A form of the Euler equations preserving potential flow

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/77316/1/AIAA-1999-3280-269.pd

Transforming Energy Networks via Peer to Peer Energy Trading: Potential of Game Theoretic Approaches

Peer-to-peer (P2P) energy trading has emerged as a next-generation energy management mechanism for the smart grid that enables each prosumer of the network to participate in energy trading with one another and the grid. This poses a significant challenge in terms of modeling the decision-making process of each participant with conflicting interest and motivating prosumers to participate in energy trading and to cooperate, if necessary, for achieving different energy management goals. Therefore, such decision-making process needs to be built on solid mathematical and signal processing tools that can ensure an efficient operation of the smart grid. This paper provides an overview of the use of game theoretic approaches for P2P energy trading as a feasible and effective means of energy management. As such, we discuss various games and auction theoretic approaches by following a systematic classification to provide information on the importance of game theory for smart energy research. Then, the paper focuses on the P2P energy trading describing its key features and giving an introduction to an existing P2P testbed. Further, the paper zooms into the detail of some specific game and auction theoretic models that have recently been used in P2P energy trading and discusses some important finding of these schemes.Comment: 38 pages, single column, double spac

A third-order fluctuation splitting scheme that preserves potential flow

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/76630/1/AIAA-2001-2595-100.pd

Automatic detection of equiaxed dendrites using computer vision neural networks

Equaixed dendrites are frequently encountered in solidification. They typically form in large numbers, which makes their detection, localization, and tracking practically impossible for a human eye. In this paper, we show how recent progress in the field of machine learning can be leveraged to tackle this problem and we present computer vision neural network to automatically detect equiaxed dendrites. Our network is trained using phase-field simulation results, and proper data augmentation allows to perform the detection task in solidification conditions entirely different from those simulated for training. For example, here we show how they can successfully detect dendrites of various sizes in a microgravity solidification experiment. We discuss challenges in training such a network along with our solutions for them, and compare the performance of neural network with traditional methods of shapes detection

Fragile three-dimensionality in the quasi-one-dimensional cuprate PrBa_2Cu_4O_8

In this article we report on the experimental realization of dimensional crossover phenomena in the chain compound PrBa$_2$Cu$_4$O$_8$ using temperature, high magnetic fields and disorder as independent tuning parameters. In purer crystals of PrBa$_2$Cu$_4$O$_8$, a highly anisotropic three-dimensional Fermi-liquid state develops at low temperatures. This metallic state is extremely susceptible to disorder however and localization rapidly sets in. We show, through quantitative comparison of the relevant energy scales, that this metal/insulator crossover occurs precisely when the scattering rate within the chain exceeds the interchain hopping rate(s), i.e. once carriers become confined to a single conducting element.Comment: 12 pages, 5 figures, published at http://www.iop.org/EJ/article/1367-2630/8/9/172/njp6_9_172.htm

Irradiation-induced confinement in a quasi-one-dimensional metal

The anisotropic resistivity of PrBa$_2$Cu$_4$O$_8$ has been measured as a function of electron irradiation fluence. Localization effects are observed for extremely small amounts of disorder corresponding to electron mean-free-paths of order 100 unit cells. Estimates of the localization corrections suggest that this anomalous localization threshold heralds a crossover to a ground state with pronounced one-dimensional character in which conduction electrons become confined to a small cluster of chains.Comment: 4 pages, 4 figure

Impact of Demand-Response on the Efficiency and Prices in Real-Time Electricity Markets

International audienceWe study the effect of Demand-Response (DR) in dynamic real-time electricity markets. We use a two-stage market model that takes into account the dynamical aspects of gen-eration, demand, and DR. We study the real-time market prices in two scenarios: in the former, consumers anticipate or delay their flexible loads in reaction to market prices; in the latter, the flexible loads are controlled by an independent aggregator. For both scenarios, we show that, when users are price-takers, any competitive equilibrium is efficient: the players' selfish responses to prices coincide with a socially optimal policy. Moreover, the price process is the same in all scenarios. For the numerical evaluation of the properties of the equilibrium, we develop a solution technique based on the Alternating Direction Method of Multipliers (ADMM) and trajectorial forecasts. The forecasts are computed us-ing wind generation data from the UK. We challenge the assumption that all players have full information. If the as-sumption is verified, then, as expected, the social welfare increases with the amount of DR available, since DR relaxes the ramping constraints of generation. However, if the day-ahead market cannot observe how elastic loads are affected by DR, a large quantity of DR can be detrimental and leads to a decrease in the welfare. Furthermore, the DR operator has an incentive to under-dimension the quantity of avail-able DR. Finally, we compare DR with an actual energy storage system. We find that storage has a faster response-time and thus performs better when only a limited amount is installed. However, storage suffers from charge-discharge in-efficiency: with DR, prices do concentrate on marginal cost (for storage, they do not) and provide a better welfare

Antibacterial potential of Saussurea obvallata petroleum ether extract: A spiritually revered medicinal plant

Uttarakhand Himalayan region holds Asteraceae or Compositae as the largest family of flowering, medicinal and aromatic plants. Species belonging to this family rises from low altitude to the alpine region. Among Asteraceae, Saussurea obvallata (DC.) Edgew. is widely used in several indigenous systems of medicine. Flowers, leaves and rhizomes of S. obvallata are used for several traditional, religious, therapeutic and ornamental purposes. Aim of this study was to determine the chemical composition and antibacterial efficacy of petroleum ether extract (PEE) of S. obvallata. Gas chromatography-mass spectrometry (GC-MS) analysis was used for identifying phytochemicals present in the plant extract. Furthermore, the PEE was assessed for in-vitro antibacterial activity against selected Gram positive and negative strains. Structure of squalene and \u3b1-linolenic acid methyl ester were identified in PEE by GC-MS analysis, by comparing the results obtained with NIST library and literature reports. PEE exhibited significant activity against Staphylococcus aureus, Escherichia coli, Bacillus cereus, Bacillus subtilis with IC50 value of 87.2 \ub1 1.6, 98.4 \ub1 1.1 and 90.2 \ub1 1.8 \u3bcg/ml, respectively. These results showed that squalene and a-linolenic acid derivative identified in S. obvallata may be responsible for the observed antibacterial activity. To the best of our knowledge, this is the first report focused on the chemical composition and antibacterial activity of S. obvallata