Sharif Digital Repository

The Kardar-Parisi-Zhang (KPZ) equation in (1 + 1) dimensions dynamically develops sharply connected valley structures within which the height derivative is not continuous. We develop a statistical theory for the KPZ equation in (1 + 1) dimensions driven with a random forcing that is white in time and Gaussian-correlated in space. A master equation is derived for the joint probability density function of height difference and height gradient P(h-h̄,∂xh,t) when the forcing correlation length is much smaller than the system size and much larger than the typical sharp valley width. In the time scales before the creation of the sharp valleys, we find the exact generating function of h-h̄ and ∂xh.... 

The Kardar-Parisi-Zhang (KPZ) equation in [formula presented] dimensions dynamically develops sharply connected valley structures within which the height derivative is not continuous. We develop a statistical theory for the KPZ equation in [formula presented] dimensions driven with a random forcing that is white in time and Gaussian-correlated in space. A master equation is derived for the joint probability density function of height difference and height gradient [formula presented] when the forcing correlation length is much smaller than the system size and much larger than the typical sharp valley width. In the time scales before the creation of the sharp valleys, we find the exact... 

We introduce a method by which stochastic processes are mapped onto complex networks. As examples, we construct the networks for such time series as those for free-jet and low-temperature helium turbulence, the German stock market index (the DAX), and white noise. The networks are further studied by contrasting their geometrical properties, such as the mean length, diameter, clustering, and average number of connections per node. By comparing the network properties of the original time series investigated with those for the shuffled and surrogate series, we are able to quantify the effect of the long-range correlations and the fatness of the probability distribution functions of the series... 

With the advent of small-scale heat and electricity producers in distribution energy systems, the interdependencies between energy carriers have been increased. Moreover, the rapid deployment of micro CHP, electric heat pumps, electricity-to-heat appliances etc., calls for new local market frameworks to be employed in distribution energy systems. In response, this paper presents a new energy market framework based on the concept of peer-to-peer negotiations to facilitate energy transactions between agents at the distribution level while addressing the interdependencies between different energy carriers. Moreover, linear optimization problems are proposed to investigate the optimal strategies... 

Space constraint is a limiting factor for the widespread commercial adaptation of switched reluctance generators (SRGs). Maximizing the output power and minimizing the dc bus filter size are thus highly desired. The output power profiles of a typical SRG are determined by applying various excitation angles. Excitation for maximum output power is obtained while limiting the rms value of the phase currents. The dc bus current of an SRG drive, operating in single pulse mode, is highly distorted by low-frequency ripples. Introducing a freewheeling angle in the excitation pattern can lower the current ripple factor. A novel transform is proposed to establish a relationship between the... 

The rapid deployment of district heating systems in local energy markets and increasing the number of small-scale heat producers along with the expansion of local electricity markets increase the need for a transaction framework to manage the transactions between local participants in both heat and electricity markets. This paper presents a peer-to-peer thermal energy transaction framework to manage the transactions between small-scale heat prosumers. This framework enables small-scale thermal energy producers and consumers to participate in the market as price maker agents. Moreover, the optimal strategy of heat market participants is determined by proposing a linear profit function for... 

Proliferation of Plug-in Hybrid Electric Vehicles (PHEVs) and integration of various distributed generation (DG) technologies have been recognized to play an undeniable role in modern power systems of the future. In order to effectively model the interactions of these two technologies, this paper develops a multi-criteria framework to coordinate the charging behaviors of PHEVs within an energy hub platform. In this regard, the desirable charging profiles from the viewpoint of both PHEV owners and hub manager are first captured and reported to the PHEVs Coordinator Entity (PCE). The PCE, then, runs an optimization framework in which several criteria including the PHEV owners’ convenience,... 

Reinforcement learning (RL) is a subset of artificial intelligence in which a decision-making agent tries to act optimally in an environment by controlling different parameters. There is no need to identify and mathematically formulate the environmental constraints in such a method. Moreover, the RL agent does not need prior information about future outcomes to act optimally in the current situation. However, its performance is adversely affected by the environmental complexity, which increases the agent's effort to choose the optimal action in a particular condition. Integrating RL and linear programming (LP) methods is beneficial to tackle this problem as it reduces the state-action space... 

This paper proposes a new experimental procedure for magnetic characterization of switched reluctance machines. In the existing methods, phase voltage and current data are captured and further processed to find the flux linkage. Conventionally, assuming zero initial flux value, the flux linkage can be found by integrating the corresponding voltage term. However, the initial flux value is usually unknown, e.g., it can be nonzero when the current is zero due to the residual flux effect, and, thus, imposes error in magnetic characterization. The proposed method addresses this issue by considering an additional equation in steady state. This method injects a low-frequency sinusoidal current to... 

Using the potential of off-grid photovoltaic systems is a feasible way to supply electrical energy to locations which are far from the national electricity grid. In the design process of these systems, it is important to choose an appropriate capacity of these panels, since it should be able to steadily supply energy in all-weather conditions, especially cloudy days. In the conventional algorithm to design these panels and determine the capacity of these photovoltaic arrays, the number of cloudy days is not considered. Thus, in this papers, a new method is introduced in order to find out the appropriate capacity of off-grid photovoltaic arrays in the planning process of these systems. © 2019... 

With the increasing rate of population in big cities around the world, the tendency to build new buildings in the suburb of main cities or to build large apartments in the main cities has been highlighted. In this regard, building residential complexes has seen a dramatic increase in these areas as it makes it possible to build a large number of residential units within a reasonable space. Although these complexes have brought numerous benefits, they are some challenges regarding their construction processes. One main concern associated with these complexes is how to optimally install energy components such as transformers, combined heat and power (CHP) units, boilers etc., in the shared... 

By detailed analytical treatment of the shock dynamics in the Burgers turbulence with large scale forcing we calculate the velocity structure functions between pairs of points displaced both in time and space. Our analytical treatment verifies the so-called Taylor's frozen-flow hypothesis without relying on any closure and under very general assumptions. We discuss the limitation of the hypothesis and show that it is valid up to time scales smaller than the correlation time scale of temporal velocity correlation function. We support the analytical calculation by performing numerical simulation of the periodically kicked Burgers equation. © 2008 The American Physical Society  

The stochastic φ4-theory in d dimensions dynamically develops domain wall structures within which the order parameter is not continuous. We develop a statistical theory for the φ4-theory driven with a random forcing which is white in time and Gaussian-correlated in space. A master equation is derived for the probability density function (PDF) of the order parameter, when the forcing correlation length is much smaller than the system size, but much larger than the typical width of the domain walls. Moreover, exact expressions for the one-point PDF and all the moments 〈 φn 〉 are given. We then investigate the intermittency issue in the strong coupling limit, and derive the tail of the PDF of... 

A screw dislocation outside an infinite cylindrical nano-inhomogeneity of circular cross section is considered within the isotropic theory of gradient elasticity. Fields of total displacements, elastic and plastic distortions, elastic strains and stresses are derived and analyzed in detail. In contrast with the case of classical elasticity, the gradient solutions are shown to possess no singularities at the dislocation line. Moreover, all stress components are continuous and smooth at the interface unlike the classical solution. As a result, the image force exerted on the dislocation due to the differences in elastic and gradient constants of the matrix and inhomogeneity, remains finite when...