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Alina A. Alexeenko

Publications and source records attributed to Alina A. Alexeenko.

5 recordsLinked to original sources

Direct Modeling of Pore Size Evolution and Microcollapse in Lyophilization by Population Balance

In the primary drying step of pharmaceutical freeze drying, it is well known that amorphous excipients are prone to "microcollapse" as they approach their glass transition temperature. Existing modeling approaches for this phenomenon generally entail either avoidance of this regime or an experimentally burdensome empirical assessment of the resulting drop in resistance to mass transfer. In this work, we approach the phenomenon head-on by developing a population balance model for the pore size distribution of a freeze-dried cake during microcollapse and relating the pore size to mass transfer resistance. By treating the population balance with the method of moments and an interpolative closure, we keep the model's computational burden on par with the literature-standard model for primary drying. For a literature example when mass transfer resistance clearly varies as a function of product temperature during drying, we fit the population balance model to cases with high and low product temperature and show that it can then simulate intermediate cases with equal accuracy. The validity of the expression for mass transfer resistance is demonstrated with another literature data set, where pore size distributions were measured after the fact for a formulation without microcollapse; only a single parameter from this model needs to be fit to those cases to yield predictive accuracy in product temperature on par with post-hoc empirical assessment. Finally, a sophisticated multi-experiment fit for one formulation across a range of conditions yields quantitative agreement in product temperatures, suggesting that the rate constant for microcollapse behavior may be a material parameter and independent of the precise porous geometry.

physics.flu-dyn↗

Quantification of thermally-driven flows in microsystems using Boltzmann equation in deterministic and stochastic contexts

When the flow is sufficiently rarefied, a temperature gradient, for example, between two walls separated by a few mean free paths, induces a gas flow---an observation attributed to the thermo-stress convection effects at microscale. The dynamics of the overall thermo-stress convection process is governed by the Boltzmann equation---an integro-differential equation describing the evolution of the molecular distribution function in six-dimensional phase space---which models dilute gas behavior at the molecular level to accurately describe a wide range of flow phenomena. Approaches for solving the full Boltzmann equation with general inter-molecular interactions rely on two perspectives: one stochastic in nature often delegated to the direct simulation Monte Carlo (DSMC) method; and the others deterministic by virtue. Among the deterministic approaches, the discontinuous Galerkin fast spectral (DGFS) method has been recently introduced for solving the full Boltzmann equation with general collision kernels, including the variable hard/soft sphere models---necessary for simulating flows involving diffusive transport. In this work, the deterministic DGFS method; Bhatnagar-Gross-Krook (BGK), Ellipsoidal statistical BGK, and Shakhov kinetic models; and the widely-used stochastic DSMC method, are utilized to assess the thermo-stress convection process in MIKRA---Micro In-Plane Knudsen Radiometric Actuator---a microscale compact low-power pressure sensor utilizing the Knudsen forces. BGK model under-predicts the heat-flux, shear-stress, and flow speed; S-model over-predicts; whereas ESBGK comes close to the DSMC results. On the other hand, both the statistical/DSMC and deterministic/DGFS methods, segregated in perspectives, yet, yield inextricable results.

physics.comp-ph↗

A discontinuous Galerkin fast spectral method for multi-species full Boltzmann on streaming multi-processors

When the molecules of a gaseous system are far apart, say in microscale gas flows where the surface to volume ratio is high and hence the surface forces dominant, the molecule-surface interactions lead to the formation of a local thermodynamically non-equilibrium region extending few mean free paths from the surface. The dynamics of such systems is accurately described by Boltzmann equation. However, the multi-dimensional nature of Boltzmann equation presents a huge computational challenge. With the recent mathematical developments and the advent of petascale, the dynamics of full Boltzmann equation is now tractable. We present an implementation of the recently introduced multi-species discontinuous Galerkin fast spectral (DGFS) method for solving full Boltzmann on streaming multi-processors. The present implementation solves the inhomogeneous Boltzmann equation in span of few minutes, making it at least two order-of-magnitude faster than the present state-of-art stochastic method---direct simulation Monte Carlo---widely used for solving Boltzmann equation. Various performance metrics, such as weak/strong scaling have been presented. A parallel efficiency of 0.96--0.99 is demonstrated on 36 Nvidia Tesla-P100 GPUs.

physics.comp-ph↗

A discontinuous Galerkin fast spectral method for the multi-species Boltzmann equation

We introduce a fast Fourier spectral method for the multi-species Boltzmann collision operator. The method retains the riveting properties of the single-species fast spectral method (Gamba et al. SIAM J. Sci. Comput., 39 pp. B658--B674 2017) including: (a) spectral accuracy, (b) reduced computational complexity compared to direct spectral method, (c) reduced memory requirement in the precomputation, and (d) applicability to general collision kernels. The fast collision algorithm is then coupled with discontinuous Galerkin discretization in the physical space (Jaiswal et al. J. Comp. Phys., 378 pp. 178--208 2019) to result in a highly accurate deterministic method (DGFS) for the full Boltzmann equation of gas mixtures. A series of numerical tests is performed to illustrate the efficiency and accuracy of the proposed method. Various benchmarks highlighting different collision kernels, different mass ratios, momentum transfer, heat transfer, and in particular the diffusive transport have been studied. The results are directly compared with the direct simulation Monte Carlo (DSMC) method.

physics.comp-ph↗

A Discontinuous Galerkin Fast Spectral Method for the Full Boltzmann Equation with General Collision Kernels

The Boltzmann equation, an integro-differential equation for the molecular distribution function in the physical and velocity phase space, governs the fluid flow behavior at a wide range of physical conditions, including compressible, turbulent, as well as flows involving further physics such as non-equilibrium internal energy exchange and chemical reactions. Despite its wide applicability, deterministic solution of the Boltzmann equation presents a huge computational challenge, and often the collision operator is simplified for practical reasons. In this work, we introduce a highly accurate deterministic method for the full Boltzmann equation which couples the Runge-Kutta discontinuous Galerkin (RKDG) discretization in time and physical space (Su et al., Comp. Fluids, 109 pp. 123-136, 2015) and the recently developed fast Fourier spectral method in velocity space (Gamba et al., SIAM J. Sci. Comput., 39 pp.~B658--B674, 2017). The novelty of this approach encompasses three aspects: first, the fast spectral method for the collision operator applies to general collision kernels with little or no practical limitations, and in order to adapt to the spatial discretization, we propose here a singular-value-decomposition based algorithm to further reduce the cost in evaluating the collision term; second, the DG formulation employed has high order of accuracy at element-level, and has shown to be more efficient than the finite volume method; thirdly, the element-local compact nature of DG as well as our collision algorithm is amenable to effective parallelization on massively parallel architectures. The solver has been verified against analytical Bobylev-Krook-Wu solution. Further, the standard benchmark test cases of rarefied Fourier heat transfer, Couette flow, oscillatory Couette flow, normal shock wave, lid-driven cavity flow, and thermally driven cavity flow have been studied.

physics.comp-ph↗