Results for “forward modeling” — Page 58

NASA NTRS2016

The GIRE2 Model and Its Application to the Europa Mission

We present an empirical model of Jupiter's electron radiation environment and its application to the design of the future NASA mission to Europa. The model is based on data from the Galileo spacecraft. Measurements of the high-energy, omni-directional electrons from the Energetic Particle Detector (EPD) and magnetic field from the Magnetometer (MAG) onboard Galileo are used for this purpose. Ten-minute averages of the EPD data are used to provide an omni-directional electron flux spectrum at 0.238, 0.416, 0.706, 1.5, 2.0, and 11.0 MeV. Additionally, data from the Geiger Tube Telescope onboard Pioneer 10 and 11 are used to calculate the flux of 31 MeV electrons. The Galileo Interim Radiation Electron model v.2 (GIRE2) combines these datasets with the original Divine model and synchrotron observations to estimate the trapped electron radiation environment. Unlike the original Divine model, which was based on flybys of the Voyager and Pioneer spacecraft, the new GIRE2 model covers about 7 years of data and more than 30 orbits around Jupiter from the Galileo spacecraft. The model represents a step forward in the study of the Jovian radiation environment and is a valuable tool to assist in the design of future missions to Jupiter. This paper gives an overview of GIRE2 and focuses on its application to the design of the future NASA mission to Europa. The spacecraft will orbit Jupiter and perform multiple flybys of the moon Europa, which is embedded in the middle of a very strong radiation environment. The radiation environment surrounding the moon as well as along the trajectory are described in the paper together with the implications of this environment on the design of a mission.

De Soria-Santacruz Pich, Maria↗

NASA NTRSDate not supplied

A Radiometric Consistent Spectral Fingerprinting Algorithm for Continuity Products of Hyperspectral Sounders

A radiometric consistent climate fingerprinting methodology has been developed to derive long-term temperature, water vapor, cloud, trace gases, and surface skin temperature anomaly time series from the hyper-spectral sounder measurements of multiple platforms. The spectral fingerprinting methodology requires the use of radiative kernels that are radiometrically consistent with observations. Radiative kernels are built using space-time averaged Jacobians that are physically retrieved from observations under all sky conditions. The physical retrieval algorithm uses the Principal Component based Radiative Transfer Model (PCRTM) for the forward simulation. The incorporation of multiple scattering simulation in PCRTM allows the direct radiative relationship between single field-of-view (FOV) radiance observations and corresponding thermal dynamic variables including cloud properties to be established. Therefore, radiance ?closure? can be achieved under all-sky conditions by the fingerprinting scheme. This methodology has been used to derive climate anomalies from the space-time averaged spectra of AIRS/AMSU and CrIS/ATMS. The use of a consistent fingerprinting scheme provides an effective mean of generating continuity product by merging observations from different platforms and therefore facilitating the long-term climate trend study.

Wan Wu↗

NASA NTRSDate not supplied

Investigation of Longitudinal Aero-Propulsive Interactions of a Small Quadrotor Unmanned Aircraft System

Aerodynamic propulsive and airframe interactions significantly influence the forces and moments of multirotor vehicles. This paper presents recent results studying the influence of these effects on a small quadrotor vehicle in hover and forward flight. Aerodynamic interaction model development was explored utilizing system identification tools and incorporated into a previously developed NASA quadrotor flight dynamic simulation. The aerodynamic interaction model improved accuracy of the simulation in comparison to free-flight and static wind tunnel results. Comparisons between models of different fidelity were completed to demonstrate the effects of aerodynamic interaction on model accuracy and provide recommendations for modelling requirements.

George Altamirano↗

NASA NTRSDate not supplied

Bond Line Thickness Estimation in Composite Structures Using Multiple Inspection Techniques

Imaging and other nondestructive evaluation techniques are commonly used for material characterization and defect recognition in safety critical aerospace applications, with data fusion providing the framework for uncertainty quantification in these contexts. Most commonly, forward physics-based modeling predicts the response conditioned on material properties and defect assumptions, and probabilistic methods are used to infer the hidden state of the subject of the inspection from a combination of prior information, likelihoods, and inspection data. In this paper Bayesian methods are used to estimate bond thickness in lap joints comprised of aluminum adherends using a combination of infrared thermography and ultrasound. The concept of the conflation of probability distributions is applied to combine the posterior distributions derived from thermography and ultrasound and the quality of the fused estimates are compared against the individual estimates against synthetic data that was created to mimic the inspection of a lap joint comprised of aluminum adherends.

thermal nondestructive evaluation↗

NASA NTRSDate not supplied

Bond Line Thickness Estimation in Composite Structures Using Multiple Inspection Techniques

Imaging and other nondestructive evaluation techniques are commonly used for material characterization and defect recognition in safety critical aerospace applications, with data fusion providing the framework for uncertainty quantification in these contexts. Most commonly, forward physics-based modeling predicts the response conditioned on material properties and defect assumptions, and probabilistic methods are used to infer the hidden state of subject of the inspection from a combination of prior information, likelihoods, and inspection data. In this paper Bayesian methods are used to estimate bond thickness in lap joints comprised of aluminum adherends using a combination of infrared thermography, digital radiography, and ultrasound. The accuracy of the fused estimates are validated against data generated from synthetic specimens, and by comparison against high resolution X-ray computed tomography inspections of built specimens.

thermal nondestructive evaluation↗

DOE OSTI2022

Snowmass2021: Vera C. Rubin Observatory as a Flagship Dark Matter Experiment

Establishing that Vera C. Rubin Observatory is a flagship dark matter experiment is an essential pathway toward understanding the physical nature of dark matter. In the past two decades, wide-field astronomical surveys and terrestrial laboratories have jointly created a phase transition in the ecosystem of dark matter models and probes. Going forward, any robust understanding of dark matter requires astronomical observations, which still provide the only empirical evidence for dark matter to date. We have a unique opportunity right now to create a dark matter experiment with Rubin Observatory Legacy Survey of Space and Time (LSST). This experiment will be a coordinated effort to perform dark matter research, and provide a large collaborative team of scientists with the necessary organizational and funding supports. This approach leverages existing investments in Rubin. Studies of dark matter with Rubin LSST will also guide the design of, and confirm the results from, other dark matter experiments. Supporting a collaborative team to carry out a dark matter experiment with Rubin LSST is the key to achieving the dark matter science goals that have already been identified as high priority by the high-energy physics and astronomy communities.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Characterizing leaf-scale fluorescence with spectral invariants

Sun-induced chlorophyll fluorescence (SIF) is increasingly recognized as a non-destructive probe for tracking terrestrial photosynthesis. Emerging developments in spectral invariants theory provide an innovative and efficient approach for representing SIF radiative transfer processes at the canopy scale. However, modeling leaf-scale fluorescence based on the spectral invariants properties (SIP) remains underexplored. In this study, the spectral invariants theory is employed for the first time to model the leaf-scale total, backward and forward fluorescence (leaf-SIP SIF). The leaf-SIP SIF model separates the leaf-scale radiative transfer process into two distinct components: the wavelength-dependent one associated with leaf biochemical properties, and the wavelength-independent component linked to leaf structural characteristics. The leaf structure-related effects are characterized by two spectrally invariant parameters: the photon recollision probability (p) and the scattering asymmetry parameter (q), which are parameterized using the directly measurable leaf dry matter. Evaluation against field measurements shows that the proposed leaf-SIP SIF model has a good performance, with coefficient of determination (R 2 ) of 0.89, 0.89, 0.90 and root mean squared errors (RMSE) of 1.28, 0.69, 0.74 Wm -2 µm -1 sr -1 , respectively for the total, backward, and forward fluorescence (660–800 nm). The leaf-SIP SIF model with a more concise formulation demonstrates comparable performance with the widely used Fluspect model. Further, the leaf-SIP SIF model provides a simple and efficient approach for simulating leaf-scale fluorescence, with the potential to be integrated into a unified SIP-based model framework for simulating the radiative transfer processes across the soil-leaf-canopy-atmosphere continuum.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2002

Hierarchies of Models: Toward Understanding Planetary Nebulae

Stars like our sun (initial masses between 0.8 to 8 solar masses) end their lives as swollen red giants surrounded by cool extended atmospheres. The nuclear reactions in their cores create carbon, nitrogen and oxygen, which are transported by convection to the outer envelope of the stellar atmosphere. As the star finally collapses to become a white dwarf, this envelope is expelled from the star to form a planetary nebula (PN) rich in organic molecules. The physics, dynamics, and chemistry of these nebulae are poorly understood and have implications not only for our understanding of the stellar life cycle but also for organic astrochemistry and the creation of prebiotic molecules in interstellar space. We are working toward generating three-dimensional models of planetary nebulae (PNe), which include the size, orientation, shape, expansion rate and mass distribution of the nebula. Such a reconstruction of a PN is a challenging problem for several reasons. First, the data consist of images obtained over time from the Hubble Space Telescope (HST) and spectra obtained from Kitt Peak National Observatory (KPNO) and Cerro Tololo Inter-American Observatory (CTIO). These images are of course taken from a single viewpoint in space, which amounts to a very challenging tomographic reconstruction. Second, the fact that we have two disparate and orthogonal data types requires that we utilize a method that allows these data to be used together to obtain a solution. To address these first two challenges we employ Bayesian model estimation using a parameterized physical model that incorporates much prior information about the known physics of the PN. In our previous works we have found that the forward problem of the comprehensive model is extremely time consuming. To address this challenge, we explore the use of a set of hierarchical models, which allow us to estimate increasingly more detailed sets of model parameters. These hierarchical models of increasing complexity are akin to scientific theories of increasing sophistication, with each new model/theory being a refinement of a previous one by either incorporating additional prior information or by introducing a new set of parameters to model an entirely new phenomenon. We apply these models to both a simulated and a real ellipsoidal PN to initially estimate the position, angular size, and orientation of the nebula as a two-dimensional object and use these estimates to later examine its three-dimensional properties. The efficiency/accuracy tradeoffs of the techniques are studied to determine the advantages and disadvantages of employing a set of hierarchical models over a single comprehensive model.

Knuth, Kevin H.↗

NASA NTRS2003

Hierarchies of Models: Toward Understanding Planetary Nebulae

Stars like our sun (initial masses between 0.8 to 8 solar masses) end their lives as swollen red giants surrounded by cool extended atmospheres. The nuclear reactions in their cores create carbon, nitrogen and oxygen, which are transported by convection to the outer envelope of the stellar atmosphere. As the star finally collapses to become a white dwarf, this envelope is expelled from the star to form a planetary nebula (PN) rich in organic molecules. The physics, dynamics, and chemistry of these nebulae are poorly understood and have implications not only for our understanding of the stellar life cycle but also for organic astrochemistry and the creation of prebiotic molecules in interstellar space. We are working toward generating three-dimensional models of planetary nebulae (PNe), which include the size, orientation, shape, expansion rate and mass distribution of the nebula. Such a reconstruction of a PN is a challenging problem for several reasons. First, the data consist of images obtained over time from the Hubble Space Telescope (HST) and spectra obtained from Kitt Peak National Observatory (KPNO) and Cerro Tololo Inter-American Observatory (CTIO). These images are of course taken from a single viewpoint in space, which amounts to a very challenging tomographic reconstruction. Second, the fact that we have two disparate and orthogonal data types requires that we utilize a method that allows these data to be used together to obtain a solution. To address these first two challenges we employ Bayesian model estimation using a parameterized physical model that incorporates much prior information about the known physics of the PN. In our previous works we have found that the forward problem of the comprehensive model is extremely time consuming. To address this challenge, we explore the use of a set of hierarchical models, which allow us to estimate increasingly more detailed sets of model parameters. These hierarchical models of increasing complexity are akin to scientific theories of increasing sophistication, with each new model/theory being a refinement of a previous one by either incorporating additional prior information or by introducing a new set of parameters to model an entirely new phenomenon. We apply these models to both a simulated and a real ellipsoidal PN to initially estimate the position, angular size, and orientation of the nebula as a two-dimensional object and use these estimates to later examine its three-dimensional properties. The efficiency/accuracy tradeoffs of the techniques are studied to determine the advantages and disadvantages of employing a set of hierarchical models over a single comprehensive model.

Knuth, Kevin H.↗

NASA NTRS1991

The Flowfield Around a STOVL Aircraft Model in Ground Effect

An experimental investigation was conducted to determine the causes of hot gas ingestion of engine inlets in STOVL and V/STOVL aircraft in ground effect. Marker nephelometry was used to establish the interactions between the jets, forward velocity, and ground for a typical aircraft model configuration. The aircraft test model consisted of a two inlet configuration with four low subsonic velocity jets impacting vertically on a flat plate. The vertical distance between the plate and model under-surface was adjustable, and a wind tunnel provided forward air velocities from 0 to 0.1 times the jet velocity to simulate landing into a wind. Single frame pictures of the smoke concentration distribution in the flowfield revealed several vortical features in the interaction region, which were affected variously by the distance between the ground plane and model, the forward wind velocity, and the inlet suction. Some of these vortical features, such as the ground vortex, have been seen before in experiments using single jets. Other vortical features in the flowfield, such as the forward vortex pair, have not been seen before. Frame-averaged experimental smoke concentration profiles compared favorably with numerical time-averaged predictions of temperature distribution carried out at the University of Illinois. However, such predictions did not seem to reveal some aspects of the vortical flow features which should affect instantaneous distortion into the engine inlet.

Maclean, Roderick J.↗

DOE OSTI2021

Simulation and Modeling of Time-Resolved X-Ray Detector for the Saturn Accelerator

In this work, we present the technology-aided computer design (TCAD) device simulation and modeling of a silicon p-i-n diode for detecting time-dependent X-ray radiation. We show that the simulated forward and reverse breakdown current–voltage characteristics agree well with the measured data under nonradiation environment by only calibrating carrier lifetimes for the forward bias case and avalanche model critical fields for the reverse bias condition. Using the calibrated parameters and other nominal material properties, we simulated the radiation responses of the p-i-n diode and compared with experimental data when the diode was exposed to X-ray radiation at Sandia’s Saturn facility and the Idaho State University (ISU) TriMeV facility. For Saturn’s Gaussian dose-rate pulses, we show three findings from TCAD simulations. First, the simulated photocurrents are in excellent agreement with the measured data for two dose-rate pulses with peak values of 1.16×10 10 and 1.88×10 10 rad(Si)/s. Second, the simulation results of high dose-rate pulses predict increased delayed photocurrents with longer time tails in the diode electrical responses due to excess carrier generation. Third, simulated peak values of diode radiation responses versus peak dose rates at different bias conditions provide useful guidance to determine the dose-rate range that the p-i-n diode can reliably detect in experiment. For TriMeV’s non-Gaussian dose-rate pulse, our simulated diode response is in decent agreement with the measured data without further calibration. We also studied the effects of device geometry, recombination process, and dose-rate enhancement via TCAD simulations to understand the higher measured response in the time after the peak dose-rate radiation for the p-i-n diode exposed to TriMeV irradiation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRSDate not supplied

Recent Updates to the Object Reentry Survival Analysis Tool (ORSAT) Version 7.1

The Object Reentry Survival Analysis Tool (ORSAT) code is maintained and used by the NASA Orbital Debris Program Office (ODPO) and has been under continuous development and improvement since the mid-1990s. ORSAT is an object-oriented reentry simulation tool; it models a satellite as a collection of discrete components that follow independent trajectories upon the breakup of the parent object. Version 7.1 of the tool incorporates five years of new thermal and aerodynamic model development, multi-processor parametric study capability, codebase upgrades, and numerous bug-fixes. The thermal demise model was completely rewritten using a forward-time/central-space numerical stencil and incorporating a new pyrolysis model for fiber-reinforced plastic (FRP) materials. New aerodynamic and aeroheating models for hollow cylinders and hollow square prisms were developed using a combination of flow simulations in the direct simulation Monte Carlo (DSMC) Analysis Code (DAC) and Data Parallel Line Relaxation (DPLR) code and free-flight tests in the University of Texas at San Antonio’s Hypersonic Wind Tunnel. The latest version also incorporates a mechanical, strength-based demise model for FRP materials. Minor improvements include an update to the Fortran 2018 codebase; improved integration and speed with the Python-based, multi-core, parametric study tool, AutoORSAT; and fixes for many minor bugs. This new version of ORSAT will enable more accurate reentry risk assessments for modern satellites. This paper presents an overview of these changes and a summary of the verification and validation performed on the final code.

Benton R. Greene↗

NASA NTRSDate not supplied

Recent Updates to the Object Reentry Survival Analysis Tool (ORSAT) Version 7.1

The Object Reentry Survival Analysis Tool (ORSAT) code is maintained and used by the NASA Orbital Debris Program Office (ODPO) and has been under continuous development and improvement since the mid-1990s. ORSAT is an object-oriented reentry simulation tool; it models a satellite as a collection of discrete components that follow independent trajectories upon the breakup of the parent object. Version 7.1 of the tool incorporates five years of new thermal and aerodynamic model development, multi-processor parametric study capability, codebase upgrades, and numerous bug-fixes. The thermal demise model was completely rewritten using a forward-time/central-space numerical stencil and incorporating a new pyrolysis model for fiber-reinforced plastic (FRP) materials. New aerodynamic and aeroheating models for hollow cylinders and hollow square prisms were developed using a combination of flow simulations in the direct simulation Monte Carlo (DSMC) Analysis Code (DAC) and Data Parallel Line Relaxation (DPLR) code and free-flight tests in the University of Texas at San Antonio’s Hypersonic Wind Tunnel. The latest version also incorporates a mechanical, strength-based demise model for FRP materials. Minor improvements include an update to the Fortran 2018 codebase; improved integration and speed with the Python-based, multi-core, parametric study tool, AutoORSAT; and fixes for many minor bugs. This new version of ORSAT will enable more accurate reentry risk assessments for modern satellites. This paper presents an overview of these changes and a summary of the verification and validation performed on the final code.

Benton R. Greene↗

DOE OSTI2021

Calibr8 v.1.0

Calibr8 provides an application to rapidly prototype and perform material model calibration for complex plasticity models using advanced adjoint or forward sensitivity analyses for execution on massively parallel machines. These techniques can be orders of magnitude faster than traditional finite difference approaches for material model calibration. The underlying technology used in Calibr8 is automatic differentiation, which allows for the rapid implementation and testing of new plasticity models within its framework. Additionally, Calibr8 can perform adjoint-based error estimation to approximate discretization errors for user-implemented plasticity models. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-10630 O

Granzow, BrianN.↗

NASA NTRS1992

A fast, uncoupled, compressible, two-dimensional, unsteady boundary layer algorithm with separation for engine inlets

A finite difference boundary layer algorithm was developed to model viscous effects when an inviscid core flow solution is given. This algorithm solved each boundary layer equation separately, then iterated to find a solution. Solving the boundary layer equations sequentially was 2.4 to 4.0 times faster than solving the boundary layer equations simultaneously. This algorithm used a modified Baldwin-Lomax turbulence model, a weighted average of forward and backward differencing of the pressure gradient, and a backward sweep of the pressure. With these modifications, the boundary layer algorithm was able to model flows with and without separation. The number of grid points used in the boundary layer algorithm affected the stability of the algorithm as well as the accuracy of the predictions of friction coefficients and momentum thicknesses. Results of this boundary layer algorithm compared well with experimental observations of friction coefficients and momentum thicknesses. In addition, when used interactively with an inviscid flow algorithm, this boundary layer algorithm corrected for viscous effects to give a good match with experimental observations for pressures in a supersonic inlet.

Roach, Robert L.↗

NASA NTRS1992

A fast, uncoupled, compressible, two-dimensional, unsteady boundary layer algorithm with separation for engine inlets

A finite difference boundary layer algorithm was developed to model viscous effects when an inviscid core flow solution is given. This algorithm solved each boundary layer equation separately, then iterated to find a solution. Solving the boundary layer equations sequentially was 2.4 to 4.0 times faster than solving the boundary layer equations simultaneously. This algorithm used a modified Baldwin-Lomax turbulence model, a weighted average of forward and backward differencing of the pressure gradient, and a backward sweep of the pressure. With these modifications, the boundary layer algorithm was able to model flows with and without separation. The number of grid points used in the boundary layer algorithm affected the stability of the algorithm affected the stability of the algorithm as well as the accuracy of the predictions of friction coefficients and momentum thicknesses. Results of this boundary layer algorithm compared well with experimental observations of friction coefficients and momentum thicknesses. In addition, when used interactively with an inviscid flow algorithm, this boundary layer algorithm corrected for viscous effects to give a good match with experimental observations for pressures in a supersonic inlet.

Roach, Robert L.↗

NASA NTRS1958

Effects of Nose Shape and Spray Control Strips on Emergence and Planing Spray of Hydro-ski Models

The emergence and planing-spray characteristics of flat-bottom surfaces representative of hydro-skis with various bow shapes and deflectors were investigated for trims of 12° and 20° and a speed of 30 feet per second. The emergence-spray characteristics of the models with various bow shapes were investigated for depths of submersion of the bow from 0.50 inch to -0.50 inch. The planing-spray characteristics of the models with the various deflectors were determined for a draft corresponding to a length-beam ratio of 4 . The emergence- and planing-spray patterns are shown in the photographs taken from forward of and above the models and from the side of the models. The most favorable emergence spray was obtained with a bow of triangular plan form and sharp profile. The greatest improvement in planing spray was obtained with vertical chine strips and a transverse barrier strip located forward of the wetted planing area.

John R McGehee↗

NASA NTRS1983

Field-incidence transmission of treated orthotropic and laminated composite panels

In an effort to improve understanding of the phenomenon of noise transmission through the sidewalls of an aircraft fuselage, an analytical model was developed for the field incidence transmission loss of an orthotropic or laminated composite infinite panel with layers of various noise insulation treatments. The model allows for four types of treatments, impervious limp septa, orthotropic trim panels, porous blankets, and air spaces, while it also takes into account the effects of forward speed. Agreement between the model and transmission loss data for treated panels is seen to be fairly good overall. In comparison with transmission loss data for untreated composite panels, excellent agreement occurred.

Koval, L. R.↗