Solving Vlasov-Poisson-Fokker-Planck Equations using NRxx method

2017 ◽  
Vol 21 (3) ◽  
pp. 782-807 ◽  
Author(s):  
Yanli Wang ◽  
Shudao Zhang

AbstractWe present a numerical method to solve the Vlasov-Poisson-Fokker-Planck (VPFP) system using the NRxx method proposed in [4, 7, 9]. A globally hyperbolic moment system similar to that in [23] is derived. In this system, the Fokker-Planck (FP) operator term is reduced into the linear combination of the moment coefficients, which can be solved analytically under proper truncation. The non-splitting method, which can keep mass conservation and the balance law of the total momentum, is used to solve the whole system. A numerical problem for the VPFP system with an analytic solution is presented to indicate the spectral convergence with the moment number and the linear convergence with the grid size. Two more numerical experiments are tested to demonstrate the stability and accuracy of the NRxx method when applied to the VPFP system.

2015 ◽  
Vol 25 (11) ◽  
pp. 1550148 ◽  
Author(s):  
Chaoliang Luo ◽  
Shangjiang Guo

In this paper, by using Lyapunov functions and exponents, Feller's scale functions, and the Fokker–Planck equations, we investigate the stability and bifurcation of stochastic closed orbit equations with singular diffusion coefficients.


2015 ◽  
Vol 3 (1) ◽  
pp. 48
Author(s):  
Elona Shehu ◽  
Elona Meka

The quality of the loan portfolio in Albanian banking system is facing many obstacles during the last decade. In this paper we look at possible determinants of assets quality. During the recent financial crisis commercial banks were confronted with deteriorating asset quality that threatened not only the banking industry, but also the stability of the entire financial system. This study aims to examine the correlation between non-performing loans and the macroeconomic determinants in Albania during the last decade. NPLs are considered to be of a high importance as they represent the high risk exposure of banking system. A solid bank with healthy assets increases the market efficiency. Our approach is based on a panel data regression analysis technique from 2005-2015. Within this methodology this study finds robust evidence on the existing relationship between lending interest rate, real GDP growth and NPLs. We expect to find a negative relationship between lending interest rate and asset quality. Further we assume an inverse relationship between GDP growth and non-performing loans, suggesting that NPLs decrease if the economy is growing. Furthermore this study proposes a solution platform, which looks deeper into the possibility of creating a secondary active market for troubled loans, restructuring the banking system or implementing the Podgorica model. This research paper opens a new lieu of discussion in terms of academic debates and decision-making policies.


Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2830
Author(s):  
Sili Wang ◽  
Mark P. Panning ◽  
Steven D. Vance ◽  
Wenzhan Song

Locating underground microseismic events is important for monitoring subsurface activity and understanding the planetary subsurface evolution. Due to bandwidth limitations, especially in applications involving planetarily-distributed sensor networks, networks should be designed to perform the localization algorithm in-situ, so that only the source location information needs to be sent out, not the raw data. In this paper, we propose a decentralized Gaussian beam time-reverse imaging (GB-TRI) algorithm that can be incorporated to the distributed sensors to detect and locate underground microseismic events with reduced usage of computational resources and communication bandwidth of the network. After the in-situ distributed computation, the final real-time location result is generated and delivered. We used a real-time simulation platform to test the performance of the system. We also evaluated the stability and accuracy of our proposed GB-TRI localization algorithm using extensive experiments and tests.


2021 ◽  
pp. 1-31
Author(s):  
S.H. Derrouaoui ◽  
Y. Bouzid ◽  
M. Guiatni

Abstract Recently, transformable Unmanned Aerial Vehicles (UAVs) have become a subject of great interest in the field of flying systems, due to their maneuverability, agility and morphological capacities. They can be used for specific missions and in more congested spaces. Moreover, this novel class of UAVs is considered as a viable solution for providing flying robots with specific and versatile functionalities. In this paper, we propose (i) a new design of a transformable quadrotor with (ii) generic modeling and (iii) adaptive control strategy. The proposed UAV is able to change its flight configuration by rotating its four arms independently around a central body, thanks to its adaptive geometry. To simplify and lighten the prototype, a simple mechanism with a light mechanical structure is proposed. Since the Center of Gravity (CoG) of the UAV moves according to the desired morphology of the system, a variation of the inertia and the allocation matrix occurs instantly. These dynamics parameters play an important role in the system control and its stability, representing a key difference compared with the classic quadrotor. Thus, a new generic model is developed, taking into account all these variations together with aerodynamic effects. To validate this model and ensure the stability of the designed UAV, an adaptive backstepping control strategy based on the change in the flight configuration is applied. MATLAB simulations are provided to evaluate and illustrate the performance and efficiency of the proposed controller. Finally, some experimental tests are presented.


Author(s):  
Weitao Chen ◽  
Shenhai Ran ◽  
Canhui Wu ◽  
Bengt Jacobson

AbstractCo-simulation is widely used in the industry for the simulation of multidomain systems. Because the coupling variables cannot be communicated continuously, the co-simulation results can be unstable and inaccurate, especially when an explicit parallel approach is applied. To address this issue, new coupling methods to improve the stability and accuracy have been developed in recent years. However, the assessment of their performance is sometimes not straightforward or is even impossible owing to the case-dependent effect. The selection of the coupling method and its tuning cannot be performed before running the co-simulation, especially with a time-varying system.In this work, the co-simulation system is analyzed in the frequency domain as a sampled-data interconnection. Then a new coupling method based on the H-infinity synthesis is developed. The method intends to reconstruct the coupling variable by adding a compensator and smoother at the interface and to minimize the error from the sample-hold process. A convergence analysis in the frequency domain shows that the coupling error can be reduced in a wide frequency range, which implies good robustness. The new method is verified using two co-simulation cases. The first case is a dual mass–spring–damper system with random parameters and the second case is a co-simulation of a multibody dynamic (MBD) vehicle model and an electric power-assisted steering (EPAS) system model. Experimental results show that the method can improve the stability and accuracy, which enables a larger communication step to speed up the explicit parallel co-simulation.


2021 ◽  
Vol 11 (5) ◽  
pp. 2098
Author(s):  
Heyi Wei ◽  
Wenhua Jiang ◽  
Xuejun Liu ◽  
Bo Huang

Knowledge of the sunshine requirements of landscape plants is important information for the adaptive selection and configuration of plants for urban greening, and is also a basic attribute of plant databases. In the existing studies, the light compensation point (LCP) and light saturation point (LSP) have been commonly used to indicate the shade tolerance for a specific plant; however, these values are difficult to adopt in practice because the landscape architect does not always know what range of solar radiation is the best for maintaining plant health, i.e., normal growth and reproduction. In this paper, to bridge the gap, we present a novel digital framework to predict the sunshine requirements of landscape plants. First, the research introduces the proposed framework, which is composed of a black-box model, solar radiation simulation, and a health standard system for plants. Then, the data fitting between solar radiation and plant growth response is used to obtain the value of solar radiation at different health levels. Finally, we adopt the LI-6400XT Portable Photosynthetic System (Li-Cor Inc., Lincoln, NE, USA) to verify the stability and accuracy of the digital framework through 15 landscape plant species of a residential area in the city of Wuhan, China, and also compared and analyzed the results of other researchers on the same plant species. The results show that the digital framework can robustly obtain the values of the healthy, sub-healthy, and unhealthy levels for the 15 landscape plant species. The purpose of this study is to provide an efficient forecasting tool for large-scale surveys of plant sunshine requirements. The proposed framework will be beneficial for the adaptive selection and configuration of urban plants and will facilitate the construction of landscape plant databases in future studies.


Author(s):  
Luca Giuggioli ◽  
Zohar Neu

Noise and time delays, or history-dependent processes, play an integral part in many natural and man-made systems. The resulting interplay between random fluctuations and time non-locality are essential features of the emerging complex dynamics in non-Markov systems. While stochastic differential equations in the form of Langevin equations with additive noise for such systems exist, the corresponding probabilistic formalism is yet to be developed. Here we introduce such a framework via an infinite hierarchy of coupled Fokker–Planck equations for the n -time probability distribution. When the non-Markov Langevin equation is linear, we show how the hierarchy can be truncated at n  = 2 by converting the time non-local Langevin equation to a time-local one with additive coloured noise. We compare the resulting Fokker–Planck equations to an earlier version, solve them analytically and analyse the temporal features of the probability distributions that would allow to distinguish between Markov and non-Markov features. This article is part of the theme issue ‘Nonlinear dynamics of delay systems’.


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