Search NASA⌕ Search

SEARCH · Search NASA

Results for “ECN”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

High pressure/high temperature multiphase simulations of dodecane injection to nitrogen: Application on ECN Spray-A

The present work investigates the complex phenomena associated with pressure/high temperature dodecane injection for the Engine Combustion Network (ECN) Spray-A case, employing more elaborate thermodynamic closures, to avoid well known deficiencies concerning density and speed of sound prediction using traditional cubic models. A tabulated thermodynamic approach is proposed here, based on log 10 (p)-T tables, providing very high accuracy across a large range of pressures, spanning from 0 to 2500 bar, with only a small number of interpolation points. The tabulation approach is directly extensible to any thermodynamic model, existing or to be developed in the future. Here NIST REFPROP properties are used, combined with PC-SAFT Vapor-Liquid-Equilibrium to identify the liquid in mixtures penetration, hence avoiding the use of an arbitrary threshold for mass fraction. Identified liquid and vapour penetration are compared against experimental data from the ECN database showing a good agreement, within approximately 3–8% for axial penetration of liquid, 2% for vapor axial penetration and within experimental uncertainty for radial distribution of mass fraction. Analysis of the vortex evolution indicates that driving mechanisms behind the jet break-up are vortex tilting/stretching, then baroclinic torque, leading to Rayleigh-Taylor instabilities, closely followed by vortex dilation and finally viscous effects.

42 ENGINEERING↗
DOE OSTI2024

Spray process of multi-component gasoline surrogate fuel under ECN Spray G conditions

As modern gasoline direct injection (GDI) engines utilize sophisticated injection strategies, a detailed understanding of the air-fuel mixing process is crucial to further improvements in engine emission and fuel economy. In this study, a comprehensive evaluation of the spray process of single-component iso-octane (IC8) and multi-component gasoline surrogate E00 (36 % n-pentane, 46 % iso-octane, and 18 % n-undecane, by volume) fuels was conducted using an Engine Combustion Network (ECN) Spray G injector. High-speed extinction, schlieren, and microscopy imaging campaigns were carried out under engine-like ambient conditions in a spray vessel. Experimental results including liquid/vapor penetration, local liquid volume fraction, droplet size, and projected liquid film on the nozzle tip were compared under ECN G1 (573 K, 3.5 kg/m 3 ), G2 (333 K, 0.5 kg/m 3 ), and G3 (333 K, 1.01 kg/m 3 ) conditions. In addition to the experiments, preferential evaporation process of the E00 fuel was elucidated by Large–Eddy Simulations (LES). The three-dimensional liquid volume fraction measurement enabled by the computed tomographic reconstruction showed substantial plume collapse for E00 under the G2 and G3 conditions having wider plume growth and plume-to-plume interaction due to the fuel high vapor pressure. Here, the CFD simulation of E00 showed an inhomogeneity in the way fuel components vaporized, with more volatile components carried downstream in the spray after the end of injection. The high vapor pressure of E00 also results in ~4 μm smaller average droplet diameter than IC8, reflecting a higher rate of initial vaporization even though the final boiling point temperature is higher. Consistent with high vapor pressure, E00 had a wider plume cone angle and enhanced interaction with the wall to cover the entire surface of the nozzle tip in a film. However, the liquid fuel underwent faster evaporation, so the final projected tip wetting area was smaller than the IC8 under the flash-boiling condition.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Detailed mixing measurements from single-hole converging ECN injectors using Rayleigh scattering

Time resolved liquid and vapor fields of dodecane and oxymethylene ethers are measured from Spray A-3 and Spray D using high speed Rayleigh scattering and diffuse back illumination at the Engine Combustion Network (ECN) Spray A condition of 900 K and 22.8 kg/m 3 . Global quantities including mixture fraction, vapor and liquid penetration, as well as spreading angle are measured. The mixture fraction fields and vapor penetration profiles are well predicted by the 1-D Musculus-Kattke model. The mixture fraction field and vapor penetration from Spray A-3 are similar to those measured from Spray A in previous works. Spray D exhibits higher mixture fraction fields and vapor penetration due to its larger nozzle diameter. The quasi-steady mixture fraction fields from these injectors scale well when distance from the injector is normalized by the nozzle diameter. The turbulent dissipation structures were also analyzed based on the orientation, thickness, and magnitude of the mixing layers. Furthermore, the orientation and thickness are similar to other measurements in atmospheric gas jets, while the magnitude is lower. The thickness and magnitude are subject to uncertainties due to limitations in the imaging resolution of the system but still provide an order of magnitude as a useful reference for comparison against computational fluid dynamic simulations.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Computational study of the ECN spray C via one-way coupling of internal nozzle flow and ensuing spray

Here, in this study, computational fluid dynamics simulations of the Engine Combustion Network Spray C injector were performed to investigate the effect of the internal nozzle flow on the development of the ensuing spray in automotive fuel injectors. A set of simulation best practices was first developed to achieve an accurate representation of the internal nozzle flow. Detailed, spatiotemporally defined information was extracted at the injector’s orifice exit and stored in maps that were subsequently employed to initialize a Lagrangian spray by means of a static, one-way coupling (OWC) approach. To highlight the impact of the in-nozzle flow on the spray, the OWC approach was compared with the conventional rate-of-injection (ROI) approach, for which the spray parcels are commonly initialized using a blob injection model. The results indicated that, using the ROI approach, considerable evaporation was observed within the plume in the near-nozzle region. On the other hand, the OWC approach showed evidence of evaporation farther downstream and at the plume periphery. The different behavior observed with the two approaches was mostly due to substantial differences in fuel mass distribution. The liquid fuel concentration predicted by the OWC approach matched well with X-ray tomography measurements of projected fuel mass per unit volume, in terms of both magnitude and distribution. In contrast, an unphysical distribution of fuel mass characterized by an extremely low liquid concentration was predicted by the ROI approach. In the far-field, the effect of the in-nozzle flow was found to be weaker as the spray penetrated and interacted with the ambient gas. In this region, the OWC and ROI approaches provided similar predictions of vapor penetration, spray morphology, and mixing-related characteristics.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Numerical study on spray collapse process of ECN spray G injector under flash boiling conditions

This work features a numerical study of the spray collapse process that occurs under flash-boiling, gasoline-direct-injection conditions. The Engine Combustion Network's Spray G injector was modeled, and iso-octane, n-hexane, and propane were used as fuels with the goal to investigate fuel property effects. The development of individual jets and jet-to-jet interaction were analyzed to reveal the physical mechanisms of spray collapse. The results agreed qualitatively well with the experimental data of propane available from the literature and the predictions revealed the model's ability to capture the near-nozzle shock structures witnessed in the experiments. Simulations showed that the flow development of flashing sprays was strongly tied with the fuel properties. Specifically, under-expanded jets were not observed with iso-octane due to the fuel's low vapor pressure. In the case of n-hexane, the jets were under-expanded, and a low-pressure core was observed inside the jets due to the flow expansion. With propane, the very strong expansion caused the flow to become transonic and generate a unique shock structure near the nozzle exit. The shock structure revealed the formation of primary shock cells within the jets and secondary shock cells induced by jet-to-jet interaction. Based on the results, the spray collapse under flash boiling conditions was mainly attributed to two effects, i.e., the decrease in pressure at the spray center induced by the low-pressure cores inside and between the jets, and the isolation effect due to the jet-to-jet interaction which contributed to maintain the pressure differential between the spray center and the ambient.

42 ENGINEERING↗
DOE OSTI2020

Enhanced Explicit Congestion Notification (EECN) in TCP with P4 Programming

In current TCP/IP networks, TCP mainly relies on packet drops as an indication of congestion. With the emergence of Explicit Congestion Notification (ECN), TCP can detect the congestion through packets with marked bits instead of dropped packets. ECN thus reduces the unnecessary delay due to packet drops, especially for bandwidth-delay sensitive connections. However, ECN still relies on the receiver for congestion indication, which incurs a round trip time (RTT) before the sender can react to the congestion. In network environments with a high bandwidth-delay product (BDP), this could be problematic. In this paper, we present an enhanced ECN mechanism for the early detection of congestion using P4 programming. In our proposed scheme, the sender does not have to wait for the receiver to indicate congestion because switches in the network can indicate congestion. We evaluate our scheme comparing our proposed solution with standard TCP and TCP with the conventional ECN. Experimental results show that our scheme outperforms ECN as the RTT grows.

ECN↗
DOE OSTI2022

Electrochemical noise studies on localized corrosion of Ni and Ni-20Cr in molten ZnCl 2

The electrochemical noise (ECN) technique was employed to study corrosion of two model systems, i.e. pure Ni and a binary Ni-20 wt%Cr (Ni20Cr) alloy in molten ZnCl 2 at 623 K. Here we measured ECN transients in current and open-circuit potential from two nominally identical Ni-Ni and Ni20Cr-Ni20Cr electrodes and one galvanic Ni-Ni20Cr electrode pair. The behavior of ECN is quite distinct among the three-electrode systems, and it is correlated with the various microscopic observations of micro- and nano-scale morphological features. Based on the ECN study coupled with the microstructural analysis, the origins of ECN in the molten salt environment as well as the mechanisms of localized corrosion in the three systems are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

AI Improves the Accuracy, Reliability, and Economic Value of Continental‐Scale Flood Predictions

Accurate flood early warnings are critical to minimize damage and loss of life. Current large‐scale operational forecasting systems, however, have limited accuracy, description of uncertainty, and computational efficiency. While Artificial intelligence (AI) can address these limitations in principle, the accuracy and reliability of AI forecasts have thus far proven insufficient. Here we present a novel hybrid framework that integrates AI‐based machinery termed Errorcastnet (ECN) with the National Water Model (NWM) to showcase the potential of ensemble AI flood forecasts over the contiguous U.S. ECN boosts prediction accuracy four‐ to six‐fold across lead times of 1–10 days, while providing uncertainty quantification. It also outperforms Google's state‐of‐the‐art global AI model. ECN‐based forecasts offer superior economic value (up to four‐fold) for decision‐making as compared to those from NWM alone. ECN performs well in varied ecoregions, physiography, and land management conditions. The framework is computationally efficient, enabling national‐scale ensemble forecasts in minutes.

artificial intelligence↗
DOE OSTI2022

Assembly and Evolution of Artificial Metalloenzymes within E. coli Nissle 1917 for Enantioselective and Site-Selective Functionalization of C–H and C=C Bonds

The potential applications afforded by the generation and reactivity of artificial metalloenzymes (ArMs) in microorganisms are vast. Here we show that a non-pathogenic E. coli strain, Nissle 1917 (EcN), is a suitable host for the creation of ArMs from cytochrome P450s and artificial heme cofactors. An outer-membrane receptor in EcN transports an iridium porphyrin into the cell, and the Ir-CYP119 (CYP119 containing iridium porphyrin) assembled in vivo catalyzes carbene insertions into benzylic C-H bonds enantioselectively and site-selectively. The application of EcN as a whole-cell screening platform eliminates the need for laborious processing procedures, drastically increases the ease and throughput of screening, and accelerates the development of Ir-CYP119 with improved catalytic properties. Studies to identify the transport machinery suggest that a transporter different from the previously assumed ChuA receptor serves to usher the iridium porphyrin into the cytoplasm.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

X-Ray Radiography and Phase-Contrast Imaging of the Engine Combustion Network Spray B Sprays and Injection

X-ray measurements of diesel sprays from two of the Engine Combustion Network (ECN) Spray B injectors are described. Measurements in these three-hole nozzles complement both visible light measurements of these sprays and previous x-ray measurements of the axial single-hole ECN Spray A injectors. Both axial and lateral motions of the injector needle valve were measured with x-ray phase contrast imaging. Additionally, the liquid mass distribution in room temperature sprays at elevated ambient pressure was determined with x-ray radiography. Measurements of both needle valve motion and spray distribution were performed at both the standard Spray A/B conditions and with selected variations of injection pressure, ambient density, and injection timing. The needle valve motion for the Spray B injectors is quite similar to that of the Spray A injectors, though little lateral motion is seen in either Spray B injector. Compared to the sprays from the Spray A injectors, the sprays from Spray B penetrate more slowly in the near-nozzle region, demonstrate a broader, more uniform distribution in the transverse direction, and are significantly more variable with respect to time. These differences demonstrate the importance of studies with multi-hole nozzles to provide insight into applied diesel combustion.

42 ENGINEERING↗
DOE OSTI2021

Development of a Turbulent Liquid Spray Atomization Model for Diesel Engine Simulations (Final Technical Report)

This project addresses the systematic lack of predictive capabilities by spray models within engine CFD codes. We develop a new modeling approach to predict the breakup of diesel sprays based on recent literature showing that liquid turbulence plays a fundamental role in spray atomization. A new body of quantitative validation data is also developed as a critical element of the project, leveraging the joint capabilities of Georgia Tech’s high-pressure continuous-flow spray chamber and Argonne National Lab’s near-nozzle x-ray diagnostics at the Advanced Photon Source. This project contributes spatially-resolved measurements of drop size distribution within well-characterized diesel injectors, Spray A and D, from the Engine Combustion Network (ECN) to the engine combustion community for the first time. Utilizing this new body of measurements, we validate and demonstrate a new spray model for diesel sprays, termed the KH-Faeth model, that predicts global and local spray characteristic more accurately than the widely adopted and employed KH model. Predicted drop size distributions are seen to predict measured drops sizes both quantitatively and predictively, with accurate response in droplet size distributions over a wide range of ambient density, injection pressure, and injector nozzle size (Spray A and D) without model tuning. The KH-Faeth model can reduce error in the predicted centerline droplet size profile by up to 80% for ECN Spray D simulations when compared to use of the widely employed KH model.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS2001

Improving Explicit Congestion Notification with the Mark-Front Strategy

Delivering congestion signals is essential to the performance of networks. Current TCP/IP networks use packet losses to signal congestion. Packet losses not only reduces TCP performance, but also adds large delay. Explicit Congestion Notification (ECN) delivers a faster indication of congestion and has better performance. However, current ECN implementations mark the packet from the tail of the queue. In this paper, we propose the mark-front strategy to send an even faster congestion signal. We show that mark-front strategy reduces buffer size requirement, improves link efficiency and provides better fairness among users. Simulation results that verify our analysis are also presented.

Liu, Chunlei↗
DOE OSTI2023

A physics-driven Σ-Y atomization model for heavy-duty engine simulations

The atomization of a liquid jet is a multi-scale and multi-physics problem of interest for many engineering applications. Particularly, it drives the fuel-oxidizer mixing and dictates the efficiency of combustion engines. High-fidelity multi-phase simulations remain challenging due to the excessive computational cost required to capture all the atomization scales. Thus, atomization models are necessary to represent sub-grid liquid structures. Here, in this work, a modified Σ-Y model in the context of Eulerian-Lagrangian Spray Atomization (ELSA) is used to transport the surface area density of the spray. The model's predictive performance is assessed under various operating conditions relevant to heavy-duty engines using the Engine Combustion Network (ECN) Spray C and Spray D research-grade injectors. The classic droplet collision formulation of the Σ-Y model alone does not replicate the response of the measured spray surface area to changes in injector, ambient pressure, and injection pressure, requiring individual tuning of the model's parameters. Instead, a transition between dense and dilute spray breakup mechanisms is proposed in terms of the average droplet spacing. The collision breakup mechanism represents the dilute spray, whereas the droplet size in the dense spray is driven by a competition between the integral scale of turbulence and the balance between the turbulent kinetic energy and the surface energy of the droplets. Such an approach minimizes the requirements for model tuning. Moreover, the role of the constants of a compressible standard k-ε RANS model is assessed in the injector's internal flow and external spray simulation framework, and an updated set is proposed. The results are validated against x-ray radiography and Ultra-Small Angle X-ray Scattering (USAXS) data and highlight the predictive capabilities of the proposed physics-driven Σ-Y model, which is compatible with engine simulation turnaround times.

42 ENGINEERING↗
DOE OSTI2023

Considerations for the temperature stratification in a pre-burn constant-volume combustion chamber

In recent years, the Engine Combustion Network (ECN) has developed as a worldwide reference for understanding and describing engine combustion processes, successfully bringing together experimental and numerical efforts. Since experiments and numerical simulations both target the same boundary conditions, an accurate characterization of the stratified environment that is inevitably present in experimental facilities is required. The difference between the core-, and pressure-derived bulk-temperature of pre-burn combustion vessels has been addressed in various previous publications. Additionally, thermocouple measurements have provided initial data on the boundary layer close to the injector nozzle, showing a transition to reduced ambient temperatures. The conditions at the start of fuel injection influence physicochemical properties of a fuel spray, including near nozzle mixing, heat release computations, and combustion parameters. To address the temperature stratification in more detail, thermocouple measurements at larger distances from the spray axis have been conducted. Both the temperature field prior to the pre-combustion event that preconditions the high-temperature, high-pressure ambient, as well as the stratification at the moment of fuel injection were studied. To reveal the cold boundary layer near the injector with a better spatial resolution, Rayleigh scattering experiments and thermocouple measurements at various distances close to the nozzle have been carried out. The impact of the boundary layers and temperature stratification are illustrated and quantified using numerical simulations at Spray A conditions. Next to a reference simulation with a uniform temperature field, six different stratified temperature distributions have been generated. These distributions were based on the mean experimental temperature superimposed by a randomized variance, again derived from the experiments. The results showed that an asymmetric flame structure arises in the computed results when the temperature stratification input is used. In these predictions, first-stage ignition is advanced by 24 $\mu$s , while second-stage ignition is delayed by 11 $\mu$s. At the same time a lift-off length difference between the top and the bottom of up to 1.1 mm is observed. Furthermore, the lift-off length is less stable over time. Given the shown dependency, the temperature data is made available along with the vessel geometry data as a recommended basis for future numerical simulations.

42 ENGINEERING↗