Enhanced Near-Surface Flaw Detection in Additively Manufactured Metal Ti-5Al-5V-5Mo-3Cr Using the Total Focusing Method

Additive manufacturing (AM) enables the fabrication of complex components with high geometric freedom, but it can introduce near-surface flaws due to rapid solidification, resulting in porosity and lack of fusion. In addition, localized melting and steep thermal gradients favor the formation of micro-cracks. Conventional ultrasonic techniques have shortcomings in detecting such flaws because of front-wall interference, further affected by surface roughness and anisotropy. This study evaluates the effectiveness of the Total Focusing Method (TFM), an advanced ultrasonic imaging technique implemented in Full Matrix Capture (FMC), for near-surface flaw detection in Laser Powder Bed Fusion (LPBF) AM components. To assess TFM performance, subsurface side-drilled holes (SDHs) in AM Ti-5Al-5V-5Mo-3Cr (Ti-5553) material were used as the reference reflectors and compared with Phased Array Ultrasonic Testing (PAUT) under identical conditions. Results showed that TFM achieved higher spatial resolution and more reliable detection of shallow flaws, successfully detecting features as shallow as 0.40 ± 0.05 mm below the surface, whereas PAUT was limited to greater depths. These findings demonstrate TFM as a reliable non-destructive evaluation method for shallow flaws in AM parts, while contributing one of the first systematic comparative datasets of PAUT and TFM for shallow SDHs in LPBF titanium alloys.

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Publication Details

Journal
Sensors
Published
2025-10-17
DOI
https://doi.org/10.3390/s25206425
Citations
1
Primary Topic
Welding Techniques and Residual Stresses
Type
article
Field-Weighted Citation Impact
0.71

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article

Enhanced Near-Surface Flaw Detection in Additively Manufactured Metal Ti-5Al-5V-5Mo-3Cr Using the Total Focusing Method

Catalin Mandache, Thomas W. Krause, Mohammad Ebrahim Bajgholi, P. R. Underhill et al.
1 citations
Sensors
Welding Techniques and Residual Stresses
0.71
article

Enhanced Near-Surface Flaw Detection in Additively Manufactured Metal Ti-5Al-5V-5Mo-3Cr Using the Total Focusing Method

Catalin Mandache, Thomas W. Krause, Mohammad Ebrahim Bajgholi, P. R. Underhill, Kate van Herpt
article en
1 citations

Abstract

Additive manufacturing (AM) enables the fabrication of complex components with high geometric freedom, but it can introduce near-surface flaws due to rapid solidification, resulting in porosity and lack of fusion. In addition, localized melting and steep thermal gradients favor the formation of micro-cracks. Conventional ultrasonic techniques have shortcomings in detecting such flaws because of front-wall interference, further affected by surface roughness and anisotropy. This study evaluates the effectiveness of the Total Focusing Method (TFM), an advanced ultrasonic imaging technique implemented in Full Matrix Capture (FMC), for near-surface flaw detection in Laser Powder Bed Fusion (LPBF) AM components. To assess TFM performance, subsurface side-drilled holes (SDHs) in AM Ti-5Al-5V-5Mo-3Cr (Ti-5553) material were used as the reference reflectors and compared with Phased Array Ultrasonic Testing (PAUT) under identical conditions. Results showed that TFM achieved higher spatial resolution and more reliable detection of shallow flaws, successfully detecting features as shallow as 0.40 ± 0.05 mm below the surface, whereas PAUT was limited to greater depths. These findings demonstrate TFM as a reliable non-destructive evaluation method for shallow flaws in AM parts, while contributing one of the first systematic comparative datasets of PAUT and TFM for shallow SDHs in LPBF titanium alloys.

SensorsVol. 25(20)
Queen's University (CA), National Research Council Canada (CA), Royal Military College of Canada (CA), École de Technologie Supérieure (CA)
Natural Sciences and Engineering Research Council of Canada
Openalex Percentile: Top 26%
Welding Techniques and Residual Stresses
0.71
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Enhanced Near-Surface Flaw Detection in Additively Manufactured Metal Ti-5Al-5V-5Mo-3Cr Using the Total Focusing Method — Catalin Mandache, Thomas W. Krause, et al. · Sensors (2025) | TGRS Research Map | TGRS