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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Chemiluminescence Measurements in a Combustor Using a 7-Point Lean Direct Injector Array Configuration for Gas Turbine Engine Applications

This paper reports results for a 7-point lean direct injector (LDI) array for a particular configuration. The LDI configuration in this study used a 60 degrees center pilot swirler and 52.5 degrees on the six outer swirlers. Chemiluminescence images of C2 and CH were collected at a frame rate of 25 Hz using an intensified CCD camera. Narrow bandwidth filters were coupled with the CCD camera in order to spectrally isolate C2 and CH signals. C2 was captured at 515 nm, and the CH signal was acquired at 430 nm. Six inlet conditions were considered in this study, all with the same inlet pressure, 75 psia, and same inlet temperature, 800 degcrees Fahrenheit. These conditions aimed to observe the effect of equivalence ratio, fuel staging, and reference velocity on C2 and CH emissions. Based on the chemiluminescence images, the changes in the inlet conditions was evident in both the pilot and outers. Additionally, the pilot (center injector element) appeared well isolated from the six outer elements under all test conditions.

lean direct injection↗
NASA NTRS2019

Combustion and Emissions Study Using a 7-Point Lean Direct Injector Array

This paper continues a parametric study in which we consider the effect of air swirler configuration on the flame structure and combustor performance using a circular 7-point Lean Direct Injector Array for gas turbine applications. The injector array consists of a center swirler element surrounded by six swirler elements. Parameters considered in this study include swirler angle (60° or 52°), handedness (co-swirling or counter-swirling) and center swirler offset. The primary focus considers flame stability, comparing four key air swirler configurations: for 1) fuel-lean flames; 2) high cold flow air reference velocity flames. We determined that the baseline swirler configuration had the best lean stability and could sustain the highest reference velocity. For this baseline configuration, we also compare the lean-blowout limits of four aircraft gas turbine reference fuels. With regard to lean blow-out, we determined that C4 could sustain the leanest flame, followed closely by A2. A1 was a poor performer.

gas turbine combustors↗
NASA NTRS2019

Combustion and Emissions Study Using a 7-Point Lean Direct Injector Array Focus on Flame Stability

This paper continues a parametric study in which we consider the effect of air swirler configuration on the flame structure and combustor performance using a circular 7-point Lean Direct Injector Array for gas turbine applications. The injector array consists of a center swirler element surrounded by six swirler elements. Parameters considered in this study include swirler angle (60° or 52°), handedness (co-swirling or counter-swirling) and center swirler offset. The primary focus considers flame stability, comparing four key air swirler configurations: for 1) fuel-lean flames; 2) high cold flow air reference velocity flames. We determined that the baseline swirler configuration had the best lean stability and could sustain the highest reference velocity. For this baseline configuration, we also compare the lean-blowout limits of four aircraft gas turbine reference fuels. With regard to lean blow-out, we determined that C4 could sustain the leanest flame, followed closely by A2. A1 was a poor performer.

fluid mixing↗
NASA NTRSDate not supplied

Large-Eddy Simulations of a Single-Injector Cooling Flow Using the High-Order Flux Reconstruction Method

A single-injector cooling flow into a heated crossflow was used as a validation case for large eddy simulations (LES) from two high-order CFD codes with comparisons to a state-of-the-art Reynolds averaged Navier-Stokes (RANS) turbulence model. The focus of this paper is on the validation of LES for one of the high-order CFD codes, namely the GFR (Glenn Flux Reconstruction) code that is being developed at NASA Glenn Research Center. Fourth-order LES were performed for the single-injector cooling flow configuration at blowing ratios of both 1.0 and 2.0, and a fifth-order LES was also performed with a blowing ratio of 1.0. The GFR simulations agree very well with the experiment mean quantities and reasonably well with the experiment turbulence quantities. The LES solutions from GFR and the other high-order CFD code, FDL3DI, agreed very closely for nearly every flow quantity examined, despite the fact that these two codes use completely different numerical methods, different grid geometries and domains, and different inflow boundary conditions. Finally, both LES show a significant accuracy improvement over RANS turbulence models for flows with large temperature gradients, where the standard gradient diffusion approximation is insufficient for temperature predictions.

Large Eddy Simulations↗
NASA NTRSDate not supplied

Large Eddy Simulations of a Single-Injector Cooling Flow Using the High-Order Flux Reconstruction Method

A single-injector cooling flow into a heated crossflow was used as a validation case for large eddy simulations (LES) from two high-order CFD codes with comparisons to a state-of-the-art Reynolds averaged Navier-Stokes (RANS) turbulence model. The focus of this paper is on the validation of LES for one of the high-order CFD codes, namely the GFR (Glenn Flux Reconstruction) code that is being developed at NASA Glenn Research Center. Fourth-order LES were performed for the single-injector cooling flow configuration at blowing ratios of both 1.0 and 2.0, and a fifth-order LES was also performed with a blowing ratio of 1.0. The GFR simulations agree very well with the experiment mean quantities and reasonably well with the experiment turbulence quantities. The LES solutions from GFR and the other high-order CFD code, FDL3DI, agreed very closely for nearly every flow quantity examined, despite the fact that these two codes use completely different numerical methods, different grid geometries and domains, and different inflow boundary conditions. Finally, both LES show a significant accuracy improvement over RANS turbulence models for flows with large temperature gradients, where the standard gradient diffusion approximation is insufficient for temperature predictions.

Large Eddy Simulation↗
NASA NTRSDate not supplied

Two-Dimensional Network Flow Modeling of No-Vent Tank Filling of A Cryogenic Tank With Thermo-Dynamic Vent System Assisted Injector

A finite volume-based network flow modeling tool, Generalized Fluid System Simulation Program (GFSSP), was used to simulate the no-vent filling of a cryogenic tank with a thermodynamic vent system assisted injector. The tank was discretized into nodes in the radial and axial directions to calculate two-dimensional axisymmetric flow with heat transfer between the solid wall and fluid. The nodes are connected by branches where momentum equations are solved to calculate the flowrates. The mass and energy conservation equations and the equation of state are solved to calculate pressure, temperature, and resident mass at the nodes. The energy conservation equations at the solid nodes were solved to calculate the temperature of the solid wall. The system of equations was solved by a combination of successive substitution and simultaneous Newton-Raphson method. The numerical model accounts for a) different regimes of pool boiling heat transfer, b) condensation of vapor around the spray droplets, c) condensation of vapor at the interface of the cooled injector and ullage, and d) condensation at the liquid-vapor interphase. The numerical predictions of tank pressure, filling rate, and wall temperatures were compared with the test data. The paper also presents the effect of nodal discretization by comparing the results of the 1D and 2D models and examines the effect of the droplet diameter on tank filling.

Nodal Model↗
NASA NTRS2023

Two-Dimensional Network Flow Modeling of No-Vent Tank Filling of A Cryogenic Tank With Thermo-Dynamic Vent System Assisted Injector

A finite volume-based network flow modeling tool, Generalized Fluid System Simulation Program (GFSSP), was used to simulate the no-vent filling of a cryogenic tank with a thermodynamic vent system assisted injector. The tank was discretized into nodes in the radial and axial directions to calculate two-dimensional axisymmetric flow with heat transfer between the solid wall and fluid. The nodes are connected by branches where momentum equations are solved to calculate the flowrates. The mass and energy conservation equations and the equation of state are solved to calculate pressure, temperature, and resident mass at the nodes. The energy conservation equations at the solid nodes were solved to calculate the temperature of the solid wall. The system of equations was solved by a combination of successive substitution and simultaneous Newton-Raphson method. The numerical model accounts for a) different regimes of pool boiling heat transfer, b) condensation of vapor around the spray droplets, c) condensation of vapor at the interface of the cooled injector and ullage, and d) condensation at the liquid-vapor interphase. The numerical predictions of tank pressure, filling rate, and wall temperatures were compared with the test data. The paper also presents the effect of nodal discretization by comparing the results of the 1D and 2D models and examines the effect of the droplet diameter on tank filling.

Nodal Model↗
NASA NTRSDate not supplied

Comparisons of Mixing Efficiency for the Strut Fuel Injector Obtained from Large-Eddy and Reynolds-Averaged Simulations, and Experiments

Mixing efficiency is obtained for a strut fuel injector at hypervelocity flow conditions by using large-eddy simulations (LES), Reynolds-averaged simulations (RAS), and experiments. The injector and flow conditions have been previously investigated by using RAS and experiments as a part of the Enhanced Injection and Mixing Project (EIMP) at the NASA Langley Research Center (LaRC). Because the fidelity of LES is a strong function of the grid, the mixing efficiency is obtained on two grids, the coarser of which is a factor of two coarser in each of the three dimensions with respect to the fine grid. The RAS uses the two-equation linear eddy viscosity and diffusivity modeling of Menter. In RAS, the species diffusivity model exhibits a strong dependence on the turbulent Schmidt number, which is often adjusted until some metric of engineering interest, such as the mixing efficiency, matches the experimental data. In the absence of experimental data, scale-resolving simulations, such as LES, have been proposed as surrogates for experiments that could provide the data needed to “calibrate” the turbulent Schmidt number in the RAS models. This approach is followed because LES requires significantly more computational resources (CPU, data storage, and time) than RAS, making it prohibitive for use in many engineering applications and specifically for parameter exploration or optimization. Here we examine the mixing efficiency obtained from several RAS with different values of the turbulent Schmidt number, and compare the results with those obtained from the LES and experiments. In addition, the least squares fitting approach was used to demonstrate how to obtain an estimate for the turbulent Schmidt number from LES analytically. These estimates were then used together with prior knowledge about RAS model sensitivity to select a turbulence model that was expected to best match the LES data.

LES↗
NASA NTRSDate not supplied

Comparisons of Mixing Efficiency for the Strut Fuel Injector Obtained from Large-Eddy and Reynolds-Averaged Simulations, and Experiments

Mixing efficiency is obtained for a strut fuel injector at hypervelocity flow conditions by using large-eddy simulations (LES), Reynolds-averaged simulations (RAS), and experiments. The injector and flow conditions have been previously investigated by using RAS and experiments as a part of the Enhanced Injection and Mixing Project (EIMP) at the NASA Langley Research Center (LaRC). Because the fidelity of LES is a strong function of the grid, the mixing efficiency is obtained on two grids, the coarser of which is a factor of two coarser in each of the three dimensions with respect to the fine grid. The RAS uses the two-equation linear eddy viscosity and diffusivity modeling of Menter. In RAS, the species diffusivity model exhibits a strong dependence on the turbulent Schmidt number, which is often adjusted until some metric of engineering interest, such as the mixing efficiency, matches the experimental data. In the absence of experimental data, scale-resolving simulations, such as LES, have been proposed as surrogates for experiments that could provide the data needed to “calibrate” the turbulent Schmidt number in the RAS models. This approach is followed because LES requires significantly more computational resources (CPU, data storage, and time) than RAS, making it prohibitive for use in many engineering applications and specifically for parameter exploration or optimization. Here we examine the mixing efficiency obtained from several RAS with different values of the turbulent Schmidt number, and compare the results with those obtained from the LES and experiments. In addition, the least squares fitting approach was used to demonstrate how to obtain an estimate for the turbulent Schmidt number from LES analytically. These estimates were then used together with prior knowledge about RAS model sensitivity to select a turbulence model that was expected to best match the LES data.

LES↗
DOE OSTI2021

Volumetric micro-injector for capillary electrophoresis

A volumetric microfluidic injector for capillary electrophoresis (CE) for highly repeatable sample injection has been designed and built to eliminate known injection bias in hydrodynamic injection. A defined volume from 1-10 nL or 0.1-100 nL of sample is confined in a defined region of a micro-valve PDMS microfluidic injector chip and electrophoretic potential is applied to drive sample into a separation device such as an embedded fused silica capillary for separation and detection. Using a 75 μm ID capillary, the RSD of an absorbance peak area as low as 1.32% (n=11) is obtained. As a comparison, the time-dependent injection was tested using the same chip which resulted in an inferior repeatability.

Ha, Noel Seunghyun↗
DOE OSTI2022

Air-fuel micromix injector having multibank ports for adaptive cooling of high temperature combustor

A method of using a combustor for high temperature combustion. The combustor is equipped with a showerhead type micromix air-fuel injector. The injector faceplate has its ports concentrically arranged into “banks”, to which delivery of fuel can be controlled on a bank-by-bank basis. During combustor operation, the temperature of the air into the combustor is monitored. If the temperature is above a predetermined threshold, fuel is delivered to fewer than all banks of ports. As a result, the bank(s) of ports to which fuel is not delivered inject only air into the combustion chamber, and the other bank(s) of ports inject the air-fuel mixture as usual.

Coogan, Shane B.↗
DOE OSTI2023

IOTA Proton Injector Beamline Installation

The IOTA Proton Injector (IPI), currently under installation at the Fermilab Accelerator Science and Technology facility, is a beamline capable of delivering 20-mA pulses of protons at 2.5 MeV to the Integrable Optics Test Accelerator (IOTA) ring. First beam in the IPI beamline is anticipated in 2023, when it will operate alongside the existing electron injector beamline to facilitate further fundamental physics research and continued development of novel accelerator technologies in the IOTA ring. This report details the expected operational profile, known challenges, and the current state of installation.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Status of the IOTA Proton Injector

The IOTA Proton Injector (IPI), currently under installation at the Fermilab Accelerator Science and Technology facility (FAST), is a machine capable of delivering 20 mA pulses of protons at 2.5 MeV to the Integrable Optics Test Accelerator (IOTA) ring. First beam in the IPI beamline is anticipated in the first half of 2024, when it will operate alongside the existing electron injector beamline to facilitate further beam physics research and continued development of novel accelerator technologies at the IOTA ring. This report details the expected operational profile, known challenges, and the current state of installation.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Performance of the Fermilab Linac Injector

The Fermilab Linac injection line consists of a 35 keV magnetron-type H\textsuperscript{-} ion source, two-solenoid Low Energy Beam Transport (LEBT), 201 MHz 4-rod 750 keV Radio Frequency Quadrupole (RFQ), and a Medium Energy Transport (MEBT) containing 4 quadrupoles and a bunching cavity. The injector delivers 25 mA, 48 µs pulses to the drift-tube Linac at a repetition rate of 15Hz. The transmission efficiency of the injector has been lower than expected since commissioning. Recent beam current measurements suggest that the beam is primarily lost upstream of the RFQ exit. Numerical simulations indicate that ions passing through the non-linear field region of the solenoids could produce a beam with an increased emittance resulting in up to 50\% of the LEBT beam current failing to meet the RFQ acceptance. An aperture restriction was installed upstream of the first solenoid to remove these ions. This report describes the results of measurements and simulations as well as the LEBT tuning.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Optimization of a Secondary Air Injector for a Rich-Quench-Lean (RQL) Ammonia Combustor Using Computational Fluid Dynamics

Ammonia has emerged as a promising medium for moving hydrogen around the globe due to its energy density, existing infrastructure for production, transportation, and storage, and multiple applications from fertilizer to power generation. However, one of the most significant challenges with ammonia combustion for power generation is the formation of nitrogen oxides (NOx) during combustion. Several combustion strategies have been developed to minimize the formation of NOx. One such strategy, known as rich-quench-lean (RQL), is a method that combusts NH3 in a fuel-rich environment, followed by a quick mix section and a lean burnout section. Rapid mixing of secondary air before lean burnout is thought to be important to minimize the formation of NOx. A genetic algorithm (GA) is used to parametrically vary the secondary air injector design, including the diameter, count, and angles over a constrained design space. The designs are evaluated using a non-reacting OpenFOAM model, with the objective function being the uniformity index of the secondary air (modeled as a scalar). Optimization campaigns show that traditional correlation-based designs might not be adequate. After running 414 OpenFOAM models, the optimal design is 32, 1 mm diameter, angled air injectors, increasing the uniformity index at the outlet of the quick mix zone by 36.8%. The most promising designs will be manufactured and tested in a small RQL burner setup, which is expected to lead to validation and insight into the practical usage of NH3 combustion for power generation.

ammonia combustion↗
DOE OSTI2020

Gaseous jet through an outward opening injector: Details of mixing characteristic and turbulence scales

Direct injection (DI) strategy of natural gas (NG) into internal combustion engines (ICE) has led to higher thermal efficiency and lower exhaust emissions. In order to thoroughly understand the most relevant phenomena affecting the performances of such engines, computational fluid dynamics (CFD) plays a key role as an accurate description of the jet evolution and interaction within the combustion chamber is required to that aim. Accurate description of high-pressure gaseous jets is rather challenging at high Mach numbers, as the injected gas is strongly under-expanded once in the ambient, giving room to shocks due to compressibility effects. Also the interaction between shock waves and mixing layers needs to be carefully represented with a multi-dimensional model, calling for substantial computational resources requirements. In this paper a numerical investigation of the behavior of a gaseous jet (Argon) through an outward opening injector has been carried out. A Large Eddy Simulation (LES) approach has been used in order to track the structures derived by the interaction of the injected fuel with the surrounding ambient. Although already good results were obtained using a Reynolds Averaged Navier-Stokes (RANS) approach, the adoption of LES is required to characterize more accurately the jet properties in terms of vortex structures and mixing effectiveness. Finally, the effect of the Nozzle Pressure Ratio (NPR) on the jet evolution has been highlighted in the paper, showing how a higher NPR would give a faster injection process, compromising however the homogeneity of the mixture.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Prototype tests of the electromagnetic particle injector-2 for fast time response disruption mitigation in tokamaks

Predicting and controlling disruptions is an important and urgent issue for ITER. Some disruptions with a short warning time may be unavoidable. For these cases, a fast time response disruption mitigation method is essential. Experimental tests on a prototype system of a novel, rapid time-response disruption mitigation system being developed for tokamak-based reactors and as a backup option for ITER, referred to as the electromagnetic particle injector (EPI), have been able to verify the primary advantages of the concept. These are its ability to meet short warning time scales of <10 ms while attaining the projected high velocities for deep radiative payload penetration in reactor-scale plasmas. The EPI relies on an electromagnetic propulsion system. A metallic sabot is accelerated electromagnetically to the required velocities (>1 km s -1 ) within 2 ms, at which point it releases a radiative payload consisting of a shell pellet or well-defined microspheres. Initial experimental tests from the prototype system show attainment of over 600 m s -1 in about 1 ms. Finally, essential aspects of payload separation from the sabot and sabot capture have also been demonstrated at 200 m s -1 , and the method can be extended to over 2 km s -1 .

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗