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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Stability and Heat Transfer Characteristics of Condensing Films

The overall objective of this research is to investigate the fundamental physics of film condensation in reduced gravity. The condensation of vapor on a cool surface is important in many engineering problems,including spacecraft thermal control and also the behavior of condensate films that may form on the interior surfaces of spacecraft. To examine the effects of body force on condensing films, two different geometries have been tested in the laboratory: (1) a stabilizing gravitational body force (+1g, or condensing surface facing 'upwards') and (2) de-stabilizing gravitational body force (-1g, or 'downwards'). For each geometry, different fluid configurations are employed to help isolate the fluid mechanical and thermal mechanisms operative in condensing films. The fluid configurations are (a) a condensing film, and (b) a non-condensing film with film growth by mass addition by through the plate surface. Condensation experiments are conducted in a test cell containing a cooled copper or brass plate with an exposed diameter of 12.7 cm. The metal surface is polished to allow for double-pass shadowgraph imaging, and the test surface is instrumented with imbedded heat transfer gauges and thermocouples. Representative shadowgraph images of a condensing, unstable (-1g) n-pentane film are shown. The interfacial disturbances associated with the de-stabilizing body force leading to droplet formation and break-off can be clearly seen. The heat transfer coefficient associated with the condensing film is shown. The heat transfer coefficient is seen to initially decrease, consistent with the increased thermal resistance due to layer growth. For sufficiently long time, a steady value of heat transfer is observed, accompanied by continuous droplet formation and break-off. The non-condensing cell consists of a stack of thin stainless steel disks 10 cm in diameter mounted in a brass enclosure. The disks are perforated with a regular pattern of 361 holes each 0.25 mm in diameter. Non-condensing experiments in -1g have employed 50 cSt and 125 cSt silicone oil pumped through the perforated disks at a specified rate by a syringe micropump. The time to droplet break-off and the disturbance wavelengths appear to decrease with increasing pumping rate. The ability to reliably perform multi-point, ultrasonic measurements of the film thickness has been demonstrated. A linear array of eight transducers of 6 mm diameter (with a beam footprint of comparable size) are pulsed with a square-wave signal at a frequency of 5 MHz and a pulse duration of approximately 0.3 s. For thin films (60 m to 2-3 mm in thickness) the layer thickness is determined by frequency analysis, where the received ultrasound pulse is Fourier transformed and the spacing between the peaks in the frequency spectrum is analyzed. For thicker layers (up to at least 1 cm in thickness), time-domain analysis is performed of the received ultrasound pulses to generate directly the layer thickness. A time-trace of the film thickness at a point using a single transducer in the linear array is shown for the case of an unstable (-1g) n-pentane film. The oscillations in film thickness are evidently due to the passage and/or shedding of droplets from the cooled plate surface. The entire transducer array was used to measure the changes in film thickness resulting from the passage of gravity waves generated either by an oscillating wall or the impact of a single droplet on the free surface of a film. The enclosure in both cases was 14 cm square and the transducer spacing was 12 mm. Best results were obtained using as test fluid a mixture of 50% glycerol and 50% water with a fluid layer thickness of 3-5 mm. In both cases the measured wavelengths and wave propagation speeds using the ultrasound technique compared reasonably well with those observed by optical imaging. Additional information can be found in the original extended abstract.

Hermanson, J. C.↗
NASA NTRS2011

Validation and Simulation of Ares I Scale Model Acoustic Test - 3 - Modeling and Evaluating the Effect of Rainbird Water Deluge Inclusion

The Ares I Scale Model Acoustics Test (ASMAT) is a series of live-fire tests of scaled rocket motors meant to simulate the conditions of the Ares I launch configuration. These tests have provided a well documented set of high fidelity measurements useful for validation including data taken over a range of test conditions and containing phenomena like Ignition Over-Pressure and water suppression of acoustics. Building on dry simulations of the ASMAT tests with the vehicle at 5 ft. elevation (100 ft. real vehicle elevation), wet simulations of the ASMAT test setup have been performed using the Loci/CHEM computational fluid dynamics software to explore the effect of rainbird water suppression inclusion on the launch platform deck. Two-phase water simulation has been performed using an energy and mass coupled lagrangian particle system module where liquid phase emissions are segregated into clouds of virtual particles and gas phase mass transfer is accomplished through simple Weber number controlled breakup and boiling models. Comparisons have been performed to the dry 5 ft. elevation cases, using configurations with and without launch mounts. These cases have been used to explore the interaction between rainbird spray patterns and launch mount geometry and evaluate the acoustic sound pressure level knockdown achieved through above-deck rainbird deluge inclusion. This comparison has been anchored with validation from live-fire test data which showed a reduction in rainbird effectiveness with the presence of a launch mount.

Strutzenberg, Louise L.↗
NASA NTRS2022

Evaluating Twenty-Year Trends in Earth’s Energy Flows from Observations and Reanalyses

Satellite, reanalysis, and ocean in situ data are analyzed to evaluate regional, hemispheric and global mean trends in Earth’s energy fluxes during the first twenty years of the 21st century. Regional trends in net top-of-atmosphere (TOA) radiation from the Clouds and the Earth’s Radiant Energy System (CERES), ECMWF Reanalysis 5 (ERA5), and a model similar to ERA5 with prescribed sea surface temperature (SST) and sea ice differ markedly, particularly over the Eastern Pacific Ocean, where CERES observes large positive trends. Hemispheric and global mean net TOA flux trends for the two reanalyses are smaller than CERES, and their climatological means are half those of CERES in the southern hemisphere (SH) and more than nine times larger in the northern hemisphere (NH). The regional trend pattern of the divergence of total atmospheric energy transport (TEDIV) over ocean determined using ERA5 analyzed fields is similar to that inferred from the difference between TOA and surface fluxes from ERA5 short-term forecasts. There is also agreement in the trend pattern over ocean for surface fluxes inferred as a residual between CERES net TOA flux and ERA5 analysis TEDIV and surface fluxes obtained directly from ERA5 forecasts. Robust trends are observed over the Gulf Stream associated with enhanced surface-to-atmosphere transfer of heat. Within the ocean, larger trends in ocean heating rate are found in the NH than the SH after 2005, but the magnitude of the trend varies greatly among datasets.

Norman G Loeb↗
DOE OSTI2020

A Group of O-Acetyltransferases Catalyze Xyloglucan Backbone Acetylation and Can Alter Xyloglucan Xylosylation Pattern and Plant Growth When Expressed in Arabidopsis

Abstract Xyloglucan is a major hemicellulose in plant cell walls and exists in two distinct types, XXXG and XXGG. While the XXXG-type xyloglucan from dicot species only contains O-acetyl groups on side-chain galactose (Gal) residues, the XXGG-type xyloglucan from Poaceae (grasses) and Solanaceae bears O-acetyl groups on backbone glucosyl (Glc) residues. Although O-acetyltransferases responsible for xyloglucan Gal acetylation have been characterized, the biochemical mechanism underlying xyloglucan backbone acetylation remains to be elucidated. In this study, we showed that recombinant proteins of a group of DUF231 members from rice and tomato were capable of transferring acetyl groups onto O-6 of Glc residues in cello-oligomer acceptors, indicating that they are xyloglucan backbone 6-O-acetyltransferases (XyBATs). We further demonstrated that XyBAT-acetylated cellohexaose oligomers could be readily xylosylated by AtXXT1 (Arabidopsis xyloglucan xylosyltransferase 1) to generate acetylated, xylosylated cello-oligomers, whereas AtXXT1-xylosylated cellohexaose oligomers were much less effectively acetylated by XyBATs. Heterologous expression of a rice XyBAT in Arabidopsis led to a severe reduction in cell expansion and plant growth and a drastic alteration in xyloglucan xylosylation pattern with the formation of acetylated XXGG-type units, including XGG, XGGG, XXGG, XXGG,XXGGG and XXGGG (G denotes acetylated Glc). In addition, recombinant proteins of two Arabidopsis XyBAT homologs also exhibited O-acetyltransferase activity toward cellohexaose, suggesting their possible role in mediating xyloglucan backbone acetylation in vivo. Our findings provide new insights into the biochemical mechanism underlying xyloglucan backbone acetylation and indicate the importance of maintaining the regular xyloglucan xylosylation pattern in cell wall function.

Cell Biology↗
NASA NTRS1989

On the Nature of Navier-stokes Turbulence

Several turbulent and nonturbulent solutions of the Navier-Stokes equations are obtained. The unaveraged equations are used numerically in conjunction with tools and concepts from nonlinear dynamics, including time series, phase portraits, Poincare sections, largest Liapunov exponents, power spectra, and strange attractors. Initially neighboring solutions for a low-Reynolds-number fully developed turbulence are compared. The solutions, separate exponentially with time, having a positive Liapunov exponent. Thus the turbulence is characterized as chaotic. In a search for solutions which contrast with the turbulent ones, the Reynolds number is reduced. Several qualitatively different flows are noted. These are, fully chaotic, complex period, weakly chaotic, simple periodic, and fixed-point. Of these, only the fully chaotic flows are classified as turbulent. Those flows have both a positive Liapunov exponent and Poincare sections without pattern. By contrast, the weakly chaotic flows have some pattern in their Poincare sections. The fixed-point and periodic flows are nonturbulent, since turbulence, is both time-dependent and aperiodic. Turbulent solutions are obtained in which energy cascades from large to small-scale motions. In general, the spectral energy transfer takes place between wavenumber bands that are considerably separated. The special transfer can occur either as a result of nonlinear turbulence self-interaction or by interaction of turbulence with mean gradients. Turbulent systems are compared with those studied in kinetic theory. The two types of systems are fundamentally different (continuous and dissipative as opposed to discrete and conservative), but there are similarities. For instance, both are nonlinear and show sensitive dependence on initial conditions. Also, the turbulent and molecular stress tensors are identical if the macroscopic velocities for the turbulent stress are replaced by molecular velocities.

Deissler, Robert G.↗
NASA NTRS1989

Damage-tolerant composite materials produced by stitching carbon fibers

NASA-Langley has undertaken the investigation of composite damage-tolerance enhancement and fabrication economies-maximization via reinforcement-stitching, in combination with resin transfer molding. Attention is given to results obtained by an experimental evaluation of composites tailored for damage tolerance by stitching layers of dry carbon-fiber fabric with closely-spaced threads, in order to furnish through-the-thickness reinforcement. Various stitching patterns and thread materials have been evaluated, using flat-plate specimens; blade-stiffened structural elements have been fabricated and tested. The results presented indicate that stitched laminates furnish damage tolerance performance comparable to that of more expensive, toughened-matrix composites.

Dow, Marvin B.↗
NASA NTRS2009

Polyimide-Foam/Aerogel Composites for Thermal Insulation

Composites of specific types of polymer foams and aerogel particles or blankets have been proposed to obtain thermal insulation performance superior to those of the neat polyimide foams. These composites have potential to also provide enhanced properties for vibration dampening or acoustic attenuation. The specific type of polymer foam is denoted "TEEK-H", signifying a series, denoted H, within a family of polyimide foams that were developed at NASA s Langley Research Center and are collectively denoted TEEK (an acronym of the inventors names). The specific types of aerogels include Nanogel aerogel particles from Cabot Corporation in Billerica, MA. and of Spaceloft aerogel blanket from Aspen Aerogels in Northborough, MA. The composites are inherently flame-retardant and exceptionally thermally stable. There are numerous potential uses for these composites, at temperatures from cryogenic to high temperatures, in diverse applications that include aerospace vehicles, aircraft, ocean vessels, buildings, and industrial process equipment. Some low-temperature applications, for example, include cryogenic storage and transfer or the transport of foods, medicines, and chemicals. Because of thermal cycling, aging, and weathering most polymer foams do not perform well at cryogenic temperatures and will undergo further cracking over time. The TEEK polyimides are among the few exceptions to this pattern, and the proposed composites are intended to have all the desirable properties of TEEK-H foams, plus improved thermal performance along with enhanced vibration or acoustic-attenuation performance. A composite panel as proposed would be fabricated by adding an appropriate amount of TEEK friable balloons into a mold to form a bottom layer. A piece of flexible aerogel blanket material, cut to the desired size and shape, would then be placed on the bottom TEEK layer and sandwiched between another top layer of polyimide friable balloons so that the aerogel blanket would become completely encased in an outer layer of TEEK friable balloons. Optionally, the process could be further repeated to produce multiple aerogel-blanket layers interspersed with and encased by TEEK friable balloons.

Williams, Martha↗
DOE OSTI2021

Seasonal changes in the drivers of water physico-chemistry variability of a small freshwater tidal river

Where rivers meet the sea, tides can exert a physical and chemical influence on the lower reaches of a river. How tidal dynamics in these tidal river reaches interact with upstream hydrological drivers such as storm rainfall, which ultimately determines the quantity and composition of material transferred from watersheds to estuaries, is currently unknown. We monitored a small freshwater tidal river in the Pacific Northwest, USA in high resolution over one year to evaluate the relative importance of tides versus upstream hydrological flows (i.e., base flow and precipitation events) on basic physico-chemical parameters (pH, dissolved oxygen, turbidity, specific conductivity, and temperature), and how these interactions relate to the downstream estuary. Tidal variability and diurnal cycles (i.e. solar radiation) dominated water physico-chemical variability in the summer, but the influence of these drivers was overshadowed by storm-driven sharp pulses in river physico-chemistry during the remainder of the year. Within such events, we found incidences of counterclockwise hysteresis of pH, counterclockwise hysteresis of dissolved oxygen, and clockwise hysteresis of turbidity, although systematic trends were not observed across events. The dominance of storm rainfall in the river’s physico-chemistry dynamics, and similar pulses of decreased pH observed in adjacent estuarine waters, suggest that the linkage between tidal streams and the broader system is variable throughout the year. High-frequency monitoring of tidal river biogeochemistry is therefore crucial to enable the assessment of how the relative strength of these drivers may change with future sea level rise and altered precipitation patterns to modulate biogeochemical dynamics across the land-ocean-atmosphere continuum.

aquatic↗
NASA NTRS2016

Predictive Simulation of Gas Adsorption in Fixed-Beds and Limitations due to the Ill-Posed Danckwerts Boundary Condition

The 1-D axially dispersed plug flow model is a mathematical model widely used for the simulation of adsorption processes. Lumped mass transfer coefficients such as the Glueckauf linear driving force (LDF) term and the axial dispersion coefficient are generally obtained by fitting simulation results to the experimental breakthrough test data. An approach is introduced where these parameters, along with the only free parameter in the energy balance equations, are individually fit to specific test data that isolates the appropriate physics. It is shown that with this approach this model provides excellent simulation results for the C02 on zeolite SA sorbent/sorbate system; however, for the H20 on zeolite SA system, non-physical deviations from constant pattern behavior occur when fitting dispersive experimental results with a large axial dispersion coefficient. A method has also been developed that determines a priori what values of the LDF and axial dispersion terms will result in non-physical simulation results for a specific sorbent/sorbate system when using the one-dimensional axially dispersed plug flow model. A relationship between the steepness of the adsorption equilibrium isotherm as indicated by the distribution factor, the magnitude of the axial dispersion and mass transfer coefficient, and the resulting non-physical behavior is derived. This relationship is intended to provide a guide for avoiding non-physical behavior by limiting the magnitude of the axial dispersion term on the basis of the mass transfer coefficient and distribution factor.

Knox, James Clinton↗
NASA NTRS2018

Advances in Hyperspectral Image Classification Methods for Vegetation and Agricultural Cropland Studies

Hyperspectral data are becoming more widely available via sensors on airborne and unmanned aerial vehicle (UAV) platforms, as well as proximal platforms. While space-based hyperspectral data continue to be limited in availability, multiple spaceborne Earth-observing missions on traditional platforms are scheduled for launch, and companies are experimenting with small satellites for constellations to observe the Earth, as well as for planetary missions. Land cover mapping via classification is one of the most important applications of hyperspectral remote sensing and will increase in significance as time series of imagery are more readily available. However, while the narrow bands of hyperspectral data provide new opportunities for chemistry-based modeling and mapping, challenges remain. Hyperspectral data are high dimensional, and many bands are highly correlated or irrelevant for a given classification problem. For supervised classification methods, the quantity of training data is typically limited relative to the dimension of the input space. The resulting Hughes phenomenon, often referred to as the curse of dimensionality, increases potential for unstable parameter estimates, overfitting, and poor generalization of classifiers. This is particularly problematic for parametric approaches such as Gaussian maximum likelihood–based classifiers that have been the backbone of pixel-based multispectral classification methods. This issue has motivated investigation of alternatives, including regularization of the class covariance matrices, ensembles of weak classifiers, development of feature selection and extraction methods, adoption of nonparametric classifiers, and exploration of methods to exploit unlabeled samples via semi-supervised and active learning. Data sets are also quite large, motivating computationally efficient algorithms and implementations. This chapter provides an overview of the recent advances in classification methods for mapping vegetation using hyperspectral data. Three data sets that are used in the hyperspectral classification literature (e.g., Botswana Hyperion satellite data and AVIRIS airborne data over both Kennedy Space Center and Indian Pines) are described in Section 3.2 and used to illustrate methods described in the chapter. An additional high-resolution hyperspectral data set acquired by a SpecTIR sensor on an airborne platform over the Indian Pines area is included to exemplify the use of new deep learning approaches, and a multiplatform example of airborne hyperspectral data is provided to demonstrate transfer learning in hyperspectral image classification. Classical approaches for supervised and unsupervised feature selection and extraction are reviewed in Section 3.3. In particular, nonlinearities exhibited in hyperspectral imagery have motivated development of nonlinear feature extraction methods in manifold learning, which are outlined in Section 3.3.1.4. Spatial context is also important in classification of both natural vegetation with complex textural patterns and large agricultural fields with significant local variability within fields. Approaches to exploit spatial features at both the pixel level (e.g., co-occurrence–based texture and extended morphological attribute profiles [EMAPs]) and integration of segmentation approaches (e.g., HSeg) are discussed in this context in Section 3.3.2. Recently, classification methods that leverage nonparametric methods originating in the machine learning community have grown in popularity. An overview of both widely used and newly emerging approaches, including support vector machines (SVMs), Gaussian mixture models, and deep learning based on convolutional neural networks is provided in Section 3.4. Strategies to exploit unlabeled samples, including active learning and metric learning, which combine feature extraction and augmentation of the pool of training samples in an active learning framework, are outlined in Section 3.5. Integration of image segmentation with classification to accommodate spatial coherence typically observed in vegetation is also explored, including as an integrated active learning system. Exploitation of multisensor strategies for augmenting the pool of training samples is investigated via a transfer learning framework in Section 3.5.1.2. Finally, we look to the future, considering opportunities soon to be provided by new paradigms, as hyperspectral sensing is becoming common at multiple scales from ground-based and airborne autonomous vehicles to manned aircraft and space-based platforms.

Pasolli, Edoardo↗
DOE OSTI2020

Giant virus diversity and host interactions through global metagenomics

Our current knowledge about nucleocytoplasmic large DNA viruses (NCLDVs) is largely derived from viral isolates that are co-cultivated with protists and algae. Here we reconstructed 2,074 NCLDV genomes from sampling sites across the globe by building on the rapidly increasing amount of publicly available metagenome data. This led to an 11-fold increase in phylogenetic diversity and a parallel 10-fold expansion in functional diversity. Analysis of 58,023 major capsid proteins from large and giant viruses using metagenomic data revealed the global distribution patterns and cosmopolitan nature of these viruses. The discovered viral genomes encoded a wide range of proteins with putative roles in photosynthesis and diverse substrate transport processes, indicating that host reprogramming is probably a common strategy in the NCLDVs. Furthermore, inferences of horizontal gene transfer connected viral lineages to diverse eukaryotic hosts. We anticipate that the global diversity of NCLDVs that we describe here will establish giant viruses-which are associated with most major eukaryotic lineages-as important players in ecosystems across Earth's biomes.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1973

SEC vidicon testing

Results obtained from several basic measurements of the performance of an SEC vidicon camera head are presented. The measurements or tests are patterned around the sensor requirements which exist for a rapid response coronagraph. Following a brief description of the SEC vidicon camera head, test set-up, and operating procedures, results are presented for five basic tests. These tests include: (1) Input-output, or transfer, characteristics; (2) modulation transfer function; (3) signal-to-noise ratio; (4) photocathode sensitivity; and (5) target gain. The input-output characteristics and photocathode sensitivity measurements were obtained for three bandpasses centered about 4000, 5250, and 6200 A. Results are also given for the variation of photocathode sensitivity with position on the cathode surface.

Johnson, D. S., Jr.↗
NASA NTRS1999

Gravitational Acceleration Effects on Macrosegregation: Experiment and Computational Modeling

Experiments were performed under terrestrial gravity (1g) and during parabolic flights (10-2 g) to study the solidification and macrosegregation patterns of Al-Cu alloys. Alloys having 2% and 5% Cu were solidified against a chill at two different cooling rates. Microscopic and Electron Microprobe characterization was used to produce microstructural and macrosegregation maps. In all cases positive segregation occurred next to the chill because shrinkage flow, as expected. This positive segregation was higher in the low-g samples, apparently because of the higher heat transfer coefficient. A 2-D computational model was used to explain the experimental results. The continuum formulation was employed to describe the macroscopic transports of mass, energy, and momentum, associated with the solidification phenomena, for a two-phase system. The model considers that liquid flow is driven by thermal and solutal buoyancy, and by solidification shrinkage. The solidification event was divided into two stages. In the first one, the liquid containing freely moving equiaxed grains was described through the relative viscosity concept. In the second stage, when a fixed dendritic network was formed after dendritic coherency, the mushy zone was treated as a porous medium. The macrosegregation maps and the cooling curves obtained during experiments were used for validation of the solidification and segregation model. The model can explain the solidification and macrosegregation patterns and the differences between low- and high-gravity results.

Leon-Torres, J.↗
DOE OSTI2022

Kingdom-Wide Analysis of Fungal Protein-Coding and tRNA Genes Reveals Conserved Patterns of Adaptive Evolution

Protein-coding genes evolved codon usage bias due to the combined but uneven effects of adaptive and nonadaptive influences. Studies in model fungi agree on codon usage bias as an adaptation for fine-tuning gene expression levels; however, such knowledge is lacking for most other fungi. Our comparative genomics analysis of over 450 species supports codon usage and transfer RNAs (tRNAs) as coadapted for translation speed and this is most likely a realization of convergent evolution. Rather than drift, phylogenetic reconstruction inferred adaptive radiation as the best explanation for the variation of interspecific codon usage bias. Although the phylogenetic signals for individual codon and tRNAs frequencies are lower than expected by genetic drift, we found remarkable conservation of highly expressed genes being codon optimized for translation by the most abundant tRNAs, especially by inosine-modified tRNAs. As an application, we present a sequence-to-expression neural network that uses codons to reliably predict highly expressed transcripts. The kingdom Fungi, with over a million species, includes many key players in various ecosystems and good targets for biotechnology. Collectively, our results have implications for better understanding the evolutionary success of fungi, as well as informing the biosynthetic manipulation of fungal genes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

FAIRification, Quality Assessment, and Missingness Pattern Discovery for Spatiotemporal Photovoltaic Data

The ongoing growth of the photovoltaic market has pushed the demand for power forecasting and performance evaluation for a huge population of PV power plants. Through access to a large number of time series data sets from different power plants, we have found common issues that impede the modeling process. Namely, the time series data are hard to transfer between groups due to differences in variable nomenclature, and the quality of the data sets can vary. We address the issue of variable nomenclature by FAIRifying spatiotemporal PV time series data. Through the creation of a solar power plant ontology, we propose standards for the naming and structure of metadata used to describe the data from these power plants. Using the structure from this ontology, we have developed both R and Python packages for the automation of the FAIRification process. We have also developed an R package that automates the analysis of the quality of a data set through the designation of letter grades. With access to large time series data sets across many power plants, we can utilize spatiotemporal coherence between the sites in order to improve the quality of our data. To solve the issue of data missingness, we propose the use of Spatiotemporal-GNN autoencoders to detect and impute missing values from a data set by utilizing data from power plants nearby.

14 SOLAR ENERGY↗
DOE OSTI2022

Damage of prismatic lithium‐ion cells subject to bending: Test, model, and detection

Abstract The mechanically induced internal short circuit (ISC) is one of the major safety concerns of lithium‐ion batteries. Mechanical abuse tests are often performed to evaluate the integrity and safety of lithium‐ion batteries under mechanical loadings. Except for the widely explored compression‐dominated indentation tests, bending is another typical real‐world loading condition that is tension‐dominated. To investigate the mechanical damage and ISC behavior of batteries under bending, we carried out controlled three‐point bending tests in four progressive steps on prismatic battery cells with maximum deflections ranging from 38% to 76% of the cell thickness. None of the tested cells experienced an ISC. We then conducted 3D X‐ray computed tomography (CT) scanning on the bent cells after unloading. X‐ray CT images showed three out of the four tested cells have extensive cracking in the electrode layers at the bottom side (opposite to the loading head). This indicates that cracking does not necessarily lead to an ISC under bending. Electrochemical impedance spectroscopy was also measured on the bent cells and substantial changes were observed. Both the bulk resistance and charge‐transfer resistance increased significantly after bending, which could influence the battery performance and lifespan. We then developed a detailed finite (FE) element model to further investigate the mechanical deformation and failure mechanisms. The FE model successfully predicts the load–displacement response and reproduces the deformation patterns. The findings and the FE model developed in the present study provide useful insights and tools for the battery structure and crash safety design. image

25 ENERGY STORAGE↗
DOE OSTI2018

Symmetry breakdown of electron emission in extreme ultraviolet photoionization of argon

Short wavelength free-electron lasers (FELs), providing pulses of ultrahigh photon intensity, have revolutionized spectroscopy on ionic targets. Their exceptional photon flux enables multiple photon absorptions within a single femtosecond pulse, which in turn allows for deep insights into the photoionization process itself as well as into evolving ionic states of a target. Here we employ ultraintense pulses from the FEL FERMI to spectroscopically investigate the sequential emission of electrons from gaseous, atomic argon in the neutral as well as the ionic ground state. A pronounced forward-backward symmetry breaking of the angularly resolved emission patterns with respect to the light propagation direction is experimentally observed and theoretically explained for the region of the Cooper minimum, where the asymmetry of electron emission is strongly enhanced. Furthermore, these findings aim to originate a better understanding of the fundamentals of photon momentum transfer in ionic matter.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Explainable tokamak-agnostic forecasting of fusion plasma instability via megahertz turbulent fluctuations

Scientific applications of artificial intelligence (AI) often remain limited by device-specific training and unexplained “black-box” approaches, creating fundamental barriers to cross-system generalization. This challenge is critical for nuclear fusion, where future reactors will have limited operational data for AI training. Here, we demonstrate that our neural network, trained solely on megahertz-scale turbulence measurements from one machine (DIII-D), forecasts Type-I edge localized mode (ELM) onsets in a different tokamak (KSTAR) through zero-shot weight transfer following physics-consistent preprocessing without device-specific retraining. Through an explainable AI framework combining gradient-weighted class activation mapping with physics validation, we reveal that our network can internalize physics relationships governing the ELM instabilities rather than memorizing device-specific patterns. The network perceives spatiotemporal features that correlate consistently with independently calculated instability growth rates, magnetohydrodynamic stability limits, and pedestal structure dynamics. Statistical analyses of dimensionally-reduced saliency features reveal the identical triangular features between the saliency representations, instability growth rates, and prediction probability across tokamaks, providing evidence that our forecasting system can show tokamak-agnostic generalization. This work contributes to a foundation for explainable scientific AI systems, where cross-system developments are essential for transcending traditional domain-specific constraints.

AI↗