Quantifying the dynamic spreading of a molten sand droplet using multiphase mesoscopic simulations

Koneru, Rahul; Flatau, Alison B.; Li, Zhen; Bravo, Luis; Murugan, Muthuvel; Ghoshal, Anindya; Karniadakis, George

doi:10.1103/physrevfluids.7.103602

Cited by 5 publications

(5 citation statements)

References 51 publications

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“…Inspired by the experimental results of Eddi et al (2013), the simulations of Koneru et al (2022) and the current simulations, we propose a simple sigmoid type dependence for α:…”

Section: Simulation Resultsmentioning

confidence: 98%

“…To simulate molten CMAS, the parameter mapping of Koneru et al (2022) was used together with the open-source code LAMMPS (Thompson et al 2022). In brief, the properties of molten CMAS at approximately 1260 • C, based on the experimental data from Naraparaju et al (2019), Bansal & Choi (2014) and Wiesner et al (2016), were used.…”

Section: Simulation Parameters and System Set-upmentioning

confidence: 99%

“…To simulate molten CMAS, the parameter mapping of Koneru et al. (2022) was used together with the open-source code LAMMPS (Thompson et al. 2022).…”

Section: Multiphase Many-body Dissipative Particle Dynamics Simulationsmentioning

confidence: 99%

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Characterization of partial wetting by CMAS droplets using multiphase many-body dissipative particle dynamics and data-driven discovery based on PINNs

Kiyani,

Kooshkbaghi,

Shukla

et al. 2024

J. Fluid Mech.

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The molten sand that is a mixture of calcia, magnesia, alumina and silicate, known as CMAS, is characterized by its high viscosity, density and surface tension. The unique properties of CMAS make it a challenging material to deal with in high-temperature applications, requiring innovative solutions and materials to prevent its buildup and damage to critical equipment. Here, we use multiphase many-body dissipative particle dynamics simulations to study the wetting dynamics of highly viscous molten CMAS droplets. The simulations are performed in three dimensions, with varying initial droplet sizes and equilibrium contact angles. We propose a parametric ordinary differential equation (ODE) that captures the spreading radius behaviour of the CMAS droplets. The ODE parameters are then identified based on the physics-informed neural network (PINN) framework. Subsequently, the closed-form dependency of parameter values found by the PINN on the initial radii and contact angles are given using symbolic regression. Finally, we employ Bayesian PINNs (B-PINNs) to assess and quantify the uncertainty associated with the discovered parameters. In brief, this study provides insight into spreading dynamics of CMAS droplets by fusing simple parametric ODE modelling and state-of-the-art machine-learning techniques.

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“…Inspired by the experimental results of Eddi et al (2013), the simulations of Koneru et al (2022) and the current simulations, we propose a simple sigmoid type dependence for α:…”

Section: Simulation Resultsmentioning

confidence: 98%

Section: Simulation Parameters and System Set-upmentioning

confidence: 99%

See 1 more Smart Citation

Characterization of partial wetting by CMAS droplets using multiphase many-body dissipative particle dynamics and data-driven discovery based on PINNs

Kiyani,

Kooshkbaghi,

Shukla

et al. 2024

J. Fluid Mech.

Self Cite

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“…Designing experimental configurations for achieving the seamless and uninterrupted 3D printing of diverse bioinks can prove to be both costly and time intensive. Since viscosity, surface forces between bioink, printhead, and PDMS and stage speed, all contribute towards high print fidelity, we developed a multiphase many-body dissipative particle dynamics (mDPD) model [18,19] to simulate the dynamic process of droplet bioprinting with a system setup shown in Figure 2A(i) .…”

Section: Resultsmentioning

confidence: 99%

Droplet bioprinting of acellular and cell-laden structures at high-resolutions

Kunwar,

Aryal,

Poudel

et al. 2023

Preprint

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Advances in Digital Light Processing (DLP) based (bio) printers have made printing of intricate structures at high resolution possible using a wide range of photosensitive bioinks. A typical setup of a DLP bioprinter includes a vat or reservoir filled with liquid bioink, which presents challenges in terms of cost associated with bioink synthesis, high waste, and gravity-induced cell settling, contaminations, or variation in bioink viscosity during the printing process. Here, we report a vat-free, low-volume, waste-free droplet bioprinting method capable of rapidly printing 3D soft structures at high resolution using model bioinks. A multiphase many-body dissipative particle dynamics (mDPD) model was developed to simulate the dynamic process of droplet-based DLP printing and elucidate the roles of surface wettability and bioink viscosity. Process variables such as light intensity, photo-initiator concentration, and bioink formulations were optimized to print 3D soft structures (∼0.4 to 3 kPa) with an XY resolution of 38 ± 1.5 μm and Z resolution of 237±5.4 μm. To demonstrate its versatility, droplet bioprinting was used to print a range of acellular 3D structures such as a lattice cube, a Mayan pyramid, a heart-shaped structure, and a microfluidic chip with endothelialized channels. Droplet bioprinting, performed using model C3H/10T1/2 cells, exhibited high viability (90%) and cell spreading. Additionally, microfluidic devices with internal channel network lined with endothelial cells showed robust monolayer formation while osteoblast-laden constructs showed mineral deposition upon osteogenic induction. Overall, droplet bioprinting could be a low-cost, no-waste, easy-to-use, method to make customized bioprinted constructs for a range of biomedical applications.

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“…Designing experimental configurations for achieving the seamless and uninterrupted 3D printing of diverse bioinks can prove to be both costly and time intensive. Since viscosity, surface forces between bioink, printhead, and PDMS and stage speed, all contribute towards high print fidelity, we developed a multiphase many-body dissipative particle dynamics (mDPD) model [38,39] to simulate the dynamic process of droplet bioprinting with a system setup shown in figure 2(A(i)). Here, the bioink droplet of 50 µl with a viscosity of 4 mPa•s is used with printhead diameter (D) = 6.9 mm.…”

Section: Simulation Studies Of the Droplet Printing Processmentioning

confidence: 99%

Droplet bioprinting of acellular and cell-laden structures at high-resolutions

Kunwar,

Aryal,

Poudel

et al. 2024

Biofabrication

View full text Add to dashboard Cite

Advances in Digital Light Processing (DLP) based (bio) printers have made printing of intricate structures at high resolution possible using a wide range of photosensitive bioinks. A typical setup of a DLP bioprinter includes a vat or reservoir filled with liquid bioink, which presents challenges in terms of cost associated with bioink synthesis, high waste, and gravity-induced cell settling, contaminations, or variation in bioink viscosity during the printing process. Here, we report a vat-free, low-volume, waste-free droplet bioprinting method capable of rapidly printing 3D soft structures at high resolution using model bioinks. A multiphase many-body dissipative particle dynamics (mDPD) model was developed to simulate the dynamic process of droplet-based DLP printing and elucidate the roles of surface wettability and bioink viscosity. Process variables such as light intensity, photo-initiator concentration, and bioink formulations were optimized to print 3D soft structures (~0.4 to 3 kPa) with an XY resolution of 38 ± 1.5 μm and Z resolution of 237±5.4 µm. To demonstrate its versatility, droplet bioprinting was used to print a range of acellular 3D structures such as a lattice cube, a Mayan pyramid, a heart-shaped structure, and a microfluidic chip with endothelialized channels. Droplet bioprinting, performed using model C3H/10T1/2 cells, exhibited high viability (90%) and cell spreading. Additionally, microfluidic devices with internal channel network lined with endothelial cells showed robust monolayer formation while osteoblast-laden constructs showed mineral deposition upon osteogenic induction. Overall, droplet bioprinting could be a low-cost, no-waste, easy-to-use, method to make customized bioprinted constructs for a range of biomedical applications.

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Quantifying the dynamic spreading of a molten sand droplet using multiphase mesoscopic simulations

Cited by 5 publications

References 51 publications

Characterization of partial wetting by CMAS droplets using multiphase many-body dissipative particle dynamics and data-driven discovery based on PINNs

Characterization of partial wetting by CMAS droplets using multiphase many-body dissipative particle dynamics and data-driven discovery based on PINNs

Droplet bioprinting of acellular and cell-laden structures at high-resolutions

Droplet bioprinting of acellular and cell-laden structures at high-resolutions

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