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At least 91 records · Page 5

Hybrid Kinetic Model of the Interaction Between the Dense Plasma Clouds and Magnetospheric Plasma on Large Time and Spatial Scales, and Comparison With MMS Observations

We present a new simulation results of the cloud dynamics in the ambient magnetospheric plasma on the large time and spatial scales. It was assumed that these impulsive structures observed by the MMS spacecraft originally were created because of the reconnection at the magnetopause. Our new 3-D hybrid kinetic modeling on the large time and spatial scales captures several of these processes: an excitation of the electromagnetic waves (whistler and shear-Alfvén waves) and plasma instabilities (mirror and flute); a formation of shock waves, and collapsing diamagnetic cavity; particle acceleration. A strong overshoot in plasma density profile was observed in the modeling and MMS observation at the interface between the cloud and magnetospheric plasma. The cloud expansion into ambient magnetospheric plasma causes the flute waves connected with excitation of the Rayleigh-Taylor instability observed at the overshoot in plasma density profile across the external magnetic field. The modeling demonstrates a formation of the whistler waves at the initial stage which propagate in the external magnetic field direction. At the later stage, a formation of shear-Alfvén waves was observed

A. S. Lipatov↗

A Hybrid CFD/Engineering Model Tool for Lunar Lander Surface Erosion Prediction

Plume-Surface Interaction (PSI) between lander engine plumes and landing area regolith poses risks to the landers and space exploration missions through view obscuration and high-energy ejecta impacts from eroded particle clouds and vehicle tilting from plume-induced craters. To address these risks, NASA MSFC Fluid Dynamics Branch (ER42) has developed a cascade of predictive simulation capabilities for PSI, including the recent development of a hybrid CFD/engineering model tool that allows for rapid PSI simulations with a descending/ascending vehicle and an eroding surface. The development of this fully-coupled, moving body/eroding surface simulation capability is detailed along with a demonstration of the tool’s capabilities on the Apollo 12 Lunar Module landing. Predictions of eroded mass flow rates as a function of time are verified against Apollo 12 flight data, from which the developed, viscous erosion model has been calibrated.

Plume Surface Interaction↗

A Hybrid CFD/Engineering Model Tool for Lunar Lander Surface Erosion Prediction

Plume-Surface Interaction (PSI) between lander engine plumes and landing area regolith poses risks to the landers and space exploration missions through view obscuration and high-energy ejecta impacts from eroded particle clouds and vehicle tilting from plume-induced craters. To address these risks, NASA MSFC Fluid Dynamics Branch (ER42) has developed a cascade of predictive simulation capabilities for PSI, including the recent development of a hybrid CFD/engineering model tool that allows for rapid PSI simulations with a descending/ascending vehicle and an eroding surface. The development of this fully-coupled, moving body/eroding surface simulation capability is detailed along with a demonstration of the tool’s capabilities on the Apollo 12 Lunar Module landing. Predictions of eroded mass flow rates as a function of time are verified against Apollo 12 flight data, from which the developed, viscous erosion model has been calibrated.

Plume Surface Interaction↗

Comparison of Ice Shapes on Full-Chord and Truncated Swept Wing Models

A research program was conducted to evaluate the effectiveness of icing tunnel hybrid model design. A hybrid design is where the full-scale leading edge of a wing section is maintained only to a certain percentage of the local chord, while the aft section of the model is redesigned into a shortened or truncated planform. Ice shape geometries on a full-chord length and hybrid versions of the swept CRM65 wing model were obtained in NASA Icing Research Tunnel and compared. For most test conditions, the overall size and shape of the ice shapes compared well. On the main part of the ice shape, the hybrid model had larger chordwise extent, resulting in wider ice shape. For the scallop ice shapes, the ice shape heights at attachment line location were identical. For conditions that produced rime shape, hybrid model ice shapes were larger overall, even at the attachment line location. The only location where there was more ice on the full chord model was on the lower surface, downstream of where the hybrid model no longer had full-scale leading edge. For the test conditions where ice mass measurements were acquired for both models, the full-chord models had 11-22% less ice mass than on the hybrid wing. These differences were larger and opposite of those predicted from LEWICE 3D ice prediction calculations. Further investigation is needed in order determine the cause of the differences between the full-chord and hybrid models.

Icing↗

Comparison of Ice Shapes on Full-Chord and Truncated Swept Wing Models

A research program was conducted to evaluate the effectiveness of icing tunnel hybrid model design. A hybrid design is where the full-scale leading edge of a wing section is maintained only to a certain percentage of the local chord, while the aft section of the model is redesigned into a shortened or truncated planform. Ice shape geometries on a full-chord length and hybrid versions of the swept CRM65 wing model were obtained in NASA Icing Research Tunnel and compared. For most test conditions, the overall size and shape of the ice shapes compared well. On the main part of the ice shape, the hybrid model had larger chordwise extent, resulting in wider ice shape. For the scallop ice shapes, the ice shape heights at attachment line location were identical. For conditions that produced rime shape, hybrid model ice shapes were larger overall, even at the attachment line location. The only location where there was more ice on the full chord model was on the lower surface, downstream of where the hybrid model no longer had full-scale leading edge. For the test conditions where ice mass measurements were acquired for both models, the full-chord models had 11-22% less ice mass than on the hybrid wing. These differences were larger and opposite of those predicted from LEWICE 3D ice prediction calculations. Further investigation is needed in order determine the cause of the differences between the full-chord and hybrid models.

Icing↗

An Intercomparison of 2-D Models Within a Common Framework

A model intercomparison among the Atmospheric and Environmental Research (AER) 2-D model, the Goddard Space Flight Center (GSFC) 2-D model, and the Lawrence Livermore National Laboratory 2-D model allows us to separate differences due to model transport from those due to the model's chemical formulation. This is accomplished by constructing two hybrid models incorporating the transport parameters of the GSFC and LLNL models within the AER model framework. By comparing the results from the native models (AER and e.g. GSFC) with those from the hybrid model (e.g. AER chemistry with GSFC transport), differences due to chemistry and transport can be identified. For the analysis, we examined an inert tracer whose emission pattern is based on emission from a High Speed Civil Transport (HSCT) fleet; distributions of trace species in the 2015 atmosphere; and the response of stratospheric ozone to an HSCT fleet. Differences in NO(y) in the upper stratosphere are found between models with identical transport, implying different model representations of atmospheric chemical processes. The response of O3 concentration to HSCT aircraft emissions differs in the models from both transport-dominated differences in the HSCT-induced perturbations of H2O and NO(y) as well as from differences in the model represent at ions of O3 chemical processes. The model formulations of cold polar processes are found to be the most significant factor in creating large differences in the calculated ozone perturbations

Weisenstein, Debra K.↗

Model-Based Prognostics of Hybrid Systems

Model-based prognostics has become a popular approach to solving the prognostics problem. However, almost all work has focused on prognostics of systems with continuous dynamics. In this paper, we extend the model-based prognostics framework to hybrid systems models that combine both continuous and discrete dynamics. In general, most systems are hybrid in nature, including those that combine physical processes with software. We generalize the model-based prognostics formulation to hybrid systems, and describe the challenges involved. We present a general approach for modeling hybrid systems, and overview methods for solving estimation and prediction in hybrid systems. As a case study, we consider the problem of conflict (i.e., loss of separation) prediction in the National Airspace System, in which the aircraft models are hybrid dynamical systems.

prognosis↗

Cluster-cluster clustering

The cluster correlation function xi sub c(r) is compared with the particle correlation function, xi(r) in cosmological N-body simulations with a wide range of initial conditions. The experiments include scale-free initial conditions, pancake models with a coherence length in the initial density field, and hybrid models. Three N-body techniques and two cluster-finding algorithms are used. In scale-free models with white noise initial conditions, xi sub c and xi are essentially identical. In scale-free models with more power on large scales, it is found that the amplitude of xi sub c increases with cluster richness; in this case the clusters give a biased estimate of the particle correlations. In the pancake and hybrid models (with n = 0 or 1), xi sub c is steeper than xi, but the cluster correlation length exceeds that of the points by less than a factor of 2, independent of cluster richness. Thus the high amplitude of xi sub c found in studies of rich clusters of galaxies is inconsistent with white noise and pancake models and may indicate a primordial fluctuation spectrum with substantial power on large scales.

Barnes, J.↗

Building Hybrid Rover Models for NASA: Lessons Learned

Particle filters have recently become popular for diagnosis and monitoring of hybrid systems. In this paper we describe our experiences using particle filters on a real diagnosis problem, the NASA Ames Research Center's K-9 rover. As well as the challenge of modelling the dynamics of the system, there are two major issues in applying a particle filter to such a model. The first is the asynchronous nature of the system-observations from different subsystems arrive at different rates, and occasionally out of order, leading to large amounts of uncertainty in the state of the system. The second issue is data interpretation. The particle filter produces a probability distribution over the state of the system, from which summary statistics that can be used for control or higher-level diagnosis must be extracted. We describe our approaches to both these problems, as well as other modelling issues that arose in this domain.

Willeke, Thomas↗

Hybrid-PIC Modeling of a High-Voltage, High-Specific-Impulse Hall Thruster

The primary life-limiting mechanism of Hall thrusters is the sputter erosion of the discharge channel walls by high-energy propellant ions. Because of the difficulty involved in characterizing this erosion experimentally, many past efforts have focused on numerical modeling to predict erosion rates and thruster lifespan, but those analyses were limited to Hall thrusters operating in the 200-400V discharge voltage range. Thrusters operating at higher discharge voltages (V(sub d) >= 500 V) present an erosion environment that may differ greatly from that of the lower-voltage thrusters modeled in the past. In this work, HPHall, a well-established hybrid-PIC code, is used to simulate NASA's High-Voltage Hall Accelerator (HiVHAc) at discharge voltages of 300, 400, and 500V as a first step towards modeling the discharge channel erosion. It is found that the model accurately predicts the thruster performance at all operating conditions to within 6%. The model predicts a normalized plasma potential profile that is consistent between all three operating points, with the acceleration zone appearing in the same approximate location. The expected trend of increasing electron temperature with increasing discharge voltage is observed. An analysis of the discharge current oscillations shows that the model predicts oscillations that are much greater in amplitude than those measured experimentally at all operating points, suggesting that the differences in oscillation amplitude are not strongly associated with discharge voltage.

Hall Thrusters↗

Retrieval of Soil Moisture and Roughness from the Polarimetric Radar Response

The main objective of this investigation was the characterization of soil moisture using imaging radars. In order to accomplish this task, a number of intermediate steps had to be undertaken. In this proposal, the theoretical, numerical, and experimental aspects of electromagnetic scattering from natural surfaces was considered with emphasis on remote sensing of soil moisture. In the general case, the microwave backscatter from natural surfaces is mainly influenced by three major factors: (1) the roughness statistics of the soil surface, (2) soil moisture content, and (3) soil surface cover. First the scattering problem from bare-soil surfaces was considered and a hybrid model that relates the radar backscattering coefficient to soil moisture and surface roughness was developed. This model is based on extensive experimental measurements of the radar polarimetric backscatter response of bare soil surfaces at microwave frequencies over a wide range of moisture conditions and roughness scales in conjunction with existing theoretical surface scattering models in limiting cases (small perturbation, physical optics, and geometrical optics models). Also a simple inversion algorithm capable of providing accurate estimates of soil moisture content and surface rms height from single-frequency multi-polarization radar observations was developed. The accuracy of the model and its inversion algorithm is demonstrated using independent data sets. Next the hybrid model for bare-soil surfaces is made fully polarimetric by incorporating the parameters of the co- and cross-polarized phase difference into the model. Experimental data in conjunction with numerical simulations are used to relate the soil moisture content and surface roughness to the phase difference statistics. For this purpose, a novel numerical scattering simulation for inhomogeneous dielectric random surfaces was developed. Finally the scattering problem of short vegetation cover above a rough soil surface was considered. A general scattering model for grass-blades of arbitrary cross section was developed and incorporated in a first order random media model. The vegetation model and the bare-soil model are combined and the accuracy of the combined model is evaluated against experimental observations from a wheat field over the entire growing season. A complete set of ground-truth data and polarimetric backscatter data were collected. Also an inversion algorithm for estimating soil moisture and surface roughness from multi-polarized multi-frequency observations of vegetation-covered ground is developed.

Sarabandi, Kamal↗

Additional Comparison of Ice Shapes on Full-Chord and Truncated Swept Wing Models from January 2022

A research program was conducted to evaluate the effectiveness of icing tunnel hybrid model design. A hybrid design is where the full-scale leading edge of a wing section is maintained only to a certain percentage of the local chord, while the aft section of the model is redesigned into a shortened or truncated planform. An initial study was conducted in 2020 where the ice shape geometries on a full-chord length version of the swept CRM65 wing model were compared to those from the hybrid version of CRM65 that were obtained in NASA Icing Research Tunnel in 2015. The results were reported in a 2021 paper. For most test conditions, the overall size and shape of the ice shapes compared well. However, the ice shapes from the full-chord model were generally slightly smaller than those from the hybrid model. A follow-on test was conducted in 2022 and obtained ice shapes on both full-chord and hybrid wing models during the same test campaign to eliminate the differences in the tunnel configuration as a cause for the differences observed during the previous investigation. The ice shapes obtained on the full-chord model compared much better to those obtained on the hybrid model during the 2022 test, with nearly identical cross sections and ice mass values generally within 5%.

Icing↗

Additional Comparison of Ice Shapes on Full-Chord and Truncated Swept Wing Models from January 2022

A research program was conducted to evaluate the effectiveness of icing tunnel hybrid model design. A hybrid design is where the full-scale leading edge of a wing section is maintained only to a certain percentage of the local chord, while the aft section of the model is redesigned into a shortened or truncated planform. An initial study was conducted in 2020 where the ice shape geometries on a full-chord length version of the swept CRM65 wing model were compared to those from the hybrid version of CRM65 that were obtained in the NASA Icing Research Tunnel in 2015. The results were reported in a 2021 paper. For most test conditions, the overall size and shape of the ice shapes compared well. However, the ice shapes from the full-chord model were generally slightly smaller than those from the hybrid model. A follow-on test was conducted in 2022 and obtained ice shapes on both full-chord and hybrid wing models during the same test campaign to eliminate the differences in the tunnel spray nozzle configuration and calibration as a cause for the differences observed during the previous investigation. The ice shapes obtained on the full-chord model compared much better to those obtained on the hybrid model during the 2022 test, with nearly identical cross sections and ice mass values generally within 5%.

Icing↗

Prognostics for Systems Health Management - Model and Hybrid Based Approaches. Where are We Heading?

To facilitate and solve the prediction problem, awareness of the current state and health of the system is key, since it is necessary to perform condition-based system health predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditional. In case of next generation electric aircrafts, computing remaining flying time is safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. In order to tackle and solve the prediction problem, it is essential to have awareness of the current health state of the system, especially since it is necessary to perform condition-based predictions. To be able to predict the future state of the system, it is also required to possess knowledge of the current and future operational conditions and flight profiles for accurate estimation of end-of-discharge (EOD) for the batteries. Similar framework can be implemented to other complex systems and subsystems. Our research approach is to develop a system level health monitoring safety indicator which runs estimation and prediction algorithms to estimate remaining useful life predictions at system, subsystem swell as component levels. Given models of the current and future system behavior, a general approach of model-based prognostics is discussed as a solution to the prediction problem and further for decision making. Data driven prognostics approaches have been equally used with good results in the past, where respective approaches have their own challenges to tackle. This limits their applicability to complex real-world domains: (a) high complexity or incompleteness of physics-based models and (b) limited representativeness of the training dataset for data-driven models. With the advent of internet of things for data collection and increased use of ML algorithms, hybrid approaches are the next avenue to reduce the challenges and achieve better results. An hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety critical systems is presented. In this framework, we use physics-based performance models to infer unobservable model parameters related to the system's components health solving a calibration problem.

Prognostics↗

An Efficient Model-based Diagnosis Engine for Hybrid Systems Using Structural Model Decomposition

Complex hybrid systems are present in a large range of engineering applications, like mechanical systems, electrical circuits, or embedded computation systems. The behavior of these systems is made up of continuous and discrete event dynamics that increase the difficulties for accurate and timely online fault diagnosis. The Hybrid Diagnosis Engine (HyDE) offers flexibility to the diagnosis application designer to choose the modeling paradigm and the reasoning algorithms. The HyDE architecture supports the use of multiple modeling paradigms at the component and system level. However, HyDE faces some problems regarding performance in terms of complexity and time. Our focus in this paper is on developing efficient model-based methodologies for online fault diagnosis in complex hybrid systems. To do this, we propose a diagnosis framework where structural model decomposition is integrated within the HyDE diagnosis framework to reduce the computational complexity associated with the fault diagnosis of hybrid systems. As a case study, we apply our approach to a diagnostic testbed, the Advanced Diagnostics and Prognostics Testbed (ADAPT), using real data.

Structural Decomposition↗

A Fast Hybrid (3-D/1-D) Model for Thermal Radiative Transfer in Cirrus via Successive Orders of Scattering

We investigate the impact of cirrus cloud heterogeneity on the direct emission by cloud or surface and on the scattering by ice particles in the thermal infrared (TIR). Realistic 3-D cirri are modeled with the 3DCLOUD code, and top-of-atmosphere radiances are simulated by the 3-D Monte Carlo radiative transfer (RT) algorithm 3DMCPOL for two (8.65 micrometers and 12.05 micrometers) channels of the Imaging Infrared Radiometer on CALIPSO. At nadir, comparisons of 1-D and 3-D RT show that 3-D radiances are larger than their 1-D counterparts for direct emission but smaller for scattered radiation. For our cirrus cases, 99% of the 3-D total radiance is computed by the third scattering order, which corresponds to 90% of the total computational effort, but larger optical thicknesses need more scattering orders. To radically accelerate the 3-D RT computations (using only few percent of 3-D RT time with a Monte Carlo code), even in the presence of large optical depths, we develop a hybrid model based on exact 3-D direct emission, the first scattering order from 1-D in each homogenized column, and an empirical adjustment linearly dependent on the optical thickness to account for higher scattering orders. Good agreement is found between the hybrid model and the exact 3-D radiances for two very different cirrus models without changing the empirical parameters. We anticipate that a future deterministic implementation of the hybrid model will be fast enough to process multiangle thermal imagery in a practical tomographic reconstruction of 3-D cirrus fields.

radiative transfer↗

Oblique High Mach Number Heliospheric Shocks: The Role of α Particles

Spacecraft observations of heliospheric shocks often find oscillations in the magnetic field and density both, upstream and downstream. The downstream magnetic oscillations of oblique collisionless shocks were detected by Wind with 10.9 samples/s and DSCOVR spacecraft with high temporal resolution of 50 samples/s. The density oscillations associated with the shocks are also evident in proton and α particle density by Wind (with much lower temporal resolution). Recently, we have investigated low Mach number low-β oblique shock oscillations using satellite data and 2.5D hybrid modeling with electrons modeled as fluid and ions modeled as particles and found that α particles—an important component of heliospheric plasma—may affect considerably the downstream oscillations and the shock structure. The objective of the present study is to investigate the effects of α particles on high Mach number heliospheric shocks dynamics, oscillations, nonstationarity, and shock-front rippling. We extend the study to high Mach number shocks (M > 3), investigate several α particle typical densities, and compare the results for the various shock parameters. We model the effects of α particles on the shock ramp, wake, and downstream oscillation structure and the kinetic properties of proton and α particle velocity distributions at various locations downstream of the shocks. Using the 2.5D hybrid model we found that the modeled high Mach number quasi-perpendicular shock magnetic and density structures are significantly affected by α particles with typical solar wind relative abundances, suggesting that the observed high Mach number shocks are similarly affected by α particles.

Leon Ofman↗