Analytical modeling of battery cycle life
An analytical model related to the physical and chemical processes involved in battery wear and failure is discussed. The model is described using the data from the Crane tests.
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.
An analytical model related to the physical and chemical processes involved in battery wear and failure is discussed. The model is described using the data from the Crane tests.
Since its inception in the early 2010s, the NASA High Efficiency Centrifugal Compressor (HECC) has been enigmatic for the propulsion research community: experimental data and numerical simulations of the stage have generally not aligned in their quantifications of performance metrics. Typically, the fault for these disagreements is assigned to the numerical simulations as the simulations are models, and models are inherently incomplete representations of the experiment. This “incompleteness” may manifest in assumptions regarding roughness or heat transfer, simplifications of the flow path (i.e., neglecting bleed flows), or the oft-scapegoated turbulence model. In the case of HECC, recent work showed unexpected discrepancies between the intended impeller geometry defined in the design report (termed Design-Intent) and the manufactured impeller used in the experimental campaigns (termed As-Manufactured). That work used numerical simulations to establish that the geometric differences between the Design-Intent and As-Manufactured impellers were significant enough to result in drastically different performance predictions for the HECC vaneless diffuser configuration. The Design-Intent impeller simulations over predicted the performance relative to the experiment, whereas the As-Manufactured simulations better represented the experimental data, both in terms of one-dimensional performance metrics and spanwise flow profiles. This effort expands on that work by examining in detail the geometry and aerodynamic performance of the HECC vaned diffuser configuration. Further differences between the Design-Intent and As-Manufactured geometries have been discovered in the vaned diffuser and exit guide vanes, and these differences are documented herein. The summations of the geometric differences for all of the components were used to create two numerical models of HECC vaned diffuser configuration: the Design-Intent simulations which are generated from the original geometry definitions given in the design report and the As-Manufactured simulations which are the best available representation of the manufactured compressor hardware used in the experimental test campaigns. In congruence with the earlier vaneless diffuser work, the numerical predictions of the Design-Intent choked mass flow rate, total pressure ratio, and efficiency were notably greater than that of the As-Manufactured simulations. To increase confidence in the experimental dataset, measurements from a recent test campaign conducted in 2024 are used to validate the original experimental data acquired from 2012 to 2014 with good repeatability overall, especially considering the passage of time and differences in the data acquisition systems between the test campaigns. Both numerical simulations were then extensively evaluated against the experimental data. The As-Manufactured simulations provided better estimates of the stage performance than the Design-Intent cases in terms of most performance metrics. Nonetheless, more detailed results still show opportunities for improvement. Despite a more accurate representation of the physical hardware, characterization of the impeller work input remains a challenge even for rigorously developed numerical models.
Since its inception in the early 2010s, the NASA High Efficiency Centrifugal Compressor (HECC) has been enigmatic for the propulsion research community: experimental data and numerical simulations of the stage have generally not aligned in their quantifications of performance metrics. Typically, the fault for these disagreements is assigned to the numerical simulations as the simulations are models, and models are inherently incomplete representations of the experiment. This “incompleteness” may manifest in assumptions regarding roughness or heat transfer, simplifications of the flow path (i.e., neglecting bleed flows), or the oft-scapegoated turbulence model. In the case of HECC, recent work showed unexpected discrepancies between the intended impeller geometry defined in the design report (termed Design-Intent) and the manufactured impeller used in the experimental campaigns (termed As-Manufactured). That work used numerical simulations to establish that the geometric differences between the Design-Intent and As-Manufactured impellers were significant enough to result in drastically different performance predictions for the HECC vaneless diffuser configuration. The Design-Intent impeller simulations over predicted the performance relative to the experiment, whereas the As-Manufactured simulations better represented the experimental data, both in terms of one-dimensional performance metrics and spanwise flow profiles. This effort expands on that work by examining in detail the geometry and aerodynamic performance of the HECC vaned diffuser configuration. Further differences between the Design-Intent and As-Manufactured geometries have been discovered in the vaned diffuser and exit guide vanes, and these differences are documented herein. The summations of the geometric differences for all of the components were used to create two numerical models of HECC vaned diffuser configuration: the Design-Intent simulations which are generated from the original geometry definitions given in the design report and the As-Manufactured simulations which are the best available representation of the manufactured compressor hardware used in the experimental test campaigns. In congruence with the earlier vaneless diffuser work, the numerical predictions of the Design-Intent choked mass flow rate, total pressure ratio, and efficiency were notably greater than that of the As-Manufactured simulations. To increase confidence in the experimental dataset, measurements from a recent test campaign conducted in 2024 are used to validate the original experimental data acquired from 2012 to 2014 with good repeatability overall, especially considering the passage of time and differences in the data acquisition systems between the test campaigns. Both numerical simulations were then extensively evaluated against the experimental data. The As-Manufactured simulations provided better estimates of the stage performance than the Design-Intent cases in terms of most performance metrics. Nonetheless, more detailed results still show opportunities for improvement. Despite a more accurate representation of the physical hardware, characterization of the impeller work input remains a challenge even for rigorously developed numerical models.
Several aspects of lithium primary cell technology are discussed with respect to aerospace application. Particular attention is given to the statistical analysis of battery data and accelerated testing.
Here, we present a machine learning (ML) method for efficient computation of vibrational thermal expectation values of physical properties from first principles. Our approach is based on the nonperturbative frozen phonon formulation in which stochastic Monte Carlo algorithm is employed to sample configurations of nuclei in a supercell at finite temperatures based on a first-principles phonon model. A deep-learning neural network is trained to accurately predict physical properties associated with sampled phonon configurations, thus bypassing the time-consuming ab initio calculations. To incorporate the point-group symmetry of the electronic system into the ML model, group-theoretical methods are used to develop a symmetry-invariant descriptor for phonon configurations in the supercell. We apply our ML approach to compute the temperature dependent electronic energy gap of silicon based on density functional theory (DFT). We show that, with less than a hundred DFT calculations for training the neural network model, an order of magnitude larger number of sampling can be achieved for the computation of the vibrational thermal expectation values. Our work highlights the promising potential of ML techniques for finite temperature first-principles electronic structure methods.
An approach that combines experimental and numerical analyses has been implemented to characterize the fundamentals of flashback events and flame-holding phenomena during high-hydrogen combustion in a jet-in-crossflow (JICF) configuration. Such flame dynamics are visualized experimentally using nanosecond (ns)-based hydroxyl planar laser-induced fluorescence (OH-PLIF) and chemiluminescence diagnostics techniques. The JICF burner has an optically accessible premixing tube allowing the optical diagnostics. The testing was conducted for varied premixer velocities (V) and equivalence ratio (ϕ) for 90–100% (H 2 , by mole) H 2 /CH 4 reactant mixtures at atmospheric temperature and pressure conditions. Two distinct flashback events were identified – conventional rich flashback and lean flashback, recorded while increasing ϕ and decreasing ϕ, respectively. The cause of lean flashback was attributed to lower momentum flux ratio which bends the jet sharply, closer toward the injection plane. The mean OH-PLIF images characterized the flame-holding behavior, where the flame was found to be stabilized on the leeward side only or on both windward and leeward sides as a lifted flame near the fuel port. A large eddy simulation (LES) with detailed chemistry combustion modeling approach was implemented along with an OH* submechanism, and it showed qualitative agreement with the integrated line-of-sight chemiluminescence results as well as the planar OH-PLIF measurements.
Eddy covariance (EC), the gold standard for measuring ecosystem scale gas and heat exchanges, has transformed our understanding of the breathing of the biosphere, and thus global change biology. Despite numerous methodological improvements and insights gained from the technique, the community faces persistent challenges that have been present since the first EC measurements. Here, we review the theoretical developments underpinning EC. We present theoretical developments in four important areas that have relevance to EC measurements of the net ecosystem exchanges (NEE) of gases and heat from a single tower: (i) measuring the total vertical flux density, (ii) flux attenuation, (iii) coordinate rotations, and (iv) energy balance closure. Persistent problems with EC measurements, such as the inability to close the energy budget, led us to identify two priorities for revisiting the theory underlying: (i) sensible heat flux calculations, and (ii) constraining the mean vertical wind velocity. We present a framework for improved calculation of sensible heat flux derived from first principles of fluid mechanics and thermodynamics that considers coupled heat and mass transfer so that conservation of both is obeyed. These refinements are motivated by the need for unbiased measurements of energy and mass transfer between the land surface and atmosphere for ecosystem research and to validate satellite observations and land surface models.
Performance results of a digital test signal-generator hardware-demonstration unit are reported. Capabilities available include baseband and intermediate frequency (IF) spectrum generation, for which test results are provided. Repeatability in the setting of a given signal-to-noise ratio (SNR) when a baseband or an IF spectrum is being generated ranges from 0.01 dB at high SNR's or high data rates to 0.3 dB at low data rates or low SNR's. Baseband symbol SNR and carrier SNR (P c /N o ) accuracies of 0.1 dB were verified with the built-in statistics circuitry. At low SNR's that accuracy remains to be fully verified. These results were confirmed with measurements from a demodulator synchronizer assembly for the baseband spectrum generation, and with a digital receiver (Pioneer 10 receiver) for the IF spectrum generation.
This work introduces a completely rewritten version of the programRMCProfile(version 7), big-box, reverse Monte Carlo modelling software for analysis of total scattering data. The major new feature ofRMCProfile7is the ability to refine multiple phases simultaneously, which is relevant for many current research areas such as energy materials, catalysis and engineering. Other new features include improved support for molecular potentials and rigid-body refinements, as well as multiple different data sets. An empirical resolution correction and calculation of the pair distribution function as a back-Fourier transform are now also available.RMCProfile7is freely available for download at https://rmcprofile.ornl.gov/.
Artemesia tridentatais a foundational plant taxon in western North America and an important medicinal plant threatened by climate change. Low-cost fabrication of sensors is critical for developing large-area sensor networks for understanding and monitoring a range of environmental conditions. However, the availability of materials and manufacturing processes is still in the early stages, limiting the capacity to develop cost-effective sensors at a large scale. In this study, we demonstrate the fabrication of low-cost flexible sensors using laser-induced graphene (LIG); a graphitic material synthesized using a 450-nm wavelength bench top laser patterned onto polyimide substrates. We demonstrate the effect of the intensity and focus of the incident beam on the morphology and electrical properties of the synthesized material. Raman analyses of the synthesized LIG show a defect-rich graphene with a crystallite size in the tens of nanometers. This shows that the high level of disorder within the LIG structure, along with the porous nature of the material provide a good surface for gas adsorption. The initial characterization of the material has shown an analyte response represented by a change in resistance of up to 5% in the presence of volatile organic compounds (VOCs) that are emitted and detected byArtemisiaspecies. Bend testing up to 100 cycles provides evidence that these sensors will remain resilient when deployed across the landscapes to assess VOC signaling in plant communities. The versatile low-cost laser writing technique highlights the promise of low-cost and scalable fabrication of LIG sensors for gas sensor monitoring.
Identifying thermodynamic signatures of electronic phases, such as superconductivity, is challenging in low-dimensional materials due to strong fluctuations and low probing volume. Spectroscopic methods are often used to identify new bulk phases, but their main measurable quantity—electronic energy gaps—is no longer an effective order parameter in low-dimensional and fluctuating systems. Combining angle-resolved photoemission with a domain-adversarial neural network, we report a data-driven method to identify thermodynamic phase transitions solely based on single-particle spectra. We demonstrate 97.6% accuracy in cuprate superconductor Bi 2 Sr 2 CaCu 2 O 8+δ with strong superconducting fluctuations. This model notably compensates for the scarcity of experimental data by leveraging virtually inexhaustible simulated data. Further, its explainability reveals the crucial role of in-gap spectral weight in detecting phase fluctuations and thermodynamic transitions. Our work pinpoints the spectroscopic signatures of fluctuating orders and enables using spectroscopy for machine-learning-assisted material discovery for low-dimensional and strong coupling systems.
The laser altimeter, consisting of a Q switched ruby laser, transmitting optics, counting timer, receiving optics, and a photomultiplier is described. Harmonic analysis of the mission data is also presented.
This paper will delineate the criteria required for the selection of batteries as a power source for space experiments. Four basic types of batteries will be explored, lead acid, silver zinc, alkaline manganese and nickel cadmium. A detailed description of the lead acid and silver zinc cells while a brief exploration of the alkaline manganese and nickel cadmium will be given. The factors involved in battery selection such as packaging, energy density, discharge voltage regulation, and cost will be thoroughly examined. The pros and cons of each battery type will be explored. Actual laboratory test data acquired for the lead acid and silver zinc cell will be discussed. This data will include discharging under various temperature conditions, after three months of storage and with different types of loads. A description of the required maintenance for each type of battery will be investigated. The lifetime and number of charge/discharge cycles will be discussed.
Landsat 10 will be the upcoming mission in the 50+ year Landsat series of Earth observation platforms. The centerpiece of the observatory will be a super-spectral imager known as the Landsat Instrument Suite (LandIS). The sensor will feature 26 spectral channels from the visible through near-, short-wave, and thermal infrared wavelengths with spatial resolutions of 10, 20, and 60 meters on the ground, depending on the band. These enhancements over the legacy Landsat instruments will ensure data continuity with the existing archive and will expand upon the core Landsat capabilities to enable new applications in Earth science. After a competitive procurement, NASA selected the design submitted by the Raytheon Company for the LandIS instrument. The innovative Raytheon instrument concept utilizes an advanced whiskbroom architecture to fulfill the strict radiometric, spatial, and geometric image quality requirements demanded by the Landsat 10 mission and fits within restrictive mass, volume, and power constraints. The instrument will continue the Landsat directive to image all daylit land and near-shore water areas, along with select nighttime imaging. On-board calibration source data will ensure high radiometric and geometric accuracy and stability consistent with previous missions to enable continuity in data products available to users. This paper discusses the driving requirements for LandIS and provides a description of the chosen design and operations concept of the instrument.
Progress and the future plans for the following objectives are discussed: (1) Assess the accuracy at which the SIR-C/X-SAR standard data products can be calibrated through the use of ground calibrators to estimate the end-to-end system polarization calibration constants (or distortion parameters) and incorporate the constants into the data processing; (2) Study the cross-calibration between three multipolarization systems: SIR-C, the National Aeronautics and Space Administration/Jet Propulsion Laboratory (NASA/JPL) DC-8 SAR, and the University of Michigan ground-based polarimetric scatterometer; (3) Evaluate the calibration "stability" of SIR-C/X-SAR (measured by variations in the calibration constants) over the range swath width and over a specified distance in azimuth. Variations over a 12-hour period (between ascending and descending passes) will also be studied; and (4) Develop a cost-effective calibration plan including development of inexpensive polarimetric active calibrators.
The orbit data for the Intelsat 4 spacecraft is described. The performance and characteristics of the battery used for this spacecraft are discussed. Graphs are presented which relate battery voltage to various eclipse seasons.
In this study, we apply the electromagnetic (EM) melt processing of thermoplastics on an innovative EM field-driven powder bed fusion additive manufacturing (AM) concept for high-performance functional parts: Selective Microwave Melting/Sintering (SMM/SMS). This technique leverages the EM susceptibility of carbon nanotube-coated polymer micro-pellets to achieve rapid, localized heating and powder fusion. Thus, selective microwave melting (SMM) was used to fabricate multilayer specimens made of recycled polyphenylene sulfide (rPPS) and carbon nanotubes (CNTs). The resulting SMM specimens exhibited very good interlayer integrity, localized fusion at pellet boundaries, and tolerable residual porosity, indicating effective fusion and acceptable consolidation. CNT-rich interphases were retained after irradiation, generating anisotropic electrically active network pathways and enabling conductivity enhancement at low filler content. At only 1.0 wt% CNT, the specimens exhibited electrical conductivity approximately three orders of magnitude higher than neat rPPS. Dynamic mechanical analysis showed improved viscoelastic response relative to neat rPPS, while tensile testing confirmed that the SMM-processed specimens retained practical mechanical integrity despite localized voids. These results demonstrate that SMM can effectively consolidate EM susceptible thermoplastic powder beds while preserving their segregated conductive networks. This may become a scalable route for producing multifunctional thermoplastic parts with low filler loadings, tunable anisotropy, and structured materials and parts. Overall, the findings suggest that EM field-based AM can help overcome key limitations of conventional thermoplastic processing by enabling scalable, energy-efficient fabrication of nanostructured composites and expanding AM to a broader range of resins, including high-performance thermoplastics with customized functional properties.
Understanding and exploiting material flexibility through phenomena such as the bending and twisting of molecular crystals has been a subject of increased interest owing to the number of applications that benefit from these properties, such as optoelectronics, mechanophotonics, soft robotics, and smart sensors. Here, we report the growth of spontaneously bent and twisted ammonium urate crystals induced by the keto–enol tautomerism of the urate molecule. The major tautomer is native to biogenic crystals, whereas the minor tautomer functions as an effective crystal growth modifier to induce naturally bent and twisted ammonium urate crystals. We show that the degree of curvature can be tailored based on the judicious selection of growth conditions. A combination of state-of-the-art microscopy and spectroscopy techniques are used to characterize the origin of bending. Spatially resolved nano-electron diffraction and high-resolution electron microscopy of naturally bent crystals show nearly single crystallinity with local lattice deformations generated by a combination of screw and edge dislocations. These observations are consistent with photoinduced force microscopy and contact resonance atomic force microscopy, which confirmed spatially resolved changes in the intermolecular interactions and the mechanical properties throughout the cross-sectional and axial regions of bent crystals. A mechanism of bending involving the generation of regionally specific dislocations is proposed as an alternative to more commonly reported models. These findings highlight a unique characteristic of tautomeric crystals that may have broader implications for other biogenic materials.