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Report describes application of generalized control algorithm for automatic robotic arc welding in vertical-up configuration. Applicable to variety of welding processes, previously applied to welding in downhand configuration. Generalized algorithm and application to downhand welding described in "Method for Automatic Downhand Welding" (MFS-27209).
The goal of this research effort is to develop an integrated control software environment for the purpose of creating an intelligent neurocontrol system. The system will be capable of estimating states, identifying parameters, diagnosing conditions, planning control strategies, and producing intelligent control actions. The distinct features of such control system are adaptability and on-line learning capability. The proposed system will be flexible to allow structure adaptability to account for changes in the dynamic system such as sensory failures and/or component degradations. The developed system should learn system uncertainties and changes, as they occur, while maintaining minimal control level on the dynamic system. The research activities set to achieve the research objective are summarized by the following general items: (1) Development of a system identifier or diagnostic system; (2) Development of a robust neurocontroller system, and; (3) Integration of above systems to create a robust Integration Control system (RIC-system). Two contrary approaches are investigated in this research: classical (traditional) design approach, and the simultaneous design approach. However, in both approaches neural network is the base for the development of different functions of the system. The two resulting designs will be tested and simulation results will be compared for better possible implementation.
The goal of this research effort is to develop an integrated control software environment for the purpose of creating an intelligent neurocontrol system. The system will be capable of estimating states, identifying parameters, diagnosing conditions, planning control strategies, and producing intelligent control actions. The distinct features of such control system are: adaptability and on-line learning capability. The proposed system will be flexible to allow structure adaptability to account for changes in the dynamic system such as: sensory failures and/or component degradations. The developed system should learn system uncertainties and changes, as they occur, while maintaining minimal control level on the dynamic system. The research activities set to achieve the research objective are summarized by the following general items: (1) Development of a system identifier or diagnostic system, (2) Development of a robust neurocontroller system, and 3. Integration of above systems to create a Robust Integrated Control system (RIC-system). Two contrary approaches are investigated in this research: classical (traditional) design approach, and the simultaneous design approach. However, in both approaches neural network is the base for the development of different functions of the system. The two resulting designs will be tested and simulation results will be compared for better possible implementation.
During this decade, NASA is charged to return humans to the surface of the Moon. One of the most challenging aspects to operating on the lunar surface is the regolith present, which is pervasive and damaging. To support systems design and validation for this environment, the handling and application of lunar simulants onto test articles or systems becomes important, albeit difficult. A device to apply the same amount of dust uniformly was developed in a previous study (Hollingsworth et al., 2006) but was only utilized with Mars dust simulant during that previous project. The current work provides evaluation of this device with multiple lunar simulants, each representing different composition as found at various locations on the Moon’s surface. Enhancements to the design and operation of the dust distributor are also described, along with a new digital imaging technique to calculate the percent surface coverage of the dust after deposition. The results support the use of the distributor and improved techniques to provide a uniform coating of dust on test articles and systems.
During this decade, NASA is charged to return humans to the surface of the Moon. One of the most challenging aspects to operating on the lunar surface is the regolith present, which is pervasive and damaging. To support systems design and validation for this environment, the handling and application of lunar simulants onto test articles or systems becomes important, albeit difficult. A device to apply the same amount of dust uniformly was developed in a previous study but was only utilized with Mars dust simulant during that previous project. The current work provides evaluation of this device with multiple lunar simulants, each representing different composition as found at various locations on the Moon’s surface. Enhancements to the design and operation of the dust distributor are also described, along with a new digital imaging technique to calculate the percent surface coverage of the dust after deposition. The results support the use of the distributor and improved techniques to provide a uniform coating of dust on test articles and systems.
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We report the test results for a 120 GeV proton beam incident on superconducting nanowire particle detectors of various wire sizes. NbN devices with the same sensitive area were fabricated with different wire widths and tested at a temperature of 3 K. The relative detection efficiency was extracted from bias current scans for each device. The results demonstrate efficient detection of high energy protons for wire widths less than 400 nm. These results are particularly relevant for novel applications at accelerator facilities, such as the Electron-Ion Collider, where cryogenic cooling is readily available.