Determination of elastic constants of additive manufactured Inconel 625 specimens using an ultrasonic technique

Javidrad, H. R.; Salemi, Sina

doi:10.1007/s00170-020-05321-x

Cited by 33 publications

(11 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Some research studies have obtained orthotropic constants by computing the vibration response using the finite element (FE) method or semianalytical methods. [ 23–26 ] However, the knowledge of the dynamic response of Ti–6Al–4V provides directional and tension–compression asymmetrical elastic properties, as reported here and in previous studies. [ 13–16 ]…”

Section: Introductionsupporting

confidence: 62%

“…Some research studies have obtained orthotropic constants by computing the vibration response using the finite element (FE) method or semianalytical methods. [23][24][25][26] However, the knowledge of the dynamic response of Ti-6Al-4V provides directional and tension-compression asymmetrical elastic properties, as reported here and in previous studies. [13][14][15][16] The rise of new technologies and manufacturing of highly critical components has brought a growing interest for nondestructive nanomechanical characterization procedures.…”

supporting

confidence: 64%

See 1 more Smart Citation

Nanomechanical Characterization of the Deformation Response of Orthotropic Ti–6Al–4V

et al. 2021

View full text Add to dashboard Cite

The research interest in titanium alloys lies in the fact that their exceptional mechanical properties make them ideal for specific industrial applications, such as biomedical, aerospace, and military industries. [1][2][3] Despite its high cost, Ti-6Al-4V alloy is currently the most widely used titanium alloy, [4] combining good biocompatibility and corrosion resistance, [5][6][7][8][9][10] high strength, low weight, and ductility. [11][12][13][14][15][16] Several manufacturing processes among the aforementioned applications contemplate the implementation of material characterization procedures, either on pristine samples of the material or on previously manufactured parts. The most commonly applied experimental procedures to identify the macroscopic orthotropic elastoplastic properties of a material include monotonic tensile, [17,18] compression, [19,20] and shear [21,22] tests of material samples obtained from its orthogonal directions. The main limitations of these tests are the size of the specimens and their subsequent destruction,

show abstract

Section: Introductionsupporting

confidence: 62%

supporting

confidence: 64%

Nanomechanical Characterization of the Deformation Response of Orthotropic Ti–6Al–4V

et al. 2021

View full text Add to dashboard Cite

show abstract

“…In this technique, the flat sample is rotated in a liquid bath, and the acoustic transducers are stationary. The second approach is sometimes referred to as the polygon method [43,44]. In this approach, acoustic transducers are placed on twelve sample wedges.…”

Section: Alloy Processing Sample Preparation and Dynamic Pulse-echo Ultrasonic Testingmentioning

confidence: 99%

Measurement of the Anisotropic Dynamic Elastic Constants of Additive Manufactured and Wrought Ti6Al4V Alloys

et al. 2022

View full text Add to dashboard Cite

Additively manufactured (AM) materials and hot rolled materials are typically orthotropic, and exhibit anisotropic elastic properties. This paper elucidates the anisotropic elastic properties (Young’s modulus, shear modulus, and Poisson’s ratio) of Ti6Al4V alloy in four different conditions: three AM (by selective laser melting, SLM, electron beam melting, EBM, and directed energy deposition, DED, processes) and one wrought alloy (for comparison). A specially designed polygon sample allowed measurement of 12 sound wave velocities (SWVs), employing the dynamic pulse-echo ultrasonic technique. In conjunction with the measured density values, these SWVs enabled deriving of the tensor of elastic constants (Cij) and the three-dimensional (3D) Young’s moduli maps. Electron backscatter diffraction (EBSD) and micro-computed tomography (μCT) were employed to characterize the grain size and orientation as well as porosity and other defects which could explain the difference in the measured elastic constants of the four materials. All three types of AM materials showed only minor anisotropy. The wrought (hot rolled) alloy exhibited the highest density, virtually pore-free μCT images, and the highest ultrasonic anisotropy and polarity behavior. EBSD analysis revealed that a thin β-phase layer that formed along the elongated grain boundaries caused the ultrasonic polarity behavior. The finding that the elastic properties depend on the manufacturing process and on the angle relative to either the rolling direction or the AM build direction should be taken into account in the design of products. The data reported herein is valuable for materials selection and finite element analyses in mechanical design. The pulse-echo measurement procedure employed in this study may be further adapted and used for quality control of AM materials and parts.

show abstract

“…Generally, porosity originates from a lack of uniformity along the building direction because the cooling rate is varied during AM building. In contrast, the plane normal to the building direction is relatively uniform [21]. In our experiments, the ultrasonic measurement was conducted using a transducer attached to the surface in the direction normal to the building direction, as shown in Figure 4.…”

Section: Procedures To Train and Test The Modelsmentioning

confidence: 99%

“…The relation between the ultrasonic velocity and attenuation, and the properties of microstructures, including the porosity and grain size, was studied by Karthik et al [20], who used a water-immersion ultrasonic method. Javidrad et al [21] correlated the elastic modulus affected by the porosity content with the ultrasonic velocity in varying the propagation directions of ultrasonic waves using a contact ultrasonic method.…”

Section: Introductionmentioning

confidence: 99%

Deep Learning-Based Ultrasonic Testing to Evaluate the Porosity of Additively Manufactured Parts with Rough Surfaces

Park

Hong

et al. 2021

Metals

View full text Add to dashboard Cite

Ultrasonic testing (UT) has been actively studied to evaluate the porosity of additively manufactured parts. Currently, ultrasonic measurements of as-deposited parts with a rough surface remain problematic because the surface lowers the signal-to-noise ratio (SNR) of ultrasonic signals, which degrades the UT performance. In this study, various deep learning (DL) techniques that can effectively extract the features of defects, even from signals with a low SNR, were applied to UT, and their performance in terms of the porosity evaluation of additively manufactured parts with rough surfaces was investigated. Experimentally, the effects of the processing conditions of additive manufacturing on the resulting porosity were first analyzed using both optical and scanning acoustic microscopy. Second, convolutional neural network (CNN), deep neural network, and multi-layer perceptron models were trained using time-domain ultrasonic signals obtained from additively manufactured specimens with various levels of porosity and surface roughness. The experimental results showed that all the models could evaluate porosity accurately, even that of the as-deposited specimens. In particular, the CNN delivered the best performance at 94.5%. However, conventional UT could not be applied because of the low SNR. The generalization performance when using newly manufactured as-deposited specimens was high at 90%.

show abstract

Determination of elastic constants of additive manufactured Inconel 625 specimens using an ultrasonic technique

Cited by 33 publications

References 37 publications

Nanomechanical Characterization of the Deformation Response of Orthotropic Ti–6Al–4V

Nanomechanical Characterization of the Deformation Response of Orthotropic Ti–6Al–4V

Measurement of the Anisotropic Dynamic Elastic Constants of Additive Manufactured and Wrought Ti6Al4V Alloys

Deep Learning-Based Ultrasonic Testing to Evaluate the Porosity of Additively Manufactured Parts with Rough Surfaces

Contact Info

Product

Resources

About