Analysis of nano-particle release from the surface of structural concrete members by laser ablation using soft computing. (November 2022) - Su, Zibing; Wang, Rui; Petković, Dalibor; Denic, Nebojsa; Marzouki, Riadh; Amine Khadimallah, Mohamed
Highlights: High hardness and brittleness of the ceramics limits the micro machining process. Laser ablation with micro and nano microstructures. Material removal rate (MRR) and aspect ratio. Abstract: The paper is concerned with the evaluation of laser-treated cementitious surfaces. It is part of a bigger investigation into the laser cleaning procedure and its impact on the change of the Nano particles of cementitious composites and concrete member structures. Because of the wide range of absorptivity of highly developed surfaces of concrete members and cementitious materials, their reactions to laser irradiation varied significantly. Even while laser could effectively remove the particles from the surface of concrete members, there are usually some residual surface modifications related with mortar removing, fracture development, and glazing (melted mortar). In this study, a large amount of thermal stress is created with low power densities (300 W/cm 2 ) and large spot sizes (50 mm) that promote structural concrete member cracking. By raise of power density, the cement matrix material melts make the thermal ablation mode ineffective. This procedure is also heavily influenced by the beam diameter to aggregate size rate. As a result, due to stable size of aggregate, the procedure is not scalable. In this study, the findings of ablation experiments on cement and concrete member specimens performed with a Yb-fiber laser with a power of 1 kW and a focused beam width of 800 m have been delivered through fiber optic beam delivery. In order to know the influence of substrate composition on ablation ratio and processes, the laser–surface interaction was examined on type I Portland cement with varying amounts of sand or fine silica. The primary objective is to maximize the material removal rate (MRR) and aspect proportion of alumina, stainless steel, and chromium (Cr). The goal of this study is to use an adaptive neural fuzzy inference system (ANFIS) to categorize the multiple input variables for MRR and ratios based on process variables. Scanning speed, annealing temperature, laser power, and laser frequency are all input parameters. The prediction might be crucial in determining the ideal circumstances for micro and Nano architectures of concrete members created by laser ablation. According to the data, annealing power has the greatest impact on aspect ratio, whereas micro structure width has the most effect on MRR. Analysis revealed that contaminants of alumina, stainless steel, and chromium (Cr) were highly segregated into distinct areas of the aerosol's particle size distribution.