In situ observation and measurement of composites subjected to extremely high temperature Xufei Fang, Helong Yu, Guobing Zhang, Hengqiang Su, Hongxiang Tang, and Xue Feng Citation: Review of Scientific Instruments 85, 035104 (2014); doi: 10.1063/1.4866975 View online: http://dx.doi.org/10.1063/1.4866975 View Table of Contents: http://scitation.aip.org/content/aip/journal/rsi/85/3?ver=pdfcov Published by the AIP Publishing Articles you may be interested in Diamond micro-Raman thermometers for accurate gate temperature measurements Appl. Phys. Lett. 104, 213503 (2014); 10.1063/1.4879849 Temperature recovery from degenerated infrared image based on the principle for temperature measurement using infrared sensor J. Appl. Phys. 115, 043522 (2014); 10.1063/1.4863783 Measurement of thermodynamic temperature of high temperature fixed points AIP Conf. Proc. 1552, 329 (2013); 10.1063/1.4819561 Infrared camera diagnostic for heat flux measurements on the National Spherical Torus Experiment Rev. Sci. Instrum. 74, 5090 (2003); 10.1063/1.1623625 Thermographic temperature determination of gray materials with an infrared camera in different environments Rev. Sci. Instrum. 68, 2422 (1997); 10.1063/1.1148127
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REVIEW OF SCIENTIFIC INSTRUMENTS 85, 035104 (2014)
In situ observation and measurement of composites subjected to extremely high temperature Xufei Fang,1 Helong Yu,2 Guobing Zhang,1 Hengqiang Su,2 Hongxiang Tang,2 and Xue Feng1,a) 1 2
AML, Department of Engineering Mechanics, Tsinghua University, Beijing 100084, China College of Information Technology, Jilin Agricultural University, Changchun 130118, China
(Received 2 January 2014; accepted 13 February 2014; published online 6 March 2014) In this work, we develop an instrument to study the ablation and oxidation process of materials such as C/SiC (carbon fiber reinforced silicon carbide composites) and ultra-high temperature ceramic in extremely high temperature environment. The instrument is integrated with high speed cameras with filtering lens, infrared thermometers and water vapor generator for image capture, temperature measurement, and humid atmosphere, respectively. The ablation process and thermal shock as well as the temperature on both sides of the specimen can be in situ monitored. The results show clearly the dynamic ablation and liquid oxide flowing. In addition, we develop an algorithm for the post-processing of the captured images to obtain the deformation of the specimens, in order to better understand the behavior of the specimen subjected to high temperature. © 2014 AIP Publishing LLC. [http://dx.doi.org/10.1063/1.4866975] I. INTRODUCTION
Power supply setup, such as engine and gas turbine, is usually subjected to high temperature environment to achieve efficient energy conversion. However, the condition of such environment is extremely complex mixing multi-physical coupling and chemical reaction,1 which challenges the reliability of materials and structures as it is very difficult to measure in situ the response of the materials. Due to the above reasons, an environmental simulation method is of great importance. For experimental simulation, there are mainly two types of methods. One is to simulate the whole environmental factors and directly obtain the results of the tests. Although this method is approaching closer and closer to the real working condition, the cost also rises steeply. Another way is to develop new simulation theories and experimental methods based on the physical and chemical interaction between the environment and the materials, and this method focuses on the simulation of controlled factors which may dominate the damage or fracture of the materials. However, due to the difficulties of determining such dominating factors, the simple models established at present all have certain limits. Thus, the comprehensive way of simulation is still under exploration and a balance between these two main types of simulation must be met. Moreover, the postprocessing as part of the simulation is also of great importance to better understand the evolution and fracture of the materials. In addition, for the development of engine efficiency, it is a key issue to study the ablation, oxidation, and fracture of the materials used in engines such as refractory metals, C/SiC, and ultra-high temperature ceramics (UHTCs) due to their excellent mechanical properties at high temperature.2–9 a) Author to whom correspondence should be addressed. Electronic mail:
[email protected]
0034-6748/2014/85(3)/035104/6/$30.00
Better understanding of the failure mechanisms of these materials means more potentiality to improve the performance of them and for wider application as well. As mentioned above, high temperature induces chemical reaction (e.g., oxidation) and chemo-mechanical coupling effects.1, 10 Usually, materials oxidize first at high temperature and the oxide film grows on the surface of materials. Thus, film stress can control the oxidation and reliability of materials.11–16 Therefore, real-time observation and measurement of the oxidation, ablation, or fracture evolution will contribute a lot to the improvements in such areas. Due to the transient properties of such processes, high-speed recording technique is required. For example, Shukla et al.17, 18 used high-speed camera to record the dynamic transient response of sandwich composites exposed to highly transient shock loadings which revealed new important features of the transient deformation and fracture process. Close range high speed photogrammetry was also used for the measurement of the soil nail walls for displacement due to its simplicity, low cost, high efficiency and high speed.19 Wang et al.20 carried out experiment on the conventional Taylor bar set-up and obtained the dynamic stress-strain curves by means of a high speed camera and the dynamic Digital Image Correlation (DIC) technique. However, the application of high-speed camera to observe the ablation or oxidation process is yet to be improved. In this work, we present an integrated instrument to provide a comprehensive method to study the materials such as C/SiC composites and UHTCs at high temperature in simulated environment, such as in combustion chamber of engine. The apparatus is integrated with high speed camera for image capturing, infrared thermometer for temperature measuring, and water vapor generator for providing a humid atmosphere to simulate the combustion when necessary. This equipment can be used to capture the oxidation and ablation process for realtime recording and measurement.
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II. EXPERIMENTAL SETUP AND MEASUREMENT PRINCIPLE A. Experimental set up
The whole setup includes a basic ablation testing stage and can also be extended for wider application. Fang et al.9 integrated this setup into a steel chamber by supplying a water vapor generating device and humidity sensor to simulate the combustion chamber environment. The basic setup consists of an oxyacetylene heating system, a temperature measuring system, an image collecting and processing system, and a specimen holding stage. The image acquisition and processing system consists of two high speed cameras with filtering lens to capture the evolution process on both sides of the specimen. The high speed cameras were controlled by a single computer with a trigger, so that the images from both cameras can be synchronized. It is also necessary to have light compensation for the image capturing due to the filtering lens fixed onto the camera lens. The temperature measuring system consists of two infrared radiation thermometers, both controlled by a second computer with a trigger in order to record both surfaces of the specimen for synchronization. The specimen holding stage has three parts, a slide rail, a support bar, and a clamp. The clamp is on top of the support bar, which is further attached on the slide rail and can be moved towards or away from the oxyacetylene torch nozzle to adjust the ablation distance for the specimen. Furthermore, for the integration of the water vapor generating system, a water vapor monitor, a water vapor generator, and a humidity sensor was used. The humidity monitor records the real time vapor percentage and gives feedback to the water vapor monitor to control the generation rate of the water vapor in order to maintain a stable water vapor supplement. The whole set up shown in Fig. 1 is developed based on our previous setup for ablation test.9 Image processing technology is used to analyze and measure the morphology and deformation of specimens. The
FIG. 1. Scheme of the apparatus for ablation simulation integrated with high speed camera, infrared thermometers, and water vapor generator.
FIG. 2. Black body thermal emission intensity as a function of wavelength for various absolute temperatures.
image processing section consists mainly of two steps. The first step is to capture high resolution images at high temperature with strong radiation. Here, we applied band-pass filtering with the specified filter lens to avoid the radiation. The second step is to process the images obtained in the experiment and process the images themselves. We discuss these two steps in detail in the following.
B. The principle of band-filtering method at high temperature
Materials emit strong radiation on the surface at high temperature during the ablation test. This disturbs the detection of the surface evolution. In order to avoid the ambient temperature effects and changes in effective wavelength, we utilized a variety of band-pass filters to observe the surface of the material at high temperature.21 The method is based on Wien’s law, as is shown in Fig. 2. It should be noted that there is a great difference of temperature between the flame and the surface of the material. The hotter an object is the shorter the wavelength at which it emits most of its radiation. Thus, the longer band-pass method is frequently used to avoid detecting the radiation from the flame and to restrict the emitted radiation to being mainly from the surface of the material. Figure 3 shows an example by using band-pass filtering method and light compensation method. Figure 3(a) shows the original image captured for the surface of the specimen, Fig. 3(b) shows an image captured with strong radiation, which makes the surface information of the specimen hard to distinguish. In Fig. 3(c), the filtering system is added, which strongly reduced the light intensity, and results in a dark image. In Fig. 3(d), it shows that on the basis of the system shown in Fig. 3(c), by using proper light compensation, we obtained clear image of the surface at high temperature with strong radiation. As shown above, this method can effectively reduce the high temperature radiation disturbance and capture clear and
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Rev. Sci. Instrum. 85, 035104 (2014)
FIG. 3. Filtering and light compensation method at high temperature.
stable images in the environment with radiation, smog, air flow convection and so on. C. The basic principle of image processing
The marks or speckles on specimen surface are usually used to measure the deformation. However, in high temperature environment with ablation test, the marks or speckles change greatly due to oxidation and thermal stress. Thus, the methods with respect to marks or speckles (e.g., digital image correlation method) become invalid. Here, we introduce the method of Maximally Stable Extremal Regions (MSER) for features detection in images. The features of specimen with oxidation can be still obtained even when the marks or speckles changed, and so these features can be used to compute the specimen displacement and deformation. This MSER technique was proposed by Matas et al.22 to find the maximum stable (i.e., unchanged) region correspondences between image elements from two images with different viewpoints. MSER in most cases has the highest scores in detecting the changes between two continuous images. We utilized its properties to measure the deformation at high temperature for oxidation ablation between two continuous images and further give the strain fields of the specimen. The basic algorithm principle is shown in Fig. 4. After we detect the local invariant features by using MSER method, it is necessary to quantitatively describe the detected features, i.e., to find proper feature describing method (feature descriptor) for MSER features. Mikolajczyk et al.23 studied most of the feature descriptors and found that scale-invariant feature transform (SIFT) descriptor has the best property under most circumstances. SIFT is a computer vision algorithm to detect and describe local features
in images.24 In our work, we combine the MSER feature regions and SIFT descriptor together and propose a more robust method for high temperature image correlation. Here is an example to illustrate the computing process of the deformation by using MSER method and SIFT descriptor. The region to be calculated (as the blue area showed in Fig. 5) in the reference image is divided into a virtual mesh form when using the MSER method to compute the displacement and deformation. The full field displacement is obtained by estimating the displacements of each mesh node. The distance (calculating step) between two mesh nodes is selected from 2 to 10 pixels. In the calculation for displacements and deformations, the area centered at a point (x0 , y0 ) to be computed with a size of (2M + 1) × (2M + 1) pixels in the reference image is selected as the sub-region (as showed in Fig. 5). The MSER feature region detection is applied in the subset and then several MSERs are obtained. Then by using SIFT descriptor to describe the points in the stable regions (here it should be noted that since the region is already detected to be stable, it is assumed that the points detected and described by SIFT descriptor is also stable), then we can conduct the deformation calculation by comparing these correlated points in the reference and current images, illustrated in Fig. 6. For the point N in Fig. 6, we have x = x + uN = x + u +
∂u ∂u x + y, ∂x ∂y
∂v ∂v y = y + vN = y + v + x + y. ∂x ∂y
(1)
Then the displacement and deformation could be obtained by Eq. (1).
FIG. 4. Algorithm and calculation process for deformation.
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FIG. 6. Correlated points in the reference and current images (before and after deformation, respectively). FIG. 5. Computing region and MSER detection for speckle image.
III. EXPERIMENTAL RESULTS AND DISCUSSION A. Experiment of UHTC
Here, we first present an example of experiment conducted on UHTC specimen subjected to oxyacetylene ablation. The size of the specimen is 30 mm × 30 mm × 3 mm. As is known, the UHTC materials are sensitive to thermal shock.25, 26 In order to avoid the specimen cracking (since in this work we focus on the oxidation evolution of the materials rather than thermal shock), we adjusted the flux of the mixed gas to control the thermal heat density on the one hand, and by controlling the distance between the nozzle of the heating device and the surface of the specimen to make the specimen be heated in a steady state, then by gradually shortening the distance by making the nozzle tip approaching the surface of the specimen closer and by raising the flux of the mixed gas to increase the temperature to which the specimen was subject. The surface temperature was measured by using infrared thermometer (Raytek, USA), and the surface evolution was recorded by using high speed camera (Redlake-X3) from the front (while the back surface was being heated). A band-pass filter lens was placed on the camera to filter the strong radiation. The results are shown in Fig. 7. The result could be bet-
ter and clearer if higher speed camera were used. The surface evolution was recorded and the phase transition (SiO2 oxide transforms from solid state to liquid state) was also clearly observed while the surface temperature was 1800 ◦ C measured by the infrared thermometer. As we can see in Fig. 7(a), the shining and white area in the middle of the specimen represents the surface reaction process, and Fig. 7(b) shows more clearly a dark circle around the middle shining part, which indicates the heat conducting process as well as Fig. 7(c). In fact, the dark circle shown in Figs. 7(b) and 7(c) propagates wavelike with a changing of its brightness. In order to illustrate the computation of strain, we conduct the MSER method to obtain the in-plane strain. We use the surface texture of UHTC as speckles and obtain the local features by MSER method. Then we can compute the displacement and deformation by correlating the local features as described above. Figure 8 shows the in-plane strain field of blue rectangle in Fig. 7(b). It is found the center of the specimen (i.e., the heating spot) is subjected to maximal deformation due to the thermal stress as is expected. B. Experiment of C/SiC
Here, we present another example of experiment conducted on C/SiC specimen. The specimen was ablated in the
FIG. 7. Morphologies of UHTC specimen at different times in the ablation process at 2100 ◦ C: (a) t = 0 s; (b) t = 5 s; and (c) t = 10 s.
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FIG. 8. Strain fields measured by using the MSER method for specimens: (a)εxx ; (b)ε yy ; and (c)ε xy .
simulative combustion chamber by using oxyacetylene heating system, the surface evolution of the C/SiC specimen was recorded by using high speed camera (Redlake-X3) with a frame speed of 500 frames per second. The infrared thermometer showed the temperature on the front surface of the specimen varied from 1750 ◦ C to 1800 ◦ C. The surface morphology of specimens is shown in Fig. 9(a). The white beads are the liquid SiO2 generated due to the thermal ablation. The newly generated liquid SiO2 are in the center on the surface of the specimen, and was driven to the outside area by the flushing force of the flowing gas (with a speed of approximately 100 m/s). The liquid SiO2 are very tiny at the beginning of its generation with an average diameter of 200 μm, while it grows bigger and bigger as it was flushed to the outside of the ablation pit. As shown in Fig. 9(a), the mean diameter of the liquid SiO2 beads around the outside circle of the ablation pit are approximately 1 mm. Furthermore, we use the features detection method proposed above to compute the velocity field of the flowing liquid SiO2 . The red spots marked in Fig. 9(b) show correspondingly the marked positions of the generated fluid SiO2 (white beads shown in Fig. 9(a)) to trace the flow routine of them by using image processing technique, which is based on the local invariant characterization of the image. Then based on the method introduced above, the corresponding velocity field can be calculated and is given in Fig. 9(c)
to show the surface evolution of the generated liquid SiO2 beads. Thus, we not only can clearly observe the evolution of the reactive product, the generated liquid SiO2 , but also we can obtain the flowing speed of them. If a more advanced recording equipment and more accurate feature detection technique was available, the fusing process of the liquid SiO2 could even be obtained from the presented images. IV. CONCLUSION
Equipment for thermal ablation test was developed and integrated with high speed camera system, thermometers, and water vapor generator. With this equipment, it realizes the simulation of materials such as UHTCs and C/SiC used in combustion chamber with water vapor, oxygen pressure, controlling and integrating the high speed photography and temperature measurement at the same time. The ablation process and evolution can be recorded in situ. By slowing down the video of the high speed photography, the oxide formation, flow, and evolution process can be clearly seen and further analyzed. In the post-processing section, we developed a new image processing technique to calculate the deformation and analyze the oxidation of the specimens and to further understand the behavior of the specimen subjected to high temperature.
FIG. 9. (a) Ablation process of C/SiC with generated liquid SiO2 ; (b) characteristic points labeled in the captured image; and (c) velocity field of the liquid SiO2 beads.
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ACKNOWLEDGMENTS
We gratefully acknowledge the support from National Natural Science Foundation of China (Grant Nos. 11222220, 11227801, 11320101001, 11002078, and 11372155) and Tsinghua University Initiative Scientific Research Program (No. 2011Z02173). 1 K.
Loeffel and L. Anand, Int. J. Plast. 27, 1409 (2011). Krenkel, B. Heidenreich, and R. Renz, Adv. Eng. Mater. 4, 427 (2002). 3 R. Naslain, A. Guette, F. Rebillat, R. Pailler, F. Langlais, and X. Bourrat, J. Solid State Chem. 177, 449 (2004). 4 F. Monteverde, S. Guicciardi, and A. Bellosi, Mater. Sci. Eng., A 346, 310 (2003). 5 F. Monteverde, A. Bellosi, and L. Scatteia, Mater. Sci. Eng., A 485, 415 (2008). 6 C. Morz, Am. Ceram. Soc. Bull. 73, 141 (1994). 7 S. R. Levine, E. J. Opila, M. C. Halbig, J. D. Kiser, M. Singh, and J. A. Salem, J. Eur. Ceram. Soc. 22, 2757 (2002). 8 A. L. Chamberlain, W. G. Fahrenholtz, G. E. Hilmas, and D. T. Ellerby, J. Am. Ceram. Soc. 87, 1170 (2004). 9 X. F. Fang, F. S. Liu, H. Q. Su, and X. Feng, Ceram. Int. 40, 2985 (2014). 10 X. L. Dong, X. F. Fang, X. Feng, and K. C. Hwang, J. Am. Ceram. Soc. 96, 44 (2013). 2 W.
Rev. Sci. Instrum. 85, 035104 (2014) 11 Jianli
Ruan, Xue Feng, Guobing Zhang, Yong Wang, and Daining Fang, “Dynamic thermoelastic analysis of a slab using finite integral transformation method,” AIAA J. 48, 1833–1839 (2010). 12 X. L. Dong, X. Feng, and K. C. Hwang, J. Appl. Phys. 112, 023502 (2012). 13 M. A. Brown, A. J. Rosakis, X. Feng, Y. Huang, and E. Ustundag, Int. J. Solids Struct. 44, 1755 (2007). 14 X. Feng, Y. Huang, and A. J. Rosakis, Int. J. Solids Struct. 45, 3688 (2008). 15 X. Feng, Y. Huang, and A. J. Rosakis, J. Appl. Mech. 74, 1276 (2007). 16 X. Feng, Y. Huang, and A. J. Rosakis, J. Appl. Mech. 75, 021022 (2008). 17 S. A. Tekalur, A. E. Bogdanovich, and A. Shukla, Compos. Sci. Technol. 69, 736 (2009). 18 M. Jackson and A. Shukla, Composites, Part B 42, 155 (2011). 19 F. Esmaeili, M. Varshosaz, and H. Ebadi, Measurement 46, 3449 (2013). 20 L. Wang, Y. Ding, and L. Yang, Int. J. Impact Eng. 62, 48 (2013). 21 D. R. LoveJoy, J. Opt. Soc. Am. 50, 698 (1960). 22 J. Matas, O. Chum, M. Urban, and T. Pajdla, Image Vision Comput. 22, 761 (2004). 23 K. Mikolajczyk, T. Tuytelaars, C. Schmid, A. Zisserman, T. Kadir, and L. Van Gool, Int. J. Comput. Vision 65, 43 (2005). 24 D. G. Lowe, “Object recognition from local scale-invariant features,” in The Proceedings of the Seventh IEEE International Conference on Computer Vision, 1999 (IEEE, 1999), Vol. 2, p. 1150. 25 A. Paul, S. Venugopal, J. G. P. Binner, B. Vaidhyanathan, A. C. J. Heaton, and P. M. Brown, J. Eur. Ceram. Soc. 33, 423 (2013). 26 I. G. Talmy, J. A. Zaykoski, and M. M. Opeka, J. Eur. Ceram. Soc. 30, 2253 (2010).
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REVIEW OF SCIENTIFIC INSTRUMENTS 85, 035104 (2014)
In situ observation and measurement of composites subjected to extremely high temperature Xufei Fang,1 Helong Yu,2 Guobing Zhang,1 Hengqiang Su,2 Hongxiang Tang,2 and Xue Feng1,a) 1 2
AML, Department of Engineering Mechanics, Tsinghua University, Beijing 100084, China College of Information Technology, Jilin Agricultural University, Changchun 130118, China
(Received 2 January 2014; accepted 13 February 2014; published online 6 March 2014) In this work, we develop an instrument to study the ablation and oxidation process of materials such as C/SiC (carbon fiber reinforced silicon carbide composites) and ultra-high temperature ceramic in extremely high temperature environment. The instrument is integrated with high speed cameras with filtering lens, infrared thermometers and water vapor generator for image capture, temperature measurement, and humid atmosphere, respectively. The ablation process and thermal shock as well as the temperature on both sides of the specimen can be in situ monitored. The results show clearly the dynamic ablation and liquid oxide flowing. In addition, we develop an algorithm for the post-processing of the captured images to obtain the deformation of the specimens, in order to better understand the behavior of the specimen subjected to high temperature. © 2014 AIP Publishing LLC. [http://dx.doi.org/10.1063/1.4866975] I. INTRODUCTION
Power supply setup, such as engine and gas turbine, is usually subjected to high temperature environment to achieve efficient energy conversion. However, the condition of such environment is extremely complex mixing multi-physical coupling and chemical reaction,1 which challenges the reliability of materials and structures as it is very difficult to measure in situ the response of the materials. Due to the above reasons, an environmental simulation method is of great importance. For experimental simulation, there are mainly two types of methods. One is to simulate the whole environmental factors and directly obtain the results of the tests. Although this method is approaching closer and closer to the real working condition, the cost also rises steeply. Another way is to develop new simulation theories and experimental methods based on the physical and chemical interaction between the environment and the materials, and this method focuses on the simulation of controlled factors which may dominate the damage or fracture of the materials. However, due to the difficulties of determining such dominating factors, the simple models established at present all have certain limits. Thus, the comprehensive way of simulation is still under exploration and a balance between these two main types of simulation must be met. Moreover, the postprocessing as part of the simulation is also of great importance to better understand the evolution and fracture of the materials. In addition, for the development of engine efficiency, it is a key issue to study the ablation, oxidation, and fracture of the materials used in engines such as refractory metals, C/SiC, and ultra-high temperature ceramics (UHTCs) due to their excellent mechanical properties at high temperature.2–9 a) Author to whom correspondence should be addressed. Electronic mail:
[email protected]
0034-6748/2014/85(3)/035104/6/$30.00
Better understanding of the failure mechanisms of these materials means more potentiality to improve the performance of them and for wider application as well. As mentioned above, high temperature induces chemical reaction (e.g., oxidation) and chemo-mechanical coupling effects.1, 10 Usually, materials oxidize first at high temperature and the oxide film grows on the surface of materials. Thus, film stress can control the oxidation and reliability of materials.11–16 Therefore, real-time observation and measurement of the oxidation, ablation, or fracture evolution will contribute a lot to the improvements in such areas. Due to the transient properties of such processes, high-speed recording technique is required. For example, Shukla et al.17, 18 used high-speed camera to record the dynamic transient response of sandwich composites exposed to highly transient shock loadings which revealed new important features of the transient deformation and fracture process. Close range high speed photogrammetry was also used for the measurement of the soil nail walls for displacement due to its simplicity, low cost, high efficiency and high speed.19 Wang et al.20 carried out experiment on the conventional Taylor bar set-up and obtained the dynamic stress-strain curves by means of a high speed camera and the dynamic Digital Image Correlation (DIC) technique. However, the application of high-speed camera to observe the ablation or oxidation process is yet to be improved. In this work, we present an integrated instrument to provide a comprehensive method to study the materials such as C/SiC composites and UHTCs at high temperature in simulated environment, such as in combustion chamber of engine. The apparatus is integrated with high speed camera for image capturing, infrared thermometer for temperature measuring, and water vapor generator for providing a humid atmosphere to simulate the combustion when necessary. This equipment can be used to capture the oxidation and ablation process for realtime recording and measurement.
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Rev. Sci. Instrum. 85, 035104 (2014)
II. EXPERIMENTAL SETUP AND MEASUREMENT PRINCIPLE A. Experimental set up
The whole setup includes a basic ablation testing stage and can also be extended for wider application. Fang et al.9 integrated this setup into a steel chamber by supplying a water vapor generating device and humidity sensor to simulate the combustion chamber environment. The basic setup consists of an oxyacetylene heating system, a temperature measuring system, an image collecting and processing system, and a specimen holding stage. The image acquisition and processing system consists of two high speed cameras with filtering lens to capture the evolution process on both sides of the specimen. The high speed cameras were controlled by a single computer with a trigger, so that the images from both cameras can be synchronized. It is also necessary to have light compensation for the image capturing due to the filtering lens fixed onto the camera lens. The temperature measuring system consists of two infrared radiation thermometers, both controlled by a second computer with a trigger in order to record both surfaces of the specimen for synchronization. The specimen holding stage has three parts, a slide rail, a support bar, and a clamp. The clamp is on top of the support bar, which is further attached on the slide rail and can be moved towards or away from the oxyacetylene torch nozzle to adjust the ablation distance for the specimen. Furthermore, for the integration of the water vapor generating system, a water vapor monitor, a water vapor generator, and a humidity sensor was used. The humidity monitor records the real time vapor percentage and gives feedback to the water vapor monitor to control the generation rate of the water vapor in order to maintain a stable water vapor supplement. The whole set up shown in Fig. 1 is developed based on our previous setup for ablation test.9 Image processing technology is used to analyze and measure the morphology and deformation of specimens. The
FIG. 1. Scheme of the apparatus for ablation simulation integrated with high speed camera, infrared thermometers, and water vapor generator.
FIG. 2. Black body thermal emission intensity as a function of wavelength for various absolute temperatures.
image processing section consists mainly of two steps. The first step is to capture high resolution images at high temperature with strong radiation. Here, we applied band-pass filtering with the specified filter lens to avoid the radiation. The second step is to process the images obtained in the experiment and process the images themselves. We discuss these two steps in detail in the following.
B. The principle of band-filtering method at high temperature
Materials emit strong radiation on the surface at high temperature during the ablation test. This disturbs the detection of the surface evolution. In order to avoid the ambient temperature effects and changes in effective wavelength, we utilized a variety of band-pass filters to observe the surface of the material at high temperature.21 The method is based on Wien’s law, as is shown in Fig. 2. It should be noted that there is a great difference of temperature between the flame and the surface of the material. The hotter an object is the shorter the wavelength at which it emits most of its radiation. Thus, the longer band-pass method is frequently used to avoid detecting the radiation from the flame and to restrict the emitted radiation to being mainly from the surface of the material. Figure 3 shows an example by using band-pass filtering method and light compensation method. Figure 3(a) shows the original image captured for the surface of the specimen, Fig. 3(b) shows an image captured with strong radiation, which makes the surface information of the specimen hard to distinguish. In Fig. 3(c), the filtering system is added, which strongly reduced the light intensity, and results in a dark image. In Fig. 3(d), it shows that on the basis of the system shown in Fig. 3(c), by using proper light compensation, we obtained clear image of the surface at high temperature with strong radiation. As shown above, this method can effectively reduce the high temperature radiation disturbance and capture clear and
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FIG. 3. Filtering and light compensation method at high temperature.
stable images in the environment with radiation, smog, air flow convection and so on. C. The basic principle of image processing
The marks or speckles on specimen surface are usually used to measure the deformation. However, in high temperature environment with ablation test, the marks or speckles change greatly due to oxidation and thermal stress. Thus, the methods with respect to marks or speckles (e.g., digital image correlation method) become invalid. Here, we introduce the method of Maximally Stable Extremal Regions (MSER) for features detection in images. The features of specimen with oxidation can be still obtained even when the marks or speckles changed, and so these features can be used to compute the specimen displacement and deformation. This MSER technique was proposed by Matas et al.22 to find the maximum stable (i.e., unchanged) region correspondences between image elements from two images with different viewpoints. MSER in most cases has the highest scores in detecting the changes between two continuous images. We utilized its properties to measure the deformation at high temperature for oxidation ablation between two continuous images and further give the strain fields of the specimen. The basic algorithm principle is shown in Fig. 4. After we detect the local invariant features by using MSER method, it is necessary to quantitatively describe the detected features, i.e., to find proper feature describing method (feature descriptor) for MSER features. Mikolajczyk et al.23 studied most of the feature descriptors and found that scale-invariant feature transform (SIFT) descriptor has the best property under most circumstances. SIFT is a computer vision algorithm to detect and describe local features
in images.24 In our work, we combine the MSER feature regions and SIFT descriptor together and propose a more robust method for high temperature image correlation. Here is an example to illustrate the computing process of the deformation by using MSER method and SIFT descriptor. The region to be calculated (as the blue area showed in Fig. 5) in the reference image is divided into a virtual mesh form when using the MSER method to compute the displacement and deformation. The full field displacement is obtained by estimating the displacements of each mesh node. The distance (calculating step) between two mesh nodes is selected from 2 to 10 pixels. In the calculation for displacements and deformations, the area centered at a point (x0 , y0 ) to be computed with a size of (2M + 1) × (2M + 1) pixels in the reference image is selected as the sub-region (as showed in Fig. 5). The MSER feature region detection is applied in the subset and then several MSERs are obtained. Then by using SIFT descriptor to describe the points in the stable regions (here it should be noted that since the region is already detected to be stable, it is assumed that the points detected and described by SIFT descriptor is also stable), then we can conduct the deformation calculation by comparing these correlated points in the reference and current images, illustrated in Fig. 6. For the point N in Fig. 6, we have x = x + uN = x + u +
∂u ∂u x + y, ∂x ∂y
∂v ∂v y = y + vN = y + v + x + y. ∂x ∂y
(1)
Then the displacement and deformation could be obtained by Eq. (1).
FIG. 4. Algorithm and calculation process for deformation.
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FIG. 6. Correlated points in the reference and current images (before and after deformation, respectively). FIG. 5. Computing region and MSER detection for speckle image.
III. EXPERIMENTAL RESULTS AND DISCUSSION A. Experiment of UHTC
Here, we first present an example of experiment conducted on UHTC specimen subjected to oxyacetylene ablation. The size of the specimen is 30 mm × 30 mm × 3 mm. As is known, the UHTC materials are sensitive to thermal shock.25, 26 In order to avoid the specimen cracking (since in this work we focus on the oxidation evolution of the materials rather than thermal shock), we adjusted the flux of the mixed gas to control the thermal heat density on the one hand, and by controlling the distance between the nozzle of the heating device and the surface of the specimen to make the specimen be heated in a steady state, then by gradually shortening the distance by making the nozzle tip approaching the surface of the specimen closer and by raising the flux of the mixed gas to increase the temperature to which the specimen was subject. The surface temperature was measured by using infrared thermometer (Raytek, USA), and the surface evolution was recorded by using high speed camera (Redlake-X3) from the front (while the back surface was being heated). A band-pass filter lens was placed on the camera to filter the strong radiation. The results are shown in Fig. 7. The result could be bet-
ter and clearer if higher speed camera were used. The surface evolution was recorded and the phase transition (SiO2 oxide transforms from solid state to liquid state) was also clearly observed while the surface temperature was 1800 ◦ C measured by the infrared thermometer. As we can see in Fig. 7(a), the shining and white area in the middle of the specimen represents the surface reaction process, and Fig. 7(b) shows more clearly a dark circle around the middle shining part, which indicates the heat conducting process as well as Fig. 7(c). In fact, the dark circle shown in Figs. 7(b) and 7(c) propagates wavelike with a changing of its brightness. In order to illustrate the computation of strain, we conduct the MSER method to obtain the in-plane strain. We use the surface texture of UHTC as speckles and obtain the local features by MSER method. Then we can compute the displacement and deformation by correlating the local features as described above. Figure 8 shows the in-plane strain field of blue rectangle in Fig. 7(b). It is found the center of the specimen (i.e., the heating spot) is subjected to maximal deformation due to the thermal stress as is expected. B. Experiment of C/SiC
Here, we present another example of experiment conducted on C/SiC specimen. The specimen was ablated in the
FIG. 7. Morphologies of UHTC specimen at different times in the ablation process at 2100 ◦ C: (a) t = 0 s; (b) t = 5 s; and (c) t = 10 s.
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FIG. 8. Strain fields measured by using the MSER method for specimens: (a)εxx ; (b)ε yy ; and (c)ε xy .
simulative combustion chamber by using oxyacetylene heating system, the surface evolution of the C/SiC specimen was recorded by using high speed camera (Redlake-X3) with a frame speed of 500 frames per second. The infrared thermometer showed the temperature on the front surface of the specimen varied from 1750 ◦ C to 1800 ◦ C. The surface morphology of specimens is shown in Fig. 9(a). The white beads are the liquid SiO2 generated due to the thermal ablation. The newly generated liquid SiO2 are in the center on the surface of the specimen, and was driven to the outside area by the flushing force of the flowing gas (with a speed of approximately 100 m/s). The liquid SiO2 are very tiny at the beginning of its generation with an average diameter of 200 μm, while it grows bigger and bigger as it was flushed to the outside of the ablation pit. As shown in Fig. 9(a), the mean diameter of the liquid SiO2 beads around the outside circle of the ablation pit are approximately 1 mm. Furthermore, we use the features detection method proposed above to compute the velocity field of the flowing liquid SiO2 . The red spots marked in Fig. 9(b) show correspondingly the marked positions of the generated fluid SiO2 (white beads shown in Fig. 9(a)) to trace the flow routine of them by using image processing technique, which is based on the local invariant characterization of the image. Then based on the method introduced above, the corresponding velocity field can be calculated and is given in Fig. 9(c)
to show the surface evolution of the generated liquid SiO2 beads. Thus, we not only can clearly observe the evolution of the reactive product, the generated liquid SiO2 , but also we can obtain the flowing speed of them. If a more advanced recording equipment and more accurate feature detection technique was available, the fusing process of the liquid SiO2 could even be obtained from the presented images. IV. CONCLUSION
Equipment for thermal ablation test was developed and integrated with high speed camera system, thermometers, and water vapor generator. With this equipment, it realizes the simulation of materials such as UHTCs and C/SiC used in combustion chamber with water vapor, oxygen pressure, controlling and integrating the high speed photography and temperature measurement at the same time. The ablation process and evolution can be recorded in situ. By slowing down the video of the high speed photography, the oxide formation, flow, and evolution process can be clearly seen and further analyzed. In the post-processing section, we developed a new image processing technique to calculate the deformation and analyze the oxidation of the specimens and to further understand the behavior of the specimen subjected to high temperature.
FIG. 9. (a) Ablation process of C/SiC with generated liquid SiO2 ; (b) characteristic points labeled in the captured image; and (c) velocity field of the liquid SiO2 beads.
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ACKNOWLEDGMENTS
We gratefully acknowledge the support from National Natural Science Foundation of China (Grant Nos. 11222220, 11227801, 11320101001, 11002078, and 11372155) and Tsinghua University Initiative Scientific Research Program (No. 2011Z02173). 1 K.
Loeffel and L. Anand, Int. J. Plast. 27, 1409 (2011). Krenkel, B. Heidenreich, and R. Renz, Adv. Eng. Mater. 4, 427 (2002). 3 R. Naslain, A. Guette, F. Rebillat, R. Pailler, F. Langlais, and X. Bourrat, J. Solid State Chem. 177, 449 (2004). 4 F. Monteverde, S. Guicciardi, and A. Bellosi, Mater. Sci. Eng., A 346, 310 (2003). 5 F. Monteverde, A. Bellosi, and L. Scatteia, Mater. Sci. Eng., A 485, 415 (2008). 6 C. Morz, Am. Ceram. Soc. Bull. 73, 141 (1994). 7 S. R. Levine, E. J. Opila, M. C. Halbig, J. D. Kiser, M. Singh, and J. A. Salem, J. Eur. Ceram. Soc. 22, 2757 (2002). 8 A. L. Chamberlain, W. G. Fahrenholtz, G. E. Hilmas, and D. T. Ellerby, J. Am. Ceram. Soc. 87, 1170 (2004). 9 X. F. Fang, F. S. Liu, H. Q. Su, and X. Feng, Ceram. Int. 40, 2985 (2014). 10 X. L. Dong, X. F. Fang, X. Feng, and K. C. Hwang, J. Am. Ceram. Soc. 96, 44 (2013). 2 W.
Rev. Sci. Instrum. 85, 035104 (2014) 11 Jianli
Ruan, Xue Feng, Guobing Zhang, Yong Wang, and Daining Fang, “Dynamic thermoelastic analysis of a slab using finite integral transformation method,” AIAA J. 48, 1833–1839 (2010). 12 X. L. Dong, X. Feng, and K. C. Hwang, J. Appl. Phys. 112, 023502 (2012). 13 M. A. Brown, A. J. Rosakis, X. Feng, Y. Huang, and E. Ustundag, Int. J. Solids Struct. 44, 1755 (2007). 14 X. Feng, Y. Huang, and A. J. Rosakis, Int. J. Solids Struct. 45, 3688 (2008). 15 X. Feng, Y. Huang, and A. J. Rosakis, J. Appl. Mech. 74, 1276 (2007). 16 X. Feng, Y. Huang, and A. J. Rosakis, J. Appl. Mech. 75, 021022 (2008). 17 S. A. Tekalur, A. E. Bogdanovich, and A. Shukla, Compos. Sci. Technol. 69, 736 (2009). 18 M. Jackson and A. Shukla, Composites, Part B 42, 155 (2011). 19 F. Esmaeili, M. Varshosaz, and H. Ebadi, Measurement 46, 3449 (2013). 20 L. Wang, Y. Ding, and L. Yang, Int. J. Impact Eng. 62, 48 (2013). 21 D. R. LoveJoy, J. Opt. Soc. Am. 50, 698 (1960). 22 J. Matas, O. Chum, M. Urban, and T. Pajdla, Image Vision Comput. 22, 761 (2004). 23 K. Mikolajczyk, T. Tuytelaars, C. Schmid, A. Zisserman, T. Kadir, and L. Van Gool, Int. J. Comput. Vision 65, 43 (2005). 24 D. G. Lowe, “Object recognition from local scale-invariant features,” in The Proceedings of the Seventh IEEE International Conference on Computer Vision, 1999 (IEEE, 1999), Vol. 2, p. 1150. 25 A. Paul, S. Venugopal, J. G. P. Binner, B. Vaidhyanathan, A. C. J. Heaton, and P. M. Brown, J. Eur. Ceram. Soc. 33, 423 (2013). 26 I. G. Talmy, J. A. Zaykoski, and M. M. Opeka, J. Eur. Ceram. Soc. 30, 2253 (2010).
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