Synthetic Aperture Radar (SAR) data processing

The available and optimal methods for generating SAR imagery for NASA applications were identified. The SAR image quality and data processing requirements associated with these applications were studied. Mathematical operations and algorithms required to process sensor data into SAR imagery were defined. The architecture of SAR image formation processors was discussed, and technology necessary to implement the SAR data processors used in both general purpose and dedicated imaging systems was addressed

Simulation of Enhanced-Explosive Devices in Chambers and Tunnels

Introduction: Shock-dispersed fuel (SDF) explosives use a small chemical charge to disperse a combustible fuel that burns in the post-detonation environment. The energy released in the combustion process has the potential for generating higher pressures and temperatures than conventional explosives. However, the development of these types of novel explosive systems requires a detailed understanding of all of the modes of energy release. Objective: The objective of this project is develop a simulation capability for predicting explosion and combustion phase of SDF charges and apply that capability to quantifying the behavior of these types of explosives. Methodology: We approximate the dynamics of an SDF charge using high Reynolds number, fast chemistry model that effectively captures the thermodynamic behavior of SDF charges and accurately models the key modes of energy release. The overall computational model is combined with Adaptive Mesh Refinement (AMR) , implemented in a parallel adaptive framework suited to the massively parallel computer systems. Results: We have developed a multiphase version of the model and used it to simulate an SDF charge in which the dispersed fuel is aluminum flakes. Flow visualizations show that the combustion field is turbulent for the chamber and tunnel cases studied. During the 3 milli-seconds of simulation, over 90% of the Al fuel was consumed for the chamber case, while about 40% was consumed in the tunnel case in agreement with Al-SDF experiments. Significance to DoD: DoD has a requirement to develop enhanced energetic materials to support future military systems. The SDF charges described here utilize the combustion mechanism to increase energy per gram of fuel by a factor of 7 to 10 over conventional (detonating) charges, and increase the temperature of the explosion cloud to 2,000-4,000 K (depending on the SDF fuel). Accurate numerical simulation of such SDF explosions allows one to understand the energy release mechanism, and thereby design full-scale systems with greatly improved explosive efficiency

Simulation of Combustion of C/B Clouds in Explosions

Abstract not provide

Numerical Simulations of Thermobaric Explosions

A Model of the energy evolution in thermobaric explosions is presented. It is based on the two-phase formulation: conservation laws for the gas and particle phases along with inter-phase interaction terms. It incorporates a Combustion Model based on the mass conservation laws for fuel, air and products; source/sink terms are treated in the fast-chemistry limit appropriate for such gas dynamic fields. The Model takes into account both the afterburning of the detonation products of the booster with air, and the combustion of the fuel (Al or TNT detonation products) with air. Numerical simulations were performed for 1.5-g thermobaric explosions in five different chambers (volumes ranging from 6.6 to 40 liters and length-to-diameter ratios from 1 to 12.5). Computed pressure waveforms were very similar to measured waveforms in all cases - thereby proving that the Model correctly predicts the energy evolution in such explosions. The computed global fuel consumption {mu}(t) behaved as an exponential life function. Its derivative {dot {mu}}(t) represents the global rate of fuel consumption. It depends on the rate of turbulent mixing which controls the rate of energy release in thermobaric explosions

Simulation of Turbulent Combustion Fields of Shock-Dispersed Aluminum Using the AMR Code

We present a Model for simulating experiments of combustion in Shock-Dispersed-Fuel (SDF) explosions. The SDF charge consisted of a 0.5-g spherical PETN booster, surrounded by 1-g of fuel powder (flake Aluminum). Detonation of the booster charge creates a high-temperature, high-pressure source (PETN detonation products gases) that both disperses the fuel and heats it. Combustion ensues when the fuel mixes with air. The gas phase is governed by the gas-dynamic conservation laws, while the particle phase obeys the continuum mechanics laws for heterogeneous media. The two phases exchange mass, momentum and energy according to inter-phase interaction terms. The kinetics model used an empirical particle burn relation. The thermodynamic model considers the air, fuel and booster products to be of frozen composition, while the Al combustion products are assumed to be in equilibrium. The thermodynamic states were calculated by the Cheetah code; resulting state points were fit with analytic functions suitable for numerical simulations. Numerical simulations of combustion of an Aluminum SDF charge in a 6.4-liter chamber were performed. Computed pressure histories agree with measurements

Closure properties of solutions to heat inequalities

We prove that if $u_1,u_2 : (0,\infty) \times \R^d \to (0,\infty)$ are sufficiently well-behaved solutions to certain heat inequalities on $\R^d$ then the function $u: (0,\infty) \times \R^d \to (0,\infty)$ given by $u^{1/p}=u_1^{1/p_1} * u_2^{1/p_2}$ also satisfies a heat inequality of a similar type provided $\tfrac{1}{p_1} + \tfrac{1}{p_2} = 1 + \tfrac{1}{p}$. On iterating, this result leads to an analogous statement concerning $n$-fold convolutions. As a corollary, we give a direct heat-flow proof of the sharp $n$-fold Young convolution inequality and its reverse form.Comment: 12 page

Chemical-looping combustion - a thermodynamic study

Published versio

Relativistic MHD with Adaptive Mesh Refinement

This paper presents a new computer code to solve the general relativistic magnetohydrodynamics (GRMHD) equations using distributed parallel adaptive mesh refinement (AMR). The fluid equations are solved using a finite difference Convex ENO method (CENO) in 3+1 dimensions, and the AMR is Berger-Oliger. Hyperbolic divergence cleaning is used to control the $\nabla\cdot {\bf B}=0$ constraint. We present results from three flat space tests, and examine the accretion of a fluid onto a Schwarzschild black hole, reproducing the Michel solution. The AMR simulations substantially improve performance while reproducing the resolution equivalent unigrid simulation results. Finally, we discuss strong scaling results for parallel unigrid and AMR runs.Comment: 24 pages, 14 figures, 3 table