Results for “Physics Modeling” — Page 16

NASA NTRSDate not supplied

Systems Health Management and Prognostics Approaches for Electric Aircrafts

As more and more electric vehicles emerge in our daily operation progressively, a very critical challenge lies in the prediction of remaining driving flying time/distance for the flying vehicles. This information is important, particularly in the case of auto vehicles, because such vehicles can become self-aware, autonomously compute its own capabilities, and identify how to best plan and successfully complete vehicular missions safely. In case of electric aircrafts, computing the remaining flying time is also safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. To facilitate and solve the prediction problem, awareness of the current health state of the system is key, since it is necessary to perform condition-based predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Latest achievements of data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. Given models of the current and future system behavior, a general approach of model-based prognostics can solve the prediction problem and further decision-making. A systematic prediction framework is implemented to identify all possible sources of uncertainty, quantify each of them individually, and mathematically estimate their combined effect on the system-level quantity of interest, in this case, the remaining flying time/distance of the unmanned aircraft. Note - This presentation contains all previously published information.

Systems Health Managent↗

NASA NTRSDate not supplied

Health Monitoring and Prognostics for Electric Aircrafts

As more and more electric vehicles emerge in our daily operation progressively, a very critical challenge lies in the prediction of remaining driving flying time/distance for the flying vehicles. This information is important, particularly in the case of auto vehicles, because such vehicles can become self-aware, autonomously compute its own capabilities, and identify how to best plan and successfully complete vehicular missions safely. In case of electric aircrafts, computing the remaining flying time is also safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. To facilitate and solve the prediction problem, awareness of the current health state of the system is key, since it is necessary to perform condition-based predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Latest achievements of data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. Given models of the current and future system behavior, a general approach of model-based prognostics can solve the prediction problem and further decision-making. A systematic prediction framework is implemented to identify all possible sources of uncertainty, quantify each of them individually, and mathematically estimate their combined effect on the system-level quantity of interest, in this case, the remaining flying time/distance of the unmanned aircraft. Note - This presentation contains all previously approved and published information.

Systems Health Managent↗

NASA NTRS1984

Modeling of the surface static displacements and fault plane slip for the 1979 Imperial Valley earthquake

Three-dimensional finite element modeling techniques are used to synthesize geodetic and seismological results for 1979 Imperial Valley earthquake. The strategy pursued consists of two principal steps. In the first step, the seismologically-derived coseismic fault slip is taken as a function of position in the fault plane and is applied directly to the three-dimensional dislocation model. In the second step, a physical model of stresses and constitutive parameters is perturbed so as to reproduce the observed fault slip. Hence, the principal features of the coseismic slip pattern are explained by a stress-driven fault model in which: (1) a spatially unresolved asperity is found equivalent to a stress drop of 18 MPa averaged over an area of 15 sq km, and (2) driving stress is essentially absent on the fault segment overlapping the 1940 earthquake rupture zone.

Slade, M. A.↗

NASA NTRS1987

Composite load spectra for select space propulsion structural components

The objective of this program is to develop generic load models to simulate the composite load spectra (CLS) that are induced in space propulsion system components representative of the space shuttle main engines (SSME). These models are being developed through describing individual component loads with an appropriate mix of deterministic and state-of-the-art probabilistic models that are related to key generic variables. Combinations of the individual loads are used to synthesize the composite loads spectra. A second approach for developing the composite loads spectra load model simulation, the option portion of the contract will develop coupled models which combine the individual load models. Statistically varying coefficients of the physical models will be used to obtain the composite load spectra.

Newell, J. F.↗

NASA NTRS1989

Computing viscous reactive flow over blunt winged vehicles

A hypersonic flow simulation methodology is developed for analyzing thermochemical nonequilibrium and viscous phenomena associated with space-flight vehicles at realistic conditions. The computer code consists of grid generation, Navier-Stokes and species models, and equation solvers for a complete configuration at arbitrary angles of attack. Provisions are implemented in the code to consider chemically frozen or equilibrium chemistry, inviscid model, conic configurations and simplifications of physical parameters for verifying solution consistency and accuracy. Implications of physical modeling and input parameters on a blunt-cone flow are investigated in details. Applications to USA Orbiter-like vehicles have emphasized the leeside canopy flow as well as the bow-wing shock interaction problem at Mach 22 and 40 deg angle of attack. Comparison of windward centerline pressures and heating rates with available wind-tunnel and flight data is in progress.

Li, C. P.↗

NASA NTRS1998

Development of Ultrasonic and Fabry-Perot Interferometer for Non-Destruction Inspection of Aging Aircraft

Fabry-Perot Interferometer (FPI) sensor detection system was continued and refined modifications were made in the data acquisition and evaluation process during the last year. The ultrasonic and FPI detection system was improved from one to multiple sensor detectors. Physical models were developed to understand the physical phenomenon of this work. Multilayered flawed samples were fabricated for inspection by a prototype ultrasonic and FPI detection. Experimental data was verified with simulated results. Undergraduate students that were associated with this research gained valuable knowledge from this experience. This was a learning process helping students to understand the importance of research and its application to solve important technological problems. As a result of our students exposure to this research two and planning to continue this type of research work in graduate school. A prototype instrument package was laboratory tested an actual airframe structure for documentation purposes.

Smith, Alphonso C.↗

NASA NTRSDate not supplied

NASA Earth: Synthetic Spectranomics - Deep Learning of Surface 3-D Geometry, Chemistry, and Hyperspectra to Inform Next-generation Land Models

Machine and deep learning (ML/DL) have transformed our approach to Earth observation and system modeling (EOSM), unifying both in view of ML/DL models as a form of data assimilation (DA). Trained on diverse Earth observation records, detailed physical models, or hybrids of both in physics-informed machine learning, ML/DL may improve upon existing Earth system model (ESM) formulations while creating entirely new classes of models. One important application of deep learning is observation synthesis, allowing ESM developers to prepare for the increased spatial, temporal, and spectral/polar resolution of proposed future observing systems. This may involve the retrospective application of learning algorithms to existing observational records, with or without physical radiative transfer models, to co-inform mission planning and ESM development while providing a degree of data continuity for new missions.

Adam Erickson↗

NASA NTRS1988

Mesoscale monitoring of the soil freeze/thaw boundary from orbital microwave radiometry

The fundamental objectives are to test the feasibility of delineating the lateral boundary between frozen and thawed condition in the surface layer of soil from orbital microwave radiometry and secondly to examine the sensitivity of general circulation models to an explicit parameterization of the boundary condition. Physical models were developed to relate emissivity to scene properties and a simulation package was developed to predict brightness temperature as a function of emissivity and physical temperature in order to address issues of heterogeneity, scaling, and scene dynamics. Radiative transfer models were develped for both bare soil surfaces and those obscured by an intervening layer of vegetation or snow. These models relate the emissivity to the physical properties of the soil and to those of the snow or vegetation cover. A SMMR simulation package was developed to evaluate the adequacy of the emission models and the limiting effects of scaling for realistic scenarios incorporating spatially heterogeneous scenes with dynamic moisture and temperature gradients at the pixel scale.

Ulaby, Fawwaz T.↗

NASA NTRS1974

Optical image of a cometary nucleus: 1980 flyby of Comet Encke

The feasibility was investigated of obtaining optical images of a cometary nucleus via a flyby of Comet Encke. A physical model of the dust cloud surrounding the nucleus was developed by using available physical data and theoretical knowledge of cometary physics. Using this model and a Mie scattering code, calculations were made of the absolute surface brightness of the dust in the line of sight of the on-board camera and the relative surface brightness of the dust compared to the nucleus. The brightness was calculated as a function of heliocentric distance and for different phase angles (sun-comet-spacecraft angle).

Wells, W. C.↗

NASA NTRS2002

Physical and statistical modeling of Saturn's troposphere

We analyze the 5.2-pm spectra of Saturn by utilizing two independent methods: (a) physical models based on the relevant atmospheric parameters and (b) statistical analysis, based on principal components analysis (PCA), to determine the influence of the variation of phosphine and the opacity of clouds deep within Saturn's atmosphere to understand the dynamics in its atmosphere.

Saturn↗

NASA NTRS2017

Multi-Layer RF Tissue Phantoms for Mimicking a Human Core

This work presents the design recipe, fabrication process and characterization of tissue-simulating materials, configured as a physical model to mimic the electrical and some physical properties of an abdominal cavity. The complete three layer design is called the human core model (HCM). To our knowledge, presented is the first hybrid skin-muscle phantom developed to mimic the electrical properties of the intervening tissue layers of an abdominal cavity within the frequency band of 1 GHz 2 GHz, a band of interest for human body sensing due to its deep detection depth. To complete the model, a liquid blood phantom was also developed and characterized in this frequency band. The phantoms were characterized with respect to complex dielectric constant using the Agilent 85070E dielectric probe kit, and the results compared to the Gabriel model, which is used as the standard for human tissue characterization. Since the tissue impedance is an important parameter for characterizing on-body sensors and near field antenna performance, the impedance of the phantoms were also calculated and presented in the analysis.

Bonds, Quenton↗

NASA NTRSDate not supplied

Digital Twins and Living Models at NASA

The idea of a “digital twin” was born at NASA in the 1960s as a “living model” of the Apollo mission. In response to Apollo 13’s oxygen tank explosion and subsequent damage to the main engine, NASA employed multiple simulators to evaluate the failure and extended a physical model of the vehicle to include digital components. This “digital twin” was the first of its kind, allowing for a continuous ingestion of data to model the events leading to up to the accident for forensic analysis and exploration of next steps. Fast forward half a century and NASA, along with others in the aerospace community, continues to develop and utilize high-fidelity digital models of physical systems and components as well as the extreme environments in which they operate. NASA aims to travel further and stay longer in space as we realize the Artemis program, taking us from the moon to Mars by establishing a sustainable presence on the Moon to prepare for missions to Mars. We will no longer be able to rely on constant connectivity with an asset nor be in-the-loop for on-demand human intervention in the event of an anomaly. Further, the importance of digital twins is increasing as we seek alternatives for certification of structures so large that they cannot be fully evaluated in existing test facilities and autonomous systems that are not deterministic. The idea of a digital twin is not a new one. What is new is the scale, ordinality, and non-deterministic nature of the models that are critical to achieving NASA’s goals. Their number and autonomy from each other as well as the reference system is suggestive of a changing ecosystem, returning us the idea of a living model.

Digital Twin↗

NASA NTRS2017

Multi-Layer RF Tissue Phantoms for Mimicking a Human Core

This work presents the design recipe, fabrication process and characterization of tissue-simulating materials, configured as a physical model to mimic the electrical and some physical properties of an abdominal cavity. The complete three-layer design is called the human core model (HCM) see Fig. 1. To our knowledge, presented is the first hybrid skin-muscle phantom developed to mimic the electrical properties of the intervening tissue layers of an abdominal cavity within the frequency band of 1 GHz - 2 GHz, a band of interest for human body sensing due to its deep detection depth.

Biomedical Microwave Sensing↗

NASA NTRS1994

Evaluation of SSME test data reduction methods

Accurate prediction of hardware and flow characteristics within the Space Shuttle Main Engine (SSME) during transient and main-stage operation requires a significant integration of ground test data, flight experience, and computational models. The process of integrating SSME test measurements with physical model predictions is commonly referred to as data reduction. Uncertainties within both test measurements and simplified models of the SSME flow environment compound the data integration problem. The first objective of this effort was to establish an acceptability criterion for data reduction solutions. The second objective of this effort was to investigate the data reduction potential of the ROCETS (Rocket Engine Transient Simulation) simulation platform. A simplified ROCETS model of the SSME was obtained from the MSFC Performance Analysis Branch . This model was examined and tested for physical consistency. Two modules were constructed and added to the ROCETS library to independently check the mass and energy balances of selected engine subsystems including the low pressure fuel turbopump, the high pressure fuel turbopump, the low pressure oxidizer turbopump, the high pressure oxidizer turbopump, the fuel preburner, the oxidizer preburner, the main combustion chamber coolant circuit, and the nozzle coolant circuit. A sensitivity study was then conducted to determine the individual influences of forty-two hardware characteristics on fourteen high pressure region prediction variables as returned by the SSME ROCETS model.

Santi, L. Michael↗

NASA NTRS2016

Evaluating Multispectral Snowpack Reflectivity With Changing Snow Correlation Lengths

This study investigates the sensitivity of multispectral reflectivity to changing snow correlation lengths. Matzler's ice-lamellae radiative transfer model was implemented and tested to evaluate the reflectivity of snow correlation lengths at multiple frequencies from the ultraviolet (UV) to the microwave bands. The model reveals that, in the UV to infrared (IR) frequency range, the reflectivity and correlation length are inversely related, whereas reflectivity increases with snow correlation length in the microwave frequency range. The model further shows that the reflectivity behavior can be mainly attributed to scattering rather than absorption for shallow snowpacks. The largest scattering coefficients and reflectivity occur at very small correlation lengths (approximately 10(exp -5 m) for frequencies higher than the IR band. In the microwave range, the largest scattering coefficients are found at millimeter wavelengths. For validation purposes, the ice-lamella model is coupled with a multilayer snow physics model to characterize the reflectivity response of realistic snow hydrological processes. The evolution of the coupled model simulated reflectivities in both the visible and the microwave bands is consistent with satellite-based reflectivity observations in the same frequencies. The model results are also compared with colocated in situ snow correlation length measurements (Cold Land Processes Field Experiment 2002-2003). The analysis and evaluation of model results indicate that the coupled multifrequency radiative transfer and snow hydrology modeling system can be used as a forward operator in a data-assimilation framework to predict the status of snow physical properties, including snow correlation length.

Kang, Do Hyuk↗

NASA NTRS1993

Spray combustion model improvement study, 1

This study involves the development of numerical and physical modeling in spray combustion. These modeling efforts are mainly motivated to improve the physical submodels of turbulence, combustion, atomization, dense spray effects, and group vaporization. The present mathematical formulation can be easily implemented in any time-marching multiple pressure correction methodologies such as MAST code. A sequence of validation cases includes the nonevaporating, evaporating and_burnin dense_sprays.

Chen, C. P.↗

NASA NTRS2014

NuSTAR Detection of High-Energy X-Ray Emission and Rapid Variability from Sagittarius A(star) Flares

Sagittarius A(star) harbors the supermassive black hole that lies at the dynamical center of our Galaxy. Sagittarius A(star) spends most of its time in a low luminosity emission state but flares frequently in the infrared and X-ray, increasing up to a few hundred fold in brightness for up to a few hours at a time. The physical processes giving rise to the X-ray flares are uncertain. Here we report the detection with the NuSTAR observatory in Summer and Fall 2012 of four low to medium amplitude X-ray flares to energies up to 79 keV. For the first time, we clearly see that the power-law spectrum of Sagittarius A(star) X-ray flares extends to high energy, with no evidence for a cut off. Although the photon index of the absorbed power-law fits are in agreement with past observations, we find a difference between the photon index of two of the flares (significant at the 95% confidence level). The spectra of the two brightest flares (approx. 55 times quiescence in the 2- 10 keV band) are compared to simple physical models in an attempt to identify the main X-ray emission mechanism, but the data do not allow us to significantly discriminate between them. However, we confirm the previous finding that the parameters obtained with synchrotron models are, for the X-ray emission, physically more reasonable than those obtained with inverse-Compton models. One flare exhibits large and rapid (less than 100 s) variability, which, considering the total energy radiated, constrains the location of the flaring region to be within approx. 10 Schwarzschild radii of the black hole.

NuSTAR detection of high-energy X-ray emission and↗

NASA NTRS1980

Millimeter wave attenuation prediction using a piecewise uniform rain rate model

A piecewise uniform rain rate distribution model is introduced as a quasi-physical model of real rain along earth-space millimeter wave propagation paths. It permits calculation of the total attenuation from specific attenuation in a simple fashion. The model predications are verified by comparison with direct attenuation measurements for several frequencies, elevation angles, and locations. Also, coupled with the Rice-Holmberg rain rate model, attenuation statistics are predicated from rainfall accumulation data.

Persinger, R. R.↗