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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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Quantum-based molecular dynamics is combined with a statistical analysis framework to test connections between observable chemical products resulting from polymer degradation.
Predictive battery life models are commonly utilized to extrapolate degradation trends observed during accelerated aging tests for simulation of degradation in real-world applications. Thus, fitting accelerated aging data as accurately as possible and with low uncertainty is crucial for making believable projections of battery lifetime, but it is challenging to identify algebraic expressions that accurately fit multivariate degradation trends. A review of models published in literature reveal some common expressions for fitting calendar aging data, which is only dependent on temperature and state-of-charge, but no consistency across many models for fitting cycle aging data, indicating the need for a statistically rigorous data driven approach for developing empirical models. This talk will describe a machine-learning assisted method for identification of predictive battery life models utilizing bilevel optimization and symbolic regression. Bilevel optimization with cross-validation is used to statistically determine cell- and stress-dependent model parameters, while symbolic regression identifies both linear and multiplicative candidate expressions to predict stress-dependent degradation rates by selecting low-order subsets of features from a generated feature library. Because model expressions are identified empirically, it is crucial to ensure resulting models behave according to physical expectations, so the stability of models for interpolation or extrapolation is interrogated qualitatively through simulation and quantitatively through cross-validation and uncertainty quantification via bootstrap resampling. This model identification approach substantially improves upon models identified purely using expert judgement in terms of both accuracy and uncertainty. Model simulation and validation is then conducted by deriving a state-equation form of the predictive model, enabling simulation of battery aging under dynamic stresses. This enables validation of the predictive battery model on lab-based tests with varying conditions or on drive-cycle or application-cycle testing protocols. Parameter uncertainty can be carried forward into model simulation, giving lifetime estimates and confidence windows for cell- or system-level lifetime. The financial impact of battery model uncertainty can be estimated by incorporating uncertainty into a technoeconomic model.
MDPCT1 is a four-layer cos-theta Nb3Sn dipole demonstrator developed and tested at FNAL in the framework of the U.S. Magnet Development Program. The magnet reached record fields for accelerator magnets of 14.1 T at 4.5 K in the first test and 14.5 T at 1.9 K in the second test and then showed large degradation. While its inner coils performed exceptionally well with only two quenches up to 14.5 T and no evidence of degradation, the outer coils degraded over the course of testing. By adopting new measurement and analysis techniques at FNAL we are discussing in detail what happened. Both success and failure in our diagnostics are discussed. The evolution of techniques over the course of two tests (and three thermal cycles) shows the path to address challenges brought by the first four-layer magnet tested at FNAL. This paper presents the analysis of quench data along with diagnostic features and complementary measurements taken in support of the magnet performance analysis.
Here, we report on observations of strong degradation of a polycarbonate vessel by a solvent being considered for a CO 2 capture process, diethyl sebacate. This degradation led to failure of a polymeric hollow fiber membrane unit. Additional tests showed rapid degradation of polycarbonate safety glasses and polystyrene-based petri dishes by exposure to diethyl sebacate at ambient conditions. We also report on safe operations with diethyl sebacate in extensive experiments studying the corrosion of steel in CO 2 -pressurized reactors lined with PTFE and using PTFE gaskets. Used diethyl sebacate was also stored for long time periods in bottles made from low-density polyethylene bottles without physical deterioration. These observations indicate that care must be taken in development of new contactors and processes for CO 2 capture with diethyl sebacate and related solvents and in the choice of material for storage.
This case study presents a characterization and optimization of an application code for extracting parton distribution functions from high energy electron-proton scattering data. Profiling this application code reveals that the phase-space density computation accounts for 93% of the overall execution time for a single iteration on a single core. When executing multiple iterations in parallel on a multicore system, the application spends 78% of its overall execution time idling due to load imbalance. We address these issues by first transforming the application code from Python to C++ and then tackling the application load imbalance via a hybrid scheduling strategy that combines dynamic and static scheduling. These techniques result in a 62% reduction in CPU idle time and a 2.46x speedup in overall execution time per node. In addition, the typically enabled power-management mechanisms in supercomputers (e.g., AMD Turbo Core, Intel Turbo Boost, and RAPL) can significantly impact intra-node scalability when more than 50% of the CPU cores are used. This finding underscores the importance of understanding system interactions with power management, as they can adversely impact application performance, and highlights the necessity of intra-node scaling tests to identify performance degradation that inter-node scaling tests might otherwise overlook.
This viewgraph presentation gives a detailed review of the Direct Methanol Based Fuel Cell (DMFC) stack and investigates the Ruthenium that was found at the exit of the stack. The topics include: 1) Motivation; 2) Pathways for Cell Degradation; 3) Cell Duration Testing; 4) Duration Testing, MEA Analysis; and 5) Stack Degradation Analysis.
A test was conducted from November 2008 to January 2009 to help determine the compatibility of an inhibited propylene glycol/water solution with planned Constellation vehicles. Dowfrost(TradeMark) HD was selected as the baseline for Orion, as well as other Constellation systems. Therefore, the same Dowfrost(TradeMark) HD/Water solution planned for Orion was chosen for this test. The fluid was subjected to a thermal fluid loop that had flightlike properties, as compared to Orion. The fluid loop had similar wetted materials, temperatures, flow rates, and aluminum wetted surface area to fluid volume ratio. The test was designed to last for 10 years, the life expectancy of the lunar habitat. However, the test lasted less than two months. System filters became clogged with precipitate, rendering the fluid system inoperable. Upon examination of the precipitate, it was determined that the precipitate composition contained aluminum, which could have only come from materials in the test stand, as aluminum is not part of the Dowfrost(TradeMark HD composition. Also, the fluid pH was determined to have increased from 10.1, at the first test sample, to 12.2, at the completion of the test. This high of a pH is corrosive to aluminum and was certainly a contributing factor to the development of precipitate. Chemical analyses and bench-top tests are currently ongoing to determine the underlying cause for this rapid degradation of the fluid. Hamilton Sundstrand, the contractor developing the Orion thermal fluid loop, is performing a parallel effort to not only understand the cause of fluid degradation in the test, but also to investigate solutions to avoid this problem in the Orion s thermal control system. JSC also consulted with the Hamilton Sundstrand team in the development of this test and the subsequent analysis.
In support of aviation fuel burn and emission reduction goals, NASA is pursuing high-payoff research investments that promise to transform aviation. This includes investments in Electrified Aircraft Propulsion (EAP). Multiple technology challenges must be addressed to unlock the full potential of EAP. This includes addressing challenges related to propulsion controls, which will be vital for ensuring efficient coordinated operation of EAP subsystems. This paper presents results from real-time hardware-in-theloop (HIL) testing of a control design for a single aisle partially-turboelectric aircraft propulsion concept conducted at the NASA Electric Aircraft Testbed (NEAT) facility. The control system under test is designed for a propulsion concept consisting of two wing-mounted turbofan engines that produce thrust and generate electrical power to drive a boundary layer ingesting tailfan propulsor via an electrical motor. An integrated control strategy is applied to ensure coordinated operation of the turbofan and tailfan subsystems during steady-state and transient operation throughout the flight envelope. The NEAT test of this integrated control design consists of a partially HIL, partially simulated configuration. A subscale representation of the electrical system design is implemented in hardware and mechanically coupled to electric machines that emulate turbomachinery and propulsor shaft dynamics. The hardware configuration is then operated under the control of a real-time computer application that runs a simulation of the propulsion system and the developed control logic. The NEAT facility test campaign includes a series of experiments that subject the control design to throttle transients conducted throughout the flight envelope and full-flight mission profiles. Testing under simulated performance degradation is also conducted to evaluate control design robustness. This includes constant and abrupt changes in degradation levels. Results from the HIL test are presented and shown to be in good agreement with pretest simulation predictions demonstrating the efficacy of the integrated control design approach.
While evaluating various options for liquid methane and liquid oxygen propellant management for lunar missions, Innovative Engineering Solutions (IES) conceived the flexible screen device as a potential simple alternative to conventional propellant management devices (PMD). An apparatus was designed and fabricated to test flexible screen devices in liquid nitrogen. After resolution of a number of issues (discussed in detail in the paper), a fine mesh screen (325 by 2300 wires per inch) spring return assembly was successfully tested. No significant degradation in the screen bubble point was observed either due to the screen stretching process or due to cyclic fatigue during testing. An estimated 30 to 50 deflection cycles, and approximately 3 to 5 thermal cycles, were performed on the final screen specimen, prior to and between formally recorded testing. These cycles included some "abusive" pressure cycling, where gas or liquid was driven through the screen at rates that produced differential pressures across the screen of several times the bubble point pressure. No obvious performance degradation or other changes were observed over the duration of testing. In summary, it is felt by the author that these simple tests validated the feasibility of the flexible screen PMD concept for use with cryogenic propellants.
Qualification tests of solar cell modules are described. These modules continue to show improvement over earlier type modules tested. Cell cracking and delamination are less prevalent, and interconnect problems and electrical degradation from environmental testing are now rare.
Analytical studies, ground-test data, and flight data before 1967 indicated that degradation of Apollo thermal-control coatings could be expected, possibly to an extent requiring spacecraft design changes to accomplish the worst-case lunar-landing mission. On the Apollo 9 mission, specimens of Apollo thermal-control coatings were retrieved by the astronauts during the extravehicular activity. These specimens were the first to be returned to earth from space unaffected by entry conditions. Subsequent measurements of the thermophysical properties (solar absorptance and hemispherical emittance) of the thermal-control-sample coatings revealed degradation levels well within the design capability of the Apollo spacecraft.
A standardized way of comparing the thermal performance of different pipelines in different sizes is needed. Vendor data for vacuum-insulated piping are typically given in heat leak rate per unit length (W/m) for a specific diameter pipeline. An overall k-value for actual field installations (k(sub oafi)) is therefore proposed as a more generalized measure for thermal performance comparison and design calculation. The k(sub oafi) provides a direct correspondence to the k-values reported for insulation materials and illustrates the large difference between ideal multilayer insulation (MLI) and actual MLI performance. In this experimental research study, a section of insulated piping was tested under cryogenic vacuum conditions, including simulated spacers and bending. Several different insulation systems were tested using a 1-meter-long cylindrical cryostat test apparatus. The simulated spacers tests showed significant degradation in the thermal performance of a given insulation system. An 18-meter-long pipeline test apparatus is now in operation at the Cryogenics Test Laboratory, NASA Kennedy Space Center, for conducting liquid nitrogen thermal performance tests.
Deep learning algorithms often are developed and trained on a training dataset and deployed on test datasets. Any systematic difference between the training and a test dataset may severely degrade the final algorithm performance on the test dataset—what is known as the domain shift problem . This issue is prevalent in many scientific domains where algorithms are trained on simulated data but applied to real-world datasets. Typically, the domain shift problem is solved through various domain adaptation (DA) methods. However, these methods are often tailored for a specific downstream task, such as classification or semantic segmentation, and may not easily generalize to different tasks. This work explores the feasibility of using an alternative way to solve the domain shift problem that is not specific to any downstream algorithm. The proposed approach relies on modern Unpaired Image-to-Image (UI2I) translation techniques, designed to find translations between different image domains in a fully unsupervised fashion. In this study, the approach is applied to a domain shift problem commonly encountered in Liquid Argon Time Projection Chamber (LArTPC) detector research when seeking a way to translate samples between two differently distributed LArTPC detector datasets deterministically. This translation allows for mapping real-world data into the simulated data domain where the downstream algorithms can be run with much less domain-shift-related performance degradation. Conversely, using the translation from the simulated data to a real-world domain can increase the realism of the simulated dataset and reduce the magnitude of any systematic uncertainties. To evaluate the quality of the translations, we use both pixel-wise metrics and a downstream task to measure the effectiveness of UI2I methods for mitigating the domain shift problem. We adapted several popular UI2I translation algorithms to work on scientific data and demonstrated the viability of these techniques for solving the domain shift problem with LArTPC detector data. To facilitate further development of DA techniques for scientific datasets, the ‘Simple Liquid-Argon Track Samples’ dataset used in this study is also published.
Samples of S-13G that had been exposed to the salt air environment of Cape Kennedy, Florida were irradiated with simulated solar ultraviolet radiation after various cleaning treatments. In both of the the tests conducted two of the salt air exposed samples were not cleaned, two were lightly cleaned with water and detergent (i.e. rinsed), and two were vigorously scrubbed. Several other white thermal control coatings were also irradiated. The solar absorptance values of these coatings before and as a result of the ultraviolet irradiation are reported for exposure levels up to approximately 2000 ESH.
NASA has been developing additive manufacturing (AM) for various technical and programmatic advantages for complex rocket engine and aerospace components. This maturation has focused on various AM processes, new alloys, characterizing material properties, developing standards, producing demonstrator parts, and integrating AM hardware in liquid rocket engines through test-fail-fix cycles, as well as application and dissemination of lessons learned of the AM lifecycle. The importance of proper AM processing was made evident in the failure of a Laser Powder Bed Fusion (L-PBF) copper-alloy combustion chamber during a hot-fire test due to a degraded material quality. The hot-fire test aimed to demonstrate high duty cycle under a risk-tolerant development project, where consequences of component failure would be minimal. However, the unintentional component failure emphasized the necessity of robust material characterization and rigorous process control procedures for the safe use of AM components in critical applications. This presentation provides an overview of the development failure, a discussion on the evaluation of the failed chamber and supplemental chambers produced at the same time, a representative material samples that included intentional build witness lines, and a summary of the key results and recommendations from the evaluations. NASA continues to approach AM processes and designs with a level of risk and acceptance of failures that is appropriate for the project objectives, with the overall goal of safe implementation of AM technology and transferring AM technology into commercial space applications. This presentation with provide critical awareness to the community lessons learned on proper implementation of AM.
NASA has been developing additive manufacturing (AM) for various technical and programmatic advantages for complex rocket engine and aerospace components. This maturation has focused on various AM processes, new alloys, characterizing material properties, developing standards, producing demonstrator parts, and integrating AM hardware in liquid rocket engines through test-fail-fix cycles, as well as application and dissemination of lessons learned of the AM lifecycle. The importance of proper AM processing was made evident in the failure of a Laser Powder Bed Fusion (L-PBF) copper-alloy combustion chamber during a hot-fire test due to a degraded material quality. The hot-fire test aimed to demonstrate high duty cycle under a risk-tolerant development project, where consequences of component failure would be minimal. However, the unintentional component failure emphasized the necessity of robust material characterization and rigorous process control procedures for the safe use of AM components in critical applications. This presentation provides an overview of the development failure, a discussion on the evaluation of the failed chamber and supplemental chambers produced at the same time, a representative material samples that included intentional build witness lines, and a summary of the key results and recommendations from the evaluations. NASA continues to approach AM processes and designs with a level of risk and acceptance of failures that is appropriate for the project objectives, with the overall goal of safe implementation of AM technology and transferring AM technology into commercial space applications. This presentation with provide critical awareness to the community lessons learned on proper implementation of AM.
Graphite/epoxy laminates were tested under bolt-bearing loads for a range of bolt clampup torques and for several test conditions involving water. High clampup torque improved both the static strength and fatigue limit by about 100 percent compared to a simple pin-bearing case, which had no through-the-thickness constraint. The static strength improvement was explained in terms of failure modes. Bolt clampup also influenced the hole elongation that developed before failure. For both the static and fatigue tests, the hole elongations were much larger for the low-torque clampup. Tests in water degraded static bearing strength only slightly, but reduced the fatigue limit about 40 percent below that for tests conducted in air.
Graphite/epoxy laminates (T300/5208) were tested under bolt-bearing loads for a range of bolt clampup torques and for several test conditions involving water. High clampup torque improved both the static strength and fatigue limit by about 100 percent compared to a simple pin-bearing case, which had no through-the-thickness constraint. The static strength improvement was explained in terms of failure modes. Bolt clampup also influenced the hole elongation that developed before failure. For both the static and fatigue tests, the hole elongations were much larger for the low-torque-clampup case than for the pin-bearing case or for tests with moderate clampup torques. Tests in water degraded static bearing strength only slightly, but reduced the fatigue limit about 40 percent below that for tests conducted in air.