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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Topological Antiferromagnetic Van der Waals Phase in Topological Insulator/Ferromagnet Heterostructures Synthesized by a CMOS-Compatible Sputtering Technique

Breaking time-reversal symmetry by introducing magnetic order, thereby opening a gap in the topological surface state bands, is essential for realizing useful topological properties such as the quantum anomalous Hall and axion insulator states. In this work, a novel topological antiferromagnetic (AFM) phase is created at the interface of a sputtered, c-axis-oriented, topological insulator/ferromagnet heterostructure—Bi 2 Te 3 /Ni 80 Fe 20 because of diffusion of Ni in Bi 2 Te 3 (Ni-Bi 2 Te 3 ). The AFM property of the Ni-Bi2Te3 interfacial layer is established by observation of spontaneous exchange bias in the magnetic hysteresis loop and compensated moments in the depth profile of the magnetization using polarized neutron reflectometry. Analysis of the structural and chemical properties of the Ni-Bi2Te3 layer is carried out using selected-area electron diffraction, electron energy loss spectroscopy, and X-ray photoelectron spectroscopy. These studies, in parallel with first-principles calculations, indicate a solid-state chemical reaction that leads to the formation of Ni=Te bonds and the presence of topological antiferromagnetic (AFM) compound NiBi 2 Te 4 in the Ni-Bi 2 Te 3 interface layer. The Neél temperature of the Ni-Bi 2 Te 3 layer is ≈ 63 K, which is higher than that of typical magnetic topological insulators (MTIs). The presented results provide a pathway toward industrial complementary metal-oxide-semiconductor (CMOS)-process-compatible sputtered-MTI heterostructures, leading to novel materials for topological quantum devices.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Evaluating the Benefits of Bayesian Hierarchical Methods for Analyzing Heterogeneous Environmental Datasets: A Case Study of Marine Organic Carbon Fluxes

Large compilations of heterogeneous environmental observations are increasingly available as public databases, allowing researchers to test hypotheses across datasets. Statistical complexities arise when analyzing compiled data due to unbalanced spatial sampling, variable environmental context, mixed measurement techniques, and other reasons. Hierarchical Bayesian modeling is increasingly used in environmental science to describe these complexities, however few studies explicitly compare the utility of hierarchical Bayesian models to simpler and more commonly applied methods. Here we demonstrate the utility of the hierarchical Bayesian approach with application to a large compiled environmental dataset consisting of 5,741 marine vertical organic carbon flux observations from 407 sampling locations spanning eight biomes across the global ocean. We fit a global scale Bayesian hierarchical model that describes the vertical profile of organic carbon flux with depth. Profile parameters within a particular biome are assumed to share a common deviation from the global mean profile. Individual station-level parameters are then modeled as deviations from the common biome-level profile. The hierarchical approach is shown to have several benefits over simpler and more common data aggregation methods. First, the hierarchical approach avoids statistical complexities introduced due to unbalanced sampling and allows for flexible incorporation of spatial heterogeneitites in model parameters. Second, the hierarchical approach uses the whole dataset simultaneously to fit the model parameters which shares information across datasets and reduces the uncertainty up to 95% in individual profiles. Third, the Bayesian approach incorporates prior scientific information about model parameters; for example, the non-negativity of chemical concentrations or mass-balance, which we apply here. We explicitly quantify each of these properties in turn. We emphasize the generality of the hierarchical Bayesian approach for diverse environmental applications and its increasing feasibility for large datasets due to recent developments in Markov Chain Monte Carlo algorithms and easy-to-use high-level software implementations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Linear Reciprocating Tribometer for In Situ Neutron Reflectometry of Soft Matter

Neutron reflectometry is a technique for measuring structure near planar interfaces that has been previously used to non-destructively characterize the polymer density of hydrated, dilute, and soft materials. Previous investigations have conducted neutron reflectometry measurements of liquids, gels, emulsion, and polymer solutions at rest, in compression, and subject to shear stress. However, correlating structure with tribological properties of soft materials presents significant experimental challenges for prior instruments due to wall slip, sample thickness, and structural heterogeneity (e.g., depth-wise gradients). A linear reciprocating tribometer offers several advantages for in situ neutron reflectometry studies, including uniform velocity profiles, constant shear stress over large regions of interest, and independent control of normal force and sliding velocity during measurements. This work outlines basic considerations for the design of a custom linear reciprocating tribometer that operates in a neutron beamline and includes commissioning measurements. The tribometer is designed to compress soft and hydrated materials against linearly reciprocating silicon disks. The three key design considerations for this tribometer are (1) safety, (2) neutron transmission, and (3) sample positioning. This instrument design will enable in situ studies of soft matter and illuminate the role of interfacial structure on tribological phenomena.

42 ENGINEERING↗
DOE OSTI2025

On the Relationship Between Methane Production in Anaerobic Incubations of Peat Material and In Situ Methane Emissions

Anaerobic incubations of peat have been widely used to explore soil processes, but this in vitro technique raises many questions as to how well it reproduces in situ conditions. To investigate this, we conducted 60–100 days (+25 days pre‐incubation) anaerobic, temperature‐controlled incubation experiments across a temperature range of 1–26°C on samples from bog and fen habitats, at two different depths (9–19 and 25–35 cm). Here, we observed exponential increases in CO 2 and methane production with temperature in all conditions. We then compared field‐based measurements of methane emission with modeled expectations by extrapolating incubation‐determined methane production rates based on (a) soil temperature profiles, (b) the observed incubation temperature‐methane production relationship, and (c) seasonal thaw depth from each site. The resulting incubation‐extrapolated methane production agreed with measured emission rates within a factor of two at both sites and corresponded to 182 ± 54% and 59 ± 14% of the measured average yearly fluxes from the field for the bog and fen, respectively. The underestimation of fen methane fluxes may be due to the lack of living plant root‐derived dissolved organic carbon inputs in incubations, a key process in fens. Conversely, the overestimation in bogs could be attributed to methane oxidation in the field, which is absent in anaerobic incubation conditions. Nonetheless incubations predicted greenhouse gas emissions from a northern peatland within a factor of two.

Biological and medical sciences,Geosciences,Enviro↗
DOE OSTI2023

Measurement of a radial flow profile with eddy current flow meters and deep neural networks

Eddy current flow meters (ECFMs) measure flows of conductive fluids. Recent interest in ECFMs has increased due to applications in advanced nuclear reactors. ECFMs are well suited for such applications, as they can provide non-invasive measurements of flow in fluids that are often difficult to measure. Traditionally, ECFMs are operated using an alternating current at a single frequency, limiting ECFMs to measure average fluid velocities, blockages, or voids. Here, we expand the capabilities of ECFMs by measuring the fluid radial velocity profile of liquid mercury. To accomplish this, we made several ECFM sensitivity measurements at a range of frequencies. Different frequencies vary the electromagnetic skin depth of the device. By adjusting frequencies, we probed the fluid velocity at various radial locations and constructed a flow-velocity profile. The relationship between the ECFM measurements and velocity profile is nonlinear and requires solving an inverse problem. Using electromagnetic finite-element simulations to train a deep neural network (DNN), we created a model that provides a stable general relationship between the sensitivity measurements of an ECFM and the fluid velocity profile. Using ECFM measurements of liquid mercury, our DNN model calculates a flow profile that agrees well with computational fluid dynamics (CFD) simulations. This technique has potential to improve flow monitoring for optimization, safe operation of conductive fluid loops, and/or validating complex CFD models.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Constraints on Metastable Helium in the Atmospheres of WASP-69b and WASP-52b with Ultranarrowband Photometry

Infrared observations of metastable 2{sup 3}S helium absorption with ground- and space-based spectroscopy are rapidly maturing, as this species is a unique probe of exoplanet atmospheres. Specifically, the transit depth in the triplet feature (with vacuum wavelengths near 1083.3 nm) can be used to constrain the temperature and mass-loss rate of an exoplanet’s upper atmosphere. Here, we present a new photometric technique to measure metastable 2{sup 3}S helium absorption using an ultranarrowband filter (FWHM 0.635 nm) coupled to a beam-shaping diffuser installed in the Wide-field Infrared Camera on the 200 inch Hale Telescope at Palomar Observatory. We use telluric OH lines and a helium arc lamp to characterize refractive effects through the filter and to confirm our understanding of the filter transmission profile. We benchmark our new technique by observing a transit of WASP-69b and detect an excess absorption of 0.498% ± 0.045% (11.1σ), consistent with previous measurements after considering our bandpass. We then use this method to study the inflated gas giant WASP-52b and place a 95th percentile upper limit on excess absorption in our helium bandpass of 0.47%. Using an atmospheric escape model, we constrain the mass-loss rate for WASP-69b to be 5.25{sub −0.46}{sup +0.65}×10{sup −4} M{sub J} Gyr{sup −1} (3.32{sub −0.56}{sup +0.67}×10{sup −3} M{sub J} Gyr{sup −1}) at 7000 K (12,000 K). Additionally, we set an upper limit on the mass-loss rate of WASP-52b at these temperatures of 2.1×10{sup −4} M{sub J} Gyr{sup −1} (2.1×10{sup −3} M{sub J} Gyr{sup −1}). These results show that ultranarrowband photometry can reliably quantify absorption in the metastable helium feature.

79 ASTRONOMY AND ASTROPHYSICS↗
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 OSTI2022

Inverse metal-assisted chemical etching of germanium with gold and hydrogen peroxide

Abstract Metal-assisted chemical etching (MACE) is a flexible technique for texturing the surface of semiconductors. In this work, we study the spatial variation of the etch profile, the effect of angular orientation relative to the crystallographic planes, and the effect of doping type. We employ gold in direct contact with germanium as the metal catalyst, and dilute hydrogen peroxide solution as the chemical etchant. With this catalyst-etchant combination, we observe inverse-MACE, where the area directly under gold is not etched, but the neighboring, exposed germanium experiences enhanced etching. This enhancement in etching decays exponentially with the lateral distance from the gold structure. An empirical formula for the gold-enhanced etching depth as a function of lateral distance from the edge of the gold film is extracted from the experimentally measured etch profiles. The lateral range of enhanced etching is approximately 10–20 μ m and is independent of etchant concentration. At length scales beyond a few microns, the etching enhancement is independent of the orientation with respect to the germanium crystallographic planes. The etch rate as a function of etchant concentration follows a power law with exponent smaller than 1. The observed etch rates and profiles are independent of whether the germanium substrate is n-type, p-type, or nearly intrinsic.

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

Photothermal Atomic Force Microscopy Coupled with Infrared Spectroscopy (AFM-IR) Analysis of High Extinction Coefficient Materials: A Case Study with Silica and Silicate Glasses

Photothermal atomic force microscopy coupled with infrared spectroscopy (AFM-IR) brings significant value as a spatially resolved surface analysis technique for disordered oxide materials such as glasses, but additional development and fundamental understanding of governing principles is needed to interpret AFM-IR spectra, since the existing theory described for organic materials does not work for materials with high extinction coefficients for infrared (IR) absorption. This paper describes theoretical calculation of a transient temperature profile inside the IR-absorbing material considering IR refraction at the interface as well as IR adsorption and heat transfer inside the sample. Furthermore, this calculation explains the differences in peak positions and amplitudes of AFM-IR spectra from those of specular reflectance and extinction coefficient spectra. It also addresses the information depth of the AFM-IR characterization of bulk materials. AFM-IR applied to silica and silicate glass surfaces has demonstrated novel capability of characterizing subsurface structural changes and surface heterogeneity due to mechanical stresses from physical contacts, as well as chemical alterations manifested in surface layers through aqueous corrosion.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Multicriteria-Based Selection of Microalgae Biorefineries: Biomass Composition Defines the Most Suitable Product Portfolios

The supply of microalgae-derived biofuels and bioproducts will be vital in a global-scale bioeconomy. As the diversity of microalgae strains and their compositional plasticity may yield a wide array of products of market interest, the design of effective biorefineries is a central aspect in the path to making microalgae-based products available in the market. In this way, the conversion of microalgae biomass should be planned to employ mature technologies, while maximizing economic and environmental benefits obtained from a diverse product portfolio. This study applied sequential, hybrid Multicriteria Decision Analyses (MCDA) to aid the decision-making process of outlining the most suitable biorefining pathways for specific compositional profiles. For this, the methodology simultaneously considered multiple technical, economic, and environmental criteria, such as market aspects for the main algae-derived products, potential reduction in greenhouse gas (GHG) emissions provided by the biobased alternatives, and technology readiness level of conversion routes, among others. The framework was tested using productivity and compositional data for 13 high-productivity summer strains cultivated under varying nutrient availability. The analysis pointed to compositional profile being a key driver in defining the core biorefining strategy of algae biomass, with lipid-to-carbohydrate ratios higher than roughly 1 warranting the preferential processing of lipids into hydrocarbon fuels with the remainder of the algae biomass compounds being sent to higher-value applications, such as carboxylic acids and renewable thermoplastic substitutes. An in-depth process simulation, techno-economic assessment (TEA), and life-cycle analysis (LCA) effort was carried out as a closing step to corroborate the results stemming from the proposed framework. This study validates the use of MCDAs as a screening method prior to implementing more time-consuming analysis techniques and makes a compelling case for this approach as a product selection tool on a wide range of algae species, thus helping establish species-agnostic (but composition-driven) biorefineries.

biofuels↗
DOE OSTI2024

Accelerating Multivariate Functional Approximation Computation with Domain Decomposition Techniques⋆

Modeling large datasets through Multivariate Functional Approximations (MFA) provide an elegant way to handle many visualization and scientific analysis workflows. The process necessitates scalable data partitioning methods to compute MFA representations efficiently without compromising the accuracy or continuity of the reconstructed solution. We propose a domain -decomposed method for computing the MFA with B -spline bases, which reduces the total work per task and uses a restricted Additive Schwarz (RAS) method to converge the control point data degrees -of -freedom along subdomain boundaries. We provide an in-depth analysis of the parallel approach with domain decomposition solvers, aiming to minimize local subdomain error residuals and recover high -order continuity at subdomain interfaces with appropriate choices of knot overlaps. The communication cost, determined by the overlap regions in the RAS implementation, is optimized to recover the numerical error profile of the single subdomain case. Our proposed method stands in contrast to previous methods, which typically only recover either C 0 or at best C 1 continuity for arbitrary B -spline degree expansions, or those that require post -processing to blend discontinuities in the reconstructed data. We demonstrate the effectiveness of our approach using analytical and real -world datasets in 1D, 2D, and 3D through both strong and weak scaling studies. The performance results indicate that the overall cost of computing the approximation is directly proportional to the underlying nearest -neighbor communication implementation, and is only weakly dependent on the overlap region size that determines the size of the messages. This finding underscores the efficiency and scalability of our proposed method, making it a promising solution for handling large datasets in scientific workflows.

additive Schwarz solvers↗
DOE OSTI2020

Extracting band edge profiles at semiconductor heterostructures from hard-x-ray core-level photoelectron spectra

Hard-x-ray photoelectron spectroscopy (HAXPES) is a valuable source of information on band-edge profiles deep inside semiconductor thin films and heterojunctions. However, extracting this information requires robust and physically meaningful decomposition of spectra into contributions from individual atomic planes. We present an approach that utilizes the physical requirements of a monotonic dependence of the built-in electrostatic potential on depth and continuity of the potential function and its derivatives. These constraints enable efficient extraction of band-edge profiles and allow one to capture details of the electronic structure, including determination of the signs and magnitudes of the band bending as well as the valence band offsets. The utility of this approach to generate quantitative insight into the electronic structure of complex materials is illustrated for epitaxial SrTiO 3 on intrinsic Si(001).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

AlCl 3 -Dosed Si(100)-2 × 1: Adsorbates, Chlorinated Al Chains, and Incorporated Al

The adsorption of AlCl 3 on Si(100) and the effect of annealing the AlCl 3 -dosed substrate were studied to reveal key surface processes for the development of atomic-precision, acceptor-doping techniques. This investigation was performed via scanning tunneling microscopy (STM), X-ray photoelectron spectroscopy (XPS), and density functional theory (DFT) calculations. At room temperature, AlCl 3 readily adsorbed to the Si substrate dimers and dissociated to form a variety of species. Annealing the AlCl 3 -dosed substrate at temperatures below 450 °C produced unique chlorinated aluminum chains (CACs) elongated along the Si(100) dimer row direction. An atomic model for the chains is proposed with supporting DFT calculations. Al was incorporated into the Si substrate upon annealing at 450 °C and above, and Cl desorption was observed for temperatures beyond 450 °C. Al-incorporated samples were encapsulated in Si and characterized by secondary ion mass spectrometry (SIMS) depth profiling to quantify the Al atom concentration, which was found to be in excess of 10 20 cm –3 across a ~2.7 nm-thick δ-doped region. Here, the Al concentration achieved here and the processing parameters utilized promote AlCl 3 as a viable gaseous precursor for novel acceptor-doped Si materials and devices for quantum computing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

High-Resolution Thermal Profiling of a High-Power Diode Laser Facet During Aging

Here, we study the facet temperature distribution of a high-power diode laser over its lifetime using a noncontact, high spatial resolution CCD-based thermoreflectance technique. Based on the known correlation between non-radiative defects and heating, thermal maps can provide valuable information regarding the formation and evolution of small point defects that are at or near the facet during aging. In the laser under study in this work we measure the appearance of local hot spots on the facet, including concentrated hot spots that appear just before or just after COD and are correlated with loss of local light emission. The locations of these hot spots do not exhibit morphology changes in high-resolution SEM imaging of the facet, indicating that the related defects are too small to be observable in SEM or are located at some depth under the facet. Prior to COD, we measure a gradual facet temperature increase accompanied by a gradual optical power decrease and gradual facet optical absorption increase, indicating gradual degradation of the laser.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Mass spectral molecular mapping shows benefits of thermal evaporation in prelithiated silicon-based electrodes

Silicon based composites have become increasingly popular as potential anodes for lithium-ion batteries due to their large storage capacity and potential ability to generate batteries with energy densities greater than 350 Wh kg −1 . These anodes often see reduced initial columbic efficiency (ICE) due to disruptive volume expansionup to 300% and continuous solid electrolyte interphase (SEI) layer formation. Prelithiation, where an excess reservoir of Li is added to the electrode to compensate for irreversible SEI formation losses during their sample preparation, has proven to solve the issue of immediate capacity loss. Thermal evaporation is a prelithiation technique with limited studies on its effectiveness. In this study, time-of-flight secondary ion mass spectrometry (ToF-SIMS) is used to highlight the benefits of prelithiation via thermal evaporation. ToF-SIMS provides chemical mapping and spatial information in 2D and 3D visualizing the deposition of lithium, identifying Li x Si y alloy and Li x Si y O z silicate formation, and the distribution of lithium passivation into the electrodes. Passivation under different atmospheric conditions, such as inert Argon (Ar) and Ar/ carbon dioxide (CO 2 ), highlights the impact of the environment on the passivation effectiveness and formation of Li x Si y alloy and Li x Si y O z silicate. The ToF-SIMS molecular imaging and depth profiling results indicate that prelithiation via thermal evaporation effectively distributes lithium throughout the depth profile thickness of several hundred nanometers. It induces a greater degree of Li x Si y O z silicate formation over Li x Si y alloy. Our ToF-SIMS characterization results show the effectiveness of thermal evaporation in producing a more stable electrode and an electrode with an effective lithium reserve that can preserve its capacity.

Parker, Gabriel D. [Oak Ridge National Laboratory ↗
DOE OSTI2023

How deep should we go to understand roots at the top of the world?

Harsh environmental conditions and the short summers of northern, high-latitude biomes impose unique constraints on the plants that live in the arctic tundra and the boreal forest. To escape the harsh aboveground environment, plants in these habitats often allocate a large portion of their biomass belowground to facilitate nutrient acquisition. In turn, the proximity of living plant roots to vast stores of sequestered soil carbon in these biomes means that shifts in rooting depth distribution and the size of the root–soil interface could significantly contribute to ongoing climate change. Indeed, plant ‘priming’ of rhizosphere decomposition via root exudation, particularly from shallowly distributed roots, can lead to losses of carbon from tundra soils. While we have a hard-won understanding of the distribution of plant communities across the arctic tundra and the boreal forest from direct field observations scaled to the landscape level using climate-informed mapping techniques (i.e. the Circumpolar Arctic Vegetation Map (CAVM); Walker et al. , 2005), these vegetation maps are only the tip of the iceberg (Iversen et al. , 2015). Root form and function remain hidden beneath the land surface. In an article recently published in New Phytologist , Blume-Werry et al. (2023, 10.1111/nph.18998) asked whether rooting depth distribution, and ensuing carbon emissions, could be inferred from commonly used vegetation mapping classifications across the pan-Arctic. An important question to guide our understanding, mapping, and prediction of belowground characteristics and ecosystem feedbacks at the top of the world. Unfortunately, they found that the answer was ‘not quite’. While rooting depth distribution varied demonstrably, in turn causing substantial changes in modeled carbon emissions via rhizosphere ‘priming’, variation across rooting depth profiles did not correspond with vegetation mapping classes. If we are unable to predict belowground rooting depth distributions across large spatial scales by leveraging aboveground vegetation community distributions, how then should belowground researchers proceed?

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Physics-Informed and Data-Driven Prediction of Residual Stress in Three-Dimensional Machining

Efficient and reliable prediction of machining-induced residual stress (RS) is a key requirement for truly integrated computational materials engineering (ICME). Currently available process modeling approaches, including empirical, analytical, and numerical methodologies lack predictive power and require substantial calibration and validation data. Moreover, most model-based approaches consider only two-dimensional (2D) (i.e., orthogonal), cutting processes. Meanwhile, industrial processes such as milling, turning, and drilling are inherently three-dimensional (3D). The present work attempts to bridge the gap between 2D and 3D through careful consideration of the process physics, including geometric, kinematic, and size-effect constraints to realize robust prediction of how RS develops in 3D machining. Using a novel in-situ experimental technique and digital image correlation (DIC) to determine equivalent Hertzian contact widths, contact pressures, and friction coefficients, the proposed methodology leverages a discretized conversion algorithm that includes multi-pass shakedown effects. This paper presents a semi-analytical model to predict machining-induced RS in 3D turning operations, which are used representatively for 3D processes more generally. Rather than follow a ‘brute force’ 3D FEM approach or conduct countless experiments to train a purely data-driven machine learning algorithm, the proposed approach builds on previous 2D modeling work. Through careful consideration of the process physics, including complex geometry/kinematic considerations of 3D turning, the authors demonstrated an experimentally calibrated approach, as well as validation based on published RS data. Model predictions and previously published measurement data of RS depth profiles for turning of Inconel 718 were compared for a range of process parameters. Correlation between the proposed 3D model and validation data was found to be within the margin of experimental error for most conditions. The proposed model appears to capture the overall behavior of 3D RS depth profiles with acceptable accuracy, particularly the key metrics of near-surface stress, peak stress magnitude and location, as well as overall stress profile depth. This report presents a physics-informed, data-driven approach for efficient calibration of a 2D model for machining-induced RS through DIC analysis of in-situ characterized subsurface displacement fields.

42 ENGINEERING↗
DOE OSTI2021

Exploring the Effects of Piston Bowl Geometry and Injector Included Angle on Dual-Fuel and Single-Fuel RCCI

Abstract Reactivity control compression ignition (RCCI) is a low-temperature combustion technique that has been proposed to meet the current demand for high thermal efficiency and low engine-out emissions. However, its requirement of two separate fuel systems (i.e., a low-reactivity fuel system and a high-reactivity fuel system) has been one of its major challenges in the last decade. This leads to the single-fuel RCCI concept, where the secondary fuel (reformates of diesel) is generated from the primary fuel (diesel) through catalytic partial oxidation reformation. Following the in-depth analysis of the reformate fuel (reformates of diesel) and its benefit as the low-reactivity fuel with diesel, the effects of the start of injection (SOI) timing of diesel and the energy-based blend ratio were also studied in detail. In this study, the effects of piston profile and the injector included angles were experimentally examined using both conventional fuel pairs (gasoline—diesel and natural gas—diesel) and reformate RCCI. A validated computational fluid dynamics (CFD) model was also used for a better understanding of the experimental trends. Comparing a reentrant bowl piston with a shallow bowl piston at a constant compression ratio and SOI, the latter showed better thermal efficiency, regardless of the fuel combination, due to its 10% lower surface area for the heat transfer. Comparing the 150-degree included angle and 60-degree included angle on the shallow bowl piston, the latter showed better combustion efficiency, regardless of the fuel combination, due to its earlier combustion phasing (at constant SOI timing). The effect was particularly prominent on reformate RCCI because of its incredibly high diluent concentration, which retards the combustion further for the 150-deg injector. Later, using convergecfd, seven different injector included angles were studied at a constant SOI. With the change in injector included angle, the region of the cylinder targeted by the fuel spray varies significantly, and it was found to have a significant impact on the combustion efficiency and the engine-out emissions. As the injector included angle changed from 60-deg to 150-deg, the combustion efficiency increased by 15% and the CO, NOx, and HC emissions decreased by 96%, 70%, and 86%, respectively.

Engineering↗