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At least 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

Improved Chemistry and Attenuation Models for Communication Blackout Simulation During Mars 2020 Entry

As a blunt body enters a planetary atmosphere, a plasma forms in the hypersonic shock layer and attenuates radio communication causing signal blackout for some duration of the entry sequence. In our previous work,1 computational fluid dynamics (CFD) was applied to model the entry flow around the Mars 2020 spacecraft, including ionization and electron density throughout the flow field, and predict ultra-high frequency (UHF) radio wave attenuation due to electrons. In total, 17 chemical species and their spatial profiles are modelled around the Mars 2020 spacecraft at 11 different points in time during entry. Although the simulation predicted the onset of attenuation well, the timing of the end of the predicted blackout window significantly preceded the end time observed during the 2021 landing. The present work seeks to improve the attenuation model by accounting for the fact that electrons undergo collisions with heavier species in the flow, which is an effect that was neglected in previous analyses. It is determined that including electron collisions increases the overall magnitude of attenuation predicted especially towards the end of the measured attenuation period, improving qualitative agreement between predicted and measured attenuation to both spacecraft receiving the signal from Mars 2020. To explore the remaining uncertainty in signal attenuation predictions further, a sensitivity study is performed to investigate the impact of associative ionization and electron-impact ionization rate coefficients on the electron density predicted by CFD and on the resulting attenuation predictions. These coefficients are believed to contain up to order-of-magnitude uncertainty, and therefore may significantly affect the number density of electrons throughout the flow field. Variations in associative ionization coefficients demonstrate significant impact on the magnitude of attenuation due to variation in the electron density coming from associative ionization. However, the start and end times of the predicted signal attenuation period are only slightly impacted by said variation.

Eve Papajak↗
NASA NTRS2024

Improved Chemistry and Attenuation Models for Communication Blackout Simulation During Mars 2020 Entry

As a blunt body enters a planetary atmosphere, a plasma forms in the hypersonic shock layer and attenuates radio communication causing signal blackout for some duration of the entry sequence. In our previous work,1 computational fluid dynamics (CFD) was applied to model the entry flow around the Mars 2020 spacecraft, including ionization and electron density throughout the flow field, and predict ultra-high frequency (UHF) radio wave attenuation due to electrons. In total, 17 chemical species and their spatial profiles are modelled around the Mars 2020 spacecraft at 11 different points in time during entry. Although the simulation predicted the onset of attenuation well, the timing of the end of the predicted blackout window significantly preceded the end time observed during the 2021 landing. The present work seeks to improve the attenuation model by accounting for the fact that electrons undergo collisions with heavier species in the flow, which is an effect that was neglected in previous analyses. It is determined that including electron collisions increases the overall magnitude of attenuation predicted especially towards the end of the measured attenuation period, improving qualitative agreement between predicted and measured attenuation to both spacecraft receiving the signal from Mars 2020. To explore the remaining uncertainty in signal attenuation predictions further, a sensitivity study is performed to investigate the impact of associative ionization and electron-impact ionization rate coefficients on the electron density predicted by CFD and on the resulting attenuation predictions. These coefficients are believed to contain up to order-of-magnitude uncertainty, and therefore may significantly affect the number density of electrons throughout the flow field. Variations in associative ionization coefficients demonstrate significant impact on the magnitude of attenuation due to variation in the electron density coming from associative ionization. However, the start and end times of the predicted signal attenuation period are only slightly impacted by said variation.

Eve Papajak↗
DOE OSTI2026

Calculating shock Hugoniot and isentropes using multiphase equation of state tables and application to shock and release of diamond ablators in inertial confinement fusion implosions

Advances in shock and ramp compression techniques now allow experimental access to unprecedented extreme conditions of pressure and temperature, providing a means to test theoretical models. Here, we describe a simple methodology to compute multi-phase shock Hugoniot and isentropes using multiphase equation of state tables. We treat explicitly the phase coexistence along the phase boundary to reveal the evolution of the sample as it undergoes the phase transformation in adiabatic conditions. We illustrate the method by calculating the predicted shock and shock-and-release behavior of diamond at conditions relevant for the initial stage of inertial confinement fusion implosions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Reduced‐Order Modeling of Energetic Materials Using Physics‐Aware Recurrent Convolutional Neural Networks in a Latent Space (LatentPARC)

Physics-aware deep learning (PADL) has gained popularity for use in spatiotemporal dynamics simulations, such as those in computational modeling of energetic materials (EM). We show that the challenge PADL methods face while learning complex field evolution problems can be simplified and accelerated by decoupling it into two tasks: learning complex geometric features in evolving fields and modeling dynamics over these features in a lower-dimensional feature space. We build upon our previous work on physics-aware recurrent convolutional neural networks (PARC). PARC embeds knowledge of underlying physics into its neural network architecture for more robust and accurate prediction of evolving physical fields. PARC was shown to effectively learn complex nonlinear features such as the formation of hotspots and coupled shock fronts in various initiation scenarios of EMs, as a function of microstructures, serving effectively as a microstructure-aware burn model. Here, we further accelerate PARC and reduce its computational cost by projecting the original dynamics onto a lower-dimensional invariant manifold, or “latent space.” The projected latent representation encodes the complex geometry of evolving fields (e.g., temperature and pressure) in a set of data-driven features. The reduced dimension of this latent space allows us to learn the dynamics during the initiation of EM with a lighter and more efficient model. We observe a significant decrease in training and inference time while maintaining results comparable to PARC at inference. This work takes steps towards enabling rapid prediction of EM thermomechanics at larger scales and characterization of EM structure–property–performance linkages at a full application scale.

Mathematics and Computing↗
NASA NTRS1974

Pioneer 10 observations of the solar wind interation with Jupiter

Pioneer 10 Plasma Analyzer experiment flight data during the Jupiter flyby are presented. The observations show that the interaction of Jupiter's magnetic field with the solar wind is similar in many ways to that at earth, but the scale size is over 100 times larger. Jupiter is found to have a detached standing bow shock wave of high Alfven Mach number. Jupiter has a prominent magnetopause which deflects the magnetosheath plasma and excludes its direct entry into the Jovian magnetosphere. The sunward hemisphere of Jupiter's outer magnetosphere is found to be highly inflated with thermal plasma and a high beta region which is highly responsive to changes in solar wind dynamic pressure. Observational arguments are presented which tend to discount a thin disklike magnetosphere but, rather, favor a Jovian magnetosphere, albeit probabily considerably flattened as compared to the earth's magnetosphere, yet still with reasonable thickness. Results concerning the shock jump conditions, the magnetosheath flow field and inferred internal magnetospheric plasma are presented.

Wolfe, J. H.↗
DOE OSTI2026

A wide-range thermodynamically consistent constitutive model for dynamic loading of partially saturated porous media

SUMMARY This paper presents a novel thermodynamically consistent constitutive model for partially saturated porous rocks across a wide range of conditions. The material states generated behind the shock wave from an explosive source can vary significantly, ranging from crushed and melted rock near the source to a poroelastic medium in the far field. In the model, rock strength is determined by the effective pressure, which is calculated using two independent equations of state: one for the solid rock and another for the pore fluid. The model accounts for shock-induced liquefaction resulting from fluid pressure buildup in the pore spaces near the explosive source. Simultaneously, it describes the increase in wave propagation speed due to elastic pore contraction in both dry and partially saturated rocks. This model is applied to investigate how fluid saturation affects the amplitude and shape of the generated waves, as well as the residual stress surrounding the cavity formed by spherical explosions.

Vorobiev, Oleg [Lawrence Livermore National Labora↗
NASA NTRS1990

The dynamics and control of fluctuating pressure loads in the reattachment region of a supersonic free shear layer

The primary aim is to investigate the mechanisms which cause the unsteady wall-pressure fluctuations in shock wave turbulent shear layer interactions. The secondary aim is to find means to reduce the magnitude of the fluctuating pressure loads by controlling the unsteady shock motion. The particular flow proposed for study is the unsteady shock wave interaction formed in the reattachment zone of a separated supersonic flow. Similar flows are encountered in many practical situations, and they are associated with high levels of fluctuating wall pressure. Wall pressure fluctuations were measured in the reattachment region of the supersonic free shear layer. The free shear layer was formed by the separation of a Mach 2.9 turbulent boundary layer from a backward facing step. Reattachment occurred on a 20 deg ramp. By adjusting the position of the ramp, the base pressure was set equal to the freestream pressure, and the free shear layer formed in the absence of a separation shock. An array of flush-mounted, miniature, high-frequency pressure transducers was used to make multichannel measurements of the fluctuating wall pressure in the vicinity of the reattachment region. Contrary to previous observations of this flow, the reattachment region was found to be highly unsteady, and the pressure fluctuations were found to be significant. The overall behavior of the wall pressure loading is similar in scale and magnitude to the unsteadiness of the wall pressure field in compression ramp flows at the same Mach number. Rayleigh scattering was used to visualize the instantaneous shock structure in the streamwise and spanwise direction. Spanwise wrinkles on the order of half the boundary layer thickness were observed.

Smits, A. J.↗
NASA NTRSDate not supplied

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↗
NASA NTRSDate not supplied

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↗
DOE OSTI2022

Developing Reaction Chemistry Models from Reactive Molecular Dynamics: TATB

Reactive Molecular Dynamic (RMD) are used to simulate the cook-off chemistry of TATB at a variety of fixed density and fixed temperature conditions. The chemical transformations are monitored using a Coordination Geometry Analysis (CGA) approach which tracks which atom types are bonded to each specific atom. This particularly identifies oxidation state changes that occur during the transformations. Correlations between these different chemical changes are identified using a Non-negative Matrix Factorization (NMF) approach. These identify reduced order chemistry models for the TATB system which contains six components whose concentration profiles are a function of both the temperature and density/pressure. The time histories of these transformations appear to show exponential growth/decay properties that could be fit with Arrhenius rates. These components should form the basis of deflagration rate models for these materials which could then be used in mesoscale simulations to analyze accidental initiation, shock-to-detonation and detonation propagation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1994

Interpretation of waverider performance data using computational fluid dynamics

A computational study was conducted to better understand experimental results obtained from wind-tunnel tests of a Mach 4 conical-flow-derived waverider and a comparative reference configuration, which showed that the aerodynamic performance of the reference configuration was slightly better than that of the waverider. The computational results showed that the predicted surface pressure values and the integrated lift and drag coefficients were much lower for the reference model because the reference model bottom is an expansion surface. However, the lift-drag ratios for the reference model were higher due to a relatively low drag for a comparable amount of lift. The results also showed that the reference model exhibited the same shock attachment characteristics as the conical-flow-derived waverider, and is therefore also a waverider. The shock attachment characteristic gives the waverider a performance advantage over conventional hypersonic vehicles, and the results suggest that altering the bottom surface does not cause significant performance degradation. Flowfield solutions also show that the conical-flow waverider model has better propulsion/airframe integration characteristics than the reference configuration. The results also suggest that generating flowfields other than conical ones may be used to design waveriders with improved aerodynamic performance.

COMPUTATIONAL FLUID DYNAMICS↗
NASA NTRS1981

Supersonic Stall Flutter of High Speed Fans

An analytical model is developed for predicting the onset of supersonic stall bending flutter in axial flow compressors. The analysis is based on a modified two dimensional, compressible, unsteady actuator disk theory. It is applied to a rotor blade row by considering a cascade of airfoils whose geometry and dynamic response coincide with those of a rotor blade element at 85 percent of the span height (measured from the hub). The rotor blades are assumed to be unshrouded (i.e., free standing) and to vibrate in their first flexural mode. The effects of shock waves and flow separation are included in the model through quasi-steady, empirical, rotor total-pressure-loss and deviation-angle correlations. The actuator disk model predicts the unsteady aerodynamic force acting on the cascade blading as a function of the steady flow field entering the cascade and the geometry and dynamic response of the cascade. Calculations show that the present model predicts the existence of a bending flutter mode at supersonic inlet Mach numbers. This flutter mode is suppressed by increasing the reduced frequency of the system or by reducing the steady state aerodynamic loading on the cascade. The validity of the model for predicting flutter is demonstrated by correlating the measured flutter boundary of a high speed fan stage with its predicted boundary. This correlation uses a level of damping for the blade row (i.e., the log decrement of the rotor system) that is estimated from the experimental flutter data. The predicted flutter boundary is shown to be in good agreement with the measured boundary.

Adamczyk, J. J.↗
DOE OSTI2024

Impulse-driven release of gas-encapsulated drops

Gas-encapsulated drops, much like antibubbles, are drops enclosed in a bubble within a liquid. They show potential as payload carriers in fluid transport and mixing techniques where sound waves can be leveraged to induce the collapse of the gas core and the subsequent release of the drop. Here, the interaction of millimetre-sized gas-encapsulated drops with impulsive laser-induced shock waves is investigated to gain fundamental insights into the release process. Experimental synchrotron X-ray phase contrast imaging, which allows the drop dynamics to be visualised inside the encapsulating bubble, is complemented by numerical simulations to study the intricate physics at play. Three drop dynamical release regimes are discovered, namely the drop impact , partial deposition and jet impact regimes. The regime type is mainly dependent on the shape of the bubble interface impacting the drop and the associated Weber and Reynolds numbers. The drop dynamics of the drop impact and partial deposition regimes show similarities with the canonical configuration of drops impacting flat liquid surfaces, whereas the jet impact regime resembles binary drop collisions, which allows existing scaling laws to be applied to describe the underlying processes. The release of the drop is investigated numerically. The time evolution of the drop dissemination within the surrounding liquid discloses enhanced mixing for dynamics involving high Weber and Reynolds numbers such as the drop impact and jet impact regimes.

42 ENGINEERING↗
NASA NTRS1988

Origin of petrofabrics and magnetic anisotropy in ordinary chondrites

Three-dimensional finite strain and magnetic susceptibility anisotropy have been determined for 15 ordinary chondrites. The axes of strain and magnetic ellipsoids roughly correlate in both magnitude and orientation. The shapes of these ellipsoids are generally oblate spheroids that define a dominant foliation and a weak lineation. These characteristics suggest deformation involving uniaxial compaction. The degree of uniaxial deformation correlates with intensity of shock, as indicated by optical, TEM and chemical criteria. These data, plus the lack of a relationship between foliation and metamorphic history, indicate that dynamic processes, i.e., impacts, produced planar deformation fabrics in chondrites.

Sneyd, Deana S.↗
NASA NTRS1988

Numerical methods for turbulent flow

It has generally become accepted that the Navier-Strokes equations predict the dynamic behavior of turbulent as well as laminar flows of a fluid at a point in space away form a discontinuity such as a shock wave. Turbulence is also closely related to the phenomena of non-uniqueness of solutions of the Navier-Strokes equations. These second order, nonlinear partial differential equations can be solved analytically for only a few simple flows. Turbulent flow fields are much to complex to lend themselves to these few analytical methods. Numerical methods, therefore, offer the only possibility of achieving a solution of turbulent flow equations. In spite of recent advances in computer technology, the direct solution, by discrete methods, of the Navier-Strokes equations for turbulent flow fields is today, and in the foreseeable future, impossible. Thus the only economically feasible way to solve practical turbulent flow problems numerically is to use statistically averaged equations governing mean-flow quantities. The objective is to study some recent developments relating to the use of numerical methods to study turbulent flow.

Turner, James C., Jr.↗
NASA NTRS1989

A class of high resolution explicit and implicit shock-capturing methods

An attempt is made to give a unified and generalized formulation of a class of high resolution, explicit and implicit shock capturing methods, and to illustrate their versatility in various steady and unsteady complex shock wave computations. Included is a systematic review of the basic design principle of the various related numerical methods. Special emphasis is on the construction of the basis nonlinear, spatially second and third order schemes for nonlinear scalar hyperbolic conservation laws and the methods of extending these nonlinear scalar schemes to nonlinear systems via the approximate Riemann solvers and the flux vector splitting approaches. Generalization of these methods to efficiently include equilibrium real gases and large systems of nonequilibrium flows are discussed. Some issues concerning the applicability of these methods that were designed for homogeneous hyperbolic conservation laws to problems containing stiff source terms and shock waves are also included. The performance of some of these schemes is illustrated by numerical examples for 1-, 2- and 3-dimensional gas dynamics problems.

Yee, H. C.↗
NASA NTRS1989

Calculation of nonequilibrium hydrogen-air reactions with implicit flux vector splitting method

Two methods, fully- and loosely-coupled, are developed to incorporate nonequilibrium hydrogen-air chemistry into the fluid dynamic implicit flux vector splitting code (F3D). The new code (F3D/Chem) is validated against other existing codes for two cases: nozzle expansion, and shock-induced combustion around a blunt body. The shock-induced combustion case is compared also with an experimental data. The reaction rate constants are varied in an effort to reproduce the experimental data. The fully- and loosely-coupled methods are found to yield comparable results, but the computation time is shorter using the loosely-coupled method. The present method is found to reproduce results obtained using different existing codes. The experimental data was not reproduced with any selected rate coefficients set.

Lee, Seung-Ho↗
NASA NTRS1992

Transonic aeroelastic computations on wings using Navier-Stokes equations

Aeroelastic computations are made on fighter type wings in the transonic regime. The flow is modeled using the Navier-Stokes equations and is coupled with structural equations of motion. The flow equations are solved by a time accurate finite difference scheme with moving grids. The coupled aeroelastic equations of motion are solved using the linear acceleration method. The configuration adaptive dynamic grids are time-accurately generated using the aeroelastically deformed shape of the wing. Computations are made for oscillating rigid wings with moving shock waves in the presence of leading edge vortices. The computed results compare well with the experiment. Unsteady computations are made to demonstrate the shock-vortex interaction phenomenon on wings in ramp motion. Effects of flexibility and pitch rate are demonstrated for flows with vortices.

Guruswamy, Guru P.↗