61 research outputs found
Fluctuating hydrodynamics of multi-species, non-reactive mixtures
In this paper we discuss the formulation of the fuctuating Navier-Stokes
(FNS) equations for multi-species, non-reactive fluids. In particular, we
establish a form suitable for numerical solution of the resulting stochastic
partial differential equations. An accurate and efficient numerical scheme,
based on our previous methods for single species and binary mixtures, is
presented and tested at equilibrium as well as for a variety of non-equilibrium
problems. These include the study of giant nonequilibrium concentration
fluctuations in a ternary mixture in the presence of a diffusion barrier, the
triggering of a Rayleigh-Taylor instability by diffusion in a four-species
mixture, as well as reverse diffusion in a ternary mixture. Good agreement with
theory and experiment demonstrates that the formulation is robust and can serve
as a useful tool in the study of thermal fluctuations for multi-species fluids.
The extension to include chemical reactions will be treated in a sequel paper
A Numerical Study of Methods for Moist Atmospheric Flows: Compressible Equations
We investigate two common numerical techniques for integrating reversible
moist processes in atmospheric flows in the context of solving the fully
compressible Euler equations. The first is a one-step, coupled technique based
on using appropriate invariant variables such that terms resulting from phase
change are eliminated in the governing equations. In the second approach, which
is a two-step scheme, separate transport equations for liquid water and vapor
water are used, and no conversion between water vapor and liquid water is
allowed in the first step, while in the second step a saturation adjustment
procedure is performed that correctly allocates the water into its two phases
based on the Clausius-Clapeyron formula. The numerical techniques we describe
are first validated by comparing to a well-established benchmark problem.
Particular attention is then paid to the effect of changing the time scale at
which the moist variables are adjusted to the saturation requirements in two
different variations of the two-step scheme. This study is motivated by the
fact that when acoustic modes are integrated separately in time (neglecting
phase change related phenomena), or when sound-proof equations are integrated,
the time scale for imposing saturation adjustment is typically much larger than
the numerical one related to the acoustics
Field dependent competing magnetic ordering in multiferroic Ni3V2O8
The geometrically frustrated magnet Ni3V2O8 undergoes a series of competing
magnetic ordering at low temperatures. Most importantly, one of the
incommensurate phases has been reported to develop a ferroelectric correlation
caused by spin frustration. Here we report an extensive thermodynamic,
dielectric and magnetic study on clean polycrystalline samples of this novel
multiferroic compound. Our low temperature specific heat data at high fields up
to 14 Tesla clearly identify the development of a new magnetic field induced
phase transition below 2 K that shows signatures of simultaneous electric
ordering. We also report temperature and field dependent dielectric constant
that enables us to quantitatively estimate the strength of magneto-electric
coupling in this improper ferroelectric material.Comment: 18 pages, 4 figures. Accepted for publication in Euro. Phys. Let
On the high fidelity simulation of chemical explosions and their interaction with solid particle clouds
High explosive charges when detonated ensue in a flow field characterized by several physical phenomena that include blast wave propagation, hydrodynamic instabilities, real gas effects, fluid mixing and afterburn effects. Solid metal particles are often added to explosives to augment the total impulsive loading, either through direct bombardment if inert, or through afterburn energy release if reactive. These multiphase explosive charges, termed as heterogeneous explosives, are of interest from a scientific perspective as they involve the confluence and interplay of various additional physical phenomena such as shock-particle interaction, particle dispersion, ignition, and inter-phase mass, momentum and energy transfer.
In the current research effort, chemical explosions in multiphase environments are investigated using a robust, state-of-the-art Eulerian-gas, Lagrangian-solid methodology that can handle both the dense and dilute particle regimes. Explosions into ambient air as well as into aluminum particle clouds are investigated, and hydrodynamic instabilities such as Rayleigh- Taylor and Richtmyer-Meshkov result in a mixing layer where the detonation products mix with the air and afterburn. The particles in the ambient cloud, when present, are observed to pick up significant amounts of momentum and heat from the gas, and thereafter disperse, ignite and burn. The amount of mixing and afterburn are observed to be independent of particle size, but dependent on the particle mass loading and cloud dimensions. Due to fast response times, small particles are observed to cluster as they interact with the vortex rings in the mixing layer, which leads to their preferential ignition/ combustion.
The total deliverable impulsive loading from heterogeneous explosive charges containing inert steel particles is estimated for a suite of operating parameters and compared, and it is demonstrated that heterogeneous explosive charges deliver a higher near-field impulse than homogeneous explosive charges containing the same mass of the high explosive. Furthermore, particles are observed to introduce significant amounts of hydrodynamic instabilities in the mixing layer, resulting in augmented fluctuation intensities and fireball size, and different growth rates for heterogeneous explosions compared to homogeneous explosions. For aluminized explosions, the particles are observed to burn in two regimes, and the average particle velocities at late times are observed to be independent of the initial solid volume fraction in the explosive charge. Overall, this thesis provides useful insights on the role played by solid particles in chemical explosions.Ph.D.Committee Chair: Menon, Suresh; Committee Member: Jagoda, Jeff; Committee Member: Ruffin, Stephen; Committee Member: Thadhani, Naresh; Committee Member: Walker, Mitchel
TensorFlow reinforcement learning quick start guide: get up and running with training and deploying intelligent, self-learning agents using Python
This book is an essential guide for anyone interested in Reinforcement Learning. The book provides an actionable reference for Reinforcement Learning algorithms and their applications using TensorFlow and Python. It will help readers leverage the power of algorithms such as Deep Q-Network (DQN), Deep Deterministic Policy Gradients (DDPG), and ..
- …