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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Flow visualisation in real-size optical injectors of conventional, additised, and renewable gasoline blends

Research on renewable and alternative fuels is crucial for improving the energy and environmental efficiency of modern gasoline internal combustion engines. To highlight the influence of fuel rheological and thermodynamic properties on phase change and atomisation processes, three types of gasoline blends were tested. More specifically, the campaign comprised a reference gasoline, an ethanol/gasoline blend (10% v/v) representative of renewable fuels, and an additised gasoline sample treated with viscoelasticity-inducing agents. High-speed imaging of the transient two-phase flow field arising in the internal geometry and the near-nozzle spray region of gasoline injectors was performed employing Diffuse Backlight Illumination. The metallic body of a commercial injector was modified to fit transparent tips realising two nozzle layouts, namely a two-hole real size model resembling the Engine Combustion Network spray G injector and an enraged replica with an offset hole. Experiments were conducted at realistic operating conditions comprising an injection pressure of 100 bar and ambient pressures in the range of 0.1–6.0 bar to cover the entire range of chamber pressures prevailing in Gasoline Direct Injection engines. The action of viscoelastic additives was verified to have a suppressive effect on in-nozzle cavitation (6% reduction in cavitation extent) , while also enhancing spray atomisation at flash-boing conditions, in a manner resembling the more volatile gasoline/ethanol blends. Finally, persisting liquid ligaments were found to form after the end of injection for the additised sample, owing to the surfactant nature of the additives.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2021

High-speed phase contrast imaging of spray breakup of jet fuels under combusting conditions

X-ray phase contrast imaging is conducted at 90,517 Hz on a fuel spray to characterize the breakup of the bulk fuel into ligaments and individual droplets in a single-sector, swirl-stabilized combustor under reacting conditions. Phase contrast imaging is used to qualitatively assess spray breakup for two fuels: Jet-A, which represents a normal viscosity fuel, and a blend of JP-5 (64%) and farnesane (36% by volume), which represents a high-viscosity fuel, at three fuel-flow rates and two air inlet temperatures. Time-series images of the fuels show that atomization occurs much more rapidly at higher fuel pressure with thinner ligaments being rapidly shredded. The high-viscosity fuel is qualitatively observed to have markedly longer, thicker ligaments and larger droplet diameters after the primary breakup than the normal viscosity fuel. Using an image processing and droplet quantification strategy, the mean droplet velocity magnitudes were found to decrease with decreasing fuel pressure and fuel-flow rate. The increase in preheat temperature from 323 to 370 K results in an increase in the mean droplet velocity magnitude and a decrease in numerical average and Sauter mean diameter, indicating improved atomization. The high-viscosity fuel was found to have larger average droplet diameters at each condition than the normal viscosity fuel. The increased preheat is found to enhance the combustion efficiency, which is hypothesized to couple with the improved atomization due to the higher combustion temperatures. This indicates the importance of examining spray atomization and breakup under realistic combusting conditions for relevant fuels as the heat release directly couples with the atomization process.

42 ENGINEERING↗
DOE OSTI2021

Effect of Hydrogen on Steady-State and Transient Combustion Instability Characteristics

This paper examines the effects of steady-state and transient hydrogen enrichment on thermoacoustic instability in a model gas turbine combustor. Combustion instability, a feedback loop between flame heat release rate oscillations and combustor acoustics, is characterized in a swirl-stabilized flame operated at a range of hydrogen–natural gas fuel blends and heat rates. Measurements of combustor chamber pressure fluctuations and CH* chemiluminescence imaging are used to characterize instability at a range of operating conditions. Steady-state tests show that both mixture heat rate and hydrogen content affect system stability. At a given heat rate, higher levels of hydrogen result in unstable combustion. As heat rate increases, instability occurs at lower concentrations of hydrogen in the fuel. Transient operation was tested in two directions—instability onset and decay—and two hydrogen-addition times—a short time of 1 ms and a longer time of 4 s. Results show that instability onset processes, through the transient addition of hydrogen, are highly repeatable regardless of the timescale of hydrogen addition. Certain instability decay processes are less repeatable, resulting in cases that do not fully transition from unstable to stable combustion despite similar changes in hydrogen fuel flow rate. Flame behavior before, during, and after the transient is characterized using high-speed CH* chemiluminescence imaging. Analysis of the high-speed images shows changes in flame stabilization and dynamics during the onset and decay processes. Finally, the results of this study can have implications for systems that experience variations in fuel composition, particularly in light of growing interest in hydrogen as a renewable fuel.

42 ENGINEERING↗
DOE OSTI2021

Efficient Prompt Scintillation and Fast Neutron-Gamma Ray Discrimination Using Amorphous Blends of Difluorenylsilane Organic Glass and in-situ Polymerized Vinyltoluene

High performance radiation detection materials are an integral part of national security, medical imaging, and nuclear physics applications. Those that offer compositional and manufacturing versatility are of particular interest. In this work, we report a new family of radiological particle-discriminating scintillators containing bis(9,9-dimethyl-9H-fluoren-2- yl)diphenylsilane (compound “P2”) and in-situ polymerized vinyltoluene (PVT) that is phase stable and mechanically robust at any blend ratio. The gamma-ray light yield increases nearly linearly across the composition range, to ~16,400 photons/MeV at 75 % wt. P2. These materials are also capable of γ/n pulse shape discrimination (PSD) and between 20-50 % P2 loading are competitive with the PSD quality of commercially-available plastic scintillators. The 137 Cs scintillation rise and decay times are sensitive to P2 loading and approach the values for “pure” P2. Additionally, the radiation detection performance of P2-PVT blends can be made stable in 60°C air for at least 1.5 months with the application of a thin film of poly(vinylalcohol) to the scintillator surfaces.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Physics constrained unsupervised deep learning for rapid, high resolution scanning coherent diffraction reconstruction

By circumventing the resolution limitations of optics, coherent diffractive imaging (CDI) and ptychography are making their way into scientific fields ranging from X-ray imaging to astronomy. Yet, the need for time consuming iterative phase recovery hampers real-time imaging. While supervised deep learning strategies have increased reconstruction speed, they sacrifice image quality. Furthermore, these methods’ demand for extensive labeled training data is experimentally burdensome. Here, we propose an unsupervised physics-informed neural network reconstruction method, PtychoPINN, that retains the factor of 100-to-1000 speedup of deep learning-based reconstruction while improving reconstruction quality by combining the diffraction forward map with real-space constraints from overlapping measurements. In particular, PtychoPINN gains a factor of 4 in linear resolution and an 8 dB improvement in PSNR while also accruing improvements in generalizability and robustness. This blend of performance and computational efficiency offers exciting prospects for high-resolution real-time imaging in high-throughput environments such as X-ray free electron lasers (XFELs) and diffraction-limited light sources.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

KMT-2019-BLG-1715: Planetary Microlensing Event with Three Lens Masses and Two Source Stars

We investigate the gravitational microlensing event KMT-2019-BLG-1715, the light curve of which shows two short-term anomalies from a caustic-crossing binary-lensing light curve: one with a large deviation and the other with a small deviation. We identify five pairs of solutions, in which the anomalies are explained by adding an extra lens or source component in addition to the base binary-lens model. We resolve the degeneracies by applying a method in which the measured flux ratio between the first and second source stars is compared with the flux ratio deduced from the ratio of the source radii. Applying this method leaves a single pair of viable solutions, in both of which the major anomaly is generated by a planetary-mass third body of the lens, and the minor anomaly is generated by a faint second source. A Bayesian analysis indicates that the lens comprises three masses: a planet-mass object with ∼2.6 M {sub J} and binary stars of K and M dwarfs lying in the galactic disk. We point out the possibility that the lens is the blend, and this can be verified by conducting high-resolution follow-up imaging for the resolution of the lens from the source.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

SITCOMTN-128: Unrecognized Blends in LSSTComCam Data Preview 1 ECDFS

Unrecognized blends are a class of blended objects where two (or more) objects are so close on the sky that they are mistakenly identified as a single object. These objects can cause a variety of issues for science and simple validation. We can identify such objects by using higher resolution imaging from a space based telescope that will not be affected by ground based seeing and then label detected objects as isolated, recognized blends, or unrecognized blends. We find that for objects with 23 < i < 24.5, 18% of objects are unrecognized blends.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

100 kHz OH PLIF of High-Pressure H2/NH3 and H2/CH4 Flames

The reaction zones in a multi-element, multi-stage, micromix injector are investigated using planar laser-induced fluorescence (PLIF) imaging of the hydroxyl (OH) radical at a 100 kHz repetition rate. The combustor is operated at a pressure of ∼10 bar. Multiple fuel blends of hydrogen, methane, and ammonia are considered to study the effect of changing fuel composition on the flame structure. Compact regions of high OH signal are observed in each flame for fuel mixtures with high hydrogen content, indicating rapid reactant consumption in the shear layers. Instantaneous images exhibit wrinkled flame fronts and the formation of unreacted pockets due to highly turbulent burning. The addition of methane is observed to reduce the reactivity and flame speed, resulting in more diffuse regions of OH between each flame. The shape of the reactant core is altered, and the length scale of the flame surface wrinkling is increased. Ammonia addition has a more severe effect on the distribution of OH and the local flame structure than methane addition. A time series of images shows the presence of OH vortical structures and significant turbulent fluctuations in the flames near the wall, suggesting the presence of a recirculation zone that could drive the observed disparity in flame lengths.

Hodge, Alexander J. [Purdue University]↗
DOE OSTI2025

Development of Hydrogen Burner for FT4000® Aeroderivative Engine - Final Report

This report details an effort to develop a retrofittable fuel/air injector for the FT4000® aeroderivative gas turbine that enables use of hydrogen as a carbon-free fuel for efficient power generation. The FT4000 engine’s low-NOx combustor was developed by Pratt & Whitney and RTX Technology Research Center with core technology from the Pratt & Whitney PW4000 turbofan aircraft engine. The current FT4000 production engine operates on either natural gas or No. 2 fuel oil with water injection to achieve high thermal efficiency and low emissions. This engine is fielded by Mitsubishi Power Aero and delivers 70 MW of power with a simple-cycle efficiency of over 41% when operating with wet compression. The work reported here advances the technology readiness level of the FT4000 combustor for operation with hydrogen, starting with an experimental assessment of the current production hardware with increasing hydrogen content mixed with natural gas and ending with improved nozzle concepts for fully robust operation with 100% hydrogen. High-pressure single-sector combustor rig tests have been completed, demonstrating the ability for the dual fuel nozzle to operate an FT4000 combustor on 100% hydrogen with low nitrogen oxide (NOx) emissions. Metal temperature measurements and video images of the flame structure from zero to 100% hydrogen highlight opportunities to improve the fuel nozzle robustness for high hydrogen conditions. The design of new fuel/air mixer concepts to improve durability and operability with high hydrogen levels was also completed. A total of eleven new concepts were developed and analyzed, ranging from modifications to the bill-of-materials nozzle to fully clean sheet designs. The concepts were evaluated with non-reacting and reacting flow evaluations to assess the performance of the new hardware designs. Non-reacting tests included Phase Doppler Particle Analysis (PDPA) for droplet size and velocity, mechanical patternation for liquid water flux, and planar laser induced fluorescence (PLIF) with acetone-seeding for gaseous fuel/air mixing characterization. Five scaled candidate fuel nozzle designs, in addition to a scaled bill-of-materials nozzle, were then successfully evaluated in an atmospheric pressure burner rig. The nozzles were evaluated for performance with natural gas, hydrogen/natural gas blends, and pure hydrogen. For 100% hydrogen, the nozzles were evaluated with and without water injection. Optical and infrared imaging of the flame and fuel nozzle was captured. NOx emissions were sampled from fixed emissions probes. The results show measurable differences between the various designs, and the data was used to down-select the two most promising designs to advance to future full pressure rig testing. Results from this study have cleared the current production FT4000 engines with dual fuel nozzles to operate at baseload power on blends of hydrogen mixed with natural gas and water. Two promising nozzle designs have been developed to enable fully robust operation with up to 100% hydrogen. These nozzles require validation at full baseload operating conditions before they can be introduced to the field.

03 NATURAL GAS↗
DOE OSTI2022

Model development for flash boiling spray and validations with isooctane, hexane, ethanol and their binary mixtures

The objective of this study is to develop a comprehensive model for spray atomization under the consideration of flash boiling, which includes nucleation, bubble growth, and droplet breakup. Although flash boiling has been previously studied, there is still no well-established analytical and numerical model of their mechanisms, or general guidelines on the implementation of this atomization strategy. In this study, detailed formulations are elaborated for the unified spray atomization model under both non-flash and flash boiling conditions. Next, the model was implemented into CFD software and 3-D simulations were performed for model validations. Two fuel blends are tested: ethanol-isooctane blends and hexane-isooctane blends. Simulation results were compared with the experimental measurements conducted using two methodologies, DBI (Diffuse Backlight Imaging) system for spray images captured by a high-speed camera, and a PDA (Phase Doppler Anemometry) system for droplet size measurement during the spray injection process. It was found that the current flash boiling model can accurately capture the spray characteristics under different environment conditions, such as the spray plume interactions and liquid penetration. The averaged Sauter mean diameter (SMD) calculations match the measurement sufficiently well. The spray structures for both single- and multi-component fuels during the injection process are well represented by current model.

42 ENGINEERING↗
DOE OSTI2021

gp_blendclass_singleband

The code used for the data preprocessing, image simulation, and model training and analysis reported in the paper "Gaussian Process Classification for Galaxy Blend Identification in LSST" (arXiv:2107.09246).

Buchanan, JamesJ.↗
DOE OSTI2022

Experimental Investigation of Cavitation-Induced Erosion Using X-Ray Imaging and Tomography

High injection pressure in diesel engines can lead to cavitation-induced erosion in injector nozzles. One important factor affecting the severity of erosion is the fuel and its properties. Traditionally, modeling and simulation studies have used single-component representations of fuels, but realistic fuels feature a multitude of components and can even include volatile additives such as water and alcohol. To provide realistic benchmarks and comparisons, experimental measurements quantifying erosion characteristics were made using ultra-low sulfur diesel (ULSD) and two alternative diesel fuels (ADF). X-ray imaging and computed tomography were used to investigate cavitation-induced erosion onset and progression. Hard X-ray tomography revealed injector internal geometry, including details such as surface marks from the manufacturing process and erosion patterns from repeated injections. Erosion progression was measured using X-ray tomography and imaging performed between injections. The critical erosion site was found to be similar across different fuel blends, while the erosion rate and incubation time were sensitive to the fuel blend. The injector geometry and the erosion characteristics were also prepared for numerical model development and validation.

42 ENGINEERING↗
DOE OSTI2024

Dynamics of hydrogen–ammonia–natural gas lean-premixed high-pressure flames

The influence of fuel composition on self-excited combustion instabilities in a high-pressure combustor operated with ammonia, hydrogen, and natural gas fuels is characterized with high-frequency pressure measurements and imaging of the flame structure. A micromix multi-stage injector with 19 elements is used to introduce the fuel blend premixed with heated air into an optically accessible combustor operated at ~1.1 MPa. As hydrogen is substituted for natural gas, longitudinal thermoacoustic instabilities are observed in the combustor with pressure fluctuation amplitudes as large as 8% of the mean chamber value. In the absence of natural gas, limit-cycle instability magnitude is largely insensitive to ammonia addition. However, fuel compositions with > 20% natural gas result in positive correlation between instability amplitude and ammonia concentration. Spatial distribution of heat release in the combustor evaluated from OH* chemiluminescence imaging reveals axial growth in the regions of heat release fluctuation as hydrogen decreases, thus correlating flame length to instability amplitude. Distinct transitions from the first harmonic of the fundamental longitudinal acoustic mode (~1100 Hz) to the fundamental mode (~550 Hz) are observed with root mean square pressure fluctuations exceeding 7% of the mean chamber value. Here, these cases correspond to hydrogen mole fractions ≤ 50%. Analysis of the phase relationship between pressure fluctuations upstream and downstream of the flame zone indicates acoustic coupling of the injector as a key contributor to instability growth.

03 NATURAL GAS↗
DOE OSTI2023

Detecting Dwarf Galaxies Around NGC 55

In order to improve our understanding of the satellite populations of low-mass galaxies, the DECam Local Volume Exploration (DELVE) – DEEP Survey is performing a search for satellites around the isolated, low-mass galaxy, NGC 55. As part of this search, we characterize our dwarf galaxy detection sensitivity by injecting artificial dwarf galaxies into our data set and measuring the fraction that we can recover. Additionally, we inject and recover artificial dwarfs to test how the blending of resolved stars affects the detection of dwarf galaxies. We inject 650 artificial dwarfs across 26 DELVE-DEEP coadded images of the NGC 55 halo and use the software tool, Source Extractor, to perform source recovery. A dwarf-search pipeline is then run on our dwarf-injected catalogs, utilizing the photutils function, find peaks, and detections are recorded as a function of dwarf size and luminosity. Our results demonstrate that we are most sensitive to large, bright dwarf galaxies, and our sensitivity begins to decrease as we approach DELVE-DEEP’s detection limit or blending causes significant reductions in recovered magnitude. We also find that our results are hindered by the limitations of star-galaxy separation applied to distant, faint sources, which is possibly a consequence of the blending of small star clusters within dwarf galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

HAIMOS Ensemble Forecasts for Intra-day and Day- Ahead GHI, DNI and Ramps

The objective of this research is to develop a hybrid physics-based/data-driven forecast model to improve direct normal and global horizontal irradiance (DNI and GHI) prediction for horizons ranging from 1 to 72 hours. Project objectives also address key gaps in state-of-the-art solar forecasting: accurate probabilistic solar forecasts and the forecasting of large irradiance ramps (ramp onset and magnitude). The proposed model ensembles Numerical Weather Prediction (NWP) forecasts, determinist physics-based algorithms, and new-generation cloud cover products (high-resolution rapid refresh satellite images and Large Eddy Simulations). The result is the Hybrid Adaptive Input Model Objective Selection (HAIMOS) ensemble model. HAIMOS blends state of the art machine learning methodologies with physics-based models for cloud cover and cloud optical depth forecasts. The technical activities followed a two-pronged strategy. First, the preprocessing of data, the selection of inputs to the nonlinear approximators, the type of approximator and objective functions, and post-processing ensembling techniques included in HAIMOS were all optimized adaptively to find the best model for a specific goal (reduce DNI/GHI forecast error, improve the prediction of ramp onset, etc.). Second, a large effort was put in improving cloud identification and the forecast of cloud cover and cloud optical depth. To this end, new-generation cloud parametrization products were developed in this work. These include improved algorithms to assist in cloud identification, cloud classification and cloud parametrization from satellite images – three key factors in the accuracy of 1 to 6-hours irradiance forecasts and prediction of ramp onset. Furthermore, we also included cloud information extracted from high resolution rapid refresh satellite images (GOES-16) and Large Eddy Simulations (LES). LES was used to model the atmosphere in detail over locations of interest and produce cloud optical depth forecasts. Once these data streams were validated, they were used as input data to the HAIMOS forecast. The model was developed using data from several climatologically distinct locations with potential for high solar penetration. In the last year of the project, we conducted a validation campaign according to the guidelines stipulated by the Topic Area 1 project as described in the FOA. This effort brings, for the first time, proven machine-learning methodologies for generating state-of-the-art solar forecasts interweaved with detailed physics-based models for cloud detection, and cloud optical depth forecasts. HAIMOS will generate accurate irradiance probabilistic forecast to assist in reducing solar generation prediction error. Globally optimized solar forecast models are more likely to impact solar energy stakeholders. The goal of this project was to increase the state-of-the-art forecast skill from their present values of 10 to 35%. At the end of the project, we achieved between 30% and 50% forecast skill across a wide range of horizons for both GHI and DNI.

14 SOLAR ENERGY↗
DOE OSTI2020

KMT-2019-BLG-0842Lb: A Cold Planet below the Uranus/Sun Mass Ratio

We report the discovery of a cold planet with a very low planet/host mass ratio of q = (4.09 ± 0.27) × 10 -5 , which is similar to the ratio of Uranus/Sun (q = 4.37 × 10 -5 ) in the solar system. The Bayesian estimates for the host mass, planet mass, system distance, and planet–host projected separation are M {sub host} = 0.76 ± 0.40M ⊙ , M planet = 10.3 ± 5.5M ⊕ , D L = 3.3 ± 1.3 kpc, and a ⊥ = 3.3 ± 1.4 au, respectively. The consistency of the color and brightness expected from the estimated lens mass and distance with those of the blend suggests the possibility that the most blended light comes from the planet host, and this hypothesis can be established if high-resolution images are taken during the next (2020) bulge season. We discuss the importance of conducting optimized photometry and aggressive follow-up observations for moderately or very high magnification events to maximize the detection rate of planets with very low mass ratios.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Galaxy Clustering with LSST: Effects of Number Count Bias from Blending

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) will survey the southern sky to create the largest galaxy catalog to date, and its statistical power demands an improved understanding of systematic effects such as source overlaps, also known as blending. In this work we study how blending introduces a bias in the number counts of galaxies (instead of the flux and colors), and how it propagates into galaxy clustering statistics. We use the 300 deg 2 DC2 image simulation and its resulting galaxy catalog (LSST Dark Energy Science Collaboration et al. 2021) to carry out this study. We find that, for a LSST Year 1 (Y1)-like cosmological analyses, the number count bias due to blending leads to small but statistically significant differences in mean redshift measurements when comparing an observed sample to an unblended calibration sample. In the two-point correlation function, blending causes differences greater than 3σ on scales below approximately 10', but large scales are unaffected. We fit Ω m and linear galaxy bias in a Bayesian cosmological analysis and find that the recovered parameters from this limited area sample, with the LSST Y1 scale cuts, are largely unaffected by blending. Our main results hold when considering photometric redshift and a LSST Year 5 (Y5)-like sample.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Polyolefin blends with co-continuous architectures enabled by dynamic covalent crosslinking

Blending polymers produces brittle materials due to macrophase separation and poor interfacial adhesion, which is exemplified by mixtures of polyolefins. This presents a formidable challenge for the mechanical recycling of mixed plastic waste. Here, we demonstrate that dynamic covalent crosslinking of immiscible polyolefin blends creates macrophase separated co-continuous architectures, yet they display excellent mechanical properties, which challenges the conventional wisdom regarding morphology-property relationships in polymer blend compatibilization. We find that the position and orientation of dynamic crosslinks and their influence on crystallinity are key to understanding the structure-morphology-property relationships. In particular, high-resolution microscopy imaging reveals alignment of crystallite planes with strong orientational preference, particularly at polymer-polymer interfaces, which contribute to material performance. We further demonstrate that changes in crosslinker density and valency allow the properties of binary and ternary polyolefin blends to be tuned in a modular fashion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗