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All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

Final Report on Portable Laser Coating Removal Systems Field Demonstrations and Testing

Processes currently used throughout the National Aeronautics and Space Administration (NASA) to remove corrosion and coatings from structures, ground service equipment and small components results in waste streams consisting of toxic chemicals, spent media blast materials, and waste water. When chemicals are used in these processes they are typically high in volatile organic compounds (VOC) and are considered hazardous air pollutants (HAP). When blast media is used, the volume of hazardous waste generated is increased significantly. Many of the coatings historically used within NASA contain toxic metals such as hexavalent chromium, and lead. These materials are highly regulated and restrictions on worker exposure continue to increase. Most recently the EPA reduced the permissible exposure limit (PEL) for hexavalent chromium. The new standard lowers OSHA's PEL for hexavalent chromium from 52 to 5 micrograms of Cr(V1) per cubic meter of air as an 8-hour time-weighted average. Hexavalent chromium is found in the pretreatment and primer coatings used within the Shuttle Program. In response to the need to continue to protect assets within the agency and the growing concern over these new regulations, NASA is researching different ways to continue the required maintenance of both facility and flight equipment in a safe, efficient and environmentally preferable manner. The use of laser energy to remove prepare surfaces for a variety of processes, such as corrosion and coating removal, weld preparation and non destructive evaluation is a relatively new technology that has shown itself to be environmentally preferable and in many cases less labor intensive than currently used removal methods. The development of a Portable Laser Coating Removal System (PLCRS) started as the goal of a Joint Group on Pollution Prevention (JG-PP) project, led by the Air Force, where several types of lasers in several configurations were thoroughly evaluated. Following this project, NASA decided to evaluate the best performers on processes and coatings specific to the agency. Laser systems used during this project were all of a similar design, most of which had integrated vacuum systems in order to collect materials removed from substrate surfaces during operation. Due to the fact that the technology lends itself to a bide variety of processes, several site demonstrations were organized in order to allow for greater evaluation of the laser systems across NASA. The project consisted of an introductory demonstration and a more in-depth evaluation at Wright-Patterson Air Force Base. Additionally, field demonstrations occurred at Glenn Research Center and Kennedy Space Center. During these demonstrations several NASA specific applications were evaluated, including the removal of coatings within Orbiter tile cavities and Teflon from Space Shuttle Main Engine gaskets, removal of heavy grease from Solid Rocket Booster components and the removal of coatings on weld lines for Shuttle and general ground service equipment for non destructive evaluation (NDE). In addition, several general industry applications such as corrosion removal, structural coating removal, weld-line preparation and surface cleaning were evaluated. This included removal of coatings and corrosion from surfaces containing lead-based coatings and applications similar to launch-structure maintenance and Crawler maintenance. During the project lifecycle, an attempt was made to answer process specific concerns and questions as they arose. Some of these initially unexpected questions concerned the effects lasers might have on substrates used on flight equipment including strength, surface re-melting, substrate temperature and corrosion resistance effects. Additionally a concern was PPE required for operating such a system including eye, breathing and hearing protection. Most of these questions although not initially planned, were fully explored as a part of this project. Generally the results from tesng were very positive. Corrosion was effectively removed from steel, but less successfully from aluminum alloys. Coatings were able to be removed, with varying results, generally dark, matte and thin coatings were easier to remove. Steel and aluminum panels were able to be cleaned for welding, with no known deleterious effects and weld-lines were able to have coatings removed in critical areas for NDE while saving time as compared to other methods.

Rothgeb, Matthew J.↗
NASA NTRS2008

Final Report on NASA Portable Laser Coating Removal Systems Field Demonstrations and Testing

Processes currently used throughout the National Aeronautics and Space Administration (NASA) to remove corrosion and coatings from structures, ground service equipment, small parts and flight components result in waste streams consisting of toxic chemicals, spent media blast materials, and waste water. When chemicals are used in these processes they are typically high in volatile organic compounds (VOC) and are considered hazardous air pollutants (HAP). When blast media is used, the volume of hazardous waste generated is increased significantly. Many of the coatings historically used within NASA contain toxic metals such as hexavalent chromium, and lead. These materials are highly regulated and restrictions on worker exposure continue to increase. Most recently the Occupational Safety and Health Administration (OSHA) reduced the permissible exposure limit (PEL) for hexavalent chromium (CrVI) from 52 to 5 micrograms per cubic meter of air as an 8-hour time-weighted average. Hexavalent chromium is found in numerous pretreatment and primer coatings used within the Space Shuttle Program. In response to the need to continue to protect assets within the agency and the growing concern over these new regulations, NASA is researching different ways to continue the required maintenance of both facility and flight equipment in a safe, efficient, and environmentally preferable manner. The use of laser energy to prepare surfaces for a variety of processes, such as corrosion and coating removal, weld preparation, and non destructive evaluation (NDE) is a relatively new application of the technology that has been proven to be environmentally preferable and in many cases less labor intensive than currently used removal methods. The novel process eliminates VOCs and blast media and captures the removed coatings with an integrated vacuum system. This means that the only waste generated are the coatings that are removed, resulting in an overall cleaner process. The development of a Portable Laser Coating Removal System (PLCRS) started as the goal of a Joint Group on Pollution Prevention (JG-PP) project, led by the Air Force, where several types of lasers in several configurations were thoroughly evaluated. Following this project, NASA decided to evaluate the best performers on processes and coatings specific to the agency. Laser systems used during this project were all of a similar design, between 40 and 500 Watts, most of which had integrated vacuum systems in order to collect materials removed from substrate surfaces during operation.

Rothgeb, Matthew J↗
NASA NTRS2007

Monitoring by Use of Clusters of Sensor-Data Vectors

The inductive monitoring system (IMS) is a system of computer hardware and software for automated monitoring of the performance, operational condition, physical integrity, and other aspects of the health of a complex engineering system (e.g., an industrial process line or a spacecraft). The input to the IMS consists of streams of digitized readings from sensors in the monitored system. The IMS determines the type and amount of any deviation of the monitored system from a nominal or normal ( healthy ) condition on the basis of a comparison between (1) vectors constructed from the incoming sensor data and (2) corresponding vectors in a database of nominal or normal behavior. The term inductive reflects the use of a process reminiscent of traditional mathematical induction to learn about normal operation and build the nominal-condition database. The IMS offers two major advantages over prior computational monitoring systems: The computational burden of the IMS is significantly smaller, and there is no need for abnormal-condition sensor data for training the IMS to recognize abnormal conditions. The figure schematically depicts the relationships among the computational processes effected by the IMS. Training sensor data are gathered during normal operation of the monitored system, detailed computational simulation of operation of the monitored system, or both. The training data are formed into vectors that are used to generate the database. The vectors in the database are clustered into regions that represent normal or nominal operation. Once the database has been generated, the IMS compares the vectors of incoming sensor data with vectors representative of the clusters. The monitored system is deemed to be operating normally or abnormally, depending on whether the vector of incoming sensor data is or is not, respectively, sufficiently close to one of the clusters. For this purpose, a distance between two vectors is calculated by a suitable metric (e.g., Euclidean distance) and "sufficiently close" signifies lying at a distance less than a specified threshold value. It must be emphasized that although the IMS is intended to detect off-nominal or abnormal performance or health, it is not necessarily capable of performing a thorough or detailed diagnosis. Limited diagnostic information may be available under some circumstances. For example, the distance of a vector of incoming sensor data from the nearest cluster could serve as an indication of the severity of a malfunction. The identity of the nearest cluster may be a clue as to the identity of the malfunctioning component or subsystem. It is possible to decrease the IMS computation time by use of a combination of cluster-indexing and -retrieval methods. For example, in one method, the distances between each cluster and two or more reference vectors can be used for the purpose of indexing and retrieval. The clusters are sorted into a list according to these distance values, typically in ascending order of distance. When a set of input data arrives and is to be tested, the data are first arranged as an ordered set (that is, a vector). The distances from the input vector to the reference points are computed. The search of clusters from the list can then be limited to those clusters lying within a certain distance range from the input vector; the computation time is reduced by not searching the clusters at a greater distance.

Iverson, David L.↗
NASA NTRS1992

Deep near-infrared survey of the Southern Sky (DENIS)

DENIS (Deep Near-Infrared Survey of the Southern Sky) will be the first complete census of astronomical sources in the near-infrared spectral range. The challenges of this novel survey are both scientific and technical. Phenomena radiating in the near-infrared range from brown dwarfs to galaxies in the early stages of cosmological evolution, the scientific exploitation of data relevant over such a wide range requires pooling expertise from several of the leading European astronomical centers. The technical challenges of a project which will provide an order of magnitude more sources than given by the IRAS space mission, and which will involve advanced data-handling and image-processing techniques, likewise require pooling of hardware and software resources, as well as of human expertise. The DENIS project team is composed of some 40 scientists, computer specialists, and engineers located in 5 European Community countries (France, Germany, Italy, The Netherlands, and Spain), with important contributions from specialists in Australia, Brazil, Chile, and Hungary. DENIS will survey the entire southern sky in 3 colors, namely in the I band at a wavelength of 0.8 micron, in the 1.25 micron J band, and in the 2.15 micron K' band. The sensitivity limits will be 18th magnitude in the I band, 16th in the J band, and 14.5th in the K' band. The angular resolution achieved will be 1 arcsecond in the I band, and 3.0 arcseconds in the J and K' bands. The European Southern Observatory 1 m telescope on La Silla will be dedicated to survey use during operations expected to last four years, commencing in late 1993. DENIS aims to provide the astronomical community with complete digitized infrared images of the full southern sky and a catalogue of extracted objects, both of the best quality and in readily accessible form. This will be achieved through dedicated software packages and specialized catalogues, and with assistance from the Leiden and Paris Data Analysis Centers. The data will be mailed on DAT tapes from La Silla to the two Data Analysis Centers for further processing. Two centers are necessary because of the shear quantity of data and because of the complementary roles the Centers will develop, each exploiting its own particular expertise. The Leiden Data Analysis Center (LDAC) will extract objects, establish their parameters, and archive them into a source catalogue. The LDAC will collaborate with the Groningen Space Research group that has gained experience in infrared image handling from the IRAS satellite. The Paris Data Analysis Center (PDAC) will be responsible for archiving and preprocessing the raw data to provide a homogeneous set of data suitable for further reduction in both the Leiden and Paris data analysis streams. The PDAC will also extract and archive images for the sources flagged by the LDAC as extended, and create a catalogue of galaxies. In exploiting the DENIS data we foresee the collaboration with other data analysis centers, such as the Observatoire de Lyon where the relevant DENIS catalogue of galaxies can be incorporated into their extragalactic database. The Point Sources and the Small Extended Sources catalogues could be incorporated in the Late Type Star database at Montpellier, and in the SIMBAD database as CDS. At Groningen the IRAS Point Source catalogue and/or image data can be merged with the DENIS catalogues. At Meudon algorithms and software will be developed with main goal assessing the limits reachable for the homogeneity and intrinsic consistency between the ensemble of the images in the data base (flat-fielding, relative positioning of the fields, bootstrapped flux calibration) but also for the data analysis.

Deul, E.↗