Modeling multiphase fluid flow, mass transfer, and chemical reactions in bioreactors using large-eddy simulation
Engineering in Life Sciences (November 2022)
Navraj Hanspal, Brian DeVincentis, John A. Thomas
Understanding scale-up mechanisms is critical for reducing performance losses in industrial applications. In this article, M-Star works with Corteva Agriscience to present a transient large eddy simulation (LES) modeling approach for simulating the interlinked physics describing free surface hydrodynamics, multiphase mixing, reaction kinetics, and mass transport in bioreactor systems.
M-Star unites with Corteva Agriscience and SPX FLOW to evaluate predictions from the parcel model compared to measured data and predictions from full-fidelity discrete bubble models. When appropriate, the parcel-based model presents order-of-magnitude reductions in computational runtime with minimal loss in physical fidelity.
Computational prediction of blend time in a large-scale viral inactivation process for monoclonal antibodies biomanufacturing
Biotechnology and Bioengineering (October 2022)
Chadakarn Sirasitthichoke, Duc Hoang, Poonam Phalak, Piero M. Armenante, Barak I. Barnoon, Ishaan Shandil
M-Star, together with Bristol Myers Squibb, New Jersey Institute of Technology, and University of Massachusetts Lowell, used a CFD model based on the Lattice Boltzmann method (LBM) to predict the blend time to homogenize a Triton X-100 solution added during a typical full-scale commercial VI process. The results obtained in this study were used to support actual production at the biomanufacturing site.
Blending and Cavern Formation within Non-Newtonian Fluids in Stirred Tanks: Application to Nuclear Waste Fluid Processing
Chemical Engineering Science (October 2022)
Sean Noble, Michael R. Poirier, John A. Thomas
M-Star collaborates with the Savannah River National Laboratory to predict the time-accurate fluid flow and mixing properties of non-Newtonian fluids. Across the range of fluids and systems, the simulations required no reparameterization or retuning between scenarios. This generality allowed them to model a nuclear waste processing unit operation.
Modeling gas release from a Bingham plastic slurry and deconvoluting measured data
Chemical Engineering Science (June 2022)
Michael R. Poirier, John A. Thomas, John M. Pareizs
M-Star works with the US Department of Energy performing Lattice Boltzmann computational fluid dynamics simulations to evaluate the impact of yield stress, impeller speed, and bubble size on the release of retained gas from a Bingham plastic slurry.
Modeling free surface gas transfer in agitated lab-scale bioreactors
Chemical Engineering Communications (June 2022)
John A. Thomas, Anisur Rahman, Johannes Wutz, Ying Wang, Brian DeVincentis, Brendan McGuire, Lei Cao
In this study, AbbVie works with M-Star to find that the free surface mass transfer rate in lab-scale systems is consistent with empirical relationships regardless of the mechanical action driving motion. Also, the computational approach is shown to be practical within the context of industrial analysis and design timescales.
An analysis of organism lifelines in an industrial bioreactor using Lattice-Boltzmann CFD
Engineering in Life Sciences (March 2022)
In this work by the Delft University of Technology, the performance of LB-LES in resolving substrate gradients in large-scale bioreactors is explored, combined with the inclusion of a Lagrangian biotic phase to provide the microbial perspective.
Predicting the diameters of droplets produced in turbulent liquid–liquid dispersion
AiCHE Journal (February 2022)
John A. Thomas, Brian DeVincentis, Johannes Wutz, Francesco Ricci
The droplet size distribution in liquid–liquid dispersions is a complex convolution of impeller speed, impeller type, fluid properties, and flow conditions. In this work with Boehringer Ingelheim, we present three a priori modeling approaches for predicting the droplet diameter distributions as a function of system operating conditions.
Computational prediction of the just-suspended speed, Njs, in stirred vessels using the Lattice Boltzmann method (LBM) coupled with a novel mathematical approach
Chemical Engineering Science (January 2022)
Chadakarn Sirasitthichoke, Baran Teoman, John Thomas, Piero M. Armenante
Determining the minimum agitation speed to achieve suspension of solids and liquids in a stirred vessel is of significant importance in industrial processes. In this article published jointly with M-Star and New Jersey Institute of Technology, the just-suspended speed is computationally predicted for a stirred, fully baffled vessel provided with different axial or radial impellers using M-Star CFD, coupled with a novel mathematical method.
Modeling Mass Transfer in Stirred Microbioreactors
Chemical Engineering Science (2022)
Hooman Farsani, Johannes Wutz, Brian DeVincentis, John A Thomas, Seyed Pouria Motevalian
Microbioreactors play a pivotal role in making biologic medicines. In fact, 10 of the top 15 selling drugs worldwide were made in a bioreactor. In this paper, M-Star and Pfizer present a generalized framework for modeling mass transfer in two-stage, stirred tank bioreactors to aid the scale-up process.
Validation of Novel Lattice Boltzmann Large Eddy Simulations (LB LES) for Equipment Characterization in Biopharma
Maike Kuschel, Jürgen Fitschen, Marko Hoffmann, Alexandra von Kameke, Michael Schlüter, Thomas Wucherpfennig
In this study, transient LB LES were applied to simulate a 3 L bioreactor system. The results were compared to novel 4D particle tracking (4D PTV) experiments, which resolve the motion of thousands of passive tracer particles on their journey through the bioreactor.
A CFD Digital Twin to Understand Miscible Fluid Blending
AAPS PharmSciTech (2021)
John Thomas, Kushal Sinha, Gayathri Shivkumar, Lei Cao, Marina Funck, Sherwin Shang, Nandkishor K. Nere
The mixing of stratified miscible fluids with widely different material properties is a common step in biopharmaceutical manufacturing processes. Differences between the fluid densities and viscosities, however, can lead to order-of-magnitude increase in blend times relative to the blending of single-fluid systems. In this work, M-Star and AbbVie build accelerated digital twins of a physical mixing tank to predict real-time fluid mechanics with a fidelity that rivals experimental data.
A Mechanistic Approach for Predicting Mass Transfer in Bioreactors
Chemical Engineering Science (2021)
John A. Thomas, Xiaoming Liu, Brian DeVincentis, Helen Hua, Grace Yao, Michael C. Borys, Kathryn Aron, Girish Pendse
In this work, M-Star pairs with Bristol Myers Squibb to propose, implement, and validate a mechanistic transport model for predicting oxygen transfer rates within stirred tank bioreactors. To begin, we describe the relevant conservation laws and key principles from turbulence theory that govern mass transfer.
Novel Evaluation Method to Determine the Local Mixing Time Distribution in Stirred Tank Reactors
Chemical Engineering Science: X (2021)
J. Fitschen, S. Hofmann, J. Wutz, A.v. Kameke, M. Hoffmann, T. Wucherpfennig, M. Schlüter
A novel image analysis will be presented in this study for the detailed characterization of mixing processes by taking into account the history of mixing. The method is based on the experimental determination of the local mixing time distribution by using a multi-color change caused by a pH-change in a bromothymol blue solution.
Time Scales and Turbulent Spectra above the Base of Stirred Vessels from Large Eddy Simulations
Flow, Turbulence and Combustion (2020)
Jason J. Giacomelli, Harry E. A. Van den Akker
Single-phase Large Eddy Simulations (LESs) have been conducted with M-Star CFD software to compute spectra and time scales of the turbulent flow field at positions above the base of a stirred tank as these time scales may be important to the application of solids suspension.
A Spectral Approach of Suspending Solid Particles in a Turbulent Stirred Vessel
Transport Phenomena and Fluid Mechanics (2020)
Jason J. Giacomelli, Harry E. A. Van den Akker
The 2015 Grenville-Mak-Brown (GMB) correlation for predicting the just suspended condition assumes that the length scale of the suspending eddy is equivalent to the particle diameter. This article investigates the role of the time scale of the relevant eddies with respect to the particle response time.