in this paper, the accuracy of k- and k- turbulence models in super sonic boundary layer capturing of smooth/rough flat plates have been comprehensively investigated. among these investigations, some sorts of sensitivity analysis, including change in turbulence model, generated-grid density, near wall affects, c magnitude (for boundary layers generated on smooth flat plates), and change in c...

Châtelet surfaces provide a rich source of geometrically rational surfaces which do not always satisfy the Hasse principle. We investigate the frequency that such counter-examples arise over the rationals. This is joint work with T. Browning. Jörg Brüdern, On the Möbius function Alina Cojocaru, Frobenius fields for elliptic curves Abstract: Let E be an elliptic curve defined over Q. For a prime...

PURPOSE To enable accurate magnetic resonance (MR) parameter mapping with accelerated data acquisition, utilizing recent advances in constrained imaging with sparse sampling. THEORY AND METHODS A new constrained reconstruction method based on low-rank and sparsity constraints is proposed to accelerate MR parameter mapping. More specifically, the proposed method simultaneously imposes low-rank...

In this paper, 8 mm thickness 2205 duplex stainless steel (DSS) plates were successfully welded using keyhole tungsten inert gas welding (K-TIG) welding, and numerical simulations performed applying the finite element method. Three models of combined heat source adopted to verify accuracy experiment. The process under different speeds simulated, temperature field, molten pool shape, thermal cyc...

For a finite state Markov process and a finite collection {Γk, k ∈ K} of subsets of its state space, let τk be the first time the process visits the set Γk. We derive explicit/recursive formulas for the joint density and tail probabilities of the stopping times {τk, k ∈ K}. The formulas are natural generalizations of those associated with the jump times of a simple Poisson process. We give a nu...

• Many kernel-based learning algorithms have the computational load. • The Nyström low-rank approximation is designed for reducing the computation. • We propose the spectrum decomposition condition with a theoretical justification. • Asymptotic error bounds on eigenvalues and eigenvectors are derived. • Numerical experiments are provided for covariance kernel and Wishart matrix. AMS subject cla...

We present a family of algorithms for computing symmetric rank-revealing VSV decompositions, based on triangular factorization of the matrix. The VSV decomposition consists of a middle symmetric matrix that reveals the numerical rank in having three blocks with small norm, plus an orthogonalmatrix whose columns span approximations to the numerical range and null space. We show that for semi-de ...