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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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At least 487 records · Page 27

Progressive Failure Analysis Correlation with Notched Composite Laminate Test Data

Testing of small and intermediate laminate panels with notches was performed and Progressive Failure Analyses (PFA) models were developed for aid in test planning and for correlation with the test data. Two progressive damage failure models were included in the study: the commercially available Abaqus built-in damage model and COmplete STress Reduction (COSTR) damage model developed at NASA Langley Research Center (LaRC). The finite elements models used for the analysis were developed using shell elements. The pre-test PFA results obtained from the two damage models were compared to test data. Then a post-test PFA with updated material properties based on additional available material property data was executed with the COSTR damage model and compared to the test data. The panels tested in compression all exhibited less scatter in the failure load with self-similar failure behavior. The panels tested in tension exhibited more scatter in the failure load with a failure mode that included delamination of plies. However, a self-similar crack path was also observed as the overall failure mode for all panels tested. When comparing test data to the pre-test analysis results, both damage models with shell element models were considered adequate for predicting the behavior and failure load of both the small and intermediate panels when tested in compression. However, for the tension load cases, larger differences were observed between the test and analysis results. When comparing test data to the post-test analysis performed using the COSTR damage model, better correlation was observed. However, large discrepancies were still observed for the tension load cases. Consequently, a higher fidelity finite element model including solid elements for sub-laminates and the modeling of cohesive layers between sub-laminate layers is recommended for tension loading of notched composite laminates.

Damage Model,Progressive Failure Analysis,Open Hol↗

Projecting Large Fires in the Western US With an Interpretable and Accurate Hybrid Machine Learning Method

More frequent and widespread large fires are occurring in the western United States (US), yet reliable methods for predicting these fires, particularly with extended lead times and a high spatial resolution, remain challenging. In this study, we proposed an interpretable and accurate hybrid machine learning (ML) model, that explicitly represented the controls of fuel flammability, fuel availability, and human suppression effects on fires. The model demonstrated notable accuracy with a F 1 -score of 0.846 ± 0.012, surpassing process-driven fire danger indices and four commonly used ML models by up to 40% and 9%, respectively. More importantly, the ML model showed remarkably higher interpretability relative to other ML models. Specifically, by demystifying the “black box” of each ML model using the explainable AI techniques, we identified substantial structural differences across ML fire models, even among those with similar accuracy. The relationships between fires and their drivers, identified by our model, were aligned closer with established fire physical principles. The ML structural discrepancy led to diverse fire predictions and our model predictions exhibited greater consistency with actual fire occurrence. With the highly interpretable and accurate model, we revealed the strong compound effects from multiple climate variables related to evaporative demand, energy release component, temperature, and wind speed, on the dynamics of large fires and megafires in the western US. Our findings highlight the importance of assessing the structural integrity of models in addition to their accuracy. They also underscore the critical need to address the rise in compound climate extremes linked to large wildfires.

54 ENVIRONMENTAL SCIENCES↗

Investigating laser ablated plume dynamics of carbon and aluminum targets

Recently acquired high-resolution images of nanosecond laser ablation plumes suggest a strong correlation between the internal plume structure and the type of material being ablated. However, the details of this relation are currently not well understood. In this work, we attempt to explore this correlation using a 2D radiation hydrodynamics model to study the dependence of internal plume structure formation on the ablation material. Here spatio-temporal emission maps and plume expansion velocities from experimental measurements are compared with the model predictions, including synthetic emission maps. The shape and expansion rate of an outer air plume region are found to be in good agreement for both carbon and aluminum, as are the inner material plume dynamics for carbon ablation. The largest disagreement is observed in the case of a polished aluminum target, where the chaotic inner plume features seen in the experimental images are not observed in the model. The possible physical mechanisms responsible for this discrepancy are discussed. This effort constitutes a continued development toward a predictive model of ablation plume dynamics and chemistry for various materials in extreme environments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Hydroacoustic forcing function modeling using DNS database

A wall pressure frequency spectrum model (Blake 1971 ) has been evaluated using databases from Direct Numerical Simulations (DNS) of a turbulent boundary layer (Na & Moin 1996). Good agreement is found for moderate to strong adverse pressure gradient flows in the absence of separation. In the separated flow region, the model underpredicts the directly calculated spectra by an order of magnitude. The discrepancy is attributed to the violation of the model assumptions in that part of the flow domain. DNS computed coherence length scales and the normalized wall pressure cross-spectra are compared with experimental data. The DNS results are consistent with experimental observations.

Zawadzki, I.↗

Stratospheric Chlorine partitioning: Constraints from Shuttle-borne Measurements of [HCl], [ClNO3] and [ClO]

Measured stratospheric mixing ratios of HCl, ClNO3, and ClO from ATMOS and MAS are poorly reproduced by models using recommended kinetic parameters. This discrepancy is not resolved by new rates for the reactions Cl+CH4 and OH+HCl derived from weighted fits to laboratory measurements. A deficit in modeled [HCl] and corresponding overprediction of [ClNO3] and [ClO], which increases with altitude, suggests that production of HCl between 20 and 50 km is much faster than predicted from recommended rates.

Michelsen, H. A.↗

Path discrepancies between great circle and rhumb line

A mathematical model for a comparative analysis of great circle vs. rhumb line navigation in the continental United States has been developed at the Avionics Engineering Center, Ohio University. A FORTRAN simulation of the model has been implemented on the IBM 370 computer. The simulation predicts pertinent navigation information for the two flight paths. The basis for the project, which is a part of an M.S. thesis, is to provide a data base for computing discrepancies between the two flight paths. This document briefly describes the model and discusses the implications of the results obtained.

Kaul, R.↗

Effect of the Jovian oblateness on Pioneer 10/11 radio occultations

The oblateness of Jupiter, which was neglected in the standard inversion technique for radio occultation data, has a substantial effect on the refractivity profiles of the neutral Jovian atmosphere derived from the Pioneer 10/11 occultations. The geometry of the Pioneer 10 entry and exit occultations has the effect that oblateness should account for much of the discrepancy of the results with plausible atmospheric models. The effect of the oblateness on Pioneer 11 entry is smaller, where much of the discrepancy could be due to other effects, such as cycle-slip in the spacecraft transponder. Theory indicates that the Pioneer 11 exit occultation should be affected by the oblateness in the opposite sense from the first three occultations; and, indeed, the data which had not been invertible under the spherical assumption produced reasonable results when an oblateness correction was applied.

Hubbard, W. B.↗

Model correction and updating of a stochastic degradation model for failure prognostics of miter gates

Understanding the degradation of the quoin block is vital for failure prognostics in miter gates. Due to the complicated degradation mechanism, degradation models based on simplifications and assumptions cannot accurately describe the damage evolution. It is observed that small errors in a simplified degradation model can lead to a large discrepancy in the remaining useful life estimation attributed to error accumulation over time. Aiming to address this issue in failure prognostics, this paper presents a dynamic model correction framework for a simplified degradation model using strain measurements. In the proposed framework, a polynomial chaos expansion (PCE) model is employed to compensate the missing physics in a simplified stochastic degradation model. Here, a maximum likelihood estimation method is developed to estimate the uncertain parameters of the simplified physics-based degradation model along with the unknown PCE model parameters using strain measurements as the observables. The updated damage degradation model is then applied to failure prognostics of a miter gate. Results of a case study show that the proposed approach can effectively improve the accuracy of failure prognostics in miter gates.

42 ENGINEERING↗

Solar models with enhanced energy transport in the core

The discrepancy between the observed and computed flux of solar neutrinos can be eliminated if the temperature gradient in the core of the model, and hence its central temperature, is reduced. This could in principle be accomplished by reducing the core opacity; alternatively, it has been proposed that a fraction of the energy transport in the solar core results from the motion of hypothetical particles (the so-called WIMPs). The resulting changes in solar structure have measurable effects on the frequencies of the solar 5-minute oscillations. Here, models are considered where the opacity in the solar core has been decreased in a manner which roughly simulates the effects of the WIMPs. The analysis of the models and their frequencies provides insight into the consequences of modifications to the physics of solar models. In particular, it is found that models with the observed neutrino flux are inconsistent with observations of low-degree solar oscillations.

Christensen-Dalsgaard, J.↗

Strong Sensitivity of Simulated Biomass Burning Aerosol Transport and Radiative Effects Over the South Atlantic to Carbonaceous Aerosol Aging and Particle Density

Biomass burning aerosol (BBA) impacts climate through aerosol‐cloud‐radiation interactions, but models disagree on the sign and magnitude of BBA radiative effects. We quantify the sensitivity of BBA radiative effects and transport to three BBA‐relevant processes and properties: parameterized oxidative aging of organic aerosol (OA), a combined change to black carbon (BC) density and the method for calculating aerosol refractive index, and reduction in OA density. We evaluate Unified Model simulations against two aircraft campaigns from summer 2017 over the Southeast Atlantic. The model generally performs well, such that discrepancies between the observational data sets may sometimes limit the precision of the evaluation. Our newly developed aging parameterization reproduces observed OA:BC mass ratios well and allows modeled OA:BC to decrease with smoke age, but increases bias in aerosol extinction and changes the BBA radiative effect little (+0.12 W m -2 ). We calculate aerosol refractive index using either a volume‐weighted component average or the Maxwell‐Garnett (MG) mixing assumption, which represents BC as small inclusions in a host material. Compared to MG mixing, the volume‐weighted average refractive index and reduced BC density increase aerosol absorption, substantially increasing the total BBA radiative effect (+2.66 W m -2 ) and amount of BBA transported across the ocean through BC self‐lofting. Reducing OA density to better match literature values changes the total BBA radiative effect by −1.96 W m -2 . Changes to direct radiative effects exceed changes to cloud radiative effects. Our findings emphasize the sensitivity of aerosol radiative effects and transport to these processes and properties, which we suggest could be improved in climate models.

Southeast Atlantic↗

Hybrid data-driven and model-informed online tool wear detection in milling machines

Precision machining tool wear is responsible for low product throughput and quality. Monitoring the tool wear online is vital to prevent degradation in machining quality. However, direct real-time tool wear measurement is not practical. This paper presents residual-based anomaly detection models, combining a hybrid model comprised of a physics-based model and a data-driven model (a decision tree or a neural network) to predict signals of interest (e.g., power or forces) under nominal conditions, followed by Page’s cumulative sum test for detecting tool wear on-line using the computer numerical control machine measurements. The most informative features are ranked using dynamic programming and its approximation variants from real-time measurements and machine settings, such as the width of cut, depth of cut, feed rate and spindle speed, that serve as inputs to the predictive models. The baseline nominal model is incrementally updated with experimental data via a gradient boosted adaptation model to generate the residuals that account for discrepancies between the actual machine data under normal conditions and the baseline nominal model predictions. The hybrid model is validated against 20 Mazak milling machine experimental tests and one Haas run-to-failure experiment. The proposed anomaly detector is applied to synthetic data from simulations of the physics-based model at different operating conditions, measurement noise levels, and tool wear levels, and the methods were able to achieve an overall 92% accuracy in data with 1% noise. The anomaly detection methods based on hybrid model reduced the false alarms of either the data-driven or physical-based models alone, and are found to be capable of good online detection of tool wear.

42 ENGINEERING↗

Hybrid data-driven and model-informed online tool wear detection in milling machines

Precision machining tool wear is responsible for low product throughput and quality. Monitoring the tool wear online is vital to prevent degradation in machining quality. However, direct real-time tool wear measurement is not practical. This paper presents residual-based anomaly detection models, combining a hybrid model comprised of a physics-based model and a data-driven model (a decision tree or a neural network) to predict signals of interest (e.g., power or forces) under nominal conditions, followed by Page’s cumulative sum test for detecting tool wear on-line using the computer numerical control machine measurements. The most informative features are ranked using dynamic programming and its approximation variants from real-time measurements and machine settings, such as the width of cut, depth of cut, feed rate and spindle speed, that serve as inputs to the predictive models. The baseline nominal model is incrementally updated with experimental data via a gradient boosted adaptation model to generate the residuals that account for discrepancies between the actual machine data under normal conditions and the baseline nominal model predictions. The hybrid model is validated against 20 Mazak milling machine experimental tests and one Haas run-to-failure experiment. The proposed anomaly detector is applied to synthetic data from simulations of the physics-based model at different operating conditions, measurement noise levels, and tool wear levels, and the methods were able to achieve an overall 92% accuracy in data with 1% noise. The anomaly detection methods based on hybrid model reduced the false alarms of either the data-driven or physical-based models alone, and are found to be capable of good online detection of tool wear.

Online anomaly detection↗

Storm-Time Variability of Terrestrial Hydrogen Exosphere: Kinetic Simulation Results

Recent studies of TWINS Lyman-α observations have reported an increase in geocoronal column brightness during geomagnetic storms, indicating enhanced exospheric hydrogen atom density (NH). This suggests a complex role of exospheric neutrals in determining storm-time magnetosphere dynamics and their energy release through charge-exchange processes. We developed a Model for Analyzing Terrestrial Exosphere (MATE) to investigate storm-time exospheric behaviors and their physical drivers. MATE traces test hydrogen atoms backward in time from locations in the exosphere to a nominal exobase altitude of 500 km, employing Newtonian mechanics with gravitational force. The model then calculates the phase-space densities (PSDs) of test hydrogen atoms at the exobase using the Maxwellian distribution with physics-based exobase conditions from the TIMEGCM upper atmosphere model. MATE maps PSDs at the exobase to the exosphere using Liouville’s Theorem under collisionless assumptions and derives NH by integrating the PSDs across velocity space. We conducted MATE simulation before, during, and after a minor geomagnetic storm from 12 to 18 June 2008, and compared the model results with NH estimates from the TWINS geocorona data. MATE reproduces storm-time density enhancements soon after the minimum Dst is reached, matching well with a general trend of TWINS NH estimates. The results suggest that upper atmospheric heating during a geomagnetic storm increases the number of ballistic and escaping hydrogen atoms entering the exosphere from the exobase, thereby boosting NH. However, the magnitude of modeled NH mismatches the TWINS NH estimates. The potential mechanisms of this density discrepancy include the physics excluded in the MATE model — such as neutralneutral collisions, neutral-plasma charge exchange, solar radiation pressure, and photoionization — as well as the higher exobase hydrogen density of TIMEGCM compared to typical empirical values, which will be addressed in future.

Hyunju K Connor↗

A multifrequency study of sub-parsec jets with the Event Horizon Telescope

Context. The 2017 observing campaign of the Event Horizon Telescope (EHT) delivered the first very long baseline interferometry (VLBI) images at the observing frequency of 230 GHz, leading to a number of unique studies on black holes and relativistic jets from active galactic nuclei (AGN). In total, eighteen sources were observed, including the main science targets, Sgr A* and M 87, and various calibrators. Sixteen sources were AGN.Aims. We investigated the morphology of the sixteen AGN in the EHT 2017 data set, focusing on the properties of the VLBI cores: size, flux density, and brightness temperature. We studied their dependence on the observing frequency in order to compare it with the Blandford-Königl (BK) jet model. In particular, we aimed to study the signatures of jet acceleration and magnetic energy conversion.Methods. We modeled the source structure of seven AGN in the EHT 2017 data set using linearly polarized circular Gaussian components (1749+096, 1055+018, BL Lac, J0132–1654, J0006–0623, CTA 102, and 3C 454.3) and collected results for the other nine AGN from dedicated EHT publications, complemented by lower frequency data in the 2–86 GHz range. Combining these data into a multifrequency EHT+ data set, we studied the dependences of the VLBI core component flux density, size, and brightness temperature on the frequency measured in the AGN host frame (and hence on the distance from the central black hole), characterizing them with power law fits. We compared the observations with the BK jet model and estimated the magnetic field strength dependence on the distance from the central black hole.Results. Our observations spanning event horizon to parsec scales indicate a deviation from the standard BK model, particularly in the decrease of the brightness temperature with the observing frequency. Only some of the discrepancies may be alleviated by tweaking the model parameters or the jet collimation profile. Either bulk acceleration of the jet material, energy transfer from the magnetic field to the particles, or both are required to explain the observations. For our sample, we estimate a general radial dependence of the Doppler factor δ ∝ r≤0.5. This interpretation is consistent with a magnetically accelerated sub-parsec jet. We also estimate a steep decrease of the magnetic field strength with radius B ∝ r−3, hinting at jet acceleration or efficient magnetic energy dissipation.Key words: techniques: interferometric / galaxies: active / galaxies: jets / galaxies: nuclei / quasars: general / quasars: supermassive black holes⋆⋆ Deceased.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Jupiter's atmosphere - Observations and interpretation of the microwave spectrum near 1.25-cm wavelength

Measurements of Jupiter's disk-temperature spectrum in the 20- to 24-GHz (1.5 cm less than lambda less than 1.25 cm) region are reported. These data are combined with previously published data to produce a uniformly calibrated thermal spectrum of Jupiter in the wavelength interval 0.85 to 2.1 cm. Model studies are carried out to determine optimum pressure-temperature profiles for an assumed radiative-convective temperature structure. It is found that the temperature at the 1-bar total effective pressure level is between 140 and 165 K, with a most probable value of 153 K, provided that NH3 is uniformly saturated in the clouds on a global scale. We show that the temperature profile for the microwave model is approximately 20 K cooler than the profiles derived from infrared data. An explanation of this discrepancy is discussed in terms of a model which invokes different NH3 distributions in the belts and zones.

Klein, M. J.↗

The key role of forest disturbance in reconciling estimates of the northern carbon sink

Northern forests are an important carbon sink, but our understanding of the driving factors is limited due to discrepancies between dynamic global vegetation models (DGVMs) and atmospheric inversions. We show that DGVMs simulate a 50% lower sink (1.1 ± 0.5 PgC yr –1 over 2001–2021) across North America, Europe, Russia, and China compared to atmospheric inversions (2.2 ± 0.6 PgC yr –1 ). We explain why DGVMs underestimate the carbon sink by considering how they represent disturbance processes, specifically the overestimation of fire emissions, and the lack of robust forest demography resulting in lower forest regrowth rates than observed. We reconcile net sink estimates by using alternative disturbance-related fluxes. We estimate carbon uptake through forest regrowth by combining satellite-derived forest age and biomass maps. We calculate a regrowth flux of 1.1 ± 0.1 PgC yr –1 , and combine this with satellite-derived estimates of fire emissions (0.4 ± 0.1 PgC yr –1 ), land-use change emissions from bookkeeping models (0.9 ± 0.2 PgC yr –1 ), and the DGVM-estimated sink from CO 2 fertilisation, nitrogen deposition, and climate change (2.2 ± 0.9 PgC yr –1 ). The resulting ‘bottom-up’ net flux of 2.1 ± 0.9 PgC yr –1 agrees with atmospheric inversions. The reconciliation holds at regional scales, increasing confidence in our results.

54 ENVIRONMENTAL SCIENCES↗

Understanding the structure and mechanism of Na + diffusion in NASICON solid-state electrolytes and the effect of Sc- and Al/Y-substitution

NASICON (sodium superionic conductor) based ceramics are one of the most promising classes of solid-state electrolytes for all-solid-state batteries. However, the mechanism of sodium ion diffusion is not understood in great detail since there is still a discrepancy between reported average structure models, local structures, and the number and position of sodium sites. To close this gap, we investigate the underlying diffusion mechanism and structural changes governing the Na + transport in Na 3.4 Zr 2 Si 2.4 P 0.6 O 12 using quasielastic neutron scattering (QENS) and powder X-ray diffraction (XRD). In the temperature range from 298 K to 640 K, the correlations between structural changes of a monoclinic C2/c to rhombohedral R $\bar{3}$c phase transition and the result of ion diffusion are investigated. The analysis of the quasielastic neutron scattering data reveals two quasielastic components corresponding to the Chudley-Elliott jump-diffusion model. It clearly shows two different Na + diffusion processes, local and long-range, on two different time and length scales and allows calculations of their corresponding activation energies. Additionally, the effects of Sc 3+ and Al 3+ /Y 3+ aliovalent substitution of Zr 4+ ions on the crystal structure and Na + diffusion are also studied. We can distinguish a local, chain, and cross-chain diffusion mechanism based on correlated QENS and XRD comparison of relevant nearest crystallographic Na–Na distances. The results reveal that the Na + diffusion in these NASICONs is three-dimensional and can provide guidelines on how dopants and changes in the crystal structure can affect the Na + conductivity.

25 ENERGY STORAGE↗

Precision Measurement of the W Mass

Using proton-antiproton collision data corresponding to an integrated luminosity of 8.8 fb-1 collected in Tevatron Run 2, CDF performed a high precision measurement of the W mass. This result, 80433.5±6.4±6.9 MeV, is the most precise so far, and shows a discrepancy of 76 with Standard Model expectations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗