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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Global field reconstruction from sparse sensors with Veronoi tessellation-assisted deep learning

Achieving accurate and robust global situational awareness of a complex time-evolving field from a limited number of sensors has been a longstanding challenge. This reconstruction problem is especially difficult when sensors are sparsely positioned in a seemingly random or unorganized manner, which is often encountered in a range of scientific and engineering problems. Moreover, these sensors can be in motion and can become online or offline over time. The key leverage in addressing this scientific issue is the wealth of data accumulated from the sensors. As a solution to this problem, we propose a data-driven spatial field recovery technique founded on a structured grid-based deep-learning approach for arbitrary positioned sensors of any numbers. It should be noted that the naïve use of machine learning becomes prohibitively expensive for global field reconstruction and is furthermore not adaptable to an arbitrary number of sensors. In the present work, we consider the use of Voronoi tessellation to obtain a structured-grid representation from sensor locations enabling the computationally tractable use of convolutional neural networks. One of the central features of the present method is its compatibility with deep-learning based super-resolution reconstruction techniques for structured sensor data that are established for image processing. The proposed reconstruction technique is demonstrated for unsteady wake flow, geophysical data, and three-dimensional turbulence. The current framework is able to handle an arbitrary number of moving sensors, and thereby overcomes a major limitation with existing reconstruction methods. The presented technique opens a new pathway towards the practical use of neural networks for real-time global field estimation.

Fukami, Kai↗
DOE OSTI2020

A study of shock initiation experiments for the explosive PBX 9502 using three reactive burn models

Shock to detonation transition (SDT) experiments are essential in calibrating and validating reactive burn models for explosives. This work investigates the large collection of SDT test data for the explosive PBX 9502 at ambient temperature that was presented by Gustavsen, Sheffield, and Alcon [Journal of Applied Physics, 99, 114907 (2006)]. We first analyze the experimental data and compare two different methods of determining the shock transition time/distance (namely, the bilinear method and the single-curve method). This reveals some of the uncertainty in estimating shock transition points, which contributes to scatter in Pop-plot data. Next, we compare the WSD, AWSD, and SURFplus reactive burn models for a collection of approximately 20 experimental shots using the FLAG hydrocode. Error estimates are used to quantify how well each reactive burn model (and their respective parameter calibrations) performs at predicting the SDT process for a range of loading conditions. Additionally, the importance of mesh resolution and numerical dissipation in SDT simulations will be assessed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

The mesoscale order of nacreous pearls

A pearl’s distinguished beauty and toughness are attributable to the periodic stacking of aragonite tablets known as nacre. Nacre has naturally occurring mesoscale periodicity that remarkably arises in the absence of discrete translational symmetry. Gleaning the inspiring biomineral design of a pearl requires quantifying its structural coherence and understanding the stochastic processes that influence formation. By characterizing the entire structure of pearls (~3 mm) in a cross-section at high resolution, we show that nacre has medium-range mesoscale periodicity. Self-correcting growth mechanisms actively remedy disorder and topological defects of the tablets and act as a countervailing process to long-range disorder. Nacre has a correlation length of roughly 16 tablets (~5.5 µm) despite persistent fluctuations and topological defects. For longer distances (>25 tablets ~8.5 µm), the frequency spectrum of nacre tablets follows f –1.5 behavior, suggesting that growth is coupled to external stochastic processes—a universality found across disparate natural phenomena, which now includes pearls.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Optimal 1D Ly α forest power spectrum estimation – III. DESI early data

ABSTRACT The 1D power spectrum P1D of the Ly α forest provides important information about cosmological and astrophysical parameters, including constraints on warm dark matter models, the sum of the masses of the three neutrino species, and the thermal state of the intergalactic medium. We present the first measurement of P1D with the quadratic maximum likelihood estimator (QMLE) from the Dark Energy Spectroscopic Instrument (DESI) survey early data sample. This early sample of 54 600 quasars is already comparable in size to the largest previous studies, and we conduct a thorough investigation of numerous instrumental and analysis systematic errors to evaluate their impact on DESI data with QMLE. We demonstrate the excellent performance of the spectroscopic pipeline noise estimation and the impressive accuracy of the spectrograph resolution matrix with 2D image simulations of raw DESI images that we processed with the DESI spectroscopic pipeline. We also study metal line contamination and noise calibration systematics with quasar spectra on the red side of the Ly α emission line. In a companion paper, we present a similar analysis based on the Fast Fourier Transform estimate of the power spectrum. We conclude with a comparison of these two approaches and discuss the key sources of systematic error that we need to address with the upcoming DESI Year 1 analysis.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Opportunities for gas-phase science at short-wavelength free-electron lasers with undulator-based polarization control

Free-electron lasers (FELs) are the world's most brilliant light sources with rapidly evolving technological capabilities in terms of ultrabright and ultrashort pulses over a large range of photon energies. Their revolutionary and innovative developments have opened new fields of science regarding nonlinear light-matter interaction, the investigation of ultrafast processes from specific observer sites, and approaches to imaging matter with atomic resolution. A core aspect of FEL science is the study of isolated and prototypical systems in the gas phase with the possibility of addressing well-defined electronic transitions or particular atomic sites in molecules. Notably for polarization-controlled short-wavelength FELs, the gas phase offers new avenues for investigations of nonlinear and ultrafast phenomena in spin-orientated systems, for decoding the function of the chiral building blocks of life as well as steering reactions and particle emission dynamics in otherwise inaccessible ways. This roadmap comprises descriptions of technological capabilities of facilities worldwide, innovative diagnostics and instrumentation, as well as recent scientific highlights, novel methodology, and mathematical modeling. The experimental and theoretical landscape of using polarization controllable FELs for dichroic light-matter interaction in the gas phase will be discussed and comprehensively outlined to stimulate and strengthen global collaborative efforts of all disciplines. Published by the American Physical Society 2025

Ilchen, Markus↗
DOE OSTI2025

High-count rate effects in event processing for XRISM/ Resolve X-ray microcalorimeter: I. Ground test

The spectroscopic performance of an X-ray microcalorimeter is compromised at high count rates. We utilize the Resolve X-ray microcalorimeter onboard the XRISM satellite to examine the effects observed during high-count rate measurements and propose modeling approaches to mitigate them. We specifically address the following instrumental effects that impact performance: CPU limit, pile-up, and untriggered electrical cross-talk. Experimental data at high count rates were acquired during ground testing using the flight model instrument and a calibration X-ray source. In the experiment, data processing not limited by the performance of the onboard CPU was run in parallel, which cannot be done in orbit. This makes it possible to access the data degradation caused by limited CPU performance. We use these data to develop models that allow for a more accurate estimation of the aforementioned effects. To illustrate the application of these models in observation planning, we present a simulated observation of GX 13+1. Understanding and addressing these issues is crucial to enhancing the reliability and precision of X-ray spectroscopy in situations characterized by elevated count rates.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Comparative Study of Hydrology and Icemelt in Three Nepal River Basins Using the Glacio-Hydrological Degree-Day Model (GDM) and Observations From the Advanced Scatterometer (ASCAT)

An assessment of the water supply and its seasonal and annual changes over the century in the High Mountain Asia (HMA) region is of increasing interest due to its potential impact on one-sixth of the global population. In order to understand the changing hydrology and snow and ice melt, we used remotely sensed Advanced Scatterometer (ASCAT) observations of glacier melt (GM) and a distributed and gridded Glacio-hydrological Degree-day Model (GDM) in three river basins: Tamor, Trishuli and Marsyangdi. The GDM-estimated contribution of snowmelt, icemelt, rainfall and baseflow in river flows is found to be most accurate in the Trishuli River basin, with Nash-Sutcliffe efficiency (NSE) between the estimated and observed discharges of 0.81 and volume differences of -0.5%, and reasonably accurate in the Tamor River basin, with NSE of 0.69 and volume difference of -7.51%. Similarly, NSE of 0.81 and volume difference of 4.64% in Marsyangdi River basin. We find strong similarities in the timing of glacier melting using the GDM and from observations from the ASCAT GM, determining the seasonal start of glacier melting to within 6 days on average. In all basins ASCAT GM observes melting at higher elevations relative to GDM, average of 5,328 m a.s.l. Systematic differences in glacier melting area determined by modeling and satellite observations indicate ASCAT may have suboptimal resolution, view geometry and/or polarimetry for delineating glacier melting at the process-scale in complex topography, especially in the ablation zone. This is the first step in examining the remote sensing products that could potentially be incorporated into hydrologic models to increase the accuracy of the hydrologic flow as well as the ability to estimate river discharge in other basins with limited data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

An Algorithm to Retrieve Total Precipitable Water Vapor in the Atmosphere from FengYun 3D Medium Resolution Spectral Imager 2 (FY-3D MERSI-2) Data

The atmosphere has substantial effects on optical remote sensing imagery of the Earth’s surface from space. These effects come through the functioning of atmospheric particles on the radiometric transfer from the Earth’s surface through the atmosphere to the sensor in space. Precipitable water vapor (PWV), CO 2 , ozone, and aerosol in the atmosphere are very important among the particles through their functioning. This study presented an algorithm to retrieve total PWV from the Chinese second-generation polar-orbiting meteorological satellite FengYun 3D Medium Resolution Spectral Imager 2 (FY-3D MERSI-2) data, which have three near-infrared (NIR) water vapor absorbing channels, i.e., channel 16, 17, and 18. The algorithm was improved from the radiance ratio technique initially developed for Moderate-Resolution Imaging Spectroradiometer (MODIS) data. MODTRAN 5 was used to simulate the process of radiant transfer from the ground surfaces to the sensor at various atmospheric conditions for estimation of the coefficients of ratio technique, which was achieved through statistical regression analysis between the simulated radiance and transmittance values for FY-3D MERSI-2 NIR channels. The algorithm was then constructed as a linear combination of the three-water vapor absorbing channels of FY-3D MERSI-2. Measurements from two ground-based reference datasets were used to validate the algorithm: the sun photometer measurements of Aerosol Robotic Network (AERONET) and the microwave radiometer measurements of Energy’s Atmospheric Radiation Measurement Program (ARMP). The validation results showed that the algorithm performs very well when compared with the ground-based reference datasets. The estimated PWV values come with root mean square error (RMSE) of 0.28 g/cm 2 for the ARMP and 0.26 g/cm 2 for the AERONET datasets, with bias of 0.072 g/cm 2 and 0.096 g/cm 2 for the two reference datasets, respectively. The accuracy of the proposed algorithm revealed a better consistency with ground-based reference datasets. Thus, the proposed algorithm could be used as an alternative to retrieve PWV from FY-3D MERSI-2 data for various remote sensing applications such as agricultural monitoring, climate change, hydrologic cycle, and so on at various regional and global scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Probabilistic projections of the Amery Ice Shelf catchment, Antarctica, under conditions of high ice-shelf basal melt

Abstract. Antarctica's Lambert Glacier drains about one-sixth of the ice from the East Antarctic Ice Sheet and is considered stable due to the strong buttressing provided by the Amery Ice Shelf. While previous projections of the sea-level contribution from this sector of the ice sheet have predicted significant mass loss only with near-complete removal of the ice shelf, the ocean warming necessary for this was deemed unlikely. Recent climate projections through 2300 indicate that sufficient ocean warming is a distinct possibility after 2100. This work explores the impact of parametric uncertainty on projections of the response of the Lambert–Amery system (hereafter “the Amery sector”) to abrupt ocean warming through Bayesian calibration of a perturbed-parameter ice-sheet model ensemble. We address the computational cost of uncertainty quantification for ice-sheet model projections via statistical emulation, which employs surrogate models for fast and inexpensive parameter space exploration while retaining critical features of the high-fidelity simulations. To this end, we build Gaussian process (GP) emulators from simulations of the Amery sector at a medium resolution (4–20 km mesh) using the Model for Prediction Across Scales (MPAS)-Albany Land Ice (MALI) model. We consider six input parameters that control basal friction, ice stiffness, calving, and ice-shelf basal melting. From these, we generate 200 perturbed input parameter initializations using space filling Sobol sampling. For our end-to-end probabilistic modeling workflow, we first train emulators on the simulation ensemble and then calibrate the input parameters using observations of the mass balance, grounding line movement, and calving front movement with priors assigned via expert knowledge. Next, we use MALI to project a subset of simulations to 2300 using ocean and atmosphere forcings from a climate model for both low- and high-greenhouse-gas-emission scenarios. From these simulation outputs, we build multivariate emulators by combining GP regression with principal component dimension reduction to emulate multivariate sea-level contribution time series data from the MALI simulations. We then use these emulators to propagate uncertainty from model input parameters to predictions of glacier mass loss through 2300, demonstrating that the calibrated posterior distributions have both greater mass loss and reduced variance compared to the uncalibrated prior distributions. Parametric uncertainty is large enough through about 2130 that the two projections under different emission scenarios are indistinguishable from one another. However, after rapid ocean warming in the first half of the 22nd century, the projections become statistically distinct within decades. Overall, this study demonstrates an efficient Bayesian calibration and uncertainty propagation workflow for ice-sheet model projections and identifies the potential for large sea-level rise contributions from the Amery sector of the Antarctic Ice Sheet after 2100 under high-greenhouse-gas-emission scenarios.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

High-Fidelity Arc-Discharge Model for Hydrogen-Plasma-Smelting-Reduction of Iron Ore

Electrification and use of renewable hydrogen is currently a necessity for decarbonizing the iron-and-steel industry. In this regard, hydrogen plasma smelting reduction (HPSR) is a novel pathway that is being explored for reduction of iron ore. HPSR provides several decarbonization merits compared to conventional blast furnaces. Firstly, the use of renewable hydrogen drastically reduces the CO2 emissions compared to the use of coke. Secondly, renewable electricity in the form of a thermal plasma for making reactive hydrogen species (radicals, ions) are more efficient at reducing iron ore compared to neutral H2. Thirdly, a molten product compatible with downstream processes is obtained from the intense heat transfer from the plasma. However, the scale-up of this technology requires fundamental exploration of hydrogen plasma dynamics and its interaction with complex solid material that include phase changing iron-ore and slag. In this work, we present a first principles continuum scale model for thermal plasmas in Ar/H2 gas mixtures typically used for HPSR. The thermal plasma governing equations for mass, momentum and energy with Lorentz force and Joule heating source terms are solved along with electromagnetic equations for electrostatic and magnetic vector potential. Our solver will be based on Pele, a suite of reacting flow solvers designed for advanced scientific computing architectures (Henry De Frahan et al., Proceedings of SIAM Parallel Processing, 13-25, 2024), and will utilize adaptive mesh generation for enhanced resolutions at locations of intense physicochemical interactions. This study will present the impact of Ar to H2 ratios on excited/dissociated hydrogen species concentrations, plasma temperature and conductivity along with the impact of outgassed species (water, metal vapor, O, OH radicals) from ore surface on gas phase chemistry. Furthermore, the heat and species flux to the surface will be quantified as a function of applied voltages in a transferred arc configuration.

hydrogen plasma↗
DOE OSTI2024

Spatial Proteomics towards cellular Resolution

Introduction: Spatial biology is an emerging interdisciplinary field facilitating biological discoveries through the use of spatial omics technologies. Recent advancements in spatial transcriptomics, spatial genomics (e.g. genetic mutations and epigenetic marks), multiplexed immunofluorescence, and spatial metabolomics/lipidomics have enabled high-resolution spatial profiling of gene expression, genetic variation, protein expression, and metabolites/lipids profiles in tissue. These developments contribute to a deeper understanding of the spatial organization within tissue microenvironments at the molecular level. Areas covered: This report provides an overview of the untargeted, bottom-up mass spectrometry (MS)-based spatial proteomics workflow. It highlights recent progress in tissue dissection, sample processing, bioinformatics, and liquid chromatography (LC)-MS technologies that are advancing spatial proteomics toward cellular resolution. Expert opinion: The field of untargeted MS-based spatial proteomics is rapidly evolving and holds great promise. To fully realize the potential of spatial proteomics, it is critical to advance data analysis and develop automated and intelligent tissue dissection at the cellular or subcellular level, along with high-throughput LC-MS analyses of thousands of samples. In conclusion, achieving these goals will necessitate significant advancements in tissue dissection technologies, LC-MS instrumentation, and computational tools.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Desmearing Bonse–Hart USANS data using Bayesian Gaussian process regression

Ultra-small-angle neutron scattering (USANS) enables access to micrometer-scale structures but is intrinsically affected by strong, anisotropic resolution smearing arising from slit-geometry optics. As a result, recovery of the intrinsic scattering intensity constitutes an ill-posed inverse problem, and commonly used iterative desmearing methods lack rigorous uncertainty quantification. We present a Bayesian desmearing framework for slit-geometry USANS based on Gaussian process regression. In this approach, the scattering intensity is modeled as a smooth random function, and the instrumental point spread function is incorporated explicitly as a forward operator. The resulting formulation yields a closed-form maximum a posteriori solution with well-defined credibility intervals. Computational benchmarks and experimental validation using combined USANS and small-angle neutron scattering (SANS) measurements demonstrate that the framework enables stable desmearing, suppresses experimental noise, and preserves physically meaningful structural features under realistic conditions.

Tung, Chi-Huan [Oak Ridge National Laboratory (ORN↗
DOE OSTI2020

Using Community Science to Reveal the Global Chemogeography of River Metabolomes

River corridor metabolomes reflect organic matter (OM) processing that drives aquatic biogeochemical cycles. Recent work highlights the power of ultrahigh-resolution mass spectrometry for understanding metabolome composition and river corridor metabolism. However, there have been no studies on the global chemogeography of surface water and sediment metabolomes using ultrahigh-resolution techniques. Here, we describe a community science effort from the Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS) consortium to characterize global metabolomes in surface water and sediment that span multiple stream orders and biomes. We describe the distribution of key aspects of metabolomes including elemental groups, chemical classes, indices, and inferred biochemical transformations. We show that metabolomes significantly differ across surface water and sediment and that surface water metabolomes are more rich and variable. We also use inferred biochemical transformations to identify core metabolic processes shared among surface water and sediment. Finally, we observe significant spatial variation in sediment metabolites between rivers in the eastern and western portions of the contiguous United States. Our work not only provides a basis for understanding global patterns in river corridor biogeochemical cycles but also demonstrates that community science endeavors can enable global research projects that are unfeasible with traditional research models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Change Detection Applications in the Earth Sciences Using UAS-Based Sensing: A Review and Future Opportunities

Over the past decade, advancements in collection platforms such as unoccupied aerial systems (UAS), survey-grade GNSS, sensor packages, processing software, and spatial analytical tools have facilitated change detection analyses at an unprecedented resolution over broader spatial and temporal extents and in environments where such investigations present challenges. These technological improvements, coupled with the accessibility and versatility of UAS technology, have pushed the boundaries of spatial and temporal scales in geomorphic change detection. As a result, the cm-scale analysis of topographic signatures can detect and quantify surface anomalies during geomorphic evolution. This review focuses on the use of UAS photogrammetry for fine spatial (cm) and temporal (hours to days) scale geomorphic analyses, and it highlights analytical approaches to detect and quantify surface processes that were previously elusive. The review provides insight into topographic change characterization with precise spatial validations applied to landscape processes in various fields, such as the cryosphere and geosphere, as well as anthropogenic earth processes and national security applications. This work sheds light on previously unexplored aspects of both natural and human-engineered environments, demonstrating the potential of UAS observations in change detection. Our discussion examines the emerging horizons of UAS-based change detection, including machine learning and LIDAR systems. In addition, our meta-analysis of spatial and temporal UAS-based observations highlights the new fine-scale niche of UAS-photogrammetry. This scale advancement sets a new frontier in change detection, offering exciting possibilities for the future of land surface analysis and environmental monitoring in the field of Earth Science.

Andresen, Christian G.↗
DOE OSTI2024

Molecular-Resolution Electron Imaging of Defects and Dynamics at the Ice-Water Interface

Water crystallization into hexagonal ice (type I h ) is one of the most critical processes relevant to the Earth’s environment and human activities. However, despite recent breakthroughs in imaging non-equilibrium condensed ice structures, the ice-water interface has never been imaged at a molecular resolution. This is primarily due to the low stability of the hydrogen bonds in ice under high-resolution microscopy conditions and a lack of methods to prepare compatible samples. Here, this presentation describes the first molecular-resolution imaging of ice crystallized from liquid water and the ice-water interface using high-resolution transmission electron microscopy (HRTEM). By encapsulating deionized (DI) water between two amorphous carbon (a-C) TEM grids and subsequently freezing it with liquid N 2 on a cryo sample stage, we generated two types of ice: non-equilibrium, condensed ice from the atmosphere and encapsulated ice from the DI water (Fig. 1A). Condensed ice usually shows irregular, spherulitic shapes (Fig. 1B). Selected area electron diffraction (SAED) shows that they are a mixture of cubic and hexagonal crystals (Fig. 1C). On the contrary, encapsulated ice forms thin films that contain large-area single-crystalline regions of hexagonal ice oriented along the [0001] zone axis (Fig. 1D). Differential electron energy-loss spectroscopy (EELS) confirmed the high purity of the encapsulated ice free from organic contaminations that are common in other encapsulation methods for HRTEM such as graphene liquid cells. These single-crystalline areas are robust under the electron beam up to ~100 e/Å 2 s. Aberration-corrected HRTEM imaging in these areas achieved a line resolution of ~1.3 Å (Fig. 1E and F). This platform allows us to study near-equilibrium ice structures and dynamics at an unprecedented spatial resolution (Fig. 2). For example, we discovered subdomain-rich regions near the defective crystal edges despite the structure appearing single-crystalline according to diffraction criteria. These subdomains connect via low-angle grain boundaries with flat energy landscapes as a function of tilt angles (according to simulations), showing the high tolerance of ice to defect structures. When we tuned the sample temperature and electron flux rate, we observed radiolysis-controlled bubble generation and dissolution in ice single crystals near a steady state of bubble dynamics. Furthermore, rich beam-induced melting and recrystallization dynamics were observed at the ice-water interface with lattice resolution. These data represent the first observation of the ice-water phase transformation at the sub-nanometer level. In summary, the methods developed in this work enabled molecular-resolution observations of ice and the ice-water interface and shed light on the microstructures and phase transformation pathways. Finer control on the temperature, electron irradiation profile, and imaging detector could eventually lead to real-time observation of ice nucleation in water and address long-standing questions in the nucleation pathways.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Investigating Porous Media for Relief Printing Using Micro-Architected Materials

Advances in printed electronics are predicated on the integration of sophisticated printing technologies with functional materials. Although scalable manufacturing methods, such as letterpress and flexographic printing, have significant history in graphic arts printing, functional applications require sophisticated control and understanding of nanoscale transfer of fluid inks. In this paper, a versatile platform is introduced to study and engineer printing forms, exploiting a microscale additive manufacturing process to design micro-architected materials with controllable porosity and deformation. Building on this technology, controlled ink transfer for submicron functional films is demonstrated. The design freedom and high-resolution 3D control afforded by this method provide a rich framework for studying mechanics of fluid transfer for advanced manufacturing processes.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Thermal History of Matrix Forsterite Grains from Murchison Based on High-resolution Tomography

Protoplanetary disks are dust- and gas-rich structures surrounding protostars. Depending on the distance from the protostar, this dust is thermally processed to different degrees and accreted to form bodies of varying chemical compositions. The primordial accretion processes occurring in the early protoplanetary disk such as chondrule formation and metal segregation are not well understood. One way to constrain them is to study the morphology and composition of forsteritic grains from the matrix of carbonaceous chondrites. Here, we present high-resolution ptychographic X-ray nanotomography and multimodal chemical microtomography (X-ray diffraction and X-ray fluorescence) to reveal the early history of forsteritic grains extracted from the matrix of the Murchison CM2.5 chondrite. Here,. the 3D electron density maps revealed, at unprecedented resolution (64 nm), spherical inclusions containing Fe–Ni, very little silica-rich glass and void caps (i.e., volumes where the electron density is consistent with conditions close to vacuum) trapped in forsterite. The presence of the voids along with the overall composition, petrological textures, and shrinkage calculations is consistent with the grains experiencing one or more heating events with peak temperatures close to the melting point of forsterite (~2100 K), and subsequently cooled and contracted, in agreement with chondrule-forming conditions.

58 GEOSCIENCES↗
DOE OSTI2024

Development of Miniaturized High-Temperature Multi-Process Monitoring System

The main objective of this research program is to design, manufacture, and demonstrate a miniaturized, multi-process, monitoring system (mMPMS) for boiler condition management and easy system deployment to obtain a higher spatial resolution. This system will facilitate a Condition-Based Maintenance (CBM) philosophy that actively monitors the health of assets to predict and prevent failures and maximize availability and generating capacity at a reduced cost. CBM systems can provide boiler data that the advanced process control (APC) system can utilize for plant performance optimization, which is increasingly relevant as coal power plants shift from predominantly base-load operation to predominantly transient operation involving large load swings.

20 FOSSIL-FUELED POWER PLANTS↗