Добірка наукової літератури з теми "Population Balance Equation. Soft Matter"

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Статті в журналах з теми "Population Balance Equation. Soft Matter"

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Karimi, Mohsen, Hermes Droghetti, and Daniele L. Marchisio. "Multiscale Modeling of Expanding Polyurethane Foams via Computational Fluid Dynamics and Population Balance Equation." Macromolecular Symposia 360, no. 1 (February 2016): 108–22. http://dx.doi.org/10.1002/masy.201500108.

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Karimi, Mohsen, and Daniele L. Marchisio. "A Baseline Model for the Simulation of Polyurethane Foams via the Population Balance Equation." Macromolecular Theory and Simulations 24, no. 4 (May 19, 2015): 291–300. http://dx.doi.org/10.1002/mats.201500014.

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3

Maggioni, Giovanni Maria, and Marco Mazzotti. "A Stochastic Population Balance Equation Model for Nucleation and Growth of Crystals with Multiple Polymorphs." Crystal Growth & Design 19, no. 8 (July 9, 2019): 4698–709. http://dx.doi.org/10.1021/acs.cgd.9b00577.

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Ishaq, Muhammad, and Zhi-Min Chen. "Amplitude reflections and interaction solutions of linear and nonlinear acoustic waves with hard and soft boundaries." Physics of Fluids 34, no. 11 (November 2022): 111906. http://dx.doi.org/10.1063/5.0126558.

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Анотація:
In this study, the propagation of a fundamental plane mode in a bifurcated waveguide structure with soft–hard boundaries is analyzed by using the Helmholtz equation. The explicit solution is given to this bifurcated spaced waveguide problem by means of matching the potential across the boundary of continuity. Amplitudes of the reflected field in all those regions have been evaluated, and the energy balance has been derived. We have observed the reflection of the acoustic wave against the wavenumber and shown its variation with the duct width. Convergence of the problem has been shown graphically. In our analysis, we notice that the reflected amplitude decreases as the duct spacing increases; as a result, the acoustic energy will increase as the duct spacing increases. It is expected that our analysis could be helpful to give better understanding of wave reflection in an exhaust duct system. We then reduce the linear acoustic wave equation to the Kadomtsev–Petviashvili (KP) equation. Multiple-periodic wave interaction solutions of the KP nonlinear wave equation are investigated, and the energy transfer mechanism between the primary and higher harmonics is explained, which, to the best of our knowledge, is overlooked.
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Di Veroli, G. Y., and S. Rigopoulos. "Modeling of aerosol formation in a turbulent jet with the transported population balance equation-probability density function approach." Physics of Fluids 23, no. 4 (April 2011): 043305. http://dx.doi.org/10.1063/1.3576913.

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Vetter, Thomas. "Designing Isothermal Batch Deracemization Processes with Optimal Productivity: 1. Parametric Analysis Using a Population Balance Equation Model." Crystal Growth & Design 20, no. 7 (April 7, 2020): 4293–306. http://dx.doi.org/10.1021/acs.cgd.9b01581.

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Vetter, Thomas, Martin Iggland, David R. Ochsenbein, Flurin S. Hänseler, and Marco Mazzotti. "Modeling Nucleation, Growth, and Ostwald Ripening in Crystallization Processes: A Comparison between Population Balance and Kinetic Rate Equation." Crystal Growth & Design 13, no. 11 (October 2013): 4890–905. http://dx.doi.org/10.1021/cg4010714.

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Zerradi, Hicham, Soufiya Mizani, Hamid Loulijat, Aouatif Dezairi, and Said Ouaskit. "Population balance equation model to predict the effects of aggregation kinetics on the thermal conductivity of nanofluids." Journal of Molecular Liquids 218 (June 2016): 373–83. http://dx.doi.org/10.1016/j.molliq.2016.02.064.

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Yamamoto, Takehiro. "Modeling of Floc Forming Suspensions Coupling the Population Balance Equation for Floc Aggregation-Breakage and the White-Metzner Model." Nihon Reoroji Gakkaishi 48, no. 2 (April 15, 2020): 121–28. http://dx.doi.org/10.1678/rheology.48.121.

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Fu, Xiaoyan, Dejiang Zhang, Shijie Xu, Bo Yu, Keke Zhang, Sohrab Rohani, and Junbo Gong. "Effect of Mixing on the Particle Size Distribution of Paracetamol Continuous Cooling Crystallization Products Using a Computational Fluid Dynamics–Population Balance Equation Simulation." Crystal Growth & Design 18, no. 5 (April 16, 2018): 2851–63. http://dx.doi.org/10.1021/acs.cgd.7b01671.

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Тези доповідей конференцій з теми "Population Balance Equation. Soft Matter"

1

Zucca, Alessandro, Daniele L. Marchisio, Antonello A. Barresi, and Giancarlo Baldi. "Mathematical Modelling of Particle Formation in Combustion Processes." In ASME 8th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2006. http://dx.doi.org/10.1115/esda2006-95407.

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In recent years the problem of studying particle formation and evolution in turbulent flames has become increasingly important, for both environmental and technological reasons. Information on particle size and morphology is often required, since these characteristics largely influence the effects of particulate matter on human health and global climate in the case of soot. A mathematical model able to describe the evolution of these particulate systems must solve the population balance equation within a Computational Fluid Dynamics (CFD) code that predicts the temperature, composition and velocity fields of the flame. In this work, the recently proposed Direct Quadrature Method of Moments (DQMOM) is applied to the study of soot formation in turbulent non-premixed flames. The model takes into account nucleation, molecular growth, oxidation and aggregation of soot particles; simplified kinetic rates are employed, while velocity and scalar fields are computed by simulations based on the solution of the Reynolds Averaged Navier Stokes (RANS) equations. Different population balance formulations are implemented and compared and results show that DQMOM is a suitable modelling tool; comparison of predictions with experimental data shows that the model accurately describes the morphological properties of soot aggregates.
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