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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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Fuel cell research and technology - plate design, thermal analysis, performance characteristics, water recovery and purity, control techniques, breadboard items, and system test models
Thermal model correlation uses data from thermal balance tests to better estimate uncertain input parameter values. During the correlation process, input parameters are modified in an iterative manner which can become computationally expensive since this requires that the high-fidelity thermal model be run for each iteration. Depending on the number of thermal balance test points there can be many sets of correlation parameters that satisfy correlation criteria; and having enough data to ascertain the best set of correlation parameters to use, further increases the computational expense. Reduced-order models (ROMs) provide computationally efficient surrogates of high-fidelity models and are often built to reduce development cycle times and cost. By leveraging the speed of reduced-order models and the Correlation Analysis feature in the Veritrek software, the typical computational expense of a traditional thermal model correlation process can be significantly reduced and having access to hundreds of thousands of iteration results provides an advanced means of intelligently determining the best set of correlation parameters to use. The L’Ralph thermal team at NASA Goddard Space Flight Center explored the use of the Veritrek software for their thermal model correlation efforts. The ROM that was created allowed for the variation of 15 input parameters to match 70 temperature sensor readouts from 3 thermal balance plateus and required 125 runs of the high-fidelity Thermal Desktop® model to generate a ROM that could predict the detailed model’s results to within 0.2 K (RMS). The ROM was then used to find dozens of plausible correlation parameter values based on L’Ralph instrument test data within a few seconds. By providing several plausible correlation parameter combinations, Veritrek allowed the thermal team to explore different uncertain parameter value combinations and provided insight into how deterministic each input parameter was. This allowed for a more confident decision on the best set of correlation parameters to use, compared to traditional model correlation techniques. In this presentation, the L’Ralph thermal team will be presenting their experience with the Veritrek software and how the software was utilized to provide additional insights during the correlation process.
Thermal model correlation uses data from thermal balance tests to better estimate uncertain input parameter values. During the correlation process, input parameters are modified in an iterative manner which can become computationally expensive since this requires that the high-fidelity thermal model be run for each iteration. Depending on the number of thermal balance test points there can be many sets of correlation parameters that satisfy correlation criteria; and having enough data to ascertain the best set of correlation parameters to use, further increases the computational expense. Reduced-order models (ROMs) provide computationally efficient surrogates of high-fidelity models and are often built to reduce development cycle times and cost. By leveraging the speed of reduced-order models and the Correlation Analysis feature in the Veritrek software, the typical computational expense of a traditional thermal model correlation process can be significantly reduced and having access to hundreds of thousands of iteration results provides an advanced means of intelligently determining the best set of correlation parameters to use. The L’Ralph thermal team at NASA Goddard Space Flight Center explored the use of the Veritrek software for their thermal model correlation efforts. The ROM that was created allowed for the variation of 15 input parameters to match 70 temperature sensor readouts from 3 thermal balance plateus and required 125 runs of the high-fidelity Thermal Desktop® model to generate a ROM that could predict the detailed model’s results to within 0.2 K (RMS). The ROM was then used to find dozens of plausible correlation parameter values based on L’Ralph instrument test data within a few seconds. By providing several plausible correlation parameter combinations, Veritrek allowed the thermal team to explore different uncertain parameter value combinations and provided insight into how deterministic each input parameter was. This allowed for a more confident decision on the best set of correlation parameters to use, compared to traditional model correlation techniques. In this presentation, the L’Ralph thermal team will be presenting their experience with the Veritrek software and how the software was utilized to provide additional insights during the correlation process. "
A multi-objective test program was conducted at the NASA/JSC Radiant Heat Test Facility in which an aluminum skin/stringer test panel insulated with FRSI (Flexible Reusable Surface Insulation) was subjected to 24 simulated Space Shuttle Orbiter ascent/entry heating cycles with a cold soak in between in the 10th and 20th cycles. A two-dimensional thermal math model was developed and utilized to predict the thermal performance of the FRSI. Results are presented which indicate that the modeling techniques and property values have been proven adequate in predicting peak structure temperatures and entry thermal responses from both an ambient and cold soak condition of an FRSI covered aluminum structure.
Determining current carrying capacity (ampacity) of wire bundles in aerospace vehicles is critical not only to safety but also to efficient design. Published standards provide guidance on determining wire bundle ampacity but offer little flexibility for configurations where wire bundles of mixed gauges and currents are employed with varying external insulation jacket surface properties. Thermal modeling has been employed in an attempt to develop techniques to assist in ampacity determination for these complex configurations. Previous developments allowed analysis of wire bundle configurations but was constrained to configurations comprised of less than 50 elements. Additionally, for vacuum analyses, configurations with very low emittance external jackets suffered from numerical instability in the solution. A new thermal modeler is presented allowing for larger configurations and is not constrained for low bundle infrared emissivity calculations. Formulation of key internal radiation and interface conductance parameters is discussed including the effects of temperature and air pressure on wire to wire thermal conductance. Test cases comparing model-predicted ampacity and that calculated from standards documents are presented.
Abstract - Determining current carrying capacity (ampacity) of wire bundles in aerospace vehicles is critical not only to safety but also to efficient design. Published standards provide guidance on determining wire bundle ampacity but offer little flexibility for configurations where wire bundles of mixed gauges and currents are employed with various external insulation jacket surface properties. Thermal modeling has been employed in an attempt to develop techniques to assist in ampacity determination for these complex configurations. An earlier tool allowed analysis of wire bundle configurations but was constrained to configurations comprised of less than 50 elements. Additionally, for vacuum analyses, configurations with very low emittance external jackets suffered from numerical instability in the solution. A new thermal modeler is presented allowing for larger configurations and is not constrained by low bundle jacket surface infrared emittance calculations. Formulation of key internal radiation and interface conductance parameters is discussed including the effects of temperature and ambient air pressure on wire-to-wire thermal conductance. Test cases comparing model-predicted ampacity and that calculated from standards documents are presented.
There are two important but observationally uncertain parameters in the grid averaged surface energy budgets of mesoscale models - surface moisture availability and thermal heat capacity. A technique has been successfully developed for assimilating Geostationary Operational Environmental Satellite (GOES) skin temperature tendencies during the mid-morning time frame to improve specification of surface moisture. In a new application of the technique, the use of satellite skin temperature tendencies in early evening is explored to improve specification of the surface thermal heat capacity. Together, these two satellite assimilation constraints have been shown to significantly improve the characterization of the surface energy budget of a mesoscale model on fine spatial scales. The GOES assimilation without the adjusted heat capacity was run operationally during the International H2O Project on a 12-km grid. This paper presents the results obtained when using both the moisture availability and heat capacity retrievals in concert. Preliminary results indicate that retrieved moisture availability alone improved the verification statistics of 2-meter temperature and dew point forecasts. Results from the 1.5 month long study period using the bulk heat capacity will be presented at the meeting.
Phase change material based thermal energy storage has many current and potential applications in the heating and cooling of buildings, battery and electronics thermal management, thermal textiles, and dry cooling of power plants. However, connecting lab scale thermal data obtained with differential scanning calorimetry (DSC) to the performance of large-scale practical systems has been a major challenge primarily due to the dependence of supercooling on the size and temperature gradient of the system. Here we show how a phase change material’s supercooling behavior can be characterized experimentally using common lab scale thermal analysis techniques. We then develop a statistics based theoretical model that uses the lab-scale data on small samples to quantitatively predict the supercooling performance for a general thermal energy storage application of any size, including also allowing for the possibility of temperature gradients. Finally, we validate the modeling methodology by comparing to experimental results for solid-solid phase change in neopentyl glycol, which shows how the model successfully predicts the changes in supercooling temperature across a large range of cooling rates (2 orders of magnitude) and volumes (3 orders of magnitude). By accounting for thermal gradients, the model avoids ~2x error incurred by lumped approximations.
Thermal analysis of a vehicle designed to return samples from another planet, such as the Earth Entry vehicle for the Mars Sample Return mission, presents several unique challenges. The scientific purpose of a sample return mission is to return samples to Earth for detailed investigation. The Earth Entry Vehicle (EEV) must contain the samples after they have been collected and protect them from the high hearing rates of entry into the Earth's atmosphere. This requirement necessitates inclusion of detailed thermal analysis early in the design of the vehicle. This paper will describe the challenges and solutions for a preliminary thermal analysis of an Earth Entry Vehicle. The primary challenges included accurate updates of model .geometry, applying heat fluxes that change with position and time during exo-atmospheric cruise and entry, and incorporating orthotropic material properties. Many different scenarios were evaluated for the exo-atmospheric cruise to attain the desired thermal condition. The severity of the heat pulse during entry and the material response led to some unique modeling solutions. Overall, advanced modeling techniques and mathematical solutions were successfully used in predicting the thermal behavior of this complex system.
Thermal analysis of a vehicle designed to return samples from another planet, such as the Earth Entry vehicle for the Mars Sample Return mission, presents several unique challenges. The scientific purpose of a sample return mission is to return samples to Earth for detailed investigation. The Earth Entry Vehicle (EEV) must contain the samples after they have been collected and protect them from the high heating rates of entry into the Earth's atmosphere. This requirement necessitates inclusion of detailed thermal analysis early in the design of the vehicle. This paper will describe the challenges and solutions for a preliminary thermal analysis of an Earth Entry Vehicle. The primary challenges included accurate updates of model geometry, applying heat fluxes that change with position and time during exo-atmospheric cruise and entry, and incorporating orthotropic material properties. Many different scenarios were evaluated for the exoatmospheric cruise to attain the desired thermal condition. The severity of the heat pulse during entry and the material response led to some unique modeling solutions. Overall, advanced modeling techniques and mathematical solutions were successfully used in predicting the thermal behavior of this complex system.
Uranium-zirconium (U-Zr) alloys are candidate fuel systems for transmutation based reactors that can be used to burn long-lived minor actinides and fission products in fast spectrum reactors. Metallic fuels have also been gaining more recent attention for applications as accident tolerant fuels, as well as for use in small modular reactors. This research focused on a “science-based” approach to capture the connections between U and U-Zr alloys’ three-dimensional (3-D) microstructure, thermal properties, and mechanical properties through closely coordinated experiments and modeling efforts from the unirradiated to the irradiated fuels. Advanced characterization and modeling techniques were used to understand irradiation-induced microstructural evolution and its direct impact on the thermal and mechanical properties of U and U-Zr fuel. Closely coordinated experiments and modeling were performed to provide crucial data that does not currently exist. Overall, this research spanned multiple length and time scales within the models and experiments. The scope of the research encompassed the understanding of the irradiation effects in U and various U-Zr alloys with particular attention paid to three task areas: (1) microstructural evolution, (2) in-situ/ex-situ thermal and mechanical properties, and (3) multiscale modeling connections to microstructure, thermal, and mechanical properties. This research resulted in (1) the 3-D characterization of neutron irradiated U-Zr fuel in multiple phase regions to better understand fission gas swelling and constituent redistribution, (2) development of a microstructural model linking thermal and mechanical properties via in situ Raman and nanoindentation, (3) and mesoscale phase field modeling was coupled with the AEH method in the MOOSE framework was used to calculate the effective thermal conductivities of U-Zr fuels consisting of α-U and δ-UZr 2 heterogeneous microstructures.
Laser powder bed fusion (LPBF) Additive Manufacturing (AM) has the potential to enable the production of components with novel designs and material properties unachievable otherwise. However, process repeatability is a challenge, making qualification ill-defined and greatly reducing the utility of what could be an important manufacturing technology. In this work, a combination of modeling, uncertainty quantification (UQ), and experimentation are used in an effort to predict and bound the range of possible outcomes of the LPBF process. Quantities of interest predicted are melt pool dimensions, microstructure features, and mechanical distortions. A combination of high fidelity thermal-fluid models, microstructure growth models, and reduced fidelity, rapid thermal and mechanical models are used. Uncertainty propagation techniques are used to predict probability distributions of quantities of interest from estimates of process uncertainties. Repeated experiments are done to quantify observed probability distributions and compared to predicted distributions to determine if predictions are precise and accurate. Novel modeling methods are microstrucutre characterization techniques are also discussed. It is found that high fidelity models do a generally good job bounding experimentally observed melt pool morphologies for both bead-on-plate and powder bed cases. Microstructure models are able to bound a number of experimentally observed microstructure statistics, but with low precision due to challenges with calibrating the microstructure growth model parameters. A developed modified inherent strain distortion model does not accurately predict observed distortions. A lumped laser distortion model shows promise in being both accurately and precisely bounding observed outcomes from the deflection comb build, but requires further evaluation on more builds and geometries.
Research was done in the following areas: development and validation of solution algorithms, modeling techniques, integrated finite elements for flow-thermal-structural analysis and design, optimization of aircraft and spacecraft for the best performance, reduction of loads and increase in the dynamic structural stability of flexible airframes by the use of active control, methods for predicting steady and unsteady aerodynamic loads and aeroelastic characteristics of flight vehicles with emphasis on the transonic range, and methods for predicting and reducing helicoper vibrations.
The SIRTF (Space Infrared Telescope Facility) optical subsystem, including the primary mirror, has been modeled using lumped-parameter techniques and a thermal and cryogenic transient analysis program developed previously. Since silica mirrors have been shown to have significantly less distortion due to cryogenic cooldown, a silica primary mirror of approximately 1 m diameter is being considered. Thermal responses to variations in aperture heat load and heat sink temperature have been explored. Calculations have been made of system noise components from primary mirror spatial and temporal temperature variations. Background-limited infrared observations can be made at wavelengths out to 200 micrometers. Mirror thermal performance with and without copper wires for cooling is also considered.
During a post-test inspection of a Booster Separation Motor (BSM) from a Lot Acceptance Test (LAT), a crack was noticed in the graphite throat. Since this was an out-of-family occurrence, an investigation team was formed to determine the cause of the crack. This paper will describe thermal analysis techniques used in support of this investigation. Models were generated to predict gradients in nominal motor conditions, as well as potentially anomalous conditions. Analysis was also performed on throats that were tested in the Laser Hardened Material Evaluation Laboratory (LHMEL). Some of these throats were pre-cracked, while others represented configurations designed to amplify effects of thermal stresses. Results from these analyses will be presented in this paper.
During a post-test inspection of a Booster Separation Motor (BSM) from a Lot Acceptance Test (LAT), a crack was noticed in the graphite throat. Since this was an out-of-family occurrence, an investigation team was formed to determine the cause of the crack. This paper will describe thermal analysis techniques used in support of this investigation. Models were generated to predict gradients in nominal motor conditions, as well as potentially anomalous conditions. Analysis was also performed on throats that were tested in the Laser Hardened Material Evaluation Laboratory (LHMEL). Some of these throats were pre-cracked, while others represented configurations designed to amplify effects of thermal stresses. Results from these analyses will be presented in this paper.
In this presentation to the NASA Aeronautics Sensor Working Group the application of a strain sensor is outlined. The high-temperature extrinsic Fabry-Perot interferometer (EFPI) strain sensor was developed due to a need for robust strain sensors that operate accurately and reliably beyond 1800 F. Specifically, the new strain sensor would provide data for validating finite element models and thermal-structural analyses. Sensor attachment techniques were also developed to improve methods of handling and protecting the fragile sensors during the harsh installation process. It was determined that thermal sprayed attachments are preferable even though cements are simpler to apply as cements are more prone to bond failure and are often corrosive. Previous thermal/mechanical cantilever beam testing of EFPI yielded very little change to 1200 F, with excellent correlation with SG to 550 F. Current combined thermal/mechanical loading for sensitivity testing is accomplished by a furnace/cantilever beam loading system. Dilatometer testing has can also be used in sensor characterization to evaluate bond integrity, evaluate sensitivity and accuracy and to evaluate sensor-to-sensor scatter, repeatability, hysteresis and drift. Future fiber optic testing will examine single-mode silica EFPIs in a combined thermal/mechanical load fixture on C-C and C-SiC substrates, develop a multi-mode Sapphire strain-sensor, test and evaluate high-temperature fiber Bragg Gratings for use as strain and temperature sensors and attach and evaluate a high-temperature heat flux gauge.
The applications of adaptive optics extend across multiple sectors, encompassing areas such as LiDAR, biological and chemical sensing, and free-space optical communications. The advent of metasurfaces optics with reconfigurability has offered a versatile platform for the design of compact optical components, offering a compelling alternative to their conventional bulky counterparts. In this study, we introduce the PROWESS (Phase change Reconfigurable Optical WavEfront Synthesis System project at NASA LaRC), electrically reconfigurable metasurfaces using low-loss, high-contrast phase change material (PCM), Ge2Sb2Se4Te integrated with IR-transparent silicon microheater for various practical applications. The talk covers a reliable platform for switching large-scale PCM-based devices utilizing a microheater and an architecture for the metasurface switching within an integrated circuit configuration, which is compatible with standard foundry fabrication processes. The utilization of near- to midinfrared transparent silicon microheater in the proposed architecture opens possibilities for the development of reconfigurable transmissive optics such as filters, zoom lenses, and beam steering modules. We demonstrated switching of 140 µm × 140 µm PCM pixel, on a 200 µm × 200 µm silicon microheater for several thousand cycles. Further, we performed an in-depth investigation into the failure mechanism utilizing techniques such as transmission electron microscopy and thermal modeling. Guidelines for device performance improvement are proposed, and an improved design with larger endurance is shown in progress. With further progress, we aim to unlock the full potential of PCM-based devices and advance the field of adaptive optics with demonstrable examples including a reconfigurable beam steerer for ocean surface flash LiDAR and Navigation Doppler LiDAR for precise lunar landing missions.