Hydrodynamic correlation functions of a driven granular fluid in steady state

We study a homogeneously driven granular fluid of hard spheres at intermediate volume fractions and focus on time-delayed correlation functions in the stationary state. Inelastic collisions are modeled by incomplete normal restitution, allowing for efficient simulations with an event-driven algorithm. The incoherent scattering function Fincoh(q,t ) is seen to follow time-density superposition with a relaxation time that increases significantly as the volume fraction increases. The statistics of particle displacements is approximately Gaussian. For the coherent scattering function S(q,ω), we compare our results to the predictions of generalized fluctuating hydrodynamics, which takes into account that temperature fluctuations decay either diffusively or with a finite relaxation rate, depending on wave number and inelasticity. For sufficiently small wave number q we observe sound waves in the coherent scattering function S(q,ω) and the longitudinal current correlation function Cl(q,ω). We determine the speed of sound and the transport coefficients and compare them to the results of kinetic theory.

Design and Development of an FPGA-based Distributed Computing Processing Platform

This thesis presents two frameworks- a software framework and a hardware core manager framework- which, together, can be used to develop a processing platform using a distributed system of field-programmable gate array (FPGA) boards. The software framework providesusers with the ability to easily develop applications that exploit the processing power of FPGAs while the hardware core manager framework gives users the ability to configure and interact with multiple FPGA boards and/or hardware cores. This thesis describes the design and development of these frameworks and analyzes the performance of a system that was constructed using the frameworks. The performance analysis included measuring the effect of incorporating additional hardware components into the system and comparing the system to a software-only implementation. This work draws conclusions based on the provided results of the performance analysis and offers suggestions for future work.

Strong Dynamical Heterogeneity and Universal Scaling in Driven Granular Fluids

Large-scale simulations of two-dimensional bidisperse granular fluids allow us to determine spatial correlations of slow particles via the four-point structure factor S-4 (q, t). Both cases, elastic (epsilon = 1) and inelastic (epsilon < 1) collisions, are studied. As the fluid approaches structural arrest, i.e., for packing fractions in the range 0.6 <= phi <= 0.805, scaling is shown to hold: S-4 (q, t)/chi(4)(t) = s(q xi(t)). Both the dynamic susceptibility chi(4)(tau(alpha)) and the dynamic correlation length xi(tau(alpha)) evaluated at the alpha relaxation time tau(alpha) can be fitted to a power law divergence at a critical packing fraction. The measured xi(tau(alpha)) widely exceeds the largest one previously observed for three-dimensional (3d) hard sphere fluids. The number of particles in a slow cluster and the correlation length are related by a robust power law, chi(4)(tau(alpha)) approximate to xi(d-p) (tau(alpha)), with an exponent d - p approximate to 1.6. This scaling is remarkably independent of epsilon, even though the strength of the dynamical heterogeneity at constant volume fraction depends strongly on epsilon.