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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Quantifying the Material Processing Conditions for an Optimized FSW Process

In friction stir welding (FSW), a rotating threaded pin tool is inserted into a weld seam and literally stirs the edgs of the seam together. This environmentally friendly, solid-state technique has been successfully used in the joining of materials that are difficult to fusion weld. To determine optimal processing parameters for producing a defect free weld, a better understanding of the resulting metal deformation flow path and velocity is required. In this study the metal flow fields are marked by the use of thin (0.001 in. tungsten) wires embedded in the weld seam at various locations. X-ray radiographs record the position and segmentation of the wire and are used to elucidate the flow field. Microstructures observed in a FSW cross-section in an aluminum alloy are related to their respective strain-strain rate-temperature histones along their respective flow trajectories. Two kinds of trajectories, each subjecting the weld metal to a distinct thermomechanical process and imparting a distinct microstructure, can be differentiated within the weld structure.

Schneider, Judy↗
NASA NTRSDate not supplied

Development of Laser Powder Bed Fusion NASA HR-2 for Hydrogen Sensitive Liquid Rocket Engine Applications

The National Aeronautics and Space Administration (NASA) has been involved in the development and maturation of metal additive manufacturing (AM) for space applications since the late 2000s. AM has provided new design and manufacturing opportunities to reduce cost and schedule, consolidate parts, and optimize performance. Laser Powder Bed Fusion (L-PBF) is one of the most commonly used AM processes to fabricate components of complex shape requiring fine feature resolution. Due to exposure to high-pressure gaseous hydrogen, mechanical property degradation caused by hydrogen environment embrittlement (HEE) is a critical concern for many materials in liquid hydrogen propulsion systems. NASA has identified the need to develop and advance new materials in unique engine applications using liquid hydrogen as a propellant. One such material being developed at NASA Marshall Space Flight Center is L-PBF NASA HR-2 (Hydrogen Resistant-2), a high-strength Fe-Ni-based superalloy resistant to HEE. The chemistry of NASA HR-2 was formulated to meet requirements for key liquid rocket engine (LRE) components that operate in high-pressure hydrogen environments. Initial development and material characterization found that NASA HR-2 has excellent L-PBF printability, and its microstructure evolves well after heat treatment. This new alloy has undergone fundamental metallurgical evaluations, heat treatment studies, detailed microstructure characterization, and mechanical testing across a range of temperatures. Tensile testing was performed in a pressurized gaseous hydrogen (GH2) environment to assess its resistance to HEE. L-PBF NASA HR-2 has an average yield stress of 95 ksi, an ultimate tensile stress of 165 ksi, and a very high fracture elongation of 34 - 36% when tested in a high-pressure (5 ksi) hydrogen environment. The tensile property data confirms hydrogen has little influence on HR-2’s ductility, strength, and fracture behavior. L-PBF NASA HR-2 is a promising option for many hydrogen-sensitive LRE components that require exceptional resistance to HEE. This paper will provide an overview of the L-PBF process development, material characterization, mechanical and thermophysical properties, and LRE hardware development for NASA HR-2.

Po S Chen↗
NASA NTRSDate not supplied

Development of Laser Powder Bed Fusion NASA HR-2 for Hydrogen Sensitive Liquid Rocket Engine Applications

The National Aeronautics and Space Administration (NASA) has been involved in the development and maturation of metal additive manufacturing (AM) for space applications since the late 2000’s. AM has provided new design and manufacturing opportunities to reduce cost and schedule, consolidate parts, and optimize performance. Laser Powder Bed Fusion (L-PBF) is one of the most commonly used AM processes to fabricate components that have complex shape and need fine feature resolution. Due to exposure to high pressure gaseous hydrogen, mechanical property degradation caused by hydrogen environment embrittlement (HEE) is a critical concern for many materials in liquid hydrogen propulsion systems. NASA has identified the need to develop and advance new materials in unique engine applications using liquid hydrogen as a propellant. One such material being developed at NASA Marshall Space Flight Center is L-PBF NASA HR-2 (Hydrogen Resistant-2), a high-strength Fe-Ni-based superalloy resistant to HEE. The chemistry of NASA HR-2 was formulated to meet requirements for key liquid rocket engine (LRE) components that operate in high-pressure hydrogen environments. Initial development and material characterization found NASA HR-2 has excellent L-PBF printability and its microstructure evolves well after heat treatment. This new alloy has undergone fundamental metallurgical evaluations, heat treatment studies, detailed microstructure characterization, and mechanical testing across a range of temperatures. Tensile testing was performed in pressurized gaseous hydrogen (GH2) environment to assess its resistance to HEE. L-PBF NASA HR-2 has an average yield stress of 95 ksi, ultimate tensile stress of 165 ksi, and very high fracture elongation at 34 - 36% when tested in a 5 ksi high pressure hydrogen environment. The tensile property data confirms hydrogen has little influence on its ductility, strength, and fracture behavior. L-PBF NASA HR-2 is a promising option for many hydrogen sensitive LRE components that require exceptional resistance to HEE. The development of L-PBF NASA HR-2 is funded under the grants provided by Jacobs TIPI program and the Liquid Engine Office at NASA Marshall Space Flight Center. This paper will provide an overview of the L-PBF process development, material characterization, mechanical and thermophysical properties, and LRE hardware development for NASA HR-2.

NASA HR-2↗
NASA NTRSDate not supplied

Development of Laser Powder Bed Fusion NASA HR-2 for Hydrogen Sensitive Liquid Rocket Engine Applications

The National Aeronautics and Space Administration (NASA) has been involved in the development and maturation of metal additive manufacturing (AM) for space applications since the late 2000’s. AM has provided new design and manufacturing opportunities to reduce cost and schedule, consolidate parts, and optimize performance. Laser Powder Bed Fusion (L-PBF) is one of the most commonly used AM processes to fabricate components that have complex shape and need fine feature resolution. Due to exposure to high pressure gaseous hydrogen, mechanical property degradation caused by hydrogen environment embrittlement (HEE) is a critical concern for many materials in liquid hydrogen propulsion systems. NASA has identified the need to develop and advance new materials in unique engine applications using liquid hydrogen as a propellant. One such material being developed at NASA Marshall Space Flight Center is L-PBF NASA HR-2 (Hydrogen Resistant-2), a high-strength Fe-Ni-based superalloy resistant to HEE. The chemistry of NASA HR-2 was formulated to meet requirements for key liquid rocket engine (LRE) components that operate in high-pressure hydrogen environments. Initial development and material characterization found NASA HR-2 has excellent L-PBF printability and its microstructure evolves well after heat treatment. This new alloy has undergone fundamental metallurgical evaluations, heat treatment studies, detailed microstructure characterization, and mechanical testing across a range of temperatures. Tensile testing was performed in pressurized gaseous hydrogen (GH2) environment to assess its resistance to HEE. L-PBF NASA HR-2 has an average yield stress of 95 ksi, ultimate tensile stress of 165 ksi, and very high fracture elongation at 34 - 36% when tested in a 5 ksi high pressure hydrogen environment. The tensile property data confirms hydrogen has little influence on its ductility, strength, and fracture behavior. L-PBF NASA HR-2 is a promising option for many hydrogen sensitive LRE components that require exceptional resistance to HEE. The development of L-PBF NASA HR-2 is funded under the grants provided by Jacobs TIPI program and the Liquid Engine Office at NASA Marshall Space Flight Center. This paper will provide an overview of the L-PBF process development, material characterization, mechanical and thermophysical properties, and LRE hardware development for NASA HR-2.

NASA HR-2↗
NASA NTRSDate not supplied

NASA Armstrong Flight Research Center Dynamics and Controls (530)

AFRC Controls and Dynamics Branch - Research Areas: - Traditional GN&C - Classical and advanced control algorithms - Risk based approaches for safety critical applications - Integration of novel sensors and sensor fusion (FOSS, LIDAR, etc.) - Trajectory optimization and control - Flight/System Dynamics - Equations of Motion and integrated modeling of vehicles and vehicle systems - Unique and novel vehicle dynamics - Methods for extracting relevant vehicle dynamic information from flight data - Human and vehicle interfaces and interactions - Handling Qualities and Pilot-in-the-loop oscillations (PIO) predictions and design metrics - Ride quality research - Autonomy - Novel algorithms, sensors, and sensor fusion - Bounding risk for testing automated systems - Pilot/Operator interactions - Engineering Support and Airworthiness Assessments - Aircraft modifications and experimental configurations

Chris Miller↗
NASA NTRS2023

Additive Manufacturing of Oxide Dispersion Strengthened Multi Principle Element Alloys for Future Aerospace Applications

Oxide Dispersion Strengthened (ODS) materials have long been of interest for their high temperature applications, and additive manufacturing enables their manufacturing viability. The ODS multi-principle element alloy NiCoCr was prepared using powder metallurgy techniques, additively manufactured, and evaluated for its processingmicrostructure-property relationships. The high temperature foundations of nickel-base superalloys and ODS materials were combined with the manufacturing advantages of 3D printing and the chemical simplicity of NiCoCr to inspire this work, which was divided into powder and printed material assessments. The project was achieved through multiple iterative project loops to assess the processing parameters’ impact on the microstructure and mechanical properties of the feedstock powder and printed material. The powder investigations (Chapter 3) focused on understanding the oxide coating that formed on the metal powder following acoustic mixing. Time of Flight Secondary Ion Mass Spectrometry was used to semi-quantitatively assess the amount of yttrium on the surface of the mixed powders, and indicated that a combination of higher mixing condition energy and moderate mixing time resulted in the most oxide coating on the NiCoCr powder. The results were supported by a qualitative assessment of scanning electron images of coated powder particles. Following mixing, the ODS NiCoCr was consolidated by Laser Powder Bed Fusion. The evaluations of the printed material (Chapter 4) frst considered screening experiments including Archimedes’ density, porosity, and grain size and number metrics from electron backscatter diffraction data. After the ideal additive manufacturing parameters were identifed, both the oxide homogeneity and yield strength were discussed for the idealized printed material. Overall, the project suggests that the combined use of qualitative or semi-quantitative powder surface analysis with Archimedes’ density analyses can be a valid high-throughput technique which can lead to process optimization of Laser Powder Bed Fusion additively manufactured ODS material.

Laura G Wilson↗
NASA NTRS1999

Performance Optimization of the Gasdynamic Mirror Propulsion System

Nuclear fusion appears to be a most promising concept for producing extremely high specific impulse rocket engines. Engines such as these would effectively open up the solar system to human exploration and would virtually eliminate launch window restrictions. A preliminary vehicle sizing and mission study was performed based on the conceptual design of a Gasdynamic Mirror (GDM) fusion propulsion system. This study indicated that the potential specific impulse for this engine is approximately 142,000 sec. with about 22,100 N of thrust using a deuterium-tritium fuel cycle. The engine weight inclusive of the power conversion system was optimized around an allowable engine mass of 1500 Mg assuming advanced superconducting magnets and a Field Reversed Configuration (FRC) end plug at the mirrors. The vehicle habitat, lander, and structural weights are based on a NASA Mars mission study which assumes the use of nuclear thermal propulsion' Several manned missions to various planets were analyzed to determine fuel requirements and launch windows. For all fusion propulsion cases studied, the fuel weight remained a minor component of the total system weight regardless of when the missions commenced. In other words, the use of fusion propulsion virtually eliminates all mission window constraints and effectively allows unlimited manned exploration of the entire solar system. It also mitigates the need to have a large space infrastructure which would be required to support the transfer of massive amounts of fuel and supplies to lower a performing spacecraft.

Emrich, William J., Jr.↗
NASA NTRS2008

Issues in Data Fusion for Satellite Aerosol Measurements for Applications with GIOVANNI System at NASA GES DISC

We look at issues, barriers and approaches for Data Fusion of satellite aerosol data as available from the GES DISC GIOVANNI Web Service. Daily Global Maps of AOT from a single satellite sensor alone contain gaps that arise due to various sources (sun glint regions, clouds, orbital swath gaps at low latitudes, bright underlying surfaces etc.). The goal is to develop a fast, accurate and efficient method to improve the spatial coverage of the Daily AOT data to facilitate comparisons with Global Models. Data Fusion may be supplemented by Optimal Interpolation (OI) as needed.

Gopalan, Arun↗
NASA NTRS2018

The Fusion Driven Rocket: Nuclear Propulsion through Direct Conversion of Fusion Energy

The future of manned space exploration and development of space depends critically on the creation of a dramatically more efficient propulsion architecture for in-space transportation. A very persuasive reason for investigating the applicability of nuclear power in rockets is the vast energy density gain of nuclear fuel when compared to chemical combustion energy. The Fusion Driven rocket (FDR) represents a revolutionary approach to fusion propulsion where the power source releases its energy directly into the propellant, not requiring conversion to electricity. It employs a solid lithium propellant that requires no significant tankage mass. The propellant is rapidly heated and accelerated to high exhaust velocity (> 30 km/s), while having no substantial physical interaction with the spacecraft thereby avoiding damage to the rocket and limiting both the thermal heat load and radiator mass. The key to achieving this stems from research at MSNW and the UW on the magnetically driven implosion of metal foils onto a magnetized plasma target to obtain fusion conditions. A logical extension of this work leads to a method that utilizes these metal shells (or liners) to not only achieve fusion conditions, but to serve as the propellant as well. Several low-mass, magnetically driven metal liners are inductively driven to converge radially and axially and form a thick blanket surrounding the target plasmoid and compress the plasmoid to fusion conditions. Virtually all of the radiant, neutron and particle energy from the plasma is absorbed by the encapsulating, thick metal blanket thereby isolating the spacecraft from the fusion. This energy, in addition to the intense Ohmic heating at peak magnetic field compression, is adequate to vaporize and ionize the metal blanket. The expansion of this hot, ionized metal propellant through a magnetically insulated nozzle produces high thrust at the optimal Isp. The energy from the fusion process, along with the waste heat, is thus utilized at very high efficiency. The basic scheme for FDR is illustrated and described in the report (see Fig. 2) The two most critical issues in meeting challenges introduced employing magneto-inertial fusion as the power source is driver efficiency and “stand-off” – the ability to isolate and protect fusion and thruster from the resultant fusion energy. By employing metal shells for compression, it is possible to produce the desired convergent motion inductively by inserting the metal sheets along the inner surface of cylindrical or conically tapered coils. Both stand-off and energy efficiency issues are solved by this arrangement. 3 This two year effort focused on achieving three key criteria for the Fusion Driven Rocket to move forward for technological development: (1) the physics of the FDR must be fully understood and validated, (2) the design and technology development for the FDR required for its implementation in space must be fully characterized, and (3) an in-depth analysis of the rocket design and spacecraft integration as well as mission architectures enabled by the FDR need to be performed. A subscale, laboratory liner compression test facility was assembled at the University of Washington Plasma Dynamics Laboratory with sufficient liner kinetic energy (~ 0.5 MJ) to reach conditions required for fusion breakeven conditions. Detailed experimental studies of the dynamic behavior of the driven liners as well as liner convergence and magnetic compression were performed. The development of both the 1D liner dynamics code and the full 3D ANSYS® liner calculations was achieved. The characterization of both the FDR and spacecraft as well as a design architecture analysis was conducted that included an examination of a wide range of mission architectures and destinations for which this fusion propulsion system would be enabling or critical. In particular a rapid, single launch manned Mars mission was developed.

Energy↗
NASA NTRS1988

Kuhn-Tucker optimization based reliability analysis for probabilistic finite elements

The fusion of probability finite element method (PFEM) and reliability analysis for fracture mechanics is considered. Reliability analysis with specific application to fracture mechanics is presented, and computational procedures are discussed. Explicit expressions for the optimization procedure with regard to fracture mechanics are given. The results show the PFEM is a very powerful tool in determining the second-moment statistics. The method can determine the probability of failure or fracture subject to randomness in load, material properties and crack length, orientation, and location.

Liu, W. K.↗
NASA NTRS1993

Data fusion with artificial neural networks (ANN) for classification of earth surface from microwave satellite measurements

A data fusion system with artificial neural networks (ANN) is used for fast and accurate classification of five earth surface conditions and surface changes, based on seven SSMI multichannel microwave satellite measurements. The measurements include brightness temperatures at 19, 22, 37, and 85 GHz at both H and V polarizations (only V at 22 GHz). The seven channel measurements are processed through a convolution computation such that all measurements are located at same grid. Five surface classes including non-scattering surface, precipitation over land, over ocean, snow, and desert are identified from ground-truth observations. The system processes sensory data in three consecutive phases: (1) pre-processing to extract feature vectors and enhance separability among detected classes; (2) preliminary classification of Earth surface patterns using two separate and parallely acting classifiers: back-propagation neural network and binary decision tree classifiers; and (3) data fusion of results from preliminary classifiers to obtain the optimal performance in overall classification. Both the binary decision tree classifier and the fusion processing centers are implemented by neural network architectures. The fusion system configuration is a hierarchical neural network architecture, in which each functional neural net will handle different processing phases in a pipelined fashion. There is a total of around 13,500 samples for this analysis, of which 4 percent are used as the training set and 96 percent as the testing set. After training, this classification system is able to bring up the detection accuracy to 94 percent compared with 88 percent for back-propagation artificial neural networks and 80 percent for binary decision tree classifiers. The neural network data fusion classification is currently under progress to be integrated in an image processing system at NOAA and to be implemented in a prototype of a massively parallel and dynamically reconfigurable Modular Neural Ring (MNR).

Lure, Y. M. Fleming↗
NASA NTRS1991

Space fusion energy conversion using a field reversed configuration reactor: A new technical approach for space propulsion and power

The fusion energy conversion design approach, the Field Reversed Configuration (FRC) - when burning deuterium and helium-3, offers a new method and concept for space transportation with high energy demanding programs, like the Manned Mars Mission and planetary science outpost missions require. FRC's will increase safety, reduce costs, and enable new missions by providing a high specific power propulsion system from a high performance fusion engine system that can be optimally designed. By using spacecraft powered by FRC's the space program can fulfill High Energy Space Missions (HESM) in a manner not otherwise possible. FRC's can potentially enable the attainment of high payload mass fractions while doing so within shorter flight times.

Schulze, Norman R.↗
NASA NTRS1993

Engineering workstation: Sensor modeling

The purpose of the engineering workstation is to provide an environment for rapid prototyping and evaluation of fusion and image processing algorithms. Ideally, the algorithms are designed to optimize the extraction of information that is useful to a pilot for all phases of flight operations. Successful design of effective fusion algorithms depends on the ability to characterize both the information available from the sensors and the information useful to a pilot. The workstation is comprised of subsystems for simulation of sensor-generated images, image processing, image enhancement, and fusion algorithms. As such, the workstation can be used to implement and evaluate both short-term solutions and long-term solutions. The short-term solutions are being developed to enhance a pilot's situational awareness by providing information in addition to his direct vision. The long term solutions are aimed at the development of complete synthetic vision systems. One of the important functions of the engineering workstation is to simulate the images that would be generated by the sensors. The simulation system is designed to use the graphics modeling and rendering capabilities of various workstations manufactured by Silicon Graphics Inc. The workstation simulates various aspects of the sensor-generated images arising from phenomenology of the sensors. In addition, the workstation can be used to simulate a variety of impairments due to mechanical limitations of the sensor placement and due to the motion of the airplane. Although the simulation is currently not performed in real-time, sequences of individual frames can be processed, stored, and recorded in a video format. In that way, it is possible to examine the appearance of different dynamic sensor-generated and fused images.

Pavel, M↗
NASA NTRSDate not supplied

Distributed Target Tracking With Optimal Data Migration

The paper presents an Extended Kalman Filter based framework for airborne target tracking using dynamic information fusion from multi-modal sensors with geodiversity. First, the algorithm execution location is determined using an optimal data migration strategy, next the sensors information is dynamically fused at each estimation instance using validity flag for each sensor reading, finally the target estimation is updated based on the fused innovation vector. The approach is applied to synthetic data generated from the radar and camera models located on the ground for the simulated target flight in Reflection simulation environment.

Distributed sensing↗
NASA NTRSDate not supplied

Understanding the Impact of Unobservable Variables on the Performance of Predictive Models: The Need for Feature Space Partitioning and Fusion

When developing predictive models over a dataset, the model is globally optimized across the entire feature space to learn a decision boundary. However, when unobservable variables—which cannot be measured or estimated—interact with the observable variables, this can negatively impact the optimization applied to the decision boundary since the data samples introduced by unobservable variables may have little to no association with the applied global optimization. This, consequently, penalizes the entire decision boundary and model performance. This paper examines some of the detrimental effects of unobservable variables, particularly their role in creating new modes in the distribution of observable variables and reducing the separability of class distributions. Such challenges result in skewed or warped decision boundaries and decreased accuracy of model predictions, particularly for interpretable models like logistic regression and decision trees. Through two illustrative case examples, we highlight the need to address the challenges imposed by unobservable variables. We propose a strategy to mitigate these challenges by creating local regions within the feature space through partitioning. This enables the optimization of local models within the regions to overcome the impact of unobservability in different feature space localities. Research into a more sophisticated partitioning strategy and where the partition should be relative to the sample of interest is left as future work. Through the analysis of the impact of unobservability and the development of a partitioning method, we demonstrate the clear need for a partitioning strategy that integrates knowledge from multiple local models to estimate risk factors using information fusion. Thus, we establish the foundation and motivation for using partitioning and information fusion to overcome the effects of unobservability in predictive models. Formal fusion methods, such as Dempster-Shafer theory, can better leverage the information from local regions to improve the performance of interpretable predictive models in the presence of unobservable variables.

Time Series Data↗
NASA NTRS2004

Computer Tomography 3-D Imaging of the Metal Deformation Flow Path in Friction Stir Welding

In friction stir welding, a rotating threaded pin tool is inserted into a weld seam and literally stirs the edges of the seam together. This solid-state technique has been successfully used in the joining of materials that are difficult to fusion weld such as aluminum alloys. To determine optimal processing parameters for producing a defect free weld, a better understanding of the resulting metal deformation flow path is required. Marker studies are the principal method of studying the metal deformation flow path around the FSW pin tool. In our study, we have used computed tomography (CT) scans to reveal the flow pattern of a lead wire embedded in a FSW weld seam. At the welding temperature of aluminum, the lead becomes molten and thus tracks the aluminum deformation flow paths in a unique 3-dimensional manner. CT scanning is a convenient and comprehensive way of collecting and displaying tracer data. It marks an advance over previous more tedious and ambiguous radiographic/metallographic data collection methods.

Schneider, Judy↗
NASA NTRSDate not supplied

Target Tracking with Distributed Sensing and Optimal Data Migration

The paper presents an Extended Kalman Filter based framework for airborne target tracking using adaptive information fusion from multi-modal multi-rate distributed sensors network. First, the tracking algorithm execution location is determined using an optimal data migration strategy, which also computes the associated delays for each sensor data to arrive at the computing location. Next, the fast (zero-delay) sensors information is dynamically fused in the filter correction procedure at the arrival instance of each valid sensor reading. Finally, the target estimation is updated based on the valid slow (delayed) data, which are grouped according to the delay-time steps before application of the Larsen's method. This approach is applied to the synthetic sensor data generated by means of the ground based radar and camera models for the simulated target flight in Reflection simulation environment.

Distributed sensing↗