97 research outputs found
Recommended from our members
Boundary adaptation in grid generation for CFD analysis of screw compressors
This paper describes some aspects of an advanced grid generation method used, with Computational Fluid Dynamics (CFD) procedures, to model three‐dimensional flow through screw compressors. The increased accuracy of the flow predictions thus derived, enable such machines to be designed with improved performance and for lower development costs.
To achieve this, a wholly original boundary adaptation procedure has been developed, in order to allow for convenient mapping of the internal grid points of a screw compressor, which is sufficiently flexible to fit any arbitrary rotor profile. The procedure includes a practical transformation method, which adapts the computationally transformed region to produce a regular boundary distribution on the mesh boundaries. It also allows for subsequent generation of an algebraic grid, which enables the three‐dimensional domain of a screw compressor to be mapped regularly even in regions where the flow patterns are complex and the geometrical aspect ratio is high.
This procedure enables more efficient use of a CFD solver for the estimation of the flow parameters within both oil free and oil injected screw compressors, with either ideal fluids or real fluids, with or without change of phase
An efficient method for constructing an ILU preconditioner for solving large sparse nonsymmetric linear systems by the GMRES method
AbstractThe main idea of this paper is in determination of the pattern of nonzero elements of the LU factors of a given matrix A. The idea is based on taking the powers of the Boolean matrix derived from A. This powers of a Boolean matrix strategy (PBS) is an efficient, effective, and inexpensive approach. Construction of an ILU preconditioner using PBS is described and used in solving large nonsymmetric sparse linear systems. Effectiveness of the proposed ILU preconditioner in solving large nonsymmetric sparse linear systems by the GMRES method is also shown. Numerical experiments are performed which show that it is possible to considerably reduce the number of GMRES iterations when the ILU preconditioner constructed here is used. In numerical examples, the influence of k, the dimension of the Krylov subspace, on the performance of the GMRES method using an ILU preconditioner is tested. For all the tests carried out, the best value for k is found to be 10
Quadrature Strategies for Constructing Polynomial Approximations
Finding suitable points for multivariate polynomial interpolation and
approximation is a challenging task. Yet, despite this challenge, there has
been tremendous research dedicated to this singular cause. In this paper, we
begin by reviewing classical methods for finding suitable quadrature points for
polynomial approximation in both the univariate and multivariate setting. Then,
we categorize recent advances into those that propose a new sampling approach
and those centered on an optimization strategy. The sampling approaches yield a
favorable discretization of the domain, while the optimization methods pick a
subset of the discretized samples that minimize certain objectives. While not
all strategies follow this two-stage approach, most do. Sampling techniques
covered include subsampling quadratures, Christoffel, induced and Monte Carlo
methods. Optimization methods discussed range from linear programming ideas and
Newton's method to greedy procedures from numerical linear algebra. Our
exposition is aided by examples that implement some of the aforementioned
strategies
Complexity of parallel matrix computations
AbstractWe estimate parallel complexity of several matrix computations under both Boolean and arithmetic machine models using deterministic and probabilistic approaches. Those computations include the evaluation of the inverse, the determinant, and the characteristic polynomial of a matrix. Recently, processor efficiency of the previous parallel algorithms for numerical matrix inversion has been substantially improved in (Pan and Reif, 1987), reaching optimum estimates up to within a logarithmic factor; that work, however, applies neither to the evaluation of the determinant and the characteristic polynomial nor to exact matrix inversion nor to the numerical inversion of ill-conditioned matrices. We present four new approaches to the solution of those latter problems (having several applications to combinatorial computations) in order to extend the suboptimum time and processor bounds of (Pan and Reif, 1987) to the case of computing the inverse, determinant, and characteristic polynomial of an arbitrary integer input matrix. In addition, processor efficient algorithms using polylogarithmic parallel time are devised for some other matrix computations, such as triangular and QR-factorizations of a matrix and its reduction to Hessenberg form
Hard isogeny problems over RSA moduli and groups with infeasible inversion
We initiate the study of computational problems on elliptic curve isogeny
graphs defined over RSA moduli. We conjecture that several variants of the
neighbor-search problem over these graphs are hard, and provide a comprehensive
list of cryptanalytic attempts on these problems. Moreover, based on the
hardness of these problems, we provide a construction of groups with infeasible
inversion, where the underlying groups are the ideal class groups of imaginary
quadratic orders.
Recall that in a group with infeasible inversion, computing the inverse of a
group element is required to be hard, while performing the group operation is
easy. Motivated by the potential cryptographic application of building a
directed transitive signature scheme, the search for a group with infeasible
inversion was initiated in the theses of Hohenberger and Molnar (2003). Later
it was also shown to provide a broadcast encryption scheme by Irrer et al.
(2004). However, to date the only case of a group with infeasible inversion is
implied by the much stronger primitive of self-bilinear map constructed by
Yamakawa et al. (2014) based on the hardness of factoring and
indistinguishability obfuscation (iO). Our construction gives a candidate
without using iO.Comment: Significant revision of the article previously titled "A Candidate
Group with Infeasible Inversion" (arXiv:1810.00022v1). Cleared up the
constructions by giving toy examples, added "The Parallelogram Attack" (Sec
5.3.2). 54 pages, 8 figure
- …