A Computational Fluid Dynamics (CFD) Study of Material Transport and Deposition in Aerosol Jet Printing (AJP) Process

2018 ◽  
Author(s):  
Roozbeh (Ross) Salary ◽  
Jack P. Lombardi ◽  
Darshana L. Weerawarne ◽  
Prahalada K. Rao ◽  
Mark D. Poliks
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Gas Flow ◽  
Complex Geometry ◽  
Sensor Data ◽  
Cfd Model ◽  
Material Transport ◽  
Jet Printing ◽  
Computational Fluid Dynamics Cfd ◽  
Aerosol Jet Printing

The objective of this work is to forward a 3D computational fluid dynamics (CFD) model to explain the aerodynamics behind aerosol transport and deposition in aerosol jet printing (AJP). The CFD model allows for: (i) mapping of velocity fields as well as particle trajectories; and (ii) investigation of post-deposition phenomena of sticking, rebounding, spreading, and splashing. The complex geometry of the deposition head was modeled in the ANSYS-Fluent environment, based on a patented design as well as accurate measurements, obtained from 3D X-ray CT imaging. The entire volume of the geometry was subsequently meshed, using a mixture of smooth and soft quadrilateral elements, with consideration of layers of inflation to obtain an accurate solution near the walls. A combined approach — based on the density-based and pressure-based Navier-Stokes formation — was adopted to obtain steady-state solutions and to bring the conservation imbalances below a specified linearization tolerance (10−6). Turbulence was modeled, using the realizable k-ε viscose model with scalable wall functions. A coupled two-phase flow model was set up to track a large number of injected particles. The boundary conditions were defined based on experimental sensor data. A single-factor factorial experiment was conducted to investigate the influence of sheath gas flow rate (ShGFR) on line morphology, and also validate the CFD model.

A Computational Fluid Dynamics (CFD) Study of Material Flow in Pneumatic Microextrusion (PME) Additive Manufacturing Process

2020 ◽  
Author(s):  
Ye Jien Yeow ◽  
Mohan Yu ◽  
James B. Day ◽  
Roozbeh (Ross) Salary
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Gas Flow ◽  
Fluid Model ◽  
Accurate Solution ◽  
Sensor Data ◽  
Cfd Model ◽  
Transient Pressure ◽  
Material Transport ◽  
Computational Fluid Dynamics Cfd

Abstract The objective of this study is to investigate the underlying physical phenomena behind material transport in pneumatic micro-extrusion (PME) process, using a computational fluid dynamics (CFD) model. The geometry of the PME deposition head assembly (including a micro-capillary having a diameter of 200 μm) was set up in the ANSYS-Fluent environment, based on a patented design in addition to direct measurements of the dimensions of the assembly. Subsequently, the geometry was meshed using tetrahedron cells. Besides, five layers of inflation were defined with the aim to obtain an accurate solution near all wall boundaries. The transient, pressure-based Navier-Stokes algorithm (based on absolute velocity formulation) was the mathematical model of choice, used to obtain transient solutions. To account for the effects of compressibility as well as viscose heating, the energy equation (in addition to the continuity and momentum equations) was utilized in the CFD model. Furthermore, the explicit volume of fluid model (composed of two Eulerian phases) and the laminar viscose model were used to collectively establish a viscose two-phase flow model for the molten polymer (PCL) deposition in the PME process. Pressure-velocity coupling was implemented using the semi-implicit method for pressure linked equations (SIMPLE). Finally, experimental sensor data was used with the aim to: (i) define the boundary conditions (as follows), and (ii) validate the CFD model. In this study, PCL powder was loaded into the cartridge, maintained at 120 °C, defined as the temperature of all stationery walls (with no slip condition). Pressure inlet was the type of boundary defined for the high-pressure gas flow in the PME process, set at 550 kPa. The laminar molten PCL flow was deposited on a glass substrate, steadily and uniformly kept at 45 °C, defined as the temperature of the substrate wall, moving with a speed of 0.35 mm/s. Overall, the results of this study pave the way for better understanding of the causal phenomena behind material transport and deposition in the PME process toward fabrication of bone tissue scaffolds with optimal functional properties.

In Situ Sensor-Based Monitoring and Computational Fluid Dynamics (CFD) Modeling of Aerosol Jet Printing (AJP) Process

2016 ◽  
Author(s):  
Roozbeh (Ross) Salary ◽  
Jack P. Lombardi ◽  
M. Samie Tootooni ◽  
Ryan Donovan ◽  
Prahalad K. Rao ◽  
...  
Keyword(s):  
Fluid Dynamics ◽  
Image Processing ◽  
Computational Fluid Dynamics ◽  
Gas Flow ◽  
Cfd Modeling ◽  
Process Window ◽  
Cfd Model ◽  
Jet Printing ◽  
Aerosol Jet Printing

The aim of this paper is to demonstrate a pathway for in situ real-time monitoring and closed-loop control of aerosol jet printing (AJP) process. To achieve this aim, we instrumented an Optomec AJ-300 aerosol jet printer with multiple temporal and image-based sensors. Experiments were conducted by varying the sheath gas flow rate (ShGFR) and, subsequently, the line morphology was acquired online using a CCD camera mounted coaxial to the nozzle (perpendicular to the platen). To assess the line morphology, we devised a novel digital image processing method that quantifies aspects of line morphology, such as line density, overspray, continuity, edge smoothness, etc. As a result, an optimal process window was established. Next, the underlying aerodynamic phenomena that influence the line morphology are explained based on a two dimensional computational fluid dynamics (2D-CFD) model. Thus, the image processing approach proposed in this work can be used to detect incipient process drifts, while the CFD model will be valuable to suggest the appropriate corrective action to bring the process back in control. We further validate that there is a good agreement between the online and offline results with respect to the quantified morphology of the lines.

Computational Fluid Dynamics Modeling and Online Monitoring of Aerosol Jet Printing Process

2016 ◽  
Vol 139 (2) ◽  
Author(s):  
Roozbeh (Ross) Salary ◽  
Jack P. Lombardi ◽  
M. Samie Tootooni ◽  
Ryan Donovan ◽  
Prahalad K. Rao ◽  
...  
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Flow Rate ◽  
Gas Flow ◽  
Online Monitoring ◽  
Print Quality ◽  
Cfd Model ◽  
Gas Flow Rate ◽  
Jet Printing ◽  
Aerosol Jet Printing

The objectives of this paper in the context of aerosol jet printing (AJP)—an additive manufacturing (AM) process—are to: (1) realize in situ online monitoring of print quality in terms of line/electronic trace morphology; and (2) explain the causal aerodynamic interactions that govern line morphology based on a two-dimensional computational fluid dynamics (2D-CFD) model. To realize these objectives, an Optomec AJ-300 aerosol jet printer was instrumented with a charge coupled device (CCD) camera mounted coaxial to the nozzle (perpendicular to the platen). Experiments were conducted by varying two process parameters, namely, sheath gas flow rate (ShGFR) and carrier gas flow rate (CGFR). The morphology of the deposited lines was captured from the online CCD images. Subsequently, using a novel digital image processing method proposed in this study, six line morphology attributes were quantified. The quantified line morphology attributes are: (1) line width, (2) line density, (3) line edge quality/smoothness, (4) overspray (OS), (5) line discontinuity, and (6) internal connectivity. The experimentally observed line morphology trends as a function of ShGFR and CGFR were verified with computational fluid dynamics (CFD) simulations. The image-based line morphology quantifiers proposed in this work can be used for online detection of incipient process drifts, while the CFD model is valuable to ascertain the appropriate corrective action to bring the process back in control in case of a drift.

Computational Fluid Dynamics (CFD) Simulation of Liquid-Liquid Mixing in Mixer Settler

2012 ◽  
Vol 57 (1) ◽  
pp. 173-178 ◽  
Author(s):  
M. Shabani ◽  
A. Mazahery
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Process Simulation ◽  
Chemical Process ◽  
Cfd Simulation ◽  
Complex Geometry ◽  
Physical Parameters ◽  
Cfd Model ◽  
Liquid Mixing ◽  
Computational Fluid Dynamics Cfd

Computational Fluid Dynamics (CFD) Simulation of Liquid-Liquid Mixing in Mixer Settler Mixer-settlers are widely used inmetallurgical, mineral and chemical process. One of the greatest challenges in the area of hydrometallurgy process simulation is agitation made by impeller inside mixer-settler which yet presents one of the most common operations. Computational fluid dynamics (CFD) model has been developed to predict the effect of different physical parameters including temperature and density on the mixing characteristics of the system. It is noted that non-isotropic nature of flow in a mixer-settler, the complex geometry of rotating impellers and the large disparity in geometric scales present are some of the factors which contribute to the simulation difficulty. The experimental data for different velocity outlet was also used in order to validate the model.

A Computational Fluid Dynamics Investigation of Pneumatic Atomization, Aerosol Transport, and Deposition in Aerosol Jet Printing Process

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Roozbeh (Ross) Salary ◽  
Jack P. Lombardi ◽  
Darshana L. Weerawarne ◽  
Prahalada Rao ◽  
Mark D. Poliks
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
In Situ Monitoring ◽  
Cfd Model ◽  
Monitoring And Control ◽  
Aerosol Transport ◽  
Jet Printing ◽  
And Control ◽  
Aerosol Jet Printing

Abstract Aerosol jet printing (AJP) is a direct-write additive manufacturing technique, which has emerged as a high-resolution method for the fabrication of a broad spectrum of electronic devices. Despite the advantages and critical applications of AJP in the printed-electronics industry, AJP process is intrinsically unstable, complex, and prone to unexpected gradual drifts, which adversely affect the morphology and consequently the functional performance of a printed electronic device. Therefore, in situ process monitoring and control in AJP is an inevitable need. In this respect, in addition to experimental characterization of the AJP process, physical models would be required to explain the underlying aerodynamic phenomena in AJP. The goal of this research work is to establish a physics-based computational platform for prediction of aerosol flow regimes and ultimately, physics-driven control of the AJP process. In pursuit of this goal, the objective is to forward a three-dimensional (3D) compressible, turbulent, multiphase computational fluid dynamics (CFD) model to investigate the aerodynamics behind: (i) aerosol generation, (ii) aerosol transport, and (iii) aerosol deposition on a moving free surface in the AJP process. The complex geometries of the deposition head as well as the pneumatic atomizer were modeled in the ansys-fluent environment, based on patented designs in addition to accurate measurements, obtained from 3D X-ray micro-computed tomography (μ-CT) imaging. The entire volume of the constructed geometries was subsequently meshed using a mixture of smooth and soft quadrilateral elements, with consideration of layers of inflation to obtain an accurate solution near the walls. A combined approach, based on the density-based and pressure-based Navier–Stokes formation, was adopted to obtain steady-state solutions and to bring the conservation imbalances below a specified linearization tolerance (i.e., 10−6). Turbulence was modeled using the realizable k-ε viscous model with scalable wall functions. A coupled two-phase flow model was, in addition, set up to track a large number of injected particles. The boundary conditions of the CFD model were defined based on experimental sensor data, recorded from the AJP control system. The accuracy of the model was validated using a factorial experiment, composed of AJ-deposition of a silver nanoparticle ink on a polyimide substrate. The outcomes of this study pave the way for the implementation of physics-driven in situ monitoring and control of AJP.

Modeling of High Temperature Gas Flow 3D Distribution in BF Throat Based on the Computational Fluid Dynamics

2015 ◽  
Vol 19 (2) ◽  
pp. 269-276 ◽  
Author(s):  
Jian Qi An ◽  
◽  
Kai Peng ◽  
Wei Hua Cao ◽  
Min Wu ◽  
...  
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Gas Flow ◽  
Numerical Solutions ◽  
Flow Distribution ◽  
Three Dimensions ◽  
Cfd Model ◽  
Ansys Fluent ◽  
Proposed Model ◽  
Computational Fluid Dynamics Cfd

This paper aims at building a Computational Fluid Dynamics (CFD) model which can describe the gas flow three dimensions (3D) distribution in blast furnace (BF) throat. Firstly, the boundary conditions are obtained by rebuilding central gas flow shape in BF based on computer graphics. Secondly, the CFD model is built based on turbulent model by analyzing the features of gas flow. Finally, a method which can get the numerical solutions of the model is proposed by using CFD software ANSYS/FLUENT. The proposed model can reflect the changes of the gas flow distribution, and can help to guide the operation of furnace burdening and to ensure the BF stable and smooth production.

Validation of a Computationally Efficient Computational Fluid Dynamics (CFD) Model for Industrial Bubble Column Bioreactors

2014 ◽  
Vol 53 (37) ◽  
pp. 14526-14543 ◽  
Author(s):  
Dale D. McClure ◽  
Hannah Norris ◽  
John M. Kavanagh ◽  
David F. Fletcher ◽  
Geoffrey W. Barton
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Bubble Column ◽  
Cfd Model ◽  
Computationally Efficient ◽  
Computational Fluid Dynamics Cfd

scholarly journals Journal Bearing: An Integrated CFD-Analytical Approach for the Estimation of the Trajectory and Equilibrium Position

2020 ◽  
Vol 10 (23) ◽  
pp. 8573
Author(s):  
Franco Concli
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Pressure Distribution ◽  
Equilibrium Position ◽  
Analytical Approach ◽  
Journal Bearing ◽  
Cfd Model ◽  
Cavitation Model ◽  
Computational Fluid Dynamics Cfd ◽  
The Mathematical Model

For decades, journal bearings have been designed based on the half-Sommerfeld equations. The semi-analytical solution of the conservation equations for mass and momentum leads to the pressure distribution along the journal. However, this approach admits negative values for the pressure, phenomenon without experimental evidence. To overcome this, negative values of the pressure are artificially substituted with the vaporization pressure. This hypothesis leads to reasonable results, even if for a deeper understanding of the physics behind the lubrication and the supporting effects, cavitation should be considered and included in the mathematical model. In a previous paper, the author has already shown the capability of computational fluid dynamics to accurately reproduce the experimental evidences including the Kunz cavitation model in the calculations. The computational fluid dynamics (CFD) results were compared in terms of pressure distribution with experimental data coming from different configurations. The CFD model was coupled with an analytical approach in order to calculate the equilibrium position and the trajectory of the journal. Specifically, the approach was used to study a bearing that was designed to operate within tight tolerances and speeds up to almost 30,000 rpm for operation in a gearbox.

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