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At least 775 records · Page 43

Numerical and experimental investigation of the flame kernel growth in a methane/air mixture near the lean flammability limit

Lean combustion has the potential to improve the thermal efficiency of spark-ignition engines, but it faces the significant challenge of increased cycle-to-cycle variation due to low mixture reactivity and unstable flame dynamics. Computational fluid dynamics (CFD) employing predictive models can guide engine design and optimize operating strategies for lean combustion. However, ignition and combustion models have rarely been validated at fuel-lean conditions, and a fundamental understanding of the early flame kernel growth process is also lacking for a successful sub-model development. Here, the present study develops a numerical simulation framework used to investigate early flame kernel growth in methane/air mixtures. A nanosecond-pulsed discharge (NPD) approach is employed to effectively decouple the flame kernel growth from the electrical discharge due to their difference in timescales, and equivalence ratios near the experimentally measured lean flammability limit (LFL) are selected to focus on challenging mixture conditions. Three numerical investigations, such as the choice of turbulence modeling, grid size, and grid control strategies, are examined to match both LFL and flame kernel structure measured from experiments. It is demonstrated that a quasi-direct numerical simulation (QDNS) with a fixed grid embedding of 10 μm can predict the LFL as φ CFD =0.61 and match the displacement speed of the kernel’s boundary marked in schlieren images. To predict the LFL and flame kernel shape, a fine grid (Δ≤12.5 μm) is needed to capture the consumption of formaldehyde (CH 2 O) in kernel’s reaction branches attached to the anode, and adaptive mesh refinement is replaced with the fixed embedding due to loss of simulation accuracy. Also, it is found that a large-eddy simulation (LES) using the Dynamic Structure model is not suitable for the NPD-induced flame kernel simulation because artificial sub-grid turbulent kinetic energy induced by shock dynamics alters the flow velocity calculation, resulting in divergence of LES from QDNS. Lastly, the simulation well matches the experimental data for the flame kernel evolution in three mixture conditions (φ = 0.7, 0.61, 0.55), showing toroidal flame kernel expansion and flame kernel growth/extinction.

33 ADVANCED PROPULSION SYSTEMS↗

New Tools for Automating Arcjet Sample Recession Tracking and Analysis

Arcjet Computer Vision (arcjetCV) has been significantly upgraded to enhance accuracy and performance in tracking material recession and shock-material standoff in test videos. These improvements include integrating new machine learning models, developing a specialized edge detection class, and incorporating a more comprehensive training dataset. These upgrades have refined the software’s ability to automate time-resolved recession tracking, making it more precise and reliable for analyzing complex physical processes. In parallel, a new tool called STARscan (Spatial Targeting and Alignment Rig for Scanning) is being developed to capture detailed 3D surface data before and after testing. By comparing these pre- and post-test scans with arcjetCV’s automated video analysis results, users can achieve a more comprehensive assessment of material recession. This method enables cross-validation of results, improving confidence in the analysis of tested materials. The expanded capabilities of arcjetCV have been successfully demonstrated on videos from various facilities, including the NASA Ames arcjets, UIUC’s PlasmatronX, and the VKI Plasmatron. It has been adopted as a new standard for in-situ recession tracking by the Mars Sample Return Project and Orion. ArcjetCV’s improved efficiency and accuracy are critical for reducing testing uncertainties and validating heatshield material performance under extreme conditions. The software’s user-friendly graphical interface ensures ease of use, enabling seamless processing and precise analysis of arcjet videos, providing deeper insights into material behavior in hypersonic environments. ArcjetCV is now available on both PyPI and Conda, allowing easy installation via "pip install arcjetCV" or through the Conda package manager, ensuring broad accessibility and streamlined deployment for users across various platforms.

Ablation↗

A stress-based fracture model for reacting metal ejecta

The evolution of reacting metal ejecta continues to be a topic of interest at the forefront of metals in reactive and extreme environments. Ejecta are small particles formed when the surface of a metal undergoes Richtmyer–Meshkov instability from a strong shock. Experiments have shown that in the case where ejecta are in ambient conditions that induce a reaction, the ejecta behave irregularly. The ejecta temperature rises and then plateaus, and the acceleration profile shows unexpected jumps. These variations are assumed to be related to the exothermic heat release and particle mass loss caused by the reaction. To explain this phenomenon, efforts to model this in simulations have increased. While current models can capture many of these physical processes, they currently assign a constant reaction shell thickness with little physical reasoning. This work remedies this problem by assigning a dynamic physically informed shell thickness to the reacting particles, using solid analysis. The shell thickness of the particles impacts the rate of change of reacted mass in the system, as well as the rate at which the particles react. The model is based on a simple stress–strain relationship and gives a dynamic assignment for when the reacting particle should begin to fracture. We compare our model to the previous computational and simulation data to analyze the effects of different model parameters.

42 ENGINEERING↗

A Dynamic PCA and Machine Learning Tool for Automated Identification of Solar Wind Disturbances Impacting Earth’s Magnetosphere

Earth’s magnetosphere is continuously impacted by solar wind and interplanetary magnetic field (IMF) disturbances, such as shocks, discontinuities, magnetic clouds and more. Understanding how such disturbances propagate from the Sun and what is their impact on the different magnetospheric domains is key to understanding and forecasting energy transfer from the solar wind to Earth. The large number of overlapping solar wind and magnetospheric missions carrying magnetometers and the recent advances in communications and data storage technologies have enabled an unprecedented quantity of high-fidelity magnetic field data captured by in-situ spacecraft to be available at the click of a button. However, this massive quantity of available data can prove unwieldy for researchers, limiting the identification of interesting phenomena and disturbances to a relatively small percentage of the total dataset. Several techniques have been previously developed for automated identification of specific types of magnetic anomalies, but these methods are typically mission-specific and can be difficult to generalize. We present initial results for a generic method of automated anomaly detection in magnetic field measurements based on dimensionality reduction and unsupervised clustering via machine learning. The benefit of our technique is its high degree of generalizability and flexibility which make it a most useful data survey tool for a wide range of magnetic field datasets. This method can also be applied simultaneously to other observed time-series properties like plasma density, pressure, and velocity for more accurate event identification. Additionally, the application of this method to data captured by multiple spacecraft enables the simultaneous identification of disturbances and the determination of their propagation characteristics. Initial evaluation of this technique has been performed using data from Magnetospheric MultiScale (MMS) and THEMIS-ARTEMIS missions, providing a testbed scenario for the future Heliophysics Environmental and Radiation Measurement Experiment Suite (HERMES) platform instruments that will measure solar wind and IMF properties from lunar orbit onboard the Gateway station.

Miguel Martinez-Ledesma↗

A Dynamic PCA and Machine Learning Tool for Automated Identification of Solar Wind Disturbances Impacting Earth’s Magnetosphere

Earth’s magnetosphere is continuously impacted by solar wind and interplanetary magnetic field (IMF) disturbances, such as shocks, discontinuities, magnetic clouds and more. Understanding how such disturbances propagate from the Sun and what is their impact on the different magnetospheric domains is key to understanding and forecasting energy transfer from the solar wind to Earth. The large number of overlapping solar wind and magnetospheric missions carrying magnetometers and the recent advances in communications and data storage technologies have enabled an unprecedented quantity of high-fidelity magnetic field data captured by in-situ spacecraft to be available at the click of a button. However, this massive quantity of available data can prove unwieldy for researchers, limiting the identification of interesting phenomena and disturbances to a relatively small percentage of the total dataset. Several techniques have been previously developed for automated identification of specific types of magnetic anomalies, but these methods are typically mission-specific and can be difficult to generalize. We present initial results for a generic method of automated anomaly detection in magnetic field measurements based on dimensionality reduction and unsupervised clustering via machine learning. The benefit of our technique is its high degree of generalizability and flexibility which make it a most useful data survey tool for a wide range of magnetic field datasets. This method can also be applied simultaneously to other observed time-series properties like plasma density, pressure, and velocity for more accurate event identification. Additionally, the application of this method to data captured by multiple spacecraft enables the simultaneous identification of disturbances and the determination of their propagation characteristics. Initial evaluation of this technique has been performed using data from Magnetospheric MultiScale (MMS) and THEMIS-ARTEMIS missions, providing a testbed scenario for the future Heliophysics Environmental and Radiation Measurement Experiment Suite (HERMES) platform instruments that will measure solar wind and IMF properties from lunar orbit onboard the Gateway station.

Miguel Martinez-Ledesma↗

Creation of Speed-of-Sound Inject Data for Technical Nuclear Forensics

Technical Nuclear Forensics (TNF) exercises simulate a detonation of a nuclear device within the United States, usually in a city. Speed-of-sound (SOS) phenomenology are the atmospheric overpressure and ground shock mechanical motions that are observed at over-pressure (air-blast and infrasound) and seismic sensors, respectively (Figure 1). Amplitudes of SOS data are related to the explosive yield (Kinney and Graham, 1985; Koper et al., 2002; Bonner et al., 2013ab; Ford et al., 2014, 2021; Templeton et al., 2018; Schnurr et al., 2020). Within the country, the United States Prompt Diagnostics System (USPDS) includes a network of geophysical sensors to capture such SOS signals. During the TNF exercise, the event data will be analyzed by the players who know nothing about the technical details of the source (e.g. location, yield, explosive). Specifically, they will use the Integrated Yield Determination Tool (IYDT) to estimate the yield and height-of-burst or depth-of-burial (HOB/DOB). The IYDT allows the user to measure features on the overpressure and seismic channels, evaluate the consistency of features and jointly estimate yield and HOB/DOB. For these exercises, SOS data are simulated for the location, emplacement and yield of the device and signals are propagated to the observing stations. This document describes the steps undertaken in the simulation, validation, preparation and verification of SOS signals for TNF exercises.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Calibrating hypersonic turbulence flow models with the HIFiRE-1 experiment using data-driven machine-learned models.

In this paper we study the efficacy of combining machine-learning methods with projection-based model reduction techniques for creating data-driven surrogate models of computationally expensive, high-fidelity physics models. Such surrogate models are essential for many-query applications e.g., engineering design optimization and parameter estimation, where it is necessary to invoke the high-fidelity model sequentially, many times. Surrogate models are usually constructed for individual scalar quantities. However there are scenarios where a spatially varying field needs to be modeled as a function of the model’s input parameters. Here we develop a method to do so, using projections to represent spatial variability while a machine-learned model captures the dependence of the model’s response on the inputs. The method is demonstrated on modeling the heat flux and pressure on the surface of the HIFiRE-1 geometry in a Mach 7.16 turbulent flow. The surrogate model is then used to perform Bayesian estimation of freestream conditions and parameters of the SST (Shear Stress Transport) turbulence model embedded in the high-fidelity (Reynolds-Averaged Navier–Stokes) flow simulator, using shock-tunnel data. The paper provides the first-ever Bayesian calibration of a turbulence model for complex hypersonic turbulent flows. We find that the primary issues in estimating the SST model parameters are the limited information content of the heat flux and pressure measurements and the large model-form error encountered in a certain part of the flow.

42 ENGINEERING↗

Experimental evaluation of a Mach 3.5 axisymmetric inlet

Wind tunnel test results for a large scale inlet model designed for Mach 3.5 are presented and compared with analytical predictions. The inlet is an axisymmetric mixed-compression type with a lip diameter of 49.723 cm. The inlet design was developed using analytical procedures. Data are shown for freestream Mach numbers from 0.6 to 3.5. The test results indicate that boundary layer bleed requirements can be accurately predicted. Good agreement was obtained with analytical predictions of the flowfield structure and boundary layer development in the supersonic diffuser yielding high performance at the design Mach number. The highest engine face total pressure recovery at Mach 3.5 was 85.8%; this was obtained at 0.05 Mach tolerance with only 2.8% total pressure distortion and 13.4% bleed. In the started Mach number range from 1.6 to 3.5, the total pressure recovery in the throat, downstream of the terminal normal shock, ranged between 91% and 95%. Total pressure losses in the subsonic diffuser varied from 3% to 13%. The higher losses occuring between Mach 2.5 and 3.2 were believed to be caused by the rapid rate of increase in the area of the diffuser just downstream of the throat, possibly coupled with inadequate centerbody throat bleed. In the unstarted mode at transonic speeds, the maximum inlet flow was over 99% of the theoretical maximum capture mass-flow.

Syberg, J.↗

Comparison of Electron Capture Rates in the N = 50 Region using 1D Simulations of Core-collapse Supernovae

Abstract Recent studies have highlighted the sensitivity of core-collapse supernovae (CCSNe) models to electron-capture (EC) rates on neutron-rich nuclei near the N = 50 closed-shell region. In this work, we perform a large suite of one-dimensional CCSN simulations for 200 stellar progenitors using recently updated EC rates in this region. For comparison, we repeat the simulations using two previous implementations of EC rates: a microphysical library with parametrized N = 50 rates (LMP), and an older independent-particle approximation (IPA). We follow the simulations through shock revival up to several seconds post-bounce, and show that the EC rates produce a consistent imprint on CCSN properties, often surpassing the role of the progenitor itself. Notable impacts include the timescale of core collapse, the electron fraction and mass of the inner core at bounce, the accretion rate through the shock, the success or failure of revival, and the properties of the central compact remnant. We also compare the observable neutrino signal of the neutronization burst in a DUNE-like detector, and find consistent impacts on the counts and mean energies. Overall, the updated rates result in properties that are intermediate between LMP and IPA, and yet slightly more favorable to explosion than both.

79 ASTRONOMY AND ASTROPHYSICS↗

Kinetic mix at gas-shell interface in inverted corona fusion targets

Gas-filled, laser-driven “inverted corona” fusion targets have attracted interest as a low-convergence neutron source and platform for studying kinetic physics. At the fill pressures under investigation, ejected particles from the shell can penetrate deeply into the gas before colliding, leading to significant mixing across the gas–shell interface. Here, we use kinetic-ion, fluid-electron hybrid particle-in-cell simulations to explore the nature of that mix. Simulations of the system demonstrate characteristics of a weakly collisional electrostatic shock, whereby a strong electric field accelerates shell ions into the rarefied gas and reflects upstream gas ions. This interpenetration is mediated by collisional processes: At higher initial gas pressure, fewer shell particles pass into the mix region and reach the hotspot. This effect is detectable through neutron yield scaling vs gas pressure. Predictions of neutron yield scaling show excellent agreement with experimental data recorded at the OMEGA laser facility, suggesting that 1D kinetic mechanisms are sufficient to capture the mix process.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Rayleigh–Taylor and Richtmyer–Meshkov instabilities: A journey through scales

Hydrodynamic instabilities such as Rayleigh–Taylor (RT) and Richtmyer–Meshkov (RM) instabilities usually appear in conjunction with the Kelvin–Helmholtz (KH) instability and are found in many natural phenomena and engineering applications. They frequently result in turbulent mixing, which has a major impact on the overall flow development and other effective material properties. This can either be a desired outcome, an unwelcome side effect, or just an unavoidable consequence, but must in all cases be characterized in any model. The RT instability occurs at an interface between different fluids, when the light fluid is accelerated into the heavy. The RM instability may be considered a special case of the RT instability, when the acceleration provided is impulsive in nature such as that resulting from a shock wave. Here in this pedagogical review, we provide an extensive survey of the applications and examples where such instabilities play a central role. First, fundamental aspects of the instabilities are reviewed including the underlying flow physics at different stages of development, followed by an overview of analytical models describing the linear, nonlinear and fully turbulent stages. RT and RM instabilities pose special challenges to numerical modeling, due to the requirement that the sharp interface separating the fluids be captured with fidelity. These challenges are discussed at length here, followed by a summary of the significant progress in recent years in addressing them. Examples of the pivotal roles played by the instabilities in applications are given in the context of solar prominences, ionospheric flows in space, supernovae, inertial fusion and pulsed-power experiments, pulsed detonation engines and Scramjets. Progress in our understanding of special cases of RT/RM instabilities is reviewed, including the effects of material strength, chemical reactions, magnetic fields, as well as the roles the instabilities play in ejecta formation and transport, and explosively expanding flows. The article is addressed to a broad audience, but with particular attention to graduate students and researchers who are interested in the state-of-the-art in our understanding of the instabilities and the unique issues they present in the applications in which they are prominent.

42 ENGINEERING↗

Numerical simulation of a powered-lift landing, tracking flow features using overset grids, and simulation of high lift devices on a fighter-lift-and-control wing

Attached as appendices to this report are documents describing work performed on the simulation of a landing powered-lift delta wing, the tracking of flow features using overset grids, and the simulation of flaps on the Wright Patterson Lab's fighter-lift-and-control (FLAC) wing. Numerical simulation of a powered-lift landing includes the computation of flow about a delta wing at four fixed heights as well as a simulated landing, in which the delta wing descends toward the ground. Comparison of computed and experimental lift coefficients indicates that the simulations capture the qualitative trends in lift-loss encountered by thrust-vectoring aircraft operating in ground effect. Power spectra of temporal variations of pressure indicate computed vortex shedding frequencies close to the jet exit are in the experimentally observed frequency range; the power spectra of pressure also provide insights into the mechanisms of lift oscillations. Also, a method for using overset grids to track dynamic flow features is described and the method is validated by tracking a moving shock and vortices shed behind a circular cylinder. Finally, Chimera gridding strategies were used to develop pressure coefficient contours for the FLAC wing for a Mach no. of 0.18 and Reynolds no. of 2.5 million.

Chawla, Kalpana↗

Simulation to a Newborn Supernova Remnant from a Low-mass Iron Core Star

Supernova remnant observations show a high degree of asymmetry, mixing, and inhomogeneity. These asymmetries are seeded during the early seconds of the explosion and are further enhanced and modified as the shock and ejecta move through the stellar progenitor and into the circumstellar medium. We present simulations of a 9.6 M⊙ zero-metallicity progenitor initialized after shock revival and evolved for several years when the ejecta is in the circumstellar medium. A suite of 1D and 2D simulations examines the effects of neutron-star wind and radioactive decay heating. In 1D, decay heating forms a low-density bubble that suppresses the reverse shock. While in 2D, the heating is localized to metal-rich pockets, inflating them and compressing the surrounding material into dense shells. In 3D, the neutron-star wind and decay heating modify the plume morphology, producing more large-scale structures. The extended plume morphology leads to an asymmetrical shock breakout. After breakout, the leading plumes cannot keep up with the shock front, resulting in deceleration and fragmentation by the reverse shock while retaining the large-scale asymmetry. The projected ejecta morphology and velocities are strongly viewing angle dependent. The relatively uniform metal-rich distribution does not resemble the strongly inhomogeneous ejecta structure of Cas A. The 160-isotope decay network shows that 24.4% of the radioactive heating comes from decay chains other than the canonical 56Ni chain. The low explosion energy, low 56Ni yield, and Ni/Fe ratio greater than unity suggest an observational signature similar to an electron capture supernova.

Neopane, Sudarshan [University of Tennessee (UT)]↗

Understanding the low-temperature chemistry of 1,2,4-trimethylbenzene

1,2,4-trimethylbenzene is an important representative aromatic component of gasoline/diesel/jet fuels and thus it is necessary to understand its low-temperature chemistry. In this paper, ignition delay times (IDTs) of both 1,2,4-trimethylbenzene (124TMB) and its blends with n -heptane were measured at engine-like conditions using both a high-pressure shock tube and a rapid compression machine for fuel in ‘air’ mixtures at pressures of 10 and 30 atm and at temperatures in the range 600 – 1100K. The experiments in this study show for the first time that 124TMB presents a two-stage ignition behavior at engine relevant conditions. Blending n -heptane with 124TMB can significantly increase mixture reactivity at temperatures below 1000K. A new detailed mechanism has been developed to simulate the experimentally measured IDT data. The mechanism can capture well the two-stage ignition behavior as well as the ignition delays at different pressures, equivalence ratios over a wide temperature range, for both pure fuels and their blended mixtures. Flux analyses show that the benzylic radicals (formed via H-atom abstraction from the methyl groups ortho-sites on 124TMB) can add to O 2 forming $\mathrm{R\dot{O}_2}$ radicals, which can isomerize to $\dot{Q}$OOH by intramolecular H-atom transfer from the ortho- methyl group and these $\dot{Q}$OOH radicals undergo a second addition to O 2 . This is analogous to the chain branching reaction pathways of alkanes. The chain branching reaction pathways are responsible for the first-stage heat release of 124TMB. In conclusion, the competitions between chain branching and both chain propagating and chain termination reaction pathways lead to a less pronounced negative temperature coefficient (NTC) behavior for 124TMB oxidation, compared to two-stage ignition behavior observed for alkanes and other fuels.

1,2,4-trimethylbenzene↗

Numerical Experiment with Time and Spatial Accuracy of Navier-Stokes Computation For Helicopter Problems

Helicopter flowfields are highly unsteady, nonlinear and three-dimensional. In forward flight and in hover, the rotor blades interact with the tip vortex and wake sheet developed by either itself or the other blades. This interaction, known as blade-vortex interactions (BVI), results in unsteady loading of the blades and can cause a distinctive acoustic signature. Accurate and cost-effective computational fluid dynamic solutions that capture blade-vortex interactions can help rotor designers and engineers to predict rotor performance and to develop designs for low acoustic signature. Such a predictive method must preserve a blade's shed vortex for several blade revolutions before being dissipated. A number of researchers have explored the requirements for this task. This paper will outline some new capabilities that have been added to the NASA Ames' OVERFLOW code to improve its overall accuracy for both vortex capturing and unsteady flows. To highlight these improvements, a number of case studies will be presented. These case studies consist of free convection of a 2-dimensional vortex, dynamically pitching 2-D airfoil including light-stall, and a full 3-D unsteady viscous solution of a helicopter rotor in forward flight In this study both central and upwind difference schemes are modified to be more accurate. Central difference scheme is chosen for this simulation because the flowfield is not dominated by strong shocks. The feature of shock-vortex interaction in such a flow is less important than the dominant blade-vortex interaction. The scheme is second-order accurate in time and solves the thin-layer Navier-Stokes equations in fully-implicit manner at each time-step. The spatial accuracy is either second and fourth-order central difference or third-order upwind difference using Roe-flux and MUSCLE scheme. This paper will highlight and demonstrate the methods for several sample cases and for a helicopter rotor. Preliminary computations on a rotor were performed by using this method and are in the process of documentation.

Ahmad, Jasim↗

Boundary Layer Instabilities Over a Cone-Cylinder-Flare Model at Mach 6

Computations are performed to investigate the boundary-layer instabilities over a sharp cone-cylinder-flare model at zero degrees angle of attack. The model geometry and the flow conditions are selected to match the experiments conducted in the Boeing/AFOSR Mach 6 Quiet Tunnel (BAM6QT) at Purdue University. The geometry consists of a nominally sharp 5-degree half-angle cone, followed by a cylindrical segment and then a 10-degree flare. An axisymmetric separation bubble is generated as a result of the laminar shock/boundary-layer interaction in the cylinder-flare region. The comparison of the laminar flow solution and the schlieren images shows a remarkable agreement between the respective locations of both the boundarylayer edge and the reattachment shock. The predicted heat flux distribution is also in agreement with the measured values downstream of the reattachment location. The analysis of convective and global instabilities is performed for flare half angles equal to 8, 10, and 12 degrees and nosetip radii equal to 0.1, 1, and 5 mm. The linear amplification of first and second Mack mode instabilities that begin to amplify in the cone region are computed with a combination of the parabolized stability equations (PSE) and the harmonic linearized Navier-Stokes equations (HLNSE). The predicted frequency spectra of the surface pressure fluctuations associated with both planar and oblique instability waves are compared with the measured spectra at the various locations of the PCB and Kulite sensors. The comparison shows that the computational analysis captures the distinct lobes within the disturbance amplification spectra measured in the experiments, but some differences in amplification characteristics are noted at low frequencies. Overall, the oblique disturbances are found to be more amplified than the planar disturbances. To our knowledge, this represents the first successful comparison between convective instability analysis and measured surface pressure fluctuations for a hypersonic configuration with a separation bubble. Finally, the global instability analysis shows that the laminar flow becomes supercritical for flare half angles larger than 8 degrees. The unstable global mode for the experimental configuration of a 10 degrees flare and a sharp nosetip cone corresponds to a stationary three-dimensional disturbance that is concentrated in the recirculation region and achieves its maximum growth rate for an azimuthal wavenumber of 5.

Boundary layer transition↗

Background-Oriented Schlieren used in a hypersonic inlet test at NASA GRC

Background Oriented Schlieren (BOS) is a derivative of the classical schlieren technology, which is used to visualize density gradients, such as shock wave structures in a wind tunnel. Changes in refractive index resulting from density gradients cause light rays to bend, resulting in apparent motion of a random background pattern. The apparent motion of the pattern is determined using cross-correlation algorithms (between no-flow and with-flow image pairs) producing a schlieren-like image. One advantage of BOS is its simplified setup which enables a larger field-of-view (FOV) than traditional schlieren systems. In the present study, BOS was implemented into the Combined Cycle Engine Large-Scale Inlet Mode Transition Experiment (CCE LIMX) in the 10x10 Supersonic Wind Tunnel at NASA Glenn Research Center. The model hardware for the CCE LIMX accommodates a fully integrated turbine based combined cycle propulsion system. To date, inlet mode transition between turbine and ramjet operation has been successfully demonstrated. High-speed BOS was used to visualize the behavior of the flow structures shock waves during unsteady inlet unstarts, a phenomenon known as buzz. Transient video images of inlet buzz were recorded for both the ramjet flow path (high speed inlet) and turbine flow path (low speed inlet). To understand the stability limits of the inlet, operation was pushed to the point of unstart and buzz. BOS was implemented in order to view both inlets simultaneously, since the required FOV was beyond the capability of the current traditional schlieren system. An example of BOS data (Images 1-6) capturing inlet buzz are presented.

Background-oriented schlieren↗

Furrow microtubules and localized exocytosis in cleaving Xenopus laevis embryos

In dividing Xenopus eggs, furrowing is accompanied by expansion of a new domain of plasma membrane in the cleavage plane. The source of the new membrane is known to include a store of oogenetically produced exocytotic vesicles, but the site where their exocytosis occurs has not been described. Previous work revealed a V-shaped array of microtubule bundles at the base of advancing furrows. Cold shock or exposure to nocodazole halted expansion of the new membrane domain, which suggests that these microtubules are involved in the localized exocytosis. In the present report, scanning electron microscopy revealed collections of pits or craters, up to approximately 1.5 micro m in diameter. These pits are evidently fusion pores at sites of recent exocytosis, clustered in the immediate vicinity of the deepening furrow base and therefore near the furrow microtubules. Confocal microscopy near the furrow base of live embryos labeled with the membrane dye FM1-43 captured time-lapse sequences of individual exocytotic events in which irregular patches of approximately 20 micro m(2) of unlabeled membrane abruptly displaced pre-existing FM1-43-labeled surface. In some cases, stable fusion pores, approximately 2 micro m in diameter, were seen at the surface for up to several minutes before suddenly delivering patches of unlabeled membrane. To test whether the presence of furrow microtubule bundles near the surface plays a role in directing or concentrating this localized exocytosis, membrane expansion was examined in embryos exposed to D(2)O to induce formation of microtubule monasters randomly under the surface. D(2)O treatment resulted in a rapid, uniform expansion of the egg surface via random, ectopic exocytosis of vesicles. This D(2)O-induced membrane expansion was completely blocked with nocodazole, indicating that the ectopic exocytosis was microtubule-dependent. Results indicate that exocytotic vesicles are present throughout the egg subcortex, and that the presence of microtubules near the surface is sufficient to mobilize them for exocytosis at the end of the cell cycle.

Non-NASA Center↗