Basic processes occurring in gaseous plasmas in various charge density and energy states Final report
Sensitive laser diagnostic procedures and properties of gaseous plasmas at various charge densities and energy states
SEARCH · Engineering Papers
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Sensitive laser diagnostic procedures and properties of gaseous plasmas at various charge densities and energy states
The investigation conducted at the Tennessee Valley Authority's Sequoyah Nuclear Power Plant to determine and correct increasing vibrations in the vertical reactor coolant pumps is described. Diagnostic procedures to determine the vibration causes and evaluate the corrective measures taken are also described.
Analytic differential emission measure distributions have been derived for coronal plasma in flare loops heated both by collisions of high-energy suprathermal electrons with background plasma, and by ohmic heating by the beam-normalizing return current. For low densities, reverse current heating predominates, while for higher densities collisional heating predominates. There is thus a minimum peak temperature in an electron-heated loop. In contrast to previous approximate analyses, it is found that a stable reverse current can dominate the heating rate in a flare loop, especially in the low corona. Two 'scaling laws' are found which relate the peak temperature in the loop to the suprathermal electron flux. These laws are testable observationally and constitute a new diagnostic procedure for examining modes of energy transport in flaring loops.
Automatic failure-cause diagnosis is a key element in autonomous operation of space power systems such as Space Station's. A rule-based diagnostic system has been developed for determining the cause of degraded performance. The knowledge required for such diagnosis is elicited from the system engineering process by using traditional failure analysis techniques. Symptoms, failures, causes, and detector information are represented with structured data; and diagnostic procedural knowledge is represented with rules. Detected symptoms instantiate failure modes and possible causes consistent with currently held beliefs about the likelihood of the cause. A diagnosis concludes with an explanation of the observed symptoms in terms of a chain of possible causes and subcauses.
This paper reports on an in situ silicon deposition process diagnostics, using CARS performed at state-of-the-art a-Si:H film deposition conditions in a reactor designed for a-Si:H solar cell fabrication. The diagnostics procedure measures the silane depletion in an RF plasma as a function of the silane flow rate (where the relationship is linear between 50-percent depletion, at a flow rate of 5.6 sccm, and about 8-percent depletion, at 80 sccm) and the RF power (where the silane depletion is linearly dependent on the RF power in the region of 4 to 12 W). The linear RF power dependence of the silane depletion is considered to be consistent with the mechanism of silane decomposition primarily by electron impact dissociations, while the flow rate dependence is interpreted in terms of the residence time of the SiH4 molecules in the glow discharge region, where an increase of the residence time at a low flow rate results in a high depletion ratio.
The work performed under Contracts NAS3-23929 and NAS3-24633 is presented. MTI evaluated the feasibility of high-speed balancing for both the T700 power turbine rotor and the compressor rotor. Modifications were designed for the existing Corpus Christi Army Depot (CCAD) T53/T55 high-speed balancing system for balancing T700 power turbine rotors. Tests conducted under these contracts included a high-speed balancing evaluation for T700 power turbines in the Army/NASA drivetrain facility at MTI. The high-speed balancing tests demonstrated the reduction of vibration amplitudes at operating speed for both low-speed balanced and non-low-speed balanced T700 power turbines. In addition, vibration data from acceptance tests of T53, T55, and T700 engines were analyzed and a vibration diagnostic procedure developed.
The paper presents an approach to the implementation of an automated satellite diagnosis capability which emphasizes techniques offering flexibility in the application of diagnostic strategies. The system utilizes a structural and behavioral model of the satellite; it uses a form of spreading activation to perform the diagnostic procedures on the model. A Dempster-Shafer evidential framework was implemented, making it possible to integrate evidence from the multiple sources necessary for building useful systems.
Two years ago Dr. Sherrie Gott of the Air Force Human Resources Laboratory described an avionics troubleshooting tutor being developed under the Basic Job Skills Research Program. The tutor, known as Sherlock, is directed at teaching the diagnostic procedures necessary to investigate complex test equipment used to maintain F-15 fighter aircraft. Since Dr. Gott's presentation in 1987, the tutor has undergone field testing at two Air Force F-15 flying wings. The results of the field test showed that after an average of 20 hours on the tutor, the 16 airmen in the experimental group (who average 28 months of experience) showed significant performance gains when compared to a control group (having a mean experience level of 37 months) who continued participating in the existing on-the-job training program. Troubleshooting performance of the tutored group approached the level of proficiency of highly experienced airmen (averaging approximately 114 months of experience), and these performance gains were confirmed in delayed testing six months following the intervention. The tutor is currently undergoing a hardware and software conversion form a Xerox Lisp environment to a PC-based environment using an object-oriented programming language. Summarized here are the results of the successful field test. The focus is on: (1) the instructional features that contributed to Sherlock's success; and (2) the implementation of these features in the PC-based version of the avionics troubleshooting tutor.
The sources of sub-Saharan precipitation are studied using diagnostic procedures integrated into the code of the GISS climate model. Water vapor evaporating from defined source regions is 'tagged', allowing the determination of the relative contributions of each evaporative source to the simulated July rainfall in the Sahel. Two June-July simulations are studied to compare the moisture sources, moisture convergence patterns and the spatial variations of precipitation for rainy and drought conditions. Results for this case study indicate that patterns of moisture convergence and divergence over northern Africa had a stronger influence on model rainfall over the sub-Sahara than did evaporation rates over the adjacent oceans or moisture advection from ocean to continent. While local continental evaporation contributed significant amounts of water to Sahelian precipitation in the'rainy' simulation, moisture from the Indian Ocean did not precipitate over the Sahel in either case.
The paper is an operating manual for the Dynamic Stability Instrumentation System in specific NASA Langley wind tunnels. The instrumentation system performs either a synchronous demodulation or a Fast Fourier Transform on dynamic balance strain gage signals, and ultimately computes aerodynamic coefficients. The dynamic balance converts sting motor rotation into pitch or yaw plane or roll axis oscillation, with timing information provided by a shaft encoder. Additional instruments control model attitude and balance temperature and monitor sting vibrations. Other instruments perform self-calibration and diagnostics. Procedures for conducting calibrations and wind-off and wind-on tests are listed.
During the period covered by this report, the PI has contributed in an advisory capacity to various aspects of the evaluation of the nature run, including the development of research plans, the derivation of diagnostic procedures, and the interpretation of the results of the evaluation. Computing and data analysis have been performed by Dr. Jusem in consultation with Dr. Atlas. The PI's contribution to this effort has been rendered primarily by means of scheduled biweekly phone discussions with Dr. Jusem, supplemented by electronic mailings and postings on the Web.
This presentation discusses an approach to estimate model error using observation residuals. Based on the sequential fixed-lag smoother; we introduce a diagnostic procedure to allow estimating model error over a dense observing system. Optimality considerations are examined in light of the sequential results. The procedure is re-interpreted in the language of variational assimilation, such as 4d-Var. Illustrations of the approach are given by studying both identical-twin and fraternal-twin experimental settings for a system governed by Lorenz-type dynamics. Preliminary results by looking at observation residual statistics for the ECMWF data assimilation system are also shown. The presentation will be part of a series of discussions on issues related to four-dimensional data assimilation under weak-constraint and methodologies to estimate model error.
The U.S. medical community depends on a reliable supply of the radioisotope molybdenum-99 (Mo-99) for nuclear medical diagnostic procedures. Mo-99's decay product, technetium-99m (Tc-99m), is used in over 40,000 medical procedures in the United States each day to diagnose heart disease and cancer, to study organ structure and function, and to perform other important medical applications. For example, patients undergoing a common procedure—the cardiac “stress test”—likely have benefited from Tc-99m. Historically, Mo-99 was primarily produced through the fission of uranium-235, in the form of highly enriched uranium (HEU) targets irradiated in research and test reactors. HEU is a proliferation-sensitive material that, if diverted or stolen, could be used as a component of a nuclear weapon. NNSA’s Office of Material Management and Minimization (M3) manages the Molybdenum-99 (Mo-99) Program as part of its mission to minimize the use of HEU in civilian applications. The Mo-99 Program assists global Mo-99 production facilities in converting to non-HEU processes and supports the establishment of domestic supplies of Mo-99 without the use of proliferation-sensitive HEU. As part of this program, M3 funds U.S. national laboratories to provide non-proprietary technical support to U.S. companies working to establish non-HEU-based Mo-99 production capabilities. The results of this research are published on OSTI.gov for the benefit of the Mo-99 community and the public. However, it can be difficult for readers without a scientific background to understand and interpret these publications. In order to increase public understanding of the work being done in M3’s Mo-99 Program, this paper aims to provide an overview of a key, recent national laboratory technical publication in terms that can be understood by readers without a technical background. To accomplish this, the paper first explains key scientific concepts—primarily related to chemistry—that provide a foundation for understanding research in this area. This includes chromatography, absorption vs. adsorption, dissolution and precipitation, and liquid-liquid extraction. Drawing on these concepts, the paper then provides an explanation for non-technical audiences of the Argonne National Laboratory publication entitled Recovery of High Specific Activity Molybdenum-99 from Accelerator-Induced Fission on Low-Enriched Uranium for Technetium-99m Generators (Brown, M.A. et al., 2021) and related article Separation and Purification of Mo-99 Produced from Natural U3O8 Targets via Photo-Fission (Brown, M.A. et al., 2021).
Radioisotopes play a vital role in nuclear medicine, enabling the performance of diagnostic procedures such as Positron Emission Tomography (PET) and Single Photon Emission Computed Tomography (SPECT), in addition to innovative targeted therapies for selectively delivering cytotoxic radiation doses to tumor cells while minimizing damage to healthy tissue [1]. Beta emitting radionuclides such as 90Y and 131I find wide use in radio-immunotherapy, with the radiopharmaceuticals 90Y-ibritumomab tiuxetan (Zevalin®) and 131I-tositumomab (Bexxar®) having received FDA approval for treatment of non-Hodgkin’s lymphoma through targeting the CD20 surface receptor, which is commonly expressed in many B cell non-Hodgkin’s lymphoma subtypes [2, 3]. 90Y has also been successfully applied for treatment of brain tumors [4, 5] and liver cancer [6]. The favorable chelation chemistry of 90Y enables its use with a variety of ligands for the development of radiopharmaceuticals suitable for targeting different carcinoma types [1].
The design, development, and operation of complex space, lunar and planetary exploration systems require the development of general procedures that describe a detailed set of instructions capturing how mission tasks are performed. For both crewed and uncrewed NASA systems, mission safety and the accomplishment of the scientific mission objectives are highly dependent on the correctness of procedures. In this paper, we describe how to use the auto-generated diagnostic trees from existing diagnostic models to improve the verification of standard operating procedures. Specifically, we introduce a systematic method, namely the Diagnostic Tree for Verification (DTV), developed with the goal of leveraging the information contained within auto-generated diagnostic trees in order to check the correctness of procedures, to streamline the procedures in terms of reducing the number of steps or use of resources in them, and to propose alternative procedural steps adaptive to changing operational conditions. The application of the DTV method to a spacecraft electrical power system shows the feasibility of the approach and its range of capabilities
The authors propose a new procedure, designated the adjoint-based genesis diagnostic (AGD) procedure, for studying triggering mechanisms and the subsequent genesis of the synoptic phenomena of interest. This procedure makes use of a numerical model sensitivity to initial conditions and the nonlinear evolution of the initial perturbations that are designed using this sensitivity. The model sensitivity is evaluated using the associated adjoint model. This study uses the dry version of the National Center for Atmospheric Research Mesoscale Adjoint Modeling System (MAMS) for the numerical experiments. The authors apply the AGD procedure to two cases of Alpine lee cyclogenesis that were observed during the Alpine Experiment special observations period. The results show that the sensitivity fields that are produced by the adjoint model and the associated initial perturbations are readily related to the probable triggering mechanisms for these cyclones. Additionally, the nonlinear evolution of these initial perturbations points toward the physical processes involved in the lee cyclone formation. The AGD experiments for a weak cyclone case indicate that the MAMS forecast model has an underrepresented topographic forcing due to the sigma vertical coordinate and that this model error can be compensated by adjustments in the initial conditions that are related to the triggering mechanisms, which is not associated with the topographic blocking mechanism.
Voltage taps remain the standard and reliable diagnostic tool for detecting quenches in superconducting magnets. However, they identify a quench only at the time of voltage rise and do not provide information on earlier physical precursors. In this work, we investigate whether acoustic emission data can reveal precursor activity that occurs before conventional voltage detection using machine learning techniques. We introduce an event selection method and a weakly supervised machine learning procedure to learn data-driven criteria for identifying potential acoustic precursors to quenches. Two Convolutional Neural Network (CNN) architectures are trained: one on acoustic sensor events from our selection procedure and one on the Fast Fourier Transforms (FFTs) of these events. Both networks are trained iteratively using confidence-weighted loss functions to associate certain subsets of training data with a precursor label. We evaluate the performance of these models by examining the time distribution of events classified as potential precursors relative to the quench onset. Results indicate that the proposed approach can possibly distinguish acoustic emission events occurring closer to the quench from earlier acoustic activity during ramping, suggesting the potential for flagging quench precursors in acoustic data.