Surface integrity of additive manufacturing parts: a comparison between optical topography measuring techniques

Additive Manufacturing (AM) presents significant industry-specific advantages allowing the creation of complex geometries and internal features that cannot be produced using conventional manufacturing processes. However, a current limitation of AM is the degraded dimensional control and surface integrity of specific surfaces. The parts are constructed through layer-by-layer approach, each layer presenting a characteristic ‘fingerprint’. The functional performance of the final part is influenced by the morphology of the outer surface as well as by the surface quality introduced at intermediate layers. Surface texture metrology therefore can play an enabling role in AM-related manufacture and research. The use of optical topography measurement instrumentation allows for a high level of detail in the acquisition of topographic information. Some of the most commonly used optical measuring instruments are Vertical Scanning Interferometry (CSI), Imaging Confocal Microscopy (CONF), and Focus Variation (FV), each one has benefits and drawbacks in terms of acquisition time and measurement resolution. AM surfaces overall present complex topographical features, requiring the acquisition of large surface areas and large z-scans which considerably increases the acquisition time. Speed is a key factor in industrial practice, and time optimization is required for quality control and surface analysis before down-stream processes. This paper reports on the measurement and characterisation of the surface texture of metal powder bed fusion AM parts. All measurements were performed in the same SENSOFAR S-NEOX instrument using the commonly used optical technologies (CSI, CONF, and FV) and the latest step in confocal measurement technology called Continuous Confocal (C-CONF). The resolution and acquisition time of each technique is analysed in order to check the suitability of each method to characterize and describe the AM surface microstructures in a time-efficient way

Fingering Instabilities in Dewetting Nanofluids

The growth of fingering patterns in dewetting nanofluids (colloidal solutions of thiol-passivated gold nanoparticles) has been followed in real time using contrast-enhanced video microscopy. The fingering instability on which we focus here arises from evaporatively-driven nucleation and growth a nanoscopically thin "precursor" solvent film behind the macroscopic contact line. We find that well-developed isotropic fingering structures only form for a narrow range of experimental parameters. Numerical simulations, based on a modification of the Monte Carlo approach introduced by Rabani et al. [Nature 426, 271 (2003)], reproduce the patterns we observe experimentally

Reconstruction of three-dimensional porous media using generative adversarial neural networks

To evaluate the variability of multi-phase flow properties of porous media at the pore scale, it is necessary to acquire a number of representative samples of the void-solid structure. While modern x-ray computer tomography has made it possible to extract three-dimensional images of the pore space, assessment of the variability in the inherent material properties is often experimentally not feasible. We present a novel method to reconstruct the solid-void structure of porous media by applying a generative neural network that allows an implicit description of the probability distribution represented by three-dimensional image datasets. We show, by using an adversarial learning approach for neural networks, that this method of unsupervised learning is able to generate representative samples of porous media that honor their statistics. We successfully compare measures of pore morphology, such as the Euler characteristic, two-point statistics and directional single-phase permeability of synthetic realizations with the calculated properties of a bead pack, Berea sandstone, and Ketton limestone. Results show that GANs can be used to reconstruct high-resolution three-dimensional images of porous media at different scales that are representative of the morphology of the images used to train the neural network. The fully convolutional nature of the trained neural network allows the generation of large samples while maintaining computational efficiency. Compared to classical stochastic methods of image reconstruction, the implicit representation of the learned data distribution can be stored and reused to generate multiple realizations of the pore structure very rapidly.Comment: 21 pages, 20 figure

Controlling Pattern Formation in Nanoparticle Assemblies via Directed Solvent Dewetting

We have achieved highly localised control of pattern formation in two dimensional nanoparticle assemblies by direct modification of solvent dewetting dynamics. A striking dependence of nanoparticle organisation on the size of atomic force microscope-generated surface heterogeneities is observed and reproduced in numerical simulations. Nanoscale features induce rupture of the solvent-nanoparticle film, causing the local flow of solvent to carry nanoparticles into confinement. Microscale heterogeneities instead slow the evaporation of the solvent, producing a remarkably abrupt interface between different nanoparticle patterns

Controlling pattern formation in nanoparticle assemblies via directed solvent dewetting.

We have achieved highly localized control of pattern formation in two-dimensional nanoparticle assemblies by direct modification of solvent dewetting dynamics. A striking dependence of nanoparticle organization on the size of atomic force microscope-generated surface heterogeneities is observed and reproduced in numerical simulations. Nanoscale features induce a rupture of the solvent-nanoparticle film, causing the local flow of solvent to carry nanoparticles into confinement. Microscale heterogeneities instead slow the evaporation of the solvent, producing a remarkably abrupt interface between different nanoparticle patterns

Off-site population radiological dose and risk assessment for potential airborne emissions from the Weldon Spring Site

Radiological doses and health risks to the population around the Weldon Spring site from potential airborne emissions during remedial action at the chemical plant area of the site have been assessed with the Clean Air Act Assessment Package-1988 computer code. Two treatment options are being considered for waste produced by site cleanup activities: chemical stabilization/solidification and vitrification. Over the entire cleanup period of 7 years, the collective dose received by the people who live within 80 km (50 mi) of the site (about 3 million persons) is estimated to be about 34 person-rem for the chemical stabilization/ solidification option and 32 person-rem for the vitrification option. By comparison, the same population is expected to receive about 6 [times] 10[sup 6] person-rem from natural background radiation during that time. If only the population within a reasonable radius of impact is considered (about 10,700 persons live within 5 km [3 mi] of the site), the remedial action activities are estimated to result in about 5 person-rem over the entire cleanup period; the same population is expected to receive about 20,000 person-rem from natural background radiation during that time. Because the doses are low, no cancers or genetic effects are expected to occur among the population around the Weldon Spring site as a result of exposures resulting from potential radioactive releases to the atmosphere during remediation of the chemicalplant area

Simulating temporal evolution of pressure in two-phase flow in porous media

We have simulated the temporal evolution of pressure due to capillary and viscous forces in two-phase drainage in porous media. We analyze our result in light of macroscopic flow equations for two-phase flow. We also investigate the effect of the trapped clusters on the pressure evolution and on the effective permeability of the system. We find that the capillary forces play an important role during the displacements for both fast and slow injection rates and both when the invading fluid is more or less viscous than the defending fluid. The simulations are based on a network simulator modeling two-phase drainage displacements on a two-dimensional lattice of tubes.Comment: 12 pages, LaTeX, 14 figures, Postscrip

Droplet fragmentation: 3D imaging of a previously unidentified pore-scale process during multiphase flow in porous media

Using X-ray computed microtomography, we have visualized and quantified the in situ structure of a trapped nonwetting phase (oil) in a highly heterogeneous carbonate rock after injecting a wetting phase (brine) at low and high capillary numbers. We imaged the process of capillary desaturation in 3D and demonstrated its impacts on the trapped nonwetting phase cluster size distribution. We have identified a previously unidentified pore-scale event during capillary desaturation. This pore-scale event, described as droplet fragmentation of the nonwetting phase, occurs in larger pores. It increases volumetric production of the nonwetting phase after capillary trapping and enlarges the fluid−fluid interface, which can enhance mass transfer between the phases. Droplet fragmentation therefore has implications for a range of multiphase flow processes in natural and engineered porous media with complex heterogeneous pore spaces