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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Bubble departure and sliding in high-pressure flow boiling of water

Bubble growth, departure and sliding in low-pressure flow boiling has received considerable attention in the past. However, most applications of boiling heat transfer rely on high-pressure flow boiling, for which very little is known, as experimental data are scarce and very difficult to obtain. In this work, we conduct an experiment using high-resolution optical techniques. By combining backlit shadowgraphy and phase-detection imaging, we track bubble shape and physical footprint with high spatial ($6\,\mathrm {\mu }{\rm m}$) and temporal ($33\,\mathrm {\mu }{\rm s}$) resolutions, as well as bubble size and position as bubbles nucleate and slide on top of the heated surface. We show that at pressures above 1 MPa bubbles retain a spherical shape throughout the growth and sliding process. We analytically derive non-dimensional numbers to correlate bubble velocity and liquid velocity throughout the turbulent boundary layer and predict the sliding of bubbles on the surface, solely from physical properties and the bubble growth rate. We also show that these non-dimensional solutions can be leveraged to formulate elementary criteria that predict the effect of pressure and flow rate on bubble departure diameter and growth time.

Mechanics↗
DOE OSTI2020

Time-Sequenced Flow Field Prediction in an Optima Spark-Ignition Direct-Injection Engine Using Bidirectional Recurrent Neural Network (bi-RNN) with Long Short-Term Memory

To further improve the energy conversion efficiency of internal combustion engine, the transient and complex air flow movement inside the cylinder needs to be better understood and controlled. Although the in-cylinder flow fields are highly stochastic with strong cycle-to-cycle fluctuations, machine learning can still provide an efficient way to learn and regress the complex flow movement process inside the cylinder. In this work, a bidirectional recurrent neural network (bi-RNN) model with long short-term memory was applied to predict the in-cylinder flow fields at different time steps using training data from mull-cycle particle image velocimetry (PIV) measurements. To evaluate the agreement between the true and predicted flow fields, structure and magnitude comparison indices are calculated both globally and locally. The comparison results show that the bi-RNN model can accurately predict the bulk flow and vortex motions from early intake stroke to compression stroke. This work demonstrates that the machine learning model has the potential to predict the underlying dynamics of the interaction between in-cylinder flows and provides a reliable way to improve temporal resolution in PIV flow data to better reveal transient in-cylinder flow features.

Bi-RNN model↗
DOE OSTI2023

Laser Speckle Pattern Stability in Hypersonic Regimes for Experimental Mechanics and Metrological Studies

Here, an empirical study assessing the suitability of laser speckle patterns for use in experimental mechanics research conducted at hypersonic conditions is presented. Speckle patterns generated via coherent optical scattering from a gold-coated graphite surface inserted into a Mach 10 air stream were collected and analyzed using Computer-Aided Speckle Interferometry using two methodologies: a typical spanwise approach involving increasing temporal span between image pairs, and a sequential approach that utilizes a combination of temporal re-referencing and spatial resampling. Results were characterized for spatial-temporal stability and variance. Our observations demonstrate that optical methods relying on stable and properly formed speckle patterns can be used in a hypersonic regime at various Reynolds numbers and common camera frame rates, but the technique is sensitive to the conditions of the airflow and the processing methodology chosen.

42 ENGINEERING↗
DOE OSTI2024

X-ray nano-holotomography reconstruction with simultaneous probe retrieval

In conventional tomographic reconstruction, the pre-processing step includes flat-field correction, where each sample projection on the detector is divided by a reference image taken without the sample. When using coherent X-rays as a probe, this approach overlooks the phase component of the illumination field (probe), leading to artifacts in phase-retrieved projection images, which are then propagated to the reconstructed 3D sample representation. The problem intensifies in nano-holotomography with focusing optics, which, due to various imperfections creates high-frequency components in the probe function. Here, we present a new iterative reconstruction scheme for holotomography, simultaneously retrieving the complex-valued probe function. Implemented on GPUs, this algorithm results in 3D reconstruction resolving twice thinner layers in a 3D ALD standard sample measured using nano-holotomography.

Nikitin, Viktor↗
DOE OSTI2020

An advanced workflow for single-particle imaging with the limited data at an X-ray free-electron laser

An improved analysis for single-particle imaging (SPI) experiments, using the limited data, is presented here. Results are based on a study of bacteriophage PR772 performed at the Atomic, Molecular and Optical Science instrument at the Linac Coherent Light Source as part of the SPI initiative. Existing methods were modified to cope with the shortcomings of the experimental data: inaccessibility of information from half of the detector and a small fraction of single hits. The general SPI analysis workflow was upgraded with the expectation-maximization based classification of diffraction patterns and mode decomposition on the final virus-structure determination step. The presented processing pipeline allowed us to determine the 3D structure of bacteriophage PR772 without symmetry constraints with a spatial resolution of 6.9 nm. The obtained resolution was limited by the scattering intensity during the experiment and the relatively small number of single hits.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Technical Performance and Cost Optimization of Unobtrusive Multi-static Serial LiDAR Imager (UMSLI) for Wide-area Surveillance and Identification of Marine Life at Marine Energy Installations

Florida Atlantic University developed an underwater optical monitoring system prototype - Unobtrusive Multi-static Serial LiDAR Imager (UMSLI) - suitable for marine energy full project lifecycle observation (baseline, commissioning, and decommissioning), with an automated real-time classification of marine animals. With precursor 2014 DOE funding (award DE-EE0006787), a prototype UMSLI was demonstrated in a controlled laboratory environment and achieved a TRL 6. This EERE DE-EE0007828 award aimed to both increase the TRL of the UMSLI by improving the technology performance (e.g., increase distance of marine animal target detection capability, add additional species classification capabilities, improve the system performance during the day, etc.) and reduce the cost. The UMSLI presents a novel application of underwater distributed Light Detection And Ranging (LiDAR), an advanced remote sensing method that uses light in the form of laser pulses for an application, this paired with an algorithm provides 360 degrees underwater detection, imaging, and classification of marine life. This solution for underwater monitoring of biota preserves the advantages of traditional optical and acoustic solutions while overcoming many associated disadvantages for marine energy site environmental monitoring, such as difficulties in species detection and classification in low light or night and turbid environments. This new approach is a purposefully designed, reconfigurable adaptation of an existing class 3B laser technology into one UMSLI instrument that can be easily mounted on or around different classes of marine energy equipment, such as devices to capture ocean current energy or wave energy. The system uses relatively low average power, utilizes far-red (> 635nm) laser illumination to be invisible and eye-safe to marine animals, is compact, and cost-effective. The equipment is designed for long-term, maintenance-free operations (i.e., current design is targeting more than 7 days continuous operation), to inherently generate a sparse primary dataset that only includes detected anomalies, and to allow robust real-time automated animal classification and identification with a low data bandwidth requirement. The technology’s overarching goal for application, is a system that can be deployed to collect pre-installation baseline species observations at a proposed marine energy deployment site with minimal post-processing overhead. The envisioned system will also produce high-resolution imagery of marine animals through a wide range of conditions and support automated tracking and notification of the presence of managed animals within established perimeters of marine energy equipment to satisfy deployed marine energy projects’ endangered and threatened species monitoring requirements. Through the current project, we demonstrated the UMSLI prototype in an operational environment and increased the UMSLI’s Technology Readiness Level from 6 to 7. The project resulted in many novel technologies, including: 1) an eye-safe red laser based, low-cost LiDAR system that can detect targets up to 10 meters distance; 2) the GAN-based machine learning underwater LiDAR image enhancement technique (this is the first known application of GAN technique in underwater LiDAR); 3) LiDAR-based real-time automated detection capabilities; and 4) a template matching based automated classification tool. These technologies build a solid foundation for future efforts to develop an extended range electro-optical monitoring system suitable for marine energy deployments. In addition to technology development, a key lesson learned is that addressing regulatory and safety requirements must be front and center in any marine energy monitoring applications.

16 TIDAL AND WAVE POWER↗
DOE OSTI2021

Joining Light Metals with Polymer Composites Through Metal Overcasting

This work investigates a unique technique to join aluminum (Al) and magnesium (Mg) alloys to carbon fiber reinforced polymer (CFRP) composites without the use of adhesives or mechanical fasteners. The joints were made using an overcasting technique where the molten alloys were cast around the polymer composites using high pressure die casting method. Rapid cooling during casting allowed the composite to be embedded inside the cast metal without causing any gross damage to the former even though the molten metal temperature exceeded the melting point of the composite matrix by several 100’s of deg. C. The metal/composite interface was examined using optical microscopy and x-ray imaging and the joint strength was examined through tensile testing. Although evidence of polymer melting was evident in the x-ray images, the embedded section of the composite coupons retained their overall shape and integrity. Preliminary tension tests on Al/CFRP composites showed strength degradation of the CFRP and it failed near the metal/CFRP interface (outside the joint). Strength degradation in the CFRP suggests that the overcasting process needs further optimization to minimize thermal excursion in the CFRP. Nevertheless, the overcasting process shows great promise as a unique joining technique with application in fabricating light-weight structures for automotive and transportation industries.

overcasting, Casting, Mg Castings, Al Casting, Joi↗
DOE OSTI2024

Unraveling the Nature of Lasing Emission from Hybrid Silicon Nitride and Colloidal Nanocrystal Photonic Crystals with Low Refractive Index Contrast

Silicon nitride is used for its low optical loss and high thermal stability, making it a suitable platform for visible-light applications in integrated photonic devices. However, its application has been limited due to inefficient light emission, a problem addressed by integrating various types of light emitters onto the platform. In particular, the integration of solution-processable colloidal nanocrystals (NCs) as optical gain materials onto the silicon nitride platform is a promising route but requires a more solid theoretical footing. By leveraging 2D surface-emitting photonic crystal structures combined with NCs, we effectively confine and manipulate light to achieve lasing from green to red. Building on this, we model the light–matter interactions of the low index contrast NC/nitride platform, validated by extensive experimental validations through Fourier imaging techniques, revealing the full photonic band structure and showing clear mode congestion. Finally, these comprehensive studies confirm the potential of hybrid NC-based structures for fully integrated on-chip laser applications and indicate routes for further improvement.

BIC Lasing↗
DOE OSTI2022

A puzzle solved after two decades: SN 2002gh among the brightest of superluminous supernovae

ABSTRACT We present optical photometry and spectroscopy of the superluminous SN 2002gh from maximum light to +204 d, obtained as part of the Carnegie Type II Supernova (CATS) project. SN 2002gh is among the most luminous discovered supernovae ever, yet it remained unnoticed for nearly two decades. Using Dark Energy Camera archival images we identify the potential supernova (SN) host galaxy as a faint dwarf galaxy, presumably having low metallicity, and in an apparent merging process with other nearby dwarf galaxies. We show that SN 2002gh is among the brightest hydrogen-poor SLSNe with MV = −22.40 ± 0.02, with an estimated peak bolometric luminosity of 2.6 ± 0.1 × 1044 erg s−1. We discount the decay of radioactive nickel as the main SN power mechanism, and assuming that the SN is powered by the spin-down of a magnetar we obtain two alternative solutions. The first case, is characterized by significant magnetar power leakage, and Mej between 0.6 and 3.2 M⊙, Pspin = 3.2 ms, and B = 5 × 1013 G. The second case does not require power leakage, resulting in a huge ejecta mass of about 30 M⊙, a fast spin period of Pspin ∼ 1 ms, and B ∼ 1.6 × 1014 G. We estimate a zero-age main-sequence mass between 14 and 25 M⊙ for the first case and of about 135 M⊙ for the second case. The latter case would place the SN progenitor among the most massive stars observed to explode as an SN.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Three-dimensional super line-localization in low signal-to-noise microscope images via prior-apprised unsupervised learning (PAUL)

Biological processes such as processive enzyme turnover and intracellular cargo tracking involve the dynamic motion of a small "article" along a curvilinear biopolymer track. To understand these processes that occur across multiple length and time scales, one must acquire both the trajectory of the particle and the position of the track along which it moves, possibly by combining high-resolution single-particle tracking with conventional microscopy. Yet, usually there is a significant resolution mismatch between these modalities: while the tracked particle is localized with a precision of 10 nm, the image of the surroundings is limited by optical difraction, with 200 nm lateral and 500 nm axial resolutions. Compared to the particle's trajectory, the surrounding curvilinear structure appears as a blurred and noisy image. This disparity in the spatial resolutions of the particle trajectory and the surrounding curvilinear structure image makes data reconstruction, as well as interpretation, particularly challenging. Analysis is further complicated when the curvilinear structures are oriented arbitrarily in 3D space. Here, we present a prior-apprised unsupervised learning (PAUL) approach to extract information from 3D images where the underlying features resemble a curved line such as a filament or microtubule. This three-stage framework starts with a Hessian-based feature enhancement, which is followed by feature registration, where local line segments are detected on repetitively sampled subimage tiles. In the final stage, statistical learning, segments are clustered based on their geometric relationships. Principal curves are then approximated from each segment group via statistical tools including principal component analysis, bootstrap and kernel transformation. This procedure is characterized on simulated images, where sub-voxel medium deviations from true curves have been achieved. The 3D PAUL approach has also been implemented for successful line localization in experimental 3D images of gold nanowires obtained using a multifocal microscope. Lastly, this work not only bridges the resolution gap between two microscopy modalities, but also allows us to conduct 3D super line-localization imaging experiments, without using super-resolution techniques.

42 ENGINEERING↗
DOE OSTI2023

Exploring Mission Design for Imaging Spectroscopy Retrievals for Land and Aquatic Ecosystems

The retrieval algorithms used for optical remote sensing satellite data to estimate Earth's geophysical properties have specific requirements for spatial resolution, temporal revisit, spectral range and resolution, and instrument signal-to-noise ratio (SNR) performance to meet biogeoscience objectives. Studies to estimate surface properties from hyperspectral data use a range of algorithms sensitive to various sources of spectroscopic uncertainty, which are in turn influenced by mission architecture choices. Retrieval algorithms vary across scientific fields and may be more or less sensitive to mission architecture choices that affect spectral, spatial, or temporal resolutions and spectrometer SNR. We used representative remote sensing algorithms across terrestrial and aquatic study domains to inform aspects of mission design that are most important for impacting accuracy in each scientific area. We simulated the propagation of uncertainties in the retrieval process including the effects of different instrument configuration choices. We found that retrieval accuracy and information content degrade consistently at >10 nm spectral resolution, >30 m spatial resolution, and >8-day revisit. In these studies, the noise reduction associated with lower spatial resolution improved accuracy vis à vis high spatial resolution measurements. The interplay between spatial resolution, temporal revisit, and SNR can be quantitatively assessed for imaging spectroscopy missions and used to identify key components of algorithm performance and mission observing criteria.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A Retrospective of Findings From the FORTE Satellite Mission

We revisit the findings from the FORTE satellite program (1997–2004), which collected optical imaging of lightning as well as optical and radio frequency time series waveforms globally from low-earth-orbit. These include surveys of the earth's radio frequency anthropogenic noise environment; earth surface reflectivity at radio frequencies; a scheme for classifying lightning discharge types on the basis of their very high frequency time domain power envelope; insights into the polarization and radiation pattern characteristics of different lightning types, with implications for the underlying discharge processes; and estimates of cloud optical properties based on the statistics of scattered light. Most significantly, FORTE was uniquely suited to capture large samples of data from the rare discharge known as “narrow bipolar events,” enabling detailed examination of their basic characteristics and confirming that they appear to result from fundamentally distinct physical processes compared to other lightning. In particular, despite representing huge charge transfer they evidently produce little-to-no light output.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Euclid I. Overview of the Euclid mission

The current standard model of cosmology successfully describes a variety of measurements, but the nature of its main ingredients, dark matter and dark energy, remains unknown. Euclid is a medium-class mission in the Cosmic Vision 2015–2025 programme of the European Space Agency (ESA) that will provide high-resolution optical imaging, as well as near-infrared imaging and spectroscopy, over about 14 000 deg 2 of extragalactic sky. In addition to accurate weak lensing and clustering measurements that probe structure formation over half of the age of the Universe, its primary probes for cosmology, these exquisite data will enable a wide range of science. This paper provides a high-level overview of the mission, summarising the survey characteristics, the various data-processing steps, and data products. We also highlight the main science objectives and expected performance.

cosmology↗
DOE OSTI2022

Exploring leakage in dielectric films via automated experiments in scanning probe microscopy

Here electronic conduction pathways in dielectric thin films are explored using automated experiments in scanning probe microscopy (SPM). In this study, we use large field of view scanning to identify the position of localized conductive spots and develop an SPM workflow to probe their dynamic behavior at higher spatial resolution as a function of time, voltage, and scanning process in an automated fashion. Using this approach, we observe the variable behaviors of the conductive spots in a 20-nm-thick ferroelectric Hf 0.54 Zr 0.48 O 2 film, where conductive spots disappear and reappear during continuous scanning. There are also fresh conductive spots that develop during scanning. The automated workflow is universal and can be integrated into a wide range of microscopy techniques, including SPM, electron microscopy, optical microscopy, and chemical imaging.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Particle velocity measurement within a free-falling particle curtain using microscopic shadow velocimetry

We report an optical method for particle velocity measurement that is suitable for the measurement of particle velocities within dense particle-laden flows with high spatial resolution. The technique is based on particle shadow velocimetry with the use of a long-distance microscopic lens for images collection. The narrow depth of field of the lens allows particles within the focal plane to have much higher pattern intensities than those outside it on the collected images. Data processing was then employed to remove particles from outside the focal plane based on the gradient of the signal and a threshold. Following this, particle velocity was calculated from two successive images in the usual way. The technique was successfully demonstrated in a free-falling particle curtain with volume fractions in the four-way coupling regime of near-spherical micro-particles falling under gravity. The method was successfully employed to measure the transverse velocity profile through the curtain, which is the first time that such a measurement has been performed. Other highly-fidelity experimental data, which is also well suited to model development and validation, include the particle mass flow rate, curtain thickness and opacity.

Han, Shipu (ORCID:0000000278545882)↗
DOE OSTI2020

Analyzing the Validity of Brazilian Testing Using Digital Image Correlation and Numerical Simulation Techniques

Characterizing the mechanical behavior of rocks plays a crucial role to optimize the fracturing process in unconventional reservoirs. However, due to the intrinsic anisotropy and heterogeneity in unconventional resources, fracture process prediction remains the most significant challenge for sustainable and economic hydrocarbon production. During the deformation tracking under compression, deploying conventional methods (strain gauge, extensometer, etc.) is insufficient to measure the deformation since the physical attachment of the device is restricted to the size of the sample, monitoring limited point-wise deformation, producing difficulties in data retrieval, and a tendency to lose track in failure points, etc. Where conventional methods are limited, the application of digital image correlation (DIC) provides detailed and additional information of strain evolution and fracture patterns under loading. DIC is an image-based optical method that records an object with a camera and monitors the random contrast speckle pattern painted on the facing surface of the specimen. To overcome the existing limitations, this paper presents numerical modeling of Brazilian disc tests under quasi-static conditions to understand the full-field deformation behaviors and finally, it is validated by DIC. As the direct tensile test has limitations in sample preparation and test execution, the Brazilian testing principle is commonly used to evaluate indirectly the tensile strength of rocks. The two-dimensional numerical model was built to predict the stress distribution and full-field deformation on Brazilian disc under compression based on the assumptions of a homogenous, isotropic and linear elastic material. The uniaxial compression test was conducted using the DIC technique to determine the elastic properties of Spider Berea sandstone, which were used as inputs for the simulation model. The model was verified by the analytical solution and compared with the digital image correlation. The numerical simulation results showed that the solutions matched reasonably with the analytical solutions where the maximum deviation of stress distribution was obtained as 14.59%. The strain evolution (normal and shear strains) and displacements along the central horizontal and vertical planes were investigated in three distinguishable percentages of peak loads (20%, 40%, and 90%) to understand the deformation behaviors in rock. The simulation results demonstrated that the strain evolution contours consistently matched with DIC generated contours with a reasonable agreement. The changes in displacement along the central horizontal and vertical planes showed that numerical simulation and DIC generated experimental results were repeatable and matched closely. In terms of validation, Brazilian testing to measure the indirect tensile strength of rocks is still an issue of debate. The numerical model of fracture propagation supported by digital image correlation from this study can be used to explain the fracturing process in the homogeneous material and can be extended to non-homogeneous cases by incorporating heterogeneity, which is essential for rock mechanics field applications.

58 GEOSCIENCES↗
DOE OSTI2026

Development of a coupled experimental–computational approach for engineering optimization of spout-fluidized bed particle coating systems

The design of spout-fluidized bed (SFB) coating systems for nuclear particle fuels typically relies on trial-and-error processes, comprising iterative and time-consuming coating deposition experiments and post-deposition characterization. At an engineering scale, this approach to guided SFB system design is inefficient, highlighting the need for streamlined experimental methodologies which can correlate fluidization conditions to downstream coating outcomes. In this study, we combine time-resolved particle image velocimetry (PIV) with CFD–DEM simulations to benchmark hydrodynamic behavior in a 3D spout-fluidized bed. By exploiting easily accessible optical measurements of particle motion at the bed wall and within the spouting region, we obtain quantitative velocity fields that can be directly compared with model predictions of the occluded bed region, without resorting to complex imaging and characterization techniques such as X-ray or magnetic resonance tomography. Experimental benchmarking reveals strong agreement between CFD–DEM and PIV in the spout and annulus regions, while discrepancies near the wall highlight areas for future model development. Here, the proposed integrated experimental–numerical framework will enable a direct connection between measured variables and numerically predicted fluidization performance of dense, surrogate nuclear particle fuel feedstock such that experimental SFB component design can be rapidly evaluated, informing design decisions for nozzle geometry and operating conditions. Future work will extend this framework by correlating quantified fluidization metrics across nozzle geometries and operating conditions with the resulting coating morphology, microstructure, and uniformity. Establishing these correlations will enable predictive links between hydrodynamic performance and coating quality, providing a rational, scalable basis for optimizing SFB design prior to coating deposition.

CFD/DEM↗