HIGH-SPEED IMAGING FOR AN OPTICALLY ACCESSIBLE ROTATING DETONATION ENGINE

2020 ◽  
Author(s):  
Yuhui Wang ◽  
◽  
Jialing Le ◽  
Keyword(s):  
Low Temperature ◽  
Flow Rate ◽  
High Speed ◽  
Equivalence Ratio ◽  
Air Flow ◽  
Detonation Waves ◽  
Outer Diameter ◽  
Air Flow Rate ◽  
High Speed Imaging ◽  
Rotating Detonation

Nonpremixed rotating detonation waves (RDWs) for ethylene or hydrogen and air sources at room temperatures 283-284 K were obtained in the same hollow combustor. The combustor was optically accessible by embedded a piece of quartz glass in the combustor wall. The hollow combustor channel here had an outer diameter 100 mm. Fuel and air were injected into the combustor from 150 cylindrical orifices of a diameter 0.8 mm axially and a circular channel with a width 1 mm radially, respectively. The detonation speeds for ethylene and air were 1562 or 1389 m/s for the air flow rate 642.35 g/s at an equivalence ratio 0.78. The detonation speed for hydrogen and air were 2013 m/s for the air flow rate 327.73 g/s at an equivalence ratio 1.24. Hydrogen operation was more stable than ethylene operation in the condition of low temperature gas sources. High-speed images showed RDW structures were changeful and unstable. Low-temperature regions could intrude into and break the detonation wave.

Air Entrainment and Bubble Generation by a Hydrofoil in a Turbulent Channel Flow

2019 ◽  
Author(s):  
Ichiro Kumagai ◽  
Kakeru Taguchi ◽  
Chiharu Kawakita ◽  
Tatsuya Hamada ◽  
Yuichi Murai
Keyword(s):  
Channel Flow ◽  
Flow Rate ◽  
High Speed ◽  
Air Flow ◽  
Air Entrainment ◽  
Air Bubbles ◽  
Air Flow Rate ◽  
Bubble Generation ◽  
Gas Liquid Flow ◽  
Entrained Air

Abstract Air entrainment and bubble generation by a hydrofoil bubble generator for ship drag reduction have been investigated using a small high-speed channel tunnel with the gap of 20 mm in National Maritime Research Institute (NMRI). A hydrofoil (NACA4412, chord length = 40 mm) was installed in the channel and an air induction pipe was placed above the hydrofoil. The flow rate of the entrained air was quantitatively measured by thermal air flow sensors at the inlet of the air induction pipe. The gas-liquid flow around the hydrofoil was visualized by a backlight method and recorded by a high-speed video camera. As the flow velocity in the channel increased, the negative pressure generated above the suction side of the hydrofoil lowered the hydrostatic pressure in the channel, then the atmospheric air was entrained into the channel flow. The entrained air was broken into small air bubbles by the turbulent flow in the channel. The threshold of air entrainment, the air flow rate, and gas-liquid flow pattern depends on Reynolds number, angle of attack (AOA), and hydrofoil type. We identified at least three modes of air entrainment behavior: intermittent air entrainment, stable air entrainment, and air entrainment with a ventilated cavity. At high flow speed in our experimental condition (9 m/s), a large volume of air bubbles was generated by this hydrofoil system (e.g. air flow rate was 50 l/min for NACA4412 at AOA 16 degrees), which has a high potential to reduce ship drag.

Thermal Performance Analysis Of Solar Air Heaters

1984 ◽  
pp. 1-15
Author(s):  
Mohamad Jamil ◽  
Prof. Madya Amer Nordin Darus
Keyword(s):  
Performance Analysis ◽  
Low Temperature ◽  
Flat Plate ◽  
Flow Rate ◽  
Thermal Performance ◽  
Air Flow ◽  
Design Parameters ◽  
Air Flow Rate ◽  
Governing Equations ◽  
Radiation Exchange

A computer routine to calculate the thermal performance of several different low temperature types of flat-plate air heaters is to be discussed. Analysis of each type is also described. The programme accepts as input real or simulated flux, collector geometry, air flow rate and enviromental data. It computes temperatures and extracts energy as a function of time of the day. The programme evaluates radiation,convection, conduction and wind losses, and the radiation exchange with the enviromental conditions.The procedure used in the derivation of the governing equations is also described. The prediction of performance provided by this programme is particularly useful in comparing performances of different collectors and for studying a specific collector's performance with changes in enviroment and design parameters which can be controlled to some extent by the designer.

Application of a Convolutional Neural Network for Wave Mode Identification in a Rotating Detonation Combustor Using High-Speed Imaging

2020 ◽  
Author(s):  
Kristyn B. Johnson ◽  
Donald H. Ferguson ◽  
Robert S. Tempke ◽  
Andrew C. Nix
Keyword(s):  
Neural Network ◽  
Detonation Wave ◽  
High Speed ◽  
Wave Mode ◽  
Classification Performance ◽  
Detonation Waves ◽  
Single Image ◽  
High Speed Imaging ◽  
Mode Identification ◽  
Rotating Detonation

Abstract Utilizing a neural network, individual down-axis images of combustion waves in a Rotating Detonation Engine (RDE) can be classified according to the number of detonation waves present and their directional behavior. While the ability to identify the number of waves present within individual images might be intuitive, the further classification of wave rotational direction is a result of the detonation wave’s profile, which suggests its angular direction of movement. The application of deep learning is highly adaptive and therefore can be trained for a variety of image collection methods across RDE study platforms. In this study, a supervised approach is employed where a series of manually classified images is provided to a neural network for the purpose of optimizing the classification performance of the network. These images, referred to as the training set, are individually labeled as one of ten modes present in an experimental RDE. Possible classifications include deflagration, clockwise and counterclockwise variants of co-rotational detonation waves with quantities ranging from one to three waves, as well as single, double and triple counter-rotating detonation waves. After training the network, a second set of manually classified images, referred to as the validation set, is used to evaluate the performance of the model. The ability to predict the detonation wave mode in a single image using a trained neural network substantially reduces computational complexity by circumnavigating the need to evaluate the temporal behavior of individual pixels throughout time. Results suggest that while image quality is critical, it is possible to accurately identify the modal behavior of the detonation wave based on only a single image rather than a sequence of images or signal processing. Successful identification of wave behavior using image classification serves as a stepping stone for further machine learning integration in RDE research and comprehensive real-time diagnostics.

scholarly journals Combustion Characteristics in Rotating Detonation Engines

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Yuhui Wang ◽  
Wenyou Qiao ◽  
JialingLe
Keyword(s):  
Detonation Wave ◽  
Flow Rate ◽  
Detonation Waves ◽  
Outer Diameter ◽  
Combustion Mode ◽  
Hydrogen Flow ◽  
Pulsed Detonation ◽  
Rotating Detonation Engine ◽  
Rotating Detonation Engines ◽  
Rotating Detonation

A lot of studies on rotating detonation engines have been carried out due to the higher thermal efficiency. However, the number, rotating directions, and intensities of rotating detonation waves are changeful when the flow rate, equivalence ratio, inflow conditions, and engine schemes vary. The present experimental results showed that the combustion mode of a rotating detonation engine was influenced by the combustor scheme. The annular detonation channel had an outer diameter of 100 mm and an inner diameter of 80 mm. Air and hydrogen were injected into the combustor from 60 cylindrical orifices in a diameter of 2 mm and a circular channel with a width of 2 mm, respectively. When the air mass flow rate was increased by keeping hydrogen flow rate constant, the combustion mode varied. Deflagration and diffusive combustion, multiple counterrotating detonation waves, longitudinal pulsed detonation, and a single rotating detonation wave occurred. Both longitudinal pulsed detonation and a single rotating detonation wave occurred at different times in the same operation. They could change between each other, and the evolution direction depended on the air flow rate. The operations with a single rotating detonation wave occurred at equivalence ratios lower than 0.60, which was helpful for the engine cooling and infrared stealth. The generation mechanism of longitudinal pulsed detonation is developed.

Application of a Convolutional Neural Network for Wave Mode Identification in a Rotating Detonation Combustor Using High-Speed Imaging

2021 ◽  
pp. 1-22
Author(s):  
Kristyn B. Johnson ◽  
Donald H. Ferguson ◽  
Robert S. Tempke ◽  
Andrew C. Nix
Keyword(s):  
Neural Network ◽  
Detonation Wave ◽  
High Speed ◽  
Wave Mode ◽  
Classification Performance ◽  
Detonation Waves ◽  
Single Image ◽  
High Speed Imaging ◽  
Mode Identification ◽  
Rotating Detonation

Abstract Utilizing a neural network, individual down-axis images of combustion waves in a Rotating Detonation Engine (RDE) can be classified according to the number of detonation waves present and their directional behavior. While the ability to identify the number of waves present within individual images might be intuitive, the further classification of wave rotational direction is a result of the detonation wave's profile, which suggests its angular direction of movement. The application of deep learning is highly adaptive and therefore can be trained for a variety of image collection methods across RDE study platforms. In this study, a supervised approach is employed where a series of manually classified images is provided to a neural network for the purpose of optimizing the classification performance of the network. These images, referred to as the training set, are individually labeled as one of ten modes present in an experimental RDE. Possible classifications include deflagration, clockwise and counterclockwise variants of corotational detonation waves with quantities ranging from one to three waves, as well as single, double and triple counter-rotating detonation waves. The ability to predict the detonation wave mode in a single image using a trained neural network substantially reduces computational complexity by circumnavigating the need to evaluate the temporal behavior of individual pixels throughout time. Results suggest that while image quality is critical, it is possible to accurately identify the modal behavior of the detonation wave based on only a single image rather than a sequence of images or signal processing.

Experimental Feasibility Study of Radial Injection Cooling of Three-Pad Air Foil Bearings

2013 ◽  
Vol 135 (4) ◽  
Author(s):  
Suman K. Shrestha ◽  
Daejong Kim ◽  
Young Cheol Kim
Keyword(s):  
Heat Exchange ◽  
Flow Rate ◽  
High Speed ◽  
Air Flow ◽  
Air Flow Rate ◽  
Design Factor ◽  
Cooling Performance ◽  
Radial Injection ◽  
Cooling Air Flow ◽  
Cooling Air

The foil bearing (FB) is one type of hydrodynamic bearing using air or another gas as a lubricant. When FBs are designed, installed, and operated properly, they are a very cost-effective and reliable solution for oil-free turbomachinery. Because there is no mechanical contact between the rotor and its bearings, quiet operation with very low friction is possible once the rotor lifts off the bearings. However, because of the high speed of operation, thermal management is a very important design factor to consider. The most widely accepted cooling method for FBs is axial flow cooling, which uses cooling air or gas passing through heat-exchange channels formed underneath the top foil. The advantage of axial cooling is that no hardware modification is necessary to implement it, because the elastic foundation structures of the FB serve as the heat-exchange channels. Its disadvantage is that an axial temperature gradient exists on the journal shaft and bearing. In this paper, the cooling characteristics of axial cooling are compared with those of multipoint radial injection, which uses high-speed injection of cooling air onto the shaft at multiple locations. Experiments were performed on a three-pad FB 49 mm in diameter and 37.5 mm in length, at speeds of 30,000 rpm and 40,000 rpm. Injection speeds were chosen to be higher than the journal surface speed, but the total cooling air flow rate was matched to that of the axial cooling cases. Experimental results show that radial injection cooling is comparable to axial cooling at 30,000 rpm, in terms of cooling performance. Tests at 40,000 rpm reveal that the axial cooling performance reaches saturation when the pressure drop across the bearing is larger than 1000 Pa, while the cooling performance of radial injection is proportional to the cooling air flow rate and does not become saturated. Overall, multipoint radial injection is better than axial cooling at high rotor speeds.

Spray Generated by an Airblast Atomizer at High-Pressure Conditions

2007 ◽  
Author(s):  
Feras Z. Batarseh ◽  
Ilia V. Roisman ◽  
Cam Tropea
Keyword(s):  
Water Flow ◽  
Flow Rate ◽  
High Speed ◽  
Velocity Vector ◽  
Ambient Pressure ◽  
Air Flow ◽  
Water Flow Rate ◽  
The Other ◽  
Air Flow Rate ◽  
Spray Visualization

We present an experimental investigation of a spray generated by an airblast atomizer. Experiments have been performed in a pressure chamber equipped by transparent windows allowing an optical access to the spray. Several techniques of spray investigation have been applied: spray visualization using the high-speed video system, spray visualization and instantaneous velocity measurements using the PIV technique, spray velocimetry and sizing using the IPI and phase Doppler instruments. Phase Doppler instrument has been used to characterize the droplets in the spray: their diameter, two components of the velocity vector. Also the integral parameters of the spray, such as the local volume flux density, have been characterized. We conduct a parametric study of the effect of the ambient pressure, the air flow rate and the water flow rate on an atomized spray. Measurements at different radial locations in the spray and in two planes were performed. The measurements in these two planes allow one to determine the distributions of all the three components of the average drop velocity vector: axial, radial and azimuthal. PDA measurements show that atomized spray is sensitive to any change in the studied parameters. For example, increasing air flow rate from 20 SCMH to 45 SCMH and keeping same water flow rate and pressure, leads to an increase in all velocity components and also to a change in droplets diameters. On the other hand, keeping constant pressure and air flow rate and increasing water flow rate from 0.7 to 1.4 l/hr, leads to an increase in water droplets sizes and the axial velocity component, whereas the other velocity components show a non uniform change. Moreover, increasing the ambient pressure leads to the growth of the spray velocity and drops diameters.

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