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.

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.

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.

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.

Effect of Gas Flow Rates on Quality of Aerosol Jet Printed Traces With Nanoparticle Conducting Ink

2019 ◽  
Vol 142 (1) ◽  
Author(s):  
Neil Dalal ◽  
Yuan Gu ◽  
Guang Chen ◽  
Daniel R. Hines ◽  
Abhijit Dasgupta ◽  
...  
Keyword(s):  
Flow Rate ◽  
Gas Flow ◽  
Effective Conductivity ◽  
Print Quality ◽  
Gas Flow Rate ◽  
Sem Images ◽  
Flow Rates ◽  
Aerosol Jet Printing ◽  
Cohesive Cracking

Abstract This paper focuses on the influence of carrier gas flow rate (CGFR) and sheath gas flow rate (SGFR) on the quality of conductive traces printed with nanoparticle inks using aerosol jet printing (AJP). This investigation was motivated by previous results of two AJP specimens that were printed at different gas flow rates and yielded significantly different thermal cycling durability lifetimes. A parametric sensitivity study was executed by printing and examining serpentine trace structures at 15 different combinations of CGFRs and SGFRs. The analysis included quantifying the trace's macroscale geometry, electrical properties, and micromorphological features. Interesting macroscale results include an increase in effective conductivity with increasing CGFR. At the microscale, image processing of high magnification scanning electron microscope (SEM) images of the printed traces revealed that agglomerations of silver clusters on the surface of traces became coarser at higher CGFR and also that agglomerates in the bulk were finer than those on the surface. Crystalline silver deposits were observed at all flow rates. In addition, cross sectioning of the printed traces showed higher incidences of buried cohesive cracking at higher gas flow rates. These cohesive cracks reduce the robustness of the traces but may not always be visible from the surface. The degree of cohesive cracking was seen to be broadly correlated with the coarseness of the surface agglomerates, thus suggesting that the coarseness of surface agglomerates may provide a visible surrogate measure of the print quality. The results of this study suggest that print quality may degrade as gas flow rates increase.

Experimentally Validated Computational Fluid Dynamics Model for Data Center With Active Tiles

2018 ◽  
Vol 140 (1) ◽  
Author(s):  
Jayati Athavale ◽  
Yogendra Joshi ◽  
Minami Yoda
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Flow Rate ◽  
Data Center ◽  
Hot Spot ◽  
Volume Flow Rate ◽  
Optimal Number ◽  
Inlet Temperature ◽  
Cfd Model ◽  
Level Model

Abstract This paper presents an experimentally validated room-level computational fluid dynamics (CFD) model for raised-floor data center configurations employing active tiles. Active tiles are perforated floor tiles with integrated fans, which increase the local volume flow rate by redistributing the cold air supplied by the computer room air conditioning (CRAC) unit to the under-floor plenum. The numerical model of the data center room consists of one cold aisle with 12 racks arranged on both sides and three CRAC units sited around the periphery of the room. The commercial CFD software package futurefacilities6sigmadcx is used to develop the model for three configurations: (a) an aisle populated with ten (i.e., all) passive tiles; (b) a single active tile and nine passive tiles in the cold aisle; and (c) an aisle populated with all active tiles. The predictions from the CFD model are found to be in good agreement with the experimental data, with an average discrepancy between the measured and computed values for total flow rate and rack inlet temperature less than 4% and 1.7 °C, respectively. The validated models were then used to simulate steady-state and transient scenarios following cooling failure. This physics-based and experimentally validated room-level model can be used for temperature and flow distributions prediction and identifying optimal number and locations of active tiles for hot spot mitigation in data centers.

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.

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.

Experimentally Validated Computational Fluid Dynamics Model for a Data Center With Cold Aisle Containment

2015 ◽  
Vol 137 (2) ◽  
Author(s):  
Sami A. Alkharabsheh ◽  
Bahgat G. Sammakia ◽  
Saurabh K. Shrivastava
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Flow Rate ◽  
Data Center ◽  
Flow Distribution ◽  
Temperature Measurements ◽  
Experimental Measurements ◽  
Air Conditioner ◽  
Cfd Model ◽  
Good Agreement

This paper presents the results of an experimentally validated computational fluid dynamics (CFD) model for a data center with fully implemented fan curves on both the servers and the computer room air conditioner (CRAC). Both open and contained cold aisle systems are considered in this study. This work is divided into sections for the baseline system (prior to installing containment) calibration and the fully contained cold aisle system calibration and leakage characterization. In the open system, the fan curve of the CRAC unit is extracted from the manufacturer data, while the fan curve of the load banks is obtained through experimental measurements. The experimental results are found to be in good agreement with the average model predictions. In the fully contained cold aisle system, a detailed containment CFD model is developed based on experimental measurements. The model is validated by comparing the flow rate through the perforated floor tiles and the rack inlet temperatures with the experimental measurements. The CFD results are found to be in good agreement with the experimental data with an average relative error between the measured and computed flow rate of approximately 6.7%. Temperature measurements are used to calibrate the sources of leakage in the containment and rack mounting rails. The temperature measurements and the CFD results agree well with an average difference of less than 1 °C. This study provides important modeling guidelines for data centers. In order to predict the performance of contained cold aisle systems flow distribution, it is crucial that physics based models of fan curves, server internal resistances, detailed rack models, and other design details are all accurate and experimentally verified.

In Situ Functional Monitoring of Aerosol Jet-Printed Electronic Devices Using a Combined Sparse Representation-Based Classification (SRC) Approach

2018 ◽  
Author(s):  
Roozbeh (Ross) Salary ◽  
Jack P. Lombardi ◽  
Darshana L. Weerawarne ◽  
M. Samie Tootooni ◽  
Prahalada K. Rao ◽  
...  
Keyword(s):  
Sparse Representation ◽  
Functional Properties ◽  
Process Parameters ◽  
Flow Rate ◽  
Gas Flow ◽  
Electronic Devices ◽  
In Situ Monitoring ◽  
Gas Flow Rate ◽  
Aerosol Jet Printing

The goal of this work is in situ monitoring of the functional properties of aerosol jet-printed electronic devices. In pursuit of this goal, the objective is to develop a multiple-input, single-output (MISO) machine learning model to estimate the device functional properties in a near real-time fashion as a function of process parameters as well as 2D/3D features of line morphology. The aim is to use the MISO model for in situ estimation and thus, monitoring of line/device resistance in aerosol jet printing (AJP) process. To realize this objective, silver nanoparticle structures are printed by varying three process parameters: (i) sheath gas flow rate (ShGFR), (ii) exhaust gas flow rate (EGFR), and (iii) print speed (PS). Subsequently, line morphology is captured in situ using a high-resolution charge-coupled device (CCD) camera, mounted coaxial to the nozzle. Besides, utilizing 2D/3D quantifiers (introduced in the authors’ previous publications), the line morphology is further quantified, and the extracted features (e.g., line width, overspray, cross-sectional area, etc.) are fed as inputs to a novel sparse representation-based classification (SRC) model. The four-point probe method is used for measurement of resistance, and definition of a priori classification labels. The outcome of this research paves the way for future control of device functional properties in AJP process.

Experimentally Validated Computational Fluid Dynamics Model for Data Center With Active Tiles

2017 ◽  
Author(s):  
Jayati D. Athavale ◽  
Yogendra Joshi ◽  
Minami Yoda
Keyword(s):  
Fluid Dynamics ◽  
Experimental Data ◽  
Computational Fluid Dynamics ◽  
Flow Rate ◽  
Data Center ◽  
Hot Spots ◽  
Cfd Model ◽  
Floor Tiles ◽  
Computational Fluid Dynamics Cfd ◽  
Plenum Pressure

This paper presents an experimentally validated room-level computational fluid dynamics (CFD) model for raised-floor data center configurations employing active tiles. Active tiles are perforated floor tiles with integrated fans, which increase the local volume flowrate by redistributing the cold air supplied by the computer room air conditioning (CRAC) unit to the under-floor plenum. In a previous study [1], experiments were conducted to explore the potential of active tiles for economically and efficiently eliminating hot spots in data center. Our results indicated that active tiles, as the actuators closest to the racks, can significantly and quickly impact the local distribution of cooling resources. They could therefore be used in an appropriate control framework to rapidly mitigate hot spots, and maintain local conditions in an energy-efficient manner. The numerical model of the data center room operates in an under-floor supply and ceiling return cooling configuration and consists of one cold aisle with 12 racks arranged on both sides and three CRAC units sited around the periphery of the room. The commercial computational fluid dynamics (CFD) software package Future Facilities 6SigmaDCX [2], which is specifically designed for data center simulation, is used to develop the model. First, a baseline model using only passive tiles was developed and experimental data were used to verify and calibrate plenum leakage for the room. Then a CFD model incorporating active tiles was developed for two configurations: (a) a single active tile and 9 passive tiles in the cold aisle; and (b) an aisle populated with 10 (i.e., all) active tiles. The active tiles are modeled as a combination of a grill, fan elements and flow blockages to closely mimic the actual active tile used in the experimental studies. The fan curve for the active tile fans is included in the model to account for changes in flow rate through the tiles in response to changes in plenum pressure. The model with active tiles is validated by comparing the flow rate through the floor tiles, relative plenum pressure and rack inlet temperatures for selected racks with the experimental measurements. The predictions from the CFD model are found to be in good agreement with the experimental data, with an average discrepancy between the measured and computed values for total flow rate and rack inlet temperature less than 4% and 1.7 °C, respectively. These validated models were then used to simulate steady state and transient scenarios following cooling failure. This physics-based and experimentally validated room-level model can be used to predict temperature and flow distributions in a data center using active tiles. These predictions can then be used to identify the optimal number and locations of active tiles to mitigate hot spots, without adversely affecting other parts of the data center.

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