An advanced meshless method for time fractional diffusion equation

Recently, because of the new developments in sustainable engineering and renewable energy, which are usually governed by a series of fractional partial differential equations (FPDEs), the numerical modelling and simulation for fractional calculus are attracting more and more attention from researchers. The current dominant numerical method for modeling FPDE is Finite Difference Method (FDM), which is based on a pre-defined grid leading to inherited issues or shortcomings including difficulty in simulation of problems with the complex problem domain and in using irregularly distributed nodes. Because of its distinguished advantages, the meshless method has good potential in simulation of FPDEs. This paper aims to develop an implicit meshless collocation technique for FPDE. The discrete system of FPDEs is obtained by using the meshless shape functions and the meshless collocation formulation. The stability and convergence of this meshless approach are investigated theoretically and numerically. The numerical examples with regular and irregular nodal distributions are used to validate and investigate accuracy and efficiency of the newly developed meshless formulation. It is concluded that the present meshless formulation is very effective for the modeling and simulation of fractional partial differential equations

Active optical clock based on four-level quantum system

Active optical clock, a new conception of atomic clock, has been proposed recently. In this report, we propose a scheme of active optical clock based on four-level quantum system. The final accuracy and stability of two-level quantum system are limited by second-order Doppler shift of thermal atomic beam. To three-level quantum system, they are mainly limited by light shift of pumping laser field. These limitations can be avoided effectively by applying the scheme proposed here. Rubidium atom four-level quantum system, as a typical example, is discussed in this paper. The population inversion between $6S_{1/2}$ and $5P_{3/2}$ states can be built up at a time scale of $10^{-6}$s. With the mechanism of active optical clock, in which the cavity mode linewidth is much wider than that of the laser gain profile, it can output a laser with quantum-limited linewidth narrower than 1 Hz in theory. An experimental configuration is designed to realize this active optical clock.Comment: 5 page

Deconfinement Phase Transition in an Expanding Quark system in Relaxation Time Approximation

We investigated the effects of nonequilibrium and collision terms on the deconfinement phase transition of an expanding quark system in Friedberg-Lee model in relaxation time approximation. By calculating the effective quark potential, the critical temperature of the phase transition is dominated by the mean field, while the collisions among quarks and mesons change the time structure of the phase transition significantly.Comment: 7 pages, 7 figure

The 7-channel FIR HCN Interferometer on J-TEXT Tokamak

A seven-channel far-infrared hydrogen cyanide (HCN) laser interferometer has been established aiming to provide the line integrated plasma density for the J-TEXT experimental scenarios. A continuous wave glow discharge HCN laser designed with a cavity length 3.4 m is used as the laser source with a wavelength of 337 {\mu}m and an output power up to 100 mW. The system is configured as a Mach-Zehnder type interferometer. Phase modulation is achieved by a rotating grating, with a modulation frequency of 10 kHz which corresponds to the temporal resolution of 0.1 ms. The beat signal is detected by TGS detector. The phase shift induced by the plasma is derived by the comparator with a phase sensitivity of 0.06 fringe. The experimental results measured by the J-TEXT interferometer are presented in details. In addition, the inversed electron density profile done by a conventional approach is also given. The kinematic viscosity of dimethyl silicone and vibration control is key issues for the system performance. The laser power stability under different kinematic viscosity of silicone oil is presented. A visible improvement of measured result on vibration reduction is shown in the paper.Comment: conference (15th-International Symposium on Laser-Aided Plasma Diagnostics

Modeling and simulating of reservoir operation using the artificial neural network, support vector regression, deep learning algorithm

Reservoirs and dams are vital human-built infrastructures that play essential roles in flood control, hydroelectric power generation, water supply, navigation, and other functions. The realization of those functions requires efficient reservoir operation, and the effective controls on the outflow from a reservoir or dam. Over the last decade, artificial intelligence (AI) techniques have become increasingly popular in the field of streamflow forecasts, reservoir operation planning and scheduling approaches. In this study, three AI models, namely, the backpropagation (BP) neural network, support vector regression (SVR) technique, and long short-term memory (LSTM) model, are employed to simulate reservoir operation at monthly, daily, and hourly time scales, using approximately 30 years of historical reservoir operation records. This study aims to summarize the influence of the parameter settings on model performance and to explore the applicability of the LSTM model to reservoir operation simulation. The results show the following: (1) for the BP neural network and LSTM model, the effects of the number of maximum iterations on model performance should be prioritized; for the SVR model, the simulation performance is directly related to the selection of the kernel function, and sigmoid and RBF kernel functions should be prioritized; (2) the BP neural network and SVR are suitable for the model to learn the operation rules of a reservoir from a small amount of data; and (3) the LSTM model is able to effectively reduce the time consumption and memory storage required by other AI models, and demonstrate good capability in simulating low-flow conditions and the outflow curve for the peak operation period

Permafrost, Lakes, and Climate-Warming Methane Feedback: What is the Worst We Can Expect?

http://globalchange.mit.edu/research/publications/2275Permafrost degradation is likely enhanced by climate warming. Subsequent landscape subsidence and hydrologic changes support expansion of lakes and wetlands. Their anaerobic environments can act as strong emission sources of methane and thus represent a positive feedback to climate warming. Using an integrated earth-system model framework, which considers the range of policy and uncertainty in climatechange projections, we examine the influence of near-surface permafrost thaw on the prevalence of lakes, its subsequent methane emission, and potential feedback under climate warming. We find that increases in atmospheric CH4 and radiative forcing from increased lake CH4 emissions are small, particularly when weighed against unconstrained human emissions. The additional warming from these methane sources, across the range of climate policy and response, is no greater than 0.1 C by 2100. Further, for this temperature feedback to be discernable by 2100 would require at least an order of magnitude larger methaneemission response. Overall, the biogeochemical climate-warming feedback from boreal and Arctic lake emissions is relatively small whether or not humans choose to constrain global emissions.This work was supported under the Department of Energy Climate Change Prediction Program Grant DE-PS02-08ER08-05. The authors gratefully acknowledge this as well as additional financial support provided by the MIT Joint Program on the Science and Policy of Global Change through a consortium of industrial sponsors and Federal grants. Development of the IGSM applied in this research is supported by the U.S. Department of Energy, Office of Science (DE-FG02-94ER61937); the U.S. Environmental Protection Agency, EPRI, and other U.S. government agencies and a consortium of 40 industrial and foundation sponsors