No Arabic abstract
On contrary to the customary thought, the well-known ``lemma that the distribution function of a collisionless Boltzmann gas keeps invariant along a molecules path represents not the strength but the weakness of the standard theory. One of its consequences states that the velocity distribution at any point is a condensed ``image of all, complex and even discontinuous, structures of the entire spatial space. Admitting the inability to describe the entire space with a microscopic quantity, this paper introduces a new type of distribution function, called the solid-angle-average distribution function. With help of the new distribution function, the dynamical behavior of collisionless Boltzmann gas is formulated in terms of a set of integrals defined by molecular paths. In the new formalism, not only that the difficulties associated with the standard theory are surmounted but also that some of practical gases become calculable in terms of todays computer.
We report progress in the development of a model-based hybrid probabilistic approach to an on-board IVHM for solid rocket boosters (SRBs) that can accommodate the abrupt changes of the model parameters in various nonlinear dynamical off-nominal regimes. The work is related to the ORION mission program. Specifically, a case breach fault for SRBs is considered that takes into account burning a hole through the rocket case, as well as ablation of the nozzle throat under the action of hot gas flow. A high-fidelity model (HFM) of the fault is developed in FLUENT in cylindrical symmetry. The results of the FLUENT simulations are shown to be in good agreement with quasi-stationary approximation and analytical solution of a system of one-dimensional partial differential equations (PDEs) for the gas flow in the combustion chamber and in the hole through the rocket case.
An effective modeling method for nonlinear distributed parameter systems (DPSs) is critical for both physical system analysis and industrial engineering. In this Rapid Communication, we propose a novel DPS modeling approach, in which a high-order nonlinear Volterra series is used to separate the time/space variables. With almost no additional computational complexity, the modeling accuracy is improved more than 20 times in average comparing with the traditional method.
In this work we study of the dynamics of large size random neural networks. Different methods have been developed to analyse their behavior, most of them rely on heuristic methods based on Gaussian assumptions regarding the fluctuations in the limit of infinite sizes. These approaches, however, do not justify the underlying assumptions systematically. Furthermore, they are incapable of deriving in general the stability of the derived mean field equations, and they are not amenable to analysis of finite size corrections. Here we present a systematic method based on Path Integrals which overcomes these limitations. We apply the method to a large non-linear rate based neural network with random asymmetric connectivity matrix. We derive the Dynamic Mean Field (DMF) equations for the system, and derive the Lyapunov exponent of the system. Although the main results are well known, here for the first time, we calculate the spectrum of fluctuations around the mean field equations from which we derive the general stability conditions for the DMF states. The methods presented here, can be applied to neural networks with more complex dynamics and architectures. In addition, the theory can be used to compute systematic finite size corrections to the mean field equations.
Geant4 has been used throughout the nuclear and high-energy physics community to simulate energy depositions in various detectors and materials. These simulations have mostly been run with a source beam outside the detector. In the case of low-background physics, however, a primary concern is the effect on the detector from radioactivity inherent in the detector parts themselves. From this standpoint, there is no single source or beam, but rather a collection of sources with potentially complicated spatial extent. LUXSim is a simulation framework used by the LUX collaboration that takes a component-centric approach to event generation and recording. A new set of classes allows for multiple radioactive sources to be set within any number of components at run time, with the entire collection of sources handled within a single simulation run. Various levels of information can also be recorded from the individual components, with these record levels also being set at runtime. This flexibility in both source generation and information recording is possible without the need to recompile, reducing the complexity of code management and the proliferation
We use a probabilistic approach to study the rate of convergence to equilibrium for a collisionless (Knudsen) gas in dimension equal to or larger than 2. The use of a coupling between two stochastic processes allows us to extend and refine, in total variation distance, the polynomial rate of convergence given in [AG11] and [KLT13]. This is, to our knowledge, the first quantitative result in collisionless kinetic theory in dimension equal to or larger than 2 that does not require any symmetry of the domain, nor a monokinetic regime. Our study is also more general in terms of reflection at the boundary: we allow for rather general diffusive reflections and for a specular reflection component.