Nonlinear Reduced Order Modeling of Plasticization Cylinder

Reduced Order Modeling of Nonlinear Control Systems

An Approach for Reduced Order Modeling of Nonlinear Power Systems

-In this paper we present an approach for the reduced order modeling of nonlinear power systems. We describe a combined symbolic-numeric methodology for a local model order reduction which is based on the theory of singularly perturbed systems. Since the properties of power systems are taken into account, we were able to define an easy to use formula which eliminates the necessity of engineerin...

Reduced Order Modeling of Some Nonlinear Stochastic Partial Differential Equations

Determining accurate statistical information about outputs from ensembles of realizations is not generally possible whenever the input-output map involves the (computational) solution of systems of nonlinear partial differential equations (PDEs). This is due to the high cost of effecting each realization. Recently, in applications such as control and optimization that also require multiple solu...

Nonlinear Reduced-Order Modeling of Double Column Air Separation Plants

Cryogenic air separation plants produce purified oxygen, nitrogen and argon for the steel, chemical, food processing, semiconductor and health care industries. Cryogenic temperatures (–170 to –190 ◦C) are achieved via turbine expansion. Electricity required to power gas turbines represents the largest operational cost in air separation plants. Continued deregulation of the electric utility indu...

Reduced Order Modeling for Nonlinear Multi-component Models

Reduced order modeling plays an indispensible role in most real-world complex models. A hybrid application of order reduction methods, introduced previously, has been shown to effectively reduce the computational cost required to find a reduced order model with quantifiable bounds on the reduction errors, which is achieved by hybridizing the application of local variational and global sampling ...