The equation of state Soave-Redlich-Kwong (SRK) and its modification (predictive SRK or PSRK) are applied to simulate multicomponet distillation, which separate main component of spearmint essential oil. The simulation model is based on bubble point method, and the Wang-Henke algorithm. Spearmint essential oil is considered in the study and the original experimental data were obtained f...

The objective of this paper is to develop the method for selection of the optimal structure of simultaneous equation system from the given model set in the condition of the limited sample of observations. The identification purpose is the model selection with the best predictive possibility. The information criteria for selecting the best model of nonlinear simultaneous equation system from the...

Flow over a downstream-facing step is predicted using the F.E.M. A two-equation model of turbulence is employed where the transport of turbulence kinetic energy and dissipation rate are depicted using transport-type equations, i.e. the two-equation model of turbulence. The results obtained are compared with other models and experimental results. Generally, the model was found to be under-predic...

The multi-scale Gibbs–Helmholtz constrained (GHC) equation is a new predictive cubic equation of state that constrains the energy parameter in the SRK equation to satisfy the Gibbs–Helmholtz equation. It makes use of internal energies of departure calculated from NTP Monte Carlo simulations at the molecular length scale and a novel up-scaling expression to determine the energy parameter at the ...

-Two alternative solutions to the generalized predictive control (GPC) design problem are given for the case when the output horizon is larger than or equal to the plant order. First, using multirate models of the discrete-time plant, we present a state-space solution that does not require state observers or Riccati equation iterations for its implementation. Second, it is shown, via simple alg...

The Predictive Performance Equation (PPE) is a mathematical model of learning and forgetting developed to capture performance effectiveness across training histories, and to generate precise, quantitative point predictions of performance by extrapolating the unique mathematical regularities indicative of the learner. This equation is implemented in the Predictive Performance Optimizer (PPO) cog...