on Forster et al. (2020), while the second simulation used the 2019 emissions with the 2020 meteorology, referred to here as 2020BAU. The 2020BAU data set allowed for the decoupling of the emission component from the meteorology. When compared to the same period in 2019, NO 2 column amounts during the lockdowns were reduced in 35 out of 36 cities. While reduced emissions contributed most to the observed total change in NO 2 during the lockdowns, the effects of meteorology were significant, ranging between 40% (Chennai) and 15% (Beijing). In China, an increase in NO 2 levels due to meteorology were observed in five out of the seven cities considered in the study. Use of different a-priori NO 2 profiles from the two simulations in our TROPOMI retrievals allowed for a determination of retrieval errors that ranged from -1.7% to -11.0%. We used the quality assurance flag > 0.75 to select the highest quality scenes in the study period. Using the GMI, we estimated the sampling biases to be in the range -11% to 10% of the total change for the cities in our study.