Ultrasonic characterisation of process-induced pores in selective laser melted TiB <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si13.svg" display="inline" id="d1e1025"> <mml:msub> <mml:mrow/> <mml:mrow> <mml:mn>2</mml:mn> </mml:mr

Process-induced pores in metal additive manufacturing (AM) components critically compromise mechanical performance, necessitating reliable characterisation methods for quality assurance. While ultrasound offers promising advantages for rapid, non-destructive evaluation with deep penetration, existing studies struggle to isolate pore effects from confounding grain scattering. This work overcomes these limitations by investigating selective laser melted TiB 2 /Al composites, whose ceramic-reinforced microstructure exhibits refined equiaxed grains and minimal texture, effectively suppressing grain scattering to reveal fundamental pore-ultrasound interactions. We systematically examined how porosity (0.22%–2.21%), morphology, and size distribution influence ultrasonic attenuation and velocity. This was achieved through integrated experimental measurements and three-dimensional pore-scale finite element simulations incorporating realistic pores derived from stereological transformation of microscopy data. Our findings reveal hierarchical pore effects: porosity exhibits strong linear correlations with both attenuation coefficient and phase velocity under the same pore morphology conditions; irregular morphologies amplify these effects, generating fivefold higher attenuation sensitivity and twofold higher velocity sensitivity compared to spherical pores; size variations primarily affect attenuation with minimal velocity impact. Additional, we demonstrated ultrasound’s spatial mapping capability for detecting subtle microstructural heterogeneities, with attenuation exhibiting superior porosity sensitivity. These quantitative pore-ultrasound relationships establish a robust framework for non-destructive evaluation in metal AM, enabling morphology-sensitive quality control and process optimisation for safety-critical applications.