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At least 685 records · Page 38

Ion Thruster Used to Propel the Deep Space 1 Spacecraft to Comet Encounters

The NASA Solar Electric Propulsion Technology Applications Readiness (NSTAR) Project provided a xenon ion propulsion system to the Deep Space 1 (DS1) spacecraft to validate the propulsion system as well as perform primary propulsion for asteroid and comet encounters. The On-Board Propulsion Branch of the NASA Glenn Research Center at Lewis Field developed engineering model versions of the 30-cm-diameter ion thruster and the 2.5-kW power processor unit (PPU). Glenn then transferred the thruster and PPU technologies to Hughes Electron Dynamics and managed the contract, which supplied two flight sets of thrusters and PPU s to the Deep Space 1 spacecraft and to a ground-based life verification test at the Jet Propulsion Laboratory (JPL). In addition to managing the DS1 spacecraft development, JPL was responsible for the NSTAR Project management, thruster life tests, the feed system, diagnostics, and propulsion subsystem integration. The ion propulsion development team included NASA Glenn, JPL, Hughes Electronics, Moog Inc., and Spectrum Astro Inc. The overall NSTAR subsystem dry mass, including thruster, PPU, controller, cables, and the xenon storage and feed system, is 48 kg. The mass of the xenon stored onboard DS1 was about 81 kg, and the spacecraft wet mass was approximately 500 kg.The DS1 spacecraft was launched on October 24, 1998, and on July 29, 1999, it flew within 16 miles of the small asteroid Braille (formerly 1992KD) at a relative speed of 35,000 mph. As of November 1999, the ion propulsion system had performed flawlessly for nearly 149 days of thrusting. NASA has approved an extension to the mission, which will allow DS1 to continue thrusting to encounters with two comets in 2001. The DS1 optical and plasma diagnostic instruments will be used to investigate the comet and space environments. The spacecraft is scheduled to fly past the dormant comet Wilson- Harrington in January 2001 and the very active comet Borrelly in September 2001, at which time approximately 500 days of ion engine thrusting will have been completed.

Sovey, James S.↗

MACHINE LEARNING BASED CHEMICAL EXPLOSIVE MODE ANALYSIS (ML-CEMA)

The software consists of a Machine Learning based Chemical Explosive Mode Analysis (ML-CEMA) tool for advanced computational flame diagnostics. CEMA, originally based on eigen-analysis of the local thermochemical system, is capable of identifying reaction fronts and limit phenomena such as auto-ignition and extinction in practical combustion systems, such as internal combustion engines and gas turbine combustors. However, the original CEMA is computationally expensive for large reaction mechanisms that are typically needed to describe fuel chemistry of practical large-hydrocarbon fuels. This novel ML-CEMA tool employs a ML technique to accelerate the eigen-analysis of the basic CEMA approach by orders of magnitude, thus making it suitable for practical fuels. In ML-CEMA,zero-dimensional (0D) reactors and one-dimensional (1D) premixed flames are first used to generate a large number of data points for neural network based ML training. The trained ML model is then used to perform CEMA prediction. This ML-CEMA tool has been demonstrated in canonical 0D and 1D configurations as well as highly-transient three-dimensional spray flames exhibiting multi-mode turbulent combustion, showing promising results. ML-CEMA, as a standalone tool, can be used for computationally-efficient diagnostics of massive datasets generated from both experiments and simulations. For example, based on spatially resolved measurements of a small set of reactive scalars(such as temperature, hydroxyl radical and formaldehyde), ML-CEMA can effectively identify flame fronts and rare events. ML-CEMA also provides a robust online or offline flame feature detection tool. When used for on-the-fly simulations, ML-CEMA further enables zone-adaptive combustion modeling, in which the predicted eigenvalue is used as a robust mode indicator for judicious assignment of locally-valid combustion models. This ML-CEMA based zone-adaptive model can lead to substantial computational cost savings when used for large-scale simulations of multi-mode combustion systems. Third Party Code Web Page to Download Code Web Page Location of Third Party License

Xu, Chao↗

Rapid Evaluation Framework for the CMIP7 Assessment Fast Track

As Earth system models (ESMs) grow in complexity and in volume of output data, there is an increasing need for rapid, comprehensive evaluation of their scientific performance. The upcoming Assessment Fast Track for the Seventh Phase of the Coupled Model Intercomparison Project (CMIP7) will require expeditious response for model analyses designed to inform and drive integrated Earth system assessments. To meet this challenge, the Rapid Evaluation Framework (REF), a community-driven platform for benchmarking and performance assessment of ESMs, was designed and developed. The initial implementation of the REF, constructed to meet the near-term needs of the CMIP7 Assessment Fast Track, builds upon four disparate community evaluation and benchmarking tools that are coupled together using the Coordinated Model Evaluation Capabilities (CMEC) framework. The REF runs within a containerized workflow for portability and reproducibility and is aimed at generating and organizing diagnostics covering a variety of model variables. The REF leverages well documented observational datasets to provide assessments of model fidelity across a collection of diagnostics. All diagnostics were identified and selected with community involvement and consultation. Operational integration with the Earth System Grid Federation (ESGF) will permit automated execution of the REF for selected diagnostics as soon as model output data are published on ESGF by the originating modeling centers. The REF is designed to be portable across a range of current computational platforms to facilitate use by modeling centers for assessing the evolution of model versions or gauging the relative performance of CMIP simulations before being published on ESGF. When integrated into production simulation workflows, results from the REF provide immediate quantitative feedback that allows model developers and scientists to quickly identify model biases and performance issues. After the REF is released to the community, its subsequent development and support will be prioritized by an international consortium of scientists and engineers, enabling a broader impact across Earth science disciplines. For instance, the REF will facilitate improvements to models and will enhance confidence in model projections through process-based selection of models based on their performance with respect to observations. Production of reproducible diagnostics and community-based assessments are key features of the REF. Furthermore, providing interoperability with existing evaluation packages assures that contributions from previous community efforts will be available for use in future model intercomparison projects.

Hoffman, Forrest [ORNL] (ORCID:0000000158024134)↗

Understanding the ignition process and flame structure of conventional and oxygenated fuels under engine relevant conditions – An optical study

Renewably generated synthetic fuels such as poly-oxymethylene ethers (OME) have a significant potential to effectively break the soot-NOX trade-off in compression ignition engines by using exhaust gas recirculation (EGR) to maintain low nitrogen oxide (NOX) emissions while maintaining good efficiency and simultaneously contributing to circular carbon economy. However, owing to the fundamental differences in properties of OME when compared to fossil-based diesel fuels, it is critical to fully understand its ignition and combustion phenomenology to take advantage of this fuel to its utmost potential. In this context, this work outlines the results of a systematic experimental study performed in a heavy-duty, single-cylinder, optical engine probing the spatial and temporal progression of fuel decomposition and ignition behavior of OME when compared to n-dodecane, a diesel-fuel surrogate. Thermodynamic analysis and optical diagnostics techniques including simultaneous HCHO-PLIF and OH-PLIF complemented by high-speed OH* chemiluminescence were employed along with parametric sweeps of intake temperature and EGR dilution rates. OME does not exhibit any observable low temperature heat release irrespective of the ambient oxygen concentration. Differences in the observed diffusive flame structure such as longer flame lift-off length, less pronounced combustion recession, faster premixed burn at ignition (“volumetric” ignition), non-sooting behavior suggest that the inherent presence of fuel-bound oxygen in OME can skew the air-fuel ratio (AFR) distribution within the jet thereby reducing the reliance of combustion on mixing and air entrainment. This leads to rapid late-cycle oxidation leading to shorter combustion duration and favorable combustion phasing. Results also suggest that OME exhibits relatively weak negative temperature coefficient (NTC) behavior, however, the OME fuel-decomposition kinetic-pathways produce significant concentration of HCHO, which might be erroneously interpreted as a product of cool-flames.

Air-fuel ratio↗

Multi-fidelity physics-informed machine learning for probabilistic damage diagnosis

Machine learning (ML) models are gaining popularity in structural health monitoring (SHM) because of their ability to learn the complex relationship between damage and sensor data. However, the lack of sufficient experimental data for structures with different degrees of damage is a key problem in training ML models for SHM. This problem can be alleviated by using physics-based models to generate the required training data to build physics-informed ML (PIML) models for SHM. However, it takes significant computational effort to perform enough high-fidelity simulations of the diagnostic test. It is thus desirable to know whether the available computational resource budget should be expended on numerous low-fidelity physics simulations, or a small number of high-fidelity simulations, or their combination. In this paper, we investigate this aspect of generating adequate training data for PIML, by constructing multi-fidelity PIML models. We evaluate the performance of several PIML models, trained with different amounts of low-fidelity and high-fidelity data, in locating hidden cracks in concrete structures using a nonlinear dynamics-based diagnosis technique. Here, we find that high-fidelity physics simulations that do not cover the (test and damage) parameter space do not improve the performance of diagnostic PIML models built using data from many low-fidelity physics simulations.

42 ENGINEERING↗

Tensile Property and Lifetime Prediction for Low-Temperature Aged Uranium-Niobium Alloys

Thermal aging models and lifetime predictions for uranium-niobium (U-Nb) alloys were created using an approach similar to those previously employed. Lifetime estimates for generic U-6Nb components were thus updated; the reported value being 800 years. This update represents a small change in lifetime vs. that of the 2012 assessment (540 years). This lifetime estimate emerged from consideration of several model fits specific to the aging datasets and properties chosen. Aging was quantified using quasi-static tensile properties measured on specimens artificially aged for up to 10 years. The major change relative to the most recent 2012 LANL assessment was that a more comprehensive body of U-Nb literature data was mined, in addition to being augmented by the latest LANL and UK AWE data. The tensile data compilation was published separately (LANL report LA-14493, December 2016). Recognizing the chemical banding of industrially produced U-6Nb, models were developed for the mid-range (6 wt.%) and extrema (4 and 8 wt.%) compositions. Lifetime estimates were calculated for all three alloy classes (4, 6, 8 wt.% nominal) and two measures of total tensile elongation (TE) to failure, namely TE-ext. — extensometer method, and TE-NCD — normalized crosshead displacement method. The conservative assumption was made that whichever composition (4, 6, or 8 wt.% Nb) and property (TE-ext or TE-NCD) was the first to cross the ductility failure threshold would limit the lifetime of the entire component. Tensile strength properties did not figure into the lifetime predictions, but could be useful as age-sensitive diagnostics and were also modeled. Of these, only first yield strength is expected to show a change at 40°C aging vs. time = 0 over the ~100-year timespan of engineering interest. Second yield strength evolves more slowly, and ultimate tensile strength slower still. Among all the models, the apparent activation energies for aging were mostly in the narrow 29– 37 kcal/mol range, which is close to that for diffusion of Nb in gamma-uranium. This agreement may be coincidental. The data from recent long-term aging studies substantially improved the model fit quality and robustness of the lifetimes. Appendices document sensitivity studies of the model fits and lifetimes with respect to using more limited datasets. These results highlight the limitations of relying solely on data from scattered literature studies and smaller datasets more generally.

36 MATERIALS SCIENCE↗

Capsule defects measurement [Slides]

Recent high yield shots a NIF showed that capsule defects are limiting shot performance. Voids in the capsule are not well understood in how they degrade yield performance. Recent simulations show that voids can reduce compressibility without any diagnostic signatures but reduced yield. In extreme cases loss of compression is expected. Up to 10,000 voids might be necessary to measure the different effects. Experiments using capsules with engineered defects can help guide simulations and improve our understanding of the physics involved. The knowledge gained can be applied to other problems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Flight Test of Propulsion Monitoring and Diagnostic System

The objective of this program was to perform flight tests of the propulsion monitoring and diagnostic system (PMDS) technology concept developed by Honeywell under the NASA Advanced General Aviation Transport Experiment (AGATE) program. The PMDS concept is intended to independently monitor the performance of the engine, providing continuous status to the pilot along with warnings if necessary as well as making the data available to ground maintenance personnel via a special interface. These flight tests were intended to demonstrate the ability of the PMDS concept to detect a class of selected sensor hardware failures, and the ability to successfully model the engine for the purpose of engine diagnosis.

Gabel, Steve↗

Physics-Based Methods of Failure Analysis and Diagnostics in Human Space Flight

The Integrated Health Management (IHM) for the future aerospace systems requires to interface models of multiple subsystems in an efficient and accurate information environment at the earlier stages of system design. The complexity of modern aeronautic and aircraft systems (including e.g. the power distribution, flight control, solid and liquid motors) dictates employment of hybrid models and high-level reasoners for analysing mixed continuous and discrete information flow involving multiple modes of operation in uncertain environments, unknown state variables, heterogeneous software and hardware components. To provide the information link between key design/performance parameters and high-level reasoners we rely on development of multi-physics performance models, distributed sensors networks, and fault diagnostic and prognostic (FD&P) technologies in close collaboration with system designers. The main challenges of our research are related to the in-flight assessment of the structural stability, engine performance, and trajectory control. The main goal is to develop an intelligent IHM that not only enhances components and system reliability, but also provides a post-flight feedback helping to optimize design of the next generation of aerospace systems. Our efforts are concentrated on several directions of the research. One of the key components of our strategy is an innovative approach to the diagnostics/prognostics based on the real time dynamical inference (DI) technologies extended to encompass hybrid systems with hidden state trajectories. The major investments are into the multiphysics performance modelling that provides an access of the FD&P technologies to the main performance parameters of e.g. solid and liquid rocket motors and composite materials of the nozzle and case. Some of the recent results of our research are discussed in this chapter. We begin by introducing the problem of dynamical inference of stochastic nonlinear models and reviewing earlier results. Next, we present our analytical approach to the solution of this problem based on the path integral formulation. The resulting algorithm does not require an extensive global search for the model parameters, provides optimal compensation for the effects of dynamical noise, and is robust for a broad range of dynamical models. In the following Section the strengths of the algorithm are illustrated illustrated by inferring the parameters of the stochastic Lorenz system and comparing the results with those of earlier research. Next, we discuss a number of recent results in application to the development of the IHM for aerospace system. Firstly, we apply dynamical inference approach to a solution of classical three tank problems with mixed unknown continuous and binary parameters. The problem is considered in the context of ground support system for filling fuel tanks of liquid rocket motors. It is shown that the DI algorithm is well suited for successful solution of a hybrid version of this benchmark problem even in the presence of additional periodic and stochastic perturbation of unknown strength. Secondly, we illustrate our approach by its application to an analysis of the nozzle fault in a solid rocket motor (SRM). The internal ballistics of the SRM is modelled as a set of one-dimensional partial differential equations coupled to the dynamics of the propellant regression. In this example we are specifically focussed on the inference of discrete and continuous parameters of the nozzle blocking fault and on the possibility of an application of the DI algorithm to reducing the probability of "misses" of an on-board FD&P for SRM. In the next section re-contact problem caused by first stage/upper stage separation failure is discussed. The reaction forces imposed on the nozzle of the upper stage during the re-contact and their connection to the nozzle damage and to the thrust vector control (TVC) signal are obtained. It is shown that transient impact induced torquean be modelled as a response of an effective damped oscillator. A possible application of the DI algorithm to the inference of damage parameters and predicting fault dynamics ahead of time using the actuator signal is discussed. Finally, we formulate Bayesian inferential framework for development of the IHM system for in-flight structural health monitoring (SHM) of composite materials. We consider the signal generated by piezoelectric actuator mounted on composite structure generating elastic waves in it. The signal received by the sensor is than compared with the baseline signal. The possibility of damage inference is discussed in the context of development of the SHM.

Smelyanskiy, Vadim N.↗

Preparation for Hollow Cathode Testing for the Advanced Electric Propulsion System at NASA Glenn Research Center

NASA Glenn Research Center is performing activities to support the unique needs of hollow cathode development and testing for the Advanced Electric Propulsion System (AEPS). Three existing vacuum facilities have been outfitted as cathode test facilities, and each will serve a different role in upcoming testing. Vacuum Facility 67 is being developed to serve as a long-duration test facility for the Engineering Development Unit cathode, which is to be delivered by the AEPS contractor. It will feature a thruster-like magnetic field simulator and cold-cycle capability via a liquid nitrogen-cooled cold plate. Vacuum Facility 17 is being developed as a test facility for short- to medium-duration experiments in order to provide auxiliary support for the long-duration testing. It will feature a magnetic field simulator but not cold-cycling. Finally, Vacuum Facility 1 will be a high-pumping speed cathode development environment, and will feature an array of plasma and temperature diagnostics. In addition to the facility preparation work, a new cathode, referred to as the Mark II, has been designed. The Mark II is an evolution of the Technology Demonstration Unit cathodes that better evokes the geometry, fabrication, and construction of the forthcoming Engineering Development Unit. This cathode serves as a transition between the Technology Demonstration Unit cathodes used during early thruster development and the forthcoming Engineering Development Unit cathodes. It will be used as a means of verifying the new test facilities prior to arrival of Engineering Development Unit hardware. Details of the Mark II design and key features are presented, as well as details of future work to be performed.

Hall, Scott J.↗

Preparation for Hollow Cathode Testing for the Advanced Electric Propulsion System at NASA Glenn Research Center

NASA Glenn Research Center is performing activities to support the unique needs of hollow cathode development and testing for the Advanced Electric Propulsion System (AEPS). Three existing vacuum facilities have been outfitted as cathode test facilities, and each will serve a different role in upcoming testing. Vacuum Facility 67 is being developed to serve as a long-duration test facility for the Engineering Development Unit cathode, which is to be delivered by the AEPS contractor. It will feature a thruster-like magnetic field simulator and cold-cycle capability via a liquid nitrogen-cooled cold plate. Vacuum Facility 17 is being developed as a test facility for short- to medium-duration experiments in order to provide auxiliary support for the long-duration testing. It will feature a magnetic field simulator but not cold-cycling. Finally, Vacuum Facility 1 will be a high-pumping speed cathode development environment, and will feature an array of plasma and temperature diagnostics. In addition to the facility preparation work, a new cathode, referred to as the Mark II, has been designed. The Mark II is an evolution of the Technology Demonstration Unit cathodes that better evokes the geometry, fabrication, and construction of the forthcoming Engineering Development Unit. This cathode serves as a transition between the Technology Demonstration Unit cathodes used during early thruster development and the forthcoming Engineering Development Unit cathodes. It will be used as a means of verifying the new test facilities prior to arrival of Engineering Development Unit hardware. Details of the Mark II design and key features are presented, as well as details of future work to be performed.

Advanced Electric Propulsion System (AEPS)↗

Preparation for Hollow Cathode Testing for the Advanced Electric Propulsion System at NASA Glenn Research Center

NASA Glenn Research Center is performing activities to support the unique needs of hollow cathode development and testing for the Advanced Electric Propulsion System (AEPS). Three existing vacuum facilities have been outfitted as cathode test facilities, and each will serve a different role in upcoming testing. Vacuum Facility 67 is being developed to serve as a long-duration test facility for the Engineering Development Unit cathode, which is to be delivered by the AEPS contractor. It will feature a thruster-like magnetic field simulator and cold-cycle capability via a liquid nitrogen-cooled cold plate. Vacuum Facility 17 is being developed as a test facility for short- to medium-duration experiments in order to provide auxiliary support for the long-duration testing. It will feature a magnetic field simulator but not cold-cycling. Finally, Vacuum Facility 1 will be a high-pumping speed cathode development environment, and will feature an array of plasma and temperature diagnostics. In addition to the facility preparation work, a new cathode, referred to as the Mark II, has been designed. The Mark II is an evolution of the Technology Demonstration Unit cathodes that better evokes the geometry, fabrication, and construction of the forthcoming Engineering Development Unit. This cathode serves as a transition between the Technology Demonstration Unit cathodes used during early thruster development and the forthcoming Engineering Development Unit cathodes. It will be used as a means of verifying the new test facilities prior to arrival of Engineering Development Unit hardware. Details of the Mark II design and key features are presented, as well as details of future work to be performed.

Hall, Scott J.↗

Computational Study of Variable Fuel-Air Ratio and Hydrogen Doping in a Rotating Detonation Engine

Rotating detonation engines (RDEs) hold great promise as a technology for powering aviation engines. The pressure gain that results from continuously traversing detonation waves enables high theoretical performance compared to deflagration-based combustion. However, the harsh operating conditions inside an RDE restrict the availability of suitable experimental diagnostics to study these systems in detail and the range of spatial and temporal scales render numerical simulations of these systems difficult. In this study, we have combined adaptive mesh refinement and a robust shock-capturing approach to study RDE systems computationally using the compressible, reactive solver PeleC. Multi-species transport along with compressible Navier-Stokes equations are solved in the model along with finite-rate chemistry. Complex geometries are represented using an embedded boundary method with second-order spatial accuracy and the system is evolved in time using a second-order Runge-Kutta method. We present studies of a methane-air RDE system that is doped with varying levels of hydrogen. Our analysis focusses on how fuel mixture and doping levels effect the detonation flame structure and the generation of multiple wave modes.

ADVANCED PROPULSION SYSTEMS↗

CONFIG - Adapting qualitative modeling and discrete event simulation for design of fault management systems

CONFIG is a modeling and simulation tool prototype for analyzing the normal and faulty qualitative behaviors of engineered systems. Qualitative modeling and discrete-event simulation have been adapted and integrated, to support early development, during system design, of software and procedures for management of failures, especially in diagnostic expert systems. Qualitative component models are defined in terms of normal and faulty modes and processes, which are defined by invocation statements and effect statements with time delays. System models are constructed graphically by using instances of components and relations from object-oriented hierarchical model libraries. Extension and reuse of CONFIG models and analysis capabilities in hybrid rule- and model-based expert fault-management support systems are discussed.

Malin, Jane T.↗

A simplified dynamic model of the Space Shuttle main engine

A simplified model is presented of the space shuttle main engine (SSME) dynamics valid within the range of operation of the engine. This model is obtained by linking the linearized point models obtained at 25 different operating points of SSME. The simplified model was developed for use with a model-based diagnostic scheme for failure detection and diagnostics studies, as well as control design purposes.

Duyar, Ahmet↗

A simplified dynamic model of Space Shuttle Main Engine

A simplified dynamic model is presented of the Space Shuttle Main Engine (SSME) dynamics valid within the range of operation of the engine. This model is obtained by linking the linearized point models obtained at 25 different operating points of SSME. The simplified model was developed for use with a model-based diagnostic scheme for failure detection and diagnostics studies, as well as control design purposes.

Duyar, Ahmet↗