A New Sensor for On-Line Monitoring the Temperature and Velocity of Thermal Spray Particles

2000 ◽  
Author(s):  
G. Bourque ◽  
M. Lamontagne ◽  
C. Moreau
Keyword(s):  
Time Delay ◽  
Thermal Spray ◽  
Optical Fibers ◽  
Cross Correlation ◽  
Mean Velocity ◽  
Mean Temperature ◽  
On Line ◽  
Band Pass ◽  
The Mean ◽  
Thermal Spray Processes

Abstract In this paper, we describe a new sensor for monitoring inflight particles in thermal spray processes. The sensor can measure simultaneously and in real-time, the mean velocity and mean temperature of the particle jet for a very broad range of powder feed rates. The thermal radiation emitted by the hot particles is collected by a lens and focused on two optical fibers. Knowing the distance between the optical fibers and the magnification of the optics, the mean particle velocity is computed by measuring the time delay between the signals collected in the two fibers by cross-correlation. The signals are band-pass filtered to prevent spurious reflection, equipment movement and noise from disturbing the measurement. Using the same signals filtered at two specific wavelengths, the mean temperature of the particle jet is obtained by the two-color pyrometry technique. In this technique, the temperature is computed from the ratio of the light intensity detected at two different wavelengths.

Instantaneous velocity and temperature measurements in oscillating diffusion flames

1974 ◽  
Vol 338 (1615) ◽  
pp. 479-501 ◽  
Keyword(s):  
Diffusion Flames ◽  
Frequency Doubling ◽  
Instantaneous Velocity ◽  
Temperature Measurements ◽  
Mean Velocity ◽  
Temperature Distributions ◽  
Mean Temperature ◽  
Instantaneous Temperature ◽  
The Mean ◽  
The Many

Measurements of instantaneous velocity, instantaneous temperature, and the corresponding mean and r. m. s. values, obtained in a range of diffusion flames, are presented. The velocity measurements were obtained with a laser anemometer and the temperature measurements with a thermocouple. The flames were formed by burning methane, town gas and hydrogen at the exit from burner tubes of external diameters 15.0, 9.2, 6.3 and 3.2 mm; the corresponding inside diameters were 13.0, 5.1, 5.1 and 2.5 mm. The mean velocity of the gas at exit from the tube ranged from 0.6 to 5.3 m/s. All flames exhibited discrete frequencies in the vicinity of 11 Hz. The instantaneous velocity and temperature signals were close to sinusoidal, except in the vicinity of the reaction zone where double frequencies and spiky signals were observed. The r. m. s. temperature distributions exhibited minima in the region of the maximum values of mean temperature; the r. m. s. velocity distributions were similar in form but the location of the minimum occurred downstream of the corresponding r. m. s. temperature minimum. The minimum in the r. m. s. velocity and temperature distributions were consistant with the observed frequency doubling and stemmed from the need for the frequency to increase to allow an increase in mean temperature in regions where the instantaneous temperature had attained its adiabatic flame value. A flame model is postulated and shown to represent the many observed features of the oscillating flames. It appears that the oscillations stem from aerodynamic instabilities associated with inflexion points in the local, instantaneous velocity distributions.

Cross-Correlation Velocimetry for Measurement of Velocity and Temperature Profiles in Low-Speed, Turbulent, Nonisothermal Flows

1992 ◽  
Vol 114 (2) ◽  
pp. 331-337 ◽  
Author(s):  
V. Motevalli ◽  
C. H. Marks ◽  
B. J. McCaffrey
Keyword(s):  
Cross Correlation ◽  
Temperature Profiles ◽  
Fire Plume ◽  
Mean Velocity ◽  
Low Speed ◽  
Nonisothermal Flows ◽  
Degree Of Confidence ◽  
The Mean ◽  
Temperature Time ◽  
Better Than

A technique utilizing thermocouple pairs as sensors to measure velocity and temperature profiles in low-speed, turbulent, nonisothermal flows is described here. In this technique, Cross-Correlation Velocimetry (CCV), the temperature-time records from a pair of thermocouples, one downstream of the other, are cross-correlated to determine the flow’s preferred mean velocity while temperature is measured directly. The velocity measurements have undergone extensive verification using hotwire, pitot tube, and Laser-Doppler Velocimetry to determine the degree of confidence in this technique. This work demonstrates that the CCV technique is quite reliable and can measure the mean preferred component of the convective velocity with better than ±5 percent certainty. Application of this technique to the measurement of velocities in a ceiling jet induced by a fire plume is briefly presented here.

Hybrid RANS-LES Simulation of Turbulent Heat Transfer in a Channel Flow With Imposed Spanwise and Streamwise Mean Temperature Gradient

2019 ◽  
Author(s):  
Olalekan O. Shobayo ◽  
D. Keith Walters
Keyword(s):  
Heat Transfer ◽  
Temperature Gradient ◽  
Channel Flow ◽  
Plane Channel ◽  
Turbulent Heat Transfer ◽  
Turbulent Heat ◽  
Mean Velocity ◽  
Eddy Simulation ◽  
Mean Temperature ◽  
The Mean

Abstract Computational fluid dynamics (CFD) results for turbulent flow and heat transfer in a plane channel are presented. This study presents an idealized fully-developed planar channel flow case for which the mean velocity gradient is non-zero only in the wall-normal direction, and the mean temperature gradient is imposed to be uniform and non-zero in the streamwise or spanwise direction. Previous studies have documented direct numerical simulation results for periodic channel flow with mean temperature gradient in both the streamwise and wall-normal directions, but limited investigations exist documenting the effect of imposed spanwise gradient. The objective of this study is to evaluate turbulent heat flux predictions for three different classes of modeling approach: Reynolds-averaged Navier-Stokes (RANS), large-eddy simulation (LES), and hybrid RANS-LES. Results are compared to available DNS data at Prandtl number of 0.71 and Reynolds number of 180 based on friction velocity and channel half-width. Specific models evaluated include the k-ω SST RANS model, monotonically integrated LES (MILES), improved delayed detached eddy simulation (IDDES), and dynamic hybrid RANS-LES (DHRL). The DHRL model includes both the standard formulation that has been previously documented in the literature as well as a modified version developed specifically to improve predictive capability for flows in which the primary mean velocity and mean temperature gradients are not closely aligned. The modification consists of using separate RANS-to-LES blending parameters in the momentum and energy equations. Results are interrogated to evaluate the performance of the three different model types and specifically to evaluate the performance of the new modified DHRL variant compared with the baseline version.

scholarly journals Air Velocity, Air Temperature, Fiber Vibration and Fiber Diameter Measurements on a Practical Melt Blowing Die

2004 ◽  
Vol os-13 (3) ◽  
pp. 1558925004os-13 ◽  
Author(s):  
Eric M. Moore ◽  
Dimitrios V. Papavassiliou ◽  
Robert L. Shambaugh
Keyword(s):  
Fiber Diameter ◽  
Diameter Distribution ◽  
Process Conditions ◽  
Air Velocity ◽  
Melt Blowing ◽  
Mean Velocity ◽  
Slot Die ◽  
On Line ◽  
The Mean ◽  
Light Absorbance

Numerous measurements were taken during the operation of a practical melt blowing slot die. On-line measurements were taken of the mean velocity and temperature of the air jets. Also, on-line measurements of fiber vibration amplitude were done. Off-line measurements were taken to determine fiber diameter distributions in the nonwoven webs. The light absorbance of these non-woven mats was measured and related to fiber diameter distribution and mat basis weight. Process conditions were varied across the operating range of the die to produce a variety of finished mats. It was found that the mean air velocity and temperature decayed in a manner similar to that observed in both laboratory-scale melt blowing dies and (more generally) in rectangular jets. Fiber vibrations were found to be strongly dependent on operating temperature and air flow rate. The fiber light absorbance correlated well with the projected area of the fibers present in the mat.

Mean velocity of optically detected intraaxonal particles measured by a cross-correlation method

1976 ◽  
Vol 54 (6) ◽  
pp. 859-869 ◽  
Author(s):  
R. S. Smith ◽  
Z. J. Koles
Keyword(s):  
Cross Correlation ◽  
Correlation Method ◽  
Nerve Fibers ◽  
Mean Velocity ◽  
Myelinated Nerve ◽  
Optical Signals ◽  
Accuracy And Precision ◽  
Small Collection ◽  
The Mean ◽  
Optically Detected

A method which uses the cross correlation of optical signals is described for the determination of the mean velocity of somatopetally moving particles within nerve fibers. The method was validated by simulation experiments and by comparing the results with those obtained by averaging collections of velocities of individual particles. The significant contribution of the method is that it allows objective and rapid serial evaluations of mean particle velocity within individual nerve fibers with good accuracy and precision. A series of results from normal myelinated nerve fibers from Xenopus laevis is presented. Considerable variation (up to 50%) in mean velocity was found between individual nerve fibers. The mean of all determinations indicates that the mean velocity of somatopetally moving particles in axons with diameters > 10 μm is in the region of 1.14 μm/s at a temperature of 22–24 °C. The findings are compared with the small collection of such determinations which have been reported in the literature.

Correction to ‘Free convection effect on the oscillatory flow past an infinite, vertical, porous plate with constant suction. I’ (Soundalgekar, V. M. 1973)

1977 ◽  
Vol 353 (1673) ◽  
pp. 221-223 ◽  
Keyword(s):  
Free Convection ◽  
Skin Friction ◽  
Mathematical Reasoning ◽  
Frictional Heating ◽  
Porous Plate ◽  
Fluid Temperature ◽  
Mean Velocity ◽  
Plate Temperature ◽  
Mean Temperature ◽  
The Mean

In the paper noted in the title we have found a few mistakes and wish to correct them in this note. First we infer from the non-dimensional temperature θ (= ( T ' - T ' ∞ ) / ( T ' w - T ' ∞ )) and the Grashof number G (= ( T ' w - T ' ∞ ) / ∆ T with ∆ T = U 0 v 2 0 / vg x β ) that T ' ∞ only is kept constant and as G varies so does T ' w . For example, as G , being positive, takes increasing values T ' w increases and hence the fluid subsequently gets heated up as a result of heat-balance. Consequently we expect the fluid temperatures θ 0 (say, for a fixed Y ) to increase with positive G and to decrease with negative G and these results are not in evidence from figures 5-7 of Soundalgekar (1973), which are incorrect. That the results incorporated in and depicted by figures 5-7 cannot be all correct may be understood by a simple mathematical reasoning, namely: if E > 0, θ 0 cannot have a minimum as shown in figure 5 because from equation (20) of the reference, θ H 0 < 0 when θ ' 0 = 0 and if E < 0, θ 0 cannot have a maximum as shown in figure 7. Further it is necessary to know the quantitative nature of the errors committed in the paper. Therefore we have reworked out the problem and evaluated on I. B. M. 1620 the numerical values of the dimensionless mean velocity u 0 , the mean skin friction τ and the mean temperature θ 0 . We have found that the mean velocity diagrams, the values of the mean skin friction and the expression (37) for θ 0 are all correct. But the mean temperature profiles as shown in figures 5-7 are all incorrect! The correct values of the dimensionless mean temperature θ 0 have been presented in this note through figures 1-3. It is quite clear that θ 0 , as expected, increases with positive G significantly in the case of air ( P = 0.71). Physically it means that as the plate temperature T ' w increases (positive G increases) the fluid-temperature increases. This behaviour of θ 0 gets duly reversed when G , being negative, takes increasing values (see figure 3, P = 0.71). In the presence of free convection parameter G the mean temperature θ 0 increases as the frictional heating (positive E ) increases, a result in contrast to that reported by Soundalgekar. Moreover when the Prandtl number P is large, the effect of G (positive or negative) on θ 0 is almost insignificant - a result contrary to the one obtained by Soundalgekar.

Cross-Correlation Techniques Applied to Pulsating Flow Measurement

1970 ◽  
Vol 3 (6) ◽  
pp. T109-T112 ◽  
Author(s):  
S. A. Abeysekera ◽  
M. S. Beck
Keyword(s):  
Steady Flow ◽  
Transit Time ◽  
Cross Correlation ◽  
Pulsating Flow ◽  
Transitional Region ◽  
Mean Flow ◽  
Worst Case ◽  
On Line ◽  
The Mean ◽  
The Cross

A new method for measuring pulsating flow has been devised in which the mean flow velocity is derived from the transit time of temperature fluctuations between two points in a pipe. The transit time is determined from the cross-correlation of the temperatures at these points. The method has been tested with water and linear calibrations have been obtained in the laminar (Re. < 2000) and turbulent (Re. > 3000) regions, however it is non-linear in the transitional region (2000 < Re. < 3000). Tests with steady flow and pulsating flow with pulsation frequencies between 1 Hz and 5 Hz give very similar calibrations. In the worst case, on/off pulsations at 5 Hz, the deviation from the steady flow reading is only 8 per cent. The process transducers are robust thermocouples. The cross-correlation function can be computed by an on-line digital computer, alternatively one of the commercially available cross-correlators can be used.

scholarly journals Measurements of debris flow velocity through cross-correlation of instrumentation data

2005 ◽  
Vol 5 (1) ◽  
pp. 137-142 ◽  
Author(s):  
M. Arattano ◽  
L. Marchi
Keyword(s):  
Debris Flow ◽  
Cross Correlation ◽  
Time Lag ◽  
Ground Vibration ◽  
Front Velocity ◽  
Correlation Technique ◽  
Ultrasonic Sensors ◽  
Mean Velocity ◽  
Different Types ◽  
The Mean

Abstract. Detection of debris flow occurrence can be efficiently obtained through different types of sensors. A pair of ultrasonic sensors placed at a known distance from each other along a torrent have been used as a method to obtain mean front velocity of debris-flows, in addition to their use as detectors of debris flow occurrence. Also seismic and acoustic sensors have been employed to measure debris-flow front velocity and discharge in the same manner. In order to obtain velocity measurements, however, these methods require the presence of a well identifiable and defined main front in the debris flow wave. The time lag between the recordings of the front of the wave at two consecutive stations allows an estimation of its mean velocity. When a well-defined front is not present and no recurrent feature can be found along the wave, the measurement of velocity may prove difficult. The cross-correlation technique may help identifying the mean velocity of the flow in such cases. In fact, cross correlation allows to determine the mean time lag elapsed between the recording of two sets of data of the same event at different positions. This technique may be also used to measure velocity using signals coming from different types of sensors, for instance where a ground vibration detector has been placed along a torrent where an ultrasonic sensor was already present or viceversa. An application has been made using field data recorded through seismic and ultrasonic sensors in a small instrumented catchment in the Italian Alps (Moscardo Torrent).

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