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The JPL has designed and built a plume contamination monitoring package to be installed on a NOAA environmental services satellite. The package is designed to monitor any condensible contamination that occurs during the ignition and burn of a TE-M-364-15 apogee kick motor. The instrumentation and system interface are described, and attention is given to preflight analysis and test.
A remote-sensing experiment conducted on May 17, 1977, over the Surry nuclear power station on the James River, Virginia is discussed. Isotherms of the thermal plume from the power station were derived from remotely sensed data and compared with in situ water temperature measurements provided by the Virginia Electric and Power Company, VEPCO. The results of this study were also qualitatively compared with those from other previous studies under comparable conditions of the power station's operation and the ambient flow. These studies included hydraulic model predictions carried out by Pritchard and Carpenter and a 5-year in situ monitoring program based on boat surveys.
Two optical sensors developed in UW-Madison labs were evaluated for their potential to characterize rocket engine exhaust plumes and liquid oxygen (LOX) fluid properties. The plume sensor is based on wavelength-agile absorption spectroscopy A device called a chirped white pulse emitter (CWPE) is used to generate the wavelength agile light, scanning, for example, 1340 - 1560 nm every microsecond. Properties of the gases in the rocket plume (for example temperature and water mole fraction) can be monitored using these wavelength scans. We have performed preliminary tests in static gas cells, a laboratory GOX/GH2 thrust chamber, and a solid-fuel hybrid thrust chamber, and these initial tests demonstrate the potential of the CWPE for monitoring rocket plumes. The LOX sensor uses an alternative to wavelength agile sensing: two independent, fixed-wavelength lasers are combined into a single fiber. One laser is absorbed by LOX and the other not: by monitoring the differential transmission the LOX concentration in cryogenic feed lines can be inferred. The sensor was successful in interrogating static LOX pools in laboratory tests. Even in ice- and bubble-laden cryogenic fluids, LOX concentrations were measured to better than 1% with a 3 microsec time constant.
Preliminary analyses of ERTS-1 imagery demonstrates the utility of the satellite to monitor turbidity plumes generated by the Welland Canal, and the Genese and Oswego Rivers. Although visible in high altitude photographs, the Niagara River plume is not readily identifiable from satellite imagery.
Stennis Space Center (SSC) is pursuing the advancement of experimental techniques and theoretical developments in the field of plume spectroscopy for application to rocket development testing programs and engine health monitoring. Exhaust plume spectral data for the Space Shuttle Main Engine (SSME) are routinely acquired. The usefulness of this data depends upon qualitative and quantitative interpretation of spectral features and their correlation with the engine performance. A knowledge of the emission spectral characteristics of effluent materials in the exhaust plume is essential. A study of SSME critical components and their materials identified 30 elements and 53 materials whose engine exhaust plume spectral might be required. The most important were evaluated using SSC's Diagnostic Testbed Facility Thruster (DTFT), a 1200-lbf, liquid oxygen/gaseous hydrogen rocket engine which very nearly replicates the temperature and pressure conditions of the SSME exhaust plume in the first Mach diamond. This report presents the spectral data for the 10 most important elements and 27 most important materials which are strongly to moderately emitting in the DTFT exhaust plume. The covered spectral range is 300 to 426 nm and the spectral resolution is 0.25 nm. Spectral line identification information is provided and line interference effects are considered.
The UV-Vis spectroscopic system for plume diagnostics monitors rocket engine health by using several analytical tools developed at Stennis Space Center (SSC), including the rocket plume spectroscopy simulation code (RPSSC), to identify and quantify the alloys from the metallic elements observed in engine plumes. Because the hydrocarbon-fueled rocket engine is likely to contain C2, CO, CH, CN, and NO in addition to OH and H2O, the relevant electronic bands of these molecules in the spectral range of 300 to 850 nm in the RPSSC have been included. SSC incorporated several enhancements and modifications to the original line-by-line spectral simulation computer program implemented for plume spectral data analysis and quantification in 1994. These changes made the program applicable to the Space Shuttle Main Engine (SSME) and the Diagnostic Testbed Facility Thruster (DTFT) exhaust plume spectral data. Modifications included updating the molecular and spectral parameters for OH, adding spectral parameter input files optimized for the 10 elements of interest in the spectral range from 320 to 430 nm and linking the output to graphing and analysis packages. Additionally, the ability to handle the non-uniform wavelength interval at which the spectral computations are made was added. This allowed a precise superposition of wavelengths at which the spectral measurements have been made with the wavelengths at which the spectral computations are done by using the line-by-line (LBL) code. To account for hydrocarbon combustion products in the plume, which might interfere with detection and quantification of metallic elements in the spectral region of 300 to 850 nm, the spectroscopic code has been enhanced to include the carbon-based combustion species of C2, CO, and CH. In addition, CN and NO have spectral bands in 300 to 850 nm and, while these molecules are not direct products of hydrocarbon-oxygen combustion systems, they can show up if nitrogen or a nitrogen compound is present as an impurity in the propellants and/or these can form in the boundary layer as a result of interaction of the hot plume with the atmosphere during the ground testing of engines. Ten additional electronic band systems of these five molecules have been included into the code. A comprehensive literature search was conducted to obtain the most accurate values for the molecular and the spectral parameters, including Franck-Cordon factors and electronic transition moments for all ten band systems. For each elemental transition in the RPSSC, six spectral parameters - Doppler broadened line width at half-height, pressure-broadened line width at half-height, electronic multiplicity of the upper state, electronic term energy of the upper state, Einstein transition probability coefficient, and the atomic line center - are required. Input files have been created for ten elements of Ni, Fe, Cr, Co, Cu, Ca, Mn, Al, Ag, and Pd, which retain only relatively moderate to strong transitions in 300 to 430 nm spectral range for each element. The number of transitions in the input files is 68 for Ni; 148 for Fe; 6 for Cr; 87 for Co; 1 for Ca; 3 for Mn; 2 each for Cu, Al, and Ag; and 11 for Pd.
The method of silhouettes proceeds from the premise that the 3D location and shape of an arbitrary object can be approximated via the cross section of a series of conical volumes whose focal points are arranged at sites surrounding the object; the projection of each conical volume onto a picture plane at each focal point is identical to a projection of the outline of the object onto that picture plane. Attention is presently given to the use of the silhouettes method for gas plume dispersion monitoring through the 3D reconstruction of plumes from imagery acquired at strategically located stations in the plumes' path.
The main purpose of this research is to study the spreading of the 2020 wildfire plumes in the San Francisco Bay Area. Last year’s fire plumes have caused severe impact on regional air quality and public health over large part of the west coast. We studied fire plumes with two datasets: aerosol optical depth (AOD) retrieved from MODIS sensor onboard two NASA satellites (Terra and Aqua), and surface PM2.5 measurements from US EPA. Satellite can monitor fire plumes from a top-down view, including active fire location, emission amount, spreading of the fire plume in both horizontal and vertical directions. EPA records air quality using the ground network of in-situ sensors. In general the two points of view are consistent with each other. But in the peak of the 2020 fire season, we found an episode where the AOD and PM2.5 are out-of-phase for two days. We explored the possible mechanism for this shift with available meteorological measurements, including both ground measurements and sounding data. By tracking the evolution of the sounding data, we concluded a heated near surface inversion layer might shield the region from aloft fire plumes for two days before they touch down and severely downgraded the air quality over the whole Bay area.
Determination of the elemental composition of lunar, asteroid, and planetary surfaces is a major concern for science and resource utilization of space. The science associated with the development of a satellite or lunar rover laser-mass spectrometer instrument is presented here. The instrument would include a pulsed laser with sufficient energy to create a plasma on a remote surface. Ions ejected from this plasma travel back to the spacecraft or rover, where they are analyzed by a time-of-flight mass spectrometer, giving the elemental and isotope composition. This concept is based on the LIMA-D instrument on board the former Soviet Union Phobos-88 spacecraft sent to Mars. A laser-mass spectrometer placed on a rover or satellite would substantially improve the data return over alternative techniques. The spatial resolution would be centimeters, and a complete mass spectrum could be achieved in one laser shot. An experiment is described that demonstrates these features. A 400 mj Nd:YAG laser is focused, to an intensity of 10(exp 11) w/sq cm, onto a Al, Ag, Cu, Ge, or lunar simulant target. A plasma forms from which ions are ejected. Some of these ions travel down an 18-m evacuated flight tube to a microchannel plate detector. Alternatively, the ions are captured by an ion trap where they are stored until pulsed into a 1-m time-of-flight mass spectrometer, giving the elemental composition of the remote surface. A television camera monitors the plasma plume shape, and a photodiode monitors the temporal plasma emission . With this system, ions of Al, Ag, Cu, Ge, and lunar simulant have been detected at 18 m. The mass spectrum from the ion trap and 1-m time-of-flight tube will be presented.
The main purpose of this research is to study the spreading of the 2020 wildfire plumes in the San Francisco Bay Area. Last year’s fire plumes have caused severe impact on regional air quality and public health over large part of the west coast. We studied fire plumes with two datasets: aerosol optical depth (AOD) retrieved from MODIS sensor onboard two NASA satellites (Terra and Aqua), and surface PM2.5 measurements from US Environmental Protection Agency (EPA). Satellite can monitor fire plumes from a top-down view, including active fire location, emission amount, spreading of the fire plume in both horizontal and vertical directions. EPA records air quality using the ground network of in-situ sensors. In general, the two points of view are consistent with each other. But in the peak of the 2020 fire season, we found an episode where the AOD and PM2.5 are out-of-phase for two days, in addition data from NASA satellite AERONET was use to corroborate AOD information for the episode, yielding similar results. Thereafter, we explored the possible mechanism for this shift with available meteorological measurements, including both ground measurements and sounding data. By tracking the evolution of the sounding data, we concluded a heated near surface inversion layer might shield the region from aloft fire plumes for two days before they touch down and severely downgraded the air quality over the whole Bay area.
Federal and state laws require the imminent retrofit of offstream condenser cooling to the newer steam electric stations. Waiver can be granted based on sound experimental data, demonstrating that existing once-through cooling will not adversely affect aquatic ecosystems. Conventional methods for monitoring thermal plumes, and some remote sensing alternatives, are reviewed, using on going work at one Maryland power plant for illustration.
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Fourier transformation and digital filtering techniques were used to separate the superpositioned spectral phenomena observed in the exhaust plumes of liquid propellant rocket engines. Space shuttle main engine (SSME) spectral data were used to show that extraction of spectral lines in the spatial frequency domain does not introduce error, and extraction of the background continuum introduces only minimal error. Error introduced during band extraction could not be quantified due to poor spectrometer resolution. Based on the atomic and molecular species found in the SSME plume, it was determined that spectrometer resolution must be 0.03 nm for SSME plume spectral monitoring.
Fourier transformation and digital filtering techniques were used to separate the superpositioned spectral phenomena observed in the exhaust plumes of liquid propellant rocket engines. Space shuttle main engine (SSME) spectral data were used to show that extraction of spectral lines in the spatial frequency domain does not introduce error, and extraction of the background continuum introduces only minimal error. Error introduced during band extraction could not be quantified due to poor spectrometer resolution. Based on the atomic and molecular species found in the SSME plume, it was determined that spectrometer resolution must be 0.03 nm for SSME plume spectral monitoring.
The process of applying spectroscopy to the Space Shuttle Main Engine (SSME) for plume diagnostics, as it exists today, originated at Marshall Space Flight Center in Huntsville, Alabama, and its implementation was assured largely through the efforts of Sverdrup, AEDC, in Tullahoma, Tennessee. This process, Optical Plume Anomaly Detection (OPAD), has formed the basis for various efforts in the development of in-flight plume spectroscopy and in addition produced a viable test stand vehicle health monitor. The purpose of this paper will be to provide an introduction to the OPAD system by discussing the process of obtaining data as well as the methods of examining and interpreting the data.
An investigation of Space Shuttle Main Engine (SSME) testing failures identified optical events which appeared to be precursors of those failures. A program was therefore undertaken to detect plume trace phenomena characteristic of the engine and to design a monitoring system, responsive to excessive activity in the plume, capable of delivering a warning of an anomalous condition. By sensing the amount of extraneous material entrained in the plume and considering engine history, it may be possible to identify wearing of failing components in time for a safe shutdown and thus prevent a catastrophic event. To investigate the possibilities of safe shutdown and thus prevent a monitor to initiate the shutdown procedure, a large amount of plume data were taken from SSME firings using laboratory instrumentation. Those data were used to design a more specialized instrument dedicated to rocket plume diagnostics. The spectral wavelength range of the baseline data was about 220 nanometers (nm) to 15 micrometer with special attention given to visible and near UV. The data indicates that a satisfactory design will include a polychromator covering the range of 250 nM to 1000 nM, along with a continuous coverage spectrometer, each having a resolution of at least 5A degrees. The concurrent requirements for high resolution and broad coverage are normally at odds with one another in commercial instruments, therefore necessitating the development of special instrumentation. The design of a polychromator is reviewed herein, with a detailed discussion of the continuous coverage spectrometer delayed to a later forum. The program also requires the development of applications software providing detection, variable background discrimination, noise reduction, filtering, and decision making based on varying historical data.
The appearance of visible objects in the exhaust plume of space shuttle main engines (SSME) during test firings is discussed. A program was undertaken to attempt to identify anomalous material resulting from wear, normal or excessive, of internal parts, allowing time monitoring of engine condition or detection of failure precursors. Measurements were taken during test firings at Stennis Space Center and at the Santa Suzanna facility in California. The results indicated that a system having high spectral resolution, a fast time response, and a wide spectral range was required to meet all requirements, thus two special systems have been designed and built. One is the Optical Plume Anomaly Detector (OPAD). The other instrument, which is described in this report, is the superspectrometer, an optical multichannel analyzer having 8,192 channels covering the spectral band 250 to 1,000 nm.
This presentation introduces operational users to a machine-learning based Dust Probability product developed by the NASA SPoRT program for the application of detecting and monitoring blowing dust plumes at night. Advances in earth observing satellites has improved monitoring and detection of dust both day and night through derived imagery such as the Dust RGB. However, limitations of the RGB at night result in less contrast between dust and land surface features, as seen by the user. A Machine Learning (ML) model has been developed and applied to GOES-16 ABI to overcome this limitation and improve nighttime dust detection. The ML capability is a subset of Artificial Intelligence methods. In this case the Dust ML model was developed using a simple Random Forest (RF) model, typically used to solve classification challenges (or to provide regression type output). The goal was to leverage the strengths of the RF model to learn how to identify blowing dust, and hence, overcome the limitation of a user trying to detect blowing dust within the satellite imagery by eye alone. A brief description of the ML model development will be provided. However, the focus of the presentation will be on the initial user feedback from the assessment of this tool for the 2022 blowing dust events of March through April. During this time several users across the U.S. Southwest collaborated to apply this Dust ML product at night as a complement to the existing Dust RGB in order to determine if it provided greater operational efficiency and value.