Modelling of surface evolution in abrasive jet micro-machining including particle second strikes: A level set methodology

Burzynski, T.; Papini, M.

doi:10.1016/j.jmatprotec.2012.01.002

Cited by 14 publications

(3 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Beyond this, second strike effects that resulted from ricocheted particles from the channel side-walls into the center of the channel resulted in an approximately 10% under-prediction of depth. This well-known phenomenon causes an increase in the erosion rate at the channel center that cannot be modelled without advanced particle-tracking methods [66]. Both the maskless and shadow mask techniques resulted in some frosting of the surface adjacent to the channel edges.…”

Section: Effect Of Erosive Efficacy Footprint Widthmentioning

confidence: 99%

Sculpting Desired Topographies Using Abrasive Jet Micro-Machining

Sookhaklari¹

2021

Preprint

View full text Add to dashboard Cite

Abrasive jet micromachining (AJM) uses a jet of high-speed particles to erode a wide variety of materials. Given a set of process parameters, surface evolution models capable of predicting the shape of straight, constant-depth channels in a wide variety of materials are well-established. This dissertation presents novel methods for solving the unaddressed more challenging and industrially relevant inverse problem of determining the process parameters required to machine a particular user-specified feature topography. Since the air driven jet used in AJM is divergent, the edges of the desired features are usually defined using a mask which is attached to the surface of the target material. This dissertation presents alternate techniques using stationary or moving shadow masks that can be moved over the surface and maskless techniques, in order to allow direct writing of desired features on the surface. A mathematical framework is then introduced to determine the direct writing source velocity function and path required to create a desired shallow topography. It is also shown how the methodology can be used with existing surface evolution models to predict the feature shape at any depth. The methodologies are demonstrated to work well for the AJM of constant depth micro-channels with user-specified cross-sectional shape, gradient etched micro-channels with specified texture along their length, and pockets with texture in two perpendicular directions. Finally, a new technique is introduced that utilizes a rotating patterned mask in order to control the AJM erosive footprint size and shape. Models for predicting the rotating mask pattern required to create virtually any desired footprint are presented, and experimentally verified for symmetric and asymmetric W-shaped, trapezoidal and wedge shaped footprints.

show abstract

Section: Effect Of Erosive Efficacy Footprint Widthmentioning

confidence: 99%

Sculpting Desired Topographies Using Abrasive Jet Micro-Machining

Sookhaklari¹

2021

Preprint

View full text Add to dashboard Cite

show abstract

“…As shown in Figures 2.12,3.8 and 4.10 (x ≥ 0), there was no significant discrepancy between predicted and measured surface evolution of ductile (PMMA) features in terms of profile depth and overall shape well beyond AR of 1, without consideration of second strike effects. The majority of the material in this chapter has been accepted for publication in [51].…”

Section: Motivationmentioning

confidence: 99%

Modelling surface evolution in abrasive jet micromachining using level set methods

Burzynski¹

2021

Preprint

View full text Add to dashboard Cite

The time dependent surface evolution in abrasive jet micromachining (AJM) is described by a partial differential equation which is difficult to solve using analytical or traditional numerical techniques. These techniques can yield incorrect predicted profile evolution or fail altogether under certain conditions. More recently developed particle tracking cellular automaton simulations can address some of these limitations but are difficult to implement and are computationally expensive. In this work, level set methods (LSM) were introduced to develop novel surface evolution models to predict resulting feature shapes in AJM. Initially, a LSM-based numerical model was developed to predict the surface evolution of unmasked channels machined at normal and oblique jet impact angles (incidence), as well as masked micro-channels and micro-holes at normal incidence, in both brittle and ductile targets. This model was then extended to allow the prediction of: surface evolution of inclined masked micro-channels made using AJM at oblique incidence, where the developing profiles rapidly become multi-valued necessitating a more complex formulation; mask erosive wear by permitting surface evolution of both the mask and target micro-channels simultaneously at any jet incidence; and surface damage due to secondary particle strikes in brittle target micro-channels resulting from particle mask-to-target and target-to-target ricochets at any jet incidence. For all the models, a general ‘masking’ function was developed by applying previous concepts to model the adjustment to abrasive mass flux incident to the target or mask surfaces to reflect the range of particle sizes that are ‘visible’ to these surfaces. The models were also optimized for computational efficiency using an adaptive Narrow Band LSM scheme. All models were experimentally verified and, where possible, compared against existing models. Generally, good predictive capabilities and improvements over previous attempts in terms of feature prediction or execution time, were observed. The time dependent surface evolution in abrasive jet micromachining (AJM) is described by a partial differential equation which is difficult to solve using analytical or traditional numerical techniques. These techniques can yield incorrect predicted profile evolution or fail altogether under certain conditions. More recently developed particle tracking cellular automaton simulations can address some of these limitations but are difficult to implement and are computationally expensive.In this work, level set methods (LSM) were introduced to develop novel surface evolution models to predict resulting feature shapes in AJM. Initially, a LSM-based numerical model was developed to predict the surface evolution of unmasked channels machined at normal and oblique jet impact angles (incidence), as well as masked micro-channels and micro-holes at normal incidence, in both brittle and ductile targets.This model was then extended to allow the prediction of: surface evolution of inclined masked micro-channels made using AJM at oblique incidence, where the developing profiles rapidly become multi-valued necessitating a more complex formulation; mask erosive wear by permitting surface evolution of both the mask and target micro-channels simultaneously at any jet incidence; and surface damage due to secondary particle strikes in brittle target micro-channels resulting from particle mask-to-target and target-to-target ricochets at any jet incidence. For all the models, a general ‘masking’ functionwas developed by applying previous concepts to model the adjustment to abrasive mass flux incident to the target or mask surfaces to reflect the range of particle sizes that are ‘visible’ to these surfaces. The models were also optimized for computational efficiency using an adaptive Narrow Band LSM scheme.All models were experimentally verified and, where possible, compared against existing models. Generally, good predictive capabilities and improvements over previous attempts in terms of feature prediction or execution time, were observed.The proposed LSM-based models can be practical assistive tools during the micro-fabrication of complex MEMS and microfluidic devices using AJM.

show abstract

“…What results is a partial differential equation that can be solved for the time evolving shape of the eroding feature [7,17,25].…”

Section: Modelmentioning

confidence: 99%