Acquisition and Analysis of Continuous Acoustic Emission Waveform for Classification of Damage Sources in Ceramic Fiber Mat

Similar documents
DAMAGE EVALUATION BY FREQUENCY ANALYSIS OF CONTINU- OUS RECORDED AE WAVEFORM

REAL-TIME DENOISING OF AE SIGNALS BY SHORT TIME FOURIER TRANSFORM AND WAVELET TRANSFORM

Enoki 2. moving. sensors. CPU and. More info about this article:

Research Center for Advanced Science and Technology The University of Tokyo Tokyo 153, Japan

ARRIVAL TIME DETECTION IN THIN MULTILAYER PLATES ON THE BASIS OF AKAIKE INFORMATION CRITERION

NONDESTRUCTIVE EVALUATION OF CLOSED CRACKS USING AN ULTRASONIC TRANSIT TIMING METHOD J. Takatsubo 1, H. Tsuda 1, B. Wang 1

ACOUSTIC AND ELECTROMAGNETIC EMISSION FROM CRACK CREATED IN ROCK SAMPLE UNDER DEFORMATION

DETECTION AND SIZING OF SHORT FATIGUE CRACKS EMANATING FROM RIVET HOLES O. Kwon 1 and J.C. Kim 1 1 Inha University, Inchon, Korea

BENDING FRACTURE BEHAVIOR OF 3D-WOVEN SiC/SiC COMPOSITES WITH TRANSPIRATION COOLING STRUCTURE CHARACTERIZED BY AE WAVELET ANALYSIS

ULTRASOUND IN CFRP DETECTED BY ADVANCED OPTICAL FIBER SENSOR FOR COMPOSITE STRUCTURAL HEALTH MONITORING

DEVELOPMENT OF MEASUREMENT SYSTEM USING OPTICAL FIBER AE SENSORS FOR ACTUAL PIPING

Ultrasonic Guided Wave Testing of Cylindrical Bars

Tool Condition Monitoring using Acoustic Emission and Vibration Signature in Turning

NONLINEAR C-SCAN ACOUSTIC MICROSCOPE AND ITS APPLICATION TO CHARACTERIZATION OF DIFFUSION- BONDED INTERFACES OF DIFFERENT METALS

A Study on Correlation of AE Signals from Different AE Sensors in Valve Leakage Rate Detection

Measurement of phase velocity dispersion curves and group velocities in a plate using leaky Lamb waves

Ultrasonic Imaging of Microscopic Defects to Help Improve Reliability of Semiconductors and Electronic Devices

EWGAE 2010 Vienna, 8th to 10th September

redefining the limits of ultrasound

DEVELOPMENT OF STABILIZED AND HIGH SENSITIVE OPTICAL FI- BER ACOUSTIC EMISSION SYSTEM AND ITS APPLICATION

Development of Concave and Convex Roll Defect Inspection Technology for Steel Sheets by Magnetic Flux Leakage Testing Method

1409. Comparison study between acoustic and optical sensors for acoustic wave

XYZ Stage. Surface Profile Image. Generator. Servo System. Driving Signal. Scanning Data. Contact Signal. Probe. Workpiece.

Advanced Lab LAB 6: Signal Acquisition & Spectrum Analysis Using VirtualBench DSA Equipment: Objectives:

AE Frequency analysis of Damage Mechanism in CFRP Laminates Based on Hilbert Huang Transform

The Development of Laser Ultrasonic Visualization Equipment and its Application in Nondestructive Inspection

INTERNAL CONCRETE INSPECTION AND EVALUATION METHODS FOR STEEL PLATE-BONDED SLABS BY USING ELASTIC WAVES VIA ANCHOR BOLTS

THE EXTRACTION METHOD FOR DISPERSION CURVES FROM SPECTROGRAMS USING HOUGH TRANSFORM

LAB #7: Digital Signal Processing

EMBEDDED FBG SENSORS AND AWG-BASED WAVELENGTH INTERROGATOR FOR HEALTH MONITORING OF COMPOSITE MATERIALS

Recommendation of RILEM TC 212-ACD: acoustic emission and related NDE techniques for crack detection and damage evaluation in concrete*

Transducer degradation and high amplitude behavior of broadband piezoelectric stack transducer for vibrothermography

Frequency-Amplitude class of acoustic emission for different fracture mechanisms in C/SiC composite

Advanced Data Analysis Pattern Recognition & Neural Networks Software for Acoustic Emission Applications. Topic: Waveforms in Noesis

Experimental Research on Cavitation Erosion Detection Based on Acoustic Emission Technique

MECHANICAL PROPERTY OF CARBON NANOTUBE YARN REINFORCED EPOXY

Chapter 5. Signal Analysis. 5.1 Denoising fiber optic sensor signal

19 th INTERNATIONAL CONGRESS ON ACOUSTICS MADRID, 2-7 SEPTEMBER 2007

Spectrum and Energy Distribution Characteristic of Electromagnetic Emission Signals during Fracture of Coal

SIGNAL PROCESSING OF ACOUSTIC EMISSION DATA FOR CHIP-BREAKAGE RECOGNITION IN MACHINING

ASSESSMENT OF WALL-THINNING IN CARBON STEEL PIPE BY USING LASER-GENERATED GUIDED WAVE

Acoustic Emission For Damage Monitoring of Glass /Polyester Composites under Buckling Loading

SAEU2S USB Acoustic Emission

Acoustic Emission Signal Associated to Fiber Break during a Single Fiber Fragmentation Test: Modeling and Experiment

Monitoring of the Reactive Air Brazing by Acoustic Emission Analysis

Capacitive MEMS accelerometer for condition monitoring

Panasonic, 2 Channel FFT Analyzer VS-3321A. DC to 200kHz,512K word memory,and 2sets of FDD

ACOUSTIC EMISSION MEASUREMENTS ON SHELL STRUCTURES WITH DIRECTLY ATTACHED PIEZO-CERAMIC

ACOUSTIC EMISSION OF COMPOSITE WING SEGMENT DURING FATIGUE TESTS

ANALYSIS OF ACOUSTIC EMISSION FROM IMPACT AND FRACTURE OF CFRP LAMINATES

Experimental Study on Feature Selection Using Artificial AE Sources

Multi-spectral acoustical imaging

Partial Discharge Signal Detection by Piezoelectric Ceramic Sensor and The Signal Processing

SIGNAL PROCESSING FOR ADVANCED CORRELATION ULTRASONIC VELOCITY PROFILER

EFFECTS OF LATERAL PLATE DIMENSIONS ON ACOUSTIC EMISSION SIGNALS FROM DIPOLE SOURCES. M. A. HAMSTAD*, A. O'GALLAGHER and J. GARY

A GENERIC TECHNIQUE FOR ACOUSTIC EMISSION SOURCE LOCATION

Generation Laser Scanning Method for Visualizing Ultrasonic Waves Propagating on a 3-D Object

Multi-Channel Time Digitizing Systems

VIBRATION ANALYZER. Vibration Analyzer VA-12

High-temperature Ultrasonic Thickness Gauges for On-line Monitoring of Pipe Thinning for FAC Proof Test Facility

A train bearing fault detection and diagnosis using acoustic emission

Monitoring damage growth in composite materials by FBG sensors

N. Papadakis, N. Reynolds, C.Ramirez-Jimenez, M.Pharaoh

Response spectrum Time history Power Spectral Density, PSD

Lesson 02: Sound Wave Production. This lesson contains 24 slides plus 11 multiple-choice questions.

How to Use the Method of Multivariate Statistical Analysis Into the Equipment State Monitoring. Chunhua Yang

Stabilized Interrogation and Multiplexing. Techniques for Fiber Bragg Grating Vibration Sensors

Non-Contact Ultrasound CERAMIC ANALYSIS, INCLUDING REFRACTORIES & FILTERS

A SIMPLE METHOD TO COMPARE THE SENSITIVITY OF DIFFERENT AE SENSORS FOR TANK FLOOR TESTING

A Wire-Guided Transducer for Acoustic Emission Sensing

Transmitter Identification Experimental Techniques and Results

Comparative Analysis of Triaxial Shock Accelerometer Output

ON LAMB MODES AS A FUNCTION OF ACOUSTIC EMISSION SOURCE RISE TIME #

THE PROPAGATION OF PARTIAL DISCHARGE PULSES IN A HIGH VOLTAGE CABLE

Location of Leaks in Liquid Filled Pipelines under Operation

AGN 008 Vibration DESCRIPTION. Cummins Generator Technologies manufacture ac generators (alternators) to ensure compliance with BS 5000, Part 3.

Implementation of electromagnetic acoustic resonance in pipe inspection

DEVELOPMENT OF HEAT-RESISTANT OPTICAL FIBER AE SENSOR

State of the Art Room Temperature Scanning Hall Probe Microscopy using High Performance micro-hall Probes

JOURNAL OF ACOUSTIC EMISSION

Development of the air-coupled ultrasonic vertical reflection method

VALVE CONDITION MONITORING BY USING ACOUSTIC EMISSION TECHNIQUE MOHD KHAIRUL NAJMIE BIN MOHD NOR BACHELOR OF ENGINEERING UNIVERSITI MALAYSIA PAHANG

Quick Assessment of the Anomalies in Concrete Structure Using Dispersive Characteristic of Surface wave

Rayleigh Wave Interaction and Mode Conversion in a Delamination

COMPOSITES FROM PIEZOELECTRIC FIBERS AS SENSORS AND EMITTERS FOR ACOUSTIC APPLICATIONS*

Detectability of kissing bonds using the non-linear high frequency transmission technique

DAMAGE-TYPE IDENTIFICATION IN A CFRP CROSS-PLY LAMINATE FROM ACOUSTIC EMISSION SIGNALS DETECTED BY A FIBER-OPTIC SENSOR IN A NEW REMOTE CONFIGURATION

A New Capacitive Sensing Circuit using Modified Charge Transfer Scheme

Transient Current Measurement for Advance Materials & Devices

Internally biased PZT materials for high-power sonar transducers

Experimental Study on Quantitative Application of Electromagnetic Radiation Excited by Coal-rock Fracture

DATA ANALYSIS FOR VALVE LEAK DETECTION OF NUCLEAR POWER PLANT SAFETY CRITICAL COMPONENTS

Impact Monitoring in Smart Composites Using Stabilization Controlled FBG Sensor System

Signal Analysis of CMP Process based on AE Monitoring System

Experiment 1 LRC Transients

Development and Application of 500MSPS Digitizer for High Resolution Ultrasonic Measurements

Development of High Temperature Acoustic Emission Sensing System Using Fiber Bragg Grating

Sound velocity measurement using transfer function method

4: EXPERIMENTS WITH SOUND PULSES

Portable FFT Analyzer CF-9200/9400

Transcription:

Materials Transactions, Vol. 48, No. 6 (27) pp. 1221 to 1226 Special Issue on Advances in Non-Destructive Inspection and Materials Evaluation #27 The Japanese Society for Non-Destructive Inspection Acquisition and Analysis of Continuous Acoustic Emission Waveform for Classification of Damage Sources in Ceramic Fiber Mat Kaita Ito* and Manabu Enoki Department of Materials Engineering, The University of Tokyo, Tokyo 113-8656, Japan Waveforms of acoustic emission (AE) events come close and sometimes overlap each other when AE activity is very high. Conventional AE measurement systems which handle discrete AE events are not suitable for this situation because miss-detection of AE event occurs frequently. A new AE measurement system named as Continuous Wave Memory (CWM) was developed to solve this problem by recording the AE waveforms continuously to hard disks for several hours throughout the testing time. This new system enabled multiple analysis of one waveform with different filtering parameters. Short time Fourier transform (STFT) gave the time frequency magnitude characteristic of continuous AE waveforms and useful information for evaluation of degradation of materials. In this study, the degradation of ceramic fiber mat during cyclic compression test and the effect of binder-addition were evaluated by this new system. STFT results clearly showed the classification of degradation of the mat; breakage of fibers was the main source in the early compression cycles and sporadic friction between fibers became the main source of AE in the later compression cycles. The effect of organic binder to prevent the degradation of the mat was also estimated. It was observed that the friction signal disappeared and the breakage signal weakened in the binder-added specimens. [doi:1.232/matertrans.i-mra2785] (Received September 5, 26; Accepted February 27, 27; Published May 25, 27) Keywords: acoustic emission, continuous wave memory, continuous waveform recording, ceramic fiber mat, short time Fourier transform 1. Introduction Waveforms of acoustic emission (AE) events come close and sometimes overlap each other when AE activity is very high. In such environment, conventional AE measurement systems frequently fail to detect AE events because they process AE events sequentially while the next event arrives within the dead-time of the last event. In our previous studies, 1,2) AE events of ceramic fiber mat were measured under cyclic compression tests to estimate the gradual degradation of gripping force of the mat which fixes the catalytic converter of car exhaust gas inside the case. However, conventional AE measurement systems frequently missed the AE events as the increase of compression stress, leading finally to saturation of signal processing. Continuous recording of AE waveform is an idea to solve this dead-time problem. An AE system based on digital signal processing has been commercially available, making continuous data recording possible. Thompson et al. 3) suggested a system to monitor the critical period of fracture propagation of rocks. However, the recording time of their system was very limited to a few minutes because they adopted semiconductor memory as the storage device of continuous AE waveform. Kurz et al. 4) showed another system which can record the transient AE waveforms as long as one AE event length without interval to high-capacity hard disks. However, their system could not handle the continuous AE waveform directly and their 2.5 MHz sampling frequency was not enough for usual AE measurement of materials. Semiconductor memory and hard disk have trade-off relationship between their speeds and capacities, therefore it is important to utilize the advantages of both devices to develop a practical continuous AE waveform recorder. In this study, a new AE measurement and analysis system was developed to solve the problems about dead-time and storage device, and evaluated the degradation of the ceramic fiber mat. This new system was named Continuous Wave Memory (CWM) and enabled continuous recording of AE waveforms with 1 MHz sampling frequency to hard disks for several hours. Short time Fourier transform (STFT) 5) was adopted as a method for direct handling of continuous AE waveforms and gave the time frequency magnitude characteristic of the continuous AE waveforms as useful information for classification of degradation 6) of the ceramic fiber mat. 2. Continuous Wave Memory 2.1 Hardware Figure 1 shows block diagram of the hardware of CWM system. CWM is built up by PC and commodity type hardware. CWM can convert 4 ch AE signals into digital Sensors Preamps Dual-core CPU Athlon64X2 38+, AMD Inc. 2MB/s/ch AD converter PCI-3525, Interface Corp. AD converter PCI-3525, Interface Corp. 12MB/s HDD (RAID-) ST325823A x2 Seagate Tech. LLC 1MHz, 12bit conversion Continuous Wave Memory *Graduate Student, The University of Tokyo Fig. 1 Block diagram of the CWM hardware.

1222 K. Ito and M. Enoki Input Measured waveform (from ADC) Recorded waveform (from HDD) Fig. 2 Real-time Analysis Post Analysis waveform data continuously with 1 MHz sampling frequency and 12bit resolution by high-speed analog-to-digital converter (PCI-3525, Interface Inc.). The digitalized waveform data are recorded to hard disk array which is parallelized and accelerated by RAID- technology. 7) The data recording rate is 2 MB/s/ch, therefore the maximum recording time is 1.7 hours for 4 ch or 6.9 hours for 1 ch in the current hard disk with a capacity of 5 GB. 2.2 Software Figure 2 shows block diagram of the software of CWM system to handle the continuous AE waveform. In this software, multiple steps of signal processing can be performed in parallel on a common ring-buffer to reduce calculation time by effective use of multi-core CPU. In realtime analysis, a measured waveform is directly imported from analog-to-digital converter just like conventional AE measurement systems and AE parameters are calculated immediately. Post analysis with different filtering parameters is also possible using completely recorded AE waveform. Short time Fourier transform (STFT) is one of evaluation methods of continuous waveform, which calculates time frequency magnitude characteristic along the procedure as shown in Fig. 3. A continuous AE waveform is split into short sections with 124 samples, the split waveforms are applied to FFT method one-by-one, and 496 FFT results are averaged to adjust the time resolution and plotted in the form of 3D graph. The horizontal axis shows density of the mat which is converted from the time data and the vertical axis shows frequency of AE signal and the 3rd axis which is expressed as the contrast change reflecting the magnitude of AE signals at this point. 3. Experimental Procedures Processing AE event RMS voltage Frequency filter STFT etc. Block diagram of the CWM software. Output AE parameters Filtered waveform (to HDD) Ceramic fiber mat of catalytic converter unit was compressed cyclically with experimental equipments as shown in Fig. 4. The commercial mat with component of 72% alumina and 28% silica was cut into cylindrical shape of 25.4 mm in diameter. The load and AE signal were monitored during the tests. AE signal was captured by piezoelectric lead zirconate titanate (PZT) sensor with built-in head-amp (M34, Fuji Ceramics corp.). The sensor has a flat frequency characteristic from 2 khz to 6 khz. The signal was amplified again by preamplifier (A12, Fuji Ceramics corp.) and then inputted to CWM system. The SiC jig was water cooled around the sensor to keep the constant sensitivity of PZT and ensure performance of the head-amp in the sensor package Measured Waveform (Time and Voltage) STFT Data (Time, Frequency and Magnitude) Time to Mat density Fig. 3 STFT (124 samples window) from the heat of the electric furnace. The range of compression was controlled by density of specimen which was calculated from the gap of upper and lower parts of jig because the weight and the cross-section area of spongy mat specimen were almost constant during the cyclic compression test. Degradation of the gripping force occurs during press-fit part of manufacturing process and also in-service period. Although an organic binder is added before the press-fit process to reduce the damage of fibers, it is volatilized by the heat of the first running of engine. Therefore, two conditions of compression were tested as follows. The specimens with variable content of organic binder were compressed from completely unloading state as.15 g/cm 3 to.4 g/cm 3 at room temperature to simulate the press-fit process. On the other hand, only binder-less specimens were compressed cyclically between.331 g/cm 3 and.376 g/cm 3 at room temperature to simulate the in-service environment. 4. Results and Discussion Calculation procedures of short time Fourier transform (STFT). Load cell (1kN) Water cooling Electric furnace SiC jig Specimen AE sensor M34, Fuji Ceramics Corp. Fig. 4 Amp Data logger Pressure monitor Preamp A12 Fuji Ceramics Corp. CWM AE monitor Experimental equipments of cyclic compression test. Figure 5 shows AE signals with high activity from a mat specimen by CWM and schematic of AE event processing in

Acquisition and Analysis of Continuous Acoustic Emission Waveform for Classification of Damage Sources in Ceramic Fiber Mat 1223 Voltage, V / V.4.2 -.2 Missed event by conventional systems Threshold voltage : Measuring : Dead-time -.4 2 4 6 8 1 Fig. 5 Time, t / µs An example of AE signal with high activity. conventional AE measurement systems. Conventional systems detect an AE event when the amplitude of AE signal exceeds the pre-set threshold voltage and then process it oneby-one sequentially. Therefore, miss-detection of an event occurs if the next event arrives within the dead-time of the previous event. On the contrary, there is no dead-time on CWM system and all events can be detected successfully even AE signals with high activity. Figures 6 and 7 show waveforms and frequency characteristics of two typical types of AE events which were detected during the cyclic compression test of the ceramic fiber mat. The sources of these waveforms can be considered to be related to the shape of waveforms; 6) the burst type waveform with 6 khz peak frequency is thought to be due to breakage of fibers and the continuous type waveform with 2 khz peak frequency is due to friction of fibers, respectively. These frequency characteristics are reasonable because it is well known that the frequency of the AE signal has positive correlation with the formation time of the event. 8) The breakage of fiber should be result from faster event than the friction between fibers, therefore the breakage of fibers has higher peak frequency than the friction between fibers. Figure 8 shows STFT results of the 1st compression of specimens with different fraction of organic binder. The magnitude is normalized by the maximum magnitude in each graph. Although similar frequency characteristic with two Magnitude 1 8 6 4 2 Continuous type Burst type 5 1 Fig. 7 Frequency characteristics of AE waveforms both the continuous and burst type. peaks as shown in Fig. 7 in binder-less specimen is observed, the breakage signal with 6 khz peak frequency becomes weaker as addition of the binder and the friction signal with 2 khz peak frequency almost disappears in binder-added specimens. Figure 9 shows the maximum value of magnitude of these two peak frequencies and the pressure during the 1st compression cycle, i.e. at the highest compressed state. These results show that the organic binder has a positive effect in protecting the ceramic fibers from the damage in compression. It is reasonable that the organic binder prevents the friction between fibers because the observation result (Fig. 1) shows that the organic binder mainly bonds the cross point of fibers. Figure 11 shows results in the 1st, 1th and 7th compression of the binder-less specimens. Although both the breakage signal and the friction signal become stronger as the progress of compression during the 1st compression, there is only a sporadical friction signal during the 7th compression. The characteristic of AE signal changed gradually during the cyclic compression test, so the result of the 1th compression demonstrates the transition behavior. Figure 12 also shows results of 1% binder-added specimen for the 1st, 1th and 7th compression. The friction signal is not observed and there are only weak breakage signals throughout the test. Figures 13 and 14 show SEM photographs of a binder-less and a binder-added specimen which were taken on the same place of the same specimen before and after 1 and 1 cycles of compression. In binder-less specimen, the SEM observation shows that the fibers are gradually rearranged to uneven distribution and finally large voids appear. On the contrary, no rearrangement is seen in.1.1 Voltage, V / V -.1-2 2 4 6 Time, t / µs Voltage, V / V -.1-2 2 4 Time, t / µs 6 Fig. 6 Typical AE waveforms of continuous type and burst type.

1224 K. Ito and M. Enoki 1 75 5 25 (d) Fig. 8 STFT results of %, 1%, 5% and (d) 1% binder specimens during the 1st compression. 2 Magnitude 15 1 5 Friction (2kHz) Breakage (6kHz) 5 1 Binder content (%) Fig. 9 Binder contents vs. the magnitude of STFT. binder-added specimen. These results show that the friction AE signal reflected this sporadic rearrangement of fibers and the organic binder effectively prevented the rearrangement of fibers. 5. Conclusions (1) An AE measurement system named Continuous Wave Memory (CWM) was developed in order to record AE waveforms continuously to hard disks for several hours with sufficient high sampling frequency. (2) Continuous AE waveform of ceramic fiber mat was measured and analyzed by CWM system during cyclic Fig. 1 5µm SEM observation of 1% binder-added specimen. compression test. Time frequency magnitude characteristic of AE signal was calculated by short time Fourier transform (STFT) method to classify the source of AE. Two peak frequencies were found at 6 khz and 2 khz in these tests and the sources of AE were attributed to the breakage of fibers and friction between fibers, respectively. (3) Effect of organic binder in the ceramic fiber mat was evaluated by CWM and SEM observation. The friction

Acquisition and Analysis of Continuous Acoustic Emission Waveform for Classification of Damage Sources in Ceramic Fiber Mat 1225 Fig. 11 STFT results of a binder-less specimen during the 1st, 1th and 7th compression. Fig. 12 STFT results of a 1% binder-added specimen during the 1st, 1th and 7th compression. Fig. 13 SEM observation of binder-less specimen before, after 1 cycles and after 1 cycles of compression. Fig. 14 SEM observation of 1% binder-added specimen before, after 1 cycles and after 1 cycles of compression.

1226 K. Ito and M. Enoki AE signal due to rearrangement of fibers was not detected in binder-added specimens. These results show that the organic binder has a positive effect in protecting the fibers from the damage under compression. (4) Both the breakage and friction signals were detected during the early cycles in binder-less specimens, while there was only sporadical friction signal in the later cycles. On the other hand, there was only weak breakage signal throughout the test in binder-added specimens. Degradation process during cyclic composition for both binder-less and binder-added specimens were clearly identified by AE. Acknowledgement The present research is supported by Ibiden Co., ltd. and the 21st Century COE Program Human-Friendly Materials based on Chemistry from the Ministry of Education, Culture, Sports, Science, and Technology of Japan. REFERENCES 1) K. Ito, M. Enoki and H. Takahashi: Review of Progress in Quantitative Non-destructive Evaluation 24 (American Inst. Phys., 24) pp. 1129 1136. 2) K. Ito, M. Enoki and H. Takahashi: Progress in Acoustic Emission XII (Japanese Soc. for Non-destructive Inspection, 24) pp. 77 84. 3) B. D. Thompson, R. P. Young and D. A. Lockner: Pure and Appl. Geophys. 163 (26) 995 119. 4) J. H. Kurz, V. Wolter, G. Bahr and M. Motz: Otto-Graf-Journal 14 (23) 115 13. 5) M. K. Klymik, İ. Güler, A. Dizibüyük and M. Akin: Computers in Bio. Med. 35 (25) 63 616. 6) X. Li: Int. J. Machine Tools and Manufacture 42 (22) 157 165. 7) D. A. Patterson, G. A. Gibson and R. H. Katz: Proc. SIGMOD 1988, (ACM SIGMOD, 1988) pp. 19 116. 8) W. Schaarwachter and H. Ebener: Acta Metall. Mater. 38 (199) 195 25.