Abstract. We consider the system of equations that describes small nonstationary motions of viscous incompressible fluid with a large number of small rigid interacting particles. This system is a microscopic mathematical model of complex fluids such as colloidal suspensions, polymer solutions etc. We suppose that the system of particles depends on a small parameter ε in such a way that the size...

Using the idea of the penguin box expansion we find an analytic expression for ε/ε in the Standard Model as a function of mt, ms(mc) and two non-perturbative parameters B (1/2) 6 and B (3/2) 8 . This formula includes next-to-leading QCD/QED short distance effects calculated recently by means of the operator product expansion and renormalization group techniques. We also derive an analytic expre...

Different variants for buoyancy-affected terms in k-ε turbulence model have been utilized to predict the flow parameters more accurately, and investigate applicability of alternative k-ε turbulence buoyant closures in numerical simulation of a horizontal gravity current. The additional non-isotropic turbulent stress due to buoyancy has been considered in production term, based on Algebraic Stre...

Strong final state interaction (FSI) effects can play a central role in the Standard Model prediction of weak K → 2π matrix elements. Here, I discuss how FSI's affect the direct CP violation parameter ε ′ /ε by solving the Omnès problem for the necessary K → 2π amplitudes. The main results of this analysis have been reported in a previous paper 1 and are further discussed in Refs. 2,3. The resu...

This paper focuses on the developing a mechanistic model of the biopolymerization process and linking with the feedforward neural network model to obtain a hybrid model of lipase-catalyzed ring-opening polymerization of ε-caprolactone (ε-CL) for Poly (ε-caprolactone) PCL production using feed forward neural networks and control using model predictive control. Model predictive control (MPC) has ...