Multiscale Characterization of Automotive Surface Coating Formation for Sustainable Manufacturing

Xiao, Jie; Li, Jia; Piluso, Cristina; Huang, Yinlun

doi:10.1016/s1004-9541(08)60099-3

Cited by 4 publications

(3 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Y.W. Jia et al [14] simplified the cathode air intake system of fuel cell, simulated and analyzed the cathode inlet form with FLUENT software. The results showed that the adoption of layout scheme with two gas inlet at the two ends or the high-pressure system can improve the heterogeneity in stack significantly.…”

Section: Simulation Based On Ansys/fluentmentioning

confidence: 99%

Simulation Researches of PEMFC Based on ANSYS / FLUENT

Wang

et al. 2011

AMR

View full text Add to dashboard Cite

The internal mass transfer and the distribution of each component in proton exchange membrane fuel cell (PEMFC), including the hydrogen-oxygen proton exchange membrane fuel cell (H2-O2PEMFC) and direct methanol fuel cell (DMFC), have great effects on the life and performance of cell. Simulation with software is one of the most important research methods. In this paper, the recent researches on the working conditions of PEMFC modeled with commercial software ANSYS / FLUENT are summarized, and on the basis, new visions for further study about abnormal fuel cells are brought forward.

show abstract

Section: Simulation Based On Ansys/fluentmentioning

confidence: 99%

Simulation Researches of PEMFC Based on ANSYS / FLUENT

Wang

et al. 2011

AMR

View full text Add to dashboard Cite

show abstract

“…Paint-based surface coatings are conventionally manufactured through two consecutive operational steps, i.e., spray and curing . In operation, coating formation involves a continuous deposition of a large quantity of small droplets on a substrate, which is followed by solvent evaporation and thermal curing of the wet thin film. , It has been found experimentally that the initial morphology of the substrate does affect the final coating morphology, since some textures of the coating on a rough surface do not appear in the coating on a smooth substrate such as glasses .…”

Section: Introductionmentioning

confidence: 99%

Computational Study of Single Droplet Deposition on Randomly Rough Surfaces: Surface Morphological Effect on Droplet Impact Dynamics

Xiao

Pan

Xia

et al. 2018

Ind. Eng. Chem. Res.

Self Cite

View full text Add to dashboard Cite

Tremendous efforts have been devoted to the modeling of droplet deposition on smooth and patterned surfaces with ordered structures. However, systematic work focusing on randomly rough surfaces, which are the most common bare substrate surfaces, can be hardly identified. A phase field modeling method together with a unique analysis approach has been developed in this work to characterize single droplet deposition on randomly rough surfaces. It is interesting to observe that the droplet shape evolves quite differently on a randomly rough surface, as compared to a patterned surface, even if two surfaces have the same roughness. Parametric studies have been carried out to explore how the morphological metrics of randomly rough surfaces, which include the Wenzel roughness parameter (W r ) and the root-mean-square roughness (R r ), can affect droplet impact dynamics. The quantitative relationships derived from this study can eventually shed light on droplet shape on-aim control during the deposition process, which is of great practical importance in many applications.

show abstract

“…This makes current qual-ity control rely only on post-process sampling, causes various quality problems, leads to inefficient energy and material utilization, and generates excessive amounts of waste and pollutants [2,3]. Furthermore, there exists a clear knowledge disconnection between the macroscale bulk production and finer-scale material properties and product behavior [4,5]. In production, operational settings are always being adjusted based on experience in the macroscale; hence the true optimality could almost never be realized.…”

Section: Introductionmentioning

confidence: 99%