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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Computational Aerodynamic Analysis in Support of the CRM Tail Cone Thruster Configuration Wind Tunnel Test

NASA’s Advanced Air Transport Technology (AATT) project is breaching the boundaries of aircraft design in pursuit of eco-friendly solutions that are compatible with urban noise comfort levels. Boundary layer ingesting (BLI) propulsion systems promise to reduce fuel burn with additional potential benefits in noise reduction. Type-II BLI systems of the STARC-ABL type are the subject of a test campaign planned for fiscal year 2022 in the National Transonic Facility (NTF), for which a CRM-based model with a retrofitted tail cone thruster (TCT) has been designed. The present work is a precursor to the NTF test, where the 240 cases planned for the experiment were simulated using the Launch, Ascent and Vehicle Aerodynamics (LAVA)computational framework. Solution sensitivity to angle of attack, engine operating conditions, and the presence of the supporting structure (sting) in the wind tunnel test are analyzed in the extensive dataset. The main flow features contributing to the inlet distortion are identified as the vertical tail wake, wing downwash and fuselage upsweep vortices, with the latter two experiencing the greatest sensitivity to angle of attack. Finally, results from an inlet-guide-vane(IGV) design/integration study are presented. The LAVA team and the turbomachinery design team at NASA’s Ames and Glenn Research Centers are collaborating in an effort to reduce flow distortion upstream of the fan by means of integrating an IGV system into the CRM-TCT model. A significant improvement in flow distortion metrics has been achieved since the initial design iteration. Results employing an actuator zone model with realistic radially-varying thrust profiles to simulate first-order fan effects within LAVA are presented.

AATT↗
NASA NTRS2005

Computer Simulation of the VASIMR Engine

The goal of this project is to develop a magneto-hydrodynamic (MHD) computer code for simulation of the VASIMR engine. This code is designed be easy to modify and use. We achieve this using the Cactus framework, a system originally developed for research in numerical relativity. Since its release, Cactus has become an extremely powerful and flexible open source framework. The development of the code will be done in stages, starting with a basic fluid dynamic simulation and working towards a more complex MHD code. Once developed, this code can be used by students and researchers in order to further test and improve the VASIMR engine.

Garrison, David↗
NASA NTRS2012

Methods for Computationally Efficient Structured CFD Simulations of Complex Turbomachinery Flows

This research presents more efficient computational methods by which to perform multi-block structured Computational Fluid Dynamics (CFD) simulations of turbomachinery, thus facilitating higher-fidelity solutions of complicated geometries and their associated flows. This computational framework offers flexibility in allocating resources to balance process count and wall-clock computation time, while facilitating research interests of simulating axial compressor stall inception with more complete gridding of the flow passages and rotor tip clearance regions than is typically practiced with structured codes. The paradigm presented herein facilitates CFD simulation of previously impractical geometries and flows. These methods are validated and demonstrate improved computational efficiency when applied to complicated geometries and flows.

Herrick, Gregory P.↗
NASA NTRS2022

Flows in Enthalpy-based Thermal Evolution of Loops

Plasma-filled loop structures are common in the solar corona. Because detailed modeling of the dynamical evolution of these structures is computationally costly, an efficient method for computing approximate but quick physics-based solutions is to rely on space-integrated 0D simulations. The enthalpy-based thermal evolution of loops (EBTEL) framework is a commonly used method to study the exchange of mass and energy between the corona and transition region. EBTEL solves for density, temperature, and pressure, averaged over the coronal part of the loop, velocity at coronal base, and the instantaneous differential emission measure distribution in the transition region. The current single-fluid version of the code, EBTEL2, assumes that at all stages the flows are subsonic. However, sometimes the solutions show the presence of supersonic flows during the impulsive phase of heat input. It is thus necessary to account for this effect. Here, we upgrade EBTEL2 to EBTEL3 by including the kinetic energy term in the Navier–Stokes equation. We compare the solutions from EBTEL3 with those obtained using EBTEL2, as well as the state-of-the-art field-aligned hydrodynamics code HYDRAD. We find that the match in pressure between EBTEL3 and HYDRAD is better than that between EBTEL2 and HYDRAD. Additionally, the velocities predicted by EBTEL3 are in close agreement with those obtained with HYDRAD when the flows are subsonic. However, EBTEL3 solutions deviate substantially from HYDRAD’s when the latter predicts supersonic flows. Using the mismatches in the solution, we propose a criterion to determine the conditions under which EBTEL can be used to study flows in the system.

Solar coronal heating↗
NASA NTRS2001

Time-Dependent Simulations of Turbopump Flows

The objective of the current effort is to provide a computational framework for design and analysis of the entire fuel supply system of a liquid rocket engine, including high-fidelity unsteady turbopump flow analysis. This capability is needed to support the design of pump sub-systems for advanced space transportation vehicles that are likely to involve liquid propulsion systems. To date, computational tools for design/analysis of turbopump flows are based on relatively lower fidelity methods. An unsteady, three-dimensional viscous flow analysis tool involving stationary and rotational components for the entire turbopump assembly has not been available for real-world engineering applications. The present effort will provide developers with information such as transient flow phenomena at start up, impact of non-uniform inflows, system vibration and impact on the structure. In the proposed paper, the progress toward the capability of complete simulation of the turbo-pump for a liquid rocket engine is reported. The Space Shuttle Main Engine (SSME) turbo-pump is used as a test case for evaluation of the hybrid MPI/Open-MP and MLP versions of the INS3D code. The relative motion of the grid systems for the rotor-stator interaction was obtained using overset grid techniques. Time-accuracy of the scheme has been evaluated with simple test cases. Unsteady computations for the SSME turbo-pump, which contains 114 zones with 34.5 million grid points, are carried out on Origin 2000 systems at NASA Ames Research Center. Results from these time-accurate simulations with moving boundary capability will be presented along with the performance of parallel versions of the code.

Kris, Cetin C.↗
NASA NTRS1990

Probabilistic simulation of uncertainties in thermal structures

Development of probabilistic structural analysis methods for hot structures is a major activity at NASA-Lewis, and consists of five program elements: (1) probabilistic loads, (2) probabilistic finite element analysis, (3) probabilistic material behavior, (4) assessment of reliability and risk, and (5) probabilistic structural performance evaluation. Attention is given to quantification of the effects of uncertainties for several variables on High Pressure Fuel Turbopump blade temperature, pressure, and torque of the Space Shuttle Main Engine; the evaluation of the cumulative distribution function for various structural response variables based on assumed uncertainties in primitive structural variables; evaluation of the failure probability; reliability and risk-cost assessment; and an outline of an emerging approach for eventual hot structures certification. Collectively, the results demonstrate that the structural durability/reliability of hot structural components can be effectively evaluated in a formal probabilistic framework. In addition, the approach can be readily extended to computationally simulate certification of hot structures for aerospace environments.

Chamis, C. C.↗
NASA NTRS2004

QuakeSim and the Solid Earth Research Virtual Observatory

We are developing simulation and analysis tools in order to develop a solid Earth science framework for understanding and studying active tectonic and earthquake processes. The goal of QuakeSim and its extension, the Solid Earth Research Virtual Observatory (SERVO), is to study the physics of earthquakes using state-of-the-art modeling, data manipulation, and pattern recognition technologies. We are developing clearly defined accessible data formats and code protocols as inputs to simulations, which are adapted to high-performance computers. The solid Earth system is extremely complex and nonlinear resulting in computationally intensive problems with millions of unknowns. With these tools it will be possible to construct the more complex models and simulations necessary to develop hazard assessment systems critical for reducing future losses from major earthquakes. We are using Web (Grid) service technology to demonstrate the assimilation of multiple distributed data sources (a typical data grid problem) into a major parallel high-performance computing earthquake forecasting code. Such a linkage of Geoinformatics with Geocomplexity demonstrates the value of the Solid Earth Research Virtual Observatory (SERVO) Grid concept, and advances Grid technology by building the first real-time large-scale data assimilation grid.

virtual observatory↗
NASA NTRS1990

Probabilistic simulation of uncertainties in thermal structures

Development of probabilistic structural analysis methods for hot structures is a major activity at Lewis Research Center. It consists of five program elements: (1) probabilistic loads; (2) probabilistic finite element analysis; (3) probabilistic material behavior; (4) assessment of reliability and risk; and (5) probabilistic structural performance evaluation. Recent progress includes: (1) quantification of the effects of uncertainties for several variables on high pressure fuel turbopump (HPFT) blade temperature, pressure, and torque of the Space Shuttle Main Engine (SSME); (2) the evaluation of the cumulative distribution function for various structural response variables based on assumed uncertainties in primitive structural variables; (3) evaluation of the failure probability; (4) reliability and risk-cost assessment, and (5) an outline of an emerging approach for eventual hot structures certification. Collectively, the results demonstrate that the structural durability/reliability of hot structural components can be effectively evaluated in a formal probabilistic framework. In addition, the approach can be readily extended to computationally simulate certification of hot structures for aerospace environments.

Chamis, Christos C.↗
NASA NTRS2019

Onboard Decision-Making for Nominal and Contingency sUAS Flight

This study presents an onboard decision-making architecture for small unmanned aerial systems (sUAS). The decision-maker is part of NASA's SAFE50 project that is working under the UAS Traffic Management (UTM) Technical Capability Level (TCL) 4 to provide autonomous point-to-point UAV flight in BVLOS, high-density urban environments. The decision-maker monitors various metrics to determine the safety and feasibility of the mission and categorizes flight states as Nominal, Off-Nominal, Alternate Land, and Land Now in a finite state machine. Changes in the monitored metrics serve as transitions in the state machine and trigger replanning. Navigation degradation and communication failure are simulated to show the feasibility of the decision-maker framework in appropriately switching the flight state.

Baculi, Joshua↗
NASA NTRS2018

Comparison of CFD and DSMC Using Calibrated Transport Parameters

Hypersonic re-entry flows span a wide range of length scales where regions of both rarefied and continuum flow exist. Traditional computational fluid dynamics (CFD) techniques do not provide an accurate solution for the rarefied regions of such ‘mixed’ flow fields. Although direct simulation Monte Carlo (DSMC) can be used to accurately capture both the continuum and rarefied features of ‘mixed’ flow fields, they are computationally expensive when employed to simulate the low Knudsen number continuum regimes. Thus, a hybrid framework for seamlessly combining the two methodologies, CFD and DSMC, continues to be a topic of significant research effort. Ensuring consistency in the reaction kinetics and transport models employed within CFD and DSMC is a crucial requirement for obtaining a reliable solution from a hybrid framework for combined continuum/rarefied high speed flows. This paper represents one of the first studies to utilize the calibrated transport parameters developed to ensure consistency between CFD and DSMC solvers. The new variable soft sphere (VSS) parameters are compared to both previous “standard” variable hard sphere (VHS) parameters and also to solutions from the CFD transport properties that the new parameters were developed to reproduce.

Liechty, D. S.↗
NASA NTRSDate not supplied

A Synthesis Plug-in for Steady and Unsteady Loading and Thickness Noise Auralization

This paper describes the development and architecture of a plugin for the NASA Auralization Framework that synthesizes rotor sound pressures sample by sample for simulated propagation to auralize rotorcraft flyovers. The main component of the plugin is a preprocessor that synthesizes sound pressures before propagation methods are called. Rotor blade loadings, motion, and geometry data from various tools serve as input to the plugin. Farassat formulation 1A, a solution to the Ffowcs Williams-Hawkings equation, is used for the sound pressure calculations. Use of the plugin is demonstrated with two examples of steady periodic sound synthesis, but the synthesis method and preprocessor architecture described in this paper are also applicable to unsteady periodic and aperiodic sound syntheses.

Siddhartha Krishnamurthy↗
NASA NTRSDate not supplied

High-Fidelity Aerodynamic Analysis and Optimization of the SUSAN Electrofan Concept

The Subsonic Single Aft Engine (SUSAN) Electrofan is a new single-aisle regional jet class transport aircraft being studied by NASA, which benefits from reduced fuel consumption through a reduction in the number of hydrocarbon fuel-burning engines from two to one. This is achieved through a hybrid-electric system architecture, where a series of generators are used to extract power from a fuel-consuming tail cone thruster to drive electric propulsors mounted on the wings. To support the development of these propulsion systems, which involve high levels of propulsion-airframe integration, this paper presents high-fidelity analyses through computational fluid dynamics (CFD) simulations provided by the Launch Ascent and Vehicle Aerodynamics (LAVA) framework, which also includes capabilities for modeling the effect of active propulsors. A trade space exploration is performed to investigate the advantages of several wing mounted distributed electric propulsion system configurations, including over-wing, under-wing, and trailing-edge arrangements. For the aft fuselage propulsor, focus is on the sizing of the inlet, core, and bypass ducts. High-fidelity aerodynamic shape optimization is also used to help minimize the inlet distortion intensity experienced by the aft propulsor fan through a reshaping of the fuselage.

CAS↗
NASA NTRSDate not supplied

Community Radiative Transfer Model: Implementing A New Cloud Scattering Database and Developing the Forward Radar Module

The Mie theory is used by many fast RT models to estimate the optical properties of single particles. The Mie theory assumes spherical shapes for ice or snow particles with mixture of air and ice. However, hydrometeors scattering radiation at microwave frequencies have different shapes, sizes, and orientations. Therefore, using Mie theory to determine their optical properties leads to large uncertainties in all-sky radiative transfer calculations. The discrete dipole approximation (DDA) which approximates the optical properties of large objects in terms of discrete dipoles has shown promises in calculating the scattering properties of particles with different shapes in the microwave frequencies. The goal of the research was to enhance the CRTM scattering calculations for frozen hydrometeors in the microwave frequencies using the DDA technique. Given that such optical properties cannot be practically calculated on the fly, pre-computed look-up tables need to be implemented into the fast RT models to calculate the scattering properties of these particles using the DDA technique and the inputs provided by the users. Therefore, we implemented such pre-computed DDA databases into CRTM. In addition to using stand-alone CRTM calculations using collocated ATMS and reanalysis profiles, the data assimilation experiments conducted using the NOAA FV3GFS forecast system will be used to evaluate the scattering improvements. Additionally, we used the backscattering information from the DDA database to implement a radar simulator into CRTM. The radar operators takes advantage of CRTM different modules to calculate clouds absorption and scattering properties. In addition to the forward model both adjoint and tangent linear of the radar simulator are implemented and evaluated as well. The radar simulator is currently being tested within the JEDI/GEOS data assimilation framework to facilitate the assimilation of radar measurements such as CloudSat CPR and GPM DPR into the NASA GEOS model.

Isaac Moradi↗
NASA NTRSDate not supplied

Developing the CRTM Active Sensor Module

Active sensors provide vertically resolved atmospheric and cloud information, however the assimilation of such observations into NWP models has been limited for several reasons including lack of reliable forward model. We present the development of CRTM active sensor module including its adjoint and tangent linear by taking advantage of current CRTM modules for calculating atmospheric transmittance and cloud absorption and scattering. Current CRTM cloud coefficients lack cloud backscattering information, thus we have implemented a new cloud scattering database generated using the discrete dipole technique that include backscattering coefficients. The radar simulator is currently being tested within the JEDI/GEOS data assimilation framework to facilitate the assimilation of radar measurements such as CloudSat CPR and GPM DPR into the NASA GEOS model.

CRTM↗
NASA NTRSDate not supplied

Recent Developments in the Assimilation of Microwave and Radar Observations Into NWP Models

Microwave observations play a very important role in improving the weather forecasts. Although these observations are routinely assimilated into NWP models in clear-sky conditions, assimilation of all-sky microwave observations is very limited. Two main factors contributing to this limitation are inaccuracy in the input cloud and hydrometeor profiles used as input to the radiative transfer model and also error in scattering calculations performed by the radiative transfer model itself. The Mie theory is used by many fast RT models to estimate the optical properties of single particles. The Mie theory assumes spherical shapes for ice or snow particles with mixture of air and ice. However, hydrometeors scattering radiation at microwave frequencies have different shapes, sizes, and orientations. Therefore, using Mie theory to determine their optical properties leads to large uncertainties in all-sky radiative transfer calculations. The discrete dipole approximation (DDA) which approximates the optical properties of large objects in terms of discrete dipoles has shown promise in calculating the scattering properties of particles with different shapes in the microwave frequencies. This presentation focuses on recent advancements in the CRTM scattering calculations for frozen hydrometeors in the microwave frequencies using the DDA technique. In addition to using stand-alone CRTM calculations using collocated ATMS and reanalysis profiles, the data assimilation experiments conducted using the NOAA FV3GFS forecast system are used to evaluate the scattering improvements. Additionally, the backscattering information from the DDA database was used to implement a radar simulator into CRTM. The radar operator takes advantage of CRTM different modules to calculate clouds absorption and scattering properties. In addition to the forward model both adjoint and tangent linear of the radar simulator are implemented and evaluated as well. The radar simulator is currently being tested within the JEDI/GEOS data assimilation framework to facilitate the assimilation of radar measurements such as CloudSat CPR and GPM DPR into the NASA GEOS model.

Isaac Moradi↗
NASA NTRSDate not supplied

Enhancing CRTM All-Sky Simulations and Implementation of A New Active Sensor Module

Microwave observations play a very important role in improving the weather forecasts. Although these observations are routinely assimilated into NWP models in clear-sky conditions, assimilation of all-sky microwave observations is very limited. Two main factors contributing to this limitation are inaccuracy in the input cloud and hydrometeor profiles used as input to the radiative transfer model and also error in scattering calculations performed by the radiative transfer model itself. The Mie theory is used by many fast RT models to estimate the optical properties of single particles. The Mie theory assumes spherical shapes for ice or snow particles with mixture of air and ice. However, hydrometeors scattering radiation at microwave frequencies have different shapes, sizes, and orientations. Therefore, using Mie theory to determine their optical properties leads to large uncertainties in all-sky radiative transfer calculations. The discrete dipole approximation (DDA) which approximates the optical properties of large objects in terms of discrete dipoles has shown promise in calculating the scattering properties of particles with different shapes in the microwave frequencies. This presentation focuses on recent advancements in the CRTM scattering calculations for frozen hydrometeors in the microwave frequencies using the DDA technique. In addition to using stand-alone CRTM calculations using collocated ATMS and reanalysis profiles, the data assimilation experiments conducted using the NOAA FV3GFS forecast system are used to evaluate the scattering improvements. Additionally, the backscattering information from the DDA database was used to implement a radar simulator into CRTM. The radar operator takes advantage of CRTM different modules to calculate clouds absorption and scattering properties. In addition to the forward model both adjoint and tangent linear of the radar simulator are implemented and evaluated as well. The radar simulator is currently being tested within the JEDI/GEOS data assimilation framework to facilitate the assimilation of radar measurements such as CloudSat CPR and GPM DPR into the NASA GEOS model.

Isaac Moradi↗
NASA NTRSDate not supplied

CRTM Microwave Cloud Scattering Lookup Tables and Radar Simulator

Microwave observations play a very important role in improving the weather forecasts. Although these observations are routinely assimilated into NWP models in clear-sky conditions, assimilation of all-sky microwave observations is very limited. Two main factors contributing to this limitation are inaccuracy in the input cloud and hydrometeor profiles used as input to the radiative transfer model and also error in scattering calculations performed by the radiative transfer model itself. The Mie theory is used by many fast RT models to estimate the optical properties of single particles. The Mie theory assumes spherical shapes for ice or snow particles with mixture of air and ice. However, hydrometeors scattering radiation at microwave frequencies have different shapes, sizes, and orientations. Therefore, using Mie theory to determine their optical properties leads to large uncertainties in all-sky radiative transfer calculations. The discrete dipole approximation (DDA) which approximates the optical properties of large objects in terms of discrete dipoles has shown promise in calculating the scattering properties of particles with different shapes in the microwave frequencies. This presentation focuses on recent advancements in the CRTM scattering calculations for frozen hydrometeors in the microwave frequencies using the DDA technique. In addition to using stand-alone CRTM calculations using collocated ATMS and reanalysis profiles, the data assimilation experiments conducted using the NOAA FV3GFS forecast system are used to evaluate the scattering improvements. Additionally, the backscattering information from the DDA database was used to implement a radar simulator into CRTM. The radar operator takes advantage of CRTM different modules to calculate clouds absorption and scattering properties. In addition to the forward model both adjoint and tangent linear of the radar simulator are implemented and evaluated as well. The radar simulator is currently being tested within the JEDI/GEOS data assimilation framework to facilitate the assimilation of radar measurements such as CloudSat CPR and GPM DPR into the NASA GEOS model.

Isaac Moradi↗
NASA NTRSDate not supplied

Tradeoffs When Considering Deep Reinforcement Learning for Contingency Management in Advanced Air Mobility

Air transportation is undergoing a rapid evolution globally with the introduction of Advanced Air Mobility (AAM) and with it comes novel challenges and opportunities for transforming aviation. As AAM operations introduce increasing heterogeneity in vehicle capabilities and density, increased levels of automation are likely necessary to achieve operational safety and efficiency goals. This paper focuses on one example where increased automation has been suggested. Autonomous operations will need contingency management systems that can monitor evolving risk across a span of interrelated (or interdependent) hazards and, if necessary, execute appropriate control interventions via supervised or automated decision making. Accommodating this complex environment may require automated functions (autonomy) that apply artificial intelligence (AI) techniques that can adapt and respond to a quickly changing environment. This paper explores the use of Deep Reinforcement Learning (DRL) which has shown promising performance in complex and high-dimensional environments where the objective can be constructed as a sequential decision-making problem. An extension of a prior formulation of the contingency management problem as a Markov Decision Process (MDP) is presented and uses a DRL framework to train agents that mitigate hazards present in the simulation environment. A comparison of these learning-based agents and classical techniques is presented in terms of their performance, verification difficulties, and development process.

machine learningautonomous systems; flight simulat↗