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Acoustic Phased Array Quantification of Quiet Technology Demonstrator 3 Advanced Inlet Liner Noise Component

Acoustic phased array flyover noise measurements were acquired as part of the Boeing 737 MAX-7 NASA Advanced Inlet Liner segment of the Quiet Technology Demonstrator 3 (QTD3) flight test program. This paper reports on the processes used for separating and quantifying the engine inlet, exhaust and airframe noise source components and provides sample phased array-based comparisons of the component noise source levels associated with the inlet liner treatment configurations. Full scale flyover noise testing of NASA advanced inlet liners was conducted as part of the Quiet Technology Demonstrator 3 flight test program in July and August of 2018. Details on the inlet designs and testing are provided in the companion paper of Reference 1. The present paper provides supplemental details relating to the acoustic phased array portion of the analyses provided in Ref. 1. In brief, the test article was a Boeing 737MAX-7 aircraft with a modified right hand (starboard side) engine inlet, which consisted of either a production inlet liner, a NASA designed inlet liner or a simulated hard wall configuration (accomplished by applying speed tape over the inlet acoustic treatment areas). In all three configurations, the engine forward fan case acoustic panel was replaced with a unperforated (hardwall) panel. No other modifications to any other acoustic treatment areas were made. The left hand (port side) engine was a production engine and was flown at idle thrust for all measurements in order to isolate the effects of the inlet liners to the right hand engine. As described in Ref. 1, the NASA inlet treatment consists of laterally cut slots (cut perpendicular to the flow direction) which are designed to reduce excrescence drag while maintaining or exceeding the liner acoustic noise reduction capabilities. The NASA inlet liner consists of a Multi-Degree of Freedom (MDOF) design with two breathable septum layers inserted into each honeycomb cell [1]. The aircraft noise measurements were acquired for both takeoff (flaps 1 setting, gear up) and approach (flaps 30 gear up and gear down) configurations. The inlet and flight test configurations are summarized in Table 1. Table 1: Inlet Treatment and Flight Configurations Inlet Forward Fan Case Aircraft Production Hardwall Flaps 1, gear up; flaps 30 gear up; flaps 30 gear down NASA Hardwall Flaps 1, gear up; flaps 30 gear up; flaps 30 gear down Hardwall Hardwall Flaps 1, gear up; flaps 30 gear up; flaps 30 gear down III.Test Description and Hardware The flight testing was conducted at the Grant County airport in Moses Lake, WA, between 27 July and 6 August 2018. The noise measurement instrumentation included 8 flush dish microphones arranged in a noise certification configuration as well as an 840 microphone phased array. The flush dish microphones were used to quantify the levels and differences in levels between the various inlet treatments. The phased array was used to separate and quantify the narrowband (tonal) and broadband noise component levels from the engine inlet/exhaust and from the airframe. Phased array extraction of the broadband component was critical to this study because it allowed for the separation of the inlet component from the total airplane level noise even when it was significantly below the total level. Figure 1 provides an overview of the phased array microphone layout as well as a detailed image of an individual phased array microphone mounted in a plate holder (the microphone sensor is the dot in the center of the plate). The ground plane ensemble array microphones (referred to as “ensemble array” in this paper) were mounted in plates with “flower petal” edges designed to minimize edge scattering effects. Fig. 1 Flyover test microphone layout. The phased array configuration was the result of a progressive development of concepts originally implemented in Ref. 2 and refined over the following years, consisting namely of multiple multi-arm logarithmic spiral subarrays designed to cover overlapping frequency ranges and optimized for various aircraft emission angles. For the present case, the signals from all 840 microphones were acquired on a single system. The 840 microphones were parsed into 11 primary subarray sets spanning from smallest to largest aperture size and labeled accordingly as “a, b, …, k”, where “a” corresponds to the smallest fielded subarray and “k” corresponds to the largest aperture subarray. The apertures ranged from approximately 10 ft to 427 ft in size (in the flight direction) with the subarrays consisting of between 215 and 312 microphones. Figure 2 shows three such subarrays, k, h and a. As done in Ref. 2, microphones were shared between subarrays in order to reduce total channel count. Fig. 2 Sample subarray sizes (20° from overhead – refer to Figure 3a discussion). In addition to the above, each of the 11 primary subarray sets consisted of four subarrays optimized to provide near equivalent array spatial resolution in both the flight and lateral directions within 30 degrees of overhead (i.e., airplane directly above the center of the array), namely, at angles  of 0, ±10, ±20 and ±30 degrees relative to overhead where angle  is defined as shown in Figure 3a. This allowed for optimized aircraft noise measurements from 60 to 120 degree emission angle.6 An example of this pletharray design is shown in Figure 3b for the k subarray. When the aircraft is at overhead, the microphones indicated by the blue markers are used for beamforming. When the aircraft is at angles ±10 degrees from overhead, both the blue and red colored microphones are used, and so on for the ±20 and ±30 degree aircraft locations. See Ref. 3 for extensive details on pletharray design for aeroacoustic phased array testing. 6 In the discussions that follow, emission angle values are used. These are the angles at the time sound is emitted relative to the engine axis and are calculated based on flight path angle, body aircraft body angle with respect to the relative wind direction, and engine axis angle relative to aircraft body angle.

Brusniak, Leon↗

Chemical kinetic studies of atmospheric reactions using tunable diode laser spectroscopy

IR absorption using tunable diode laser spectroscopy provides a sensitive and quantitative detection method for laboratory kinetic studies of atmospheric trace gases. Improvements in multipass cell design, real time signal processing, and computer controlled data acquisition and analysis have extended the applicability of the technique. We have developed several optical systems using off-axis resonator mirror designs which maximize path length while minimizing both the sample volume and the interference fringes inherent in conventional 'White' cells. Computerized signal processing using rapid scan (300 kHz), sweep integration with 100 percent duty cycle allows substantial noise reduction while retaining the advantages of using direct absorption for absolute absorbance measurements and simultaneous detection of multiple species. Peak heights and areas are determined by curve fitting using nonlinear least square methods. We have applied these techniques to measurements of: (1) heterogeneous uptake chemistry of atmospheric trace gases (HCl, H2O2, and N2O5) on aqueous and sulfuric acid droplets; (2) vapor pressure measurements of nitric acid and water over prototypical stratospheric aerosol (nitric acid trihydrate) surfaces; and (3) discharge flow tube kinetic studies of the HO2 radical using isotopic labeling for product channel and mechanistic analysis. Results from each of these areas demonstrate the versatility of TDL absorption spectroscopy for atmospheric chemistry applications.

Worsnop, Douglas R.↗

Exploring Sentinel-1 and Sentinel-2 diversity for Flood inundation mapping using deep learning

Identification of flood water extent from satellite images has historically relied on either synthetic aperture radar (SAR) or multi-spectral (MS) imagery. MS sensors are limited to cloud free conditions, whereas SAR imagery is plagued by noise-like speckle. Prior studies that use combinations of MS and SAR data to overcome individual limitations of these sensors have not fully examined sensitivity of flood mapping performance to different combinations of SAR and MS derived spectral indices or band transformations in color space. This study explores the use of diverse bands of Sentinel 2 (S2) through well-established water indices and Sentinel 1 (S1) derived SAR imagery along with their combinations to assess their capability for generating accurate flood inundation maps. The robustness in performance of S-1 and S-2 band combinations was evaluated using 446 hand labeled flood inundation images spanning across 11 flood events from Sen1Floods11 dataset which are highly diverse in terms of land cover as well as location. A modified K-fold cross validation approach is used to evaluate the performance of 32 combinations of S1 and S2 bands using a fully connected deep convolutional neural network known as U-Net. Our results indicated that usage of elevation information has improved the capability of S1 imagery to produce more accurate flood inundation maps. Compared to a median F1 score of 0.62 when using only S1 bands, the combined use of S1 and elevation information led to an improved median F1 score of 0.73. Water extraction indices based on S2 bands have a statistically significant superior performance in comparison to S1. Among all the band combinations, HSV (Hue, Saturation, Value) transformation of S2 bands provides a median F1 score of 0.9, outperforming the commonly used water spectral indices owing to HSV’s transformation’s superior contrast distinguishing abilities. Additionally, U-Net algorithm was able to learn the relationship between raw S2 based water extraction indices and their corresponding raw S2 bands, but not of HSV owing to relatively complex computation involved in the latter. Results of the paper establishes important benchmarks for the extension of S1 and S2 data-based flood inundation mapping efforts over large spatial extents.

Goutam Konapala↗

Analysis of the Accuracy of Actuation Electronics in the Laser Interferometer Space Antenna Pathfinder

The Laser Interferometer Space Antenna Pathfinder (LPF) main observable, labelled∆g, is the differential force per unit mass acting on the two test masses in free fall condition, after the contribution of all non-gravitational forces have been compensated. At low frequencies the differential force is compensated by an applied electrostatic actuation force,which then must be subtracted from the measured acceleration to obtain∆g. Any inaccuracy in the actuation force contaminates the residual acceleration. This study investigates the accuracy of the electrostatic actuation system and its impact on the LPF main observable. It is shown that the inaccuracy is mainly caused by the rounding errors in the waveform processing and also by the random error caused by the analog to digital converter (ADC) random noise in the control loop. Both errors are one order of magnitude smaller than the resolution of the commanded voltages. We developed a simulator based on the LPF design to compute the close-to-reality actuation voltages and consequently, the resulting actuation forces. The simulator is applied in post-processing the LPF data.

M. Armano↗

NASA Tech Briefs, October 2003

Topics covered include: Cryogenic Temperature-Gradient Foam/Substrate Tensile Tester; Flight Test of an Intelligent Flight-Control System; Slat Heater Boxes for Thermal Vacuum Testing; System for Testing Thermal Insulation of Pipes; Electrical-Impedance-Based Ice-Thickness Gauges; Simulation System for Training in Laparoscopic Surgery; Flasher Powered by Photovoltaic Cells and Ultracapacitors; Improved Autoassociative Neural Networks; Toroidal-Core Microinductors Biased by Permanent Magnets; Using Correlated Photons to Suppress Background Noise; Atmospheric-Fade-Tolerant Tracking and Pointing in Wireless Optical Communication; Curved Focal-Plane Arrays Using Back-Illuminated High-Purity Photodetectors; Software for Displaying Data from Planetary Rovers; Software for Refining or Coarsening Computational Grids; Software for Diagnosis of Multiple Coordinated Spacecraft; Software Helps Retrieve Information Relevant to the User; Software for Simulating a Complex Robot; Software for Planning Scientific Activities on Mars; Software for Training in Pre-College Mathematics; Switching and Rectification in Carbon-Nanotube Junctions; Scandia-and-Yttria-Stabilized Zirconia for Thermal Barriers; Environmentally Safer, Less Toxic Fire-Extinguishing Agents; Multiaxial Temperature- and Time-Dependent Failure Model; Cloverleaf Vibratory Microgyroscope with Integrated Post; Single-Vector Calibration of Wind-Tunnel Force Balances; Microgyroscope with Vibrating Post as Rotation Transducer; Continuous Tuning and Calibration of Vibratory Gyroscopes; Compact, Pneumatically Actuated Filter Shuttle; Improved Bearingless Switched-Reluctance Motor; Fluorescent Quantum Dots for Biological Labeling; Growing Three-Dimensional Corneal Tissue in a Bioreactor; Scanning Tunneling Optical Resonance Microscopy; The Micro-Arcsecond Metrology Testbed; Detecting Moving Targets by Use of Soliton Resonances; and Finite-Element Methods for Real-Time Simulation of Surgery.

Source record↗

Ion-assisted tropospheric OH measurement technique

The present technique measures atmospheric OH concentrations by first titrating OH into isotopically labeled H2(exp 34)SO4 by a series of gas phase reactions in an effectively wall-less flow tube reactor on a time-scale which is short in comparison to the OH lifetime. The gas phase H2SO4 concentration is then determined by reacting it with NO3(-)(center dot)HNO3 ions in a flow tube, and subsequently measuring the resulting (HSO4(-))/(NO3(-)) ion ratio. Since the determination of H2SO4 concentration does not depend on the measurement of an absolute photon flux or chemical concentration but rather only on the relative concentration measurement of two fairly similar mass ions in conjunction with a fixed reaction time and reaction rate coefficient, no in-field calibration technique should be required. The ion-assisted OH measurement technique provides a concentration measurement about once each 10 to 20 seconds and had a detection sensitivity less than or equal to 1 x 10(exp 5) molecules/cu cm (2 standard deviations) with an integration time of 5 minutes during the past field study. Typically, the total background signal level is in the low 10(exp 6) molecule/cu cm range with the scatter in this background (or background noise in 5 minutes) in the mid 10(exp 4) molecules/cu cm range.

Eisele, Fred L.↗

Single Event Transients in Voltage Regulators for FPGA Power Supply Applications

As with other bipolar analog devices, voltage regulators are known to be sensitive to single event transients (SET). In typical applications, large output capacitors are used to provide noise immunity. Therefore, since SET amplitude and duration are generally small, they are often of secondary importance due to this capacitance filtering. In low voltage applications, however, even small SET are a concern. Over-voltages may cause destructive conditions. Under-voltages may cause functional interrupts and may also trigger electrical latchup conditions. In addition, internal protection circuits which are affected by load as well as internal thermal effects can also be triggered from heavy ions, causing dropouts or shutdown ranging from milliseconds to seconds. In the case of FPGA power supplies applications, SETS are critical. For example, in the case of Actel FPGA RTAX family, core power supply voltage is 1.5V. Manufacturer specifies an absolute maximum rating of 1.6V and recommended operating conditions between 1.425V and 1.575V. Therefore, according to the manufacturer, any transient of amplitude greater than 75 mV can disrupt normal circuit functions, and overvoltages greater than 100 mV may damage the FPGA. We tested five low dropout voltage regulators for SET sensitivity under a large range of circuit application conditions.

Poivey, Christian↗