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                <identifier>oai:data.mendeley.com/9pgm6v5hfh.1</identifier>
                <datestamp>2025-11-26T11:59:14Z</datestamp>
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    <dc:creator id="https://orcid.org/0000-0002-9845-8372">Gubareva, Kristina</dc:creator>
    <dc:title>MATLAB Code for Parametric Analysis of Generalized Couette Flow in Micropolar Fluids: Reynolds, Taylor and Micropolarity Parameter Study</dc:title>
    <dc:publisher>Mendeley Data</dc:publisher>
    <dc:description>This MATLAB R2023b code performs a systematic parametric analysis of generalized Couette flow in a micropolar fluid with couple stresses. The study investigates the influence of three key dimensionless parameters: the micropolarity parameter s (ranging from 0.03 to 5.0), the Reynolds number Re (30 to 250), and the Taylor number Ta (10 to 250). The implementation is based on exact analytical solutions derived via the Lin–Sidorov–Aristov ansatz. The package includes comprehensive parameter scanning across extended ranges and generates eight types of publication-ready visualizations: three-dimensional surfaces of maximum velocity, heat maps of velocity and its gradients, derivative-based curvature analysis, full-field velocity isolines, comparative deviation metrics between classical and micropolar solutions, contour maps of maximum deviations, flow uniformity optimization analysis, and complex deviation surfaces in the multi-parameter space. This dataset provides a complete computational framework for researchers studying non-Newtonian and microstructured fluids in microfluidic, biomedical, and industrial applications.</dc:description>
    <dc:subject>Applied Mathematics</dc:subject>
    <dc:subject>Fluid Dynamics</dc:subject>
    <dc:subject>Computational Fluid Dynamics</dc:subject>
    <dc:subject>Continuum Mechanics</dc:subject>
    <dc:subject>Soft Matter Physics</dc:subject>
    <dc:contributor id="https://orcid.org/0000-0002-2349-7801">Prosviryakov, Evgenii</dc:contributor>
    <dc:type>Dataset</dc:type>
    <dc:identifier>doi:10.17632/9pgm6v5hfh.1</dc:identifier>
    <dc:identifier>oai:data.mendeley.com/9pgm6v5hfh.1</dc:identifier>
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    <dc:date>2025-11-26T11:59:14Z</dc:date>
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