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Materials Data on NaSrAs by Materials Project

NaSrAs crystallizes in the hexagonal P-62m space group. The structure is three-dimensional. Na1+ is bonded to four As3- atoms to form NaAs4 tetrahedra that share corners with six equivalent SrAs5 square pyramids, corners with ten equivalent NaAs4 tetrahedra, edges with six equivalent SrAs5 square pyramids, and edges with two equivalent NaAs4 tetrahedra. There are two shorter (2.99 Å) and two longer (3.06 Å) Na–As bond lengths. Sr2+ is bonded to five As3- atoms to form SrAs5 square pyramids that share corners with ten equivalent SrAs5 square pyramids, corners with six equivalent NaAs4 tetrahedra, edges with six equivalent SrAs5 square pyramids, and edges with six equivalent NaAs4 tetrahedra. There are one shorter (3.27 Å) and four longer (3.31 Å) Sr–As bond lengths. There are two inequivalent As3- sites. In the first As3- site, As3- is bonded in a 9-coordinate geometry to three equivalent Na1+ and six equivalent Sr2+ atoms. In the second As3- site, As3- is bonded in a 9-coordinate geometry to six equivalent Na1+ and three equivalent Sr2+ atoms.

36 MATERIALS SCIENCE↗

An algorithm for domain decomposition in finite element analysis

A simple and efficient algorithm is described for automatic decomposition of an arbitrary finite element domain into a specified number of subdomains for finite element and substructuring analysis in a multiprocessor computer environment. The algorithm is designed to balance the work loads, to minimize the communication among processors and to minimize the bandwidths of the resulting system of equations. Small- to large-scale finite element models, which have two-node elements (truss, beam element), three-node elements (triangular element) and four-node elements (quadrilateral element), are solved on the Convex computer to illustrate the effectiveness of the proposed algorithm. A FORTRAN computer program is also included.

Al-Nasra, M.↗

Parallel-vector computation for linear structural analysis and non-linear unconstrained optimization problems

Several parallel-vector computational improvements to the unconstrained optimization procedure are described which speed up the structural analysis-synthesis process. A fast parallel-vector Choleski-based equation solver, pvsolve, is incorporated into the well-known SAP-4 general-purpose finite-element code. The new code, denoted PV-SAP, is tested for static structural analysis. Initial results on a four processor CRAY 2 show that using pvsolve reduces the equation solution time by a factor of 14-16 over the original SAP-4 code. In addition, parallel-vector procedures for the Golden Block Search technique and the BFGS method are developed and tested for nonlinear unconstrained optimization. A parallel version of an iterative solver and the pvsolve direct solver are incorporated into the BFGS method. Preliminary results on nonlinear unconstrained optimization test problems, using pvsolve in the analysis, show excellent parallel-vector performance indicating that these parallel-vector algorithms can be used in a new generation of finite-element based structural design/analysis-synthesis codes.

Nguyen, D. T.↗