The Trilinos Project is an effort to facilitate the design, development, integration and ongoing support of mathematical software libraries within an object-oriented framework for the solution of large-scale, complex multi-physics engineering and scientific problems. Trilinos addresses two fundamental issues of developing software for these problems: (i) Providing a streamlined process and set of tools for development of new algorithmic implementations and (ii) promoting interoperability of independently developed software. Trilinos uses a two-level software structure designed around collections of packages. A Trilinos package is an integral unit usually developed by a small team of experts in a particular algorithms area such as algebraic preconditioners, nonlinear solvers, etc. Packages exist underneath the Trilinos top level, which provides a common look-and-feel, including configuration, documentation, licensing, and bug-tracking.Here we present the overall Trilinos design, describing our use of abstract interfaces and default concrete implementations. We discuss the services that Trilinos provides to a prospective package and how these services are used by various packages. We also illustrate how packages can be combined to rapidly develop new algorithms. Finally, we discuss how Trilinos facilitates highquality software engineering practices that are increasingly required from simulation software.

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The FDNY-START system may allow providers to prioritize casualties using an intermediate category (Orange) more properly aligned to meet patient needs, and as such, may reduce the rates of over-triage compared with START. The FDNY-START system decreases the variability in patient sorting while maintaining high field utility without needing computer assistance or extensive retraining. Comparison of triage algorithms at actual MCIs is needed; however, initial feedback is promising, suggesting that FDNY-START can improve triage with minimal additional training and cost.

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Iterative methods for solving linear systems of equations can be very e cient if the structure of the coe cient matrix can be exploited to accelerate the convergence of the iterative process. However, for classes of problems for which suitable preconditioners cannot be found or for which the iteration scheme does not converge, iterative techniques may be inappropriate. This paper proposes a technique for de ating the eigenvalues, and associated eigenvectors, of the iteration matrix which either slow down convergence or cause divergence. This process is completely general and works by approximating the eigenspace I P corresponding to the unstable or slowly converging modes and then applying a coupled iteration scheme on I P and its orthogonal complementQ: