Implementation of CHyQMOM in OpenFOAM for the simulation of non-equilibrium gas-particle flows under one-way and two-way coupling

The modeling of dilute gas-particle flows is challenging due to particle-trajectory crossing (PTC). Lagrangian particle tracking can be used, but requires a large number of parcels resulting in high computational costs. A less costly method is the Eulerian number density function (NDF) approach, based on the Boltzmann equation, often solved in terms of lower-order moments of the NDF. In this context the conditional hyperbolic quadrature method of moments (CHyQMOM) was developed and is here implemented for the first time in the OpenFOAM-7, together with high-order advection schemes and a new operator splitting procedure. The resulting solver is used to simulate different test cases: phase segregation problems, collision-less and weakly-collisional PTC flows, asymmetric and symmetric Taylor-Green vortex flow and a dilute gas-particle riser. Results, validated against analytical solutions and predictions obtained with Lagrangian particle tracking, show that the implemented CHyQMOM can be used to handle highly non-equilibrium flows. (c) 2021 Elsevier B.V. All rights reserved

Going Public and the Enrichment of a Supportive Network

Past research on initial public offerings suggests that the reputation of a company positively affects the success of the offering. Success is usually measured in financial terms as if the essence of the operation lay only in the short-term inflow of money. In this paper, we investigate important albeit often neglected implications of going public by combining evidence from a series of preliminary case studies taken from the results of a survey of 57 Italian initial public offerings. Evidence from our research suggests that, besides providing an important inflow of capital, going public may actually improve the reputational and social capital of a company, by increasing its visibility, prestige and perceived trustworthiness. Therefore, going public may be an important way to support entrepreneurial activity, as it may expand and reinforce the network of relationships that offer access to external resources, complementary skills and investment opportunities

QEEFoam: A Quasi-Eulerian-Eulerian model for polydisperse turbulent gas-liquid flows. Implementation in OpenFOAM, verification and validation

In this paper we present a new multiphase computational model for polydisperse turbulent gas-liquid flows. In this model the gas phase is transported by a single convection equation and the effect of turbulent dispersion is addressed by including a diffusion term. In order to close the system of equations, the gas phase velocity is calculated by employing the slip velocity concept or by solving an ODE. This procedure shares similarity with the Euler-Lagrange (E-L) method, in which the gas velocity is updated by bubble Lagrangian tracking, and with the Euler-Euler (E-E) method, and for this reason it is called the Quasi-Eulerian-Eulerian (Q-E-E) method. In order to account for polydispersity one single transport equation is added to describe the effects of bubble breakage and coalescence on the mean bubble size. The novel Q-E-E method was implemented in the open-source code OpenFOAM-7 and was used to simulate turbulent gas-liquid flows with three different geometries operating under different conditions. The predictions for the dynamical vortex structures, local phase fraction, global gas holdup, mean bubble size and vertical/horizontal liquid velocities were verified against the solution provided by the E-L solver or against published experimental data. Good agreement was found and with extremely small computational costs

MARTINI coarse-grained model for poly-ε-caprolactone in acetone-water mixtures

In this work we present the development of a MARTINI-type coarse-graining (CG) model for poly-ε-caprolactone (PCL) dissolved in a solvent binary mixture of acetone and water. A thermodynamic/conformational procedure is adopted to build up the CG model of the system, starting from the standard MARTINI force field. The single CG bead is parametrized upon solvation free energy calculations, whereas the conformation of the whole polymer chain is optimized using the radius of gyration values calculated at different chain lengths. The model is then able to reproduce the correct thermodynamics of the system, as well as the conformation of single PCL chains, especially in pure water and acetone. The results obtained here are then used to simulate the interactions between multiple longer PCL chains in solution. The model developed here can be used in the future to achieve deeper insight into the dynamics of the polymer self-assembly

Computational Fluid Dynamics data for improving freeze-dryers design

Computational Fluid Dynamics (CFD) can be used to simulate different parts of an industrial freeze-drying equipment and to properly design them; in particular data concerning the freeze-dryer chamber and the duct connecting the chamber with the condenser, with the valves and vanes eventually present are given here, and can be used to understand the behavior of the apparatus allowing an improved design. Pilot and large scale freeze-drying chambers have been considered; data of a detailed simulation of a complete pilot scale apparatus, including duct and condenser are included. Data on conductance of an empty duct with different L/D ratio, on disk valves with different geometry, and on mushroom valve are presented. Velocity, pressure, temperature and composition fields are reported on selected planes for chambers and valves. Results of dynamic simulations are also presented, to evaluate possible performance of monitoring device in the chamber. Some further data, with detailed interpretation and discussion of the presented data can be found in the related research article by Barresi et al. [1] and Marchisio et al. [2] [1] A.A. Barresi, V. Rasetto, D.L. Marchisio, Use of Computational Fluid Dynamics for improving freeze-dryers design and understanding. Part 1: modelling the lyophilisation chamber, Eur. J. Pharm. Biopharm. 129 (2018) 30–44.http://dx.doi.org/10.1016/j.ejpb.2018.05.008. [2] D.L. Marchisio, M. Galan, A.A. Barresi, Use of Computational Fluid Dynamics for improving freeze-dryers design and understanding. Part 2: condenser duct and valve modelling, Eur. J. Pharm. Biopharm. 129 (2018) 45–57.http://dx.doi.org/10.1016/j.ejpb.2018.05.003

From Computational Fluid Dynamics to Structure Interpretation via Neural Networks: An Application to Flow and Transport in Porous Media

The modeling of flow and transport in porous media is of the utmost importance in many chemical engineering applications, including catalytic reactors, batteries, and CO2 storage. The aim of this study is to test the use of fully connected (FCNN) and convolutional neural networks (CNN) for the prediction of crucial properties in porous media systems: The permeability and the filtration rate. The data-driven models are trained on a dataset of computational fluid dynamics (CFD) simulations. To this end, the porous media geometries are created in silico by a discrete element method, and a rigorous setup of the CFD simulations is presented. The models trained have as input both geometrical and operating conditions features so that they could find application in multiscale modeling, optimization problems, and in-line control. The average error on the prediction of the permeability is lower than 2.5%, and that on the prediction of the filtration rate is lower than 5% in all the neural networks models. These results are achieved with at least a dataset of ~ 100 CFD simulations

Use of Computational Fluid Dynamics for improving freeze-dryers design and understanding. Part 1: Modelling the lyophilisation chamber

This manuscript shows how computational models, mainly based on Computational Fluid Dynamics (CFD), can be used to simulate different parts of an industrial freeze-drying equipment and to properly design them; in particular, the freeze-dryer chamber and the duct connecting the chamber with the condenser, with the valves and vanes eventually present are analysed in this work. In Part 1, it will be shown how CFD can be employed to improve specific designs, to perform geometry optimization, to evaluate different design choices and how it is useful to evaluate the effect on product drying and batch variance. Such an approach allows an in-depth process understanding and assessment of the critical aspects of lyophilisation. This can be done by running either steady-state or transient simulations with imposed sublimation rates or with multi-scale approaches. This methodology will be demonstrated on freeze-drying equipment of different sizes, investigating the influence of the equipment geometry and shelf inter-distance. The effect of valve type (butterfly and mushroom) and shape on duct conductance and critical flow conditions will be instead investigated in Part 2

A multienvironment conditional probability density function model for turbulent reacting flows

The multienvironment conditional probability density function (MECPDF) model was first proposed by Fox [Computational Models for Turbulent Reacting Flows (Cambridge University Press, Cambridge, 2003)] as a simple extension of multienvironment probability density function models for turbulent reacting flows. Like the conditional moment closure (CMC) and the laminar flamelet model (LFM), the MECPDF model describes the reacting scalars conditioned on the value of the mixture fraction. However, unlike CMC and LFM, the new model provides a consistent description of conditional fluctuations in both the scalar dissipation rate and the reacting scalars, and hence can be used to model partial extinction and reignition in homogeneous turbulent reacting flows. In this work, a general derivation of the MECPDF model is presented for a single reaction-progress variable using the direct quadrature method of moments. Extensions of the model to multiple reaction-progress variables and conditioning on the mixture-fraction vector are also discussed. After deriving the model, the closure assumptions are validated using direct simulations for pure diffusion of two randomly distributed, initially correlated scalar fields. Two homogeneous applications are then considered: nonreactive mixing starting from nontrivial initial conditions, and reactive mixing with partial extinction and reignition