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NASA NTRSDate not supplied

Uncertainty Quantification of CFD Model Assumptions Against Sonic Boom Noise Prediction of a Commercial Supersonic Transport

This paper presents the results of uncertainty modeling of sonic boom noise generation from commercial supersonic transport considering the Spalart-Allmaras (SA) turbulence modeling parameters as well as Mach number, angle of attack and altitude. Sample generation and analysis for this uncertainty model was performed by UQPCE, which is a software package developed at the NASA Langley Research Center. To build the uncertainty model, 42 cases of sonic boom noise calculation were performed. Computation of the ground noise can be briefly summarized in two steps. First, the near field pressure waveforms are sampled from CFD calculation using the NASA Langley’s FUN3D solver. Second, this information is passed to an atmospheric propagation code, sBOOM, which solves an augmented Burger’s equation and simulates how the near field waveforms will change while passing through the atmosphere. The ground signature is further processed to obtain the perceived loudness, PLdB. Having a high spatial resolution near the shockwave in the CFD calculation is critical in sonic boom noise prediction. Because the variation in the input parameters for the current uncertainty quantification (UQ) study is likely to lead to change in shock location, angle and strength, the grid adaptation for shock capturing is independently applied for each condition. The final mesh used in the CFD calculation consists of approximately 420 million cells. The pressure signatures are sampled at three, four and five body lengths away from the aircraft to make sure the three dimensional effects around the aircraft are resolved. The results of the UQ analysis shows that within the three aleatory variables, the angle of attack had the most impact against ground noise, followed by the altitude and the Mach number. Between the two SA model parameters, the Kármán constant (𝜅) was significantly more important than the turbulent Prandtl number (𝜎), but these two parameters were only marginally significant in the overall prediction variance in ground noise. The UQ procedure explained in this paper can be widely applied to other model parameters.

Uncertainty Quantification↗

NASA NTRSDate not supplied

Nearfield Summary and Analysis of the Third AIAA Sonic Boom Prediction Workshop C608 Low Boom Demonstrator

A summary and statistical analysis of the nearfield Computational Fluid Dynamics (CFD)submissions for the Third AIAA Sonic Boom Prediction Workshop is provided with a focus onthe C608 Low Boom Flight Test Demonstrator. The C608 is more complex in terms of geometryand propulsion boundary conditions than previous workshop cases and is more representativeof vehicles with lower ground loudness and the potential for lower annoyance. The nearfieldsignatures submitted by the participants are propagated to the ground to compute statisticsof loudness measures over the vehicle sonic boom carpet. Principle component analysis isused to extract the primary variation modes. Context from previous sonic boom workshopsindicates that this workshop has the lowest variation even though the case is more challengingbecause it is quieter and more complex. The results documented in this summary indicate thatthe international state-of-the-art for nearfield CFD has a variation that is small enough formeaningful low-boom design and analysis. Low-boom configuration analysis methods with lowvariation are important tools to develop certification processes for addressing the prohibitionon overland supersonic commercial flight.

sonic boom CFD workshop c608↗

NASA NTRS2023

Development of a Field-Deployable Microphone Phased Array for Airframe Noise Flyover Measurements

This technical memorandum describes in detail the construction and use of a large channel-count, field-deployable microphone phased array designed for airframe noise flyover measurements for a range of aircraft types and scales. The array incorporated 185 hardened, weather-resistant sensors suitable for outdoor use. A custom 4-mA current loop receiver circuit with temperature compensation was developed to power the sensors over extended cable lengths with minimal loss of signal-to-noise. Extensive calibrations and performance testing of the sensors were conducted to verify the design specifications. A compact data system combining sensor power, signal conditioning, and digitization was assembled for use with the array. Complementing the data system was a robust analysis system capable of near real-time presentation of beamformed and deconvolved contour plots and integrated spectra obtained from data acquired during flyover passes of the array. Additional instrumentation systems needed to process the array data were also developed, including a commercial 10-meter weather station comprised of a sonic anemometer, aspirated temperature/humidity probe and pressure sensor. Unique methods for assessing the health of the array in-situ were developed and demonstrated. A detailed mock-up of the instrumentation suite (phased array, weather station, and data processor) was performed in the NASA Langley Acoustic Development Laboratory in 2014 to vet the system performance. Issues with the sensors and electronics were identified during the mock-up and subsequently corrected. The array was then deployed for preliminary field testing at Fort A.P. Hill in Virginia in 2015 followed by the array being utilized in three separate full-scale airframe noise test campaigns at Edwards Air Force Base in California from 2016 to 2018 where the system was used to characterize the noise generated by both baseline and treated flaps and main landing gear on a commercial transport-sized vehicle.

Phased Array↗

NASA NTRSDate not supplied

Enhanced Simulation Techniques in Predicting Sonic Boom Loudness Using CFD

This paper outlines advancements in predicting sonic boom loudness within the Launch, Ascent, and Vehicle Aerodynamics (LAVA) computational framework. Traditionally, a two step process consisting of a steady state computational fluid dynamics problem for near-field analysis and a far-field propagation solver for calculation of loudness metrics has been used. Improvements to this process made in this work include utilizing a high-order space marching method for mid-field computations, developing a novel output-based mesh adaptation method targeting error in near-field pressure sig-natures, and developing a robust scripting system using curvilinear grids to increase robustness and simplify the process of running large databases of simulation cases. These advancements are detailed and applied to the simulation of the X-59, presenting comparative cost and timing analyses between the prior two step workflow and the current three step procedure. We achieve increased accuracy and robustness for loudness predictions with at least a50%computational cost reduction.

CST↗

DOE OSTI2022

Classification of Ultrasonic Weld Quality using Acoustic Signatures Acquired During Manufacture

Ultrasonic welding is a process is based on generating a solid-state bond between two metals by applying moderate pressure and high intensity sound waves (20-70 kHz frequencies) at their interface. During the solid-state process numerous material, surface, instrument, and environmental factors contribute to bond formation, strength, and durability. The inherent difficulty of measuring and controlling each of these factors has, to date, made predicting bond quality elusive. In this work, a Sonics model MWB20 ultrasonic spot welder with integral base, was used to produce a variety of welds of different metal foils under varying weld conditions. Acoustic measurements were recorded throughout the measurement process. Subsequent analysis of the signals using metrics that approximate the energy dispersed during the weld proved to successfully predict weld quality. Two metrics based on normalized energy differential and Renyi entropy were developed into Python and C++ scripts for direct analysis of weld acoustic data.

36 MATERIALS SCIENCE↗

NASA NTRSDate not supplied

Uncertainty Quantification of CFD Model Assumptions Against Sonic Boom Noise Prediction of a Commercial Supersonic Transport

This paper presents the results of uncertainty modeling of sonic boom noise generation from commercial supersonic transport considering the Spalart-Allmaras (SA) turbulence modeling parameters as well as Mach number, angle of attack and altitude. Sample generation and analysis for this uncertainty model was performed by UQPCE, which is a software package developed at the NASA Langley Research Center. To build the uncertainty model, 42 cases of sonic boom noise calculation were performed. Computation of the ground noise can be briefly summarized in two steps. First, the near field pressure waveforms are sampled from CFD calculation using the NASA Langley’s FUN3D solver. Second, this information is passed to an atmospheric propagation code, sBOOM, which solves an augmented Burger’s equation and simulates how the near field waveforms will change while passing through the atmosphere. The ground signature is further processed to obtain the perceived loudness, PLdB. Having a high spatial resolution near the shock wave in the CFD calculation is critical in sonic boom noise prediction. Because the variation in the input parameters for the current uncertainty quantification (UQ) study is likely to lead to change in shock location, angle and strength, the grid adaptation for shock capturing is independently applied for each condition. The final mesh used in the CFD calculation consists of approximately 420 million cells. The pressure signatures are sampled at three, four and five body lengths away from the aircraft to make sure the three dimensional effects around the aircraft are resolved. The results of the UQ analysis shows that within the three aleatory variables, the angle of attack had the most impact against ground noise, followed by the altitude and the Mach number. Between the two SA model parameters, the Kármán constant (𝜅) was significantly more important than the turbulent Prandtl number (𝜎), but these two parameters were only marginally significant in the overall prediction variance in ground noise. The UQ procedure explained in this paper can be widely applied to other model parameters.

Uncertainty Quantifications↗

DOE OSTI2024

Eddy Covariance Flux / Processed Data

This dataset consists of estimates of mean and turbulent quantities from a vertical array of instruments installed on the barge met mast, including: sonic anemometers, relative humidity and temperature, pressure, and rain. One of the levels consists of a paired sonic anemometer and infrared gas analyzer for direct covariance sensible and latent heat fluxes. Mean and turbulent quantities are determined over 20-minute averaging periods.

17 WIND ENERGY↗

DOE OSTI2024

Eddy Covariance Flux / Processed Data

17 WIND ENERGY↗

NASA NTRS1975

Flow processes in electric discharge drivers

The performance of an electric discharge shock tube is discussed from the point of view that the conditions at the sonic station are the primary controlling variables (likewise in comparing designs), and that the analysis of the flow on either side of the sonic station should be done separately. The importance of considering mass-flow rate in matching a given driver design to the downstream flow required for a particular shock-wave speed is stressed. It is shown that a driver based on the principle of liquid injection (of H2) is superior to one based on the Ludwieg tube, because of the greater mass-flow rate and the absence of a massive diaphragm.

Baganoff, D.↗

DOE OSTI2023

Production of graphene-derivatives using organic molecules for supercapacitors and beyond

Graphene is rapidly expanding for applications ranging from nanoelectronics to space exploration. A material with such enormous potential requires a variety of synthesis methods. Here, we report a library of relatively sustainable redox-active organic molecules for the reduction of graphene oxide (GO) namely N,N,N',N'-tetramethyl-p-phenylenediamine (TMPD), 7,7,8,8-tetracyanoquinodimethane (TCNQ), ferrocene (Ferro), and decamethylferrocene (DFerro). Among them, the reduction of GO using TMPD starts even with simple hand-shaking for just a few minutes. By controlling the sonication time under ambient conditions, one can control the electronic properties of the reduced graphene oxide (rGO). The resulting free-standing films delivered a capacitance of 185 F/g when tested them as supercapacitor electrodes. We also demonstrated that TMPD can exfoliate graphite into few-layer graphene sheets with simple sonication. Here, we further show that under mild heating, these molecules can serve as dopants during the reduction process to produce nitrogen-doped graphene. Our results may guide researchers to explore sustainable organic molecules for the large-scale production of graphene-based materials for diverse applications.

36 MATERIALS SCIENCE↗

DOE OSTI2020

ARM: CAMSRSUDSMOVIE

caminst

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

A conserved molecular logic for neurogenesis to gliogenesis switch in the cerebral cortex

During development, neural stem cells in the cerebral cortex, also known as radial glial cells (RGCs), generate excitatory neurons, followed by production of cortical macroglia and inhibitory neurons that migrate to the olfactory bulb (OB). Understanding the mechanisms for this lineage switch is fundamental for unraveling how proper numbers of diverse neuronal and glial cell types are controlled. We and others recently showed that Sonic Hedgehog (Shh) signaling promotes the cortical RGC lineage switch to generate cortical oligodendrocytes and OB interneurons. During this process, cortical RGCs generate intermediate progenitor cells that express critical gliogenesis genes Ascl1, Egfr, and Olig2. The increased Ascl1 expression and appearance of Egfr + and Olig2 + cortical progenitors are concurrent with the switch from excitatory neurogenesis to gliogenesis and OB interneuron neurogenesis in the cortex. While Shh signaling promotes Olig2 expression in the developing spinal cord, the exact mechanism for this transcriptional regulation is not known. Furthermore, the transcriptional regulation of Olig2 and Egfr has not been explored. Here, we show that in cortical progenitor cells, multiple regulatory programs, including Pax6 and Gli3, prevent precocious expression of Olig2, a gene essential for production of cortical oligodendrocytes and astrocytes. We identify multiple enhancers that control Olig2 expression in cortical progenitors and show that the mechanisms for regulating Olig2 expression are conserved between the mouse and human. Our study reveals evolutionarily conserved regulatory logic controlling the lineage switch of cortical neural stem cells.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Pyrolysis Molecular Beam Mass Spectrometry_Analysis_of_Natural_Variants_of_Poplulus_Trichocarpa_Leaves

Select leaves from natural variants of Poplar (Populus Trichocarpa) grown in a greenhouse at Oak Ridge National Laboratory were analyzed by Pyrolysis-Molecular Beam Mass Spectrometry (Py-MBMS). Leaves were harvested, cryomilled and kept frozen until analysis. Py-MBMS analysis was conducted using approximately 4 mg of biomass and each sample was analyzed in duplicate. A Frontier PY2020 unit pyrolyzed samples at 500°C for 30 s in 80 µL deactivated stainless steel cups. An Extrel Super-Sonic MBMS Model Max 1000 was used to collect mass spectral data fromm/z30 to 450 at 17 eV and processed using Merlin Automation software (V3). Spectral ion intensities were normalized to the total ion chromatogram signal for each sample for analysis of spectral variance. Lignin content (wt %) was estimated based on relative responses from standards of known Klason lignin content using mean-normalized ion intensities ofm/z120, 124 (G), 137 (G), 138 (G), 150 (G), 152, 154 (S), 164 (G), 167 (S), 168 (S), 178 (G), 180, 181, 182 (S), 194 (S), 208 (S) and 210 (S) where G indicates guaiacyl-derived ions, S indicates syringyl-derived ions, and other ions either derive from other lignin monomers or multiple sources. Ratios of S and G lignin monomer units (S/G) were obtained by dividing the sum of S-based ions by the sum of G-based ions using mean-normalized ion intensities.

CBI↗

DOE OSTI2026

Pyrolysis_Molecular_Beam_Mass_Spectrometry_Analysis_of_Specific_Switchgrass_Genotypes

Select natural variant switchgrass genotypes grown in Tifton, GA were analyzed by Pyrolysis-Molecular Beam Mass Spectrometry (Py-MBMS). Biomass was harvested, milled, several genotypes were analyzed with and without being destarched and extracted with ethanol prior to analysis (indicated with -DE if destarched and extracted). Py-MBMS analysis was conducted using approximately 4 mg of biomass and each sample was analyzed in duplicate. A Frontier PY2020 unit pyrolyzed samples at 500°C for 30 s in 80 µL deactivated stainless steel cups. An Extrel Super-Sonic MBMS Model Max 1000 was used to collect mass spectral data fromm/z30 to 450 at 17 eV and processed using Merlin Automation software (V3). Spectral ion intensities were normalized to the total ion chromatogram signal for each sample for analysis of spectral variance. Lignin content (wt %) was estimated based on relative responses from standards of known Klason lignin content using mean-normalized ion intensities ofm/z120, 124 (G), 137 (G), 138 (G), 150 (G), 152, 154 (S), 164 (G), 167 (S), 168 (S), 178 (G), 180, 181, 182 (S), 194 (S), 208 (S) and 210 (S) where G indicates guaiacyl-derived ions, S indicates syringyl-derived ions, and other ions either derive from other lignin monomers or multiple sources. Ratios of S and G lignin monomer units (S/G) were obtained by dividing the sum of S-based ions by the sum of G-based ions using mean-normalized ion intensities.

CBI↗

DOE OSTI2026

Pyrolysis_Molecular_Beam_Mass_Spectrometry_Analysis_of_hybrid_cross_of_Populus_tremula_x_P_alba_717-1B4_and_overexpression_of_a_lectin_receptor-like_kinase_(PtLecRLK1)

Stem tissues from the hybrid poplarPopulus tremula × P. albaclone 717-1B4 and from lectin receptor-like kinase overexpression lines PP7 and PP19 were individually colonized with the ectomycorrhizal fungiLaccaria bicolorstrain S238N,Hyaloscypha finlandicastrain PMI746, orUmbelopsis vinaceastrain PMI3018, as well as with a mixed fungal inoculum; non-inoculated plants served as controls. Plants were grown in a greenhouse at Oak Ridge National Laboratory and harvested in January 2025. Stem samples were analyzed using Pyrolysis–Molecular Beam Mass Spectrometry (Py-MBMS). Stems were harvested, debarked, dried, milled, destarched and ethanol extracted prior to analysis. Py-MBMS analysis was conducted using approximately 4 mg of wood from biomass and each sample was analyzed in duplicate. A Frontier PY2020 unit pyrolyzed samples at 500°C for 30 s in 80 µL deactivated stainless steel cups. An Extrel Super-Sonic MBMS Model Max 1000 was used to collect mass spectral data fromm/z30 to 450 at 17 eV and processed using Merlin Automation software (V3). Spectral ion intensities were normalized to the total ion chromatogram signal for each sample for analysis of spectral variance. Lignin content (wt %) was estimated based on relative responses from standards of known Klason lignin content using mean-normalized ion intensities ofm/z120, 124 (G), 137 (G), 138 (G), 150 (G), 152, 154 (S), 164 (G), 167 (S), 168 (S), 178 (G), 180, 181, 182 (S), 194 (S), 208 (S) and 210 (S) where G indicates guaiacyl-derived ions, S indicates syringyl-derived ions, and other ions either derive from other lignin monomers or multiple sources. Ratios of S and G lignin monomer units (S/G) were obtained by dividing the sum of S-based ions by the sum of G-based ions using mean-normalized ion intensities.

CBI↗

NASA NTRS1972

Review of critical flow rate, propagation of pressure pulse, and sonic velocity in two-phase media

For single-phase media, the critical discharge velocity, the sonic velocity, and the pressure pulse propagation velocity can be expressed in the same form by assuming isentropic, equilibria processes. In two-phase mixtures, the same concept is not valid due to the existence of interfacial transports of momentum, heat, and mass. Thus, the three velocities should be treated differently and separately for each particular condition, taking into account the various transport processes involved under that condition. Various attempts are reviewed to predict the critical discharge rate or the propagation velocities by considering slip ratio (momentum change), evaporation (mass and heat transport), flow pattern, etc. Experimental data were compared with predictions based on various theorems. The importance is stressed of the time required to achieve equilibrium as compared with the time available during the process, for example, of passing a pressure pulse.

Hsu, Y.↗

DOE OSTI2026

Extracting Critical Metals from Authentic Bauxite Residue

Securing domestic sources of critical minerals (CM) is paramount to ensuring a robust and self-sustaining technology infrastructure. Utilizing untapped non-conventional sources, like acid mine drainage, coal ash, bauxite residue/red mud, and more is an emerging approach that addresses this national concern while identifying new value-added pathways originating from waste streams. Red mud is a byproduct of the Bayer process that produces alumina and contains a wealth of CM – 50 µg/g Ga, 2.9 mg/g total rare earth elements plus yttrium, 12 mg/g Mn, 58 mg/g Al, and others. About 170 MM tonnes of red mud are co-produced annually alongside the 142 MM tonnes of alumina generated, highlighting the abundancy of this feedstock. In this work, different strategies were explored for extracting CM from authentic bauxite residue that involve thermal heating, microwave heating, and sonication all with different acids and buffers. CM recovery was then explored one step further by testing the adsorption of the extracted metals onto NETL’s Multi-functional Sorbent Technology (MUST). Microwave treatment of red mud proved the most effective CM extraction, whereas sonication was less desirable due to scale-up concerns. Successful recovery of CM from this leachate with MUST supports further studies toward optimizing the overall process.

bauxite residue↗

NASA NTRS1959

Investigation at Mach Numbers of 0.20 to 3.50 of a Blended Diamond Wing and Body Combination of Sonic Design but with Low Wave-Drag Increase with Increasing Mach Number

A diamond wing and body combination was designed to have an area distribution which would result in near optimum zero-lift wave-drag coefficients at a Mach number of 1.00, and decreasing wave-drag coefficient with increasing Mach number up to near sonic leading-edge conditions for the wing. The airfoil section were computed by varying their shape along with the body radii (blending process) to match the selected area distribution and the given plan form. The exposed wing section had an average maximum thickness of about 3 percent of the local chords, and the maximum thickness of the center-line chord was 5.49 percent. The wing had an aspect ratio of 2 and a leading-edge sweep of 45 deg. Test data were obtained throughout the Mach number range from 0.20 to 3.50 at Reynolds numbers based on the mean aerodynamic chord of roughly 6,000,000 to 9,000,000. The zero-lift wave-drag coefficients of the diamond model satisfied the design objectives and were equal to the low values for the Mach number 1.00 equivalent body up to the limit of the transonic tests. From the peak drag coefficient near M = 1.00 there was a gradual decrease in wave-drag coefficient up to M = 1.20. Above sonic leading-edge conditions of the wing there was a rise in the wave-drag coefficient which was attributed in part to the body contouring as well as to the wing geometry. The diamond model had good lift characteristics, in spite of the prediction from low-aspect-ratio theory that the rear half of the diamond wing would carry little lift. The experimental lift-curve slope obtained at supersonic speeds were equal to or greater than the values predicted by linear theory. Similarly the other basic aerodynamic parameters, aerodynamic center position, and maximum lift-drag ratios were satisfactorily predicted at supersonic speeds.

Holdaway, George H.↗