Numerical study of turbulent cavitating flows in thermal regime

Abstract

Originality The interaction between RANS turbulence closure and non isothermal phase transition is rarely studied. It is the first time such a study on the turbulent Prandtl number effect is reported in cavitating flows.

Yang-Laplace Decomposition Method for Nonlinear System of Local Fractional Partial Differential Equations

“…Fractional partial differential equations is a fundamental tool for the analysis of physical phenomena, such as, electromagnetic, acoustics, viscoelasticity, electrochemistry, and others. These physical and other phenomena are expressed by fractional partial differential equations, which have been solved by several numerical-analytical methods ( [13], [21], [25]). Among them, one of the most popular methods is the so-called Adomian decomposition method (ADM), which has been developed between the 1970s and 1990s by George Adomian ( [1]- [5]).…”

System of Riemann‐Liouville fractional differential equations with nonlocal boundary conditions: Existence, uniqueness, and multiplicity of solutions

“…3 A recent studies [12][13][14][15] discuss the application of integrodifferential equations of fractional order and their numerical solutions. The applications of fractional differential calculus in studying the wave patterns are discussed in Goncalves and Islam et al 16,17 As the presence of fractional differential equations in various fields is increasing, it is essential to investigate the existence/stability of solutions of different fractional order differential systems.…”

Numerical solutions of fuzzy time fractional advection‐diffusion equations in double parametric form of fuzzy number

“…Fractional differential equations (FDEs) have attracted much attention in recent years because of applications and potential applications in biology, chemistry, physics, engineering, and certain other areas of study. [1][2][3][4][5][6][7][8][9][10][11][12][13] In the mainstream study of processes modelled by FDEs, the parameters and variables are deemed to be crisp or defined exactly. In reality, although these parameters may be vague and uncertain because of experimental and measurement errors, which then lead to fuzzy FDEs.…”