Alternative Fuels Data Center: Electric Vehicle Charging Network Expands at

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Basic Principles of Electrical Network Reliability Optimization in Liberalised Electricity Market

NASA Astrophysics Data System (ADS)

Oleinikova, I.; Krishans, Z.; Mutule, A.

2008-01-01

The authors propose to select long-term solutions to the reliability problems of electrical networks in the stage of development planning. The guide lines or basic principles of such optimization are: 1) its dynamical nature; 2) development sustainability; 3) integrated solution of the problems of network development and electricity supply reliability; 4) consideration of information uncertainty; 5) concurrent consideration of the network and generation development problems; 6) application of specialized information technologies; 7) definition of requirements for independent electricity producers. In the article, the major aspects of liberalized electricity market, its functions and tasks are reviewed, with emphasis placed on the optimization of electrical network development as a significant component of sustainable management of power systems.

Geometric properties-dependent neural synchrony modulated by extracellular subthreshold electric field

NASA Astrophysics Data System (ADS)

Wei, Xile; Si, Kaili; Yi, Guosheng; Wang, Jiang; Lu, Meili

2016-07-01

In this paper, we use a reduced two-compartment neuron model to investigate the interaction between extracellular subthreshold electric field and synchrony in small world networks. It is observed that network synchronization is closely related to the strength of electric field and geometric properties of the two-compartment model. Specifically, increasing the electric field induces a gradual improvement in network synchrony, while increasing the geometric factor results in an abrupt decrease in synchronization of network. In addition, increasing electric field can make the network become synchronous from asynchronous when the geometric parameter is set to a given value. Furthermore, it is demonstrated that network synchrony can also be affected by the firing frequency and dynamical bifurcation feature of single neuron. These results highlight the effect of weak field on network synchrony from the view of biophysical model, which may contribute to further understanding the effect of electric field on network activity.

Alternative Fuels Data Center: New York Broadens Network for Electric

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Global Electricity Trade Network: Structures and Implications

PubMed Central

Ji, Ling; Jia, Xiaoping; Chiu, Anthony S. F.; Xu, Ming

2016-01-01

Nations increasingly trade electricity, and understanding the structure of the global power grid can help identify nations that are critical for its reliability. This study examines the global grid as a network with nations as nodes and international electricity trade as links. We analyze the structure of the global electricity trade network and find that the network consists of four sub-networks, and provide a detailed analysis of the largest network, Eurasia. Russia, China, Ukraine, and Azerbaijan have high betweenness measures in the Eurasian sub-network, indicating the degrees of centrality of the positions they hold. The analysis reveals that the Eurasian sub-network consists of seven communities based on the network structure. We find that the communities do not fully align with geographical proximity, and that the present international electricity trade in the Eurasian sub-network causes an approximately 11 million additional tons of CO2 emissions. PMID:27504825

Global Electricity Trade Network: Structures and Implications.

PubMed

Ji, Ling; Jia, Xiaoping; Chiu, Anthony S F; Xu, Ming

2016-01-01

Nations increasingly trade electricity, and understanding the structure of the global power grid can help identify nations that are critical for its reliability. This study examines the global grid as a network with nations as nodes and international electricity trade as links. We analyze the structure of the global electricity trade network and find that the network consists of four sub-networks, and provide a detailed analysis of the largest network, Eurasia. Russia, China, Ukraine, and Azerbaijan have high betweenness measures in the Eurasian sub-network, indicating the degrees of centrality of the positions they hold. The analysis reveals that the Eurasian sub-network consists of seven communities based on the network structure. We find that the communities do not fully align with geographical proximity, and that the present international electricity trade in the Eurasian sub-network causes an approximately 11 million additional tons of CO2 emissions.

Robust network data envelopment analysis approach to evaluate the efficiency of regional electricity power networks under uncertainty.

PubMed

Fathollah Bayati, Mohsen; Sadjadi, Seyed Jafar

2017-01-01

In this paper, new Network Data Envelopment Analysis (NDEA) models are developed to evaluate the efficiency of regional electricity power networks. The primary objective of this paper is to consider perturbation in data and develop new NDEA models based on the adaptation of robust optimization methodology. Furthermore, in this paper, the efficiency of the entire networks of electricity power, involving generation, transmission and distribution stages is measured. While DEA has been widely used to evaluate the efficiency of the components of electricity power networks during the past two decades, there is no study to evaluate the efficiency of the electricity power networks as a whole. The proposed models are applied to evaluate the efficiency of 16 regional electricity power networks in Iran and the effect of data uncertainty is also investigated. The results are compared with the traditional network DEA and parametric SFA methods. Validity and verification of the proposed models are also investigated. The preliminary results indicate that the proposed models were more reliable than the traditional Network DEA model.

Robust network data envelopment analysis approach to evaluate the efficiency of regional electricity power networks under uncertainty

PubMed Central

Sadjadi, Seyed Jafar

2017-01-01

In this paper, new Network Data Envelopment Analysis (NDEA) models are developed to evaluate the efficiency of regional electricity power networks. The primary objective of this paper is to consider perturbation in data and develop new NDEA models based on the adaptation of robust optimization methodology. Furthermore, in this paper, the efficiency of the entire networks of electricity power, involving generation, transmission and distribution stages is measured. While DEA has been widely used to evaluate the efficiency of the components of electricity power networks during the past two decades, there is no study to evaluate the efficiency of the electricity power networks as a whole. The proposed models are applied to evaluate the efficiency of 16 regional electricity power networks in Iran and the effect of data uncertainty is also investigated. The results are compared with the traditional network DEA and parametric SFA methods. Validity and verification of the proposed models are also investigated. The preliminary results indicate that the proposed models were more reliable than the traditional Network DEA model. PMID:28953900

Design principles of electrical synaptic plasticity.

PubMed

O'Brien, John

2017-09-08

Essentially all animals with nervous systems utilize electrical synapses as a core element of communication. Electrical synapses, formed by gap junctions between neurons, provide rapid, bidirectional communication that accomplishes tasks distinct from and complementary to chemical synapses. These include coordination of neuron activity, suppression of voltage noise, establishment of electrical pathways that define circuits, and modulation of high order network behavior. In keeping with the omnipresent demand to alter neural network function in order to respond to environmental cues and perform tasks, electrical synapses exhibit extensive plasticity. In some networks, this plasticity can have dramatic effects that completely remodel circuits or remove the influence of certain cell types from networks. Electrical synaptic plasticity occurs on three distinct time scales, ranging from milliseconds to days, with different mechanisms accounting for each. This essay highlights principles that dictate the properties of electrical coupling within networks and the plasticity of the electrical synapses, drawing examples extensively from retinal networks. Copyright © 2017 The Author. Published by Elsevier B.V. All rights reserved.

Electrical Mapping of Silver Nanowire Networks: A Versatile Tool for Imaging Network Homogeneity and Degradation Dynamics during Failure.

PubMed

Sannicolo, Thomas; Charvin, Nicolas; Flandin, Lionel; Kraus, Silas; Papanastasiou, Dorina T; Celle, Caroline; Simonato, Jean-Pierre; Muñoz-Rojas, David; Jiménez, Carmen; Bellet, Daniel

2018-05-22

Electrical stability and homogeneity of silver nanowire (AgNW) networks are critical assets for increasing their robustness and reliability when integrated as transparent electrodes in devices. Our ability to distinguish defects, inhomogeneities, or inactive areas at the scale of the entire network is therefore a critical issue. We propose one-probe electrical mapping (1P-mapping) as a specific simple tool to study the electrical distribution in these discrete structures. 1P-mapping has allowed us to show that the tortuosity of the voltage equipotential lines of AgNW networks under bias decreases with increasing network density, leading to a better electrical homogeneity. The impact of the network fabrication technique on the electrical homogeneity of the resulting electrode has also been investigated. Then, by combining 1P-mapping with electrical resistance measurements and IR thermography, we propose a comprehensive analysis of the evolution of the electrical distribution in AgNW networks when subjected to increasing voltage stresses. We show that AgNW networks experience three distinctive stages: optimization, degradation, and breakdown. We also demonstrate that the failure dynamics of AgNW networks at high voltages occurs through a highly correlated and spatially localized mechanism. In particular the in situ formation of cracks could be clearly visualized. It consists of two steps: creation of a crack followed by propagation nearly parallel to the equipotential lines. Finally, we show that current can dynamically redistribute during failure, by following partially damaged secondary pathways through the crack.

60-Hz electric and magnetic fields generated by a distribution network.

PubMed

Héroux, P

1987-01-01

From a mobile unit, 60-Hz electric and magnetic fields generated by Hydro-Québec's distribution network were measured. Nine runs, representative of various human environments, were investigated. Typical values were 32 V/m and 0.16 microT. The electrical distribution networks investigated were major contributors to the electric and magnetic environments.

Analysis of the energy efficiency of the implementation power electric generated modules in the CHS

NASA Astrophysics Data System (ADS)

Sukhikh, A. A.; Milyutin, V. A.; Lvova, A. M.

2017-11-01

Application on the Central heat source (CHS) local generation of electricity is primarily aimed at solving problems of own needs of electric energy that not only guarantees the independence of the work of the CHS from external electrical networks, but will prevent the stop of heat supply of consumers and defrosting heating networks in case of accidents in electrical networks caused by natural or anthropogenic factors. Open the prospects of electric power supply stand-alone objects, such commercial or industrial objects on the territory of a particular neighborhood.

ROLE OF THE NETWORK FORMER IN SEMICONDUCTING OXIDE GLASSES.

DTIC Science & Technology

SEMICONDUCTOR DEVICES, * GLASS ), (*ELECTRICAL NETWORKS, GLASS ), ELECTRICAL PROPERTIES, SEEBECK EFFECT, BORATES, PHOSPHATES, ELECTRICAL RESISTANCE, X RAY DIFFRACTION, ANNEALING, OXIDATION, OXIDES, ELECTRODES, VANADIUM

Effects of Electrical and Optogenetic Deep Brain Stimulation on Synchronized Oscillatory Activity in Parkinsonian Basal Ganglia.

PubMed

Ratnadurai-Giridharan, Shivakeshavan; Cheung, Chung C; Rubchinsky, Leonid L

2017-11-01

Conventional deep brain stimulation of basal ganglia uses high-frequency regular electrical pulses to treat Parkinsonian motor symptoms but has a series of limitations. Relatively new and not yet clinically tested, optogenetic stimulation is an effective experimental stimulation technique to affect pathological network dynamics. We compared the effects of electrical and optogenetic stimulation of the basal gangliaon the pathologicalParkinsonian rhythmic neural activity. We studied the network response to electrical stimulation and excitatory and inhibitory optogenetic stimulations. Different stimulations exhibit different interactions with pathological activity in the network. We studied these interactions for different network and stimulation parameter values. Optogenetic stimulation was found to be more efficient than electrical stimulation in suppressing pathological rhythmicity. Our findings indicate that optogenetic control of neural synchrony may be more efficacious than electrical control because of the different ways of how stimulations interact with network dynamics.

Application of Artificial Neural Networks in the Heart Electrical Axis Position Conclusion Modeling

NASA Astrophysics Data System (ADS)

Bakanovskaya, L. N.

2016-08-01

The article touches upon building of a heart electrical axis position conclusion model using an artificial neural network. The input signals of the neural network are the values of deflections Q, R and S; and the output signal is the value of the heart electrical axis position. Training of the network is carried out by the error propagation method. The test results allow concluding that the created neural network makes a conclusion with a high degree of accuracy.

Virtual CO2 Emission Flows in the Global Electricity Trade Network.

PubMed

Qu, Shen; Li, Yun; Liang, Sai; Yuan, Jiahai; Xu, Ming

2018-06-05

Quantifying greenhouse gas emissions due to electricity consumption is crucial for climate mitigation in the electric power sector. Current practices primarily use production-based emission factors to quantify emissions for electricity consumption, assuming production and consumption of electricity take place within the same region. The increasingly intensified cross-border electricity trade complicates the accounting for emissions of electricity consumption. This study employs a network approach to account for the flows in the whole electricity trade network to estimate CO 2 emissions of electricity consumption for 137 major countries/regions in 2014. Results show that in some countries, especially those in Europe and Southern Africa, the impacts of electricity trade on the estimation of emission factors and embodied emissions are significant. The changes made to emission factors by considering intergrid electricity trade can have significant implications for emission accounting and climate mitigation when multiplied by total electricity consumption of the corresponding countries/regions.

Evaluating North American Electric Grid Reliability Using the Barabasi-Albert Network Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chassin, David P.; Posse, Christian

2005-09-15

The reliability of electric transmission systems is examined using a scale-free model of network topology and failure propagation. The topologies of the North American eastern and western electric grids are analyzed to estimate their reliability based on the Barabási-Albert network model. A commonly used power system reliability index is computed using a simple failure propagation model. The results are compared to the values of power system reliability indices previously obtained using other methods and they suggest that scale-free network models are usable to estimate aggregate electric grid reliability.

Evaluating North American Electric Grid Reliability Using the Barabasi-Albert Network Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chassin, David P.; Posse, Christian

2005-09-15

The reliability of electric transmission systems is examined using a scale-free model of network topology and failure propagation. The topologies of the North American eastern and western electric grids are analyzed to estimate their reliability based on the Barabasi-Albert network model. A commonly used power system reliability index is computed using a simple failure propagation model. The results are compared to the values of power system reliability indices previously obtained using standard power engineering methods, and they suggest that scale-free network models are usable to estimate aggregate electric grid reliability.

Design of pressure-driven microfluidic networks using electric circuit analogy.

PubMed

Oh, Kwang W; Lee, Kangsun; Ahn, Byungwook; Furlani, Edward P

2012-02-07

This article reviews the application of electric circuit methods for the analysis of pressure-driven microfluidic networks with an emphasis on concentration- and flow-dependent systems. The application of circuit methods to microfluidics is based on the analogous behaviour of hydraulic and electric circuits with correlations of pressure to voltage, volumetric flow rate to current, and hydraulic to electric resistance. Circuit analysis enables rapid predictions of pressure-driven laminar flow in microchannels and is very useful for designing complex microfluidic networks in advance of fabrication. This article provides a comprehensive overview of the physics of pressure-driven laminar flow, the formal analogy between electric and hydraulic circuits, applications of circuit theory to microfluidic network-based devices, recent development and applications of concentration- and flow-dependent microfluidic networks, and promising future applications. The lab-on-a-chip (LOC) and microfluidics community will gain insightful ideas and practical design strategies for developing unique microfluidic network-based devices to address a broad range of biological, chemical, pharmaceutical, and other scientific and technical challenges.

Self-assembled tunable networks of sticky colloidal particles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Demortiere, Arnaud; Snezhko, Oleksiy Alexey; Sapozhnikov, Maksim

Self-assembled tunable networks of microscopic polymer fibers ranging from wavy colloidal "fur" to highly interconnected networks are created from polymer systems and an applied electric field. The networks emerge via dynamic self-assembly in an alternating (ac) electric field from a non-aqueous suspension of "sticky" polymeric colloidal particles with a controlled degree of polymerization. The resulting architectures are tuned by the frequency and amplitude of the electric field and surface properties of the particles.

Stochastic resonance enhancement of small-world neural networks by hybrid synapses and time delay

NASA Astrophysics Data System (ADS)

Yu, Haitao; Guo, Xinmeng; Wang, Jiang

2017-01-01

The synergistic effect of hybrid electrical-chemical synapses and information transmission delay on the stochastic response behavior in small-world neuronal networks is investigated. Numerical results show that, the stochastic response behavior can be regulated by moderate noise intensity to track the rhythm of subthreshold pacemaker, indicating the occurrence of stochastic resonance (SR) in the considered neural system. Inheriting the characteristics of two types of synapses-electrical and chemical ones, neural networks with hybrid electrical-chemical synapses are of great improvement in neuron communication. Particularly, chemical synapses are conducive to increase the network detectability by lowering the resonance noise intensity, while the information is better transmitted through the networks via electrical coupling. Moreover, time delay is able to enhance or destroy the periodic stochastic response behavior intermittently. In the time-delayed small-world neuronal networks, the introduction of electrical synapses can significantly improve the signal detection capability by widening the range of optimal noise intensity for the subthreshold signal, and the efficiency of SR is largely amplified in the case of pure chemical couplings. In addition, the stochastic response behavior is also profoundly influenced by the network topology. Increasing the rewiring probability in pure chemically coupled networks can always enhance the effect of SR, which is slightly influenced by information transmission delay. On the other hand, the capacity of information communication is robust to the network topology within the time-delayed neuronal systems including electrical couplings.

Prediction of Industrial Electric Energy Consumption in Anhui Province Based on GA-BP Neural Network

NASA Astrophysics Data System (ADS)

Zhang, Jiajing; Yin, Guodong; Ni, Youcong; Chen, Jinlan

2018-01-01

In order to improve the prediction accuracy of industrial electrical energy consumption, a prediction model of industrial electrical energy consumption was proposed based on genetic algorithm and neural network. The model use genetic algorithm to optimize the weights and thresholds of BP neural network, and the model is used to predict the energy consumption of industrial power in Anhui Province, to improve the prediction accuracy of industrial electric energy consumption in Anhui province. By comparing experiment of GA-BP prediction model and BP neural network model, the GA-BP model is more accurate with smaller number of neurons in the hidden layer.

Robustness of a multimodal piezoelectric damping involving the electrical analogue of a plate

NASA Astrophysics Data System (ADS)

Lossouarn, Boris; Cunefare, Kenneth A.; Aucejo, Mathieu; Deü, Jean-François

2016-04-01

Multimodal passive damping of a mechanical structure can be implemented by a coupling to a secondary structure exhibiting similar modal properties. When considering a piezoelectric coupling, the secondary structure is an electrical network. A suitable topology for such a network can be obtained by a finite difference formulation of the mechanical equations, followed by a direct electromechanical analogy. This procedure is applied to the Kirchhoff-Love theory in order to find the electrical analogue of a clamped plate. The passive electrical network is implemented with inductors, transformers and the inherent capacitance of the piezoelectric patches. The electrical resonances are tuned to approach those of several mechanical modes simultaneously. This yields a broadband reduction of the plate vibrations through the array of interconnected piezoelectric patches. The robustness of the control strategy is evaluated by introducing perturbations in the mechanical or electrical designs. A non-optimal tuning is considered by way of a uniform variation of the network inductance. Then, the effect of local or boundary modifications of the electromechanical system is observed experimentally. In the end, the use of an analogous electrical network appears as an efficient and robust solution for the multimodal control of a plate.

Multimodal vibration damping of a plate by piezoelectric coupling to its analogous electrical network

NASA Astrophysics Data System (ADS)

Lossouarn, B.; Deü, J.-F.; Aucejo, M.; Cunefare, K. A.

2016-11-01

Multimodal damping can be achieved by coupling a mechanical structure to an electrical network exhibiting similar modal properties. Focusing on a plate, a new topology for such an electrical analogue is found from a finite difference approximation of the Kirchhoff-Love theory and the use of the direct electromechanical analogy. Discrete models based on element dynamic stiffness matrices are proposed to simulate square plate unit cells coupled to their electrical analogues through two-dimensional piezoelectric transducers. A setup made of a clamped plate covered with an array of piezoelectric patches is built in order to validate the control strategy and the numerical models. The analogous electrical network is implemented with passive components as inductors, transformers and the inherent capacitance of the piezoelectric patches. The effect of the piezoelectric coupling on the dynamics of the clamped plate is significant as it creates the equivalent of a multimodal tuned mass damping. An adequate tuning of the network then yields a broadband vibration reduction. In the end, the use of an analogous electrical network appears as an efficient solution for the multimodal control of a plate.

CO2 Emissions Embodied in Interprovincial Electricity Transmissions in China.

PubMed

Qu, Shen; Liang, Sai; Xu, Ming

2017-09-19

Existing studies on the evaluation of CO 2 emissions due to electricity consumption in China are inaccurate and incomplete. This study uses a network approach to calculate CO 2 emissions of purchased electricity in Chinese provinces. The CO 2 emission factors of purchased electricity range from 265 g/kWh in Sichuan to 947 g/kWh in Inner Mongolia. We find that emission factors of purchased electricity in many provinces are quite different from the emission factors of electricity generation. This indicates the importance of the network approach in accurately reflecting embodied emissions. We also observe substantial variations of emissions factors of purchased electricity within subnational grids: the provincial emission factors deviate from the corresponding subnational-grid averages from -58% to 44%. This implies that using subnational-grid averages as required by Chinese government agencies can be quite inaccurate for reporting indirect CO 2 emissions of enterprises' purchased electricity. The network approach can improve the accuracy of the quantification of embodied emissions in purchased electricity and emission flows embodied in electricity transmission.

Endogenous Cortical Oscillations Constrain Neuromodulation by Weak Electric Fields

PubMed Central

Schmidt, Stephen L.; Iyengar, Apoorva K.; Foulser, A. Alban; Boyle, Michael R.; Fröhlich, Flavio

2014-01-01

Background Transcranial alternating current stimulation (tACS) is a non-invasive brain stimulation modality that may modulate cognition by enhancing endogenous neocortical oscillations with the application of sine-wave electric fields. Yet, the role of endogenous network activity in enabling and shaping the effects of tACS has remained unclear. Objective We combined optogenetic stimulation and multichannel slice electrophysiology to elucidate how the effect of weak sine-wave electric field depends on the ongoing cortical oscillatory activity. We hypothesized that the structure of the response to stimulation depended on matching the stimulation frequency to the endogenous cortical oscillation. Methods We studied the effect of weak sine-wave electric fields on oscillatory activity in mouse neocortical slices. Optogenetic control of the network activity enabled the generation of in vivo like cortical oscillations for studying the temporal relationship between network activity and sine-wave electric field stimulation. Results Weak electric fields enhanced endogenous oscillations but failed to induce a frequency shift of the ongoing oscillation for stimulation frequencies that were not matched to the endogenous oscillation. This constraint on the effect of electric field stimulation imposed by endogenous network dynamics was limited to the case of weak electric fields targeting in vivo-like network dynamics. Together, these results suggest that the key mechanism of tACS may be enhancing but not overriding of intrinsic network dynamics. Conclusion Our results contribute to understanding the inconsistent tACS results from human studies and propose that stimulation precisely adjusted in frequency to the endogenous oscillations is key to rational design of non-invasive brain stimulation paradigms. PMID:25129402

Synchronization properties of networks of electrically coupled neurons in the presence of noise and heterogeneities.

PubMed

Ostojic, Srdjan; Brunel, Nicolas; Hakim, Vincent

2009-06-01

We investigate how synchrony can be generated or induced in networks of electrically coupled integrate-and-fire neurons subject to noisy and heterogeneous inputs. Using analytical tools, we find that in a network under constant external inputs, synchrony can appear via a Hopf bifurcation from the asynchronous state to an oscillatory state. In a homogeneous net work, in the oscillatory state all neurons fire in synchrony, while in a heterogeneous network synchrony is looser, many neurons skipping cycles of the oscillation. If the transmission of action potentials via the electrical synapses is effectively excitatory, the Hopf bifurcation is supercritical, while effectively inhibitory transmission due to pronounced hyperpolarization leads to a subcritical bifurcation. In the latter case, the network exhibits bistability between an asynchronous state and an oscillatory state where all the neurons fire in synchrony. Finally we show that for time-varying external inputs, electrical coupling enhances the synchronization in an asynchronous network via a resonance at the firing-rate frequency.

Computational model of electrically coupled, intrinsically distinct pacemaker neurons.

PubMed

Soto-Treviño, Cristina; Rabbah, Pascale; Marder, Eve; Nadim, Farzan

2005-07-01

Electrical coupling between neurons with similar properties is often studied. Nonetheless, the role of electrical coupling between neurons with widely different intrinsic properties also occurs, but is less well understood. Inspired by the pacemaker group of the crustacean pyloric network, we developed a multicompartment, conductance-based model of a small network of intrinsically distinct, electrically coupled neurons. In the pyloric network, a small intrinsically bursting neuron, through gap junctions, drives 2 larger, tonically spiking neurons to reliably burst in-phase with it. Each model neuron has 2 compartments, one responsible for spike generation and the other for producing a slow, large-amplitude oscillation. We illustrate how these compartments interact and determine the dynamics of the model neurons. Our model captures the dynamic oscillation range measured from the isolated and coupled biological neurons. At the network level, we explore the range of coupling strengths for which synchronous bursting oscillations are possible. The spatial segregation of ionic currents significantly enhances the ability of the 2 neurons to burst synchronously, and the oscillation range of the model pacemaker network depends not only on the strength of the electrical synapse but also on the identity of the neuron receiving inputs. We also compare the activity of the electrically coupled, distinct neurons with that of a network of coupled identical bursting neurons. For small to moderate coupling strengths, the network of identical elements, when receiving asymmetrical inputs, can have a smaller dynamic range of oscillation than that of its constituent neurons in isolation.

Gross domestic product estimation based on electricity utilization by artificial neural network

NASA Astrophysics Data System (ADS)

Stevanović, Mirjana; Vujičić, Slađana; Gajić, Aleksandar M.

2018-01-01

The main goal of the paper was to estimate gross domestic product (GDP) based on electricity estimation by artificial neural network (ANN). The electricity utilization was analyzed based on different sources like renewable, coal and nuclear sources. The ANN network was trained with two training algorithms namely extreme learning method and back-propagation algorithm in order to produce the best prediction results of the GDP. According to the results it can be concluded that the ANN model with extreme learning method could produce the acceptable prediction of the GDP based on the electricity utilization.

Electrical Properties of an m × n Hammock Network

NASA Astrophysics Data System (ADS)

Tan, Zhen; Tan, Zhi-Zhong; Zhou, Ling

2018-05-01

Electrical property is an important problem in the field of natural science and physics, which usually involves potential, current and resistance in the electric circuit. We investigate the electrical properties of an arbitrary hammock network, which has not been resolved before, and propose the exact potential formula of an arbitrary m × n hammock network by means of the Recursion-Transform method with current parameters (RT-I) pioneered by one of us [Z. Z. Tan, Phys. Rev. E 91 (2015) 052122], and the branch currents and equivalent resistance of the network are derived naturally. Our key technique is to setting up matrix equations and making matrix transformation, the potential formula derived is a meaningful discovery, which deduces many novel applications. The discovery of potential formula of the hammock network provides new theoretical tools and techniques for related scientific research. Supported by the Natural Science Foundation of Jiangsu Province under Grant No. BK20161278

EMMNet: sensor networking for electricity meter monitoring.

PubMed

Lin, Zhi-Ting; Zheng, Jie; Ji, Yu-Sheng; Zhao, Bao-Hua; Qu, Yu-Gui; Huang, Xu-Dong; Jiang, Xiu-Fang

2010-01-01

Smart sensors are emerging as a promising technology for a large number of application domains. This paper presents a collection of requirements and guidelines that serve as a basis for a general smart sensor architecture to monitor electricity meters. It also presents an electricity meter monitoring network, named EMMNet, comprised of data collectors, data concentrators, hand-held devices, a centralized server, and clients. EMMNet provides long-distance communication capabilities, which make it suitable suitable for complex urban environments. In addition, the operational cost of EMMNet is low, compared with other existing remote meter monitoring systems based on GPRS. A new dynamic tree protocol based on the application requirements which can significantly improve the reliability of the network is also proposed. We are currently conducting tests on five networks and investigating network problems for further improvements. Evaluation results indicate that EMMNet enhances the efficiency and accuracy in the reading, recording, and calibration of electricity meters.

EMMNet: Sensor Networking for Electricity Meter Monitoring

PubMed Central

Lin, Zhi-Ting; Zheng, Jie; Ji, Yu-Sheng; Zhao, Bao-Hua; Qu, Yu-Gui; Huang, Xu-Dong; Jiang, Xiu-Fang

2010-01-01

Smart sensors are emerging as a promising technology for a large number of application domains. This paper presents a collection of requirements and guidelines that serve as a basis for a general smart sensor architecture to monitor electricity meters. It also presents an electricity meter monitoring network, named EMMNet, comprised of data collectors, data concentrators, hand-held devices, a centralized server, and clients. EMMNet provides long-distance communication capabilities, which make it suitable suitable for complex urban environments. In addition, the operational cost of EMMNet is low, compared with other existing remote meter monitoring systems based on GPRS. A new dynamic tree protocol based on the application requirements which can significantly improve the reliability of the network is also proposed. We are currently conducting tests on five networks and investigating network problems for further improvements. Evaluation results indicate that EMMNet enhances the efficiency and accuracy in the reading, recording, and calibration of electricity meters. PMID:22163551

System and method for islanding detection and prevention in distributed generation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bhowmik, Shibashis; Mazhari, Iman; Parkhideh, Babak

Various examples are directed to systems and methods for detecting an islanding condition at an inverter configured to couple a distributed generation system to an electrical grid network. A controller may determine a command frequency and a command frequency variation. The controller may determine that the command frequency variation indicates a potential islanding condition and send to the inverter an instruction to disconnect the distributed generation system from the electrical grid network. When the distributed generation system is disconnected from the electrical grid network, the controller may determine whether the grid network is valid.

Network meta-analysis, electrical networks and graph theory.

PubMed

Rücker, Gerta

2012-12-01

Network meta-analysis is an active field of research in clinical biostatistics. It aims to combine information from all randomized comparisons among a set of treatments for a given medical condition. We show how graph-theoretical methods can be applied to network meta-analysis. A meta-analytic graph consists of vertices (treatments) and edges (randomized comparisons). We illustrate the correspondence between meta-analytic networks and electrical networks, where variance corresponds to resistance, treatment effects to voltage, and weighted treatment effects to current flows. Based thereon, we then show that graph-theoretical methods that have been routinely applied to electrical networks also work well in network meta-analysis. In more detail, the resulting consistent treatment effects induced in the edges can be estimated via the Moore-Penrose pseudoinverse of the Laplacian matrix. Moreover, the variances of the treatment effects are estimated in analogy to electrical effective resistances. It is shown that this method, being computationally simple, leads to the usual fixed effect model estimate when applied to pairwise meta-analysis and is consistent with published results when applied to network meta-analysis examples from the literature. Moreover, problems of heterogeneity and inconsistency, random effects modeling and including multi-armed trials are addressed. Copyright © 2012 John Wiley & Sons, Ltd. Copyright © 2012 John Wiley & Sons, Ltd.

Swelling characteristics of acrylic acid polyelectrolyte hydrogel in a dc electric field

NASA Astrophysics Data System (ADS)

Jabbari, Esmaiel; Tavakoli, Javad; Sarvestani, Alireza S.

2007-10-01

A novel application of environmentally sensitive polyelectrolytes is in the fabrication of BioMEMS devices as sensors and actuators. Poly(acrylic acid) (PAA) gels are anionic polyelectrolyte networks that exhibit volume expansion in aqueous physiological environments. When an electric field is applied to PAA polyelectrolyte gels, the fixed anionic polyelectrolyte charges and the requirement of electro-neutrality in the network generate an osmotic pressure, above that in the absence of the electric field, to expand the network. The objective of this research was to investigate the effect of an externally applied dc electric field on the volume expansion of the PAA polyelectrolyte gel in a simulated physiological solution of phosphate buffer saline (PBS). For swelling studies in the electric field, two platinum-coated plates, as electrodes, were wrapped in a polyethylene sheet to protect the plates from corrosion and placed vertically in a vessel filled with PBS. The plates were placed on a rail such that the distance between the two plates could be adjusted. The PAA gel was synthesized by free radical crosslinking of acrylic acid monomer with ethylene glycol dimethacrylate (EGDMA) crosslinker. Our results demonstrate that volume expansion depends on the intensity of the electric field, the PAA network density, network homogeneity, and the position of the gel in the field relative to positive/negative electrodes. Our model predictions for PAA volume expansion, based on the dilute electrolyte concentration in the gel network, is in excellent agreement with the experimental findings in the high-electric-field regime (250-300 Newton/Coulomb).

Infrastructure for Integration of Legacy Electrical Equipment into a Smart-Grid Using Wireless Sensor Networks.

PubMed

de Araújo, Paulo Régis C; Filho, Raimir Holanda; Rodrigues, Joel J P C; Oliveira, João P C M; Braga, Stephanie A

2018-04-24

At present, the standardisation of electrical equipment communications is on the rise. In particular, manufacturers are releasing equipment for the smart grid endowed with communication protocols such as DNP3, IEC 61850, and MODBUS. However, there are legacy equipment operating in the electricity distribution network that cannot communicate using any of these protocols. Thus, we propose an infrastructure to allow the integration of legacy electrical equipment to smart grids by using wireless sensor networks (WSNs). In this infrastructure, each legacy electrical device is connected to a sensor node, and the sink node runs a middleware that enables the integration of this device into a smart grid based on suitable communication protocols. This middleware performs tasks such as the translation of messages between the power substation control centre (PSCC) and electrical equipment in the smart grid. Moreover, the infrastructure satisfies certain requirements for communication between the electrical equipment and the PSCC, such as enhanced security, short response time, and automatic configuration. The paper’s contributions include a solution that enables electrical companies to integrate their legacy equipment into smart-grid networks relying on any of the above mentioned communication protocols. This integration will reduce the costs related to the modernisation of power substations.

Infrastructure for Integration of Legacy Electrical Equipment into a Smart-Grid Using Wireless Sensor Networks

PubMed Central

de Araújo, Paulo Régis C.; Filho, Raimir Holanda; Oliveira, João P. C. M.; Braga, Stephanie A.

2018-01-01

At present, the standardisation of electrical equipment communications is on the rise. In particular, manufacturers are releasing equipment for the smart grid endowed with communication protocols such as DNP3, IEC 61850, and MODBUS. However, there are legacy equipment operating in the electricity distribution network that cannot communicate using any of these protocols. Thus, we propose an infrastructure to allow the integration of legacy electrical equipment to smart grids by using wireless sensor networks (WSNs). In this infrastructure, each legacy electrical device is connected to a sensor node, and the sink node runs a middleware that enables the integration of this device into a smart grid based on suitable communication protocols. This middleware performs tasks such as the translation of messages between the power substation control centre (PSCC) and electrical equipment in the smart grid. Moreover, the infrastructure satisfies certain requirements for communication between the electrical equipment and the PSCC, such as enhanced security, short response time, and automatic configuration. The paper’s contributions include a solution that enables electrical companies to integrate their legacy equipment into smart-grid networks relying on any of the above mentioned communication protocols. This integration will reduce the costs related to the modernisation of power substations. PMID:29695099

Time series prediction in the case of nonlinear loads by using ADALINE and NAR neural networks

NASA Astrophysics Data System (ADS)

Ghiormez, L.; Panoiu, M.; Panoiu, C.; Tirian, O.

2018-01-01

This paper presents a study regarding the time series prediction in the case of an electric arc furnace. The considered furnace is a three phase load and it is used to melt scrap in order to obtain liquid steel. The furnace is powered by a three-phase electrical supply and therefore has three graphite electrodes. The furnace is a nonlinear load that can influence the equipment connected to the same electrical power supply network. The nonlinearity is given by the electric arc that appears at the furnace between the graphite electrode and the scrap. Because of the disturbances caused by the electric arc furnace during the elaboration process of steel it is very useful to predict the current of the electric arc and the voltage from the measuring point in the secondary side of the furnace transformer. In order to make the predictions were used ADALINE and NAR neural networks. To train the networks and to make the predictions were used data acquired from the real technological plant.

Towards Smart Grid Dynamic Ratings

NASA Astrophysics Data System (ADS)

Cheema, Jamal; Clark, Adrian; Kilimnik, Justin; Pavlovski, Chris; Redman, David; Vu, Maria

2011-08-01

The energy distribution industry is giving greater attention to smart grid solutions as a means for increasing the capabilities, efficiency and reliability of the electrical power network. The smart grid makes use of intelligent monitoring and control devices throughout the distribution network to report on electrical properties such as voltage, current and power, as well as raising network alarms and events. A further aspect of the smart grid embodies the dynamic rating of electrical assets of the network. This fundamentally involves a rating of the load current capacity of electrical assets including feeders, transformers and switches. The mainstream approach to rate assets is to apply the vendor plate rating, which often under utilizes assets, or in some cases over utilizes when environmental conditions reduce the effective rated capacity, potentially reducing lifetime. Using active intelligence we have developed a rating system that rates assets in real time based upon several events. This allows for a far more efficient and reliable electrical grid that is able to extend further the life and reliability of the electrical network. In this paper we describe our architecture, the observations made during development and live deployment of the solution into operation. We also illustrate how this solution blends with the smart grid by proposing a dynamic rating system for the smart grid.

Excitement and synchronization of small-world neuronal networks with short-term synaptic plasticity.

PubMed

Han, Fang; Wiercigroch, Marian; Fang, Jian-An; Wang, Zhijie

2011-10-01

Excitement and synchronization of electrically and chemically coupled Newman-Watts (NW) small-world neuronal networks with a short-term synaptic plasticity described by a modified Oja learning rule are investigated. For each type of neuronal network, the variation properties of synaptic weights are examined first. Then the effects of the learning rate, the coupling strength and the shortcut-adding probability on excitement and synchronization of the neuronal network are studied. It is shown that the synaptic learning suppresses the over-excitement, helps synchronization for the electrically coupled network but impairs synchronization for the chemically coupled one. Both the introduction of shortcuts and the increase of the coupling strength improve synchronization and they are helpful in increasing the excitement for the chemically coupled network, but have little effect on the excitement of the electrically coupled one.

Social representations of electricity network technologies: exploring processes of anchoring and objectification through the use of visual research methods.

PubMed

Devine-Wright, Hannah; Devine-Wright, Patrick

2009-06-01

The aim of this study was to explore everyday thinking about the UK electricity network, in light of government policy to increase the generation of electricity from renewable energy sources. Existing literature on public perceptions of electricity network technologies was broadened by adopting a more socially embedded conception of the construction of knowledge using the theory of social representations (SRT) to explore symbolic associations with network technologies. Drawing and association tasks were administered within nine discussion groups held in two places: a Scottish town where significant upgrades to the local transmission network were planned and an English city with no such plans. Our results illustrate the ways in which network technologies, such as high voltage (HV) pylons, are objectified in talk and drawings. These invoked positive as well as negative symbolic and affective associations, both at the level of specific pylons, and the 'National Grid' as a whole and are anchored in understanding of other networks such as mobile telecommunications. We conclude that visual methods are especially useful for exploring beliefs about technologies that are widespread, proximal to our everyday experience but nevertheless unfamiliar topics of everyday conversation.

Modeling of synchronization behavior of bursting neurons at nonlinearly coupled dynamical networks.

PubMed

Çakir, Yüksel

2016-01-01

Synchronization behaviors of bursting neurons coupled through electrical and dynamic chemical synapses are investigated. The Izhikevich model is used with random and small world network of bursting neurons. Various currents which consist of diffusive electrical and time-delayed dynamic chemical synapses are used in the simulations to investigate the influences of synaptic currents and couplings on synchronization behavior of bursting neurons. The effects of parameters, such as time delay, inhibitory synaptic strengths, and decay time on synchronization behavior are investigated. It is observed that in random networks with no delay, bursting synchrony is established with the electrical synapse alone, single spiking synchrony is observed with hybrid coupling. In small world network with no delay, periodic bursting behavior with multiple spikes is observed when only chemical and only electrical synapse exist. Single-spike and multiple-spike bursting are established with hybrid couplings. A decrease in the synchronization measure is observed with zero time delay, as the decay time is increased in random network. For synaptic delays which are above active phase period, synchronization measure increases with an increase in synaptic strength and time delay in small world network. However, in random network, it increases with only an increase in synaptic strength.

Multi-focus and multi-level techniques for visualization and analysis of networks with thematic data

NASA Astrophysics Data System (ADS)

Cossalter, Michele; Mengshoel, Ole J.; Selker, Ted

2013-01-01

Information-rich data sets bring several challenges in the areas of visualization and analysis, even when associated with node-link network visualizations. This paper presents an integration of multi-focus and multi-level techniques that enable interactive, multi-step comparisons in node-link networks. We describe NetEx, a visualization tool that enables users to simultaneously explore different parts of a network and its thematic data, such as time series or conditional probability tables. NetEx, implemented as a Cytoscape plug-in, has been applied to the analysis of electrical power networks, Bayesian networks, and the Enron e-mail repository. In this paper we briefly discuss visualization and analysis of the Enron social network, but focus on data from an electrical power network. Specifically, we demonstrate how NetEx supports the analytical task of electrical power system fault diagnosis. Results from a user study with 25 subjects suggest that NetEx enables more accurate isolation of complex faults compared to an especially designed software tool.

Self-organizing intelligent network of smart electrical heating devices as an alternative to traditional ways of heating

NASA Astrophysics Data System (ADS)

Zaslavsky, Aleksander M.; Tkachov, Viktor V.; Protsenko, Stanislav M.; Bublikov, Andrii V.; Suleimenov, Batyrbek; Orshubekov, Nurbek; Gromaszek, Konrad

2017-08-01

The paper considers the problem of automated decentralized distribution of the electric energy among unlimited-power electric heaters providing the given temperature distribution within the zones of monitored object heating in the context of maximum use of electric power which limiting level is time-dependent randomly. Principles of collective selforganization automata for solving the problem are analyzed. It has been shown that after all the automata make decision, equilibrium of Nash type is attained when unused power within the electric network is not more than a power of any non-energized electric heater.

Developing Large-Scale Bayesian Networks by Composition: Fault Diagnosis of Electrical Power Systems in Aircraft and Spacecraft

NASA Technical Reports Server (NTRS)

Mengshoel, Ole Jakob; Poll, Scott; Kurtoglu, Tolga

2009-01-01

In this paper, we investigate the use of Bayesian networks to construct large-scale diagnostic systems. In particular, we consider the development of large-scale Bayesian networks by composition. This compositional approach reflects how (often redundant) subsystems are architected to form systems such as electrical power systems. We develop high-level specifications, Bayesian networks, clique trees, and arithmetic circuits representing 24 different electrical power systems. The largest among these 24 Bayesian networks contains over 1,000 random variables. Another BN represents the real-world electrical power system ADAPT, which is representative of electrical power systems deployed in aerospace vehicles. In addition to demonstrating the scalability of the compositional approach, we briefly report on experimental results from the diagnostic competition DXC, where the ProADAPT team, using techniques discussed here, obtained the highest scores in both Tier 1 (among 9 international competitors) and Tier 2 (among 6 international competitors) of the industrial track. While we consider diagnosis of power systems specifically, we believe this work is relevant to other system health management problems, in particular in dependable systems such as aircraft and spacecraft. (See CASI ID 20100021910 for supplemental data disk.)

Nanoscale Control over the Mixing Behavior of Surface-Confined Bicomponent Supramolecular Networks Using an Oriented External Electric Field

PubMed Central

2017-01-01

Strong electric fields are known to influence the properties of molecules as well as materials. Here we show that by changing the orientation of an externally applied electric field, one can locally control the mixing behavior of two molecules physisorbed on a solid surface. Whether the starting two-component network evolves into an ordered two-dimensional (2D) cocrystal, yields an amorphous network where the two components phase separate, or shows preferential adsorption of only one component depends on the solution stoichiometry. The experiments are carried out by changing the orientation of the strong electric field that exists between the tip of a scanning tunneling microscope and a solid substrate. The structure of the two-component network typically changes from open porous at negative substrate bias to relatively compact when the polarity of the applied bias is reversed. The electric-field-induced mixing behavior is reversible, and the supramolecular system exhibits excellent stability and good response efficiency. When molecular guests are adsorbed in the porous networks, the field-induced switching behavior was found to be completely different. Plausible reasons behind the field-induced mixing behavior are discussed. PMID:29112378

Evaluating the electricity intensity of evolving water supply mixes: the case of California’s water network

NASA Astrophysics Data System (ADS)

Stokes-Draut, Jennifer; Taptich, Michael; Kavvada, Olga; Horvath, Arpad

2017-11-01

Climate change is making water supply less predictable, even unreliable, in parts of the world. Urban water providers, especially in already arid areas, will need to diversify their water resources by switching to alternative sources and negotiating trading agreements to create more resilient and interdependent networks. The increasing complexity of these networks will likely require more operational electricity. The ability to document, visualize, and analyze water-energy relationships will be critical to future water planning, especially as data needed to conduct the analyses become increasingly available. We have developed a network model and decision-support tool, WESTNet, to perform these tasks. Herein, WESTNet was used to analyze a model of California’s 2010 urban water network as well as the projected system for 2020 and 2030. Results for California’s ten hydrologic regions show that the average number of water sources per utility and total electricity consumption for supplying water will increase in spite of decreasing per-capita water consumption. Electricity intensity (kWh m-3) will increase in arid regions of the state due to shifts to alternative water sources such as indirect potable water reuse, desalination, and water transfers. In wetter, typically less populated, regions, reduced water demand for electricity-intensive supplies will decrease the electricity intensity of the water supply mix, though total electricity consumption will increase due to urban population growth. The results of this study provide a baseline for comparing current and potential innovations to California’s water system. The WESTNet tool can be applied to diverse water systems in any geographic region at a variety of scales to evaluate an array of network-dependent water-energy parameters.

Electromagnetic compatibility of PLC adapters for in-home/domestic networks

NASA Astrophysics Data System (ADS)

Potisk, Lukas; Hallon, Jozef; Orgon, Milos; Fujdiak, Radek

2018-01-01

The use of programable logic controllers (PLC) technology in electrical networks 230 V causes electromagnetic radiation that interferes with other electrical equipment connected to the network [1-4]. Therefore, this article describes the issues of electromagnetic compatibility (EMC) of new PLC adapters used in IP broadband services in a multi-user environment. The measurements of disturbing electromagnetic field originated in PLC adapters were made in a certified laboratory EMC (laboratory of electromagnetic compatibility) in the Institute of Electrical Engineering at Faculty of Electrical Engineering and Information Technology of the Slovak University of Technology in Bratislava. The measured spectra of the radiated electromagnetic field will be compared with the results obtained when testing older PLC modems [5].

Conductive network formation of carbon nanotubes in elastic polymer microfibers and its effect on the electrical conductance: Experiment and simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cho, Hyun Woo; Kim, Jeongmin; Sung, Bong June, E-mail: jjpark@chonnam.ac.kr, E-mail: bjsung@sogang.ac.kr

We investigate how the electrical conductance of microfibers (made of polymers and conductive nanofillers) decreases upon uniaxial deformation by performing both experiments and simulations. Even though various elastic conductors have been developed due to promising applications for deformable electronic devices, the mechanism at a molecular level for electrical conductance change has remained elusive. Previous studies proposed that the decrease in electrical conductance would result from changes in either distances or contact numbers between conductive fillers. In this work, we prepare microfibers of single walled carbon nanotubes (SWCNTs)/polyvinyl alcohol composites and investigate the electrical conductance and the orientation of SWCNTs uponmore » uniaxial deformation. We also perform extensive Monte Carlo simulations, which reproduce experimental results for the relative decrease in conductance and the SWCNTs orientation. We investigate the electrical networks of SWCNTs in microfibers and find that the decrease in the electrical conductance upon uniaxial deformation should be attributed to a subtle change in the topological structure of the electrical network.« less

Networks: How Energy Links People, Goods and Services, Grades 4, 5. Interdisciplinary Student/Teacher Materials in Energy, the Environment, and the Economy.

ERIC Educational Resources Information Center

Johnson, Bette; Swinton, Olivia

The purpose of this unit is to investigate a simple energy network and to make an analogy with similar mutually supporting networks in the natural and man-made worlds. The lessons in this unit develop the network idea around a simple electrical distribution system that we depend on and also into further consideration of electrical energy itself.…

Interdisciplinary Student/Teacher Materials in Energy, the Environment, and the Economy. Networks: How Energy Links People, Goods and Services, Grades 4, 5.

ERIC Educational Resources Information Center

Johnson, Bette; Swinton, Olivia

The purpose of this unit is to investigate a simple energy network and to make an analogy with similar mutually supporting networks in the natural and man-made worlds. The lessons in this unit develop the network idea around a simple electrical distribution system that we depend on and also into further consideration of electrical energy itself.…

Micro-economic analysis of the physical constrained markets: game theory application to competitive electricity markets

NASA Astrophysics Data System (ADS)

Bompard, E.; Ma, Y. C.; Ragazzi, E.

2006-03-01

Competition has been introduced in the electricity markets with the goal of reducing prices and improving efficiency. The basic idea which stays behind this choice is that, in competitive markets, a greater quantity of the good is exchanged at a lower price, leading to higher market efficiency. Electricity markets are pretty different from other commodities mainly due to the physical constraints related to the network structure that may impact the market performance. The network structure of the system on which the economic transactions need to be undertaken poses strict physical and operational constraints. Strategic interactions among producers that game the market with the objective of maximizing their producer surplus must be taken into account when modeling competitive electricity markets. The physical constraints, specific of the electricity markets, provide additional opportunity of gaming to the market players. Game theory provides a tool to model such a context. This paper discussed the application of game theory to physical constrained electricity markets with the goal of providing tools for assessing the market performance and pinpointing the critical network constraints that may impact the market efficiency. The basic models of game theory specifically designed to represent the electricity markets will be presented. IEEE30 bus test system of the constrained electricity market will be discussed to show the network impacts on the market performances in presence of strategic bidding behavior of the producers.

Modeling Geoelectric Fields and Geomagnetically Induced Currents Around New Zealand to Explore GIC in the South Island's Electrical Transmission Network

NASA Astrophysics Data System (ADS)

Divett, T.; Ingham, M.; Beggan, C. D.; Richardson, G. S.; Rodger, C. J.; Thomson, A. W. P.; Dalzell, M.

2017-10-01

Transformers in New Zealand's South Island electrical transmission network have been impacted by geomagnetically induced currents (GIC) during geomagnetic storms. We explore the impact of GIC on this network by developing a thin-sheet conductance (TSC) model for the region, a geoelectric field model, and a GIC network model. (The TSC is composed of a thin-sheet conductance map with underlying layered resistivity structure.) Using modeling approaches that have been successfully used in the United Kingdom and Ireland, we applied a thin-sheet model to calculate the electric field as a function of magnetic field and ground conductance. We developed a TSC model based on magnetotelluric surveys, geology, and bathymetry, modified to account for offshore sediments. Using this representation, the thin sheet model gave good agreement with measured impedance vectors. Driven by a spatially uniform magnetic field variation, the thin-sheet model results in electric fields dominated by the ocean-land boundary with effects due to the deep ocean and steep terrain. There is a strong tendency for the electric field to align northwest-southeast, irrespective of the direction of the magnetic field. Applying this electric field to a GIC network model, we show that modeled GIC are dominated by northwest-southeast transmission lines rather than east-west lines usually assumed to dominate.

Developing a tissue-engineered neural-electrical relay using encapsulated neuronal constructs on conducting polymer fibers.

PubMed

Cullen, D Kacy; R Patel, Ankur; Doorish, John F; Smith, Douglas H; Pfister, Bryan J

2008-12-01

Neural-electrical interface platforms are being developed to extracellularly monitor neuronal population activity. Polyaniline-based electrically conducting polymer fibers are attractive substrates for sustained functional interfaces with neurons due to their flexibility, tailored geometry and controlled electro-conductive properties. In this study, we addressed the neurobiological considerations of utilizing small diameter (<400 microm) fibers consisting of a blend of electrically conductive polyaniline and polypropylene (PA-PP) as the backbone of encapsulated tissue-engineered neural-electrical relays. We devised new approaches to promote survival, adhesion and neurite outgrowth of primary dorsal root ganglion neurons on PA-PP fibers. We attained a greater than ten-fold increase in the density of viable neurons on fiber surfaces to approximately 700 neurons mm(-2) by manipulating surrounding surface charges to bias settling neuronal suspensions toward fibers coated with cell-adhesive ligands. This stark increase in neuronal density resulted in robust neuritic extension and network formation directly along the fibers. Additionally, we encapsulated these neuronal networks on PA-PP fibers using agarose to form a protective barrier while potentially facilitating network stability. Following encapsulation, the neuronal networks maintained integrity, high viability (>85%) and intimate adhesion to PA-PP fibers. These efforts accomplished key prerequisites for the establishment of functional electrical interfaces with neuronal populations using small diameter PA-PP fibers-specifically, improved neurocompatibility, high-density neuronal adhesion and neuritic network development directly on fiber surfaces.

Electrode material comprising graphene-composite materials in a graphite network

DOEpatents

Kung, Harold H.; Lee, Jung K.

2014-07-15

A durable electrode material suitable for use in Li ion batteries is provided. The material is comprised of a continuous network of graphite regions integrated with, and in good electrical contact with a composite comprising graphene sheets and an electrically active material, such as silicon, wherein the electrically active material is dispersed between, and supported by, the graphene sheets.

Electrode material comprising graphene-composite materials in a graphite network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kung, Harold H.; Lee, Jung K.

A durable electrode material suitable for use in Li ion batteries is provided. The material is comprised of a continuous network of graphite regions integrated with, and in good electrical contact with a composite comprising graphene sheets and an electrically active material, such as silicon, wherein the electrically active material is dispersed between, and supported by, the graphene sheets.

Reduction technique of drop voltage and power losses to improve power quality using ETAP Power Station simulation model

NASA Astrophysics Data System (ADS)

Satrio, Reza Indra; Subiyanto

2018-03-01

The effect of electric loads growth emerged direct impact in power systems distribution. Drop voltage and power losses one of the important things in power systems distribution. This paper presents modelling approach used to restructrure electrical network configuration, reduce drop voltage, reduce power losses and add new distribution transformer to enhance reliability of power systems distribution. Restructrure electrical network was aimed to analyse and investigate electric loads of a distribution transformer. Measurement of real voltage and real current were finished two times for each consumer, that were morning period and night period or when peak load. Design and simulation were conduct by using ETAP Power Station Software. Based on result of simulation and real measurement precentage of drop voltage and total power losses were mismatch with SPLN (Standard PLN) 72:1987. After added a new distribution transformer and restructrured electricity network configuration, the result of simulation could reduce drop voltage from 1.3 % - 31.3 % to 8.1 % - 9.6 % and power losses from 646.7 watt to 233.29 watt. Result showed, restructrure electricity network configuration and added new distribution transformer can be applied as an effective method to reduce drop voltage and reduce power losses.

Storage of electric and magnetic energy in passive nonreciprocal networks

NASA Technical Reports Server (NTRS)

Smith, W. E.

1969-01-01

Examination of the relation of stored electric and magnetic energy within a system to the terminal behavior of nonreciprocal passive networks shows both similarities and important differences between wholly reciprocal systems and systems containing nonreciprocal elements.

Noise-sustained synchronization between electrically coupled FitzHugh-Nagumo networks

NASA Astrophysics Data System (ADS)

Cascallares, Guadalupe; Sánchez, Alejandro D.; dell'Erba, Matías G.; Izús, Gonzalo G.

2015-09-01

We investigate the capability of electrical synapses to transmit the noise-sustained network activity from one network to another. The particular setup we consider is two identical rings with excitable FitzHugh-Nagumo cell dynamics and nearest-neighbor antiphase intra-ring coupling, electrically coupled between corresponding nodes. The whole system is submitted to independent local additive Gaussian white noises with common intensity η, but only one ring is externally forced by a global adiabatic subthreshold harmonic signal. We then seek conditions for a particular noise level to promote synchronized stable firing patterns. By running numerical integrations with increasing η, we observe the excitation activity to become spatiotemporally self-organized, until η is so strong that spoils sync between networks for a given value of the electric coupling strength. By means of a four-cell model and calculating the stationary probability distribution, we obtain a (signal-dependent) non-equilibrium potential landscape which explains qualitatively the observed regimes, and whose barrier heights give a good estimate of the optimal noise intensity for the sync between networks.

A network thermodynamic method for numerical solution of the Nernst-Planck and Poisson equation system with application to ionic transport through membranes.

PubMed

Horno, J; González-Caballero, F; González-Fernández, C F

1990-01-01

Simple techniques of network thermodynamics are used to obtain the numerical solution of the Nernst-Planck and Poisson equation system. A network model for a particular physical situation, namely ionic transport through a thin membrane with simultaneous diffusion, convection and electric current, is proposed. Concentration and electric field profiles across the membrane, as well as diffusion potential, have been simulated using the electric circuit simulation program, SPICE. The method is quite general and extremely efficient, permitting treatments of multi-ion systems whatever the boundary and experimental conditions may be.

Neural network based short-term load forecasting using weather compensation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chow, T.W.S.; Leung, C.T.

This paper presents a novel technique for electric load forecasting based on neural weather compensation. The proposed method is a nonlinear generalization of Box and Jenkins approach for nonstationary time-series prediction. A weather compensation neural network is implemented for one-day ahead electric load forecasting. The weather compensation neural network can accurately predict the change of actual electric load consumption from the previous day. The results, based on Hong Kong Island historical load demand, indicate that this methodology is capable of providing a more accurate load forecast with a 0.9% reduction in forecast error.

The Study on the Communication Network of Wide Area Measurement System in Electricity Grid

NASA Astrophysics Data System (ADS)

Xiaorong, Cheng; Ying, Wang; Yangdan, Ni

Wide area measurement system(WAMS) is a fundamental part of security defense in Smart Grid, and the communication system of WAMS is an important part of Electric power communication network. For a large regional network is concerned, the real-time data which is transferred in the communication network of WAMS will affect the safe operation of the power grid directly. Therefore, WAMS raised higher requirements for real-time, reliability and security to its communication network. In this paper, the architecture of WASM communication network was studied according to the seven layers model of the open systems interconnection(OSI), and the network architecture was researched from all levels. We explored the media of WAMS communication network, the network communication protocol and network technology. Finally, the delay of the network were analyzed.

Mechanical and Electrical Characterization of Entangled Networks of Carbon Nanofibers

PubMed Central

Mousavi, Arash K.; Atwater, Mark A.; Mousavi, Behnam K.; Jalalpour, Mohammad; Taha, Mahmoud Reda; Leseman, Zayd C.

2014-01-01

Entangled networks of carbon nanofibers are characterized both mechanically and electrically. Results for both tensile and compressive loadings of the entangled networks are presented for various densities. Mechanically, the nanofiber ensembles follow the micromechanical model originally proposed by van Wyk nearly 70 years ago. Interpretations are given on the mechanisms occurring during loading and unloading of the carbon nanofiber components. PMID:28788709

Interface Control Document for the EMPACT Module that Estimates Electric Power Transmission System Response to EMP-Caused Damage

DOE Office of Scientific and Technical Information (OSTI.GOV)

Werley, Kenneth Alan; Mccown, Andrew William

The EPREP code is designed to evaluate the effects of an Electro-Magnetic Pulse (EMP) on the electric power transmission system. The EPREP code embodies an umbrella framework that allows a user to set up analysis conditions and to examine analysis results. The code links to three major physics/engineering modules. The first module describes the EM wave in space and time. The second module evaluates the damage caused by the wave on specific electric power (EP) transmission system components. The third module evaluates the consequence of the damaged network on its (reduced) ability to provide electric power to meet demand. Thismore » third module is the focus of the present paper. The EMPACT code serves as the third module. The EMPACT name denotes EMP effects on Alternating Current Transmission systems. The EMPACT algorithms compute electric power transmission network flow solutions under severely damaged network conditions. Initial solutions are often characterized by unacceptible network conditions including line overloads and bad voltages. The EMPACT code contains algorithms to adjust optimally network parameters to eliminate network problems while minimizing outages. System adjustments include automatically adjusting control equipment (generator V control, variable transformers, and variable shunts), as well as non-automatic control of generator power settings and minimal load shedding. The goal is to evaluate the minimal loss of customer load under equilibrium (steady-state) conditions during peak demand.« less

Design of the smart home system based on the optimal routing algorithm and ZigBee network.

PubMed

Jiang, Dengying; Yu, Ling; Wang, Fei; Xie, Xiaoxia; Yu, Yongsheng

2017-01-01

To improve the traditional smart home system, its electric wiring, networking technology, information transmission and facility control are studied. In this paper, we study the electric wiring, networking technology, information transmission and facility control to improve the traditional smart home system. First, ZigBee is used to replace the traditional electric wiring. Second, a network is built to connect lots of wireless sensors and facilities, thanks to the capability of ZigBee self-organized network and Genetic Algorithm-Particle Swarm Optimization Algorithm (GA-PSOA) to search for the optimal route. Finally, when the smart home system is connected to the internet based on the remote server technology, home environment and facilities could be remote real-time controlled. The experiments show that the GA-PSOA reduce the system delay and decrease the energy consumption of the wireless system.

Design of the smart home system based on the optimal routing algorithm and ZigBee network

PubMed Central

Xie, Xiaoxia

2017-01-01

To improve the traditional smart home system, its electric wiring, networking technology, information transmission and facility control are studied. In this paper, we study the electric wiring, networking technology, information transmission and facility control to improve the traditional smart home system. First, ZigBee is used to replace the traditional electric wiring. Second, a network is built to connect lots of wireless sensors and facilities, thanks to the capability of ZigBee self-organized network and Genetic Algorithm-Particle Swarm Optimization Algorithm (GA-PSOA) to search for the optimal route. Finally, when the smart home system is connected to the internet based on the remote server technology, home environment and facilities could be remote real-time controlled. The experiments show that the GA-PSOA reduce the system delay and decrease the energy consumption of the wireless system. PMID:29131868

Decompositions of injection patterns for nodal flow allocation in renewable electricity networks

NASA Astrophysics Data System (ADS)

Schäfer, Mirko; Tranberg, Bo; Hempel, Sabrina; Schramm, Stefan; Greiner, Martin

2017-08-01

The large-scale integration of fluctuating renewable power generation represents a challenge to the technical and economical design of a sustainable future electricity system. In this context, the increasing significance of long-range power transmission calls for innovative methods to understand the emerging complex flow patterns and to integrate price signals about the respective infrastructure needs into the energy market design. We introduce a decomposition method of injection patterns. Contrary to standard flow tracing approaches, it provides nodal allocations of link flows and costs in electricity networks by decomposing the network injection pattern into market-inspired elementary import/export building blocks. We apply the new approach to a simplified data-driven model of a European electricity grid with a high share of renewable wind and solar power generation.

Synchronization of Lienard-Type Oscillators in Uniform Electrical Networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sinha, Mohit; Dorfler, Florian; Johnson, Brian B.

2016-08-01

This paper presents a condition for global asymptotic synchronization of Lienard-type nonlinear oscillators in uniform LTI electrical networks with series R-L circuits modeling interconnections. By uniform electrical networks, we mean that the per-unit-length impedances are identical for the interconnecting lines. We derive conditions for global asymptotic synchronization for a particular feedback architecture where the derivative of the oscillator output current supplements the innate current feedback induced by simply interconnecting the oscillator to the network. Our proof leverages a coordinate transformation to a set of differential coordinates that emphasizes signal differences and the particular form of feedback permits the formulation ofmore » a quadratic Lyapunov function for this class of networks. This approach is particularly interesting since synchronization conditions are difficult to obtain by means of quadratic Lyapunov functions when only current feedback is used and for networks composed of series R-L circuits. Our synchronization condition depends on the algebraic connectivity of the underlying network, and reiterates the conventional wisdom from Lyapunov- and passivity-based arguments that strong coupling is required to ensure synchronization.« less

Three essays on "making" electric power markets

NASA Astrophysics Data System (ADS)

Kench, Brian Thomas

2000-10-01

Technological change over the past three decades has altered most of the basic conditions in the electric power industry. Because of technical progress, the dominant paradigm has shifted from the provision of electric power by regulated and vertically integrated local natural monopolies to competition and vertical separation. In the first essay I provide a historical context of the electric industry's power current deregulation debate. Then a dynamic model of induced institutional change is used to investigate how endogenous technological advancements have induced radical institutional change in the generation and transmission segments of the electric power industry. Because the Federal Energy Regulatory Commission (FERC) ordered regulated utilities to provide open access to their transmission networks and to separate their generation and transmission functions, transmission networks have been used more intensively and in much different ways then in the past. The second essay tests experimentally the predictions of neoclassical theory for a radial electric power market under two alternative deregulated transmission institutions: financial transmission rights and physical transmission rights. Experimental evidence presented there demonstrates that an electric power market with physical transmission rights governing its transmission network generates more "right" market signals relative to a transmission network governed by financial transmission rights. The move to a greater reliance on markets for electric power is an idea that has animated sweeping and dramatic changes in the traditional business of electric power. The third essay examines two of the most innovative and complex initiatives of making electric power markets in the United States: California and PJM. As those markets mature and others are made, they must revise their governance mechanisms to eliminate rules that create inefficiency and adopt rules that work efficiently elsewhere. I argue that restructured electric power markets in the United States we should consider adopting an integrated procurement approach for electric power and ancillary services, binding forward markets for those commodities, and a market for physical transmission rights.

Electricity storage: Friend or foe of the networks?

NASA Astrophysics Data System (ADS)

Jamasb, Tooraj

2017-06-01

As storage technology progresses it offers a range of solutions and services to users and the electricity industry. A new study explores whether or not this will eventually lead to self-sufficient consumers and spell the end of the networks as we know them.

Network based management for multiplexed electric vehicle charging

DOEpatents

Gadh, Rajit; Chung, Ching Yen; Qui, Li

2017-04-11

A system for multiplexing charging of electric vehicles, comprising a server coupled to a plurality of charging control modules over a network. Each of said charging modules being connected to a voltage source such that each charging control module is configured to regulate distribution of voltage from the voltage source to an electric vehicle coupled to the charging control module. Data collection and control software is provided on the server for identifying a plurality of electric vehicles coupled to the plurality of charging control modules and selectively distributing charging of the plurality of charging control modules to multiplex distribution of voltage to the plurality of electric vehicles.

Neural network control of a parallel hybrid-electric propulsion system for a small unmanned aerial vehicle

NASA Astrophysics Data System (ADS)

Harmon, Frederick G.

2005-11-01

Parallel hybrid-electric propulsion systems would be beneficial for small unmanned aerial vehicles (UAVs) used for military, homeland security, and disaster-monitoring missions. The benefits, due to the hybrid and electric-only modes, include increased time-on-station and greater range as compared to electric-powered UAVs and stealth modes not available with gasoline-powered UAVs. This dissertation contributes to the research fields of small unmanned aerial vehicles, hybrid-electric propulsion system control, and intelligent control. A conceptual design of a small UAV with a parallel hybrid-electric propulsion system is provided. The UAV is intended for intelligence, surveillance, and reconnaissance (ISR) missions. A conceptual design reveals the trade-offs that must be considered to take advantage of the hybrid-electric propulsion system. The resulting hybrid-electric propulsion system is a two-point design that includes an engine primarily sized for cruise speed and an electric motor and battery pack that are primarily sized for a slower endurance speed. The electric motor provides additional power for take-off, climbing, and acceleration and also serves as a generator during charge-sustaining operation or regeneration. The intelligent control of the hybrid-electric propulsion system is based on an instantaneous optimization algorithm that generates a hyper-plane from the nonlinear efficiency maps for the internal combustion engine, electric motor, and lithium-ion battery pack. The hyper-plane incorporates charge-depletion and charge-sustaining strategies. The optimization algorithm is flexible and allows the operator/user to assign relative importance between the use of gasoline, electricity, and recharging depending on the intended mission. A MATLAB/Simulink model was developed to test the control algorithms. The Cerebellar Model Arithmetic Computer (CMAC) associative memory neural network is applied to the control of the UAVs parallel hybrid-electric propulsion system. The CMAC neural network approximates the hyper-plane generated from the instantaneous optimization algorithm and produces torque commands for the internal combustion engine and electric motor. The CMAC neural network controller saves on the required memory as compared to a large look-up table by two orders of magnitude. The CMAC controller also prevents the need to compute a hyper-plane or complex logic every time step.

Diagnosis and Reconfiguration using Bayesian Networks: An Electrical Power System Case Study

NASA Technical Reports Server (NTRS)

Knox, W. Bradley; Mengshoel, Ole

2009-01-01

Automated diagnosis and reconfiguration are important computational techniques that aim to minimize human intervention in autonomous systems. In this paper, we develop novel techniques and models in the context of diagnosis and reconfiguration reasoning using causal Bayesian networks (BNs). We take as starting point a successful diagnostic approach, using a static BN developed for a real-world electrical power system. We discuss in this paper the extension of this diagnostic approach along two dimensions, namely: (i) from a static BN to a dynamic BN; and (ii) from a diagnostic task to a reconfiguration task. More specifically, we discuss the auto-generation of a dynamic Bayesian network from a static Bayesian network. In addition, we discuss subtle, but important, differences between Bayesian networks when used for diagnosis versus reconfiguration. We discuss a novel reconfiguration agent, which models a system causally, including effects of actions through time, using a dynamic Bayesian network. Though the techniques we discuss are general, we demonstrate them in the context of electrical power systems (EPSs) for aircraft and spacecraft. EPSs are vital subsystems on-board aircraft and spacecraft, and many incidents and accidents of these vehicles have been attributed to EPS failures. We discuss a case study that provides initial but promising results for our approach in the setting of electrical power systems.

Energy-aware virtual network embedding in flexi-grid networks.

PubMed

Lin, Rongping; Luo, Shan; Wang, Haoran; Wang, Sheng

2017-11-27

Network virtualization technology has been proposed to allow multiple heterogeneous virtual networks (VNs) to coexist on a shared substrate network, which increases the utilization of the substrate network. Efficiently mapping VNs on the substrate network is a major challenge on account of the VN embedding (VNE) problem. Meanwhile, energy efficiency has been widely considered in the network design in terms of operation expenses and the ecological awareness. In this paper, we aim to solve the energy-aware VNE problem in flexi-grid optical networks. We provide an integer linear programming (ILP) formulation to minimize the electricity cost of each arriving VN request. We also propose a polynomial-time heuristic algorithm where virtual links are embedded sequentially to keep a reasonable acceptance ratio and maintain a low electricity cost. Numerical results show that the heuristic algorithm performs closely to the ILP for a small size network, and we also demonstrate its applicability to larger networks.

The impact of electric vehicles on the outlook of future energy system

NASA Astrophysics Data System (ADS)

Zhuk, A.; Buzoverov, E.

2018-02-01

Active promotion of electric vehicles (EVs) and technology of fast EV charging in the medium term may cause significant peak loads on the energy system, what necessitates making strategic decisions related to the development of generating capacities, distribution networks with EV charging infrastructure, and priorities in the development of battery electric vehicles and vehicles with electrochemical generators. The paper analyses one of the most significant aspects of joint development of electric transport system and energy system in the conditions of substantial growth of energy consumption by EVs. The assessments of per-unit-costs of operation and depreciation of EV power unit were made, taking into consideration the expenses of electric power supply. The calculations show that the choice of electricity buffering method for EV fast charging depends on the character of electricity infrastructure in the region where the electric transport is operating. In the conditions of high density of electricity network and a large number of EVs, the stationary storage facilities or the technology of distributed energy storage in EV batteries - vehicle-to-grid (V2G) technology may be used for buffering. In the conditions of low density and low capacity of electricity networks, the most economical solution could be usage of EVs with traction power units based on the combination of air-aluminum electrochemical generator and a buffer battery of small capacity.

Relationship between inter-stimulus-intervals and intervals of autonomous activities in a neuronal network.

PubMed

Ito, Hidekatsu; Minoshima, Wataru; Kudoh, Suguru N

2015-08-01

To investigate relationships between neuronal network activity and electrical stimulus, we analyzed autonomous activity before and after electrical stimulus. Recordings of autonomous activity were performed using dissociated culture of rat hippocampal neurons on a multi-electrodes array (MEA) dish. Single stimulus and pared stimuli were applied to a cultured neuronal network. Single stimulus was applied every 1 min, and paired stimuli was performed by two sequential stimuli every 1 min. As a result, the patterns of synchronized activities of a neuronal network were changed after stimulus. Especially, long range synchronous activities were induced by paired stimuli. When 1 s inter-stimulus-intervals (ISI) and 1.5 s ISI paired stimuli are applied to a neuronal network, relatively long range synchronous activities expressed in case of 1.5 s ISI. Temporal synchronous activity of neuronal network is changed according to inter-stimulus-intervals (ISI) of electrical stimulus. In other words, dissociated neuronal network can maintain given information in temporal pattern and a certain type of an information maintenance mechanism was considered to be implemented in a semi-artificial dissociated neuronal network. The result is useful toward manipulation technology of neuronal activity in a brain system.

ELECTRIC VEHICLE CONVERSIONS USING ALTERNATIVE ENERGY TO DRIVE ALASKAN RURAL COMMUNITIES

EPA Science Inventory

This proposal concerns sustainable transportation in rural Alaskan communities which are not part of a road or electrical network (off grid). In most off-grid communities, the road networks generally are less than 50 square miles, so transportation needs are limited. This limi...

Managing Ongoing EVSE Costs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hodge, Cabell

The costs associated with EVSE begin with picking the best location and unit for the job, but they continue with electricity and network charges through the life of your vehicle. This presentation tells how to balance electricity demand charges and network management costs through smart planning at your program's inception.

Why do electricity policy and competitive markets fail to use advanced PV systems to improve distribution power quality?

DOE Office of Scientific and Technical Information (OSTI.GOV)

McHenry, Mark P.; Johnson, Jay; Hightower, Mike

The increasing pressure for network operators to meet distribution network power quality standards with increasing peak loads, renewable energy targets, and advances in automated distributed power electronics and communications is forcing policy-makers to understand new means to distribute costs and benefits within electricity markets. Discussions surrounding how distributed generation (DG) exhibits active voltage regulation and power factor/reactive power control and other power quality capabilities are complicated by uncertainties of baseline local distribution network power quality and to whom and how costs and benefits of improved electricity infrastructure will be allocated. DG providing ancillary services that dynamically respond to the networkmore » characteristics could lead to major network improvements. With proper market structures renewable energy systems could greatly improve power quality on distribution systems with nearly no additional cost to the grid operators. Renewable DG does have variability challenges, though this issue can be overcome with energy storage, forecasting, and advanced inverter functionality. This paper presents real data from a large-scale grid-connected PV array with large-scale storage and explores effective mitigation measures for PV system variability. As a result, we discuss useful inverter technical knowledge for policy-makers to mitigate ongoing inflation of electricity network tariff components by new DG interconnection requirements or electricity markets which value power quality and control.« less

Why do electricity policy and competitive markets fail to use advanced PV systems to improve distribution power quality?

DOE PAGES

McHenry, Mark P.; Johnson, Jay; Hightower, Mike

2016-01-01

The increasing pressure for network operators to meet distribution network power quality standards with increasing peak loads, renewable energy targets, and advances in automated distributed power electronics and communications is forcing policy-makers to understand new means to distribute costs and benefits within electricity markets. Discussions surrounding how distributed generation (DG) exhibits active voltage regulation and power factor/reactive power control and other power quality capabilities are complicated by uncertainties of baseline local distribution network power quality and to whom and how costs and benefits of improved electricity infrastructure will be allocated. DG providing ancillary services that dynamically respond to the networkmore » characteristics could lead to major network improvements. With proper market structures renewable energy systems could greatly improve power quality on distribution systems with nearly no additional cost to the grid operators. Renewable DG does have variability challenges, though this issue can be overcome with energy storage, forecasting, and advanced inverter functionality. This paper presents real data from a large-scale grid-connected PV array with large-scale storage and explores effective mitigation measures for PV system variability. As a result, we discuss useful inverter technical knowledge for policy-makers to mitigate ongoing inflation of electricity network tariff components by new DG interconnection requirements or electricity markets which value power quality and control.« less

Modulation of hippocampal rhythms by subthreshold electric fields and network topology

PubMed Central

Berzhanskaya, Julia; Chernyy, Nick; Gluckman, Bruce J.; Schiff, Steven J.; Ascoli, Giorgio A.

2012-01-01

Theta (4–12 Hz) and gamma (30–80 Hz) rhythms are considered important for cortical and hippocampal function. Although several neuron types are implicated in rhythmogenesis, the exact cellular mechanisms remain unknown. Subthreshold electric fields provide a flexible, area-specific tool to modulate neural activity and directly test functional hypotheses. Here we present experimental and computational evidence of the interplay among hippocampal synaptic circuitry, neuronal morphology, external electric fields, and network activity. Electrophysiological data are used to constrain and validate an anatomically and biophysically realistic model of area CA1 containing pyramidal cells and two interneuron types: dendritic- and perisomatic-targeting. We report two lines of results: addressing the network structure capable of generating theta-modulated gamma rhythms, and demonstrating electric field effects on those rhythms. First, theta-modulated gamma rhythms require specific inhibitory connectivity. In one configuration, GABAergic axo-dendritic feedback on pyramidal cells is only effective in proximal but not distal layers. An alternative configuration requires two distinct perisomatic interneuron classes, one exclusively receiving excitatory contacts, the other additionally targeted by inhibition. These observations suggest novel roles for particular classes of oriens and basket cells. The second major finding is that subthreshold electric fields robustly alter the balance between different rhythms. Independent of network configuration, positive electric fields decrease, while negative fields increase the theta/gamma ratio. Moreover, electric fields differentially affect average theta frequency depending on specific synaptic connectivity. These results support the testable prediction that subthreshold electric fields can alter hippocampal rhythms, suggesting new approaches to explore their cognitive functions and underlying circuitry. PMID:23053863

The Use of Artificial Neural Networks for Forecasting the Electric Demand of Stand-Alone Consumers

NASA Astrophysics Data System (ADS)

Ivanin, O. A.; Direktor, L. B.

2018-05-01

The problem of short-term forecasting of electric power demand of stand-alone consumers (small inhabited localities) situated outside centralized power supply areas is considered. The basic approaches to modeling the electric power demand depending on the forecasting time frame and the problems set, as well as the specific features of such modeling, are described. The advantages and disadvantages of the methods used for the short-term forecast of the electric demand are indicated, and difficulties involved in the solution of the problem are outlined. The basic principles of arranging artificial neural networks are set forth; it is also shown that the proposed method is preferable when the input information necessary for prediction is lacking or incomplete. The selection of the parameters that should be included into the list of the input data for modeling the electric power demand of residential areas using artificial neural networks is validated. The structure of a neural network is proposed for solving the problem of modeling the electric power demand of residential areas. The specific features of generation of the training dataset are outlined. The results of test modeling of daily electric demand curves for some settlements of Kamchatka and Yakutia based on known actual electric demand curves are provided. The reliability of the test modeling has been validated. A high value of the deviation of the modeled curve from the reference curve obtained in one of the four reference calculations is explained. The input data and the predicted power demand curves for the rural settlement of Kuokuiskii Nasleg are provided. The power demand curves were modeled for four characteristic days of the year, and they can be used in the future for designing a power supply system for the settlement. To enhance the accuracy of the method, a series of measures based on specific features of a neural network's functioning are proposed.

Broadband electrical impedance matching for piezoelectric ultrasound transducers.

PubMed

Huang, Haiying; Paramo, Daniel

2011-12-01

This paper presents a systematic method for designing broadband electrical impedance matching networks for piezoelectric ultrasound transducers. The design process involves three steps: 1) determine the equivalent circuit of the unmatched piezoelectric transducer based on its measured admittance; 2) design a set of impedance matching networks using a computerized Smith chart; and 3) establish the simulation model of the matched transducer to evaluate the gain and bandwidth of the impedance matching networks. The effectiveness of the presented approach is demonstrated through the design, implementation, and characterization of impedance matching networks for a broadband acoustic emission sensor. The impedance matching network improved the power of the acquired signal by 9 times.

Drive Control Scheme of Electric Power Assisted Wheelchair Based on Neural Network Learning of Human Wheelchair Operation Characteristics

NASA Astrophysics Data System (ADS)

Tanohata, Naoki; Seki, Hirokazu

This paper describes a novel drive control scheme of electric power assisted wheelchairs based on neural network learning of human wheelchair operation characteristics. “Electric power assisted wheelchair” which enhances the drive force of the operator by employing electric motors is expected to be widely used as a mobility support system for elderly and disabled people. However, some handicapped people with paralysis of the muscles of one side of the body cannot maneuver the wheelchair as desired because of the difference in the right and left input force. Therefore, this study proposes a neural network learning system of such human wheelchair operation characteristics and a drive control scheme with variable distribution and assistance ratios. Some driving experiments will be performed to confirm the effectiveness of the proposed control system.

Memristors in the electrical network of Aloe vera L.

PubMed Central

Volkov, Alexander G; Reedus, Jada; Mitchell, Colee M; Tucket, Clayton; Forde-Tuckett, Victoria; Volkova, Maya I; Markin, Vladislav S; Chua, Leon

2014-01-01

A memristor is a resistor with memory, which is a non-linear passive two-terminal electrical element relating magnetic flux linkage and electrical charge. Here we found that memristors exist in vivo. The electrostimulation of the Aloe vera by bipolar sinusoidal or triangle periodic waves induce electrical responses with fingerprints of memristors. Uncouplers carbonylcyanide-3-chlorophenylhydrazone and carbonylcyanide-4-trifluoromethoxy-phenyl hydrazone decrease the amplitude of electrical responses at low and high frequencies of bipolar periodic sinusoidal or triangle electrostimulating waves. Memristive behavior of an electrical network in the Aloe vera is linked to the properties of voltage gated ion channels: the K+ channel blocker TEACl reduces the electric response to a conventional resistor. Our results demonstrate that a voltage gated K+ channel in the excitable tissue of plants has properties of a memristor. The discovery of memristors in plants creates a new direction in the modeling and understanding of electrical phenomena in plants. PMID:25763487

MARSnet: Mission-aware Autonomous Radar Sensor Network for Future Combat Systems 12/8/06 to 12/31/09

DTIC Science & Technology

2010-01-01

8/06 to 12/31/09. Qilian Liang Department of Electrical Engineering 416 Yates Street, Room 518 University of Texas at Arlington Arlington, TX 76019...Modeling in Foliage Environment Jing Liang and Qilian Liang, Senior Member, IEEE Department of Electrical Engineering University of Texas at Arlington E...32 46 of 816 NEW: Network-enabled Electronic Warfare for Target Recognition Qilian Liang Xiuzhen Cheng Sherwood W. Samn Dept of Electrical

Multiple mechanisms switch an electrically coupled, synaptically inhibited neuron between competing rhythmic oscillators.

PubMed

Gutierrez, Gabrielle J; O'Leary, Timothy; Marder, Eve

2013-03-06

Rhythmic oscillations are common features of nervous systems. One of the fundamental questions posed by these rhythms is how individual neurons or groups of neurons are recruited into different network oscillations. We modeled competing fast and slow oscillators connected to a hub neuron with electrical and inhibitory synapses. We explore the patterns of coordination shown in the network as a function of the electrical coupling and inhibitory synapse strengths with the help of a novel visualization method that we call the "parameterscape." The hub neuron can be switched between the fast and slow oscillators by multiple network mechanisms, indicating that a given change in network state can be achieved by degenerate cellular mechanisms. These results have importance for interpreting experiments employing optogenetic, genetic, and pharmacological manipulations to understand circuit dynamics. Copyright © 2013 Elsevier Inc. All rights reserved.

Impact of delays on the synchronization transitions of modular neuronal networks with hybrid synapses

NASA Astrophysics Data System (ADS)

Liu, Chen; Wang, Jiang; Yu, Haitao; Deng, Bin; Wei, Xile; Tsang, Kaiming; Chan, Wailok

2013-09-01

The combined effects of the information transmission delay and the ratio of the electrical and chemical synapses on the synchronization transitions in the hybrid modular neuronal network are investigated in this paper. Numerical results show that the synchronization of neuron activities can be either promoted or destroyed as the information transmission delay increases, irrespective of the probability of electrical synapses in the hybrid-synaptic network. Interestingly, when the number of the electrical synapses exceeds a certain level, further increasing its proportion can obviously enhance the spatiotemporal synchronization transitions. Moreover, the coupling strength has a significant effect on the synchronization transition. The dominated type of the synapse always has a more profound effect on the emergency of the synchronous behaviors. Furthermore, the results of the modular neuronal network structures demonstrate that excessive partitioning of the modular network may result in the dramatic detriment of neuronal synchronization. Considering that information transmission delays are inevitable in intra- and inter-neuronal networks communication, the obtained results may have important implications for the exploration of the synchronization mechanism underlying several neural system diseases such as Parkinson's Disease.

A multi-criteria decision aid methodology to design electric vehicles public charging networks

NASA Astrophysics Data System (ADS)

Raposo, João; Rodrigues, Ana; Silva, Carlos; Dentinho, Tomaz

2015-05-01

This article presents a new multi-criteria decision aid methodology, dynamic-PROMETHEE, here used to design electric vehicle charging networks. In applying this methodology to a Portuguese city, results suggest that it is effective in designing electric vehicle charging networks, generating time and policy based scenarios, considering offer and demand and the city's urban structure. Dynamic-PROMETHE adds to the already known PROMETHEE's characteristics other useful features, such as decision memory over time, versatility and adaptability. The case study, used here to present the dynamic-PROMETHEE, served as inspiration and base to create this new methodology. It can be used to model different problems and scenarios that may present similar requirement characteristics.

Passive Responses Resembling Action Potentials: A Device for the Classroom

ERIC Educational Resources Information Center

Newman, Ian A.; Pickard, Barbara G.

1975-01-01

Describes the construction and operation of a network of entirely passive electrical components that gives a response to an electrical shock similar to an action potential. The network of resistors, capacitors, and diodes was developed to produce responses that would mimic those observed, for example, when a dark-grown pea epicotyl is shocked…

Transient Analysis Generator /TAG/ simulates behavior of large class of electrical networks

NASA Technical Reports Server (NTRS)

Thomas, W. J.

1967-01-01

Transient Analysis Generator program simulates both transient and dc steady-state behavior of a large class of electrical networks. It generates a special analysis program for each circuit described in an easily understood and manipulated programming language. A generator or preprocessor and a simulation system make up the TAG system.

Analysis of electrical tomography sensitive field based on multi-terminal network and electric field

NASA Astrophysics Data System (ADS)

He, Yongbo; Su, Xingguo; Xu, Meng; Wang, Huaxiang

2010-08-01

Electrical tomography (ET) aims at the study of the conductivity/permittivity distribution of the interested field non-intrusively via the boundary voltage/current. The sensor is usually regarded as an electric field, and finite element method (FEM) is commonly used to calculate the sensitivity matrix and to optimize the sensor architecture. However, only the lumped circuit parameters can be measured by the data acquisition electronics, it's very meaningful to treat the sensor as a multi terminal network. Two types of multi terminal network with common node and common loop topologies are introduced. Getting more independent measurements and making more uniform current distribution are the two main ways to minimize the inherent ill-posed effect. By exploring the relationships of network matrixes, a general formula is proposed for the first time to calculate the number of the independent measurements. Additionally, the sensitivity distribution is analyzed with FEM. As a result, quasi opposite mode, an optimal single source excitation mode, that has the advantages of more uniform sensitivity distribution and more independent measurements, is proposed.

Application of neural network for real-time measurement of electrical resistivity in cold crucible

NASA Astrophysics Data System (ADS)

Votava, Pavel; Poznyak, Igor

2017-08-01

The article describes use of an Induction furnace with cold crucible as a tool for real-time measurement of a melted material electrical resistivity. The measurement is based on an inverse problem solution of a 2D mathematical model, possibly implementable in a microcontroller or a FPGA in a form of a neural network. The 2D mathematical model results has been provided as a training set for the neural network. At the end, the implementation results are discussed together with uncertainty of measurement, which is done by the neural network implementation itself.

Noise-assisted energy transport in electrical oscillator networks with off-diagonal dynamical disorder.

PubMed

León-Montiel, Roberto de J; Quiroz-Juárez, Mario A; Quintero-Torres, Rafael; Domínguez-Juárez, Jorge L; Moya-Cessa, Héctor M; Torres, Juan P; Aragón, José L

2015-11-27

Noise is generally thought as detrimental for energy transport in coupled oscillator networks. However, it has been shown that for certain coherently evolving systems, the presence of noise can enhance, somehow unexpectedly, their transport efficiency; a phenomenon called environment-assisted quantum transport (ENAQT) or dephasing-assisted transport. Here, we report on the experimental observation of such effect in a network of coupled electrical oscillators. We demonstrate that by introducing stochastic fluctuations in one of the couplings of the network, a relative enhancement in the energy transport efficiency of 22.5 ± 3.6% can be observed.

The Electrical Network of Maize Root Apex is Gravity Dependent

PubMed Central

Masi, Elisa; Ciszak, Marzena; Comparini, Diego; Monetti, Emanuela; Pandolfi, Camilla; Azzarello, Elisa; Mugnai, Sergio; Baluška, Frantisek; Mancuso, Stefano

2015-01-01

Investigations carried out on maize roots under microgravity and hypergravity revealed that gravity conditions have strong effects on the network of plant electrical activity. Both the duration of action potentials (APs) and their propagation velocities were significantly affected by gravity. Similarly to what was reported for animals, increased gravity forces speed-up APs and enhance synchronized electrical events also in plants. The root apex transition zone emerges as the most active, as well as the most sensitive, root region in this respect. PMID:25588706

The electrical network of maize root apex is gravity dependent.

PubMed

Masi, Elisa; Ciszak, Marzena; Comparini, Diego; Monetti, Emanuela; Pandolfi, Camilla; Azzarello, Elisa; Mugnai, Sergio; Baluška, Frantisek; Mancuso, Stefano

2015-01-15

Investigations carried out on maize roots under microgravity and hypergravity revealed that gravity conditions have strong effects on the network of plant electrical activity. Both the duration of action potentials (APs) and their propagation velocities were significantly affected by gravity. Similarly to what was reported for animals, increased gravity forces speed-up APs and enhance synchronized electrical events also in plants. The root apex transition zone emerges as the most active, as well as the most sensitive, root region in this respect.

Introduction of a new opto-electrical phase-locked loop in CMOS technology: the PMD-PLL

NASA Astrophysics Data System (ADS)

Ringbeck, Thorsten; Schwarte, Rudolf; Buxbaum, Bernd

1999-12-01

The huge and increasing need of information in the industrial world demands an enormous potential of bandwidth in telecommunication systems. Optical communication provides all participants with the whole spectrum of digital services like videophone, cable TV, video conferencing and online services. Especially fast and low cost opto-electrical receivers are badly needed in order to expand fiber networks to every home (FTTH--fiber to the home or FTTD--fiber to the desk, respectively). This paper proposes a new receiver structure which is designed to receiver optical data which are encoded by code division multiple access techniques (CDMA). For data recovery in such CDMA networks phase locked loops (PLL) are needed, which synchronize the local oscillator with the incoming clock. In optical code division multiple access networks these PLLs could be realized either with an electrical PLL after opto-electrical converting or directly in the optical path with a pure optical PLL.

The microeconomics of residential photovoltaics: Tariffs, network operation and maintenance, and ancillary services in distribution-level electricity markets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boero, Riccardo; Backhaus, Scott N.; Edwards, Brian K.

Here, we develop a microeconomic model of a distribution-level electricity market that takes explicit account of residential photovoltaics (PV) adoption. The model allows us to study the consequences of most tariffs on PV adoption and the consequences of increased residential PV adoption under the assumption of economic sustainability for electric utilities. We also validated the model using U.S. data and extend it to consider different pricing schemes for operation and maintenance costs of the distribution network and for ancillary services. Results show that net metering promotes more environmental benefits and social welfare than other tariffs. But, if costs to operatemore » the distribution network increase, net metering will amplify the unequal distribution of surplus among households. In conclusion, maintaining the economic sustainability of electric utilities under net metering may become extremely difficult unless the uneven distribution of surplus is legitimated by environmental benefits.« less

The microeconomics of residential photovoltaics: Tariffs, network operation and maintenance, and ancillary services in distribution-level electricity markets

DOE PAGES

Boero, Riccardo; Backhaus, Scott N.; Edwards, Brian K.

2016-11-12

Here, we develop a microeconomic model of a distribution-level electricity market that takes explicit account of residential photovoltaics (PV) adoption. The model allows us to study the consequences of most tariffs on PV adoption and the consequences of increased residential PV adoption under the assumption of economic sustainability for electric utilities. We also validated the model using U.S. data and extend it to consider different pricing schemes for operation and maintenance costs of the distribution network and for ancillary services. Results show that net metering promotes more environmental benefits and social welfare than other tariffs. But, if costs to operatemore » the distribution network increase, net metering will amplify the unequal distribution of surplus among households. In conclusion, maintaining the economic sustainability of electric utilities under net metering may become extremely difficult unless the uneven distribution of surplus is legitimated by environmental benefits.« less

Electrical network method for the thermal or structural characterization of a conducting material sample or structure

DOEpatents

Ortiz, Marco G.

1993-01-01

A method for modeling a conducting material sample or structure system, as an electrical network of resistances in which each resistance of the network is representative of a specific physical region of the system. The method encompasses measuring a resistance between two external leads and using this measurement in a series of equations describing the network to solve for the network resistances for a specified region and temperature. A calibration system is then developed using the calculated resistances at specified temperatures. This allows for the translation of the calculated resistances to a region temperature. The method can also be used to detect and quantify structural defects in the system.

Electrical network method for the thermal or structural characterization of a conducting material sample or structure

DOEpatents

Ortiz, M.G.

1993-06-08

A method for modeling a conducting material sample or structure system, as an electrical network of resistances in which each resistance of the network is representative of a specific physical region of the system. The method encompasses measuring a resistance between two external leads and using this measurement in a series of equations describing the network to solve for the network resistances for a specified region and temperature. A calibration system is then developed using the calculated resistances at specified temperatures. This allows for the translation of the calculated resistances to a region temperature. The method can also be used to detect and quantify structural defects in the system.

All Optical Solution for Free Space Optics Point to Point Links

NASA Astrophysics Data System (ADS)

Hirayama, Daigo

Optical network systems are quickly replacing electrical network systems. Optical systems provide better bandwidth, faster data rates, better security to networks, and are less susceptible to noise. Free Space Optics (systems) still rely on numerous electrical systems such as the modulation and demodulation systems to convert optical signals to electrical signals for the transmitting laser. As the concept of the entirely optical network becomes more realizable, the electrical components of the FSO system will become a hindrance to communications. The focus of this thesis is to eliminate the electrical devices for the FSO point to point links by replacing them with optical devices. The concept is similar to an extended beam connector. However, where an extended beam connector deals with a gap of a few millimeters, my focus looks at distances from 100 meters to one kilometer. The aim is to achieve a detectable signal of 1nW at a distance of 500 meters at a wavelength of 1500-1600nm. This leads to application in building to building links and mobile networks. The research examines the design of the system in terms of generating the wave, the properties of the fiber feeding the wave, and the power necessary to achieve a usable distance. The simulation is executed in Code V by Synopsys, which is an industry standard to analyze optical systems. A usable device with a range of around 500m was achieved with an input power of 1mW. The approximations of the phase function resulted in some aberrations to the profile of the beam, but were not very detrimental to the function of the device. The removal of electrical devices from a FSO point to point link decreased the power used to establish the link and decreased the cost.

Systems Modelling of the Socio-Technical Aspects of Residential Electricity Use and Network Peak Demand.

PubMed

Lewis, Jim; Mengersen, Kerrie; Buys, Laurie; Vine, Desley; Bell, John; Morris, Peter; Ledwich, Gerard

2015-01-01

Provision of network infrastructure to meet rising network peak demand is increasing the cost of electricity. Addressing this demand is a major imperative for Australian electricity agencies. The network peak demand model reported in this paper provides a quantified decision support tool and a means of understanding the key influences and impacts on network peak demand. An investigation of the system factors impacting residential consumers' peak demand for electricity was undertaken in Queensland, Australia. Technical factors, such as the customers' location, housing construction and appliances, were combined with social factors, such as household demographics, culture, trust and knowledge, and Change Management Options (CMOs) such as tariffs, price, managed supply, etc., in a conceptual 'map' of the system. A Bayesian network was used to quantify the model and provide insights into the major influential factors and their interactions. The model was also used to examine the reduction in network peak demand with different market-based and government interventions in various customer locations of interest and investigate the relative importance of instituting programs that build trust and knowledge through well designed customer-industry engagement activities. The Bayesian network was implemented via a spreadsheet with a tickbox interface. The model combined available data from industry-specific and public sources with relevant expert opinion. The results revealed that the most effective intervention strategies involve combining particular CMOs with associated education and engagement activities. The model demonstrated the importance of designing interventions that take into account the interactions of the various elements of the socio-technical system. The options that provided the greatest impact on peak demand were Off-Peak Tariffs and Managed Supply and increases in the price of electricity. The impact in peak demand reduction differed for each of the locations and highlighted that household numbers, demographics as well as the different climates were significant factors. It presented possible network peak demand reductions which would delay any upgrade of networks, resulting in savings for Queensland utilities and ultimately for households. The use of this systems approach using Bayesian networks to assist the management of peak demand in different modelled locations in Queensland provided insights about the most important elements in the system and the intervention strategies that could be tailored to the targeted customer segments.

Systems Modelling of the Socio-Technical Aspects of Residential Electricity Use and Network Peak Demand

PubMed Central

Lewis, Jim; Mengersen, Kerrie; Buys, Laurie; Vine, Desley; Bell, John; Morris, Peter; Ledwich, Gerard

2015-01-01

Provision of network infrastructure to meet rising network peak demand is increasing the cost of electricity. Addressing this demand is a major imperative for Australian electricity agencies. The network peak demand model reported in this paper provides a quantified decision support tool and a means of understanding the key influences and impacts on network peak demand. An investigation of the system factors impacting residential consumers’ peak demand for electricity was undertaken in Queensland, Australia. Technical factors, such as the customers’ location, housing construction and appliances, were combined with social factors, such as household demographics, culture, trust and knowledge, and Change Management Options (CMOs) such as tariffs, price, managed supply, etc., in a conceptual ‘map’ of the system. A Bayesian network was used to quantify the model and provide insights into the major influential factors and their interactions. The model was also used to examine the reduction in network peak demand with different market-based and government interventions in various customer locations of interest and investigate the relative importance of instituting programs that build trust and knowledge through well designed customer-industry engagement activities. The Bayesian network was implemented via a spreadsheet with a tickbox interface. The model combined available data from industry-specific and public sources with relevant expert opinion. The results revealed that the most effective intervention strategies involve combining particular CMOs with associated education and engagement activities. The model demonstrated the importance of designing interventions that take into account the interactions of the various elements of the socio-technical system. The options that provided the greatest impact on peak demand were Off-Peak Tariffs and Managed Supply and increases in the price of electricity. The impact in peak demand reduction differed for each of the locations and highlighted that household numbers, demographics as well as the different climates were significant factors. It presented possible network peak demand reductions which would delay any upgrade of networks, resulting in savings for Queensland utilities and ultimately for households. The use of this systems approach using Bayesian networks to assist the management of peak demand in different modelled locations in Queensland provided insights about the most important elements in the system and the intervention strategies that could be tailored to the targeted customer segments. PMID:26226511

Accelerated reliability testing of highly aligned single-walled carbon nanotube networks subjected to DC electrical stressing.

PubMed

Strus, Mark C; Chiaramonti, Ann N; Kim, Young Lae; Jung, Yung Joon; Keller, Robert R

2011-07-01

We investigate the electrical reliability of nanoscale lines of highly aligned, networked, metallic/semiconducting single-walled carbon nanotubes (SWCNTs) fabricated through a template-based fluidic assembly process. We find that these SWCNT networks can withstand DC current densities larger than 10 MA cm(-2) for several hours and, in some cases, several days. We develop test methods that show that the degradation rate, failure predictability and total device lifetime can be linked to the initial resistance. Scanning electron and transmission electron microscopy suggest that fabrication variability plays a critical role in the rate of degradation, and we offer an empirical method of quickly determining the long-term performance of a network. We find that well-fabricated lines subject to constant electrical stress show a linear accumulation of damage reminiscent of electromigration in metallic interconnects, and we explore the underlying physical mechanisms that could cause such behavior.

Gap junctions between CA3 pyramidal cells contribute to network synchronization in neonatal hippocampus.

PubMed

Molchanova, Svetlana M; Huupponen, Johanna; Lauri, Sari E; Taira, Tomi

2016-08-01

Direct electrical coupling between neurons through gap junctions is prominent during development, when synaptic connectivity is scarce, providing the additional intercellular connectivity. However, functional studies of gap junctions are hampered by the unspecificity of pharmacological tools available. Here we have investigated gap-junctional coupling between CA3 pyramidal cells in neonatal hippocampus and its contribution to early network activity. Four different gap junction inhibitors, including the general blocker carbenoxolone, decreased the frequency of network activity bursts in CA3 area of hippocampus of P3-6 rats, suggesting the involvement of electrical connections in the generation of spontaneous network activity. In CA3 pyramidal cells, spikelets evoked by local stimulation of stratum oriens, were inhibited by carbenoxolone, but not by inhibitors of glutamatergic and GABAergic synaptic transmission, signifying the presence of electrical connectivity through axo-axonic gap junctions. Carbenoxolone also decreased the success rate of firing antidromic action potentials in response to stimulation, and changed the pattern of spontaneous action potential firing of CA3 pyramidal cells. Altogether, these data suggest that electrical coupling of CA3 pyramidal cells contribute to the generation of the early network events in neonatal hippocampus by modulating their firing pattern and synchronization. Copyright © 2016 Elsevier Ltd. All rights reserved.

Numerical investigation into blood clotting at the bone-dental implant interface in the presence of an electrical stimulus.

PubMed

Vanegas-Acosta, J C; Garzón-Alvarado, D A; Lancellotti, V

2013-12-01

The insertion of a dental implant activates a sequence of wound healing events ending with bone formation and implant osseointegration. This sequence starts with the blood coagulation process and the formation of a fibrin network that detains spilt blood. Fibrin formation can be simplified as the kinetic reaction between thrombin and fibrinogen preceding the conversion of fibrinogen into fibrin. Based on experimental observations of the electrical properties of these molecules, we present a hypothesis for the mechanism of a static electrical stimulus in controlling the formation of the blood clot. Specifically, the electrical stimulus increases the fibrin network formation in such a way that a preferential region of higher fibrin density is obtained. This hypothesis is validated by means of a numerical model for the blood clot formation at the bone-dental implant interface. Numerical results compare favorably to experimental observations for blood clotting with and without the static electrical stimulus. It is concluded that the density of the fibrin network depends on the strength of the static electrical stimulus, and that the blood clot formation has a preferential direction of formation in the presence of the electrical signal. © 2013 Published by Elsevier Ltd. All rights reserved.

Forecasting of the electrical actuators condition using stator’s current signals

NASA Astrophysics Data System (ADS)

Kruglova, T. N.; Yaroshenko, I. V.; Rabotalov, N. N.; Melnikov, M. A.

2017-02-01

This article describes a forecasting method for electrical actuators realized through the combination of Fourier transformation and neural network techniques. The method allows finding the value of diagnostic functions in the iterating operating cycle and the number of operational cycles in time before the BLDC actuator fails. For forecasting of the condition of the actuator, we propose a hierarchical structure of the neural network aiming to reduce the training time of the neural network and improve estimation accuracy.

Stability Enhancement of Silver Nanowire Networks with Conformal ZnO Coatings Deposited by Atmospheric Pressure Spatial Atomic Layer Deposition.

PubMed

Khan, Afzal; Nguyen, Viet Huong; Muñoz-Rojas, David; Aghazadehchors, Sara; Jiménez, Carmen; Nguyen, Ngoc Duy; Bellet, Daniel

2018-06-06

Silver nanowire (AgNW) networks offer excellent electrical and optical properties and have emerged as one of the most attractive alternatives to transparent conductive oxides to be used in flexible optoelectronic applications. However, AgNW networks still suffer from chemical, thermal, and electrical instabilities, which in some cases can hinder their efficient integration as transparent electrodes in devices such as solar cells, transparent heaters, touch screens, and organic light emitting diodes. We have used atmospheric pressure spatial atomic layer deposition (AP-SALD) to fabricate hybrid transparent electrode materials in which the AgNW network is protected by a conformal thin layer of zinc oxide. The choice of AP-SALD allows us to maintain the low-cost and scalable processing of AgNW-based transparent electrodes. The effects of the ZnO coating thickness on the physical properties of AgNW networks are presented. The composite electrodes show a drastic enhancement of both thermal and electrical stabilities. We found that bare AgNWs were stable only up to 300 °C when subjected to thermal ramps, whereas the ZnO coating improved the stability up to 500 °C. Similarly, ZnO-coated AgNWs exhibited an increase of 100% in electrical stability with respect to bare networks, withstanding up to 18 V. A simple physical model shows that the origin of the stability improvement is the result of hindered silver atomic diffusion thanks to the presence of the thin oxide layer and the quality of the interfaces of hybrid electrodes. The effects of ZnO coating on both the network adhesion and optical transparency are also discussed. Finally, we show that the AP-SALD ZnO-coated AgNW networks can be effectively used as very stable transparent heaters.

An electric-analog simulation of elliptic partial differential equations using finite element theory

USGS Publications Warehouse

Franke, O.L.; Pinder, G.F.; Patten, E.P.

1982-01-01

Elliptic partial differential equations can be solved using the Galerkin-finite element method to generate the approximating algebraic equations, and an electrical network to solve the resulting matrices. Some element configurations require the use of networks containing negative resistances which, while physically realizable, are more expensive and time-consuming to construct. ?? 1982.

Control of a solar-energy-supplied electrical-power system without intermediate circuitry

NASA Astrophysics Data System (ADS)

Leistner, K.

A computer control system is developed for electric-power systems comprising solar cells and small numbers of users with individual centrally controlled converters (and storage facilities when needed). Typical system structures are reviewed; the advantages of systems without an intermediate network are outlined; the demands on a control system in such a network (optimizing generator working point and power distribution) are defined; and a flexible modular prototype system is described in detail. A charging station for lead batteries used in electric automobiles is analyzed as an example. The power requirements of the control system (30 W for generator control and 50 W for communications and distribution control) are found to limit its use to larger networks.

The Local Structure of Globalization. The Network Dynamics of Foreign Direct Investments in the International Electricity Industry

NASA Astrophysics Data System (ADS)

Koskinen, Johan; Lomi, Alessandro

2013-05-01

We study the evolution of the network of foreign direct investment (FDI) in the international electricity industry during the period 1994-2003. We assume that the ties in the network of investment relations between countries are created and deleted in continuous time, according to a conditional Gibbs distribution. This assumption allows us to take simultaneously into account the aggregate predictions of the well-established gravity model of international trade as well as local dependencies between network ties connecting the countries in our sample. According to the modified version of the gravity model that we specify, the probability of observing an investment tie between two countries depends on the mass of the economies involved, their physical distance, and the tendency of the network to self-organize into local configurations of network ties. While the limiting distribution of the data generating process is an exponential random graph model, we do not assume the system to be in equilibrium. We find evidence of the effects of the standard gravity model of international trade on evolution of the global FDI network. However, we also provide evidence of significant dyadic and extra-dyadic dependencies between investment ties that are typically ignored in available research. We show that local dependencies between national electricity industries are sufficient for explaining global properties of the network of foreign direct investments. We also show, however, that network dependencies vary significantly over time giving rise to a time-heterogeneous localized process of network evolution.

Effect of the mechanical deformation on the electrical properties of the polymer/CNT fiber

NASA Astrophysics Data System (ADS)

Cho, Hyun Woo; Sung, Bong June; Nano-Bio Computational Chemistry Laboratory Team

2014-03-01

We elucidate the effect of the mechanical deformation on the electrical properties of the polymer/CNT fiber. The conductive polymer fiber has drawn a great attention for its potential application to a stretchable electronics such as wearable devices and artificial muscles, etc. However, the electrical conductivity of the polymer-based stretchable electronics decreases significantly during the deformation, which may limit the applicability of the polymer/CNT fiber for the stretchable electronics. Moreover, its physical origin for the decrease in electrical conductivity has not been explained clearly. In this work, we employ a coarse-grained model for the polymer/CNT fiber, and we calculate the electric conductivity using global tunneling network (GTN) model. We show that the electric conductivity decreases during the elongation of the polymer/CNT fiber. We also find using critical path approximation (CPA) that the structure of the electrical network of the CNTs changes collectively during the elongation of the fiber, which is strongly responsible for the reduction of the electrical conductivity of the polymer/CNT fiber.

Electricity exchange and the valuation of transnational transmission access: A case study of intra-regional integration of the electric industries of Argentina and Chile

NASA Astrophysics Data System (ADS)

Brereton, Beverly Ann

The interconnection of neighboring electricity networks provides opportunities for the realization of synergies between electricity systems. Examples of the synergies to be realized are the rationalized management of the electricity networks whose fuel source domination differs, and the exploitation of non-coincident system peak demands. These factors allow technology diversity in the satisfaction of electricity demand, the coordination of planning and maintenance schedules between the networks by exploiting the cost differences in the pool of generation assets and the load configuration differences in the neighboring locations. The interconnection decision studied in this dissertation focused on the electricity networks of Argentina and Chile whose electricity systems operate in isolation at the current time. The cooperative game-theoretic framework was applied in the analysis of the decision facing the two countries and the net surplus to be derived from interconnection was evaluated. Measurement of the net gains from interconnection used in this study were reflected in changes in generating costs under the assumption that demand is fixed under all scenarios. With the demand for electricity assumed perfectly inelastic, passive or aggressive bidding strategies were considered under the scenarios for the generators in the two countries. The interconnection decision was modeled using a linear power flow model which utilizes linear programming techniques to reflect dispatch procedures based on generation bids. Results of the study indicate that the current interconnection project between Argentina and Chile will not result in positive net surplus under a variety of scenarios. Only under significantly reduced interconnection cost will the venture prove attractive. Possible sharing mechanisms were also explored in the research and a symmetric distribution of the net surplus to be derived under the reduced interconnection cost scenario was recommended to preserve equity in the allocation of the interconnection gains.

Dynamics of global supply chain and electric power networks: Models, pricing analysis, and computations

NASA Astrophysics Data System (ADS)

Matsypura, Dmytro

In this dissertation, I develop a new theoretical framework for the modeling, pricing analysis, and computation of solutions to electric power supply chains with power generators, suppliers, transmission service providers, and the inclusion of consumer demands. In particular, I advocate the application of finite-dimensional variational inequality theory, projected dynamical systems theory, game theory, network theory, and other tools that have been recently proposed for the modeling and analysis of supply chain networks (cf. Nagurney (2006)) to electric power markets. This dissertation contributes to the extant literature on the modeling, analysis, and solution of supply chain networks, including global supply chains, in general, and electric power supply chains, in particular, in the following ways. It develops a theoretical framework for modeling, pricing analysis, and computation of electric power flows/transactions in electric power systems using the rationale for supply chain analysis. The models developed include both static and dynamic ones. The dissertation also adds a new dimension to the methodology of the theory of projected dynamical systems by proving that, irrespective of the speeds of adjustment, the equilibrium of the system remains the same. Finally, I include alternative fuel suppliers, along with their behavior into the supply chain modeling and analysis framework. This dissertation has strong practical implications. In an era in which technology and globalization, coupled with increasing risk and uncertainty, complicate electricity demand and supply within and between nations, the successful management of electric power systems and pricing become increasingly pressing topics with relevance not only for economic prosperity but also national security. This dissertation addresses such related topics by providing models, pricing tools, and algorithms for decentralized electric power supply chains. This dissertation is based heavily on the following coauthored papers: Nagurney, Cruz, and Matsypura (2003), Nagurney and Matsypura (2004, 2005, 2006), Matsypura and Nagurney (2005), Matsypura, Nagurney, and Liu (2006).

AC Electric Field Communication for Human-Area Networking

NASA Astrophysics Data System (ADS)

Kado, Yuichi; Shinagawa, Mitsuru

We have proposed a human-area networking technology that uses the surface of the human body as a data transmission path and uses an AC electric field signal below the resonant frequency of the human body. This technology aims to achieve a “touch and connect” intuitive form of communication by using the electric field signal that propagates along the surface of the human body, while suppressing both the electric field radiating from the human body and mutual interference. To suppress the radiation field, the frequency of the AC signal that excites the transmitter electrode must be lowered, and the sensitivity of the receiver must be raised while reducing transmission power to its minimally required level. We describe how we are developing AC electric field communication technologies to promote the further evolution of a human-area network in support of ubiquitous services, focusing on three main characteristics, enabling-transceiver technique, application-scenario modeling, and communications quality evaluation. Special attention is paid to the relationship between electro-magnetic compatibility evaluation and regulations for extremely low-power radio stations based on Japan's Radio Law.

ESB-based Sensor Web integration for the prediction of electric power supply system vulnerability.

PubMed

Stoimenov, Leonid; Bogdanovic, Milos; Bogdanovic-Dinic, Sanja

2013-08-15

Electric power supply companies increasingly rely on enterprise IT systems to provide them with a comprehensive view of the state of the distribution network. Within a utility-wide network, enterprise IT systems collect data from various metering devices. Such data can be effectively used for the prediction of power supply network vulnerability. The purpose of this paper is to present the Enterprise Service Bus (ESB)-based Sensor Web integration solution that we have developed with the purpose of enabling prediction of power supply network vulnerability, in terms of a prediction of defect probability for a particular network element. We will give an example of its usage and demonstrate our vulnerability prediction model on data collected from two different power supply companies. The proposed solution is an extension of the GinisSense Sensor Web-based architecture for collecting, processing, analyzing, decision making and alerting based on the data received from heterogeneous data sources. In this case, GinisSense has been upgraded to be capable of operating in an ESB environment and combine Sensor Web and GIS technologies to enable prediction of electric power supply system vulnerability. Aside from electrical values, the proposed solution gathers ambient values from additional sensors installed in the existing power supply network infrastructure. GinisSense aggregates gathered data according to an adapted Omnibus data fusion model and applies decision-making logic on the aggregated data. Detected vulnerabilities are visualized to end-users through means of a specialized Web GIS application.

ESB-Based Sensor Web Integration for the Prediction of Electric Power Supply System Vulnerability

PubMed Central

Stoimenov, Leonid; Bogdanovic, Milos; Bogdanovic-Dinic, Sanja

2013-01-01

Electric power supply companies increasingly rely on enterprise IT systems to provide them with a comprehensive view of the state of the distribution network. Within a utility-wide network, enterprise IT systems collect data from various metering devices. Such data can be effectively used for the prediction of power supply network vulnerability. The purpose of this paper is to present the Enterprise Service Bus (ESB)-based Sensor Web integration solution that we have developed with the purpose of enabling prediction of power supply network vulnerability, in terms of a prediction of defect probability for a particular network element. We will give an example of its usage and demonstrate our vulnerability prediction model on data collected from two different power supply companies. The proposed solution is an extension of the GinisSense Sensor Web-based architecture for collecting, processing, analyzing, decision making and alerting based on the data received from heterogeneous data sources. In this case, GinisSense has been upgraded to be capable of operating in an ESB environment and combine Sensor Web and GIS technologies to enable prediction of electric power supply system vulnerability. Aside from electrical values, the proposed solution gathers ambient values from additional sensors installed in the existing power supply network infrastructure. GinisSense aggregates gathered data according to an adapted Omnibus data fusion model and applies decision-making logic on the aggregated data. Detected vulnerabilities are visualized to end-users through means of a specialized Web GIS application. PMID:23955435

Noise-assisted energy transport in electrical oscillator networks with off-diagonal dynamical disorder

PubMed Central

León-Montiel, Roberto de J.; Quiroz-Juárez, Mario A.; Quintero-Torres, Rafael; Domínguez-Juárez, Jorge L.; Moya-Cessa, Héctor M.; Torres, Juan P.; Aragón, José L.

2015-01-01

Noise is generally thought as detrimental for energy transport in coupled oscillator networks. However, it has been shown that for certain coherently evolving systems, the presence of noise can enhance, somehow unexpectedly, their transport efficiency; a phenomenon called environment-assisted quantum transport (ENAQT) or dephasing-assisted transport. Here, we report on the experimental observation of such effect in a network of coupled electrical oscillators. We demonstrate that by introducing stochastic fluctuations in one of the couplings of the network, a relative enhancement in the energy transport efficiency of 22.5 ± 3.6% can be observed. PMID:26610864

Node-node correlations and transport properties in scale-free networks

NASA Astrophysics Data System (ADS)

Obregon, Bibiana; Guzman, Lev

2011-03-01

We study some transport properties of complex networks. We focus our attention on transport properties of scale-free and small-world networks and compare two types of transport: Electric and max-flow cases. In particular, we construct scale-free networks, with a given degree sequence, to estimate the distribution of conductances for different values of assortative/dissortative mixing. For the electric case we find that the distributions of conductances are affect ed by the assortative mixing of the network whereas for the max-flow case, the distributions almost do not show changes when node-node correlations are altered. Finally, we compare local and global transport in terms of the average conductance for the small-world (Watts-Strogatz) model

Modeling the resilience of critical infrastructure: the role of network dependencies.

PubMed

Guidotti, Roberto; Chmielewski, Hana; Unnikrishnan, Vipin; Gardoni, Paolo; McAllister, Therese; van de Lindt, John

2016-01-01

Water and wastewater network, electric power network, transportation network, communication network, and information technology network are among the critical infrastructure in our communities; their disruption during and after hazard events greatly affects communities' well-being, economic security, social welfare, and public health. In addition, a disruption in one network may cause disruption to other networks and lead to their reduced functionality. This paper presents a unified theoretical methodology for the modeling of dependent/interdependent infrastructure networks and incorporates it in a six-step probabilistic procedure to assess their resilience. Both the methodology and the procedure are general, can be applied to any infrastructure network and hazard, and can model different types of dependencies between networks. As an illustration, the paper models the direct effects of seismic events on the functionality of a potable water distribution network and the cascading effects of the damage of the electric power network (EPN) on the potable water distribution network (WN). The results quantify the loss of functionality and delay in the recovery process due to dependency of the WN on the EPN. The results show the importance of capturing the dependency between networks in modeling the resilience of critical infrastructure.

Modeling the resilience of critical infrastructure: the role of network dependencies

PubMed Central

Guidotti, Roberto; Chmielewski, Hana; Unnikrishnan, Vipin; Gardoni, Paolo; McAllister, Therese; van de Lindt, John

2017-01-01

Water and wastewater network, electric power network, transportation network, communication network, and information technology network are among the critical infrastructure in our communities; their disruption during and after hazard events greatly affects communities’ well-being, economic security, social welfare, and public health. In addition, a disruption in one network may cause disruption to other networks and lead to their reduced functionality. This paper presents a unified theoretical methodology for the modeling of dependent/interdependent infrastructure networks and incorporates it in a six-step probabilistic procedure to assess their resilience. Both the methodology and the procedure are general, can be applied to any infrastructure network and hazard, and can model different types of dependencies between networks. As an illustration, the paper models the direct effects of seismic events on the functionality of a potable water distribution network and the cascading effects of the damage of the electric power network (EPN) on the potable water distribution network (WN). The results quantify the loss of functionality and delay in the recovery process due to dependency of the WN on the EPN. The results show the importance of capturing the dependency between networks in modeling the resilience of critical infrastructure. PMID:28825037

Topological properties of a self-assembled electrical network via ab initio calculation

NASA Astrophysics Data System (ADS)

Stephenson, C.; Lyon, D.; Hübler, A.

2017-02-01

Interacting electrical conductors self-assemble to form tree like networks in the presence of applied voltages or currents. Experiments have shown that the degree distribution of the steady state networks are identical over a wide range of network sizes. In this work we develop a new model of the self-assembly process starting from the underlying physical interaction between conductors. In agreement with experimental results we find that for steady state networks, our model predicts that the fraction of endpoints is a constant of 0.252, and the fraction of branch points is 0.237. We find that our model predicts that these scaling properties also hold for the network during the approach to the steady state as well. In addition, we also reproduce the experimental distribution of nodes with a given Strahler number for all steady state networks studied.

Modelling Feedback Excitation, Pacemaker Properties and Sensory Switching of Electrically Coupled Brainstem Neurons Controlling Rhythmic Activity

PubMed Central

Hull, Michael J.; Soffe, Stephen R.; Willshaw, David J.; Roberts, Alan

2016-01-01

What cellular and network properties allow reliable neuronal rhythm generation or firing that can be started and stopped by brief synaptic inputs? We investigate rhythmic activity in an electrically-coupled population of brainstem neurons driving swimming locomotion in young frog tadpoles, and how activity is switched on and off by brief sensory stimulation. We build a computational model of 30 electrically-coupled conditional pacemaker neurons on one side of the tadpole hindbrain and spinal cord. Based on experimental estimates for neuron properties, population sizes, synapse strengths and connections, we show that: long-lasting, mutual, glutamatergic excitation between the neurons allows the network to sustain rhythmic pacemaker firing at swimming frequencies following brief synaptic excitation; activity persists but rhythm breaks down without electrical coupling; NMDA voltage-dependency doubles the range of synaptic feedback strengths generating sustained rhythm. The network can be switched on and off at short latency by brief synaptic excitation and inhibition. We demonstrate that a population of generic Hodgkin-Huxley type neurons coupled by glutamatergic excitatory feedback can generate sustained asynchronous firing switched on and off synaptically. We conclude that networks of neurons with NMDAR mediated feedback excitation can generate self-sustained activity following brief synaptic excitation. The frequency of activity is limited by the kinetics of the neuron membrane channels and can be stopped by brief inhibitory input. Network activity can be rhythmic at lower frequencies if the neurons are electrically coupled. Our key finding is that excitatory synaptic feedback within a population of neurons can produce switchable, stable, sustained firing without synaptic inhibition. PMID:26824331

Teaching Structured Design of Network Algorithms in Enhanced Versions of SQL

ERIC Educational Resources Information Center

de Brock, Bert

2004-01-01

From time to time developers of (database) applications will encounter, explicitly or implicitly, structures such as trees, graphs, and networks. Such applications can, for instance, relate to bills of material, organization charts, networks of (rail)roads, networks of conduit pipes (e.g., plumbing, electricity), telecom networks, and data…

Enhancement of electrical signaling in neural networks on graphene films.

PubMed

Tang, Mingliang; Song, Qin; Li, Ning; Jiang, Ziyun; Huang, Rong; Cheng, Guosheng

2013-09-01

One of the key challenges for neural tissue engineering is to exploit supporting materials with robust functionalities not only to govern cell-specific behaviors, but also to form functional neural network. The unique electrical and mechanical properties of graphene imply it as a promising candidate for neural interfaces, but little is known about the details of neural network formation on graphene as a scaffold material for tissue engineering. Therapeutic regenerative strategies aim to guide and enhance the intrinsic capacity of the neurons to reorganize by promoting plasticity mechanisms in a controllable manner. Here, we investigated the impact of graphene on the formation and performance in the assembly of neural networks in neural stem cell (NSC) culture. Using calcium imaging and electrophysiological recordings, we demonstrate the capabilities of graphene to support the growth of functional neural circuits, and improve neural performance and electrical signaling in the network. These results offer a better understanding of interactions between graphene and NSCs, also they clearly present the great potentials of graphene as neural interface in tissue engineering. Copyright © 2013 Elsevier Ltd. All rights reserved.

Value Creation Through Integrated Networks and Convergence

DOE Office of Scientific and Technical Information (OSTI.GOV)

De Martini, Paul; Taft, Jeffrey D.

2015-04-01

Customer adoption of distributed energy resources and public policies are driving changes in the uses of the distribution system. A system originally designed and built for one-way energy flows from central generating facilities to end-use customers is now experiencing injections of energy from customers anywhere on the grid and frequent reversals in the direction of energy flow. In response, regulators and utilities are re-thinking the design and operations of the grid to create more open and transactive electric networks. This evolution has the opportunity to unlock significant value for customers and utilities. Alternatively, failure to seize this potential may insteadmore » lead to an erosion of value if customers seek to defect and disconnect from the system. This paper will discuss how current grid modernization investments may be leveraged to create open networks that increase value through the interaction of intelligent devices on the grid and prosumerization of customers. Moreover, even greater value can be realized through the synergistic effects of convergence of multiple networks. This paper will highlight examples of the emerging nexus of non-electric networks with electricity.« less

Using a Conflict Map as an Instructional Tool To Change Student Conceptions in Simple Series Electric-Circuits.

ERIC Educational Resources Information Center

Tsai, Chin-Chung

2003-01-01

Examines the effects of using a conflict map on 8th grade students' conceptual change and ideational networks about simple series electric circuits. Analyzes student interview data through a flow map method. Shows that the use of conflict maps could help students construct greater, richer, and more integrated ideational networks about electric…

Memory elements in the electrical network of Mimosa pudica L.

PubMed Central

Volkov, Alexander G; Reedus, Jada; Mitchell, Colee M; Tuckett, Clayton; Volkova, Maya I; Markin, Vladislav S; Chua, Leon

2014-01-01

The fourth basic circuit element, a memristor, is a resistor with memory that was postulated by Chua in 1971. Here we found that memristors exist in vivo. The electrostimulation of the Mimosa pudica by bipolar sinusoidal or triangle periodic waves induce electrical responses with fingerprints of memristors. Uncouplers carbonylcyanide-3-chlorophenylhydrazone and carbonylcyanide-4-trifluoromethoxy-phenyl hydrazone decrease the amplitude of electrical responses at low and high frequencies of bipolar sinusoidal or triangle periodic electrostimulating waves. Memristive behavior of an electrical network in the Mimosa pudica is linked to the properties of voltage gated ion channels: the channel blocker TEACl reduces the electric response to a conventional resistor. Our results demonstrate that a voltage gated K+ channel in the excitable tissue of plants has properties of a memristor. The discovery of memristors in plants creates a new direction in the modeling and understanding of electrical phenomena in plants. PMID:25482796

Memory elements in the electrical network of Mimosa pudica L.

PubMed

Volkov, Alexander G; Reedus, Jada; Mitchell, Colee M; Tuckett, Clayton; Volkova, Maya I; Markin, Vladislav S; Chua, Leon

2014-01-01

The fourth basic circuit element, a memristor, is a resistor with memory that was postulated by Chua in 1971. Here we found that memristors exist in vivo. The electrostimulation of the Mimosa pudica by bipolar sinusoidal or triangle periodic waves induce electrical responses with fingerprints of memristors. Uncouplers carbonylcyanide-3-chlorophenylhydrazone and carbonylcyanide-4-trifluoromethoxy-phenyl hydrazone decrease the amplitude of electrical responses at low and high frequencies of bipolar sinusoidal or triangle periodic electrostimulating waves. Memristive behavior of an electrical network in the Mimosa pudica is linked to the properties of voltage gated ion channels: the channel blocker TEACl reduces the electric response to a conventional resistor. Our results demonstrate that a voltage gated K(+) channel in the excitable tissue of plants has properties of a memristor. The discovery of memristors in plants creates a new direction in the modeling and understanding of electrical phenomena in plants.

The control of a parallel hybrid-electric propulsion system for a small unmanned aerial vehicle using a CMAC neural network.

PubMed

Harmon, Frederick G; Frank, Andrew A; Joshi, Sanjay S

2005-01-01

A Simulink model, a propulsion energy optimization algorithm, and a CMAC controller were developed for a small parallel hybrid-electric unmanned aerial vehicle (UAV). The hybrid-electric UAV is intended for military, homeland security, and disaster-monitoring missions involving intelligence, surveillance, and reconnaissance (ISR). The Simulink model is a forward-facing simulation program used to test different control strategies. The flexible energy optimization algorithm for the propulsion system allows relative importance to be assigned between the use of gasoline, electricity, and recharging. A cerebellar model arithmetic computer (CMAC) neural network approximates the energy optimization results and is used to control the parallel hybrid-electric propulsion system. The hybrid-electric UAV with the CMAC controller uses 67.3% less energy than a two-stroke gasoline-powered UAV during a 1-h ISR mission and 37.8% less energy during a longer 3-h ISR mission.

Simulation Tools and Techniques for Analyzing the Impacts of Photovoltaic System Integration

NASA Astrophysics Data System (ADS)

Hariri, Ali

Solar photovoltaic (PV) energy integration in distribution networks is one of the fastest growing sectors of distributed energy integration. The growth in solar PV integration is incentivized by various clean power policies, global interest in solar energy, and reduction in manufacturing and installation costs of solar energy systems. The increase in solar PV integration has raised a number of concerns regarding the potential impacts that might arise as a result of high PV penetration. Some impacts have already been recorded in networks with high PV penetration such as in China, Germany, and USA (Hawaii and California). Therefore, network planning is becoming more intricate as new technologies are integrated into the existing electric grid. The integrated new technologies pose certain compatibility concerns regarding the existing electric grid infrastructure. Therefore, PV integration impact studies are becoming more essential in order to have a better understanding of how to advance the solar PV integration efforts without introducing adverse impacts into the network. PV impact studies are important for understanding the nature of the new introduced phenomena. Understanding the nature of the potential impacts is a key factor for mitigating and accommodating for said impacts. Traditionally, electric power utilities relied on phasor-based power flow simulations for planning their electric networks. However, the conventional, commercially available, phasor-based simulation tools do not provide proper visibility across a wide spectrum of electric phenomena. Moreover, different types of simulation approaches are suitable for specific types of studies. For instance, power flow software cannot be used for studying time varying phenomena. At the same time, it is not practical to use electromagnetic transient (EMT) tools to perform power flow solutions. Therefore, some electric phenomena caused by the variability of PV generation are not visible using the conventional utility simulation software. On the other hand, EMT simulation tools provide high accuracy and visibility over a wide bandwidth of frequencies at the expense of larger processing and memory requirements, limited network size, and long simulation time. Therefore, there is a gap in simulation tools and techniques that can efficiently and effectively identify potential PV impact. New planning simulation tools are needed in order to accommodate for the simulation requirements of new integrated technologies in the electric grid. The dissertation at hand starts by identifying some of the potential impacts that are caused by high PV penetration. A phasor-based quasi-static time series (QSTS) analysis tool is developed in order to study the slow dynamics that are caused by the variations in the PV generation that lead to voltage fluctuations. Moreover, some EMT simulations are performed in order to study the impacts of PV systems on the electric network harmonic levels. These studies provide insights into the type and duration of certain impacts, as well as the conditions that may lead to adverse phenomena. In addition these studies present an idea about the type of simulation tools that are sufficient for each type of study. After identifying some of the potential impacts, certain planning tools and techniques are proposed. The potential PV impacts may cause certain utilities to refrain from integrating PV systems into their networks. However, each electric network has a certain limit beyond which the impacts become substantial and may adversely interfere with the system operation and the equipment along the feeder; this limit is referred to as the hosting limit (or hosting capacity). Therefore, it is important for utilities to identify the PV hosting limit on a specific electric network in order to safely and confidently integrate the maximum possible PV systems. In the following dissertation, two approaches have been proposed for identifying the hosing limit: 1. Analytical approach: this is a theoretical mathematical approach that demonstrated the understanding of the fundamentals of electric power system operation. It provides an easy way to estimate the maximum amount of PV power that can be injected at each node in the network. This approach has been tested and validated. 2. Stochastic simulation software approach: this approach provides a comprehensive simulation software that can be used in order to identify the PV hosting limit. The software performs a large number of stochastic simulation while varying the PV system size and location. The collected data is then analyzed for violations in the voltage levels, voltage fluctuations and reverse power flow. (Abstract shortened by ProQuest.).

Developing Large-Scale Bayesian Networks by Composition: Fault Diagnosis of Electrical Power Systems in Aircraft and Spacecraft

NASA Technical Reports Server (NTRS)

Mengshoel, Ole Jakob; Poll, Scott; Kurtoglu, Tolga

2009-01-01

This CD contains files that support the talk (see CASI ID 20100021404). There are 24 models that relate to the ADAPT system and 1 Excel worksheet. In the paper an investigation into the use of Bayesian networks to construct large-scale diagnostic systems is described. The high-level specifications, Bayesian networks, clique trees, and arithmetic circuits representing 24 different electrical power systems are described in the talk. The data in the CD are the models of the 24 different power systems.

Fiber-Optic Distribution Of Pulsed Power To Multiple Sensors

NASA Technical Reports Server (NTRS)

Kirkham, Harold

1996-01-01

Optoelectronic systems designed according to time-sharing scheme distribute optical power to multiple integrated-circuit-based sensors in fiber-optic networks. Networks combine flexibility of electronic sensing circuits with advantage of electrical isolation afforded by use of optical fibers instead of electrical conductors to transmit both signals and power. Fiber optics resist corrosion and immune to electromagnetic interference. Sensor networks of this type useful in variety of applications; for example, in monitoring strains in aircraft, buildings, and bridges, and in monitoring and controlling shapes of flexible structures.

Inhibition Potentiates the Synchronizing Action of Electrical Synapses

PubMed Central

Pfeuty, Benjamin; Golomb, David; Mato, Germán; Hansel, David

2007-01-01

In vivo and in vitro experimental studies have found that blocking electrical interactions connecting GABAergic interneurons reduces oscillatory activity in the γ range in cortex. However, recent theoretical works have shown that the ability of electrical synapses to promote or impede synchrony, when alone, depends on their location on the dendritic tree of the neurons, the intrinsic properties of the neurons and the connectivity of the network. The goal of the present paper is to show that this versatility in the synchronizing ability of electrical synapses is greatly reduced when the neurons also interact via inhibition. To this end, we study a model network comprising two-compartment conductance-based neurons interacting with both types of synapses. We investigate the effect of electrical synapses on the dynamical state of the network as a function of the strength of the inhibition. We find that for weak inhibition, electrical synapses reinforce inhibition-generated synchrony only if they promote synchrony when they are alone. In contrast, when inhibition is sufficiently strong, electrical synapses improve synchrony even if when acting alone they would stabilize asynchronous firing. We clarify the mechanism underlying this cooperative interplay between electrical and inhibitory synapses. We show that it is relevant in two physiologically observed regimes: spike-to-spike synchrony, where neurons fire at almost every cycle of the population oscillations, and stochastic synchrony, where neurons fire irregularly and at a rate which is substantially lower than the frequency of the global population rhythm. PMID:18946530

Short-term forecasting of electric loads using nonlinear autoregressive artificial neural networks with exogenous vector inputs

DOE PAGES

Buitrago, Jaime; Asfour, Shihab

2017-01-01

Short-term load forecasting is crucial for the operations planning of an electrical grid. Forecasting the next 24 h of electrical load in a grid allows operators to plan and optimize their resources. The purpose of this study is to develop a more accurate short-term load forecasting method utilizing non-linear autoregressive artificial neural networks (ANN) with exogenous multi-variable input (NARX). The proposed implementation of the network is new: the neural network is trained in open-loop using actual load and weather data, and then, the network is placed in closed-loop to generate a forecast using the predicted load as the feedback input.more » Unlike the existing short-term load forecasting methods using ANNs, the proposed method uses its own output as the input in order to improve the accuracy, thus effectively implementing a feedback loop for the load, making it less dependent on external data. Using the proposed framework, mean absolute percent errors in the forecast in the order of 1% have been achieved, which is a 30% improvement on the average error using feedforward ANNs, ARMAX and state space methods, which can result in large savings by avoiding commissioning of unnecessary power plants. Finally, the New England electrical load data are used to train and validate the forecast prediction.« less

Micro-grid platform based on NODE.JS architecture, implemented in electrical network instrumentation

NASA Astrophysics Data System (ADS)

Duque, M.; Cando, E.; Aguinaga, A.; Llulluna, F.; Jara, N.; Moreno, T.

2016-05-01

In this document, I propose a theory about the impact of systems based on microgrids in non-industrialized countries that have the goal to improve energy exploitation through alternatives methods of a clean and renewable energy generation and the creation of the app to manage the behavior of the micro-grids based on the NodeJS, Django and IOJS technologies. The micro-grids allow the optimal way to manage energy flow by electric injection directly in electric network small urban's cells in a low cost and available way. In difference from conventional systems, micro-grids can communicate between them to carry energy to places that have higher demand in accurate moments. This system does not require energy storage, so, costs are lower than conventional systems like fuel cells, solar panels or else; even though micro-grids are independent systems, they are not isolated. The impact that this analysis will generate, is the improvement of the electrical network without having greater control than an intelligent network (SMART-GRID); this leads to move to a 20% increase in energy use in a specified network; that suggest there are others sources of energy generation; but for today's needs, we need to standardize methods and remain in place to support all future technologies and the best option are the Smart Grids and Micro-Grids.

Short-term forecasting of electric loads using nonlinear autoregressive artificial neural networks with exogenous vector inputs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Buitrago, Jaime; Asfour, Shihab

Short-term load forecasting is crucial for the operations planning of an electrical grid. Forecasting the next 24 h of electrical load in a grid allows operators to plan and optimize their resources. The purpose of this study is to develop a more accurate short-term load forecasting method utilizing non-linear autoregressive artificial neural networks (ANN) with exogenous multi-variable input (NARX). The proposed implementation of the network is new: the neural network is trained in open-loop using actual load and weather data, and then, the network is placed in closed-loop to generate a forecast using the predicted load as the feedback input.more » Unlike the existing short-term load forecasting methods using ANNs, the proposed method uses its own output as the input in order to improve the accuracy, thus effectively implementing a feedback loop for the load, making it less dependent on external data. Using the proposed framework, mean absolute percent errors in the forecast in the order of 1% have been achieved, which is a 30% improvement on the average error using feedforward ANNs, ARMAX and state space methods, which can result in large savings by avoiding commissioning of unnecessary power plants. Finally, the New England electrical load data are used to train and validate the forecast prediction.« less

Carbon nanotubes might improve neuronal performance by favouring electrical shortcuts.

PubMed

Cellot, Giada; Cilia, Emanuele; Cipollone, Sara; Rancic, Vladimir; Sucapane, Antonella; Giordani, Silvia; Gambazzi, Luca; Markram, Henry; Grandolfo, Micaela; Scaini, Denis; Gelain, Fabrizio; Casalis, Loredana; Prato, Maurizio; Giugliano, Michele; Ballerini, Laura

2009-02-01

Carbon nanotubes have been applied in several areas of nerve tissue engineering to probe and augment cell behaviour, to label and track subcellular components, and to study the growth and organization of neural networks. Recent reports show that nanotubes can sustain and promote neuronal electrical activity in networks of cultured cells, but the ways in which they affect cellular function are still poorly understood. Here, we show, using single-cell electrophysiology techniques, electron microscopy analysis and theoretical modelling, that nanotubes improve the responsiveness of neurons by forming tight contacts with the cell membranes that might favour electrical shortcuts between the proximal and distal compartments of the neuron. We propose the 'electrotonic hypothesis' to explain the physical interactions between the cell and nanotube, and the mechanisms of how carbon nanotubes might affect the collective electrical activity of cultured neuronal networks. These considerations offer a perspective that would allow us to predict or engineer interactions between neurons and carbon nanotubes.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Trinklei, Eddy; Parker, Gordon; Weaver, Wayne

This report presents a scoping study for networked microgrids which are defined as "Interoperable groups of multiple Advanced Microgrids that become an integral part of the electricity grid while providing enhanced resiliency through self-healing, aggregated ancillary services, and real-time communication." They result in optimal electrical system configurations and controls whether grid-connected or in islanded modes and enable high penetrations of distributed and renewable energy resources. The vision for the purpose of this document is: "Networked microgrids seamlessly integrate with the electricity grid or other Electric Power Sources (EPS) providing cost effective, high quality, reliable, resilient, self-healing power delivery systems." Scopingmore » Study: Networked Microgrids September 4, 2014 Eddy Trinklein, Michigan Technological University Gordon Parker, Michigan Technological University Wayne Weaver, Michigan Technological University Rush Robinett, Michigan Technological University Lucia Gauchia Babe, Michigan Technological University Chee-Wooi Ten, Michigan Technological University Ward Bower, Ward Bower Innovations LLC Steve Glover, Sandia National Laboratories Steve Bukowski, Sandia National Laboratories Prepared by Michigan Technological University Houghton, Michigan 49931 Michigan Technological University« less

Towards more Global Coordination of Atmospheric Electricity Measurements (GloCAEM)

NASA Astrophysics Data System (ADS)

Nicoll, Keri; Harrison, Giles

2017-04-01

Earth's atmospheric electrical environment has been studied since the 1750s but its more recent applications to science questions around clouds and climate highlight the incompleteness of our understanding, in part due to lack of suitable global measurements. The Global Electric Circuit (GEC) sustains the near-surface fair weather (FW) electric field, which is present globally in regions which are not strongly electrically disturbed by weather or pollution. It can be measured routinely at the surface using well established instrumentation such as electric field mills. Despite the central role of lightning as a weather hazard and the potentially widespread importance of charge for atmospheric processes, research is hampered by the fragmented nature of surface atmospheric electricity measurements. This makes anything other than local studies in fortuitous fair weather conditions difficult. In contrast to detection of global lightning using satellite measurements and ground-based radio networks, the FW electric field and GEC cannot be measured by remote sensing and no similar measurement networks exist for its study. This presents an opportunity as many researchers worldwide now make high temporal resolution measurements of the FW electric field routinely, which is neither coordinated nor exploited. The GLOCAEM (Global Coordination of Atmospheric Electricity Measurements) project is currently bringing some of these experts together to make the first steps towards an effective global network for FW atmospheric electricity monitoring. A specific objective of the project is to establish the first modern archive of international FW atmospheric electric field data in close to real time to allow global studies of atmospheric electricity to be straightforwardly and robustly performed. Data will be archived through the UK Centre for Environmental Data Analysis (CEDA) and will be available for download by users from early 2018. Both 1 second and 1 minute electric field data will be archived, along with meteorological measurements (if available) for ease of interpretation of electrical measurements. Although the primary aim of the project is to provide a close to real time electric field database, archiving of existing historical electric field datasets is also planned to extend the range of studies possible. This presentation will provide a summary of progress with the GLOCAEM project.

Critical behaviour in charging of electric vehicles

NASA Astrophysics Data System (ADS)

Carvalho, Rui; Buzna, Lubos; Gibbens, Richard; Kelly, Frank

2015-09-01

The increasing penetration of electric vehicles over the coming decades, taken together with the high cost to upgrade local distribution networks and consumer demand for home charging, suggest that managing congestion on low voltage networks will be a crucial component of the electric vehicle revolution and the move away from fossil fuels in transportation. Here, we model the max-flow and proportional fairness protocols for the control of congestion caused by a fleet of vehicles charging on two real-world distribution networks. We show that the system undergoes a continuous phase transition to a congested state as a function of the rate of vehicles plugging to the network to charge. We focus on the order parameter and its fluctuations close to the phase transition, and show that the critical point depends on the choice of congestion protocol. Finally, we analyse the inequality in the charging times as the vehicle arrival rate increases, and show that charging times are considerably more equitable in proportional fairness than in max-flow.

Oscillations emerging from noise-driven steady state in networks with electrical synapses and subthreshold resonance

PubMed Central

Tchumatchenko, Tatjana; Clopath, Claudia

2014-01-01

Oscillations play a critical role in cognitive phenomena and have been observed in many brain regions. Experimental evidence indicates that classes of neurons exhibit properties that could promote oscillations, such as subthreshold resonance and electrical gap junctions. Typically, these two properties are studied separately but it is not clear which is the dominant determinant of global network rhythms. Our aim is to provide an analytical understanding of how these two effects destabilize the fluctuation-driven state, in which neurons fire irregularly, and lead to an emergence of global synchronous oscillations. Here we show how the oscillation frequency is shaped by single neuron resonance, electrical and chemical synapses.The presence of both gap junctions and subthreshold resonance are necessary for the emergence of oscillations. Our results are in agreement with several experimental observations such as network responses to oscillatory inputs and offer a much-needed conceptual link connecting a collection of disparate effects observed in networks. PMID:25405458

The quantum CP-violating kaon system reproduced in the electronic laboratory

NASA Astrophysics Data System (ADS)

Caruso, M.; Fanchiotti, H.; García Canal, C. A.; Mayosky, M.; Veiga, A.

2016-11-01

The equivalence between the Schrödinger dynamics of a quantum system with a finite number of basis states and a classical dynamics is realized in terms of electric networks. The isomorphism that connects in a univocal way both dynamical systems was applied to the case of neutral mesons, kaons in particular, and the class of electric networks univocally related to the quantum system was analysed. Moreover, under CPT invariance, the relevant ɛ parameter that measures CP violation in the kaon system is reinterpreted in terms of network parameters. All these results were explicitly shown by means of both a numerical simulation of the implied networks and by constructing the corresponding circuits.

Forecasting Electric Power Generation of Photovoltaic Power System for Energy Network

NASA Astrophysics Data System (ADS)

Kudo, Mitsuru; Takeuchi, Akira; Nozaki, Yousuke; Endo, Hisahito; Sumita, Jiro

Recently, there has been an increase in concern about the global environment. Interest is growing in developing an energy network by which new energy systems such as photovoltaic and fuel cells generate power locally and electric power and heat are controlled with a communications network. We developed the power generation forecast method for photovoltaic power systems in an energy network. The method makes use of weather information and regression analysis. We carried out forecasting power output of the photovoltaic power system installed in Expo 2005, Aichi Japan. As a result of comparing measurements with a prediction values, the average prediction error per day was about 26% of the measured power.

Energy regeneration model of self-consistent field of electron beams into electric power*

NASA Astrophysics Data System (ADS)

Kazmin, B. N.; Ryzhov, D. R.; Trifanov, I. V.; Snezhko, A. A.; Savelyeva, M. V.

2016-04-01

We consider physic-mathematical models of electric processes in electron beams, conversion of beam parameters into electric power values and their transformation into users’ electric power grid (onboard spacecraft network). We perform computer simulation validating high energy efficiency of the studied processes to be applied in the electric power technology to produce the power as well as electric power plants and propulsion installation in the spacecraft.

Network Capacity Assessment of CHP-based Distributed Generation on Urban Energy Distribution Networks

NASA Astrophysics Data System (ADS)

Zhang, Xianjun

The combined heat and power (CHP)-based distributed generation (DG) or dis-tributed energy resources (DERs) are mature options available in the present energy market, considered to be an effective solution to promote energy efficiency. In the urban environment, the electricity, water and natural gas distribution networks are becoming increasingly interconnected with the growing penetration of the CHP-based DG. Subsequently, this emerging interdependence leads to new topics meriting serious consideration: how much of the CHP-based DG can be accommodated and where to locate these DERs, and given preexisting constraints, how to quantify the mutual impacts on operation performances between these urban energy distribution networks and the CHP-based DG. The early research work was conducted to investigate the feasibility and design methods for one residential microgrid system based on existing electricity, water and gas infrastructures of a residential community, mainly focusing on the economic planning. However, this proposed design method cannot determine the optimal DG sizing and siting for a larger test bed with the given information of energy infrastructures. In this context, a more systematic as well as generalized approach should be developed to solve these problems. In the later study, the model architecture that integrates urban electricity, water and gas distribution networks, and the CHP-based DG system was developed. The proposed approach addressed the challenge of identifying the optimal sizing and siting of the CHP-based DG on these urban energy networks and the mutual impacts on operation performances were also quantified. For this study, the overall objective is to maximize the electrical output and recovered thermal output of the CHP-based DG units. The electricity, gas, and water system models were developed individually and coupled by the developed CHP-based DG system model. The resultant integrated system model is used to constrain the DG's electrical output and recovered thermal output, which are affected by multiple factors and thus analyzed in different case studies. The results indicate that the designed typical gas system is capable of supplying sufficient natural gas for the DG normal operation, while the present water system cannot support the complete recovery of the exhaust heat from the DG units.

Electric Vehicles in Colorado: Anticipating Consumer Demand for Direct Current Fast Charging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wood, Eric W.; Rames, Clement L.

To support the State of Colorado in planning for growth in direct current fast charging (DCFC) for electric vehicles, the National Renewable Energy Laboratory (NREL) has partnered with the Regional Air Quality Council (RAQC) and the Colorado Department of Transportation (CDOT) to analyze a number of DCFC investment scenarios. NREL analyzed existing electric vehicle registration data from IHS Markit (IHS) to highlight early trends in the electric vehicle market, which were compared with sales forecasts predicting large growth in the Colorado electric vehicle market. Electric vehicle forecasts were then used to develop future DCFC scenarios to be evaluated in amore » simulation environment to estimate consumer benefits of the hypothetical DCFC networks in terms of increased driving range and electric vehicle miles traveled (eVMT). Simulated utilization of the hypothetical DCFC networks was analyzed for geographic trends, particularly for correlations with vehicle electric range. Finally, a subset of simulations is presented for consumers with potentially inconsistent access to charging at their home location and presumably greater reliance on public DCFC infrastructure.« less

Distal gap junctions and active dendrites can tune network dynamics.

PubMed

Saraga, Fernanda; Ng, Leo; Skinner, Frances K

2006-03-01

Gap junctions allow direct electrical communication between CNS neurons. From theoretical and modeling studies, it is well known that although gap junctions can act to synchronize network output, they can also give rise to many other dynamic patterns including antiphase and other phase-locked states. The particular network pattern that arises depends on cellular, intrinsic properties that affect firing frequencies as well as the strength and location of the gap junctions. Interneurons or GABAergic neurons in hippocampus are diverse in their cellular characteristics and have been shown to have active dendrites. Furthermore, parvalbumin-positive GABAergic neurons, also known as basket cells, can contact one another via gap junctions on their distal dendrites. Using two-cell network models, we explore how distal electrical connections affect network output. We build multi-compartment models of hippocampal basket cells using NEURON and endow them with varying amounts of active dendrites. Two-cell networks of these model cells as well as reduced versions are explored. The relationship between intrinsic frequency and the level of active dendrites allows us to define three regions based on what sort of network dynamics occur with distal gap junction coupling. Weak coupling theory is used to predict the delineation of these regions as well as examination of phase response curves and distal dendritic polarization levels. We find that a nonmonotonic dependence of network dynamic characteristics (phase lags) on gap junction conductance occurs. This suggests that distal electrical coupling and active dendrite levels can control how sensitive network dynamics are to gap junction modulation. With the extended geometry, gap junctions located at more distal locations must have larger conductances for pure synchrony to occur. Furthermore, based on simulations with heterogeneous networks, it may be that one requires active dendrites if phase-locking is to occur in networks formed with distal gap junctions.

Assessment of critical path analyses of the relationship between permeability and electrical conductivity of pore networks

NASA Astrophysics Data System (ADS)

Skaggs, Todd H.

2011-10-01

Critical path analysis (CPA) is a method for estimating macroscopic transport coefficients of heterogeneous materials that are highly disordered at the micro-scale. Developed originally to model conduction in semiconductors, numerous researchers have noted that CPA might also have relevance to flow and transport processes in porous media. However, the results of several numerical investigations of critical path analysis on pore network models raise questions about the applicability of CPA to porous media. Among other things, these studies found that (i) in well-connected 3D networks, CPA predictions were inaccurate and became worse when heterogeneity was increased; and (ii) CPA could not fully explain the transport properties of 2D networks. To better understand the applicability of CPA to porous media, we made numerical computations of permeability and electrical conductivity on 2D and 3D networks with differing pore-size distributions and geometries. A new CPA model for the relationship between the permeability and electrical conductivity was found to be in good agreement with numerical data, and to be a significant improvement over a classical CPA model. In sufficiently disordered 3D networks, the new CPA prediction was within ±20% of the true value, and was nearly optimal in terms of minimizing the squared prediction errors across differing network configurations. The agreement of CPA predictions with 2D network computations was similarly good, although 2D networks are in general not well-suited for evaluating CPA. Numerical transport coefficients derived for regular 3D networks of slit-shaped pores were found to be in better agreement with experimental data from rock samples than were coefficients derived for networks of cylindrical pores.

Teaching Network Security with IP Darkspace Data

ERIC Educational Resources Information Center

Zseby, Tanja; Iglesias Vázquez, Félix; King, Alistair; Claffy, K. C.

2016-01-01

This paper presents a network security laboratory project for teaching network traffic anomaly detection methods to electrical engineering students. The project design follows a research-oriented teaching principle, enabling students to make their own discoveries in real network traffic, using data captured from a large IP darkspace monitor…

Stability and chaos of Rulkov map-based neuron network with electrical synapse

NASA Astrophysics Data System (ADS)

Wang, Caixia; Cao, Hongjun

2015-02-01

In this paper, stability and chaos of a simple system consisting of two identical Rulkov map-based neurons with the bidirectional electrical synapse are investigated in detail. On the one hand, as a function of control parameters and electrical coupling strengthes, the conditions for stability of fixed points of this system are obtained by using the qualitative analysis. On the other hand, chaos in the sense of Marotto is proved by a strict mathematical way. These results could be useful for building-up large-scale neurons networks with specific dynamics and rich biophysical phenomena.

Large-size, high-uniformity, random silver nanowire networks as transparent electrodes for crystalline silicon wafer solar cells.

PubMed

Xie, Shouyi; Ouyang, Zi; Jia, Baohua; Gu, Min

2013-05-06

Metal nanowire networks are emerging as next generation transparent electrodes for photovoltaic devices. We demonstrate the application of random silver nanowire networks as the top electrode on crystalline silicon wafer solar cells. The dependence of transmittance and sheet resistance on the surface coverage is measured. Superior optical and electrical properties are observed due to the large-size, highly-uniform nature of these networks. When applying the nanowire networks on the solar cells with an optimized two-step annealing process, we achieved as large as 19% enhancement on the energy conversion efficiency. The detailed analysis reveals that the enhancement is mainly caused by the improved electrical properties of the solar cells due to the silver nanowire networks. Our result reveals that this technology is a promising alternative transparent electrode technology for crystalline silicon wafer solar cells.

Functional Differentiation of a Population of Electrically-Coupled Heterogeneous Elements in a Microcircuit

PubMed Central

Sasaki, Kosei; Cropper, Elizabeth C; Weiss, Klaudiusz R; Jing, Jian

2013-01-01

Although electrical coupling is present in many microcircuits, the extent to which it will determine neuronal firing patterns and network activity remains poorly understood. This is particularly true when the coupling is present in a population of heterogeneous, or intrinsically distinct circuit elements. We examine this question in the Aplysia californica feeding motor network in five electrically-coupled identified cells, B64, B4/5, B70, B51 and a newly-identified interneuron B71. These neurons exhibit distinct activity patterns during the radula retraction phase of motor programs. In a subset of motor programs, retraction can be flexibly extended by adding a phase of network activity (hyper-retraction). This is manifested most prominently as an additional burst in the radula closure motoneuron B8. Two neurons that excite B8 (B51 and B71) and one that inhibits it (B70) are active during hyper-retraction. Consistent with their near synchronous firing, B51 and B71 showed one of the strongest coupling ratios in this group of neurons. Nonetheless, by manipulating their activity, we found that B51 preferentially acted as a driver of B64/B71 activity, whereas B71 played a larger role in driving B8 activity. In contrast, B70 was weakly coupled to other neurons and its inhibition of B8 counter-acted the excitatory drive to B8. Finally, the distinct firing patterns of the electrically-coupled neurons were fine-tuned by their intrinsic properties and the largely chemical cross-inhibition between some of them. Thus, the small microcircuit of Aplysia feeding network is advantageous in understanding how a population of electrically-coupled heterogeneous neurons may fulfill specific network functions. PMID:23283325

An innovation diffusion model of a local electricity network that is influenced by internal and external factors

NASA Astrophysics Data System (ADS)

Hattam, Laura; Greetham, Danica Vukadinović

2018-01-01

Haynes et al. (1977) derived a nonlinear differential equation to determine the spread of innovations within a social network across space and time. This model depends upon the imitators and the innovators within the social system, where the imitators respond to internal influences, whilst the innovators react to external factors. Here, this differential equation is applied to simulate the uptake of a low-carbon technology (LCT) within a real local electricity network that is situated in the UK. This network comprises of many households that are assigned to certain feeders. Firstly, travelling wave solutions of Haynes' model are used to predict adoption times as a function of the imitation and innovation influences. Then, the grid that represents the electricity network is created so that the finite element method (FEM) can be implemented. Next, innovation diffusion is modelled with Haynes' equation and the FEM, where varying magnitudes of the internal and external pressures are imposed. Consequently, the impact of these model parameters is investigated. Moreover, LCT adoption trajectories at fixed feeder locations are calculated, which give a macroscopic understanding of the uptake behaviour at specific network sites. Lastly, the adoption of LCTs at a household level is examined, where microscopic and macroscopic approaches are combined.

Applying the Network Simulation Method for testing chaos in a resistively and capacitively shunted Josephson junction model

NASA Astrophysics Data System (ADS)

Bellver, Fernando Gimeno; Garratón, Manuel Caravaca; Soto Meca, Antonio; López, Juan Antonio Vera; Guirao, Juan L. G.; Fernández-Martínez, Manuel

In this paper, we explore the chaotic behavior of resistively and capacitively shunted Josephson junctions via the so-called Network Simulation Method. Such a numerical approach establishes a formal equivalence among physical transport processes and electrical networks, and hence, it can be applied to efficiently deal with a wide range of differential systems. The generality underlying that electrical equivalence allows to apply the circuit theory to several scientific and technological problems. In this work, the Fast Fourier Transform has been applied for chaos detection purposes and the calculations have been carried out in PSpice, an electrical circuit software. Overall, it holds that such a numerical approach leads to quickly computationally solve Josephson differential models. An empirical application regarding the study of the Josephson model completes the paper.

The Use of Generating Sets with ING Gas Engines in "Shore to Ship" Systems

NASA Astrophysics Data System (ADS)

Tarnapowicz, Dariusz; German-Galkin, Sergiej

2016-09-01

The main sources of air pollution in ports are ships, on which electrical energy is produced in the autonomous generating sets Diesel-Generator. The most effective way to reduce harmful exhaust emissions from ships is to exclude marine generating sets and provide the shore-side electricity in "Shore to Ship" system. The main problem in the implementation of power supply for ships from land is connected with matching parameters of voltage in onshore network with marine network. Currently, the recommended solution is to supply ships from the onshore electricity network with the use of power electronic converters. This article presents an analysis of the "Shore to Ship" system with the use of generating sets with LNG gas engines. It shows topologies with LNG - Generator sets, environmental benefits of such a solution, advantages and disadvantages.

Programmability of nanowire networks

NASA Astrophysics Data System (ADS)

Bellew, A. T.; Bell, A. P.; McCarthy, E. K.; Fairfield, J. A.; Boland, J. J.

2014-07-01

Electrical connectivity in networks of nanoscale junctions must be better understood if nanowire devices are to be scaled up from single wires to functional material systems. We show that the natural connectivity behaviour found in random nanowire networks presents a new paradigm for creating multi-functional, programmable materials. In devices made from networks of Ni/NiO core-shell nanowires at different length scales, we discover the emergence of distinct behavioural regimes when networks are electrically stressed. We show that a small network, with few nanowire-nanowire junctions, acts as a unipolar resistive switch, demonstrating very high ON/OFF current ratios (>105). However, large networks of nanowires distribute an applied bias across a large number of junctions, and thus respond not by switching but instead by evolving connectivity. We demonstrate that these emergent properties lead to fault-tolerant materials whose resistance may be tuned, and which are capable of adaptively reconfiguring under stress. By combining these two behavioural regimes, we demonstrate that the same nanowire network may be programmed to act both as a metallic interconnect, and a resistive switch device with high ON/OFF ratio. These results enable the fabrication of programmable, multi-functional materials from random nanowire networks.Electrical connectivity in networks of nanoscale junctions must be better understood if nanowire devices are to be scaled up from single wires to functional material systems. We show that the natural connectivity behaviour found in random nanowire networks presents a new paradigm for creating multi-functional, programmable materials. In devices made from networks of Ni/NiO core-shell nanowires at different length scales, we discover the emergence of distinct behavioural regimes when networks are electrically stressed. We show that a small network, with few nanowire-nanowire junctions, acts as a unipolar resistive switch, demonstrating very high ON/OFF current ratios (>105). However, large networks of nanowires distribute an applied bias across a large number of junctions, and thus respond not by switching but instead by evolving connectivity. We demonstrate that these emergent properties lead to fault-tolerant materials whose resistance may be tuned, and which are capable of adaptively reconfiguring under stress. By combining these two behavioural regimes, we demonstrate that the same nanowire network may be programmed to act both as a metallic interconnect, and a resistive switch device with high ON/OFF ratio. These results enable the fabrication of programmable, multi-functional materials from random nanowire networks. Electronic supplementary information (ESI) available: Nanowire statistics (length, diameter statistics, and oxide thickness) are provided. Forming curves for single junctions and networks. Passive voltage contrast image demonstrating selectivity of conductive pathways in 100 μm network. See DOI: 10.1039/c4nr02338b

Study on key technologies of vehicle networking system platform for electric automobiles based on micro-service

NASA Astrophysics Data System (ADS)

Ye, Fei

2018-04-01

With the rapid increase of electric automobiles and charging piles, the elastic expansion and online rapid upgrade were required for the vehicle networking system platform (system platform for short). At present, it is difficult to meet the operation needs due to the traditional huge rock architecture used by the system platform. This paper studied the system platform technology architecture based on "cloud platform +micro-service" to obtain a new generation of vehicle networking system platform with the combination of elastic expansion and application, thus significantly improving the service operation ability of system.

Flexible transparent conductors based on metal nanowire networks

DOE PAGES

Guo, Chuan Fei; Ren, Zhifeng

2015-04-01

Few conductors are transparent and flexible. Metals have the best electrical conductivity, but they are opaque and stiff in bulk form. However, metals can be transparent and flexible when they are very thin or properly arranged on the nanoscale. This review focuses on the flexible transparent conductors based on percolating networks of metal. Specifically, we discuss the fabrication, the means to improve the electrical conductivity, the large stretchability and its mechanism, and the applications of these metal networks. We also suggest some criteria for evaluating flexible transparent conductors and propose some new research directions in this emerging field.

Models for the modern power grid

NASA Astrophysics Data System (ADS)

Nardelli, Pedro H. J.; Rubido, Nicolas; Wang, Chengwei; Baptista, Murilo S.; Pomalaza-Raez, Carlos; Cardieri, Paulo; Latva-aho, Matti

2014-10-01

This article reviews different kinds of models for the electric power grid that can be used to understand the modern power system, the smart grid. From the physical network to abstract energy markets, we identify in the literature different aspects that co-determine the spatio-temporal multilayer dynamics of power system. We start our review by showing how the generation, transmission and distribution characteristics of the traditional power grids are already subject to complex behaviour appearing as a result of the the interplay between dynamics of the nodes and topology, namely synchronisation and cascade effects. When dealing with smart grids, the system complexity increases even more: on top of the physical network of power lines and controllable sources of electricity, the modernisation brings information networks, renewable intermittent generation, market liberalisation, prosumers, among other aspects. In this case, we forecast a dynamical co-evolution of the smart grid and other kind of networked systems that cannot be understood isolated. This review compiles recent results that model electric power grids as complex systems, going beyond pure technological aspects. From this perspective, we then indicate possible ways to incorporate the diverse co-evolving systems into the smart grid model using, for example, network theory and multi-agent simulation.

Simulation studies of multiple large wind turbine generators on a utility network

NASA Technical Reports Server (NTRS)

Gilbert, L. J.; Triezenberg, D. M.

1979-01-01

The potential electrical problems that may be inherent in the inertia of clusters of wind turbine generators and an electric utility network were investigated. Preliminary and limited results of an analog simulation of two MOD-2 wind generators tied to an infinite bus indicate little interaction between the generators and between the generators and the bus. The system demonstrated transient stability for the conditions considered.

Nonvolatile Ionic Two-Terminal Memory Device

NASA Technical Reports Server (NTRS)

Williams, Roger M.

1990-01-01

Conceptual solid-state memory device nonvolatile and erasable and has only two terminals. Proposed device based on two effects: thermal phase transition and reversible intercalation of ions. Transfer of sodium ions between source of ions and electrical switching element increases or decreases electrical conductance of element, turning switch "on" or "off". Used in digital computers and neural-network computers. In neural networks, many small, densely packed switches function as erasable, nonvolatile synaptic elements.

Regulation and competition without privatization: Norway`s experience

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moen, J.; Hamrin, J.

The competitive market for the hydro-based Norwegian electricity system is working well, with end-user prices only slightly above the wholesale market. Pool prices are reflecting only weather-related variations, and no market power abuses are evident. The challenge now is to restructure ownership of the wires and retail suppliers to lower wheeling costs and avoid cross-subsidization. Since the Norwegian Energy Act came into effect in 1991, the electricity industry in Norway has operated as one of the most deregulated electricity industries in the world. The Energy Act introduced third party access to the retail market and competition in electricity production. Themore » generation, sale and purchase of electricity is now highly competitive, with customers free to buy electricity from any generator, trader or the electricity Pool. Transmission pricing was separated from power purchasing arrangements, so that the buying and selling of electricity as a product is distinct from the transmission of electricity as a service. Transmission and distribution networks continue to maintain natural monopolies, with network owners providing wheeling service across their networks to customers who are connected to them. These monopoly sectors of the industry are subject to regulation by the government-appointed regulatory body, Norwegian Water Resources and Energy Administration (NVE). Regulation is on a cost-of-service basis, with the revenue allowance determined by NVE. The main force behind the Norwegian reform was the desire for efficiency gains to be achieved through a total restructure of the commercial character of the energy service industry (ESI). Unlike the U.K., in Norway the monopoly franchise for both generation and retail supply was removed in one step without any transition period, and the old pool was reformed to provide the needed structure for this new competitive energy market.« less

Highly Adaptive Solid-Liquid Interfacing Triboelectric Nanogenerator for Harvesting Diverse Water Wave Energy.

PubMed

Zhao, Xue Jiao; Kuang, Shuang Yang; Wang, Zhong Lin; Zhu, Guang

2018-05-22

Harvesting water wave energy presents a significantly practical route to energy supply for self-powered wireless sensing networks. Here we report a networked integrated triboelectric nanogenerator (NI-TENG) as a highly adaptive means of harvesting energy from interfacing interactions with various types of water waves. Having an arrayed networking structure, the NI-TENG can accommodate diverse water wave motions and generate stable electric output regardless of how random the water wave is. Nanoscaled surface morphology consisting of dense nanowire arrays is the key for obtaining high electric output. A NI-TENG having an area of 100 × 70 mm 2 can produce a stable short-circuit current of 13.5 μA and corresponding electric power of 1.03 mW at a water wave height of 12 cm. This merit promises practical applications of the NI-TENG in real circumstances, where water waves are highly variable and unpredictable. After energy storage, the generated electric energy can drive wireless sensing by autonomously transmitting data at a period less than 1 min. This work proposes a viable solution for powering individual standalone nodes in a wireless sensor network. Potential applications include but are not limited to long-term environment monitoring, marine surveillance, and off-shore navigation.

The role of latitude in mobilism debates

PubMed Central

Irving, Edward

2005-01-01

In the early 1920s, the continental displacement theory of Wegener, latitude studies of Köppen and Wegener, and Argand's ideas on mountain building led to the first mobilistic paleogeography. In the 1930s and 1940s, many factors caused its general abandonment. Mobilism was revived in the 1950s and 1960s by measurements of long-term displacement of crustal blocks relative to each other (tectonic displacement) and to Earth's geographic pole (latitudinal displacement). Also, short-term or current displacements can now be measured. I briefly outline the categories of tectonic and current displacement and focus on latitudinal displacement. Integration of tectonic and latitudinal displacement in the early 1970s completed the new mobilistic paleogeography, in which the transformation of rock magnetization directions into paleopoles and latitudes and the finite rotation of spherical plates about pivot points play complementary roles; this new synthesis now provides a quantitative basis for studying long-term evolution of Earth's surface features and climate, the changing environments in which life evolves. PMID:15684058

A dual-scale metal nanowire network transparent conductor for highly efficient and flexible organic light emitting diodes.

PubMed

Lee, Jinhwan; An, Kunsik; Won, Phillip; Ka, Yoonseok; Hwang, Hyejin; Moon, Hyunjin; Kwon, Yongwon; Hong, Sukjoon; Kim, Changsoon; Lee, Changhee; Ko, Seung Hwan

2017-02-02

Although solution processed metal nanowire (NW) percolation networks are a strong candidate to replace commercial indium tin oxide, their performance is limited in thin film device applications due to reduced effective electrical areas arising from the dimple structure and percolative voids that single size metal NW percolation networks inevitably possess. Here, we present a transparent electrode based on a dual-scale silver nanowire (AgNW) percolation network embedded in a flexible substrate to demonstrate a significant enhancement in the effective electrical area by filling the large percolative voids present in a long/thick AgNW network with short/thin AgNWs. As a proof of concept, the performance enhancement of a flexible phosphorescent OLED is demonstrated with the dual-scale AgNW percolation network compared to the previous mono-scale AgNWs. Moreover, we report that mechanical and oxidative robustness, which are critical for flexible OLEDs, are greatly increased by embedding the dual-scale AgNW network in a resin layer.

Evaluation and prediction of solar radiation for energy management based on neural networks

NASA Astrophysics Data System (ADS)

Aldoshina, O. V.; Van Tai, Dinh

2017-08-01

Currently, there is a high rate of distribution of renewable energy sources and distributed power generation based on intelligent networks; therefore, meteorological forecasts are particularly useful for planning and managing the energy system in order to increase its overall efficiency and productivity. The application of artificial neural networks (ANN) in the field of photovoltaic energy is presented in this article. Implemented in this study, two periodically repeating dynamic ANS, that are the concentration of the time delay of a neural network (CTDNN) and the non-linear autoregression of a network with exogenous inputs of the NAEI, are used in the development of a model for estimating and daily forecasting of solar radiation. ANN show good productivity, as reliable and accurate models of daily solar radiation are obtained. This allows to successfully predict the photovoltaic output power for this installation. The potential of the proposed method for controlling the energy of the electrical network is shown using the example of the application of the NAEI network for predicting the electric load.

Cell-cell bioelectrical interactions and local heterogeneities in genetic networks: a model for the stabilization of single-cell states and multicellular oscillations.

PubMed

Cervera, Javier; Manzanares, José A; Mafe, Salvador

2018-04-04

Genetic networks operate in the presence of local heterogeneities in single-cell transcription and translation rates. Bioelectrical networks and spatio-temporal maps of cell electric potentials can influence multicellular ensembles. Could cell-cell bioelectrical interactions mediated by intercellular gap junctions contribute to the stabilization of multicellular states against local genetic heterogeneities? We theoretically analyze this question on the basis of two well-established experimental facts: (i) the membrane potential is a reliable read-out of the single-cell electrical state and (ii) when the cells are coupled together, their individual cell potentials can be influenced by ensemble-averaged electrical potentials. We propose a minimal biophysical model for the coupling between genetic and bioelectrical networks that associates the local changes occurring in the transcription and translation rates of an ion channel protein with abnormally low (depolarized) cell potentials. We then analyze the conditions under which the depolarization of a small region (patch) in a multicellular ensemble can be reverted by its bioelectrical coupling with the (normally polarized) neighboring cells. We show also that the coupling between genetic and bioelectric networks of non-excitable cells, modulated by average electric potentials at the multicellular ensemble level, can produce oscillatory phenomena. The simulations show the importance of single-cell potentials characteristic of polarized and depolarized states, the relative sizes of the abnormally polarized patch and the rest of the normally polarized ensemble, and intercellular coupling.

Electrical conductivity modeling and experimental study of densely packed SWCNT networks.

PubMed

Jack, D A; Yeh, C-S; Liang, Z; Li, S; Park, J G; Fielding, J C

2010-05-14

Single-walled carbon nanotube (SWCNT) networks have become a subject of interest due to their ability to support structural, thermal and electrical loadings, but to date their application has been hindered due, in large part, to the inability to model macroscopic responses in an industrial product with any reasonable confidence. This paper seeks to address the relationship between macroscale electrical conductivity and the nanostructure of a dense network composed of SWCNTs and presents a uniquely formulated physics-based computational model for electrical conductivity predictions. The proposed model incorporates physics-based stochastic parameters for the individual nanotubes to construct the nanostructure such as: an experimentally obtained orientation distribution function, experimentally derived length and diameter distributions, and assumed distributions of chirality and registry of individual CNTs. Case studies are presented to investigate the relationship between macroscale conductivity and nanostructured variations in the bulk stochastic length, diameter and orientation distributions. Simulation results correspond nicely with those available in the literature for case studies of conductivity versus length and conductivity versus diameter. In addition, predictions for the increasing anisotropy of the bulk conductivity as a function of the tube orientation distribution are in reasonable agreement with our experimental results. Examples are presented to demonstrate the importance of incorporating various stochastic characteristics in bulk conductivity predictions. Finally, a design consideration for industrial applications is discussed based on localized network power emission considerations and may lend insight to the design engineer to better predict network failure under high current loading applications.

Multiple Factors-Aware Diffusion in Social Networks

DTIC Science & Technology

2015-05-22

Multiple Factors-Aware Diffusion in Social Networks Chung-Kuang Chou(B) and Ming-Syan Chen Department of Electrical Engineering, National Taiwan...propagates from nodes to nodes over a social network . The behavior that a node adopts an information piece in a social network can be affected by...Twitter dataset. Keywords: Social networks · Diffusion models 1 Introduction Information diffusion in social networks has been an active research field

CMOS nanoelectrode array for all-electrical intracellular electrophysiological imaging

NASA Astrophysics Data System (ADS)

Abbott, Jeffrey; Ye, Tianyang; Qin, Ling; Jorgolli, Marsela; Gertner, Rona S.; Ham, Donhee; Park, Hongkun

2017-05-01

Developing a new tool capable of high-precision electrophysiological recording of a large network of electrogenic cells has long been an outstanding challenge in neurobiology and cardiology. Here, we combine nanoscale intracellular electrodes with complementary metal-oxide-semiconductor (CMOS) integrated circuits to realize a high-fidelity all-electrical electrophysiological imager for parallel intracellular recording at the network level. Our CMOS nanoelectrode array has 1,024 recording/stimulation 'pixels' equipped with vertical nanoelectrodes, and can simultaneously record intracellular membrane potentials from hundreds of connected in vitro neonatal rat ventricular cardiomyocytes. We demonstrate that this network-level intracellular recording capability can be used to examine the effect of pharmaceuticals on the delicate dynamics of a cardiomyocyte network, thus opening up new opportunities in tissue-based pharmacological screening for cardiac and neuronal diseases as well as fundamental studies of electrogenic cells and their networks.

Self-triggering superconducting fault current limiter

DOEpatents

Yuan, Xing [Albany, NY; Tekletsadik, Kasegn [Rexford, NY

2008-10-21

A modular and scaleable Matrix Fault Current Limiter (MFCL) that functions as a "variable impedance" device in an electric power network, using components made of superconducting and non-superconducting electrically conductive materials. The matrix fault current limiter comprises a fault current limiter module that includes a superconductor which is electrically coupled in parallel with a trigger coil, wherein the trigger coil is magnetically coupled to the superconductor. The current surge doing a fault within the electrical power network will cause the superconductor to transition to its resistive state and also generate a uniform magnetic field in the trigger coil and simultaneously limit the voltage developed across the superconductor. This results in fast and uniform quenching of the superconductors, significantly reduces the burnout risk associated with non-uniformity often existing within the volume of superconductor materials. The fault current limiter modules may be electrically coupled together to form various "n" (rows).times."m" (columns) matrix configurations.

Global potential for wind-generated electricity

PubMed Central

Lu, Xi; McElroy, Michael B.; Kiviluoma, Juha

2009-01-01

The potential of wind power as a global source of electricity is assessed by using winds derived through assimilation of data from a variety of meteorological sources. The analysis indicates that a network of land-based 2.5-megawatt (MW) turbines restricted to nonforested, ice-free, nonurban areas operating at as little as 20% of their rated capacity could supply >40 times current worldwide consumption of electricity, >5 times total global use of energy in all forms. Resources in the contiguous United States, specifically in the central plain states, could accommodate as much as 16 times total current demand for electricity in the United States. Estimates are given also for quantities of electricity that could be obtained by using a network of 3.6-MW turbines deployed in ocean waters with depths <200 m within 50 nautical miles (92.6 km) of closest coastlines. PMID:19549865

Electric field mill network products to improve detection of the lightning hazard

NASA Technical Reports Server (NTRS)

Maier, Launa M.

1987-01-01

An electric field mill network has been used at Kennedy Space Center for over 10 years as part of the thunderstorm detection system. Several algorithms are currently available to improve the informational output of the electric field mill data. The charge distributions of roughly 50 percent of all lightning can be modeled as if they reduced the charged cloud by a point charge or a point dipole. Using these models, the spatial differences in the lightning induced electric field changes, and a least squares algorithm to obtain an optimum solution, the three-dimensional locations of the lightning charge centers can be located. During the lifetime of a thunderstorm, dynamically induced charging, modeled as a current source, can be located spatially with measurements of Maxwell current density. The electric field mills can be used to calculate the Maxwell current density at times when it is equal to the displacement current density. These improvements will produce more accurate assessments of the potential electrical activity, identify active cells, and forecast thunderstorm termination.

Design process of a photonics network for military platforms

NASA Astrophysics Data System (ADS)

Nelson, George F.; Rao, Nagarajan M.; Krawczak, John A.; Stevens, Rick C.

1999-02-01

Technology development in photonics is rapidly progressing. The concept of a Unified Network will provide re- configurable network access to platform sensors, Vehicle Management Systems, Stores and avionics. The re-configurable taps into the network will accommodate present interface standards and provide scaleability for the insertion of future interfaces. Significant to this development is the design and test of the Optical Backplane Interconnect System funded by Naval Air Systems Command and developed by Lockheed Martin Tactical Defense Systems - Eagan. OBIS results in the merging of the electrical backplane and the optical backplane, with interconnect fabric and card edge connectors finally providing adequate electrical and optical card access. Presently OBIS will support 1.2 Gb/s per fiber over multiples of 12 fibers per ribbon cable.

Smart Grid Communications System Blueprint

NASA Astrophysics Data System (ADS)

Clark, Adrian; Pavlovski, Chris

2010-10-01

Telecommunications operators are well versed in deploying 2G and 3G wireless networks. These networks presently support the mobile business user and/or retail consumer wishing to place conventional voice calls and data connections. The electrical power industry has recently commenced transformation of its distribution networks by deploying smart monitoring and control devices throughout their networks. This evolution of the network into a `smart grid' has also motivated the need to deploy wireless technologies that bridge the communication gap between the smart devices and information technology systems. The requirements of these networks differ from traditional wireless networks that communications operators have deployed, which have thus far forced energy companies to consider deploying their own wireless networks. We present our experience in deploying wireless networks to support the smart grid and highlight the key properties of these networks. These characteristics include application awareness, support for large numbers of simultaneous cell connections, high service coverage and prioritized routing of data. We also outline our target blueprint architecture that may be useful to the industry in building wireless and fixed networks to support the smart grid. By observing our experiences, telecommunications operators and equipment manufacturers will be able to augment their current networks and products in a way that accommodates the needs of the emerging industry of smart grids and intelligent electrical networks.

Modification of electrical properties of silicon dioxide through intrinsic nano-patterns

NASA Astrophysics Data System (ADS)

Majee, Subimal; Barshilia, Devesh; Banerjee, Debashree; Kumar, Sanjeev; Mishra, Prabhash; Akhtar, Jamil

2018-05-01

The inherent network of nanopores and voids in silicon dioxide (SiO2) is generally undesirable for aspects of film quality, electrical insulation and dielectric performance. However, if we view these pores as natural nano-patterns embedded in a dielectric matrix then that opens up new vistas for exploration. The nano-pattern platform can be used to tailor electrical, optical, magnetic and mechanical properties of the carrier film. In this article we report the tunable electrical properties of thermal SiO2 thin-film achieved through utilization of the metal-nanopore network where the pores are filled with metallic Titanium (Ti). Without any intentional chemical doping, we have shown that the electrical resistivity of the oxide film can be controlled through physical filling up of the intrinsic oxide nanopores with Ti. The electrical resistivity of the composite film remains constant even after complete removal of the metal from the film surface except the pores. Careful morphological, electrical and structural analyses are carried out to establish that the presence of Ti in the nanopores play a crucial role in the observed conductive nature of the nanoporous film.

Bioprinting: Functional droplet networks

NASA Astrophysics Data System (ADS)

Durmus, Naside Gozde; Tasoglu, Savas; Demirci, Utkan

2013-06-01

Tissue-mimicking printed networks of droplets separated by lipid bilayers that can be functionalized with membrane proteins are able to spontaneously fold and transmit electrical currents along predefined paths.

Multi-label spacecraft electrical signal classification method based on DBN and random forest

PubMed Central

Li, Ke; Yu, Nan; Li, Pengfei; Song, Shimin; Wu, Yalei; Li, Yang; Liu, Meng

2017-01-01

In spacecraft electrical signal characteristic data, there exists a large amount of data with high-dimensional features, a high computational complexity degree, and a low rate of identification problems, which causes great difficulty in fault diagnosis of spacecraft electronic load systems. This paper proposes a feature extraction method that is based on deep belief networks (DBN) and a classification method that is based on the random forest (RF) algorithm; The proposed algorithm mainly employs a multi-layer neural network to reduce the dimension of the original data, and then, classification is applied. Firstly, we use the method of wavelet denoising, which was used to pre-process the data. Secondly, the deep belief network is used to reduce the feature dimension and improve the rate of classification for the electrical characteristics data. Finally, we used the random forest algorithm to classify the data and comparing it with other algorithms. The experimental results show that compared with other algorithms, the proposed method shows excellent performance in terms of accuracy, computational efficiency, and stability in addressing spacecraft electrical signal data. PMID:28486479

Multi-label spacecraft electrical signal classification method based on DBN and random forest.

PubMed

Li, Ke; Yu, Nan; Li, Pengfei; Song, Shimin; Wu, Yalei; Li, Yang; Liu, Meng

2017-01-01

In spacecraft electrical signal characteristic data, there exists a large amount of data with high-dimensional features, a high computational complexity degree, and a low rate of identification problems, which causes great difficulty in fault diagnosis of spacecraft electronic load systems. This paper proposes a feature extraction method that is based on deep belief networks (DBN) and a classification method that is based on the random forest (RF) algorithm; The proposed algorithm mainly employs a multi-layer neural network to reduce the dimension of the original data, and then, classification is applied. Firstly, we use the method of wavelet denoising, which was used to pre-process the data. Secondly, the deep belief network is used to reduce the feature dimension and improve the rate of classification for the electrical characteristics data. Finally, we used the random forest algorithm to classify the data and comparing it with other algorithms. The experimental results show that compared with other algorithms, the proposed method shows excellent performance in terms of accuracy, computational efficiency, and stability in addressing spacecraft electrical signal data.

Tagging and tracking individual networks within a complex mitochondrial web with photoactivatable GFP.

PubMed

Twig, Gilad; Graf, Solomon A; Wikstrom, Jakob D; Mohamed, Hibo; Haigh, Sarah E; Elorza, Alvaro; Deutsch, Motti; Zurgil, Naomi; Reynolds, Nicole; Shirihai, Orian S

2006-07-01

Assembly of mitochondria into networks supports fuel metabolism and calcium transport and is involved in the cellular response to apoptotic stimuli. A mitochondrial network is defined as a continuous matrix lumen whose boundaries limit molecular diffusion. Observation of individual networks has proven challenging in live cells that possess dense populations of mitochondria. Investigation into the electrical and morphological properties of mitochondrial networks has therefore not yielded consistent conclusions. In this study we used matrix-targeted, photoactivatable green fluorescent protein to tag single mitochondrial networks. This approach, coupled with real-time monitoring of mitochondrial membrane potential, permitted the examination of matrix lumen continuity and fusion and fission events over time. We found that adjacent and intertwined mitochondrial structures often represent a collection of distinct networks. We additionally found that all areas of a single network are invariably equipotential, suggesting that a heterogeneous pattern of membrane potential within a cell's mitochondria represents differences between discrete networks. Interestingly, fission events frequently occurred without any gross morphological changes and particularly without fragmentation. These events, which are invisible under standard confocal microscopy, redefine the mitochondrial network boundaries and result in electrically disconnected daughter units.

Electric Power Engineering Cost Predicting Model Based on the PCA-GA-BP

NASA Astrophysics Data System (ADS)

Wen, Lei; Yu, Jiake; Zhao, Xin

2017-10-01

In this paper a hybrid prediction algorithm: PCA-GA-BP model is proposed. PCA algorithm is established to reduce the correlation between indicators of original data and decrease difficulty of BP neural network in complex dimensional calculation. The BP neural network is established to estimate the cost of power transmission project. The results show that PCA-GA-BP algorithm can improve result of prediction of electric power engineering cost.

A Design of a Network Model to the Electric Power Trading System Using Web Services

NASA Astrophysics Data System (ADS)

Maruo, Tomoaki; Matsumoto, Keinosuke; Mori, Naoki; Kitayama, Masashi; Izumi, Yoshio

Web services are regarded as a new application paradigm in the world of the Internet. On the other hand, many business models of a power trading system has been proposed to aim at load reduction by consumers cooperating with electric power suppliers in an electric power market. Then, we propose a network model of power trading system using Web service in this paper. The adaptability of Web services to power trading system was checked in the prototype of our network model and we got good results for it. Each server provides functions as a SOAP server, and it is coupled loosely with each other through SOAP. Storing SOAP message in HTTP packet can establish the penetration communication way that is not conscious of a firewall. Switching of a dynamic server is possible by means of rewriting the server point information on WSDL at the time of obstacle generating.

Platonic Relationships among Resistors

ERIC Educational Resources Information Center

Allen, Bradley; Liu, Tongtian

2015-01-01

Calculating the effective resistance of an electrical network is a common problem in introductory physics courses. Such calculations are typically restricted to two-dimensional networks, though even such networks can become increasingly complex, leading to several studies on their properties. Furthermore, several authors have used advanced…

Power processing

NASA Technical Reports Server (NTRS)

Schwarz, F. C.

1971-01-01

Processing of electric power has been presented as a discipline that draws on almost every field of electrical engineering, including system and control theory, communications theory, electronic network design, and power component technology. The cost of power processing equipment, which often equals that of expensive, sophisticated, and unconventional sources of electrical energy, such as solar batteries, is a significant consideration in the choice of electric power systems.

Impact of a changing environment on the built heritage

NASA Astrophysics Data System (ADS)

Grossi, C. M.; Brimblecombe, P.; Bonazza, A.

2012-04-01

Stone monuments are degraded by both climate and pollution. Deterioration by pollution was especially intense from the 1700s and until the late 20th century the dominant impact of air pollution was the sulfation of surfaces. The parallel deposition of soot caused blackening and on some surfaces dark coloured crusts. The decrease of sulfur and soot from coal combustion during the last decades of the 20th century led to cleaner air in cities, a decrease of pollution-decay rates on building stones and a public desire for cleaner buildings. Although there were decreases in SO2, it was replaced by ozone, nitrogen oxides and particles richer in organic compounds, the result of an extensive use of automobiles. Deposited organic compounds can oxidise in modern urban environments in a yellowing process. The future may reveal variation in building colour from biological growth in a changing climate. In urban atmospheres with less sulfur, biological growth is more effective. A greater rate of delivery of nitrate to building surfaces that acts as "airborne fertiliser" favours colonisation. Depending on climate, there might be different processes (e.g. greening or reddening) and patterns of colouration. Climate is also a relevant factor in the weathering of monuments. Recent research suggests the concept of Heritage Climatology in the study of climate interactions with monuments, materials and sites. These parameters concentrate on aspects and combinations of meteorological variables that relate to material damage. The Köppen-Geiger climate classification can be a good approximation for some heritage risks. For instance, the number of salt transitions shows distinct seasonality which can be related to Köppen-Geiger climate types and their change during the 21th century. The study of changing pollution and climate impacts on the built heritage needs the output of pollution emissions and climate change models, which are prone to uncertainties. The use of multiple climate models or ENSEMBLES may improve the accuracy and reliability of predictions. This approach has been used to predict salt damage. However, more work is needed on the uncertainty in predictions and the way this affects the management of stone heritage. There is public availability of climate and pollution data, but frequently these need to be unified and made user-friendly for cultural heritage researchers in many countries, e.g. the UKCP09 user interface is a good example of friendly-availability for probabilistic projections and downscaled climate change data, but available data are limited to the UK. The utilisation of these improved techniques can contribute to better strategies for managing buildings.

David Palchak | NREL

Science.gov Websites

Electrical load forecasting with artificial neural networks Demand-side management optimization with Matlab -58491. D. Palchak, S. Suryanarayanan, and D. Zimmerle. "An Artificial Neural Network in Short-Term

Investigation of a generator system for generating electrical power, to supply directly to the public network, using a windmill

NASA Technical Reports Server (NTRS)

Tromp, C.

1979-01-01

A windpowered generator system is described which uses a windmill to convert mechanical energy to electrical energy for a three phase (network) voltage of constant amplitude and frequency. The generator system controls the windmill by the number of revolutions so that the power drawn from the wind for a given wind velocity is maximum. A generator revolution which is proportional to wind velocity is achieved. The stator of the generator is linked directly to the network and a feed converter at the rotor takes care of constant voltage and frequency at the stator.

Cellular computational platform and neurally inspired elements thereof

DOEpatents

Okandan, Murat

2016-11-22

A cellular computational platform is disclosed that includes a multiplicity of functionally identical, repeating computational hardware units that are interconnected electrically and optically. Each computational hardware unit includes a reprogrammable local memory and has interconnections to other such units that have reconfigurable weights. Each computational hardware unit is configured to transmit signals into the network for broadcast in a protocol-less manner to other such units in the network, and to respond to protocol-less broadcast messages that it receives from the network. Each computational hardware unit is further configured to reprogram the local memory in response to incoming electrical and/or optical signals.

Analysis of large power systems

NASA Technical Reports Server (NTRS)

Dommel, H. W.

1975-01-01

Computer-oriented power systems analysis procedures in the electric utilities are surveyed. The growth of electric power systems is discussed along with the solution of sparse network equations, power flow, and stability studies.

Distribution and Network of Basal Temporal Language Areas: A Study of the Combination of Electric Cortical Stimulation and Diffusion Tensor Imaging.

PubMed

Enatsu, Rei; Kanno, Aya; Ookawa, Satoshi; Ochi, Satoko; Ishiai, Sumio; Nagamine, Takashi; Mikuni, Nobuhiro

2017-10-01

The basal temporal language area (BTLA) is considered to have several functions in language processing; however, its brain network is still unknown. This study investigated the distribution and networks of the BTLA using a combination of electric cortical stimulation and diffusion tensor imaging (DTI). 10 patients with intractable focal epilepsy who underwent presurgical evaluation with subdural electrodes were enrolled in this study (language dominant side: 6 patients, language nondominant side: 4 patients). Electric stimulation at 50 Hz was applied to the electrodes during Japanese sentence reading, morphograms (kanji) reading, and syllabograms (kana) reading tasks to identify the BTLA. DTI was used to identify the subcortical fibers originating from the BTLA found by electric stimulation. The BTLA was found in 6 patients who underwent implantation of the subdural electrodes in the dominant hemisphere. The BTLA was located anywhere between 20 mm and 56 mm posterior to the temporal tips. In 3 patients, electric stimulation of some or all areas within the BTLA induced disturbance in reading of kanji words only. DTI detected the inferior longitudinal fasciculus (ILF) in all patients and the uncinate fasciculus (UF) in 1 patient, originating from the BTLA. ILF was detected from both kanji-specific areas and kanji-nonspecific areas. This study indicates that the network of the BTLA is a part of a ventral stream and is mainly composed of the ILF, which acts as a critical structure for lexical retrieval. ILF is also associated with the specific processing of kanji words. Copyright © 2017 Elsevier Inc. All rights reserved.

Skeleton-supported stochastic networks of organic memristive devices: Adaptations and learning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Erokhina, Svetlana; Sorokin, Vladimir; Erokhin, Victor, E-mail: victor.erokhin@fis.unipr.it

Stochastic networks of memristive devices were fabricated using a sponge as a skeleton material. Cyclic voltage-current characteristics, measured on the network, revealed properties, similar to the organic memristive device with deterministic architecture. Application of the external training resulted in the adaptation of the network electrical properties. The system revealed an improved stability with respect to the networks, composed from polymer fibers.

Airborne Network Optimization with Dynamic Network Update

DTIC Science & Technology

2015-03-26

Faculty Department of Electrical and Computer Engineering Graduate School of Engineering and Management Air Force Institute of Technology Air University...Member Dr. Barry E. Mullins Member AFIT-ENG-MS-15-M-030 Abstract Modern networks employ congestion and routing management algorithms that can perform...airborne networks. Intelligent agents can make use of Kalman filter predictions to make informed decisions to manage communication in airborne networks. The

A Planning Guide for Instructional Networks, Part II.

ERIC Educational Resources Information Center

Daly, Kevin F.

1994-01-01

This second in a series of articles on planning for instructional computer networks focuses on site preparation, installation, service, and support. Highlights include an implementation schedule; classroom and computer lab layouts; electrical power needs; workstations; network cable; telephones; furniture; climate control; and security. (LRW)

Multiscaling statistics of high frequency global solar radiation data in the Guadeloupean Archipelago

NASA Astrophysics Data System (ADS)

Calif, R.; Schmitt, F. G.; Huang, Y.; Soubdhan, T.

2013-12-01

The part of the solar power production from photovoltaiccs systems is constantly increasing in the electric grids. Solar energy converter devices such as photovoltaic cells are very sensitive to instantaneous solar radiation fluctuations. Thus rapid variation of solar radiation due to changes in the local meteorological condition can induce large amplitude fluctuations of the produced electrical power and reduce the overall efficiency of the system. When large amount of photovoltaic electricity is send into a weak or small electricity network such as island network, the electric grid security can be in jeopardy due to these power fluctuations. The integration of this energy into the electrical network remains a major challenge, due to the high variability of solar radiation in time and space. To palliate these difficulties, it is essential to identify the characteristic of these fluctuations in order to anticipate the eventuality of power shortage or power surge. A good knowledge of the intermittency of global solar radiation is crucial for selecting the location of a solar power plant and predicting the generation of electricity. This work presents a multifractal analysis study of 367 daily global solar radiation sequences measured with a sampling rate of 1 Hz over one year at Guadeloupean Archipelago (French West Indies) located at 16o15'N latitude and 60o30'W longitude. The mean power spectrum computed follows a power law behaviour close to the Kolmogorov spectrum. The intermittent and multifractal properties of global solar radiation data are investigated using several methods. Under this basis, a characterization for each day using three multifractal parameters is proposed.

Study on Fuel Cell Network System Considering Reduction in Fuel Cell Capacity Using Load Leveling and Heat Release Loss

NASA Astrophysics Data System (ADS)

Obara, Shin'ya; Kudo, Kazuhiko

Reduction in fuel cell capacity linked to a fuel cell network system is considered. When the power demand of the whole network is small, some of the electric power generated by the fuel cell is supplied to a water electrolysis device, and hydrogen and oxygen gases are generated. Both gases are compressed with each compressor and they are stored in cylinders. When the electric demand of the whole network is large, both gases are supplied to the network, and fuel cells are operated by these hydrogen and oxygen gases. Furthermore, an optimization plan is made to minimize the quantity of heat release of the hot water piping that connects each building. Such an energy network is analyzed assuming connection of individual houses, a hospital, a hotel, a convenience store, an office building, and a factory. Consequently, compared with the conventional system, a reduction of 46% of fuel cell capacity is expected.

Fault detection and classification in electrical power transmission system using artificial neural network.

PubMed

Jamil, Majid; Sharma, Sanjeev Kumar; Singh, Rajveer

2015-01-01

This paper focuses on the detection and classification of the faults on electrical power transmission line using artificial neural networks. The three phase currents and voltages of one end are taken as inputs in the proposed scheme. The feed forward neural network along with back propagation algorithm has been employed for detection and classification of the fault for analysis of each of the three phases involved in the process. A detailed analysis with varying number of hidden layers has been performed to validate the choice of the neural network. The simulation results concluded that the present method based on the neural network is efficient in detecting and classifying the faults on transmission lines with satisfactory performances. The different faults are simulated with different parameters to check the versatility of the method. The proposed method can be extended to the Distribution network of the Power System. The various simulations and analysis of signals is done in the MATLAB(®) environment.

Silver nanowires network encapsulated by low temperature sol-gel ZnO for transparent flexible electrodes with ambient stability

NASA Astrophysics Data System (ADS)

Shin, Wonjung; Cho, Wonki; Baik, Seung Jae

2018-01-01

As a geometrically engineered realization of transparent electrode, Ag nanowires network is promising for its superior characteristics both on electrical conductivity and optical transmittance. However, for a potential commercialization of Ag nanowires network, further investigations on encapsulation materials are necessary to prevent degradation caused by ambient aging. In addition, the temperature range of the coating process for the encapsulation material needs to be low enough to prevent degradation of polymer substrates during the film coating processes, when considering emerging flexible device application of transparent electrodes. We present experimental results showing that low temperature sol-gel ZnO processed under 130 °C is an effective encapsulation material preventing ambient oxidation of Ag nanowires network without degrading electrical, optical, and mechanical properties.

Autaptic effects on synchrony of neurons coupled by electrical synapses

NASA Astrophysics Data System (ADS)

Kim, Youngtae

2017-07-01

In this paper, we numerically study the effects of a special synapse known as autapse on synchronization of population of Morris-Lecar (ML) neurons coupled by electrical synapses. Several configurations of the ML neuronal populations such as a pair or a ring or a globally coupled network with and without autapses are examined. While most of the papers on the autaptic effects on synchronization have used networks of neurons of same spiking rate, we use the network of neurons of different spiking rates. We find that the optimal autaptic coupling strength and the autaptic time delay enhance synchronization in our neural networks. We use the phase response curve analysis to explain the enhanced synchronization by autapses. Our findings reveal the important relationship between the intraneuronal feedback loop and the interneuronal coupling.

Vibration reduction for smart periodic structures via periodic piezoelectric arrays with nonlinear interleaved-switched electronic networks

NASA Astrophysics Data System (ADS)

Bao, Bin; Guyomar, Daniel; Lallart, Mickaël

2017-01-01

Smart periodic structures covered by periodically distributed piezoelectric patches have drawn more and more attention in recent years for wave propagation attenuation and corresponding structural vibration suppression. Since piezoelectric materials are special type of energy conversion materials that link mechanical characteristics with electrical characteristics, shunt circuits coupled with such materials play a key role in the wave propagation and/or vibration control performance in smart periodic structures. Conventional shunt circuit designs utilize resistive shunt (R-shunt) and resonant shunt (RL-shunt). More recently, semi-passive nonlinear approaches have also been developed for efficiently controlling the vibrations of such structures. In this paper, an innovative smart periodic beam structure with nonlinear interleaved-switched electric networks based on synchronized switching damping on inductor (SSDI) is proposed and investigated for vibration reduction and wave propagation attenuation. Different from locally resonant band gap mechanism forming narrow band gaps around the desired resonant frequencies, the proposed interleaved electrical networks can induce new broadly low-frequency stop bands and broaden primitive Bragg stop bands by virtue of unique interleaved electrical configurations and the SSDI technique which has the unique feature of realizing automatic impedance adaptation with a small inductance. Finite element modeling of a Timoshenko electromechanical beam structure is also presented for validating dispersion properties of the structure. Both theoretical and experimental results demonstrate that the proposed beam structure not only shows better vibration and wave propagation attenuation than the smart beam structure with independent switched networks, but also has technical simplicity of requiring only half of the number of switches than the independent switched network needs.

Application of Neural Networks to Predict UH-60L Electrical Generator Condition using (IMD-HUMS) Data

DTIC Science & Technology

2006-12-01

Data transfer unit ( DTU ) • Remote data concentrator (RDC) • Main processor unit (MPU) • 2 junction boxes (JB1/JB2) • 20 drive train and...NETWORKS TO PREDICT UH-60L ELECTRICAL GENERATOR CONDITION USING (IMD-HUMS) DATA by Evangelos Tourvalis December 2006 Thesis Advisor...including the time for reviewing instruction, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the

Designing Predictive Diagnose Method for Insulation Resistance Degradation of the Electrical Power Cables from Neutral Insulated Power Networks

NASA Astrophysics Data System (ADS)

Dobra, R.; Pasculescu, D.; Risteiu, M.; Buica, G.; Jevremović, V.

2017-06-01

This paper describe some possibilities to minimize voltages switching-off risks from the mining power networks, in case of insulated resistance faults by using a predictive diagnose method. The cables from the neutral insulated power networks (underground mining) are designed to provide a flexible electrical connection between portable or mobile equipment and a point of supply, including main feeder cable for continuous miners, pump cable, and power supply cable. An electronic protection for insulated resistance of mining power cables can be made using this predictive strategy. The main role of electronic relays for insulation resistance degradation of the electrical power cables, from neutral insulated power networks, is to provide a permanent measurement of the insulated resistance between phases and ground, in order to switch-off voltage when the resistance value is below a standard value. The automat system of protection is able to signalize the failure and the human operator will be early informed about the switch-off power and will have time to take proper measures to fix the failure. This logic for fast and automat switch-off voltage without aprioristic announcement is suitable for the electrical installations, realizing so a protection against fires and explosion. It is presented an algorithm and an anticipative relay for insulated resistance control from three-phase low voltage installations with insulated neutral connection.

Electronic Neural Networks

NASA Technical Reports Server (NTRS)

Thakoor, Anil

1990-01-01

Viewgraphs on electronic neural networks for space station are presented. Topics covered include: electronic neural networks; electronic implementations; VLSI/thin film hybrid hardware for neurocomputing; computations with analog parallel processing; features of neuroprocessors; applications of neuroprocessors; neural network hardware for terrain trafficability determination; a dedicated processor for path planning; neural network system interface; neural network for robotic control; error backpropagation algorithm for learning; resource allocation matrix; global optimization neuroprocessor; and electrically programmable read only thin-film synaptic array.

Engineering highly organized and aligned single walled carbon nanotube networks for electronic device applications: Interconnects, chemical sensor, and optoelectronics

NASA Astrophysics Data System (ADS)

Kim, Young Lae

For 20 years, single walled carbon nanotubes (SWNTs) have been studied actively due to their unique one-dimensional nanostructure and superior electrical, thermal, and mechanical properties. For these reasons, they offer the potential to serve as building blocks for future electronic devices such as field effect transistors (FETs), electromechanical devices, and various sensors. In order to realize these applications, it is crucial to develop a simple, scalable, and reliable nanomanufacturing process that controllably places aligned SWNTs in desired locations, orientations, and dimensions. Also electronic properties (semiconducting/metallic) of SWNTs and their organized networks must be controlled for the desired performance of devices and systems. These fundamental challenges are significantly limiting the use of SWNTs for future electronic device applications. Here, we demonstrate a strategy to fabricate highly controlled micro/nanoscale SWNT network structures and present the related assembly mechanism to engineer the SWNT network topology and its electrical transport properties. A method designed to evaluate the electrical reliability of such nano- and microscale SWNT networks is also presented. Moreover, we develop and investigate a robust SWNT based multifunctional selective chemical sensor and a range of multifunctional optoelectronic switches, photo-transistors, optoelectronic logic gates and complex optoelectronic digital circuits.

Watchdog Project

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, Rhett; Campbell, Jack; Hadley, Mark

The Watchdog Project completed 100% of the project Statement of Project Objective (SOPO). The Watchdog project was a very aggressive project looking to accomplish commercialization of technology that had never been commercialized, as a result it took six years to complete not the original three that were planned. No additional federal funds were requested from the original proposal and SEL contributed the additional cost share required to complete the project. The result of the Watchdog Project is the world’s first industrial rated Software Defined Network (SDN) switch commercially available. This technology achieved the SOPOO and DOE Roadmap goals to havemore » strong network access control, improve reliability and network performance, and give the asset owner the ability to minimize attack surface before and during an attack. The Watchdog project is an alliance between CenterPoint Energy Houston Electric, Pacific Northwest National Laboratories (PNNL), and Schweitzer Engineering Laboratories, Inc. (SEL). SEL is the world’s leader in microprocessor-based electronic equipment for protecting electric power systems. PNNL performs basic and applied research to deliver energy, environmental, and national security for our nation. CenterPoint Energy is the third largest publicly traded natural gas delivery company in the U.S and third largest combined electricity and natural gas delivery company. The Watchdog Project efforts were combined with the SDN Project efforts to produce the entire SDN system solution for the critical infrastructure. The Watchdog project addresses Topic Area of Interest 5: Secure Communications, for the DEFOA- 0000359 by protecting the control system local area network itself and the communications coming from and going to the electronic devices on the local network. Local area networks usually are not routed and have little or no filtering capabilities. Combine this with the fact control system protocols are designed with inherent trust the control system owners have very little choice on how to protect communications on the local network. The Watchdog project reduces security risks in electric sector control system local area networks (LANs) by providing: Network access control (NAC) Multi-Layer firewall (physical through transport layer) Containment of malware or unauthorized traffic spreading across the network White list protocols and application message types filtering Configurable, proactive traffic engineering The Watchdog project achieved all of the above by developing an SDN switch.« less

Local Area Networks and the Learning Lab of the Future.

ERIC Educational Resources Information Center

Ebersole, Dennis C.

1987-01-01

Considers educational applications of local area computer networks and discusses industry standards for design established by the International Standards Organization (ISO) and Institute of Electrical and Electronic Engineers (IEEE). A futuristic view of a learning laboratory using a local area network is presented. (Author/LRW)

Smart sensorless prediction diagnosis of electric drives

NASA Astrophysics Data System (ADS)

Kruglova, TN; Glebov, NA; Shoshiashvili, ME

2017-10-01

In this paper, the discuss diagnostic method and prediction of the technical condition of an electrical motor using artificial intelligent method, based on the combination of fuzzy logic and neural networks, are discussed. The fuzzy sub-model determines the degree of development of each fault. The neural network determines the state of the object as a whole and the number of serviceable work periods for motors actuator. The combination of advanced techniques reduces the learning time and increases the forecasting accuracy. The experimental implementation of the method for electric drive diagnosis and associated equipment is carried out at different speeds. As a result, it was found that this method allows troubleshooting the drive at any given speed.

Energy Systems Integration News | Energy Systems Integration Facility |

Science.gov Websites

Grid Modernization Project Informed by ESIF Research The Hawaii Public Utilities Commission approved on (HECO) to upgrade its five island power grids. The plan describes the scope and estimated cost to update the energy networks of Hawaiian Electric, Maui Electric, and Hawaii Electric Light in the next five

Damage Diagnosis in Semiconductive Materials Using Electrical Impedance Measurements

NASA Technical Reports Server (NTRS)

Ross, Richard W.; Hinton, Yolanda L.

2008-01-01

Recent aerospace industry trends have resulted in an increased demand for real-time, effective techniques for in-flight structural health monitoring. A promising technique for damage diagnosis uses electrical impedance measurements of semiconductive materials. By applying a small electrical current into a material specimen and measuring the corresponding voltages at various locations on the specimen, changes in the electrical characteristics due to the presence of damage can be assessed. An artificial neural network uses these changes in electrical properties to provide an inverse solution that estimates the location and magnitude of the damage. The advantage of the electrical impedance method over other damage diagnosis techniques is that it uses the material as the sensor. Simple voltage measurements can be used instead of discrete sensors, resulting in a reduction in weight and system complexity. This research effort extends previous work by employing finite element method models to improve accuracy of complex models with anisotropic conductivities and by enhancing the computational efficiency of the inverse techniques. The paper demonstrates a proof of concept of a damage diagnosis approach using electrical impedance methods and a neural network as an effective tool for in-flight diagnosis of structural damage to aircraft components.

The Increase of Power Efficiency of Underground Coal Mining by the Forecasting of Electric Power Consumption

NASA Astrophysics Data System (ADS)

Efremenko, Vladimir; Belyaevsky, Roman; Skrebneva, Evgeniya

2017-11-01

In article the analysis of electric power consumption and problems of power saving on coal mines are considered. Nowadays the share of conditionally constant costs of electric power for providing safe working conditions underground on coal mines is big. Therefore, the power efficiency of underground coal mining depends on electric power expense of the main technological processes and size of conditionally constant costs. The important direction of increase of power efficiency of coal mining is forecasting of a power consumption and monitoring of electric power expense. One of the main approaches to reducing of electric power costs is increase in accuracy of the enterprise demand in the wholesale electric power market. It is offered to use artificial neural networks to forecasting of day-ahead power consumption with hourly breakdown. At the same time use of neural and indistinct (hybrid) systems on the principles of fuzzy logic, neural networks and genetic algorithms is more preferable. This model allows to do exact short-term forecasts at a small array of input data. A set of the input parameters characterizing mining-and-geological and technological features of the enterprise is offered.

Description of a MIL-STD-1553B Data Bus Ada Driver for the LeRC EPS Testbed

NASA Technical Reports Server (NTRS)

Mackin, Michael A.

1995-01-01

This document describes the software designed to provide communication between control computers in the NASA Lewis Research Center Electrical Power System Testbed using MIL-STD-1553B. The software drivers are coded in the Ada programming language and were developed on a MSDOS-based computer workstation. The Electrical Power System (EPS) Testbed is a reduced-scale prototype space station electrical power system. The power system manages and distributes electrical power from the sources (batteries or photovoltaic arrays) to the end-user loads. The electrical system primary operates at 120 volts DC, and the secondary system operates at 28 volts DC. The devices which direct the flow of electrical power are controlled by a network of six control computers. Data and control messages are passed between the computers using the MIL-STD-1553B network. One of the computers, the Power Management Controller (PMC), controls the primary power distribution and another, the Load Management Controller (LMC), controls the secondary power distribution. Each of these computers communicates with two other computers which act as subsidiary controllers. These subsidiary controllers are, in turn, connected to the devices which directly control the flow of electrical power.

The Future of Centrally-Organized Wholesale Electricity Markets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Glazer, Craig; Morrison, Jay; Breakman, Paul

The electricity grid in the United States is organized around a network of large, centralized power plants and high voltage transmission lines that transport electricity, sometimes over large distances, before it is delivered to the customer through a local distribution grid. This network of centralized generation and high voltage transmission lines is called the “bulk power system.” Costs relating to bulk power generation typically account for more than half of a customer’s electric bill.1 For this reason, the structure and functioning of wholesale electricity markets have major impacts on costs and economic value for consumers, as well as energy securitymore » and national security. Diverse arrangements for bulk power wholesale markets have evolved over the last several decades. The Southeast and Western United States outside of California have a “bilateral-based” bulk power system where market participants enter into long-term bilateral agreements — using competitive procurements through power marketers, direct arrangements among utilities or with other generation owners, and auctions and exchanges.« less

On the reliability of voltage and power as input parameters for the characterization of high power ultrasound applications

NASA Astrophysics Data System (ADS)

Haller, Julian; Wilkens, Volker

2012-11-01

For power levels up to 200 W and sonication times up to 60 s, the electrical power, the voltage and the electrical impedance (more exactly: the ratio of RMS voltage and RMS current) have been measured for a piezocomposite high intensity therapeutic ultrasound (HITU) transducer with integrated matching network, two piezoceramic HITU transducers with external matching networks and for a passive dummy 50 Ω load. The electrical power and the voltage were measured during high power application with an inline power meter and an RMS voltage meter, respectively, and the complex electrical impedance was indirectly measured with a current probe, a 100:1 voltage probe and a digital scope. The results clearly show that the input RMS voltage and the input RMS power change unequally during the application. Hence, the indication of only the electrical input power or only the voltage as the input parameter may not be sufficient for reliable characterizations of ultrasound transducers for high power applications in some cases.

Geography and the costs of urban energy infrastructure: The case of electricity and natural gas capital investments

NASA Astrophysics Data System (ADS)

Senyel, Muzeyyen Anil

Investments in the urban energy infrastructure for distributing electricity and natural gas are analyzed using (1) property data measuring distribution plant value at the local/tax district level, and (2) system outputs such as sectoral numbers of customers and energy sales, input prices, company-specific characteristics such as average wages and load factor. Socio-economic and site-specific urban and geographic variables, however, often been neglected in past studies. The purpose of this research is to incorporate these site-specific characteristics of electricity and natural gas distribution into investment cost model estimations. These local characteristics include (1) socio-economic variables, such as income and wealth; (2) urban-related variables, such as density, land-use, street pattern, housing pattern; (3) geographic and environmental variables, such as soil, topography, and weather, and (4) company-specific characteristics such as average wages, and load factor. The classical output variables include residential and commercial-industrial customers and sales. In contrast to most previous research, only capital investments at the local level are considered. In addition to aggregate cost modeling, the analysis focuses on the investment costs for the system components: overhead conductors, underground conductors, conduits, poles, transformers, services, street lighting, and station equipment for electricity distribution; and mains, services, regular and industrial measurement and regulation stations for natural gas distribution. The Box-Cox, log-log and additive models are compared to determine the best fitting cost functions. The Box-Cox form turns out to be superior to the other forms at the aggregate level and for network components. However, a linear additive form provides a better fit for end-user related components. The results show that, in addition to output variables and company-specific variables, various site-specific variables are statistically significant at the aggregate and disaggregate levels. Local electricity and natural gas distribution networks are characterized by a natural monopoly cost structure and economies of scale and density. The results provide evidence for the economies of scale and density for the aggregate electricity and natural gas distribution systems. However, distribution components have varying economic characteristics. The backbones of the networks (overhead conductors for electricity, and mains for natural gas) display economies of scale and density, but services in both systems and street lighting display diseconomies of scale and diseconomies of density. Finally multi-utility network cost analyses are presented for aggregate and disaggregate electricity and natural gas capital investments. Economies of scope analyses investigate whether providing electricity and natural gas jointly is economically advantageous, as compared to providing these products separately. Significant economies of scope are observed for both the total network and the underground capital investments.

Neural network based inspection of voids and karst conduits in hydro-electric power station tunnels using GPR

NASA Astrophysics Data System (ADS)

Kilic, Gokhan; Eren, Levent

2018-04-01

This paper reports on the fundamental role played by Ground Penetrating Radar (GPR), alongside advanced processing and presentation methods, during the tunnel boring project at a Dam and Hydro-Electric Power Station. It identifies from collected GPR data such issues as incomplete grouting and the presence of karst conduits and voids and provides full details of the procedures adopted. In particular, the application of collected GPR data to the Neural Network (NN) method is discussed.

Wireless Local Area Networks: The Next Evolutionary Step.

ERIC Educational Resources Information Center

Wodarz, Nan

2001-01-01

The Institute of Electrical and Electronics Engineers recently approved a high-speed wireless standard that enables devices from different manufacturers to communicate through a common backbone, making wireless local area networks more feasible in schools. Schools can now use wireless access points and network cards to provide flexible…

Inductors and Inductance-Resistance Networks.

ERIC Educational Resources Information Center

Kirwin, Gerald J.

This programed booklet presents ideas related to inductors and inductance--resistance networks. It is designed for the engineering student who is familiar with differential equations and electrical networks. A variety of cases are considered with the idea of developing in the student a broad acquaintance with the inductor response. The booklet is…

Wireless Sensor Network Radio Power Management and Simulation Models

DTIC Science & Technology

2010-01-01

The Open Electrical & Electronic Engineering Journal, 2010, 4, 21-31 21 1874-1290/10 2010 Bentham Open Open Access Wireless Sensor Network Radio...Air Force Institute of Technology, Wright-Patterson AFB, OH, USA Abstract: Wireless sensor networks (WSNs) create a new frontier in collecting and...consumption. Keywords: Wireless sensor network , power management, energy-efficiency, medium access control (MAC), simulation pa- rameters. 1

Thin-Film Nanowire Networks for Transparent Conductor Applications: Simulations of Sheet Resistance and Percolation Thresholds

NASA Astrophysics Data System (ADS)

Winey, Karen I.; Mutiso, Rose M.; Sherrott, Michelle C.; Rathmell, Aaron R.; Wiley, Benjamin J.

2013-03-01

Thin-film metal nanowire networks are being pursued as a viable alternative to the expensive and brittle indium tin oxide (ITO) for transparent conductors. For high performance applications, nanowire networks must exhibit high transmittance at low sheet resistance. Previously, we have used complimentary experimental, simulation and theoretical techniques to explore the effects of filler aspect ratio (L/D), orientation, and size-dispersity on the electrical conductivity of three-dimensional rod-networks in bulk polymer nanocomposites. We adapted our 3D simulation approach and analytical percolation model to study the electrical properties of thin-film rod-networks. By fitting our simulation results to experimental results, we determined the average effective contact resistance between silver nanowires. This contact resistance was then used to quantify how the sheet resistance depends on the aspect ratio of the rods and to show that networks made of nanowires with L/D greater than 100 yield sheet resistances lower than the required 100 Ohm/sq. We also report the critical area fraction of rods required to form a percolated network in thin-film networks and provide an analytical expression for the critical area fraction as a function of L/D.

Ice-Templated Bimodal-Porous Silver Nanowire/PDMS Nanocomposites for Stretchable Conductor.

PubMed

Oh, Jae Young; Lee, Dongju; Hong, Soon Hyung

2018-06-27

A three-dimensional (3D) bimodal-porous silver nanowire (AgNW) nanostructure with superior electrical properties is fabricated by freeze drying of AgNW aqueous dispersion with macrosized ice spheres for bimodal-porous structure. The ice sphere dispersed AgNW solution yields a 3D AgNW network at the surface of ice sphere and formation of macropores by removal of ice sphere during freeze-drying process. The resulting nanostructures exhibit excellent electrical properties due to their low electrical percolation threshold by the formation of macropores, which results in an efficient and dense 3D AgNW network with a small amount of AgNWs. The highly conductive and stretchable AgNW/poly(dimethylsiloxane) (PDMS) nanocomposites are made by impregnating the 3D porous conductive network with highly stretchable poly(dimethylsiloxane) (PDMS) matrix. The AgNW/PDMS nanocomposites exhibit a high conductivity of 42 S/cm with addition of relatively small amount of 2 wt %. The high conductivity is retained when stretched up to 120% elongation even after 100 stretching-releasing cycles. Due to high electrical conductivity and superior stretchability of AgNW/PDMS nanocomposites, these are expected to be used in stretchable electronic devices.

Modeling of electrochemical flow capacitors using Stokesian dynamics

NASA Astrophysics Data System (ADS)

Karzar Jeddi, Mehdi; Luo, Haoxiang; Cummings, Peter; Hatzell, Kelsey

2017-11-01

Electrochemical flow capacitors (EFCs) are supercapacitors designed to store electrical energy in the form of electrical double layer (EDL) near the surface of porous carbon particles. During its operation, a slurry of activated carbon beads and smaller carbon black particles is pumped between two flat and parallel electrodes. In the charging phase, ions in the electrolyte diffuse to the EDL, and electrical charges percolate through the dynamic network of particles from the flat electrodes; during the discharging phase, the process is reversed with the ions released to the bulk fluid and electrical charges percolating back through the network. In these processes, the relative motion and contact of particle of different sizes affect not only the rheology of the slurry but also charge transfer of the percolation network. In this study, we use Stoekesian dynamics simulation to investigate the role of hydrodynamic interactions of packed carbon particles in the charging/discharging behaviors of EFCs. We derived mobility functions for polydisperse spheres near a no-slip wall. A code is implemented and validated, and a simple charging model has been incorporated to represent charge transfer. Theoretical formulation and results demonstration will be presented in this talk.

Relative Localization in Wireless Sensor Networks for Measurement of Electric Fields under HVDC Transmission Lines

PubMed Central

Cui, Yong; Wang, Qiusheng; Yuan, Haiwen; Song, Xiao; Hu, Xuemin; Zhao, Luxing

2015-01-01

In the wireless sensor networks (WSNs) for electric field measurement system under the High-Voltage Direct Current (HVDC) transmission lines, it is necessary to obtain the electric field distribution with multiple sensors. The location information of each sensor is essential to the correct analysis of measurement results. Compared with the existing approach which gathers the location information by manually labelling sensors during deployment, the automatic localization can reduce the workload and improve the measurement efficiency. A novel and practical range-free localization algorithm for the localization of one-dimensional linear topology wireless networks in the electric field measurement system is presented. The algorithm utilizes unknown nodes' neighbor lists based on the Received Signal Strength Indicator (RSSI) values to determine the relative locations of nodes. The algorithm is able to handle the exceptional situation of the output permutation which can effectively improve the accuracy of localization. The performance of this algorithm under real circumstances has been evaluated through several experiments with different numbers of nodes and different node deployments in the China State Grid HVDC test base. Results show that the proposed algorithm achieves an accuracy of over 96% under different conditions. PMID:25658390

Relative localization in wireless sensor networks for measurement of electric fields under HVDC transmission lines.

PubMed

Cui, Yong; Wang, Qiusheng; Yuan, Haiwen; Song, Xiao; Hu, Xuemin; Zhao, Luxing

2015-02-04

In the wireless sensor networks (WSNs) for electric field measurement system under the High-Voltage Direct Current (HVDC) transmission lines, it is necessary to obtain the electric field distribution with multiple sensors. The location information of each sensor is essential to the correct analysis of measurement results. Compared with the existing approach which gathers the location information by manually labelling sensors during deployment, the automatic localization can reduce the workload and improve the measurement efficiency. A novel and practical range-free localization algorithm for the localization of one-dimensional linear topology wireless networks in the electric field measurement system is presented. The algorithm utilizes unknown nodes' neighbor lists based on the Received Signal Strength Indicator (RSSI) values to determine the relative locations of nodes. The algorithm is able to handle the exceptional situation of the output permutation which can effectively improve the accuracy of localization. The performance of this algorithm under real circumstances has been evaluated through several experiments with different numbers of nodes and different node deployments in the China State Grid HVDC test base. Results show that the proposed algorithm achieves an accuracy of over 96% under different conditions.

Polymer-stabilized liquid crystalline topological defect network for micro-pixelated optical devices

NASA Astrophysics Data System (ADS)

Araoka, Fumito; Le, Khoa V.; Fujii, Shuji; Orihara, Hiroshi; Sasaki, Yuji

2018-02-01

Spatially and temporally controlled topological defects in nematic liquid crystals (NLCs) are promising for its potential in optical applications. Utilization of self-organization is a key to fabricate complex micro- and nano-structures which are often difficult to obtain by conventional lithographic tools. Using photo-polymerization technique, here we show a polymer-stabilized NLC having a micro-pixelated structure of regularly ordered umbilical defects which are induced by an electric field. Due to the formation of polymer network, the self-organized pattern is kept stable without deterioration. Moreover, the polymer network allows to template other LCs whose optical properties can be tuned with external stimuli such as temperature and electric fields.

Synaptic Effects of Electric Fields

NASA Astrophysics Data System (ADS)

Rahman, Asif

Learning and sensory processing in the brain relies on the effective transmission of information across synapses. The strength and efficacy of synaptic transmission is modifiable through training and can be modulated with noninvasive electrical brain stimulation. Transcranial electrical stimulation (TES), specifically, induces weak intensity and spatially diffuse electric fields in the brain. Despite being weak, electric fields modulate spiking probability and the efficacy of synaptic transmission. These effects critically depend on the direction of the electric field relative to the orientation of the neuron and on the level of endogenous synaptic activity. TES has been used to modulate a wide range of neuropsychiatric indications, for various rehabilitation applications, and cognitive performance in diverse tasks. How can a weak and diffuse electric field, which simultaneously polarizes neurons across the brain, have precise changes in brain function? Designing therapies to maximize desired outcomes and minimize undesired effects presents a challenging problem. A series of experiments and computational models are used to define the anatomical and functional factors leading to specificity of TES. Anatomical specificity derives from guiding current to targeted brain structures and taking advantage of the direction-sensitivity of neurons with respect to the electric field. Functional specificity originates from preferential modulation of neuronal networks that are already active. Diffuse electric fields may recruit connected brain networks involved in a training task and promote plasticity along active synaptic pathways. In vitro, electric fields boost endogenous synaptic plasticity and raise the ceiling for synaptic learning with repeated stimulation sessions. Synapses undergoing strong plasticity are preferentially modulated over weak synapses. Therefore, active circuits that are involved in a task could be more susceptible to stimulation than inactive circuits. Moreover, stimulation polarity has asymmetric effects on synaptic strength making it easier to enhance ongoing plasticity. These results suggest that the susceptibility of brain networks to an electric field depends on the state of synaptic activity. Combining a training task, which activates specific circuits, with TES may lead to functionally-specific effects. Given the simplicity of TES and the complexity of brain function, understanding the mechanisms leading to specificity is fundamental to the rational advancement of TES.

Automated Demand Response Approaches to Household Energy Management in a Smart Grid Environment

NASA Astrophysics Data System (ADS)

Adika, Christopher Otieno

The advancement of renewable energy technologies and the deregulation of the electricity market have seen the emergence of Demand response (DR) programs. Demand response is a cost-effective load management strategy which enables the electricity suppliers to maintain the integrity of the power grid during high peak periods, when the customers' electrical load is high. DR programs are designed to influence electricity users to alter their normal consumption patterns by offering them financial incentives. A well designed incentive-based DR scheme that offer competitive electricity pricing structure can result in numerous benefits to all the players in the electricity market. Lower power consumption during peak periods will significantly enhance the robustness of constrained networks by reducing the level of power of generation and transmission infrastructure needed to provide electric service. Therefore, this will ease the pressure of building new power networks as we avoiding costly energy procurements thereby translating into huge financial savings for the power suppliers. Peak load reduction will also reduce the inconveniences suffered by end users as a result of brownouts or blackouts. Demand response will also drastically lower the price peaks associated with wholesale markets. This will in turn reduce the electricity costs and risks for all the players in the energy market. Additionally, DR is environmentally friendly since it enhances the flexibility of the power grid through accommodation of renewable energy resources. Despite its many benefits, DR has not been embraced by most electricity networks. This can be attributed to the fact that the existing programs do not provide enough incentives to the end users and, therefore, most electricity users are not willing to participate in them. To overcome these challenges, most utilities are coming up with innovative strategies that will be more attractive to their customers. Thus, this dissertation presents various demand response schemes that can be deployed by electricity providers to manage customer loads. This study also addresses the problem of manual demand response by proposing smart systems that will autonomously execute the DR programs without the direct involvement of the customers.

Simulation of short-term electric load using an artificial neural network

NASA Astrophysics Data System (ADS)

Ivanin, O. A.

2018-01-01

While solving the task of optimizing operation modes and equipment composition of small energy complexes or other tasks connected with energy planning, it is necessary to have data on energy loads of a consumer. Usually, there is a problem with obtaining real load charts and detailed information about the consumer, because a method of load-charts simulation on the basis of minimal information should be developed. The analysis of work devoted to short-term loads prediction allows choosing artificial neural networks as a most suitable mathematical instrument for solving this problem. The article provides an overview of applied short-term load simulation methods; it describes the advantages of artificial neural networks and offers a neural network structure for electric loads of residential buildings simulation. The results of modeling loads with proposed method and the estimation of its error are presented.

Corticocortical evoked potentials reveal projectors and integrators in human brain networks.

PubMed

Keller, Corey J; Honey, Christopher J; Entz, Laszlo; Bickel, Stephan; Groppe, David M; Toth, Emilia; Ulbert, Istvan; Lado, Fred A; Mehta, Ashesh D

2014-07-02

The cerebral cortex is composed of subregions whose functional specialization is largely determined by their incoming and outgoing connections with each other. In the present study, we asked which cortical regions can exert the greatest influence over other regions and the cortical network as a whole. Previous research on this question has relied on coarse anatomy (mapping large fiber pathways) or functional connectivity (mapping inter-regional statistical dependencies in ongoing activity). Here we combined direct electrical stimulation with recordings from the cortical surface to provide a novel insight into directed, inter-regional influence within the cerebral cortex of awake humans. These networks of directed interaction were reproducible across strength thresholds and across subjects. Directed network properties included (1) a decrease in the reciprocity of connections with distance; (2) major projector nodes (sources of influence) were found in peri-Rolandic cortex and posterior, basal and polar regions of the temporal lobe; and (3) major receiver nodes (receivers of influence) were found in anterolateral frontal, superior parietal, and superior temporal regions. Connectivity maps derived from electrical stimulation and from resting electrocorticography (ECoG) correlations showed similar spatial distributions for the same source node. However, higher-level network topology analysis revealed differences between electrical stimulation and ECoG that were partially related to the reciprocity of connections. Together, these findings inform our understanding of large-scale corticocortical influence as well as the interpretation of functional connectivity networks. Copyright © 2014 the authors 0270-6474/14/349152-12$15.00/0.

Low pass filter for plasma discharge

DOEpatents

Miller, Paul A.

1994-01-01

An isolator is disposed between a plasma reactor and its electrical energy source in order to isolate the reactor from the electrical energy source. The isolator operates as a filter to attenuate the transmission of harmonics of a fundamental frequency of the electrical energy source generated by the reactor from interacting with the energy source. By preventing harmonic interaction with the energy source, plasma conditions can be readily reproduced independent of the electrical characteristics of the electrical energy source and/or its associated coupling network.

A Multi Agent-Based Framework for Simulating Household PHEV Distribution and Electric Distribution Network Impact

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cui, Xiaohui; Liu, Cheng; Kim, Hoe Kyoung

2011-01-01

The variation of household attributes such as income, travel distance, age, household member, and education for different residential areas may generate different market penetration rates for plug-in hybrid electric vehicle (PHEV). Residential areas with higher PHEV ownership could increase peak electric demand locally and require utilities to upgrade the electric distribution infrastructure even though the capacity of the regional power grid is under-utilized. Estimating the future PHEV ownership distribution at the residential household level can help us understand the impact of PHEV fleet on power line congestion, transformer overload and other unforeseen problems at the local residential distribution network level.more » It can also help utilities manage the timing of recharging demand to maximize load factors and utilization of existing distribution resources. This paper presents a multi agent-based simulation framework for 1) modeling spatial distribution of PHEV ownership at local residential household level, 2) discovering PHEV hot zones where PHEV ownership may quickly increase in the near future, and 3) estimating the impacts of the increasing PHEV ownership on the local electric distribution network with different charging strategies. In this paper, we use Knox County, TN as a case study to show the simulation results of the agent-based model (ABM) framework. However, the framework can be easily applied to other local areas in the US.« less

SERS investigations and electrical recording of neuronal networks with three-dimensional plasmonic nanoantennas (Conference Presentation)

NASA Astrophysics Data System (ADS)

De Angelis, Francesco

2017-06-01

SERS investigations and electrical recording of neuronal networks with three-dimensional plasmonic nanoantennas Michele Dipalo, Valeria Caprettini, Anbrea Barbaglia, Laura Lovato, Francesco De Angelis e-mail: francesco.deangelis@iit.it Istituto Italiano di Tecnologia, Via Morego 30, 16163, Genova Biological systems are analysed mainly by optical, chemical or electrical methods. Normally each of these techniques provides only partial information about the environment, while combined investigations could reveal new phenomena occurring in complex systems such as in-vitro neuronal networks. Aiming at the merging of optical and electrical investigations of biological samples, we introduced three-dimensional plasmonic nanoantennas on CMOS-based electrical sensors [1]. The overall device is then capable of enhanced Raman Analysis of cultured cells combined with electrical recording of neuronal activity. The Raman measurements show a much higher sensitivity when performed on the tip of the nanoantenna in respect to the flat substrate [2]; this effect is a combination of the high plasmonic field enhancement and of the tight adhesion of cells on the nanoantenna tip. Furthermore, when plasmonic opto-poration is exploited [3] the 3D nanoelectrodes are able to penetrate through the cell membrane thus accessing the intracellular environment. Our latest results (unpublished) show that the technique is completely non-invasive and solves many problems related to state-of-the-art intracellular recording approaches on large neuronal networks. This research received funding from ERC-IDEAS Program: "Neuro-Plasmonics" [Grant n. 616213]. References: [1] M. Dipalo, G. C. Messina, H. Amin, R. La Rocca, V. Shalabaeva, A. Simi, A. Maccione, P. Zilio, L. Berdondini, F. De Angelis, Nanoscale 2015, 7, 3703. [2] R. La Rocca, G. C. Messina, M. Dipalo, V. Shalabaeva, F. De Angelis, Small 2015, 11, 4632. [3] G. C. Messina et al., Spatially, Temporally, and Quantitatively Controlled Delivery of Broad Range of Molecules into Selected Cells through Plasmonic Nanotubes. Advanced Materials 2015.

Intelligent, self-contained robotic hand

DOEpatents

Krutik, Vitaliy; Doo, Burt; Townsend, William T.; Hauptman, Traveler; Crowell, Adam; Zenowich, Brian; Lawson, John

2007-01-30

A robotic device has a base and at least one finger having at least two links that are connected in series on rotary joints with at least two degrees of freedom. A brushless motor and an associated controller are located at each joint to produce a rotational movement of a link. Wires for electrical power and communication serially connect the controllers in a distributed control network. A network operating controller coordinates the operation of the network, including power distribution. At least one, but more typically two to five, wires interconnect all the controllers through one or more joints. Motor sensors and external world sensors monitor operating parameters of the robotic hand. The electrical signal output of the sensors can be input anywhere on the distributed control network. V-grooves on the robotic hand locate objects precisely and assist in gripping. The hand is sealed, immersible and has electrical connections through the rotary joints for anodizing in a single dunk without masking. In various forms, this intelligent, self-contained, dexterous hand, or combinations of such hands, can perform a wide variety of object gripping and manipulating tasks, as well as locomotion and combinations of locomotion and gripping.

Process for anodizing a robotic device

DOEpatents

Townsend, William T [Weston, MA

2011-11-08

A robotic device has a base and at least one finger having at least two links that are connected in series on rotary joints with at least two degrees of freedom. A brushless motor and an associated controller are located at each joint to produce a rotational movement of a link. Wires for electrical power and communication serially connect the controllers in a distributed control network. A network operating controller coordinates the operation of the network, including power distribution. At least one, but more typically two to five, wires interconnect all the controllers through one or more joints. Motor sensors and external world sensors monitor operating parameters of the robotic hand. The electrical signal output of the sensors can be input anywhere on the distributed control network. V-grooves on the robotic hand locate objects precisely and assist in gripping. The hand is sealed, immersible and has electrical connections through the rotary joints for anodizing in a single dunk without masking. In various forms, this intelligent, self-contained, dexterous hand, or combinations of such hands, can perform a wide variety of object gripping and manipulating tasks, as well as locomotion and combinations of locomotion and gripping.

Dopamine Attenuates Ketamine-Induced Neuronal Apoptosis in the Developing Rat Retina Independent of Early Synchronized Spontaneous Network Activity.

PubMed

Dong, Jing; Gao, Lingqi; Han, Junde; Zhang, Junjie; Zheng, Jijian

2017-07-01

Deprivation of spontaneous rhythmic electrical activity in early development by anesthesia administration, among other interventions, induces neuronal apoptosis. However, it is unclear whether enhancement of neuronal electrical activity attenuates neuronal apoptosis in either normal development or after anesthesia exposure. The present study investigated the effects of dopamine, an enhancer of spontaneous rhythmic electrical activity, on ketamine-induced neuronal apoptosis in the developing rat retina. TUNEL and immunohistochemical assays indicated that ketamine time- and dose-dependently aggravated physiological and ketamine-induced apoptosis and inhibited early-synchronized spontaneous network activity. Dopamine administration reversed ketamine-induced neuronal apoptosis, but did not reverse the inhibitory effects of ketamine on early synchronized spontaneous network activity despite enhancing it in controls. Blockade of D1, D2, and A2A receptors and inhibition of cAMP/PKA signaling partially antagonized the protective effect of dopamine against ketamine-induced apoptosis. Together, these data indicate that dopamine attenuates ketamine-induced neuronal apoptosis in the developing rat retina by activating the D1, D2, and A2A receptors, and upregulating cAMP/PKA signaling, rather than through modulation of early synchronized spontaneous network activity.

A modular neural network scheme applied to fault diagnosis in electric power systems.

PubMed

Flores, Agustín; Quiles, Eduardo; García, Emilio; Morant, Francisco; Correcher, Antonio

2014-01-01

This work proposes a new method for fault diagnosis in electric power systems based on neural modules. With this method the diagnosis is performed by assigning a neural module for each type of component comprising the electric power system, whether it is a transmission line, bus or transformer. The neural modules for buses and transformers comprise two diagnostic levels which take into consideration the logic states of switches and relays, both internal and back-up, with the exception of the neural module for transmission lines which also has a third diagnostic level which takes into account the oscillograms of fault voltages and currents as well as the frequency spectrums of these oscillograms, in order to verify if the transmission line had in fact been subjected to a fault. One important advantage of the diagnostic system proposed is that its implementation does not require the use of a network configurator for the system; it does not depend on the size of the power network nor does it require retraining of the neural modules if the power network increases in size, making its application possible to only one component, a specific area, or the whole context of the power system.

A Modular Neural Network Scheme Applied to Fault Diagnosis in Electric Power Systems

PubMed Central

Flores, Agustín; Morant, Francisco

2014-01-01

This work proposes a new method for fault diagnosis in electric power systems based on neural modules. With this method the diagnosis is performed by assigning a neural module for each type of component comprising the electric power system, whether it is a transmission line, bus or transformer. The neural modules for buses and transformers comprise two diagnostic levels which take into consideration the logic states of switches and relays, both internal and back-up, with the exception of the neural module for transmission lines which also has a third diagnostic level which takes into account the oscillograms of fault voltages and currents as well as the frequency spectrums of these oscillograms, in order to verify if the transmission line had in fact been subjected to a fault. One important advantage of the diagnostic system proposed is that its implementation does not require the use of a network configurator for the system; it does not depend on the size of the power network nor does it require retraining of the neural modules if the power network increases in size, making its application possible to only one component, a specific area, or the whole context of the power system. PMID:25610897

Extension algorithm for generic low-voltage networks

NASA Astrophysics Data System (ADS)

Marwitz, S.; Olk, C.

2018-02-01

Distributed energy resources (DERs) are increasingly penetrating the energy system which is driven by climate and sustainability goals. These technologies are mostly connected to low- voltage electrical networks and change the demand and supply situation in these networks. This can cause critical network states. Network topologies vary significantly and depend on several conditions including geography, historical development, network design or number of network connections. In the past, only some of these aspects were taken into account when estimating the network investment needs for Germany on the low-voltage level. Typically, fixed network topologies are examined or a Monte Carlo approach is used to quantify the investment needs at this voltage level. Recent research has revealed that DERs differ substantially between rural, suburban and urban regions. The low-voltage network topologies have different design concepts in these regions, so that different network topologies have to be considered when assessing the need for network extensions and investments due to DERs. An extension algorithm is needed to calculate network extensions and investment needs for the different typologies of generic low-voltage networks. We therefore present a new algorithm, which is capable of calculating the extension for generic low-voltage networks of any given topology based on voltage range deviations and thermal overloads. The algorithm requires information about line and cable lengths, their topology and the network state only. We test the algorithm on a radial, a loop, and a heavily meshed network. Here we show that the algorithm functions for electrical networks with these topologies. We found that the algorithm is able to extend different networks efficiently by placing cables between network nodes. The main value of the algorithm is that it does not require any information about routes for additional cables or positions for additional substations when it comes to estimating network extension needs.

An overview of natural hazard impacts to railways and urban transportation systems

NASA Astrophysics Data System (ADS)

Bíl, Michal; Nezval, Vojtěch; Bílová, Martina; Andrášik, Richard; Kubeček, Jan

2017-04-01

We present an overview and two case studies of natural hazard impacts on rail transportation systems in the Czech Republic. Flooding, landsliding, heavy snowfall, windstorms and glaze (black ice) are the most common natural processes which occur in this region. Whereas flooding and landsliding usually cause direct damage to the transportation infrastructure, other hazards predominantly cause indirect losses. Railway and urban tramline networks are almost fully dependent on electricity which is provided by a system of overhead lines (electric lines above the tracks). These lines are extremely susceptible to formation of glaze which blocks conduction of electric current. A December 2014 glaze event caused significant indirect losses in the largest Czech cities and railways due to the above-mentioned process. Details of this event will be provided during the presentation. Windstorms usually cause tree falls which can affect overhead lines and physically block railway tracks. Approximately 30 % of the Czech railway network is closer than 50 m from the nearest forest. This presents significant potential for transport interruption due to falling trees. Complicated legal relations among the owners of the plots of land along railways, the environment (full-grown trees and related habitat), and the railway administrator are behind many traffic interruptions due to falling trees. We have registered 2040 tree falls between 2012 and 2015 on the railway network. A model of the fallen tree hazard was created for the entire Czech railway network. Both above-mentioned case studies provide illustrative examples of the increased fragility of the modern transportation systems which fully rely on electricity. Natural processes with a low destructive power are thereby able to cause network wide service cut-offs.

Serial and parallel power equipment with high-temperature superconducting elements

NASA Technical Reports Server (NTRS)

Bencze, Laszlo; Goebl, Nandor; Palotas, Bela; Vajda, Istvan

1995-01-01

One of the prospective, practical applications of high-temperature superconductors is the fault-current limitation in electrical energy networks. The development and testing of experimental HTSC serial current limiters have been reported in the literature. A Hungarian electric power company has proposed the development of a parallel equipment for arc suppressing both in the industrial and customers' networks. On the basis of the company's proposal the authors have outlined the scheme of a compound circuit that can be applied both for current limitation and arc suppressing. In this paper the design principles and methods of the shunt equipment are presented. These principles involve the electrical, mechanical and cryogenic aspects with the special view on the electrical and mechanical connection between the HTSC material and the current lead. Preliminary experiments and tests have been carried out to demonstrate the validity of the design principles developed. The results of the experiments and of the technological investigations are presented.

System for adjusting frequency of electrical output pulses derived from an oscillator

DOEpatents

Bartholomew, David B.

2006-11-14

A system for setting and adjusting a frequency of electrical output pulses derived from an oscillator in a network is disclosed. The system comprises an accumulator module configured to receive pulses from an oscillator and to output an accumulated value. An adjustor module is configured to store an adjustor value used to correct local oscillator drift. A digital adder adds values from the accumulator module to values stored in the adjustor module and outputs their sums to the accumulator module, where they are stored. The digital adder also outputs an electrical pulse to a logic module. The logic module is in electrical communication with the adjustor module and the network. The logic module may change the value stored in the adjustor module to compensate for local oscillator drift or change the frequency of output pulses. The logic module may also keep time and calculate drift.

Sensorless FOC Performance Improved with On-Line Speed and Rotor Resistance Estimator Based on an Artificial Neural Network for an Induction Motor Drive

PubMed Central

Gutierrez-Villalobos, Jose M.; Rodriguez-Resendiz, Juvenal; Rivas-Araiza, Edgar A.; Martínez-Hernández, Moisés A.

2015-01-01

Three-phase induction motor drive requires high accuracy in high performance processes in industrial applications. Field oriented control, which is one of the most employed control schemes for induction motors, bases its function on the electrical parameter estimation coming from the motor. These parameters make an electrical machine driver work improperly, since these electrical parameter values change at low speeds, temperature changes, and especially with load and duty changes. The focus of this paper is the real-time and on-line electrical parameters with a CMAC-ADALINE block added in the standard FOC scheme to improve the IM driver performance and endure the driver and the induction motor lifetime. Two kinds of neural network structures are used; one to estimate rotor speed and the other one to estimate rotor resistance of an induction motor. PMID:26131677

Intelligent sensor and controller framework for the power grid

DOEpatents

Akyol, Bora A.; Haack, Jereme Nathan; Craig, Jr., Philip Allen; Tews, Cody William; Kulkarni, Anand V.; Carpenter, Brandon J.; Maiden, Wendy M.; Ciraci, Selim

2015-07-28

Disclosed below are representative embodiments of methods, apparatus, and systems for monitoring and using data in an electric power grid. For example, one disclosed embodiment comprises a sensor for measuring an electrical characteristic of a power line, electrical generator, or electrical device; a network interface; a processor; and one or more computer-readable storage media storing computer-executable instructions. In this embodiment, the computer-executable instructions include instructions for implementing an authorization and authentication module for validating a software agent received at the network interface; instructions for implementing one or more agent execution environments for executing agent code that is included with the software agent and that causes data from the sensor to be collected; and instructions for implementing an agent packaging and instantiation module for storing the collected data in a data container of the software agent and for transmitting the software agent, along with the stored data, to a next destination.

Sensorless FOC Performance Improved with On-Line Speed and Rotor Resistance Estimator Based on an Artificial Neural Network for an Induction Motor Drive.

PubMed

Gutierrez-Villalobos, Jose M; Rodriguez-Resendiz, Juvenal; Rivas-Araiza, Edgar A; Martínez-Hernández, Moisés A

2015-06-29

Three-phase induction motor drive requires high accuracy in high performance processes in industrial applications. Field oriented control, which is one of the most employed control schemes for induction motors, bases its function on the electrical parameter estimation coming from the motor. These parameters make an electrical machine driver work improperly, since these electrical parameter values change at low speeds, temperature changes, and especially with load and duty changes. The focus of this paper is the real-time and on-line electrical parameters with a CMAC-ADALINE block added in the standard FOC scheme to improve the IM driver performance and endure the driver and the induction motor lifetime. Two kinds of neural network structures are used; one to estimate rotor speed and the other one to estimate rotor resistance of an induction motor.

Optimising reverse logistics network to support policy-making in the case of Electrical and Electronic Equipment.

PubMed

Achillas, Ch; Vlachokostas, Ch; Aidonis, D; Moussiopoulos, N; Iakovou, E; Banias, G

2010-12-01

Due to the rapid growth of Waste Electrical and Electronic Equipment (WEEE) volumes, as well as the hazardousness of obsolete electr(on)ic goods, this type of waste is now recognised as a priority stream in the developed countries. Policy-making related to the development of the necessary infrastructure and the coordination of all relevant stakeholders is crucial for the efficient management and viability of individually collected waste. This paper presents a decision support tool for policy-makers and regulators to optimise electr(on)ic products' reverse logistics network. To that effect, a Mixed Integer Linear Programming mathematical model is formulated taking into account existing infrastructure of collection points and recycling facilities. The applicability of the developed model is demonstrated employing a real-world case study for the Region of Central Macedonia, Greece. The paper concludes with presenting relevant obtained managerial insights. Copyright © 2010 Elsevier Ltd. All rights reserved.

Intelligent sensor and controller framework for the power grid

DOE Office of Scientific and Technical Information (OSTI.GOV)

Akyol, Bora A.; Haack, Jereme Nathan; Craig, Jr., Philip Allen

Disclosed below are representative embodiments of methods, apparatus, and systems for monitoring and using data in an electric power grid. For example, one disclosed embodiment comprises a sensor for measuring an electrical characteristic of a power line, electrical generator, or electrical device; a network interface; a processor; and one or more computer-readable storage media storing computer-executable instructions. In this embodiment, the computer-executable instructions include instructions for implementing an authorization and authentication module for validating a software agent received at the network interface; instructions for implementing one or more agent execution environments for executing agent code that is included with themore » software agent and that causes data from the sensor to be collected; and instructions for implementing an agent packaging and instantiation module for storing the collected data in a data container of the software agent and for transmitting the software agent, along with the stored data, to a next destination.« less

Alternative Fuels Data Center: Electric Vehicles Charge up at State Parks

Science.gov Websites

with free electric vehicle charging. For information about this project, contact State of West Virginia Vehicle Charging Aug. 4, 2017 Photo of a car Johnson Space Center Explores Alternative Fuel Vehicles May 19, 2017 Photo of a car. Electric Vehicle Charging Network Expands at National Parks May 11, 2017

A study of the electrical properties of complex resistor network based on NW model

NASA Astrophysics Data System (ADS)

Chang, Yunfeng; Li, Yunting; Yang, Liu; Guo, Lu; Liu, Gaochao

2015-04-01

The power and resistance of two-port complex resistor network based on NW small world network model are studied in this paper. Mainly, we study the dependence of the network power and resistance on the degree of port vertices, the connection probability and the shortest distance. Qualitative analysis and a simplified formula for network resistance are given out. Finally, we define a branching parameter and give out its physical meaning in the analysis of complex resistor network.

Understanding the mechanisms leading to failure in metallic nanowire-based transparent heaters, and solution for stability enhancement

NASA Astrophysics Data System (ADS)

Lagrange, M.; Sannicolo, T.; Muñoz-Rojas, D.; Guillo Lohan, B.; Khan, A.; Anikin, M.; Jiménez, C.; Bruckert, F.; Bréchet, Y.; Bellet, D.

2017-02-01

Silver nanowire (AgNW) networks are emerging as one of the most promising alternatives to indium tin oxide (ITO) for transparent electrodes in flexible electronic devices. They can be used in a variety of optoelectronic applications such as solar cells, touch panels and organic light-emitting diodes. Recently they have also proven to be very efficient when used as transparent heaters (THs). In addition to the study of AgNW networks acting as THs in regular use, i.e. at low voltage and moderate temperature, their stability and physical behavior at higher voltages and for longer durations should be studied in view of their integration into real devices. The properties of AgNW networks deposited by spray coating on glass or flexible transparent substrates are thoroughly studied via in situ measurements. The AgNW networks’ behavior at different voltages for different durations and under different atmospheric conditions, both in air and under vacuum, has been examined. At low voltage, a reversible electrical response is observed while irreversibility and even failure are observed at higher voltages. In order to gain a deeper insight into the behavior of AgNW networks used as THs, simple but realistic physical models are proposed and are found to be in fair agreement with the experimental data. Finally, as the stability of AgNW networks is a key issue, we demonstrate that coating AgNW networks with a very thin layer of TiO2 using atomic layer deposition (ALD) improves the material’s resistance against electrical and thermal instabilities without altering optical transmittance. We show that the critical annealing temperature associated to network breakdown increases from 270 °C for the as-deposited AgNW networks to 420 °C for AgNW networks coated with TiO2. Similarly, the electrical failure which occurs at 7 V for the as-deposited networks increases to 13 V for TiO2-coated networks. TiO2 is also proved to stabilize AgNW networks during long duration operation and at high voltage. Temperature higher than 235 °C was achieved at 7 V without failure.

Etude et simulation de la MADA

NASA Astrophysics Data System (ADS)

Defontaines, Remi

Over the past ten years, the production of electric energy using wind turbines has increased eight times. This production of energy is in full expansion, and different means are now at the dispositions of researchers to finally explore it to the maximum. The DFIG is a type of wind turbine that has been the object of numerous studies over the past several years. This wind turbine functions with the speed of the wind. Its principle particularity is that it is constituted of an asynchronous machine, a wound-rotor and is capable of providing active power to the network by the stator and the rotor. This structure permits a good performance over a wide range of wind speeds, at a reasonable cost. It manages to be cost-effective because it uses weakly dimensioned power converters. Despite its advantages, there is a problem: its connection to the network. The electric network is not always stable; it regularly suffers voltage damage (low voltage, unbalance or overvoltage). This damage can result in fault from poor quality in the machine, and this damages or even destroys the power converters. To avoid this issue, the wind turbine disconnects from the network when it undergoes deterioration. The goal of this research is to find a strategy that allows the wind turbine to function even when the network voltage deteriorates, which in turn results in avoiding disconnection and therefore the loss of electrical power.

Distributed Processing System for Restoration of Electric Power Distribution Network Using Two-Layered Contract Net Protocol

NASA Astrophysics Data System (ADS)

Kodama, Yu; Hamagami, Tomoki

Distributed processing system for restoration of electric power distribution network using two-layered CNP is proposed. The goal of this study is to develop the restoration system which adjusts to the future power network with distributed generators. The state of the art of this study is that the two-layered CNP is applied for the distributed computing environment in practical use. The two-layered CNP has two classes of agents, named field agent and operating agent in the network. In order to avoid conflicts of tasks, operating agent controls privilege for managers to send the task announcement messages in CNP. This technique realizes the coordination between agents which work asynchronously in parallel with others. Moreover, this study implements the distributed processing system using a de-fact standard multi-agent framework, JADE(Java Agent DEvelopment framework). This study conducts the simulation experiments of power distribution network restoration and compares the proposed system with the previous system. We confirmed the results show effectiveness of the proposed system.

Analysis of the error of the developed method of determination the active conductivity reducing the insulation level between one phase of the network and ground, and insulation parameters in a non-symmetric network with isolated neutral with voltage above 1000 V

NASA Astrophysics Data System (ADS)

Utegulov, B. B.

2018-02-01

In the work the study of the developed method was carried out for reliability by analyzing the error in indirect determination of the insulation parameters in an asymmetric network with an isolated neutral voltage above 1000 V. The conducted studies of the random relative mean square errors show that the accuracy of indirect measurements in the developed method can be effectively regulated not only by selecting a capacitive additional conductivity, which are connected between phases of the electrical network and the ground, but also by the selection of measuring instruments according to the accuracy class. When choosing meters with accuracy class of 0.5 with the correct selection of capacitive additional conductivity that are connected between the phases of the electrical network and the ground, the errors in measuring the insulation parameters will not exceed 10%.

Exploring the impact of network tariffs on household electricity expenditures using load profiles and socio-economic characteristics

NASA Astrophysics Data System (ADS)

Azarova, Valeriya; Engel, Dominik; Ferner, Cornelia; Kollmann, Andrea; Reichl, Johannes

2018-04-01

Growing self-generation and storage are expected to cause significant changes in residential electricity utilization patterns. Commonly applied volumetric network tariffs may induce imbalance between different groups of households and their respective contribution to recovering the operating costs of the grid. Understanding consumer behaviour and appliance usage together with socio-economic factors can help regulatory authorities to adapt network tariffs to new circumstances in a fair way. Here, we assess the effects of 11 network tariff scenarios on household budgets using real load profiles from 765 households. Thus we explore the possibly disruptive impact of applying peak-load-based tariffs on the budgets of households when they have been mainly charged for consumed volumes before. Our analysis estimates the change in household network expenditure for different combinations of energy, peak and fixed charges, and can help to design tariffs that recover the costs needed for the sustainable operation of the grid.

Wireless Sensor Network for Radiometric Detection and Assessment of Partial Discharge in High-Voltage Equipment

NASA Astrophysics Data System (ADS)

Upton, D. W.; Saeed, B. I.; Mather, P. J.; Lazaridis, P. I.; Vieira, M. F. Q.; Atkinson, R. C.; Tachtatzis, C.; Garcia, M. S.; Judd, M. D.; Glover, I. A.

2018-03-01

Monitoring of partial discharge (PD) activity within high-voltage electrical environments is increasingly used for the assessment of insulation condition. Traditional measurement techniques employ technologies that either require off-line installation or have high power consumption and are hence costly. A wireless sensor network is proposed that utilizes only received signal strength to locate areas of PD activity within a high-voltage electricity substation. The network comprises low-power and low-cost radiometric sensor nodes which receive the radiation propagated from a source of PD. Results are reported from several empirical tests performed within a large indoor environment and a substation environment using a network of nine sensor nodes. A portable PD source emulator was placed at multiple locations within the network. Signal strength measured by the nodes is reported via WirelessHART to a data collection hub where it is processed using a location algorithm. The results obtained place the measured location within 2 m of the actual source location.

Analysis and Design of Manycore Processor-to-DRAM Opto-Electrical Networks with Integrated Silicon Photonics

DTIC Science & Technology

2009-12-24

Networks Silicon-Photonic Clos Networks for Global On-Chip Communication Ajay Joshi* Christopher Batten? Yong-Jin Kwon! Scott Beamer! Imran Shamim ...4th edition, 2007. •A\\ [13] A Joshi, C Batten, Y Kwon, S Beamer, Imran Shamim , Krste Asanovic, and Vladimir Sto- janovic. Silicon-photonic clos

MPNACK: an optical switching scheme enabling the buffer-less reliable transmission

NASA Astrophysics Data System (ADS)

Yu, Xiaoshan; Gu, Huaxi; Wang, Kun; Xu, Meng; Guo, Yantao

2016-01-01

Optical data center networks are becoming an increasingly promising solution to solve the bottlenecks faced by electrical networks, such as low transmission bandwidth, high wiring complexity, and unaffordable power consumption. However, the optical circuit switching (OCS) network is not flexible enough to carry the traffic burst while the optical packet switching (OPS) network cannot solve the packet contention in an efficient way. To this end, an improved switching strategy named OPS with multi-hop Negative Acknowledgement (MPNACK) is proposed. This scheme uses a feedback mechanism, rather than the buffering structure, to handle the optical packet contention. The collided packet is treated as a NACK packet and sent back to the source server. When the sender receives this NACK packet, it knows a collision happens in the transmission path and a retransmission procedure is triggered. Overall, the OPS-NACK scheme enables a reliable transmission in the buffer-less optical network. Furthermore, with this scheme, the expensive and energy-hungry elements, optical or electrical buffers, can be removed from the optical interconnects, thus a more scalable and cost-efficient network can be constructed for cloud computing data centers.

Multiple-Ring Digital Communication Network

NASA Technical Reports Server (NTRS)

Kirkham, Harold

1992-01-01

Optical-fiber digital communication network to support data-acquisition and control functions of electric-power-distribution networks. Optical-fiber links of communication network follow power-distribution routes. Since fiber crosses open power switches, communication network includes multiple interconnected loops with occasional spurs. At each intersection node is needed. Nodes of communication network include power-distribution substations and power-controlling units. In addition to serving data acquisition and control functions, each node acts as repeater, passing on messages to next node(s). Multiple-ring communication network operates on new AbNET protocol and features fiber-optic communication.

Research on Risk Manage of Power Construction Project Based on Bayesian Network

NASA Astrophysics Data System (ADS)

Jia, Zhengyuan; Fan, Zhou; Li, Yong

With China's changing economic structure and increasingly fierce competition in the market, the uncertainty and risk factors in the projects of electric power construction are increasingly complex, the projects will face huge risks or even fail if we don't consider or ignore these risk factors. Therefore, risk management in the projects of electric power construction plays an important role. The paper emphatically elaborated the influence of cost risk in electric power projects through study overall risk management and the behavior of individual in risk management, and introduced the Bayesian network to the project risk management. The paper obtained the order of key factors according to both scene analysis and causal analysis for effective risk management.

A Petri Net model for distributed energy system

NASA Astrophysics Data System (ADS)

Konopko, Joanna

2015-12-01

Electrical networks need to evolve to become more intelligent, more flexible and less costly. The smart grid is the next generation power energy, uses two-way flows of electricity and information to create a distributed automated energy delivery network. Building a comprehensive smart grid is a challenge for system protection, optimization and energy efficient. Proper modeling and analysis is needed to build an extensive distributed energy system and intelligent electricity infrastructure. In this paper, the whole model of smart grid have been proposed using Generalized Stochastic Petri Nets (GSPN). The simulation of created model is also explored. The simulation of the model has allowed the analysis of how close the behavior of the model is to the usage of the real smart grid.

The Applied Mathematics for Power Systems (AMPS)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chertkov, Michael

2012-07-24

Increased deployment of new technologies, e.g., renewable generation and electric vehicles, is rapidly transforming electrical power networks by crossing previously distinct spatiotemporal scales and invalidating many traditional approaches for designing, analyzing, and operating power grids. This trend is expected to accelerate over the coming years, bringing the disruptive challenge of complexity, but also opportunities to deliver unprecedented efficiency and reliability. Our Applied Mathematics for Power Systems (AMPS) Center will discover, enable, and solve emerging mathematics challenges arising in power systems and, more generally, in complex engineered networks. We will develop foundational applied mathematics resulting in rigorous algorithms and simulation toolboxesmore » for modern and future engineered networks. The AMPS Center deconstruction/reconstruction approach 'deconstructs' complex networks into sub-problems within non-separable spatiotemporal scales, a missing step in 20th century modeling of engineered networks. These sub-problems are addressed within the appropriate AMPS foundational pillar - complex systems, control theory, and optimization theory - and merged or 'reconstructed' at their boundaries into more general mathematical descriptions of complex engineered networks where important new questions are formulated and attacked. These two steps, iterated multiple times, will bridge the growing chasm between the legacy power grid and its future as a complex engineered network.« less

Intelligent optical networking with photonic cross connections

NASA Astrophysics Data System (ADS)

Ceuppens, L.; Jerphagnon, Olivier L.; Lang, Jonathan; Banerjee, Ayan; Blumenthal, Daniel J.

2002-09-01

Optical amplification and dense wavelength division multiplexing (DWDM) have fundamentally changed optical transport networks. Now that these technologies are widely adopted, the bottleneck has moved from the outside line plant to nodal central offices, where electrical switching equipment has not kept pace. While OEO technology was (and still is) necessary for grooming and traffic aggregation, the transport network has dramatically changed, requiring a dramatic rethinking of how networks need to be designed and operated. While todays transport networks carry remarkable amounts of bandwidth, their optical layer is fundamentally static and provides for only simple point-to-point transport. Efficiently managing the growing number of wavelengths can only be achieved through a new breed of networking element. Photonic switching systems (PSS) can efficiently execute these functions because they are bit rate, wavelength, and protocol transparent. With their all-optical switch cores and interfaces, PSS can switch optical signals at various levels of granularity wavelength, sub band, and composite DWDM fiber levels. Though cross-connect systems with electrical switch cores are available, they perform these functions at very high capital costs and operational inefficiencies. This paper examines enabling technologies for deployment of intelligent optical transport networks (OTN), and takes a practical perspective on survivability architecture migration and implementation issues.

Autonomous Optimization of Targeted Stimulation of Neuronal Networks

PubMed Central

Kumar, Sreedhar S.; Wülfing, Jan; Okujeni, Samora; Boedecker, Joschka; Riedmiller, Martin

2016-01-01

Driven by clinical needs and progress in neurotechnology, targeted interaction with neuronal networks is of increasing importance. Yet, the dynamics of interaction between intrinsic ongoing activity in neuronal networks and their response to stimulation is unknown. Nonetheless, electrical stimulation of the brain is increasingly explored as a therapeutic strategy and as a means to artificially inject information into neural circuits. Strategies using regular or event-triggered fixed stimuli discount the influence of ongoing neuronal activity on the stimulation outcome and are therefore not optimal to induce specific responses reliably. Yet, without suitable mechanistic models, it is hardly possible to optimize such interactions, in particular when desired response features are network-dependent and are initially unknown. In this proof-of-principle study, we present an experimental paradigm using reinforcement-learning (RL) to optimize stimulus settings autonomously and evaluate the learned control strategy using phenomenological models. We asked how to (1) capture the interaction of ongoing network activity, electrical stimulation and evoked responses in a quantifiable ‘state’ to formulate a well-posed control problem, (2) find the optimal state for stimulation, and (3) evaluate the quality of the solution found. Electrical stimulation of generic neuronal networks grown from rat cortical tissue in vitro evoked bursts of action potentials (responses). We show that the dynamic interplay of their magnitudes and the probability to be intercepted by spontaneous events defines a trade-off scenario with a network-specific unique optimal latency maximizing stimulus efficacy. An RL controller was set to find this optimum autonomously. Across networks, stimulation efficacy increased in 90% of the sessions after learning and learned latencies strongly agreed with those predicted from open-loop experiments. Our results show that autonomous techniques can exploit quantitative relationships underlying activity-response interaction in biological neuronal networks to choose optimal actions. Simple phenomenological models can be useful to validate the quality of the resulting controllers. PMID:27509295

Autonomous Optimization of Targeted Stimulation of Neuronal Networks.

PubMed

Kumar, Sreedhar S; Wülfing, Jan; Okujeni, Samora; Boedecker, Joschka; Riedmiller, Martin; Egert, Ulrich

2016-08-01

Driven by clinical needs and progress in neurotechnology, targeted interaction with neuronal networks is of increasing importance. Yet, the dynamics of interaction between intrinsic ongoing activity in neuronal networks and their response to stimulation is unknown. Nonetheless, electrical stimulation of the brain is increasingly explored as a therapeutic strategy and as a means to artificially inject information into neural circuits. Strategies using regular or event-triggered fixed stimuli discount the influence of ongoing neuronal activity on the stimulation outcome and are therefore not optimal to induce specific responses reliably. Yet, without suitable mechanistic models, it is hardly possible to optimize such interactions, in particular when desired response features are network-dependent and are initially unknown. In this proof-of-principle study, we present an experimental paradigm using reinforcement-learning (RL) to optimize stimulus settings autonomously and evaluate the learned control strategy using phenomenological models. We asked how to (1) capture the interaction of ongoing network activity, electrical stimulation and evoked responses in a quantifiable 'state' to formulate a well-posed control problem, (2) find the optimal state for stimulation, and (3) evaluate the quality of the solution found. Electrical stimulation of generic neuronal networks grown from rat cortical tissue in vitro evoked bursts of action potentials (responses). We show that the dynamic interplay of their magnitudes and the probability to be intercepted by spontaneous events defines a trade-off scenario with a network-specific unique optimal latency maximizing stimulus efficacy. An RL controller was set to find this optimum autonomously. Across networks, stimulation efficacy increased in 90% of the sessions after learning and learned latencies strongly agreed with those predicted from open-loop experiments. Our results show that autonomous techniques can exploit quantitative relationships underlying activity-response interaction in biological neuronal networks to choose optimal actions. Simple phenomenological models can be useful to validate the quality of the resulting controllers.

Local network assessment

NASA Astrophysics Data System (ADS)

Glen, D. V.

1985-04-01

Local networks, related standards activities of the Institute of Electrical and Electronics Engineers the American National Standards Institute and other elements are presented. These elements include: (1) technology choices such as topology, transmission media, and access protocols; (2) descriptions of standards for the 802 local area networks (LAN's); high speed local networks (HSLN's) and military specification local networks; and (3) intra- and internetworking using bridges and gateways with protocols Interconnection (OSI) reference model. The convergence of LAN/PBX technology is also described.

Electricity generation and transmission planning in deregulated power markets

NASA Astrophysics Data System (ADS)

He, Yang

This dissertation addresses the long-term planning of power generation and transmission facilities in a deregulated power market. Three models with increasing complexities are developed, primarily for investment decisions in generation and transmission capacity. The models are presented in a two-stage decision context where generation and transmission capacity expansion decisions are made in the first stage, while power generation and transmission service fees are decided in the second stage. Uncertainties that exist in the second stage affect the capacity expansion decisions in the first stage. The first model assumes that the electric power market is not constrained by transmission capacity limit. The second model, which includes transmission constraints, considers the interactions between generation firms and the transmission network operator. The third model assumes that the generation and transmission sectors make capacity investment decisions separately. These models result in Nash-Cournot equilibrium among the unregulated generation firms, while the regulated transmission network operator supports the competition among generation firms. Several issues in the deregulated electric power market can be studied with these models such as market powers of generation firms and transmission network operator, uncertainties of the future market, and interactions between the generation and transmission sectors. Results deduced from the developed models include (a) regulated transmission network operator will not reserve transmission capacity to gain extra profits; instead, it will make capacity expansion decisions to support the competition in the generation sector; (b) generation firms will provide more power supplies when there is more demand; (c) in the presence of future uncertainties, the generation firms will add more generation capacity if the demand in the future power market is expected to be higher; and (d) the transmission capacity invested by the transmission network operator depends on the characteristic of the power market and the topology of the transmission network. Also, the second model, which considers interactions between generation and transmission sectors, yields higher social welfare in the electric power market, than the third model where generation firms and transmission network operator make investment decisions separately.

Efficient Probabilistic Diagnostics for Electrical Power Systems

NASA Technical Reports Server (NTRS)

Mengshoel, Ole J.; Chavira, Mark; Cascio, Keith; Poll, Scott; Darwiche, Adnan; Uckun, Serdar

2008-01-01

We consider in this work the probabilistic approach to model-based diagnosis when applied to electrical power systems (EPSs). Our probabilistic approach is formally well-founded, as it based on Bayesian networks and arithmetic circuits. We investigate the diagnostic task known as fault isolation, and pay special attention to meeting two of the main challenges . model development and real-time reasoning . often associated with real-world application of model-based diagnosis technologies. To address the challenge of model development, we develop a systematic approach to representing electrical power systems as Bayesian networks, supported by an easy-to-use speci.cation language. To address the real-time reasoning challenge, we compile Bayesian networks into arithmetic circuits. Arithmetic circuit evaluation supports real-time diagnosis by being predictable and fast. In essence, we introduce a high-level EPS speci.cation language from which Bayesian networks that can diagnose multiple simultaneous failures are auto-generated, and we illustrate the feasibility of using arithmetic circuits, compiled from Bayesian networks, for real-time diagnosis on real-world EPSs of interest to NASA. The experimental system is a real-world EPS, namely the Advanced Diagnostic and Prognostic Testbed (ADAPT) located at the NASA Ames Research Center. In experiments with the ADAPT Bayesian network, which currently contains 503 discrete nodes and 579 edges, we .nd high diagnostic accuracy in scenarios where one to three faults, both in components and sensors, were inserted. The time taken to compute the most probable explanation using arithmetic circuits has a small mean of 0.2625 milliseconds and standard deviation of 0.2028 milliseconds. In experiments with data from ADAPT we also show that arithmetic circuit evaluation substantially outperforms joint tree propagation and variable elimination, two alternative algorithms for diagnosis using Bayesian network inference.

Electrical Conductivity in Transparent Silver Nanowire Networks: Simulations and Experiments

NASA Astrophysics Data System (ADS)

Sherrott, Michelle; Mutiso, Rose; Rathmell, Aaron; Wiley, Benjamin; Winey, Karen

2012-02-01

We model and experimentally measure the electrical conductivity of two-dimensional networks containing finite, conductive cylinders with aspect ratio ranging from 33 to 333. We have previously used our simulations to explore the effects of cylinder orientation and aspect ratio in three-dimensional composites, and now extend the simulation to consider two-dimensional silver nanowire networks. Preliminary results suggest that increasing the aspect ratio and area fraction of these rods significantly decreases the sheet resistance of the film. For all simulated aspect ratios, this sheet resistance approaches a constant value for high area fractions of rods. This implies that regardless of aspect ratio, there is a limiting minimum sheet resistance that is characteristic of the properties of the nanowires. Experimental data from silver nanowire networks will be incorporated into the simulations to define the contact resistance and corroborate experimentally measured sheet resistances of transparent thin films.

Computerized power supply analysis: State equation generation and terminal models

NASA Technical Reports Server (NTRS)

Garrett, S. J.

1978-01-01

To aid engineers that design power supply systems two analysis tools that can be used with the state equation analysis package were developed. These tools include integration routines that start with the description of a power supply in state equation form and yield analytical results. The first tool uses a computer program that works with the SUPER SCEPTRE circuit analysis program and prints the state equation for an electrical network. The state equations developed automatically by the computer program are used to develop an algorithm for reducing the number of state variables required to describe an electrical network. In this way a second tool is obtained in which the order of the network is reduced and a simpler terminal model is obtained.

Intelligent vehicle electrical power supply system with central coordinated protection

NASA Astrophysics Data System (ADS)

Yang, Diange; Kong, Weiwei; Li, Bing; Lian, Xiaomin

2016-07-01

The current research of vehicle electrical power supply system mainly focuses on electric vehicles (EV) and hybrid electric vehicles (HEV). The vehicle electrical power supply system used in traditional fuel vehicles is rather simple and imperfect; electrical/electronic devices (EEDs) applied in vehicles are usually directly connected with the vehicle's battery. With increasing numbers of EEDs being applied in traditional fuel vehicles, vehicle electrical power supply systems should be optimized and improved so that they can work more safely and more effectively. In this paper, a new vehicle electrical power supply system for traditional fuel vehicles, which accounts for all electrical/electronic devices and complex work conditions, is proposed based on a smart electrical/electronic device (SEED) system. Working as an independent intelligent electrical power supply network, the proposed system is isolated from the electrical control module and communication network, and access to the vehicle system is made through a bus interface. This results in a clean controller power supply with no electromagnetic interference. A new practical battery state of charge (SoC) estimation method is also proposed to achieve more accurate SoC estimation for lead-acid batteries in traditional fuel vehicles so that the intelligent power system can monitor the status of the battery for an over-current state in each power channel. Optimized protection methods are also used to ensure power supply safety. Experiments and tests on a traditional fuel vehicle are performed, and the results reveal that the battery SoC is calculated quickly and sufficiently accurately for battery over-discharge protection. Over-current protection is achieved, and the entire vehicle's power utilization is optimized. For traditional fuel vehicles, the proposed vehicle electrical power supply system is comprehensive and has a unified system architecture, enhancing system reliability and security.

Space Station laboratory module power loading analysis

NASA Astrophysics Data System (ADS)

Fu, S. J.

1994-07-01

The electrical power system of Space Station Freedom is an isolated electrical power generation and distribution network designed to meet the demands of a large number of electrical loads. An algorithm is developed to determine the power bus loading status under normal operating conditions to ensure the supply meets demand. The probabilities of power availability for payload operations (experiments) are also derived.

Simulation of demand management and grid balancing with electric vehicles

NASA Astrophysics Data System (ADS)

Druitt, James; Früh, Wolf-Gerrit

2012-10-01

This study investigates the potential role of electric vehicles in an electricity network with a high contribution from variable generation such as wind power. Electric vehicles are modelled to provide demand management through flexible charging requirements and energy balancing for the network. Balancing applications include both demand balancing and vehicle-to-grid discharging. This study is configured to represent the UK grid with balancing requirements derived from wind generation calculated from weather station wind speeds on the supply side and National Grid data from on the demand side. The simulation models 1000 individual vehicle entities to represent the behaviour of larger numbers of vehicles. A stochastic trip generation profile is used to generate realistic journey characteristics, whilst a market pricing model allows charging and balancing decisions to be based on realistic market price conditions. The simulation has been tested with wind generation capacities representing up to 30% of UK consumption. Results show significant improvements to load following conditions with the introduction of electric vehicles, suggesting that they could substantially facilitate the uptake of intermittent renewable generation. Electric vehicle owners would benefit from flexible charging and selling tariffs, with the majority of revenue derived from vehicle-to-grid participation in balancing markets.

Adaptive Energy Forecasting and Information Diffusion for Smart Power Grids

DOE Office of Scientific and Technical Information (OSTI.GOV)

Simmhan, Yogesh; Agarwal, Vaibhav; Aman, Saim

2012-05-16

Smart Power Grids exemplify an emerging class of Cyber Physical Applications that exhibit dynamic, distributed and data intensive (D3) characteristics along with an always-on paradigm to support operational needs. Smart Grids are an outcome of instrumentation, such as Phasor Measurement Units and Smart Power Meters, that is being deployed across the transmission and distribution network of electric grids. These sensors provide utilities with improved situation awareness on near-realtime electricity usage by individual consumers, and the power quality and stability of the transmission network.

The Evaluation of Rekeying Protocols Within the Hubenko Architecture as Applied to Wireless Sensor Networks

DTIC Science & Technology

2009-03-01

SENSOR NETWORKS THESIS Presented to the Faculty Department of Electrical and Computer Engineering Graduate School of Engineering and...hierarchical, and Secure Lock within a wireless sensor network (WSN) under the Hubenko architecture. Using a Matlab computer simulation, the impact of the...rekeying protocol should be applied given particular network parameters, such as WSN size. 10 1.3 Experimental Approach A computer simulation in

Comparison of GEOS-5 AGCM planetary boundary layer depths computed with various definitions

NASA Astrophysics Data System (ADS)

McGrath-Spangler, E. L.; Molod, A.

2014-07-01

Accurate models of planetary boundary layer (PBL) processes are important for forecasting weather and climate. The present study compares seven methods of calculating PBL depth in the GEOS-5 atmospheric general circulation model (AGCM) over land. These methods depend on the eddy diffusion coefficients, bulk and local Richardson numbers, and the turbulent kinetic energy. The computed PBL depths are aggregated to the Köppen-Geiger climate classes, and some limited comparisons are made using radiosonde profiles. Most methods produce similar midday PBL depths, although in the warm, moist climate classes the bulk Richardson number method gives midday results that are lower than those given by the eddy diffusion coefficient methods. Additional analysis revealed that methods sensitive to turbulence driven by radiative cooling produce greater PBL depths, this effect being most significant during the evening transition. Nocturnal PBLs based on Richardson number methods are generally shallower than eddy diffusion coefficient based estimates. The bulk Richardson number estimate is recommended as the PBL height to inform the choice of the turbulent length scale, based on the similarity to other methods during the day, and the improved nighttime behavior.

Designing domestic rainwater harvesting systems under different climatic regimes in Italy.

PubMed

Campisano, A; Gnecco, I; Modica, C; Palla, A

2013-01-01

Nowadays domestic rainwater harvesting practices are recognized as effective tools to improve the sustainability of drainage systems within the urban environment, by contributing to limiting the demand for potable water and, at the same time, by mitigating the generation of storm water runoff at the source. The final objective of this paper is to define regression curves to size domestic rainwater harvesting (DRWH) systems in the main Italian climatic regions. For this purpose, the Köppen-Geiger climatic classification is used and, furthermore, suitable precipitation sites are selected for each climatic region. A behavioural model is implemented to assess inflow, outflow and change in storage volume of a rainwater harvesting system according to daily mass balance simulations based on historical rainfall observations. The performance of the DRWH system under various climate and operational conditions is examined as a function of two non-dimensional parameters, namely the demand fraction (d) and the modified storage fraction (sm). This last parameter allowed the evaluation of the effects of the rainfall intra-annual variability on the system performance.

Comparison of GEOS-5 AGCM planetary boundary layer depths computed with various definitions

NASA Astrophysics Data System (ADS)

McGrath-Spangler, E. L.; Molod, A.

2014-03-01

Accurate models of planetary boundary layer (PBL) processes are important for forecasting weather and climate. The present study compares seven methods of calculating PBL depth in the GEOS-5 atmospheric general circulation model (AGCM) over land. These methods depend on the eddy diffusion coefficients, bulk and local Richardson numbers, and the turbulent kinetic energy. The computed PBL depths are aggregated to the Köppen climate classes, and some limited comparisons are made using radiosonde profiles. Most methods produce similar midday PBL depths, although in the warm, moist climate classes, the bulk Richardson number method gives midday results that are lower than those given by the eddy diffusion coefficient methods. Additional analysis revealed that methods sensitive to turbulence driven by radiative cooling produce greater PBL depths, this effect being most significant during the evening transition. Nocturnal PBLs based on Richardson number are generally shallower than eddy diffusion coefficient based estimates. The bulk Richardson number estimate is recommended as the PBL height to inform the choice of the turbulent length scale, based on the similarity to other methods during the day, and the improved nighttime behavior.

Historical perspective

NASA Astrophysics Data System (ADS)

Landsberg, H. E.

It was a pleasure to learn, from a recent (May 4) issue of Eos, of the formation of a permanent Committee on History of Geophysics. There is a dire need for reference material, books, and articles on geophysical history.Let me recommend to them that they take a good look at the Dictionary of the History of Science (W.F. Bynum, E.J. Browne, Roy Porter (Eds.), Princeton University Press, 494 pp., 1981). What follows is not a book review, although it may appear so. It is meant to be a challenge to place geophysics on the map in historical context. In this book, hydrology is dealt with in one sentence under the heading ‘cycle,’ geomagnetism under ‘declination and dip,’ and its history ends with Edward Sabine. Seismology appears under earthquakes. No important seismologist is mentioned. In the biographical index, Wiechert is included only for a contribution to physics. Where are Sir Harold Jeffreys, Galitzin, Gutenberg, Mohorovičić, Lehman, and many others? Meteorology ends with V. Bjerknes and Solberg; Köppen, Richardson, Rossby, and other notables [of] the last century do not seem to exist.

Seasonal variation of fecal contamination in drinking water sources in developing countries: a systematic review.

PubMed

Kostyla, Caroline; Bain, Rob; Cronk, Ryan; Bartram, Jamie

2015-05-01

Accounting for fecal contamination of drinking water sources is an important step in improving monitoring of global access to safe drinking water. Fecal contamination varies with time while its monitoring is often infrequent. We sought to understand seasonal trends in fecal contamination to guide best practices to capture seasonal variation and ascertain the extent to which the results of a single sample may overestimate compliance with health guidelines. The findings from 22 studies from developing countries written in English and identified through a systematic review were analyzed. Fecal contamination in improved drinking water sources was shown to follow a statistically significant seasonal trend of greater contamination during the wet season (p<0.001). This trend was consistent across fecal indicator bacteria, five source types, twelve Köppen-Geiger climate zones, and across both rural and urban areas. Guidance on seasonally representative water quality monitoring by the World Health Organization and national water quality agencies could lead to improved assessments of access to safe drinking water. Copyright © 2015 Elsevier B.V. All rights reserved.

Electrical transmission between mammalian neurons is supported by a small fraction of gap junction channels.

PubMed

Curti, Sebastian; Hoge, Gregory; Nagy, James I; Pereda, Alberto E

2012-06-01

Electrical synapses formed by gap junctions between neurons create networks of electrically coupled neurons in the mammalian brain, where these networks have been found to play important functional roles. In most cases, interneuronal gap junctions occur at remote dendro-dendritic contacts, making difficult accurate characterization of their physiological properties and correlation of these properties with their anatomical and morphological features of the gap junctions. In the mesencephalic trigeminal (MesV) nucleus where neurons are readily accessible for paired electrophysiological recordings in brain stem slices, our recent data indicate that electrical transmission between MesV neurons is mediated by connexin36 (Cx36)-containing gap junctions located at somato-somatic contacts. We here review evidence indicating that electrical transmission between these neurons is supported by a very small fraction of the gap junction channels present at cell-cell contacts. Acquisition of this evidence was enabled by the unprecedented experimental access of electrical synapses between MesV neurons, which allowed estimation of the average number of open channels mediating electrical coupling in relation to the average number of gap junction channels present at these contacts. Our results indicate that only a small proportion of channels (~0.1 %) appear to be conductive. On the basis of similarities with other preparations, we postulate that this phenomenon might constitute a general property of vertebrate electrical synapses, reflecting essential aspects of gap junction function and maintenance.

Simplified Calculation of the Electrical Conductivity of Composites with Carbon Nanotubes

NASA Astrophysics Data System (ADS)

Ivanov, S. G.; Aniskevich, A.; Kulakov, V.

2018-03-01

The electrical conductivity of two groups of polymer nanocomposites filled with the same NC7000 carbon nanotubes (CNTs) beyond the percolation threshold is described with the help of simple formulas. Different manufacturing process of the nanocomposites led to different CNT network structures, and, as a consequence, their electrical conductivity, at the same CNT volume, differed by two orders of magnitude. The relation between the electrical conductivity and the volume content of CNTs of the first group of composites (with a higher electrical conductivity) is described assuming that the CNT network structure is close to a statistically homogeneous one. The formula for this case, derived on the basis of a self-consistent model, includes only two parameters: the effective longitudinal electrical conductivity of CNT and the percolation threshold (the critical value of CNT volume content). These parameters were determined from two experimental points of electrical conductivity as a function of the volume fraction of CNTs. The second group of nanocomposites had a pronounced agglomerative structure, which was confirmed by microscopy data. To describe the low electrical conductivity of this group of nanocomposites, a formula based on known models of micromechanics is proposed. Two parameters of this formula were determined from experimental data of the first group, but the other two — of the second group of nanocomposites. A comparison of calculation and experimental relations confirmed the practical expediency of using the approach described.

Architecture and Methods for Substation SCADA Cybersecurity: Best Practices

DOE Office of Scientific and Technical Information (OSTI.GOV)

Albunashee, Hamdi; Al Sarray, Muthanna; McCann, Roy

There are over 3000 electricity providers in the United States, encompassing investor and publicly owned utilities as well as electric cooperatives. There has been ongoing trends to increasingly automate and provide remote control and monitoring of electric energy delivery systems. The deployment of computer network technologies has increased the efficiency and reliability of electric power infrastructure. However, the increased use of digital communications has also increased the vulnerability to malicious cyber attacks [1]. In 2004 the National Research Councils (National Academies) formed a committee of specialists to address these vulnerabilities and propose possible solutions with an objective to prioritize themore » R&D needs for developing countermeasures. The committee addressed many potential concerns in the electric power delivery system and classified them based upon different criteria and presented recommendations to minimize the gap between the academic research directions and the needs of the electric utility industry. The complexity and diversity of the electric power delivery system in the U.S. has opened many ports for attackers and intruders [1]. This complexity and diversity is attributed to the fact that power delivery system is a network of substations, transmission and distribution lines, sub-networks of controlling, sensing and monitoring units, and human operator involvement for running the system [1]. Accordingly, any incident such as the occurrence of a fault or disturbance in this complex network cannot be deferred and should be resolved within an order of milliseconds, otherwise there is risk of large-scale outages similar to the occurrences in India and the U.S. in 2003 [2]. There are three main vulnerabilities in supervisory control and data acquisition (SCADA) systems commonly identified—physical vulnerability, cyber vulnerability and personal vulnerability [1]. In terms of cyber threats, SCADA systems are the most critical elements in the electric power grid in the U.S. Unauthorized access to a SCADA system could enable/disable unexpected equipment (such as disable the protection system or a circuit breaker) which could cause large scale disruptions of electric power delivery. This paper provides an overview of power system SCADA technologies in transmission substations (Section 2) and summarizes the best practices for implementing a cyber security program. After introducing SCADA system operations in Section 2, a description of the security challenges for SCADA systems is presented in Section 3. In Section 4, NECRC Critical Infrastructure Protection standards CIP-002 through CIP-009 are summarized. An overview of industry best practices is presented in Section 5.« less

Developing a Mixed Neural Network Approach to Forecast the Residential Electricity Consumption Based on Sensor Recorded Data

PubMed Central

Bâra, Adela; Stănică, Justina-Lavinia; Coculescu, Cristina

2018-01-01

In this paper, we report a study having as a main goal the obtaining of a method that can provide an accurate forecast of the residential electricity consumption, refining it up to the appliance level, using sensor recorded data, for residential smart homes complexes that use renewable energy sources as a part of their consumed electricity, overcoming the limitations of not having available historical meteorological data and the unwillingness of the contractor to acquire such data periodically in the future accurate short-term forecasts from a specialized institute due to the implied costs. In this purpose, we have developed a mixed artificial neural network (ANN) approach using both non-linear autoregressive with exogenous input (NARX) ANNs and function fitting neural networks (FITNETs). We have used a large dataset containing detailed electricity consumption data recorded by sensors, monitoring a series of individual appliances, while in the NARX case we have also used timestamps datasets as exogenous variables. After having developed and validated the forecasting method, we have compiled it in view of incorporating it into a cloud solution, being delivered to the contractor that can provide it as a service for a monthly fee to both the operators and residential consumers. PMID:29734761

Developing a Mixed Neural Network Approach to Forecast the Residential Electricity Consumption Based on Sensor Recorded Data.

PubMed

Oprea, Simona-Vasilica; Pîrjan, Alexandru; Căruțașu, George; Petroșanu, Dana-Mihaela; Bâra, Adela; Stănică, Justina-Lavinia; Coculescu, Cristina

2018-05-05

In this paper, we report a study having as a main goal the obtaining of a method that can provide an accurate forecast of the residential electricity consumption, refining it up to the appliance level, using sensor recorded data, for residential smart homes complexes that use renewable energy sources as a part of their consumed electricity, overcoming the limitations of not having available historical meteorological data and the unwillingness of the contractor to acquire such data periodically in the future accurate short-term forecasts from a specialized institute due to the implied costs. In this purpose, we have developed a mixed artificial neural network (ANN) approach using both non-linear autoregressive with exogenous input (NARX) ANNs and function fitting neural networks (FITNETs). We have used a large dataset containing detailed electricity consumption data recorded by sensors, monitoring a series of individual appliances, while in the NARX case we have also used timestamps datasets as exogenous variables. After having developed and validated the forecasting method, we have compiled it in view of incorporating it into a cloud solution, being delivered to the contractor that can provide it as a service for a monthly fee to both the operators and residential consumers.

Emergence of Critical Behavior in β-Cell Network

NASA Astrophysics Data System (ADS)

Westacott, Matthew; Hraha, Thomas; McClatchey, Mason; Pozzoli, Marina; Benninger, Richard

2014-03-01

The β-cell is a cell type located in the Islet of Langerhans, a micro-organ of the pancreas which maintains glucose homeostasis through secretion of insulin. An electrophysiological process governing insulin release occurs through initial uptake of blood glucose and generation of ATP which inhibits the ATP sensitive potassium channel (K-ATP) causing membrane depolarization (activation). Neighboring β-cells are electrically coupled through gap junctions which allow passage of cationic molecules, creating a network of coupled electrical oscillators. Cells exhibiting hyperpolzarized (inactive) membrane potential affect behavior of neighboring cells by electrically suppressing their depolarization. Here we observe critical behavior between global active-inactive states by increasing the number of inactive elements with the K-ATP inhibitor Diazoxide and a tunable ATP insensitive transgenic mouse model. We show this behavior occurs due to from cell-cell coupling as mice lacking β-cell gap junctions show no critical behavior. Also, a computational β-cell model was expanded to construct a coupled β-cell network and we show this model replicates the critical behavior seen in-vitro.While electrical activity of single β-cells is well studied these data highlight a newly defined characteristic of their emergent multicellular behavior within the Islet of Langerhans and may elucidate pathophysiology of Diabetes due to mutations in the K-ATP channel.

On-track testing of a power harvesting device for railroad track health monitoring

NASA Astrophysics Data System (ADS)

Hansen, Sean E.; Pourghodrat, Abolfazl; Nelson, Carl A.; Fateh, Mahmood

2010-03-01

A considerable proportion of railroad infrastructure exists in regions which are comparatively remote. With regard to the cost of extending electrical infrastructure into these areas, road crossings in these areas do not have warning light systems or crossing gates and are commonly marked with reflective signage. For railroad track health monitoring purposes, distributed sensor networks can be applicable in remote areas, but the same limitation regarding electrical infrastructure is the hindrance. This motivated the development of an energy harvesting solution for remote railroad deployment. This paper describes on-track experimental testing of a mechanical device for harvesting mechanical power from passing railcar traffic, in view of supplying electrical power to warning light systems at crossings and to remote networks of sensors. The device is mounted to and spans two rail ties and transforms the vertical rail displacement into electrical energy through mechanical amplification and rectification into a PMDC generator. A prototype was tested under loaded and unloaded railcar traffic at low speeds. Stress analysis and speed scaling analysis are presented, results of the on-track tests are compared and contrasted to previous laboratory testing, discrepancies between the two are explained, and conclusions are drawn regarding suitability of the device for illuminating high-efficiency LED lights at railroad crossings and powering track-health sensor networks.

Constraints on the Geophysical Detection of Brine within the Europa Ice Shell From a Synthesis of Dielectric Spectroscopy Measurements

NASA Astrophysics Data System (ADS)

Stillman, D. E.; Grimm, R. E.; MacGregor, J. A.; Sander-Olhoeft, M.; Brown, J.

2016-12-01

The numerous chaos regions, lenticulae and double layer ridges on Europa's surface suggest that pockets of liquid currently exist or did exist. Here we investigate the sensitivity of ice-penetrating radar (IPR) and magnetotelluric (MT) methods to the putative electrical properties of Europa's ice shell, based on a set of plausible ice-shell scenarios and a synthesis of laboratory dielectric spectroscopy measurements of hundreds of ice samples. We evaluate models of the electrical conductivity of the ice shell as a function of impurity content, temperature and liquid vein network tortuosity. Europa's ice shell is estimated to be 5-30 km thick. If its thickness exceeds 10 km, the shell likely convects within its bottom 70%, while the upper part is thermally conductive. These convective downwellings and upwellings are estimated to have core temperatures of 235 K and 253 K, respectively. Downwellings are so cold that they are below of eutectic temperature of most Europa-relevant salts, but not below that of Europa-relevant acids. Given the low temperature of downwelling ice, IPR is expected to penetrate through it. Warmer upwellings may possess significant amounts of unfrozen water if the shell is acid- or salt-rich. The injection of liquid or the melting of acid- or salt-rich ice will eventually lead to refreezing, as the shell conducts away this excess heat. As liquid freezes, impurities are rejected and concentrated in a liquid vein network surrounding relatively pure ice crystals. These vein networks remain liquid as long as the temperature is greater than that of the eutectic of the bulk impurities. Therefore, in upwellings, vein networks should be briny and hence more electrically conductive. The electrical conductivity of these vein networks depends on the initial impurity concentration of the liquid, impurity type, temperature and the tortuosity of any vein networks. The latter property decreases with increasing ice recrystallization. We conclude that IPR will likely be able to map the top of the unfrozen zone, assuming typical marine ice salt concentrations, but not penetrate through it. MT measurements could complement IPR effectively, because they could measure a conductivity depth profile within the unfrozen part of the ice shell, where the electrical conductivity exceeds 0.1 mS/m.

Network model and short circuit program for the Kennedy Space Center electric power distribution system

NASA Technical Reports Server (NTRS)

1976-01-01

Assumptions made and techniques used in modeling the power network to the 480 volt level are discussed. Basic computational techniques used in the short circuit program are described along with a flow diagram of the program and operational procedures. Procedures for incorporating network changes are included in this user's manual.

Modulation of molecular hybridization and charge screening in a carbon nanotube network channel using the electrical pulse method.

PubMed

Woo, Jun-Myung; Kim, Seok Hyang; Chun, Honnggu; Kim, Sung Jae; Ahn, Jinhong; Park, Young June

2013-09-21

In this paper, we investigate the effect of electrical pulse bias on DNA hybridization events in a biosensor platform, using a Carbon Nanotube Network (CNN) and Gold Nano Particles (GNP) as an electrical channel. The scheme provides both hybridization rate enhancement of bio molecules, and electrical measurement in a transient state to avoid the charge screening effect, thereby significantly improving the sensitivity. As an example, the probe DNA molecules oscillate with pulse trains, resulting in the enhancement of DNA hybridization efficiency, and accordingly of the sensor performances in Tris-EDTA (TE) buffer solution, by as much as over three times, compared to the non-biasing conditions. More importantly, a wide dynamic range of 10(6) (target-DNA concentration from 5 pM to 5 μM) is achieved in human serum. In addition, the pulse biasing method enables one to obtain the conductance change, before the ions within the Electrical Double Layer (EDL) are redistributed, to avoid the charge screening effect, leading to an additional sensitivity enhancement.

Improved Electrical Contact For Dowhhole Drilling Networks

DOEpatents

Hall, David R.; Hall, Jr., H. Tracy; Pixton, David S.; Dahlgren, Scott; Fox, Joe; Sneddon, Cameron

2005-08-16

An electrical contact system for transmitting information across tool joints while minimizing signal reflections that occur at the tool joints includes a first electrical contact comprising an annular resilient material. An annular conductor is embedded within the annular resilient material and has a surface exposed from the annular resilient material. A second electrical contact is provided that is substantially equal to the first electrical contact. Likewise, the second electrical contact has an annular resilient material and an annular conductor. The two electrical contacts configured to contact one another such that the annular conductors of each come into physical contact. The annular resilient materials of each electrical contact each have dielectric characteristics and dimensions that are adjusted to provide desired impedance to the electrical contacts.

Electrical localization of weakly electric fish using neural networks

NASA Astrophysics Data System (ADS)

Kiar, Greg; Mamatjan, Yasin; Jun, James; Maler, Len; Adler, Andy

2013-04-01

Weakly Electric Fish (WEF) emit an Electric Organ Discharge (EOD), which travels through the surrounding water and enables WEF to locate nearby objects or to communicate between individuals. Previous tracking of WEF has been conducted using infrared (IR) cameras and subsequent image processing. The limitation of visual tracking is its relatively low frame-rate and lack of reliability when visually obstructed. Thus, there is a need for reliable monitoring of WEF location and behaviour. The objective of this study is to provide an alternative and non-invasive means of tracking WEF in real-time using neural networks (NN). This study was carried out in three stages. First stage was to recreate voltage distributions by simulating the WEF using EIDORS and finite element method (FEM) modelling. Second stage was to validate the model using phantom data acquired from an Electrical Impedance Tomography (EIT) based system, including a phantom fish and tank. In the third stage, the measurement data was acquired using a restrained WEF within a tank. We trained the NN based on the voltage distributions for different locations of the WEF. With networks trained on the acquired data, we tracked new locations of the WEF and observed the movement patterns. The results showed a strong correlation between expected and calculated values of WEF position in one dimension, yielding a high spatial resolution within 1 cm and 10 times higher temporal resolution than IR cameras. Thus, the developed approach could be used as a practical method to non-invasively monitor the WEF in real-time.

Complex Dynamical Networks Constructed with Fully Controllable Nonlinear Nanomechanical Oscillators.

PubMed

Fon, Warren; Matheny, Matthew H; Li, Jarvis; Krayzman, Lev; Cross, Michael C; D'Souza, Raissa M; Crutchfield, James P; Roukes, Michael L

2017-10-11

Control of the global parameters of complex networks has been explored experimentally in a variety of contexts. Yet, the more difficult prospect of realizing arbitrary network architectures, especially analog physical networks that provide dynamical control of individual nodes and edges, has remained elusive. Given the vast hierarchy of time scales involved, it also proves challenging to measure a complex network's full internal dynamics. These span from the fastest nodal dynamics to very slow epochs over which emergent global phenomena, including network synchronization and the manifestation of exotic steady states, eventually emerge. Here, we demonstrate an experimental system that satisfies these requirements. It is based upon modular, fully controllable, nonlinear radio frequency nanomechanical oscillators, designed to form the nodes of complex dynamical networks with edges of arbitrary topology. The dynamics of these oscillators and their surrounding network are analog and continuous-valued and can be fully interrogated in real time. They comprise a piezoelectric nanomechanical membrane resonator, which serves as the frequency-determining element within an electrical feedback circuit. This embodiment permits network interconnections entirely within the electrical domain and provides unprecedented node and edge control over a vast region of parameter space. Continuous measurement of the instantaneous amplitudes and phases of every constituent oscillator node are enabled, yielding full and detailed network data without reliance upon statistical quantities. We demonstrate the operation of this platform through the real-time capture of the dynamics of a three-node ring network as it evolves from the uncoupled state to full synchronization.

Discrete Dual Porosity Modeling of Electrical Current Flow in Fractured Media

NASA Astrophysics Data System (ADS)

Roubinet, D.; Irving, J.

2013-12-01

The study of fractured rocks is highly important in a variety of research fields and applications such as hydrogeology, geothermal energy, hydrocarbon extraction, and the long-term storage of toxic waste. Fractured media are characterized by a large contrast in permeability between the fractures and the rock matrix. For hydrocarbon extraction, the presence of highly conductive fractures is an advantage as they allow for quick and easy access to the resource. For toxic waste storage, however, the fractures represent a significant drawback as there is an increased risk of leakage and migration of pollutants deep into the subsurface. In both cases, the identification of fracture network characteristics is a critical, challenging, and required step. A number of previous studies have indicated that the presence of fractures in geological materials can have a significant impact on geophysical electrical resistivity measurements. It thus appears that, in some cases, geoelectrical surveys might be used to obtain useful information regarding fracture network characteristics. However, existing geoelectrical modeling tools and inversion methods are not properly adapted to deal with the specific challenges of fractured media. This prevents us from fully exploring the potential of the method to characterize fracture network properties. We thus require, as a first step, the development of accurate and efficient numerical modeling tools specifically designed for fractured domains. Building on the discrete fracture network (DFN) approach that has been widely used for modeling groundwater flow in fractured rocks, we have developed a discrete dual-porosity model for electrical current flow in fractured media. Our novel approach combines an explicit representation of the fractures with fracture-matrix electrical flow exchange at the block-scale. Tests in two dimensions show the ability of our method to deal with highly heterogeneous fracture networks in a highly computationally efficient manner, which permits us to study the impact of fractures and their properties on the electrical response of the domain. With additional development, the method will be extended to three dimensions and used in the context of geoelectrical field investigations.

Photonic band gap materials: towards an all-optical transistor

NASA Astrophysics Data System (ADS)

Florescu, Marian

2002-05-01

The transmission of information as optical signals encoded on light waves traveling through optical fibers and optical networks is increasingly moving to shorter and shorter distance scales. In the near future, optical networking is poised to supersede conventional transmission over electric wires and electronic networks for computer-to-computer communications, chip-to-chip communications, and even on-chip communications. The ever-increasing demand for faster and more reliable devices to process the optical signals offers new opportunities in developing all-optical signal processing systems (systems in which one optical signal controls another, thereby adding "intelligence" to the optical networks). All-optical switches, two-state and many-state all-optical memories, all-optical limiters, all-optical discriminators and all-optical transistors are only a few of the many devices proposed during the last two decades. The "all-optical" label is commonly used to distinguish the devices that do not involve dissipative electronic transport and require essentially no electrical communication of information. The all-optical transistor action was first observed in the context of optical bistability [1] and consists in a strong differential gain regime, in which, for small variations in the input intensity, the output intensity has a very strong variation. This analog operation is for all-optical input what transistor action is for electrical inputs.

One-to-one neuron-electrode interfacing.

PubMed

Greenbaum, Alon; Anava, Sarit; Ayali, Amir; Shein, Mark; David-Pur, Moshe; Ben-Jacob, Eshel; Hanein, Yael

2009-09-15

The question of neuronal network development and organization is a principle one, which is closely related to aspects of neuronal and network form-function interactions. In-vitro two-dimensional neuronal cultures have proved to be an attractive and successful model for the study of these questions. Research is constraint however by the search for techniques aimed at culturing stable networks, whose electrical activity can be reliably and consistently monitored. A simple approach to form small interconnected neuronal circuits while achieving one-to-one neuron-electrode interfacing is presented. Locust neurons were cultured on a novel bio-chip consisting of carbon-nanotube multi-electrode-arrays. The cells self-organized to position themselves in close proximity to the bio-chip electrodes. The organization of the cells on the electrodes was analyzed using time lapse microscopy, fluorescence imaging and scanning electron microscopy. Electrical recordings from well identified cells is presented and discussed. The unique properties of the bio-chip and the specific neuron-nanotube interactions, together with the use of relatively large insect ganglion cells, allowed long-term stabilization (as long as 10 days) of predefined neural network topology as well as high fidelity electrical recording of individual neuron firing. This novel preparation opens ample opportunity for future investigation into key neurobiological questions and principles.

Energy Systems Integration: Demonstrating Distributed Resource Communications

DOE Office of Scientific and Technical Information (OSTI.GOV)

2017-01-01

Overview fact sheet about the Electric Power Research Institute (EPRI) and Schneider Electric Integrated Network Testbed for Energy Grid Research and Technology Experimentation (INTEGRATE) project at the Energy Systems Integration Facility. INTEGRATE is part of the U.S. Department of Energy's Grid Modernization Initiative.

Passively Damped Laminated Piezoelectric Shell Structures with Integrated Electric Networks

NASA Technical Reports Server (NTRS)

Saravanos, Dimitris A.

1999-01-01

Multi-field mechanics are presented for curvilinear piezoelectric laminates interfaced with distributed passive electric components. The equations of motion for laminated piezoelectric shell structures with embedded passive electric networks are directly formulated and solved using a finite element methodology. The modal damping and frequencies of the piezoelectric shell are calculated from the poles of the system. Experimental and numerical results are presented for the modal damping and frequency of composite beams with a resistively shunted piezoceramic patch. The modal damping and frequency of plates, cylindrical shells and cylindrical composite blades with piezoelectric-resistor layers are predicted. Both analytical and experimental studies illustrate a unique dependence of modal damping and frequencies on the shunting resistance and show the effect of structural shape and curvature on piezoelectric damping.

A compact model for electroosmotic flows in microfluidic devices

NASA Astrophysics Data System (ADS)

Qiao, R.; Aluru, N. R.

2002-09-01

A compact model to compute flow rate and pressure in microfluidic devices is presented. The microfluidic flow can be driven by either an applied electric field or a combined electric field and pressure gradient. A step change in the ζ-potential on a channel wall is treated by a pressure source in the compact model. The pressure source is obtained from the pressure Poisson equation and conservation of mass principle. In the proposed compact model, the complex fluidic network is simplified by an electrical circuit. The compact model can predict the flow rate, pressure distribution and other basic characteristics in microfluidic channels quickly with good accuracy when compared to detailed numerical simulation. Using the compact model, fluidic mixing and dispersion control are studied in a complex microfluidic network.

The prediction of the residual life of electromechanical equipment based on the artificial neural network

NASA Astrophysics Data System (ADS)

Zhukovskiy, Yu L.; Korolev, N. A.; Babanova, I. S.; Boikov, A. V.

2017-10-01

This article is devoted to the prediction of the residual life based on an estimate of the technical state of the induction motor. The proposed system allows to increase the accuracy and completeness of diagnostics by using an artificial neural network (ANN), and also identify and predict faulty states of an electrical equipment in dynamics. The results of the proposed system for estimation the technical condition are probability technical state diagrams and a quantitative evaluation of the residual life, taking into account electrical, vibrational, indirect parameters and detected defects. Based on the evaluation of the technical condition and the prediction of the residual life, a decision is made to change the control of the operating and maintenance modes of the electric motors.

Flywheel-Based Fast Charging Station - FFCS for Electric Vehicles and Public Transportation

NASA Astrophysics Data System (ADS)

Gabbar, Hossam A.; Othman, Ahmed M.

2017-08-01

This paper demonstrates novel Flywheel-based Fast Charging Station (FFCS) for high performance and profitable charging infrastructures for public electric buses. The design criteria will be provided for fast charging stations. The station would support the private and open charging framework. Flywheel Energy storage system is utilized to offer advanced energy storage for charging stations to achieve clean public transportation, including electric buses with reducing GHG, including CO2 emission reduction. The integrated modelling and management system in the station is performed by a decision-based control platform that coordinates the power streams between the quick chargers, the flywheel storage framework, photovoltaic cells and the network association. There is a tidy exchange up between the capacity rate of flywheel framework and the power rating of the network association.”

A Petri Net model for distributed energy system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Konopko, Joanna

2015-12-31

Electrical networks need to evolve to become more intelligent, more flexible and less costly. The smart grid is the next generation power energy, uses two-way flows of electricity and information to create a distributed automated energy delivery network. Building a comprehensive smart grid is a challenge for system protection, optimization and energy efficient. Proper modeling and analysis is needed to build an extensive distributed energy system and intelligent electricity infrastructure. In this paper, the whole model of smart grid have been proposed using Generalized Stochastic Petri Nets (GSPN). The simulation of created model is also explored. The simulation of themore » model has allowed the analysis of how close the behavior of the model is to the usage of the real smart grid.« less

Electric Field Sensor for Lightning Early Warning System

NASA Astrophysics Data System (ADS)

Premlet, B.; Mohammed, R.; Sabu, S.; Joby, N. E.

2017-12-01

Electric field mills are used popularly for atmospheric electric field measurements. Atmospheric Electric Field variation is the primary signature for Lightning Early Warning systems. There is a characteristic change in the atmospheric electric field before lightning during a thundercloud formation.A voltage controlled variable capacitance is being proposed as a method for non-contacting measurement of electric fields. A varactor based mini electric field measurement system is developed, to detect any change in the atmospheric electric field and to issue lightning early warning system. Since this is a low-cost device, this can be used for developing countries which are facing adversities. A network of these devices can help in forming a spatial map of electric field variations over a region, and this can be used for more improved atmospheric electricity studies in developing countries.

Power flow analysis and optimal locations of resistive type superconducting fault current limiters.

PubMed

Zhang, Xiuchang; Ruiz, Harold S; Geng, Jianzhao; Shen, Boyang; Fu, Lin; Zhang, Heng; Coombs, Tim A

2016-01-01

Based on conventional approaches for the integration of resistive-type superconducting fault current limiters (SFCLs) on electric distribution networks, SFCL models largely rely on the insertion of a step or exponential resistance that is determined by a predefined quenching time. In this paper, we expand the scope of the aforementioned models by considering the actual behaviour of an SFCL in terms of the temperature dynamic power-law dependence between the electrical field and the current density, characteristic of high temperature superconductors. Our results are compared to the step-resistance models for the sake of discussion and clarity of the conclusions. Both SFCL models were integrated into a power system model built based on the UK power standard, to study the impact of these protection strategies on the performance of the overall electricity network. As a representative renewable energy source, a 90 MVA wind farm was considered for the simulations. Three fault conditions were simulated, and the figures for the fault current reduction predicted by both fault current limiting models have been compared in terms of multiple current measuring points and allocation strategies. Consequently, we have shown that the incorporation of the E - J characteristics and thermal properties of the superconductor at the simulation level of electric power systems, is crucial for estimations of reliability and determining the optimal locations of resistive type SFCLs in distributed power networks. Our results may help decision making by distribution network operators regarding investment and promotion of SFCL technologies, as it is possible to determine the maximum number of SFCLs necessary to protect against different fault conditions at multiple locations.

7 CFR 1753.2 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-01-01

..., which has been approved by RUS, for improving the telecommunications network of those Telecommunications... plant—The facilities that conduct electrical or optical signals between the central office and the subscriber's network interface or between central offices. Performance bond—A surety bond on a form...

nordman

Science.gov Websites

, India, July 2015. "The Fit Grid"-Principles for a better electric future, submission for the . 2013 Report. Energy Reporting Framework and IETF Energy Management Working Group (concluded) Device networked buildings (February 12, 2008). Buildings as Networks: Danger, Opportunity, and Guiding Principles

Endogenous field feedback promotes the detectability for exogenous electric signal in the hybrid coupled population.

PubMed

Wei, Xile; Zhang, Danhong; Lu, Meili; Wang, Jiang; Yu, Haitao; Che, Yanqiu

2015-01-01

This paper presents the endogenous electric field in chemical or electrical synaptic coupled networks, aiming to study the role of endogenous field feedback in the signal propagation in neural systems. It shows that the feedback of endogenous fields to network activities can reduce the required energy of the noise and enhance the transmission of input signals in hybrid coupled populations. As a common and important nonsynaptic interactive method among neurons, particularly, the endogenous filed feedback can not only promote the detectability of exogenous weak signal in hybrid coupled neural population but also enhance the robustness of the detectability against noise. Furthermore, with the increasing of field coupling strengths, the endogenous field feedback is conductive to the stochastic resonance by facilitating the transition of cluster activities from the no spiking to spiking regions. Distinct from synaptic coupling, the endogenous field feedback can play a role as internal driving force to boost the population activities, which is similar to the noise. Thus, it can help to transmit exogenous weak signals within the network in the absence of noise drive via the stochastic-like resonance.

District heating and cooling systems for communities through power plant retrofit and distribution networks. Phase 1: identificaion and assessment. Final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1979-09-01

Appendix A, Utility Plant Characteristics, contains information describing the characteristics of seven utility plants that were considered during the final site selection process. The plants are: Valley Electric Generating Plant, downtown Milwaukee; Manitowoc Electric Generating Plant, downtown Manitowoc; Blount Street Electric Generating Plant, downtown Madison; Pulliam Electric Generating Plant, downtown Green Bay; Edgewater Electric Generating Plant, downtown Sheboygan; Rock River Electric Generating Plant, near Janesville and Beloit; and Black Hawk Electric Generating Plant, downtown Beloit. Additional appendices are: Future Loads; hvac Inventory; Load Calculations; Factors to Induce Potential Users; Turbine Retrofit/Distribution System Data; and Detailed Economic Analysis Results/Data.

75 FR 870 - Granting of Request for Early Termination of the Waiting Period Under the Premerger Notification...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-01-06

... Brokers Network, LLC. G FNI International, Inc. 03-DEC-09 20100178 G Windstream Corporation. G NuVox, Inc. G NuVox, Inc. 20100179 G ALLETE, Inc. G Square Butte Electric Cooperative. G Square Butte Electric...

Electrical Identification and Selective Microstimulation of Neuronal Compartments Based on Features of Extracellular Action Potentials

NASA Astrophysics Data System (ADS)

Radivojevic, Milos; Jäckel, David; Altermatt, Michael; Müller, Jan; Viswam, Vijay; Hierlemann, Andreas; Bakkum, Douglas J.

2016-08-01

A detailed, high-spatiotemporal-resolution characterization of neuronal responses to local electrical fields and the capability of precise extracellular microstimulation of selected neurons are pivotal for studying and manipulating neuronal activity and circuits in networks and for developing neural prosthetics. Here, we studied cultured neocortical neurons by using high-density microelectrode arrays and optical imaging, complemented by the patch-clamp technique, and with the aim to correlate morphological and electrical features of neuronal compartments with their responsiveness to extracellular stimulation. We developed strategies to electrically identify any neuron in the network, while subcellular spatial resolution recording of extracellular action potential (AP) traces enabled their assignment to the axon initial segment (AIS), axonal arbor and proximal somatodendritic compartments. Stimulation at the AIS required low voltages and provided immediate, selective and reliable neuronal activation, whereas stimulation at the soma required high voltages and produced delayed and unreliable responses. Subthreshold stimulation at the soma depolarized the somatic membrane potential without eliciting APs.

Alternative energy balances for Bulgaria to mitigate climate change

NASA Astrophysics Data System (ADS)

Christov, Christo

1996-01-01

Alternative energy balances aimed to mitigate greenhouse gas (GHG) emissions are developed as alternatives to the baseline energy balance. The section of mitigation options is based on the results of the GHG emission inventory for the 1987 1992 period. The energy sector is the main contributor to the total CO2 emissions of Bulgaria. Stationary combustion for heat and electricity production as well as direct end-use combustion amounts to 80% of the total emissions. The parts of the energy network that could have the biggest influence on GHG emission reduction are identified. The potential effects of the following mitigation measures are discussed: rehabilitation of the combustion facilities currently in operation; repowering to natural gas; reduction of losses in thermal and electrical transmission and distribution networks; penetration of new combustion technologies; tariff structure improvement; renewable sources for electricity and heat production; wasteheat utilization; and supply of households with natural gas to substitute for electricity in space heating and cooking. The total available and the achievable potentials are estimated and the implementation barriers are discussed.

Thunderstorm Hypothesis Reasoner

NASA Technical Reports Server (NTRS)

Mulvehill, Alice M.

1994-01-01

THOR is a knowledge-based system which incorporates techniques from signal processing, pattern recognition, and artificial intelligence (AI) in order to determine the boundary of small thunderstorms which develop and dissipate over the area encompassed by KSC and the Cape Canaveral Air Force Station. THOR interprets electric field mill data (derived from a network of electric field mills) by using heuristics and algorithms about thunderstorms that have been obtained from several domain specialists. THOR generates two forms of output: contour plots which visually describe the electric field activity over the network and a verbal interpretation of the activity. THOR uses signal processing and pattern recognition to detect signatures associated with noise or thunderstorm behavior in a near real time fashion from over 31 electrical field mills. THOR's AI component generates hypotheses identifying areas which are under a threat from storm activity, such as lightning. THOR runs on a VAX/VMS at the Kennedy Space Center. Its software is a coupling of C and FORTRAN programs, several signal processing packages, and an expert system development shell.

Integrating Emerging Topics through Online Team Design in a Hybrid Communication Networks Course: Interaction Patterns and Impact of Prior Knowledge

ERIC Educational Resources Information Center

Reisslein, Jana; Seeling, Patrick; Reisslein, Martin

2005-01-01

An important challenge in the introductory communication networks course in electrical and computer engineering curricula is to integrate emerging topics, such as wireless Internet access and network security, into the already content-intensive course. At the same time it is essential to provide students with experiences in online collaboration,…

Advanced Computational Techniques for Power Tube Design.

DTIC Science & Technology

1986-07-01

fixturing applications, in addition to the existing computer-aided engineering capabilities. o Helix TWT Manufacturing has Implemented a tooling and fixturing...illustrates the ajor features of this computer network. ) The backbone of our system is a Sytek Broadband Network (LAN) which Interconnects terminals and...automatic network analyzer (FANA) which electrically characterizes the slow-wave helices of traveling-wave tubes ( TWTs ) -- both for engineering design

An EBIC study of dislocation networks in unprocessed and unprocessed web silicon ribbon. [for solar cells

NASA Technical Reports Server (NTRS)

Fieldler, F. S.; Ast, D.

1982-01-01

Experimental techniques for the preparation of electron beam induced current samples of Web-dentritic silicon are described. Both as grown and processed material were investigated. High density dislocation networks were found close to twin planes in the bulk of the material. The electrical activity of these networks is reduced in processed material.

Response of power systems to the San Fernando Valley earthquake of 9 February 1971. Final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schiff, A.J.; Yao, J.T.P.

1972-01-01

The impact of the San Fernando Valley earthquake on electric power systems is discussed. Particular attention focused on the following three areas; (1) the effects of an earthquake on the power network in the Western States, (2) the failure of subsystems and components of the power system, and (3) the loss of power to hospitals. The report includes sections on the description and functions of major components of a power network, existing procedures to protect the network, safety devices within the system which influence the network, a summary of the effects of the San Fernando Valley earthquake on the Westernmore » States Power Network, and present efforts to reduce the network vulnerability to faults. Also included in the report are a review of design procedures and practices prior to the San Fernando Valley earthquake and descriptions of types of damage to electrical equipment, dynamic analysis of equipment failures, equipment surviving the San Fernando Valley earthquake and new seismic design specifications. In addition, some observations and insights gained during the study, which are not directly related to power systems are discussed.« less

High-resolution CMOS MEA platform to study neurons at subcellular, cellular, and network levels†

PubMed Central

Müller, Jan; Ballini, Marco; Livi, Paolo; Chen, Yihui; Radivojevic, Milos; Shadmani, Amir; Viswam, Vijay; Jones, Ian L.; Fiscella, Michele; Diggelmann, Roland; Stettler, Alexander; Frey, Urs; Bakkum, Douglas J.; Hierlemann, Andreas

2017-01-01

Studies on information processing and learning properties of neuronal networks would benefit from simultaneous and parallel access to the activity of a large fraction of all neurons in such networks. Here, we present a CMOS-based device, capable of simultaneously recording the electrical activity of over a thousand cells in in vitro neuronal networks. The device provides sufficiently high spatiotemporal resolution to enable, at the same time, access to neuronal preparations on subcellular, cellular, and network level. The key feature is a rapidly reconfigurable array of 26 400 microelectrodes arranged at low pitch (17.5 μm) within a large overall sensing area (3.85 × 2.10 mm2). An arbitrary subset of the electrodes can be simultaneously connected to 1024 low-noise readout channels as well as 32 stimulation units. Each electrode or electrode subset can be used to electrically stimulate or record the signals of virtually any neuron on the array. We demonstrate the applicability and potential of this device for various different experimental paradigms: large-scale recordings from whole networks of neurons as well as investigations of axonal properties of individual neurons. PMID:25973786

High-resolution CMOS MEA platform to study neurons at subcellular, cellular, and network levels.

PubMed

Müller, Jan; Ballini, Marco; Livi, Paolo; Chen, Yihui; Radivojevic, Milos; Shadmani, Amir; Viswam, Vijay; Jones, Ian L; Fiscella, Michele; Diggelmann, Roland; Stettler, Alexander; Frey, Urs; Bakkum, Douglas J; Hierlemann, Andreas

2015-07-07

Studies on information processing and learning properties of neuronal networks would benefit from simultaneous and parallel access to the activity of a large fraction of all neurons in such networks. Here, we present a CMOS-based device, capable of simultaneously recording the electrical activity of over a thousand cells in in vitro neuronal networks. The device provides sufficiently high spatiotemporal resolution to enable, at the same time, access to neuronal preparations on subcellular, cellular, and network level. The key feature is a rapidly reconfigurable array of 26 400 microelectrodes arranged at low pitch (17.5 μm) within a large overall sensing area (3.85 × 2.10 mm(2)). An arbitrary subset of the electrodes can be simultaneously connected to 1024 low-noise readout channels as well as 32 stimulation units. Each electrode or electrode subset can be used to electrically stimulate or record the signals of virtually any neuron on the array. We demonstrate the applicability and potential of this device for various different experimental paradigms: large-scale recordings from whole networks of neurons as well as investigations of axonal properties of individual neurons.

Electron percolation in realistic models of carbon nanotube networks

NASA Astrophysics Data System (ADS)

Simoneau, Louis-Philippe; Villeneuve, Jérémie; Rochefort, Alain

2015-09-01

The influence of penetrable and curved carbon nanotubes (CNT) on the charge percolation in three-dimensional disordered CNT networks have been studied with Monte-Carlo simulations. By considering carbon nanotubes as solid objects but where the overlap between their electron cloud can be controlled, we observed that the structural characteristics of networks containing lower aspect ratio CNT are highly sensitive to the degree of penetration between crossed nanotubes. Following our efficient strategy to displace CNT to different positions to create more realistic statistical models, we conclude that the connectivity between objects increases with the hard-core/soft-shell radii ratio. In contrast, the presence of curved CNT in the random networks leads to an increasing percolation threshold and to a decreasing electrical conductivity at saturation. The waviness of CNT decreases the effective distance between the nanotube extremities, hence reducing their connectivity and degrading their electrical properties. We present the results of our simulation in terms of thickness of the CNT network from which simple structural parameters such as the volume fraction or the carbon nanotube density can be accurately evaluated with our more realistic models.

Nano-soldering of magnetically aligned three-dimensional nanowire networks.

PubMed

Gao, Fan; Gu, Zhiyong

2010-03-19

It is extremely challenging to fabricate 3D integrated nanostructures and hybrid nanoelectronic devices. In this paper, we report a simple and efficient method to simultaneously assemble and solder nanowires into ordered 3D and electrically conductive nanowire networks. Nano-solders such as tin were fabricated onto both ends of multi-segmented nanowires by a template-assisted electrodeposition method. These nanowires were then self-assembled and soldered into large-scale 3D network structures by magnetic field assisted assembly in a liquid medium with a high boiling point. The formation of junctions/interconnects between the nanowires and the scale of the assembly were dependent on the solder reflow temperature and the strength of the magnetic field. The size of the assembled nanowire networks ranged from tens of microns to millimeters. The electrical characteristics of the 3D nanowire networks were measured by regular current-voltage (I-V) measurements using a probe station with micropositioners. Nano-solders, when combined with assembling techniques, can be used to efficiently connect and join nanowires with low contact resistance, which are very well suited for sensor integration as well as nanoelectronic device fabrication.

Fluid power network for centralized electricity generation in offshore wind farms

NASA Astrophysics Data System (ADS)

Jarquin-Laguna, A.

2014-06-01

An innovative and completely different wind-energy conversion system is studied where a centralized electricity generation within a wind farm is proposed by means of a hydraulic network. This paper presents the dynamic interaction of two turbines when they are coupled to the same hydraulic network. Due to the stochastic nature of the wind and wake interaction effects between turbines, the operating parameters (i.e. pitch angle, rotor speed) of each turbine are different. Time domain simulations, including the main turbine dynamics and laminar transient flow in pipelines, are used to evaluate the efficiency and rotor speed stability of the hydraulic system. It is shown that a passive control of the rotor speed, as proposed in previous work for a single hydraulic turbine, has strong limitations in terms of performance for more than one turbine coupled to the same hydraulic network. It is concluded that in order to connect several turbines, a passive control strategy of the rotor speed is not sufficient and a hydraulic network with constant pressure is suggested. However, a constant pressure network requires the addition of active control at the hydraulic motors and spear valves, increasing the complexity of the initial concept. Further work needs to be done to incorporate an active control strategy and evaluate the feasibility of the constant pressure hydraulic network.

Characterization and management of electrical noise in the new Australian military HF communication network

NASA Astrophysics Data System (ADS)

Vyden, Bruce

2000-03-01

The Australian Defense Force's (ADF's) High Frequency (HF) communication network is soon to be replaced by a modernized system. Characterization of electrical noise at the receiver sites proposed for the new system is crucial to its performance. Consequently receiver site noise will be measured under the HF Modernization implementation contract that was awarded to Boeing Australia Ltd. Unfortunately the utility of the noise measurements is constrained by the uncertainties of both the ionosphere and atmosphere. This paper discusses some of the issues related to the methodology for measuring the noise and exposes some unresolved issues.

French wind generator systems. [as auxiliary power sources for electrical networks

NASA Technical Reports Server (NTRS)

Noel, J. M.

1973-01-01

The experimental design of a wind driven generator with a rated power of 800 kilovolt amperes and capable of being connected to the main electrical network is reported. The rotor is a three bladed propeller; each blade is twisted but the fixed pitch is adjustable. The asynchronous 800-kilovolt ampere generator is driven by the propeller through a gearbox. A dissipating resistor regulates the machine under no-load conditions. The first propeller on the machine lasted 18 months; replacement of the rigid propeller with a flexible structure resulted in breakdown due to flutter effects.

Conducting single-molecule magnet materials.

PubMed

Cosquer, Goulven; Shen, Yongbing; Almeida, Manuel; Yamashita, Masahiro

2018-05-11

Multifunctional molecular materials exhibiting electrical conductivity and single-molecule magnet (SMM) behaviour are particularly attractive for electronic devices and related applications owing to the interaction between electronic conduction and magnetization of unimolecular units. The preparation of such materials remains a challenge that has been pursued by a bi-component approach of combination of SMM cationic (or anionic) units with conducting networks made of partially oxidized (or reduced) donor (or acceptor) molecules. The present status of the research concerning the preparation of molecular materials exhibiting SMM behaviour and electrical conductivity is reviewed, describing the few molecular compounds where both SMM properties and electrical conductivity have been observed. The evolution of this research field through the years is discussed. The first reported compounds are semiconductors in spite being able to present relatively high electrical conductivity, and the SMM behaviour is observed at low temperatures where the electrical conductivity of the materials is similar to that of an insulator. During the recent years, a breakthrough has been achieved with the coexistence of high electrical conductivity and SMM behaviour in a molecular compound at the same temperature range, but so far without evidence of a synergy between these properties. The combination of high electrical conductivity with SMM behaviour requires not only SMM units but also the regular and as far as possible uniform packing of partially oxidized molecules, which are able to provide a conducting network.

Automatic control in multidrive electrotechnical complexes with semiconductor converters

NASA Astrophysics Data System (ADS)

Vasilev, B. U.; Mardashov, D. V.

2017-01-01

The frequency convertor and the automatic control system, which can be used in the multi-drive electromechanical system with a few induction motions, are considered. The paper presents the structure of existing modern multi-drive electric drives inverters, namely, electric drives with a total frequency converter and few electric motions, and an electric drive, in which the converter is used for power supply and control of the independent frequency. It was shown that such technical solutions of frequency converters possess a number of drawbacks. The drawbacks are given. It was shown that the control of technological processes using the electric drive of this structure may be provided under very limited conditions, as the energy efficiency and the level of electromagnetic compatibility of electric drives is low. The authors proposed using a multi-inverter structure with an active rectifier in multidrive electric drives with induction motors frequency converters. The application of such frequency converter may solve the problem of electromagnetic compatibility, namely, consumption of sinusoidal currents from the network and the maintenance of a sinusoidal voltage and energy compatibility, namely, consumption of practically active energy from the network. Also, the paper proposes the use of the automatic control system, which by means of a multi-inverter frequency converter provides separate control of drive machines and flexible regulation of technological processes. The authors present oscillograms, which confirm the described characteristics of the developed electrical drive. The possible subsequent ways to improve the multi-motor drives are also described.

Automated electric valve for electrokinetic separation in a networked microfluidic chip.

PubMed

Cui, Huanchun; Huang, Zheng; Dutta, Prashanta; Ivory, Cornelius F

2007-02-15

This paper describes an automated electric valve system designed to reduce dispersion and sample loss into a side channel when an electrokinetically mobilized concentration zone passes a T-junction in a networked microfluidic chip. One way to reduce dispersion is to control current streamlines since charged species are driven along them in the absence of electroosmotic flow. Computer simulations demonstrate that dispersion and sample loss can be reduced by applying a constant additional electric field in the side channel to straighten current streamlines in linear electrokinetic flow (zone electrophoresis). This additional electric field was provided by a pair of platinum microelectrodes integrated into the chip in the vicinity of the T-junction. Both simulations and experiments of this electric valve with constant valve voltages were shown to provide unsatisfactory valve performance during nonlinear electrophoresis (isotachophoresis). On the basis of these results, however, an automated electric valve system was developed with improved valve performance. Experiments conducted with this system showed decreased dispersion and increased reproducibility as protein zones isotachophoretically passed the T-junction. Simulations of the automated electric valve offer further support that the desired shape of current streamlines was maintained at the T-junction during isotachophoresis. Valve performance was evaluated at different valve currents based on statistical variance due to dispersion. With the automated control system, two integrated microelectrodes provide an effective way to manipulate current streamlines, thus acting as an electric valve for charged species in electrokinetic separations.

Network complexity and synchronous behavior--an experimental approach.

PubMed

Neefs, P J; Steur, E; Nijmeijer, H

2010-06-01

We discuss synchronization in networks of Hindmarsh-Rose neurons that are interconnected via gap junctions, also known as electrical synapses. We present theoretical results for interactions without time-delay. These results are supported by experiments with a setup consisting of sixteen electronic equivalents of the Hindmarsh-Rose neuron. We show experimental results of networks where time-delay on the interaction is taken into account. We discuss in particular the influence of the network topology on the synchronization.

Electric utilities and the info-way - are electrics and telcos fellow travelers or competitors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ashworth, M.J.

1994-03-15

This article examines the future role of telecommunications and the so-called information superhighway in the operations of electric utilities. Utilities should take advantage of information technology through informal alliances with telecommunications hardware and service suppliers, should limit investments in alternative meter-level technologies to those that are cheap, easily integrated, and flexible, and should consider outsourcing network implementation, maintenance, and management functions.

Neural Network Analysis of Musculoskeletal Responses to Electrical AC-Stimulus

DTIC Science & Technology

2001-10-25

FAM, SOM I. INTRODUCTION Various kinds of electrical measurements have been used to investigate the human body, including the mechanical or chemical...measurements were obtained from five points; namely, the patients’ wrists, ankles and back. The electrodes of an IF Electrotherapy unit [5] were attached...musculoskeletal responses to electrical AC-stimulus M. Hannula1, E. Alasaarela2 , J. Laitinen1 1Institute of Technology , Oulu Polytechnic, Oulu, Finland

Resting electrical network activity in traps of the aquatic carnivorous plants of the genera Aldrovanda and Utricularia

PubMed Central

Masi, Elisa; Ciszak, Marzena; Colzi, Ilaria; Adamec, Lubomir; Mancuso, Stefano

2016-01-01

In this study the MEA (multielectrode array) system was used to record electrical responses of intact and halved traps, and other trap-free tissues of two aquatic carnivorous plants, Aldrovanda vesiculosa and Utricularia reflexa. They exhibit rapid trap movements and their traps contain numerous glands. Spontaneous generation of spikes with quite uniform shape, propagating across the recording area, has been observed for all types of sample. In the analysis of the electrical network, higher richer synchronous activity was observed relative to other plant species and organs previously described in the literature: indeed, the time intervals between the synchronized clusters (the inter-spike intervals) create organized patterns and the propagation times vary non-linearly with the distance due to this synchronization. Interestingly, more complex electrical activity was found in traps than in trap-free organs, supporting the hypothesis that the nature of the electrical activity may reflect the anatomical and functional complexity of different organs. Finally, the electrical activity of functionally different traps of Aldrovanda (snapping traps) and Utricularia (suction traps) was compared and some differences in the features of signal propagation were found. According to these results, a possible use of the MEA system for the study of different trap closure mechanisms is proposed. PMID:27117956

A generalized electro-elastic theory of polymer networks

NASA Astrophysics Data System (ADS)

Cohen, Noy

2018-01-01

A rigorous multi-scale analysis of the electromechanical coupling in dielectric polymers is conducted. The body couples stemming from a misalignment between the electric field and the electric-dipole density vector are studied and the conservation laws for polymer networks are derived. Using variational principles, expressions for the polarization and the stress are determined. Interestingly, it is found that the stress tensor resulting from coupled loadings in which the electric field is misaligned with the principal stretch directions is not symmetric and the asymmetry arises from the body couples. Next, the electro-mechanical response of a chain is analyzed. The deformations of the individual polymer chains are related to the macroscopic deformation via two highly non-linear constraints - the first pertaining to the compatibility of the local deformations with the imposed macroscopic one and the second stems from the symmetric part of the stress at equilibrium. In accord with the proposed framework, an amended three-chains model is introduced. The predictions of this model are found to be in excellent agreement with experimental findings. Lastly, the behavior of a polymer subjected to a simple shear and an electric field is studied. The offset between the electric field and the principal directions gives rise to body couples, a polarization that is not aligned with the electric field, and an asymmetric stress tensor.

Coordinated Scheduling for Interdependent Electric Power and Natural Gas Infrastructures

DOE PAGES

Zlotnik, Anatoly; Roald, Line; Backhaus, Scott; ...

2016-03-24

The extensive installation of gas-fired power plants in many parts of the world has led electric systems to depend heavily on reliable gas supplies. The use of gas-fired generators for peak load and reserve provision causes high intraday variability in withdrawals from high-pressure gas transmission systems. Such variability can lead to gas price fluctuations and supply disruptions that affect electric generator dispatch, electricity prices, and threaten the security of power systems and gas pipelines. These infrastructures function on vastly different spatio-temporal scales, which prevents current practices for separate operations and market clearing from being coordinated. Here in this article, wemore » apply new techniques for control of dynamic gas flows on pipeline networks to examine day-ahead scheduling of electric generator dispatch and gas compressor operation for different levels of integration, spanning from separate forecasting, and simulation to combined optimal control. We formulate multiple coordination scenarios and develop tractable physically accurate computational implementations. These scenarios are compared using an integrated model of test networks for power and gas systems with 24 nodes and 24 pipes, respectively, which are coupled through gas-fired generators. The analysis quantifies the economic efficiency and security benefits of gas-electric coordination and dynamic gas system operation.« less

Optical interconnections and networks; Proceedings of the Meeting, The Hague, Netherlands, Mar. 14, 15, 1990

NASA Technical Reports Server (NTRS)

Bartelt, Hartmut (Editor)

1990-01-01

The conference presents papers on interconnections, clock distribution, neural networks, and components and materials. Particular attention is given to a comparison of optical and electrical data interconnections at the board and backplane levels, a wafer-level optical interconnection network layout, an analysis and simulation of photonic switch networks, and the integration of picosecond GaAs photoconductive devices with silicon circuits for optical clocking and interconnects. Consideration is also given to the optical implementation of neural networks, invariance in an optoelectronic implementation of neural networks, and the recording of reversible patterns in polymer lightguides.

Heterogeneous collaborative sensor network for electrical management of an automated house with PV energy.

PubMed

Castillo-Cagigal, Manuel; Matallanas, Eduardo; Gutiérrez, Alvaro; Monasterio-Huelin, Félix; Caamaño-Martín, Estefaná; Masa-Bote, Daniel; Jiménez-Leube, Javier

2011-01-01

In this paper we present a heterogeneous collaborative sensor network for electrical management in the residential sector. Improving demand-side management is very important in distributed energy generation applications. Sensing and control are the foundations of the "Smart Grid" which is the future of large-scale energy management. The system presented in this paper has been developed on a self-sufficient solar house called "MagicBox" equipped with grid connection, PV generation, lead-acid batteries, controllable appliances and smart metering. Therefore, there is a large number of energy variables to be monitored that allow us to precisely manage the energy performance of the house by means of collaborative sensors. The experimental results, performed on a real house, demonstrate the feasibility of the proposed collaborative system to reduce the consumption of electrical power and to increase energy efficiency.

Revealing networks from dynamics: an introduction

NASA Astrophysics Data System (ADS)

Timme, Marc; Casadiego, Jose

2014-08-01

What can we learn from the collective dynamics of a complex network about its interaction topology? Taking the perspective from nonlinear dynamics, we briefly review recent progress on how to infer structural connectivity (direct interactions) from accessing the dynamics of the units. Potential applications range from interaction networks in physics, to chemical and metabolic reactions, protein and gene regulatory networks as well as neural circuits in biology and electric power grids or wireless sensor networks in engineering. Moreover, we briefly mention some standard ways of inferring effective or functional connectivity.

Probability of conductive bond formation in a percolating network of nanowires with fusible tips

NASA Astrophysics Data System (ADS)

Rykaczewski, Konrad; Wang, Robert Y.

2018-03-01

Meeting the heat dissipation demands of microelectronic devices requires development of polymeric composites with high thermal conductivity. This property is drastically improved by percolation networks of metallic filler particles that have their particle-to-particle contact resistances reduced through thermal or electromagnetic fusing. However, composites with fused metallic fillers are electrically conductive, which prevents their application within the chip-board and the inter-chip gaps. Here, we propose that electrically insulating composites for these purposes can be achieved by the application of fusible metallic coatings to the tips of nanowires with thermally conductive but electrically insulating cores. We derive analytical models that relate the ratio of the coated and total nanowire lengths to the fraction of fused, and thus conductive, bonds within percolating networks of these structures. We consider two types of materials for these fusible coatings. First, we consider silver-like coatings, which form only conductive bonds when contacting the silver-like coating of another nanowire. Second, we consider liquid metal-like coatings, which form conductive bonds regardless of whether they contact a coated or an uncoated segment of another nanowire. These models were validated using Monte Carlo simulations, which also revealed that electrical short-circuiting is highly unlikely until most of the wire is coated. Furthermore, we demonstrate that switching the tip coating from silver- to liquid metal-like materials can double the fraction of conductive bonds. Consequently, this work provides motivation to develop scalable methods for fabrication of the hybrid liquid-coated nanowires, whose dispersion in a polymer matrix is predicted to yield highly thermally conductive but electrically insulating composites.

Hydrogel Actuation by Electric Field Driven Effects

NASA Astrophysics Data System (ADS)

Morales, Daniel Humphrey

Hydrogels are networks of crosslinked, hydrophilic polymers capable of absorbing and releasing large amounts of water while maintaining their structural integrity. Polyelectrolyte hydrogels are a subset of hydrogels that contain ionizable moieties, which render the network sensitive to the pH and the ionic strength of the media and provide mobile counterions, which impart conductivity. These networks are part of a class of "smart" material systems that can sense and adjust their shape in response to the external environment. Hence, the ability to program and modulate hydrogel shape change has great potential for novel biomaterial and soft robotics applications. We utilized electric field driven effects to manipulate the interaction of ions within polyelectrolyte hydrogels in order to induce controlled deformation and patterning. Additionally, electric fields can be used to promote the interactions of separate gel networks, as modular components, and particle assemblies within gel networks to develop new types of soft composite systems. First, we present and analyze a walking gel actuator comprised of cationic and anionic gel legs attached by electric field-promoted polyion complexation. We characterize the electro-osmotic response of the hydrogels as a function of charge density and external salt concentration. The gel walkers achieve unidirectional motion on flat elastomer substrates and exemplify a simple way to move and manipulate soft matter devices in aqueous solutions. An 'ionoprinting' technique is presented with the capability to topographically structure and actuate hydrated gels in two and three dimensions by locally patterning ions induced by electric fields. The bound charges change the local mechanical properties of the gel to induce relief patterns and evoke localized stress, causing rapid folding in air. The ionically patterned hydrogels exhibit programmable temporal and spatial shape transitions which can be tuned by the duration and/or strength of the applied electric field. We extend the use of ionoprinting to develop multi-responsive bilayer gel systems capable of more complex shape transformation. The localized crosslinked regions determine the bending axis as the gel responds to the external environment. The bending can be tuned to reverse direction isothermally by changing the solvent quality or by changing the temperature at a fixed concentration. The multi-responsive behavior is caused by the volume transitions of a non-ionic, thermos-sensitive hydrogel coupled with a superabsorbent ionic hydrogel. Lastly, electric field driven microparticle assembly, using dielectrophoretic (DEP) forces, organized colloidal microparticles within a hydrogel matrix. The use of DEP forces enables rapid, efficient and precise control over the colloidal distribution. The resulting supracolloidal endoskeleton structures impart directional bending as the hydrogel shrinks. We compare the ordered particles structures to random particle distributions in affecting the hydrogel sheet bending response. This study demonstrates a universal technique for imparting directional properties in hydrogels towards new generations of hybrid soft materials.

Local Area Networks.

ERIC Educational Resources Information Center

Nasatir, Marilyn; And Others

1990-01-01

Four papers discuss LANs (local area networks) and library applications: (1) "Institute for Electrical and Electronic Engineers Standards..." (Charles D. Brown); (2) "Facilities Planning for LANs..." (Gail Persky); (3) "Growing up with the Alumni Library: LAN..." (Russell Buchanan); and (4) "Implementing a LAN...at the Health Sciences Library"…

Loss Reduction on Adoption of High Voltage LT Less Distribution

NASA Astrophysics Data System (ADS)

Tiwari, Deepika; Adhikari, Nikhileshwar Prasad; Gupta, Amit; Bajpai, Santosh Kumar

2016-06-01

In India there is a need to improve the quality of the electricity distribution process which has increased varying from year to year. In distribution networks, the limiting factor to load carrying capacity is generally the voltage reduction. High voltage distribution system (HVDS) is one of the steps to reduce line losses in electrical distribution network. It helps to reduce the length of low tension (LT) lines and makes the power available close to the users. The high voltage power distribution system reduces the probability of power theft by hooking HVDS suggests an increase in installation of small capacity single-phase transformers in the network which again save considerable energy. This paper is compared to existing conventional low tension distribution network with HVDS. The paper gives a clear picture of reduction in distribution losses with adoption of HVDS system. Losses Reduction of 11 kV Feeder in Nuniya (India) with adoption of HVDS have been worked out/ quantified and benefits thereby in generating capacity have discussed.

Influence of graphene quantum dots on electrical properties of polymer composites

NASA Astrophysics Data System (ADS)

Arthisree, D.; Joshi, Girish M.

2017-07-01

We successfully prepared synthetic nanocomposite (SNC) by dispersing graphene quantum dots (GQD) in cellulose acetate (CA) polymer system. The dispersion and occupied network of GQD were foreseen by microscopic techniques. The variation of plane to crossed linked array network was observed by the polarizing optical microscopic (POM) technique. The scanning electron microscopy (SEM) revealed the leaves like impressions of GQD in host polymer system. The series network of GQD occupied in CA at higher resolution was confirmed by transmission electron microscopy (TEM). The two dimensional (2D) topographic images demonstrated an entangled polymer network to plane morphology. The variation in surface roughness was evaluated from the dimensional (3D) topography. The influence of temperature on AC conductivity with highest value (4  ×  10-5 S cm-1), contributes to the decrease in activation energy. The DC conductivity obeys the percolation criteria co-related to the GQD loading by weight fraction. Furthermore, this synthetic nanocomposite is feasible for the development of sensing and electrical applications.

International Standardization in the Design of "Shore to Ship" - Power Supply Systems of Ships in Port

NASA Astrophysics Data System (ADS)

Tarnapowicz, Dariusz; German-Galkin, Sergiej

2018-03-01

The decisive source of air pollution emissions in ports is the berthed ships. This is primarily caused by the work of ship's autonomous generator sets. One way of reducing the air pollution emissions in ports is the supply of ships from electricity inland system. The main problem connected with the power connection of ships to the inland network is caused by different values of levels and frequencies of voltages in these networks (in various countries) in relation to different values of levels and frequencies of voltages present in the ship's network. It is also important that the source power can range from a few hundred kW up to several MW. In order to realize a universal „Shore to Ship" system that allows the connection of ships to the electricity inland network, the international standardization is necessary. This article presents the current recommendations, standards and regulations for the design of „Shore to Ship" systems.

Community Microgrid Scheduling Considering Network Operational Constraints and Building Thermal Dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Guodong; Ollis, Thomas B.; Xiao, Bailu

Here, this paper proposes a Mixed Integer Conic Programming (MICP) model for community microgrids considering the network operational constraints and building thermal dynamics. The proposed optimization model optimizes not only the operating cost, including fuel cost, purchasing cost, battery degradation cost, voluntary load shedding cost and the cost associated with customer discomfort due to room temperature deviation from the set point, but also several performance indices, including voltage deviation, network power loss and power factor at the Point of Common Coupling (PCC). In particular, the detailed thermal dynamic model of buildings is integrated into the distribution optimal power flow (D-OPF)more » model for the optimal operation of community microgrids. The heating, ventilation and air-conditioning (HVAC) systems can be scheduled intelligently to reduce the electricity cost while maintaining the indoor temperature in the comfort range set by customers. Numerical simulation results show the effectiveness of the proposed model and significant saving in electricity cost could be achieved with network operational constraints satisfied.« less

Smart PV grid to reinforce the electrical network

NASA Astrophysics Data System (ADS)

AL-Hamad, Mohamed Y.; Qamber, Isa S.

2017-11-01

Photovoltaic (PV) became the new competitive energy resources of the planet and needs to be engaged in grid to break up the congestion in both Distribution and Transmission systems. The objective of this research is to reduce the load flow through the distribution and transmission equipment by 20%. This reduction will help in relief networks loaded equipment's in all networks. Many projects are starting to develop in the GCC countries and need to be organized to achieve maximum benefits from involving the Renewable Energy Sources (RES) in the network. The GCC countries have a good location for solar energy with high intensity of the solar radiation and clear sky along the year. The opportunities of the solar energy is to utilize and create a sustainable energy resource for this region. Moreover, the target of this research is to engage the PV technology in such a way to lower the over loaded equipment and increases the electricity demand at the consumer's side.

Community Microgrid Scheduling Considering Network Operational Constraints and Building Thermal Dynamics

DOE PAGES

Liu, Guodong; Ollis, Thomas B.; Xiao, Bailu; ...

2017-10-10

Here, this paper proposes a Mixed Integer Conic Programming (MICP) model for community microgrids considering the network operational constraints and building thermal dynamics. The proposed optimization model optimizes not only the operating cost, including fuel cost, purchasing cost, battery degradation cost, voluntary load shedding cost and the cost associated with customer discomfort due to room temperature deviation from the set point, but also several performance indices, including voltage deviation, network power loss and power factor at the Point of Common Coupling (PCC). In particular, the detailed thermal dynamic model of buildings is integrated into the distribution optimal power flow (D-OPF)more » model for the optimal operation of community microgrids. The heating, ventilation and air-conditioning (HVAC) systems can be scheduled intelligently to reduce the electricity cost while maintaining the indoor temperature in the comfort range set by customers. Numerical simulation results show the effectiveness of the proposed model and significant saving in electricity cost could be achieved with network operational constraints satisfied.« less

Ag@Ni core-shell nanowire network for robust transparent electrodes against oxidation and sulfurization.

PubMed

Eom, Hyeonjin; Lee, Jaemin; Pichitpajongkit, Aekachan; Amjadi, Morteza; Jeong, Jun-Ho; Lee, Eungsug; Lee, Jung-Yong; Park, Inkyu

2014-10-29

Silver nanowire (Ag NW) based transparent electrodes are inherently unstable to moist and chemically reactive environment. A remarkable stability improvement of the Ag NW network film against oxidizing and sulfurizing environment by local electrodeposition of Ni along Ag NWs is reported. The optical transmittance and electrical resistance of the Ni deposited Ag NW network film can be easily controlled by adjusting the morphology and thickness of the Ni shell layer. The electrical conductivity of the Ag NW network film is increased by the Ni coating via welding between Ag NWs as well as additional conductive area for the electron transport by electrodeposited Ni layer. Moreover, the chemical resistance of Ag NWs against oxidation and sulfurization can be dramatically enhanced by the Ni shell layer electrodeposited along the Ag NWs, which provides the physical barrier against chemical reaction and diffusion as well as the cathodic protection from galvanic corrosion. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Defects formation and spiral waves in a network of neurons in presence of electromagnetic induction.

PubMed

Rostami, Zahra; Jafari, Sajad

2018-04-01

Complex anatomical and physiological structure of an excitable tissue (e.g., cardiac tissue) in the body can represent different electrical activities through normal or abnormal behavior. Abnormalities of the excitable tissue coming from different biological reasons can lead to formation of some defects. Such defects can cause some successive waves that may end up to some additional reorganizing beating behaviors like spiral waves or target waves. In this study, formation of defects and the resulting emitted waves in an excitable tissue are investigated. We have considered a square array network of neurons with nearest-neighbor connections to describe the excitable tissue. Fundamentally, electrophysiological properties of ion currents in the body are responsible for exhibition of electrical spatiotemporal patterns. More precisely, fluctuation of accumulated ions inside and outside of cell causes variable electrical and magnetic field. Considering undeniable mutual effects of electrical field and magnetic field, we have proposed the new Hindmarsh-Rose (HR) neuronal model for the local dynamics of each individual neuron in the network. In this new neuronal model, the influence of magnetic flow on membrane potential is defined. This improved model holds more bifurcation parameters. Moreover, the dynamical behavior of the tissue is investigated in different states of quiescent, spiking, bursting and even chaotic state. The resulting spatiotemporal patterns are represented and the time series of some sampled neurons are displayed, as well.

Artificial neural network and SARIMA based models for power load forecasting in Turkish electricity market

PubMed Central

2017-01-01

Load information plays an important role in deregulated electricity markets, since it is the primary factor to make critical decisions on production planning, day-to-day operations, unit commitment and economic dispatch. Being able to predict the load for a short term, which covers one hour to a few days, equips power generation facilities and traders with an advantage. With the deregulation of electricity markets, a variety of short term load forecasting models are developed. Deregulation in Turkish Electricity Market has started in 2001 and liberalization is still in progress with rules being effective in its predefined schedule. However, there is a very limited number of studies for Turkish Market. In this study, we introduce two different models for current Turkish Market using Seasonal Autoregressive Integrated Moving Average (SARIMA) and Artificial Neural Network (ANN) and present their comparative performances. Building models that cope with the dynamic nature of deregulated market and are able to run in real-time is the main contribution of this study. We also use our ANN based model to evaluate the effect of several factors, which are claimed to have effect on electrical load. PMID:28426739

Artificial neural network and SARIMA based models for power load forecasting in Turkish electricity market.

PubMed

Bozkurt, Ömer Özgür; Biricik, Göksel; Tayşi, Ziya Cihan

2017-01-01

Load information plays an important role in deregulated electricity markets, since it is the primary factor to make critical decisions on production planning, day-to-day operations, unit commitment and economic dispatch. Being able to predict the load for a short term, which covers one hour to a few days, equips power generation facilities and traders with an advantage. With the deregulation of electricity markets, a variety of short term load forecasting models are developed. Deregulation in Turkish Electricity Market has started in 2001 and liberalization is still in progress with rules being effective in its predefined schedule. However, there is a very limited number of studies for Turkish Market. In this study, we introduce two different models for current Turkish Market using Seasonal Autoregressive Integrated Moving Average (SARIMA) and Artificial Neural Network (ANN) and present their comparative performances. Building models that cope with the dynamic nature of deregulated market and are able to run in real-time is the main contribution of this study. We also use our ANN based model to evaluate the effect of several factors, which are claimed to have effect on electrical load.

Percolation dans des reseaux realistes de nanostructures de carbone

NASA Astrophysics Data System (ADS)

Simoneau, Louis-Philippe

Carbon nanotubes have very interesting mechanical and electrical properties for various applications in electronics. They are highly resistant to deformation and can be excellent conductors or semiconductors. However, manipulating individual nanotubes to build structured devices remains very difficult. There is no method for controlling all of the electrical properties, the orientation and the spatial positioning of a large number of nanotubes. The fabrication of disordered networks of nanotubes is much easier, and these systems have a good electrical conductivity which makes them very interesting, especially as materials of transparent and flexible electrodes. There are three main methods of production used to make networks of nanotubes: the solution deposition, the direct growth on substrate and the embedding in a polymer matrix. The solution deposition method can form networks of various densities on a variety of substrates, the direct growth of nanotubes allows the creation of very clean networks on substrates such as SiO2, and the embedding in a polymer matrix can give composite volumes containing varying amounts of nanotubes. Many parameters such as the length of the tubes, their orientation or their tortuosity influence the properties of these networks and the presence of structural disorder complicates the understanding of their interactions. Predicting the properties of a network, such as conductivity, from a few characteristics such as size and density of the tubes can be difficult. This task becomes even more complex if one wants to identify the parameters that will optimize the performance of a device containing the material. We chose to address the carbon nanotube networks problem by developing a series of computer simulation tools that are mainly based on the Monte Carlo method. We take into account a large number of parameters to describe the characteristics of the networks, which allows for a more reliable representation of real networks as well as versatility in the choice of network components that can be simulated. The tools we have developed, grouped together in the RPH-HPN software Reseaux percolatifs hybrides - Hybrid Percolation Networks, construct random networks, detect contact between the tubes, translate the systems to equivalent electrical circuits and calculate global properties. An infinity of networks can have the same basic characteristics (size, diameter, etc.) and therefore the properties of a particular random network are not necessarily representative of the average properties of all networks. To obtain those general properties, we simulate a large number of random networks with the same basic characteristics and the average of the quantities is determined. The network constituent elements can be spheres, rods or snakes. The use of such geometries for network elements makes contact detection simple and quick, and more faithfully reproduce the form of carbon nanotubes. We closely monitor the geometrical and electrical properties of these elements through stochastic distributions of our choice. We can choose the length, diameter, orientation, chirality, tortuosity and impenetrable nature of the elements in order to properly reproduce real networks characteristics. We have considered statistical distribution functions that are rectangular, Gaussian, and Lorentzian, but all other distributions that can be expressed mathematically can also be envisioned. During the creation of a particular network, we generate the elements one by one. Each of their properties is sampled from a preselected distribution. Efficient algorithms used in various fields were adapted to our needs to manage the detection of contacts, clusters and percolation. In addition, we model more realistic contact between rigid nanotubes using an original method used to create the network that does not require a relaxation phase. Finally, we use Kirchhoff's laws to solve the equivalent electrical circuit conventionally. First, we evaluated the impact of a simplification widely used in other nanotube networks simulations studies. Values of the contact resistance at the junction between two nanotubes that are reported in the literature vary over a wide range, while almost all the simulations use a unique value for this parameter. Therefore, we assessed the effect of the presence of various stochastic distributions of contact resistances on the electrical properties of the networks. To do this, we used the experimental results of our collaborators in order to reproduce them by simulation. Our results show that, despite the existence of a wide range of contact resistance values, the nature of the statistical distribution has little impact on the conductivity obtained by simulation. Use of a single value for all connections of a network gives a total conductivity comparable to the experimental conductivity, and similar to that obtained using Gaussian, Lorentzian and uniform rectangular distributions. In fact, the dominant factor is not the type of distribution used to represent the resistance, but the central value of the distribution. Furthermore, we showed by studying bimodal distributions that the presence of lower resistance paths, even in small proportion, can rapidly increase the conductivity of the network. However, the type of stochastic distribution used to sample the spatial orientation of the nanotubes has a significant impact. We observed different behaviors for each of the three forms of distribution of orientation angles that we studied. In each case, a different distribution width maximize the conductivity of the networks. To optimize the conductivity, this distribution width, which is actually the deviation from the main direction, should in general be narrow. The formation of conductive paths is greatly enhanced in the presence of a majority of tubes closely aligned with the conduction direction and a small portion of tubes randomly aligned. The portion of misaligned tubes strongly contributes to the connectivity of nanotubes network by linking several clusters of aligned tubes. In order to increase the realism of our simulations, we also studied the influence of the interpenetrability of nanotubes on the electrical properties of networks. To do this, we describe the nanotubes with mutually impenetrable rigid cores that are surrounded by permeable shells. Thus, by varying the radius of the rigid cores, we have shown that a decrease in the interpenetrability of the nanotubes can increase the conductivity of the networks up to five orders of magnitude. We attribute this increase in conductivity to a greater connectivity of the nanotubes in the network. The more tubes are impenetrable, the more they push back against each other, and the better is the spreading of connected clusters in space. The second parameter on which we focused to improve the realism is the tortuosity of the nanotubes. We investigated the electrical properties of networks where the nanotubes are segmented into ten sections joined end to end. The angle between two consecutive segments is sampled from a uniform rectangular distribution and the variation of the bounds of this distribution allows us to vary the general tortuosity of the network. We observe that the more the tubes are tortuous, the higher the percolation threshold is, and the lower is the total conductivity. This can be nearly two orders of magnitude lower for networks with twisted tubes. We further note that the increase of the percolation threshold is attenuated when the wavy nanotubes have rigid cores. As part of our project, we have developed tools that, to the best of our knowledge, offer the best physical representation of nanotubes in a network of carbon nanotubes to date. This allowed us to study networks of complex geometries and measure the importance of the statistical distributions of parameters in optimizing the conductivity of networks. We have also established that the rigid tube-tube contacts and the nanotube tortuosity have strong impacts on the percolation threshold and conductivity. This work has demonstrated the importance of modeling for the understanding and the adequate description of complex processes, and the development needed to accurately reproduce the behavior of real systems. These tools can now be used to guide the creation of nanotube networks with targeted properties, and also to explore even more complex systems containing for example mixtures of nanotubes and quantum dots.

77 FR 47828 - Amended Notice of Intent To Prepare the Hawai'i Clean Energy Programmatic Environmental Impact...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-08-10

... efficiency and renewable energy activities and technologies to be analyzed in the PEIS and, accordingly, has... Renewables, (4) Alternative Transportation Fuels and Modes, and (5) Electrical Transmission and Distribution... Kaua'i; electric vehicle public charging networks; efficient appliance rebates; solar water heating...

[Mobilization of the stomach and colon using high-frequency electric welding of tissues apparatus].

PubMed

Sukhin, I A; Ostapenko, O M; Kachan, S H; Bilylovets', O M; Honchar, I V

2012-08-01

The experience of the native high-frequency electrical generator 300M EC-1 "Patonmed" for mobilization of advanced vascular network, particularly stomach and colon are presented. The variants of modes depending on the diameter of blood vessels and accompanied diseases are suggested.

Islanding detection and over voltage mitigation using wireless sensor networks and electric vehicle charging stations.

DOT National Transportation Integrated Search

2016-06-01

An islanding condition occurs when a distributed generation (DG) unit continues to energize a : part of the grid while said part has been isolated from the main electrical utility. In this event, if : the power of the DG exceeds the load, a transient...

Application of Neural Network Technologies for Price Forecasting in the Liberalized Electricity Market

NASA Astrophysics Data System (ADS)

Gerikh, Valentin; Kolosok, Irina; Kurbatsky, Victor; Tomin, Nikita

2009-01-01

The paper presents the results of experimental studies concerning calculation of electricity prices in different price zones in Russia and Europe. The calculations are based on the intelligent software "ANAPRO" that implements the approaches based on the modern methods of data analysis and artificial intelligence technologies.

The SENNAPE Project: An University-Industry Joint Program in Information Technology.

ERIC Educational Resources Information Center

Seixas, J. M.; Maidantchik, C.; Caloba, L. P.

The SENNAPE (Software Engineering and Neural Networks Applied to Physics and Electricity) project has been putting together the European and the Brazilian industries towards neural processing developments in the fields of high-energy physics and electricity. It is a multi-disciplinary international collaboration with the participation of different…

Heat-electrical regeneration way to intensive energy saving in an electric arc furnaces

NASA Astrophysics Data System (ADS)

Kartavtcev, S.; Matveev, S.; Neshporenko, E.

2018-03-01

Energy saving in steel production is of great significance for its large economical scale of 1500 mil t/year and high-energy consumption. Steady trend of last years is an increase of steel production in electric arc furnaces (EAF) with a very high consumption of electricity up to 750 kWh/ton. The intention to reduce so much energy consumption they can reach by many ways. One of such way is a transforming heat energy of liquid steel to electricity and destine it to steel electric arc process. Under certain conditions, it may lead to “zero” consumption of electric power in the process. The development of these conditions leads to the formation of energy-efficient heat schemes, with a minimum electricity consumption from the external network.

Review Of E-Beam Electrical Test Techniques

NASA Astrophysics Data System (ADS)

Hohn, Fritz J.

1987-09-01

Electron beams as a viable technique for contactless testing of electrical functions and electrical integrity of different active devices in VLSI-chips has been demonstrated over the past years. This method of testing electronic networks, most widely used in the laboratory environment, is based on an electron probe which is deflected from point to point in the network. A current of secondary electrons emitted in response to the impingement of the electron probe is converted to a signal indicating the presence of a voltage or varying potential at the different points. Voltage contrast, electron beam induced current, dual potential approach, stroboscopic techniques and other methods have been developed and are used to detect different functional failures in devices. Besides the VLSI application, the contactless testing of three dimensional conductor networks of a 10cm x 10cm x .8cm multilayer ceramic module poses a different and new application for the electron beam test technique. A dual potential electron beam test system allows to generate electron beam induced voltage contrast. The same system at a different potential is used to detect this voltage contrast over the large area without moving the substrate and thus test for the electrical integrity of the networks. Less attention in most of the applications has been paid to the electron optical environment, mostly SEM's were upgraded or converted to do the job of a "voltage contrast" machine. This by no means will satisfy all requirements and more thoughts have to be given to aspects such as: low voltage electron guns: thermal emitter, Schottky emitter, field emitter, low voltage electron optics, two lens systems, different means of detection, signal processing - storage and others. This paper will review available E-beam test techniques, specific applications and some critical components.

The eGo grid model: An open-source and open-data based synthetic medium-voltage grid model for distribution power supply systems

NASA Astrophysics Data System (ADS)

Amme, J.; Pleßmann, G.; Bühler, J.; Hülk, L.; Kötter, E.; Schwaegerl, P.

2018-02-01

The increasing integration of renewable energy into the electricity supply system creates new challenges for distribution grids. The planning and operation of distribution systems requires appropriate grid models that consider the heterogeneity of existing grids. In this paper, we describe a novel method to generate synthetic medium-voltage (MV) grids, which we applied in our DIstribution Network GeneratOr (DINGO). DINGO is open-source software and uses freely available data. Medium-voltage grid topologies are synthesized based on location and electricity demand in defined demand areas. For this purpose, we use GIS data containing demand areas with high-resolution spatial data on physical properties, land use, energy, and demography. The grid topology is treated as a capacitated vehicle routing problem (CVRP) combined with a local search metaheuristics. We also consider the current planning principles for MV distribution networks, paying special attention to line congestion and voltage limit violations. In the modelling process, we included power flow calculations for validation. The resulting grid model datasets contain 3608 synthetic MV grids in high resolution, covering all of Germany and taking local characteristics into account. We compared the modelled networks with real network data. In terms of number of transformers and total cable length, we conclude that the method presented in this paper generates realistic grids that could be used to implement a cost-optimised electrical energy system.

Electric Vehicles Charging Scheduling Strategy Considering the Uncertainty of Photovoltaic Output

NASA Astrophysics Data System (ADS)

Wei, Xiangxiang; Su, Su; Yue, Yunli; Wang, Wei; He, Luobin; Li, Hao; Ota, Yutaka

2017-05-01

The rapid development of electric vehicles and distributed generation bring new challenges to security and economic operation of the power system, so the collaborative research of the EVs and the distributed generation have important significance in distribution network. Under this background, an EVs charging scheduling strategy considering the uncertainty of photovoltaic(PV) output is proposed. The characteristics of EVs charging are analysed first. A PV output prediction method is proposed with a PV database then. On this basis, an EVs charging scheduling strategy is proposed with the goal to satisfy EVs users’ charging willingness and decrease the power loss in distribution network. The case study proves that the proposed PV output prediction method can predict the PV output accurately and the EVs charging scheduling strategy can reduce the power loss and stabilize the fluctuation of the load in distributed network.

Dielectric and diamagnetic susceptibilities near percolative superconductor-insulator transitions.

PubMed

Loh, Yen Lee; Karki, Pragalv

2017-10-25

Coarse-grained superconductor-insulator composites exhibit a superconductor-insulator transition governed by classical percolation, which should be describable by networks of inductors and capacitors. We study several classes of random inductor-capacitor networks on square lattices. We present a unifying framework for defining electric and magnetic response functions, and we extend the Frank-Lobb bond-propagation algorithm to compute these quantities by network reduction. We confirm that the superfluid stiffness scales approximately as [Formula: see text] as the superconducting bond fraction p approaches the percolation threshold p c . We find that the diamagnetic susceptibility scales as [Formula: see text] below percolation, and as [Formula: see text] above percolation. For models lacking self-capacitances, the electric susceptibility scales as [Formula: see text]. Including a self-capacitance on each node changes the critical behavior to approximately [Formula: see text].

An electrical model of vapor-anode, multitube AMTEC cells[Alkali Metal Thermal to Electric Conversion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tournier, J.M.; El-Genk, M.S.

1998-07-01

A two-dimensional electrical model of vapor-anode, multi-tube AMTEC cells was developed, which included four options of current collector configurations. Simulation results of several cells tested at AFRL showed that electrical losses in the current collector networks and the connecting leads were negligible. The polarization/concentration losses in the TiN electrodes were significant, amounting to 25%--50% of the cell theoretical power, while the contact and BASE ionic losses amounted to less than 16% of the cell theoretical power.

Voltage management of distribution networks with high penetration of distributed photovoltaic generation sources

NASA Astrophysics Data System (ADS)

Alyami, Saeed

Installation of photovoltaic (PV) units could lead to great challenges to the existing electrical systems. Issues such as voltage rise, protection coordination, islanding detection, harmonics, increased or changed short-circuit levels, etc., need to be carefully addressed before we can see a wide adoption of this environmentally friendly technology. Voltage rise or overvoltage issues are of particular importance to be addressed for deploying more PV systems to distribution networks. This dissertation proposes a comprehensive solution to deal with the voltage violations in distribution networks, from controlling PV power outputs and electricity consumption of smart appliances in real time to optimal placement of PVs at the planning stage. The dissertation is composed of three parts: the literature review, the work that has already been done and the future research tasks. An overview on renewable energy generation and its challenges are given in Chapter 1. The overall literature survey, motivation and the scope of study are also outlined in the chapter. Detailed literature reviews are given in the rest of chapters. The overvoltage and undervoltage phenomena in typical distribution networks with integration of PVs are further explained in Chapter 2. Possible approaches for voltage quality control are also discussed in this chapter, followed by the discussion on the importance of the load management for PHEVs and appliances and its benefits to electric utilities and end users. A new real power capping method is presented in Chapter 3 to prevent overvoltage by adaptively setting the power caps for PV inverters in real time. The proposed method can maintain voltage profiles below a pre-set upper limit while maximizing the PV generation and fairly distributing the real power curtailments among all the PV systems in the network. As a result, each of the PV systems in the network has equal opportunity to generate electricity and shares the responsibility of voltage regulation. The method does not require global information and can be implemented either under a centralized supervisory control scheme or in a distributed way via consensus control. Chapter 4 investigates autonomous operation schedules for three types of intelligent appliances (or residential controllable loads) without receiving external signals for cost saving and for assisting the management of possible photovoltaic generation systems installed in the same distribution network. The three types of controllable loads studied in the chapter are electric water heaters, refrigerators deicing loads, and dishwashers, respectively. Chapter 5 investigates the method to mitigate overvoltage issues at the planning stage. A probabilistic method is presented in the chapter to evaluate the overvoltage risk in a distribution network with different PV capacity sizes under different load levels. Kolmogorov--Smirnov test (K--S test) is used to identify the most proper probability distributions for solar irradiance in different months. To increase accuracy, an iterative process is used to obtain the maximum allowable injection of active power from PVs. Conclusion and discussions on future work are given in Chapter 6.

Capacitors and Resistance-Capacitance Networks.

ERIC Educational Resources Information Center

Balabanian, Norman; Root, Augustin A.

This programed textbook was developed under a contract with the United States Office of Education as Number 5 in a series of materials for use in an electrical engineering sequence. It is divided into three parts--(1) capacitors, (2) voltage-current relationships, and (3) simple resistance-capacitance networks. (DH)

10 CFR Appendix H to Subpart B of... - Uniform Test Method for Measuring the Power Consumption of Television Sets

Code of Federal Regulations, 2014 CFR

2014-01-01

... connections (e.g., Wi-Fi and Ethernet), the TV shall be configured and connected to a single network source in... Hierarchy Priority Network connection type 1 Wi-Fi (Institution of Electrical and Electronics Engineers—IEEE...

Defining toxicological tipping points in neuronal network development.

PubMed

Frank, Christopher L; Brown, Jasmine P; Wallace, Kathleen; Wambaugh, John F; Shah, Imran; Shafer, Timothy J

2018-02-02

Measuring electrical activity of neural networks by microelectrode array (MEA) has recently shown promise for screening level assessments of chemical toxicity on network development and function. Important aspects of interneuronal communication can be quantified from a single MEA recording, including individual firing rates, coordinated bursting, and measures of network synchrony, providing rich datasets to evaluate chemical effects. Further, multiple recordings can be made from the same network, including during the formation of these networks in vitro. The ability to perform multiple recording sessions over the in vitro development of network activity may provide further insight into developmental effects of neurotoxicants. In the current study, a recently described MEA-based screen of 86 compounds in primary rat cortical cultures over 12 days in vitro was revisited to establish a framework that integrates all available primary measures of electrical activity from MEA recordings into a composite metric for deviation from normal activity (total scalar perturbation). Examining scalar perturbations over time and increasing concentration of compound allowed for definition of critical concentrations or "tipping points" at which the neural networks switched from recovery to non-recovery trajectories for 42 compounds. These tipping point concentrations occurred at predominantly lower concentrations than those causing overt cell viability loss or disrupting individual network parameters, suggesting tipping points may be a more sensitive measure of network functional loss. Comparing tipping points for six compounds with plasma concentrations known to cause developmental neurotoxicity in vivo demonstrated strong concordance and suggests there is potential for using tipping points for chemical prioritization. Published by Elsevier Inc.

Inversion of quasi-3D DC resistivity imaging data using artificial neural networks

NASA Astrophysics Data System (ADS)

Neyamadpour, Ahmad; Wan Abdullah, W. A. T.; Taib, Samsudin

2010-02-01

The objective of this paper is to investigate the applicability of artificial neural networks in inverting quasi-3D DC resistivity imaging data. An electrical resistivity imaging survey was carried out along seven parallel lines using a dipole-dipole array to confirm the validation of the results of an inversion using an artificial neural network technique. The model used to produce synthetic data to train the artificial neural network was a homogeneous medium of 100Ωm resistivity with an embedded anomalous body of 1000Ωm resistivity. The network was trained using 21 datasets (comprising 12159 data points) and tested on another 11 synthetic datasets (comprising 6369 data points) and on real field data. Another 24 test datasets (comprising 13896 data points) consisting of different resistivities for the background and the anomalous bodies were used in order to test the interpolation and extrapolation of network properties. Different learning paradigms were tried in the training process of the neural network, with the resilient propagation paradigm being the most efficient. The number of nodes, hidden layers, and efficient values for learning rate and momentum coefficient have been studied. Although a significant correlation between results of the neural network and the conventional robust inversion technique was found, the ANN results show more details of the subsurface structure, and the RMS misfits for the results of the neural network are less than seen with conventional methods. The interpreted results show that the trained network was able to invert quasi-3D electrical resistivity imaging data obtained by dipole-dipole configuration both rapidly and accurately.

Hardening Software Defined Networks

DTIC Science & Technology

2014-07-01

networks [2, 35] and electrical systems [28, 37, 25]. Effects of cascading have also been modeled in the study of communication networks such as the AS...is necessary to examine both potential failures of the system , and the risks inherent in success. A true end-to-end perspective includes the complete... potential herd immunity) or only local benefit. Club goods theories provide a strong theoretical foundation for determining the importance and risks of

CHIPS. Volume 29, Issue 1, January - March 2011

DTIC Science & Technology

2011-03-01

services, like electricity, heating or cable television. Bank/Finance Fraud: • They may create counterfeit checks using their victim’s name or...consolidating disparate, stove- piped networks into a single, modern, cost-effective enterprise network with a high level of service that meets...Holland, NGEN program manager. “If NMCI is not the most secure network in the world, it is certainly close. There is no shortfall flexibility

Nonlinear inversion of electrical resistivity imaging using pruning Bayesian neural networks

NASA Astrophysics Data System (ADS)

Jiang, Fei-Bo; Dai, Qian-Wei; Dong, Li

2016-06-01

Conventional artificial neural networks used to solve electrical resistivity imaging (ERI) inversion problem suffer from overfitting and local minima. To solve these problems, we propose to use a pruning Bayesian neural network (PBNN) nonlinear inversion method and a sample design method based on the K-medoids clustering algorithm. In the sample design method, the training samples of the neural network are designed according to the prior information provided by the K-medoids clustering results; thus, the training process of the neural network is well guided. The proposed PBNN, based on Bayesian regularization, is used to select the hidden layer structure by assessing the effect of each hidden neuron to the inversion results. Then, the hyperparameter α k , which is based on the generalized mean, is chosen to guide the pruning process according to the prior distribution of the training samples under the small-sample condition. The proposed algorithm is more efficient than other common adaptive regularization methods in geophysics. The inversion of synthetic data and field data suggests that the proposed method suppresses the noise in the neural network training stage and enhances the generalization. The inversion results with the proposed method are better than those of the BPNN, RBFNN, and RRBFNN inversion methods as well as the conventional least squares inversion.

Data-Aware Retrodiction for Asynchronous Harmonic Measurement in a Cyber-Physical Energy System.

PubMed

Liu, Youda; Wang, Xue; Liu, Yanchi; Cui, Sujin

2016-08-18

Cyber-physical energy systems provide a networked solution for safety, reliability and efficiency problems in smart grids. On the demand side, the secure and trustworthy energy supply requires real-time supervising and online power quality assessing. Harmonics measurement is necessary in power quality evaluation. However, under the large-scale distributed metering architecture, harmonic measurement faces the out-of-sequence measurement (OOSM) problem, which is the result of latencies in sensing or the communication process and brings deviations in data fusion. This paper depicts a distributed measurement network for large-scale asynchronous harmonic analysis and exploits a nonlinear autoregressive model with exogenous inputs (NARX) network to reorder the out-of-sequence measuring data. The NARX network gets the characteristics of the electrical harmonics from practical data rather than the kinematic equations. Thus, the data-aware network approximates the behavior of the practical electrical parameter with real-time data and improves the retrodiction accuracy. Theoretical analysis demonstrates that the data-aware method maintains a reasonable consumption of computing resources. Experiments on a practical testbed of a cyber-physical system are implemented, and harmonic measurement and analysis accuracy are adopted to evaluate the measuring mechanism under a distributed metering network. Results demonstrate an improvement of the harmonics analysis precision and validate the asynchronous measuring method in cyber-physical energy systems.

Nanowire mesh solar fuels generator

DOEpatents

Yang, Peidong; Chan, Candace; Sun, Jianwei; Liu, Bin

2016-05-24

This disclosure provides systems, methods, and apparatus related to a nanowire mesh solar fuels generator. In one aspect, a nanowire mesh solar fuels generator includes (1) a photoanode configured to perform water oxidation and (2) a photocathode configured to perform water reduction. The photocathode is in electrical contact with the photoanode. The photoanode may include a high surface area network of photoanode nanowires. The photocathode may include a high surface area network of photocathode nanowires. In some embodiments, the nanowire mesh solar fuels generator may include an ion conductive polymer infiltrating the photoanode and the photocathode in the region where the photocathode is in electrical contact with the photoanode.

ELECTRIC PHASE ANGLE OF CELL MEMBRANES

PubMed Central

Cole, Kenneth S.

1932-01-01

From the theory of an electric network containing any combination of resistances and a single variable impedance element having a constant phase angle independent of frequency, it is shown that the graph of the terminal series reactance against the resistance is an arc of a circle with the position of the center depending upon the phase angle of the variable element. If it be assumed that biological systems are equivalent to such a network, the hypotheses are supported at low and intermediate frequencies by data on red blood cells, muscle, nerve, and potato. For some tissues there is a marked divergence from the circle at high frequencies, which is not interpreted. PMID:19872673

Stochastic methods for analysis of power flow in electric networks

NASA Astrophysics Data System (ADS)

1982-09-01

The modeling and effects of probabilistic behavior on steady state power system operation were analyzed. A solution to the steady state network flow equations which adhere both to Kirchoff's Laws and probabilistic laws, using either combinatorial or functional approximation techniques was obtained. The development of sound techniques for producing meaningful data to serve as input is examined. Electric demand modeling, equipment failure analysis, and algorithm development are investigated. Two major development areas are described: a decomposition of stochastic processes which gives stationarity, ergodicity, and even normality; and a powerful surrogate probability approach using proportions of time which allows the calculation of joint events from one dimensional probability spaces.

Low-Cost, Robust, Threat-Aware Wireless Sensor Network for Assuring the Nation's Energy Infrastructure

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carols H. Rentel

2007-03-31

Eaton, in partnership with Oak Ridge National Laboratory and the Electric Power Research Institute (EPRI) has completed a project that applies a combination of wireless sensor network (WSN) technology, anticipatory theory, and a near-term value proposition based on diagnostics and process uptime to ensure the security and reliability of critical electrical power infrastructure. Representatives of several Eaton business units have been engaged to ensure a viable commercialization plan. Tennessee Valley Authority (TVA), American Electric Power (AEP), PEPCO, and Commonwealth Edison were recruited as partners to confirm and refine the requirements definition from the perspective of the utilities that actually operatemore » the facilities to be protected. Those utilities have cooperated with on-site field tests as the project proceeds. Accomplishments of this project included: (1) the design, modeling, and simulation of the anticipatory wireless sensor network (A-WSN) that will be used to gather field information for the anticipatory application, (2) the design and implementation of hardware and software prototypes for laboratory and field experimentation, (3) stack and application integration, (4) develop installation and test plan, and (5) refinement of the commercialization plan.« less

An open data repository for steady state analysis of a 100-node electricity distribution network with moderate connection of renewable energy sources.

PubMed

Lazarou, Stavros; Vita, Vasiliki; Ekonomou, Lambros

2018-02-01

The data of this article represent a real electricity distribution network on twenty kilovolts (20 kV) at medium voltage level of the Hellenic electricity distribution system [1]. This network has been chosen as suitable for smart grid analysis. It demonstrates moderate penetration of renewable sources and it has capability in part of time for reverse power flows. It is suitable for studies of load aggregation, storage, demand response. It represents a rural line of fifty-five kilometres (55 km) total length, a typical length for this type. It serves forty-five (45) medium to low voltage transformers and twenty-four (24) connections to photovoltaic plants. The total installed load capacity is twelve mega-volt-ampere (12 MVA), however the maximum observed load is lower. The data are ready to perform load flow simulation on Matpower [2] for the maximum observed load power on the half production for renewables. The simulation results and processed data for creating the source code are also provided on the database available at http://dx.doi.org/10.7910/DVN/1I6MKU.

Torsional vibration measurements on rotating shaft system using laser doppler vibrometer

NASA Astrophysics Data System (ADS)

Xiang, Ling; Yang, Shixi; Gan, Chunbiao

2012-11-01

In this work, a laser torsional vibrameter was used to measure the torsion vibration of a rotating shaft system under electrical network impact. Based on the principles of laser Doppler velocimetry, the laser torsional vibrometer (LTV) are non-contact measurement of torsional oscillation of rotating shafts, offering significant advantages over conventional techniques. Furthermore, a highly complex shafting system is analyzed by a modified Riccati torsional transfer matrix. The system is modeled as a chain consisting of an elastic spring with concentrated mass points, and the multi-segments lumped mass model is established for this shafting system. By the modified Riccati torsional transfer matrix method, an accumulated calculation is effectively eliminated to obtain the natural frequencies. The electrical network impacts can activize the torsional vibration of shaft system, and the activized torsion vibration frequencies contained the natural frequencies of shaft system. The torsional vibrations of the shaft system were measured under electrical network impacts in laser Doppler torsional vibrometer. By comparisons, the natural frequencies by measurement were consistent with the values by calculation. The results verify the instrument is robust, user friendly and can be calibrated in situ. The laser torsional vibrometer represents a significant step forward in rotating machinery diagnostics.

Flue gas desulfurization gypsum agricultural network alabama (cotton)

USDA-ARS?s Scientific Manuscript database

Flue gas desulfurization gypsum (FGDG) is an excellent source of gypsum (CaSO4•2H2O) that can be beneficially used in agriculture. Research was conducted as part of the Flue Gas Desulfurization Gypsum Agricultural Network program sponsored by the Electric Power Research Institute in collaboration wi...

Communications and control for electric power systems: Power system stability applications of artificial neural networks

NASA Technical Reports Server (NTRS)

Toomarian, N.; Kirkham, Harold

1994-01-01

This report investigates the application of artificial neural networks to the problem of power system stability. The field of artificial intelligence, expert systems, and neural networks is reviewed. Power system operation is discussed with emphasis on stability considerations. Real-time system control has only recently been considered as applicable to stability, using conventional control methods. The report considers the use of artificial neural networks to improve the stability of the power system. The networks are considered as adjuncts and as replacements for existing controllers. The optimal kind of network to use as an adjunct to a generator exciter is discussed.

The General-Use Nodal Network Solver (GUNNS) Modeling Package for Space Vehicle Flow System Simulation

NASA Technical Reports Server (NTRS)

Harvey, Jason; Moore, Michael

2013-01-01

The General-Use Nodal Network Solver (GUNNS) is a modeling software package that combines nodal analysis and the hydraulic-electric analogy to simulate fluid, electrical, and thermal flow systems. GUNNS is developed by L-3 Communications under the TS21 (Training Systems for the 21st Century) project for NASA Johnson Space Center (JSC), primarily for use in space vehicle training simulators at JSC. It has sufficient compactness and fidelity to model the fluid, electrical, and thermal aspects of space vehicles in real-time simulations running on commodity workstations, for vehicle crew and flight controller training. It has a reusable and flexible component and system design, and a Graphical User Interface (GUI), providing capability for rapid GUI-based simulator development, ease of maintenance, and associated cost savings. GUNNS is optimized for NASA's Trick simulation environment, but can be run independently of Trick.

Three levels of neuroelectronic interfacing: silicon chips with ion channels, nerve cells, and brain tissue.

PubMed

Fromherz, Peter

2006-12-01

We consider the direct electrical interfacing of semiconductor chips with individual nerve cells and brain tissue. At first, the structure of the cell-chip contact is studied. Then we characterize the electrical coupling of ion channels--the electrical elements of nerve cells--with transistors and capacitors in silicon chips. On that basis it is possible to implement signal transmission between microelectronics and the microionics of nerve cells in both directions. Simple hybrid neuroelectronic systems are assembled with neuron pairs and with small neuronal networks. Finally, the interfacing with capacitors and transistors is extended to brain tissue cultured on silicon chips. The application of highly integrated silicon chips allows an imaging of neuronal activity with high spatiotemporal resolution. The goal of the work is an integration of neuronal network dynamics with digital electronics on a microscopic level with respect to experiments in brain research, medical prosthetics, and information technology.

Carbon nanotubes and carbon onions for modification of styrene-acrylate copolymer based nanocomposites

DOE Office of Scientific and Technical Information (OSTI.GOV)

Merijs-Meri, Remo; Zicans, Janis; Ivanova, Tatjana

2014-05-15

Styrene acrylate polymer (SAC) nanocomposites with various carbon nanofillers (multiwalled carbon nanotubes MWCNTs and onion like carbon OLC) are manufactured by means of latex based routes. Concentration of the carbon nanofillers is changed in a broad interval starting from 0.01 up to 10 wt. %. Elastic, dielectric and electromagnetic properties of SAC nanocomposites are investigated. Elastic modulus, electrical conductivity and electromagnetic radiation absorption of the investigated SAC nanocomposites increase along with rising nanofiller content. The effect of the addition of anisometric MWCNTs on the elastic properties of the composite is higher than in the case of the addition of OLC.more » Higher electrical conductivity of the OLC containing nanocomposites is explained with the fact that reasonable agglomeration of the nanofiller can promote the development of electrically conductive network. Efficiency of the absorption of electromagnetic radiation depends on the development of conductive network within the SAC matrix.« less

Lead-acid batteries with polymer-structured electrodes for electric-vehicle applications

NASA Astrophysics Data System (ADS)

Soria, M. L.; Fullea, J.; Sáez, F.; Trinidad, F.

Some years ago a consortium of enterprises and a university from different European countries and industrial sectors was established to work together in the development of lighter lead-acid batteries for electrical and conventional vehicles with new innovative materials and process techniques, with the final goal of increasing the energy density by means of a battery weight reduction. Its main idea was to substitute the heavy lead alloy grids (mechanical support of the active masses and collectors of the current produced during the charge and discharge reactions) by lightweight metallised polymeric network structures (PNS) with reduced mesh dimensions in comparison to conventional grids. The network was then coated with conductive materials and corrosion resistant layers to conduct the current flow. In this paper, the electrode characteristics and the design features of the batteries prepared in the project will be described and their electrical performance presented.

Internal services simulation control in 220/110kV power transformer station Mintia

NASA Astrophysics Data System (ADS)

Ciulica, D.; Rob, R.

2018-01-01

The main objectives in developing the electric transport and distribution networks infrastructure are satisfying the electric energy demand, ensuring the continuity of supply to customers, minimizing electricity losses in the transmission and distribution networks of public interest. This paper presents simulations in functioning of the internal services system 400/230 V ac in the 220/110 kV power transformer station Mintia. Using simulations in Visual Basic, the following premises are taken into consideration. All the ac consumers of the 220/110 kV power transformer station Mintia will be supplied by three 400/230 V transformers for internal services which can mutual reserve. In case of damaging at one transformer, the others are able to assume the entire consumption using automatic release of reserves. The simulation program studies three variants in which the continuity of supply to customers are ensured. As well, by simulations, all the functioning situations are analyzed in detail.

The Intrinsic Electrophysiological Properties of Mammalian Neurons: Insights into Central Nervous System Function

NASA Astrophysics Data System (ADS)

Llinas, Rodolfo R.

1988-12-01

This article reviews the electroresponsive properties of single neurons in the mammalian central nervous system (CNS). In some of these cells the ionic conductances responsible for their excitability also endow them with autorhythmic electrical oscillatory properties. Chemical or electrical synaptic contacts between these neurons often result in network oscillations. In such networks, autorhytmic neurons may act as true oscillators (as pacemakers) or as resonators (responding preferentially to certain firing frequencies). Oscillations and resonance in the CNS are proposed to have diverse functional roles, such as (i) determining global functional states (for example, sleep-wakefulness or attention), (ii) timing in motor coordination, and (iii) specifying connectivity during development. Also, oscillation, especially in the thalamo-cortical circuits, may be related to certain neurological and psychiatric disorders. This review proposes that the autorhythmic electrical properties of central neurons and their connectivity form the basis for an intrinsic functional coordinate system that provides internal context to sensory input.

A gigantically increased ratio of electrical to thermal conductivity and synergistically enhanced thermoelectric properties in interface-controlled TiO2-RGO nanocomposites.

PubMed

Nam, Woo Hyun; Lim, Young Soo; Kim, Woochul; Seo, Hyeon Kook; Dae, Kyun Seong; Lee, Soonil; Seo, Won-Seon; Lee, Jeong Yong

2017-06-14

We report synergistically enhanced thermoelectric properties through the independently controlled charge and thermal transport properties in a TiO 2 -reduced graphene oxide (RGO) nanocomposite. By the consolidation of TiO 2 -RGO hybrid powder using spark plasma sintering, we prepared an interface-controlled TiO 2 -RGO nanocomposite where its grain boundaries are covered with the RGO network. Both the enhancement in electrical conductivity and the reduction in thermal conductivity were simultaneously achieved thanks to the beneficial effects of the RGO network, and detailed mechanisms are discussed. This led to the gigantic increase in the ratio of electrical to thermal conductivity by six orders of magnitude and also the synergistic enhancement in the thermoelectric figure of merit by two orders. Our results present a strategy for the realization of 'phonon-glass electron-crystals' through interface control using graphene in graphene hybrid thermoelectric materials.

Heterogeneous Collaborative Sensor Network for Electrical Management of an Automated House with PV Energy

PubMed Central

Castillo-Cagigal, Manuel; Matallanas, Eduardo; Gutiérrez, Álvaro; Monasterio-Huelin, Félix; Caamaño-Martín, Estefaná; Masa-Bote, Daniel; Jiménez-Leube, Javier

2011-01-01

In this paper we present a heterogeneous collaborative sensor network for electrical management in the residential sector. Improving demand-side management is very important in distributed energy generation applications. Sensing and control are the foundations of the “Smart Grid” which is the future of large-scale energy management. The system presented in this paper has been developed on a self-sufficient solar house called “MagicBox” equipped with grid connection, PV generation, lead-acid batteries, controllable appliances and smart metering. Therefore, there is a large number of energy variables to be monitored that allow us to precisely manage the energy performance of the house by means of collaborative sensors. The experimental results, performed on a real house, demonstrate the feasibility of the proposed collaborative system to reduce the consumption of electrical power and to increase energy efficiency. PMID:22247680

Simple electrical model and initial experiments for intra-body communications.

PubMed

Gao, Y M; Pun, S H; Du, M; Mak, P U; Vai, M I

2009-01-01

Intra-Body Communication(IBC) is a short range "wireless" communication technique appeared in recent years. This technique relies on the conductive property of human tissue to transmit the electric signal among human body. This is beneficial for devices networking and sensors among human body, and especially suitable for wearable sensors, telemedicine system and home health care system as in general the data rates of physiologic parameters are low. In this article, galvanic coupling type IBC application on human limb was investigated in both its mathematical model and related experiments. The experimental results showed that the proposed mathematical model was capable in describing the galvanic coupling type IBC under low frequency. Additionally, the calculated result and experimental result also indicated that the electric signal induced by the transmitters of IBC can penetrate deep into human muscle and thus, provide an evident that IBC is capable of acting as networking technique for implantable devices.

Rational modulation of neuronal processing with applied electric fields.

PubMed

Bikson, Marom; Radman, Thomas; Datta, Abhishek

2006-01-01

Traditional approaches to electrical stimulation, using trains of supra-threshold pulses to trigger action potentials, may be replaced or augmented by using 'rational' sub-threshold stimulation protocols that incorporate knowledge of single neuron geometry, inhomogeneous tissue properties, and nervous system information coding. Sub-threshold stimulation, at intensities (well) below those sufficient to trigger action potentials, may none-the-less exert a profound effect on brain function through modulation of concomitant neuronal activity. For example, small DC fields may coherently polarize a network of neurons and thus modulate the simultaneous processing of afferent synaptic input as well as resulting changes in synaptic plasticity. Through 'activity-dependent plasticity', sub-threshold fields may allow specific targeting of pathological networks and are thus particularly suitable to overcome the poor anatomical focus of noninvasive (transcranial) electrical stimulation. Additional approaches to improve targeting in transcranial stimulation using novel electrode configurations are also introduced.

RBF neural network prediction on weak electrical signals in Aloe vera var. chinensis

NASA Astrophysics Data System (ADS)

Wang, Lanzhou; Zhao, Jiayin; Wang, Miao

2008-10-01

A Gaussian radial base function (RBF) neural network forecast on signals in the Aloe vera var. chinensis by the wavelet soft-threshold denoised as the time series and using the delayed input window chosen at 50, is set up to forecast backward. There was the maximum amplitude at 310.45μV, minimum -75.15μV, average value -2.69μV and <1.5Hz at frequency in Aloe vera var. chinensis respectively. The electrical signal in Aloe vera var. chinensis is a sort of weak, unstable and low frequency signals. A result showed that it is feasible to forecast plant electrical signals for the timing by the RBF. The forecast data can be used as the preferences for the intelligent autocontrol system based on the adaptive characteristic of plants to achieve the energy saving on the agricultural production in the plastic lookum or greenhouse.

Support vector machine for day ahead electricity price forecasting

NASA Astrophysics Data System (ADS)

Razak, Intan Azmira binti Wan Abdul; Abidin, Izham bin Zainal; Siah, Yap Keem; Rahman, Titik Khawa binti Abdul; Lada, M. Y.; Ramani, Anis Niza binti; Nasir, M. N. M.; Ahmad, Arfah binti

2015-05-01

Electricity price forecasting has become an important part of power system operation and planning. In a pool- based electric energy market, producers submit selling bids consisting in energy blocks and their corresponding minimum selling prices to the market operator. Meanwhile, consumers submit buying bids consisting in energy blocks and their corresponding maximum buying prices to the market operator. Hence, both producers and consumers use day ahead price forecasts to derive their respective bidding strategies to the electricity market yet reduce the cost of electricity. However, forecasting electricity prices is a complex task because price series is a non-stationary and highly volatile series. Many factors cause for price spikes such as volatility in load and fuel price as well as power import to and export from outside the market through long term contract. This paper introduces an approach of machine learning algorithm for day ahead electricity price forecasting with Least Square Support Vector Machine (LS-SVM). Previous day data of Hourly Ontario Electricity Price (HOEP), generation's price and demand from Ontario power market are used as the inputs for training data. The simulation is held using LSSVMlab in Matlab with the training and testing data of 2004. SVM that widely used for classification and regression has great generalization ability with structured risk minimization principle rather than empirical risk minimization. Moreover, same parameter settings in trained SVM give same results that absolutely reduce simulation process compared to other techniques such as neural network and time series. The mean absolute percentage error (MAPE) for the proposed model shows that SVM performs well compared to neural network.

Optimization of return electrodes in neurostimulating arrays

NASA Astrophysics Data System (ADS)

Flores, Thomas; Goetz, Georges; Lei, Xin; Palanker, Daniel

2016-06-01

Objective. High resolution visual prostheses require dense stimulating arrays with localized inputs of individual electrodes. We study the electric field produced by multielectrode arrays in electrolyte to determine an optimal configuration of return electrodes and activation sequence. Approach. To determine the boundary conditions for computation of the electric field in electrolyte, we assessed current dynamics using an equivalent circuit of a multielectrode array with interleaved return electrodes. The electric field modeled with two different boundary conditions derived from the equivalent circuit was then compared to measurements of electric potential in electrolyte. To assess the effect of return electrode configuration on retinal stimulation, we transformed the computed electric fields into retinal response using a model of neural network-mediated stimulation. Main results. Electric currents at the capacitive electrode-electrolyte interface redistribute over time, so that boundary conditions transition from equipotential surfaces at the beginning of the pulse to uniform current density in steady state. Experimental measurements confirmed that, in steady state, the boundary condition corresponds to a uniform current density on electrode surfaces. Arrays with local return electrodes exhibit improved field confinement and can elicit stronger network-mediated retinal response compared to those with a common remote return. Connecting local return electrodes enhances the field penetration depth and allows reducing the return electrode area. Sequential activation of the pixels in large monopolar arrays reduces electrical cross-talk and improves the contrast in pattern stimulation. Significance. Accurate modeling of multielectrode arrays helps optimize the electrode configuration to maximize the spatial resolution, contrast and dynamic range of retinal prostheses.

75 FR 33611 - Implementing the National Broadband Plan by Studying the Communications Requirements of Electric...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-06-14

... Requirements of Electric Utilities To Inform Federal Smart Grid Policy AGENCY: Department of Energy. ACTION..., but not limited to, the requirements of the Smart Grid (75 FR 26206). DOE also sought to collect... the types of networks and communications services that may be used for grid modernization...

Neural Network Control of a Parallel Hybrid-Electric Propulsion System for a Small Unmanned Aerial Vehicle

DTIC Science & Technology

2004-01-01

ion battery pack sized for endurance speed. The flexible optimization routine allows relative importance to be assigned between the use of gasoline...simulation results are provided. The two-point conceptual design includes an internal combustion engine sized for cruise and an electric motor and lithium

Alternative Fuels Data Center: EV Charging Stations Spread Through Philly

Science.gov Websites

how Philadelphia fuels electric vehicles with a growing network of public charging stations. For information about this project, contact Eastern Pennsylvania Alliance for Clean Transportation. Download Television Related Videos Photo of a car Electric Vehicles Charge up at State Parks in West Virginia Dec. 9

Parametric analysis of parameters for electrical-load forecasting using artificial neural networks

NASA Astrophysics Data System (ADS)

Gerber, William J.; Gonzalez, Avelino J.; Georgiopoulos, Michael

1997-04-01

Accurate total system electrical load forecasting is a necessary part of resource management for power generation companies. The better the hourly load forecast, the more closely the power generation assets of the company can be configured to minimize the cost. Automating this process is a profitable goal and neural networks should provide an excellent means of doing the automation. However, prior to developing such a system, the optimal set of input parameters must be determined. The approach of this research was to determine what those inputs should be through a parametric study of potentially good inputs. Input parameters tested were ambient temperature, total electrical load, the day of the week, humidity, dew point temperature, daylight savings time, length of daylight, season, forecast light index and forecast wind velocity. For testing, a limited number of temperatures and total electrical loads were used as a basic reference input parameter set. Most parameters showed some forecasting improvement when added individually to the basic parameter set. Significantly, major improvements were exhibited with the day of the week, dew point temperatures, additional temperatures and loads, forecast light index and forecast wind velocity.

Electric-Field-Directed Parallel Alignment Architecting 3D Lithium-Ion Pathways within Solid Composite Electrolyte.

PubMed

Liu, Xueqing; Peng, Sha; Gao, Shuyu; Cao, Yuancheng; You, Qingliang; Zhou, Liyong; Jin, Yongcheng; Liu, Zhihong; Liu, Jiyan

2018-05-09

It is of great significance to seek high-performance solid electrolytes via a facile chemistry and simple process for meeting the requirements of solid batteries. Previous reports revealed that ion conducting pathways within ceramic-polymer composite electrolytes mainly occur at ceramic particles and the ceramic-polymer interface. Herein, one facile strategy toward ceramic particles' alignment and assembly induced by an external alternating-current (AC) electric field is presented. It was manifested by an in situ optical microscope that Li 1.3 Al 0.3 Ti 1.7 (PO 4 ) 3 particles and poly(ethylene glycol) diacrylate in poly(dimethylsiloxane) (LATP@PEGDA@PDMS) assembled into three-dimensional connected networks on applying an external AC electric field. Scanning electron microscopy revealed that the ceramic LATP particles aligned into a necklacelike assembly. Electrochemical impedance spectroscopy confirmed that the ionic conductivity of this necklacelike alignment was significantly enhanced compared to that of the random one. It was demonstrated that this facile strategy of applying an AC electric field can be a very effective approach for architecting three-dimensional lithium-ion conductive networks within solid composite electrolyte.

Quantifying a cellular automata simulation of electric vehicles

NASA Astrophysics Data System (ADS)

Hill, Graeme; Bell, Margaret; Blythe, Phil

2014-12-01

Within this work the Nagel-Schreckenberg (NS) cellular automata is used to simulate a basic cyclic road network. Results from SwitchEV, a real world Electric Vehicle trial which has collected more than two years of detailed electric vehicle data, are used to quantify the results of the NS automata, demonstrating similar power consumption behavior to that observed in the experimental results. In particular the efficiency of the electric vehicles reduces as the vehicle density increases, due in part to the reduced efficiency of EVs at low speeds, but also due to the energy consumption inherent in changing speeds. Further work shows the results from introducing spatially restricted speed restriction. In general it can be seen that induced congestion from spatially transient events propagates back through the road network and alters the energy and efficiency profile of the simulated vehicles, both before and after the speed restriction. Vehicles upstream from the restriction show a reduced energy usage and an increased efficiency, and vehicles downstream show an initial large increase in energy usage as they accelerate away from the speed restriction.

Optimization and control of dynamic percolationin nanostructured silicon oils

NASA Astrophysics Data System (ADS)

Badard, Mathieu; Combessis, Anthony; Allais, Arnaud; Flandin, Lionel

2017-06-01

The addition of carbonaceous fillers in polymers allows the conception of composites with optimized electrical properties. The conductivity of such material depends of the fillers structuration in matrix, especially the presence of percolated network. The objective of this paper is to understand the main aggregation mechanisms of carbon nanotubes in different media. The structuration of these filler network is probed by the use of electrical and dielectrical measurements. The innovative part of our work lies in the use of liquid matrices, especially silicon oils, to overcome mechanical constraints present in polymers on the one hand and to simplify processing on the other hand. Our work has revealed a filler aggregation over time, well known as dynamic percolation. Conductivity has been modeled as a function of time and filler content from Kirkpatrick equation. The further use of an electrical field led to conductivity enhancement as well as a decrease in percolation threshold. Finally, a study of intrinsic parameters of matrix has shown a strong effect of viscosity and surface tension on nanotubes aggregation. Contribution to the topical issue "Electrical Engineering Symposium (SGE 2016)", edited by Adel Razek

Toward the Development of an Artificial Brain on a Micropatterned and Material-Regulated Biochip by Guiding and Promoting the Differentiation and Neurite Outgrowth of Neural Stem/Progenitor Cells.

PubMed

Liu, Yung-Chiang; Lee, I-Chi; Lei, Kin Fong

2018-02-14

An in vitro model mimicking the in vivo environment of the brain must be developed to study neural communication and regeneration and to obtain an understanding of cellular and molecular responses. In this work, a multilayered neural network was successfully constructed on a biochip by guiding and promoting neural stem/progenitor cell differentiation and network formation. The biochip consisted of 3 × 3 arrays of cultured wells connected with channels. Neurospheroids were cultured on polyelectrolyte multilayer (PEM) films in the culture wells. Neurite outgrowth and neural differentiation were guided and promoted by the micropatterns and the PEM films. After 5 days in culture, a 3 × 3 neural network was constructed on the biochip. The function and the connections of the network were evaluated by immunocytochemistry and impedance measurements. Neurons were generated and produced functional and recyclable synaptic vesicles. Moreover, the electrical connections of the neural network were confirmed by measuring the impedance across the neurospheroids. The current work facilitates the development of an artificial brain on a chip for investigations of electrical stimulations and recordings of multilayered neural communication and regeneration.

Research for the Cable Layout Way of the Bypass Operation System in Agricultural Power Supply Network

NASA Astrophysics Data System (ADS)

Niu, Jie; Li, Jinliang; Zou, Dehua; Yang, Qi; Li, Xu; Yan, Yu; Li, Tang

2017-05-01

Non-blackout working of agricultural power supply network is significant to shorten the outage time, decrease the outage loss, and improve the supply reliability and safety. It is impossible to hang the wire rope first and then suspend the cable because of the poor bearing ability of the pole in agricultural power supply network. A kind of new cable arrangement way, its matching tools and the flexible cable that can bear the tension by itself are needed to be put forward and developed. It is necessary to calculate the electric field intensity of the flexible cable to verify that the electric field intensity meets the insulation demand. In this new design, the fiber layer is added into the flexible cable and its maximum tension force is measured to reach to 4000 N. Based on the features of live working in the agricultural power supply network, the new layout way of the cable is proposed; the matching tools and the new flexible cable that can bear the tension by itself are developed as well in this paper. All of the research achievements can give references for the live working of the agricultural power supply network.

Simultaneous and coordinated rotational switching of all molecular rotors in a network

DOE PAGES

Zhang, Y.; Kersell, H.; Stefak, R.; ...

2016-05-09

A range of artificial molecular systems have been created that can exhibit controlled linear and rotational motion. In the development of such systems, a key step is the addition of communication between molecules in a network. Here, we show that a two-dimensional array of dipolar molecular rotors can undergo simultaneous rotational switching by applying an electric field from the tip of a scanning tunnelling microscope. Several hundred rotors made from porphyrin-based double-decker complexes can be simultaneously rotated when in a hexagonal rotor network on a Cu(111) surface by applying biases above ±1 V at 80 K. The phenomenon is observedmore » only in a hexagonal rotor network due to the degeneracy of the ground state dipole rotational energy barrier of the system. Defects are essential to increase electric torque on the rotor network and to stabilize the switched rotor domains. At low biases and low initial rotator angles, slight reorientations of individual rotors can occur resulting in the rotator arms pointing in different directions. In conclusion, analysis reveals that the rotator arm directions here are not random, but are coordinated to minimize energy via cross talk among the rotors through dipolar interactions.« less

Robustness analysis of complex networks with power decentralization strategy via flow-sensitive centrality against cascading failures

NASA Astrophysics Data System (ADS)

Guo, Wenzhang; Wang, Hao; Wu, Zhengping

2018-03-01

Most existing cascading failure mitigation strategy of power grids based on complex network ignores the impact of electrical characteristics on dynamic performance. In this paper, the robustness of the power grid under a power decentralization strategy is analysed through cascading failure simulation based on AC flow theory. The flow-sensitive (FS) centrality is introduced by integrating topological features and electrical properties to help determine the siting of the generation nodes. The simulation results of the IEEE-bus systems show that the flow-sensitive centrality method is a more stable and accurate approach and can enhance the robustness of the network remarkably. Through the study of the optimal flow-sensitive centrality selection for different networks, we find that the robustness of the network with obvious small-world effect depends more on contribution of the generation nodes detected by community structure, otherwise, contribution of the generation nodes with important influence on power flow is more critical. In addition, community structure plays a significant role in balancing the power flow distribution and further slowing the propagation of failures. These results are useful in power grid planning and cascading failure prevention.

Modeling MAC layer for powerline communications networks

NASA Astrophysics Data System (ADS)

Hrasnica, Halid; Haidine, Abdelfatteh

2001-02-01

The usage of electrical power distribution networks for voice and data transmission, called Powerline Communications, becomes nowadays more and more attractive, particularly in the telecommunication access area. The most important reasons for that are the deregulation of the telecommunication market and a fact that the access networks are still property of former monopolistic companies. In this work, first we analyze a PLC network and system structure as well as a disturbance scenario in powerline networks. After that, we define a logical structure of the powerline MAC layer and propose the reservation MAC protocols for the usage in the PLC network which provides collision free data transmission. This makes possible better network utilization and realization of QoS guarantees which can make PLC networks competitive to other access technologies.

Renewable Electricity Futures (Presentation)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mai, T.

2012-08-01

This presentation library summarizes findings of NREL's Renewable Electricity Futures study, published in June 2012. RE Futures investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050. It was presented at the 2012 RE AMP Annual Meeting. RE-AMP is an active network of 144 nonprofits and foundations across eight Midwestern states working on climate change and energy policy with the goal of reducing global warming pollution economy-wide 80% by 2050.

Utilities Power Change: Engaging Commercial Customers in Workplace Charging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lommele, Stephen; Dafoe, Wendy

As stewards of an electric grid that is available almost anywhere people park, utilities that support workplace charging are uniquely positioned to help their commercial customers be a part of the rapidly expanding network of charging infrastructure. Utilities understand the distinctive challenges of their customers, have access to technical information about electrical infrastructure, and have deep experience modeling and managing demand for electricity. This case study highlights the experiences of two utilities with workplace charging programs.

Co-evolution of electric and telecommunications networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rivkin, S.R.

1998-05-01

There are potentially significant societal benefits in co-evolution between electricity and telecommunications in the areas of common infrastructure, accelerated deployment of distributed energy, tighter integration of information flow for energy management and distribution, and improved customer care. With due regard for natural processes that are more potent than any regulation and more real than any ideology, the gains from co-evolution would far outweigh the attenuated and speculative savings from restructuring of electricity that is too simplistic.

Research on Holographic Evaluation of Service Quality in Power Data Network

NASA Astrophysics Data System (ADS)

Wei, Chen; Jing, Tao; Ji, Yutong

2018-01-01

With the rapid development of power data network, the continuous development of the Power data application service system, more and more service systems are being put into operation. Following this, the higher requirements for network quality and service quality are raised, in the actual process for the network operation and maintenance. This paper describes the electricity network and data network services status. A holographic assessment model was presented to achieve a comprehensive intelligence assessment on the power data network and quality of service in the operation and maintenance on the power data network. This evaluation method avoids the problems caused by traditional means which performs a single assessment of network performance quality. This intelligent Evaluation method can improve the efficiency of network operation and maintenance guarantee the quality of real-time service in the power data network..

Blow molding electric drives of Mechanical Engineering

NASA Astrophysics Data System (ADS)

Bukhanov, S. S.; Ramazanov, M. A.; Tsirkunenko, A. T.

2018-03-01

The article considers the questions about the analysis of new possibilities, which gives the use of adjustable electric drives for blowing mechanisms of plastic production. Thus, the use of new semiconductor converters makes it possible not only to compensate the instability of the supply network by using special dynamic voltage regulators, but to improve (correct) the power factor. The calculation of economic efficiency in controlled electric drives of blowing mechanisms is given. On the basis of statistical analysis, the calculation of the reliability parameters of the regulated electric drives’ elements under consideration is given. It is shown that an increase in the reliability of adjustable electric drives is possible both due to overestimation of the electric drive’s installed power, and in simpler schemes with pulse-vector control.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Caruso, M., E-mail: mcaruso@ugr.es; Fanchiotti, H.; Canal, C.A. Garcia

An equivalence between the Schroedinger dynamics of a quantum system with a finite number of basis states and a classical dynamics is presented. The equivalence is an isomorphism that connects in univocal way both dynamical systems. We treat the particular case of neutral kaons and found a class of electric networks uniquely related to the kaon system finding the complete map between the matrix elements of the effective Hamiltonian of kaons and those elements of the classical dynamics of the networks. As a consequence, the relevant {epsilon} parameter that measures CP violation in the kaon system is completely determined inmore » terms of network parameters. - Highlights: > We provide a formal equivalence between classical and quantum dynamics. > We make use of the decomplexification concept. > Neutral kaon systems can be represented by electric circuits. > CP symmetry violation can be taken into account by non-reciprocity. > Non-reciprocity is represented by gyrators.« less

Improving Odometric Accuracy for an Autonomous Electric Cart.

PubMed

Toledo, Jonay; Piñeiro, Jose D; Arnay, Rafael; Acosta, Daniel; Acosta, Leopoldo

2018-01-12

In this paper, a study of the odometric system for the autonomous cart Verdino, which is an electric vehicle based on a golf cart, is presented. A mathematical model of the odometric system is derived from cart movement equations, and is used to compute the vehicle position and orientation. The inputs of the system are the odometry encoders, and the model uses the wheels diameter and distance between wheels as parameters. With this model, a least square minimization is made in order to get the nominal best parameters. This model is updated, including a real time wheel diameter measurement improving the accuracy of the results. A neural network model is used in order to learn the odometric model from data. Tests are made using this neural network in several configurations and the results are compared to the mathematical model, showing that the neural network can outperform the first proposed model.

Network Analysis of Students' Use of Representations in Problem Solving

NASA Astrophysics Data System (ADS)

McPadden, Daryl; Brewe, Eric

2016-03-01

We present the preliminary results of a study on student use of representations in problem solving within the Modeling Instruction - Electricity and Magnetism (MI-E&M) course. Representational competence is a critical skill needed for students to develop a sophisticated understanding of college science topics and to succeed in their science courses. In this study, 70 students from the MI-E&M, calculus-based course were given a survey of 25 physics problem statements both pre- and post- instruction, covering both Newtonian Mechanics and Electricity and Magnetism (E&M). For each problem statement, students were asked which representations they would use in that given situation. We analyze the survey results through network analysis, identifying which representations are linked together in which contexts. We also compare the representation networks for those students who had already taken the first-semester Modeling Instruction Mechanics course and those students who had taken a non-Modeling Mechanics course.

Using graphene networks to build bioinspired self-monitoring ceramics

PubMed Central

Picot, Olivier T.; Rocha, Victoria G.; Ferraro, Claudio; Ni, Na; D'Elia, Eleonora; Meille, Sylvain; Chevalier, Jerome; Saunders, Theo; Peijs, Ton; Reece, Mike J.; Saiz, Eduardo

2017-01-01

The properties of graphene open new opportunities for the fabrication of composites exhibiting unique structural and functional capabilities. However, to achieve this goal we should build materials with carefully designed architectures. Here, we describe the fabrication of ceramic-graphene composites by combining graphene foams with pre-ceramic polymers and spark plasma sintering. The result is a material containing an interconnected, microscopic network of very thin (20–30 nm), electrically conductive, carbon interfaces. This network generates electrical conductivities up to two orders of magnitude higher than those of other ceramics with similar graphene or carbon nanotube contents and can be used to monitor ‘in situ' structural integrity. In addition, it directs crack propagation, promoting stable crack growth and increasing the fracture resistance by an order of magnitude. These results demonstrate that the rational integration of nanomaterials could be a fruitful path towards building composites combining unique mechanical and functional performances. PMID:28181518

Electro-actuated hydrogel walkers with dual responsive legs.

PubMed

Morales, Daniel; Palleau, Etienne; Dickey, Michael D; Velev, Orlin D

2014-03-07

Stimuli responsive polyelectrolyte hydrogels may be useful for soft robotics because of their ability to transform chemical energy into mechanical motion without the use of external mechanical input. Composed of soft and biocompatible materials, gel robots can easily bend and fold, interface and manipulate biological components and transport cargo in aqueous solutions. Electrical fields in aqueous solutions offer repeatable and controllable stimuli, which induce actuation by the re-distribution of ions in the system. Electrical fields applied to polyelectrolyte-doped gels submerged in ionic solution distribute the mobile ions asymmetrically to create osmotic pressure differences that swell and deform the gels. The sign of the fixed charges on the polyelectrolyte network determines the direction of bending, which we harness to control the motion of the gel legs in opposing directions as a response to electrical fields. We present and analyze a walking gel actuator comprised of cationic and anionic gel legs made of copolymer networks of acrylamide (AAm)/sodium acrylate (NaAc) and acrylamide/quaternized dimethylaminoethyl methacrylate (DMAEMA Q), respectively. The anionic and cationic legs were attached by electric field-promoted polyion complexation. We characterize the electro-actuated response of the sodium acrylate hydrogel as a function of charge density and external salt concentration. We demonstrate that "osmotically passive" fixed charges play an important role in controlling the bending magnitude of the gel networks. The gel walkers achieve unidirectional motion on flat elastomer substrates and exemplify a simple way to move and manipulate soft matter devices and robots in aqueous solutions.

Using Reputation Based Trust to Overcome Malfunctions and Malicious Failures in Electric Power Protection Systems

DTIC Science & Technology

2011-09-01

concert with a physical attack. Additionally, the importance of preventive measures implemented by a social human network to counteract a cyber attack...integrity of the data stored on specific computers. This coordinated cyber attack would have been successful if not for the trusted social network...established by Mr. Hillar Aarelaid, head of the Estonian computer 6 emergency response team (CERT). This social network consisted of Mr. Hillar Aarelaid

Tunable microlens arrays using polymer network liquid crystal

NASA Astrophysics Data System (ADS)

Ren, Hongwen; Fan, Yun-Hsing; Gauza, Sebastian; Wu, Shin-Tson

2004-02-01

A tunable-focus microlens array based on polymer network liquid crystal (PNLC) is demonstrated. The PNLC was prepared using an ultraviolet (UV) light exposure through a patterned photomask. The photocurable monomer in each of the UV exposed spot forms an inhomogeneous centro-symmetrical polymer network which acts as a lens when a homogeneous electric field is applied to the cell. The focal length of the microlens arrays is tunable with the applied voltage.

Security-Enhanced Autonomous Network Management

NASA Technical Reports Server (NTRS)

Zeng, Hui

2015-01-01

Ensuring reliable communication in next-generation space networks requires a novel network management system to support greater levels of autonomy and greater awareness of the environment and assets. Intelligent Automation, Inc., has developed a security-enhanced autonomous network management (SEANM) approach for space networks through cross-layer negotiation and network monitoring, analysis, and adaptation. The underlying technology is bundle-based delay/disruption-tolerant networking (DTN). The SEANM scheme allows a system to adaptively reconfigure its network elements based on awareness of network conditions, policies, and mission requirements. Although SEANM is generically applicable to any radio network, for validation purposes it has been prototyped and evaluated on two specific networks: a commercial off-the-shelf hardware test-bed using Institute of Electrical Engineers (IEEE) 802.11 Wi-Fi devices and a military hardware test-bed using AN/PRC-154 Rifleman Radio platforms. Testing has demonstrated that SEANM provides autonomous network management resulting in reliable communications in delay/disruptive-prone environments.

Assessment of foetal exposure to the homogeneous magnetic field harmonic spectrum generated by electricity transmission and distribution networks.

PubMed

Fiocchi, Serena; Liorni, Ilaria; Parazzini, Marta; Ravazzani, Paolo

2015-04-01

During the last decades studies addressing the effects of exposure to Extremely Low Frequency Electromagnetic Fields (ELF-EMF) have pointed out a possible link between those fields emitted by power lines and childhood leukaemia. They have also stressed the importance of also including in the assessment the contribution of frequency components, namely harmonics, other than the fundamental one. Based on the spectrum of supply voltage networks allowed by the European standard for electricity quality assessment, in this study the exposure of high-resolution three-dimensional models of foetuses to the whole harmonic content of a uniform magnetic field with a fundamental frequency of 50 Hz, was assessed. The results show that the main contribution in terms of induced electric fields to the foetal exposure is given by the fundamental frequency component. The harmonic components add some contributions to the overall level of electric fields, however, due to the extremely low permitted amplitude of the harmonic components with respect to the fundamental, their amplitudes are low. The level of the induced electric field is also much lower than the limits suggested by the guidelines for general public exposure, when the amplitude of the incident magnetic field is set at the maximum permitted level.

A cardiac electrical activity model based on a cellular automata system in comparison with neural network model.

PubMed

Khan, Muhammad Sadiq Ali; Yousuf, Sidrah

2016-03-01

Cardiac Electrical Activity is commonly distributed into three dimensions of Cardiac Tissue (Myocardium) and evolves with duration of time. The indicator of heart diseases can occur randomly at any time of a day. Heart rate, conduction and each electrical activity during cardiac cycle should be monitor non-invasively for the assessment of "Action Potential" (regular) and "Arrhythmia" (irregular) rhythms. Many heart diseases can easily be examined through Automata model like Cellular Automata concepts. This paper deals with the different states of cardiac rhythms using cellular automata with the comparison of neural network also provides fast and highly effective stimulation for the contraction of cardiac muscles on the Atria in the result of genesis of electrical spark or wave. The specific formulated model named as "States of automaton Proposed Model for CEA (Cardiac Electrical Activity)" by using Cellular Automata Methodology is commonly shows the three states of cardiac tissues conduction phenomena (i) Resting (Relax and Excitable state), (ii) ARP (Excited but Absolutely refractory Phase i.e. Excited but not able to excite neighboring cells) (iii) RRP (Excited but Relatively Refractory Phase i.e. Excited and able to excite neighboring cells). The result indicates most efficient modeling with few burden of computation and it is Action Potential during the pumping of blood in cardiac cycle.

Assessment of Foetal Exposure to the Homogeneous Magnetic Field Harmonic Spectrum Generated by Electricity Transmission and Distribution Networks

PubMed Central

Fiocchi, Serena; Liorni, Ilaria; Parazzini, Marta; Ravazzani, Paolo

2015-01-01

During the last decades studies addressing the effects of exposure to Extremely Low Frequency Electromagnetic Fields (ELF-EMF) have pointed out a possible link between those fields emitted by power lines and childhood leukaemia. They have also stressed the importance of also including in the assessment the contribution of frequency components, namely harmonics, other than the fundamental one. Based on the spectrum of supply voltage networks allowed by the European standard for electricity quality assessment, in this study the exposure of high-resolution three-dimensional models of foetuses to the whole harmonic content of a uniform magnetic field with a fundamental frequency of 50 Hz, was assessed. The results show that the main contribution in terms of induced electric fields to the foetal exposure is given by the fundamental frequency component. The harmonic components add some contributions to the overall level of electric fields, however, due to the extremely low permitted amplitude of the harmonic components with respect to the fundamental, their amplitudes are low. The level of the induced electric field is also much lower than the limits suggested by the guidelines for general public exposure, when the amplitude of the incident magnetic field is set at the maximum permitted level. PMID:25837346

High Electricity Demand in the Northeast U.S.: PJM Reliability Network and Peaking Unit Impacts on Air Quality.

PubMed

Farkas, Caroline M; Moeller, Michael D; Felder, Frank A; Henderson, Barron H; Carlton, Annmarie G

2016-08-02

On high electricity demand days, when air quality is often poor, regional transmission organizations (RTOs), such as PJM Interconnection, ensure reliability of the grid by employing peak-use electric generating units (EGUs). These "peaking units" are exempt from some federal and state air quality rules. We identify RTO assignment and peaking unit classification for EGUs in the Eastern U.S. and estimate air quality for four emission scenarios with the Community Multiscale Air Quality (CMAQ) model during the July 2006 heat wave. Further, we population-weight ambient values as a surrogate for potential population exposure. Emissions from electricity reliability networks negatively impact air quality in their own region and in neighboring geographic areas. Monitored and controlled PJM peaking units are generally located in economically depressed areas and can contribute up to 87% of hourly maximum PM2.5 mass locally. Potential population exposure to peaking unit PM2.5 mass is highest in the model domain's most populated cities. Average daily temperature and national gross domestic product steer peaking unit heat input. Air quality planning that capitalizes on a priori knowledge of local electricity demand and economics may provide a more holistic approach to protect human health within the context of growing energy needs in a changing world.

An intelligent switch with back-propagation neural network based hybrid power system

NASA Astrophysics Data System (ADS)

Perdana, R. H. Y.; Fibriana, F.

2018-03-01

The consumption of conventional energy such as fossil fuels plays the critical role in the global warming issues. The carbon dioxide, methane, nitrous oxide, etc. could lead the greenhouse effects and change the climate pattern. In fact, 77% of the electrical energy is generated from fossil fuels combustion. Therefore, it is necessary to use the renewable energy sources for reducing the conventional energy consumption regarding electricity generation. This paper presents an intelligent switch to combine both energy resources, i.e., the solar panels as the renewable energy with the conventional energy from the State Electricity Enterprise (PLN). The artificial intelligence technology with the back-propagation neural network was designed to control the flow of energy that is distributed dynamically based on renewable energy generation. By the continuous monitoring on each load and source, the dynamic pattern of the intelligent switch was better than the conventional switching method. The first experimental results for 60 W solar panels showed the standard deviation of the trial at 0.7 and standard deviation of the experiment at 0.28. The second operation for a 900 W of solar panel obtained the standard deviation of the trial at 0.05 and 0.18 for the standard deviation of the experiment. Moreover, the accuracy reached 83% using this method. By the combination of the back-propagation neural network with the observation of energy usage of the load using wireless sensor network, each load can be evenly distributed and will impact on the reduction of conventional energy usage.

Toyota Prius HEV neurocontrol and diagnostics.

PubMed

Prokhorov, Danil V

2008-01-01

A neural network controller for improved fuel efficiency of the Toyota Prius hybrid electric vehicle is proposed. A new method to detect and mitigate a battery fault is also presented. The approach is based on recurrent neural networks and includes the extended Kalman filter. The proposed approach is quite general and applicable to other control systems.

A Network Steganography Lab on Detecting TCP/IP Covert Channels

ERIC Educational Resources Information Center

Zseby, Tanja; Vázquez, Félix Iglesias; Bernhardt, Valentin; Frkat, Davor; Annessi, Robert

2016-01-01

This paper presents a network security laboratory to teach data analysis for detecting TCP/IP covert channels. The laboratory is mainly designed for students of electrical engineering, but is open to students of other technical disciplines with similar background. Covert channels provide a method for leaking data from protected systems, which is a…

A design of wireless sensor networks for a power quality monitoring system.

PubMed

Lim, Yujin; Kim, Hak-Man; Kang, Sanggil

2010-01-01

Power grids deal with the business of generation, transmission, and distribution of electric power. Recently, interest in power quality in electrical distribution systems has increased rapidly. In Korea, the communication network to deliver voltage, current, and temperature measurements gathered from pole transformers to remote monitoring centers employs cellular mobile technology. Due to high cost of the cellular mobile technology, power quality monitoring measurements are limited and data gathering intervals are large. This causes difficulties in providing the power quality monitoring service. To alleviate the problems, in this paper we present a communication infrastructure to provide low cost, reliable data delivery. The communication infrastructure consists of wired connections between substations and monitoring centers, and wireless connections between pole transformers and substations. For the wireless connection, we employ a wireless sensor network and design its corresponding data forwarding protocol to improve the quality of data delivery. For the design, we adopt a tree-based data forwarding protocol in order to customize the distribution pattern of the power quality information. We verify the performance of the proposed data forwarding protocol quantitatively using the NS-2 network simulator.

Skin-Inspired Multifunctional Autonomic-Intrinsic Conductive Self-Healing Hydrogels with Pressure Sensitivity, Stretchability, and 3D Printability.

PubMed

Darabi, Mohammad Ali; Khosrozadeh, Ali; Mbeleck, Rene; Liu, Yuqing; Chang, Qiang; Jiang, Junzi; Cai, Jun; Wang, Quan; Luo, Gaoxing; Xing, Malcolm

2017-08-01

The advent of conductive self-healing (CSH) hydrogels, a class of novel materials mimicking human skin, may change the trajectory of the industrial process because of their potential applications in soft robots, biomimetic prostheses, and health-monitoring systems. Here, the development of a mechanically and electrically self-healing hydrogel based on physically and chemically cross-linked networks is reported. The autonomous intrinsic self-healing of the hydrogel is attained through dynamic ionic interactions between carboxylic groups of poly(acrylic acid) and ferric ions. A covalent cross-linking is used to support the mechanical structure of the hydrogel. Establishing a fair balance between the chemical and physical cross-linking networks together with the conductive nanostructure of polypyrrole networks leads to a double network hydrogel with bulk conductivity, mechanical and electrical self-healing properties (100% mechanical recovery in 2 min), ultrastretchability (1500%), and pressure sensitivity. The practical potential of CSH hydrogels is further revealed by their application in human motion detection and their 3D-printing performance. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Chemical sensors using coated or doped carbon nanotube networks

NASA Technical Reports Server (NTRS)

Li, Jing (Inventor); Meyyappan, Meyya (Inventor)

2010-01-01

Methods for using modified single wall carbon nanotubes ("SWCNTs") to detect presence and/or concentration of a gas component, such as a halogen (e.g., Cl.sub.2), hydrogen halides (e.g., HCl), a hydrocarbon (e.g., C.sub.nH.sub.2n+2), an alcohol, an aldehyde or a ketone, to which an unmodified SWCNT is substantially non-reactive. In a first embodiment, a connected network of SWCNTs is coated with a selected polymer, such as chlorosulfonated polyethylene, hydroxypropyl cellulose, polystyrene and/or polyvinylalcohol, and change in an electrical parameter or response value (e.g., conductance, current, voltage difference or resistance) of the coated versus uncoated SWCNT networks is analyzed. In a second embodiment, the network is doped with a transition element, such as Pd, Pt, Rh, Ir, Ru, Os and/or Au, and change in an electrical parameter value is again analyzed. The parameter change value depends monotonically, not necessarily linearly, upon concentration of the gas component. Two general algorithms are presented for estimating concentration value(s), or upper or lower concentration bounds on such values, from measured differences of response values.

Coated or doped carbon nanotube network sensors as affected by environmental parameters

NASA Technical Reports Server (NTRS)

Li, Jing (Inventor)

2011-01-01

Methods for using modified single wall carbon nanotubes ("SWCNTs") to detect presence and/or concentration of a gas component, such as a halogen (e.g., Cl.sub.2), hydrogen halides (e.g., HCl), a hydrocarbon (e.g., C.sub.nH.sub.2n+2), an alcohol, an aldehyde or a ketone, to which an unmodified SWCNT is substantially non-reactive. In a first embodiment, a connected network of SWCNTs is coated with a selected polymer, such as chlorosulfonated polyethylene, hydroxypropyl cellulose, polystyrene and/or polyvinylalcohol, and change in an electrical parameter or response value (e.g., conductance, current, voltage difference or resistance) of the coated versus uncoated SWCNT networks is analyzed. In a second embodiment, the network is doped with a transition element, such as Pd, Pt, Rh, Ir, Ru, Os and/or Au, and change in an electrical parameter value is again analyzed. The parameter change value depends monotonically, not necessarily linearly, upon concentration of the gas component. Two general algorithms are presented for estimating concentration value(s), or upper or lower concentration bounds on such values, from measured differences of response values.

Impact of electric vehicles on the IEEE 34 node distribution infrastructure

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jiang, Zeming; Shalalfel, Laith; Beshir, Mohammed J.

With the growing penetration of the electric vehicles to our daily life owing to their economic and environmental benefits, there will be both opportunities and challenges to the utilities when adopting plug-in electric vehicles (PEV) to the distribution network. In this study, a thorough analysis based on real-world project is conducted to evaluate the impacts of electric vehicles infrastructure on the grid relating to system load flow, load factor, and voltage stability. IEEE 34 node test feeder was selected and tested along with different case scenarios utilizing the electrical distribution design (EDD) software to find out the potential impacts tomore » the grid.« less

Next Day Price Forecasting in Deregulated Market by Combination of Artificial Neural Network and ARIMA Time Series Models

NASA Astrophysics Data System (ADS)

Areekul, Phatchakorn; Senjyu, Tomonobu; Urasaki, Naomitsu; Yona, Atsushi

Electricity price forecasting is becoming increasingly relevant to power producers and consumers in the new competitive electric power markets, when planning bidding strategies in order to maximize their benefits and utilities, respectively. This paper proposed a method to predict hourly electricity prices for next-day electricity markets by combination methodology of ARIMA and ANN models. The proposed method is examined on the Australian National Electricity Market (NEM), New South Wales regional in year 2006. Comparison of forecasting performance with the proposed ARIMA, ANN and combination (ARIMA-ANN) models are presented. Empirical results indicate that an ARIMA-ANN model can improve the price forecasting accuracy.

Stripe formation in an immiscible polymer blend under electric and shear-flow fields

NASA Astrophysics Data System (ADS)

Na, Yang-Ho; Shibuya, Tetsunori; Ujiie, Seiji; Nagaya, Tomoyuki; Orihara, Hiroshi

2008-04-01

We found a stripe formation in an emulsion of a liquid crystalline polymer (LCP) and a machine oil (OIL) in electric and shear fields. Through the simultaneous measurement with a confocal scanning laser microscope and a rheometer, it was clearly shown that the formation of stripes, which are periodically arrayed, leads to the increase of the shear stress. The droplets, which are one component of the emulsion, start to be connected at low electric fields and then change into the stripes with the increase of electric field. Finally, a three-dimensional network is formed at high electric fields. The period and fluctuation of the stripe structure were also investigated in detail.

Impact of electric vehicles on the IEEE 34 node distribution infrastructure

DOE PAGES

Jiang, Zeming; Shalalfel, Laith; Beshir, Mohammed J.

2014-10-01

With the growing penetration of the electric vehicles to our daily life owing to their economic and environmental benefits, there will be both opportunities and challenges to the utilities when adopting plug-in electric vehicles (PEV) to the distribution network. In this study, a thorough analysis based on real-world project is conducted to evaluate the impacts of electric vehicles infrastructure on the grid relating to system load flow, load factor, and voltage stability. IEEE 34 node test feeder was selected and tested along with different case scenarios utilizing the electrical distribution design (EDD) software to find out the potential impacts tomore » the grid.« less

Percy Thomas wind generator designs

NASA Technical Reports Server (NTRS)

Lines, C. W.

1973-01-01

The technical and economic feasibilities of constructing a windpowered generator with a capacity of 2,000 to 4,000 kilowatt are considered. Possible benefits of an integrated wind generating electric energy source in an electric utility network are elaborated. Applications of a windpowered waterpump, including its use as a pumping source for hydroelectric pump storage operations, are also mentioned. It is concluded that the greatest potential of the wind generator is to generate heat directly and not conversion to electricity and then to heat.

Design and fabrication of a photovoltaic power system for the Papago Indian village of Schuchuli (Gunsight), Arizona

NASA Technical Reports Server (NTRS)

Bifano, W. J.; Ratajczak, A. F.; Ice, W. J.

1978-01-01

A stand alone photovoltaic power system for installation in the Papago Indian village of Schuchuli is being designed and fabricated to provide electricity for village water pumping and basic domestic needs. The system will consist of a 3.5 kW (peak) photovoltaic array; controls, instrumentations, and storage batteries located in an electrical equipment building and a 120 volt dc village distribution network. The system will power a 2 HP dc electric motor.

Improvement of calculation method for electrical parameters of short network of ore-thermal furnaces

NASA Astrophysics Data System (ADS)

Aliferov, A. I.; Bikeev, R. A.; Goreva, L. P.

2017-10-01

The paper describes a new calculation method for active and inductive resistance of split interleaved current leads packages in ore-thermal electric furnaces. The method is developed on basis of regression analysis of dependencies of active and inductive resistances of the packages on their geometrical parameters, mutual disposition and interleaving pattern. These multi-parametric calculations have been performed with ANSYS software. The proposed method allows solving split current lead electrical parameters minimization and balancing problems for ore-thermal furnaces.

Artificial Neural Networks

NASA Technical Reports Server (NTRS)

Niebur, Dagmar

1995-01-01

Electric power systems represent complex systems involving many electrical components whoseoperation has to be planned, analyzed, monitored and controlled. The time-scale of tasks in electricpower systems extends from long term planning years ahead to milliseconds in the area of control. The behavior of power systems is highly non-linear. Monitoring and control involves several hundred variables which are only partly available by measurements.

If it walks like a duck: nanosensor threat assessment

NASA Astrophysics Data System (ADS)

Chachis, George C.

2003-09-01

A convergence of technologies is making deployment of unattended ground nanosensors operationally feasible in terms of energy, communications for both arbitrated and self-organizing distributed, collective behaviors. A number of nano communications technologies are already making network-centric systems possible for MicroElectrical Mechanical (MEM) sensor devices today. Similar technologies may make NanoElectrical Mechanical (NEM) sensor devices operationally feasible a few years from now. Just as organizational behaviors of large numbers of nanodevices can derive strategies from social insects and other group-oriented animals, bio-inspired heuristics for threat assessment provide a conceptual approach for successful integration of nanosensors into unattended smart sensor networks. Biological models such as the organization of social insects or the dynamics of immune systems show promise as biologically-inspired paradigms for protecting nanosensor networks for security scene analysis and battlespace awareness. The paradox of nanosensors is that the smaller the device is the more useful it is but the smaller it is the more vulnerable it is to a variety of threats. In other words simpler means networked nanosensors are more likely to fall prey to a wide-range of attacks including jamming, spoofing, Janisserian recruitment, Pied-Piper distraction, as well as typical attacks computer network security. Thus, unattended sensor technologies call for network architectures that include security and countermeasures to provide reliable scene analysis or battlespace awareness information. Such network centric architectures may well draw upon a variety of bio-inspired approaches to safeguard, validate and make sense of large quantities of information.

Optimal Resource Allocation in Electrical Network Defense

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yao, Y; Edmunds, T; Papageorgiou, D

2004-01-15

Infrastructure networks supplying electricity, natural gas, water, and other commodities are at risk of disruption due to well-engineered and coordinated terrorist attacks. Countermeasures such as hardening targets, acquisition of spare critical components, and surveillance can be undertaken to detect and deter these attacks. Allocation of available countermeasures resources to sites or activities in a manner that maximizes their effectiveness is a challenging problem. This allocation must take into account the adversary's response after the countermeasure assets are in place and consequence mitigation measures the infrastructure operation can undertake after the attack. The adversary may simply switch strategies to avoid countermeasuresmore » when executing the attack. Stockpiling spares of critical energy infrastructure components has been identified as a key element of a grid infrastructure defense strategy in a recent National Academy of Sciences report [1]. Consider a scenario where an attacker attempts to interrupt the service of an electrical network by disabling some of its facilities while a defender wants to prevent or minimize the effectiveness of any attack. The interaction between the attacker and the defender can be described in three stages: (1) The defender deploys countermeasures, (2) The attacker disrupts the network, and (3) The defender responds to the attack by rerouting power to maintain service while trying to repair damage. In the first stage, the defender considers all possible attack scenarios and deploys countermeasures to defend against the worst scenarios. Countermeasures can include hardening targets, acquiring spare critical components, and installing surveillance devices. In the second stage, the attacker, with full knowledge of the deployed countermeasures, attempts to disable some nodes or links in the network to inflict the greatest loss on the defender. In the third stage, the defender re-dispatches power and restores disabled nodes or links to minimize the loss. The loss can be measured in costs, including the costs of using more expensive generators and the economic losses that can be attributed to loss of load. The defender's goal is to minimize the loss while the attacker wants to maximize it. Assuming some level of budget constraint, each side can only defend or attack a limited number of network elements. When an element is attacked, it is assumed that it will be totally disabled. It is assumed that when an element is defended it cannot be disabled, which may mean that it will be restored in a very short time after being attacked. The rest of the paper is organized as follows. Section 2 will briefly review literature related to multilevel programming and network defense. Section 3 presents a mathematical formulation of the electrical network defense problem. Section 4 describes the solution algorithms. Section 5 discusses computational results. Finally, Sec. 6 explores future research directions.« less

Gestion de stockage d'energie thermique d'un parc de chauffe-eaux par une commande a champ moyen

NASA Astrophysics Data System (ADS)

Bourdel, Benoit

In today's energy transition, smart grids and electrical load control are very active research fields. This master's thesis is an offshoot of the SmartDesc project which aims at using energy storage capability of electric household appliances, such as water heaters and electric heaters to mitigate the fluctuations of system loads and renewable generation. The smartDESC project aims at demonstrating that the mean field game theory (MFG), as new mathematical theory, can be used to convert and control water heaters (and possibly space heater) into smart thermal capacities. Thus, a set of "modules" has been developed. These modules are used to generate the optimal control and locally interpret it, to simulate the water-heater thermophysics or water draw event, or to virtualize a telecommunication mesh network. The different aspects of the project have been first studied and developed separately. During the course of this master's research, the modules have been integrated, tested, interfaced and tuned in a common simulator. This simulator is designed to make complete electrical network simulations with a multi-scale approach (from individual water heater to global electric load and production). Firstly, the modules are precisely described theoretically and practically. Then, different types of control are applied to an uniform population of houses fitted with water heaters and controllers. The results of these controls are analysed and compared in order to understand their strengths and weaknesses. Finally, a study was conducted to analyse the resilience of a mean field control. This report demonstrates that mean field game theory in coordination with a system level aggregate model based optimization program, is able to effectively control a large population of water heaters to smooth the overall electrical load. This control offers good resilience to unforeseen circumstances that can disrupt the network. It is also demonstrated that a mean field control is able to absorb fluctuations due to wind power production. Thus, by reducing the variability of the residential sector's electrical charge, the mean field control plays a role in increasing power system stability in the face of high levels of renewable energy penetration. The next stage of smartDESC project is now to set up an intelligent electric water heater prototype. This prototype, in progress since January 2016 at Ecole Polytechnique in Montreal, is aimed at proving concretely the theories developed in the project.

Data-Aware Retrodiction for Asynchronous Harmonic Measurement in a Cyber-Physical Energy System

PubMed Central

Liu, Youda; Wang, Xue; Liu, Yanchi; Cui, Sujin

2016-01-01

Cyber-physical energy systems provide a networked solution for safety, reliability and efficiency problems in smart grids. On the demand side, the secure and trustworthy energy supply requires real-time supervising and online power quality assessing. Harmonics measurement is necessary in power quality evaluation. However, under the large-scale distributed metering architecture, harmonic measurement faces the out-of-sequence measurement (OOSM) problem, which is the result of latencies in sensing or the communication process and brings deviations in data fusion. This paper depicts a distributed measurement network for large-scale asynchronous harmonic analysis and exploits a nonlinear autoregressive model with exogenous inputs (NARX) network to reorder the out-of-sequence measuring data. The NARX network gets the characteristics of the electrical harmonics from practical data rather than the kinematic equations. Thus, the data-aware network approximates the behavior of the practical electrical parameter with real-time data and improves the retrodiction accuracy. Theoretical analysis demonstrates that the data-aware method maintains a reasonable consumption of computing resources. Experiments on a practical testbed of a cyber-physical system are implemented, and harmonic measurement and analysis accuracy are adopted to evaluate the measuring mechanism under a distributed metering network. Results demonstrate an improvement of the harmonics analysis precision and validate the asynchronous measuring method in cyber-physical energy systems. PMID:27548171

Neural electrical activity and neural network growth.

PubMed

Gafarov, F M

2018-05-01

The development of central and peripheral neural system depends in part on the emergence of the correct functional connectivity in its input and output pathways. Now it is generally accepted that molecular factors guide neurons to establish a primary scaffold that undergoes activity-dependent refinement for building a fully functional circuit. However, a number of experimental results obtained recently shows that the neuronal electrical activity plays an important role in the establishing of initial interneuronal connections. Nevertheless, these processes are rather difficult to study experimentally, due to the absence of theoretical description and quantitative parameters for estimation of the neuronal activity influence on growth in neural networks. In this work we propose a general framework for a theoretical description of the activity-dependent neural network growth. The theoretical description incorporates a closed-loop growth model in which the neural activity can affect neurite outgrowth, which in turn can affect neural activity. We carried out the detailed quantitative analysis of spatiotemporal activity patterns and studied the relationship between individual cells and the network as a whole to explore the relationship between developing connectivity and activity patterns. The model, developed in this work will allow us to develop new experimental techniques for studying and quantifying the influence of the neuronal activity on growth processes in neural networks and may lead to a novel techniques for constructing large-scale neural networks by self-organization. Copyright © 2018 Elsevier Ltd. All rights reserved.

Lithographically fabricated gold nanowire waveguides for plasmonic routers and logic gates.

PubMed

Gao, Long; Chen, Li; Wei, Hong; Xu, Hongxing

2018-06-14

Fabricating plasmonic nanowire waveguides and circuits by lithographic fabrication methods is highly desired for nanophotonic circuitry applications. Here we report an approach for fabricating metal nanowire networks by using electron beam lithography and metal film deposition techniques. The gold nanowire structures are fabricated on quartz substrates without using any adhesion layer but coated with a thin layer of Al2O3 film for immobilization. The thermal annealing during the Al2O3 deposition process decreases the surface plasmon loss. In a Y-shaped gold nanowire network, the surface plasmons can be routed to different branches by controlling the polarization of the excitation light, and the routing behavior is dependent on the length of the main nanowire. Simulated electric field distributions show that the zigzag distribution of the electric field in the nanowire network determines the surface plasmon routing. By using two laser beams to excite surface plasmons in a Y-shaped nanowire network, the output intensity can be modulated by the interference of surface plasmons, which can be used to design Boolean logic gates. We experimentally demonstrate that AND, OR, XOR and NOT gates can be realized in three-terminal nanowire networks, and NAND, NOR and XNOR gates can be realized in four-terminal nanowire networks. This work takes a step toward the fabrication of on-chip integrated plasmonic circuits.

Evaluation of Pump Pulsation in Respirable Size-Selective Sampling: Part III. Investigation of European Standard Methods

PubMed Central

Soo, Jhy-Charm; Lee, Eun Gyung; Lee, Larry A.; Kashon, Michael L.; Harper, Martin

2015-01-01

Lee et al. (Evaluation of pump pulsation in respirable size-selective sampling: part I. Pulsation measurements. Ann Occup Hyg 2014a;58:60–73) introduced an approach to measure pump pulsation (PP) using a real-world sampling train, while the European Standards (EN) (EN 1232-1997 and EN 12919-1999) suggest measuring PP using a resistor in place of the sampler. The goal of this study is to characterize PP according to both EN methods and to determine the relationship of PP between the published method (Lee et al., 2014a) and the EN methods. Additional test parameters were investigated to determine whether the test conditions suggested by the EN methods were appropriate for measuring pulsations. Experiments were conducted using a factorial combination of personal sampling pumps (six medium- and two high-volumetric flow rate pumps), back pressures (six medium- and seven high-flow rate pumps), resistors (two types), tubing lengths between a pump and resistor (60 and 90 cm), and different flow rates (2 and 2.5 l min−1 for the medium- and 4.4, 10, and 11.2 l min−1 for the high-flow rate pumps). The selection of sampling pumps and the ranges of back pressure were based on measurements obtained in the previous study (Lee et al., 2014a). Among six medium-flow rate pumps, only the Gilian5000 and the Apex IS conformed to the 10% criterion specified in EN 1232-1997. Although the AirChek XR5000 exceeded the 10% limit, the average PP (10.9%) was close to the criterion. One high-flow rate pump, the Legacy (PP = 8.1%), conformed to the 10% criterion in EN 12919-1999, while the Elite12 did not (PP = 18.3%). Conducting supplemental tests with additional test parameters beyond those used in the two subject EN standards did not strengthen the characterization of PPs. For the selected test conditions, a linear regression model [PPEN = 0.014 + 0.375 × PPNIOSH (adjusted R2 = 0.871)] was developed to determine the PP relationship between the published method (Lee et al., 2014a) and the EN methods. The 25% PP criterion recommended by Lee et al. (2014a), average value derived from repetitive measurements, corresponds to 11% PPEN. The 10% pass/fail criterion in the EN Standards is not based on extensive laboratory evaluation and would unreasonably exclude at least one pump (i.e. AirChek XR5000 in this study) and, therefore, the more accurate criterion of average 11% from repetitive measurements should be substituted. This study suggests that users can measure PP using either a real-world sampling train or a resistor setup and obtain equivalent findings by applying the model herein derived. The findings of this study will be delivered to the consensus committees to be considered when those standards, including the EN 1232-1997, EN 12919-1999, and ISO 13137-2013, are revised. PMID:25053700

Flowable Conducting Particle Networks in Redox-Active Electrolytes for Grid Energy Storage

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hatzell, K. B.; Boota, M.; Kumbur, E. C.

2015-01-01

This study reports a new hybrid approach toward achieving high volumetric energy and power densities in an electrochemical flow capacitor for grid energy storage. The electrochemical flow capacitor suffers from high self-discharge and low energy density because charge storage is limited to the available surface area (electric double layer charge storage). Here, we examine two carbon materials as conducting particles in a flow battery electrolyte containing the VO2+/VO2+ redox couple. Highly porous activated carbon spheres (CSs) and multi-walled carbon nanotubes (MWCNTs) are investigated as conducting particle networks that facilitate both faradaic and electric double layer charge storage. Charge storage contributionsmore » (electric double layer and faradaic) are distinguished for flow-electrodes composed of MWCNTs and activated CSs. A MWCNT flow-electrode based in a redox-active electrolyte containing the VO2+/VO2+ redox couple demonstrates 18% less self-discharge, 10 X more energy density, and 20 X greater power densities (at 20 mV s-1) than one based on a non-redox active electrolyte. Furthermore, a MWCNT redox-active flow electrode demonstrates 80% capacitance retention, and >95% coulombic efficiency over 100 cycles, indicating the feasibility of utilizing conducting networks with redox chemistries for grid energy storage.« less

Neuromodulation: Selected approaches and challenges

PubMed Central

Parpura, Vladimir; Silva, Gabriel A.; Tass, Peter A.; Bennet, Kevin E.; Meyyappan, Meyya; Koehne, Jessica; Lee, Kendall H.; Andrews, Russell J.

2012-01-01

The brain operates through complex interactions in the flow of information and signal processing within neural networks. The “wiring” of such networks, being neuronal or glial, can physically and/or functionally go rogue in various pathological states. Neuromodulation, as a multidisciplinary venture, attempts to correct such faulty nets. In this review, selected approaches and challenges in neuromoduation are discussed. The use of water-dispersible carbon nanotubes have proven effective in modulation of neurite outgrowth in culture as well as in aiding regeneration after spinal cord injury in vivo. Studying neural circuits using computational biology and analytical engineering approaches brings to light geometrical mapping of dynamics within neural networks, much needed information for stimulation interventions in medical practice. Indeed, sophisticated desynchronization approaches used for brain stimulation have been successful in coaxing “misfiring” neuronal circuits to resume productive firing patterns in various human disorders. Devices have been developed for the real time measurement of various neurotransmitters as well as electrical activity in the human brain during electrical deep brain stimulation. Such devices can establish the dynamics of electrochemical changes in the brain during stimulation. With increasing application of nanomaterials in devices for electrical and chemical recording and stimulating in the brain, the era of cellular, and even intracellular, precision neuromodulation will soon be upon us. PMID:23190025

Flowable conducting particle networks in redox-active electrolytes for grid energy storage

DOE PAGES

Hatzell, K. B.; Boota, M.; Kumbur, E. C.; ...

2015-01-09

This paper reports a new hybrid approach toward achieving high volumetric energy and power densities in an electrochemical flow capacitor for grid energy storage. The electrochemical flow capacitor suffers from high self-discharge and low energy density because charge storage is limited to the available surface area (electric double layer charge storage). Here, we examine two carbon materials as conducting particles in a flow battery electrolyte containing the VO 2+/VO 2 + redox couple. Highly porous activated carbon spheres (CSs) and multi-walled carbon nanotubes (MWCNTs) are investigated as conducting particle networks that facilitate both faradaic and electric double layer charge storage.more » Charge storage contributions (electric double layer and faradaic) are distinguished for flow-electrodes composed of MWCNTs and activated CSs. A MWCNT flow-electrode based in a redox-active electrolyte containing the VO 2+/VO 2 + redox couple demonstrates 18% less self-discharge, 10 X more energy density, and 20 X greater power densities (at 20 mV s -1) than one based on a non-redox active electrolyte. Additionally, a MWCNT redox-active flow electrode demonstrates 80% capacitance retention, and >95% coulombic efficiency over 100 cycles, indicating the feasibility of utilizing conducting networks with redox chemistries for grid energy storage.« less

Degradable transportation network with the addition of electric vehicles: Network equilibrium analysis

PubMed Central

Zhang, Rui; Yao, Enjian; Yang, Yang

2017-01-01

Introducing electric vehicles (EVs) into urban transportation network brings higher requirement on travel time reliability and charging reliability. Specifically, it is believed that travel time reliability is a key factor influencing travelers’ route choice. Meanwhile, due to the limited cruising range, EV drivers need to better learn about the required energy for the whole trip to make decisions about whether charging or not and where to charge (i.e., charging reliability). Since EV energy consumption is highly related to travel speed, network uncertainty affects travel time and charging demand estimation significantly. Considering the network uncertainty resulted from link degradation, which influences the distribution of travel demand on transportation network and the energy demand on power network, this paper aims to develop a reliability-based network equilibrium framework for accommodating degradable road conditions with the addition of EVs. First, based on the link travel time distribution, the mean and variance of route travel time and monetary expenses related to energy consumption are deduced, respectively. And the charging time distribution of EVs with charging demand is also estimated. Then, a nested structure is considered to deal with the difference of route choice behavior derived by the different uncertainty degrees between the routes with and without degradable links. Given the expected generalized travel cost and a psychological safety margin, a traffic assignment model with the addition of EVs is formulated. Subsequently, a heuristic solution algorithm is developed to solve the proposed model. Finally, the effects of travelers’ risk attitude, network degradation degree, and EV penetration rate on network performance are illustrated through an example network. The numerical results show that the difference of travelers’ risk attitudes does have impact on the route choice, and the widespread adoption of EVs can cut down the total system travel cost effectively when the transportation network is more reliable. PMID:28886167

Degradable transportation network with the addition of electric vehicles: Network equilibrium analysis.

PubMed

Zhang, Rui; Yao, Enjian; Yang, Yang

2017-01-01

Introducing electric vehicles (EVs) into urban transportation network brings higher requirement on travel time reliability and charging reliability. Specifically, it is believed that travel time reliability is a key factor influencing travelers' route choice. Meanwhile, due to the limited cruising range, EV drivers need to better learn about the required energy for the whole trip to make decisions about whether charging or not and where to charge (i.e., charging reliability). Since EV energy consumption is highly related to travel speed, network uncertainty affects travel time and charging demand estimation significantly. Considering the network uncertainty resulted from link degradation, which influences the distribution of travel demand on transportation network and the energy demand on power network, this paper aims to develop a reliability-based network equilibrium framework for accommodating degradable road conditions with the addition of EVs. First, based on the link travel time distribution, the mean and variance of route travel time and monetary expenses related to energy consumption are deduced, respectively. And the charging time distribution of EVs with charging demand is also estimated. Then, a nested structure is considered to deal with the difference of route choice behavior derived by the different uncertainty degrees between the routes with and without degradable links. Given the expected generalized travel cost and a psychological safety margin, a traffic assignment model with the addition of EVs is formulated. Subsequently, a heuristic solution algorithm is developed to solve the proposed model. Finally, the effects of travelers' risk attitude, network degradation degree, and EV penetration rate on network performance are illustrated through an example network. The numerical results show that the difference of travelers' risk attitudes does have impact on the route choice, and the widespread adoption of EVs can cut down the total system travel cost effectively when the transportation network is more reliable.

Precise time and time interval applications to electric power systems

NASA Technical Reports Server (NTRS)

Wilson, Robert E.

1992-01-01

There are many applications of precise time and time interval (frequency) in operating modern electric power systems. Many generators and customer loads are operated in parallel. The reliable transfer of electrical power to the consumer partly depends on measuring power system frequency consistently in many locations. The internal oscillators in the widely dispersed frequency measuring units must be syntonized. Elaborate protection and control systems guard the high voltage equipment from short and open circuits. For the highest reliability of electric service, engineers need to study all control system operations. Precise timekeeping networks aid in the analysis of power system operations by synchronizing the clocks on recording instruments. Utility engineers want to reproduce events that caused loss of service to customers. Precise timekeeping networks can synchronize protective relay test-sets. For dependable electrical service, all generators and large motors must remain close to speed synchronism. The stable response of a power system to perturbations is critical to continuity of electrical service. Research shows that measurement of the power system state vector can aid in the monitoring and control of system stability. If power system operators know that a lightning storm is approaching a critical transmission line or transformer, they can modify operating strategies. Knowledge of the location of a short circuit fault can speed the re-energizing of a transmission line. One fault location technique requires clocks synchronized to one microsecond. Current research seeks to find out if one microsecond timekeeping can aid and improve power system control and operation.

Transient Response of a Second Order System Using State Variables.

ERIC Educational Resources Information Center

LePage, Wilbur R.

This programed booklet is designed for the engineering student who is familiar with the techniques of integral calculus and electrical networks. The booklet teaches how to determine the current and voltages across a resistor, inductor, and capacitor after the switch in a network has been closed. This is a classical problem in engineering, the…

Organic memristive device as key element for neuromorphic networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Erokhin, Victor

Organic memristive device has three important properties allowing to consider it as a key element of neuromorphic systems. First, its electrical properties are somehow similar to those of synapses. Second, it can be easily transferred into an oscillator. Third, organic nature of the devices allow to assemble them into stochastic 3D networks capable to learning and adaptations.

Electrically Reconfigurable Liquid Crystalline Mirrors (Postprint)

DTIC Science & Technology

2018-04-24

preparation of a structurally chiral polymer stabilizing network that enforces anchoring of a low-molar- mass liquid crystalline media with positive...crystals (LCs). The distinctive responses detailed here are enabled by the preparation of a structurally chiral polymer stabilizing network that enforces ...aerospace systems . Dynamic changes to optical material properties including absorption, diffraction, reflection, and scatter have been the subject to

Shipboard Calibration Network Extension Utilizing COTS Products

DTIC Science & Technology

2014-09-01

to emulate the MCS system console. C. KEYBOARD VIDEO AND MOUSE (KVM) SWITCH A ServSwitch Wizard IP Plus KVM switch is used to allow remote access...9 C. KEYBOARD VIDEO AND MOUSE (KVM) SWITCH .......................... 10 D. ROUTER...mechanical, and electrical KVM Keyboard Video and Mouse LAN Local Area Network MCS Machinery Control Systems NIST National Institute of Standards and

Three-Dimensional Networked Metal-Organic Frameworks with Conductive Polypyrrole Tubes for Flexible Supercapacitors.

PubMed

Xu, Xingtao; Tang, Jing; Qian, Huayu; Hou, Shujin; Bando, Yoshio; Hossain, Md Shahriar A; Pan, Likun; Yamauchi, Yusuke

2017-11-08

Metal-organic frameworks (MOFs) with high porosity and a regular porous structure have emerged as a promising electrode material for supercapacitors, but their poor electrical conductivity limits their utilization efficiency and capacitive performance. To increase the overall electrical conductivity as well as the efficiency of MOF particles, three-dimensional networked MOFs are developed via using preprepared conductive polypyrrole (PPy) tubes as the support for in situ growth of MOF particles. As a result, the highly conductive PPy tubes that run through the MOF particles not only increase the electron transfer between MOF particles and maintain the high effective porosity of the MOFs but also endow the MOFs with flexibility. Promoted by such elaborately designed MOF-PPy networks, the specific capacitance of MOF particles has been increased from 99.2 F g -1 for pristine zeolitic imidazolate framework (ZIF)-67 to 597.6 F g -1 for ZIF-PPy networks, indicating the importance of the design of the ZIF-PPy continuous microstructure. Furthermore, a flexible supercapacitor device based on ZIF-PPy networks shows an outstanding areal capacitance of 225.8 mF cm -2 , which is far above other MOFs-based supercapacitors reported up to date, confirming the significance of in situ synthetic chemistry as well as the importance of hybrid materials on the nanoscale.

Harnessing Electrostatic Forces to Grow Bio-inspired Hierarchical Vascular Networks

NASA Astrophysics Data System (ADS)

Behler, Kristopher; Melrose, Zachary; Schott, Andrew; Wetzel, Eric

2012-02-01

Vascular networks provide a system for fluid distribution. Artificial vascular materials with enhanced properties are currently being developed that could ultimately be integrated into systems reliant upon fluid transport while retaining their structural properties. An uninterrupted and controllable supply of liquid is optimal for many applications such as continual self-healing materials, in-situ delivery of index matched fluids, thermal management and drug delivery systems could benefit from a bio-inspired vascular approach that combines complex network geometries with minimal processing parameters. Two such approaches to induce vascular networks are electrohydrodynamic viscous fingering (EHVF) and electrical treeing (ET). EHVF is a phenomenon that occurs when a low viscosity liquid is forced through a high viscosity fluid or matrix, resulting in branches due to capillary and viscous forces in the high viscosity material. By applying voltages of 0 -- 60 kV, finger diameter is reduced. ET is the result of partial discharges in a dielectric material. In the vicinity of a small diameter electrode, the local electric field is greater than the global dielectric strength, causing a localized, step-wise, breakdown to occur forming a highly branched interconnected structure. ET is a viable method to produce networks on a smaller, micron, scale than the products of the EHVF method.

Development of network-based multichannel neuromuscular electrical stimulation system for stroke rehabilitation.

PubMed

Qu, Hongen; Xie, Yongji; Liu, Xiaoxuan; He, Xin; Hao, Manzhao; Bao, Yong; Xie, Qing; Lan, Ning

2016-01-01

Neuromuscular electrical stimulation (NMES) is a promising assistive technology for stroke rehabilitation. Here we present the design and development of a multimuscle stimulation system as an emerging therapy for people with paretic stroke. A network-based multichannel NMES system was integrated based on dual bus architecture of communication and an H-bridge current regulator with a power booster. The structure of the system was a body area network embedded with multiple stimulators and a communication protocol of controlled area network to transmit muscle stimulation parameter information to individual stimulators. A graphical user interface was designed to allow clinicians to specify temporal patterns and muscle stimulation parameters. We completed and tested a prototype of the hardware and communication software modules of the multichannel NMES system. The prototype system was first verified in nondisabled subjects for safety, and then tested in subjects with stroke for feasibility with assisting multijoint movements. Results showed that synergistic stimulation of multiple muscles in subjects with stroke improved performance of multijoint movements with more natural velocity profiles at elbow and shoulder and reduced acromion excursion due to compensatory trunk rotation. The network-based NMES system may provide an innovative solution that allows more physiological activation of multiple muscles in multijoint task training for patients with stroke.

Simulation of Electromigration Based on Resistor Networks

NASA Astrophysics Data System (ADS)

Patrinos, Anthony John

A two dimensional computer simulation of electromigration based on resistor networks was designed and implemented. The model utilizes a realistic grain structure generated by the Monte Carlo method and takes specific account of the local effects through which electromigration damage progresses. The dynamic evolution of the simulated thin film is governed by the local current and temperature distributions. The current distribution is calculated by superimposing a two dimensional electrical network on the lattice whose nodes correspond to the particles in the lattice and the branches to interparticle bonds. Current is assumed to flow from site to site via nearest neighbor bonds. The current distribution problem is solved by applying Kirchhoff's rules on the resulting electrical network. The calculation of the temperature distribution in the lattice proceeds by discretizing the partial differential equation for heat conduction, with appropriate material parameters chosen for the lattice and its defects. SEReNe (for Simulation of Electromigration using Resistor Networks) was tested by applying it to common situations arising in experiments with real films with satisfactory results. Specifically, the model successfully reproduces the expected grain size, line width and bamboo effects, the lognormal failure time distribution and the relationship between current density exponent and current density. It has also been modified to simulate temperature ramp experiments but with mixed, in this case, results.

Autonomous, Decentralized Grid Architecture: Prosumer-Based Distributed Autonomous Cyber-Physical Architecture for Ultra-Reliable Green Electricity Networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

None

2012-01-11

GENI Project: Georgia Tech is developing a decentralized, autonomous, internet-like control architecture and control software system for the electric power grid. Georgia Tech’s new architecture is based on the emerging concept of electricity prosumers—economically motivated actors that can produce, consume, or store electricity. Under Georgia Tech’s architecture, all of the actors in an energy system are empowered to offer associated energy services based on their capabilities. The actors achieve their sustainability, efficiency, reliability, and economic objectives, while contributing to system-wide reliability and efficiency goals. This is in marked contrast to the current one-way, centralized control paradigm.

A Review of Control Strategy of the Large-scale of Electric Vehicles Charging and Discharging Behavior

NASA Astrophysics Data System (ADS)

Kong, Lingyu; Han, Jiming; Xiong, Wenting; Wang, Hao; Shen, Yaqi; Li, Ying

2017-05-01

Large scale access of electric vehicles will bring huge challenges to the safe operation of the power grid, and it’s important to control the charging and discharging of the electric vehicle. First of all, from the electric quality and network loss, this paper points out the influence on the grid caused by electric vehicle charging behaviour. Besides, control strategy of electric vehicle charging and discharging has carried on the induction and the summary from the direct and indirect control. Direct control strategy means control the electric charging behaviour by controlling its electric vehicle charging and discharging power while the indirect control strategy by means of controlling the price of charging and discharging. Finally, for the convenience of the reader, this paper also proposed a complete idea of the research methods about how to study the control strategy, taking the adaptability and possibility of failure of electric vehicle control strategy into consideration. Finally, suggestions on the key areas for future research are put up.

Dual percolation behaviors of electrical and thermal conductivity in metal-ceramic composites

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sun, K.; Zhang, Z. D.; Qian, L.

2016-02-08

The thermal and electrical properties including the permittivity spectra in radio frequency region were investigated for copper/yttrium iron garnet (Cu/YIG) composites. Interestingly, the percolation behaviors in electrical and thermal conductivity were obtained due to the formation of copper particles' networks. Beyond the electrical percolation threshold, negative permittivity was observed and plasmon frequency was reduced by several orders of magnitude. With the increase in copper content, the thermal conductivity was gradually increased; meanwhile, the phonon scattering effect and thermal resistance get enhanced, so the rate of increase in thermal conductivity gradually slows down. Hopefully, Cu/YIG composites with tunable electrical and thermalmore » properties have great potentials for electromagnetic interference shielding and electromagnetic wave attenuation.« less

Space Weather Effects on Current and Future Electric Power Systems

NASA Astrophysics Data System (ADS)

Munoz, D.; Dutta, O.; Tandoi, C.; Brandauer, W.; Mohamed, A.; Damas, M. C.

2016-12-01

This work addresses the effects of Geomagnetic Disturbances (GMDs) on the present bulk power system as well as the future smart grid, and discusses the mitigation of these geomagnetic impacts, so as to reduce the vulnerabilities of the electric power network to large space weather events. Solar storm characterized by electromagnetic radiation generates geo-electric fields that result in the flow of Geomagnetically Induced Currents (GICs) through the transmission lines, followed by transformers and the ground. As the ground conductivity and the power network topology significantly vary with the region, it becomes imperative to estimate of the magnitude of GICs for different places. In this paper, the magnitude of GIC has been calculated for New York State (NYS) with the help of extensive modelling of the whole NYS electricity transmission network using real data. Although GIC affects only high voltage levels, e.g. above 300 kV, the presence of coastline in NYS makes the low voltage transmission lines also susceptible to GIC. Besides this, the encroachment of technologies pertaining to smart grid implementation, such as Phasor Measurement Units (PMUs), Microgrids, Flexible AC Transmission System (FACTS), and Information and Communication Technology (ICT) have been analyzed for GMD impacts. Inaccurate PMU results due to scintillation of GPS signals that are affected by electromagnetic interference of solar storm, presence of renewable energy resources in coastal areas that are more vulnerable to GMD, the ability of FACTS devices to either block or pave new path for GICs and so on, shed some light on impacts of GMD on smart grid technologies.

Electric network interconnection of Mashreq Arab Countries

DOE Office of Scientific and Technical Information (OSTI.GOV)

El-Amin, I.M.; Al-Shehri, A.M.; Opoku, G.

1994-12-01

Power system interconnection is a well established practice for a variety of technical and economical reasons. Several interconnected networks exist worldwide for a number of factors. Some of these networks cross international boundaries. This presentation discusses the future developments of the power systems of Mashreq Arab Countries (MAC). MAC consists of Bahrain, Egypt, Iraq, Jordan, Kuwait, Lebanon, Oman, Qatar, Saudi Arabia, United Arab Emirates (UAE), and Yemen. Mac power systems are operated by government or semigovernment bodies. Many of these countries have national or regional electric grids but are generally isolated from each other. With the exception of Saudi Arabiamore » power systems, which employ 60 Hz, all other MAC utilities use 50 Hz frequency. Each country is served by one utility, except Saudi Arabia, which is served by four major utilities and some smaller utilities serving remote towns and small load centers. The major utilities are the Saudi Consolidated electric Company in the Eastern Province (SCECO East), SCECO Center, SCECO West, and SCECO South. These are the ones considered in this study. The energy resources in MAC are varied. Countries such as Egypt, Iraq, and Syria have significant hydro resources.The gulf countries and Iraq have abundant fossil fuel, The variation in energy resources as well as the characteristics of the electric load make it essential to look into interconnections beyond the national boundaries. Most of the existing or planned interconnections involve few power systems. A study involving 12 countries and over 20 utilities with different characteristics represents a very large scale undertaking.« less

Multi-mode energy management strategy for fuel cell electric vehicles based on driving pattern identification using learning vector quantization neural network algorithm

NASA Astrophysics Data System (ADS)

Song, Ke; Li, Feiqiang; Hu, Xiao; He, Lin; Niu, Wenxu; Lu, Sihao; Zhang, Tong

2018-06-01

The development of fuel cell electric vehicles can to a certain extent alleviate worldwide energy and environmental issues. While a single energy management strategy cannot meet the complex road conditions of an actual vehicle, this article proposes a multi-mode energy management strategy for electric vehicles with a fuel cell range extender based on driving condition recognition technology, which contains a patterns recognizer and a multi-mode energy management controller. This paper introduces a learning vector quantization (LVQ) neural network to design the driving patterns recognizer according to a vehicle's driving information. This multi-mode strategy can automatically switch to the genetic algorithm optimized thermostat strategy under specific driving conditions in the light of the differences in condition recognition results. Simulation experiments were carried out based on the model's validity verification using a dynamometer test bench. Simulation results show that the proposed strategy can obtain better economic performance than the single-mode thermostat strategy under dynamic driving conditions.

Plasmonic welded single walled carbon nanotubes on monolayer graphene for sensing target protein

NASA Astrophysics Data System (ADS)

Kim, Jangheon; Kim, Gi Gyu; Kim, Soohyun; Jung, Wonsuk

2016-05-01

We developed plasmonic welded single walled carbon nanotubes (SWCNTs) on monolayer graphene as a biosensor to detect target antigen molecules, fc fusion protein without any treatment to generate binder groups for linker and antibody. This plasmonic welding induces atomic networks between SWCNTs as junctions containing carboxylic groups and improves the electrical sensitivity of a SWCNTs and the graphene membrane to detect target protein. We investigated generation of the atomic networks between SWCNTs by field-emission scanning electron microscopy and atomic force microscopy after plasmonic welding process. We compared the intensity ratios of D to G peaks from the Raman spectra and electrical sheet resistance of welded SWCNTs with the results of normal SWCNTs, which decreased from 0.115 to 0.086 and from 10.5 to 4.12, respectively. Additionally, we measured the drain current via source/drain voltage after binding of the antigen to the antibody molecules. This electrical sensitivity of the welded SWCNTs was 1.55 times larger than normal SWCNTs.

Method of Calculating the Correction Factors for Cable Dimensioning in Smart Grids

NASA Astrophysics Data System (ADS)

Simutkin, M.; Tuzikova, V.; Tlusty, J.; Tulsky, V.; Muller, Z.

2017-04-01

One of the main causes of overloading electrical equipment by currents of higher harmonics is the great increasing of a number of non-linear electricity power consumers. Non-sinusoidal voltages and currents affect the operation of electrical equipment, reducing its lifetime, increases the voltage and power losses in the network, reducing its capacity. There are standards that respects emissions amount of higher harmonics current that cannot provide interference limit for a safe level in power grid. The article presents a method for determining a correction factor to the long-term allowable current of the cable, which allows for this influence. Using mathematical models in the software Elcut, it was described thermal processes in the cable in case the flow of non-sinusoidal current. Developed in the article theoretical principles, methods, mathematical models allow us to calculate the correction factor to account for the effect of higher harmonics in the current spectrum for network equipment in any type of non-linear load.

Ion transferring in polyelectrolyte networks in electric fields

NASA Astrophysics Data System (ADS)

Li, Honghao; Erbas, Aykut; Zwanikken, Jos; Olvera de La Cruz, Monica

Ion-conducting polyelectrolyte gels have drawn the attention of many researchers in the last few decades as they have wide applications not only in lithium batteries but also as stretchable, transparent ionic conductor or ionic cables devices. However, ion dynamics in polyelectrolyte gels has been much less studied analytically or computationally due to the complicated interplay of long-range electrostatic and short-range interactions. Here we propose a coarse-grained non-equilibrium molecular dynamics simulation to study the ion dynamics in polyelectrolyte gels under external electric fields. We found a nonlinear response region where the molar conductivity of polyelectrolyte gels increases with external fields. We propose counterion redistribution under electric fields as the driving mechanism. We also found the ionic conductivity to be modulated by changing polylelectrolyte network topology such as the chain length. Our discovery reveals the essential difference of ion dynamics between electrolytes and polyelectrolyte gels. These results will expand our understanding in charged polymeric systems and help in designing ion-conducting devices with higher conductivity.

Report on the survey for electrostatic discharges on Mars using NASA's Deep Space Network (DSN)

NASA Astrophysics Data System (ADS)

Arabshahi, S.; Majid, W.; Geldzahler, B.; Kocz, J.; Schulter, T.; White, L.

2017-12-01

Mars atmosphere has strong dust activity. It is suggested that the larger regional storms are capable of producing electric fields large enough to initiate electrostatic discharges. The storms have charging process similar to terrestrial dust devils and have hot cores and complicated vortex winds similar to terrestrial thunderstorms. However, due to uncertainties in our understanding of the electrical environment of the storms and absence of related in-situ measurements, the existence (or non-existence) of such electrostatic discharges on the planet is yet to be confirmed. Knowing about the electrical activity on Mars is essential for future human explorations of the planet. We have recently launched a long-term monitoring campaign at NASA's Madrid Deep Space Communication Complex (MDSCC) to search for powerful discharges on Mars. The search occurs during routine tracking of Mars orbiting spacecraft by Deep Space Network (DSN) radio telescope. In this presentation, we will report on the result of processing and analysis of the data from the first six months of our campaign.

Random network model of electrical conduction in two-phase rock

NASA Astrophysics Data System (ADS)

Fuji-ta, Kiyoshi; Seki, Masayuki; Ichiki, Masahiro

2018-05-01

We developed a cell-type lattice model to clarify the interconnected conductivity mechanism of two-phase rock. We quantified electrical conduction networks in rock and evaluated electrical conductivity models of the two-phase interaction. Considering the existence ratio of conductive and resistive cells in the model, we generated natural matrix cells simulating a natural mineral distribution pattern, using Mersenne Twister random numbers. The most important and prominent feature of the model simulation is a drastic increase in the pseudo-conductivity index for conductor ratio R > 0.22. This index in the model increased from 10-4 to 100 between R = 0.22 and 0.9, a change of four orders of magnitude. We compared our model responses with results from previous model studies. Although the pseudo-conductivity computed by the model differs slightly from that of the previous model, model responses can account for the conductivity change. Our modeling is thus effective for quantitatively estimating the degree of interconnection of rock and minerals.

Carbon nanotubes/fluorinated polymers nanocomposite thin films for electrical contacts lubrication

NASA Astrophysics Data System (ADS)

Benedetto, A.; Viel, P.; Noël, S.; Izard, N.; Chenevier, P.; Palacin, S.

2007-09-01

The need to operate in extreme environmental conditions (ultra high vacuum, high temperatures, aerospatial environment, …) and the miniaturization toward micro electromechanical systems is demanding new materials in the field of low-level electrical contacts lubrication. Dry and chemically immobilized lubrication is expected to be an alternative to the traditional wet lubricants oils. With the goal to conciliate electrical conductivity and lubricant properties we designed nanocomposite thin films composed of a 2D carbon nanotubes network embedded in an organic matrix. The nanotubes networks were deposited on gold surfaces modified by electrochemical cathodic grafting of poly(acrylonitrile). The same substrate served for covalently bonding the low-friction organic matrix. Three different matrixes were tested: a perfluorinated oligomer chemically grafted and two different polyfluorinated acrylates electrochemically grafted. The nanocomposite thin films have been characterized by ATR FT-IR, XPS and Raman spectroscopy. We measured the effects of the different matrixes and the nanotubes addition on the tribological properties and on the contact resistances of the films.

Ultrahigh Oxidation Resistance and High Electrical Conductivity in Copper-Silver Powder.

PubMed

Li, Jiaxiang; Li, Yunping; Wang, Zhongchang; Bian, Huakang; Hou, Yuhang; Wang, Fenglin; Xu, Guofu; Liu, Bin; Liu, Yong

2016-12-22

The electrical conductivity of pure Cu powder is typically deteriorated at elevated temperatures due to the oxidation by forming non-conducting oxides on surface, while enhancing oxidation resistance via alloying is often accompanied by a drastic decline of electrical conductivity. Obtaining Cu powder with both a high electrical conductivity and a high oxidation resistance represents one of the key challenges in developing next-generation electrical transferring powder. Here, we fabricate a Cu-Ag powder with a continuous Ag network along grain boundaries of Cu particles and demonstrate that this new structure can inhibit the preferential oxidation in grain boundaries at elevated temperatures. As a result, the Cu-Ag powder displays considerably high electrical conductivity and high oxidation resistance up to approximately 300 °C, which are markedly higher than that of pure Cu powder. This study paves a new pathway for developing novel Cu powders with much enhanced electrical conductivity and oxidation resistance in service.

Fast-response and scattering-free polymer network liquid crystals for infrared light modulators

NASA Astrophysics Data System (ADS)

Fan, Yun-Hsing; Lin, Yi-Hsin; Ren, Hongwen; Gauza, Sebastian; Wu, Shin-Tson

2004-02-01

A fast-response and scattering-free homogeneously aligned polymer network liquid crystal (PNLC) light modulator is demonstrated at λ=1.55 μm wavelength. Light scattering in the near-infrared region is suppressed by optimizing the polymer concentration such that the network domain sizes are smaller than the wavelength. The strong polymer network anchoring assists LC to relax back quickly as the electric field is removed. As a result, the PNLC response time is ˜250× faster than that of the E44 LC mixture except that the threshold voltage is increased by ˜25×.

Patterns recognition of electric brain activity using artificial neural networks

NASA Astrophysics Data System (ADS)

Musatov, V. Yu.; Pchelintseva, S. V.; Runnova, A. E.; Hramov, A. E.

2017-04-01

An approach for the recognition of various cognitive processes in the brain activity in the perception of ambiguous images. On the basis of developed theoretical background and the experimental data, we propose a new classification of oscillating patterns in the human EEG by using an artificial neural network approach. After learning of the artificial neural network reliably identified cube recognition processes, for example, left-handed or right-oriented Necker cube with different intensity of their edges, construct an artificial neural network based on Perceptron architecture and demonstrate its effectiveness in the pattern recognition of the EEG in the experimental.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Yanhong; Gao, Ping; Bi, Kaifeng

Conducting pathway of percolation network was identified in resistive switching devices (RSDs) with the structure of silver/amorphous silicon/p-type silicon (Ag/a-Si/p-Si) based on its gradual RESET-process and the stochastic complex impedance spectroscopy characteristics (CIS). The formation of the percolation network is attributed to amounts of nanocrystalline Si particles as well as defect sites embedded in a-Si layer, in which the defect sites supply positions for Ag ions to nucleate and grow. The similar percolation network has been only observed in Ag-Ge-Se based RSD before. This report provides a better understanding for electric properties of RSD based on the percolation network.

Floating compression of Ag nanowire networks for effective strain release of stretchable transparent electrodes

NASA Astrophysics Data System (ADS)

Pyo, Jun Beom; Kim, Byoung Soo; Park, Hyunchul; Kim, Tae Ann; Koo, Chong Min; Lee, Jonghwi; Son, Jeong Gon; Lee, Sang-Soo; Park, Jong Hyuk

2015-10-01

Manipulation of the configuration of Ag nanowire (NW) networks has been pursued to enhance the performance of stretchable transparent electrodes. However, it has remained challenging due to the high Young's modulus and low yield strain of Ag NWs, which lead to their mechanical failure when subjected to structural deformation. We demonstrate that floating a Ag NW network on water and subsequent in-plane compression allows convenient development of a wavy configuration in the Ag NW network, which can release the applied strain. A greatly enhanced electromechanical stability of Ag NW networks can be achieved due to their wavy configuration, while the NW networks maintain the desirable optical and electrical properties. Moreover, the produced NW networks can be transferred to a variety of substrates, offering flexibility for device fabrication. The Ag NW networks with wavy configurations are used as compliant electrodes for dielectric elastomer actuators. The study demonstrates their promising potential to provide improved performance for soft electronic devices.Manipulation of the configuration of Ag nanowire (NW) networks has been pursued to enhance the performance of stretchable transparent electrodes. However, it has remained challenging due to the high Young's modulus and low yield strain of Ag NWs, which lead to their mechanical failure when subjected to structural deformation. We demonstrate that floating a Ag NW network on water and subsequent in-plane compression allows convenient development of a wavy configuration in the Ag NW network, which can release the applied strain. A greatly enhanced electromechanical stability of Ag NW networks can be achieved due to their wavy configuration, while the NW networks maintain the desirable optical and electrical properties. Moreover, the produced NW networks can be transferred to a variety of substrates, offering flexibility for device fabrication. The Ag NW networks with wavy configurations are used as compliant electrodes for dielectric elastomer actuators. The study demonstrates their promising potential to provide improved performance for soft electronic devices. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr03814f

Prediction of heart abnormality using MLP network

NASA Astrophysics Data System (ADS)

Hashim, Fakroul Ridzuan; Januar, Yulni; Mat, Muhammad Hadzren; Rizman, Zairi Ismael; Awang, Mat Kamil

2018-02-01

Heart abnormality does not choose gender, age and races when it strikes. With no warning signs or symptoms, it can result to a sudden death of the patient. Generally, heart's irregular electrical activity is defined as heart abnormality. Via implementation of Multilayer Perceptron (MLP) network, this paper tries to develop a program that allows the detection of heart abnormality activity. Utilizing several training algorithms with Purelin activation function, an amount of heartbeat signals received through the electrocardiogram (ECG) will be employed to condition the MLP network.

Electromagnetic Pulse (EMP) Survivability of Telecommunications Assets

DTIC Science & Technology

1987-02-06

Program Approach ES-2 2-1 EMP Mitigation Program Approach 2-2 2-2 Approach To The Assessment Of EMP Effects On Networks 2-3 2-3 Zone-Boundary Model 2-5...2-4 Approach To The Assessment Of EMP Effects On Networks 2-6 4-1 Zone-Boundary Model And Communications Network Elements 4-1 4-2 Important Features...data and theoretical analyses to arrive at the conclusions presented in this report. TMTrademark of Western Electric Co., Inc. ES-4 - i S

Electric Current Flow Through Two-Dimensional Networks

NASA Astrophysics Data System (ADS)

Gaspard, Mallory

In modern nanotechnology, two-dimensional atomic network structures boast promising applications as nanoscale circuit boards to serve as the building blocks of more sustainable and efficient, electronic devices. However, properties associated with the network connectivity can be beneficial or deleterious to the current flow. Taking a computational approach, we will study large uniform networks, as well as large random networks using Kirchhoff's Equations in conjunction with graph theoretical measures of network connectedness and flows, to understand how network connectivity affects overall ability for successful current flow throughout a network. By understanding how connectedness affects flow, we may develop new ways to design more efficient two-dimensional materials for the next generation of nanoscale electronic devices, and we will gain a deeper insight into the intricate balance between order and chaos in the universe. Rensselaer Polytechnic Institute, SURP Institutional Grant.

Physical Configuration of the Next Generation Home Network

NASA Astrophysics Data System (ADS)

Terada, Shohei; Kakishima, Yu; Hanawa, Dai; Oguchi, Kimio

The number of broadband users is rapidly increasing worldwide. Japan already has over 10 million FTTH users. Another trend is the rapid digitalization of home electrical equipment e. g. digital cameras and hard disc recorders. These trends will encourage the emergence of the next generation home network. In this paper, we introduce the next generation home network image and describe the five domains into which home devices can be classified. We then clarify the optimum medium with which to configure the network given the requirements imposed by the home environment. Wiring cable lengths for three network topologies are calculated. The results gained from the next generation home network implemented on the first phase testbed are shown. Finally, our conclusions are given.

Evaluating conducting network based transparent electrodes from geometrical considerations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kumar, Ankush; Kulkarni, G. U., E-mail: guk@cens.res.in

2016-01-07

Conducting nanowire networks have been developed as viable alternative to existing indium tin oxide based transparent electrode (TE). The nature of electrical conduction and process optimization for electrodes have gained much from the theoretical models based on percolation transport using Monte Carlo approach and applying Kirchhoff's law on individual junctions and loops. While most of the literature work pertaining to theoretical analysis is focussed on networks obtained from conducting rods (mostly considering only junction resistance), hardly any attention has been paid to those made using template based methods, wherein the structure of network is neither similar to network obtained frommore » conducting rods nor similar to well periodic geometry. Here, we have attempted an analytical treatment based on geometrical arguments and applied image analysis on practical networks to gain deeper insight into conducting networked structure particularly in relation to sheet resistance and transmittance. Many literature examples reporting networks with straight or curvilinear wires with distributions in wire width and length have been analysed by treating the networks as two dimensional graphs and evaluating the sheet resistance based on wire density and wire width. The sheet resistance values from our analysis compare well with the experimental values. Our analysis on various examples has revealed that low sheet resistance is achieved with high wire density and compactness with straight rather than curvilinear wires and with narrower wire width distribution. Similarly, higher transmittance for given sheet resistance is possible with narrower wire width but of higher thickness, minimal curvilinearity, and maximum connectivity. For the purpose of evaluating active fraction of the network, the algorithm was made to distinguish and quantify current carrying backbone regions as against regions containing only dangling or isolated wires. The treatment can be helpful in predicting the properties of a network simply from image analysis and will be helpful in improvisation and comparison of various TEs and better understanding of electrical percolation.« less

Evaluating conducting network based transparent electrodes from geometrical considerations

NASA Astrophysics Data System (ADS)

Kumar, Ankush; Kulkarni, G. U.

2016-01-01

Conducting nanowire networks have been developed as viable alternative to existing indium tin oxide based transparent electrode (TE). The nature of electrical conduction and process optimization for electrodes have gained much from the theoretical models based on percolation transport using Monte Carlo approach and applying Kirchhoff's law on individual junctions and loops. While most of the literature work pertaining to theoretical analysis is focussed on networks obtained from conducting rods (mostly considering only junction resistance), hardly any attention has been paid to those made using template based methods, wherein the structure of network is neither similar to network obtained from conducting rods nor similar to well periodic geometry. Here, we have attempted an analytical treatment based on geometrical arguments and applied image analysis on practical networks to gain deeper insight into conducting networked structure particularly in relation to sheet resistance and transmittance. Many literature examples reporting networks with straight or curvilinear wires with distributions in wire width and length have been analysed by treating the networks as two dimensional graphs and evaluating the sheet resistance based on wire density and wire width. The sheet resistance values from our analysis compare well with the experimental values. Our analysis on various examples has revealed that low sheet resistance is achieved with high wire density and compactness with straight rather than curvilinear wires and with narrower wire width distribution. Similarly, higher transmittance for given sheet resistance is possible with narrower wire width but of higher thickness, minimal curvilinearity, and maximum connectivity. For the purpose of evaluating active fraction of the network, the algorithm was made to distinguish and quantify current carrying backbone regions as against regions containing only dangling or isolated wires. The treatment can be helpful in predicting the properties of a network simply from image analysis and will be helpful in improvisation and comparison of various TEs and better understanding of electrical percolation.

Embedded resource accounting for coupled natural-human systems: An application to water resource impacts of the western U.S. electrical energy trade

NASA Astrophysics Data System (ADS)

Ruddell, Benjamin L.; Adams, Elizabeth A.; Rushforth, Richard; Tidwell, Vincent C.

2014-10-01

In complex coupled natural-human systems (CNH), multitype networks link social, environmental, and economic systems with flows of matter, energy, information, and value. Embedded Resource Accounting (ERA) is a systems analysis framework that includes the indirect connections of a multitype CNH network. ERA is conditioned on perceived system boundaries, which may vary according to the accountant's point of view. Both direct and indirect impacts are implicit whenever two subnetworks interact in such a system; the ratio of two subnetworks' impacts is the embedded intensity. For trade in the services of water, this is understood as the indirect component of a water footprint, and as "virtual water" trade. ERA is a generalization of input-output, footprint, and substance flow methods, and is a type of life cycle analysis. This paper presents results for the water and electrical energy system in the western U.S. This system is dominated by California, which outsources the majority of its water footprint of electrical energy. Electricity trade increases total water consumption for electricity production in the western U.S. by 15% and shifts water use to water-stressed Colorado River Basin States. A systemic underaccounting for water footprints occurs because state-level processes discount a portion of the water footprint occurring outside of the state boundary.

Monte Carlo simulations of electrical percolation in multicomponent thin films with nanofillers

NASA Astrophysics Data System (ADS)

Ni, Xiaojuan; Hui, Chao; Su, Ninghai; Jiang, Wei; Liu, Feng

2018-02-01

We developed a 2D disk-stick percolation model to investigate the electrical percolation behavior of an insulating thin film reinforced with 1D and 2D conductive nanofillers via Monte Carlo simulation. Numerical predictions of the percolation threshold in single component thin films showed good agreement with the previous published work, validating our model for investigating the characteristics of the percolation phenomena. Parametric studies of size effect, i.e., length of 1D nanofiller and diameter of 2D nanofiller, were carried out to predict the electrical percolation threshold for hybrid systems. The relationships between the nanofillers in two hybrid systems was established, which showed differences from previous linear assumption. The effective electrical conductance was evaluated through Kirchhoff’s current law by transforming it into a resistor network. The equivalent resistance was obtained from the distribution of nodal voltages by solving a system of linear equations with a Gaussian elimination method. We examined the effects of stick length, relative concentration, and contact patterns of 1D/2D inclusions on electrical performance. One novel aspect of our study is its ability to investigate the effective conductance of nanocomposites as a function of relative concentrations, which shows there is a synergistic effect when nanofillers with different dimensionalities combine properly. Our work provides an important theoretical basis for designing the conductive networks and predicting the percolation properties of multicomponent nanocomposites.

Energy Production from Biogas: Competitiveness and Support Instruments in Latvia

NASA Astrophysics Data System (ADS)

Klāvs, G.; Kundziņa, A.; Kudrenickis, I.

2016-10-01

Use of renewable energy sources (RES) might be one of the key factors for the triple win-win: improving energy supply security, promoting local economic development, and reducing greenhouse gas emissions. The authors ex-post evaluate the impact of two main support instruments applied in 2010-2014 - the investment support (IS) and the feed-in tariff (FIT) - on the economic viability of small scale (up to 2MWel) biogas unit. The results indicate that the electricity production cost in biogas utility roughly corresponds to the historical FIT regarding electricity production using RES. However, if in addition to the FIT the IS is provided, the analysis shows that the practice of combining both the above-mentioned instruments is not optimal because too high total support (overcompensation) is provided for a biogas utility developer. In a long-term perspective, the latter gives wrong signals for investments in new technologies and also creates unequal competition in the RES electricity market. To provide optimal biogas utilisation, it is necessary to consider several options. Both on-site production of electricity and upgrading to biomethane for use in a low pressure gas distribution network are simulated by the cost estimation model. The authors' estimates show that upgrading for use in a gas distribution network should be particularly considered taking into account the already existing infrastructure and technologies. This option requires lower support compared to support for electricity production in small-scale biogas utilities.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Linvill, Carl; Brutkoski, Donna

Mexico's energy reform will have far-reaching effects on how people produce and consume electricity in the country. Market liberalization will open the door to an increasing number of options for Mexican residential, commercial, and industrial consumers, and distributed generation (DG), which for Mexico includes generators of less than 500 kilowatts (kW) of capacity connected to the distribution network. Distributed generation is an option for consumers who want to produce their own electricity and provide electricity services to others. This report seeks to provide guidance to Mexican officials on designing DG economic and regulatory policies.