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Design and Operation of Pressure Swing Adsorption Processes

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Design and Operation of Pressure Swing Adsorption Processes ( design-and-operation-pressure-swing-adsorption-processes )

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conditions. On similar lines, Rambo et al. [146] developed ROMs with parametric conditions specifically for turbulent forced convection problems. Willcox has done extensive research in the field of POD-based reduced-order models (see [200, 201, 15, 34, 35, 36]). In particular, Bui-Thanh et al. [37] provided a goal-oriented framework for generating POD-based ROMs by solving a model-constrained optimization problem. ROMs are derived from solutions of detailed distributed models through the representation of eigenfunction expansions. Using the singular value decomposition, spatially distributed eigenfunctions can be derived empirically through a set of well-defined minimization problems. ROMs are then formulated through the substitution of the eigenfunction expansion into the PDE model using Galerkin projection. Truncation of those modes that have no significant contribution to the solution profile then leads to a significant reduction in the number of states which eventually leads to a much smaller optimization problem. Numerous studies report use of reduced-order modeling for the purpose of optimization and optimal control. Kunisch et al. [115] used it to control Burgers equation. Armaou et al. [14] applied the concept of model reduction to the time-dependent parabolic PDEs and generated ROMs for optimization of a diffusion-reaction process. Bendersky et al. [22] used it for optimization of the transport-reaction processes, while Theodoropoulou [185] optimized the chemical vapor deposition process using ROMs. Luna-Ortiz et al. [127] developed an input-output based optimization scheme for large-scale systems. Fahl [65] applied a trust region proper orthogonal decomposition algorithm for the optimal boundary control of a cavity flow. Bergmann et al. [25] also applied the same algorithm for optimal control of the circular cylinder wake flow considered in a laminar regime. Balsa-Canto et al. [21] solved a problem related to design and optimization of thermal sterilization in the food industry, particularly conduction-heated foods, using POD-based ROMs. LeGresley et al. [122] performed analysis and design optimization of inviscid airfoils using ROMs for both subsonic and transonic flows. Weickum et al. [198] developed extended ROMs for optimal design problems, in which ROMs are developed for the whole design space before optimization and then a trust region based strategy is used for 6.1 Motivation Chapter 6. Reduced-order Modeling for Optimization 99

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