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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Probabilistic Fracture Mechanics Analysis of the Orbiter's LH2 Feedline Flowliner

Work performed by Southwest Research Institute (SwRI) as part of an Independent Technical Assessment (ITA) for the NASA Engineering and Safety Center (NESC) is summarized. The ITA goal was to establish a flight rationale in light of a history of fatigue cracking due to flow induced vibrations in the feedline flowliners that supply liquid hydrogen to the space shuttle main engines. Prior deterministic analyses using worst-case assumptions predicted failure in a single flight. The current work formulated statistical models for dynamic loading and cryogenic fatigue crack growth properties, instead of using worst-case assumptions. Weight function solutions for bivariant stressing were developed to determine accurate crack "driving-forces". Monte Carlo simulations showed that low flowliner probabilities of failure (POF = 0.001 to 0.0001) are achievable, provided pre-flight inspections for cracks are performed with adequate probability of detection (POD)-specifically, 20/75 mils with 50%/99% POD. Measurements to confirm assumed POD curves are recommended. Since the computed POFs are very sensitive to the cyclic loads/stresses and the analysis of strain gage data revealed inconsistencies with the previous assumption of a single dominant vibrant mode, further work to reconcile this difference is recommended. It is possible that the unaccounted vibrational modes in the flight spectra could increase the computed POFs.

Bonacuse, Peter J.↗
DOE OSTI2026

Indirect climate impacts of the Hunga eruption

Injection of sulfur and water vapour by the Hunga volcanic eruption significantly altered chemical composition and radiative budget of the stratosphere. Yet, whether the eruption could also affect surface climate, especially via indirect pathways, remains poorly understood. Here we investigate these effects using large ensembles of simulations with the CESM2(WACCM6) Earth system model, incorporating interactive chemistry and aerosols in both coupled ocean and atmosphere-only configurations. We find some statistically significant extratropical regional climate responses to the eruption driven by circulation changes; these are partially linked to the modulation of El Niño–Southern Oscillation, and its associated teleconnections, and to perturbations of the stratospheric polar vortex in both hemispheres. The stratospheric anomalies affect surface climate through modulating the North Atlantic Oscillation in the Northern Hemisphere (up to three boreal winters following the eruption) and the Southern Annular Mode in the Southern Hemisphere in late 2023. The latter is partly related to a concurrent reduction in Antarctic ozone, as increased stratospheric aerosols and water vapor reach the polar vortex. Our study suggests that the eruption could have had a non-negligible influence on regional surface climate, and discusses the mechanisms via which such an influence could occur. However, the results also highlight that this forcing is relatively weak compared to interannual variability, and is subject to model uncertainties in the representation of key processes. More research is thus needed before definitive statements on the role of the eruption in contributing to surface climate and weather events in the following years are made.

Geosciences↗
NASA NTRS1993

On-board closed-loop congestion control for satellite based packet switching networks

NASA LeRC is currently investigating a satellite architecture that incorporates on-board packet switching capability. Because of the statistical nature of packet switching, arrival traffic may fluctuate and thus it is necessary to integrate congestion control mechanism as part of the on-board processing unit. This study focuses on the closed-loop reactive control. We investigate the impact of the long propagation delay on the performance and propose a scheme to overcome the problem. The scheme uses a global feedback signal to regulate the packet arrival rate of ground stations. In this scheme, the satellite continuously broadcasts the status of its output buffer and the ground stations respond by selectively discarding packets or by tagging the excessive packets as low-priority. The two schemes are evaluated by theoretical queuing analysis and simulation. The former is used to analyze the simplified model and to determine the basic trends and bounds, and the later is used to assess the performance of a more realistic system and to evaluate the effectiveness of more sophisticated control schemes. The results show that the long propagation delay makes the closed-loop congestion control less responsive. The broadcasted information can only be used to extract statistical information. The discarding scheme needs carefully-chosen status information and reduction function, and normally requires a significant amount of ground discarding to reduce the on-board packet loss probability. The tagging scheme is more effective since it tolerates more uncertainties and allows a larger margin of error in status information. It can protect the high-priority packets from excessive loss and fully utilize the downlink bandwidth at the same time.

Chu, Pong P.↗
DOE OSTI2020

A Bayesian analysis of nuclear deformation properties with Skyrme energy functionals

In spite of numerous scientific and practical applications, there is still no comprehensive theoretical description of the nuclear fission process based solely on protons, neutrons and their interactions. Furthermore, the most advanced simulations of fission are currently carried out within nuclear density functional theory (DFT). In spite of being fully quantum-mechanical and rooted in the theory of nuclear forces, DFT still depends on a dozen or so parameters characterizing the energy functional. Calibrating these parameters on experimental data results in uncertainties that must be quantified for applications. This task is very challenging because of the high computational cost of DFT calculations for fission. In this paper, we use Gaussian processes to build emulators of DFT models in order to quantify and propagate statistical uncertainties of theoretical predictions for a range of nuclear deformations relevant to describing the fission process.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1982

Design solutions for the solar cell interconnect fatigue fracture problem

Mechanical fatigue of solar cell interconnects is a major failure mechanism in photovoltaic arrays. A comprehensive approach to the reliability design of interconnects, together with extensive design data for the fatigue properties of copper interconnects, has been published. This paper extends the previous work, developing failure prediction (fatigue) data for additional interconnect material choices, including aluminum and a variety of copper-Invar and copper-steel claddings. An improved global fatigue function is used to model the probability-of-failure statistics of each material as a function of level and number of cycles of applied strain. Life-cycle economic analyses are used to evaluate the relative merits of each material choce. The copper-Invar clad composites demonstrate superior performance over pure copper. Aluminum results are disappointing.

Mon, G. R.↗
DOE OSTI2021

Adaptive Cognitive Mechanisms to Maintain Calibrated Trust and Reliance in Automation

Trust calibration for a human–machine team is the process by which a human adjusts their expectations of the automation’s reliability and trustworthiness; adaptive support for trust calibration is needed to engender appropriate reliance on automation. Herein, we leverage an instance-based learning ACT-R cognitive model of decisions to obtain and rely on an automated assistant for visual search in a UAV interface. This cognitive model matches well with the human predictive power statistics measuring reliance decisions; we obtain from the model an internal estimate of automation reliability that mirrors human subjective ratings. The model is able to predict the effect of various potential disruptions, such as environmental changes or particular classes of adversarial intrusions on human trust in automation. Finally, we consider the use of model predictions to improve automation transparency that account for human cognitive biases in order to optimize the bidirectional interaction between human and machine through supporting trust calibration. The implications of our findings for the design of reliable and trustworthy automation are discussed.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1993

Application of the target decomposition theorem to a polarimetric random media model

With advances in polarimetric radar measurements of land surfaces, the need for understanding the underlying scattering mechanisms and dominant target features has become the focus of many studies. In particular, the maximum use of the polarimetric information to identify and/or separate parameters related to the surface features such as vegetation thickness, structure, water content, and soil surface characteristics will enhance the possibility of using polarimetric radars for monitoring the earth's surface from space. In this paper, Cloude's decomposition theorem is applied to a polarimetric random media model to simulate the radar measurements of vegetated canopies. The vegetated canopies are modeled as a three layer discrete random medium with leaves and branches in the first layer, tree trunks in the second layer, and a half space of homogeneous ground with rough interface as the bottom layer. The distorted born approximation (DBA) has been used to compute full Mueller matrix of the canopy, using canonical dielectric objects such as thin discs and cylinders as leaves, branches, and trunks, respectively. The Mueller matrix and the derived covariance matrix contain information on the second order statistics of radar signals at various polarizations from the canopy. To decompose the covariance matrix to its constituent targets, the eigenvalues and eigenvectors of the covariance matrix are computed in terms of the physical parameters of the canopy. In addition, each eigenvector explicitly shows the scattering mechanisms such as odd and even reflections in the canopy. Cloude's decomposition theorem is applied using the Pauli spin matrices as a basis and an expression for the degree of disorder or the entropy for the vegetated surface is found. Then, the physical parameters estimated from in situ measurements are used in the random media to obtain realistic covariance matrices. As a result, the sensitivity of the eigenvalue spectrums and the coefficients resulting from the target decomposition theorem to the physical parameters of the canopy are examined and the possible use of Cloude's theorem to estimate vegetation and soil parameters is discussed.

Saatchi, Sasan S.↗
DOE OSTI2024

Bubble Point Measurements of cis-1,1,1,4,4,4-Hexafluorobutene [R-1336mzz(Z)] + trans-1,2-Dichloroethene [R-1130(E)] mixtures

Saturation pressures of pure R-1336mzz(Z) and R-1130(E) and bubble point pressures of three R-1336mzz(Z)/1130(E) blends were measured from 265 K to 360 K. For each pure refrigerant or refrigerant blend, a total of twenty unique saturation pressures or bubble points were measured. In total 100 unique state points were obtained. Presently, no Helmholtz-energy-explicit type equation of state (EoS) is available for R-1130(E). While an extended corresponding states EoS for R-1130(E) is available to estimate the properties of the R-1336mzz(Z)/1130(E) blend, this model does not resolve the azeotropic behavior of the mixture. Therefore, the perturbed-chain statistical-associating fluid theory (PC-SAFT) EoS is used to model the vapor–liquid equilibria of the R-1336mzz(Z)/1130(E) blend. PC-SAFT model parameters are reported, and the overall performance of the model is characterized by deviations from the experimental data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Rapid Allylic 1,6 H-Atom Transfer in an Unsaturated Criegee Intermediate

Here, a novel allylic 1,6 hydrogen-atom-transfer mechanism is established through infrared activation of the 2-butenal oxide Criegee intermediate, resulting in very rapid unimolecular decay to hydroxyl (OH) radical products. A new precursor, Z/E -1,3-diiodobut-1-ene, is synthesized and photolyzed in the presence of oxygen to generate anew four-carbon Criegee intermediate with extended conjugation across the vinyl and carbonyl oxide groups that facilitates rapid allylic 1,6 H-atom transfer. A low-energy reaction pathway involving isomerization of 2-butenal oxide from a lower-energy ( tZZ ) conformer to a higher-energy ( cZZ ) conformer followed by 1,6 hydrogen transfer via a seven-membered ring transition state is predicted theoretically and shown experimentally to yield OH products. The low-lying ( tZZ ) conformer of 2-butenaloxide is identified based on computed an harmonic frequencies and intensities of its conformers. Experimental IR action spectra recorded in the fundamental CH stretch region with OH product detection by UV laser-induced fluorescence reveal a distinctive IR transition of the low-lying ( tZZ ) conformer at 2996 cm -1 that results in rapid unimolecular decay to OH products. Statistical RRKM calculations involving a combination of conformational isomerization and unimolecular decay via 1,6 H-transfer yield an effective decay rate k eff ( E ) on the order of 10 8 s -1 at ca. 3000 cm -1 in good accord with the experiment. Unimolecular decay proceeds with significant enhancement due to quantum mechanical tunneling. A rapid thermal decay rate of ca. 10 6 s -1 is predicted by master-equation modeling of 2-butenal oxide at 298 K, 1 bar. This novel unimolecular decay pathway is expected to increase the nonphotolytic production of OH radicals upon alkene ozonolysis in the troposphere.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Human-caused long-term changes in global aridity

Widespread aridification of the land surface causes substantial environmental challenges and is generally well documented. However, the mechanisms underlying increased aridity remain relatively underexplored. Here, we investigated the anthropogenic and natural factors affecting long-term global aridity changes using multisource observation-based aridity index, factorial simulations from the Coupled Model Intercomparison Project phase 6 (CMIP6), and rigorous detection and attribution (D&A) methods. Our study found that anthropogenic forcings, mainly rising greenhouse gas emissions (GHGE) and aerosols, caused the increased aridification of the globe and each hemisphere with high statistical confidence for 1965–2014; the GHGE contributed to drying trends, whereas the aerosol emissions led to wetting tendencies; moreover, the bias-corrected CMIP6 future aridity index based on the scaling factors from optimal D&A demonstrated greater aridification than the original simulations. These findings highlight the dominant role of human effects on increasing aridification at broad spatial scales, implying future reductions in aridity will rely primarily on the GHGE mitigation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Direct estimation of the density of states for fermionic systems

Simulating time evolution is one of the most natural applications of quantum computers and is thus one of the most promising prospects for achieving practical quantum advantage. Here, we develop quantum algorithms to extract thermodynamic properties by estimating the density of states (DOS), which is a central object in quantum statistical mechanics. We introduce several key innovations that significantly improve the practicality and extend the generality of previous techniques. First, our approach allows one to estimate the DOS only for a specific subspace of the full Hilbert space. This is crucial for fermionic systems, since both canonical and grand canonical ensemble thermal equilibrium properties depend on subspaces of fixed number. Second, in our approach, by time evolving very simple, random initial states, such as randomly chosen computational basis states, we can exactly recover the DOS on average. Third, due to circuit-depth limitations, we only reconstruct the DOS up to a convolution with a Gaussian window—thus all imperfections that shift the energy levels by less than the width of the convolution window will not significantly affect the estimated DOS. For these reasons, we find the approach is a promising candidate for early quantum advantage as even short-time, noisy dynamics can yield a semiquantitative reconstruction of the DOS (convolution with a broad Gaussian window), while early fault-tolerant devices will likely enable higher-resolution DOS reconstruction through longer time evolutions. We demonstrate the practicality of our approach in representative Fermi-Hubbard and spin models and indeed find that our approach is highly robust against algorithmic errors in the time evolution and against gate noise. We further demonstrate that our approach is compatible with noisy intermediate-scale quantum (NISQ) computing NISQ-friendly variational techniques, introducing and leveraging a technique for variational time evolution.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1992

An analysis of radio pulsar nulling statistics

Survival analysis methods are used to seek correlations between the fraction of null pulsars and other pulsar characteristics for an ensemble of 72 radio pulsars. The strongest correlation is found between the null fraction and the pulse period, suggesting that nulling is a manifestation of a faltering emission mechanism. Correlations are also found between the fraction of null pulses and other parameters that have a strong dependence on the pulse period. The results presented here suggest that nulling is broad-band and may ultimately be explained in terms of polar cap models of pulsar emission.

Biggs, James D.↗
DOE OSTI2023

Self-consistent hopping theory of activated relaxation and diffusion of dilute penetrants in dense crosslinked polymer networks

We generalize a microscopic statistical mechanical theory of the activated dynamics of dilute spherical penetrants in glass-forming liquids to study the influence of crosslinking in polymer networks on the penetrant relaxation time and diffusivity over a wide range of temperature and crosslink fraction (f n ). Our calculations are relevant to recent experimental studies of a nm-sized molecule diffusing in poly-(n-butyl methacrylate) networks. The theory predicts the penetrant relaxation time increases exponentially with the glass transition temperature, T g (f n ), which grows roughly linearly with the square root of fn due to the coupling of local hopping to longer-range collective elasticity. Moreover, T g is also found to be proportional to a geometric confinement parameter defined as the ratio of the penetrant diameter to the mean network mesh size. The decoupling ratio of the penetrant and Kuhn segment alpha times displays a complex non-monotonic dependence on f n and temperature that is well collapsed based on the variable T g (f n )/T. A model for the penetrant diffusion constant that combines activated relaxation and entropic mesh confinement is proposed, which results in a significantly stronger suppression of mass transport with degree of effective supercooling than predicted for the penetrant alpha time. Furthermore, this behavior corresponds to a new network-based type of “decoupling” of diffusion and relaxation. In contrast to the diffusion of larger nanoparticles in high temperature rubbery networks, our analysis in the supercooled regime suggests that for the penetrants studied the mesh confinement effects are of secondary importance relative to the consequences of crosslink-induced slowing down of activated hopping of glassy physics origin.

Chemistry↗
NASA NTRS1975

X-ray bursts from solar flares behind the limb

Data from the OSO-7 X-ray experiment were used in a search for behind-the-limb solar X-ray bursts. Seventeen active centers were found as likely seats of such bursts. The spectra of 37 over-the-limb X-ray bursts were analyzed. The distributions of maximum temperature, maximum emission measure, and characteristic cooling time do not differ in a statistically significant way from the distributions for center events. The observations support the view that the dominant cooling mechanism is conduction, for the cooling times derived from the temperature histories are too small to be explained by radiative cooling. The fraction of over-the-limb bursts which have an nonthermal component is 2/3, exactly the same as found for the 122 X-ray bursts studied in Datlowe et al. (1974b). Thick-target models of X-ray emission would suggest that hard X-ray sources would be rapidly occulted with increasing longitude of the burst location, yet just the contrary was observed.

Roy, J.-R.↗
NASA NTRSDate not supplied

Correlations Between Porosity, Spatter, and Process Metrics for Powder Bed Fusion Laser Beam Metallic Additive Manufacturing

Components fabricated using the powder bed fusion laser beam metallic (PBF-LB/M)additive manufacturing process are the result of a multitude of weld passes conducted sequentially. Qualifying components for aerospace applications requires a thorough understanding of the process-structure-properties relationships. Porosity defects are known to have a strong adverse effect on the mechanical properties of a component. In particular, porosity defects created by lack of fusion have high aspect ratio morphologies leading to stress concentrations that become crack initiation sites. In the present work, the occurrence of spatter induced lack of fusion porosity was studied using synchronized in-situ process monitoring, additive manufacturing model-based process metrics, and high-resolution X-ray computed tomography. The results show that lack of fusion porosity is statistically correlated with unremoved welding spatter ejecta of the PBF-LB/M process and process metrics related to the hatching strategy.

Qualification↗
DOE OSTI2026

Machine learning insights into microstructural origins of transport and mechanical properties in porous microstructures

Multifunctional porous materials are increasingly needed across various fields, but their complex microstructures create significant challenges due to the intricate microstructure-property relationships. This complexity, combined with limitations of traditional analysis methods, hinders efforts to understand and optimize microstructure–property relationships. Here, to address this, we integrate physics-based mesoscale modeling with interpretable machine learning (ML) to uncover how microstructural features govern effective diffusivity and elastic modulus. At constant porosity, we show diffusivity varies by over 150 × and modulus by ∼50 ×, highlighting the power of microstructure engineering. Statistical analysis reveals bimodal behavior in diffusivity and unimodal in modulus. ML identifies connectivity as the dominant factor, while modulus is also sensitive to domain size and feature interactions. Controlled simulations further highlight domain shape as a critical feature for modulus. This framework enables efficient exploration of microstructure-property correlations, offering new insights to guide the design of advanced porous materials.

Bicontinuous microstructure↗
DOE OSTI2020

A generalized approximate control variate framework for multifidelity uncertainty quantification

We describe and analyze a variance reduction approach for Monte Carlo (MC) sampling that accelerates the estimation of statistics of computationally expensive simulation models using an ensemble of models with lower cost. These lower cost models — which are typically lower fidelity with unknown statistics — are used to reduce the variance in statistical estimators relative to a MC estimator with equivalent cost. We derive the conditions under which our proposed approximate control variate framework recovers existing multifidelity variance reduction schemes as special cases. We demonstrate that existing recursive/nested strategies are suboptimal because they use the additional low-fidelity models only to efficiently estimate the unknown mean of the first low-fidelity model. As a result, they cannot achieve variance reduction beyond that of a control variate estimator that uses a single low-fidelity model with known mean. However, there often exists about an order-of-magnitude gap between the maximum achievable variance reduction using all low-fidelity models and that achieved by a single low-fidelity model with known mean. We show that our proposed approach can exploit this gap to achieve greater variance reduction by using non-recursive sampling schemes. The proposed strategy reduces the total cost of accurately estimating statistics, especially in cases where only low-fidelity simulation models are accessible for additional evaluations. Several analytic examples and an example with a hyperbolic PDE describing elastic wave propagation in heterogeneous media are used to illustrate the main features of the methodology.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗