The Industrial importance of mixing can hardly
be exaggerated. Reactive flow processes are essential to the manufacture
of an immense variety of industrial products worth hundreds of billions
of dollars per year. Chemical, petrochemical, and pharmaceutical processes
usually require bringing reactants into close contact by imposing a mixing
flow. For fast reactions or viscous fluids, mixing is often slow compared
to the rate of reaction, and several important effects are frequently observed:
desired reactions are slowed and even halted before reaching completion,
undesired reactions are enhanced, and product selectivity is decreased.
Poor yield and reduced selectivity due to inefficient mixing directly results
in excessive production of waste requiring disposal, rework, or unproductive
downstream processing, greater separation costs, greater use of (often
toxic) solvents, and widespread damage to the environment. Hence, better
designed and controlled mixing processes could lead to significant pollution
prevention. However, reactive mixing in realistic flow systems is poorly
understood. Even the simplest case, mixing of soluble fluids, involves
four non-linearly coupled processes: convection, stretching, diffusion,
and chemical reaction. These processes typically generate partially mixed
structures that exhibit strong variability in local composition. Chemical
reactions taking place in such an inhomogeneous environment often exhibit
spatially dependent rates. Given this level of complexity, it is not surprising
that reactive mixing processes have so far eluded detailed quantification.
Our research involves an experimental and computational investigation of
mixing in several reactive systems including: stirred tank reactors, partitioned
pipe mixers and roller bottles. The fundamental concepts of chaos theory
are used to characterize the state of mixing and to optimize reactor performance.
Blending of particles is an important operation in many industrial operations.
In these systems, process performance depends strongly on the degree of
homogeneity achieved during blending. The components requiring blending
are usually powders of different size and/or density. Under such conditions,
ultimate mixture homogeneity cannot be taken for granted; quite the opposite,
unless the blending process is properly designed and controlled, the result
is often a mixture with significant composition fluctuations throughout
the powder bed. Such fluctuations can cause excessive variability in the
composition of end products, requiring whole batches of products to be
either reworked or disposed, increasing both the cost and the environmental
impact of the production process. Our research focuses on the application
of fundamental concepts from chaos theory to enhance powder blending performance
in industrial applications and on the development of accurate particle
sampling techniques and methods for quantifying the extent of mixedness
in powder systems.
Mixing Group
Page
|
Recent Publications
Experimentally Validated Computations of Flow, Mixing, and
Segregation of Non- cohesive Grains in 3D Tumbling Blenders, Powder
Technology,
accepted for publication, T. Shinbrot, M. Moakher, and F.J. Muzzio
Method of Chaotic Mixing and Improved Stirred Tank Reactors, U.S.
Patent (1999)
No. 5,921,679, (14 claims) F.J. Muzzio and D. J. Lamberto
Spontaneous Chaotic Granular Mixing, Nature 397, 676 (1999),
T.
Shinbrot, A.Alexander, and F.J. Muzzio.
Self-Similar Spatio- temporal Structure of Intermaterial Boundaries
in Chaotic Flows, Physical Review Letters 81, 3395 (1998), M.M. Alvarez,
F.J. Muzzio (*), S. Cerbelli, A. Adrover, and M. Giona.
|
