Characterization and Processing of High Temperature Shape Memory Alloys for Aerospace Applications
Explore the source record for details and available documents.
SEARCH · Search NASA
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Explore the source record for details and available documents.
Abstract not provided
The U.S. Department of Energy’s (DOE) Sunshot 2030 initiative has a goal of reducing the cost of concentrating solar power (CSP) to 5 cents per kWh for baseload power plants. One of the potential pathways to this goal includes a reduction in the cost of the supercritical CO2 (sCO2) power block to 0.9 cents per kWh. Recuperators—high and low temperatures, used in the sCO2 power cycle, contribute to >50% of the cost of the power cycle. This work studies the feasibility towards a ≥10% cost reduction for High Temperature Recuperators (HTR) used in the sCO2 power cycle. One way to address the cost reduction is by leveraging low-cost additive manufacturing, specifically, Binder Jet Additive Manufacturing (BJAM) to 3D print HTRs at scale. This study focuses on the development of a BJAM process towards 3D printing HTR cores using Stainless Steel alloy 316L (SS316L). To evaluate the suitability of the BJ process towards the HTR, high level specifications of the application are translated to materials capability requirements. Subsequently, at-temperature materials testing is conducted on as-printed and sintered additively manufactured coupons. Data from the coupons are compared against cast and wrought SS316L data obtained from the literature. Results show that the tensile properties from the BJ process compare well against cast properties. Furthermore, a baseline analysis of creep testing data is established for the BJ process, and insights are drawn from the results towards future improvements of the process.
Light weight, heat and fire resistant low smoke generating polyimide foams are developed for aircraft seating applications. The material is upgraded and classified into groups for fabrication of cushions possessing acceptable comfort properties. Refinement and selection of foaming processes using a variety of previously developd foaming techniques and definition of property relationships to arrive at the selection and classfication of polyimide foams into five groups in accordance with predetermined ILD values are emphasized.
It is pointed out that the MLA instrument represents the next generation in the Landsat series of earth resources satellites. The MLA sensor concept utilizes a pushbroom scan mode to eliminate electromechanical scan mirrors, and the lower reliabililty and higher power dissipation which accompany their employment. The pushbroom scanner makes use of a linear array which consists generally of thousands of detectors oriented perpendicular to the along-track direction of the satellite. Test techniques have been developed for the measurement of the module parameters which are critical to MLA focal plane performance. These measurements include the determination of infrared responsivity, linearity over the dynamic range, temporal noise, and fixed pattern effects on each detector element of each module tested. Tests related to spectral response, crosstalk, and spot scan profiles are also conducted. A description is provided of the test equipment involved.
This paper provides a summary overview of the vibration characteristics of split Stirling cryocoolers of the Oxford type and describes means being developed to achieve vibration levels consistent with the exacting requirements of sensitive infrared spectrometer instruments currently under development for NASA applications. A key emphasis of the paper is on exploring both active and passive means of reducing the residual upper harmonics of the drive frequency that remain with nulled back-to-back compressor and displacer units. Vibration supression results, measured with JPL's unique six-DOF force dynamometer, are presented for an 80 K Stirling cooler.
An acousto-electric levitator has been developed to study the behavior of liquid drop and solid particle clusters and arrays. Unlike an ordinary acoustic levitator that uses only a standing acoustic wave to levitate a single drop or particle, this device uses an extra electric static field and the acoustic field simultaneously to generate and levitate charged drops in two-dimensional arrays in air without any contact to a solid surface. This cluster and array generation (CAG) instrument enables us to steadily position drops and arrays to study the behavior of multiple drop and particle systems such as spray and aerosol systems relevant to the energy, environmental, and material sciences.
In this paper the emphasis is on accurate majority carrier concentration EC-V profiling of structures based on Indium Phosphide and Gallium Arsenide, using a newly developed electrolyte based on Hydrogen Flouride, Acetic Acid, Phosphoric Acid, 1-phenyl-2-propanamine and Ammonia Diflouride. Some preliminary data on the use of this electrolyte for determining the energy distribution of surface and deep states of these structures, applicable to fabrication process optimization and radiation induced defects studies of solar cells, are also provided.
Explore the source record for details and available documents.
We are introducing machine learning methods to the play fairway analysis to generate geothermal potential maps to support the evaluation of geothermal resource potential and the exploration for undiscovered blind geothermal systems in the Nevada Great Basin region. Our project aims to identify new ways to combine the play fairway data and empirically organize relationships between feature weights and labels in an improved workflow. As a means of doing this, we introduce machine learning methods to evaluate the influence of certain geological and geophysical features/feature sets in predicting geothermal favorability. This report highlights promising approaches based on supervised and unsupervised learning methods. First, we demonstrate a filter method applied to supervised classification modeling. The supervised filter method is based on permutation analysis to evaluate every possible feature combination/drop out scenario and rank feature influence based on the performance variance of supervised classification models. Additionally, we present an unsupervised factor analysis based on principal component analysis coupled with a semi-supervised kmeans clustering algorithm. This analysis allows us to identify the optimal number of groups/clusters for training sites and structural settings to identify feature patterns including correlation, variance, and latent and dominant feature relationships. The results from these methods offer a promising avenue for identifying favorable sources of predictive information to identify the locations of blind geothermal systems and furthering our understanding of complex geothermal feature and label relationships in the Great Basin region and beyond.
Tensile and compressive strain compatibility testing was performed on as-sprayed samples of the Shuttle Solid Rocket Booster external ablator material, MSA-1. Strain gages on the aluminum substrate were used to monitor strain. Strain compatibility was determined as the percent strain in the substrate at first visual evidence of MSA-1 failure. The 1/8-in. MSA-1, baselined for large areas of the SRB external skin, was characterized by a strain compatibility of 1.5 to 1.8 percent, which far exceeded the yield range of the metal substrate. Thicker MSA-1 applications (1.4 to 3/8 in.) were characterized by a lower level of strain compatibility, which appeared to be a manifestation of application limitations.
Subsurface applications, including geothermal, geological carbon sequestration, and oil and gas, typically involve maximizing either the extraction of energy or the storage of fluids. Fractures form the main pathways for flow in these systems, and locating these fractures is critical for predicting flow. However, fracture characterization is a highly uncertain process, and data from multiple sources, such as flow and geophysical are needed to reduce this uncertainty. We present a nonintrusive, sequential inversion framework for integrating data from geophysical and flow sources to constrain fracture networks in the subsurface. In this framework, we first estimate bounds on the statistics for the fracture orientations using microseismic data. These bounds are estimated through a combination of a focal mechanism (physics-based approach) and clustering analysis (statistical approach) of seismic data. Then, the fracture lengths are constrained using flow data. In conclusion, the efficacy of this inversion is demonstrated through a representative example.
This protocol demonstrates a method for electrochemical roughening of thin-film platinum electrodes without preferential dissolution at grain boundaries of the metal. Using this method, a crack free, thin-film macroelectrode surface with up to 40 times increase in active surface area was obtained. The roughening is easy to do in a standard electrochemical characterization laboratory and incudes the application of voltage pulses followed by extended application of a reductive voltage in a perchloric acid solution. The protocol includes the chemical and electrochemical preparation of both a macroscale (1.2 mm diameter) and microscale (20 µm diameter) platinum disc electrode surface, roughening the electrode surface and characterizing the effects of surface roughening on electrode active surface area. This electrochemical characterization includes cyclic voltammetry and impedance spectroscopy and is demonstrated for both the macroelectrodes and the microelectrodes. Finally, roughening increases electrode active surface area, decreases electrode impedance, increases platinum charge injection limits to those of titanium nitride electrodes of same geometry and improves substrates for adhesion of electrochemically deposited films.
Report characterizes graphite fluoride fibers made from commercially available graphitized carbon fibers and discusses some potential applications of graphite fluoride fibers in outer space. Applications include heat-sinking printed-circuit boards, solar concentrators, and absorption of radar waves. Other applications based on exploitation of increased resistance to degradation by atomic oxygen, present in low orbits around Earth.
To evaluate the response of composite materials, it is imperative that the input excitation as well as the observed output be well characterized. This characterization ideally should be in terms of displacements as a function of time with high spatial resolution. Additionally, the ability to prescribe these features for the excitation is highly desirable. Various methods for generating and detecting ultrasound in advanced composite materials are examined. Characterization and tailoring of input excitation is considered for contact and noncontact, mechanical, and electromechanical devices. Type of response as well as temporal and spatial resolution of detection methods are discussed as well. Results of investigations at Virginia Tech in application of these techniques to characterizing the response of advanced composites are presented.
Thermal heterogeneities within energy conversion and storage, material processing, nuclear processes, aerospace, and military applications are often inaccessible to characterization by insertion sensors. When sensor deployment is possible, conventional pointwise temperature probes quickly degrade when inserted into harsh environments typical of such processes. We developed spatially-resolved ultrasonic thermometry to noninvasively measure the spatial distributions of thermal properties in such applications, even when sizable thermal gradients are present. Our method divides the path of ultrasonic propagation into segments bound by echogenic features, which create echoes in pulse-echo mode, encoding the information about interior temperature distributions. We use the acquired ultrasonic responses to estimate the internal temperature distributions by solving an inverse problem or concatenating segmental estimates. This work describes the implementation and industrial testing of the developed method at a coal-fired electrical power generation plant. We inserted an echogenically segmented Inconel 625 waveguide into the combustion zone of the utility-scale boiler and continuously acquired ultrasonic data while keeping sensitive components away from the damaging combustion environment. The accuracy of the time-dependent temperature distributions reconstructed from the ultrasonic measurements was comparable to that of thermocouples. The resiliency of ultrasonic thermometry to harsh combustion conditions was far superior to conventional insertion sensors. The measurements obtained during plant operation captured daily steam generation cycles in response to changing customer demand and intermittent contributions of renewable power sources to the power grid. These measurements have revealed new insights into the relationship between the dynamic power generation load and the conditions inside the steam generator. As a result, the successful industrial testing of spatially-resolved ultrasonic thermometry in solids indicates that the developed technology has matured to become an attractive alternative to conventional sensing in solving challenging problems of long-term thermal characterizations in extreme environments.
Radioactive waste-management applications require good measurements to qualitatively and quantitatively characterize waste materials. Often these measurements must be done in situ, and the user wishes to learn something of the isotopic and spatial distribution of the source. Therefore, there is a need for a portable instrument that can map radioactive contamination and quantify sources. This presentation introduces several instruments that have been applied to this task, along with example measurements in relevant applications. All instruments are based on 3D-position-sensitive CdZnTe (CZT) detectors. This technology routinely achieves better than 1.1% FWHM energy resolution at 662 keV and operates at room temperature with a startup time under 2 minutes. All are packaged in portable enclosures with WiFi and Bluetooth capabilities for wireless communication. These capabilities allow the technology to be used in more advanced measurements in the field. A unique capability of these detectors is the ability to image the spatial distribution of gamma rays from a single stationary measurement. The first product, Polaris-H, has been in use at commercial nuclear power plants since 2013. The system, currently used at over 50% of the US nuclear-power fleet, integrates a 3D-position-sensitive CZT detector, associated readout electronics, an embedded computer, a battery with over 7-hour life, an optical camera, and a laser range finder in a portable water-proof enclosure. The system connects wirelessly to a tablet which displays a gamma-ray spectrum and isotope-specific images of the gamma-ray distribution in all directions in real time. The CZT detectors have a dynamic range from 50 keV up to 3 MeV. Coded aperture or pinhole imaging is used for energies below 250 keV, and Compton imaging is used for energies above 250 keV. List-mode data is saved to an external USB memory stick to enable more advanced analysis, including isotopic activity analysis, via H3D's post-processing software. Additional systems based on the same architecture have been developed to optimize the technology for other applications. These include Polaris-H Quad, which provides over 3 times the sensitivity for applications involving weaker sources, and Polaris-H Shield, which uses a collimator to provide images and isotope information over a narrower field of view in order to measure weaker sources in the presence of stronger sources of the same isotope. H3D has also developed custom systems that have been mounted on robots and drones that enable remote operation of the technology. Results from the measurements collected at commercial nuclear power plants and other applicable sites will be presented to show how these instruments can be used to detect, identify, and localize gamma-ray sources. Advanced analysis techniques to show the accurate quantification of the gamma-ray source will also be presented. Applications range from characterizing simple objects, to locating hottest points, estimating contamination distributions on an isotope-by-isotope basis, and differentiating scatter and direct emissions. (authors)
Surface contrast solution NMR methods (scNMR) are emerging as powerful tools to investigate the adsorption of small molecule ligands to the surface of nanoparticles (NP), returning fundamental insight into the kinetics and thermodynamics of sorption, as well as structural information on the adsorbed species. A prerequisite for the acquisition of high quality solution NMR data is the preparation of homogeneous and stable samples that return consistent NMR spectra and allow extensive signal averaging. Unfortunately, this condition does not apply to NMR samples containing NPs that often show a tendency to sediment and accumulate at the bottom of the NMR tube over the course of the experiment. We have recently shown that preparing NMR samples in an agarose gel matrix inhibits sedimentation and allows the characterization of small molecule-NP interactions by scNMR. Unfortunately, as the agarose gel only forms in aqueous solution, this sample preparation method cannot be used to stabilize NP suspensions in a non-aqueous environment. In this work, we introduce a library of 48 organogels, based on low molecular-mass organic gelators (LMOGs), to prepare NMR samples of small molecule/NP systems in a wide range of organic solvents. In addition, we present a simple method that takes advantage of 1H transverse relaxation (1H-R2) measurements to screen the library and identify the best gelator to characterize the small molecule-NP interaction of interest in the solvent of choice. We expect the results of this study will enable the preparation of homogeneous and stable samples of NPs in non-aqueous environments, therefore dramatically increasing the applicability of scNMR to the characterization of heterogeneous interactions and to the investigation of the role played by solvent molecules in regulating the kinetics and thermodynamics of sorption.