ultrasonic ndt of steel: effect of the …...journal of chemical technology and metallurgy, 53, 2,...

Journal of Chemical Technology and Metallurgy, 53, 2, 2018

346

ULTRASONIC NDT OF STEEL: EFFECT OF THE GRAIN SIZE ON THE ULTRASONIC PROPAGATION AND ATTENUATION

Francesco Bonifazi1, Pietro Burrascano1, Andrea Di Schino1, Sabrina Mengaroni2,Federico Petrucci1, Marco Ricci3, Luca Senni1

ABSTRACT

Non-destructive techniques (NDT), such as Ultrasound Testing (UT), have been industrially exploited for decades within the material field, for a wide range of possibilities.

Ultrasonic non-destructive evaluation relies on exciting the sample under test with an ultrasonic beam and on measur-ing the beam reflected, transmitted or scattered from discontinuities within the material such as grains, fractures, voids or the microstructure itself. In this paper, the effect of the grain size and other several microstructural parameters on the ultrasonic propagation have been evaluated for an experimental low alloyed carbon steel.

Main results are: at high frequencies the attenuation coefficient follows the Rayleigh law for scattering and shows a maximum at a frequency value that increases as the grain size decreases; the value of frequency corresponding to the attenuation maximum, converted in wavelength, can be approximately compared as 3 - 4 times the average grain size.

Keywords: non destructive testing, carbon steel, microstructure.

Received 17 May 2017Accepted 28 September 2017

Journal of Chemical Technology and Metallurgy, 53, 2, 2018, 346-353

1 Università degli Studi di Perugia, Via G. Duranti 93, 06125 Perugia, Italy2 Acciai Speciali Terni, Via B. Brin 118, 05100 Terni, Italy3 Università della Calabria, 87036 Rende, Italy E-mail: [email protected]

INTRODUCTION

The production of heavy forgings of micro-alloyed steels provides advantages associated with the benefit of the application of micro-alloying elements and thermo-mechanical treatments to improve tensile properties [1 - 3], toughness [4], hot deformation [5] and weldability [6 - 7] of forgings up to the level of sheets, strips and tubes. To this aim, the effect of V addition has been exploited by means of metallurgical modelling followed by a labora-tory ingot manufacturing and a proper heat treatment has been designed to achieve the desired target tensile and contact fatigue properties [8]. Results show that ASTM A694 F70 grade requirements can be fulfilled by 0.15 % V addition and a proper heat treatment in a ferrite-pearlite microstructure, representative of a forged component [9].

In addition to that, a forged component is designed to perform a target function and, for this reason, a good quality product can be termed as one performing its assigned function for a reasonable length of time. The

quality of a machine or an assembly having a great num-ber of steel components depends on the quality factors of all the individual components. Nowadays most of the machines and systems such as for instance railways, automobiles, aircraft, ships, power plants, chemical and other industrial plants, etc., have thousands of compo-nents on which their operation depends on. To ensure the quality of such systems it is important that each in-dividual component is reliable and performs its function satisfactorily [10 - 11]. From an economic point of view, an improvement in the product quality brings economic returns to the manufacturer by increasing his production, reducing his scrap levels, enhancing his reputation as a producer of quality goods and hence boosting his sales.

This quality can be built into the manufactured goods only if suitable measures and methods of quality control are employed. Among these, methods capable of determining the quality of the products without af-fecting their serviceability, are desirable. A wide vari-ety of test schemes exist, some destructive and some

Francesco Bonifazi, Pietro Burrascano, Andrea Di Schino, Sabrina Mengaroni, Federico Petrucci, Marco Ricci, Luca Senni

347

non-destructive but the most suitable methods are the non-destructive one. In response to this need, increas-ingly sophisticated techniques using ultrasounds, eddy currents, X-rays, dye penetrants, magnetic particles, and other forms emerged.

Ultrasonic testing (UT) is a family of NDT tech-niques based on the propagation of ultrasonic waves in the object or material tested. Most of the UT applica-tions are based on the pulse-echo measurement proce-dure where a very short ultrasonic pulse with central frequencies ranging from 0.1 - 20 MHz, is transmitted into materials to detect internal flaws or to character-ize materials [12-13]. However, instead of sending a single pulse, other procedures could be used, as in this case to provide a higher Signal-to-Noise Ratio in UT measurements. In particular, the Pulse-compression measurement scheme has been used for collecting the experimental data. Pulse-compression uses coded signals of long duration and high energy content as excitation signal and it represents a valid alternative to the pulse-echo method [14].

The characterization and optimization of the mate-rial properties is a primitive necessity to ensure the per-formances and service life of materials and components. In the demand of new characterization and evaluation techniques, ultrasonic NDT has shown a good potential for a wide variety of materials.

EXPERIMENTAL

Steel chemical composition of the considered va-nadium microalloyed steel is reported in Table 1. Steel was heat treated at different conditions to obtain the microstructures reported in Table 2.

The experimental ultrasonic set-up plays an impor-tant role in the reliability of the results obtained with this technique.

The set-up has been prepared in the NDT Labora-tory of University of Perugia and consists in UT probes with different frequencies, a couplant gel, a TiePie Handyscope HS5 that acts as digital oscilloscope (ADC) and arbitrary waveform generator (AWG), and a PC that manage data acquisition and processing by means of Labview custom virtual instrument.

In chronological order, the steps to perform the measurements were:

l A proper coded signal is numerically synthetized and passed to the arbitrary waveform generator (AWG);

l The TiePie’s AWG generates the excitation signal that drives the emitter trasducer;

l The signal from the receiver transducer is ampli-fied by a low-noise amplifier and then digitized by the ADC;

l The output digital signal is processed, elaborated and presented.

Table 1. Chemical composition of the considered steel.

Table 2. Microstructures obtained to be tested with UT.

Element

Composition, %

C Mn Si V P S N Al

Content, % 0.20 1.00 0.15 0.15 <0.015 <0.003 <0.006 <0.004

Sample Grain size Microstructure Hardness

C 49.5 μm Martensite with rare bainite 364.1±24.9

G 60.8 μm Martensite with rare bainite 403.0±25.3

E 84.1 μm Martensite with rare bainite 381.1±20.1

A 105.8 μm Martensite 382.3±18.5

I 139.2 μm Martensite 354.3±13.0


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RESULTS AND DISCUSSION

Sample IThe microstructure of specimen I is reported in Fig. 1.

Ten measurements of the attenuation were collected for this sample and then averaged to produce a single curve of the mean attenuation. In Fig. 2, the mean attenuation in frequency is plotted in a range from 7 to 36 MHz and a representation with its standard deviation is also given.

From these graphs, it is visible the increase of the

attenuation coefficient as the frequency increase start-ing from values in the range of few MHz. In particular, according with Rayleigh, this increase is proportional to the fourth power of frequency. When the frequency reaches a certain value, there is a peak after which the attenuation decreases. For a better interpretation, the graphs in frequency were converted in wavelength by dividing the sound velocity of steel (5.9*10^6 mm/s) for the frequency vector (Fig. 3).

This representation is useful also for the determina-

Fig. 1. Metallographic count of grains with histogram, distribution and mean for sample I.

Fig. 2. Plot of the mean attenuation vs frequency for sample I (left) plot and maximum identification (right) plot with the standard deviation.


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tion of the grain size; in fact, literature reports theories stating that the mean grain size is about 3 - 4 times the value of the wavelength at which there is the peak of attenuation.The peak location is for λ = 0.2950 with a maximum attenuation coefficient α = 1.1003 db/mm. For instance, in this sample the 140 μm of mean size are @ 2.1 times the wavelength.

Sample AAnalogously to sample I, the microstructure with the

grain size distribution was calculated showing a mean grain size of 105.8 μm. The average attenuation with standard deviation for each frequency is plotted in Fig. 4.

In this case, the peak correspond to α = 0.9937 db/mm for a frequency of 30 MHz.

Fig. 3. Plot of mean attenuation in wavelength a) and its standard deviation b) (sample I).

Fig. 4. Plot of mean attenuation in frequency a) and its standard deviation b) (sample A).

Fig. 5. Plot of mean attenuation in wavelength a) and its standard deviation b) (sample A).


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In the correspondant graph expressed in wavelength, the peak is for λ = 0.1967 mm, that corresponds to @ 2 times the grain size (Fig. 5).

Sample EIn sample E, from the standard calculations, the

grain size is of 84.1 μm, The profile seems more ir-regular, and the maximum peak of 1.0710 dB/mm for 20MHz correspond to a wavelength of 0.2959 mm that is about 3.4 times the average grain size (Figs. 6 - 7).

Samples G&CIn samples G and C (Figs. 8 - 12) an extra consid-

eration is necessary, in fact, from the matellographic analysis it comes out that grain growth is not completely homogeneous with prevalent small grains and some big grains. This distribution can affect the ultrasonic inspection with behaviour not ever dependent from the average grain size that in this case is 60.8 μm. The maximum frequency is for 29 MHz that corresponds to an attenuation of α = 0.8010 db/mm. The wavelength of the maximum is thus λ = 0.2034 that is @ 3.3 times

the average grain size. This bimodal distribution is more visible in this sample where the average grain size is about 49.5 μm but are visible some grains with dimen-sion over 100 μm. The behaviour in frequency is very different with a higher peak in attenuation of 1.2482 db/mm for a frequency of 29 MHz. Here, because of the dishomogeneous grain structure, the interpretation of the attenuation graphs is more difficult because two peaks seem to be present, and at the same time the attenuation peak is the highest for both frequency and amplitude.

Converted in wavelength, the peak corresponds to a wavelength of 0.2034 equal to sample G that corresponds to @ 4 times the mean grain. For simplicity, taking into ac-count the set of I, A, G samples, the comparison from their behaviour in frequency shows a trend in which frequency peak increases with the decreasing of the average grain (Fig. 12), that converted in wavelength corresponds in an increas-ing of the wavelength with the increasing of mean size.

An interesting behaviour, unknown in literature, was discovered trying to make the measurements by overlapping two samples with different mean grain size as reported below.

Fig. 6. Plot of mean attenuation in frequency a) and its standard deviation b) (sample E).

Fig. 7. Plot of mean attenuation in wavelength a) and its standard deviation b) (sample E).


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Fig. 11. Plot of mean attenuation in frequency a) and its standard deviation b) (sample C).

Fig. 8. Plot of mean attenuation in frequency a) and its standard deviation b) (sample G).

Fig. 9. Plot of mean attenuation in wavelength a) and its standard deviation b) (sample G).

Fig. 10. Plot of mean attenuation in frequency a) and its standard deviation b) (sample C).


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Fig. 12. Comparison between the profiles of mean attenuation in frequency samples I, A and G.

MIX of G-I & A-IUsing the same method, the resultant behaviour is a

mix of the single behaviours; in the first part follows the profile of sample with smaller average grain size, in the second part the profile of sample with the bigger one. For example, the mixture behaviour between G-I (Fig. 13) and A-I (Fig. 14) that had approximately the same thickness, are represented. The mix follows the G sample until a frequency of 27 MHz, from which it become to

follow the sample I. The same behaviour was found in the A-I samples in which the frequency that separate the two profiles is about 25 MHz.

CONCLUSIONSScope of the work was the study of the effect of

grain size on ultrasonic attenuation. The main conlusions are as follows:l a dependence of the attenuation on the frequency

Fig. 13. Mix samples G and I.

Fig. 14. Mix samples I and A.


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with regard to the specific domine investigated, in particular in Rayleigh region where l > D, is clearly detected;

l high frequency tests confirm the expected be-haviour; moreover, it is reported that the attenuation increases as the frequency increases. A maximum value is reached for fine grain structures;

l if two samples with the same thickness are over-lapped, the final attenuation profile is the union of the single attenuation trends. In this case therefore, the general curve in the first part follows the behaviour of the sample with the small grain structure, in second part, the one of the specimen characterized by the larger grain structure.

REFERENCES

1. R. Ordonez, C.I. Garcia, A.J. De Ardo, Effect of ther-momecanical process and cooling rate conditions on the austenite decomposition behaviour in steels, La Metallurgia Italiana, 9, 2010, 5-10.

2. C. Zitelli, S. Mengaroni, A. Di Schino, Vanadium micro-alloyed high strength steels for forgings, Me-talurgija, 56, 2017, 326-328.

3. X.Y. Song, H.J. Zhang, L.C. Fu, H.B. Yang, K. Yang, L. Zh, High strength steels, Materials Science and Engineering A, 677, 2016, 465-468.

4. A. Di Schino, C. Guarnascelli, Microstructure and cleavage resistance of high strength steel, Materials Science Forum, 638-642, 2010, 3188-3193.

5. S. Mengaroni, F. Cianetti, M. Calderini, E. Evangeli-sta, H. McQueen, Tool steels: forging simulation and microstructure evolution of large scale ingots, Acta Physica Polonica, 128, 2015, 629-632.

6. A. Di Schino, P. Di Nunzio, Effect of Nb microalloy-ing on the heat affected zone microstructure of girth welded joints, Materials Letters, 186, 2017, 86-89.

7. Z. Liu, Y. Fang, J. Qiu, M. Feng, Z. Luo, J. Yuan, Stabilization of weld pool through jet flow argon gas backing in C-Mn steel keyhole TIG welding, Journal of Materials Processing Technology, 250, 2017, 132-143.

8. P. Di Nunzio, A. Di Schino, Metallurgical aspects rela-ted to contact fatigue phenomena in steels for back-up rolls, Acta Metallurgica Slovaca, 23, 2017, 62-71.

9. C. Zitelli, G. Napoli, S. Mengaroni, A. Di Schino, High strength vanadium micro-alloyed steels for forgings: influence of quenching and tempering temperatures, Journal of Chemical Technology and Metallurgy, 52, 2017, 579-582.

10. T. Lis T., K. Nowacki, H. Kania, W. Kasprzyk, Acta Metallurgica Slovaca, 10, 2004, 336-341.

11. T. Lis T., K. Nowacki, H. Kania, II Int. Conf. „ Con-tinuous casting in the steel”, Krynica, 2004.

12. K. Nowacki, Possibility of determining steel grain size using ultrasonic wavesm Metalurgija, 48, 2009, 113-115.

13. M. Ricci, S Callegari, S. Caporale, M Monticelli, L. Battaglini, M. Eroli, P. Burrascano, L. Senni, Ex-ploiting non-linear chirp and sparse deconvolution to enhance the performanceof pulse-compression ultrasonic NDT., Proceedings of ultrasonics sympo-sium (IUS), IEEE International, 2012, 1489-1492.

14. M. Ricci, L. Senni, P. Burrascano, R. Borgna, S. Neri, M. Calderini, Pulse-compression ultrasonic technique for the inspection of forged steel with high attenuation, Insight-Non-Destructive Testing and Condition Monitoring, 54, 2012, 91-95.

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