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NASA NTRS2007

Evaluating the Capacity of Global CO2 Flux and Atmospheric Transport Models to Incorporate New Satellite Observations

As we enter the new era of satellite remote sensing for CO2 and other carbon cyclerelated quantities, advanced modeling and analysis capabilities are required to fully capitalize on the new observations. Model estimates of CO2 surface flux and atmospheric transport are required for initial constraints on inverse analyses, to connect atmospheric observations to the location of surface sources and sinks, and ultimately for future projections of carbon-climate interactions. For application to current, planned, and future remotely sensed CO2 data, it is desirable that these models are accurate and unbiased at time scales from less than daily to multi-annual and at spatial scales from several kilometers or finer to global. Here we focus on simulated CO2 fluxes from terrestrial vegetation and atmospheric transport mutually constrained by analyzed meteorological fields from the Goddard Modeling and Assimilation Office for the period 1998 through 2006. Use of assimilated meteorological data enables direct model comparison to observations across a wide range of scales of variability. The biospheric fluxes are produced by the CASA model at lxi degrees on a monthly mean basis, modulated hourly with analyzed temperature and sunlight. Both physiological and biomass burning fluxes are derived using satellite observations of vegetation, burned area (as in GFED-2), and analyzed meteorology. For the purposes of comparison to CO2 data, fossil fuel and ocean fluxes are also included in the transport simulations. In this presentation we evaluate the model's ability to simulate CO2 flux and mixing ratio variability in comparison to in situ observations at sites in Northern mid latitudes and the continental tropics. The influence of key process representations is inferred. We find that the model can resolve much of the hourly to synoptic variability in the observations, although there are limits imposed by vertical resolution of boundary layer processes. The seasonal cycle and its interannual variations generally respond adequately, but discrepancies in the tropics suggest the need for a refinement of the soil moisture dependence of the respiration flux in CASA. Examples and inferences for interpretation of satellite data will be discussed. In general, the fidelity of these simulations leads us to anticipate incorporation of real-time, highly resolved remote sensing and other observations into quantitative analyses that will reduce uncertainty in the terrestrial CO2 sink and revolutionize our understanding of the key processes controlling atmospheric CO2 and its evolution with time.

Kawa, S. R.↗

NASA NTRS2011

Simulation of Acoustics for Ares I Scale Model Acoustic Tests

The Ares I Scale Model Acoustics Test (ASMAT) is a series of live-fire tests of scaled rocket motors meant to simulate the conditions of the Ares I launch configuration. These tests have provided a well documented set of high fidelity acoustic measurements useful for validation including data taken over a range of test conditions and containing phenomena like Ignition Over-Pressure and water suppression of acoustics. To take advantage of this data, a digital representation of the ASMAT test setup has been constructed and test firings of the motor have been simulated using the Loci/CHEM computational fluid dynamics software. Results from ASMAT simulations with the rocket in both held down and elevated configurations, as well as with and without water suppression have been compared to acoustic data collected from similar live-fire tests. Results of acoustic comparisons have shown good correlation with the amplitude and temporal shape of pressure features and reasonable spectral accuracy up to approximately 1000 Hz. Major plume and acoustic features have been well captured including the plume shock structure, the igniter pulse transient, and the ignition overpressure.

Putnam, Gabriel↗

NASA NTRS2012

Ion Current Density Study of the NASA-300M and NASA-457Mv2 Hall Thrusters

NASA Glenn Research Center is developing a Hall thruster in the 15-50 kW range to support future NASA missions. As a part of the process, the performance and plume characteristics of the NASA-300M, a 20-kW Hall thruster, and the NASA-457Mv2, a 50-kW Hall thruster, were evaluated. The collected data will be used to improve the fidelity of the JPL modeling tool, Hall2De, which will then be used to aid the design of the 15-50 kW Hall thruster. This paper gives a detailed overview of the Faraday probe portion of the plume characterization study. The Faraday probe in this study is a near-field probe swept radially at many axial locations downstream of the thruster exit plane. Threshold-based integration limits with threshold values of 1/e, 1/e(sup 2), and 1/e(sup 3) times the local peak current density are tried for the purpose of ion current integration and divergence angle calculation. The NASA-300M is operated at 7 conditions and the NASA-457Mv2 at 14 conditions. These conditions span discharge voltages of 200 to 500 V and discharge power of 10 to 50 kW. The ion current density profiles of the near-field plume originating from the discharge channel are discovered to strongly resemble Gaussian distributions. A novel analysis approach involving a form of ray tracing is used to determine an effective point of origin for the near-field plume. In the process of performing this analysis, definitive evidence is discovered that showed the near-field plume is bending towards the thruster centerline.

Huang, Wensheng↗

NASA NTRS2012

Ion Current Density Study of the NASA-300M and NASA-457Mv2 Hall Thrusters

NASA Glenn Research Center is developing a Hall thruster in the 15-50 kW range to support future NASA missions. As a part of the process, the performance and plume characteristics of the NASA-300M, a 20-kW Hall thruster, and the NASA-457Mv2, a 50-kW Hall thruster, were evaluated. The collected data will be used to improve the fidelity of the JPL modeling tool, Hall2De, which will then be used to aid the design of the 15-50 kW Hall thruster. This paper gives a detailed overview of the Faraday probe portion of the plume characterization study. The Faraday probe in this study is a near-field probe swept radially at many axial locations downstream of the thruster exit plane. Threshold-based integration limits with threshold values of 1/e, 1/e2, and 1/e3 times the local peak current density are tried for the purpose of ion current integration and divergence angle calculation. The NASA-300M is operated at 7 conditions and the NASA-457Mv2 at 14 conditions. These conditions span discharge voltages of 200 to 500 V and discharge power of 10 to 50 kW. The ion current density profiles of the near-field plume originating from the discharge channel are discovered to strongly resemble Gaussian distributions. A novel analysis approach involving a form of ray tracing is used to determine an effective point of origin for the near-field plume. In the process of performing this analysis, definitive evidence is discovered that showed the near-field plume is bending towards the thruster centerline.

Huang, Wensheng↗

NASA NTRS2013

SWOT Oceanography and Hydrology Data Product Simulators

The proposed Surface Water and Ocean Topography (SWOT) mission would demonstrate a new measurement technique using radar interferometry to obtain wide-swath measurements of water elevation at high resolution over ocean and land, addressing the needs of both the hydrology and oceanography science communities. To accurately evaluate the performance of the proposed SWOT mission, we have developed several data product simulators at different levels of fidelity and complexity.

interferometry↗

NASA NTRS2015

Cubesat Constellation Design for Air Traffic Monitoring

Suitably equipped global and local air traffic can be tracked. The tracking information may then be used for control from ground-based stations by receiving the Automatic Dependent Surveillance-Broadcast (ADS-B) signal. The ADS-B signal, emitted from the aircraft's Mode-S transponder, is currently tracked by terrestrial based receivers but not over remote oceans or sparsely populated regions such as Alaska or the Pacific Ocean. Lack of real-time aircraft time/location information in remote areas significantly hinders optimal planning and control because bigger "safety bubbles" (lateral and vertical separation) are required around the aircraft until they reach radar-controlled airspace. Moreover, it presents a search-and-rescue bottleneck. Aircraft in distress, e.g. Air France AF449 that crashed in 2009, take days to be located or cannot be located at all, e.g. Malaysia Airlines MH370 in 2014. In this paper, we describe a tool for designing a constellation of small satellites which demonstrates, through high-fidelity modeling based on simulated air traffic data, the value of space-based ADS-B monitoring and provides recommendations for cost-efficient deployment of a constellation of small satellites to increase safety and situational awareness in the currently poorly-served surveillance area of Alaska. Air traffic data has been obtained from the Future ATM Concepts Evaluation Tool (FACET), developed at NASA Ames Research Center, simulated over the Alaskan airspace over a period of one day. The simulation is driven by MATLAB with satellites propagated and coverage calculated using AGI's Satellite ToolKit(STK10).

cubesats↗

NASA NTRS2019

CFD Evaluation of Lean-Direct Injection Combustors for Commercial Supersonics Technology

An overview is given of an effort that focused on using CFD analysis to complement design and configuration definition of Lean-Direct Injection (LDI) combustion concepts for NASA's Commercial Supersonic Transport (CST) program. The National Combustion Code (OpenNCC) was used to perform non-reacting and two-phase reacting flow computations for second and third generation LDI configurations at CST cruise conditions. All computations were performed with a consistent approach of mesh-generation, spray modeling, ignition and kinetics modeling. Emissions (EINOx) characteristics were predicted for CST cruise conditions, and compared with emissions data from experimental measurements to evaluate the fidelity of the CFD modeling approach to predict emissions changes in response to changes in supersonic cycle conditions.

nitrogen oxides injectors↗

NASA NTRS2019

CFD Evaluation Of Lean-Direct Injection Combustors for Commercial Supersonics Technology

Ajmani, Kumud↗

NASA NTRS2020

Motion Sickness and Concerns for Urban Air Mobility Vehicles: A Literature Review

Motion sickness is a general term for a constellation of signs and symptoms, generally due to exposure to abrupt, periodic, or unnatural accelerations, especially when traveling in a vehicle. Motion sickness results from a mismatch of the visual and nonvisual (vestibular and kinesthetic) information, the observed scene and the motion felt or lack of it. Motion sickness onset is associated with a pattern of physiological changes in heart rate, peripheral blood flow, respiration, and skin conductance and the pattern is repeatable for a particular subject but variable between subjects. Demographic factors such as gender and age that affect motion sickness are well known with children, women, and older adults more likely to be susceptible. Often motion sickness is assessed and quantified using variations of the motion sickness susceptibility questionnaires including the Pensacola Diagnostic Rating Scale and the Simulator Sickness Questionnaire. Even though symptoms are easily identified by such questionnaires, they commonly are subjective. Tools such as these questionnaires for screening individuals susceptible to motion sickness are useful, however, they are only mildly predictive. Moreover, models for predicting motion sickness, which have largely been developed for sea sickness, do not consider task characteristics. Predictions of motion sickness rates and prevalence for Urban Air Mobility (UAM) vehicles are not possible at present because data from actual flight or full-fidelity simulation are simply not yet available. Extrapolation from other modes of transportation (i.e., automobiles, buses, trains, boats, other types of aircraft) is difficult because of differences in the motion stimulus experienced, trip duration, and other factors. How UAM vehicles will change the social dynamics of passenger interaction and vehicle interior design changes (e.g., seat orientations) is unknown. Should motion sickness prove to be an issue, vehicle design modifications such as having passengers face forward, providing additional seat recline, giving each person their own climate control for airflow, perhaps ensuring the horizon is visible to all passengers (reducing visual occlusion by the headrest) and visually stabilizing displays on carry-on devices (smart phones, tablets, etc.) may benefit passengers. Several commercial companies provide wearable devices for physiological monitoring that have been validated and are suitable for use with passengers in UAM vehicles or high-fidelity simulators. Potential countermeasures for motion sickness include user-worn devices, anti-motion sickness medications, and non-pharmacological approaches such as biofeedback and Autogenic Feedback Training Exercise. Both simulator and in-vehicle UAM research is needed to evaluate the effectiveness of any potential countermeasure.

motion sickness↗

NASA NTRS2023

Blade-Wake Interaction Noise for Small Hovering Rotors, Part I: Characterization Study

This work illustrates the use of artificial neural network modeling to study and characterize broadband blade-wake interaction noise from hovering small unmanned aerial systems rotors subject to varying airfoil geometries, rotor geometries, and operating conditions. Design of experiments was used to create input feature spaces, and a high-fidelity strategy was implemented at the discrete data points defined by the input feature spaces to design airfoils and rotor blades, predict the unsteady rotor aerodynamics and aeroacoustics, and isolate the blade-wake interaction noise from the acoustic broadband noise. A metric for the blade-wake interaction noise was developed, and the ANOPP2 Artificial Neural Network Tool was used to identify an optimal prediction model for the nonlinear relationship between the input features and the metric for blade-wake interaction noise. This optimal artificial neural network was then validated over training/test data and exhibited prediction accuracy over 91% for data previously unseen by the model. A sensitivity analysis was conducted, which showed that input features that directly modify the thrust coefficient had a dominant effect over blade-wake interaction noise. The optimal prediction model along with aerodynamic simulations were used to further study the effect of varying input features on blade-wake interaction noise, and three types of blade-wake interaction noise were identified

Christopher S. Thurman↗

NASA NTRSDate not supplied

Vision-Based Distributed Sensing at Vertiports for Advanced Air Mobility and Urban Air Mobility Approach and Landing

Advanced Air Mobility (AAM) encompasses a broad vision for air transportation, including Urban Air Mobility (UAM) as a subset. AAM aims to create a more connected and efficient transportation network across various geographical settings. However, navigating AAM aircraft in GPS-denied or degraded environments during approach and landing is challenging. Traditional vision aids like glideslopes and localizers are limited in vertiport environments due to narrow beam constraints and reduced landing angle options. This paper addresses the need for accurate navigation solutions at vertiports by proposing a vision-based distributed sensing (VIDIS) system utilizing cameras with bundle adjustment to assist incoming AAM aircraft during approach and landing while monitoring surface movements to enhance safety and efficiency. Key focus areas for current and future vertiport developers include identifying suitable sensor types and infrastructure standards to support AAM operations and including vertiport markings as vision-based navigation aids. The proposed system offers a novel approach to overcoming navigation challenges in AAM operations, particularly in urban settings where traditional aids may be insufficient. Preliminary simulation results with distributed cameras demonstrate promising outcomes for implementing bundle adjustment techniques to enhance vision-based navigation solutions at vertiports. Generating waypoint-based trajectories via waypoint integration using explicit guidance synthesis (WINGS) creates smooth AAM trajectories for landing at vertiports by using the current waypoint's terminal conditions as the initial conditions for the next waypoint. Combining bundle adjustment's ground-based solution of vertiport features with WINGS, Coplanar Pose from Orthography and Scaling with Iterations (COPOSIT), and an extended Kalman filter (EKF) estimates the state of an incoming aircraft during approach and landing at vertiports. Future work includes testing VIDIS in a high-fidelity simulation and with real-world data.

Distributed sensing↗

NASA NTRSDate not supplied

Vision-Based Distributed Sensing at Vertiports for Advanced Air Mobility and Urban Air Mobility Approach and Landing

Distributed sensing↗

DOE OSTI2025

CFD Simulations of Lower Plenum Mixing

Review of model development and validation performed in the Advanced Reactor Technologies (ART) program for thermal mixing at the outlet of High Temperature Gas Reactors (HTGRs). Understanding the mixing that occurs in the lower plenum in an HTGR is necessary to facilitate design improvements and to perform reactor safety analysis. Numerical models are one possible approach to gain a better understanding of mixing in the lower plenum. Given the complexity of the geometry and the intense mixing present, it is important to perform validation of numerical models. Three models have been developed during FY2025: a porous media with Pronghorn, a Reynolds Averaged Navier Stokes (RANS) with STAR-CCM+, and a Large Eddy Simulation (LES) with NekRS. The reference facility is a scaled-down version of the lower plenum of the High Temperature Gas-Cooled Reactor - Pebble-bed Module (HTR-PM) demonstration reactor. Preliminary results of the porous media and the RANS shows general good agreement against experimental benchmark data. Future work will leverage high-fidelity results obtained through LES to guide model selection and improvements to the lower-fidelity models, with particular attention to the Pronghorn porous media.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2021

Model fusion with physics-guided machine learning: Projection-based reduced-order modeling

The unprecedented amount of data generated from experiments, field observations, and large-scale numerical simulations at a wide range of spatiotemporal scales has enabled the rapid advancement of data-driven and especially deep learning models in the field of fluid mechanics. Although these methods are proven successful for many applications, there is a grand challenge of improving their generalizability. This is particularly essential when data-driven models are employed within outer-loop applications like optimization. In this work, we put forth a physics-guided machine learning (PGML) framework that leverages the interpretable physics-based model with a deep learning model. Leveraging a concatenated neural network design from multi-modal data sources, the PGML framework is capable of enhancing the generalizability of data-driven models and effectively protects against or inform about the inaccurate predictions resulting from extrapolation. We apply the PGML framework as a novel model fusion approach combining the physics-based Galerkin projection model and long- to short-term memory (LSTM) network for parametric model order reduction of fluid flows. We demonstrate the improved generalizability of the PGML framework against a purely data-driven approach through the injection of physics features into intermediate LSTM layers. Our quantitative analysis shows that the overall model uncertainty can be reduced through the PGML approach, especially for test data coming from a distribution different than the training data. Moreover, we demonstrate that our approach can be used as an inverse diagnostic tool providing a confidence score associated with models and observations. The proposed framework also allows for multi-fidelity computing by making use of low-fidelity models in the online deployment of quantified data-driven models.

42 ENGINEERING↗

DOE OSTI2021

Physics-constrained, low-dimensional models for magnetohydrodynamics: First-principles and data-driven approaches

Plasmas are highly nonlinear and multiscale, motivating a hierarchy of models to understand and describe their behavior. However, there is a scarcity of plasma models of lower fidelity than magnetohydrodynamics (MHD), although these reduced models hold promise for understanding key physical mechanisms, efficient computation, and real-time optimization and control. Galerkin models, obtained by projection of the MHD equations onto a truncated modal basis, and data-driven models, obtained by modern machine learning and system identification, can furnish this gap in the lower levels of the model hierarchy. This work develops a reduced-order modeling framework for compressible plasmas, leveraging decades of progress in projection-based and data-driven modeling of fluids. We begin by formalizing projection-based model reduction for nonlinear MHD systems. To avoid separate modal decompositions for the magnetic, velocity, and pressure fields, we introduce an energy inner product to synthesize all of the fields into a dimensionally consistent, reduced-order basis. Next, we obtain an analytic model by Galerkin projection of the Hall-MHD equations onto these modes. We illustrate how global conservation laws constrain the model parameters, revealing symmetries that can be enforced in data-driven models, directly connecting these models to the underlying physics. We demonstrate the effectiveness of this approach on data from high-fidelity numerical simulations of a three-dimensional spheromak experiment. Finally, this manuscript builds a bridge to the extensive Galerkin literature in fluid mechanics and facilitates future principled development of projection-based and data-driven models for plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS2017

Interaction of Delaminations and Matrix Cracks in a CFRP Plate, Part II: Simulation Using an Enriched Shell Finite Element Model

Numerical simulations are presented of a recently developed test which creates multiple delaminations in a CFRP laminate specimen that grow and interact via transverse matrix cracks. A novel shell element enriched with the Floating Node Method, and a damage algorithm based on the Virtual Crack Closure Technique, were used to successfully simulate the tests. Additionally, a 3D high mesh fidelity model based on cohesive zones and continuum damage mechanics was used to simulate the tests and act as a representative of other similar state-of-the-art high mesh fidelity modeling techniques to compare to the enriched shell element. The enriched shell and high mesh fidelity models had similar levels of accuracy and generally matched the experimental data. With runtimes of 36 minutes for the shell model and 55 hours for the high mesh fidelity model, the shell model is 92 times faster than the high- fidelity simulation.

Mark W McElroy↗

NASA NTRS2020

Recent NASA Wind Tunnel Free-Flight Testing of a Multirotor Unmanned Aircraft System Vehicle

Wind tunnel free-flight tests of a small quadrotor vehicle were completed in the NASA Langley 12-Foot Low Speed Tunnel and 20-Foot Vertical Spin Tunnel. The primary objective of these tests was to acquire flight data in forward and descending flight for the purpose of assessing the fidelity of an all-attitude flight dynamics simulation previously developed from static and dynamic wind tunnel data. A secondary objective was to demonstrate and mature free-flight test methods specific to the emerging class of small unmanned aircraft and urban air mobility vehicles. Experimental flight data correlated well with simulation predictions which included steady trim conditions consistent with straight and level flight and quasi-steady conditions associated with descent velocities prone to vortex ring state development. The test method was shown to be well suited to these classes of vehicles and several unique infrastructure requirements, including tether systems and data acquisition requirements were identified. In addition, unique operational test techniques and safety procedures were developed to accommodate the testing. Results of these tests will be used to support air traffic management studies and research into safety assurance concepts that enable the integration of these classes of vehicles into the National Airspace System.

John V Foster↗

NASA NTRS2006

Increased Fidelity in Prediction Methods For Landing Gear Noise

An aeroacoustic prediction scheme has been developed for landing gear noise. The method is designed to handle the complex landing gear geometry of current and future aircraft. The gear is represented by a collection of subassemblies and simple components that are modeled using acoustic elements. These acoustic elements are generic, but generate noise representative of the physical components on a landing gear. The method sums the noise radiation from each component of the undercarriage in isolation accounting for interference with adjacent components through an estimate of the local upstream and downstream flows and turbulence intensities. The acoustic calculations are made in the code LGMAP, which computes the sound pressure levels at various observer locations. The method can calculate the noise from the undercarriage in isolation or installed on an aircraft for both main and nose landing gear. Comparisons with wind tunnel and flight data are used to initially calibrate the method, then it may be used to predict the noise of any landing gear. In this paper, noise predictions are compared with wind tunnel data for model landing gears of various scales and levels of fidelity, as well as with flight data on fullscale undercarriages. The present agreement between the calculations and measurements suggests the method has promise for future application in the prediction of airframe noise.

Lopes, Leonard V.↗