The convective period leading up to a Type Ia supernova (SN Ia) explosion is characterized by very low Mach number flows, requiring hydrodynamical methods well-suited to long-time integration. We continue the development of the low Mach number equation set for stellar scale flows by incorporating the effects of heat release due to external sources. Low Mach number hydrodynamics equations with a time-dependent background state are derived, and a numerical method based on the approximate projection formalism is presented. We demonstrate through validation with a fully compressible hydrodynamics code that this low Mach number model accurately captures the expansion of the stellar atmosphere as well as the local dynamics due to external heat sources. This algorithm provides the basis for an efficient simulation tool for studying the ignition of SNe Ia.

Adaptive mesh refinement (AMR) is a powerful technique that reduces the resources necessary to solve otherwise in-tractable problems in computational science. The AMR strategy solves the problem on a relatively coarse grid, and dynamically refines it in regions requiring higher resolution. However, AMR codes tend to be far more complicated than their uniform grid counterparts due to the software infrastructure necessary to dynamically manage the hierarchical grid framework. Despite this complexity, it is generally believed that future multi-scale applications will increasingly rely on adaptive methods to study problems at unprecedented scale and resolution. Recently, a new generation of parallel-vector architectures have become available that promise to achieve extremely high sustained performance for a wide range of applications, and are the foundation of many leadership-class computing systems worldwide. It is therefore imperative to understand the tradeoffs between conventional scalar and parallel-vector platforms for solving AMR-based calculations. In this paper, we examine the HyperCLaw AMR framework to compare and contrast performance on the Cray X1E, IBM Power3 and Power5, and SGI Altix. To the best of our knowledge, this is the first work that investigates and characterizes the performance of an AMR calculation on modern parallel-vector systems.

Type Ia supernovae (SNe Ia) are the largest thermonuclear explosions in the Universe. Their light output can be seen across great stances and has led to the discovery that the expansion rate of the Universe is accelerating. Despite the significance of SNe Ia, there are still a large number of uncertainties in current theoretical models. Computational modeling offers the promise to help answer the outstanding questions. However, even with today's supercomputers, such calculations are extremely challenging because of the wide range of length and time scales. In this paper, we discuss several new algorithms for simulations of SNe Ia and demonstrate some of their successes.

Successfully attacking underground storage facilities for chemical and biological (C/B) weapons is an important mission area for the Department of Defense. The fate of a C/B agent during an attack depends critically on the pressure and thermal environment that the agent experiences. The initial environment is determined by the blast wave from an explosive device. The byproducts of the detonation provide a fuel source that burn when mixed with oxidizer (after burning). Additional energy can be released by the ignition of the C/B agent as it mixes with the explosion products and the air in the chamber. Hot plumes venting material from any openings in the chamber can provide fuel for additional energy release when mixed with additional oxidizer. Assessment of the effectiveness of current explosives as well as the development of new explosive systems requires a detailed understanding of all of these modes of energy release. Using methodologies based on the use of higher-order Godunov schemes combined with Adaptive Mesh Refinement (AMR), implemented in aparallel adaptive framework suited to the massively parallel computer systems provided by the DOD High-Performance Computing Modernization program, we use a suite of programs to develop predictive models forthe simulation of the energetics of blast waves, deflagration waves and ejecta plumes. The programs use realistic reaction kinetic and thermodynamic models provided by standard components (such as CHEMKIN) as well as other novel methods to model enhanced explosive devices. The work described here focuses on the validation of these models against a series of bomb calorimetry experiments performed at the Ernst-Mach Institute. In this paper, we present three-dimensional simulations of the experiments, examining the explosion dynamics and the role of subsequent burning on the explosion products on the thermal and pressure environment within the calorimeter. The effects of burning are quantified by comparing two sets of computations, one in which the calorimeter is filled with nitrogen so there is no after burning and a second in which the calorimeter contains air.