###### Abstract  
Channels manufactured by laser powder bed fusion have an inherent process-induced cross formation and surface texture that require proper characterization for design and process optimization. This work undertakes surface texture characterization of AlSi10 Mg channels of nominal diameter sizes ranging from 1 mm to 9 mm using X-ray computed tomography. Profile parameters, including _Pa, Pz_, and _Pq_, were found to be interchangeable for qualitative characterization of surface texture variation. _Psk, Ppv_, and the fractal dimension could identify the presence of extreme cross and sintered particles on the measured profiles. A method for predicting the equivalent diameter of the unobstructed cross-sectional area (\(D_{\text{eq}}\)) was presented and its reduction was found to follow a logarithmic trend, as a function of channel length. An empirical model _Pa (\(\beta\), \(D\))_, as a function of local angular position (\(\beta\)) and channel diameter (\(D\)), was demonstrated on a perfect channel geometry, resulting in well-predicted roughness and internal geometry. p _applied_  
Received: 27 April 2021  
Accepted: 7 May 2021  
Submitted: 10 May 2021  
**Publisher's Note**: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. according to ISO 4287:1997 [9]. Classic parameters such as \(Ra\), \(Rz\), and \(Rq\) have all been sought to be correlated with \(k_{s}\). In 1966, [PERSON] [10] showed how the relation is highly dependent on the manufacturing origin of the investigated surface, reporting \(k_{s}\approx 2\cdot Ra\) for machined surfaces and \(k_{s}\approx 7\cdot Ra\) for energy papers. [PERSON] [11] found that \(k_{s}\approx 10\cdot Ra\) for polished surfaces and [PERSON] et al. [12] observed that \(k_{s}\approx 5.2\cdot Ra\) when considering various surfaces with different roughness. While the last relation may be the most appropriate for LPBF applications due to the anisotropy and randomness of the surfaces that are often observed, the large disparity in the suggested relations indicates that no congruent answer has been found [13]. The profile surface texture parameters mentioned above were developed to characterize the surface of conventional manufacturing techniques such as subtractive processes including milling and turning. With the increased interest in additive manufacturing (AM) and the rising use of the LPBF process as an addition to existing manufacturing practices, there exists a debate on whether the conventional profile and areal surface texture parameters are appropriate for adequately characterizing additively manufactured surfaces. The surface of LPBF components is typically showing complex features (including re-entrant features [14]) and a randomized surface texture, except for scanning lines being visible in some cases. Some research is focused on the development of better and more accurate frameworks and methods to determine the surface texture of additively manufactured components, including the development of new surface texture parameters [15; 16; 17]. In recent times, these are often used in the investigation of the influence of LPBF process parameters on the resulting surface texture [5; 18]. As long as this is the case, it is important to understand the applicability of classic surface texture parameters and how they may be, or may not be, used to characterize AM surfaces. Classic techniques for surface texture analysis are not easily used for the evaluation of internal roughness [19]. While optical techniques are increasingly used, in order to use the techniques, artifacts are typically cut into several sections. The destructive approach may limit the degree to which full characterization can be obtained. Furthermore, optical techniques have limitations in their ability to detect steep slopes, which are often present in LPBF channels [20].