Laser polishing of selective laser melted components
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Selective Laser Melting
Though superliquid-repelling surfaces are universally important in the fields of fundamental research and industrial production, the understanding and development of these surfaces to impacting liquid droplets remain elusive, especially the changes of wettability states. Surface roughness is required to obtain superliquid-repelling surfaces. However, the effect of surface roughness on the transition of these surfaces' wettability states is uncertain. Herein, we unveiled the relationship of surface roughness on regulating the wettability states of superliquid-repelling surfaces with randomly distributed rough structures through experiment and calculations. The roughness was controlled via regulating the size of surface rough structures, which were formed by a facile coating method. The results indicated that the surface rough structures could impact the value of the polar component (γsp) and then impact the wettability states of superliquid-repelling surfaces. Quantitatively, when the increment of surface roughness was low, the decrement of γsp was low and the wettability state of the superliquid-repelling surface was superhydrophobicity. When the increment of surface roughness was high, the decrement of γsp was high and the wettability state of the superliquid-repelling surface converted to superamphiphobicity. The findings will shed light onto the development of superliquid-repelling surfaces in future studies.
Wetting transition
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Summary Surface roughness is an essential rock parameter affecting petrophysical properties that are surface sensitive such as characterization of pore structure and wettability. For instance, Wenzel’s contact angle formula for rough surfaces requires knowledge of the surface roughness, and surface roughness is expected to speed up the aging of cores in crude oil for wettability restoration. In addition, proper quantification of surface roughness is critical for obtaining representative, roughness-independent, pore sizes for applications such as prediction of permeability and interpretation of capillary pressure curves. Intuitively, a surface is better characterized in 2D than in 1D. This 2D study is a continuation and enhancement of the previous 1D work, recently published in the SPE Journal (Ma et al. 2021). In this current paper, a comprehensive investigation of 1D vs. 2D surface roughness measurements is conducted to evaluate and cross validate the two approaches. In this study, surface roughness is measured on 26 carbonate rock samples by laser scanning confocal microscopy (LSCM), where both the 1D absolute increment surface roughness, Sr, and the 2D interfacial area ratio of surface roughness, Sdr, are reported. As expected, the results indicate that surface roughness characterized by 2D Sdr has a greater dynamic range than the 1D Sr measurement, i.e., the 2D Sdr provides a more representative characterization of surface roughness. A detailed account of methodologies, assumptions, limitations, validation, and applications of the 1D and 2D surface roughness characterization is documented in this paper. To extract the roughness features present on rock grain surfaces, effects of de-spiking and filter length, used to eliminate pore-size effects, are investigated. For specific applications of surface roughness corrected pore-size estimation from nuclear magnetic resonance (NMR) measurements, differences in length scales of surface roughness are compared between LSCM measurement and that derived from NMR diffusion-T2 plus BET (Brunauer-Emmett-Teller) surface area. The surface roughness-corrected NMR pore-size distribution is also validated against the pore-size distribution obtained from the measurement of micro-computed tomography (CT) scanning.
Petrophysics
Characterization
Capillary pressure
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Surface roughness of part was vital to its application.40Cr material was irradiated by large scale pulse electron beam with orthogonal experiment and the surface roughness was checked.The results indicate that the surface roughness of 40Cr is changed by different electron beam parameters.Surface roughness of part increases or decreases in terms of electron beam parameter.The samples with high and low surface roughness are tested with electron beam respectively.The results show that the surface roughness decreases with irradiation numbers increasing in high original surface roughness,contrary surface roughness increases with irradiation numbers increasing in low original surface roughness.It is analysed that the surface roughness is influenced in two opposite sidedness when it is modified on the surface with pulsed electron beam.
Electron beam processing
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This paper aims at studying the effect of polishing parameters on surface roughness by using the cloth wheel polishing process. Stainless steel was used as a specimen in this study. The investigation firstly accounted for the comparison between two polishing compounds, and the best one was used to be applied in a set of experiment. The effect of spindle speed, current and polishing time on the surface roughness of stainless steel was examined, and the results showed that polishing time and current played the significant role in degree of roughness. The optimum condition under the range of parameters considered in this work was determined, whose surface roughness was about 0.0466 μm.
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Purpose The purpose of this paper is to provide a theoretical foundation for improving the selective laser melting (SLM) surface roughness. To improve the part’s surface quality during SLM process, the upper surface roughness of SLM parts was theoretically studied and the influencing factors were analyzed through experiments. Design/methodology/approach The characteristics of single track were first investigated, and based on the analysis of single track, theoretical value of the upper surface roughness would be calculated. Two groups of cubic sample were fabricated to validate SLM parts’ surface roughness, the Ra and relative density of all the cubic parts was measured, and the difference between theoretical calculation and experiment results was studied. Then, the effect of laser energy density on surface roughness was studied. At last, the SLM part’s surface was improved by laser re-melting method. At the end of this paper, the curved surface roughness was discussed briefly. Findings The SLM upper surface roughness is affected by the width of track, scan space and the thickness of powder layer. Measured surface roughness Ra value was about 50 per cent greater than the theoretical value. The laser energy density has a great influence on the SLM fabrication quality. Different laser energy density corresponds to different fabricating characteristics. This study divided the SLM fabrication into not completely melting zone, balling zone in low energy density, successfully fabricating zone and excessive melting zone. The laser surface re-melting (LSR) process can improve the surface roughness of SLM parts greatly without considering the fabricating time and stress accumulation. Originality/value The upper surface roughness of SLM parts was theoretically studied, and the influencing factors were analyzed together; also, the LSR process was proven to be effective to improve the surface quality. This study provides a theoretical foundation to improve the surface quality of SLM parts to promote the popularization and application of metal additive manufacturing technology.
Selective Laser Melting
Relative density
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Although the concept of additive manufacturing has been proposed for several decades, momentum of selective laser melting (SLM) is finally starting to build. In SLM, density and surface roughness, as the important quality indexes of SLMed parts, are dependent on the processing parameters. However, there are few studies on their collaborative optimization in SLM to obtain high relative density and low surface roughness simultaneously in the previous literature. In this work, the response surface method was adopted to study the influences of different processing parameters (laser power, scanning speed and hatch space) on density and surface roughness of 316L stainless steel parts fabricated by SLM. The statistical relationship model between processing parameters and manufacturing quality is established. A multi-objective collaborative optimization strategy considering both density and surface roughness is proposed. The experimental results show that the main effects of processing parameters on the density and surface roughness are similar. It is noted that the effects of the laser power and scanning speed on the above objective quality show highly significant, while hatch space behaves an insignificant impact. Based on the above optimization, 316L stainless steel parts with excellent surface roughness and relative density can be obtained by SLM with optimized processing parameters.
Selective Laser Melting
Relative density
Power density
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Although the concept of additive manufacturing has been proposed for several decades, momentum in the area of selective laser melting (SLM) is finally starting to build. In SLM, density and surface roughness, as the important quality indexes of SLMed parts, are dependent on the processing parameters. However, there are few studies on their collaborative optimization during SLM to obtain high relative density and low surface roughness simultaneously in the literature. In this work, the response surface method was adopted to study the influences of different processing parameters (laser power, scanning speed and hatch space) on density and surface roughness of 316L stainless steel parts fabricated by SLM. A statistical relationship model between processing parameters and manufacturing quality is established. A multi-objective collaborative optimization strategy considering both density and surface roughness is proposed. The experimental results show that the main effects of processing parameters on the density and surface roughness are similar. We observed that the laser power and scanning speed significantly affected the above objective quality, but the influence of the hatch spacing was comparatively low. Based on the above optimization, 316L stainless steel parts with excellent surface roughness and relative density can be obtained by SLM with optimized processing parameters.
Selective Laser Melting
Relative density
Power density
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Poor surface quality presents a major limitation to the widespread use of selective laser melting (SLM) technology. In this study, systematic research has been carried out to study the influences of different processing parameters and scanning strategies on surface roughness of SLMed Hastelloy X alloy. Surface characterisations revealed that melt pool shape and the presence of partially melted particles are vital factors in determining the surface profile and resultant roughness in the final parts. By understanding the surface roughness formation mechanism, optimal surface roughness of manufactured components can be achieved.
Selective Laser Melting
Laser Scanning
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Abstract In this article, selective laser melting (SLM) equipment is used to print 316L stainless steel parts under different process parameters, and the surface roughness of the parts is measured. Based on back propagation neural networks (BP neural networks, BPNN), the upper surface roughness prediction model is established. The laser power, scanning speed, and scanning interval are used as model input, and the surface roughness of the workpiece is output. This model can easily and quickly predict the surface roughness of SLM metal printing, with high prediction accuracy, and can provide a basis for the optimization of SLM process parameters.
Selective Laser Melting
Backpropagation
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Contact area
Roughness length
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