Search NASA⌕ Search

SEARCH · Search NASA

Results for “ACOUSTIC SIMULATION”

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.

At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Validating a Monotonically-Integrated Large Eddy Simulation Code for Subsonic Jet Acoustics

The results of subsonic jet validation cases for the Naval Research Lab's Jet Engine Noise REduction (JENRE) code are reported. Two set points from the Tanna matrix, set point 3 (Ma = 0.5, unheated) and set point 7 (Ma = 0.9, unheated) are attempted on three different meshes. After a brief discussion of the JENRE code and the meshes constructed for this work, the turbulent statistics for the axial velocity are presented and compared to experimental data, with favorable results. Preliminary simulations for set point 23 (Ma = 0.5, Tj=T1 = 1.764) on one of the meshes are also described. Finally, the proposed configuration for the farfield noise prediction with JENRE's Ffowcs-Williams Hawking solver are detailed.

subsonic jet↗
NASA NTRS1998

Tutorial on the Psychophysics and Technology of Virtual Acoustic Displays

Virtual acoustics, also known as 3-D sound and auralization, is the simulation of the complex acoustic field experienced by a listener within an environment. Going beyond the simple intensity panning of normal stereo techniques, the goal is to process sounds so that they appear to come from particular locations in three-dimensional space. Although loudspeaker systems are being developed, most of the recent work focuses on using headphones for playback and is the outgrowth of earlier analog techniques. For example, in binaural recording, the sound of an orchestra playing classical music is recorded through small mics in the two "ear canals" of an anthropomorphic artificial or "dummy" head placed in the audience of a concert hall. When the recorded piece is played back over headphones, the listener passively experiences the illusion of hearing the violins on the left and the cellos on the right, along with all the associated echoes, resonances, and ambience of the original environment. Current techniques use digital signal processing to synthesize the acoustical properties that people use to localize a sound source in space. Thus, they provide the flexibility of a kind of digital dummy head, allowing a more active experience in which a listener can both design and move around or interact with a simulated acoustic environment in real time. Such simulations are being developed for a variety of application areas including architectural acoustics, advanced human-computer interfaces, telepresence and virtual reality, navigation aids for the visually-impaired, and as a test bed for psychoacoustical investigations of complex spatial cues. The tutorial will review the basic psychoacoustical cues that determine human sound localization and the techniques used to measure these cues as Head-Related Transfer Functions (HRTFs) for the purpose of synthesizing virtual acoustic environments. The only conclusive test of the adequacy of such simulations is an operational one in which the localization of real and synthesized stimuli are directly compared in psychophysical studies. To this end, the results of psychophysical experiments examining the perceptual validity of the synthesis technique will be reviewed and factors that can enhance perceptual accuracy and realism will be discussed. Of particular interest is the relationship between individual differences in HRTFs and in behavior, the role of reverberant cues in reducing the perceptual errors observed with virtual sound sources, and the importance of developing perceptually valid methods of simplifying the synthesis technique. Recent attempts to implement the synthesis technique in real time systems will also be discussed and an attempt made to interpret their quoted system specifications in terms of perceptual performance. Finally, some critical research and technology development issues for the future will be outlined.

Wenzel, Elizabeth M.↗
DOE OSTI2021

Integration of Simulated and Real Distributed Acoustic Sensor Measurements to Develop AI Enhanced Intelligent Sensing Operations

Distributed acoustic sensors (DAS) have shown remarkable success in monitoring critical civil, energy and transportation assets over long distances and under harsh environmental conditions. Integration of artificial intelligence (AI) technologies with DAS can extend their operational capabilities from conventional tasks (e.g., vibration frequency detection) to more advanced intelligent tasks like anomaly detection. However, these AI technologies often require large labeled/ annotated DAS measurements datasets of the assets in both normal and anomalous operating conditions. This data acquisition task can be both time consuming and costly. This work develops a generative adversarial network based unsupervised domain adaptation framework to build intelligent DAS operational capabilities.

Venketeswaran, Abhishek↗
NASA NTRS1995

A Variational Formulation for the Finite Element Analysis of Sound Wave Propagation in a Spherical Shell

Development of design tools to furnish optimal acoustic environments for lightweight aircraft demands the ability to simulate the acoustic system on a workstation. In order to form an effective mathematical model of the phenomena at hand, we have begun by studying the propagation of acoustic waves inside closed spherical shells. Using a fully-coupled fluid-structure interaction model based upon variational principles, we have written a finite element analysis program and are in the process of examining several test cases. Future investigations are planned to increase model accuracy by incorporating non-linear and viscous effects.

Lebiedzik, Catherine↗
DOE OSTI2022

Kimberlina 1.2 CCUS Geophysical Models and Synthetic Data Sets

This synthetic multi-scale and multi-physics data set was produced in collaboration with teams at the Lawrence Berkeley National Laboratory, National Energy Technology Laboratory, Los Alamos National Laboratory, and Colorado School of Mines through the Science-informed Machine Learning for Accelerating Real-Time Decisions in Subsurface Applications (SMART) Initiative. Data are associated with the following publication: Alumbaugh, D., Gasperikova, E., Crandall, D., Commer, M., Feng, S., Harbert, W., Li, Y., Lin, Y., and Samarasinghe, S., “The Kimberlina Synthetic Geophysical Model and Data Set for CO2 Monitoring Investigations”, The Geoscience Data Journal, 2023, DOI: 10.1002/gdj3.191. The dataset uses the Kimberlina 1.2 CO2 reservoir flow model simulations based on a hypothetical CO2 storage site in California (Birkholzer et al., 2011; Wainwright et al., 2013). Geophysical properties models (P- and S-wave seismic velocities, saturated density, and electrical resistivity) were produced with an approach similar to that of Yang et al. (2019) and Gasperikova et al. (2022) for 100 Kimberlina 1.2 reservoir models. Links to individual resources are provided below: [CO2 Saturation Models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-co2-saturation-models); Resistivity Models – [part 1](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-resistivity-models-part-1), [part 2](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-resistivity-models-part-2), and [part 3](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-resistivity-models-part-3); [Vp Velocity Models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-vp-velocity-models); [Vs Velocity Models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-vs-velocity-models); [Density Models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-density-models). The 3D distributions of geophysical properties for the 33 time stamps of the SIM001 model were used to generate synthetic seismic, gravity, and electromagnetic (EM) responses for 33 times between zero and 200 years. Synthetic surface seismic data were generated using 2D and 3D finite-difference codes that simulate the acoustic wave equation (Moczo et al., 2007). 2D data were simulated for six point-pressure sources along a 2D line with 10 m receiver spacing and a time spacing of 0.0005 s. 3D simulations were completed for 25 surface pressure sources using a source separation of 1 km in both the x and y directions and a time spacing of 0.001 s. Links to individual resources are provided below: [2D velocity models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-2d-velocity-models) and [2D surface seismic data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-2d-surface-seismic-data). [3D velocity models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-velocity-models), and 3D seismic data [year0](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year0), [year1](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year1), [year2](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year2), [year5](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year5), [year10](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year10), [year15](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year15), [year20](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year20), [year25](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year25), [year30](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year30), [year35](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year35), [year40](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year40), [year45](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year45), [year49](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year49), [year50](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year50), [year51](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year51), [year52](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year52), [year55](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year55), [year60](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year60), [year65](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year65), [year70](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year70), [year75](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year75), [year80](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year80), [year85](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year85), [year90](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year90), [year95](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year95), [year100](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year100), [year110](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year110), [year120](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year120), [year130](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year130), [year140](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year140), [year150](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year150), [year175](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year175), [year200](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year200). The Python scripts to read these models and data are provided [here](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-python-scripts). EM simulations used a borehole-to-surface survey configuration, with the source located near the reservoir level and receivers on the surface using the code developed by Commer and Newman (2008). Pseudo-2D data for the source at [2500 m](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-pseudo-2d-csem-data-tz2500m) and [3025 m](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-pseudo-2d-csem-data-tz3025m), used a 2D inline receiver configuration to simulate a response over 3D resistivity models. The [3D data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-csem-data) contain electric fields generated by borehole sources at monitoring well locations and measured over a surface receiver grid. Vector gravity data, both on the surface and in boreholes, were simulated using a modeling code developed by Rim and Li (2015). The simulation scenarios were parallel to those used for the EM: [pseudo-2D data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-gravity-data) were calculated along the same lines and within the same boreholes, and [3D data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-gravity-data) were simulated over 3D models on the surface and in three monitoring wells. A series of [synthetic well logs](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-well-logs) of CO2 saturation, acoustic velocity, density, and induction resistivity in the injection well and three monitoring wells are also provided at 0, 1, 2, 5, 10, 15, and 20 years after the initiation of injection. These were constructed by combining the low-frequency trend of the geophysical models with the high-frequency variations of actual well logs collected in the Kimberlina 1 well that was drilled at the proposed site. Measurements of permeability and pore connectivity were made on cores of Vedder Sandstone, which forms the primary reservoir unit: [CT micro scans](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-ct-micro-scans-of-vedder-formation) and [Industrial CT Images](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-industrial-ct-images-vedder-formation). These measurements provide the range of scales in the otherwise synthetic data set to be as close to a real-world situation as possible. References: Birkholzer, J.T., Zhou, Q., Cortis, A. and Finsterle, S., 2011. A sensitivity study on regional pressure buildup from large-scale CO2 storage projects. Energy Procedia, 4, 4371-4378. Commer, M., and Newman, G.A., 2008. New advances in three-dimensional controlled-source electromagnetic inversion, Geophysical Journal International, 172, 513-535. Gasperikova, E., Appriou, D., Bonneville, A., Feng, Z., Huang, L., Gao, K., Yang, X., Daley, T., 2022, Sensitivity of geophysical techniques for monitoring secondary CO2 storage plumes, Int. J. Greenh. Gas Control, Volume 114, 103585, ISSN 1750-5836, https://doi.org/10.1016/j.ijggc.2022.103585. Moczo, P., J.O. Robertsson and L. Eisner, 2007, The finite-difference time-domain method for modeling of seismic wave propagation: Advances in geophysics, 48, 421-516. Rim, H., and Y. Li, 2015, Advantages of borehole vector gravity in density imaging, Geophysics, 80, G1-G13. Wainwright, H. M.; Finsterle, S.; Zhou, Q.; Birkholzer, J. T., 2013. Modeling the Performance of Large-Scale CO2 Storage Systems: A Comparison of Different Sensitivity Analysis Methods. International Journal of Greenhouse Gas Control, 17, 189205. https://doi.org/10.1016/j.ijggc.2013.05.007, DOI: 10.18141/1603331. Yang, X., Buscheck, T.A., Mansoor, K., Wang, Z., Gao, K., Huang, L., Appriou, D., and Carroll, S.A., 2019. Assessment of geophysical monitoring methods for detection of brine and CO2 leakage in drinking water aquifers, International Journal of Greenhouse Gas Control, 90, 102803, https://doi.org/10.1016/j.ijggc.2019.102803.

CCUS↗
DOE OSTI2015

Demonstrating the saturation of stimulated Brillouin scattering by ion acoustic decay using fully kinetic simulations

The saturation of stimulated Brillouin scattering (SBS) by the decay to turbulence of the ion acoustic wave (IAW) that participates in the three-wave SBS interaction is demonstrated using a quasi-noiseless one-dimensional numerical solution to the Vlasov-Maxwell system of equations. This simulation technique permits careful examination of the decay process and its role in the complex evolution of SBS. Here, the IAW decay process is shown to be an effective SBS saturation mechanism. In our example, the instantaneous plasma reflectivity saturates at ~30% and drops to ~0% as a direct consequence of IAW decay. A contrasting example where the reflectivity is controlled by dephasing due to the nonlinear frequency of the IAW is also discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2003

Software for Acoustic Rendering

SLAB is a software system that can be run on a personal computer to simulate an acoustic environment in real time. SLAB was developed to enable computational experimentation in which one can exert low-level control over a variety of signal-processing parameters, related to spatialization, for conducting psychoacoustic studies. Among the parameters that can be manipulated are the number and position of reflections, the fidelity (that is, the number of taps in finite-impulse-response filters), the system latency, and the update rate of the filters. Another goal in the development of SLAB was to provide an inexpensive means of dynamic synthesis of virtual audio over headphones, without need for special-purpose signal-processing hardware. SLAB has a modular, object-oriented design that affords the flexibility and extensibility needed to accommodate a variety of computational experiments and signal-flow structures. SLAB s spatial renderer has a fixed signal-flow architecture corresponding to a set of parallel signal paths from each source to a listener. This fixed architecture can be regarded as a compromise that optimizes efficiency at the expense of complete flexibility. Such a compromise is necessary, given the design goal of enabling computational psychoacoustic experimentation on inexpensive personal computers.

Miller, Joel D.↗
DOE OSTI2015

SPECTROPOLARIMETRICALLY ACCURATE MAGNETOHYDROSTATIC SUNSPOT MODEL FOR FORWARD MODELING IN HELIOSEISMOLOGY

We present a technique to construct a spectropolarimetrically accurate magnetohydrostatic model of a large-scale solar magnetic field concentration, mimicking a sunspot. Using the constructed model we perform a simulation of acoustic wave propagation, conversion, and absorption in the solar interior and photosphere with the sunspot embedded into it. With the 6173 Å magnetically sensitive photospheric absorption line of neutral iron, we calculate observable quantities such as continuum intensities, Doppler velocities, as well as the full Stokes vector for the simulation at various positions at the solar disk, and analyze the influence of non-locality of radiative transport in the solar photosphere on helioseismic measurements. Bisector shapes were used to perform multi-height observations. The differences in acoustic power at different heights within the line formation region at different positions at the solar disk were simulated and characterized. An increase in acoustic power in the simulated observations of the sunspot umbra away from the solar disk center was confirmed as the slow magnetoacoustic wave.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2022

Noise Correction for Supersonic Inlet Geometry

Engine inlet geometry for supersonic aircraft is quite different than for subsonic aircraft. The present study considers whether inlet shape has a significant impact on the radiated sound and flyover noise. Axisymmetric two-dimensional simulations were performed for both subsonic and supersonic inlet geometries with the same acoustic input. The effect in the far field is complicated but overall impact on flyover noise from the effective perceived noise level (EPNL) metric was found to be only about 0.5 dB.

acoustics↗
NASA NTRS1985

Free jet feasibility study of a thermal acoustic shield concept for AST/VCE application: Dual stream nozzles

The influence of selected geometric and aerodynamic flow variables of an unsuppressed coannular plug nozzle and a coannular plug nozzle with a 20-chute outer stream suppressor were experimentally determined. A total of 136 static and simulated flight acoustic test points were conducted with 9 scale model nozzles. Also, aerodynamic measurements of four selected plumes were made with a laser velocimeter. The presence of the 180 deg shield produced different mixing characteristics on the shield side compared to the unshield side because of the reduced mixing with ambient air on the shielded side. This resulted in a stretching of the jet, yielding a higher peak mean velocity up to a length of 10 equivalent diameters from the nozzle exit. The 180 deg shield in community orientation around the suppressed coannular plug nozzle yielded acoustic benefit at all observer angles for a simulated takeoff. While the effect of shield-to-outer stream velocity ratio was small at angles up to 120 deg, beyond this angle significant acoustic benefit was realized with a shield-to-outer stream velocity ratio of 0.64.

Janardan, B. A.↗
NASA NTRS1957

Effect of standing transverse acoustic oscillations on fuel-oxidant mixing in cylindrical combustion chambers

Vapor fuel-oxidant mixing is analyzed for standing transverse acoustic fields simulating those existing in screeching or screaming combustors. The additional mixing due to the acoustic field is shown to be a function of sound pressure and frequency, stream velocity, and turbulence. The effects of these parameters are shown graphically for a realistic range of combustor conditions. The fuel-oxidant ratio at various combustor stations is shown to have a cyclic fluctuation which is in phase with the pressure fluctuations. Possible mechanisms contributing to screech and scream are discussed.

TURBINES, GAS - AFTER-BURNING↗
DOE OSTI2019

Phonon spectrum and phonon focusing in coarse-grained atomistic simulations

This work investigates the accuracy, efficiency, and applicability of coarse-grained (CG) atomistic methods in simulation of phonon dynamics. First, we compute and compare phonon dispersion relations in CG models with those in atomically resolved models, using the concurrent atomistic-continuum (CAC). The CG atomistic models using the CAC method are shown to reproduce long-wavelength phonons with great accuracy, while capturing the dynamics of some short-wavelength phonons that are usually inaccessible to CG methods. We then present CG simulation results of the propagation of heat pulses in Si with the interaction between atoms being modelled with the Stillinger-Weber potential; the experimentally observed phonon-focusing patterns in the (1 0 0) and (1 1 1) planes of Si crystals are reproduced. The accuracy and efficiency of the CAC method in CG simulation of acoustic and optical phonon branches are quantified with respect to atomically-resolved molecular dynamics simulations. The applicability and limitations of concurrent multiscale methods in the simulation of phonon transport across atomistic-continuum interface are investigated. Possible ways to overcome the limitations are discussed.

36 MATERIALS SCIENCE↗
NASA NTRS1984

Free jet feasibility study of a thermal acoustic shield concept for AST/VCE application-dual flow. Comprehensive data report. Volume 1: Test nozzles and acoustic data

Acoustic and diagnostic data that were obtained to determine the influence of selected geometric and aerodynamic flow variables of coannular nozzles with thermal acoustic shields are summarized in this comprehensive data report. A total of 136 static and simulated flight acoustic test points were conducted with 9 scale-model nozzles The tested nozzles included baseline (unshielded), 180 deg shielded, and 360 deg shielded dual flow coannular plug configurations. The baseline configurations include a high radius ratio unsuppressed coannular plug nozzle and a coanuular plug nozzle and a coannular plug nozzle with a 20-chute outer stream suppressor. The tests were conducted at nozzle temperatures and pressure typical of operating conditions of variable cycle engine.

Janardan, B. A.↗
NASA NTRS1984

Free-jet feasibility study of a thermal acoustic shield concept for AST/VCE application-dual stream nozzles. Comprehensive data report. Volume 2: Laser velocimeter and suppressor. Base pressure data

Acoustic and diagnostic data that were obtained to determine the influence of selected geometric and aerodynamic flow variables of coannular nozzles with thermal acoustic shields are summarized in this comprehensive data report. A total of 136 static and simulated flight acoustic test points were conducted with 9 scale-model nozzles. Aerodynamic laser velocimeter measurements were made for four selected plumes. In addition, static pressure data in the chute base region of the suppressor configurations were obtained to assess the influence of the shield stream on the suppressor base drag.

Janardan, B. A.↗