Competition and Cooperation of Distributed Generation and Power System

NASA Astrophysics Data System (ADS)

Miyake, Masatoshi; Nanahara, Toshiya

Advances in distributed generation technologies together with the deregulation of an electric power industry can lead to a massive introduction of distributed generation. Since most of distributed generation will be interconnected to a power system, coordination and competition between distributed generators and large-scale power sources would be a vital issue in realizing a more desirable energy system in the future. This paper analyzes competitions between electric utilities and cogenerators from the viewpoints of economic and energy efficiency based on the simulation results on an energy system including a cogeneration system. First, we examine best response correspondence of an electric utility and a cogenerator with a noncooperative game approach: we obtain a Nash equilibrium point. Secondly, we examine the optimum strategy that attains the highest social surplus and the highest energy efficiency through global optimization.

Network-Oriented Approach to Distributed Generation Planning

NASA Astrophysics Data System (ADS)

Kochukov, O.; Mutule, A.

2017-06-01

The main objective of the paper is to present an innovative complex approach to distributed generation planning and show the advantages over existing methods. The approach will be most suitable for DNOs and authorities and has specific calculation targets to support the decision-making process. The method can be used for complex distribution networks with different arrangement and legal base.

Systems of frequency distributions for water and environmental engineering

NASA Astrophysics Data System (ADS)

Singh, Vijay P.

2018-09-01

A wide spectrum of frequency distributions are used in hydrologic, hydraulic, environmental and water resources engineering. These distributions may have different origins, are based on different hypotheses, and belong to different generating systems. Review of literature suggests that different systems of frequency distributions employed in science and engineering in general and environmental and water engineering in particular have been derived using different approaches which include (1) differential equations, (2) distribution elasticity, (3) genetic theory, (4) generating functions, (5) transformations, (6) Bessel function, (7) expansions, and (8) entropy maximization. This paper revisits these systems of distributions and discusses the hypotheses that are used for deriving these systems. It also proposes, based on empirical evidence, another general system of distributions and derives a number of distributions from this general system that are used in environmental and water engineering.

Chemical-Space-Based de Novo Design Method To Generate Drug-Like Molecules.

PubMed

Takeda, Shunichi; Kaneko, Hiromasa; Funatsu, Kimito

2016-10-24

To discover drug compounds in chemical space containing an enormous number of compounds, a structure generator is required to produce virtual drug-like chemical structures. The de novo design algorithm for exploring chemical space (DAECS) visualizes the activity distribution on a two-dimensional plane corresponding to chemical space and generates structures in a target area on a plane selected by the user. In this study, we modify the DAECS to enable the user to select a target area to consider properties other than activity and improve the diversity of the generated structures by visualizing the drug-likeness distribution and the activity distribution, generating structures by substructure-based structural changes, including addition, deletion, and substitution of substructures, as well as the slight structural changes used in the DAECS. Through case studies using ligand data for the human adrenergic alpha2A receptor and the human histamine H1 receptor, the modified DAECS can generate high diversity drug-like structures, and the usefulness of the modification of the DAECS is verified.

Comparison between broadband Bessel beam launchers based on either Bessel or Hankel aperture distribution for millimeter wave short pulse generation.

PubMed

Pavone, Santi C; Mazzinghi, Agnese; Freni, Angelo; Albani, Matteo

2017-08-07

In this paper, a comparison is presented between Bessel beam launchers at millimeter waves based on either a cylindrical standing wave (CSW) or a cylindrical inward traveling wave (CITW) aperture distribution. It is theoretically shown that CITW launchers are better suited for the generation of electromagnetic short pulses because they maintain their performances over a larger bandwidth than those realizing a CSW aperture distribution. Moreover, the wavenumber dispersion of both the launchers is evaluated both theoretically and numerically. To this end, two planar Bessel beam launchers, one enforcing a CSW and the other enforcing a CITW aperture distribution, are designed at millimeter waves with a center operating frequency of f¯=60GHz and analyzed in the bandwidth 50 - 70 GHz by using an in-house developed numerical code to solve Maxwell's equations based on the method of moments. It is shown that a monochromatic Bessel beam can be efficiently generated by both the launchers over a wide fractional bandwidth. Finally, we investigate the generation of limited-diffractive electromagnetic pulses at millimeter waves, up to a certain non-diffractive range. Namely, it is shown that by feeding the launcher with a Gaussian short pulse, a spatially confined electromagnetic pulse can be efficiently generated in front of the launcher.

Study on distributed generation algorithm of variable precision concept lattice based on ontology heterogeneous database

NASA Astrophysics Data System (ADS)

WANG, Qingrong; ZHU, Changfeng

2017-06-01

Integration of distributed heterogeneous data sources is the key issues under the big data applications. In this paper the strategy of variable precision is introduced to the concept lattice, and the one-to-one mapping mode of variable precision concept lattice and ontology concept lattice is constructed to produce the local ontology by constructing the variable precision concept lattice for each subsystem, and the distributed generation algorithm of variable precision concept lattice based on ontology heterogeneous database is proposed to draw support from the special relationship between concept lattice and ontology construction. Finally, based on the standard of main concept lattice of the existing heterogeneous database generated, a case study has been carried out in order to testify the feasibility and validity of this algorithm, and the differences between the main concept lattice and the standard concept lattice are compared. Analysis results show that this algorithm above-mentioned can automatically process the construction process of distributed concept lattice under the heterogeneous data sources.

Large-scale runoff generation - parsimonious parameterisation using high-resolution topography

NASA Astrophysics Data System (ADS)

Gong, L.; Halldin, S.; Xu, C.-Y.

2011-08-01

World water resources have primarily been analysed by global-scale hydrological models in the last decades. Runoff generation in many of these models are based on process formulations developed at catchments scales. The division between slow runoff (baseflow) and fast runoff is primarily governed by slope and spatial distribution of effective water storage capacity, both acting at very small scales. Many hydrological models, e.g. VIC, account for the spatial storage variability in terms of statistical distributions; such models are generally proven to perform well. The statistical approaches, however, use the same runoff-generation parameters everywhere in a basin. The TOPMODEL concept, on the other hand, links the effective maximum storage capacity with real-world topography. Recent availability of global high-quality, high-resolution topographic data makes TOPMODEL attractive as a basis for a physically-based runoff-generation algorithm at large scales, even if its assumptions are not valid in flat terrain or for deep groundwater systems. We present a new runoff-generation algorithm for large-scale hydrology based on TOPMODEL concepts intended to overcome these problems. The TRG (topography-derived runoff generation) algorithm relaxes the TOPMODEL equilibrium assumption so baseflow generation is not tied to topography. TRG only uses the topographic index to distribute average storage to each topographic index class. The maximum storage capacity is proportional to the range of topographic index and is scaled by one parameter. The distribution of storage capacity within large-scale grid cells is obtained numerically through topographic analysis. The new topography-derived distribution function is then inserted into a runoff-generation framework similar VIC's. Different basin parts are parameterised by different storage capacities, and different shapes of the storage-distribution curves depend on their topographic characteristics. The TRG algorithm is driven by the HydroSHEDS dataset with a resolution of 3" (around 90 m at the equator). The TRG algorithm was validated against the VIC algorithm in a common model framework in 3 river basins in different climates. The TRG algorithm performed equally well or marginally better than the VIC algorithm with one less parameter to be calibrated. The TRG algorithm also lacked equifinality problems and offered a realistic spatial pattern for runoff generation and evaporation.

Large-scale runoff generation - parsimonious parameterisation using high-resolution topography

NASA Astrophysics Data System (ADS)

Gong, L.; Halldin, S.; Xu, C.-Y.

2010-09-01

World water resources have primarily been analysed by global-scale hydrological models in the last decades. Runoff generation in many of these models are based on process formulations developed at catchments scales. The division between slow runoff (baseflow) and fast runoff is primarily governed by slope and spatial distribution of effective water storage capacity, both acting a very small scales. Many hydrological models, e.g. VIC, account for the spatial storage variability in terms of statistical distributions; such models are generally proven to perform well. The statistical approaches, however, use the same runoff-generation parameters everywhere in a basin. The TOPMODEL concept, on the other hand, links the effective maximum storage capacity with real-world topography. Recent availability of global high-quality, high-resolution topographic data makes TOPMODEL attractive as a basis for a physically-based runoff-generation algorithm at large scales, even if its assumptions are not valid in flat terrain or for deep groundwater systems. We present a new runoff-generation algorithm for large-scale hydrology based on TOPMODEL concepts intended to overcome these problems. The TRG (topography-derived runoff generation) algorithm relaxes the TOPMODEL equilibrium assumption so baseflow generation is not tied to topography. TGR only uses the topographic index to distribute average storage to each topographic index class. The maximum storage capacity is proportional to the range of topographic index and is scaled by one parameter. The distribution of storage capacity within large-scale grid cells is obtained numerically through topographic analysis. The new topography-derived distribution function is then inserted into a runoff-generation framework similar VIC's. Different basin parts are parameterised by different storage capacities, and different shapes of the storage-distribution curves depend on their topographic characteristics. The TRG algorithm is driven by the HydroSHEDS dataset with a resolution of 3'' (around 90 m at the equator). The TRG algorithm was validated against the VIC algorithm in a common model framework in 3 river basins in different climates. The TRG algorithm performed equally well or marginally better than the VIC algorithm with one less parameter to be calibrated. The TRG algorithm also lacked equifinality problems and offered a realistic spatial pattern for runoff generation and evaporation.

Ensuring the Reliable Operation of the Power Grid: State-Based and Distributed Approaches to Scheduling Energy and Contingency Reserves

NASA Astrophysics Data System (ADS)

Prada, Jose Fernando

Keeping a contingency reserve in power systems is necessary to preserve the security of real-time operations. This work studies two different approaches to the optimal allocation of energy and reserves in the day-ahead generation scheduling process. Part I presents a stochastic security-constrained unit commitment model to co-optimize energy and the locational reserves required to respond to a set of uncertain generation contingencies, using a novel state-based formulation. The model is applied in an offer-based electricity market to allocate contingency reserves throughout the power grid, in order to comply with the N-1 security criterion under transmission congestion. The objective is to minimize expected dispatch and reserve costs, together with post contingency corrective redispatch costs, modeling the probability of generation failure and associated post contingency states. The characteristics of the scheduling problem are exploited to formulate a computationally efficient method, consistent with established operational practices. We simulated the distribution of locational contingency reserves on the IEEE RTS96 system and compared the results with the conventional deterministic method. We found that assigning locational spinning reserves can guarantee an N-1 secure dispatch accounting for transmission congestion at a reasonable extra cost. The simulations also showed little value of allocating downward reserves but sizable operating savings from co-optimizing locational nonspinning reserves. Overall, the results indicate the computational tractability of the proposed method. Part II presents a distributed generation scheduling model to optimally allocate energy and spinning reserves among competing generators in a day-ahead market. The model is based on the coordination between individual generators and a market entity. The proposed method uses forecasting, augmented pricing and locational signals to induce efficient commitment of generators based on firm posted prices. It is price-based but does not rely on multiple iterations, minimizes information exchange and simplifies the market clearing process. Simulations of the distributed method performed on a six-bus test system showed that, using an appropriate set of prices, it is possible to emulate the results of a conventional centralized solution, without need of providing make-whole payments to generators. Likewise, they showed that the distributed method can accommodate transactions with different products and complex security constraints.

a Framework for Distributed Mixed Language Scientific Applications

NASA Astrophysics Data System (ADS)

Quarrie, D. R.

The Object Management Group has defined an architecture (CORBA) for distributed object applications based on an Object Request Broker and Interface Definition Language. This project builds upon this architecture to establish a framework for the creation of mixed language scientific applications. A prototype compiler has been written that generates FORTRAN 90 or Eiffel stubs and skeletons and the required C++ glue code from an input IDL file that specifies object interfaces. This generated code can be used directly for non-distributed mixed language applications or in conjunction with the C++ code generated from a commercial IDL compiler for distributed applications. A feasibility study is presently underway to see whether a fully integrated software development environment for distributed, mixed-language applications can be created by modifying the back-end code generator of a commercial CASE tool to emit IDL.

An extension of the directed search domain algorithm to bilevel optimization

NASA Astrophysics Data System (ADS)

Wang, Kaiqiang; Utyuzhnikov, Sergey V.

2017-08-01

A method is developed for generating a well-distributed Pareto set for the upper level in bilevel multiobjective optimization. The approach is based on the Directed Search Domain (DSD) algorithm, which is a classical approach for generation of a quasi-evenly distributed Pareto set in multiobjective optimization. The approach contains a double-layer optimizer designed in a specific way under the framework of the DSD method. The double-layer optimizer is based on bilevel single-objective optimization and aims to find a unique optimal Pareto solution rather than generate the whole Pareto frontier on the lower level in order to improve the optimization efficiency. The proposed bilevel DSD approach is verified on several test cases, and a relevant comparison against another classical approach is made. It is shown that the approach can generate a quasi-evenly distributed Pareto set for the upper level with relatively low time consumption.

One-laser-based generation/detection of Brillouin dynamic grating and its application to distributed discrimination of strain and temperature.

PubMed

Zou, Weiwen; He, Zuyuan; Hotate, Kazuo

2011-01-31

This paper presents a novel scheme to generate and detect Brillouin dynamic grating in a polarization-maintaining optical fiber based on one laser source. Precise measurement of Brillouin dynamic grating spectrum is achieved benefiting from that the pump, probe and readout waves are coherently originated from the same laser source. Distributed discrimination of strain and temperature is also achieved with high accuracy.

Optimal Solar PV Arrays Integration for Distributed Generation

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

Omitaomu, Olufemi A; Li, Xueping

2012-01-01

Solar photovoltaic (PV) systems hold great potential for distributed energy generation by installing PV panels on rooftops of residential and commercial buildings. Yet challenges arise along with the variability and non-dispatchability of the PV systems that affect the stability of the grid and the economics of the PV system. This paper investigates the integration of PV arrays for distributed generation applications by identifying a combination of buildings that will maximize solar energy output and minimize system variability. Particularly, we propose mean-variance optimization models to choose suitable rooftops for PV integration based on Markowitz mean-variance portfolio selection model. We further introducemore » quantity and cardinality constraints to result in a mixed integer quadratic programming problem. Case studies based on real data are presented. An efficient frontier is obtained for sample data that allows decision makers to choose a desired solar energy generation level with a comfortable variability tolerance level. Sensitivity analysis is conducted to show the tradeoffs between solar PV energy generation potential and variability.« less

Deterministic MDI QKD with two secret bits per shared entangled pair

NASA Astrophysics Data System (ADS)

Zebboudj, Sofia; Omar, Mawloud

2018-03-01

Although quantum key distribution schemes have been proven theoretically secure, they are based on assumptions about the devices that are not yet satisfied with today's technology. The measurement-device-independent scheme has been proposed to shorten the gap between theory and practice by removing all detector side-channel attacks. On the other hand, two-way quantum key distribution schemes have been proposed to raise the secret key generation rate. In this paper, we propose a new quantum key distribution scheme able to achieve a relatively high secret key generation rate based on two-way quantum key distribution that also inherits the robustness of the measurement-device-independent scheme against detector side-channel attacks.

Decentralized Energy Management System for Networked Microgrids in Grid-connected and Islanded Modes

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

Wang, Zhaoyu; Chen, Bokan; Wang, Jianhui

This paper proposes a decentralized energy management system (EMS) for the coordinated operation of networked Microgirds (MGs) in a distribution system. In the grid-connected mode, the distribution network operator (DNO) and each MG are considered as distinct entities with individual objectives to minimize their own operation costs. It is assumed that both dispatchable and renewable energy source (RES)-based distributed generators (DGs) exist in the distribution network and the networked MGs. In order to coordinate the operation of all entities, we apply a decentralized bi-level algorithm to solve the problem with the first level to conduct negotiations among all entities andmore » the second level to update the non-converging penalties. In the islanded mode, the objective of each MG is to maintain a reliable power supply to its customers. In order to take into account the uncertainties of DG outputs and load consumption, we formulate the problems as two-stage stochastic programs. The first stage is to determine base generation setpoints based on the forecasts and the second stage is to adjust the generation outputs based on the realized scenarios. Case studies of a distribution system with networked MGs demonstrate the effectiveness of the proposed methodology in both grid-connected and islanded modes.« less

Fast Reliability Assessing Method for Distribution Network with Distributed Renewable Energy Generation

NASA Astrophysics Data System (ADS)

Chen, Fan; Huang, Shaoxiong; Ding, Jinjin; Ding, Jinjin; Gao, Bo; Xie, Yuguang; Wang, Xiaoming

2018-01-01

This paper proposes a fast reliability assessing method for distribution grid with distributed renewable energy generation. First, the Weibull distribution and the Beta distribution are used to describe the probability distribution characteristics of wind speed and solar irradiance respectively, and the models of wind farm, solar park and local load are built for reliability assessment. Then based on power system production cost simulation probability discretization and linearization power flow, a optimal power flow objected with minimum cost of conventional power generation is to be resolved. Thus a reliability assessment for distribution grid is implemented fast and accurately. The Loss Of Load Probability (LOLP) and Expected Energy Not Supplied (EENS) are selected as the reliability index, a simulation for IEEE RBTS BUS6 system in MATLAB indicates that the fast reliability assessing method calculates the reliability index much faster with the accuracy ensured when compared with Monte Carlo method.

Model-based VQ for image data archival, retrieval and distribution

NASA Technical Reports Server (NTRS)

Manohar, Mareboyana; Tilton, James C.

1995-01-01

An ideal image compression technique for image data archival, retrieval and distribution would be one with the asymmetrical computational requirements of Vector Quantization (VQ), but without the complications arising from VQ codebooks. Codebook generation and maintenance are stumbling blocks which have limited the use of VQ as a practical image compression algorithm. Model-based VQ (MVQ), a variant of VQ described here, has the computational properties of VQ but does not require explicit codebooks. The codebooks are internally generated using mean removed error and Human Visual System (HVS) models. The error model assumed is the Laplacian distribution with mean, lambda-computed from a sample of the input image. A Laplacian distribution with mean, lambda, is generated with uniform random number generator. These random numbers are grouped into vectors. These vectors are further conditioned to make them perceptually meaningful by filtering the DCT coefficients from each vector. The DCT coefficients are filtered by multiplying by a weight matrix that is found to be optimal for human perception. The inverse DCT is performed to produce the conditioned vectors for the codebook. The only image dependent parameter used in the generation of codebook is the mean, lambda, that is included in the coded file to repeat the codebook generation process for decoding.

Real time testing of intelligent relays for synchronous distributed generation islanding detection

NASA Astrophysics Data System (ADS)

Zhuang, Davy

As electric power systems continue to grow to meet ever-increasing energy demand, their security, reliability, and sustainability requirements also become more stringent. The deployment of distributed energy resources (DER), including generation and storage, in conventional passive distribution feeders, gives rise to integration problems involving protection and unintentional islanding. Distributed generators need to be islanded for safety reasons when disconnected or isolated from the main feeder as distributed generator islanding may create hazards to utility and third-party personnel, and possibly damage the distribution system infrastructure, including the distributed generators. This thesis compares several key performance indicators of a newly developed intelligent islanding detection relay, against islanding detection devices currently used by the industry. The intelligent relay employs multivariable analysis and data mining methods to arrive at decision trees that contain both the protection handles and the settings. A test methodology is developed to assess the performance of these intelligent relays on a real time simulation environment using a generic model based on a real-life distribution feeder. The methodology demonstrates the applicability and potential advantages of the intelligent relay, by running a large number of tests, reflecting a multitude of system operating conditions. The testing indicates that the intelligent relay often outperforms frequency, voltage and rate of change of frequency relays currently used for islanding detection, while respecting the islanding detection time constraints imposed by standing distributed generator interconnection guidelines.

Recent progress in distributed optical fiber Raman photon sensors at China Jiliang University

NASA Astrophysics Data System (ADS)

Zhang, Zaixuan; Wang, Jianfeng; Li, Yi; Gong, Huaping; Yu, Xiangdong; Liu, Honglin; Jin, Yongxing; Kang, Juan; Li, Chenxia; Zhang, Wensheng; Zhang, Wenping; Niu, Xiaohui; Sun, Zhongzhou; Zhao, Chunliu; Dong, Xinyong; Jin, Shangzhong

2012-06-01

A brief review of recent progress in researches, productions and applications of full distributed fiber Raman photon sensors at China Jiliang University (CJLU) is presented. In order to improve the measurement distance, the accuracy, the space resolution, the ability of multi-parameter measurements, and the intelligence of full distributed fiber sensor systems, a new generation fiber sensor technology based on the optical fiber nonlinear scattering fusion principle is proposed. A series of new generation full distributed fiber sensors are investigated and designed, which consist of new generation ultra-long distance full distributed fiber Raman and Rayleigh scattering photon sensors integrated with a fiber Raman amplifier, auto-correction full distributed fiber Raman photon temperature sensors based on Raman correlation dual sources, full distributed fiber Raman photon temperature sensors based on a pulse coding source, full distributed fiber Raman photon temperature sensors using a fiber Raman wavelength shifter, a new type of Brillouin optical time domain analyzers (BOTDAs) integrated with a fiber Raman amplifier for replacing a fiber Brillouin amplifier, full distributed fiber Raman and Brillouin photon sensors integrated with a fiber Raman amplifier, and full distributed fiber Brillouin photon sensors integrated with a fiber Brillouin frequency shifter. The Internet of things is believed as one of candidates of the next technological revolution, which has driven hundreds of millions of class markets. Sensor networks are important components of the Internet of things. The full distributed optical fiber sensor network (Rayleigh, Raman, and Brillouin scattering) is a 3S (smart materials, smart structure, and smart skill) system, which is easy to construct smart fiber sensor networks. The distributed optical fiber sensor can be embedded in the power grids, railways, bridges, tunnels, roads, constructions, water supply systems, dams, oil and gas pipelines and other facilities, and can be integrated with wireless networks.

100 km differential phase shift quantum key distribution experiment with low jitter up-conversion detectors

NASA Astrophysics Data System (ADS)

Diamanti, Eleni; Takesue, Hiroki; Langrock, Carsten; Fejer, M. M.; Yamamoto, Yoshihisa

2006-12-01

We present a quantum key distribution experiment in which keys that were secure against all individual eavesdropping attacks allowed by quantum mechanics were distributed over 100 km of optical fiber. We implemented the differential phase shift quantum key distribution protocol and used low timing jitter 1.55 µm single-photon detectors based on frequency up-conversion in periodically poled lithium niobate waveguides and silicon avalanche photodiodes. Based on the security analysis of the protocol against general individual attacks, we generated secure keys at a practical rate of 166 bit/s over 100 km of fiber. The use of the low jitter detectors also increased the sifted key generation rate to 2 Mbit/s over 10 km of fiber.

POLYANA-A tool for the calculation of molecular radial distribution functions based on Molecular Dynamics trajectories

NASA Astrophysics Data System (ADS)

Dimitroulis, Christos; Raptis, Theophanes; Raptis, Vasilios

2015-12-01

We present an application for the calculation of radial distribution functions for molecular centres of mass, based on trajectories generated by molecular simulation methods (Molecular Dynamics, Monte Carlo). When designing this application, the emphasis was placed on ease of use as well as ease of further development. In its current version, the program can read trajectories generated by the well-known DL_POLY package, but it can be easily extended to handle other formats. It is also very easy to 'hack' the program so it can compute intermolecular radial distribution functions for groups of interaction sites rather than whole molecules.

Highly sensitive distributed birefringence measurements based on a two-pulse interrogation of a dynamic Brillouin grating

NASA Astrophysics Data System (ADS)

Soto, Marcelo A.; Denisov, Andrey; Angulo-Vinuesa, Xabier; Martin-Lopez, Sonia; Thévenaz, Luc; Gonzalez-Herraez, Miguel

2017-04-01

A method for distributed birefringence measurements is proposed based on the interference pattern generated by the interrogation of a dynamic Brillouin grating (DBG) using two short consecutive optical pulses. Compared to existing DBG interrogation techniques, the method here offers an improved sensitivity to birefringence changes thanks to the interferometric effect generated by the reflections of the two pulses. Experimental results demonstrate the possibility to obtain the longitudinal birefringence profile of a 20 m-long Panda fibre with an accuracy of 10-8 using 16 averages and 30 cm spatial resolution. The method enables sub-metric and highly-accurate distributed temperature and strain sensing.

A user-oriented synthetic workload generator

NASA Technical Reports Server (NTRS)

Kao, Wei-Lun

1991-01-01

A user oriented synthetic workload generator that simulates users' file access behavior based on real workload characterization is described. The model for this workload generator is user oriented and job specific, represents file I/O operations at the system call level, allows general distributions for the usage measures, and assumes independence in the file I/O operation stream. The workload generator consists of three parts which handle specification of distributions, creation of an initial file system, and selection and execution of file I/O operations. Experiments on SUN NFS are shown to demonstrate the usage of the workload generator.

Effects of voltage control in utility interactive dispersed storage and generation systems

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

Kirkham, H.; Das, R.

1983-03-15

When a small generator is connected to the distribution system, the voltage at the point of interconnection is determined largely by the system and not the generator. This report examines the effect on the generator, on the load voltage and on the distribution system of a number of different voltage control strategies in the generator. Synchronous generators with three kinds of exciter control are considered, as well as induction generators and dc/ac inverters, with and without capacitor compensation. The effect of varying input power during operation (which may be experienced by generators based on renewable resources) is explored, as wellmore » as the effect of connecting and disconnecting the generator at ten percent of its rated power.« less

Distributed generation of shared RSA keys in mobile ad hoc networks

NASA Astrophysics Data System (ADS)

Liu, Yi-Liang; Huang, Qin; Shen, Ying

2005-12-01

Mobile Ad Hoc Networks is a totally new concept in which mobile nodes are able to communicate together over wireless links in an independent manner, independent of fixed physical infrastructure and centralized administrative infrastructure. However, the nature of Ad Hoc Networks makes them very vulnerable to security threats. Generation and distribution of shared keys for CA (Certification Authority) is challenging for security solution based on distributed PKI(Public-Key Infrastructure)/CA. The solutions that have been proposed in the literature and some related issues are discussed in this paper. The solution of a distributed generation of shared threshold RSA keys for CA is proposed in the present paper. During the process of creating an RSA private key share, every CA node only has its own private security. Distributed arithmetic is used to create the CA's private share locally, and that the requirement of centralized management institution is eliminated. Based on fully considering the Mobile Ad Hoc network's characteristic of self-organization, it avoids the security hidden trouble that comes by holding an all private security share of CA, with which the security and robustness of system is enhanced.

Free-Space Quantum Key Distribution using Polarization Entangled Photons

NASA Astrophysics Data System (ADS)

Kurtsiefer, Christian

2007-06-01

We report on a complete experimental implementation of a quantum key distribution protocol through a free space link using polarization-entangled photon pairs from a compact parametric down-conversion source [1]. Based on a BB84-equivalent protocol, we generated without interruption over 10 hours a secret key free-space optical link distance of 1.5 km with a rate up to 950 bits per second after error correction and privacy amplification. Our system is based on two time stamp units and relies on no specific hardware channel for coincidence identification besides an IP link. For that, initial clock synchronization with an accuracy of better than 2 ns is achieved, based on a conventional NTP protocol and a tiered cross correlation of time tags on both sides. Time tags are used to servo a local clock, allowing a streamed measurement on correctly identified photon pairs. Contrary to the majority of quantum key distribution systems, this approach does not require a trusted large-bandwidth random number generator, but integrates that into the physical key generation process. We discuss our current progress of implementing a key distribution via an atmospherical link during daylight conditions, and possible attack scenarios on a physical timing information side channel to a entanglement-based key distribution system. [1] I. Marcikic, A. Lamas-Linares, C. Kurtsiefer, Appl. Phys. Lett. 89, 101122 (2006).

Transverse momentum dependent (TMD) parton distribution functions generated in the modified DGLAP formalism based on the valence-like distributions

NASA Astrophysics Data System (ADS)

Hosseinkhani, H.; Modarres, M.; Olanj, N.

2017-07-01

Transverse momentum dependent (TMD) parton distributions, also referred to as unintegrated parton distribution functions (UPDFs), are produced via the Kimber-Martin-Ryskin (KMR) prescription. The GJR08 set of parton distribution functions (PDFs) which are based on the valence-like distributions is used, at the leading order (LO) and the next-to-leading order (NLO) approximations, as inputs of the KMR formalism. The general and the relative behaviors of the generated TMD PDFs at LO and NLO and their ratios in a wide range of the transverse momentum values, i.e. kt2 = 10, 102, 104 and 108GeV2 are investigated. It is shown that the properties of the parent valence-like PDFs are imprinted on the daughter TMD PDFs. Imposing the angular ordering constraint (AOC) leads to the dynamical variable limits on the integrals which in turn increase the contributions from the lower scales at lower kt2. The results are compared with our previous studies based on the MSTW2008 input PDFs and it is shown that the present calculation gives flatter TMD PDFs. Finally, a comparison of longitudinal structure function (FL) is made by using the produced TMD PDFs and those that were generated through the MSTW2008-LO PDF from our previous work and the corresponding data from H1 and ZEUS collaborations and a reasonable agreement is found.

Spatially distributed modal signals of free shallow membrane shell structronic system

NASA Astrophysics Data System (ADS)

Yue, H. H.; Deng, Z. Q.; Tzou, H. S.

2008-11-01

Based on the smart material and structronics technology, distributed sensor and control of shell structures have been rapidly developed for the last 20 years. This emerging technology has been utilized in aerospace, telecommunication, micro-electromechanical systems and other engineering applications. However, distributed monitoring technique and its resulting global spatially distributed sensing signals of shallow paraboloidal membrane shells are not clearly understood. In this paper, modeling of free flexible paraboloidal shell with spatially distributed sensor, micro-sensing signal characteristics, and location of distributed piezoelectric sensor patches are investigated based on a new set of assumed mode shape functions. Parametric analysis indicates that the signal generation depends on modal membrane strains in the meridional and circumferential directions in which the latter is more significant than the former, when all bending strains vanish in membrane shells. This study provides a modeling and analysis technique for distributed sensors laminated on lightweight paraboloidal flexible structures and identifies critical components and regions that generate significant signals.

An artificial EMG generation model based on signal-dependent noise and related application to motion classification

PubMed Central

Hayashi, Hideaki; Nakamura, Go; Chin, Takaaki; Tsuji, Toshio

2017-01-01

This paper proposes an artificial electromyogram (EMG) signal generation model based on signal-dependent noise, which has been ignored in existing methods, by introducing the stochastic construction of the EMG signals. In the proposed model, an EMG signal variance value is first generated from a probability distribution with a shape determined by a commanded muscle force and signal-dependent noise. Artificial EMG signals are then generated from the associated Gaussian distribution with a zero mean and the generated variance. This facilitates representation of artificial EMG signals with signal-dependent noise superimposed according to the muscle activation levels. The frequency characteristics of the EMG signals are also simulated via a shaping filter with parameters determined by an autoregressive model. An estimation method to determine EMG variance distribution using rectified and smoothed EMG signals, thereby allowing model parameter estimation with a small number of samples, is also incorporated in the proposed model. Moreover, the prediction of variance distribution with strong muscle contraction from EMG signals with low muscle contraction and related artificial EMG generation are also described. The results of experiments conducted, in which the reproduction capability of the proposed model was evaluated through comparison with measured EMG signals in terms of amplitude, frequency content, and EMG distribution demonstrate that the proposed model can reproduce the features of measured EMG signals. Further, utilizing the generated EMG signals as training data for a neural network resulted in the classification of upper limb motion with a higher precision than by learning from only measured EMG signals. This indicates that the proposed model is also applicable to motion classification. PMID:28640883

Static analysis of rectifier cabinet for nuclear power generating stations based on finite element method

NASA Astrophysics Data System (ADS)

Yin, Qiang; Chen, Tian-jin; Li, Wei-yang; Xiong, Ze-cheng; Ma, Rui

2017-09-01

In order to obtain the deformation map and equivalent stress distribution of rectifier cabinet for nuclear power generating stations, the quality distribution of structure and electrical are described, the tensile bond strengths of the rings are checked, and the finite element model of cabinet is set up by ANSYS. The transport conditions of the hoisting state and fork loading state are analyzed. The deformation map and equivalent stress distribution are obtained. The attentive problems are put forward. It is a reference for analysis method and the obtained results for the transport of rectifier cabinet for nuclear power generating stations.

Study of distributed fiber-optic laser-ultrasound generation based on ghost-mode of tilted fiber Bragg gratings

NASA Astrophysics Data System (ADS)

Tian, Jiajun; Zhang, Qi; Han, Ming

2013-05-01

Fiber-optic ultrasonic transducers are an important component of an active ultrasonic testing system for structural health monitoring. Fiber-optic transducers have several advantages such as small size, light weight, and immunity to electromagnetic interference that make them much more attractive than the current available piezoelectric transducers, especially as embedded and permanent transducers in active ultrasonic testing for structural health monitoring. In this paper, a distributed fiber-optic laser-ultrasound generation based on the ghost-mode of tilted fiber Bragg gratings is studied. The influences of the laser power and laser pulse duration on the laser-ultrasound generation are investigated. The results of this paper are helpful to understand the working principle of this laser-ultrasound method and improve the ultrasonic generation efficiency.

Anti-islanding Protection of Distributed Generation Using Rate of Change of Impedance

NASA Astrophysics Data System (ADS)

Shah, Pragnesh; Bhalja, Bhavesh

2013-08-01

Distributed Generation (DG), which is interlinked with distribution system, has inevitable effect on distribution system. Integrating DG with the utility network demands an anti-islanding scheme to protect the system. Failure to trip islanded generators can lead to problems such as threats to personnel safety, out-of-phase reclosing, and degradation of power quality. In this article, a new method for anti-islanding protection based on impedance monitoring of distribution network is carried out in presence of DG. The impedance measured between two phases is used to derive the rate of change of impedance (dz/dt), and its peak values are used for final trip decision. Test data are generated using PSCAD/EMTDC software package and the performance of the proposed method is evaluated in MatLab software. The simulation results show the effectiveness of the proposed scheme as it is capable to detect islanding condition accurately. Subsequently, it is also observed that the proposed scheme does not mal-operate during other disturbances such as short circuit and switching event.

Automatic generation of efficient array redistribution routines for distributed memory multicomputers

NASA Technical Reports Server (NTRS)

Ramaswamy, Shankar; Banerjee, Prithviraj

1994-01-01

Appropriate data distribution has been found to be critical for obtaining good performance on Distributed Memory Multicomputers like the CM-5, Intel Paragon and IBM SP-1. It has also been found that some programs need to change their distributions during execution for better performance (redistribution). This work focuses on automatically generating efficient routines for redistribution. We present a new mathematical representation for regular distributions called PITFALLS and then discuss algorithms for redistribution based on this representation. One of the significant contributions of this work is being able to handle arbitrary source and target processor sets while performing redistribution. Another important contribution is the ability to handle an arbitrary number of dimensions for the array involved in the redistribution in a scalable manner. Our implementation of these techniques is based on an MPI-like communication library. The results presented show the low overheads for our redistribution algorithm as compared to naive runtime methods.

Statistical analysis of multivariate atmospheric variables. [cloud cover

NASA Technical Reports Server (NTRS)

Tubbs, J. D.

1979-01-01

Topics covered include: (1) estimation in discrete multivariate distributions; (2) a procedure to predict cloud cover frequencies in the bivariate case; (3) a program to compute conditional bivariate normal parameters; (4) the transformation of nonnormal multivariate to near-normal; (5) test of fit for the extreme value distribution based upon the generalized minimum chi-square; (6) test of fit for continuous distributions based upon the generalized minimum chi-square; (7) effect of correlated observations on confidence sets based upon chi-square statistics; and (8) generation of random variates from specified distributions.

Cooperative Optimal Coordination for Distributed Energy Resources

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

Yang, Tao; Wu, Di; Ren, Wei

In this paper, we consider the optimal coordination problem for distributed energy resources (DERs) including distributed generators and energy storage devices. We propose an algorithm based on the push-sum and gradient method to optimally coordinate storage devices and distributed generators in a distributed manner. In the proposed algorithm, each DER only maintains a set of variables and updates them through information exchange with a few neighbors over a time-varying directed communication network. We show that the proposed distributed algorithm solves the optimal DER coordination problem if the time-varying directed communication network is uniformly jointly strongly connected, which is a mildmore » condition on the connectivity of communication topologies. The proposed distributed algorithm is illustrated and validated by numerical simulations.« less

Effects of voltage control in utility interactive dispersed storage and generation systems

NASA Technical Reports Server (NTRS)

Kirkham, H.; Das, R.

1983-01-01

When a small generator is connected to the distribution system, the voltage at the point of interconnection is determined largely by the system and not the generator. The effect on the generator, on the load voltage and on the distribution system of a number of different voltage control strategies in the generator is examined. Synchronous generators with three kinds of exciter control are considered, as well as induction generators and dc/ac inverters, with and without capacitor compensation. The effect of varying input power during operation (which may be experienced by generators based on renewable resources) is explored, as well as the effect of connecting and disconnecting the generator at ten percent of its rated power. Operation with a constant slightly lagging factor is shown to have some advantages.

Optimization of active distribution networks: Design and analysis of significative case studies for enabling control actions of real infrastructure

NASA Astrophysics Data System (ADS)

Moneta, Diana; Mora, Paolo; Viganò, Giacomo; Alimonti, Gianluca

2014-12-01

The diffusion of Distributed Generation (DG) based on Renewable Energy Sources (RES) requires new strategies to ensure reliable and economic operation of the distribution networks and to support the diffusion of DG itself. An advanced algorithm (DISCoVER - DIStribution Company VoltagE Regulator) is being developed to optimize the operation of active network by means of an advanced voltage control based on several regulations. Starting from forecasted load and generation, real on-field measurements, technical constraints and costs for each resource, the algorithm generates for each time period a set of commands for controllable resources that guarantees achievement of technical goals minimizing the overall cost. Before integrating the controller into the telecontrol system of the real networks, and in order to validate the proper behaviour of the algorithm and to identify possible critical conditions, a complete simulation phase has started. The first step is concerning the definition of a wide range of "case studies", that are the combination of network topology, technical constraints and targets, load and generation profiles and "costs" of resources that define a valid context to test the algorithm, with particular focus on battery and RES management. First results achieved from simulation activity on test networks (based on real MV grids) and actual battery characteristics are given, together with prospective performance on real case applications.

Research on the control strategy of distributed energy resources inverter based on improved virtual synchronous generator.

PubMed

Gao, Changwei; Liu, Xiaoming; Chen, Hai

2017-08-22

This paper focus on the power fluctuations of the virtual synchronous generator(VSG) during the transition process. An improved virtual synchronous generator(IVSG) control strategy based on feed-forward compensation is proposed. Adjustable parameter of the compensation section can be modified to achieve the goal of reducing the order of the system. It can effectively suppress the power fluctuations of the VSG in transient process. To verify the effectiveness of the proposed control strategy for distributed energy resources inverter, the simulation model is set up in MATLAB/SIMULINK platform and physical experiment platform is established. Simulation and experiment results demonstrate the effectiveness of the proposed IVSG control strategy.

Critical side channel effects in random bit generation with multiple semiconductor lasers in a polarization-based quantum key distribution system.

PubMed

Ko, Heasin; Choi, Byung-Seok; Choe, Joong-Seon; Kim, Kap-Joong; Kim, Jong-Hoi; Youn, Chun Ju

2017-08-21

Most polarization-based BB84 quantum key distribution (QKD) systems utilize multiple lasers to generate one of four polarization quantum states randomly. However, random bit generation with multiple lasers can potentially open critical side channels that significantly endangers the security of QKD systems. In this paper, we show unnoticed side channels of temporal disparity and intensity fluctuation, which possibly exist in the operation of multiple semiconductor laser diodes. Experimental results show that the side channels can enormously degrade security performance of QKD systems. An important system issue for the improvement of quantum bit error rate (QBER) related with laser driving condition is further addressed with experimental results.

Autonomous Decentralized Control of Supply and Demand by Inverter Based Distributed Generations in Isolated Microgrid

NASA Astrophysics Data System (ADS)

Shiki, Akira; Yokoyama, Akihiko; Baba, Jyunpei; Takano, Tomihiro; Gouda, Takahiro; Izui, Yoshio

Recently, because of the environmental burden mitigation, energy conservations, energy security, and cost reductions, distributed generations are attracting our strong attention. These distributed generations (DGs) have been already installed to the distribution system, and much more DGs will be expected to be connected in the future. On the other hand, a new concept called “Microgrid” which is a small power supply network consisting of only DGs was proposed and some prototype projects are ongoing in Japan. The purpose of this paper is to develop the three-phase instantaneous valued digital simulator of microgrid consisting of a lot of inverter based DGs and to develop a supply and demand control method in isolated microgrid. First, microgrid is modeled using MATLAB/SIMULINK. We develop models of three-phase instantaneous valued inverter type CVCF generator, PQ specified generator, PV specified generator, PQ specified load as storage battery, photovoltaic generation, fuel cell and inverter load respectively. Then we propose an autonomous decentralized control method of supply and demand in isolated microgrid where storage batteries, fuel cells, photovoltaic generations and loads are connected. It is proposed here that the system frequency is used as a means to control DG output. By changing the frequency of the storage battery due to unbalance of supply and demand, all inverter based DGs detect the frequency fluctuation and change their own outputs. Finally, a new frequency control method in autonomous decentralized control of supply and demand is proposed. Though the frequency is used to transmit the information on the supply and demand unbalance to DGs, after the frequency plays the role, the frequency finally has to return to a standard value. To return the frequency to the standard value, the characteristic curve of the fuel cell is shifted in parallel. This control is carried out corresponding to the fluctuation of the load. The simulation shows that the frequency can be controlled well and has been made clear the effectiveness of the frequency control system.

A simulation-based efficiency comparison of AC and DC power distribution networks in commercial buildings

DOE PAGES

Gerber, Daniel L.; Vossos, Vagelis; Feng, Wei; ...

2017-06-12

Direct current (DC) power distribution has recently gained traction in buildings research due to the proliferation of on-site electricity generation and battery storage, and an increasing prevalence of internal DC loads. The research discussed in this paper uses Modelica-based simulation to compare the efficiency of DC building power distribution with an equivalent alternating current (AC) distribution. The buildings are all modeled with solar generation, battery storage, and loads that are representative of the most efficient building technology. A variety of paramet ric simulations determine how and when DC distribution proves advantageous. These simulations also validate previous studies that use simplermore » approaches and arithmetic efficiency models. This work shows that using DC distribution can be considerably more efficient: a medium sized office building using DC distribution has an expected baseline of 12% savings, but may also save up to 18%. In these results, the baseline simulation parameters are for a zero net energy (ZNE) building that can island as a microgrid. DC is most advantageous in buildings with large solar capacity, large battery capacity, and high voltage distribution.« less

A simulation-based efficiency comparison of AC and DC power distribution networks in commercial buildings

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

Gerber, Daniel L.; Vossos, Vagelis; Feng, Wei

Direct current (DC) power distribution has recently gained traction in buildings research due to the proliferation of on-site electricity generation and battery storage, and an increasing prevalence of internal DC loads. The research discussed in this paper uses Modelica-based simulation to compare the efficiency of DC building power distribution with an equivalent alternating current (AC) distribution. The buildings are all modeled with solar generation, battery storage, and loads that are representative of the most efficient building technology. A variety of paramet ric simulations determine how and when DC distribution proves advantageous. These simulations also validate previous studies that use simplermore » approaches and arithmetic efficiency models. This work shows that using DC distribution can be considerably more efficient: a medium sized office building using DC distribution has an expected baseline of 12% savings, but may also save up to 18%. In these results, the baseline simulation parameters are for a zero net energy (ZNE) building that can island as a microgrid. DC is most advantageous in buildings with large solar capacity, large battery capacity, and high voltage distribution.« less

Spatial Signal Characteristics of Shallow Paraboloidal Shell Structronic Systems

NASA Astrophysics Data System (ADS)

Yue, H. H.; Deng, Z. Q.; Tzou, H. S.

Based on the smart material and structronics technology, distributed sensor and control of shell structures have been rapidly developed for the last twenty years. This emerging technology has been utilized in aerospace, telecommunication, micro-electromechanical systems and other engineering applications. However, distributed monitoring technique and its resulting global spatially distributed sensing signals of thin flexible membrane shells are not clearly understood. In this paper, modeling of free thin paraboloidal shell with spatially distributed sensor, micro-sensing signal characteristics, and location of distributed piezoelectric sensor patches are investigated based on a new set of assumed mode shape functions. Parametric analysis indicates that the signal generation depends on modal membrane strains in the meridional and circumferential directions in which the latter is more significant than the former, when all bending strains vanish in membrane shells. This study provides a modeling and analysis technique for distributed sensors laminated on lightweight paraboloidal flexible structures and identifies critical components and regions that generate significant signals.

Spatial Burnout in Water Reactors with Nonuniform Startup Distributions of Uranium and Boron

NASA Technical Reports Server (NTRS)

Fox, Thomas A.; Bogart, Donald

1955-01-01

Spatial burnout calculations have been made of two types of water moderated cylindrical reactor using boron as a burnable poison to increase reactor life. Specific reactors studied were a version of the Submarine Advanced Reactor (sAR) and a supercritical water reactor (SCW) . Burnout characteristics such as reactivity excursion, neutron-flux and heat-generation distributions, and uranium and boron distributions have been determined for core lives corresponding to a burnup of approximately 7 kilograms of fully enriched uranium. All reactivity calculations have been based on the actual nonuniform distribution of absorbers existing during intervals of core life. Spatial burnout of uranium and boron and spatial build-up of fission products and equilibrium xenon have been- considered. Calculations were performed on the NACA nuclear reactor simulator using two-group diff'usion theory. The following reactor burnout characteristics have been demonstrated: 1. A significantly lower excursion in reactivity during core life may be obtained by nonuniform rather than uniform startup distribution of uranium. Results for SCW with uranium distributed to provide constant radial heat generation and a core life corresponding to a uranium burnup of 7 kilograms indicated a maximum excursion in reactivity of 2.5 percent. This compared to a maximum excursion of 4.2 percent obtained for the same core life when w'anium was uniformly distributed at startup. Boron was incorporated uniformly in these cores at startup. 2. It is possible to approach constant radial heat generation during the life of a cylindrical core by means of startup nonuniform radial and axial distributions of uranium and boron. Results for SCW with nonuniform radial distribution of uranium to provide constant radial heat generation at startup and with boron for longevity indicate relatively small departures from the initially constant radial heat generation distribution during core life. Results for SAR with a sinusoidal distribution rather than uniform axial distributions of boron indicate significant improvements in axial heat generation distribution during the greater part of core life. 3. Uranium investments for cylindrical reactors with nonuniform radial uranium distributions which provide constant radial heat generation per unit core volume are somewhat higher than for reactors with uniform uranium concentration at startup. On the other hand, uranium investments for reactors with axial boron distributions which approach constant axial heat generation are somewhat smaller than for reactors with uniform boron distributions at startup.

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.

On hydrologic similarity: A dimensionless flood frequency model using a generalized geomorphologic unit hydrograph and partial area runoff generation

NASA Technical Reports Server (NTRS)

Sivapalan, Murugesu; Wood, Eric F.; Beven, Keith J.

1993-01-01

One of the shortcomings of the original theory of the geomorphologic unit hydrograph (GUH) is that it assumes that runoff is generated uniformly from the entire catchment area. It is now recognized that in many catchments much of the runoff during storm events is produced on partial areas which usually form on narrow bands along the stream network. A storm response model that includes runoff generation on partial areas by both Hortonian and Dunne mechanisms was recently developed by the authors. In this paper a methodology for integrating this partial area runoff generation model with the GUH-based runoff routing model is presented; this leads to a generalized GUH. The generalized GUH and the storm response model are then used to estimate physically based flood frequency distributions. In most previous work the initial moisture state of the catchment had been assumed to be constant for all the storms. In this paper we relax this assumption and allow the initial moisture conditions to vary between storms. The resulting flood frequency distributions are cast in a scaled dimensionless framework where issues such as catchment scale and similarity can be conveniently addressed. A number of experiments are performed to study the sensitivity of the flood frequency response to some of the 'similarity' parameters identified in this formulation. The results indicate that one of the most important components of the derived flood frequency model relates to the specification of processes within the runoff generation model; specifically the inclusion of both saturation excess and Horton infiltration excess runoff production mechanisms. The dominance of these mechanisms over different return periods of the flood frequency distribution can significantly affect the distributional shape and confidence limits about the distribution. Comparisons with observed flood distributions seem to indicate that such mixed runoff production mechanisms influence flood distribution shape. The sensitivity analysis also indicated that the incorporation of basin and rainfall storm scale also greatly influences the distributional shape of the flood frequency curve.

Inference for multivariate regression model based on multiply imputed synthetic data generated via posterior predictive sampling

NASA Astrophysics Data System (ADS)

Moura, Ricardo; Sinha, Bimal; Coelho, Carlos A.

2017-06-01

The recent popularity of the use of synthetic data as a Statistical Disclosure Control technique has enabled the development of several methods of generating and analyzing such data, but almost always relying in asymptotic distributions and in consequence being not adequate for small sample datasets. Thus, a likelihood-based exact inference procedure is derived for the matrix of regression coefficients of the multivariate regression model, for multiply imputed synthetic data generated via Posterior Predictive Sampling. Since it is based in exact distributions this procedure may even be used in small sample datasets. Simulation studies compare the results obtained from the proposed exact inferential procedure with the results obtained from an adaptation of Reiters combination rule to multiply imputed synthetic datasets and an application to the 2000 Current Population Survey is discussed.

A novel approach for modelling vegetation distributions and analysing vegetation sensitivity through trait-climate relationships in China

PubMed Central

Yang, Yanzheng; Zhu, Qiuan; Peng, Changhui; Wang, Han; Xue, Wei; Lin, Guanghui; Wen, Zhongming; Chang, Jie; Wang, Meng; Liu, Guobin; Li, Shiqing

2016-01-01

Increasing evidence indicates that current dynamic global vegetation models (DGVMs) have suffered from insufficient realism and are difficult to improve, particularly because they are built on plant functional type (PFT) schemes. Therefore, new approaches, such as plant trait-based methods, are urgently needed to replace PFT schemes when predicting the distribution of vegetation and investigating vegetation sensitivity. As an important direction towards constructing next-generation DGVMs based on plant functional traits, we propose a novel approach for modelling vegetation distributions and analysing vegetation sensitivity through trait-climate relationships in China. The results demonstrated that a Gaussian mixture model (GMM) trained with a LMA-Nmass-LAI data combination yielded an accuracy of 72.82% in simulating vegetation distribution, providing more detailed parameter information regarding community structures and ecosystem functions. The new approach also performed well in analyses of vegetation sensitivity to different climatic scenarios. Although the trait-climate relationship is not the only candidate useful for predicting vegetation distributions and analysing climatic sensitivity, it sheds new light on the development of next-generation trait-based DGVMs. PMID:27052108

Automated Planning and Scheduling for Planetary Rover Distributed Operations

NASA Technical Reports Server (NTRS)

Backes, Paul G.; Rabideau, Gregg; Tso, Kam S.; Chien, Steve

1999-01-01

Automated planning and Scheduling, including automated path planning, has been integrated with an Internet-based distributed operations system for planetary rover operations. The resulting prototype system enables faster generation of valid rover command sequences by a distributed planetary rover operations team. The Web Interface for Telescience (WITS) provides Internet-based distributed collaboration, the Automated Scheduling and Planning Environment (ASPEN) provides automated planning and scheduling, and an automated path planner provided path planning. The system was demonstrated on the Rocky 7 research rover at JPL.

Local operators in kinetic wealth distribution

NASA Astrophysics Data System (ADS)

Andrecut, M.

2016-05-01

The statistical mechanics approach to wealth distribution is based on the conservative kinetic multi-agent model for money exchange, where the local interaction rule between the agents is analogous to the elastic particle scattering process. Here, we discuss the role of a class of conservative local operators, and we show that, depending on the values of their parameters, they can be used to generate all the relevant distributions. We also show numerically that in order to generate the power-law tail, an heterogeneous risk aversion model is required. By changing the parameters of these operators, one can also fine tune the resulting distributions in order to provide support for the emergence of a more egalitarian wealth distribution.

Resilient Distribution System by Microgrids Formation After Natural Disasters

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

Chen, Chen; Wang, Jianhui; Qiu, Feng

2016-03-01

Microgrids with distributed generation provide a resilient solution in the case of major faults in a distribution system due to natural disasters. This paper proposes a novel distribution system operational approach by forming multiple microgrids energized by distributed generation from the radial distribution system in real-time operations, to restore critical loads from the power outage. Specifically, a mixed-integer linear program (MILP) is formulated to maximize the critical loads to be picked up while satisfying the self-adequacy and operation constraints for the microgrids formation problem, by controlling the ON/OFF status of the remotely controlled switch devices and distributed generation. A distributedmore » multi-agent coordination scheme is designed via local communications for the global information discovery as inputs of the optimization, which is suitable for autonomous communication requirements after the disastrous event. The formed microgrids can be further utilized for power quality control and can be connected to a larger microgrid before the restoration of the main grids is complete. Numerical results based on modified IEEE distribution test systems validate the effectiveness of our proposed scheme.« less

Size distributions of micro-bubbles generated by a pressurized dissolution method

NASA Astrophysics Data System (ADS)

Taya, C.; Maeda, Y.; Hosokawa, S.; Tomiyama, A.; Ito, Y.

2012-03-01

Size of micro-bubbles is widely distributed in the range of one to several hundreds micrometers and depends on generation methods, flow conditions and elapsed times after the bubble generation. Although a size distribution of micro-bubbles should be taken into account to improve accuracy in numerical simulations of flows with micro-bubbles, a variety of the size distribution makes it difficult to introduce the size distribution in the simulations. On the other hand, several models such as the Rosin-Rammler equation and the Nukiyama-Tanazawa equation have been proposed to represent the size distribution of particles or droplets. Applicability of these models to the size distribution of micro-bubbles has not been examined yet. In this study, we therefore measure size distribution of micro-bubbles generated by a pressurized dissolution method by using a phase Doppler anemometry (PDA), and investigate the applicability of the available models to the size distributions of micro-bubbles. Experimental apparatus consists of a pressurized tank in which air is dissolved in liquid under high pressure condition, a decompression nozzle in which micro-bubbles are generated due to pressure reduction, a rectangular duct and an upper tank. Experiments are conducted for several liquid volumetric fluxes in the decompression nozzle. Measurements are carried out at the downstream region of the decompression nozzle and in the upper tank. The experimental results indicate that (1) the Nukiyama-Tanasawa equation well represents the size distribution of micro-bubbles generated by the pressurized dissolution method, whereas the Rosin-Rammler equation fails in the representation, (2) the bubble size distribution of micro-bubbles can be evaluated by using the Nukiyama-Tanasawa equation without individual bubble diameters, when mean bubble diameter and skewness of the bubble distribution are given, and (3) an evaluation method of visibility based on the bubble size distribution and bubble number density is proposed, and the evaluated visibility agrees well with the visibility measured in the upper tank.

Semantic attributes based texture generation

NASA Astrophysics Data System (ADS)

Chi, Huifang; Gan, Yanhai; Qi, Lin; Dong, Junyu; Madessa, Amanuel Hirpa

2018-04-01

Semantic attributes are commonly used for texture description. They can be used to describe the information of a texture, such as patterns, textons, distributions, brightness, and so on. Generally speaking, semantic attributes are more concrete descriptors than perceptual features. Therefore, it is practical to generate texture images from semantic attributes. In this paper, we propose to generate high-quality texture images from semantic attributes. Over the last two decades, several works have been done on texture synthesis and generation. Most of them focusing on example-based texture synthesis and procedural texture generation. Semantic attributes based texture generation still deserves more devotion. Gan et al. proposed a useful joint model for perception driven texture generation. However, perceptual features are nonobjective spatial statistics used by humans to distinguish different textures in pre-attentive situations. To give more describing information about texture appearance, semantic attributes which are more in line with human description habits are desired. In this paper, we use sigmoid cross entropy loss in an auxiliary model to provide enough information for a generator. Consequently, the discriminator is released from the relatively intractable mission of figuring out the joint distribution of condition vectors and samples. To demonstrate the validity of our method, we compare our method to Gan et al.'s method on generating textures by designing experiments on PTD and DTD. All experimental results show that our model can generate textures from semantic attributes.

Using Copula Distributions to Support More Accurate Imaging-Based Diagnostic Classifiers for Neuropsychiatric Disorders

PubMed Central

Bansal, Ravi; Hao, Xuejun; Liu, Jun; Peterson, Bradley S.

2014-01-01

Many investigators have tried to apply machine learning techniques to magnetic resonance images (MRIs) of the brain in order to diagnose neuropsychiatric disorders. Usually the number of brain imaging measures (such as measures of cortical thickness and measures of local surface morphology) derived from the MRIs (i.e., their dimensionality) has been large (e.g. >10) relative to the number of participants who provide the MRI data (<100). Sparse data in a high dimensional space increases the variability of the classification rules that machine learning algorithms generate, thereby limiting the validity, reproducibility, and generalizability of those classifiers. The accuracy and stability of the classifiers can improve significantly if the multivariate distributions of the imaging measures can be estimated accurately. To accurately estimate the multivariate distributions using sparse data, we propose to estimate first the univariate distributions of imaging data and then combine them using a Copula to generate more accurate estimates of their multivariate distributions. We then sample the estimated Copula distributions to generate dense sets of imaging measures and use those measures to train classifiers. We hypothesize that the dense sets of brain imaging measures will generate classifiers that are stable to variations in brain imaging measures, thereby improving the reproducibility, validity, and generalizability of diagnostic classification algorithms in imaging datasets from clinical populations. In our experiments, we used both computer-generated and real-world brain imaging datasets to assess the accuracy of multivariate Copula distributions in estimating the corresponding multivariate distributions of real-world imaging data. Our experiments showed that diagnostic classifiers generated using imaging measures sampled from the Copula were significantly more accurate and more reproducible than were the classifiers generated using either the real-world imaging measures or their multivariate Gaussian distributions. Thus, our findings demonstrate that estimated multivariate Copula distributions can generate dense sets of brain imaging measures that can in turn be used to train classifiers, and those classifiers are significantly more accurate and more reproducible than are those generated using real-world imaging measures alone. PMID:25093634

Two dimensional distribution measurement of electric current generated in a polymer electrolyte fuel cell using 49 NMR surface coils.

PubMed

Ogawa, Kuniyasu; Sasaki, Tatsuyoshi; Yoneda, Shigeki; Tsujinaka, Kumiko; Asai, Ritsuko

2018-05-17

In order to increase the current density generated in a PEFC (polymer electrolyte fuel cell), a method for measuring the spatial distribution of both the current and the water content of the MEA (membrane electrode assembly) is necessary. Based on the frequency shifts of NMR (nuclear magnetic resonance) signals acquired from the water contained in the MEA using 49 NMR coils in a 7 × 7 arrangement inserted in the PEFC, a method for measuring the two-dimensional spatial distribution of electric current generated in a unit cell with a power generation area of 140 mm × 160 mm was devised. We also developed an inverse analysis method to determine the two-dimensional electric current distribution that can be applied to actual PEFC connections. Two analytical techniques, namely coarse graining of segments and stepwise search, were used to shorten the calculation time required for inverse analysis of the electric current map. Using this method and techniques, spatial distributions of electric current and water content in the MEA were obtained when the PEFC generated electric power at 100 A. Copyright © 2018 Elsevier Inc. All rights reserved.

Exploring changes in the spatial distribution of stream baseflow generation during a seasonal recession

USGS Publications Warehouse

Payn, R.A.; Gooseff, M.N.; McGlynn, B.L.; Bencala, K.E.; Wondzell, S.M.

2012-01-01

Relating watershed structure to streamflow generation is a primary focus of hydrology. However, comparisons of longitudinal variability in stream discharge with adjacent valley structure have been rare, resulting in poor understanding of the distribution of the hydrologic mechanisms that cause variability in streamflow generation along valleys. This study explores detailed surveys of stream base flow across a gauged, 23 km2 mountain watershed. Research objectives were (1) to relate spatial variability in base flow to fundamental elements of watershed structure, primarily topographic contributing area, and (2) to assess temporal changes in the spatial patterns of those relationships during a seasonal base flow recession. We analyzed spatiotemporal variability in base flow using (1) summer hydrographs at the study watershed outlet and 5 subwatershed outlets and (2) longitudinal series of discharge measurements every ~100 m along the streams of the 3 largest subwatersheds (1200 to 2600 m in valley length), repeated 2 to 3 times during base flow recession. Reaches within valley segments of 300 to 1200 m in length tended to demonstrate similar streamflow generation characteristics. Locations of transitions between these segments were consistent throughout the recession, and tended to be collocated with abrupt longitudinal transitions in valley slope or hillslope-riparian characteristics. Both within and among subwatersheds, correlation between the spatial distributions of streamflow and topographic contributing area decreased during the recession, suggesting a general decrease in the influence of topography on stream base flow contributions. As topographic controls on base flow evidently decreased, multiple aspects of subsurface structure were likely to have gained influence.

ITMS: Individualized Teaching Material System: Adaptive Integration of Web Pages Distributed in Some Servers.

ERIC Educational Resources Information Center

Mitsuhara, Hiroyuki; Kurose, Yoshinobu; Ochi, Youji; Yano, Yoneo

The authors developed a Web-based Adaptive Educational System (Web-based AES) named ITMS (Individualized Teaching Material System). ITMS adaptively integrates knowledge on the distributed Web pages and generates individualized teaching material that has various contents. ITMS also presumes the learners' knowledge levels from the states of their…

Consideration effect of wind farms on the network reconfiguration in the distribution systems in an uncertain environment

NASA Astrophysics Data System (ADS)

Rahmani, Kianoosh; Kavousifard, Farzaneh; Abbasi, Alireza

2017-09-01

This article proposes a novel probabilistic Distribution Feeder Reconfiguration (DFR) based method to consider the uncertainty impacts into account with high accuracy. In order to achieve the set aim, different scenarios are generated to demonstrate the degree of uncertainty in the investigated elements which are known as the active and reactive load consumption and the active power generation of the wind power units. Notably, a normal Probability Density Function (PDF) based on the desired accuracy is divided into several class intervals for each uncertain parameter. Besides, the Weiball PDF is utilised for modelling wind generators and taking the variation impacts of the power production in wind generators. The proposed problem is solved based on Fuzzy Adaptive Modified Particle Swarm Optimisation to find the most optimal switching scheme during the Multi-objective DFR. Moreover, this paper holds two suggestions known as new mutation methods to adjust the inertia weight of PSO by the fuzzy rules to enhance its ability in global searching within the entire search space.

Growth, chamber building rate and reproduction time of Palaeonummulites venosus under natural conditions.

NASA Astrophysics Data System (ADS)

Kinoshita, Shunichi; Eder, Wolfgang; Wöger, Julia; Hohenegger, Johann; Briguglio, Antonino

2017-04-01

Investigations on Palaeonummulites venosus using the natural laboratory approach for determining chamber building rate, test diameter increase rate, reproduction time and longevity is based on the decomposition of monthly obtained frequency distributions based on chamber number and test diameter into normal-distributed components. The shift of the component parameters 'mean' and 'standard deviation' during the investigation period of 15 months was used to calculate Michaelis-Menten functions applied to estimate the averaged chamber building rate and diameter increase rate under natural conditions. The individual dates of birth were estimated using the inverse averaged chamber building rate and the inverse diameter increase rate fitted by the individual chamber number or the individual test diameter at the sampling date. Distributions of frequencies and densities (i.e. frequency divided by sediment weight) based on chamber building rate and diameter increase rate resulted both in a continuous reproduction through the year with two peaks, the stronger in May /June determined as the beginning of the summer generation (generation1) and the weaker in November determined as the beginning of the winter generation (generation 2). This reproduction scheme explains the existence of small and large specimens in the same sample. Longevity, calculated as the maximum difference in days between the individual's birth date and the sampling date seems to be round about one year, obtained by both estimations based on the chamber building rate and the diameter increase rate.

Nanoscale inhomogeneity and photoacid generation dynamics in extreme ultraviolet resist materials

NASA Astrophysics Data System (ADS)

Wu, Ping-Jui; Wang, Yu-Fu; Chen, Wei-Chi; Wang, Chien-Wei; Cheng, Joy; Chang, Vencent; Chang, Ching-Yu; Lin, John; Cheng, Yuan-Chung

2018-03-01

The development of extreme ultraviolet (EUV) lithography towards the 22 nm node and beyond depends critically on the availability of resist materials that meet stringent control requirements in resolution, line edge roughness, and sensitivity. However, the molecular mechanisms that govern the structure-function relationships in current EUV resist systems are not well understood. In particular, the nanoscale structures of the polymer base and the distributions of photoacid generators (PAGs) should play a critical roles in the performance of a resist system, yet currently available models for photochemical reactions in EUV resist systems are exclusively based on homogeneous bulk models that ignore molecular-level details of solid resist films. In this work, we investigate how microscopic molecular organizations in EUV resist affect photoacid generations in a bottom-up approach that describes structure-dependent electron-transfer dynamics in a solid film model. To this end, molecular dynamics simulations and stimulated annealing are used to obtain structures of a large simulation box containing poly(4-hydroxystyrene) (PHS) base polymers and triphenylsulfonium based PAGs. Our calculations reveal that ion-pair interactions govern the microscopic distributions of the polymer base and PAG molecules, resulting in a highly inhomogeneous system with nonuniform nanoscale chemical domains. Furthermore, the theoretical structures were used in combination of quantum chemical calculations and the Marcus theory to evaluate electron transfer rates between molecular sites, and then kinetic Monte Carlo simulations were carried out to model electron transfer dynamics with molecular structure details taken into consideration. As a result, the portion of thermalized electrons that are absorbed by the PAGs and the nanoscale spatial distribution of generated acids can be estimated. Our data reveal that the nanoscale inhomogeneous distributions of base polymers and PAGs strongly affect the electron transfer and the performance of the resist system. The implications to the performances of EUV resists and key engineering requirements for improved resist systems will also be discussed in this work. Our results shed light on the fundamental structure dependence of photoacid generation and the control of the nanoscale structures as well as base polymer-PAG interactions in EVU resist systems, and we expect these knowledge will be useful for the future development of improved EUV resist systems.

Fast Grid Frequency Support from Distributed Inverter-Based Resources

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

Hoke, Anderson F

This presentation summarizes power hardware-in-the-loop testing performed to evaluate the ability of distributed inverter-coupled generation to support grid frequency on the fastest time scales. The research found that distributed PV inverters and other DERs can effectively support the grid on sub-second time scales.

Review, mapping and analysis of the agricultural plastic waste generation and consolidation in Europe.

PubMed

Briassoulis, Demetres; Babou, Epifania; Hiskakis, Miltiadis; Scarascia, Giacomo; Picuno, Pietro; Guarde, Dorleta; Dejean, Cyril

2013-12-01

A review of agricultural plastic waste generation and consolidation in Europe is presented. A detailed geographical mapping of the agricultural plastic use and waste generation in Europe was conducted focusing on areas of high concentration of agricultural plastics. Quantitative data and analysis of the agricultural plastic waste generation by category, geographical distribution and compositional range, and physical characteristics of the agricultural plastic waste per use and the temporal distribution of the waste generation are presented. Data were collected and cross-checked from a variety of sources, including European, national and regional services and organizations, local agronomists, retailers and farmers, importers and converters. Missing data were estimated indirectly based on the recorded cultivated areas and the characteristics of the agricultural plastics commonly used in the particular regions. The temporal distribution, the composition and physical characteristics of the agricultural plastic waste streams were mapped by category and by application. This study represents the first systematic effort to map and analyse agricultural plastic waste generation and consolidation in Europe.

Distributed Generation Planning using Peer Enhanced Multi-objective Teaching-Learning based Optimization in Distribution Networks

NASA Astrophysics Data System (ADS)

Selvam, Kayalvizhi; Vinod Kumar, D. M.; Siripuram, Ramakanth

2017-04-01

In this paper, an optimization technique called peer enhanced teaching learning based optimization (PeTLBO) algorithm is used in multi-objective problem domain. The PeTLBO algorithm is parameter less so it reduced the computational burden. The proposed peer enhanced multi-objective based TLBO (PeMOTLBO) algorithm has been utilized to find a set of non-dominated optimal solutions [distributed generation (DG) location and sizing in distribution network]. The objectives considered are: real power loss and the voltage deviation subjected to voltage limits and maximum penetration level of DG in distribution network. Since the DG considered is capable of injecting real and reactive power to the distribution network the power factor is considered as 0.85 lead. The proposed peer enhanced multi-objective optimization technique provides different trade-off solutions in order to find the best compromise solution a fuzzy set theory approach has been used. The effectiveness of this proposed PeMOTLBO is tested on IEEE 33-bus and Indian 85-bus distribution system. The performance is validated with Pareto fronts and two performance metrics (C-metric and S-metric) by comparing with robust multi-objective technique called non-dominated sorting genetic algorithm-II and also with the basic TLBO.

Echo-Enabled X-Ray Vortex Generation

NASA Astrophysics Data System (ADS)

Hemsing, E.; Marinelli, A.

2012-11-01

A technique to generate high-brightness electromagnetic vortices with tunable topological charge at extreme ultraviolet and x-ray wavelengths is described. Based on a modified version of echo-enabled harmonic generation for free-electron lasers, the technique uses two lasers and two chicanes to produce high-harmonic microbunching of a relativistic electron beam with a corkscrew distribution that matches the instantaneous helical phase structure of the x-ray vortex. The strongly correlated electron distribution emerges from an efficient three-dimensional recoherence effect in the echo-enabled harmonic generation transport line and can emit fully coherent vortices in a downstream radiator for access to new research in x-ray science.

Community-Based Social Networks: Generation of Power Law Degree Distribution and IP Solutions to the KPP

ERIC Educational Resources Information Center

Wu, Wentao

2012-01-01

The objective of this thesis is two-fold: (1) to investigate the degree distribution property of community-based social networks (CSNs) and (2) to provide solutions to a pertinent problem, the Key Player Problem. In the first part of this thesis, we consider a growing community-based network in which the ability of nodes competing for links to new…

Power quality control of an autonomous wind-diesel power system based on hybrid intelligent controller.

PubMed

Ko, Hee-Sang; Lee, Kwang Y; Kang, Min-Jae; Kim, Ho-Chan

2008-12-01

Wind power generation is gaining popularity as the power industry in the world is moving toward more liberalized trade of energy along with public concerns of more environmentally friendly mode of electricity generation. The weakness of wind power generation is its dependence on nature-the power output varies in quite a wide range due to the change of wind speed, which is difficult to model and predict. The excess fluctuation of power output and voltages can influence negatively the quality of electricity in the distribution system connected to the wind power generation plant. In this paper, the authors propose an intelligent adaptive system to control the output of a wind power generation plant to maintain the quality of electricity in the distribution system. The target wind generator is a cost-effective induction generator, while the plant is equipped with a small capacity energy storage based on conventional batteries, heater load for co-generation and braking, and a voltage smoothing device such as a static Var compensator (SVC). Fuzzy logic controller provides a flexible controller covering a wide range of energy/voltage compensation. A neural network inverse model is designed to provide compensating control amount for a system. The system can be optimized to cope with the fluctuating market-based electricity price conditions to lower the cost of electricity consumption or to maximize the power sales opportunities from the wind generation plant.

A New Multivariate Approach in Generating Ensemble Meteorological Forcings for Hydrological Forecasting

NASA Astrophysics Data System (ADS)

Khajehei, Sepideh; Moradkhani, Hamid

2015-04-01

Producing reliable and accurate hydrologic ensemble forecasts are subject to various sources of uncertainty, including meteorological forcing, initial conditions, model structure, and model parameters. Producing reliable and skillful precipitation ensemble forecasts is one approach to reduce the total uncertainty in hydrological applications. Currently, National Weather Prediction (NWP) models are developing ensemble forecasts for various temporal ranges. It is proven that raw products from NWP models are biased in mean and spread. Given the above state, there is a need for methods that are able to generate reliable ensemble forecasts for hydrological applications. One of the common techniques is to apply statistical procedures in order to generate ensemble forecast from NWP-generated single-value forecasts. The procedure is based on the bivariate probability distribution between the observation and single-value precipitation forecast. However, one of the assumptions of the current method is fitting Gaussian distribution to the marginal distributions of observed and modeled climate variable. Here, we have described and evaluated a Bayesian approach based on Copula functions to develop an ensemble precipitation forecast from the conditional distribution of single-value precipitation forecasts. Copula functions are known as the multivariate joint distribution of univariate marginal distributions, which are presented as an alternative procedure in capturing the uncertainties related to meteorological forcing. Copulas are capable of modeling the joint distribution of two variables with any level of correlation and dependency. This study is conducted over a sub-basin in the Columbia River Basin in USA using the monthly precipitation forecasts from Climate Forecast System (CFS) with 0.5x0.5 Deg. spatial resolution to reproduce the observations. The verification is conducted on a different period and the superiority of the procedure is compared with Ensemble Pre-Processor approach currently used by National Weather Service River Forecast Centers in USA.

AC/DC Power Systems with Applications for future Lunar/Mars base and Crew Exploration Vehicle

NASA Technical Reports Server (NTRS)

Chowdhury, Badrul H.

2005-01-01

ABSTRACT The Power Systems branch at JSC faces a number of complex issues as it readies itself for the President's initiative on future space exploration beyond low earth orbit. Some of these preliminary issues - those dealing with electric power generation and distribution on board Mars-bound vehicle and that on Lunar and Martian surface may be summarized as follows: Type of prime mover - Because solar power may not be readily available on parts of the Lunar/Mars surface and also during the long duration flight to Mars, the primary source of power will most likely be nuclear power (Uranium fuel rods) with a secondary source of fuel cell (Hydrogen supply). The electric power generation source - With nuclear power being the main prime mover, the electric power generation source will most likely be an ac generator at a yet to be determined frequency. Thus, a critical issue is whether the generator should generate at constant or variable frequency. This will decide what type of generator to use - whether it is a synchronous machine, an asynchronous induction machine or a switched reluctance machine. The type of power distribution system - the distribution frequency, number of wires (3- wire, 4-wire or higher), and ac/dc hybridization. Building redundancy and fault tolerance in the generation and distribution sub-systems so that the system is safe; provides 100% availability to critical loads; continues to operate even with faulted sub-systems; and requires minimal maintenance. This report descril_es results of a summer faculty fellowship spent in the Power Systems Branch with the specific aim of investigating some of the lessons learned in electric power generation and usage from the terrestrial power systems industry, the aerospace industry as well as NASA's on-going missions so as to recommend novel surface and vehicle-based power systems architectures in support of future space exploration initiatives. A hybrid ac/dc architecture with source side and load side redundancies and including emergency generators on both ac and dc sides is proposed. The generation frequency is 400 Hz mostly because of the technology maturity at this frequency in the aerospace industry. Power will be distributed to several ac load distribution buses through solid state variable speed, constant frequency converters on the ac side. A segmented dc ring bus supplied from ac/dc converters and with the capability of connecting/disconnecting the segments will supply power to multiple de load distribution buses. The system will have the capability of reverse flow from dc to ac side in the case of an extreme emergency on the main ac generation side.

Distributed fiber-optic laser-ultrasound generation based on ghost-mode of tilted fiber Bragg gratings.

PubMed

Tian, Jiajun; Zhang, Qi; Han, Ming

2013-03-11

Active ultrasonic testing is widely used for medical diagnosis, material characterization and structural health monitoring. Ultrasonic transducer is a key component in active ultrasonic testing. Due to their many advantages such as small size, light weight, and immunity to electromagnetic interference, fiber-optic ultrasonic transducers are particularly attractive for permanent, embedded applications in active ultrasonic testing for structural health monitoring. However, current fiber-optic transducers only allow effective ultrasound generation at a single location of the fiber end. Here we demonstrate a fiber-optic device that can effectively generate ultrasound at multiple, selected locations along a fiber in a controllable manner based on a smart light tapping scheme that only taps out the light of a particular wavelength for laser-ultrasound generation and allow light of longer wavelengths pass by without loss. Such a scheme may also find applications in remote fiber-optic device tuning and quasi-distributed biochemical fiber-optic sensing.

Money-center structures in dynamic banking systems

NASA Astrophysics Data System (ADS)

Li, Shouwei; Zhang, Minghui

2016-10-01

In this paper, we propose a dynamic model for banking systems based on the description of balance sheets. It generates some features identified through empirical analysis. Through simulation analysis of the model, we find that banking systems have the feature of money-center structures, that bank asset distributions are power-law distributions, and that contract size distributions are log-normal distributions.

Comprehensive evaluation of impacts of distributed generation integration in distribution network

NASA Astrophysics Data System (ADS)

Peng, Sujiang; Zhou, Erbiao; Ji, Fengkun; Cao, Xinhui; Liu, Lingshuang; Liu, Zifa; Wang, Xuyang; Cai, Xiaoyu

2018-04-01

All Distributed generation (DG) as the supplement to renewable energy centralized utilization, is becoming the focus of development direction of renewable energy utilization. With the increasing proportion of DG in distribution network, the network power structure, power flow distribution, operation plans and protection are affected to some extent. According to the main impacts of DG, a comprehensive evaluation model of distributed network with DG is proposed in this paper. A comprehensive evaluation index system including 7 aspects, along with their corresponding index calculation method is established for quantitative analysis. The indices under different access capacity of DG in distribution network are calculated based on the IEEE RBTS-Bus 6 system and the evaluation result is calculated by analytic hierarchy process (AHP). The proposed model and method are verified effective and validity through case study.

Generating the Local Oscillator "Locally" in Continuous-Variable Quantum Key Distribution Based on Coherent Detection

NASA Astrophysics Data System (ADS)

Qi, Bing; Lougovski, Pavel; Pooser, Raphael; Grice, Warren; Bobrek, Miljko

2015-10-01

Continuous-variable quantum key distribution (CV-QKD) protocols based on coherent detection have been studied extensively in both theory and experiment. In all the existing implementations of CV-QKD, both the quantum signal and the local oscillator (LO) are generated from the same laser and propagate through the insecure quantum channel. This arrangement may open security loopholes and limit the potential applications of CV-QKD. In this paper, we propose and demonstrate a pilot-aided feedforward data recovery scheme that enables reliable coherent detection using a "locally" generated LO. Using two independent commercial laser sources and a spool of 25-km optical fiber, we construct a coherent communication system. The variance of the phase noise introduced by the proposed scheme is measured to be 0.04 (rad2 ), which is small enough to enable secure key distribution. This technology also opens the door for other quantum communication protocols, such as the recently proposed measurement-device-independent CV-QKD, where independent light sources are employed by different users.

A study using a Monte Carlo method of the optimal configuration of a distribution network in terms of power loss sensing.

PubMed

Moon, Hyun Ho; Lee, Jong Joo; Choi, Sang Yule; Cha, Jae Sang; Kang, Jang Mook; Kim, Jong Tae; Shin, Myong Chul

2011-01-01

Recently there have been many studies of power systems with a focus on "New and Renewable Energy" as part of "New Growth Engine Industry" promoted by the Korean government. "New And Renewable Energy"-especially focused on wind energy, solar energy and fuel cells that will replace conventional fossil fuels-is a part of the Power-IT Sector which is the basis of the SmartGrid. A SmartGrid is a form of highly-efficient intelligent electricity network that allows interactivity (two-way communications) between suppliers and consumers by utilizing information technology in electricity production, transmission, distribution and consumption. The New and Renewable Energy Program has been driven with a goal to develop and spread through intensive studies, by public or private institutions, new and renewable energy which, unlike conventional systems, have been operated through connections with various kinds of distributed power generation systems. Considerable research on smart grids has been pursued in the United States and Europe. In the United States, a variety of research activities on the smart power grid have been conducted within EPRI's IntelliGrid research program. The European Union (EU), which represents Europe's Smart Grid policy, has focused on an expansion of distributed generation (decentralized generation) and power trade between countries with improved environmental protection. Thus, there is current emphasis on a need for studies that assesses the economic efficiency of such distributed generation systems. In this paper, based on the cost of distributed power generation capacity, calculations of the best profits obtainable were made by a Monte Carlo simulation. Monte Carlo simulations that rely on repeated random sampling to compute their results take into account the cost of electricity production, daily loads and the cost of sales and generate a result faster than mathematical computations. In addition, we have suggested the optimal design, which considers the distribution loss associated with power distribution systems focus on sensing aspect and distributed power generation.

Distributed bearing fault diagnosis based on vibration analysis

NASA Astrophysics Data System (ADS)

Dolenc, Boštjan; Boškoski, Pavle; Juričić, Đani

2016-01-01

Distributed bearing faults appear under various circumstances, for example due to electroerosion or the progression of localized faults. Bearings with distributed faults tend to generate more complex vibration patterns than those with localized faults. Despite the frequent occurrence of such faults, their diagnosis has attracted limited attention. This paper examines a method for the diagnosis of distributed bearing faults employing vibration analysis. The vibrational patterns generated are modeled by incorporating the geometrical imperfections of the bearing components. Comparing envelope spectra of vibration signals shows that one can distinguish between localized and distributed faults. Furthermore, a diagnostic procedure for the detection of distributed faults is proposed. This is evaluated on several bearings with naturally born distributed faults, which are compared with fault-free bearings and bearings with localized faults. It is shown experimentally that features extracted from vibrations in fault-free, localized and distributed fault conditions form clearly separable clusters, thus enabling diagnosis.

Smart grids: A paradigm shift on energy generation and distribution with the emergence of a new energy management business model

NASA Astrophysics Data System (ADS)

Cardenas, Jesus Alvaro

An energy and environmental crisis will emerge throughout the world if we continue with our current practices of generation and distribution of electricity. A possible solution to this problem is based on the Smart grid concept, which is heavily influenced by Information and Communication Technology (ICT). Although the electricity industry is mostly regulated, there are global models used as roadmaps for Smart Grids' implementation focusing on technologies and the basic generation-distribution-transmission model. This project aims to further enhance a business model for a future global deployment. It takes into consideration the many factors interacting in this energy provision process, based on the diffusion of technologies and literature surveys on the available documents in the Internet as well as peer-reviewed publications. Tariffs and regulations, distributed energy generation, integration of service providers, consumers becoming producers, self-healing devices, and many other elements are shifting this industry into a major change towards liberalization and deregulation of this sector, which has been heavily protected by the government due to the importance of electricity for consumers. We propose an Energy Management Business Model composed by four basic elements: Supply Chain, Information and Communication Technology (ICT), Stakeholders Response, and the resulting Green Efficient Energy (GEE). We support the developed model based on the literature survey, we support it with the diffusion analysis of these elements, and support the overall model with two surveys: one for peers and professionals, and other for experts in the field, based on the Smart Grid Carnegie Melon Maturity Model (CMU SEI SGMM). The contribution of this model is a simple path to follow for entities that want to achieve environmental friendly energy with the involvement of technology and all stakeholders.

Clustering, randomness and regularity in cloud fields. I - Theoretical considerations. II - Cumulus cloud fields

NASA Technical Reports Server (NTRS)

Weger, R. C.; Lee, J.; Zhu, Tianri; Welch, R. M.

1992-01-01

The current controversy existing in reference to the regularity vs. clustering in cloud fields is examined by means of analysis and simulation studies based upon nearest-neighbor cumulative distribution statistics. It is shown that the Poisson representation of random point processes is superior to pseudorandom-number-generated models and that pseudorandom-number-generated models bias the observed nearest-neighbor statistics towards regularity. Interpretation of this nearest-neighbor statistics is discussed for many cases of superpositions of clustering, randomness, and regularity. A detailed analysis is carried out of cumulus cloud field spatial distributions based upon Landsat, AVHRR, and Skylab data, showing that, when both large and small clouds are included in the cloud field distributions, the cloud field always has a strong clustering signal.

An Infrastructure for UML-Based Code Generation Tools

NASA Astrophysics Data System (ADS)

Wehrmeister, Marco A.; Freitas, Edison P.; Pereira, Carlos E.

The use of Model-Driven Engineering (MDE) techniques in the domain of distributed embedded real-time systems are gain importance in order to cope with the increasing design complexity of such systems. This paper discusses an infrastructure created to build GenERTiCA, a flexible tool that supports a MDE approach, which uses aspect-oriented concepts to handle non-functional requirements from embedded and real-time systems domain. GenERTiCA generates source code from UML models, and also performs weaving of aspects, which have been specified within the UML model. Additionally, this paper discusses the Distributed Embedded Real-Time Compact Specification (DERCS), a PIM created to support UML-based code generation tools. Some heuristics to transform UML models into DERCS, which have been implemented in GenERTiCA, are also discussed.

Estimation of synthetic flood design hydrographs using a distributed rainfall-runoff model coupled with a copula-based single storm rainfall generator

NASA Astrophysics Data System (ADS)

Candela, A.; Brigandì, G.; Aronica, G. T.

2014-07-01

In this paper a procedure to derive synthetic flood design hydrographs (SFDH) using a bivariate representation of rainfall forcing (rainfall duration and intensity) via copulas, which describes and models the correlation between two variables independently of the marginal laws involved, coupled with a distributed rainfall-runoff model, is presented. Rainfall-runoff modelling (R-R modelling) for estimating the hydrological response at the outlet of a catchment was performed by using a conceptual fully distributed procedure based on the Soil Conservation Service - Curve Number method as an excess rainfall model and on a distributed unit hydrograph with climatic dependencies for the flow routing. Travel time computation, based on the distributed unit hydrograph definition, was performed by implementing a procedure based on flow paths, determined from a digital elevation model (DEM) and roughness parameters obtained from distributed geographical information. In order to estimate the primary return period of the SFDH, which provides the probability of occurrence of a hydrograph flood, peaks and flow volumes obtained through R-R modelling were treated statistically using copulas. Finally, the shapes of hydrographs have been generated on the basis of historically significant flood events, via cluster analysis. An application of the procedure described above has been carried out and results presented for the case study of the Imera catchment in Sicily, Italy.

Unsupervised, low latency anomaly detection of algorithmically generated domain names by generative probabilistic modeling.

PubMed

Raghuram, Jayaram; Miller, David J; Kesidis, George

2014-07-01

We propose a method for detecting anomalous domain names, with focus on algorithmically generated domain names which are frequently associated with malicious activities such as fast flux service networks, particularly for bot networks (or botnets), malware, and phishing. Our method is based on learning a (null hypothesis) probability model based on a large set of domain names that have been white listed by some reliable authority. Since these names are mostly assigned by humans, they are pronounceable, and tend to have a distribution of characters, words, word lengths, and number of words that are typical of some language (mostly English), and often consist of words drawn from a known lexicon. On the other hand, in the present day scenario, algorithmically generated domain names typically have distributions that are quite different from that of human-created domain names. We propose a fully generative model for the probability distribution of benign (white listed) domain names which can be used in an anomaly detection setting for identifying putative algorithmically generated domain names. Unlike other methods, our approach can make detections without considering any additional (latency producing) information sources, often used to detect fast flux activity. Experiments on a publicly available, large data set of domain names associated with fast flux service networks show encouraging results, relative to several baseline methods, with higher detection rates and low false positive rates.

Unsupervised, low latency anomaly detection of algorithmically generated domain names by generative probabilistic modeling

PubMed Central

Raghuram, Jayaram; Miller, David J.; Kesidis, George

2014-01-01

We propose a method for detecting anomalous domain names, with focus on algorithmically generated domain names which are frequently associated with malicious activities such as fast flux service networks, particularly for bot networks (or botnets), malware, and phishing. Our method is based on learning a (null hypothesis) probability model based on a large set of domain names that have been white listed by some reliable authority. Since these names are mostly assigned by humans, they are pronounceable, and tend to have a distribution of characters, words, word lengths, and number of words that are typical of some language (mostly English), and often consist of words drawn from a known lexicon. On the other hand, in the present day scenario, algorithmically generated domain names typically have distributions that are quite different from that of human-created domain names. We propose a fully generative model for the probability distribution of benign (white listed) domain names which can be used in an anomaly detection setting for identifying putative algorithmically generated domain names. Unlike other methods, our approach can make detections without considering any additional (latency producing) information sources, often used to detect fast flux activity. Experiments on a publicly available, large data set of domain names associated with fast flux service networks show encouraging results, relative to several baseline methods, with higher detection rates and low false positive rates. PMID:25685511

A Distributed Fuzzy Associative Classifier for Big Data.

PubMed

Segatori, Armando; Bechini, Alessio; Ducange, Pietro; Marcelloni, Francesco

2017-09-19

Fuzzy associative classification has not been widely analyzed in the literature, although associative classifiers (ACs) have proved to be very effective in different real domain applications. The main reason is that learning fuzzy ACs is a very heavy task, especially when dealing with large datasets. To overcome this drawback, in this paper, we propose an efficient distributed fuzzy associative classification approach based on the MapReduce paradigm. The approach exploits a novel distributed discretizer based on fuzzy entropy for efficiently generating fuzzy partitions of the attributes. Then, a set of candidate fuzzy association rules is generated by employing a distributed fuzzy extension of the well-known FP-Growth algorithm. Finally, this set is pruned by using three purposely adapted types of pruning. We implemented our approach on the popular Hadoop framework. Hadoop allows distributing storage and processing of very large data sets on computer clusters built from commodity hardware. We have performed an extensive experimentation and a detailed analysis of the results using six very large datasets with up to 11,000,000 instances. We have also experimented different types of reasoning methods. Focusing on accuracy, model complexity, computation time, and scalability, we compare the results achieved by our approach with those obtained by two distributed nonfuzzy ACs recently proposed in the literature. We highlight that, although the accuracies result to be comparable, the complexity, evaluated in terms of number of rules, of the classifiers generated by the fuzzy distributed approach is lower than the one of the nonfuzzy classifiers.

Optimal Power Scheduling for a Medium Voltage AC/DC Hybrid Distribution Network

DOE PAGES

Zhu, Zhenshan; Liu, Dichen; Liao, Qingfen; ...

2018-01-26

With the great increase of renewable generation as well as the DC loads in the distribution network; DC distribution technology is receiving more attention; since the DC distribution network can improve operating efficiency and power quality by reducing the energy conversion stages. This paper presents a new architecture for the medium voltage AC/DC hybrid distribution network; where the AC and DC subgrids are looped by normally closed AC soft open point (ACSOP) and DC soft open point (DCSOP); respectively. The proposed AC/DC hybrid distribution systems contain renewable generation (i.e., wind power and photovoltaic (PV) generation); energy storage systems (ESSs); softmore » open points (SOPs); and both AC and DC flexible demands. An energy management strategy for the hybrid system is presented based on the dynamic optimal power flow (DOPF) method. The main objective of the proposed power scheduling strategy is to minimize the operating cost and reduce the curtailment of renewable generation while meeting operational and technical constraints. The proposed approach is verified in five scenarios. The five scenarios are classified as pure AC system; hybrid AC/DC system; hybrid system with interlinking converter; hybrid system with DC flexible demand; and hybrid system with SOPs. Results show that the proposed scheduling method can successfully dispatch the controllable elements; and that the presented architecture for the AC/DC hybrid distribution system is beneficial for reducing operating cost and renewable generation curtailment.« less

Optimal Power Scheduling for a Medium Voltage AC/DC Hybrid Distribution Network

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

Zhu, Zhenshan; Liu, Dichen; Liao, Qingfen

With the great increase of renewable generation as well as the DC loads in the distribution network; DC distribution technology is receiving more attention; since the DC distribution network can improve operating efficiency and power quality by reducing the energy conversion stages. This paper presents a new architecture for the medium voltage AC/DC hybrid distribution network; where the AC and DC subgrids are looped by normally closed AC soft open point (ACSOP) and DC soft open point (DCSOP); respectively. The proposed AC/DC hybrid distribution systems contain renewable generation (i.e., wind power and photovoltaic (PV) generation); energy storage systems (ESSs); softmore » open points (SOPs); and both AC and DC flexible demands. An energy management strategy for the hybrid system is presented based on the dynamic optimal power flow (DOPF) method. The main objective of the proposed power scheduling strategy is to minimize the operating cost and reduce the curtailment of renewable generation while meeting operational and technical constraints. The proposed approach is verified in five scenarios. The five scenarios are classified as pure AC system; hybrid AC/DC system; hybrid system with interlinking converter; hybrid system with DC flexible demand; and hybrid system with SOPs. Results show that the proposed scheduling method can successfully dispatch the controllable elements; and that the presented architecture for the AC/DC hybrid distribution system is beneficial for reducing operating cost and renewable generation curtailment.« less

Long-distance entanglement-based quantum key distribution experiment using practical detectors.

PubMed

Takesue, Hiroki; Harada, Ken-Ichi; Tamaki, Kiyoshi; Fukuda, Hiroshi; Tsuchizawa, Tai; Watanabe, Toshifumi; Yamada, Koji; Itabashi, Sei-Ichi

2010-08-02

We report an entanglement-based quantum key distribution experiment that we performed over 100 km of optical fiber using a practical source and detectors. We used a silicon-based photon-pair source that generated high-purity time-bin entangled photons, and high-speed single photon detectors based on InGaAs/InP avalanche photodiodes with the sinusoidal gating technique. To calculate the secure key rate, we employed a security proof that validated the use of practical detectors. As a result, we confirmed the successful generation of sifted keys over 100 km of optical fiber with a key rate of 4.8 bit/s and an error rate of 9.1%, with which we can distill secure keys with a key rate of 0.15 bit/s.

Online Optimization Method for Operation of Generators in a Micro Grid

NASA Astrophysics Data System (ADS)

Hayashi, Yasuhiro; Miyamoto, Hideki; Matsuki, Junya; Iizuka, Toshio; Azuma, Hitoshi

Recently a lot of studies and developments about distributed generator such as photovoltaic generation system, wind turbine generation system and fuel cell have been performed under the background of the global environment issues and deregulation of the electricity market, and the technique of these distributed generators have progressed. Especially, micro grid which consists of several distributed generators, loads and storage battery is expected as one of the new operation system of distributed generator. However, since precipitous load fluctuation occurs in micro grid for the reason of its smaller capacity compared with conventional power system, high-accuracy load forecasting and control scheme to balance of supply and demand are needed. Namely, it is necessary to improve the precision of operation in micro grid by observing load fluctuation and correcting start-stop schedule and output of generators online. But it is not easy to determine the operation schedule of each generator in short time, because the problem to determine start-up, shut-down and output of each generator in micro grid is a mixed integer programming problem. In this paper, the authors propose an online optimization method for the optimal operation schedule of generators in micro grid. The proposed method is based on enumeration method and particle swarm optimization (PSO). In the proposed method, after picking up all unit commitment patterns of each generators satisfied with minimum up time and minimum down time constraint by using enumeration method, optimal schedule and output of generators are determined under the other operational constraints by using PSO. Numerical simulation is carried out for a micro grid model with five generators and photovoltaic generation system in order to examine the validity of the proposed method.

Not all nonnormal distributions are created equal: Improved theoretical and measurement precision.

PubMed

Joo, Harry; Aguinis, Herman; Bradley, Kyle J

2017-07-01

We offer a four-category taxonomy of individual output distributions (i.e., distributions of cumulative results): (1) pure power law; (2) lognormal; (3) exponential tail (including exponential and power law with an exponential cutoff); and (4) symmetric or potentially symmetric (including normal, Poisson, and Weibull). The four categories are uniquely associated with mutually exclusive generative mechanisms: self-organized criticality, proportionate differentiation, incremental differentiation, and homogenization. We then introduce distribution pitting, a falsification-based method for comparing distributions to assess how well each one fits a given data set. In doing so, we also introduce decision rules to determine the likely dominant shape and generative mechanism among many that may operate concurrently. Next, we implement distribution pitting using 229 samples of individual output for several occupations (e.g., movie directors, writers, musicians, athletes, bank tellers, call center employees, grocery checkers, electrical fixture assemblers, and wirers). Results suggest that for 75% of our samples, exponential tail distributions and their generative mechanism (i.e., incremental differentiation) likely constitute the dominant distribution shape and explanation of nonnormally distributed individual output. This finding challenges past conclusions indicating the pervasiveness of other types of distributions and their generative mechanisms. Our results further contribute to theory by offering premises about the link between past and future individual output. For future research, our taxonomy and methodology can be used to pit distributions of other variables (e.g., organizational citizenship behaviors). Finally, we offer practical insights on how to increase overall individual output and produce more top performers. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

An observer-based compensator for distributed delays in integrated control systems

NASA Technical Reports Server (NTRS)

Luck, Rogelio; Ray, Asok

1989-01-01

This paper presents an algorithm for compensation of delays that are distributed within a control loop. The observer-based algorithm is especially suitable for compensating network-induced delays that are likely to occur in integrated control systems of the future generation aircraft. The robustness of the algorithm relative to uncertainties in the plant model have been examined.

3-D Topo Surface Visualization of Acid-Base Species Distributions: Corner Buttes, Corner Pits, Curving Ridge Crests, and Dilution Plains

ERIC Educational Resources Information Center

Smith, Garon C.; Hossain, Md Mainul

2017-01-01

Species TOPOS is a free software package for generating three-dimensional (3-D) topographic surfaces ("topos") for acid-base equilibrium studies. This upgrade adds 3-D species distribution topos to earlier surfaces that showed pH and buffer capacity behavior during titration and dilution procedures. It constructs topos by plotting…

Pareto versus lognormal: A maximum entropy test

NASA Astrophysics Data System (ADS)

Bee, Marco; Riccaboni, Massimo; Schiavo, Stefano

2011-08-01

It is commonly found that distributions that seem to be lognormal over a broad range change to a power-law (Pareto) distribution for the last few percentiles. The distributions of many physical, natural, and social events (earthquake size, species abundance, income and wealth, as well as file, city, and firm sizes) display this structure. We present a test for the occurrence of power-law tails in statistical distributions based on maximum entropy. This methodology allows one to identify the true data-generating processes even in the case when it is neither lognormal nor Pareto. The maximum entropy approach is then compared with other widely used methods and applied to different levels of aggregation of complex systems. Our results provide support for the theory that distributions with lognormal body and Pareto tail can be generated as mixtures of lognormally distributed units.

Intelligent Control of Micro Grid: A Big Data-Based Control Center

NASA Astrophysics Data System (ADS)

Liu, Lu; Wang, Yanping; Liu, Li; Wang, Zhiseng

2018-01-01

In this paper, a structure of micro grid system with big data-based control center is introduced. Energy data from distributed generation, storage and load are analized through the control center, and from the results new trends will be predicted and applied as a feedback to optimize the control. Therefore, each step proceeded in micro grid can be adjusted and orgnized in a form of comprehensive management. A framework of real-time data collection, data processing and data analysis will be proposed by employing big data technology. Consequently, a integrated distributed generation and a optimized energy storage and transmission process can be implemented in the micro grid system.

Optimal Battery Sizing in Photovoltaic Based Distributed Generation Using Enhanced Opposition-Based Firefly Algorithm for Voltage Rise Mitigation

PubMed Central

Wong, Ling Ai; Shareef, Hussain; Mohamed, Azah; Ibrahim, Ahmad Asrul

2014-01-01

This paper presents the application of enhanced opposition-based firefly algorithm in obtaining the optimal battery energy storage systems (BESS) sizing in photovoltaic generation integrated radial distribution network in order to mitigate the voltage rise problem. Initially, the performance of the original firefly algorithm is enhanced by utilizing the opposition-based learning and introducing inertia weight. After evaluating the performance of the enhanced opposition-based firefly algorithm (EOFA) with fifteen benchmark functions, it is then adopted to determine the optimal size for BESS. Two optimization processes are conducted where the first optimization aims to obtain the optimal battery output power on hourly basis and the second optimization aims to obtain the optimal BESS capacity by considering the state of charge constraint of BESS. The effectiveness of the proposed method is validated by applying the algorithm to the 69-bus distribution system and by comparing the performance of EOFA with conventional firefly algorithm and gravitational search algorithm. Results show that EOFA has the best performance comparatively in terms of mitigating the voltage rise problem. PMID:25054184

Optimal battery sizing in photovoltaic based distributed generation using enhanced opposition-based firefly algorithm for voltage rise mitigation.

PubMed

Wong, Ling Ai; Shareef, Hussain; Mohamed, Azah; Ibrahim, Ahmad Asrul

2014-01-01

This paper presents the application of enhanced opposition-based firefly algorithm in obtaining the optimal battery energy storage systems (BESS) sizing in photovoltaic generation integrated radial distribution network in order to mitigate the voltage rise problem. Initially, the performance of the original firefly algorithm is enhanced by utilizing the opposition-based learning and introducing inertia weight. After evaluating the performance of the enhanced opposition-based firefly algorithm (EOFA) with fifteen benchmark functions, it is then adopted to determine the optimal size for BESS. Two optimization processes are conducted where the first optimization aims to obtain the optimal battery output power on hourly basis and the second optimization aims to obtain the optimal BESS capacity by considering the state of charge constraint of BESS. The effectiveness of the proposed method is validated by applying the algorithm to the 69-bus distribution system and by comparing the performance of EOFA with conventional firefly algorithm and gravitational search algorithm. Results show that EOFA has the best performance comparatively in terms of mitigating the voltage rise problem.

Towards Integrating Distributed Energy Resources and Storage Devices in Smart Grid.

PubMed

Xu, Guobin; Yu, Wei; Griffith, David; Golmie, Nada; Moulema, Paul

2017-02-01

Internet of Things (IoT) provides a generic infrastructure for different applications to integrate information communication techniques with physical components to achieve automatic data collection, transmission, exchange, and computation. The smart grid, as one of typical applications supported by IoT, denoted as a re-engineering and a modernization of the traditional power grid, aims to provide reliable, secure, and efficient energy transmission and distribution to consumers. How to effectively integrate distributed (renewable) energy resources and storage devices to satisfy the energy service requirements of users, while minimizing the power generation and transmission cost, remains a highly pressing challenge in the smart grid. To address this challenge and assess the effectiveness of integrating distributed energy resources and storage devices, in this paper we develop a theoretical framework to model and analyze three types of power grid systems: the power grid with only bulk energy generators, the power grid with distributed energy resources, and the power grid with both distributed energy resources and storage devices. Based on the metrics of the power cumulative cost and the service reliability to users, we formally model and analyze the impact of integrating distributed energy resources and storage devices in the power grid. We also use the concept of network calculus, which has been traditionally used for carrying out traffic engineering in computer networks, to derive the bounds of both power supply and user demand to achieve a high service reliability to users. Through an extensive performance evaluation, our data shows that integrating distributed energy resources conjointly with energy storage devices can reduce generation costs, smooth the curve of bulk power generation over time, reduce bulk power generation and power distribution losses, and provide a sustainable service reliability to users in the power grid.

Towards Integrating Distributed Energy Resources and Storage Devices in Smart Grid

PubMed Central

Xu, Guobin; Yu, Wei; Griffith, David; Golmie, Nada; Moulema, Paul

2017-01-01

Internet of Things (IoT) provides a generic infrastructure for different applications to integrate information communication techniques with physical components to achieve automatic data collection, transmission, exchange, and computation. The smart grid, as one of typical applications supported by IoT, denoted as a re-engineering and a modernization of the traditional power grid, aims to provide reliable, secure, and efficient energy transmission and distribution to consumers. How to effectively integrate distributed (renewable) energy resources and storage devices to satisfy the energy service requirements of users, while minimizing the power generation and transmission cost, remains a highly pressing challenge in the smart grid. To address this challenge and assess the effectiveness of integrating distributed energy resources and storage devices, in this paper we develop a theoretical framework to model and analyze three types of power grid systems: the power grid with only bulk energy generators, the power grid with distributed energy resources, and the power grid with both distributed energy resources and storage devices. Based on the metrics of the power cumulative cost and the service reliability to users, we formally model and analyze the impact of integrating distributed energy resources and storage devices in the power grid. We also use the concept of network calculus, which has been traditionally used for carrying out traffic engineering in computer networks, to derive the bounds of both power supply and user demand to achieve a high service reliability to users. Through an extensive performance evaluation, our data shows that integrating distributed energy resources conjointly with energy storage devices can reduce generation costs, smooth the curve of bulk power generation over time, reduce bulk power generation and power distribution losses, and provide a sustainable service reliability to users in the power grid1. PMID:29354654

An Intrinsic Algorithm for Parallel Poisson Disk Sampling on Arbitrary Surfaces.

PubMed

Ying, Xiang; Xin, Shi-Qing; Sun, Qian; He, Ying

2013-03-08

Poisson disk sampling plays an important role in a variety of visual computing, due to its useful statistical property in distribution and the absence of aliasing artifacts. While many effective techniques have been proposed to generate Poisson disk distribution in Euclidean space, relatively few work has been reported to the surface counterpart. This paper presents an intrinsic algorithm for parallel Poisson disk sampling on arbitrary surfaces. We propose a new technique for parallelizing the dart throwing. Rather than the conventional approaches that explicitly partition the spatial domain to generate the samples in parallel, our approach assigns each sample candidate a random and unique priority that is unbiased with regard to the distribution. Hence, multiple threads can process the candidates simultaneously and resolve conflicts by checking the given priority values. It is worth noting that our algorithm is accurate as the generated Poisson disks are uniformly and randomly distributed without bias. Our method is intrinsic in that all the computations are based on the intrinsic metric and are independent of the embedding space. This intrinsic feature allows us to generate Poisson disk distributions on arbitrary surfaces. Furthermore, by manipulating the spatially varying density function, we can obtain adaptive sampling easily.

AIRSAR Web-Based Data Processing

NASA Technical Reports Server (NTRS)

Chu, Anhua; Van Zyl, Jakob; Kim, Yunjin; Hensley, Scott; Lou, Yunling; Madsen, Soren; Chapman, Bruce; Imel, David; Durden, Stephen; Tung, Wayne

2007-01-01

The AIRSAR automated, Web-based data processing and distribution system is an integrated, end-to-end synthetic aperture radar (SAR) processing system. Designed to function under limited resources and rigorous demands, AIRSAR eliminates operational errors and provides for paperless archiving. Also, it provides a yearly tune-up of the processor on flight missions, as well as quality assurance with new radar modes and anomalous data compensation. The software fully integrates a Web-based SAR data-user request subsystem, a data processing system to automatically generate co-registered multi-frequency images from both polarimetric and interferometric data collection modes in 80/40/20 MHz bandwidth, an automated verification quality assurance subsystem, and an automatic data distribution system for use in the remote-sensor community. Features include Survey Automation Processing in which the software can automatically generate a quick-look image from an entire 90-GB SAR raw data 32-MB/s tape overnight without operator intervention. Also, the software allows product ordering and distribution via a Web-based user request system. To make AIRSAR more user friendly, it has been designed to let users search by entering the desired mission flight line (Missions Searching), or to search for any mission flight line by entering the desired latitude and longitude (Map Searching). For precision image automation processing, the software generates the products according to each data processing request stored in the database via a Queue management system. Users are able to have automatic generation of coregistered multi-frequency images as the software generates polarimetric and/or interferometric SAR data processing in ground and/or slant projection according to user processing requests for one of the 12 radar modes.

Distributed query plan generation using multiobjective genetic algorithm.

PubMed

Panicker, Shina; Kumar, T V Vijay

2014-01-01

A distributed query processing strategy, which is a key performance determinant in accessing distributed databases, aims to minimize the total query processing cost. One way to achieve this is by generating efficient distributed query plans that involve fewer sites for processing a query. In the case of distributed relational databases, the number of possible query plans increases exponentially with respect to the number of relations accessed by the query and the number of sites where these relations reside. Consequently, computing optimal distributed query plans becomes a complex problem. This distributed query plan generation (DQPG) problem has already been addressed using single objective genetic algorithm, where the objective is to minimize the total query processing cost comprising the local processing cost (LPC) and the site-to-site communication cost (CC). In this paper, this DQPG problem is formulated and solved as a biobjective optimization problem with the two objectives being minimize total LPC and minimize total CC. These objectives are simultaneously optimized using a multiobjective genetic algorithm NSGA-II. Experimental comparison of the proposed NSGA-II based DQPG algorithm with the single objective genetic algorithm shows that the former performs comparatively better and converges quickly towards optimal solutions for an observed crossover and mutation probability.

Distributed Query Plan Generation Using Multiobjective Genetic Algorithm

PubMed Central

Panicker, Shina; Vijay Kumar, T. V.

2014-01-01

A distributed query processing strategy, which is a key performance determinant in accessing distributed databases, aims to minimize the total query processing cost. One way to achieve this is by generating efficient distributed query plans that involve fewer sites for processing a query. In the case of distributed relational databases, the number of possible query plans increases exponentially with respect to the number of relations accessed by the query and the number of sites where these relations reside. Consequently, computing optimal distributed query plans becomes a complex problem. This distributed query plan generation (DQPG) problem has already been addressed using single objective genetic algorithm, where the objective is to minimize the total query processing cost comprising the local processing cost (LPC) and the site-to-site communication cost (CC). In this paper, this DQPG problem is formulated and solved as a biobjective optimization problem with the two objectives being minimize total LPC and minimize total CC. These objectives are simultaneously optimized using a multiobjective genetic algorithm NSGA-II. Experimental comparison of the proposed NSGA-II based DQPG algorithm with the single objective genetic algorithm shows that the former performs comparatively better and converges quickly towards optimal solutions for an observed crossover and mutation probability. PMID:24963513

Arc Length Based Grid Distribution For Surface and Volume Grids

NASA Technical Reports Server (NTRS)

Mastin, C. Wayne

1996-01-01

Techniques are presented for distributing grid points on parametric surfaces and in volumes according to a specified distribution of arc length. Interpolation techniques are introduced which permit a given distribution of grid points on the edges of a three-dimensional grid block to be propagated through the surface and volume grids. Examples demonstrate how these methods can be used to improve the quality of grids generated by transfinite interpolation.

An Event-Based Approach to Distributed Diagnosis of Continuous Systems

NASA Technical Reports Server (NTRS)

Daigle, Matthew; Roychoudhurry, Indranil; Biswas, Gautam; Koutsoukos, Xenofon

2010-01-01

Distributed fault diagnosis solutions are becoming necessary due to the complexity of modern engineering systems, and the advent of smart sensors and computing elements. This paper presents a novel event-based approach for distributed diagnosis of abrupt parametric faults in continuous systems, based on a qualitative abstraction of measurement deviations from the nominal behavior. We systematically derive dynamic fault signatures expressed as event-based fault models. We develop a distributed diagnoser design algorithm that uses these models for designing local event-based diagnosers based on global diagnosability analysis. The local diagnosers each generate globally correct diagnosis results locally, without a centralized coordinator, and by communicating a minimal number of measurements between themselves. The proposed approach is applied to a multi-tank system, and results demonstrate a marked improvement in scalability compared to a centralized approach.

Synchrophasor Sensing and Processing based Smart Grid Security Assessment for Renewable Energy Integration

NASA Astrophysics Data System (ADS)

Jiang, Huaiguang

With the evolution of energy and power systems, the emerging Smart Grid (SG) is mainly featured by distributed renewable energy generations, demand-response control and huge amount of heterogeneous data sources. Widely distributed synchrophasor sensors, such as phasor measurement units (PMUs) and fault disturbance recorders (FDRs), can record multi-modal signals, for power system situational awareness and renewable energy integration. An effective and economical approach is proposed for wide-area security assessment. This approach is based on wavelet analysis for detecting and locating the short-term and long-term faults in SG, using voltage signals collected by distributed synchrophasor sensors. A data-driven approach for fault detection, identification and location is proposed and studied. This approach is based on matching pursuit decomposition (MPD) using Gaussian atom dictionary, hidden Markov model (HMM) of real-time frequency and voltage variation features, and fault contour maps generated by machine learning algorithms in SG systems. In addition, considering the economic issues, the placement optimization of distributed synchrophasor sensors is studied to reduce the number of the sensors without affecting the accuracy and effectiveness of the proposed approach. Furthermore, because the natural hazards is a critical issue for power system security, this approach is studied under different types of faults caused by natural hazards. A fast steady-state approach is proposed for voltage security of power systems with a wind power plant connected. The impedance matrix can be calculated by the voltage and current information collected by the PMUs. Based on the impedance matrix, locations in SG can be identified, where cause the greatest impact on the voltage at the wind power plants point of interconnection. Furthermore, because this dynamic voltage security assessment method relies on time-domain simulations of faults at different locations, the proposed approach is feasible, convenient and effective. Conventionally, wind energy is highly location-dependent. Many desirable wind resources are located in rural areas without direct access to the transmission grid. By connecting MW-scale wind turbines or wind farms to the distributions system of SG, the cost of building long transmission facilities can be avoid and wind power supplied to consumers can be greatly increased. After the effective wide area monitoring (WAM) approach is built, an event-driven control strategy is proposed for renewable energy integration. This approach is based on support vector machine (SVM) predictor and multiple-input and multiple-output (MIMO) model predictive control (MPC) on linear time-invariant (LTI) and linear time-variant (LTV) systems. The voltage condition of the distribution system is predicted by the SVM classifier using synchrophasor measurement data. The controllers equipped with wind turbine generators are triggered by the prediction results. Both transmission level and distribution level are designed based on this proposed approach. Considering economic issues in the power system, a statistical scheduling approach to economic dispatch and energy reserves is proposed. The proposed approach focuses on minimizing the overall power operating cost with considerations of renewable energy uncertainty and power system security. The hybrid power system scheduling is formulated as a convex programming problem to minimize power operating cost, taking considerations of renewable energy generation, power generation-consumption balance and power system security. A genetic algorithm based approach is used for solving the minimization of the power operating cost. In addition, with technology development, it can be predicted that the renewable energy such as wind turbine generators and PV panels will be pervasively located in distribution systems. The distribution system is an unbalanced system, which contains single-phase, two-phase and three-phase loads, and distribution lines. The complex configuration brings a challenge to power flow calculation. A topology analysis based iterative approach is used to solve this problem. In this approach, a self-adaptive topology recognition method is used to analyze the distribution system, and the backward/forward sweep algorithm is used to generate the power flow results. Finally, for the numerical simulations, the IEEE 14-bus, 30-bus, 39-bus and 118-bus systems are studied for fault detection, identification and location. Both transmission level and distribution level models are employed with the proposed control strategy for voltage stability of renewable energy integration. The simulation results demonstrate the effectiveness of the proposed methods. The IEEE 24-bus reliability test system (IEEE-RTS), which is commonly used for evaluating the price stability and reliability of power system, is used as the test bench for verifying and evaluating system performance of the proposed scheduling approach.

Limits and Economic Effects of Distributed PV Generation in North and South Carolina

NASA Astrophysics Data System (ADS)

Holt, Kyra Moore

The variability of renewable sources, such as wind and solar, when integrated into the electrical system must be compensated by traditional generation sources in-order to maintain the constant balance of supply and demand required for grid stability. The goal of this study is to analyze the effects of increasing large levels of solar Photovoltaic (PV) penetration (in terms of a percentage of annual energy production) on a test grid with similar characteristics to the Duke Energy Carolinas (DEC) and Progress Energy Carolinas (PEC) regions of North and South Carolina. PV production is modeled entering the system at the distribution level and regional PV capacity is based on household density. A gridded hourly global horizontal irradiance (GHI) dataset is used to capture the variable nature of PV generation. A unit commitment model (UCM) is then used determine the hourly dispatch of generators based on generator parameters and costs to supply generation to meet demand. Annual modeled results for six different scenarios are evaluated to determine technical, environmental and economic effects of varying levels of distributed PV penetration on the system. This study finds that the main limiting factor for PV integration in the DEC and PEC balancing authority regions is defined by the large generating capacity of base-load nuclear plants within the system. This threshold starts to affect system stability at integration levels of 5.7%. System errors, defined by imbalances caused by over or under generation with respect to demand, are identified in the model however the validity of these errors in real world context needs further examination due to the lack of high frequency irradiance data and modeling limitations. Operational system costs decreased as expected with PV integration although further research is needed to explore the impacts of the capital costs required to achieve the penetration levels found in this study. PV system generation was found to mainly displace coal generation creating a loss of revenue for generator owners. In all scenarios, CO 2 emissions were reduced with PV integration. This reduction could be used to meet impending EPA state-specific CO2 emissions targets.

Subsurface damage distribution in the lapping process.

PubMed

Wang, Zhuo; Wu, Yulie; Dai, Yifan; Li, Shengyi

2008-04-01

To systematically investigate the influence of lapping parameters on subsurface damage (SSD) depth and characterize the damage feature comprehensively, maximum depth and distribution of SSD generated in the optical lapping process were measured with the magnetorheological finishing wedge technique. Then, an interaction of adjacent indentations was applied to interpret the generation of maximum depth of SSD. Eventually, the lapping procedure based on the influence of lapping parameters on the material removal rate and SSD depth was proposed to improve the lapping efficiency.

A probabilistic approach to photovoltaic generator performance prediction

NASA Astrophysics Data System (ADS)

Khallat, M. A.; Rahman, S.

1986-09-01

A method for predicting the performance of a photovoltaic (PV) generator based on long term climatological data and expected cell performance is described. The equations for cell model formulation are provided. Use of the statistical model for characterizing the insolation level is discussed. The insolation data is fitted to appropriate probability distribution functions (Weibull, beta, normal). The probability distribution functions are utilized to evaluate the capacity factors of PV panels or arrays. An example is presented revealing the applicability of the procedure.

Worldwide telemedicine services based on distributed multimedia electronic patient records by using the second generation Web server hyperwave.

PubMed

Quade, G; Novotny, J; Burde, B; May, F; Beck, L E; Goldschmidt, A

1999-01-01

A distributed multimedia electronic patient record (EPR) is a central component of a medicine-telematics application that supports physicians working in rural areas of South America, and offers medical services to scientists in Antarctica. A Hyperwave server is used to maintain the patient record. As opposed to common web servers--and as a second generation web server--Hyperwave provides the capability of holding documents in a distributed web space without the problem of broken links. This enables physicians to browse through a patient's record by using a standard browser even if the patient's record is distributed over several servers. The patient record is basically implemented on the "Good European Health Record" (GEHR) architecture.

Molecular characterization and comparison of shale oils generated by different pyrolysis methods

USGS Publications Warehouse

Birdwell, Justin E.; Jin, Jang Mi; Kim, Sunghwan

2012-01-01

Shale oils generated using different laboratory pyrolysis methods have been studied using standard oil characterization methods as well as Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) with electrospray ionization (ESI) and atmospheric photoionization (APPI) to assess differences in molecular composition. The pyrolysis oils were generated from samples of the Mahogany zone oil shale of the Eocene Green River Formation collected from outcrops in the Piceance Basin, Colorado, using three pyrolysis systems under conditions relevant to surface and in situ retorting approaches. Significant variations were observed in the shale oils, particularly the degree of conjugation of the constituent molecules and the distribution of nitrogen-containing compound classes. Comparison of FT-ICR MS results to other oil characteristics, such as specific gravity; saturate, aromatic, resin, asphaltene (SARA) distribution; and carbon number distribution determined by gas chromatography, indicated correspondence between higher average double bond equivalence (DBE) values and increasing asphaltene content. The results show that, based on the shale oil DBE distributions, highly conjugated species are enriched in samples produced under low pressure, high temperature conditions, and under high pressure, moderate temperature conditions in the presence of water. We also report, for the first time in any petroleum-like substance, the presence of N4 class compounds based on FT-ICR MS data. Using double bond equivalence and carbon number distributions, structures for the N4 class and other nitrogen-containing compounds are proposed.

Parametric distribution approach for flow availability in small hydro potential analysis

NASA Astrophysics Data System (ADS)

Abdullah, Samizee; Basri, Mohd Juhari Mat; Jamaluddin, Zahrul Zamri; Azrulhisham, Engku Ahmad; Othman, Jamel

2016-10-01

Small hydro system is one of the important sources of renewable energy and it has been recognized worldwide as clean energy sources. Small hydropower generation system uses the potential energy in flowing water to produce electricity is often questionable due to inconsistent and intermittent of power generated. Potential analysis of small hydro system which is mainly dependent on the availability of water requires the knowledge of water flow or stream flow distribution. This paper presented the possibility of applying Pearson system for stream flow availability distribution approximation in the small hydro system. By considering the stochastic nature of stream flow, the Pearson parametric distribution approximation was computed based on the significant characteristic of Pearson system applying direct correlation between the first four statistical moments of the distribution. The advantage of applying various statistical moments in small hydro potential analysis will have the ability to analyze the variation shapes of stream flow distribution.

Assessing the detail needed to capture rainfall-runoff dynamics with physics-based hydrologic response simulation

USGS Publications Warehouse

Mirus, B.B.; Ebel, B.A.; Heppner, C.S.; Loague, K.

2011-01-01

Concept development simulation with distributed, physics-based models provides a quantitative approach for investigating runoff generation processes across environmental conditions. Disparities within data sets employed to design and parameterize boundary value problems used in heuristic simulation inevitably introduce various levels of bias. The objective was to evaluate the impact of boundary value problem complexity on process representation for different runoff generation mechanisms. The comprehensive physics-based hydrologic response model InHM has been employed to generate base case simulations for four well-characterized catchments. The C3 and CB catchments are located within steep, forested environments dominated by subsurface stormflow; the TW and R5 catchments are located in gently sloping rangeland environments dominated by Dunne and Horton overland flows. Observational details are well captured within all four of the base case simulations, but the characterization of soil depth, permeability, rainfall intensity, and evapotranspiration differs for each. These differences are investigated through the conversion of each base case into a reduced case scenario, all sharing the same level of complexity. Evaluation of how individual boundary value problem characteristics impact simulated runoff generation processes is facilitated by quantitative analysis of integrated and distributed responses at high spatial and temporal resolution. Generally, the base case reduction causes moderate changes in discharge and runoff patterns, with the dominant process remaining unchanged. Moderate differences between the base and reduced cases highlight the importance of detailed field observations for parameterizing and evaluating physics-based models. Overall, similarities between the base and reduced cases indicate that the simpler boundary value problems may be useful for concept development simulation to investigate fundamental controls on the spectrum of runoff generation mechanisms. Copyright 2011 by the American Geophysical Union.

Optimization of a stand-alone Solar PV-Wind-DG Hybrid System for Distributed Power Generation at Sagar Island

NASA Astrophysics Data System (ADS)

Roy, P. C.; Majumder, A.; Chakraborty, N.

2010-10-01

An estimation of a stand-alone solar PV and wind hybrid system for distributed power generation has been made based on the resources available at Sagar island, a remote area distant to grid operation. Optimization and sensitivity analysis has been made to evaluate the feasibility and size of the power generation unit. A comparison of the different modes of hybrid system has been studied. It has been estimated that Solar PV-Wind-DG hybrid system provides lesser per unit electricity cost. Capital investment is observed to be lesser when the system run with Wind-DG compared to Solar PV-DG.

Application of Lagrangian blending functions for grid generation around airplane geometries

NASA Technical Reports Server (NTRS)

Abolhassani, Jamshid S.; Sadrehaghighi, Ideen; Tiwari, Surendra N.

1990-01-01

A simple procedure was developed and applied for the grid generation around an airplane geometry. This approach is based on a transfinite interpolation with Lagrangian interpolation for the blending functions. A monotonic rational quadratic spline interpolation was employed for the grid distributions.

Generating the local oscillator "locally" in continuous-variable quantum key distribution based on coherent detection

DOE PAGES

Qi, Bing; Lougovski, Pavel; Pooser, Raphael C.; ...

2015-10-21

Continuous-variable quantum key distribution (CV-QKD) protocols based on coherent detection have been studied extensively in both theory and experiment. In all the existing implementations of CV-QKD, both the quantum signal and the local oscillator (LO) are generated from the same laser and propagate through the insecure quantum channel. This arrangement may open security loopholes and limit the potential applications of CV-QKD. In our paper, we propose and demonstrate a pilot-aided feedforward data recovery scheme that enables reliable coherent detection using a “locally” generated LO. Using two independent commercial laser sources and a spool of 25-km optical fiber, we construct amore » coherent communication system. The variance of the phase noise introduced by the proposed scheme is measured to be 0.04 (rad 2), which is small enough to enable secure key distribution. This technology opens the door for other quantum communication protocols, such as the recently proposed measurement-device-independent CV-QKD, where independent light sources are employed by different users.« less

Smart grid integration of small-scale trigeneration systems

NASA Astrophysics Data System (ADS)

Vacheva, Gergana; Kanchev, Hristiyan; Hinov, Nikolay

2017-12-01

This paper presents a study on the possibilities for implementation of local heating, air-conditioning and electricity generation (trigeneration) as distributed energy resource in the Smart Grid. By the means of microturbine-based generators and absorption chillers buildings are able to meet partially or entirely their electrical load curve or even supply power to the grid by following their heating and air-conditioning daily schedule. The principles of small-scale cooling, heating and power generation systems are presented at first, then the thermal calculations of an example building are performed: the heat losses due to thermal conductivity and the estimated daily heating and air-conditioning load curves. By considering daily power consumption curves and weather data for several winter and summer days, the heating/air-conditioning schedule is estimated and the available electrical energy from a microturbine-based cogeneration system is estimated. Simulation results confirm the potential of using cogeneration and trigeneration systems for local distributed electricity generation and grid support in the daily peaks of power consumption.

Strain, curvature, and twist measurements in digital holographic interferometry using pseudo-Wigner-Ville distribution based method

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

Rajshekhar, G.; Gorthi, Sai Siva; Rastogi, Pramod

2009-09-15

Measurement of strain, curvature, and twist of a deformed object play an important role in deformation analysis. Strain depends on the first order displacement derivative, whereas curvature and twist are determined by second order displacement derivatives. This paper proposes a pseudo-Wigner-Ville distribution based method for measurement of strain, curvature, and twist in digital holographic interferometry where the object deformation or displacement is encoded as interference phase. In the proposed method, the phase derivative is estimated by peak detection of pseudo-Wigner-Ville distribution evaluated along each row/column of the reconstructed interference field. A complex exponential signal with unit amplitude and the phasemore » derivative estimate as the argument is then generated and the pseudo-Wigner-Ville distribution along each row/column of this signal is evaluated. The curvature is estimated by using peak tracking strategy for the new distribution. For estimation of twist, the pseudo-Wigner-Ville distribution is evaluated along each column/row (i.e., in alternate direction with respect to the previous one) for the generated complex exponential signal and the corresponding peak detection gives the twist estimate.« less

A Study Using a Monte Carlo Method of the Optimal Configuration of a Distribution Network in Terms of Power Loss Sensing

PubMed Central

Moon, Hyun Ho; Lee, Jong Joo; Choi, Sang Yule; Cha, Jae Sang; Kang, Jang Mook; Kim, Jong Tae; Shin, Myong Chul

2011-01-01

Recently there have been many studies of power systems with a focus on “New and Renewable Energy” as part of “New Growth Engine Industry” promoted by the Korean government. “New And Renewable Energy”—especially focused on wind energy, solar energy and fuel cells that will replace conventional fossil fuels—is a part of the Power-IT Sector which is the basis of the SmartGrid. A SmartGrid is a form of highly-efficient intelligent electricity network that allows interactivity (two-way communications) between suppliers and consumers by utilizing information technology in electricity production, transmission, distribution and consumption. The New and Renewable Energy Program has been driven with a goal to develop and spread through intensive studies, by public or private institutions, new and renewable energy which, unlike conventional systems, have been operated through connections with various kinds of distributed power generation systems. Considerable research on smart grids has been pursued in the United States and Europe. In the United States, a variety of research activities on the smart power grid have been conducted within EPRI’s IntelliGrid research program. The European Union (EU), which represents Europe’s Smart Grid policy, has focused on an expansion of distributed generation (decentralized generation) and power trade between countries with improved environmental protection. Thus, there is current emphasis on a need for studies that assesses the economic efficiency of such distributed generation systems. In this paper, based on the cost of distributed power generation capacity, calculations of the best profits obtainable were made by a Monte Carlo simulation. Monte Carlo simulations that rely on repeated random sampling to compute their results take into account the cost of electricity production, daily loads and the cost of sales and generate a result faster than mathematical computations. In addition, we have suggested the optimal design, which considers the distribution loss associated with power distribution systems focus on sensing aspect and distributed power generation. PMID:22164047

Quantum Field Theory on Spacetimes with a Compactly Generated Cauchy Horizon

NASA Astrophysics Data System (ADS)

Kay, Bernard S.; Radzikowski, Marek J.; Wald, Robert M.

1997-02-01

We prove two theorems which concern difficulties in the formulation of the quantum theory of a linear scalar field on a spacetime, (M,g_{ab}), with a compactly generated Cauchy horizon. These theorems demonstrate the breakdown of the theory at certain base points of the Cauchy horizon, which are defined as 'past terminal accumulation points' of the horizon generators. Thus, the theorems may be interpreted as giving support to Hawking's 'Chronology Protection Conjecture', according to which the laws of physics prevent one from manufacturing a 'time machine'. Specifically, we prove: Theorem 1. There is no extension to (M,g_{ab}) of the usual field algebra on the initial globally hyperbolic region which satisfies the condition of F-locality at any base point. In other words, any extension of the field algebra must, in any globally hyperbolic neighbourhood of any base point, differ from the algebra one would define on that neighbourhood according to the rules for globally hyperbolic spacetimes. Theorem 2. The two-point distribution for any Hadamard state defined on the initial globally hyperbolic region must (when extended to a distributional bisolution of the covariant Klein-Gordon equation on the full spacetime) be singular at every base point x in the sense that the difference between this two point distribution and a local Hadamard distribution cannot be given by a bounded function in any neighbourhood (in M 2 M) of (x,x). In consequence of Theorem 2, quantities such as the renormalized expectation value of J2 or of the stress-energy tensor are necessarily ill-defined or singular at any base point. The proof of these theorems relies on the 'Propagation of Singularities' theorems of Duistermaat and Hörmander.

Modelling altered revenue function based on varying power consumption distribution and electricity tariff charge using data analytics framework

NASA Astrophysics Data System (ADS)

Zainudin, W. N. R. A.; Ramli, N. A.

2017-09-01

In 2010, Energy Commission (EC) had introduced Incentive Based Regulation (IBR) to ensure sustainable Malaysian Electricity Supply Industry (MESI), promotes transparent and fair returns, encourage maximum efficiency and maintains policy driven end user tariff. To cater such revolutionary transformation, a sophisticated system to generate policy driven electricity tariff structure is in great need. Hence, this study presents a data analytics framework that generates altered revenue function based on varying power consumption distribution and tariff charge function. For the purpose of this study, the power consumption distribution is being proxy using proportion of household consumption and electricity consumed in KwH and the tariff charge function is being proxy using three-tiered increasing block tariff (IBT). The altered revenue function is useful to give an indication on whether any changes in the power consumption distribution and tariff charges will give positive or negative impact to the economy. The methodology used for this framework begins by defining the revenue to be a function of power consumption distribution and tariff charge function. Then, the proportion of household consumption and tariff charge function is derived within certain interval of electricity power. Any changes in those proportion are conjectured to contribute towards changes in revenue function. Thus, these changes can potentially give an indication on whether the changes in power consumption distribution and tariff charge function are giving positive or negative impact on TNB revenue. Based on the finding of this study, major changes on tariff charge function seems to affect altered revenue function more than power consumption distribution. However, the paper concludes that power consumption distribution and tariff charge function can influence TNB revenue to some great extent.

Selecting an Architecture for a Safety-Critical Distributed Computer System with Power, Weight and Cost Considerations

NASA Technical Reports Server (NTRS)

Torres-Pomales, Wilfredo

2014-01-01

This report presents an example of the application of multi-criteria decision analysis to the selection of an architecture for a safety-critical distributed computer system. The design problem includes constraints on minimum system availability and integrity, and the decision is based on the optimal balance of power, weight and cost. The analysis process includes the generation of alternative architectures, evaluation of individual decision criteria, and the selection of an alternative based on overall value. In this example presented here, iterative application of the quantitative evaluation process made it possible to deliberately generate an alternative architecture that is superior to all others regardless of the relative importance of cost.

Comparison of anatomy-based, fluence-based and aperture-based treatment planning approaches for VMAT

NASA Astrophysics Data System (ADS)

Rao, Min; Cao, Daliang; Chen, Fan; Ye, Jinsong; Mehta, Vivek; Wong, Tony; Shepard, David

2010-11-01

Volumetric modulated arc therapy (VMAT) has the potential to reduce treatment times while producing comparable or improved dose distributions relative to fixed-field intensity-modulated radiation therapy. In order to take full advantage of the VMAT delivery technique, one must select a robust inverse planning tool. The purpose of this study was to evaluate the effectiveness and efficiency of VMAT planning techniques of three categories: anatomy-based, fluence-based and aperture-based inverse planning. We have compared these techniques in terms of the plan quality, planning efficiency and delivery efficiency. Fourteen patients were selected for this study including six head-and-neck (HN) cases, and two cases each of prostate, pancreas, lung and partial brain. For each case, three VMAT plans were created. The first VMAT plan was generated based on the anatomical geometry. In the Elekta ERGO++ treatment planning system (TPS), segments were generated based on the beam's eye view (BEV) of the target and the organs at risk. The segment shapes were then exported to Pinnacle3 TPS followed by segment weight optimization and final dose calculation. The second VMAT plan was generated by converting optimized fluence maps (calculated by the Pinnacle3 TPS) into deliverable arcs using an in-house arc sequencer. The third VMAT plan was generated using the Pinnacle3 SmartArc IMRT module which is an aperture-based optimization method. All VMAT plans were delivered using an Elekta Synergy linear accelerator and the plan comparisons were made in terms of plan quality and delivery efficiency. The results show that for cases of little or modest complexity such as prostate, pancreas, lung and brain, the anatomy-based approach provides similar target coverage and critical structure sparing, but less conformal dose distributions as compared to the other two approaches. For more complex HN cases, the anatomy-based approach is not able to provide clinically acceptable VMAT plans while highly conformal dose distributions were obtained using both aperture-based and fluence-based inverse planning techniques. The aperture-based approach provides improved dose conformity than the fluence-based technique in complex cases.

Using Python to generate AHPS-based precipitation simulations over CONUS using Amazon distributed computing

NASA Astrophysics Data System (ADS)

Machalek, P.; Kim, S. M.; Berry, R. D.; Liang, A.; Small, T.; Brevdo, E.; Kuznetsova, A.

2012-12-01

We describe how the Climate Corporation uses Python and Clojure, a language impleneted on top of Java, to generate climatological forecasts for precipitation based on the Advanced Hydrologic Prediction Service (AHPS) radar based daily precipitation measurements. A 2-year-long forecasts is generated on each of the ~650,000 CONUS land based 4-km AHPS grids by constructing 10,000 ensembles sampled from a 30-year reconstructed AHPS history for each grid. The spatial and temporal correlations between neighboring AHPS grids and the sampling of the analogues are handled by Python. The parallelization for all the 650,000 CONUS stations is further achieved by utilizing the MAP-REDUCE framework (http://code.google.com/edu/parallel/mapreduce-tutorial.html). Each full scale computational run requires hundreds of nodes with up to 8 processors each on the Amazon Elastic MapReduce (http://aws.amazon.com/elasticmapreduce/) distributed computing service resulting in 3 terabyte datasets. We further describe how we have productionalized a monthly run of the simulations process at full scale of the 4km AHPS grids and how the resultant terabyte sized datasets are handled.

Evaluation of transportation/air quality model improvements based on TOTEMS on-road driving style and tailpipe emissions data.

DOT National Transportation Integrated Search

2014-06-01

In June 2012, the Environmental Protection Agency (EPA) released the Operating Mode : Distribution Generator (OMDG) a tool for developing an operating mode distribution as an input : to the Motor Vehicle Emissions Simulator model (MOVES). The t...

Life cycle design metrics for energy generation technologies: Method, data, and case study

NASA Astrophysics Data System (ADS)

Cooper, Joyce; Lee, Seung-Jin; Elter, John; Boussu, Jeff; Boman, Sarah

A method to assist in the rapid preparation of Life Cycle Assessments of emerging energy generation technologies is presented and applied to distributed proton exchange membrane fuel cell systems. The method develops life cycle environmental design metrics and allows variations in hardware materials, transportation scenarios, assembly energy use, operating performance and consumables, and fuels and fuel production scenarios to be modeled and comparisons to competing systems to be made. Data and results are based on publicly available U.S. Life Cycle Assessment data sources and are formulated to allow the environmental impact weighting scheme to be specified. A case study evaluates improvements in efficiency and in materials recycling and compares distributed proton exchange membrane fuel cell systems to other distributed generation options. The results reveal the importance of sensitivity analysis and system efficiency in interpreting case studies.

A Variance Distribution Model of Surface EMG Signals Based on Inverse Gamma Distribution.

PubMed

Hayashi, Hideaki; Furui, Akira; Kurita, Yuichi; Tsuji, Toshio

2017-11-01

Objective: This paper describes the formulation of a surface electromyogram (EMG) model capable of representing the variance distribution of EMG signals. Methods: In the model, EMG signals are handled based on a Gaussian white noise process with a mean of zero for each variance value. EMG signal variance is taken as a random variable that follows inverse gamma distribution, allowing the representation of noise superimposed onto this variance. Variance distribution estimation based on marginal likelihood maximization is also outlined in this paper. The procedure can be approximated using rectified and smoothed EMG signals, thereby allowing the determination of distribution parameters in real time at low computational cost. Results: A simulation experiment was performed to evaluate the accuracy of distribution estimation using artificially generated EMG signals, with results demonstrating that the proposed model's accuracy is higher than that of maximum-likelihood-based estimation. Analysis of variance distribution using real EMG data also suggested a relationship between variance distribution and signal-dependent noise. Conclusion: The study reported here was conducted to examine the performance of a proposed surface EMG model capable of representing variance distribution and a related distribution parameter estimation method. Experiments using artificial and real EMG data demonstrated the validity of the model. Significance: Variance distribution estimated using the proposed model exhibits potential in the estimation of muscle force. Objective: This paper describes the formulation of a surface electromyogram (EMG) model capable of representing the variance distribution of EMG signals. Methods: In the model, EMG signals are handled based on a Gaussian white noise process with a mean of zero for each variance value. EMG signal variance is taken as a random variable that follows inverse gamma distribution, allowing the representation of noise superimposed onto this variance. Variance distribution estimation based on marginal likelihood maximization is also outlined in this paper. The procedure can be approximated using rectified and smoothed EMG signals, thereby allowing the determination of distribution parameters in real time at low computational cost. Results: A simulation experiment was performed to evaluate the accuracy of distribution estimation using artificially generated EMG signals, with results demonstrating that the proposed model's accuracy is higher than that of maximum-likelihood-based estimation. Analysis of variance distribution using real EMG data also suggested a relationship between variance distribution and signal-dependent noise. Conclusion: The study reported here was conducted to examine the performance of a proposed surface EMG model capable of representing variance distribution and a related distribution parameter estimation method. Experiments using artificial and real EMG data demonstrated the validity of the model. Significance: Variance distribution estimated using the proposed model exhibits potential in the estimation of muscle force.

Efficient transformer study: Analysis of manufacture and utility data

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

Burkes, Klaehn; Cordaro, Joe; McIntosh, John

Distribution transformers convert power from the distribution system voltage to the end-customer voltage, which consists of residences, businesses, distributed generation, campus systems, and manufacturing facilities. Amorphous metal distribution transformers (AMDT) are also more expensive and heavier than conventional silicon steel distribution transformers. This and the difficulty to measure the benefit from energy efficiency and low awareness of the technology have hindered the adoption of AMDT. This report presents the cost savings for installing AMDT and the amount of energy saved based on the improved efficiency.

SLAM, a Mathematica interface for SUSY spectrum generators

NASA Astrophysics Data System (ADS)

Marquard, Peter; Zerf, Nikolai

2014-03-01

We present and publish a Mathematica package, which can be used to automatically obtain any numerical MSSM input parameter from SUSY spectrum generators, which follow the SLHA standard, like SPheno, SOFTSUSY, SuSeFLAV or Suspect. The package enables a very comfortable way of numerical evaluations within the MSSM using Mathematica. It implements easy to use predefined high scale and low scale scenarios like mSUGRA or mhmax and if needed enables the user to directly specify the input required by the spectrum generators. In addition it supports an automatic saving and loading of SUSY spectra to and from a SQL data base, avoiding the rerun of a spectrum generator for a known spectrum. Catalogue identifier: AERX_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AERX_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 4387 No. of bytes in distributed program, including test data, etc.: 37748 Distribution format: tar.gz Programming language: Mathematica. Computer: Any computer where Mathematica version 6 or higher is running providing bash and sed. Operating system: Linux. Classification: 11.1. External routines: A SUSY spectrum generator such as SPheno, SOFTSUSY, SuSeFLAV or SUSPECT Nature of problem: Interfacing published spectrum generators for automated creation, saving and loading of SUSY particle spectra. Solution method: SLAM automatically writes/reads SLHA spectrum generator input/output and is able to save/load generated data in/from a data base. Restrictions: No general restrictions, specific restrictions are given in the manuscript. Running time: A single spectrum calculation takes much less than one second on a modern PC.

Applications of Lagrangian blending functions for grid generation around airplane geometries

NASA Technical Reports Server (NTRS)

Abolhassani, Jamshid S.; Sadrehaghighi, Ideen; Tiwari, Surendra N.; Smith, Robert E.

1990-01-01

A simple procedure has been developed and applied for the grid generation around an airplane geometry. This approach is based on a transfinite interpolation with Lagrangian interpolation for the blending functions. A monotonic rational quadratic spline interpolation has been employed for the grid distributions.

Modeling uncertainty and correlation in soil properties using Restricted Pairing and implications for ensemble-based hillslope-scale soil moisture and temperature estimation

NASA Astrophysics Data System (ADS)

Flores, A. N.; Entekhabi, D.; Bras, R. L.

2007-12-01

Soil hydraulic and thermal properties (SHTPs) affect both the rate of moisture redistribution in the soil column and the volumetric soil water capacity. Adequately constraining these properties through field and lab analysis to parameterize spatially-distributed hydrology models is often prohibitively expensive. Because SHTPs vary significantly at small spatial scales individual soil samples are also only reliably indicative of local conditions, and these properties remain a significant source of uncertainty in soil moisture and temperature estimation. In ensemble-based soil moisture data assimilation, uncertainty in the model-produced prior estimate due to associated uncertainty in SHTPs must be taken into account to avoid under-dispersive ensembles. To treat SHTP uncertainty for purposes of supplying inputs to a distributed watershed model we use the restricted pairing (RP) algorithm, an extension of Latin Hypercube (LH) sampling. The RP algorithm generates an arbitrary number of SHTP combinations by sampling the appropriate marginal distributions of the individual soil properties using the LH approach, while imposing a target rank correlation among the properties. A previously-published meta- database of 1309 soils representing 12 textural classes is used to fit appropriate marginal distributions to the properties and compute the target rank correlation structure, conditioned on soil texture. Given categorical soil textures, our implementation of the RP algorithm generates an arbitrarily-sized ensemble of realizations of the SHTPs required as input to the TIN-based Realtime Integrated Basin Simulator with vegetation dynamics (tRIBS+VEGGIE) distributed parameter ecohydrology model. Soil moisture ensembles simulated with RP- generated SHTPs exhibit less variance than ensembles simulated with SHTPs generated by a scheme that neglects correlation among properties. Neglecting correlation among SHTPs can lead to physically unrealistic combinations of parameters that exhibit implausible hydrologic behavior when input to the tRIBS+VEGGIE model.

TH-CD-202-07: A Methodology for Generating Numerical Phantoms for Radiation Therapy Using Geometric Attribute Distribution Models

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

Dolly, S; Chen, H; Mutic, S

Purpose: A persistent challenge for the quality assessment of radiation therapy treatments (e.g. contouring accuracy) is the absence of the known, ground truth for patient data. Moreover, assessment results are often patient-dependent. Computer simulation studies utilizing numerical phantoms can be performed for quality assessment with a known ground truth. However, previously reported numerical phantoms do not include the statistical properties of inter-patient variations, as their models are based on only one patient. In addition, these models do not incorporate tumor data. In this study, a methodology was developed for generating numerical phantoms which encapsulate the statistical variations of patients withinmore » radiation therapy, including tumors. Methods: Based on previous work in contouring assessment, geometric attribute distribution (GAD) models were employed to model both the deterministic and stochastic properties of individual organs via principle component analysis. Using pre-existing radiation therapy contour data, the GAD models are trained to model the shape and centroid distributions of each organ. Then, organs with different shapes and positions can be generated by assigning statistically sound weights to the GAD model parameters. Organ contour data from 20 retrospective prostate patient cases were manually extracted and utilized to train the GAD models. As a demonstration, computer-simulated CT images of generated numerical phantoms were calculated and assessed subjectively and objectively for realism. Results: A cohort of numerical phantoms of the male human pelvis was generated. CT images were deemed realistic both subjectively and objectively in terms of image noise power spectrum. Conclusion: A methodology has been developed to generate realistic numerical anthropomorphic phantoms using pre-existing radiation therapy data. The GAD models guarantee that generated organs span the statistical distribution of observed radiation therapy patients, according to the training dataset. The methodology enables radiation therapy treatment assessment with multi-modality imaging and a known ground truth, and without patient-dependent bias.« less

Analysis on Voltage Profile of Distribution Network with Distributed Generation

NASA Astrophysics Data System (ADS)

Shao, Hua; Shi, Yujie; Yuan, Jianpu; An, Jiakun; Yang, Jianhua

2018-02-01

Penetration of distributed generation has some impacts on a distribution network in load flow, voltage profile, reliability, power loss and so on. After the impacts and the typical structures of the grid-connected distributed generation are analyzed, the back/forward sweep method of the load flow calculation of the distribution network is modelled including distributed generation. The voltage profiles of the distribution network affected by the installation location and the capacity of distributed generation are thoroughly investigated and simulated. The impacts on the voltage profiles are summarized and some suggestions to the installation location and the capacity of distributed generation are given correspondingly.

Feature Selection and Parameters Optimization of SVM Using Particle Swarm Optimization for Fault Classification in Power Distribution Systems.

PubMed

Cho, Ming-Yuan; Hoang, Thi Thom

2017-01-01

Fast and accurate fault classification is essential to power system operations. In this paper, in order to classify electrical faults in radial distribution systems, a particle swarm optimization (PSO) based support vector machine (SVM) classifier has been proposed. The proposed PSO based SVM classifier is able to select appropriate input features and optimize SVM parameters to increase classification accuracy. Further, a time-domain reflectometry (TDR) method with a pseudorandom binary sequence (PRBS) stimulus has been used to generate a dataset for purposes of classification. The proposed technique has been tested on a typical radial distribution network to identify ten different types of faults considering 12 given input features generated by using Simulink software and MATLAB Toolbox. The success rate of the SVM classifier is over 97%, which demonstrates the effectiveness and high efficiency of the developed method.

Optimal Interpolation scheme to generate reference crop evapotranspiration

NASA Astrophysics Data System (ADS)

Tomas-Burguera, Miquel; Beguería, Santiago; Vicente-Serrano, Sergio; Maneta, Marco

2018-05-01

We used an Optimal Interpolation (OI) scheme to generate a reference crop evapotranspiration (ETo) grid, forcing meteorological variables, and their respective error variance in the Iberian Peninsula for the period 1989-2011. To perform the OI we used observational data from the Spanish Meteorological Agency (AEMET) and outputs from a physically-based climate model. To compute ETo we used five OI schemes to generate grids for the five observed climate variables necessary to compute ETo using the FAO-recommended form of the Penman-Monteith equation (FAO-PM). The granularity of the resulting grids are less sensitive to variations in the density and distribution of the observational network than those generated by other interpolation methods. This is because our implementation of the OI method uses a physically-based climate model as prior background information about the spatial distribution of the climatic variables, which is critical for under-observed regions. This provides temporal consistency in the spatial variability of the climatic fields. We also show that increases in the density and improvements in the distribution of the observational network reduces substantially the uncertainty of the climatic and ETo estimates. Finally, a sensitivity analysis of observational uncertainties and network densification suggests the existence of a trade-off between quantity and quality of observations.

Sensitivity field distributions for segmental bioelectrical impedance analysis based on real human anatomy

NASA Astrophysics Data System (ADS)

Danilov, A. A.; Kramarenko, V. K.; Nikolaev, D. V.; Rudnev, S. G.; Salamatova, V. Yu; Smirnov, A. V.; Vassilevski, Yu V.

2013-04-01

In this work, an adaptive unstructured tetrahedral mesh generation technology is applied for simulation of segmental bioimpedance measurements using high-resolution whole-body model of the Visible Human Project man. Sensitivity field distributions for a conventional tetrapolar, as well as eight- and ten-electrode measurement configurations are obtained. Based on the ten-electrode configuration, we suggest an algorithm for monitoring changes in the upper lung area.

Numerical analysis of the accuracy of bivariate quantile distributions utilizing copulas compared to the GUM supplement 2 for oil pressure balance uncertainties

NASA Astrophysics Data System (ADS)

Ramnath, Vishal

2017-11-01

In the field of pressure metrology the effective area is Ae = A0 (1 + λP) where A0 is the zero-pressure area and λ is the distortion coefficient and the conventional practise is to construct univariate probability density functions (PDFs) for A0 and λ. As a result analytical generalized non-Gaussian bivariate joint PDFs has not featured prominently in pressure metrology. Recently extended lambda distribution based quantile functions have been successfully utilized for summarizing univariate arbitrary PDF distributions of gas pressure balances. Motivated by this development we investigate the feasibility and utility of extending and applying quantile functions to systems which naturally exhibit bivariate PDFs. Our approach is to utilize the GUM Supplement 1 methodology to solve and generate Monte Carlo based multivariate uncertainty data for an oil based pressure balance laboratory standard that is used to generate known high pressures, and which are in turn cross-floated against another pressure balance transfer standard in order to deduce the transfer standard's respective area. We then numerically analyse the uncertainty data by formulating and constructing an approximate bivariate quantile distribution that directly couples A0 and λ in order to compare and contrast its accuracy to an exact GUM Supplement 2 based uncertainty quantification analysis.

Investigation of the sound generation mechanisms for in-duct orifice plates.

PubMed

Tao, Fuyang; Joseph, Phillip; Zhang, Xin; Stalnov, Oksana; Siercke, Matthias; Scheel, Henning

2017-08-01

Sound generation due to an orifice plate in a hard-walled flow duct which is commonly used in air distribution systems (ADS) and flow meters is investigated. The aim is to provide an understanding of this noise generation mechanism based on measurements of the source pressure distribution over the orifice plate. A simple model based on Curle's acoustic analogy is described that relates the broadband in-duct sound field to the surface pressure cross spectrum on both sides of the orifice plate. This work describes careful measurements of the surface pressure cross spectrum over the orifice plate from which the surface pressure distribution and correlation length is deduced. This information is then used to predict the radiated in-duct sound field. Agreement within 3 dB between the predicted and directly measured sound fields is obtained, providing direct confirmation that the surface pressure fluctuations acting over the orifice plates are the main noise sources. Based on the developed model, the contributions to the sound field from different radial locations of the orifice plate are calculated. The surface pressure is shown to follow a U 3.9 velocity scaling law and the area over which the surface sources are correlated follows a U 1.8 velocity scaling law.

Optimal Sizing and Placement of Battery Energy Storage in Distribution System Based on Solar Size for Voltage Regulation

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

Nazaripouya, Hamidreza; Wang, Yubo; Chu, Peter

2016-07-26

This paper proposes a new strategy to achieve voltage regulation in distributed power systems in the presence of solar energy sources and battery storage systems. The goal is to find the minimum size of battery storage and its corresponding location in the network based on the size and place of the integrated solar generation. The proposed method formulates the problem by employing the network impedance matrix to obtain an analytical solution instead of using a recursive algorithm such as power flow. The required modifications for modeling the slack and PV buses (generator buses) are utilized to increase the accuracy ofmore » the approach. The use of reactive power control to regulate the voltage regulation is not always an optimal solution as in distribution systems R/X is large. In this paper the minimum size and the best place of battery storage is achieved by optimizing the amount of both active and reactive power exchanged by battery storage and its gridtie inverter (GTI) based on the network topology and R/X ratios in the distribution system. Simulation results for the IEEE 14-bus system verify the effectiveness of the proposed approach.« less

Defense Simulation Internet: next generation information highway.

PubMed

Lilienthal, M G

1995-06-01

The Department of Defense has been engaged in the Defense Modeling and Simulation Initiative (DMSI) to provide advanced distributed simulation warfighters in geographically distributed localities. Lessons learned from the Defense Simulation Internet (DSI) concerning architecture, standards, protocols, interoperability, information sharing, and distributed data bases are equally applicable to telemedicine. Much of the vision and objectives of the DMSI are easily translated into the vision for world wide telemedicine.

A novel method for energy harvesting simulation based on scenario generation

NASA Astrophysics Data System (ADS)

Wang, Zhe; Li, Taoshen; Xiao, Nan; Ye, Jin; Wu, Min

2018-06-01

Energy harvesting network (EHN) is a new form of computer networks. It converts ambient energy into usable electric energy and supply the electrical energy as a primary or secondary power source to the communication devices. However, most of the EHN uses the analytical probability distribution function to describe the energy harvesting process, which cannot accurately identify the actual situation for the lack of authenticity. We propose an EHN simulation method based on scenario generation in this paper. Firstly, instead of setting a probability distribution in advance, it uses optimal scenario reduction technology to generate representative scenarios in single period based on the historical data of the harvested energy. Secondly, it uses homogeneous simulated annealing algorithm to generate optimal daily energy harvesting scenario sequences to get a more accurate simulation of the random characteristics of the energy harvesting network. Then taking the actual wind power data as an example, the accuracy and stability of the method are verified by comparing with the real data. Finally, we cite an instance to optimize the network throughput, which indicate the feasibility and effectiveness of the method we proposed from the optimal solution and data analysis in energy harvesting simulation.

Distributed Energy Planning for Climate Resilience

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

Stout, Sherry R; Hotchkiss, Elizabeth L; Day, Megan H

At various levels of government across the United States and globally climate resilient solutions are being adopted and implemented. Solutions vary based on predicted hazards, community context, priorities, complexity, and available resources. Lessons are being learned through the implementation process, which can be replicated regardless of level or type of government entity carrying out the resiliency planning. Through a number of analyses and technical support across the world, NREL has learned key lessons related to resilience planning associated with power generation and water distribution. Distributed energy generation is a large factor in building resilience with clean energy technologies and solutions.more » The technical and policy solutions associated with distributed energy implementation for resilience fall into a few major categories, including spatial diversification, microgrids, water-energy nexus, policy, and redundancy.« less

Toward Narrowing Fermentation Endproduct Distribution in Undefined Mixed Culture Anaerobic Conversion of Lignocellulosic Corn Fiber to Butyrate

USDA-ARS?s Scientific Manuscript database

Conversion of second-generation renewable energy sources to useful products is gaining attention as an alternative to traditional conversion of sugar and starch-based renewable energy crops. The natural recalcitrance of second-generation energy resources, such as (ligno)cellulosic feedstock, makes ...

FPGA and USB based control board for quantum random number generator

NASA Astrophysics Data System (ADS)

Wang, Jian; Wan, Xu; Zhang, Hong-Fei; Gao, Yuan; Chen, Teng-Yun; Liang, Hao

2009-09-01

The design and implementation of FPGA-and-USB-based control board for quantum experiments are discussed. The usage of quantum true random number generator, control- logic in FPGA and communication with computer through USB protocol are proposed in this paper. Programmable controlled signal input and output ports are implemented. The error-detections of data frame header and frame length are designed. This board has been used in our decoy-state based quantum key distribution (QKD) system successfully.

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.

Improved Hyperthermia Treatment of Tumors Under Consideration of Magnetic Nanoparticle Distribution Using Micro-CT Imaging.

PubMed

Dähring, H; Grandke, J; Teichgräber, U; Hilger, I

2015-12-01

Heterogeneous magnetic nanoparticle (MNP) distributions within tumors can cause regions of temperature under dosage and reduce the therapeutic efficiency. Here, micro-computed tomography (CT) imaging was used as a tool to determine the MNP distribution in vivo. The therapeutic success was evaluated based on tumor volume and temperature distribution. Tumor-bearing mice were intratumorally injected with iron oxide particles. MNP distribution was assessed by micro-CT with a low radiation dose protocol. MNPs were clearly visible, and the exact distribution to nontumor structures was detected by micro-CT. Knowledge of the intratumoral MNP distribution allowed the generation of higher temperatures within the tumor and led to higher temperature values after exposure to an alternating magnetic field (AMF). Consequently, the tumor size after 28 days was reduced to 14 and 73 % of the initial tumor volume for the MNP/AMF/CT and MNP/AMF groups, respectively. The MNP distribution pattern mainly governed the generated temperature spots in the tumor. Knowing the MNP distribution enabled individualized hyperthermia treatment and improved the overall therapeutic efficiency.

Tunable terahertz wave generation through a bimodal laser diode and plasmonic photomixer.

PubMed

Yang, S-H; Watts, R; Li, X; Wang, N; Cojocaru, V; O'Gorman, J; Barry, L P; Jarrahi, M

2015-11-30

We demonstrate a compact, robust, and stable terahertz source based on a novel two section digital distributed feedback laser diode and plasmonic photomixer. Terahertz wave generation is achieved through difference frequency generation by pumping the plasmonic photomixer with two output optical beams of the two section digital distributed feedback laser diode. The laser is designed to offer an adjustable terahertz frequency difference between the emitted wavelengths by varying the applied currents to the laser sections. The plasmonic photomixer is comprised of an ultrafast photoconductor with plasmonic contact electrodes integrated with a logarithmic spiral antenna. We demonstrate terahertz wave generation with 0.15-3 THz frequency tunability, 2 MHz linewidth, and less than 5 MHz frequency stability over 1 minute, at useful power levels for practical imaging and sensing applications.

New Technology/Old Technology: Comparing Lunar Grain Size Distribution Data and Methods

NASA Technical Reports Server (NTRS)

Fruland, R. M.; Cooper, Bonnie L.; Gonzalexz, C. P.; McKay, David S.

2011-01-01

Laser diffraction technology generates reproducible grain size distributions and reveals new structures not apparent in old sieve data. The comparison of specific sieve fractions with the Microtrac distribution curve generated for those specific fractions shows a reasonable match for the mean of each fraction between the two techniques, giving us confidence that the large existing body of sieve data can be cross-correlated with new data based on laser diffraction. It is well-suited for lunar soils, which have as much as 25% of the material in the less than 20 micrometer fraction. The fines in this range are of particular interest because they may contain a record of important space weathering processes.

Impact of Next Generation District Heating Systems on Distribution Network Heat Losses: A Case Study Approach

NASA Astrophysics Data System (ADS)

Li, Yu; Rezgui, Yacine

2018-01-01

District heating (DH) is a promising energy pathway to alleviate environmental negative impacts induced by fossil fuels. Improving the performance of DH systems is one of the major challenges facing its wide adoption. This paper discusses the heat losses of the next generation DH based on the constructed Simulink model. Results show that lower distribution temperature and advanced insulation technology greatly reduce network heat losses. Also, the network heat loss can be further minimized by a reduction of heat demand in buildings.

Nonstationary Dynamics Data Analysis with Wavelet-SVD Filtering

NASA Technical Reports Server (NTRS)

Brenner, Marty; Groutage, Dale; Bessette, Denis (Technical Monitor)

2001-01-01

Nonstationary time-frequency analysis is used for identification and classification of aeroelastic and aeroservoelastic dynamics. Time-frequency multiscale wavelet processing generates discrete energy density distributions. The distributions are processed using the singular value decomposition (SVD). Discrete density functions derived from the SVD generate moments that detect the principal features in the data. The SVD standard basis vectors are applied and then compared with a transformed-SVD, or TSVD, which reduces the number of features into more compact energy density concentrations. Finally, from the feature extraction, wavelet-based modal parameter estimation is applied.

The genomic structure: proof of the role of non-coding DNA.

PubMed

Bouaynaya, Nidhal; Schonfeld, Dan

2006-01-01

We prove that the introns play the role of a decoy in absorbing mutations in the same way hollow uninhabited structures are used by the military to protect important installations. Our approach is based on a probability of error analysis, where errors are mutations which occur in the exon sequences. We derive the optimal exon length distribution, which minimizes the probability of error in the genome. Furthermore, to understand how can Nature generate the optimal distribution, we propose a diffusive random walk model for exon generation throughout evolution. This model results in an alpha stable exon length distribution, which is asymptotically equivalent to the optimal distribution. Experimental results show that both distributions accurately fit the real data. Given that introns also drive biological evolution by increasing the rate of unequal crossover between genes, we conclude that the role of introns is to maintain a genius balance between stability and adaptability in eukaryotic genomes.

Data center thermal management

DOEpatents

Hamann, Hendrik F.; Li, Hongfei

2016-02-09

Historical high-spatial-resolution temperature data and dynamic temperature sensor measurement data may be used to predict temperature. A first formulation may be derived based on the historical high-spatial-resolution temperature data for determining a temperature at any point in 3-dimensional space. The dynamic temperature sensor measurement data may be calibrated based on the historical high-spatial-resolution temperature data at a corresponding historical time. Sensor temperature data at a plurality of sensor locations may be predicted for a future time based on the calibrated dynamic temperature sensor measurement data. A three-dimensional temperature spatial distribution associated with the future time may be generated based on the forecasted sensor temperature data and the first formulation. The three-dimensional temperature spatial distribution associated with the future time may be projected to a two-dimensional temperature distribution, and temperature in the future time for a selected space location may be forecasted dynamically based on said two-dimensional temperature distribution.

Modeling the Impacts of Solar Distributed Generation on U.S. Water Resources

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

Amanda, Smith; Omitaomu, Olufemi A; Jaron, Peck

2015-01-01

Distributed electric power generation technologies typically use little or no water per unit of electrical energy produced; in particular, renewable energy sources such as solar PV systems do not require cooling systems and present an opportunity to reduce water usage for power generation. Within the US, the fuel mix used for power generation varies regionally, and certain areas use more water for power generation than others. The need to reduce water usage for power generation is even more urgent in view of climate change uncertainties. In this paper, we present an example case within the state of Tennessee, one ofmore » the top four states in water consumption for power generation and one of the states with little or no potential for developing centralized renewable energy generations. The potential for developing PV generation within Knox County, Tennessee, is studied, along with the potential for reducing water withdrawal and consumption within the Tennessee Valley stream region. Electric power generation plants in the region are quantified for their electricity production and expected water withdrawal and consumption over one year, where electrical generation data is provided over one year and water usage is modeled based on the cooling system(s) in use. Potential solar PV electrical production is modeled based on LiDAR data and weather data for the same year. Our proposed methodology can be summarized as follows: First, the potential solar generation is compared against the local grid demand. Next, electrical generation reductions are specified that would result in a given reduction in water withdrawal and a given reduction in water consumption, and compared with the current water withdrawal and consumption rates for the existing fuel mix. The increase in solar PV development that would produce an equivalent amount of power, is determined. In this way, we consider how targeted local actions may affect the larger stream region through thoughtful energy development. This model can be applied to other regions, other types of distributed generation, and used as a framework for modeling alternative growth scenarios in power production capacity in addition to modeling adjustments to existing capacity.« less

Distributed source model for the full-wave electromagnetic simulation of nonlinear terahertz generation.

PubMed

Fumeaux, Christophe; Lin, Hungyen; Serita, Kazunori; Withayachumnankul, Withawat; Kaufmann, Thomas; Tonouchi, Masayoshi; Abbott, Derek

2012-07-30

The process of terahertz generation through optical rectification in a nonlinear crystal is modeled using discretized equivalent current sources. The equivalent terahertz sources are distributed in the active volume and computed based on a separately modeled near-infrared pump beam. This approach can be used to define an appropriate excitation for full-wave electromagnetic numerical simulations of the generated terahertz radiation. This enables predictive modeling of the near-field interactions of the terahertz beam with micro-structured samples, e.g. in a near-field time-resolved microscopy system. The distributed source model is described in detail, and an implementation in a particular full-wave simulation tool is presented. The numerical results are then validated through a series of measurements on square apertures. The general principle can be applied to other nonlinear processes with possible implementation in any full-wave numerical electromagnetic solver.

Noise-Induced Synchronization among Sub-RF CMOS Analog Oscillators for Skew-Free Clock Distribution

NASA Astrophysics Data System (ADS)

Utagawa, Akira; Asai, Tetsuya; Hirose, Tetsuya; Amemiya, Yoshihito

We present on-chip oscillator arrays synchronized by random noises, aiming at skew-free clock distribution on synchronous digital systems. Nakao et al. recently reported that independent neural oscillators can be synchronized by applying temporal random impulses to the oscillators [1], [2]. We regard neural oscillators as independent clock sources on LSIs; i. e., clock sources are distributed on LSIs, and they are forced to synchronize through the use of random noises. We designed neuron-based clock generators operating at sub-RF region (<1GHz) by modifying the original neuron model to a new model that is suitable for CMOS implementation with 0.25-μm CMOS parameters. Through circuit simulations, we demonstrate that i) the clock generators are certainly synchronized by pseudo-random noises and ii) clock generators exhibited phase-locked oscillations even if they had small device mismatches.

Design and Realization of Online Monitoring System of Distributed New Energy and Renewable Energy

NASA Astrophysics Data System (ADS)

Tang, Yanfen; Zhou, Tao; Li, Mengwen; Zheng, Guotai; Li, Hao

2018-01-01

Aimed at difficult centralized monitoring and management of current distributed new energy and renewable energy generation projects due to great varieties, different communication protocols and large-scale difference, this paper designs a online monitoring system of new energy and renewable energy characterized by distributed deployment, tailorable functions, extendible applications and fault self-healing performance. This system is designed based on international general standard for grid information data model, formulates unified data acquisition and transmission standard for different types of new energy and renewable energy generation projects, and can realize unified data acquisition and real-time monitoring of new energy and renewable energy generation projects, such as solar energy, wind power, biomass energy, etc. within its jurisdiction. This system has applied in Beijing. At present, 576 projects are connected to the system. Good effect is achieved and stability and reliability of the system have been validated.

Study on Stochastic Optimal Electric Power Procurement Strategies with Uncertain Market Prices

NASA Astrophysics Data System (ADS)

Sakchai, Siripatanakulkhajorn; Saisho, Yuichi; Fujii, Yasumasa; Yamaji, Kenji

The player in deregulated electricity markets can be categorized into three groups of GENCO (Generator Companies), TRNASCO (Transmission Companies), DISCO (Distribution Companies). This research focuses on the role of Distribution Companies, which purchase electricity from market at randomly fluctuating prices, and provide it to their customers at given fixed prices. Therefore Distribution companies have to take the risk stemming from price fluctuation of electricity instead of the customers. This entails the necessity to develop a certain method to make an optimal strategy for electricity procurement. In such a circumstance, this research has the purpose for proposing the mathematical method based on stochastic dynamic programming to evaluate the value of a long-term bilateral contract of electricity trade, and also a project of combination of the bilateral contract and power generation with their own generators for procuring electric power in deregulated market.

Analysis on flood generation processes by means of a continuous simulation model

NASA Astrophysics Data System (ADS)

Fiorentino, M.; Gioia, A.; Iacobellis, V.; Manfreda, S.

2006-03-01

In the present research, we exploited a continuous hydrological simulation to investigate on key variables responsible of flood peak formation. With this purpose, a distributed hydrological model (DREAM) is used in cascade with a rainfall generator (IRP-Iterated Random Pulse) to simulate a large number of extreme events providing insight into the main controls of flood generation mechanisms. Investigated variables are those used in theoretically derived probability distribution of floods based on the concept of partial contributing area (e.g. Iacobellis and Fiorentino, 2000). The continuous simulation model is used to investigate on the hydrological losses occurring during extreme events, the variability of the source area contributing to the flood peak and its lag-time. Results suggest interesting simplification for the theoretical probability distribution of floods according to the different climatic and geomorfologic environments. The study is applied to two basins located in Southern Italy with different climatic characteristics.

Generating high-accuracy urban distribution map for short-term change monitoring based on convolutional neural network by utilizing SAR imagery

NASA Astrophysics Data System (ADS)

Iino, Shota; Ito, Riho; Doi, Kento; Imaizumi, Tomoyuki; Hikosaka, Shuhei

2017-10-01

In the developing countries, urban areas are expanding rapidly. With the rapid developments, a short term monitoring of urban changes is important. A constant observation and creation of urban distribution map of high accuracy and without noise pollution are the key issues for the short term monitoring. SAR satellites are highly suitable for day or night and regardless of atmospheric weather condition observations for this type of study. The current study highlights the methodology of generating high-accuracy urban distribution maps derived from the SAR satellite imagery based on Convolutional Neural Network (CNN), which showed the outstanding results for image classification. Several improvements on SAR polarization combinations and dataset construction were performed for increasing the accuracy. As an additional data, Digital Surface Model (DSM), which are useful to classify land cover, were added to improve the accuracy. From the obtained result, high-accuracy urban distribution map satisfying the quality for short-term monitoring was generated. For the evaluation, urban changes were extracted by taking the difference of urban distribution maps. The change analysis with time series of imageries revealed the locations of urban change areas for short-term. Comparisons with optical satellites were performed for validating the results. Finally, analysis of the urban changes combining X-band, L-band and C-band SAR satellites was attempted to increase the opportunity of acquiring satellite imageries. Further analysis will be conducted as future work of the present study

GRID3D-v2: An updated version of the GRID2D/3D computer program for generating grid systems in complex-shaped three-dimensional spatial domains

NASA Technical Reports Server (NTRS)

Steinthorsson, E.; Shih, T. I-P.; Roelke, R. J.

1991-01-01

In order to generate good quality systems for complicated three-dimensional spatial domains, the grid-generation method used must be able to exert rather precise controls over grid-point distributions. Several techniques are presented that enhance control of grid-point distribution for a class of algebraic grid-generation methods known as the two-, four-, and six-boundary methods. These techniques include variable stretching functions from bilinear interpolation, interpolating functions based on tension splines, and normalized K-factors. The techniques developed in this study were incorporated into a new version of GRID3D called GRID3D-v2. The usefulness of GRID3D-v2 was demonstrated by using it to generate a three-dimensional grid system in the coolent passage of a radial turbine blade with serpentine channels and pin fins.

On a framework for generating PoD curves assisted by numerical simulations

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

Subair, S. Mohamed, E-mail: prajagopal@iitm.ac.in; Agrawal, Shweta, E-mail: prajagopal@iitm.ac.in; Balasubramaniam, Krishnan, E-mail: prajagopal@iitm.ac.in

2015-03-31

The Probability of Detection (PoD) curve method has emerged as an important tool for the assessment of the performance of NDE techniques, a topic of particular interest to the nuclear industry where inspection qualification is very important. The conventional experimental means of generating PoD curves though, can be expensive, requiring large data sets (covering defects and test conditions), and equipment and operator time. Several methods of achieving faster estimates for PoD curves using physics-based modelling have been developed to address this problem. Numerical modelling techniques are also attractive, especially given the ever-increasing computational power available to scientists today. Here wemore » develop procedures for obtaining PoD curves, assisted by numerical simulation and based on Bayesian statistics. Numerical simulations are performed using Finite Element analysis for factors that are assumed to be independent, random and normally distributed. PoD curves so generated are compared with experiments on austenitic stainless steel (SS) plates with artificially created notches. We examine issues affecting the PoD curve generation process including codes, standards, distribution of defect parameters and the choice of the noise threshold. We also study the assumption of normal distribution for signal response parameters and consider strategies for dealing with data that may be more complex or sparse to justify this. These topics are addressed and illustrated through the example case of generation of PoD curves for pulse-echo ultrasonic inspection of vertical surface-breaking cracks in SS plates.« less

On a framework for generating PoD curves assisted by numerical simulations

NASA Astrophysics Data System (ADS)

Subair, S. Mohamed; Agrawal, Shweta; Balasubramaniam, Krishnan; Rajagopal, Prabhu; Kumar, Anish; Rao, Purnachandra B.; Tamanna, Jayakumar

2015-03-01

The Probability of Detection (PoD) curve method has emerged as an important tool for the assessment of the performance of NDE techniques, a topic of particular interest to the nuclear industry where inspection qualification is very important. The conventional experimental means of generating PoD curves though, can be expensive, requiring large data sets (covering defects and test conditions), and equipment and operator time. Several methods of achieving faster estimates for PoD curves using physics-based modelling have been developed to address this problem. Numerical modelling techniques are also attractive, especially given the ever-increasing computational power available to scientists today. Here we develop procedures for obtaining PoD curves, assisted by numerical simulation and based on Bayesian statistics. Numerical simulations are performed using Finite Element analysis for factors that are assumed to be independent, random and normally distributed. PoD curves so generated are compared with experiments on austenitic stainless steel (SS) plates with artificially created notches. We examine issues affecting the PoD curve generation process including codes, standards, distribution of defect parameters and the choice of the noise threshold. We also study the assumption of normal distribution for signal response parameters and consider strategies for dealing with data that may be more complex or sparse to justify this. These topics are addressed and illustrated through the example case of generation of PoD curves for pulse-echo ultrasonic inspection of vertical surface-breaking cracks in SS plates.

Nonlinear dispersion-based incoherent photonic processing for microwave pulse generation with full reconfigurability.

PubMed

Bolea, Mario; Mora, José; Ortega, Beatriz; Capmany, José

2012-03-12

A novel all-optical technique based on the incoherent processing of optical signals using high-order dispersive elements is analyzed for microwave arbitrary pulse generation. We show an approach which allows a full reconfigurability of a pulse in terms of chirp, envelope and central frequency by the proper control of the second-order dispersion and the incoherent optical source power distribution, achieving large values of time-bandwidth product.

Counterfactual quantum key distribution with high efficiency

NASA Astrophysics Data System (ADS)

Sun, Ying; Wen, Qiao-Yan

2010-11-01

In a counterfactual quantum key distribution scheme, a secret key can be generated merely by transmitting the split vacuum pulses of single particles. We improve the efficiency of the first quantum key distribution scheme based on the counterfactual phenomenon. This scheme not only achieves the same security level as the original one but also has higher efficiency. We also analyze how to achieve the optimal efficiency under various conditions.

Counterfactual quantum key distribution with high efficiency

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

Sun Ying; Beijing Electronic Science and Technology Institute, Beijing 100070; Wen Qiaoyan

2010-11-15

In a counterfactual quantum key distribution scheme, a secret key can be generated merely by transmitting the split vacuum pulses of single particles. We improve the efficiency of the first quantum key distribution scheme based on the counterfactual phenomenon. This scheme not only achieves the same security level as the original one but also has higher efficiency. We also analyze how to achieve the optimal efficiency under various conditions.

Effect of Changing Treatment Disinfectants on the Microbiology of Distributed Water and Pipe Biofilm Communities using Conventional and Metagenomic Approaches

EPA Science Inventory

The purpose of this research was to add to our knowledge of chlorine and monochloramine disinfectants, with regards to effects on the microbial communities in distribution systems. A whole metagenome-based approach using sophisticated molecular tools (e.g., next generation sequen...

Towards Natural Transition in Compressible Boundary Layers

DTIC Science & Technology

2016-06-29

Behaviour of a natural laminar flow aerofoil in flight through atmospheric turbulence. Journal of Fluid Mechanics, 767:394–429, 003 2015. [70] O...DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited See report Wave packet, compressible boundary layer, subsonic flow ...Base flow generation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 3.1.1 Boundary layer profiles

Fine-Grained Linguistic Soft Constraints on Statistical Natural Language Processing Models

DTIC Science & Technology

2009-01-01

88 4 Monolingually -Derived Phrasal Paraphrase Generation for Statistical Ma- chine Translation 90 4.1...123 4.4 Spanish-English (S2E) results . . . . . . . . . . . . . . . . . . . . . . 125 4.5 Gains from using larger monolingual corpora for...96 4.2 Visual example of a phrasal distributional profile . . . . . . . . . . . . 103 4.3 Monolingual corpus-based distributional

Probability density function characterization for aggregated large-scale wind power based on Weibull mixtures

DOE PAGES

Gomez-Lazaro, Emilio; Bueso, Maria C.; Kessler, Mathieu; ...

2016-02-02

Here, the Weibull probability distribution has been widely applied to characterize wind speeds for wind energy resources. Wind power generation modeling is different, however, due in particular to power curve limitations, wind turbine control methods, and transmission system operation requirements. These differences are even greater for aggregated wind power generation in power systems with high wind penetration. Consequently, models based on one-Weibull component can provide poor characterizations for aggregated wind power generation. With this aim, the present paper focuses on discussing Weibull mixtures to characterize the probability density function (PDF) for aggregated wind power generation. PDFs of wind power datamore » are firstly classified attending to hourly and seasonal patterns. The selection of the number of components in the mixture is analyzed through two well-known different criteria: the Akaike information criterion (AIC) and the Bayesian information criterion (BIC). Finally, the optimal number of Weibull components for maximum likelihood is explored for the defined patterns, including the estimated weight, scale, and shape parameters. Results show that multi-Weibull models are more suitable to characterize aggregated wind power data due to the impact of distributed generation, variety of wind speed values and wind power curtailment.« less

Renewable Energy Power Generation Estimation Using Consensus Algorithm

NASA Astrophysics Data System (ADS)

Ahmad, Jehanzeb; Najm-ul-Islam, M.; Ahmed, Salman

2017-08-01

At the small consumer level, Photo Voltaic (PV) panel based grid tied systems are the most common form of Distributed Energy Resources (DER). Unlike wind which is suitable for only selected locations, PV panels can generate electricity almost anywhere. Pakistan is currently one of the most energy deficient countries in the world. In order to mitigate this shortage the Government has recently announced a policy of net-metering for residential consumers. After wide spread adoption of DERs, one of the issues that will be faced by load management centers would be accurate estimate of the amount of electricity being injected in the grid at any given time through these DERs. This becomes a critical issue once the penetration of DER increases beyond a certain limit. Grid stability and management of harmonics becomes an important consideration where electricity is being injected at the distribution level and through solid state controllers instead of rotating machinery. This paper presents a solution using graph theoretic methods for the estimation of total electricity being injected in the grid in a wide spread geographical area. An agent based consensus approach for distributed computation is being used to provide an estimate under varying generation conditions.

Distributed vibration fiber sensing system based on Polarization Diversity Receiver

NASA Astrophysics Data System (ADS)

Zhang, Junan; Jiang, Peng; Hu, Zhengliang; Hu, Yongming

2016-10-01

In this paper, we propose a distributed vibration fiber sensing system based on Polarization Diversity Receiver(PDR). We use Acoustic Optical Modulator(AOM) to generate pulse light and an unbalanced M-Z interferometer to generate two pulse light with a certain time delay in the same period. As the pulse lights propagating in fibers, the Backward Rayleigh scattering lights will interfere with each other. The vibration on the fiber will change the length and refractive index of fiber which results in the change of the phase of the interference signal. Hence, one arm of the M-Z interferometer is modulated by a sinusoidal phase-generated carrier(PGC) signal, and PGC demodulation algorithm has been used to acquire phase information from the Backward Rayleigh scattering lights. In order to overcome the influence of polarization-induced fading and enhance Signal Noise Ratio(SNR), we set a PDR before the photo detector. The Polarization Diversity Receiver segregates the interfere light into two lights with orthogonal states of polarization. Hence, there is always one channel has a better interfere light signal. The experiments are presented to verify the effectiveness of the distributed vibration fiber sensing system proposed.

Improved Quantum Artificial Fish Algorithm Application to Distributed Network Considering Distributed Generation.

PubMed

Du, Tingsong; Hu, Yang; Ke, Xianting

2015-01-01

An improved quantum artificial fish swarm algorithm (IQAFSA) for solving distributed network programming considering distributed generation is proposed in this work. The IQAFSA based on quantum computing which has exponential acceleration for heuristic algorithm uses quantum bits to code artificial fish and quantum revolving gate, preying behavior, and following behavior and variation of quantum artificial fish to update the artificial fish for searching for optimal value. Then, we apply the proposed new algorithm, the quantum artificial fish swarm algorithm (QAFSA), the basic artificial fish swarm algorithm (BAFSA), and the global edition artificial fish swarm algorithm (GAFSA) to the simulation experiments for some typical test functions, respectively. The simulation results demonstrate that the proposed algorithm can escape from the local extremum effectively and has higher convergence speed and better accuracy. Finally, applying IQAFSA to distributed network problems and the simulation results for 33-bus radial distribution network system show that IQAFSA can get the minimum power loss after comparing with BAFSA, GAFSA, and QAFSA.

Improved Quantum Artificial Fish Algorithm Application to Distributed Network Considering Distributed Generation

PubMed Central

Hu, Yang; Ke, Xianting

2015-01-01

An improved quantum artificial fish swarm algorithm (IQAFSA) for solving distributed network programming considering distributed generation is proposed in this work. The IQAFSA based on quantum computing which has exponential acceleration for heuristic algorithm uses quantum bits to code artificial fish and quantum revolving gate, preying behavior, and following behavior and variation of quantum artificial fish to update the artificial fish for searching for optimal value. Then, we apply the proposed new algorithm, the quantum artificial fish swarm algorithm (QAFSA), the basic artificial fish swarm algorithm (BAFSA), and the global edition artificial fish swarm algorithm (GAFSA) to the simulation experiments for some typical test functions, respectively. The simulation results demonstrate that the proposed algorithm can escape from the local extremum effectively and has higher convergence speed and better accuracy. Finally, applying IQAFSA to distributed network problems and the simulation results for 33-bus radial distribution network system show that IQAFSA can get the minimum power loss after comparing with BAFSA, GAFSA, and QAFSA. PMID:26447713

Parametric vs. non-parametric daily weather generator: validation and comparison

NASA Astrophysics Data System (ADS)

Dubrovsky, Martin

2016-04-01

As the climate models (GCMs and RCMs) fail to satisfactorily reproduce the real-world surface weather regime, various statistical methods are applied to downscale GCM/RCM outputs into site-specific weather series. The stochastic weather generators are among the most favourite downscaling methods capable to produce realistic (observed like) meteorological inputs for agrological, hydrological and other impact models used in assessing sensitivity of various ecosystems to climate change/variability. To name their advantages, the generators may (i) produce arbitrarily long multi-variate synthetic weather series representing both present and changed climates (in the latter case, the generators are commonly modified by GCM/RCM-based climate change scenarios), (ii) be run in various time steps and for multiple weather variables (the generators reproduce the correlations among variables), (iii) be interpolated (and run also for sites where no weather data are available to calibrate the generator). This contribution will compare two stochastic daily weather generators in terms of their ability to reproduce various features of the daily weather series. M&Rfi is a parametric generator: Markov chain model is used to model precipitation occurrence, precipitation amount is modelled by the Gamma distribution, and the 1st order autoregressive model is used to generate non-precipitation surface weather variables. The non-parametric GoMeZ generator is based on the nearest neighbours resampling technique making no assumption on the distribution of the variables being generated. Various settings of both weather generators will be assumed in the present validation tests. The generators will be validated in terms of (a) extreme temperature and precipitation characteristics (annual and 30 years extremes and maxima of duration of hot/cold/dry/wet spells); (b) selected validation statistics developed within the frame of VALUE project. The tests will be based on observational weather series from several European stations available from the ECA&D database.

A Wavelet-based Fast Discrimination of Transformer Magnetizing Inrush Current

NASA Astrophysics Data System (ADS)

Kitayama, Masashi

Recently customers who need electricity of higher quality have been installing co-generation facilities. They can avoid voltage sags and other distribution system related disturbances by supplying electricity to important load from their generators. For another example, FRIENDS, highly reliable distribution system using semiconductor switches or storage devices based on power electronics technology, is proposed. These examples illustrates that the request for high reliability in distribution system is increasing. In order to realize these systems, fast relaying algorithms are indispensable. The author proposes a new method of detecting magnetizing inrush current using discrete wavelet transform (DWT). DWT provides the function of detecting discontinuity of current waveform. Inrush current occurs when transformer core becomes saturated. The proposed method detects spikes of DWT components derived from the discontinuity of the current waveform at both the beginning and the end of inrush current. Wavelet thresholding, one of the wavelet-based statistical modeling, was applied to detect the DWT component spikes. The proposed method is verified using experimental data using single-phase transformer and the proposed method is proved to be effective.

GENIE(++): A Multi-Block Structured Grid System

NASA Technical Reports Server (NTRS)

Williams, Tonya; Nadenthiran, Naren; Thornburg, Hugh; Soni, Bharat K.

1996-01-01

The computer code GENIE++ is a continuously evolving grid system containing a multitude of proven geometry/grid techniques. The generation process in GENIE++ is based on an earlier version. The process uses several techniques either separately or in combination to quickly and economically generate sculptured geometry descriptions and grids for arbitrary geometries. The computational mesh is formed by using an appropriate algebraic method. Grid clustering is accomplished with either exponential or hyperbolic tangent routines which allow the user to specify a desired point distribution. Grid smoothing can be accomplished by using an elliptic solver with proper forcing functions. B-spline and Non-Uniform Rational B-splines (NURBS) algorithms are used for surface definition and redistribution. The built in sculptured geometry definition with desired distribution of points, automatic Bezier curve/surface generation for interior boundaries/surfaces, and surface redistribution is based on NURBS. Weighted Lagrance/Hermite transfinite interpolation methods, interactive geometry/grid manipulation modules, and on-line graphical visualization of the generation process are salient features of this system which result in a significant time savings for a given geometry/grid application.

Distributed Load Shedding over Directed Communication Networks with Time Delays

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

Yang, Tao; Wu, Di

When generation is insufficient to support all loads under emergencies, effective and efficient load shedding needs to be deployed in order to maintain the supply-demand balance. This paper presents a distributed load shedding algorithm, which makes efficient decision based on the discovered global information. In the global information discovery process, each load only communicates with its neighboring load via directed communication links possibly with arbitrarily large but bounded time varying communication delays. We propose a novel distributed information discovery algorithm based on ratio consensus. Simulation results are used to validate the proposed method.

Distributed Noise Generation for Density Estimation Based Clustering without Trusted Third Party

NASA Astrophysics Data System (ADS)

Su, Chunhua; Bao, Feng; Zhou, Jianying; Takagi, Tsuyoshi; Sakurai, Kouichi

The rapid growth of the Internet provides people with tremendous opportunities for data collection, knowledge discovery and cooperative computation. However, it also brings the problem of sensitive information leakage. Both individuals and enterprises may suffer from the massive data collection and the information retrieval by distrusted parties. In this paper, we propose a privacy-preserving protocol for the distributed kernel density estimation-based clustering. Our scheme applies random data perturbation (RDP) technique and the verifiable secret sharing to solve the security problem of distributed kernel density estimation in [4] which assumed a mediate party to help in the computation.

MuffinInfo: HTML5-Based Statistics Extractor from Next-Generation Sequencing Data.

PubMed

Alic, Andy S; Blanquer, Ignacio

2016-09-01

Usually, the information known a priori about a newly sequenced organism is limited. Even resequencing the same organism can generate unpredictable output. We introduce MuffinInfo, a FastQ/Fasta/SAM information extractor implemented in HTML5 capable of offering insights into next-generation sequencing (NGS) data. Our new tool can run on any software or hardware environment, in command line or graphically, and in browser or standalone. It presents information such as average length, base distribution, quality scores distribution, k-mer histogram, and homopolymers analysis. MuffinInfo improves upon the existing extractors by adding the ability to save and then reload the results obtained after a run as a navigable file (also supporting saving pictures of the charts), by supporting custom statistics implemented by the user, and by offering user-adjustable parameters involved in the processing, all in one software. At the moment, the extractor works with all base space technologies such as Illumina, Roche, Ion Torrent, Pacific Biosciences, and Oxford Nanopore. Owing to HTML5, our software demonstrates the readiness of web technologies for mild intensive tasks encountered in bioinformatics.

Distributed Coordination for Optimal Energy Generation and Distribution in Cyber-Physical Energy Networks.

PubMed

Ahn, Hyo-Sung; Kim, Byeong-Yeon; Lim, Young-Hun; Lee, Byung-Hun; Oh, Kwang-Kyo

2018-03-01

This paper proposes three coordination laws for optimal energy generation and distribution in energy network, which is composed of physical flow layer and cyber communication layer. The physical energy flows through the physical layer; but all the energies are coordinated to generate and flow by distributed coordination algorithms on the basis of communication information. First, distributed energy generation and energy distribution laws are proposed in a decoupled manner without considering the interactive characteristics between the energy generation and energy distribution. Second, a joint coordination law to treat the energy generation and energy distribution in a coupled manner taking account of the interactive characteristics is designed. Third, to handle over- or less-energy generation cases, an energy distribution law for networks with batteries is designed. The coordination laws proposed in this paper are fully distributed in the sense that they are decided optimally only using relative information among neighboring nodes. Through numerical simulations, the validity of the proposed distributed coordination laws is illustrated.

Probabilistic Wind Power Ramp Forecasting Based on a Scenario Generation Method

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

Wang, Qin; Florita, Anthony R; Krishnan, Venkat K

Wind power ramps (WPRs) are particularly important in the management and dispatch of wind power and currently drawing the attention of balancing authorities. With the aim to reduce the impact of WPRs for power system operations, this paper develops a probabilistic ramp forecasting method based on a large number of simulated scenarios. An ensemble machine learning technique is first adopted to forecast the basic wind power forecasting scenario and calculate the historical forecasting errors. A continuous Gaussian mixture model (GMM) is used to fit the probability distribution function (PDF) of forecasting errors. The cumulative distribution function (CDF) is analytically deduced.more » The inverse transform method based on Monte Carlo sampling and the CDF is used to generate a massive number of forecasting error scenarios. An optimized swinging door algorithm is adopted to extract all the WPRs from the complete set of wind power forecasting scenarios. The probabilistic forecasting results of ramp duration and start-time are generated based on all scenarios. Numerical simulations on publicly available wind power data show that within a predefined tolerance level, the developed probabilistic wind power ramp forecasting method is able to predict WPRs with a high level of sharpness and accuracy.« less

Probabilistic Wind Power Ramp Forecasting Based on a Scenario Generation Method: Preprint

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

Wang, Qin; Florita, Anthony R; Krishnan, Venkat K

2017-08-31

Wind power ramps (WPRs) are particularly important in the management and dispatch of wind power, and they are currently drawing the attention of balancing authorities. With the aim to reduce the impact of WPRs for power system operations, this paper develops a probabilistic ramp forecasting method based on a large number of simulated scenarios. An ensemble machine learning technique is first adopted to forecast the basic wind power forecasting scenario and calculate the historical forecasting errors. A continuous Gaussian mixture model (GMM) is used to fit the probability distribution function (PDF) of forecasting errors. The cumulative distribution function (CDF) ismore » analytically deduced. The inverse transform method based on Monte Carlo sampling and the CDF is used to generate a massive number of forecasting error scenarios. An optimized swinging door algorithm is adopted to extract all the WPRs from the complete set of wind power forecasting scenarios. The probabilistic forecasting results of ramp duration and start time are generated based on all scenarios. Numerical simulations on publicly available wind power data show that within a predefined tolerance level, the developed probabilistic wind power ramp forecasting method is able to predict WPRs with a high level of sharpness and accuracy.« less

B-cell Ligand Processing Pathways Detected by Large-scale Comparative Analysis

PubMed Central

Towfic, Fadi; Gupta, Shakti; Honavar, Vasant; Subramaniam, Shankar

2012-01-01

The initiation of B-cell ligand recognition is a critical step for the generation of an immune response against foreign bodies. We sought to identify the biochemical pathways involved in the B-cell ligand recognition cascade and sets of ligands that trigger similar immunological responses. We utilized several comparative approaches to analyze the gene coexpression networks generated from a set of microarray experiments spanning 33 different ligands. First, we compared the degree distributions of the generated networks. Second, we utilized a pairwise network alignment algorithm, BiNA, to align the networks based on the hubs in the networks. Third, we aligned the networks based on a set of KEGG pathways. We summarized our results by constructing a consensus hierarchy of pathways that are involved in B cell ligand recognition. The resulting pathways were further validated through literature for their common physiological responses. Collectively, the results based on our comparative analyses of degree distributions, alignment of hubs, and alignment based on KEGG pathways provide a basis for molecular characterization of the immune response states of B-cells and demonstrate the power of comparative approaches (e.g., gene coexpression network alignment algorithms) in elucidating biochemical pathways involved in complex signaling events in cells. PMID:22917187

Plasmonic modes in nanowire dimers: A study based on the hydrodynamic Drude model including nonlocal and nonlinear effects

NASA Astrophysics Data System (ADS)

Moeferdt, Matthias; Kiel, Thomas; Sproll, Tobias; Intravaia, Francesco; Busch, Kurt

2018-02-01

A combined analytical and numerical study of the modes in two distinct plasmonic nanowire systems is presented. The computations are based on a discontinuous Galerkin time-domain approach, and a fully nonlinear and nonlocal hydrodynamic Drude model for the metal is utilized. In the linear regime, these computations demonstrate the strong influence of nonlocality on the field distributions as well as on the scattering and absorption spectra. Based on these results, second-harmonic-generation efficiencies are computed over a frequency range that covers all relevant modes of the linear spectra. In order to interpret the physical mechanisms that lead to corresponding field distributions, the associated linear quasielectrostatic problem is solved analytically via conformal transformation techniques. This provides an intuitive classification of the linear excitations of the systems that is then applied to the full Maxwell case. Based on this classification, group theory facilitates the determination of the selection rules for the efficient excitation of modes in both the linear and nonlinear regimes. This leads to significantly enhanced second-harmonic generation via judiciously exploiting the system symmetries. These results regarding the mode structure and second-harmonic generation are of direct relevance to other nanoantenna systems.

Statistical Evaluation of Voltage Variation of Power Distribution System with Clustered Home-Cogeneration Systems

NASA Astrophysics Data System (ADS)

Kato, Takeyoshi; Minagata, Atsushi; Suzuoki, Yasuo

This paper discusses the influence of mass installation of a home co-generation system (H-CGS) using a polymer electrolyte fuel cell (PEFC) on the voltage profile of power distribution system in residential area. The influence of H-CGS is compared with that of photovoltaic power generation systems (PV systems). The operation pattern of H-CGS is assumed based on the electricity and hot-water demand observed in 10 households for a year. The main results are as follows. With the clustered H-CGS, the voltage of each bus is higher by about 1-3% compared with the conventional system without any distributed generators. Because H-CGS tends to increase the output during the early evening, H-CGS contributes to recover the voltage drop during the early evening, resulting in smaller voltage variation of distribution system throughout a day. Because of small rated power output about 1kW, the influence on voltage profile by the clustered H-CGS is smaller than that by the clustered PV systems. The highest voltage during the day time is not so high as compared with the distribution system with the clustered PV systems, even if the reverse power flow from H-CGS is allowed.

Maintaining Balance: The Increasing Role of Energy Storage for Renewable Integration

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

Stenclik, Derek; Denholm, Paul; Chalamala, Babu

For nearly a century, global power systems have focused on three key functions: generating, transmitting, and distributing electricity as a real-time commodity. Physics requires that electricity generation always be in real-time balance with load-despite variability in load on time scales ranging from subsecond disturbances to multiyear trends. With the increasing role of variable generation from wind and solar, the retirement of fossil-fuel-based generation, and a changing consumer demand profile, grid operators are using new methods to maintain this balance.

Growth, chamber building rate and reproduction time of Palaeonummulites venosus (Foraminifera) under natural conditions

NASA Astrophysics Data System (ADS)

Kinoshita, Shunichi; Eder, Wolfgang; Wöger, Julia; Hohenegger, Johann; Briguglio, Antonino

2017-12-01

We investigated the symbiont-bearing benthic foraminifer Palaeonummulites venosus to determine the chamber building rate (CBR), test diameter increase rate (DIR), reproduction time and longevity using the `natural laboratory' approach. This is based on the decomposition of monthly obtained frequency distributions of chamber number and test diameter into normally distributed components. Test measurements were taken using MicroCT. The shift of the mean and standard deviation of component parameters during the 15-month investigation period was used to calculate Michaelis-Menten functions applied to estimate the averaged CBR and DIR under natural conditions. The individual dates of birth were estimated using the inverse averaged CBR and the inverse DIR fitted by the individual chamber number or the individual test diameter at the sampling date. Distributions of frequencies and densities (i.e., frequency divided by sediment weight) based on both CBR and DIR revealed continuous reproduction throughout the year with two peaks, a stronger one in June determined as the onset of the summer generation (generation 1) and a weaker one in November determined as the onset of the winter generation (generation 2). This reproduction scheme explains the presence of small and large specimens in the same sample. Longevity, calculated as the maximum difference in days between the individual's birth date and the sampling date, is approximately 1.5 yr, an estimation obtained by using both CBR and DIR.

Towards an improved ensemble precipitation forecast: A probabilistic post-processing approach

NASA Astrophysics Data System (ADS)

Khajehei, Sepideh; Moradkhani, Hamid

2017-03-01

Recently, ensemble post-processing (EPP) has become a commonly used approach for reducing the uncertainty in forcing data and hence hydrologic simulation. The procedure was introduced to build ensemble precipitation forecasts based on the statistical relationship between observations and forecasts. More specifically, the approach relies on a transfer function that is developed based on a bivariate joint distribution between the observations and the simulations in the historical period. The transfer function is used to post-process the forecast. In this study, we propose a Bayesian EPP approach based on copula functions (COP-EPP) to improve the reliability of the precipitation ensemble forecast. Evaluation of the copula-based method is carried out by comparing the performance of the generated ensemble precipitation with the outputs from an existing procedure, i.e. mixed type meta-Gaussian distribution. Monthly precipitation from Climate Forecast System Reanalysis (CFS) and gridded observation from Parameter-Elevation Relationships on Independent Slopes Model (PRISM) have been employed to generate the post-processed ensemble precipitation. Deterministic and probabilistic verification frameworks are utilized in order to evaluate the outputs from the proposed technique. Distribution of seasonal precipitation for the generated ensemble from the copula-based technique is compared to the observation and raw forecasts for three sub-basins located in the Western United States. Results show that both techniques are successful in producing reliable and unbiased ensemble forecast, however, the COP-EPP demonstrates considerable improvement in the ensemble forecast in both deterministic and probabilistic verification, in particular in characterizing the extreme events in wet seasons.

Testing Pairwise Association between Spatially Autocorrelated Variables: A New Approach Using Surrogate Lattice Data

PubMed Central

Deblauwe, Vincent; Kennel, Pol; Couteron, Pierre

2012-01-01

Background Independence between observations is a standard prerequisite of traditional statistical tests of association. This condition is, however, violated when autocorrelation is present within the data. In the case of variables that are regularly sampled in space (i.e. lattice data or images), such as those provided by remote-sensing or geographical databases, this problem is particularly acute. Because analytic derivation of the null probability distribution of the test statistic (e.g. Pearson's r) is not always possible when autocorrelation is present, we propose instead the use of a Monte Carlo simulation with surrogate data. Methodology/Principal Findings The null hypothesis that two observed mapped variables are the result of independent pattern generating processes is tested here by generating sets of random image data while preserving the autocorrelation function of the original images. Surrogates are generated by matching the dual-tree complex wavelet spectra (and hence the autocorrelation functions) of white noise images with the spectra of the original images. The generated images can then be used to build the probability distribution function of any statistic of association under the null hypothesis. We demonstrate the validity of a statistical test of association based on these surrogates with both actual and synthetic data and compare it with a corrected parametric test and three existing methods that generate surrogates (randomization, random rotations and shifts, and iterative amplitude adjusted Fourier transform). Type I error control was excellent, even with strong and long-range autocorrelation, which is not the case for alternative methods. Conclusions/Significance The wavelet-based surrogates are particularly appropriate in cases where autocorrelation appears at all scales or is direction-dependent (anisotropy). We explore the potential of the method for association tests involving a lattice of binary data and discuss its potential for validation of species distribution models. An implementation of the method in Java for the generation of wavelet-based surrogates is available online as supporting material. PMID:23144961

Spatially distributed multipartite entanglement enables EPR steering of atomic clouds

NASA Astrophysics Data System (ADS)

Kunkel, Philipp; Prüfer, Maximilian; Strobel, Helmut; Linnemann, Daniel; Frölian, Anika; Gasenzer, Thomas; Gärttner, Martin; Oberthaler, Markus K.

2018-04-01

A key resource for distributed quantum-enhanced protocols is entanglement between spatially separated modes. However, the robust generation and detection of entanglement between spatially separated regions of an ultracold atomic system remain a challenge. We used spin mixing in a tightly confined Bose-Einstein condensate to generate an entangled state of indistinguishable particles in a single spatial mode. We show experimentally that this entanglement can be spatially distributed by self-similar expansion of the atomic cloud. We used spatially resolved spin read-out to reveal a particularly strong form of quantum correlations known as Einstein-Podolsky-Rosen (EPR) steering between distinct parts of the expanded cloud. Based on the strength of EPR steering, we constructed a witness, which confirmed genuine 5-partite entanglement.

Distribution-Connected PV's Response to Voltage Sags at Transmission-Scale

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

Mather, Barry; Ding, Fei

The ever increasing amount of residential- and commercial-scale distribution-connected PV generation being installed and operated on the U.S.'s electric power system necessitates the use of increased fidelity representative distribution system models for transmission stability studies in order to ensure the continued safe and reliable operation of the grid. This paper describes a distribution model-based analysis that determines the amount of distribution-connected PV that trips off-line for a given voltage sag seen at the distribution circuit's substation. Such sags are what could potentially be experienced over a wide area of an interconnection during a transmission-level line fault. The results of thismore » analysis show that the voltage diversity of the distribution system does cause different amounts of PV generation to be lost for differing severity of voltage sags. The variation of the response is most directly a function of the loading of the distribution system. At low load levels the inversion of the circuit's voltage profile results in considerable differences in the aggregated response of distribution-connected PV Less variation is seen in the response to specific PV deployment scenarios, unless pushed to extremes, and in the total amount of PV penetration attained. A simplified version of the combined CMPLDW and PVD1 models is compared to the results from the model-based analysis. Furthermore, the parameters of the simplified model are tuned to better match the determined response. The resulting tuning parameters do not match the expected physical model of the distribution system and PV systems and thus may indicate that another modeling approach would be warranted.« less

A Knowledge Generation Model via the Hypernetwork

PubMed Central

Liu, Jian-Guo; Yang, Guang-Yong; Hu, Zhao-Long

2014-01-01

The influence of the statistical properties of the network on the knowledge diffusion has been extensively studied. However, the structure evolution and the knowledge generation processes are always integrated simultaneously. By introducing the Cobb-Douglas production function and treating the knowledge growth as a cooperative production of knowledge, in this paper, we present two knowledge-generation dynamic evolving models based on different evolving mechanisms. The first model, named “HDPH model,” adopts the hyperedge growth and the hyperdegree preferential attachment mechanisms. The second model, named “KSPH model,” adopts the hyperedge growth and the knowledge stock preferential attachment mechanisms. We investigate the effect of the parameters on the total knowledge stock of the two models. The hyperdegree distribution of the HDPH model can be theoretically analyzed by the mean-field theory. The analytic result indicates that the hyperdegree distribution of the HDPH model obeys the power-law distribution and the exponent is . Furthermore, we present the distributions of the knowledge stock for different parameters . The findings indicate that our proposed models could be helpful for deeply understanding the scientific research cooperation. PMID:24626143

A knowledge generation model via the hypernetwork.

PubMed

Liu, Jian-Guo; Yang, Guang-Yong; Hu, Zhao-Long

2014-01-01

The influence of the statistical properties of the network on the knowledge diffusion has been extensively studied. However, the structure evolution and the knowledge generation processes are always integrated simultaneously. By introducing the Cobb-Douglas production function and treating the knowledge growth as a cooperative production of knowledge, in this paper, we present two knowledge-generation dynamic evolving models based on different evolving mechanisms. The first model, named "HDPH model," adopts the hyperedge growth and the hyperdegree preferential attachment mechanisms. The second model, named "KSPH model," adopts the hyperedge growth and the knowledge stock preferential attachment mechanisms. We investigate the effect of the parameters (α,β) on the total knowledge stock of the two models. The hyperdegree distribution of the HDPH model can be theoretically analyzed by the mean-field theory. The analytic result indicates that the hyperdegree distribution of the HDPH model obeys the power-law distribution and the exponent is γ = 2 + 1/m. Furthermore, we present the distributions of the knowledge stock for different parameters (α,β). The findings indicate that our proposed models could be helpful for deeply understanding the scientific research cooperation.

An artificially generated atmosphere near a lunar base

NASA Technical Reports Server (NTRS)

Burns, Jack O.; Fernini, Ilias; Sulkanen, Martin; Duric, Nebojsa; Taylor, G. Jeffrey; Johnson, Stewart W.

1992-01-01

We discuss the formation of an artificial atmosphere generated by vigorous lunar base activity in this paper. We developed an analytical, steady-state model for a lunar atmosphere based upon previous investigations of the Moon's atmosphere from Apollo. Constant gas-injection rates, ballistic trajectories, and a Maxwellian particle distribution for an oxygen-like gas are assumed. Even for the extreme case of continuous He-3 mining of the lunar regolith, we find that the lunar atmosphere would not significantly degrade astronomical observations beyond about 10 km from the mining operation.

Development of uncertainty-based work injury model using Bayesian structural equation modelling.

PubMed

Chatterjee, Snehamoy

2014-01-01

This paper proposed a Bayesian method-based structural equation model (SEM) of miners' work injury for an underground coal mine in India. The environmental and behavioural variables for work injury were identified and causal relationships were developed. For Bayesian modelling, prior distributions of SEM parameters are necessary to develop the model. In this paper, two approaches were adopted to obtain prior distribution for factor loading parameters and structural parameters of SEM. In the first approach, the prior distributions were considered as a fixed distribution function with specific parameter values, whereas, in the second approach, prior distributions of the parameters were generated from experts' opinions. The posterior distributions of these parameters were obtained by applying Bayesian rule. The Markov Chain Monte Carlo sampling in the form Gibbs sampling was applied for sampling from the posterior distribution. The results revealed that all coefficients of structural and measurement model parameters are statistically significant in experts' opinion-based priors, whereas, two coefficients are not statistically significant when fixed prior-based distributions are applied. The error statistics reveals that Bayesian structural model provides reasonably good fit of work injury with high coefficient of determination (0.91) and less mean squared error as compared to traditional SEM.

Next Generation Multimedia Distributed Data Base Systems

NASA Technical Reports Server (NTRS)

Pendleton, Stuart E.

1997-01-01

The paradigm of client/server computing is changing. The model of a server running a monolithic application and supporting clients at the desktop is giving way to a different model that blurs the line between client and server. We are on the verge of plunging into the next generation of computing technology--distributed object-oriented computing. This is not only a change in requirements but a change in opportunities, and requires a new way of thinking for Information System (IS) developers. The information system demands caused by global competition are requiring even more access to decision making tools. Simply, object-oriented technology has been developed to supersede the current design process of information systems which is not capable of handling next generation multimedia.

Generating moment matching scenarios using optimization techniques

DOE PAGES

Mehrotra, Sanjay; Papp, Dávid

2013-05-16

An optimization based method is proposed to generate moment matching scenarios for numerical integration and its use in stochastic programming. The main advantage of the method is its flexibility: it can generate scenarios matching any prescribed set of moments of the underlying distribution rather than matching all moments up to a certain order, and the distribution can be defined over an arbitrary set. This allows for a reduction in the number of scenarios and allows the scenarios to be better tailored to the problem at hand. The method is based on a semi-infinite linear programming formulation of the problem thatmore » is shown to be solvable with polynomial iteration complexity. A practical column generation method is implemented. The column generation subproblems are polynomial optimization problems; however, they need not be solved to optimality. It is found that the columns in the column generation approach can be efficiently generated by random sampling. The number of scenarios generated matches a lower bound of Tchakaloff's. The rate of convergence of the approximation error is established for continuous integrands, and an improved bound is given for smooth integrands. Extensive numerical experiments are presented in which variants of the proposed method are compared to Monte Carlo and quasi-Monte Carlo methods on both numerical integration problems and stochastic optimization problems. The benefits of being able to match any prescribed set of moments, rather than all moments up to a certain order, is also demonstrated using optimization problems with 100-dimensional random vectors. Here, empirical results show that the proposed approach outperforms Monte Carlo and quasi-Monte Carlo based approaches on the tested problems.« less

Schwarz-Christoffel Conformal Mapping based Grid Generation for Global Oceanic Circulation Models

NASA Astrophysics Data System (ADS)

Xu, Shiming

2015-04-01

We propose new grid generation algorithms for global ocean general circulation models (OGCMs). Contrary to conventional, analytical forms based dipolar or tripolar grids, the new algorithm are based on Schwarz-Christoffel (SC) conformal mapping with prescribed boundary information. While dealing with the conventional grid design problem of pole relocation, it also addresses more advanced issues of computational efficiency and the new requirements on OGCM grids arisen from the recent trend of high-resolution and multi-scale modeling. The proposed grid generation algorithm could potentially achieve the alignment of grid lines to coastlines, enhanced spatial resolution in coastal regions, and easier computational load balance. Since the generated grids are still orthogonal curvilinear, they can be readily 10 utilized in existing Bryan-Cox-Semtner type ocean models. The proposed methodology can also be applied to the grid generation task for regional ocean modeling when complex land-ocean distribution is present.

Quantum cryptography and applications in the optical fiber network

NASA Astrophysics Data System (ADS)

Luo, Yuhui

2005-09-01

Quantum cryptography, as part of quantum information and communications, can provide absolute security for information transmission because it is established on the fundamental laws of quantum theory, such as the principle of uncertainty, No-cloning theorem and quantum entanglement. In this thesis research, a novel scheme to implement quantum key distribution based on multiphoton entanglement with a new protocol is proposed. Its advantages are: a larger information capacity can be obtained with a longer transmission distance and the detection of multiple photons is easier than that of a single photon. The security and attacks pertaining to such a system are also studied. Next, a quantum key distribution over wavelength division multiplexed (WDM) optical fiber networks is realized. Quantum key distribution in networks is a long-standing problem for practical applications. Here we combine quantum cryptography and WDM to solve this problem because WDM technology is universally deployed in the current and next generation fiber networks. The ultimate target is to deploy quantum key distribution over commercial networks. The problems arising from the networks are also studied in this part. Then quantum key distribution in multi-access networks using wavelength routing technology is investigated in this research. For the first time, quantum cryptography for multiple individually targeted users has been successfully implemented in sharp contrast to that using the indiscriminating broadcasting structure. It overcomes the shortcoming that every user in the network can acquire the quantum key signals intended to be exchanged between only two users. Furthermore, a more efficient scheme of quantum key distribution is adopted, hence resulting in a higher key rate. Lastly, a quantum random number generator based on quantum optics has been experimentally demonstrated. This device is a key component for quantum key distribution as it can create truly random numbers, which is an essential requirement to perform quantum key distribution. This new generator is composed of a single optical fiber coupler with fiber pigtails, which can be easily used in optical fiber communications.

The non-radiating component of the field generated by a finite monochromatic scalar source distribution

NASA Astrophysics Data System (ADS)

Hoenders, Bernhard J.; Ferwerda, Hedzer A.

1998-09-01

We separate the field generated by a spherically symmetric bounded scalar monochromatic source into a radiative and non-radiative part. The non-radiative part is obtained by projecting the total field on the space spanned by the non-radiating inhomogeneous modes, i.e. the modes which satisfy the inhomogeneous wave equation. Using residue techniques, introduced by Cauchy, we obtain an explicit analytical expression for the non-radiating component. We also identify the part of the source distribution which corresponds to this non-radiating part. The analysis is based on the scalar wave equation.

The Effect on Non-Normal Distributions on the Integrated Moving Average Model of Time-Series Analysis.

ERIC Educational Resources Information Center

Doerann-George, Judith

The Integrated Moving Average (IMA) model of time series, and the analysis of intervention effects based on it, assume random shocks which are normally distributed. To determine the robustness of the analysis to violations of this assumption, empirical sampling methods were employed. Samples were generated from three populations; normal,…

Interpreting drinking water quality in the distribution system using Dempster-Shafer theory of evidence.

PubMed

Sadiq, Rehan; Rodriguez, Manuel J

2005-04-01

Interpreting water quality data routinely generated for control and monitoring purposes in water distribution systems is a complicated task for utility managers. In fact, data for diverse water quality indicators (physico-chemical and microbiological) are generated at different times and at different locations in the distribution system. To simplify and improve the understanding and the interpretation of water quality, methodologies for aggregation and fusion of data must be developed. In this paper, the Dempster-Shafer theory also called theory of evidence is introduced as a potential methodology for interpreting water quality data. The conceptual basis of this methodology and the process for its implementation are presented by two applications. The first application deals with the interpretation of spatial water quality data fusion, while the second application deals with the development of water quality index based on key monitored indicators. Based on the obtained results, the authors discuss the potential contribution of theory of evidence as a decision-making tool for water quality management.

Genetic Algorithm Based Multi-Agent System Applied to Test Generation

ERIC Educational Resources Information Center

Meng, Anbo; Ye, Luqing; Roy, Daniel; Padilla, Pierre

2007-01-01

Automatic test generating system in distributed computing context is one of the most important links in on-line evaluation system. Although the issue has been argued long since, there is not a perfect solution to it so far. This paper proposed an innovative approach to successfully addressing such issue by the seamless integration of genetic…

Experimental and numerical study of impact of voltage fluctuate, flicker and power factor wave electric generator to local distribution

NASA Astrophysics Data System (ADS)

Hadi, Nik Azran Ab; Rashid, Wan Norhisyam Abd; Hashim, Nik Mohd Zarifie; Mohamad, Najmiah Radiah; Kadmin, Ahmad Fauzan

2017-10-01

Electricity is the most powerful energy source in the world. Engineer and technologist combined and cooperated to invent a new low-cost technology and free carbon emission where the carbon emission issue is a major concern now due to global warming. Renewable energy sources such as hydro, wind and wave are becoming widespread to reduce the carbon emissions, on the other hand, this effort needs several novel methods, techniques and technologies compared to coal-based power. Power quality of renewable sources needs in depth research and endless study to improve renewable energy technologies. The aim of this project is to investigate the impact of renewable electric generator on its local distribution system. The power farm was designed to connect to the local distribution system and it will be investigated and analyzed to make sure that energy which is supplied to customer is clean. The MATLAB tools are used to simulate the overall analysis. At the end of the project, a summary of identifying various voltage fluctuates data sources is presented in terms of voltage flicker. A suggestion of the analysis impact of wave power generation on its local distribution is also presented for the development of wave generator farms.

Analytical and numerical solutions of the potential and electric field generated by different electrode arrays in a tumor tissue under electrotherapy.

PubMed

Bergues Pupo, Ana E; Reyes, Juan Bory; Bergues Cabrales, Luis E; Bergues Cabrales, Jesús M

2011-09-24

Electrotherapy is a relatively well established and efficient method of tumor treatment. In this paper we focus on analytical and numerical calculations of the potential and electric field distributions inside a tumor tissue in a two-dimensional model (2D-model) generated by means of electrode arrays with shapes of different conic sections (ellipse, parabola and hyperbola). Analytical calculations of the potential and electric field distributions based on 2D-models for different electrode arrays are performed by solving the Laplace equation, meanwhile the numerical solution is solved by means of finite element method in two dimensions. Both analytical and numerical solutions reveal significant differences between the electric field distributions generated by electrode arrays with shapes of circle and different conic sections (elliptic, parabolic and hyperbolic). Electrode arrays with circular, elliptical and hyperbolic shapes have the advantage of concentrating the electric field lines in the tumor. The mathematical approach presented in this study provides a useful tool for the design of electrode arrays with different shapes of conic sections by means of the use of the unifying principle. At the same time, we verify the good correspondence between the analytical and numerical solutions for the potential and electric field distributions generated by the electrode array with different conic sections.

Isolated Power Generation System Using Permanent Magnet Synchronous Generator with Improved Power Quality

NASA Astrophysics Data System (ADS)

Arya, Sabha Raj; Patel, Ashish; Giri, Ashutosh

2018-06-01

This paper deals wind energy based power generation system using Permanent Magnet Synchronous Generator (PMSG). It is controlled using advanced enhanced phase-lock loop for power quality features using distribution static compensator to eliminate the harmonics and to provide KVAR compensation as well as load balancing. It also manages rated potential at the point of common interface under linear and non-linear loads. In order to have better efficiency and reliable operation of PMSG driven by wind turbine, it is necessary to analyze the governing equation of wind based turbine and PMSG under fixed and variable wind speed. For handling power quality problems, power electronics based shunt connected custom power device is used in three wire system. The simulations in MATLAB/Simulink environment have been carried out in order to demonstrate this model and control approach used for the power quality enhancement. The performance results show the adequate performance of PMSG based power generation system and control algorithm.

Isolated Power Generation System Using Permanent Magnet Synchronous Generator with Improved Power Quality

NASA Astrophysics Data System (ADS)

Arya, Sabha Raj; Patel, Ashish; Giri, Ashutosh

2018-03-01

This paper deals wind energy based power generation system using Permanent Magnet Synchronous Generator (PMSG). It is controlled using advanced enhanced phase-lock loop for power quality features using distribution static compensator to eliminate the harmonics and to provide KVAR compensation as well as load balancing. It also manages rated potential at the point of common interface under linear and non-linear loads. In order to have better efficiency and reliable operation of PMSG driven by wind turbine, it is necessary to analyze the governing equation of wind based turbine and PMSG under fixed and variable wind speed. For handling power quality problems, power electronics based shunt connected custom power device is used in three wire system. The simulations in MATLAB/Simulink environment have been carried out in order to demonstrate this model and control approach used for the power quality enhancement. The performance results show the adequate performance of PMSG based power generation system and control algorithm.

Speckle contrast optical tomography: A new method for deep tissue three-dimensional tomography of blood flow

PubMed Central

Varma, Hari M.; Valdes, Claudia P.; Kristoffersen, Anna K.; Culver, Joseph P.; Durduran, Turgut

2014-01-01

A novel tomographic method based on the laser speckle contrast, speckle contrast optical tomography (SCOT) is introduced that allows us to reconstruct three dimensional distribution of blood flow in deep tissues. This method is analogous to the diffuse optical tomography (DOT) but for deep tissue blood flow. We develop a reconstruction algorithm based on first Born approximation to generate three dimensional distribution of flow using the experimental data obtained from tissue simulating phantoms. PMID:24761306

An adequacy-constrained integrated planning method for effective accommodation of DG and electric vehicles in smart distribution systems

NASA Astrophysics Data System (ADS)

Tan, Zhukui; Xie, Baiming; Zhao, Yuanliang; Dou, Jinyue; Yan, Tong; Liu, Bin; Zeng, Ming

2018-06-01

This paper presents a new integrated planning framework for effective accommodating electric vehicles in smart distribution systems (SDS). The proposed method incorporates various investment options available for the utility collectively, including distributed generation (DG), capacitors and network reinforcement. Using a back-propagation algorithm combined with cost-benefit analysis, the optimal network upgrade plan, allocation and sizing of the selected components are determined, with the purpose of minimizing the total system capital and operating costs of DG and EV accommodation. Furthermore, a new iterative reliability test method is proposed. It can check the optimization results by subsequently simulating the reliability level of the planning scheme, and modify the generation reserve margin to guarantee acceptable adequacy levels for each year of the planning horizon. Numerical results based on a 32-bus distribution system verify the effectiveness of the proposed method.

An object-based storage model for distributed remote sensing images

NASA Astrophysics Data System (ADS)

Yu, Zhanwu; Li, Zhongmin; Zheng, Sheng

2006-10-01

It is very difficult to design an integrated storage solution for distributed remote sensing images to offer high performance network storage services and secure data sharing across platforms using current network storage models such as direct attached storage, network attached storage and storage area network. Object-based storage, as new generation network storage technology emerged recently, separates the data path, the control path and the management path, which solves the bottleneck problem of metadata existed in traditional storage models, and has the characteristics of parallel data access, data sharing across platforms, intelligence of storage devices and security of data access. We use the object-based storage in the storage management of remote sensing images to construct an object-based storage model for distributed remote sensing images. In the storage model, remote sensing images are organized as remote sensing objects stored in the object-based storage devices. According to the storage model, we present the architecture of a distributed remote sensing images application system based on object-based storage, and give some test results about the write performance comparison of traditional network storage model and object-based storage model.

The planning and construction of Distributed Energy System in Qingdao Sino-German Eco-park

NASA Astrophysics Data System (ADS)

Wei, Cun; Zhang, Gaijing; Song, Peipei

2018-04-01

This paper introduce the development and characteristics of new energy, Eco-city and Distributed Energy System in China, a case study of Qingdao Sino-German Eco-park, research on practical application about planning and construction of Distributed Energy System in Eco-city. Results show that: we must first do a good job in energy planning, giving full play to their own advantages, and Distributed Energy System based renewable energy resources is a promising option for reducing emissions from electricity generation in Eco-city.

Asymmetric competition causes multimodal size distributions in spatially structured populations

PubMed Central

Velázquez, Jorge; Allen, Robert B.; Coomes, David A.; Eichhorn, Markus P.

2016-01-01

Plant sizes within populations often exhibit multimodal distributions, even when all individuals are the same age and have experienced identical conditions. To establish the causes of this, we created an individual-based model simulating the growth of trees in a spatially explicit framework, which was parametrized using data from a long-term study of forest stands in New Zealand. First, we demonstrate that asymmetric resource competition is a necessary condition for the formation of multimodal size distributions within cohorts. By contrast, the legacy of small-scale clustering during recruitment is transient and quickly overwhelmed by density-dependent mortality. Complex multi-layered size distributions are generated when established individuals are restricted in the spatial domain within which they can capture resources. The number of modes reveals the effective number of direct competitors, while the separation and spread of modes are influenced by distances among established individuals. Asymmetric competition within local neighbourhoods can therefore generate a range of complex size distributions within even-aged cohorts. PMID:26817778

Graphene Distributed Amplifiers: Generating Desirable Gain for Graphene Field-Effect Transistors

PubMed Central

Lyu, Hongming; Lu, Qi; Huang, Yilin; Ma, Teng; Zhang, Jinyu; Wu, Xiaoming; Yu, Zhiping; Ren, Wencai; Cheng, Hui-Ming; Wu, Huaqiang; Qian, He

2015-01-01

Ever since its discovery, graphene bears great expectations in high frequency electronics due to its irreplaceably high carrier mobility. However, it has long been blamed for the weakness in generating gains, which seriously limits its pace of development. Distributed amplification, on the other hand, has successfully been used in conventional semiconductors to increase the amplifiers’ gain-bandwidth product. In this paper, distributed amplification is first applied to graphene. Transmission lines phase-synchronize paralleled graphene field-effect transistors (GFETs), combining the gain of each stage in an additive manner. Simulations were based on fabricated GFETs whose fT ranged from 8.5 GHz to 10.5 GHz and fmax from 12 GHz to 14 GHz. A simulated four-stage graphene distributed amplifier achieved up to 4 dB gain and 3.5 GHz bandwidth, which could be realized with future IC processes. A PCB level graphene distributed amplifier was fabricated as a proof of circuit concept. PMID:26634442

Two-sided Topp-Leone Weibull distribution

NASA Astrophysics Data System (ADS)

Podeang, Krittaya; Bodhisuwan, Winai

2017-11-01

In this paper, we introduce a general class of lifetime distributions, called the two-sided Topp-Leone generated family of distribution. A special case of new family is the two-sided Topp-Leone Weibull distribution. This distribution used the two-sided Topp-Leone distribution as a generator for the Weibull distribution. The two-sided Topp-Leone Weibull distribution is presented in several shapes of distributions such as decreasing, unimodal, and bimodal which make this distribution more than flexible than the Weibull distribution. Its quantile function is presented. The parameter estimation method by using maximum likelihood estimation is discussed. The proposed distribution is applied to the strength data set, remission times of bladder cancer patients data set and time to failure of turbocharger data set. We compare the proposed distribution to the Topp-Leone Generated Weibull distribution. In conclusion, the two-sided Topp-Leone Weibull distribution performs similarly as the Topp-Leone Generated Weibull distribution in the first and second data sets. However, the proposed distribution can perform better than fit to Topp-Leone Generated Weibull distribution for the other.

A descriptive model of resting-state networks using Markov chains.

PubMed

Xie, H; Pal, R; Mitra, S

2016-08-01

Resting-state functional connectivity (RSFC) studies considering pairwise linear correlations have attracted great interests while the underlying functional network structure still remains poorly understood. To further our understanding of RSFC, this paper presents an analysis of the resting-state networks (RSNs) based on the steady-state distributions and provides a novel angle to investigate the RSFC of multiple functional nodes. This paper evaluates the consistency of two networks based on the Hellinger distance between the steady-state distributions of the inferred Markov chain models. The results show that generated steady-state distributions of default mode network have higher consistency across subjects than random nodes from various RSNs.

Sparsity-based fast CGH generation using layer-based approach for 3D point cloud model

NASA Astrophysics Data System (ADS)

Kim, Hak Gu; Jeong, Hyunwook; Ro, Yong Man

2017-03-01

Computer generated hologram (CGH) is becoming increasingly important for a 3-D display in various applications including virtual reality. In the CGH, holographic fringe patterns are generated by numerically calculating them on computer simulation systems. However, a heavy computational cost is required to calculate the complex amplitude on CGH plane for all points of 3D objects. This paper proposes a new fast CGH generation based on the sparsity of CGH for 3D point cloud model. The aim of the proposed method is to significantly reduce computational complexity while maintaining the quality of the holographic fringe patterns. To that end, we present a new layer-based approach for calculating the complex amplitude distribution on the CGH plane by using sparse FFT (sFFT). We observe the CGH of a layer of 3D objects is sparse so that dominant CGH is rapidly generated from a small set of signals by sFFT. Experimental results have shown that the proposed method is one order of magnitude faster than recently reported fast CGH generation.

Distributed Generation of Electricity and its Environmental Impacts

EPA Pesticide Factsheets

Distributed generation refers to technologies that generate electricity at or near where it will be used. Learn about how distributed energy generation can support the delivery of clean, reliable power to additional customers.

Waste prevention in liquid detergent distribution: a comparison based on life cycle assessment.

PubMed

Nessi, Simone; Rigamonti, Lucia; Grosso, Mario

2014-11-15

The distribution of liquid detergents through self-dispensing systems has been adopted in some Italian retail stores over the last few years. By enabling the consumer to refill several times the same container, it is proposed as a less waste-generating and more environmentally friendly alternative to the traditional distribution with single-use plastic containers. For this reason, its implementation is encouraged by the national waste prevention programme recently adopted in Italy. In order to assess such claims, a life cycle assessment was carried out to evaluate whether detergent distribution through self-dispensing systems actually allows to achieve the expected reduction in waste generation and environmental impacts. The focus was on the distribution within the large-scale retail trade and on the categories of laundry detergents, fabric softeners and hand dishwashing detergents. For each of them, a set of baseline single-use scenarios were compared with two alternative waste prevention scenarios, where the detergent is distributed through self-dispensing systems. Beyond waste generation, also the Cumulative Energy Demand and thirteen midpoint-level potential impact indicators were calculated for the comparison. Results showed that a reduction in waste generation up to 98% can be achieved, depending on the category of detergent, on the baseline scenario of comparison and on the number of times the refillable container is used. A progressive reduction in the energy demand and in most of the potential impacts was also observed, starting from a minimum number of uses of the refillable container. Copyright © 2014 Elsevier B.V. All rights reserved.

Probabilistic Harmonic Analysis on Distributed Photovoltaic Integration Considering Typical Weather Scenarios

NASA Astrophysics Data System (ADS)

Bin, Che; Ruoying, Yu; Dongsheng, Dang; Xiangyan, Wang

2017-05-01

Distributed Generation (DG) integrating to the network would cause the harmonic pollution which would cause damages on electrical devices and affect the normal operation of power system. On the other hand, due to the randomness of the wind and solar irradiation, the output of DG is random, too, which leads to an uncertainty of the harmonic generated by the DG. Thus, probabilistic methods are needed to analyse the impacts of the DG integration. In this work we studied the harmonic voltage probabilistic distribution and the harmonic distortion in distributed network after the distributed photovoltaic (DPV) system integrating in different weather conditions, mainly the sunny day, cloudy day, rainy day and the snowy day. The probabilistic distribution function of the DPV output power in different typical weather conditions could be acquired via the parameter identification method of maximum likelihood estimation. The Monte-Carlo simulation method was adopted to calculate the probabilistic distribution of harmonic voltage content at different frequency orders as well as the harmonic distortion (THD) in typical weather conditions. The case study was based on the IEEE33 system and the results of harmonic voltage content probabilistic distribution as well as THD in typical weather conditions were compared.

Mechanism of the free charge carrier generation in the dielectric breakdown

NASA Astrophysics Data System (ADS)

Rahim, N. A. A.; Ranom, R.; Zainuddin, H.

2017-12-01

Many studies have been conducted to investigate the effect of environmental, mechanical and electrical stresses on insulator. However, studies on physical process of discharge phenomenon, leading to the breakdown of the insulator surface are lacking and difficult to comprehend. Therefore, this paper analysed charge carrier generation mechanism that can cause free charge carrier generation, leading toward surface discharge development. Besides, this paper developed a model of surface discharge based on the charge generation mechanism on the outdoor insulator. Nernst’s Planck theory was used in order to model the behaviour of the charge carriers while Poisson’s equation was used to determine the distribution of electric field on insulator surface. In the modelling of surface discharge on the outdoor insulator, electric field dependent molecular ionization was used as the charge generation mechanism. A mathematical model of the surface discharge was solved using method of line technique (MOL). The result from the mathematical model showed that the behaviour of net space charge density was correlated with the electric field distribution.

A dynamic re-partitioning strategy based on the distribution of key in Spark

NASA Astrophysics Data System (ADS)

Zhang, Tianyu; Lian, Xin

2018-05-01

Spark is a memory-based distributed data processing framework, has the ability of processing massive data and becomes a focus in Big Data. But the performance of Spark Shuffle depends on the distribution of data. The naive Hash partition function of Spark can not guarantee load balancing when data is skewed. The time of job is affected by the node which has more data to process. In order to handle this problem, dynamic sampling is used. In the process of task execution, histogram is used to count the key frequency distribution of each node, and then generate the global key frequency distribution. After analyzing the distribution of key, load balance of data partition is achieved. Results show that the Dynamic Re-Partitioning function is better than the default Hash partition, Fine Partition and the Balanced-Schedule strategy, it can reduce the execution time of the task and improve the efficiency of the whole cluster.

Method and apparatus for anti-islanding protection of distributed generations

DOEpatents

Ye, Zhihong; John, Vinod; Wang, Changyong; Garces, Luis Jose; Zhou, Rui; Li, Lei; Walling, Reigh Allen; Premerlani, William James; Sanza, Peter Claudius; Liu, Yan; Dame, Mark Edward

2006-03-21

An apparatus for anti-islanding protection of a distributed generation with respect to a feeder connected to an electrical grid is disclosed. The apparatus includes a sensor adapted to generate a voltage signal representative of an output voltage and/or a current signal representative of an output current at the distributed generation, and a controller responsive to the signals from the sensor. The controller is productive of a control signal directed to the distributed generation to drive an operating characteristic of the distributed generation out of a nominal range in response to the electrical grid being disconnected from the feeder.

Distribution of continuous variable quantum entanglement at a telecommunication wavelength over 20  km of optical fiber.

PubMed

Feng, Jinxia; Wan, Zhenju; Li, Yuanji; Zhang, Kuanshou

2017-09-01

The distribution of continuous variable (CV) Einstein-Podolsky-Rosen (EPR)-entangled beams at a telecommunication wavelength of 1550 nm over single-mode fibers is investigated. EPR-entangled beams with quantum entanglement of 8.3 dB are generated using a single nondegenerate optical parametric amplifier based on a type-II periodically poled KTiOPO 4 crystal. When one beam of the generated EPR-entangled beams is distributed over 20 km of single-mode fiber, 1.02 dB quantum entanglement can still be measured. The degradation of CV quantum entanglement in a noisy fiber channel is theoretically analyzed considering the effect of depolarized guided acoustic wave Brillouin scattering in optical fibers. The theoretical prediction is in good agreement with the experimental results.

Wind Curtailment and the Value of Transmission under a 2050 Wind Vision

Science.gov Websites

dispatches each generating unit in the geographical footprint in the least- cost method based on many inputs just as the Wind Vision study did, in a somewhat different geographical distribution due to data distributed fairly well throughout the western U.S. The map shows kind of a different story. The map shows

Predicting the potential distribution of the amphibian pathogen Batrachochytrium dendrobatidis in East and Southeast Asia.

PubMed

Moriguchi, Sachiko; Tominaga, Atsushi; Irwin, Kelly J; Freake, Michael J; Suzuki, Kazutaka; Goka, Koichi

2015-04-08

Batrachochytrium dendrobatidis (Bd) is the pathogen responsible for chytridiomycosis, a disease that is associated with a worldwide amphibian population decline. In this study, we predicted the potential distribution of Bd in East and Southeast Asia based on limited occurrence data. Our goal was to design an effective survey area where efforts to detect the pathogen can be focused. We generated ecological niche models using the maximum-entropy approach, with alleviation of multicollinearity and spatial autocorrelation. We applied eigenvector-based spatial filters as independent variables, in addition to environmental variables, to resolve spatial autocorrelation, and compared the model's accuracy and the degree of spatial autocorrelation with those of a model estimated using only environmental variables. We were able to identify areas of high suitability for Bd with accuracy. Among the environmental variables, factors related to temperature and precipitation were more effective in predicting the potential distribution of Bd than factors related to land use and cover type. Our study successfully predicted the potential distribution of Bd in East and Southeast Asia. This information should now be used to prioritize survey areas and generate a surveillance program to detect the pathogen.

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

Kuruganti, Phani Teja

The smart grid is a combined process of revitalizing the traditional power grid applications and introducing new applications to improve the efficiency of power generation, transmission and distribution. This can be achieved by leveraging advanced communication and networking technologies. Therefore the selection of the appropriate communication technology for different smart grid applications has been debated a lot in the recent past. After comparing different possible technologies, a recent research study has arrived at a conclusion that the 3G cellular technology is the right choice for distribution side smart grid applications like smart metering, advanced distribution automation and demand response managementmore » system. In this paper, we argue that the current 3G/4G cellular technologies are not an appropriate choice for smart grid distribution applications and propose a Hybrid Spread Spectrum (HSS) based Advanced Metering Infrastructure (AMI) as one of the alternatives to 3G/4G technologies. We present a preliminary PHY and MAC layer design of a HSS based AMI network and evaluate their performance using matlab and NS2 simulations. Also, we propose a time hierarchical scheme that can significantly reduce the volume of random access traffic generated during blackouts and the delay in power outage reporting.« less

Maintaining Balance: The Increasing Role of Energy Storage for Renewable Integration

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

Stenclik, Derek; Denholm, Paul; Chalamala, Babu

For nearly a century, global power systems have focused on three key functions: to generate, transmit, and distribute electricity as a real-time commodity. Physics requires that electricity generation always be in real-time balance with load, despite variability in load on timescales ranging from sub-second disturbances to multi-year trends. With the increasing role of variable generation from wind and solar, retirements of fossil fuel-based generation, and a changing consumer demand profile, grid operators are using new methods to maintain this balance.

Maintaining Balance: The Increasing Role of Energy Storage for Renewable Integration

DOE PAGES

Stenclik, Derek; Denholm, Paul; Chalamala, Babu

2017-10-17

For nearly a century, global power systems have focused on three key functions: to generate, transmit, and distribute electricity as a real-time commodity. Physics requires that electricity generation always be in real-time balance with load, despite variability in load on timescales ranging from sub-second disturbances to multi-year trends. With the increasing role of variable generation from wind and solar, retirements of fossil fuel-based generation, and a changing consumer demand profile, grid operators are using new methods to maintain this balance.

A Review of Microgrid Architectures and Control Strategy

NASA Astrophysics Data System (ADS)

Jadav, Krishnarajsinh A.; Karkar, Hitesh M.; Trivedi, I. N.

2017-12-01

In this paper microgrid architecture and various converters control strategies are reviewed. Microgrid is defined as interconnected network of distributed energy resources, loads and energy storage systems. This emerging concept realizes the potential of distributed generators. AC microgrid interconnects various AC distributed generators like wind turbine and DC distributed generators like PV, fuel cell using inverter. While in DC microgrid output of an AC distributed generator must be converted to DC using rectifiers and DC distributed generator can be directly interconnected. Hybrid microgrid is the solution to avoid this multiple reverse conversions AC-DC-AC and DC-AC-DC that occur in the individual AC-DC microgrid. In hybrid microgrid all AC distributed generators will be connected in AC microgrid and DC distributed generators will be connected in DC microgrid. Interlinking converter is used for power balance in both microgrids, which transfer power from one microgrid to other if any microgrid is overloaded. At the end, review of interlinking converter control strategies is presented.

Validation of two (parametric vs non-parametric) daily weather generators

NASA Astrophysics Data System (ADS)

Dubrovsky, M.; Skalak, P.

2015-12-01

As the climate models (GCMs and RCMs) fail to satisfactorily reproduce the real-world surface weather regime, various statistical methods are applied to downscale GCM/RCM outputs into site-specific weather series. The stochastic weather generators are among the most favourite downscaling methods capable to produce realistic (observed-like) meteorological inputs for agrological, hydrological and other impact models used in assessing sensitivity of various ecosystems to climate change/variability. To name their advantages, the generators may (i) produce arbitrarily long multi-variate synthetic weather series representing both present and changed climates (in the latter case, the generators are commonly modified by GCM/RCM-based climate change scenarios), (ii) be run in various time steps and for multiple weather variables (the generators reproduce the correlations among variables), (iii) be interpolated (and run also for sites where no weather data are available to calibrate the generator). This contribution will compare two stochastic daily weather generators in terms of their ability to reproduce various features of the daily weather series. M&Rfi is a parametric generator: Markov chain model is used to model precipitation occurrence, precipitation amount is modelled by the Gamma distribution, and the 1st order autoregressive model is used to generate non-precipitation surface weather variables. The non-parametric GoMeZ generator is based on the nearest neighbours resampling technique making no assumption on the distribution of the variables being generated. Various settings of both weather generators will be assumed in the present validation tests. The generators will be validated in terms of (a) extreme temperature and precipitation characteristics (annual and 30-years extremes and maxima of duration of hot/cold/dry/wet spells); (b) selected validation statistics developed within the frame of VALUE project. The tests will be based on observational weather series from several European stations available from the ECA&D database. Acknowledgements: The weather generator is developed and validated within the frame of projects WG4VALUE (sponsored by the Ministry of Education, Youth and Sports of CR), and VALUE (COST ES 1102 action).

Investigation of the Quasi-Brittle Failure of Alashan Granite Viewed from Laboratory Experiments and Grain-Based Discrete Element Modeling.

PubMed

Zhou, Jian; Zhang, Luqing; Yang, Duoxing; Braun, Anika; Han, Zhenhua

2017-07-21

Granite is a typical crystalline material, often used as a building material, but also a candidate host rock for the repository of high-level radioactive waste. The petrographic texture-including mineral constituents, grain shape, size, and distribution-controls the fracture initiation, propagation, and coalescence within granitic rocks. In this paper, experimental laboratory tests and numerical simulations of a grain-based approach in two-dimensional Particle Flow Code (PFC2D) were conducted on the mechanical strength and failure behavior of Alashan granite, in which the grain-like structure of granitic rock was considered. The microparameters for simulating Alashan granite were calibrated based on real laboratory strength values and strain-stress curves. The unconfined uniaxial compressive test and Brazilian indirect tensile test were performed using a grain-based approach to examine and discuss the influence of mineral grain size and distribution on the strength and patterns of microcracks in granitic rocks. The results show it is possible to reproduce the uniaxial compressive strength (UCS) and uniaxial tensile strength (UTS) of Alashan granite using the grain-based approach in PFC2D, and the average mineral size has a positive relationship with the UCS and UTS. During the modeling, most of the generated microcracks were tensile cracks. Moreover, the ratio of the different types of generated microcracks is related to the average grain size. When the average grain size in numerical models is increased, the ratio of the number of intragrain tensile cracks to the number of intergrain tensile cracks increases, and the UCS of rock samples also increases with this ratio. However, the variation in grain size distribution does not have a significant influence on the likelihood of generated microcracks.

An Agent-Based Interface to Terrestrial Ecological Forecasting

NASA Technical Reports Server (NTRS)

Golden, Keith; Nemani, Ramakrishna; Pang, Wan-Lin; Votava, Petr; Etzioni, Oren

2004-01-01

This paper describes a flexible agent-based ecological forecasting system that combines multiple distributed data sources and models to provide near-real-time answers to questions about the state of the Earth system We build on novel techniques in automated constraint-based planning and natural language interfaces to automatically generate data products based on descriptions of the desired data products.

An Improved Algorithm to Generate a Wi-Fi Fingerprint Database for Indoor Positioning

PubMed Central

Chen, Lina; Li, Binghao; Zhao, Kai; Rizos, Chris; Zheng, Zhengqi

2013-01-01

The major problem of Wi-Fi fingerprint-based positioning technology is the signal strength fingerprint database creation and maintenance. The significant temporal variation of received signal strength (RSS) is the main factor responsible for the positioning error. A probabilistic approach can be used, but the RSS distribution is required. The Gaussian distribution or an empirically-derived distribution (histogram) is typically used. However, these distributions are either not always correct or require a large amount of data for each reference point. Double peaks of the RSS distribution have been observed in experiments at some reference points. In this paper a new algorithm based on an improved double-peak Gaussian distribution is proposed. Kurtosis testing is used to decide if this new distribution, or the normal Gaussian distribution, should be applied. Test results show that the proposed algorithm can significantly improve the positioning accuracy, as well as reduce the workload of the off-line data training phase. PMID:23966197

An improved algorithm to generate a Wi-Fi fingerprint database for indoor positioning.

PubMed

Chen, Lina; Li, Binghao; Zhao, Kai; Rizos, Chris; Zheng, Zhengqi

2013-08-21

The major problem of Wi-Fi fingerprint-based positioning technology is the signal strength fingerprint database creation and maintenance. The significant temporal variation of received signal strength (RSS) is the main factor responsible for the positioning error. A probabilistic approach can be used, but the RSS distribution is required. The Gaussian distribution or an empirically-derived distribution (histogram) is typically used. However, these distributions are either not always correct or require a large amount of data for each reference point. Double peaks of the RSS distribution have been observed in experiments at some reference points. In this paper a new algorithm based on an improved double-peak Gaussian distribution is proposed. Kurtosis testing is used to decide if this new distribution, or the normal Gaussian distribution, should be applied. Test results show that the proposed algorithm can significantly improve the positioning accuracy, as well as reduce the workload of the off-line data training phase.

High resolution, high sensitivity, dynamic distributed structural monitoring using optical frequency domain reflectometry

NASA Astrophysics Data System (ADS)

Kreger, Stephen T.; Sang, Alex K.; Garg, Naman; Michel, Julia

2013-05-01

Fiber-optic ultrasonic transducers are an important component of an active ultrasonic testing system for structural health monitoring. Fiber-optic transducers have several advantages such as small size, light weight, and immunity to electromagnetic interference that make them much more attractive than the current available piezoelectric transducers, especially as embedded and permanent transducers in active ultrasonic testing for structural health monitoring. In this paper, a distributed fiber-optic laser-ultrasound generation based on the ghost-mode of tilted fiber Bragg gratings is studied. The influences of the laser power and laser pulse duration on the laser-ultrasound generation are investigated. The results of this paper are helpful to understand the working principle of this laser-ultrasound method and improve the ultrasonic generation efficiency.

Statistical properties of Charney-Hasegawa-Mima zonal flows

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

Anderson, Johan, E-mail: anderson.johan@gmail.com; Botha, G. J. J.

2015-05-15

A theoretical interpretation of numerically generated probability density functions (PDFs) of intermittent plasma transport events in unforced zonal flows is provided within the Charney-Hasegawa-Mima (CHM) model. The governing equation is solved numerically with various prescribed density gradients that are designed to produce different configurations of parallel and anti-parallel streams. Long-lasting vortices form whose flow is governed by the zonal streams. It is found that the numerically generated PDFs can be matched with analytical predictions of PDFs based on the instanton method by removing the autocorrelations from the time series. In many instances, the statistics generated by the CHM dynamics relaxesmore » to Gaussian distributions for both the electrostatic and vorticity perturbations, whereas in areas with strong nonlinear interactions it is found that the PDFs are exponentially distributed.« less

mrpy: Renormalized generalized gamma distribution for HMF and galaxy ensemble properties comparisons

NASA Astrophysics Data System (ADS)

Murray, Steven G.; Robotham, Aaron S. G.; Power, Chris

2018-02-01

mrpy calculates the MRP parameterization of the Halo Mass Function. It calculates basic statistics of the truncated generalized gamma distribution (TGGD) with the TGGD class, including mean, mode, variance, skewness, pdf, and cdf. It generates MRP quantities with the MRP class, such as differential number counts and cumulative number counts, and offers various methods for generating normalizations. It can generate the MRP-based halo mass function as a function of physical parameters via the mrp_b13 function, and fit MRP parameters to data in the form of arbitrary curves and in the form of a sample of variates with the SimFit class. mrpy also calculates analytic hessians and jacobians at any point, and allows the user to alternate parameterizations of the same form via the reparameterize module.

Layer 1 VPN services in distributed next-generation SONET/SDH networks with inverse multiplexing

NASA Astrophysics Data System (ADS)

Ghani, N.; Muthalaly, M. V.; Benhaddou, D.; Alanqar, W.

2006-05-01

Advances in next-generation SONET/SDH along with GMPLS control architectures have enabled many new service provisioning capabilities. In particular, a key services paradigm is the emergent Layer 1 virtual private network (L1 VPN) framework, which allows multiple clients to utilize a common physical infrastructure and provision their own 'virtualized' circuit-switched networks. This precludes expensive infrastructure builds and increases resource utilization for carriers. Along these lines, a novel L1 VPN services resource management scheme for next-generation SONET/SDH networks is proposed that fully leverages advanced virtual concatenation and inverse multiplexing features. Additionally, both centralized and distributed GMPLS-based implementations are also tabled to support the proposed L1 VPN services model. Detailed performance analysis results are presented along with avenues for future research.

Recent Trend of New Type Power Delivery System and its Demonstrative Project in Japan

NASA Astrophysics Data System (ADS)

Morozumi, Satoshi; Nara, Koichi

Recently many such distributed generating systems as co-generation, photovoltaic, wind, fuel cells etc. are introduced into power distribution system, and the power system must cope with the situation with distributed generators. Moreover, such industries as IT request reliable and high quality power to preserve their businesses, and some other electric energy based industries request less reliable but cheaper electricity. From these backgrounds, several new type power delivery systems are emerging where lots of distributed generators (DGs) can be connected and many benefits offered by DGs can be realized without affecting the existing power system. They are referred to various names. In U.S.A., Microgrid, Power Park and Virtual Utilities, etc. are proposed. In Europe, DISPOWER or Smart Grid is under developing. In Japan, FRIENDS and Demand Area Network System etc. are proposed and tested in real sites. In this paper, first, general concepts of such new type power delivery systems and new businesses expected to be created by using DGs are introduced. Then, recent research activities in this area in Japan are introduced so as to stimulate new business opportunities. In the later part of this paper, related NEDO's demonstrative projects are introduced. NEDO is the largest public R&D management organization and promoting several projects regarding grid connecting issues on the power system. Those projects were planned to solve several problems on the power system where distributed renewable energy resources are installed.

Silicon photonic transceiver circuit for high-speed polarization-based discrete variable quantum key distribution

DOE PAGES

Cai, Hong; Long, Christopher M.; DeRose, Christopher T.; ...

2017-01-01

We demonstrate a silicon photonic transceiver circuit for high-speed discrete variable quantum key distribution that employs a common structure for transmit and receive functions. The device is intended for use in polarization-based quantum cryptographic protocols, such as BB84. Our characterization indicates that the circuit can generate the four BB84 states (TE/TM/45°/135° linear polarizations) with >30 dB polarization extinction ratios and gigabit per second modulation speed, and is capable of decoding any polarization bases differing by 90° with high extinction ratios.

Silicon photonic transceiver circuit for high-speed polarization-based discrete variable quantum key distribution.

PubMed

Cai, Hong; Long, Christopher M; DeRose, Christopher T; Boynton, Nicholas; Urayama, Junji; Camacho, Ryan; Pomerene, Andrew; Starbuck, Andrew L; Trotter, Douglas C; Davids, Paul S; Lentine, Anthony L

2017-05-29

We demonstrate a silicon photonic transceiver circuit for high-speed discrete variable quantum key distribution that employs a common structure for transmit and receive functions. The device is intended for use in polarization-based quantum cryptographic protocols, such as BB84. Our characterization indicates that the circuit can generate the four BB84 states (TE/TM/45°/135° linear polarizations) with >30 dB polarization extinction ratios and gigabit per second modulation speed, and is capable of decoding any polarization bases differing by 90° with high extinction ratios.

Silicon photonic transceiver circuit for high-speed polarization-based discrete variable quantum key distribution

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

Cai, Hong; Long, Christopher M.; DeRose, Christopher T.

We demonstrate a silicon photonic transceiver circuit for high-speed discrete variable quantum key distribution that employs a common structure for transmit and receive functions. The device is intended for use in polarization-based quantum cryptographic protocols, such as BB84. Our characterization indicates that the circuit can generate the four BB84 states (TE/TM/45°/135° linear polarizations) with >30 dB polarization extinction ratios and gigabit per second modulation speed, and is capable of decoding any polarization bases differing by 90° with high extinction ratios.

Oxygen distribution in tumors: A qualitative analysis and modeling study providing a novel Monte Carlo approach

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

Lagerlöf, Jakob H., E-mail: Jakob@radfys.gu.se; Kindblom, Jon; Bernhardt, Peter

2014-09-15

Purpose: To construct a Monte Carlo (MC)-based simulation model for analyzing the dependence of tumor oxygen distribution on different variables related to tumor vasculature [blood velocity, vessel-to-vessel proximity (vessel proximity), and inflowing oxygen partial pressure (pO{sub 2})]. Methods: A voxel-based tissue model containing parallel capillaries with square cross-sections (sides of 10 μm) was constructed. Green's function was used for diffusion calculations and Michaelis-Menten's kinetics to manage oxygen consumption. The model was tuned to approximately reproduce the oxygenational status of a renal carcinoma; the depth oxygenation curves (DOC) were fitted with an analytical expression to facilitate rapid MC simulations of tumormore » oxygen distribution. DOCs were simulated with three variables at three settings each (blood velocity, vessel proximity, and inflowing pO{sub 2}), which resulted in 27 combinations of conditions. To create a model that simulated variable oxygen distributions, the oxygen tension at a specific point was randomly sampled with trilinear interpolation in the dataset from the first simulation. Six correlations between blood velocity, vessel proximity, and inflowing pO{sub 2} were hypothesized. Variable models with correlated parameters were compared to each other and to a nonvariable, DOC-based model to evaluate the differences in simulated oxygen distributions and tumor radiosensitivities for different tumor sizes. Results: For tumors with radii ranging from 5 to 30 mm, the nonvariable DOC model tended to generate normal or log-normal oxygen distributions, with a cut-off at zero. The pO{sub 2} distributions simulated with the six-variable DOC models were quite different from the distributions generated with the nonvariable DOC model; in the former case the variable models simulated oxygen distributions that were more similar to in vivo results found in the literature. For larger tumors, the oxygen distributions became truncated in the lower end, due to anoxia, but smaller tumors showed undisturbed oxygen distributions. The six different models with correlated parameters generated three classes of oxygen distributions. The first was a hypothetical, negative covariance between vessel proximity and pO{sub 2} (VPO-C scenario); the second was a hypothetical positive covariance between vessel proximity and pO{sub 2} (VPO+C scenario); and the third was the hypothesis of no correlation between vessel proximity and pO{sub 2} (UP scenario). The VPO-C scenario produced a distinctly different oxygen distribution than the two other scenarios. The shape of the VPO-C scenario was similar to that of the nonvariable DOC model, and the larger the tumor, the greater the similarity between the two models. For all simulations, the mean oxygen tension decreased and the hypoxic fraction increased with tumor size. The absorbed dose required for definitive tumor control was highest for the VPO+C scenario, followed by the UP and VPO-C scenarios. Conclusions: A novel MC algorithm was presented which simulated oxygen distributions and radiation response for various biological parameter values. The analysis showed that the VPO-C scenario generated a clearly different oxygen distribution from the VPO+C scenario; the former exhibited a lower hypoxic fraction and higher radiosensitivity. In future studies, this modeling approach might be valuable for qualitative analyses of factors that affect oxygen distribution as well as analyses of specific experimental and clinical situations.« less

Oxygen distribution in tumors: a qualitative analysis and modeling study providing a novel Monte Carlo approach.

PubMed

Lagerlöf, Jakob H; Kindblom, Jon; Bernhardt, Peter

2014-09-01

To construct a Monte Carlo (MC)-based simulation model for analyzing the dependence of tumor oxygen distribution on different variables related to tumor vasculature [blood velocity, vessel-to-vessel proximity (vessel proximity), and inflowing oxygen partial pressure (pO2)]. A voxel-based tissue model containing parallel capillaries with square cross-sections (sides of 10 μm) was constructed. Green's function was used for diffusion calculations and Michaelis-Menten's kinetics to manage oxygen consumption. The model was tuned to approximately reproduce the oxygenational status of a renal carcinoma; the depth oxygenation curves (DOC) were fitted with an analytical expression to facilitate rapid MC simulations of tumor oxygen distribution. DOCs were simulated with three variables at three settings each (blood velocity, vessel proximity, and inflowing pO2), which resulted in 27 combinations of conditions. To create a model that simulated variable oxygen distributions, the oxygen tension at a specific point was randomly sampled with trilinear interpolation in the dataset from the first simulation. Six correlations between blood velocity, vessel proximity, and inflowing pO2 were hypothesized. Variable models with correlated parameters were compared to each other and to a nonvariable, DOC-based model to evaluate the differences in simulated oxygen distributions and tumor radiosensitivities for different tumor sizes. For tumors with radii ranging from 5 to 30 mm, the nonvariable DOC model tended to generate normal or log-normal oxygen distributions, with a cut-off at zero. The pO2 distributions simulated with the six-variable DOC models were quite different from the distributions generated with the nonvariable DOC model; in the former case the variable models simulated oxygen distributions that were more similar to in vivo results found in the literature. For larger tumors, the oxygen distributions became truncated in the lower end, due to anoxia, but smaller tumors showed undisturbed oxygen distributions. The six different models with correlated parameters generated three classes of oxygen distributions. The first was a hypothetical, negative covariance between vessel proximity and pO2 (VPO-C scenario); the second was a hypothetical positive covariance between vessel proximity and pO2 (VPO+C scenario); and the third was the hypothesis of no correlation between vessel proximity and pO2 (UP scenario). The VPO-C scenario produced a distinctly different oxygen distribution than the two other scenarios. The shape of the VPO-C scenario was similar to that of the nonvariable DOC model, and the larger the tumor, the greater the similarity between the two models. For all simulations, the mean oxygen tension decreased and the hypoxic fraction increased with tumor size. The absorbed dose required for definitive tumor control was highest for the VPO+C scenario, followed by the UP and VPO-C scenarios. A novel MC algorithm was presented which simulated oxygen distributions and radiation response for various biological parameter values. The analysis showed that the VPO-C scenario generated a clearly different oxygen distribution from the VPO+C scenario; the former exhibited a lower hypoxic fraction and higher radiosensitivity. In future studies, this modeling approach might be valuable for qualitative analyses of factors that affect oxygen distribution as well as analyses of specific experimental and clinical situations.

Generating Spatiotemporal Joint Torque Patterns from Dynamical Synchronization of Distributed Pattern Generators

PubMed Central

Pitti, Alexandre; Lungarella, Max; Kuniyoshi, Yasuo

2009-01-01

Pattern generators found in the spinal cord are no more seen as simple rhythmic oscillators for motion control. Indeed, they achieve flexible and dynamical coordination in interaction with the body and the environment dynamics giving to rise motor synergies. Discovering the mechanisms underlying the control of motor synergies constitutes an important research question not only for neuroscience but also for robotics: the motors coordination of high dimensional robotic systems is still a drawback and new control methods based on biological solutions may reduce their overall complexity. We propose to model the flexible combination of motor synergies in embodied systems via partial phase synchronization of distributed chaotic systems; for specific coupling strength, chaotic systems are able to phase synchronize their dynamics to the resonant frequencies of one external force. We take advantage of this property to explore and exploit the intrinsic dynamics of one specified embodied system. In two experiments with bipedal walkers, we show how motor synergies emerge when the controllers phase synchronize to the body's dynamics, entraining it to its intrinsic behavioral patterns. This stage is characterized by directed information flow from the sensors to the motors exhibiting the optimal situation when the body dynamics drive the controllers (mutual entrainment). Based on our results, we discuss the relevance of our findings for modeling the modular control of distributed pattern generators exhibited in the spinal cord, and for exploring the motor synergies in robots. PMID:20011216

Optimal charges in lead progression: a structure-based neuraminidase case study.

PubMed

Armstrong, Kathryn A; Tidor, Bruce; Cheng, Alan C

2006-04-20

Collective experience in structure-based lead progression has found electrostatic interactions to be more difficult to optimize than shape-based ones. A major reason for this is that the net electrostatic contribution observed includes a significant nonintuitive desolvation component in addition to the more intuitive intermolecular interaction component. To investigate whether knowledge of the ligand optimal charge distribution can facilitate more intuitive design of electrostatic interactions, we took a series of small-molecule influenza neuraminidase inhibitors with known protein cocrystal structures and calculated the difference between the optimal and actual charge distributions. This difference from the electrostatic optimum correlates with the calculated electrostatic contribution to binding (r(2) = 0.94) despite small changes in binding modes caused by chemical substitutions, suggesting that the optimal charge distribution is a useful design goal. Furthermore, detailed suggestions for chemical modification generated by this approach are in many cases consistent with observed improvements in binding affinity, and the method appears to be useful despite discrete chemical constraints. Taken together, these results suggest that charge optimization is useful in facilitating generation of compound ideas in lead optimization. Our results also provide insight into design of neuraminidase inhibitors.

A fully traits-based approach to modeling global vegetation distribution.

PubMed

van Bodegom, Peter M; Douma, Jacob C; Verheijen, Lieneke M

2014-09-23

Dynamic Global Vegetation Models (DGVMs) are indispensable for our understanding of climate change impacts. The application of traits in DGVMs is increasingly refined. However, a comprehensive analysis of the direct impacts of trait variation on global vegetation distribution does not yet exist. Here, we present such analysis as proof of principle. We run regressions of trait observations for leaf mass per area, stem-specific density, and seed mass from a global database against multiple environmental drivers, making use of findings of global trait convergence. This analysis explained up to 52% of the global variation of traits. Global trait maps, generated by coupling the regression equations to gridded soil and climate maps, showed up to orders of magnitude variation in trait values. Subsequently, nine vegetation types were characterized by the trait combinations that they possess using Gaussian mixture density functions. The trait maps were input to these functions to determine global occurrence probabilities for each vegetation type. We prepared vegetation maps, assuming that the most probable (and thus, most suited) vegetation type at each location will be realized. This fully traits-based vegetation map predicted 42% of the observed vegetation distribution correctly. Our results indicate that a major proportion of the predictive ability of DGVMs with respect to vegetation distribution can be attained by three traits alone if traits like stem-specific density and seed mass are included. We envision that our traits-based approach, our observation-driven trait maps, and our vegetation maps may inspire a new generation of powerful traits-based DGVMs.

High-capacity quantum key distribution via hyperentangled degrees of freedom

NASA Astrophysics Data System (ADS)

Simon, David S.; Sergienko, Alexander V.

2014-06-01

Quantum key distribution (QKD) has long been a promising area for the application of quantum effects in solving real-world problems. However, two major obstacles have stood in the way of its widespread application: low secure key generation rates and short achievable operating distances. In this paper, a new physical mechanism for dealing with the first of these problems is proposed: the interplay between different degrees of freedom in a hyperentangled system (parametric down-conversion) is used to increase the Hilbert space dimension available for key generation while maintaining security. Polarization-based Bell tests provide security checking, while orbital angular momentum (OAM) and total angular momentum (TAM) provide a higher key generation rate. Whether to measure TAM or OAM is decided randomly in each trial. The concurrent noncommutativity of TAM with OAM and polarization provides the physical basis for quantum security. TAM measurements link polarization to OAM, so that if the legitimate participants measure OAM while the eavesdropper measures TAM (or vice-versa), then polarization entanglement is lost, revealing the eavesdropper. In contrast to other OAM-based QKD methods, complex active switching between OAM bases is not required; instead, passive switching by beam splitters combined with much simpler active switching between polarization bases makes implementation at high OAM more practical.

Dielectrophoretic behaviours of microdroplet sandwiched between LN substrates

PubMed Central

Chen, Lipin; Li, Shaobei; Fan, Bolin; Yan, Wenbo; Wang, Donghui; Shi, Lihong; Chen, Hongjian; Ban, Dechao; Sun, Shihao

2016-01-01

We demonstrate a sandwich configuration for microfluidic manipulation in LiNbO3 platform based on photovoltaic effect, and the behaviours of dielectric microdroplet under this sandwich configuration are investigated. It is found that the microdroplet can generate in the form of liquid bridge inside the LiNbO3-based sandwich structure under the governing dielectrophoretic force, and the dynamic process of microdroplet generation highly depends on the substrate combinations. Dynamic features found for different combinations are explained by the different electrostatic field distribution basing on the finite-element simulation results. Moreover, the electrostatic field required by the microdroplet generation is estimated through meniscus evolution and it is found in good agreement with the simulated electrostatic field inside the sandwich gap. Several kinds of microdroplet manipulations are attempted in this work. We suggest that the local dielectrophoretic force acting on the microdroplet depends on the distribution of the accumulated irradiation dosage. Without using any additional pumping or jetting actuator, the microdroplet can be step-moved, deformed or patterned by the inconsecutive dot-irradiation scheme, as well as elastically stretched out and back or smoothly guided in a designed pass by the consecutive line-irradiation scheme. PMID:27383027

The Impact of Rate Design and Net Metering on the Bill Savings from Distributed PV for Residential Customers in California

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

Energy and Resources Group, University of California, Berkeley; Darghouth, Naim R.; Barbose, Galen

2011-06-01

Net metering has become a widespread mechanism in the U.S. for supporting customer adoption of distributed photovoltaics (PV), but has faced challenges as PV installations grow to a larger share of generation in a number of states. This paper examines the value of the bill savings that customers receive under net metering, and the associated role of retail rate design, based on a sample of approximately two hundred residential customers of California's two largest electric utilities. We find that the bill savings per kWh of PV electricity generated varies by more than a factor of four across the customers inmore » the sample, which is largely attributable to the inclining block structure of the utilities' residential retail rates. We also compare the bill savings under net metering to that received under three potential alternative compensation mechanisms, based on California's Market Price Referent (MPR). We find that net metering provides significantly greater bill savings than a full MPR-based feed-in tariff, but only modestly greater savings than alternative mechanisms under which hourly or monthly net excess generation is compensated at the MPR rate.« less

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

Dalimunthe, Amty Ma’rufah Ardhiyah; Mindara, Jajat Yuda; Panatarani, Camellia

Smart grid and distributed generation should be the solution of the global climate change and the crisis energy of the main source of electrical power generation which is fossil fuel. In order to meet the rising electrical power demand and increasing service quality demands, as well as reduce pollution, the existing power grid infrastructure should be developed into a smart grid and distributed power generation which provide a great opportunity to address issues related to energy efficiency, energy security, power quality and aging infrastructure systems. The conventional of the existing distributed generation system is an AC grid while for amore » renewable resources requires a DC grid system. This paper explores the model of smart DC grid by introducing a model of smart DC grid with the stable power generation give a minimal and compressed circuitry that can be implemented very cost-effectively with simple components. The PC based application software for controlling was developed to show the condition of the grid and to control the grid become ‘smart’. The model is then subjected to a severe system perturbation, such as incremental change in loads to test the performance of the system again stability. It is concluded that the system able to detect and controlled the voltage stability which indicating the ability of power system to maintain steady voltage within permissible rangers in normal condition.« less

Computing exact bundle compliance control charts via probability generating functions.

PubMed

Chen, Binchao; Matis, Timothy; Benneyan, James

2016-06-01

Compliance to evidenced-base practices, individually and in 'bundles', remains an important focus of healthcare quality improvement for many clinical conditions. The exact probability distribution of composite bundle compliance measures used to develop corresponding control charts and other statistical tests is based on a fairly large convolution whose direct calculation can be computationally prohibitive. Various series expansions and other approximation approaches have been proposed, each with computational and accuracy tradeoffs, especially in the tails. This same probability distribution also arises in other important healthcare applications, such as for risk-adjusted outcomes and bed demand prediction, with the same computational difficulties. As an alternative, we use probability generating functions to rapidly obtain exact results and illustrate the improved accuracy and detection over other methods. Numerical testing across a wide range of applications demonstrates the computational efficiency and accuracy of this approach.

A third-generation density-functional-theory-based method for calculating canonical molecular orbitals of large molecules.

PubMed

Hirano, Toshiyuki; Sato, Fumitoshi

2014-07-28

We used grid-free modified Cholesky decomposition (CD) to develop a density-functional-theory (DFT)-based method for calculating the canonical molecular orbitals (CMOs) of large molecules. Our method can be used to calculate standard CMOs, analytically compute exchange-correlation terms, and maximise the capacity of next-generation supercomputers. Cholesky vectors were first analytically downscaled using low-rank pivoted CD and CD with adaptive metric (CDAM). The obtained Cholesky vectors were distributed and stored on each computer node in a parallel computer, and the Coulomb, Fock exchange, and pure exchange-correlation terms were calculated by multiplying the Cholesky vectors without evaluating molecular integrals in self-consistent field iterations. Our method enables DFT and massively distributed memory parallel computers to be used in order to very efficiently calculate the CMOs of large molecules.

Improvement of Galilean refractive beam shaping system for accurately generating near-diffraction-limited flattop beam with arbitrary beam size.

PubMed

Ma, Haotong; Liu, Zejin; Jiang, Pengzhi; Xu, Xiaojun; Du, Shaojun

2011-07-04

We propose and demonstrate the improvement of conventional Galilean refractive beam shaping system for accurately generating near-diffraction-limited flattop beam with arbitrary beam size. Based on the detailed study of the refractive beam shaping system, we found that the conventional Galilean beam shaper can only work well for the magnifying beam shaping. Taking the transformation of input beam with Gaussian irradiance distribution into target beam with high order Fermi-Dirac flattop profile as an example, the shaper can only work well at the condition that the size of input and target beam meets R(0) ≥ 1.3 w(0). For the improvement, the shaper is regarded as the combination of magnifying and demagnifying beam shaping system. The surface and phase distributions of the improved Galilean beam shaping system are derived based on Geometric and Fourier Optics. By using the improved Galilean beam shaper, the accurate transformation of input beam with Gaussian irradiance distribution into target beam with flattop irradiance distribution is realized. The irradiance distribution of the output beam is coincident with that of the target beam and the corresponding phase distribution is maintained. The propagation performance of the output beam is greatly improved. Studies of the influences of beam size and beam order on the improved Galilean beam shaping system show that restriction of beam size has been greatly reduced. This improvement can also be used to redistribute the input beam with complicated irradiance distribution into output beam with complicated irradiance distribution.

Benthic Habitat-Based Framework for Ecological Production Functions: Case Study for Utilization by Estuarine Birds in a Northeast Pacific Estuary

EPA Science Inventory

Habitat-based frameworks have been proposed for developing Ecological Production Functions (EPFs) to describe the spatial distribution of ecosystem services. As proof of concept, we generated EPFs that compared bird use patterns among intertidal benthic habitats for Yaquina estu...

Second-harmonic generation from a thin spherical layer and No-generation conditions

NASA Astrophysics Data System (ADS)

Kapshai, V. N.; Shamyna, A. A.

2017-09-01

In the Rayleigh-Gans-Debye approximation, we solve the problem of second-harmonic generation by an elliptically polarized electromagnetic wave incident on the surface of a spherical particle that is coated by an optically nonlinear layer and is placed in a dielectric. The formulas obtained characterize the spatial distribution of the electric field of the second harmonic in the far-field zone. The most general form of the second-order dielectric susceptibility tensor is considered, which contains four independent components, with three of them being nonchiral and one, chiral. Consistency and inconsistencies between the obtained solution and formulas from works of other authors are found. We analyze the directivity patterns that characterize the spatial distribution of the generated radiation for the nonchiral layer and their dependences on the anisotropy and ellipticity coefficients of the incident wave. It is found that, with increasing radius of the nonlinear layer, the generated radiation becomes more directional. Combinations of parameters for which no radiation is generated are revealed. Based on this, we propose methods for experimental determination of the anisotropy coefficients.

Distributed Generation to Support Development-Focused Climate Action

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

Cox, Sadie; Gagnon, Pieter; Stout, Sherry

2016-09-01

This paper explores the role of distributed generation, with a high renewable energy contribution, in supporting low emission climate-resilient development. The paper presents potential impacts on development (via energy access), greenhouse gas emission mitigation, and climate resilience directly associated with distributed generation, as well as specific actions that may enhance or increase the likelihood of climate and development benefits. This paper also seeks to provide practical and timely insights to support distributed generation policymaking and planning within the context of common climate and development goals as the distributed generation landscape rapidly evolves globally. Country-specific distributed generation policy and program examples,more » as well as analytical tools that can inform efforts internationally, are also highlighted throughout the paper.« less

Theory of quantized systems: formal basis for DEVS/HLA distributed simulation environment

NASA Astrophysics Data System (ADS)

Zeigler, Bernard P.; Lee, J. S.

1998-08-01

In the context of a DARPA ASTT project, we are developing an HLA-compliant distributed simulation environment based on the DEVS formalism. This environment will provide a user- friendly, high-level tool-set for developing interoperable discrete and continuous simulation models. One application is the study of contract-based predictive filtering. This paper presents a new approach to predictive filtering based on a process called 'quantization' to reduce state update transmission. Quantization, which generates state updates only at quantum level crossings, abstracts a sender model into a DEVS representation. This affords an alternative, efficient approach to embedding continuous models within distributed discrete event simulations. Applications of quantization to message traffic reduction are discussed. The theory has been validated by DEVSJAVA simulations of test cases. It will be subject to further test in actual distributed simulations using the DEVS/HLA modeling and simulation environment.

Three-Axis Ground Reaction Force Distribution during Straight Walking.

PubMed

Hori, Masataka; Nakai, Akihito; Shimoyama, Isao

2017-10-24

We measured the three-axis ground reaction force (GRF) distribution during straight walking. Small three-axis force sensors composed of rubber and sensor chips were fabricated and calibrated. After sensor calibration, 16 force sensors were attached to the left shoe. The three-axis force distribution during straight walking was measured, and the local features of the three-axis force under the sole of the shoe were analyzed. The heel area played a role in receiving the braking force, the base area of the fourth and fifth toes applied little vertical or shear force, the base area of the second and third toes generated a portion of the propulsive force and received a large vertical force, and the base area of the big toe helped move the body's center of mass to the other foot. The results demonstrate that measuring the three-axis GRF distribution is useful for a detailed analysis of bipedal locomotion.

A DICOM-based 2nd generation Molecular Imaging Data Grid implementing the IHE XDS-i integration profile.

PubMed

Lee, Jasper; Zhang, Jianguo; Park, Ryan; Dagliyan, Grant; Liu, Brent; Huang, H K

2012-07-01

A Molecular Imaging Data Grid (MIDG) was developed to address current informatics challenges in archival, sharing, search, and distribution of preclinical imaging studies between animal imaging facilities and investigator sites. This manuscript presents a 2nd generation MIDG replacing the Globus Toolkit with a new system architecture that implements the IHE XDS-i integration profile. Implementation and evaluation were conducted using a 3-site interdisciplinary test-bed at the University of Southern California. The 2nd generation MIDG design architecture replaces the initial design's Globus Toolkit with dedicated web services and XML-based messaging for dedicated management and delivery of multi-modality DICOM imaging datasets. The Cross-enterprise Document Sharing for Imaging (XDS-i) integration profile from the field of enterprise radiology informatics was adopted into the MIDG design because streamlined image registration, management, and distribution dataflow are likewise needed in preclinical imaging informatics systems as in enterprise PACS application. Implementation of the MIDG is demonstrated at the University of Southern California Molecular Imaging Center (MIC) and two other sites with specified hardware, software, and network bandwidth. Evaluation of the MIDG involves data upload, download, and fault-tolerance testing scenarios using multi-modality animal imaging datasets collected at the USC Molecular Imaging Center. The upload, download, and fault-tolerance tests of the MIDG were performed multiple times using 12 collected animal study datasets. Upload and download times demonstrated reproducibility and improved real-world performance. Fault-tolerance tests showed that automated failover between Grid Node Servers has minimal impact on normal download times. Building upon the 1st generation concepts and experiences, the 2nd generation MIDG system improves accessibility of disparate animal-model molecular imaging datasets to users outside a molecular imaging facility's LAN using a new architecture, dataflow, and dedicated DICOM-based management web services. Productivity and efficiency of preclinical research for translational sciences investigators has been further streamlined for multi-center study data registration, management, and distribution.

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

Langan, Roisin T.; Archibald, Richard K.; Lamberti, Vincent

We have applied a new imputation-based method for analyzing incomplete data, called Monte Carlo Bayesian Database Generation (MCBDG), to the Spent Fuel Isotopic Composition (SFCOMPO) database. About 60% of the entries are absent for SFCOMPO. The method estimates missing values of a property from a probability distribution created from the existing data for the property, and then generates multiple instances of the completed database for training a machine learning algorithm. Uncertainty in the data is represented by an empirical or an assumed error distribution. The method makes few assumptions about the underlying data, and compares favorably against results obtained bymore » replacing missing information with constant values.« less

Cascaded Raman lasing in a PM phosphosilicate fiber with random distributed feedback

NASA Astrophysics Data System (ADS)

Lobach, Ivan A.; Kablukov, Sergey I.; Babin, Sergey A.

2018-02-01

We report on the first demonstration of a linearly polarized cascaded Raman fiber laser based on a simple half-open cavity with a broadband composite reflector and random distributed feedback in a polarization maintaining phosphosilicate fiber operating beyond zero dispersion wavelength ( 1400 nm). With increasing pump power from a Yb-doped fiber laser at 1080 nm, the random laser generates subsequently 8 W at 1262 nm and 9 W at 1515 nm with polarization extinction ratio of 27 dB. The generation linewidths amount to about 1 nm and 3 nm, respectively, being almost independent of power, in correspondence with the theory of a cascaded random lasing.

Protection of autonomous microgrids using agent-based distributed communication

DOE PAGES

Cintuglu, Mehmet H.; Ma, Tan; Mohammed, Osama A.

2016-04-06

This study presents a real-time implementation of autonomous microgrid protection using agent-based distributed communication. Protection of an autonomous microgrid requires special considerations compared to large scale distribution net-works due to the presence of power converters and relatively low inertia. In this work, we introduce a practical overcurrent and a frequency selectivity method to overcome conventional limitations. The proposed overcurrent scheme defines a selectivity mechanism considering the remedial action scheme (RAS) of the microgrid after a fault instant based on feeder characteristics and the location of the intelligent electronic devices (IEDs). A synchrophasor-based online frequency selectivity approach is proposed to avoidmore » pulse loading effects in low inertia microgrids. Experimental results are presented for verification of the pro-posed schemes using a laboratory based microgrid. The setup was composed of actual generation units and IEDs using IEC 61850 protocol. The experimental results were in excellent agreement with the proposed protection scheme.« less

Protection of autonomous microgrids using agent-based distributed communication

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

Cintuglu, Mehmet H.; Ma, Tan; Mohammed, Osama A.

This study presents a real-time implementation of autonomous microgrid protection using agent-based distributed communication. Protection of an autonomous microgrid requires special considerations compared to large scale distribution net-works due to the presence of power converters and relatively low inertia. In this work, we introduce a practical overcurrent and a frequency selectivity method to overcome conventional limitations. The proposed overcurrent scheme defines a selectivity mechanism considering the remedial action scheme (RAS) of the microgrid after a fault instant based on feeder characteristics and the location of the intelligent electronic devices (IEDs). A synchrophasor-based online frequency selectivity approach is proposed to avoidmore » pulse loading effects in low inertia microgrids. Experimental results are presented for verification of the pro-posed schemes using a laboratory based microgrid. The setup was composed of actual generation units and IEDs using IEC 61850 protocol. The experimental results were in excellent agreement with the proposed protection scheme.« less

Integrated-Circuit Pseudorandom-Number Generator

NASA Technical Reports Server (NTRS)

Steelman, James E.; Beasley, Jeff; Aragon, Michael; Ramirez, Francisco; Summers, Kenneth L.; Knoebel, Arthur

1992-01-01

Integrated circuit produces 8-bit pseudorandom numbers from specified probability distribution, at rate of 10 MHz. Use of Boolean logic, circuit implements pseudorandom-number-generating algorithm. Circuit includes eight 12-bit pseudorandom-number generators, outputs are uniformly distributed. 8-bit pseudorandom numbers satisfying specified nonuniform probability distribution are generated by processing uniformly distributed outputs of eight 12-bit pseudorandom-number generators through "pipeline" of D flip-flops, comparators, and memories implementing conditional probabilities on zeros and ones.

Smart-DS: Synthetic Models for Advanced, Realistic Testing: Distribution Systems and Scenarios

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

Krishnan, Venkat K; Palmintier, Bryan S; Hodge, Brian S

The National Renewable Energy Laboratory (NREL) in collaboration with Massachusetts Institute of Technology (MIT), Universidad Pontificia Comillas (Comillas-IIT, Spain) and GE Grid Solutions, is working on an ARPA-E GRID DATA project, titled Smart-DS, to create: 1) High-quality, realistic, synthetic distribution network models, and 2) Advanced tools for automated scenario generation based on high-resolution weather data and generation growth projections. Through these advancements, the Smart-DS project is envisioned to accelerate the development, testing, and adoption of advanced algorithms, approaches, and technologies for sustainable and resilient electric power systems, especially in the realm of U.S. distribution systems. This talk will present themore » goals and overall approach of the Smart-DS project, including the process of creating the synthetic distribution datasets using reference network model (RNM) and the comprehensive validation process to ensure network realism, feasibility, and applicability to advanced use cases. The talk will provide demonstrations of early versions of synthetic models, along with the lessons learnt from expert engagements to enhance future iterations. Finally, the scenario generation framework, its development plans, and co-ordination with GRID DATA repository teams to house these datasets for public access will also be discussed.« less

Microgrids for Service Restoration to Critical Load in a Resilient Distribution System

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

Xu, Yin; Liu, Chen-Ching; Schneider, Kevin P.

icrogrids can act as emergency sources to serve critical loads when utility power is unavailable. This paper proposes a resiliency-based methodology that uses microgrids to restore critical loads on distribution feeders after a major disaster. Due to limited capacity of distributed generators (DGs) within microgrids, dynamic performance of the DGs during the restoration process becomes essential. In this paper, the stability of microgrids, limits on frequency deviation, and limits on transient voltage and current of DGs are incorporated as constraints of the critical load restoration problem. The limits on the amount of generation resources within microgrids are also considered. Bymore » introducing the concepts of restoration tree and load group, restoration of critical loads is transformed into a maximum coverage problem, which is a linear integer program (LIP). The restoration paths and actions are determined for critical loads by solving the LIP. A 4-feeder, 1069-bus unbalanced test system with four microgrids is utilized to demonstrate the effectiveness of the proposed method. The method is applied to the distribution system in Pullman, WA, resulting in a strategy that uses generators on the Washington State University campus to restore service to the Hospital and City Hall in Pullman.« less

Independent Orbiter Assessment (IOA): Analysis of the electrical power distribution and control/electrical power generation subsystem

NASA Technical Reports Server (NTRS)

Patton, Jeff A.

1986-01-01

The results of the Independent Orbiter Assessment (IOA) of the Failure Modes and Effects Analysis (FMEA) and Critical Items List (CIL) are presented. The IOA approach features a top-down analysis of the hardware to determine failure modes, criticality, and potential critical items. To preserve independence, this analysis was accomplished without reliance upon the results contained within the NASA FMEA/CIL documentation. This report documents the independent analysis results corresponding to the Orbiter Electrical Power Distribution and Control (EPD and C)/Electrical Power Generation (EPG) hardware. The EPD and C/EPG hardware is required for performing critical functions of cryogenic reactant storage, electrical power generation and product water distribution in the Orbiter. Specifically, the EPD and C/EPG hardware consists of the following components: Power Section Assembly (PSA); Reactant Control Subsystem (RCS); Thermal Control Subsystem (TCS); Water Removal Subsystem (WRS); and Power Reactant Storage and Distribution System (PRSDS). The IOA analysis process utilized available EPD and C/EPG hardware drawings and schematics for defining hardware assemblies, components, and hardware items. Each level of hardware was evaluated and analyzed for possible failure modes and effects. Criticality was assigned based upon the severity of the effect for each failure mode.

Equilibrium Molecular Thermodynamics from Kirkwood Sampling

PubMed Central

2015-01-01

We present two methods for barrierless equilibrium sampling of molecular systems based on the recently proposed Kirkwood method (J. Chem. Phys.2009, 130, 134102). Kirkwood sampling employs low-order correlations among internal coordinates of a molecule for random (or non-Markovian) sampling of the high dimensional conformational space. This is a geometrical sampling method independent of the potential energy surface. The first method is a variant of biased Monte Carlo, where Kirkwood sampling is used for generating trial Monte Carlo moves. Using this method, equilibrium distributions corresponding to different temperatures and potential energy functions can be generated from a given set of low-order correlations. Since Kirkwood samples are generated independently, this method is ideally suited for massively parallel distributed computing. The second approach is a variant of reservoir replica exchange, where Kirkwood sampling is used to construct a reservoir of conformations, which exchanges conformations with the replicas performing equilibrium sampling corresponding to different thermodynamic states. Coupling with the Kirkwood reservoir enhances sampling by facilitating global jumps in the conformational space. The efficiency of both methods depends on the overlap of the Kirkwood distribution with the target equilibrium distribution. We present proof-of-concept results for a model nine-atom linear molecule and alanine dipeptide. PMID:25915525

Flapping wing applied to wind generators

NASA Astrophysics Data System (ADS)

Colidiuc, Alexandra; Galetuse, Stelian; Suatean, Bogdan

2012-11-01

The new conditions at the international level for energy source distributions and the continuous increasing of energy consumption must lead to a new alternative resource with the condition of keeping the environment clean. This paper offers a new approach for a wind generator and is based on the theoretical aerodynamic model. This new model of wind generator helped me to test what influences would be if there will be a bird airfoil instead of a normal wind generator airfoil. The aim is to calculate the efficiency for the new model of wind generator. A representative direction for using the renewable energy is referred to the transformation of wind energy into electrical energy, with the help of wind turbines; the development of such systems lead to new solutions based on high efficiency, reduced costs and suitable to the implementation conditions.

Energy management and cooperation in microgrids

NASA Astrophysics Data System (ADS)

Rahbar, Katayoun

Microgrids are key components of future smart power grids, which integrate distributed renewable energy generators to efficiently serve the load demand locally. However, random and intermittent characteristics of renewable energy generations may hinder the reliable operation of microgrids. This thesis is thus devoted to investigating new strategies for microgrids to optimally manage their energy consumption, energy storage system (ESS) and cooperation in real time to achieve the reliable and cost-effective operation. This thesis starts with a single microgrid system. The optimal energy scheduling and ESS management policy is derived to minimize the energy cost of the microgrid resulting from drawing conventional energy from the main grid under both the off-line and online setups, where the renewable energy generation/load demand are assumed to be non-causally known and causally known at the microgrid, respectively. The proposed online algorithm is designed based on the optimal off-line solution and works under arbitrary (even unknown) realizations of future renewable energy generation/load demand. Therefore, it is more practically applicable as compared to solutions based on conventional techniques such as dynamic programming and stochastic programming that require the prior knowledge of renewable energy generation and load demand realizations/distributions. Next, for a group of microgrids that cooperate in energy management, we study efficient methods for sharing energy among them for both fully and partially cooperative scenarios, where microgrids are of common interests and self-interested, respectively. For the fully cooperative energy management, the off-line optimization problem is first formulated and optimally solved, where a distributed algorithm is proposed to minimize the total (sum) energy cost of microgrids. Inspired by the results obtained from the off-line optimization, efficient online algorithms are proposed for the real-time energy management, which are of low complexity and work given arbitrary realizations of renewable energy generation/load demand. On the other hand, for self-interested microgrids, the partially cooperative energy management is formulated and a distributed algorithm is proposed to optimize the energy cooperation such that energy costs of individual microgrids reduce simultaneously over the case without energy cooperation while limited information is shared among the microgrids and the central controller.

Distributed cooperative control of AC microgrids

NASA Astrophysics Data System (ADS)

Bidram, Ali

In this dissertation, the comprehensive secondary control of electric power microgrids is of concern. Microgrid technical challenges are mainly realized through the hierarchical control structure, including primary, secondary, and tertiary control levels. Primary control level is locally implemented at each distributed generator (DG), while the secondary and tertiary control levels are conventionally implemented through a centralized control structure. The centralized structure requires a central controller which increases the reliability concerns by posing the single point of failure. In this dissertation, the distributed control structure using the distributed cooperative control of multi-agent systems is exploited to increase the secondary control reliability. The secondary control objectives are microgrid voltage and frequency, and distributed generators (DGs) active and reactive powers. Fully distributed control protocols are implemented through distributed communication networks. In the distributed control structure, each DG only requires its own information and the information of its neighbors on the communication network. The distributed structure obviates the requirements for a central controller and complex communication network which, in turn, improves the system reliability. Since the DG dynamics are nonlinear and non-identical, input-output feedback linearization is used to transform the nonlinear dynamics of DGs to linear dynamics. Proposed control frameworks cover the control of microgrids containing inverter-based DGs. Typical microgrid test systems are used to verify the effectiveness of the proposed control protocols.

Net Metering Policy Development and Distributed Solar Generation in Minnesota: Overview of Trends in Nationwide Policy Development and Implications of Increasing the Eligible System Size Cap

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

Doris, E.; Busche, S.; Hockett, S.

2009-12-01

The goal of the Minnesota net metering policy is to give the maximum possible encouragement to distributed generation assets, especially solar electric systems (MN 2008). However, according to a published set of best practices (NNEC 2008) that prioritize the maximum development of solar markets within states, the Minnesota policy does not incorporate many of the important best practices that may help other states transform their solar energy markets and increase the amount of grid-connected distributed solar generation assets. Reasons cited include the low system size limit of 40kW (the best practices document recommends a 2 MW limit) and a lackmore » of language protecting generators from additional utility fees. This study was conducted to compare Minnesota's policies to national best practices. It provides an overview of the current Minnesota policy in the context of these best practices and other jurisdictions' net metering policies, as well as a qualitative assessment of the impacts of raising the system size cap within the policy based on the experiences of other states.« less

Robust Operation of Soft Open Points in Active Distribution Networks with High Penetration of Photovoltaic Integration

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

Ding, Fei; Ji, Haoran; Wang, Chengshan

Distributed generators (DGs) including photovoltaic panels (PVs) have been integrated dramatically in active distribution networks (ADNs). Due to the strong volatility and uncertainty, the high penetration of PV generation immensely exacerbates the conditions of voltage violation in ADNs. However, the emerging flexible interconnection technology based on soft open points (SOPs) provides increased controllability and flexibility to the system operation. For fully exploiting the regulation ability of SOPs to address the problems caused by PV, this paper proposes a robust optimization method to achieve the robust optimal operation of SOPs in ADNs. A two-stage adjustable robust optimization model is built tomore » tackle the uncertainties of PV outputs, in which robust operation strategies of SOPs are generated to eliminate the voltage violations and reduce the power losses of ADNs. A column-and-constraint generation (C&CG) algorithm is developed to solve the proposed robust optimization model, which are formulated as second-order cone program (SOCP) to facilitate the accuracy and computation efficiency. Case studies on the modified IEEE 33-node system and comparisons with the deterministic optimization approach are conducted to verify the effectiveness and robustness of the proposed method.« less

Simulating Bubble Plumes from Breaking Waves with a Forced-Air Venturi

NASA Astrophysics Data System (ADS)

Long, M. S.; Keene, W. C.; Maben, J. R.; Chang, R. Y. W.; Duplessis, P.; Kieber, D. J.; Beaupre, S. R.; Frossard, A. A.; Kinsey, J. D.; Zhu, Y.; Lu, X.; Bisgrove, J.

2017-12-01

It has been hypothesized that the size distribution of bubbles in subsurface seawater is a major factor that modulates the corresponding size distribution of primary marine aerosol (PMA) generated when those bubbles burst at the air-water interface. A primary physical control of the bubble size distribution produced by wave breaking is the associated turbulence that disintegrates larger bubbles into smaller ones. This leads to two characteristic features of bubble size distributions: (1) the Hinze scale which reflects a bubble size above which disintegration is possible based on turbulence intensity and (2) the slopes of log-linear regressions of the size distribution on either side of the Hinze scale that indicate the state of plume evolution or age. A Venturi with tunable seawater and forced air flow rates was designed and deployed in an artificial PMA generator to produce bubble plumes representative of breaking waves. This approach provides direct control of turbulence intensity and, thus, the resulting bubble size distribution characterizable by observations of the Hinze scale and the simulated plume age over a range of known air detrainment rates. Evaluation of performance in different seawater types over the western North Atlantic demonstrated that the Venturi produced bubble plumes with parameter values that bracket the range of those observed in laboratory and field experiments. Specifically, the seawater flow rate modulated the value of the Hinze scale while the forced-air flow rate modulated the plume age parameters. Results indicate that the size distribution of sub-surface bubbles within the generator did not significantly modulate the corresponding number size distribution of PMA produced via bubble bursting.

Wigner functions for evanescent waves.

PubMed

Petruccelli, Jonathan C; Tian, Lei; Oh, Se Baek; Barbastathis, George

2012-09-01

We propose phase space distributions, based on an extension of the Wigner distribution function, to describe fields of any state of coherence that contain evanescent components emitted into a half-space. The evanescent components of the field are described in an optical phase space of spatial position and complex-valued angle. Behavior of these distributions upon propagation is also considered, where the rapid decay of the evanescent components is associated with the exponential decay of the associated phase space distributions. To demonstrate the structure and behavior of these distributions, we consider the fields generated from total internal reflection of a Gaussian Schell-model beam at a planar interface.

Control of dispatch dynamics for lowering the cost of distributed generation in the built environment

NASA Astrophysics Data System (ADS)

Flores, Robert Joseph

Distributed generation can provide many benefits over traditional central generation such as increased reliability and efficiency while reducing emissions. Despite these potential benefits, distributed generation is generally not purchased unless it reduces energy costs. Economic dispatch strategies can be designed such that distributed generation technologies reduce overall facility energy costs. In this thesis, a microturbine generator is dispatched using different economic control strategies, reducing the cost of energy to the facility. Several industrial and commercial facilities are simulated using acquired electrical, heating, and cooling load data. Industrial and commercial utility rate structures are modeled after Southern California Edison and Southern California Gas Company tariffs and used to find energy costs for the simulated buildings and corresponding microturbine dispatch. Using these control strategies, building models, and utility rate models, a parametric study examining various generator characteristics is performed. An economic assessment of the distributed generation is then performed for both the microturbine generator and parametric study. Without the ability to export electricity to the grid, the economic value of distributed generation is limited to reducing the individual costs that make up the cost of energy for a building. Any economic dispatch strategy must be built to reduce these individual costs. While the ability of distributed generation to reduce cost depends of factors such as electrical efficiency and operations and maintenance cost, the building energy demand being serviced has a strong effect on cost reduction. Buildings with low load factors can accept distributed generation with higher operating costs (low electrical efficiency and/or high operations and maintenance cost) due to the value of demand reduction. As load factor increases, lower operating cost generators are desired due to a larger portion of the building load being met in an effort to reduce demand. In addition, buildings with large thermal demand have access to the least expensive natural gas, lowering the cost of operating distributed generation. Recovery of exhaust heat from DG reduces cost only if the buildings thermal demand coincides with the electrical demand. Capacity limits exist where annual savings from operation of distributed generation decrease if further generation is installed. For low operating cost generators, the approximate limit is the average building load. This limit decreases as operating costs increase. In addition, a high capital cost of distributed generation can be accepted if generator operating costs are low. As generator operating costs increase, capital cost must decrease if a positive economic performance is desired.

Federated software defined network operations for LHC experiments

NASA Astrophysics Data System (ADS)

Kim, Dongkyun; Byeon, Okhwan; Cho, Kihyeon

2013-09-01

The most well-known high-energy physics collaboration, the Large Hadron Collider (LHC), which is based on e-Science, has been facing several challenges presented by its extraordinary instruments in terms of the generation, distribution, and analysis of large amounts of scientific data. Currently, data distribution issues are being resolved by adopting an advanced Internet technology called software defined networking (SDN). Stability of the SDN operations and management is demanded to keep the federated LHC data distribution networks reliable. Therefore, in this paper, an SDN operation architecture based on the distributed virtual network operations center (DvNOC) is proposed to enable LHC researchers to assume full control of their own global end-to-end data dissemination. This may achieve an enhanced data delivery performance based on data traffic offloading with delay variation. The evaluation results indicate that the overall end-to-end data delivery performance can be improved over multi-domain SDN environments based on the proposed federated SDN/DvNOC operation framework.

Stability assessment of a multi-port power electronic interface for hybrid micro-grid applications

NASA Astrophysics Data System (ADS)

Shamsi, Pourya

Migration to an industrial society increases the demand for electrical energy. Meanwhile, social causes for preserving the environment and reducing pollutions seek cleaner forms of energy sources. Therefore, there has been a growth in distributed generation from renewable sources in the past decade. Existing regulations and power system coordination does not allow for massive integration of distributed generation throughout the grid. Moreover, the current infrastructures are not designed for interfacing distributed and deregulated generation. In order to remedy this problem, a hybrid micro-grid based on nano-grids is introduced. This system consists of a reliable micro-grid structure that provides a smooth transition from the current distribution networks to smart micro-grid systems. Multi-port power electronic interfaces are introduced to manage the local generation, storage, and consumption. Afterwards, a model for this micro-grid is derived. Using this model, the stability of the system under a variety of source and load induced disturbances is studied. Moreover, pole-zero study of the micro-grid is performed under various loading conditions. An experimental setup of this micro-grid is developed, and the validity of the model in emulating the dynamic behavior of the system is verified. This study provides a theory for a novel hybrid micro-grid as well as models for stability assessment of the proposed micro-grid.

Analytical and numerical solutions of the potential and electric field generated by different electrode arrays in a tumor tissue under electrotherapy

PubMed Central

2011-01-01

Background Electrotherapy is a relatively well established and efficient method of tumor treatment. In this paper we focus on analytical and numerical calculations of the potential and electric field distributions inside a tumor tissue in a two-dimensional model (2D-model) generated by means of electrode arrays with shapes of different conic sections (ellipse, parabola and hyperbola). Methods Analytical calculations of the potential and electric field distributions based on 2D-models for different electrode arrays are performed by solving the Laplace equation, meanwhile the numerical solution is solved by means of finite element method in two dimensions. Results Both analytical and numerical solutions reveal significant differences between the electric field distributions generated by electrode arrays with shapes of circle and different conic sections (elliptic, parabolic and hyperbolic). Electrode arrays with circular, elliptical and hyperbolic shapes have the advantage of concentrating the electric field lines in the tumor. Conclusion The mathematical approach presented in this study provides a useful tool for the design of electrode arrays with different shapes of conic sections by means of the use of the unifying principle. At the same time, we verify the good correspondence between the analytical and numerical solutions for the potential and electric field distributions generated by the electrode array with different conic sections. PMID:21943385

Feedback-Based Projected-Gradient Method for Real-Time Optimization of Aggregations of Energy Resources

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

Dall-Anese, Emiliano; Bernstein, Andrey; Simonetto, Andrea

This paper develops an online optimization method to maximize operational objectives of distribution-level distributed energy resources (DERs), while adjusting the aggregate power generated (or consumed) in response to services requested by grid operators. The design of the online algorithm is based on a projected-gradient method, suitably modified to accommodate appropriate measurements from the distribution network and the DERs. By virtue of this approach, the resultant algorithm can cope with inaccuracies in the representation of the AC power flows, it avoids pervasive metering to gather the state of noncontrollable resources, and it naturally lends itself to a distributed implementation. Optimality claimsmore » are established in terms of tracking of the solution of a well-posed time-varying convex optimization problem.« less

Feedback-Based Projected-Gradient Method For Real-Time Optimization of Aggregations of Energy Resources: Preprint

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

Dall-Anese, Emiliano; Bernstein, Andrey; Simonetto, Andrea

This paper develops an online optimization method to maximize the operational objectives of distribution-level distributed energy resources (DERs) while adjusting the aggregate power generated (or consumed) in response to services requested by grid operators. The design of the online algorithm is based on a projected-gradient method, suitably modified to accommodate appropriate measurements from the distribution network and the DERs. By virtue of this approach, the resultant algorithm can cope with inaccuracies in the representation of the AC power, it avoids pervasive metering to gather the state of noncontrollable resources, and it naturally lends itself to a distributed implementation. Optimality claimsmore » are established in terms of tracking of the solution of a well-posed time-varying optimization problem.« less

Implementation of continuous-variable quantum key distribution with composable and one-sided-device-independent security against coherent attacks.

PubMed

Gehring, Tobias; Händchen, Vitus; Duhme, Jörg; Furrer, Fabian; Franz, Torsten; Pacher, Christoph; Werner, Reinhard F; Schnabel, Roman

2015-10-30

Secret communication over public channels is one of the central pillars of a modern information society. Using quantum key distribution this is achieved without relying on the hardness of mathematical problems, which might be compromised by improved algorithms or by future quantum computers. State-of-the-art quantum key distribution requires composable security against coherent attacks for a finite number of distributed quantum states as well as robustness against implementation side channels. Here we present an implementation of continuous-variable quantum key distribution satisfying these requirements. Our implementation is based on the distribution of continuous-variable Einstein-Podolsky-Rosen entangled light. It is one-sided device independent, which means the security of the generated key is independent of any memoryfree attacks on the remote detector. Since continuous-variable encoding is compatible with conventional optical communication technology, our work is a step towards practical implementations of quantum key distribution with state-of-the-art security based solely on telecom components.

Implementation of continuous-variable quantum key distribution with composable and one-sided-device-independent security against coherent attacks

PubMed Central

Gehring, Tobias; Händchen, Vitus; Duhme, Jörg; Furrer, Fabian; Franz, Torsten; Pacher, Christoph; Werner, Reinhard F.; Schnabel, Roman

2015-01-01

Secret communication over public channels is one of the central pillars of a modern information society. Using quantum key distribution this is achieved without relying on the hardness of mathematical problems, which might be compromised by improved algorithms or by future quantum computers. State-of-the-art quantum key distribution requires composable security against coherent attacks for a finite number of distributed quantum states as well as robustness against implementation side channels. Here we present an implementation of continuous-variable quantum key distribution satisfying these requirements. Our implementation is based on the distribution of continuous-variable Einstein–Podolsky–Rosen entangled light. It is one-sided device independent, which means the security of the generated key is independent of any memoryfree attacks on the remote detector. Since continuous-variable encoding is compatible with conventional optical communication technology, our work is a step towards practical implementations of quantum key distribution with state-of-the-art security based solely on telecom components. PMID:26514280

Non-contact assessment of melanin distribution via multispectral temporal illumination coding

NASA Astrophysics Data System (ADS)

Amelard, Robert; Scharfenberger, Christian; Wong, Alexander; Clausi, David A.

2015-03-01

Melanin is a pigment that is highly absorptive in the UV and visible electromagnetic spectra. It is responsible for perceived skin tone, and protects against harmful UV effects. Abnormal melanin distribution is often an indicator for melanoma. We propose a novel approach for non-contact melanin distribution via multispectral temporal illumination coding to estimate the two-dimensional melanin distribution based on its absorptive characteristics. In the proposed system, a novel multispectral, cross-polarized, temporally-coded illumination sequence is synchronized with a camera to measure reflectance under both multispectral and ambient illumination. This allows us to eliminate the ambient illumination contribution from the acquired reflectance measurements, and also to determine the melanin distribution in an observed region based on the spectral properties of melanin using the Beer-Lambert law. Using this information, melanin distribution maps can be generated for objective, quantitative assessment of skin type of individuals. We show that the melanin distribution map correctly identifies areas with high melanin densities (e.g., nevi).

Multi-Core Processors: An Enabling Technology for Embedded Distributed Model-Based Control (Postprint)

DTIC Science & Technology

2008-07-01

generation of process partitioning, a thread pipelining becomes possible. In this paper we briefly summarize the requirements and trends for FADEC based... FADEC environment, presenting a hypothetical realization of an example application. Finally we discuss the application of Time-Triggered...based control applications of the future. 15. SUBJECT TERMS Gas turbine, FADEC , Multi-core processing technology, disturbed based control

Multi-user distribution of polarization entangled photon pairs

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

Trapateau, J.; Orieux, A.; Diamanti, E.

We experimentally demonstrate multi-user distribution of polarization entanglement using commercial telecom wavelength division demultiplexers. The entangled photon pairs are generated from a broadband source based on spontaneous parametric down conversion in a periodically poled lithium niobate crystal using a double path setup employing a Michelson interferometer and active phase stabilisation. We test and compare demultiplexers based on various technologies and analyze the effect of their characteristics, such as losses and polarization dependence, on the quality of the distributed entanglement for three channel pairs of each demultiplexer. In all cases, we obtain a Bell inequality violation, whose value depends on themore » demultiplexer features. This demonstrates that entanglement can be distributed to at least three user pairs of a network from a single source. Additionally, we verify for the best demultiplexer that the violation is maintained when the pairs are distributed over a total channel attenuation corresponding to 20 km of optical fiber. These techniques are therefore suitable for resource-efficient practical implementations of entanglement-based quantum key distribution and other quantum communication network applications.« less

Evaluating visibility of age spot and freckle based on simulated spectral reflectance distribution and facial color image

NASA Astrophysics Data System (ADS)

Hirose, Misa; Toyota, Saori; Tsumura, Norimichi

2018-02-01

In this research, we evaluate the visibility of age spot and freckle with changing the blood volume based on simulated spectral reflectance distribution and the actual facial color images, and compare these results. First, we generate three types of spatial distribution of age spot and freckle in patch-like images based on the simulated spectral reflectance. The spectral reflectance is simulated using Monte Carlo simulation of light transport in multi-layered tissue. Next, we reconstruct the facial color image with changing the blood volume. We acquire the concentration distribution of melanin, hemoglobin and shading components by applying the independent component analysis on a facial color image. We reproduce images using the obtained melanin and shading concentration and the changed hemoglobin concentration. Finally, we evaluate the visibility of pigmentations using simulated spectral reflectance distribution and facial color images. In the result of simulated spectral reflectance distribution, we found that the visibility became lower as the blood volume increases. However, we can see that a specific blood volume reduces the visibility of the actual pigmentations from the result of the facial color images.

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

Hatta, Yoshitaka; Xiao, Bo-Wen; Yuan, Feng

We present a full evaluation of the deeply virtual Compton scattering cross section in the dipole framework in the small-x region. The result features the cosφ and cos2φ azimuthal angular correlations, which have been missing in previous studies based on the dipole model. In particular, the cos2φ term is generated by the elliptic gluon Wigner distribution of which the measurement at the planned electron-ion collider provides important information about the gluon tomography at small x. Here, we also show the consistency with the standard collinear factorization approach based on the quark and gluon generalized parton distributions.

On the use of Schwarz-Christoffel conformal mappings to the grid generation for global ocean models

NASA Astrophysics Data System (ADS)

Xu, S.; Wang, B.; Liu, J.

2015-02-01

In this article we propose two conformal mapping based grid generation algorithms for global ocean general circulation models (OGCMs). Contrary to conventional, analytical forms based dipolar or tripolar grids, the new algorithms are based on Schwarz-Christoffel (SC) conformal mapping with prescribed boundary information. While dealing with the basic grid design problem of pole relocation, these new algorithms also address more advanced issues such as smoothed scaling factor, or the new requirements on OGCM grids arisen from the recent trend of high-resolution and multi-scale modeling. The proposed grid generation algorithm could potentially achieve the alignment of grid lines to coastlines, enhanced spatial resolution in coastal regions, and easier computational load balance. Since the generated grids are still orthogonal curvilinear, they can be readily utilized in existing Bryan-Cox-Semtner type ocean models. The proposed methodology can also be applied to the grid generation task for regional ocean modeling where complex land-ocean distribution is present.

Thermal residual stress evaluation based on phase-shift lateral shearing interferometry

NASA Astrophysics Data System (ADS)

Dai, Xiangjun; Yun, Hai; Shao, Xinxing; Wang, Yanxia; Zhang, Donghuan; Yang, Fujun; He, Xiaoyuan

2018-06-01

An interesting phase-shift lateral shearing interferometry system was proposed to evaluate the thermal residual stress distribution in transparent specimen. The phase-shift interferograms was generated by moving a parallel plane plate. Based on analyzing the fringes deflected by deformation and refractive index change, the stress distribution can be obtained. To verify the validity of the proposed method, a typical experiment was elaborately designed to determine thermal residual stresses of a transparent PMMA plate subjected to the flame of a lighter. The sum of in-plane stress distribution was demonstrated. The experimental data were compared with values measured by digital gradient sensing method. Comparison of the results reveals the effectiveness and feasibility of the proposed method.

Research on distributed heterogeneous data PCA algorithm based on cloud platform

NASA Astrophysics Data System (ADS)

Zhang, Jin; Huang, Gang

2018-05-01

Principal component analysis (PCA) of heterogeneous data sets can solve the problem that centralized data scalability is limited. In order to reduce the generation of intermediate data and error components of distributed heterogeneous data sets, a principal component analysis algorithm based on heterogeneous data sets under cloud platform is proposed. The algorithm performs eigenvalue processing by using Householder tridiagonalization and QR factorization to calculate the error component of the heterogeneous database associated with the public key to obtain the intermediate data set and the lost information. Experiments on distributed DBM heterogeneous datasets show that the model method has the feasibility and reliability in terms of execution time and accuracy.

Replication Strategy for Spatiotemporal Data Based on Distributed Caching System

PubMed Central

Xiong, Lian; Tao, Yang; Xu, Juan; Zhao, Lun

2018-01-01

The replica strategy in distributed cache can effectively reduce user access delay and improve system performance. However, developing a replica strategy suitable for varied application scenarios is still quite challenging, owing to differences in user access behavior and preferences. In this paper, a replication strategy for spatiotemporal data (RSSD) based on a distributed caching system is proposed. By taking advantage of the spatiotemporal locality and correlation of user access, RSSD mines high popularity and associated files from historical user access information, and then generates replicas and selects appropriate cache node for placement. Experimental results show that the RSSD algorithm is simple and efficient, and succeeds in significantly reducing user access delay. PMID:29342897

Computation of marginal distributions of peak-heights in electropherograms for analysing single source and mixture STR DNA samples.

PubMed

Cowell, Robert G

2018-05-04

Current models for single source and mixture samples, and probabilistic genotyping software based on them used for analysing STR electropherogram data, assume simple probability distributions, such as the gamma distribution, to model the allelic peak height variability given the initial amount of DNA prior to PCR amplification. Here we illustrate how amplicon number distributions, for a model of the process of sample DNA collection and PCR amplification, may be efficiently computed by evaluating probability generating functions using discrete Fourier transforms. Copyright © 2018 Elsevier B.V. All rights reserved.

Distributed plug-and-play optimal generator and load control for power system frequency regulation

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

Zhao, Changhong; Mallada, Enrique; Low, Steven H.

A distributed control scheme, which can be implemented on generators and controllable loads in a plug-and-play manner, is proposed for power system frequency regulation. The proposed scheme is based on local measurements, local computation, and neighborhood information exchanges over a communication network with an arbitrary (but connected) topology. In the event of a sudden change in generation or load, the proposed scheme can restore the nominal frequency and the reference inter-area power flows, while minimizing the total cost of control for participating generators and loads. Power network stability under the proposed control is proved with a relatively realistic model whichmore » includes nonlinear power flow and a generic (potentially nonlinear or high-order) turbine-governor model, and further with first- and second-order turbine-governor models as special cases. Finally, in simulations, the proposed control scheme shows a comparable performance to the existing automatic generation control (AGC) when implemented only on the generator side, and demonstrates better dynamic characteristics than AGC when each scheme is implemented on both generators and controllable loads. Simulation results also show robustness of the proposed scheme to communication link failure.« less

Distributed plug-and-play optimal generator and load control for power system frequency regulation

DOE PAGES

Zhao, Changhong; Mallada, Enrique; Low, Steven H.; ...

2018-03-14

A distributed control scheme, which can be implemented on generators and controllable loads in a plug-and-play manner, is proposed for power system frequency regulation. The proposed scheme is based on local measurements, local computation, and neighborhood information exchanges over a communication network with an arbitrary (but connected) topology. In the event of a sudden change in generation or load, the proposed scheme can restore the nominal frequency and the reference inter-area power flows, while minimizing the total cost of control for participating generators and loads. Power network stability under the proposed control is proved with a relatively realistic model whichmore » includes nonlinear power flow and a generic (potentially nonlinear or high-order) turbine-governor model, and further with first- and second-order turbine-governor models as special cases. Finally, in simulations, the proposed control scheme shows a comparable performance to the existing automatic generation control (AGC) when implemented only on the generator side, and demonstrates better dynamic characteristics than AGC when each scheme is implemented on both generators and controllable loads. Simulation results also show robustness of the proposed scheme to communication link failure.« less

Real-Time Optimization and Control of Next-Generation Distribution

Science.gov Websites

Infrastructure | Grid Modernization | NREL Real-Time Optimization and Control of Next -Generation Distribution Infrastructure Real-Time Optimization and Control of Next-Generation Distribution Infrastructure This project develops innovative, real-time optimization and control methods for next-generation

Distributed Traffic Complexity Management by Preserving Trajectory Flexibility

NASA Technical Reports Server (NTRS)

Idris, Husni; Vivona, Robert A.; Garcia-Chico, Jose-Luis; Wing, David J.

2007-01-01

In order to handle the expected increase in air traffic volume, the next generation air transportation system is moving towards a distributed control architecture, in which groundbased service providers such as controllers and traffic managers and air-based users such as pilots share responsibility for aircraft trajectory generation and management. This paper presents preliminary research investigating a distributed trajectory-oriented approach to manage traffic complexity, based on preserving trajectory flexibility. The underlying hypotheses are that preserving trajectory flexibility autonomously by aircraft naturally achieves the aggregate objective of avoiding excessive traffic complexity, and that trajectory flexibility is increased by collaboratively minimizing trajectory constraints without jeopardizing the intended air traffic management objectives. This paper presents an analytical framework in which flexibility is defined in terms of robustness and adaptability to disturbances and preliminary metrics are proposed that can be used to preserve trajectory flexibility. The hypothesized impacts are illustrated through analyzing a trajectory solution space in a simple scenario with only speed as a degree of freedom, and in constraint situations involving meeting multiple times of arrival and resolving conflicts.

Domain Regeneration for Cross-Database Micro-Expression Recognition

NASA Astrophysics Data System (ADS)

Zong, Yuan; Zheng, Wenming; Huang, Xiaohua; Shi, Jingang; Cui, Zhen; Zhao, Guoying

2018-05-01

In this paper, we investigate the cross-database micro-expression recognition problem, where the training and testing samples are from two different micro-expression databases. Under this setting, the training and testing samples would have different feature distributions and hence the performance of most existing micro-expression recognition methods may decrease greatly. To solve this problem, we propose a simple yet effective method called Target Sample Re-Generator (TSRG) in this paper. By using TSRG, we are able to re-generate the samples from target micro-expression database and the re-generated target samples would share same or similar feature distributions with the original source samples. For this reason, we can then use the classifier learned based on the labeled source samples to accurately predict the micro-expression categories of the unlabeled target samples. To evaluate the performance of the proposed TSRG method, extensive cross-database micro-expression recognition experiments designed based on SMIC and CASME II databases are conducted. Compared with recent state-of-the-art cross-database emotion recognition methods, the proposed TSRG achieves more promising results.

Dynamic wave field synthesis: enabling the generation of field distributions with a large space-bandwidth product.

PubMed

Kamau, Edwin N; Heine, Julian; Falldorf, Claas; Bergmann, Ralf B

2015-11-02

We present a novel approach for the design and fabrication of multiplexed computer generated volume holograms (CGVH) which allow for a dynamic synthesis of arbitrary wave field distributions. To achieve this goal, we developed a hybrid system that consists of a CGVH as a static element and an electronically addressed spatial light modulator as the dynamic element. We thereby derived a new model for describing the scattering process within the inhomogeneous dielectric material of the hologram. This model is based on the linearization of the scattering process within the Rytov approximation and incorporates physical constraints that account for voxel based laser-lithography using micro-fabrication of the holograms in a nonlinear optical material. In this article we demonstrate that this system basically facilitates a high angular Bragg selectivity on the order of 1°. Additionally, it allows for a qualitatively low cross-talk dynamic synthesis of predefined wave fields with a much larger space-bandwidth product (SBWP ≥ 8.7 × 10(6)) as compared to the current state of the art in computer generated holography.

Enhancing performance of LCoS-SLM as adaptive optics by using computer-generated holograms modulation software

NASA Astrophysics Data System (ADS)

Tsai, Chun-Wei; Lyu, Bo-Han; Wang, Chen; Hung, Cheng-Chieh

2017-05-01

We have already developed multi-function and easy-to-use modulation software that was based on LabVIEW system. There are mainly four functions in this modulation software, such as computer generated holograms (CGH) generation, CGH reconstruction, image trimming, and special phase distribution. Based on the above development of CGH modulation software, we could enhance the performance of liquid crystal on silicon - spatial light modulator (LCoSSLM) as similar as the diffractive optical element (DOE) and use it on various adaptive optics (AO) applications. Through the development of special phase distribution, we are going to use the LCoS-SLM with CGH modulation software into AO technology, such as optical microscope system. When the LCOS-SLM panel is integrated in an optical microscope system, it could be placed on the illumination path or on the image forming path. However, LCOS-SLM provides a program-controllable liquid crystal array for optical microscope. It dynamically changes the amplitude or phase of light and gives the obvious advantage, "Flexibility", to the system

Unsteady loading of a vertical-axis turbine in the interaction with an upstream deflector

NASA Astrophysics Data System (ADS)

Kim, Daegyoum; Gharib, Morteza

2014-01-01

Torque generation and flow distribution of a lift-based vertical-axis turbine with an upstream deflecting plate are investigated in water tunnel experiments. The deployment of a deflector in front of a lift-based turbine is a promising approach to increase local flow velocity and enhance energy conversion efficiency without consideration for complicated control. For the turbine with the deflector, the phase during which the blade passes near the front end of the turbine has a major contribution to torque increase from the case without the deflector. Meanwhile, the deflector can have a negative effect in torque generation at the phase when the blade moves upstream against free stream if the turbine is placed close to the deflector in a crosswise direction. The change of nearby flow distribution by the deflector is also examined to find its correlation with torque generation. When the blade rotates through the near-wake region of the deflector, the blade can collides with the vortical structure shed from the deflector. This interaction causes significant torque fluctuation.

Efficient and universal quantum key distribution based on chaos and middleware

NASA Astrophysics Data System (ADS)

Jiang, Dong; Chen, Yuanyuan; Gu, Xuemei; Xie, Ling; Chen, Lijun

2017-01-01

Quantum key distribution (QKD) promises unconditionally secure communications, however, the low bit rate of QKD cannot meet the requirements of high-speed applications. Despite the many solutions that have been proposed in recent years, they are neither efficient to generate the secret keys nor compatible with other QKD systems. This paper, based on chaotic cryptography and middleware technology, proposes an efficient and universal QKD protocol that can be directly deployed on top of any existing QKD system without modifying the underlying QKD protocol and optical platform. It initially takes the bit string generated by the QKD system as input, periodically updates the chaotic system, and efficiently outputs the bit sequences. Theoretical analysis and simulation results demonstrate that our protocol can efficiently increase the bit rate of the QKD system as well as securely generate bit sequences with perfect statistical properties. Compared with the existing methods, our protocol is more efficient and universal, it can be rapidly deployed on the QKD system to increase the bit rate when the QKD system becomes the bottleneck of its communication system.

Density-based empirical likelihood procedures for testing symmetry of data distributions and K-sample comparisons.

PubMed

Vexler, Albert; Tanajian, Hovig; Hutson, Alan D

In practice, parametric likelihood-ratio techniques are powerful statistical tools. In this article, we propose and examine novel and simple distribution-free test statistics that efficiently approximate parametric likelihood ratios to analyze and compare distributions of K groups of observations. Using the density-based empirical likelihood methodology, we develop a Stata package that applies to a test for symmetry of data distributions and compares K -sample distributions. Recognizing that recent statistical software packages do not sufficiently address K -sample nonparametric comparisons of data distributions, we propose a new Stata command, vxdbel, to execute exact density-based empirical likelihood-ratio tests using K samples. To calculate p -values of the proposed tests, we use the following methods: 1) a classical technique based on Monte Carlo p -value evaluations; 2) an interpolation technique based on tabulated critical values; and 3) a new hybrid technique that combines methods 1 and 2. The third, cutting-edge method is shown to be very efficient in the context of exact-test p -value computations. This Bayesian-type method considers tabulated critical values as prior information and Monte Carlo generations of test statistic values as data used to depict the likelihood function. In this case, a nonparametric Bayesian method is proposed to compute critical values of exact tests.

Distributed optical fiber vibration sensing using phase-generated carrier demodulation algorithm

NASA Astrophysics Data System (ADS)

Yu, Zhihua; Zhang, Qi; Zhang, Mingyu; Dai, Haolong; Zhang, Jingjing; Liu, Li; Zhang, Lijun; Jin, Xing; Wang, Gaifang; Qi, Guang

2018-05-01

A novel optical fiber-distributed vibration-sensing system is proposed, which is based on self-interference of Rayleigh backscattering with phase-generated carrier (PGC) demodulation algorithm. Pulsed lights are sent into the sensing fiber and the Rayleigh backscattering light from a certain position along the sensing fiber would interfere through an unbalanced Michelson interferometry to generate the interference light. An improved PGC demodulation algorithm is carried out to recover the phase information of the interference signal, which carries the sensing information. Three vibration events were applied simultaneously to different positions over 2000 m sensing fiber and demodulated correctly. The spatial resolution is 10 m, and the noise level of the Φ-OTDR system we proposed is about 10-3 rad/\\surd {Hz}, and the signal-to-noise ratio is about 30.34 dB.

Hierarchical dispatch using two-stage optimisation for electricity markets in smart grid

NASA Astrophysics Data System (ADS)

Yang, Jie; Zhang, Guoshan; Ma, Kai

2016-11-01

This paper proposes a hierarchical dispatch method for the electricity markets consisting of wholesale markets and retail markets. In the wholesale markets, the generators and the retailers decide the generation and the purchase according to the market-clearing price. In the retail markets, the retailers set the retail price to adjust the electricity consumption of the consumers. Due to the two-way communications in smart grid, the retailers can decide the electricity purchase from the wholesale markets based on the information on electricity usage of consumers in the retail markets. We establish the hierarchical dispatch model for the wholesale markets and the retail markets and develop distributed algorithms to search for the optimal generation, purchase, and consumption. Numerical results show the balance between the supply and demand, the profits of the retailers, and the convergence of the distributed algorithms.

Alternative power supply systems for remote industrial customers

NASA Astrophysics Data System (ADS)

Kharlamova, N. V.; Khalyasmaa, A. I.; Eroshenko, S. A.

2017-06-01

The paper addresses the problem of alternative power supply of remote industrial clusters with renewable electric energy generation. As a result of different technologies comparison, consideration is given to wind energy application. The authors present a methodology of mean expected wind generation output calculation, based on Weibull distribution, which provides an effective express-tool for preliminary assessment of required installed generation capacity. The case study is based on real data including database of meteorological information, relief characteristics, power system topology etc. Wind generation feasibility estimation for a specific territory is followed by power flow calculations using Monte Carlo methodology. Finally, the paper provides a set of recommendations to ensure safe and reliable power supply for the final customers and, subsequently, to provide sustainable development of the regions, located far from megalopolises and industrial centres.

A Comparison of Forecast Error Generators for Modeling Wind and Load Uncertainty

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

Lu, Ning; Diao, Ruisheng; Hafen, Ryan P.

2013-12-18

This paper presents four algorithms to generate random forecast error time series, including a truncated-normal distribution model, a state-space based Markov model, a seasonal autoregressive moving average (ARMA) model, and a stochastic-optimization based model. The error time series are used to create real-time (RT), hour-ahead (HA), and day-ahead (DA) wind and load forecast time series that statistically match historically observed forecasting data sets, used for variable generation integration studies. A comparison is made using historical DA load forecast and actual load values to generate new sets of DA forecasts with similar stoical forecast error characteristics. This paper discusses and comparesmore » the capabilities of each algorithm to preserve the characteristics of the historical forecast data sets.« less

Parallel grid generation algorithm for distributed memory computers

NASA Technical Reports Server (NTRS)

Moitra, Stuti; Moitra, Anutosh

1994-01-01

A parallel grid-generation algorithm and its implementation on the Intel iPSC/860 computer are described. The grid-generation scheme is based on an algebraic formulation of homotopic relations. Methods for utilizing the inherent parallelism of the grid-generation scheme are described, and implementation of multiple levELs of parallelism on multiple instruction multiple data machines are indicated. The algorithm is capable of providing near orthogonality and spacing control at solid boundaries while requiring minimal interprocessor communications. Results obtained on the Intel hypercube for a blended wing-body configuration are used to demonstrate the effectiveness of the algorithm. Fortran implementations bAsed on the native programming model of the iPSC/860 computer and the Express system of software tools are reported. Computational gains in execution time speed-up ratios are given.

Classification of Complete Proteomes of Different Organisms and Protein Sets Based on Their Protein Distributions in Terms of Some Key Attributes of Proteins

PubMed Central

Ma, Yue; Tuskan, Gerald A.

2018-01-01

The existence of complete genome sequences makes it important to develop different approaches for classification of large-scale data sets and to make extraction of biological insights easier. Here, we propose an approach for classification of complete proteomes/protein sets based on protein distributions on some basic attributes. We demonstrate the usefulness of this approach by determining protein distributions in terms of two attributes: protein lengths and protein intrinsic disorder contents (ID). The protein distributions based on L and ID are surveyed for representative proteome organisms and protein sets from the three domains of life. The two-dimensional maps (designated as fingerprints here) from the protein distribution densities in the LD space defined by ln(L) and ID are then constructed. The fingerprints for different organisms and protein sets are found to be distinct with each other, and they can therefore be used for comparative studies. As a test case, phylogenetic trees have been constructed based on the protein distribution densities in the fingerprints of proteomes of organisms without performing any protein sequence comparison and alignments. The phylogenetic trees generated are biologically meaningful, demonstrating that the protein distributions in the LD space may serve as unique phylogenetic signals of the organisms at the proteome level. PMID:29686995

High-power, cladding-pumped all-fiber laser with selective transverse mode generation property.

PubMed

Li, Lei; Wang, Meng; Liu, Tong; Leng, Jinyong; Zhou, Pu; Chen, Jinbao

2017-06-10

We demonstrate, to the best of our knowledge, the first cladding-pumped all-fiber oscillator configuration with selective transverse mode generation based on a mode-selective fiber Bragg grating pair. Operating in the second-order (LP 11 ) mode, maximum output power of 4.2 W is obtained with slope efficiency of about 38%. This is the highest reported output power of single higher-order transverse mode generation in an all-fiber configuration. The intensity distribution profile and spectral evolution have also been investigated in this paper. Our work suggests the potential of realizing higher power with selective transverse mode operation based on a mode-selective fiber Bragg grating pair.

Simulation-based estimation of mean and standard deviation for meta-analysis via Approximate Bayesian Computation (ABC).

PubMed

Kwon, Deukwoo; Reis, Isildinha M

2015-08-12

When conducting a meta-analysis of a continuous outcome, estimated means and standard deviations from the selected studies are required in order to obtain an overall estimate of the mean effect and its confidence interval. If these quantities are not directly reported in the publications, they must be estimated from other reported summary statistics, such as the median, the minimum, the maximum, and quartiles. We propose a simulation-based estimation approach using the Approximate Bayesian Computation (ABC) technique for estimating mean and standard deviation based on various sets of summary statistics found in published studies. We conduct a simulation study to compare the proposed ABC method with the existing methods of Hozo et al. (2005), Bland (2015), and Wan et al. (2014). In the estimation of the standard deviation, our ABC method performs better than the other methods when data are generated from skewed or heavy-tailed distributions. The corresponding average relative error (ARE) approaches zero as sample size increases. In data generated from the normal distribution, our ABC performs well. However, the Wan et al. method is best for estimating standard deviation under normal distribution. In the estimation of the mean, our ABC method is best regardless of assumed distribution. ABC is a flexible method for estimating the study-specific mean and standard deviation for meta-analysis, especially with underlying skewed or heavy-tailed distributions. The ABC method can be applied using other reported summary statistics such as the posterior mean and 95 % credible interval when Bayesian analysis has been employed.

Ince-gauss based multiple intermodal phase-matched third-harmonic generations in a step-index silica optical fiber

NASA Astrophysics Data System (ADS)

Borne, Adrien; Katsura, Tomotaka; Félix, Corinne; Doppagne, Benjamin; Segonds, Patricia; Bencheikh, Kamel; Levenson, Juan Ariel; Boulanger, Benoit

2016-01-01

Several third-harmonic generation processes were performed in a single step-index germanium-doped silica optical fiber under intermodal phase-matching conditions. The nanosecond fundamental beam range between 1400 and 1600 nm. The transverse distributions of the energy were successfully modeled in the form of Ince-Gauss modes, pointing out some ellipticity of fiber core. From these experiments and theoretical calculations, we discuss the implementation of frequency degenerated triple photon generation that shares the same phase-matching condition as third-harmonic generation, which is its reverse process.

ChemScreener: A Distributed Computing Tool for Scaffold based Virtual Screening.

PubMed

Karthikeyan, Muthukumarasamy; Pandit, Deepak; Vyas, Renu

2015-01-01

In this work we present ChemScreener, a Java-based application to perform virtual library generation combined with virtual screening in a platform-independent distributed computing environment. ChemScreener comprises a scaffold identifier, a distinct scaffold extractor, an interactive virtual library generator as well as a virtual screening module for subsequently selecting putative bioactive molecules. The virtual libraries are annotated with chemophore-, pharmacophore- and toxicophore-based information for compound prioritization. The hits selected can then be further processed using QSAR, docking and other in silico approaches which can all be interfaced within the ChemScreener framework. As a sample application, in this work scaffold selectivity, diversity, connectivity and promiscuity towards six important therapeutic classes have been studied. In order to illustrate the computational power of the application, 55 scaffolds extracted from 161 anti-psychotic compounds were enumerated to produce a virtual library comprising 118 million compounds (17 GB) and annotated with chemophore, pharmacophore and toxicophore based features in a single step which would be non-trivial to perform with many standard software tools today on libraries of this size.

Distributed Propulsion Vehicles

NASA Technical Reports Server (NTRS)

Kim, Hyun Dae

2010-01-01

Since the introduction of large jet-powered transport aircraft, the majority of these vehicles have been designed by placing thrust-generating engines either under the wings or on the fuselage to minimize aerodynamic interactions on the vehicle operation. However, advances in computational and experimental tools along with new technologies in materials, structures, and aircraft controls, etc. are enabling a high degree of integration of the airframe and propulsion system in aircraft design. The National Aeronautics and Space Administration (NASA) has been investigating a number of revolutionary distributed propulsion vehicle concepts to increase aircraft performance. The concept of distributed propulsion is to fully integrate a propulsion system within an airframe such that the aircraft takes full synergistic benefits of coupling of airframe aerodynamics and the propulsion thrust stream by distributing thrust using many propulsors on the airframe. Some of the concepts are based on the use of distributed jet flaps, distributed small multiple engines, gas-driven multi-fans, mechanically driven multifans, cross-flow fans, and electric fans driven by turboelectric generators. This paper describes some early concepts of the distributed propulsion vehicles and the current turboelectric distributed propulsion (TeDP) vehicle concepts being studied under the NASA s Subsonic Fixed Wing (SFW) Project to drastically reduce aircraft-related fuel burn, emissions, and noise by the year 2030 to 2035.

Technology Solutions | Distributed Generation Interconnection Collaborative

Science.gov Websites

technologies, both hardware and software, can support the wider adoption of distributed generation on the grid . As the penetration of distributed-generation photovoltaics (DGPV) has risen rapidly in recent years posed by high penetrations of distributed PV. Other promising technologies include new utility software

Efficient generation of 1.9  W yellow light by cascaded frequency doubling of a distributed Bragg reflector tapered diode.

PubMed

Hansen, A K; Christensen, M; Noordegraaf, D; Heist, P; Papastathopoulos, E; Loyo-Maldonado, V; Jensen, O B; Skovgaard, P M W

2016-11-10

Watt-level yellow emitting lasers are interesting for medical applications, due to their high hemoglobin absorption, and for efficient detection of certain fluorophores. In this paper, we demonstrate a compact and robust diode-based laser system in the yellow spectral range. The system generates 1.9 W of single-frequency light at 562.4 nm by cascaded single-pass frequency doubling of the 1124.8 nm emission from a distributed Bragg reflector (DBR) tapered laser diode. The absence of a free-space cavity makes the system stable over a base-plate temperature range of 30 K. At the same time, the use of a laser diode enables the modulation of the pump wavelength by controlling the drive current. This is utilized to achieve a power modulation depth above 90% for the second harmonic light, with a rise time below 40  μs.

Optimal threshold of error decision related to non-uniform phase distribution QAM signals generated from MZM based on OCS

NASA Astrophysics Data System (ADS)

Han, Xifeng; Zhou, Wen

2018-03-01

Optical vector radio-frequency (RF) signal generation based on optical carrier suppression (OCS) in one Mach-Zehnder modulator (MZM) can realize frequency-doubling. In order to match the phase or amplitude of the recovered quadrature amplitude modulation (QAM) signal, phase or amplitude pre-coding is necessary in the transmitter side. The detected QAM signals usually have one non-uniform phase distribution after square-law detection at the photodiode because of the imperfect characteristics of the optical and electrical devices. We propose to use optimal threshold of error decision for non-uniform phase contribution to reduce the bit error rate (BER). By employing this scheme, the BER of 16 Gbaud (32 Gbit/s) quadrature-phase-shift-keying (QPSK) millimeter wave signal at 36 GHz is improved from 1 × 10-3 to 1 × 10-4 at - 4 . 6 dBm input power into the photodiode.

Self-organizing maps: a versatile tool for the automatic analysis of untargeted imaging datasets.

PubMed

Franceschi, Pietro; Wehrens, Ron

2014-04-01

MS-based imaging approaches allow for location-specific identification of chemical components in biological samples, opening up possibilities of much more detailed understanding of biological processes and mechanisms. Data analysis, however, is challenging, mainly because of the sheer size of such datasets. This article presents a novel approach based on self-organizing maps, extending previous work in order to be able to handle the large number of variables present in high-resolution mass spectra. The key idea is to generate prototype images, representing spatial distributions of ions, rather than prototypical mass spectra. This allows for a two-stage approach, first generating typical spatial distributions and associated m/z bins, and later analyzing the interesting bins in more detail using accurate masses. The possibilities and advantages of the new approach are illustrated on an in-house dataset of apple slices. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A distributed parameter model of transmission line transformer for high voltage nanosecond pulse generation

NASA Astrophysics Data System (ADS)

Li, Jiangtao; Zhao, Zheng; Li, Longjie; He, Jiaxin; Li, Chenjie; Wang, Yifeng; Su, Can

2017-09-01

A transmission line transformer has potential advantages for nanosecond pulse generation including excellent frequency response and no leakage inductance. The wave propagation process in a secondary mode line is indispensable due to an obvious inside transient electromagnetic transition in this scenario. The equivalent model of the transmission line transformer is crucial for predicting the output waveform and evaluating the effects of magnetic cores on output performance. However, traditional lumped parameter models are not sufficient for nanosecond pulse generation due to the natural neglect of wave propagations in secondary mode lines based on a lumped parameter assumption. In this paper, a distributed parameter model of transmission line transformer was established to investigate wave propagation in the secondary mode line and its influential factors through theoretical analysis and experimental verification. The wave propagation discontinuity in the secondary mode line induced by magnetic cores is emphasized. Characteristics of the magnetic core under a nanosecond pulse were obtained by experiments. Distribution and formation of the secondary mode current were determined for revealing essential wave propagation processes in secondary mode lines. The output waveform and efficiency were found to be affected dramatically by wave propagation discontinuity in secondary mode lines induced by magnetic cores. The proposed distributed parameter model was proved more suitable for nanosecond pulse generation in aspects of secondary mode current, output efficiency, and output waveform. In depth, comprehension of underlying mechanisms and a broader view of the working principle of the transmission line transformer for nanosecond pulse generation can be obtained through this research.

A distributed parameter model of transmission line transformer for high voltage nanosecond pulse generation.

PubMed

Li, Jiangtao; Zhao, Zheng; Li, Longjie; He, Jiaxin; Li, Chenjie; Wang, Yifeng; Su, Can

2017-09-01

A transmission line transformer has potential advantages for nanosecond pulse generation including excellent frequency response and no leakage inductance. The wave propagation process in a secondary mode line is indispensable due to an obvious inside transient electromagnetic transition in this scenario. The equivalent model of the transmission line transformer is crucial for predicting the output waveform and evaluating the effects of magnetic cores on output performance. However, traditional lumped parameter models are not sufficient for nanosecond pulse generation due to the natural neglect of wave propagations in secondary mode lines based on a lumped parameter assumption. In this paper, a distributed parameter model of transmission line transformer was established to investigate wave propagation in the secondary mode line and its influential factors through theoretical analysis and experimental verification. The wave propagation discontinuity in the secondary mode line induced by magnetic cores is emphasized. Characteristics of the magnetic core under a nanosecond pulse were obtained by experiments. Distribution and formation of the secondary mode current were determined for revealing essential wave propagation processes in secondary mode lines. The output waveform and efficiency were found to be affected dramatically by wave propagation discontinuity in secondary mode lines induced by magnetic cores. The proposed distributed parameter model was proved more suitable for nanosecond pulse generation in aspects of secondary mode current, output efficiency, and output waveform. In depth, comprehension of underlying mechanisms and a broader view of the working principle of the transmission line transformer for nanosecond pulse generation can be obtained through this research.

Generation of dark hollow femtosecond pulsed beam by phase-only liquid crystal spatial light modulator

NASA Astrophysics Data System (ADS)

Nie, Yongming; Ma, Haotong; Li, Xiujian; Hu, Wenhua; Yang, Jiankun

2011-07-01

Based on the refractive laser beam shaping system, the dark hollow femtosecond pulse beam shaping technique with a phase-only liquid crystal spatial light modulator (LC-SLM) is demonstrated. The phase distribution of the LC-SLM is derived by the energy conservation and constant optical path principle. The effects of the shaping system on the temporal properties, including spectral phase distribution and bandwidth of the femtosecond pulse, are analyzed in detail. Experimental results show that the hollow intensity distribution of the output pulsed beam can be maintained much at more than 1200mm. The spectral phase of the pulse is changed, and the pulse width is expanded from 199 to 230fs, which is caused by the spatial--temporal coupling effect. The coupling effect mainly depends on the phase-only LC-SLM itself, not on its loaded phase distribution. The experimental results indicate that the proposed shaping setup can generate a dark hollow femtosecond pulsed beam effectively, because the temporal Gaussian waveform is unchanged.

A Framework for the Evaluation of the Cost and Benefits of Microgrids

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

Morris, Greg Young; Abbey, Chad; Joos, Geza

2011-07-15

A Microgrid is recognized as an innovative technology to help integrate renewables into distribution systems and to provide additional benefits to a variety of stakeholders, such as offsetting infrastructure investments and improving the reliability of the local system. However, these systems require additional investments for control infrastructure, and as such, additional costs and the anticipated benefits need to be quantified in order to determine whether the investment is economically feasible. This paper proposes a methodology for systematizing and representing benefits and their interrelationships based on the UML Use Case paradigm, which allows complex systems to be represented in a concise,more » elegant format. This methodology is demonstrated by determining the economic feasibility of a Microgrid and Distributed Generation installed on a typical Canadian rural distribution system model as a case study. The study attempts to minimize the cost of energy served to the community, considering the fixed costs associated with Microgrids and Distributed Generation, and suggests benefits to a variety of stakeholders.« less

Providing Limited Local Electric Service During a Major Grid Outage: A First Assessment Based on Customer Willingness to Pay.

PubMed

Baik, Sunhee; Morgan, M Granger; Davis, Alexander L

2018-02-01

While they are rare, widespread blackouts of the bulk power system can result in large costs to individuals and society. If local distribution circuits remain intact, it is possible to use new technologies including smart meters, intelligent switches that can change the topology of distribution circuits, and distributed generation owned by customers and the power company, to provide limited local electric power service. Many utilities are already making investments that would make this possible. We use customers' measured willingness to pay to explore when the incremental investments needed to implement these capabilities would be justified. Under many circumstances, upgrades in advanced distribution systems could be justified for a customer charge of less than a dollar a month (plus the cost of electricity used during outages), and would be less expensive and safer than the proliferation of small portable backup generators. We also discuss issues of social equity, extreme events, and various sources of underlying uncertainty. © 2017 Society for Risk Analysis.

Integrated Joule switches for the control of current dynamics in parallel superconducting strips

NASA Astrophysics Data System (ADS)

Casaburi, A.; Heath, R. M.; Cristiano, R.; Ejrnaes, M.; Zen, N.; Ohkubo, M.; Hadfield, R. H.

2018-06-01

Understanding and harnessing the physics of the dynamic current distribution in parallel superconducting strips holds the key to creating next generation sensors for single molecule and single photon detection. Non-uniformity in the current distribution in parallel superconducting strips leads to low detection efficiency and unstable operation, preventing the scale up to large area sensors. Recent studies indicate that non-uniform current distributions occurring in parallel strips can be understood and modeled in the framework of the generalized London model. Here we build on this important physical insight, investigating an innovative design with integrated superconducting-to-resistive Joule switches to break the superconducting loops between the strips and thus control the current dynamics. Employing precision low temperature nano-optical techniques, we map the uniformity of the current distribution before- and after the resistive strip switching event, confirming the effectiveness of our design. These results provide important insights for the development of next generation large area superconducting strip-based sensors.

End-to-end distance and contour length distribution functions of DNA helices

NASA Astrophysics Data System (ADS)

Zoli, Marco

2018-06-01

I present a computational method to evaluate the end-to-end and the contour length distribution functions of short DNA molecules described by a mesoscopic Hamiltonian. The method generates a large statistical ensemble of possible configurations for each dimer in the sequence, selects the global equilibrium twist conformation for the molecule, and determines the average base pair distances along the molecule backbone. Integrating over the base pair radial and angular fluctuations, I derive the room temperature distribution functions as a function of the sequence length. The obtained values for the most probable end-to-end distance and contour length distance, providing a measure of the global molecule size, are used to examine the DNA flexibility at short length scales. It is found that, also in molecules with less than ˜60 base pairs, coiled configurations maintain a large statistical weight and, consistently, the persistence lengths may be much smaller than in kilo-base DNA.

A cloud-based X73 ubiquitous mobile healthcare system: design and implementation.

PubMed

Ji, Zhanlin; Ganchev, Ivan; O'Droma, Máirtín; Zhang, Xin; Zhang, Xueji

2014-01-01

Based on the user-centric paradigm for next generation networks, this paper describes a ubiquitous mobile healthcare (uHealth) system based on the ISO/IEEE 11073 personal health data (PHD) standards (X73) and cloud computing techniques. A number of design issues associated with the system implementation are outlined. The system includes a middleware on the user side, providing a plug-and-play environment for heterogeneous wireless sensors and mobile terminals utilizing different communication protocols and a distributed "big data" processing subsystem in the cloud. The design and implementation of this system are envisaged as an efficient solution for the next generation of uHealth systems.

Uncertainties of flood frequency estimation approaches based on continuous simulation using data resampling

NASA Astrophysics Data System (ADS)

Arnaud, Patrick; Cantet, Philippe; Odry, Jean

2017-11-01

Flood frequency analyses (FFAs) are needed for flood risk management. Many methods exist ranging from classical purely statistical approaches to more complex approaches based on process simulation. The results of these methods are associated with uncertainties that are sometimes difficult to estimate due to the complexity of the approaches or the number of parameters, especially for process simulation. This is the case of the simulation-based FFA approach called SHYREG presented in this paper, in which a rainfall generator is coupled with a simple rainfall-runoff model in an attempt to estimate the uncertainties due to the estimation of the seven parameters needed to estimate flood frequencies. The six parameters of the rainfall generator are mean values, so their theoretical distribution is known and can be used to estimate the generator uncertainties. In contrast, the theoretical distribution of the single hydrological model parameter is unknown; consequently, a bootstrap method is applied to estimate the calibration uncertainties. The propagation of uncertainty from the rainfall generator to the hydrological model is also taken into account. This method is applied to 1112 basins throughout France. Uncertainties coming from the SHYREG method and from purely statistical approaches are compared, and the results are discussed according to the length of the recorded observations, basin size and basin location. Uncertainties of the SHYREG method decrease as the basin size increases or as the length of the recorded flow increases. Moreover, the results show that the confidence intervals of the SHYREG method are relatively small despite the complexity of the method and the number of parameters (seven). This is due to the stability of the parameters and takes into account the dependence of uncertainties due to the rainfall model and the hydrological calibration. Indeed, the uncertainties on the flow quantiles are on the same order of magnitude as those associated with the use of a statistical law with two parameters (here generalised extreme value Type I distribution) and clearly lower than those associated with the use of a three-parameter law (here generalised extreme value Type II distribution). For extreme flood quantiles, the uncertainties are mostly due to the rainfall generator because of the progressive saturation of the hydrological model.

RandomSpot: A web-based tool for systematic random sampling of virtual slides.

PubMed

Wright, Alexander I; Grabsch, Heike I; Treanor, Darren E

2015-01-01

This paper describes work presented at the Nordic Symposium on Digital Pathology 2014, Linköping, Sweden. Systematic random sampling (SRS) is a stereological tool, which provides a framework to quickly build an accurate estimation of the distribution of objects or classes within an image, whilst minimizing the number of observations required. RandomSpot is a web-based tool for SRS in stereology, which systematically places equidistant points within a given region of interest on a virtual slide. Each point can then be visually inspected by a pathologist in order to generate an unbiased sample of the distribution of classes within the tissue. Further measurements can then be derived from the distribution, such as the ratio of tumor to stroma. RandomSpot replicates the fundamental principle of traditional light microscope grid-shaped graticules, with the added benefits associated with virtual slides, such as facilitated collaboration and automated navigation between points. Once the sample points have been added to the region(s) of interest, users can download the annotations and view them locally using their virtual slide viewing software. Since its introduction, RandomSpot has been used extensively for international collaborative projects, clinical trials and independent research projects. So far, the system has been used to generate over 21,000 sample sets, and has been used to generate data for use in multiple publications, identifying significant new prognostic markers in colorectal, upper gastro-intestinal and breast cancer. Data generated using RandomSpot also has significant value for training image analysis algorithms using sample point coordinates and pathologist classifications.

Modular architectures for quantum networks

NASA Astrophysics Data System (ADS)

Pirker, A.; Wallnöfer, J.; Dür, W.

2018-05-01

We consider the problem of generating multipartite entangled states in a quantum network upon request. We follow a top-down approach, where the required entanglement is initially present in the network in form of network states shared between network devices, and then manipulated in such a way that the desired target state is generated. This minimizes generation times, and allows for network structures that are in principle independent of physical links. We present a modular and flexible architecture, where a multi-layer network consists of devices of varying complexity, including quantum network routers, switches and clients, that share certain resource states. We concentrate on the generation of graph states among clients, which are resources for numerous distributed quantum tasks. We assume minimal functionality for clients, i.e. they do not participate in the complex and distributed generation process of the target state. We present architectures based on shared multipartite entangled Greenberger–Horne–Zeilinger states of different size, and fully connected decorated graph states, respectively. We compare the features of these architectures to an approach that is based on bipartite entanglement, and identify advantages of the multipartite approach in terms of memory requirements and complexity of state manipulation. The architectures can handle parallel requests, and are designed in such a way that the network state can be dynamically extended if new clients or devices join the network. For generation or dynamical extension of the network states, we propose a quantum network configuration protocol, where entanglement purification is used to establish high fidelity states. The latter also allows one to show that the entanglement generated among clients is private, i.e. the network is secure.

General advancing front packing algorithm for the discrete element method

NASA Astrophysics Data System (ADS)

Morfa, Carlos A. Recarey; Pérez Morales, Irvin Pablo; de Farias, Márcio Muniz; de Navarra, Eugenio Oñate Ibañez; Valera, Roberto Roselló; Casañas, Harold Díaz-Guzmán

2018-01-01

A generic formulation of a new method for packing particles is presented. It is based on a constructive advancing front method, and uses Monte Carlo techniques for the generation of particle dimensions. The method can be used to obtain virtual dense packings of particles with several geometrical shapes. It employs continuous, discrete, and empirical statistical distributions in order to generate the dimensions of particles. The packing algorithm is very flexible and allows alternatives for: 1—the direction of the advancing front (inwards or outwards), 2—the selection of the local advancing front, 3—the method for placing a mobile particle in contact with others, and 4—the overlap checks. The algorithm also allows obtaining highly porous media when it is slightly modified. The use of the algorithm to generate real particle packings from grain size distribution curves, in order to carry out engineering applications, is illustrated. Finally, basic applications of the algorithm, which prove its effectiveness in the generation of a large number of particles, are carried out.

How education systems shape cross-national ethnic inequality in math competence scores: Moving beyond mean differences.

PubMed

Spörlein, Christoph; Schlueter, Elmar

2018-01-01

Here we examine a conceptualization of immigrant assimilation that is based on the more general notion that distributional differences erode across generations. We explore this idea by reinvestigating the efficiency-equality trade-off hypothesis, which posits that stratified education systems educate students more efficiently at the cost of increasing inequality in overall levels of competence. In the context of ethnic inequality in math achievement, this study explores the extent to which an education system's characteristics are associated with ethnic inequality in terms of both the group means and group variances in achievement. Based on data from the 2012 PISA and mixed-effect location scale models, our analyses revealed two effects: on average, minority students had lower math scores than majority students, and minority students' scores were more concentrated at the lower end of the distribution. However, the ethnic inequality in the distribution of scores declined across generations. We did not find compelling evidence that stratified education systems increase mean differences in competency between minority and majority students. However, our analyses revealed that in countries with early educational tracking, minority students' math scores tended to cluster at the lower end of the distribution, regardless of compositional and school differences between majority and minority students.

How education systems shape cross-national ethnic inequality in math competence scores: Moving beyond mean differences

PubMed Central

Spörlein, Christoph

2018-01-01

Here we examine a conceptualization of immigrant assimilation that is based on the more general notion that distributional differences erode across generations. We explore this idea by reinvestigating the efficiency-equality trade-off hypothesis, which posits that stratified education systems educate students more efficiently at the cost of increasing inequality in overall levels of competence. In the context of ethnic inequality in math achievement, this study explores the extent to which an education system’s characteristics are associated with ethnic inequality in terms of both the group means and group variances in achievement. Based on data from the 2012 PISA and mixed-effect location scale models, our analyses revealed two effects: on average, minority students had lower math scores than majority students, and minority students’ scores were more concentrated at the lower end of the distribution. However, the ethnic inequality in the distribution of scores declined across generations. We did not find compelling evidence that stratified education systems increase mean differences in competency between minority and majority students. However, our analyses revealed that in countries with early educational tracking, minority students’ math scores tended to cluster at the lower end of the distribution, regardless of compositional and school differences between majority and minority students. PMID:29494677

Investigation on magnetoacoustic signal generation with magnetic induction and its application to electrical conductivity reconstruction.

PubMed

Ma, Qingyu; He, Bin

2007-08-21

A theoretical study on the magnetoacoustic signal generation with magnetic induction and its applications to electrical conductivity reconstruction is conducted. An object with a concentric cylindrical geometry is located in a static magnetic field and a pulsed magnetic field. Driven by Lorentz force generated by the static magnetic field, the magnetically induced eddy current produces acoustic vibration and the propagated sound wave is received by a transducer around the object to reconstruct the corresponding electrical conductivity distribution of the object. A theory on the magnetoacoustic waveform generation for a circular symmetric model is provided as a forward problem. The explicit formulae and quantitative algorithm for the electrical conductivity reconstruction are then presented as an inverse problem. Computer simulations were conducted to test the proposed theory and assess the performance of the inverse algorithms for a multi-layer cylindrical model. The present simulation results confirm the validity of the proposed theory and suggest the feasibility of reconstructing electrical conductivity distribution based on the proposed theory on the magnetoacoustic signal generation with magnetic induction.

Advanced Unstructured Grid Generation for Complex Aerodynamic Applications

NASA Technical Reports Server (NTRS)

Pirzadeh, Shahyar Z.

2008-01-01

A new approach for distribution of grid points on the surface and in the volume has been developed and implemented in the NASA unstructured grid generation code VGRID. In addition to the point and line sources of prior work, the new approach utilizes surface and volume sources for automatic curvature-based grid sizing and convenient point distribution in the volume. A new exponential growth function produces smoother and more efficient grids and provides superior control over distribution of grid points in the field. All types of sources support anisotropic grid stretching which not only improves the grid economy but also provides more accurate solutions for certain aerodynamic applications. The new approach does not require a three-dimensional background grid as in the previous methods. Instead, it makes use of an efficient bounding-box auxiliary medium for storing grid parameters defined by surface sources. The new approach is less memory-intensive and more efficient computationally. The grids generated with the new method either eliminate the need for adaptive grid refinement for certain class of problems or provide high quality initial grids that would enhance the performance of many adaptation methods.

On predicting receptivity to surface roughness in a compressible infinite swept wing boundary layer

NASA Astrophysics Data System (ADS)

Thomas, Christian; Mughal, Shahid; Ashworth, Richard

2017-03-01

The receptivity of crossflow disturbances on an infinite swept wing is investigated using solutions of the adjoint linearised Navier-Stokes equations. The adjoint based method for predicting the magnitude of stationary disturbances generated by randomly distributed surface roughness is described, with the analysis extended to include both surface curvature and compressible flow effects. Receptivity is predicted for a broad spectrum of spanwise wavenumbers, variable freestream Reynolds numbers, and subsonic Mach numbers. Curvature is found to play a significant role in the receptivity calculations, while compressible flow effects are only found to marginally affect the initial size of the crossflow instability. A Monte Carlo type analysis is undertaken to establish the mean amplitude and variance of crossflow disturbances generated by the randomly distributed surface roughness. Mean amplitudes are determined for a range of flow parameters that are maximised for roughness distributions containing a broad spectrum of roughness wavelengths, including those that are most effective in generating stationary crossflow disturbances. A control mechanism is then developed where the short scale roughness wavelengths are damped, leading to significant reductions in the receptivity amplitude.

Sparse Reconstruction for Temperature Distribution Using DTS Fiber Optic Sensors with Applications in Electrical Generator Stator Monitoring.

PubMed

Bazzo, João Paulo; Pipa, Daniel Rodrigues; da Silva, Erlon Vagner; Martelli, Cicero; Cardozo da Silva, Jean Carlos

2016-09-07

This paper presents an image reconstruction method to monitor the temperature distribution of electric generator stators. The main objective is to identify insulation failures that may arise as hotspots in the structure. The method is based on temperature readings of fiber optic distributed sensors (DTS) and a sparse reconstruction algorithm. Thermal images of the structure are formed by appropriately combining atoms of a dictionary of hotspots, which was constructed by finite element simulation with a multi-physical model. Due to difficulties for reproducing insulation faults in real stator structure, experimental tests were performed using a prototype similar to the real structure. The results demonstrate the ability of the proposed method to reconstruct images of hotspots with dimensions down to 15 cm, representing a resolution gain of up to six times when compared to the DTS spatial resolution. In addition, satisfactory results were also obtained to detect hotspots with only 5 cm. The application of the proposed algorithm for thermal imaging of generator stators can contribute to the identification of insulation faults in early stages, thereby avoiding catastrophic damage to the structure.

Nuclear Forensics Analysis with Missing and Uncertain Data

DOE PAGES

Langan, Roisin T.; Archibald, Richard K.; Lamberti, Vincent

2015-10-05

We have applied a new imputation-based method for analyzing incomplete data, called Monte Carlo Bayesian Database Generation (MCBDG), to the Spent Fuel Isotopic Composition (SFCOMPO) database. About 60% of the entries are absent for SFCOMPO. The method estimates missing values of a property from a probability distribution created from the existing data for the property, and then generates multiple instances of the completed database for training a machine learning algorithm. Uncertainty in the data is represented by an empirical or an assumed error distribution. The method makes few assumptions about the underlying data, and compares favorably against results obtained bymore » replacing missing information with constant values.« less

Experimental validation of a distribution theory based analysis of the effect of manufacturing tolerances on permanent magnet synchronous machines

NASA Astrophysics Data System (ADS)

Boscaino, V.; Cipriani, G.; Di Dio, V.; Corpora, M.; Curto, D.; Franzitta, V.; Trapanese, M.

2017-05-01

An experimental study on the effect of permanent magnet tolerances on the performances of a Tubular Linear Ferrite Motor is presented in this paper. The performances that have been investigated are: cogging force, end effect cogging force and generated thrust. It is demonstrated that: 1) the statistical variability of the magnets introduces harmonics in the spectrum of the cogging force; 2) the value of the end effect cogging force is directly linked to the values of then remanence field of the external magnets placed on the slider; 3) the generated thrust and its statistical distribution depend on the remanence field of the magnets placed on the translator.

Large-scale anisotropy of the cosmic microwave background radiation

NASA Technical Reports Server (NTRS)

Silk, J.; Wilson, M. L.

1981-01-01

Inhomogeneities in the large-scale distribution of matter inevitably lead to the generation of large-scale anisotropy in the cosmic background radiation. The dipole, quadrupole, and higher order fluctuations expected in an Einstein-de Sitter cosmological model have been computed. The dipole and quadrupole anisotropies are comparable to the measured values, and impose important constraints on the allowable spectrum of large-scale matter density fluctuations. A significant dipole anisotropy is generated by the matter distribution on scales greater than approximately 100 Mpc. The large-scale anisotropy is insensitive to the ionization history of the universe since decoupling, and cannot easily be reconciled with a galaxy formation theory that is based on primordial adiabatic density fluctuations.

Co-generation and innovative heat storage systems in small-medium CSP plants for distributed energy production

NASA Astrophysics Data System (ADS)

Giaconia, Alberto; Montagnino, Fabio; Paredes, Filippo; Donato, Filippo; Caputo, Giampaolo; Mazzei, Domenico

2017-06-01

CSP technologies can be applied for distributed energy production, on small-medium plants (on the 1 MW scale), to satisfy the needs of local communities, buildings and districts. In this perspective, reliable, low-cost, and flexible small/medium multi-generative CSP plants should be developed. Four pilot plants have been built in four Mediterranean countries (Cyprus, Egypt, Jordan, and Italy) to demonstrate the approach. In this paper, the plant built in Italy is presented, with specific innovations applied in the linear Fresnel collector design and the Thermal Energy Storage (TES) system, based on a single the use of molten salts but specifically tailored for small scale plants.

Distributions of topological observables in inclusive three- and four-jet events in pp collisions at

NASA Astrophysics Data System (ADS)

Khachatryan, V.; Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Bergauer, T.; Dragicevic, M.; Erö, J.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Hartl, C.; Hörmann, N.; Hrubec, J.; Jeitler, M.; Kiesenhofer, W.; Knünz, V.; Krammer, M.; Krätschmer, I.; Liko, D.; Mikulec, I.; Rabady, D.; Rahbaran, B.; Rohringer, H.; Schöfbeck, R.; Strauss, J.; Treberer-Treberspurg, W.; Waltenberger, W.; Wulz, C.-E.; Mossolov, V.; Shumeiko, N.; Suarez Gonzalez, J.; Alderweireldt, S.; Bansal, S.; Cornelis, T.; De Wolf, E. A.; Janssen, X.; Knutsson, A.; Lauwers, J.; Luyckx, S.; Ochesanu, S.; Rougny, R.; Van De Klundert, M.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Van Spilbeeck, A.; Blekman, F.; Blyweert, S.; D'Hondt, J.; Daci, N.; Heracleous, N.; Keaveney, J.; Lowette, S.; Maes, M.; Olbrechts, A.; Python, Q.; Strom, D.; Tavernier, S.; Van Doninck, W.; Van Mulders, P.; Van Onsem, G. P.; Villella, I.; Caillol, C.; Clerbaux, B.; De Lentdecker, G.; Dobur, D.; Favart, L.; Gay, A. P. R.; Grebenyuk, A.; Léonard, A.; Mohammadi, A.; Perniè, L.; Randle-conde, A.; Reis, T.; Seva, T.; Thomas, L.; Vander Velde, C.; Vanlaer, P.; Wang, J.; Zenoni, F.; Adler, V.; Beernaert, K.; Benucci, L.; Cimmino, A.; Costantini, S.; Crucy, S.; Dildick, S.; Fagot, A.; Garcia, G.; Mccartin, J.; Ocampo Rios, A. A.; Ryckbosch, D.; Salva Diblen, S.; Sigamani, M.; Strobbe, N.; Thyssen, F.; Tytgat, M.; Yazgan, E.; Zaganidis, N.; Basegmez, S.; Beluffi, C.; Bruno, G.; Castello, R.; Caudron, A.; Ceard, L.; Da Silveira, G. G.; Delaere, C.; du Pree, T.; Favart, D.; Forthomme, L.; Giammanco, A.; Hollar, J.; Jafari, A.; Jez, P.; Komm, M.; Lemaitre, V.; Nuttens, C.; Pagano, D.; Perrini, L.; Pin, A.; Piotrzkowski, K.; Popov, A.; Quertenmont, L.; Selvaggi, M.; Vidal Marono, M.; Vizan Garcia, J. M.; Beliy, N.; Caebergs, T.; Daubie, E.; Hammad, G. H.; Júnior, W. L. Aldá; Alves, G. A.; Brito, L.; Correa Martins Junior, M.; Martins, T. Dos Reis; Mora Herrera, C.; Pol, M. E.; Rebello Teles, P.; Carvalho, W.; Chinellato, J.; Custódio, A.; Da Costa, E. M.; De Jesus Damiao, D.; De Oliveira Martins, C.; Fonseca De Souza, S.; Malbouisson, H.; Matos Figueiredo, D.; Mundim, L.; Nogima, H.; Prado Da Silva, W. L.; Santaolalla, J.; Santoro, A.; Sznajder, A.; Tonelli Manganote, E. J.; Vilela Pereira, A.; Bernardes, C. A.; Dogra, S.; Fernandez Perez Tomei, T. R.; Gregores, E. M.; Mercadante, P. G.; Novaes, S. F.; Padula, Sandra S.; Aleksandrov, A.; Genchev, V.; Hadjiiska, R.; Iaydjiev, P.; Marinov, A.; Piperov, S.; Rodozov, M.; Sultanov, G.; Vutova, M.; Dimitrov, A.; Glushkov, I.; Litov, L.; Pavlov, B.; Petkov, P.; Bian, J. G.; Chen, G. M.; Chen, H. S.; Chen, M.; Cheng, T.; Du, R.; Jiang, C. H.; Plestina, R.; Romeo, F.; Tao, J.; Wang, Z.; Asawatangtrakuldee, C.; Ban, Y.; Li, Q.; Liu, S.; Mao, Y.; Qian, S. J.; Wang, D.; Xu, Z.; Zou, W.; Avila, C.; Cabrera, A.; Chaparro Sierra, L. F.; Florez, C.; Gomez, J. P.; Gomez Moreno, B.; Sanabria, J. C.; Godinovic, N.; Lelas, D.; Polic, D.; Puljak, I.; Antunovic, Z.; Kovac, M.; Brigljevic, V.; Kadija, K.; Luetic, J.; Mekterovic, D.; Sudic, L.; Attikis, A.; Mavromanolakis, G.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Bodlak, M.; Finger, M.; Finger, M.; Assran, Y.; Ellithi Kamel, A.; Mahmoud, M. A.; Radi, A.; Kadastik, M.; Murumaa, M.; Raidal, M.; Tiko, A.; Eerola, P.; Fedi, G.; Voutilainen, M.; Härkönen, J.; Karimäki, V.; Kinnunen, R.; Kortelainen, M. J.; Lampén, T.; Lassila-Perini, K.; Lehti, S.; Lindén, T.; Luukka, P.; Mäenpää, T.; Peltola, T.; Tuominen, E.; Tuominiemi, J.; Tuovinen, E.; Wendland, L.; Talvitie, J.; Tuuva, T.; Besancon, M.; Couderc, F.; Dejardin, M.; Denegri, D.; Fabbro, B.; Faure, J. L.; Favaro, C.; Ferri, F.; Ganjour, S.; Givernaud, A.; Gras, P.; Hamel de Monchenault, G.; Jarry, P.; Locci, E.; Malcles, J.; Rander, J.; Rosowsky, A.; Titov, M.; Baffioni, S.; Beaudette, F.; Busson, P.; Charlot, C.; Dahms, T.; Dalchenko, M.; Dobrzynski, L.; Filipovic, N.; Florent, A.; Granier de Cassagnac, R.; Mastrolorenzo, L.; Miné, P.; Mironov, C.; Naranjo, I. N.; Nguyen, M.; Ochando, C.; Ortona, G.; Paganini, P.; Regnard, S.; Salerno, R.; Sauvan, J. B.; Sirois, Y.; Veelken, C.; Yilmaz, Y.; Zabi, A.; Agram, J.-L.; Andrea, J.; Aubin, A.; Bloch, D.; Brom, J.-M.; Chabert, E. C.; Collard, C.; Conte, E.; Fontaine, J.-C.; Gelé, D.; Goerlach, U.; Goetzmann, C.; Le Bihan, A.-C.; Skovpen, K.; Van Hove, P.; Gadrat, S.; Beauceron, S.; Beaupere, N.; Boudoul, G.; Bouvier, E.; Brochet, S.; Carrillo Montoya, C. A.; Chasserat, J.; Chierici, R.; Contardo, D.; Depasse, P.; El Mamouni, H.; Fan, J.; Fay, J.; Gascon, S.; Gouzevitch, M.; Ille, B.; Kurca, T.; Lethuillier, M.; Mirabito, L.; Perries, S.; Ruiz Alvarez, J. D.; Sabes, D.; Sgandurra, L.; Sordini, V.; Vander Donckt, M.; Verdier, P.; Viret, S.; Xiao, H.; Tsamalaidze, Z.; Autermann, C.; Beranek, S.; Bontenackels, M.; Edelhoff, M.; Feld, L.; Heister, A.; Hindrichs, O.; Klein, K.; Ostapchuk, A.; Raupach, F.; Sammet, J.; Schael, S.; Schulte, J. F.; Weber, H.; Wittmer, B.; Zhukov, V.; Ata, M.; Brodski, M.; Dietz-Laursonn, E.; Duchardt, D.; Erdmann, M.; Fischer, R.; Güth, A.; Hebbeker, T.; Heidemann, C.; Hoepfner, K.; Klingebiel, D.; Knutzen, S.; Kreuzer, P.; Merschmeyer, M.; Meyer, A.; Millet, P.; Olschewski, M.; Padeken, K.; Papacz, P.; Reithler, H.; Schmitz, S. A.; Sonnenschein, L.; Teyssier, D.; Thüer, S.; Weber, M.; Cherepanov, V.; Erdogan, Y.; Flügge, G.; Geenen, H.; Geisler, M.; Haj Ahmad, W.; Hoehle, F.; Kargoll, B.; Kress, T.; Kuessel, Y.; Künsken, A.; Lingemann, J.; Nowack, A.; Nugent, I. M.; Pooth, O.; Stahl, A.; Aldaya Martin, M.; Asin, I.; Bartosik, N.; Behr, J.; Behrens, U.; Bell, A. J.; Bethani, A.; Borras, K.; Burgmeier, A.; Cakir, A.; Calligaris, L.; Campbell, A.; Choudhury, S.; Costanza, F.; Diez Pardos, C.; Dolinska, G.; Dooling, S.; Dorland, T.; Eckerlin, G.; Eckstein, D.; Eichhorn, T.; Flucke, G.; Garcia, J. Garay; Geiser, A.; Gunnellini, P.; Hauk, J.; Hempel, M.; Jung, H.; Kalogeropoulos, A.; Kasemann, M.; Katsas, P.; Kieseler, J.; Kleinwort, C.; Korol, l.; Krücker, D.; Lange, W.; Leonard, J.; Lipka, K.; Lobanov, A.; Lohmann, W.; Lutz, B.; Mankel, R.; Marfin, I.; Melzer-Pellmann, I.-A.; Meyer, A. B.; Mittag, G.; Mnich, J.; Mussgiller, A.; Naumann-Emme, S.; Nayak, A.; Ntomari, E.; Perrey, H.; Pitzl, D.; Placakyte, R.; Raspereza, A.; Ribeiro Cipriano, P. M.; Roland, B.; Ron, E.; Sahin, M. Ö.; Salfeld-Nebgen, J.; Saxena, P.; Schoerner-Sadenius, T.; Schröder, M.; Seitz, C.; Spannagel, S.; Vargas Trevino, A. D. R.; Walsh, R.; Wissing, C.; Blobel, V.; Centis Vignali, M.; Draeger, A. R.; Erfle, J.; Garutti, E.; Goebel, K.; Görner, M.; Haller, J.; Hoffmann, M.; Höing, R. S.; Junkes, A.; Kirschenmann, H.; Klanner, R.; Kogler, R.; Lange, J.; Lapsien, T.; Lenz, T.; Marchesini, I.; Ott, J.; Peiffer, T.; Perieanu, A.; Pietsch, N.; Poehlsen, J.; Poehlsen, T.; Rathjens, D.; Sander, C.; Schettler, H.; Schleper, P.; Schlieckau, E.; Schmidt, A.; Seidel, M.; Sola, V.; Stadie, H.; Steinbrück, G.; Troendle, D.; Usai, E.; Vanelderen, L.; Vanhoefer, A.; Barth, C.; Baus, C.; Berger, J.; Böser, C.; Butz, E.; Chwalek, T.; De Boer, W.; Descroix, A.; Dierlamm, A.; Feindt, M.; Frensch, F.; Giffels, M.; Gilbert, A.; Hartmann, F.; Hauth, T.; Husemann, U.; Katkov, I.; Kornmayer, A.; Kuznetsova, E.; Lobelle Pardo, P.; Mozer, M. U.; Müller, T.; Müller, Th.; Nürnberg, A.; Quast, G.; Rabbertz, K.; Röcker, S.; Simonis, H. J.; Stober, F. M.; Ulrich, R.; Wagner-Kuhr, J.; Wayand, S.; Weiler, T.; Wolf, R.; Anagnostou, G.; Daskalakis, G.; Geralis, T.; Giakoumopoulou, V. A.; Kyriakis, A.; Loukas, D.; Markou, A.; Markou, C.; Psallidas, A.; Topsis-Giotis, I.; Agapitos, A.; Kesisoglou, S.; Panagiotou, A.; Saoulidou, N.; Stiliaris, E.; Aslanoglou, X.; Evangelou, I.; Flouris, G.; Foudas, C.; Kokkas, P.; Manthos, N.; Papadopoulos, I.; Paradas, E.; Strologas, J.; Bencze, G.; Hajdu, C.; Hidas, P.; Horvath, D.; Sikler, F.; Veszpremi, V.; Vesztergombi, G.; Zsigmond, A. J.; Beni, N.; Czellar, S.; Karancsi, J.; Molnar, J.; Palinkas, J.; Szillasi, Z.; Makovec, A.; Raics, P.; Trocsanyi, Z. L.; Ujvari, B.; Swain, S. K.; Beri, S. B.; Bhatnagar, V.; Gupta, R.; Bhawandeep, U.; Kalsi, A. K.; Kaur, M.; Kumar, R.; Mittal, M.; Nishu, N.; Singh, J. B.; Kumar, Ashok; Kumar, Arun; Ahuja, S.; Bhardwaj, A.; Choudhary, B. C.; Kumar, A.; Malhotra, S.; Naimuddin, M.; Ranjan, K.; Sharma, V.; Banerjee, S.; Bhattacharya, S.; Chatterjee, K.; Dutta, S.; Gomber, B.; Jain, Sa.; Jain, Sh.; Khurana, R.; Modak, A.; Mukherjee, S.; Roy, D.; Sarkar, S.; Sharan, M.; Abdulsalam, A.; Dutta, D.; Kumar, V.; Mohanty, A. K.; Pant, L. M.; Shukla, P.; Topkar, A.; Aziz, T.; Banerjee, S.; Bhowmik, S.; Chatterjee, R. M.; Dewanjee, R. K.; Dugad, S.; Ganguly, S.; Ghosh, S.; Guchait, M.; Gurtu, A.; Kole, G.; Kumar, S.; Maity, M.; Majumder, G.; Mazumdar, K.; Mohanty, G. B.; Parida, B.; Sudhakar, K.; Wickramage, N.; Bakhshiansohi, H.; Behnamian, H.; Etesami, S. M.; Fahim, A.; Goldouzian, R.; Khakzad, M.; Mohammadi Najafabadi, M.; Naseri, M.; Paktinat Mehdiabadi, S.; Rezaei Hosseinabadi, F.; Safarzadeh, B.; Zeinali, M.; Felcini, M.; Grunewald, M.; Abbrescia, M.; Calabria, C.; Chhibra, S. 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F.; Matchev, K.; Mei, H.; Milenovic, P.; Mitselmakher, G.; Muniz, L.; Rinkevicius, A.; Shchutska, L.; Snowball, M.; Sperka, D.; Yelton, J.; Zakaria, M.; Hewamanage, S.; Linn, S.; Markowitz, P.; Martinez, G.; Rodriguez, J. L.; Adams, T.; Askew, A.; Bochenek, J.; Diamond, B.; Haas, J.; Hagopian, S.; Hagopian, V.; Johnson, K. F.; Prosper, H.; Veeraraghavan, V.; Weinberg, M.; Baarmand, M. M.; Hohlmann, M.; Kalakhety, H.; Yumiceva, F.; Adams, M. R.; Apanasevich, L.; Berry, D.; Betts, R. R.; Bucinskaite, I.; Cavanaugh, R.; Evdokimov, O.; Gauthier, L.; Gerber, C. E.; Hofman, D. J.; Kurt, P.; Moon, D. H.; O'Brien, C.; Sandoval Gonzalez, l. D.; Silkworth, C.; Turner, P.; Varelas, N.; Bilki, B.; Clarida, W.; Dilsiz, K.; Haytmyradov, M.; Merlo, J.-P.; Mermerkaya, H.; Mestvirishvili, A.; Moeller, A.; Nachtman, J.; Ogul, H.; Onel, Y.; Ozok, F.; Penzo, A.; Rahmat, R.; Sen, S.; Tan, P.; Tiras, E.; Wetzel, J.; Yi, K.; Barnett, B. A.; Blumenfeld, B.; Bolognesi, S.; Fehling, D.; Gritsan, A. V.; Maksimovic, P.; Martin, C.; Swartz, M.; Baringer, P.; Bean, A.; Benelli, G.; Bruner, C.; Kenny, R. P.; Malek, M.; Murray, M.; Noonan, D.; Sanders, S.; Sekaric, J.; Stringer, R.; Wang, Q.; Wood, J. S.; Chakaberia, I.; Ivanov, A.; Khalil, S.; Makouski, M.; Maravin, Y.; Saini, L. K.; Skhirtladze, N.; Svintradze, I.; Gronberg, J.; Lange, D.; Rebassoo, F.; Wright, D.; Baden, A.; Belloni, A.; Calvert, B.; Eno, S. C.; Gomez, J. A.; Hadley, N. J.; Kellogg, R. G.; Kolberg, T.; Lu, Y.; Mignerey, A. C.; Pedro, K.; Skuja, A.; Tonjes, M. B.; Tonwar, S. C.; Apyan, A.; Barbieri, R.; Busza, W.; Cali, I. A.; Chan, M.; Di Matteo, L.; Gomez Ceballos, G.; Goncharov, M.; Gulhan, D.; Klute, M.; Lai, Y. S.; Lee, Y.-J.; Levin, A.; Luckey, P. D.; Paus, C.; Ralph, D.; Roland, C.; Roland, G.; Stephans, G. S. F.; Sumorok, K.; Velicanu, D.; Veverka, J.; Wyslouch, B.; Yang, M.; Zanetti, M.; Zhukova, V.; Dahmes, B.; Gude, A.; Kao, S. C.; Klapoetke, K.; Kubota, Y.; Mans, J.; Pastika, N.; Rusack, R.; Singovsky, A.; Tambe, N.; Turkewitz, J.; Acosta, J. G.; Oliveros, S.; Avdeeva, E.; Bloom, K.; Bose, S.; Claes, D. R.; Dominguez, A.; Gonzalez Suarez, R.; Keller, J.; Knowlton, D.; Kravchenko, I.; Lazo-Flores, J.; Meier, F.; Ratnikov, F.; Snow, G. R.; Zvada, M.; Dolen, J.; Godshalk, A.; Iashvili, I.; Kharchilava, A.; Kumar, A.; Rappoccio, S.; Alverson, G.; Barberis, E.; Baumgartel, D.; Chasco, M.; Massironi, A.; Morse, D. M.; Nash, D.; Orimoto, T.; Trocino, D.; Wang, R. J.; Wood, D.; Zhang, J.; Hahn, K. A.; Kubik, A.; Mucia, N.; Odell, N.; Pollack, B.; Pozdnyakov, A.; Schmitt, M.; Stoynev, S.; Sung, K.; Velasco, M.; Won, S.; Brinkerhoff, A.; Chan, K. M.; Drozdetskiy, A.; Hildreth, M.; Jessop, C.; Karmgard, D. J.; Kellams, N.; Lannon, K.; Lynch, S.; Marinelli, N.; Musienko, Y.; Pearson, T.; Planer, M.; Ruchti, R.; Smith, G.; Valls, N.; Wayne, M.; Wolf, M.; Woodard, A.; Antonelli, L.; Brinson, J.; Bylsma, B.; Durkin, L. S.; Flowers, S.; Hart, A.; Hill, C.; Hughes, R.; Kotov, K.; Ling, T. Y.; Luo, W.; Puigh, D.; Rodenburg, M.; Winer, B. L.; Wolfe, H.; Wulsin, H. W.; Driga, O.; Elmer, P.; Hardenbrook, J.; Hebda, P.; Hunt, A.; Koay, S. A.; Lujan, P.; Marlow, D.; Medvedeva, T.; Mooney, M.; Olsen, J.; Piroué, P.; Quan, X.; Saka, H.; Stickland, D.; Tully, C.; Werner, J. S.; Zuranski, A.; Brownson, E.; Malik, S.; Mendez, H.; Ramirez Vargas, J. E.; Barnes, V. E.; Benedetti, D.; Bortoletto, D.; De Mattia, M.; Gutay, L.; Hu, Z.; Jha, M. K.; Jones, M.; Jung, K.; Kress, M.; Leonardo, N.; Miller, D. H.; Neumeister, N.; Radburn-Smith, B. C.; Shi, X.; Shipsey, I.; Silvers, D.; Svyatkovskiy, A.; Wang, F.; Xie, W.; Xu, L.; Zablocki, J.; Parashar, N.; Stupak, J.; Adair, A.; Akgun, B.; Ecklund, K. M.; Geurts, F. J. M.; Li, W.; Michlin, B.; Padley, B. P.; Redjimi, R.; Roberts, J.; Zabel, J.; Betchart, B.; Bodek, A.; Covarelli, R.; de Barbaro, P.; Demina, R.; Eshaq, Y.; Ferbel, T.; Garcia-Bellido, A.; Goldenzweig, P.; Han, J.; Harel, A.; Khukhunaishvili, A.; Korjenevski, S.; Petrillo, G.; Vishnevskiy, D.; Ciesielski, R.; Demortier, L.; Goulianos, K.; Mesropian, C.; Arora, S.; Barker, A.; Chou, J. P.; Contreras-Campana, C.; Contreras-Campana, E.; Duggan, D.; Ferencek, D.; Gershtein, Y.; Gray, R.; Halkiadakis, E.; Hidas, D.; Kaplan, S.; Lath, A.; Panwalkar, S.; Park, M.; Patel, R.; Salur, S.; Schnetzer, S.; Somalwar, S.; Stone, R.; Thomas, S.; Thomassen, P.; Walker, M.; Rose, K.; Spanier, S.; York, A.; Bouhali, O.; Castaneda Hernandez, A.; Eusebi, R.; Flanagan, W.; Gilmore, J.; Kamon, T.; Khotilovich, V.; Krutelyov, V.; Montalvo, R.; Osipenkov, I.; Pakhotin, Y.; Perloff, A.; Roe, J.; Rose, A.; Safonov, A.; Suarez, I.; Tatarinov, A.; Ulmer, K. A.; Akchurin, N.; Cowden, C.; Damgov, J.; Dragoiu, C.; Dudero, P. R.; Faulkner, J.; Kovitanggoon, K.; Kunori, S.; Lee, S. W.; Libeiro, T.; Volobouev, I.; Appelt, E.; Delannoy, A. G.; Greene, S.; Gurrola, A.; Johns, W.; Maguire, C.; Mao, Y.; Melo, A.; Sharma, M.; Sheldon, P.; Snook, B.; Tuo, S.; Velkovska, J.; Arenton, M. W.; Boutle, S.; Cox, B.; Francis, B.; Goodell, J.; Hirosky, R.; Ledovskoy, A.; Li, H.; Lin, C.; Neu, C.; Wood, J.; Clarke, C.; Harr, R.; Karchin, P. E.; Kottachchi Kankanamge Don, C.; Lamichhane, P.; Sturdy, J.; Belknap, D. A.; Carlsmith, D.; Cepeda, M.; Dasu, S.; Dodd, L.; Duric, S.; Friis, E.; Hall-Wilton, R.; Herndon, M.; Hervé, A.; Klabbers, P.; Lanaro, A.; Lazaridis, C.; Levine, A.; Loveless, R.; Mohapatra, A.; Ojalvo, I.; Perry, T.; Pierro, G. A.; Polese, G.; Ross, I.; Sarangi, T.; Savin, A.; Smith, W. H.; Taylor, D.; Vuosalo, C.; Woods, N.

2015-07-01

This paper presents distributions of topological observables in inclusive three- and four-jet events produced in pp collisions at a centre-of-mass energy of 7 with a data sample collected by the CMS experiment corresponding to a luminosity of 5.1. The distributions are corrected for detector effects, and compared with several event generators based on two- and multi-parton matrix elements at leading order. Among the considered calculations, MadGraph interfaced with pythia6 displays the overall best agreement with data.

Stochastic generation of hourly rainstorm events in Johor

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

Nojumuddin, Nur Syereena; Yusof, Fadhilah; Yusop, Zulkifli

2015-02-03

Engineers and researchers in water-related studies are often faced with the problem of having insufficient and long rainfall record. Practical and effective methods must be developed to generate unavailable data from limited available data. Therefore, this paper presents a Monte-Carlo based stochastic hourly rainfall generation model to complement the unavailable data. The Monte Carlo simulation used in this study is based on the best fit of storm characteristics. Hence, by using the Maximum Likelihood Estimation (MLE) and Anderson Darling goodness-of-fit test, lognormal appeared to be the best rainfall distribution. Therefore, the Monte Carlo simulation based on lognormal distribution was usedmore » in the study. The proposed model was verified by comparing the statistical moments of rainstorm characteristics from the combination of the observed rainstorm events under 10 years and simulated rainstorm events under 30 years of rainfall records with those under the entire 40 years of observed rainfall data based on the hourly rainfall data at the station J1 in Johor over the period of 1972–2011. The absolute percentage error of the duration-depth, duration-inter-event time and depth-inter-event time will be used as the accuracy test. The results showed the first four product-moments of the observed rainstorm characteristics were close with the simulated rainstorm characteristics. The proposed model can be used as a basis to derive rainfall intensity-duration frequency in Johor.« less

Analysis of overdispersed count data by mixtures of Poisson variables and Poisson processes.

PubMed

Hougaard, P; Lee, M L; Whitmore, G A

1997-12-01

Count data often show overdispersion compared to the Poisson distribution. Overdispersion is typically modeled by a random effect for the mean, based on the gamma distribution, leading to the negative binomial distribution for the count. This paper considers a larger family of mixture distributions, including the inverse Gaussian mixture distribution. It is demonstrated that it gives a significantly better fit for a data set on the frequency of epileptic seizures. The same approach can be used to generate counting processes from Poisson processes, where the rate or the time is random. A random rate corresponds to variation between patients, whereas a random time corresponds to variation within patients.

Motion Estimation System Utilizing Point Cloud Registration

NASA Technical Reports Server (NTRS)

Chen, Qi (Inventor)

2016-01-01

A system and method of estimation motion of a machine is disclosed. The method may include determining a first point cloud and a second point cloud corresponding to an environment in a vicinity of the machine. The method may further include generating a first extended gaussian image (EGI) for the first point cloud and a second EGI for the second point cloud. The method may further include determining a first EGI segment based on the first EGI and a second EGI segment based on the second EGI. The method may further include determining a first two dimensional distribution for points in the first EGI segment and a second two dimensional distribution for points in the second EGI segment. The method may further include estimating motion of the machine based on the first and second two dimensional distributions.

IRON HOMEOSTATIS IN THE LUNG

EPA Science Inventory

Iron is essential for many aspects of cellular function. However, it can also generate oxygen-based free radicals that result in injury to biological molecules. For this reason, iron acquisition and distribution are tightly regulated. Constant exposure to the atmosphere result...

Another look at the question of density and rail transit.

DOT National Transportation Integrated Search

2011-07-01

Long community discussions about rail often include whether a citys spatial distribution of : housing, employment and other trip generators is conducive to supporting rail transit. A citys : decision to construct rail transit is based on an arr...

CNV-CH: A Convex Hull Based Segmentation Approach to Detect Copy Number Variations (CNV) Using Next-Generation Sequencing Data

PubMed Central

De, Rajat K.

2015-01-01

Copy number variation (CNV) is a form of structural alteration in the mammalian DNA sequence, which are associated with many complex neurological diseases as well as cancer. The development of next generation sequencing (NGS) technology provides us a new dimension towards detection of genomic locations with copy number variations. Here we develop an algorithm for detecting CNVs, which is based on depth of coverage data generated by NGS technology. In this work, we have used a novel way to represent the read count data as a two dimensional geometrical point. A key aspect of detecting the regions with CNVs, is to devise a proper segmentation algorithm that will distinguish the genomic locations having a significant difference in read count data. We have designed a new segmentation approach in this context, using convex hull algorithm on the geometrical representation of read count data. To our knowledge, most algorithms have used a single distribution model of read count data, but here in our approach, we have considered the read count data to follow two different distribution models independently, which adds to the robustness of detection of CNVs. In addition, our algorithm calls CNVs based on the multiple sample analysis approach resulting in a low false discovery rate with high precision. PMID:26291322

CNV-CH: A Convex Hull Based Segmentation Approach to Detect Copy Number Variations (CNV) Using Next-Generation Sequencing Data.

PubMed

Sinha, Rituparna; Samaddar, Sandip; De, Rajat K

2015-01-01

Copy number variation (CNV) is a form of structural alteration in the mammalian DNA sequence, which are associated with many complex neurological diseases as well as cancer. The development of next generation sequencing (NGS) technology provides us a new dimension towards detection of genomic locations with copy number variations. Here we develop an algorithm for detecting CNVs, which is based on depth of coverage data generated by NGS technology. In this work, we have used a novel way to represent the read count data as a two dimensional geometrical point. A key aspect of detecting the regions with CNVs, is to devise a proper segmentation algorithm that will distinguish the genomic locations having a significant difference in read count data. We have designed a new segmentation approach in this context, using convex hull algorithm on the geometrical representation of read count data. To our knowledge, most algorithms have used a single distribution model of read count data, but here in our approach, we have considered the read count data to follow two different distribution models independently, which adds to the robustness of detection of CNVs. In addition, our algorithm calls CNVs based on the multiple sample analysis approach resulting in a low false discovery rate with high precision.

MAFsnp: A Multi-Sample Accurate and Flexible SNP Caller Using Next-Generation Sequencing Data

PubMed Central

Hu, Jiyuan; Li, Tengfei; Xiu, Zidi; Zhang, Hong

2015-01-01

Most existing statistical methods developed for calling single nucleotide polymorphisms (SNPs) using next-generation sequencing (NGS) data are based on Bayesian frameworks, and there does not exist any SNP caller that produces p-values for calling SNPs in a frequentist framework. To fill in this gap, we develop a new method MAFsnp, a Multiple-sample based Accurate and Flexible algorithm for calling SNPs with NGS data. MAFsnp is based on an estimated likelihood ratio test (eLRT) statistic. In practical situation, the involved parameter is very close to the boundary of the parametric space, so the standard large sample property is not suitable to evaluate the finite-sample distribution of the eLRT statistic. Observing that the distribution of the test statistic is a mixture of zero and a continuous part, we propose to model the test statistic with a novel two-parameter mixture distribution. Once the parameters in the mixture distribution are estimated, p-values can be easily calculated for detecting SNPs, and the multiple-testing corrected p-values can be used to control false discovery rate (FDR) at any pre-specified level. With simulated data, MAFsnp is shown to have much better control of FDR than the existing SNP callers. Through the application to two real datasets, MAFsnp is also shown to outperform the existing SNP callers in terms of calling accuracy. An R package “MAFsnp” implementing the new SNP caller is freely available at http://homepage.fudan.edu.cn/zhangh/softwares/. PMID:26309201

On validating remote sensing simulations using coincident real data

NASA Astrophysics Data System (ADS)

Wang, Mingming; Yao, Wei; Brown, Scott; Goodenough, Adam; van Aardt, Jan

2016-05-01

The remote sensing community often requires data simulation, either via spectral/spatial downsampling or through virtual, physics-based models, to assess systems and algorithms. The Digital Imaging and Remote Sensing Image Generation (DIRSIG) model is one such first-principles, physics-based model for simulating imagery for a range of modalities. Complex simulation of vegetation environments subsequently has become possible, as scene rendering technology and software advanced. This in turn has created questions related to the validity of such complex models, with potential multiple scattering, bidirectional distribution function (BRDF), etc. phenomena that could impact results in the case of complex vegetation scenes. We selected three sites, located in the Pacific Southwest domain (Fresno, CA) of the National Ecological Observatory Network (NEON). These sites represent oak savanna, hardwood forests, and conifer-manzanita-mixed forests. We constructed corresponding virtual scenes, using airborne LiDAR and imaging spectroscopy data from NEON, ground-based LiDAR data, and field-collected spectra to characterize the scenes. Imaging spectroscopy data for these virtual sites then were generated using the DIRSIG simulation environment. This simulated imagery was compared to real AVIRIS imagery (15m spatial resolution; 12 pixels/scene) and NEON Airborne Observation Platform (AOP) data (1m spatial resolution; 180 pixels/scene). These tests were performed using a distribution-comparison approach for select spectral statistics, e.g., established the spectra's shape, for each simulated versus real distribution pair. The initial comparison results of the spectral distributions indicated that the shapes of spectra between the virtual and real sites were closely matched.

ICESat Science Investigator led Processing System (I-SIPS)

NASA Astrophysics Data System (ADS)

Bhardwaj, S.; Bay, J.; Brenner, A.; Dimarzio, J.; Hancock, D.; Sherman, M.

2003-12-01

The ICESat Science Investigator-led Processing System (I-SIPS) generates the GLAS standard data products. It consists of two main parts the Scheduling and Data Management System (SDMS) and the Geoscience Laser Altimeter System (GLAS) Science Algorithm Software. The system has been operational since the successful launch of ICESat. It ingests data from the GLAS instrument, generates GLAS data products, and distributes them to the GLAS Science Computing Facility (SCF), the Instrument Support Facility (ISF) and the National Snow and Ice Data Center (NSIDC) ECS DAAC. The SDMS is the Planning, Scheduling and Data Management System that runs the GLAS Science Algorithm Software (GSAS). GSAS is based on the Algorithm Theoretical Basis Documents provided by the Science Team and is developed independently of SDMS. The SDMS provides the processing environment to plan jobs based on existing data, control job flow, data distribution, and archiving. The SDMS design is based on a mission-independent architecture that imposes few constraints on the science code thereby facilitating I-SIPS integration. I-SIPS currently works in an autonomous manner to ingest GLAS instrument data, distribute this data to the ISF, run the science processing algorithms to produce the GLAS standard products, reprocess data when new versions of science algorithms are released, and distributes the products to the SCF, ISF, and NSIDC. I-SIPS has a proven performance record, delivering the data to the SCF within hours after the initial instrument activation. The I-SIPS design philosophy gives this system a high potential for reuse in other science missions.

How the Slip Distribution Complexities Control the Tsunami Scenarios: a Sensitivity Analysis for the Hellenic and Calabrian Subduction Interfaces.

NASA Astrophysics Data System (ADS)

Scala, A.; Murphy, S.; Herrero, A.; Maesano, F. E.; Lorito, S.; Romano, F.; Tiberti, M. M.; Tonini, R.; Volpe, M.; Basili, R.

2017-12-01

Recent giant tsunamigenic earthquakes (Sumatra 2004, Chile 2010, Tohoku 2011) have confirmed that the complexity of seismic slip distributions may play a fundamental role in the generation and the amplitude of the tsunami waves. In particular, big patches of large slip on the shallower part of the subduction zones, as well as slow rupture propagation within low rigidity areas, can contribute to increase the tsunamigenic potential thus generating devastating coastal inundation. In the Mediterranean Sea, some subduction structures can be identified, such as the Hellenic Arc at the boundary between the African and Aegean plates, and the Calabrian Arc between the European and African plates. We have modelled these areas using discretized high-resolution 3D fault geometries with realistic variability of the strike and dip angles. In particular, the latter geometries have been constrained from the analysis of a dense network of seismic reflection profiles and the seismicity of the areas. To study the influence of different rigidity conditions, we compare the tsunami scenarios deriving from homogeneous slip to those obtained from depth-dependent slip distributions at different magnitudes. These depth-dependent slip distributions are obtained by imposing a variability with depth of both shear modulus and seismic rate, and the conservation of the dislocation over the whole subduction zone. Furthermore, we generate along the Hellenic and Calabrian arc subduction interfaces an ensemble of stochastic slip distributions using a composite source model technique. To mimic either single or multiple asperity source models, the distribution of sub-events whose sum produces the stochastic slip, are distributed based on a PDF, defined as the combination of either one or more Gaussian functions. Tsunami scenarios are then generated from this ensemble in order to address how the position of the main patch of slip can affect the tsunami amplitude along the coast.

Pseudo-random properties of a linear congruential generator investigated by b-adic diaphony

NASA Astrophysics Data System (ADS)

Stoev, Peter; Stoilova, Stanislava

2017-12-01

In the proposed paper we continue the study of the diaphony, defined in b-adic number system, and we extend it in different directions. We investigate this diaphony as a tool for estimation of the pseudorandom properties of some of the most used random number generators. This is done by evaluating the distribution of specially constructed two-dimensional nets on the base of the obtained random numbers. The aim is to see how the generated numbers are suitable for calculations in some numerical methods (Monte Carlo etc.).

Literature Survey on Operational Voltage Control and Reactive Power Management on Transmission and Sub-Transmission Networks

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

Elizondo, Marcelo A.; Samaan, Nader A.; Makarov, Yuri V.

Voltage and reactive power system control is generally performed following usual patterns of loads, based on off-line studies for daily and seasonal operations. This practice is currently challenged by the inclusion of distributed renewable generation, such as solar. There has been focus on resolving this problem at the distribution level; however, the transmission and sub-transmission levels have received less attention. This paper provides a literature review of proposed methods and solution approaches to coordinate and optimize voltage control and reactive power management, with an emphasis on applications at transmission and sub-transmission level. The conclusion drawn from the survey is thatmore » additional research is needed in the areas of optimizing switch shunt actions and coordinating all available resources to deal with uncertain patterns from increasing distributed renewable generation in the operational time frame. These topics are not deeply explored in the literature.« less

Distribution and avoidance of debris on epoxy resin during UV ns-laser scanning processes

NASA Astrophysics Data System (ADS)

Veltrup, Markus; Lukasczyk, Thomas; Ihde, Jörg; Mayer, Bernd

2018-05-01

In this paper the distribution of debris generated by a nanosecond UV laser (248 nm) on epoxy resin and the prevention of the corresponding re-deposition effects by parameter selection for a ns-laser scanning process were investigated. In order to understand the mechanisms behind the debris generation, in-situ particle measurements were performed during laser treatment. These measurements enabled the determination of the ablation threshold of the epoxy resin as well as the particle density and size distribution in relation to the applied laser parameters. The experiments showed that it is possible to reduce debris on the surface with an adapted selection of pulse overlap with respect to laser fluence. A theoretical model for the parameter selection was developed and tested. Based on this model, the correct choice of laser parameters with reduced laser fluence resulted in a surface without any re-deposited micro-particles.

Spatially distributed multipartite entanglement enables EPR steering of atomic clouds.

PubMed

Kunkel, Philipp; Prüfer, Maximilian; Strobel, Helmut; Linnemann, Daniel; Frölian, Anika; Gasenzer, Thomas; Gärttner, Martin; Oberthaler, Markus K

2018-04-27

A key resource for distributed quantum-enhanced protocols is entanglement between spatially separated modes. However, the robust generation and detection of entanglement between spatially separated regions of an ultracold atomic system remain a challenge. We used spin mixing in a tightly confined Bose-Einstein condensate to generate an entangled state of indistinguishable particles in a single spatial mode. We show experimentally that this entanglement can be spatially distributed by self-similar expansion of the atomic cloud. We used spatially resolved spin read-out to reveal a particularly strong form of quantum correlations known as Einstein-Podolsky-Rosen (EPR) steering between distinct parts of the expanded cloud. Based on the strength of EPR steering, we constructed a witness, which confirmed genuine 5-partite entanglement. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Incentive-Based Voltage Regulation in Distribution Networks: Preprint

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

Zhou, Xinyang; Chen, Lijun; Dall'Anese, Emiliano

This paper considers distribution networks fea- turing distributed energy resources, and designs incentive-based mechanisms that allow the network operator and end-customers to pursue given operational and economic objectives, while concurrently ensuring that voltages are within prescribed limits. Two different network-customer coordination mechanisms that require different amounts of information shared between the network operator and end-customers are developed to identify a solution of a well-defined social-welfare maximization prob- lem. Notably, the signals broadcast by the network operator assume the connotation of prices/incentives that induce the end- customers to adjust the generated/consumed powers in order to avoid the violation of the voltagemore » constraints. Stability of the proposed schemes is analytically established and numerically corroborated.« less

Incentive-Based Voltage Regulation in Distribution Networks

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

Dall-Anese, Emiliano; Baker, Kyri A; Zhou, Xinyang

This paper considers distribution networks fea- turing distributed energy resources, and designs incentive-based mechanisms that allow the network operator and end-customers to pursue given operational and economic objectives, while concurrently ensuring that voltages are within prescribed limits. Two different network-customer coordination mechanisms that require different amounts of information shared between the network operator and end-customers are developed to identify a solution of a well-defined social-welfare maximization prob- lem. Notably, the signals broadcast by the network operator assume the connotation of prices/incentives that induce the end- customers to adjust the generated/consumed powers in order to avoid the violation of the voltagemore » constraints. Stability of the proposed schemes is analytically established and numerically corroborated.« less

MALDI imaging facilitates new topical drug development process by determining quantitative skin distribution profiles.

PubMed

Bonnel, David; Legouffe, Raphaël; Eriksson, André H; Mortensen, Rasmus W; Pamelard, Fabien; Stauber, Jonathan; Nielsen, Kim T

2018-04-01

Generation of skin distribution profiles and reliable determination of drug molecule concentration in the target region are crucial during the development process of topical products for treatment of skin diseases like psoriasis and atopic dermatitis. Imaging techniques like mass spectrometric imaging (MSI) offer sufficient spatial resolution to generate meaningful distribution profiles of a drug molecule across a skin section. In this study, we use matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) to generate quantitative skin distribution profiles based on tissue extinction coefficient (TEC) determinations of four different molecules in cross sections of human skin explants after topical administration. The four drug molecules: roflumilast, tofacitinib, ruxolitinib, and LEO 29102 have different physicochemical properties. In addition, tofacitinib was administrated in two different formulations. The study reveals that with MALDI-MSI, we were able to observe differences in penetration profiles for both the four drug molecules and the two formulations and thereby demonstrate its applicability as a screening tool when developing a topical drug product. Furthermore, the study reveals that the sensitivity of the MALDI-MSI techniques appears to be inversely correlated to the drug molecules' ability to bind to the surrounding tissues, which can be estimated by their Log D values. Graphical abstract.

Fundamental statistical relationships between monthly and daily meteorological variables: Temporal downscaling of weather based on a global observational dataset

NASA Astrophysics Data System (ADS)

Sommer, Philipp; Kaplan, Jed

2016-04-01

Accurate modelling of large-scale vegetation dynamics, hydrology, and other environmental processes requires meteorological forcing on daily timescales. While meteorological data with high temporal resolution is becoming increasingly available, simulations for the future or distant past are limited by lack of data and poor performance of climate models, e.g., in simulating daily precipitation. To overcome these limitations, we may temporally downscale monthly summary data to a daily time step using a weather generator. Parameterization of such statistical models has traditionally been based on a limited number of observations. Recent developments in the archiving, distribution, and analysis of "big data" datasets provide new opportunities for the parameterization of a temporal downscaling model that is applicable over a wide range of climates. Here we parameterize a WGEN-type weather generator using more than 50 million individual daily meteorological observations, from over 10'000 stations covering all continents, based on the Global Historical Climatology Network (GHCN) and Synoptic Cloud Reports (EECRA) databases. Using the resulting "universal" parameterization and driven by monthly summaries, we downscale mean temperature (minimum and maximum), cloud cover, and total precipitation, to daily estimates. We apply a hybrid gamma-generalized Pareto distribution to calculate daily precipitation amounts, which overcomes much of the inability of earlier weather generators to simulate high amounts of daily precipitation. Our globally parameterized weather generator has numerous applications, including vegetation and crop modelling for paleoenvironmental studies.

Model Predictive Control-based Optimal Coordination of Distributed Energy Resources

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

Mayhorn, Ebony T.; Kalsi, Karanjit; Lian, Jianming

2013-01-07

Distributed energy resources, such as renewable energy resources (wind, solar), energy storage and demand response, can be used to complement conventional generators. The uncertainty and variability due to high penetration of wind makes reliable system operations and controls challenging, especially in isolated systems. In this paper, an optimal control strategy is proposed to coordinate energy storage and diesel generators to maximize wind penetration while maintaining system economics and normal operation performance. The goals of the optimization problem are to minimize fuel costs and maximize the utilization of wind while considering equipment life of generators and energy storage. Model predictive controlmore » (MPC) is used to solve a look-ahead dispatch optimization problem and the performance is compared to an open loop look-ahead dispatch problem. Simulation studies are performed to demonstrate the efficacy of the closed loop MPC in compensating for uncertainties and variability caused in the system.« less

Model Predictive Control-based Optimal Coordination of Distributed Energy Resources

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

Mayhorn, Ebony T.; Kalsi, Karanjit; Lian, Jianming

2013-04-03

Distributed energy resources, such as renewable energy resources (wind, solar), energy storage and demand response, can be used to complement conventional generators. The uncertainty and variability due to high penetration of wind makes reliable system operations and controls challenging, especially in isolated systems. In this paper, an optimal control strategy is proposed to coordinate energy storage and diesel generators to maximize wind penetration while maintaining system economics and normal operation performance. The goals of the optimization problem are to minimize fuel costs and maximize the utilization of wind while considering equipment life of generators and energy storage. Model predictive controlmore » (MPC) is used to solve a look-ahead dispatch optimization problem and the performance is compared to an open loop look-ahead dispatch problem. Simulation studies are performed to demonstrate the efficacy of the closed loop MPC in compensating for uncertainties and variability caused in the system.« less

Distribution of Base Pair Alternations in a Periodic DNA Chain: Application of Pólya Counting to a Physical System

NASA Astrophysics Data System (ADS)

Hillebrand, Malcolm; Paterson-Jones, Guy; Kalosakas, George; Skokos, Charalampos

2018-03-01

In modeling DNA chains, the number of alternations between Adenine-Thymine (AT) and Guanine-Cytosine (GC) base pairs can be considered as a measure of the heterogeneity of the chain, which in turn could affect its dynamics. A probability distribution function of the number of these alternations is derived for circular or periodic DNA. Since there are several symmetries to account for in the periodic chain, necklace counting methods are used. In particular, Polya's Enumeration Theorem is extended for the case of a group action that preserves partitioned necklaces. This, along with the treatment of generating functions as formal power series, allows for the direct calculation of the number of possible necklaces with a given number of AT base pairs, GC base pairs and alternations. The theoretically obtained probability distribution functions of the number of alternations are accurately reproduced by Monte Carlo simulations and fitted by Gaussians. The effect of the number of base pairs on the characteristics of these distributions is also discussed, as well as the effect of the ratios of the numbers of AT and GC base pairs.

Detection of dominant runoff generation processes in flood frequency analysis

NASA Astrophysics Data System (ADS)

Iacobellis, Vito; Fiorentino, Mauro; Gioia, Andrea; Manfreda, Salvatore

2010-05-01

The investigation on hydrologic similarity represents one of the most exciting challenges faced by hydrologists in the last few years, in order to reduce uncertainty on flood prediction in ungauged basins (e.g., IAHS Decade on Predictions in Ungauged Basins (PUB) - Sivapalan et al., 2003). In perspective, the identification of dominant runoff generation mechanisms may provide a strategy for catchment classification and identification hydrologically omogeneous regions. In this context, we exploited the framework of theoretically derived flood probability distributions, in order to interpret the physical behavior of real basins. Recent developments on theoretically derived distributions have highlighted that in a given basin different runoff processes may coexistence and modify or affect the shape of flood distributions. The identification of dominant runoff generation mechanisms represents a key signatures of flood distributions providing an insight in hydrologic similarity. Iacobellis and Fiorentino (2000) introduced a novel distribution of flood peak annual maxima, the "IF" distribution, which exploited the variable source area concept, coupled with a runoff threshold having scaling properties. More recently, Gioia et al (2008) introduced the Two Component-IF (TCIF) distribution, generalizing the IF distribution, based on two different threshold mechanisms, associated respectively to ordinary and extraordinary events. Indeed, ordinary floods are mostly due to rainfall events exceeding a threshold infiltration rate in a small source area, while the so-called outlier events, often responsible of the high skewness of flood distributions, are triggered by severe rainfalls exceeding a threshold storage in a large portion of the basin. Within this scheme, we focused on the application of both models (IF and TCIF) over a considerable number of catchments belonging to different regions of Southern Italy. In particular, we stressed, as a case of strong general interest in the field of statistical hydrology, the role of procedures for parameters estimation and techniques for model selection in the case of nested distributions. References Gioia, A., V. Iacobellis, S. Manfreda, M. Fiorentino, Runoff thresholds in derived flood frequency distributions, Hydrol. Earth Syst. Sci., 12, 1295-1307, 2008. Iacobellis, V., and M. Fiorentino (2000), Derived distribution of floods based on the concept of partial area coverage with a climatic appeal, Water Resour. Res., 36(2), 469-482. Sivapalan, M., Takeuchi, K., Franks, S. W., Gupta, V. K., Karambiri, H., Lakshmi, V., Liang, X., McDonnell, J. J., Mendiondo, E. M., O'Connell, P. E., Oki, T., Pomeroy, J. W., Schertzer, D., Uhlenbrook, S. and Zehe, E.: IAHS Decade on Predictions in Ungauged Basins (PUB), 2003-2012: Shaping an exciting future for the hydrological sciences, Hydrol. Sci. J., 48(6), 857-880, 2003.

A digital protection system incorporating knowledge based learning

NASA Astrophysics Data System (ADS)

Watson, Karan; Russell, B. Don; McCall, Kurt

A digital system architecture used to diagnoses the operating state and health of electric distribution lines and to generate actions for line protection is presented. The architecture is described functionally and to a limited extent at the hardware level. This architecture incorporates multiple analysis and fault-detection techniques utilizing a variety of parameters. In addition, a knowledge-based decision maker, a long-term memory retention and recall scheme, and a learning environment are described. Preliminary laboratory implementations of the system elements have been completed. Enhanced protection for electric distribution feeders is provided by this system. Advantages of the system are enumerated.

Upconversion-based receivers for quantum hacking-resistant quantum key distribution

NASA Astrophysics Data System (ADS)

Jain, Nitin; Kanter, Gregory S.

2016-07-01

We propose a novel upconversion (sum frequency generation)-based quantum-optical system design that can be employed as a receiver (Bob) in practical quantum key distribution systems. The pump governing the upconversion process is produced and utilized inside the physical receiver, making its access or control unrealistic for an external adversary (Eve). This pump facilitates several properties which permit Bob to define and control the modes that can participate in the quantum measurement. Furthermore, by manipulating and monitoring the characteristics of the pump pulses, Bob can detect a wide range of quantum hacking attacks launched by Eve.

Distributed Economic Dispatch in Microgrids Based on Cooperative Reinforcement Learning.

PubMed

Liu, Weirong; Zhuang, Peng; Liang, Hao; Peng, Jun; Huang, Zhiwu; Weirong Liu; Peng Zhuang; Hao Liang; Jun Peng; Zhiwu Huang; Liu, Weirong; Liang, Hao; Peng, Jun; Zhuang, Peng; Huang, Zhiwu

2018-06-01

Microgrids incorporated with distributed generation (DG) units and energy storage (ES) devices are expected to play more and more important roles in the future power systems. Yet, achieving efficient distributed economic dispatch in microgrids is a challenging issue due to the randomness and nonlinear characteristics of DG units and loads. This paper proposes a cooperative reinforcement learning algorithm for distributed economic dispatch in microgrids. Utilizing the learning algorithm can avoid the difficulty of stochastic modeling and high computational complexity. In the cooperative reinforcement learning algorithm, the function approximation is leveraged to deal with the large and continuous state spaces. And a diffusion strategy is incorporated to coordinate the actions of DG units and ES devices. Based on the proposed algorithm, each node in microgrids only needs to communicate with its local neighbors, without relying on any centralized controllers. Algorithm convergence is analyzed, and simulations based on real-world meteorological and load data are conducted to validate the performance of the proposed algorithm.

Mixing zone and drinking water intake dilution factor and wastewater generation distributions to enable probabilistic assessment of down-the-drain consumer product chemicals in the U.S.

PubMed

Kapo, Katherine E; McDonough, Kathleen; Federle, Thomas; Dyer, Scott; Vamshi, Raghu

2015-06-15

Environmental exposure and associated ecological risk related to down-the-drain chemicals discharged by municipal wastewater treatment plants (WWTPs) are strongly influenced by in-stream dilution of receiving waters which varies by geography, flow conditions and upstream wastewater inputs. The iSTREEM® model (American Cleaning Institute, Washington D.C.) was utilized to determine probabilistic distributions for no decay and decay-based dilution factors in mean annual and low (7Q10) flow conditions. The dilution factors derived in this study are "combined" dilution factors which account for both hydrologic dilution and cumulative upstream effluent contributions that will differ depending on the rate of in-stream decay due to biodegradation, volatilization, sorption, etc. for the chemical being evaluated. The median dilution factors estimated in this study (based on various in-stream decay rates from zero decay to a 1h half-life) for WWTP mixing zones dominated by domestic wastewater flow ranged from 132 to 609 at mean flow and 5 to 25 at low flow, while median dilution factors at drinking water intakes (mean flow) ranged from 146 to 2×10(7) depending on the in-stream decay rate. WWTPs within the iSTREEM® model were used to generate a distribution of per capita wastewater generated in the U.S. The dilution factor and per capita wastewater generation distributions developed by this work can be used to conduct probabilistic exposure assessments for down-the-drain chemicals in influent wastewater, wastewater treatment plant mixing zones and at drinking water intakes in the conterminous U.S. In addition, evaluation of types and abundance of U.S. wastewater treatment processes provided insight into treatment trends and the flow volume treated by each type of process. Moreover, removal efficiencies of chemicals can differ by treatment type. Hence, the availability of distributions for per capita wastewater production, treatment type, and dilution factors at a national level provides a series of practical and powerful tools for building probabilistic exposure models. Copyright © 2015 Elsevier B.V. All rights reserved.

Simulation of landslide and tsunami of the 1741 Oshima-Oshima eruption in Hokkaido, Japan

NASA Astrophysics Data System (ADS)

Ioki, K.; Yanagisawa, H.; Tanioka, Y.; Kawakami, G.; Kase, Y.; Nishina, K.; Hirose, W.; Ishimaru, S.

2017-12-01

The 1741 tsunami was generated by the Oshima-Oshima sector collapse in the southwestern Hokkaido, Japan. The tsunami caused great damage along the coast of Japan Sea in Oshima and Tsugaru peninsula and was the largest scale generated in the Japan sea. By the survey of tsunami deposits, at the coast of Okushiri Island and Hiyama in Hokkaido, tsunami deposits of this tsunami were found. In this study, the landslide and tsunami by the Oshima-Oshima eruption were modeled to explain distribution of debris deposits, tsunami heights by historical records, and distribution of tsunami deposits. First, region of landslide and debris deposits were made out from the bathymetry based on the bathymetry survey data (Satake and Kato, 2001) in the north slope of Oshima-Oshima. In addition, topography before the sector collapse and landslide volume were re-estimated. The volume of landslide was estimated at 2.2 km3. Based on those data, the landslide and tsunami were simulated using two-layer model considered soil mass and water mass. The model was made improvements the integrated model of landslide and tsunami (Yanagisawa et al., 2014). The angle of internal friction was calculated 4 cases, included the bottom friction term in soil mass, to affect the movement of landslide. The Manning's roughness coefficient was calculated 5 cases, included the bottom friction term in soil mass, to affect the generation of tsunami. By the parameter study, optimal solutions were found. As the results, soil mass slid slowly submarine slope and stopped after about 15 minutes. Distribution of computed debris deposits agree relatively well with region of debris deposits made out from the bathymetry. On the other hand, the first wave of tsunami was generated during 1 minute that soil mass was sliding. Calculated tsunami heights match with historical records along the coast of Okushiri and Hiyama in Hokkaido. Calculated inundation area of tsunami cover distribution of tsunami deposits found by tsunami deposits survey in Okushiri and Hiyama coast.

Collective bubble oscillations as a component of surf infrasound.

PubMed

Park, Joseph; Garcés, Milton; Fee, David; Pawlak, Geno

2008-05-01

Plunging surf is a known generator of infrasound, though the mechanisms have not been clearly identified. A model based on collective bubble oscillations created by demise of the initially entrained air pocket is examined. Computed spectra are compared to infrasound data from the island of Kauai during periods of medium, large, and extreme surf. Model results suggest that bubble oscillations generated by plunging waves are plausible generators of infrasound, and that dynamic bubble plume evolution on a temporal scale comparable to the breaking wave period may contribute to the broad spectral lobe of dominant infrasonic energy observed in measured data. Application of an inverse model has potential to characterize breaking wave size distributions, energy, and temporal changes in seafloor morphology based on remotely sensed infrasound.

LIMEPY: Lowered Isothermal Model Explorer in PYthon

NASA Astrophysics Data System (ADS)

Gieles, Mark; Zocchi, Alice

2017-10-01

LIMEPY solves distribution function (DF) based lowered isothermal models. It solves Poisson's equation used on input parameters and offers fast solutions for isotropic/anisotropic, single/multi-mass models, normalized DF values, density and velocity moments, projected properties, and generates discrete samples.

Reconfigurable generation and measurement of mutually unbiased bases for time-bin qudits

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

Lukens, Joseph M.; Islam, Nurul T.; Lim, Charles Ci Wen

Here, we propose a method for implementing mutually unbiased generation and measurement of time-bin qudits using a cascade of electro-optic phase modulator–coded fiber Bragg grating pairs. Our approach requires only a single spatial mode and can switch rapidly between basis choices. We obtain explicit solutions for dimensions d = 2, 3, and 4 that realize all d + 1 possible mutually unbiased bases and analyze the performance of our approach in quantum key distribution. Given its practicality and compatibility with current technology, our approach provides a promising springboard for scalable processing of high-dimensional time-bin states.

Reconfigurable generation and measurement of mutually unbiased bases for time-bin qudits

DOE PAGES

Lukens, Joseph M.; Islam, Nurul T.; Lim, Charles Ci Wen; ...

2018-03-12

Here, we propose a method for implementing mutually unbiased generation and measurement of time-bin qudits using a cascade of electro-optic phase modulator–coded fiber Bragg grating pairs. Our approach requires only a single spatial mode and can switch rapidly between basis choices. We obtain explicit solutions for dimensions d = 2, 3, and 4 that realize all d + 1 possible mutually unbiased bases and analyze the performance of our approach in quantum key distribution. Given its practicality and compatibility with current technology, our approach provides a promising springboard for scalable processing of high-dimensional time-bin states.

Reconfigurable generation and measurement of mutually unbiased bases for time-bin qudits

NASA Astrophysics Data System (ADS)

Lukens, Joseph M.; Islam, Nurul T.; Lim, Charles Ci Wen; Gauthier, Daniel J.

2018-03-01

We propose a method for implementing mutually unbiased generation and measurement of time-bin qudits using a cascade of electro-optic phase modulator-coded fiber Bragg grating pairs. Our approach requires only a single spatial mode and can switch rapidly between basis choices. We obtain explicit solutions for dimensions d = 2, 3, and 4 that realize all d + 1 possible mutually unbiased bases and analyze the performance of our approach in quantum key distribution. Given its practicality and compatibility with current technology, our approach provides a promising springboard for scalable processing of high-dimensional time-bin states.

Size Distribution and Dispersion of Droplets Generated by Impingement of Breaking Waves on Oil Slicks

NASA Astrophysics Data System (ADS)

Li, C.; Miller, J.; Wang, J.; Koley, S. S.; Katz, J.

2017-10-01

This laboratory experimental study investigates the temporal evolution of the size distribution of subsurface oil droplets generated as breaking waves entrain oil slicks. The measurements are performed for varying wave energy, as well as large variations in oil viscosity and oil-water interfacial tension, the latter achieved by premixing the oil with dispersant. In situ measurements using digital inline holography at two magnifications are applied for measuring the droplet sizes and Particle Image Velocimetry (PIV) for determining the temporal evolution of turbulence after wave breaking. All early (2-10 s) size distributions have two distinct size ranges with different slopes. For low dispersant to oil ratios (DOR), the transition between them could be predicted based on a turbulent Weber (We) number in the 2-4 range, suggesting that turbulence plays an important role. For smaller droplets, all the number size distributions have power of about -2.1, and for larger droplets, the power decreases well below -3. The measured steepening of the size distribution over time is predicted by a simple model involving buoyant rise and turbulence dispersion. Conversely, for DOR 1:100 and 1:25 oils, the diameter of slope transition decreases from ˜1 mm to 46 and 14 µm, respectively, much faster than the We-based prediction, and the size distribution steepens with increasing DOR. Furthermore, the concentration of micron-sized droplets of DOR 1:25 oil increases for the first 10 min after entrainment. These phenomena are presumably caused by the observed formation and breakup oil microthreads associated with tip streaming.

A grid spacing control technique for algebraic grid generation methods

NASA Technical Reports Server (NTRS)

Smith, R. E.; Kudlinski, R. A.; Everton, E. L.

1982-01-01

A technique which controls the spacing of grid points in algebraically defined coordinate transformations is described. The technique is based on the generation of control functions which map a uniformly distributed computational grid onto parametric variables defining the physical grid. The control functions are smoothed cubic splines. Sets of control points are input for each coordinate directions to outline the control functions. Smoothed cubic spline functions are then generated to approximate the input data. The technique works best in an interactive graphics environment where control inputs and grid displays are nearly instantaneous. The technique is illustrated with the two-boundary grid generation algorithm.

Classification of Complete Proteomes of Different Organisms and Protein Sets Based on Their Protein Distributions in Terms of Some Key Attributes of Proteins

DOE PAGES

Guo, Hao-Bo; Ma, Yue; Tuskan, Gerald A.; ...

2018-01-01

The existence of complete genome sequences makes it important to develop different approaches for classification of large-scale data sets and to make extraction of biological insights easier. Here, we propose an approach for classification of complete proteomes/protein sets based on protein distributions on some basic attributes. We demonstrate the usefulness of this approach by determining protein distributions in terms of two attributes: protein lengths and protein intrinsic disorder contents (ID). The protein distributions based on L and ID are surveyed for representative proteome organisms and protein sets from the three domains of life. The two-dimensional maps (designated as fingerprints here)more » from the protein distribution densities in the LD space defined by ln( L ) and ID are then constructed. The fingerprints for different organisms and protein sets are found to be distinct with each other, and they can therefore be used for comparative studies. As a test case, phylogenetic trees have been constructed based on the protein distribution densities in the fingerprints of proteomes of organisms without performing any protein sequence comparison and alignments. The phylogenetic trees generated are biologically meaningful, demonstrating that the protein distributions in the LD space may serve as unique phylogenetic signals of the organisms at the proteome level.« less

Classification of Complete Proteomes of Different Organisms and Protein Sets Based on Their Protein Distributions in Terms of Some Key Attributes of Proteins

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

Guo, Hao-Bo; Ma, Yue; Tuskan, Gerald A.

The existence of complete genome sequences makes it important to develop different approaches for classification of large-scale data sets and to make extraction of biological insights easier. Here, we propose an approach for classification of complete proteomes/protein sets based on protein distributions on some basic attributes. We demonstrate the usefulness of this approach by determining protein distributions in terms of two attributes: protein lengths and protein intrinsic disorder contents (ID). The protein distributions based on L and ID are surveyed for representative proteome organisms and protein sets from the three domains of life. The two-dimensional maps (designated as fingerprints here)more » from the protein distribution densities in the LD space defined by ln( L ) and ID are then constructed. The fingerprints for different organisms and protein sets are found to be distinct with each other, and they can therefore be used for comparative studies. As a test case, phylogenetic trees have been constructed based on the protein distribution densities in the fingerprints of proteomes of organisms without performing any protein sequence comparison and alignments. The phylogenetic trees generated are biologically meaningful, demonstrating that the protein distributions in the LD space may serve as unique phylogenetic signals of the organisms at the proteome level.« less

Serial Spike Time Correlations Affect Probability Distribution of Joint Spike Events.

PubMed

Shahi, Mina; van Vreeswijk, Carl; Pipa, Gordon

2016-01-01

Detecting the existence of temporally coordinated spiking activity, and its role in information processing in the cortex, has remained a major challenge for neuroscience research. Different methods and approaches have been suggested to test whether the observed synchronized events are significantly different from those expected by chance. To analyze the simultaneous spike trains for precise spike correlation, these methods typically model the spike trains as a Poisson process implying that the generation of each spike is independent of all the other spikes. However, studies have shown that neural spike trains exhibit dependence among spike sequences, such as the absolute and relative refractory periods which govern the spike probability of the oncoming action potential based on the time of the last spike, or the bursting behavior, which is characterized by short epochs of rapid action potentials, followed by longer episodes of silence. Here we investigate non-renewal processes with the inter-spike interval distribution model that incorporates spike-history dependence of individual neurons. For that, we use the Monte Carlo method to estimate the full shape of the coincidence count distribution and to generate false positives for coincidence detection. The results show that compared to the distributions based on homogeneous Poisson processes, and also non-Poisson processes, the width of the distribution of joint spike events changes. Non-renewal processes can lead to both heavy tailed or narrow coincidence distribution. We conclude that small differences in the exact autostructure of the point process can cause large differences in the width of a coincidence distribution. Therefore, manipulations of the autostructure for the estimation of significance of joint spike events seem to be inadequate.

Serial Spike Time Correlations Affect Probability Distribution of Joint Spike Events

PubMed Central

Shahi, Mina; van Vreeswijk, Carl; Pipa, Gordon

2016-01-01

Detecting the existence of temporally coordinated spiking activity, and its role in information processing in the cortex, has remained a major challenge for neuroscience research. Different methods and approaches have been suggested to test whether the observed synchronized events are significantly different from those expected by chance. To analyze the simultaneous spike trains for precise spike correlation, these methods typically model the spike trains as a Poisson process implying that the generation of each spike is independent of all the other spikes. However, studies have shown that neural spike trains exhibit dependence among spike sequences, such as the absolute and relative refractory periods which govern the spike probability of the oncoming action potential based on the time of the last spike, or the bursting behavior, which is characterized by short epochs of rapid action potentials, followed by longer episodes of silence. Here we investigate non-renewal processes with the inter-spike interval distribution model that incorporates spike-history dependence of individual neurons. For that, we use the Monte Carlo method to estimate the full shape of the coincidence count distribution and to generate false positives for coincidence detection. The results show that compared to the distributions based on homogeneous Poisson processes, and also non-Poisson processes, the width of the distribution of joint spike events changes. Non-renewal processes can lead to both heavy tailed or narrow coincidence distribution. We conclude that small differences in the exact autostructure of the point process can cause large differences in the width of a coincidence distribution. Therefore, manipulations of the autostructure for the estimation of significance of joint spike events seem to be inadequate. PMID:28066225

Partially Key Distribution with Public Key Cryptosystem Based on Error Control Codes

NASA Astrophysics Data System (ADS)

Tavallaei, Saeed Ebadi; Falahati, Abolfazl

Due to the low level of security in public key cryptosystems based on number theory, fundamental difficulties such as "key escrow" in Public Key Infrastructure (PKI) and a secure channel in ID-based cryptography, a new key distribution cryptosystem based on Error Control Codes (ECC) is proposed . This idea is done by some modification on McEliece cryptosystem. The security of ECC cryptosystem obtains from the NP-Completeness of block codes decoding. The capability of generating public keys with variable lengths which is suitable for different applications will be provided by using ECC. It seems that usage of these cryptosystems because of decreasing in the security of cryptosystems based on number theory and increasing the lengths of their keys would be unavoidable in future.

GOES-R GS Product Generation Infrastructure Operations

NASA Astrophysics Data System (ADS)

Blanton, M.; Gundy, J.

2012-12-01

GOES-R GS Product Generation Infrastructure Operations: The GOES-R Ground System (GS) will produce a much larger set of products with higher data density than previous GOES systems. This requires considerably greater compute and memory resources to achieve the necessary latency and availability for these products. Over time, new algorithms could be added and existing ones removed or updated, but the GOES-R GS cannot go down during this time. To meet these GOES-R GS processing needs, the Harris Corporation will implement a Product Generation (PG) infrastructure that is scalable, extensible, extendable, modular and reliable. The primary parts of the PG infrastructure are the Service Based Architecture (SBA), which includes the Distributed Data Fabric (DDF). The SBA is the middleware that encapsulates and manages science algorithms that generate products. The SBA is divided into three parts, the Executive, which manages and configures the algorithm as a service, the Dispatcher, which provides data to the algorithm, and the Strategy, which determines when the algorithm can execute with the available data. The SBA is a distributed architecture, with services connected to each other over a compute grid and is highly scalable. This plug-and-play architecture allows algorithms to be added, removed, or updated without affecting any other services or software currently running and producing data. Algorithms require product data from other algorithms, so a scalable and reliable messaging is necessary. The SBA uses the DDF to provide this data communication layer between algorithms. The DDF provides an abstract interface over a distributed and persistent multi-layered storage system (memory based caching above disk-based storage) and an event system that allows algorithm services to know when data is available and to get the data that they need to begin processing when they need it. Together, the SBA and the DDF provide a flexible, high performance architecture that can meet the needs of product processing now and as they grow in the future.

Renewable energy sources, the internet of things and the third industrial revolution: Smart grid and contemporary information and communication technologies

NASA Astrophysics Data System (ADS)

Kitsios, Aristidis; Bousakas, Konstantinos; Salame, Takla; Bogno, Bachirou; Papageorgas, Panagiotis; Vokas, Georgios A.; Mauffay, Fabrice; Petit, Pierre; Aillerie, Michel; Charles, Jean-Pierre

2017-02-01

In this paper, the energy efficiency of a contemporary Smart Grid that is based on Distributed Renewable Energy Sources (DRES) is examined under the scope of the communication systems utilized between the energy loads and the energy sources. What is evident is that the Internet of Things (IoT) technologies that are based on the existing Web infrastructure can be heavily introduced in this direction especially when combined with long range low bandwidth networking technologies, power line communication technologies and optimization methodologies for renewable energy generation. The renewable energy generation optimization will be based on devices embedded in the PV panels and the wind power generators, which will rely on bidirectional communications with local gateways and remote control stations for achieving energy efficiency. Smart meters and DRES combined with IoT communications will be the enabling technologies for the ultimate fusion of Internet technology and renewable energy generation realizing the Energy Internet.

Distribution of the background gas in the MITICA accelerator

NASA Astrophysics Data System (ADS)

Sartori, E.; Dal Bello, S.; Serianni, G.; Sonato, P.

2013-02-01

MITICA is the ITER neutral beam test facility to be built in Padova for the generation of a 40A D- ion beam with a 16×5×16 array of 1280 beamlets accelerated to 1MV. The background gas pressure distribution and the particle flows inside MITICA accelerator are critical aspects for stripping losses, generation of secondary particles and beam non-uniformities. To keep the stripping losses in the extraction and acceleration stages reasonably low, the source pressure should be 0.3 Pa or less. The gas flow in MITICA accelerator is being studied using a 3D Finite Element code, named Avocado. The gas-wall interaction model is based on the cosine law, and the whole vacuum system geometry is represented by a view factor matrix based on surface discretization and gas property definitions. Pressure distribution and mutual fluxes are then solved linearly. In this paper the result of a numerical simulation is presented, showing the steady-state pressure distribution inside the accelerator when gas enters the system at room temperature. The accelerator model is limited to a horizontal slice 400 mm high (1/4 of the accelerator height). The pressure profile at solid walls and through the beamlet axis is obtained, allowing the evaluation and the discussion of the background gas distribution and nonuniformity. The particle flux at the inlet and outlet boundaries (namely the grounded grid apertures and the lateral conductances respectively) will be discussed.

Pore Pressure and Stress Distributions Around a Hydraulic Fracture in Heterogeneous Rock

NASA Astrophysics Data System (ADS)

Gao, Qian; Ghassemi, Ahmad

2017-12-01

One of the most significant characteristics of unconventional petroleum bearing formations is their heterogeneity, which affects the stress distribution, hydraulic fracture propagation and also fluid flow. This study focuses on the stress and pore pressure redistributions during hydraulic stimulation in a heterogeneous poroelastic rock. Lognormal random distributions of Young's modulus and permeability are generated to simulate the heterogeneous distributions of material properties. A 3D fully coupled poroelastic model based on the finite element method is presented utilizing a displacement-pressure formulation. In order to verify the model, numerical results are compared with analytical solutions showing excellent agreements. The effects of heterogeneities on stress and pore pressure distributions around a penny-shaped fracture in poroelastic rock are then analyzed. Results indicate that the stress and pore pressure distributions are more complex in a heterogeneous reservoir than in a homogeneous one. The spatial extent of stress reorientation during hydraulic stimulations is a function of time and is continuously changing due to the diffusion of pore pressure in the heterogeneous system. In contrast to the stress distributions in homogeneous media, irregular distributions of stresses and pore pressure are observed. Due to the change of material properties, shear stresses and nonuniform deformations are generated. The induced shear stresses in heterogeneous rock cause the initial horizontal principal stresses to rotate out of horizontal planes.

A Cloud-Based X73 Ubiquitous Mobile Healthcare System: Design and Implementation

PubMed Central

Ji, Zhanlin; O'Droma, Máirtín; Zhang, Xin; Zhang, Xueji

2014-01-01

Based on the user-centric paradigm for next generation networks, this paper describes a ubiquitous mobile healthcare (uHealth) system based on the ISO/IEEE 11073 personal health data (PHD) standards (X73) and cloud computing techniques. A number of design issues associated with the system implementation are outlined. The system includes a middleware on the user side, providing a plug-and-play environment for heterogeneous wireless sensors and mobile terminals utilizing different communication protocols and a distributed “big data” processing subsystem in the cloud. The design and implementation of this system are envisaged as an efficient solution for the next generation of uHealth systems. PMID:24737958

Identification of infusion strategy for achieving repeatable nanoparticle distribution and quantification of thermal dosage using micro-CT Hounsfield unit in magnetic nanoparticle hyperthermia.

PubMed

LeBrun, Alexander; Joglekar, Tejashree; Bieberich, Charles; Ma, Ronghui; Zhu, Liang

2016-01-01

The objective of this study was to identify an injection strategy leading to repeatable nanoparticle deposition patterns in tumours and to quantify volumetric heat generation rate distribution based on micro-CT Hounsfield unit (HU) in magnetic nanoparticle hyperthermia. In vivo animal experiments were performed on graft prostatic cancer (PC3) tumours in immunodeficient mice to investigate whether lowering ferrofluid infusion rate improves control of the distribution of magnetic nanoparticles in tumour tissue. Nanoparticle distribution volume obtained from micro-CT scan was used to evaluate spreading of the nanoparticles from the injection site in tumours. Heating experiments were performed to quantify relationships among micro-CT HU values, local nanoparticle concentrations in the tumours, and the ferrofluid-induced volumetric heat generation rate (q(MNH)) when nanoparticles were subject to an alternating magnetic field. An infusion rate of 3 µL/min was identified to result in the most repeatable nanoparticle distribution in PC3 tumours. Linear relationships have been obtained to first convert micro-CT greyscale values to HU values, then to local nanoparticle concentrations, and finally to nanoparticle-induced q(MNH) values. The total energy deposition rate in tumours was calculated and the observed similarity in total energy deposition rates in all three infusion rate groups suggests improvement in minimising nanoparticle leakage from the tumours. The results of this study demonstrate that micro-CT generated q(MNH) distribution and tumour physical models improve predicting capability of heat transfer simulation for designing reliable treatment protocols using magnetic nanoparticle hyperthermia.

POI Summarization by Aesthetics Evaluation From Crowd Source Social Media.

PubMed

Qian, Xueming; Li, Cheng; Lan, Ke; Hou, Xingsong; Li, Zhetao; Han, Junwei

2018-03-01

Place-of-Interest (POI) summarization by aesthetics evaluation can recommend a set of POI images to the user and it is significant in image retrieval. In this paper, we propose a system that summarizes a collection of POI images regarding both aesthetics and diversity of the distribution of cameras. First, we generate visual albums by a coarse-to-fine POI clustering approach and then generate 3D models for each album by the collected images from social media. Second, based on the 3D to 2D projection relationship, we select candidate photos in terms of the proposed crowd source saliency model. Third, in order to improve the performance of aesthetic measurement model, we propose a crowd-sourced saliency detection approach by exploring the distribution of salient regions in the 3D model. Then, we measure the composition aesthetics of each image and we explore crowd source salient feature to yield saliency map, based on which, we propose an adaptive image adoption approach. Finally, we combine the diversity and the aesthetics to recommend aesthetic pictures. Experimental results show that the proposed POI summarization approach can return images with diverse camera distributions and aesthetics.

New model for distributed multimedia databases and its application to networking of museums

NASA Astrophysics Data System (ADS)

Kuroda, Kazuhide; Komatsu, Naohisa; Komiya, Kazumi; Ikeda, Hiroaki

1998-02-01

This paper proposes a new distributed multimedia data base system where the databases storing MPEG-2 videos and/or super high definition images are connected together through the B-ISDN's, and also refers to an example of the networking of museums on the basis of the proposed database system. The proposed database system introduces a new concept of the 'retrieval manager' which functions an intelligent controller so that the user can recognize a set of image databases as one logical database. A user terminal issues a request to retrieve contents to the retrieval manager which is located in the nearest place to the user terminal on the network. Then, the retrieved contents are directly sent through the B-ISDN's to the user terminal from the server which stores the designated contents. In this case, the designated logical data base dynamically generates the best combination of such a retrieving parameter as a data transfer path referring to directly or data on the basis of the environment of the system. The generated retrieving parameter is then executed to select the most suitable data transfer path on the network. Therefore, the best combination of these parameters fits to the distributed multimedia database system.

A matrix-algebraic formulation of distributed-memory maximal cardinality matching algorithms in bipartite graphs

DOE PAGES

Azad, Ariful; Buluç, Aydın

2016-05-16

We describe parallel algorithms for computing maximal cardinality matching in a bipartite graph on distributed-memory systems. Unlike traditional algorithms that match one vertex at a time, our algorithms process many unmatched vertices simultaneously using a matrix-algebraic formulation of maximal matching. This generic matrix-algebraic framework is used to develop three efficient maximal matching algorithms with minimal changes. The newly developed algorithms have two benefits over existing graph-based algorithms. First, unlike existing parallel algorithms, cardinality of matching obtained by the new algorithms stays constant with increasing processor counts, which is important for predictable and reproducible performance. Second, relying on bulk-synchronous matrix operations,more » these algorithms expose a higher degree of parallelism on distributed-memory platforms than existing graph-based algorithms. We report high-performance implementations of three maximal matching algorithms using hybrid OpenMP-MPI and evaluate the performance of these algorithm using more than 35 real and randomly generated graphs. On real instances, our algorithms achieve up to 200 × speedup on 2048 cores of a Cray XC30 supercomputer. Even higher speedups are obtained on larger synthetically generated graphs where our algorithms show good scaling on up to 16,384 cores.« less

On-site SiH4 generator using hydrogen plasma generated in slit-type narrow gap

NASA Astrophysics Data System (ADS)

Takei, Norihisa; Shinoda, Fumiya; Kakiuchi, Hiroaki; Yasutake, Kiyoshi; Ohmi, Hiromasa

2018-06-01

We have been developing an on-site silane (SiH4) generator based on use of the chemical etching reaction between solid silicon (Si) and the high-density H atoms that are generated in high-pressure H2 plasma. In this study, we have developed a slit-type plasma source for high-efficiency SiH4 generation. High-density H2 plasma was generated in a narrow slit-type discharge gap using a 2.45 GHz microwave power supply. The plasma’s optical emission intensity distribution along the slit was measured and the resulting distribution was reflected by both the electric power distribution and the hydrogen gas flow. Because the Si etching rate strongly affects the SiH4 generation rate, the Si etching behavior was investigated with respect to variations in the experimental parameters. The weight etch rate increased monotonically with increasing input microwave power. However, the weight etch rate decreased with increasing H2 pressure and an increasing plasma gap. This reduction in the etch rate appears to be related to shrinkage of the plasma generation area because increased input power is required to maintain a constant plasma area with increasing H2 pressure and the increasing plasma gap. Additionally, the weight etch rate also increases with increasing H2 flow rate. The SiH4 generation rate of the slit-type plasma source was also evaluated using gas-phase Fourier transform infrared absorption spectroscopy and the material utilization efficiencies of both Si and the H2 gas for SiH4 gas formation were discussed. The main etch product was determined to be SiH4 and the developed plasma source achieved a SiH4 generation rate of 10 sccm (standard cubic centimeters per minute) at an input power of 900 W. In addition, the Si utilization efficiency exceeded 60%.

Availability Based Tariff and its impact On different Industry Players-A Review

NASA Astrophysics Data System (ADS)

Holmukhe, R. M.; Pawar, Yogini; Desai, R. S.; Hasarmani, T. S.

2010-10-01

ABT is a performance-based tariff for the supply of electricity by generators owned and controlled by the central government. It is also a new system of scheduling and dispatch, which requires both generators and beneficiaries to commit to day-ahead schedules. It is a system of rewards and penalties seeking to enforce day ahead pre-committed schedules, though variations are permitted if notified One and one half hours in advance. The order emphasizes prompt payment of dues. ABT (Availability Based Tariff) along with the Electricity Act of 2003 is perhaps the most significant and definitive step taken in the Indian power sector so far to bring more efficiency and focus to this vital infrastructure. The ABT mechanism is based on financial principles. ABT scheme is for unscheduled interchange of power. The paper reviews ABT issues, its components, clauses, mechanism, benefits and the impact of grid on different players like generation utilities, grid operator, consumers involved in power generation, transmission and distribution. While the proposed tariff structure has wide implications for each player, this deals exclusively with the technology challenges/opportunities thrown up by ABT.

Generating Within-Plant Spatial Distributions of an Insect Herbivore Based on Aggregation Patterns and Per-Node Infestation Probabilities.

PubMed

Rincon, Diego F; Hoy, Casey W; Cañas, Luis A

2015-04-01

Most predator-prey models extrapolate functional responses from small-scale experiments assuming spatially uniform within-plant predator-prey interactions. However, some predators focus their search in certain plant regions, and herbivores tend to select leaves to balance their nutrient uptake and exposure to plant defenses. Individual-based models that account for heterogeneous within-plant predator-prey interactions can be used to scale-up functional responses, but they would require the generation of explicit prey spatial distributions within-plant architecture models. The silverleaf whitefly, Bemisia tabaci biotype B (Gennadius) (Hemiptera: Aleyrodidae), is a significant pest of tomato crops worldwide that exhibits highly aggregated populations at several spatial scales, including within the plant. As part of an analytical framework to understand predator-silverleaf whitefly interactions, the objective of this research was to develop an algorithm to generate explicit spatial counts of silverleaf whitefly nymphs within tomato plants. The algorithm requires the plant size and the number of silverleaf whitefly individuals to distribute as inputs, and includes models that describe infestation probabilities per leaf nodal position and the aggregation pattern of the silverleaf whitefly within tomato plants and leaves. The output is a simulated number of silverleaf whitefly individuals for each leaf and leaflet on one or more plants. Parameter estimation was performed using nymph counts per leaflet censused from 30 artificially infested tomato plants. Validation revealed a substantial agreement between algorithm outputs and independent data that included the distribution of counts of both eggs and nymphs. This algorithm can be used in simulation models that explore the effect of local heterogeneity on whitefly-predator dynamics. © The Authors 2015. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Distributed Modelling of Stormflow Generation: Assessing the Effect of Ground Cover

NASA Astrophysics Data System (ADS)

Jarihani, B.; Sidle, R. C.; Roth, C. H.; Bartley, R.; Wilkinson, S. N.

2017-12-01

Understanding the effects of grazing management and land cover changes on surface hydrology is important for water resources and land management. A distributed hydrological modelling platform, wflow, (that was developed as part of Deltares's OpenStreams project) is used to assess the effect of land management practices on runoff generation processes. The model was applied to Weany Creek, a small catchment (13.6 km2) of the Burdekin Basin, North Australia, which is being studied to understand sources of sediment and nutrients to the Great Barrier Reef. Satellite and drone-based ground cover data, high resolution topography from LiDAR, soil properties, and distributed rainfall data were used to parameterise the model. Wflow was used to predict total runoff, peak runoff, time of rise, and lag time for several events of varying magnitudes and antecedent moisture conditions. A nested approach was employed to calibrate the model by using recorded flow hydrographs at three scales: (1) a hillslope sub-catchment: (2) a gullied sub-catchment; and the 13.6 km2 catchment outlet. Model performance was evaluated by comparing observed and predicted stormflow hydrograph attributes using the Nash Sutcliffe efficiency metric. By using a nested approach, spatiotemporal patterns of overland flow occurrence across the catchment can also be evaluated. The results show that a process-based distributed model can be calibrated to simulate spatial and temporal patterns of runoff generation processes, to help identify dominant processes which may be addressed by land management to improve rainfall retention. The model will be used to assess the effects of ground cover changes due to management practices in grazed lands on storm runoff.

Distributed Computing Framework for Synthetic Radar Application

NASA Technical Reports Server (NTRS)

Gurrola, Eric M.; Rosen, Paul A.; Aivazis, Michael

2006-01-01

We are developing an extensible software framework, in response to Air Force and NASA needs for distributed computing facilities for a variety of radar applications. The objective of this work is to develop a Python based software framework, that is the framework elements of the middleware that allows developers to control processing flow on a grid in a distributed computing environment. Framework architectures to date allow developers to connect processing functions together as interchangeable objects, thereby allowing a data flow graph to be devised for a specific problem to be solved. The Pyre framework, developed at the California Institute of Technology (Caltech), and now being used as the basis for next-generation radar processing at JPL, is a Python-based software framework. We have extended the Pyre framework to include new facilities to deploy processing components as services, including components that monitor and assess the state of the distributed network for eventual real-time control of grid resources.

Analysis of critical operating conditions for LV distribution networks with microgrids

NASA Astrophysics Data System (ADS)

Zehir, M. A.; Batman, A.; Sonmez, M. A.; Font, A.; Tsiamitros, D.; Stimoniaris, D.; Kollatou, T.; Bagriyanik, M.; Ozdemir, A.; Dialynas, E.

2016-11-01

Increase in the penetration of Distributed Generation (DG) in distribution networks, raises the risk of voltage limit violations while contributing to line losses. Especially in low voltage (LV) distribution networks (secondary distribution networks), impacts of active power flows on the bus voltages and on the network losses are more dominant. As network operators must meet regulatory limitations, they have to take into account the most critical operating conditions in their systems. In this study, it is aimed to present the impact of the worst operation cases of LV distribution networks comprising microgrids. Simulation studies are performed on a field data-based virtual test-bed. The simulations are repeated for several cases consisting different microgrid points of connection with different network loading and microgrid supply/demand conditions.

Distribution-Agnostic Stochastic Optimal Power Flow for Distribution Grids: Preprint

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

Baker, Kyri; Dall'Anese, Emiliano; Summers, Tyler

2016-09-01

This paper outlines a data-driven, distributionally robust approach to solve chance-constrained AC optimal power flow problems in distribution networks. Uncertain forecasts for loads and power generated by photovoltaic (PV) systems are considered, with the goal of minimizing PV curtailment while meeting power flow and voltage regulation constraints. A data- driven approach is utilized to develop a distributionally robust conservative convex approximation of the chance-constraints; particularly, the mean and covariance matrix of the forecast errors are updated online, and leveraged to enforce voltage regulation with predetermined probability via Chebyshev-based bounds. By combining an accurate linear approximation of the AC power flowmore » equations with the distributionally robust chance constraint reformulation, the resulting optimization problem becomes convex and computationally tractable.« less

Programmable quantum random number generator without postprocessing.

PubMed

Nguyen, Lac; Rehain, Patrick; Sua, Yong Meng; Huang, Yu-Ping

2018-02-15

We demonstrate a viable source of unbiased quantum random numbers whose statistical properties can be arbitrarily programmed without the need for any postprocessing such as randomness distillation or distribution transformation. It is based on measuring the arrival time of single photons in shaped temporal modes that are tailored with an electro-optical modulator. We show that quantum random numbers can be created directly in customized probability distributions and pass all randomness tests of the NIST and Dieharder test suites without any randomness extraction. The min-entropies of such generated random numbers are measured close to the theoretical limits, indicating their near-ideal statistics and ultrahigh purity. Easy to implement and arbitrarily programmable, this technique can find versatile uses in a multitude of data analysis areas.

A Distributed Algorithm for Economic Dispatch Over Time-Varying Directed Networks With Delays

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

Yang, Tao; Lu, Jie; Wu, Di

In power system operation, economic dispatch problem (EDP) is designed to minimize the total generation cost while meeting the demand and satisfying generator capacity limits. This paper proposes an algorithm based on the gradient-push method to solve the EDP in a distributed manner over communication networks potentially with time-varying topologies and communication delays. It has been shown that the proposed method is guaranteed to solve the EDP if the time-varying directed communication network is uniformly jointly strongly connected. Moreover, the proposed algorithm is also able to handle arbitrarily large but bounded time delays on communication links. Numerical simulations are usedmore » to illustrate and validate the proposed algorithm.« less

High-speed polarization-encoded quantum key distribution based on silicon photonic integrated devices

NASA Astrophysics Data System (ADS)

Bunandar, Darius; Urayama, Junji; Boynton, Nicholas; Martinez, Nicholas; Derose, Christopher; Lentine, Anthony; Davids, Paul; Camacho, Ryan; Wong, Franco; Englund, Dirk

We present a compact polarization-encoded quantum key distribution (QKD) transmitter near a 1550-nm wavelength implemented on a CMOS-compatible silicon-on-insulator photonics platform. The transmitter generates arbitrary polarization qubits at gigahertz bandwidth with an extinction ratio better than 30 dB using high-speed carrier-depletion phase modulators. We demonstrate the performance of this device by generating secret keys at a rate of 1 Mbps in a complete QKD field test. Our work shows the potential of using advanced photonic integrated circuits to enable high-speed quantum-secure communications. This work was supported by the SECANT QKD Grand Challenge, the Samsung Global Research Outreach Program, and the Air Force Office of Scientific Research.

A suffix arrays based approach to semantic search in P2P systems

NASA Astrophysics Data System (ADS)

Shi, Qingwei; Zhao, Zheng; Bao, Hu

2007-09-01

Building a semantic search system on top of peer-to-peer (P2P) networks is becoming an attractive and promising alternative scheme for the reason of scalability, Data freshness and search cost. In this paper, we present a Suffix Arrays based algorithm for Semantic Search (SASS) in P2P systems, which generates a distributed Semantic Overlay Network (SONs) construction for full-text search in P2P networks. For each node through the P2P network, SASS distributes document indices based on a set of suffix arrays, by which clusters are created depending on words or phrases shared between documents, therefore, the search cost for a given query is decreased by only scanning semantically related documents. In contrast to recently announced SONs scheme designed by using metadata or predefined-class, SASS is an unsupervised approach for decentralized generation of SONs. SASS is also an incremental, linear time algorithm, which efficiently handle the problem of nodes update in P2P networks. Our simulation results demonstrate that SASS yields high search efficiency in dynamic environments.

Intelligent and robust optimization frameworks for smart grids

NASA Astrophysics Data System (ADS)

Dhansri, Naren Reddy

A smart grid implies a cyberspace real-time distributed power control system to optimally deliver electricity based on varying consumer characteristics. Although smart grids solve many of the contemporary problems, they give rise to new control and optimization problems with the growing role of renewable energy sources such as wind or solar energy. Under highly dynamic nature of distributed power generation and the varying consumer demand and cost requirements, the total power output of the grid should be controlled such that the load demand is met by giving a higher priority to renewable energy sources. Hence, the power generated from renewable energy sources should be optimized while minimizing the generation from non renewable energy sources. This research develops a demand-based automatic generation control and optimization framework for real-time smart grid operations by integrating conventional and renewable energy sources under varying consumer demand and cost requirements. Focusing on the renewable energy sources, the intelligent and robust control frameworks optimize the power generation by tracking the consumer demand in a closed-loop control framework, yielding superior economic and ecological benefits and circumvent nonlinear model complexities and handles uncertainties for superior real-time operations. The proposed intelligent system framework optimizes the smart grid power generation for maximum economical and ecological benefits under an uncertain renewable wind energy source. The numerical results demonstrate that the proposed framework is a viable approach to integrate various energy sources for real-time smart grid implementations. The robust optimization framework results demonstrate the effectiveness of the robust controllers under bounded power plant model uncertainties and exogenous wind input excitation while maximizing economical and ecological performance objectives. Therefore, the proposed framework offers a new worst-case deterministic optimization algorithm for smart grid automatic generation control.

Rapid prototyping of reflectors for vehicle lighting using laser activated remote phosphor

NASA Astrophysics Data System (ADS)

Lachmayer, Roland; Kloppenburg, Gerolf; Wolf, Alexander

2015-03-01

Bright white light sources are of significant importance for automotive front lighting systems. Today's upper class vehicles mainly use HID or LED as light source. As a further step in this development laser diode based systems offer high luminance, efficiency and allow the realization of new styling concepts and new dynamic lighting functions. These white laser diode systems can either be realized by mixing different spectral sources or by combining diodes with specific phosphors. Based on the approach of generating light using a laser and remote phosphor, lighting modules are manufactured. Four blue laser diodes (450 nm) are used to activate a phosphor coating and thus to achieve white light. A segmented paraboloid reflector generates the desired light distribution for an additional car headlamp. We use high speed milling and selective laser melting to build the reflector system for this lighting module. We compare the spectral reflection grade of these materials. Furthermore the generated modules are analyzed regarding their efficiency and light distribution. The use of Rapid Prototyping technologies allows an early validation of the chosen concept and is supposed to reduce cost and time in the product development process significantly. Therefor we discuss costs and times of the applied manufacturing technologies.

Hardware system of X-wave generator with simple driving pulses

NASA Astrophysics Data System (ADS)

Li, Xu; Li, Yaqin; Xiao, Feng; Ding, Mingyue; Yuchi, Ming

2013-03-01

The limited diffraction beams such as X-wave have the properties of larger depth of field. Thus, it has the potential to generate ultra-high frame rate ultrasound images. However, in practice, the real-time generation of X-wave ultrasonic field requires complex and high-cost system, especially the precise and specific voltage time distribution part for the excitation of each distinct array element. In order to simplify the hardware realization of X-wave, based on the previous works, X-wave excitation signals were decomposed and expressed as the superposition of a group of simple driving pulses, such as rectangular and triangular waves. The hardware system for the X-wave generator was also designed. The generator consists of a computer for communication with the circuit, universal serial bus (USB) based micro-controller unit (MCU) for data transmission, field programmable gate array (FPGA) based Direct Digital Synthesizer(DDS), 12-bit digital-to-analog (D/A) converter and a two stage amplifier.The hardware simulation results show that the designed system can generate the waveforms at different radius approximating the theoretical X-wave excitations with a maximum error of 0.49% triggered by the quantification of amplitude data.

Analysis of wind energy generation possibilities with various rotor types at disadvantageous wind condition zones

NASA Astrophysics Data System (ADS)

Bieniek, Andrzej

2017-10-01

The paper describe possibilities of energy generation using various rotor types but especially with multi-blade wind engine operates in the areas with unfavourable wind condition. The paper presents also wind energy conversion estimation results presented based on proposed solution of multi-blade wind turbine of outer diameter of 4 m. Based on the wind distribution histogram from the disadvantage wind condition zones (city of Basel) and taking into account design and estimated operating indexes of the considered wind engine rotor an annual energy generation was estimated. Also theoretical energy generation using various types of wind turbines operates at disadvantage wind conditions zones were estimated and compared. The conducted analysis shows that introduction of multi-blade wind rotor instead of the most popular 3- blades or vertical axis rotors results of about 5% better energy generation. Simultaneously there are energy production also at very disadvantages wind condition at wind speed lower then 4 m s-1. Based on considered construction of multi-blade wind engine the rise of rotor mounting height from 10 to 30 m results with more then 300 % better results in terms of electric energy generation.

Trial Promoter: A Web-Based Tool for Boosting the Promotion of Clinical Research Through Social Media.

PubMed

Reuter, Katja; Ukpolo, Francis; Ward, Edward; Wilson, Melissa L; Angyan, Praveen

2016-06-29

Scarce information about clinical research, in particular clinical trials, is among the top reasons why potential participants do not take part in clinical studies. Without volunteers, on the other hand, clinical research and the development of novel approaches to preventing, diagnosing, and treating disease are impossible. Promising digital options such as social media have the potential to work alongside traditional methods to boost the promotion of clinical research. However, investigators and research institutions are challenged to leverage these innovations while saving time and resources. To develop and test the efficiency of a Web-based tool that automates the generation and distribution of user-friendly social media messages about clinical trials. Trial Promoter is developed in Ruby on Rails, HTML, cascading style sheet (CSS), and JavaScript. In order to test the tool and the correctness of the generated messages, clinical trials (n=46) were randomized into social media messages and distributed via the microblogging social media platform Twitter and the social network Facebook. The percent correct was calculated to determine the probability with which Trial Promoter generates accurate messages. During a 10-week testing phase, Trial Promoter automatically generated and published 525 user-friendly social media messages on Twitter and Facebook. On average, Trial Promoter correctly used the message templates and substituted the message parameters (text, URLs, and disease hashtags) 97.7% of the time (1563/1600). Trial Promoter may serve as a promising tool to render clinical trial promotion more efficient while requiring limited resources. It supports the distribution of any research or other types of content. The Trial Promoter code and installation instructions are freely available online.

Trial Promoter: A Web-Based Tool for Boosting the Promotion of Clinical Research Through Social Media

PubMed Central

Ukpolo, Francis; Ward, Edward; Wilson, Melissa L

2016-01-01

Background Scarce information about clinical research, in particular clinical trials, is among the top reasons why potential participants do not take part in clinical studies. Without volunteers, on the other hand, clinical research and the development of novel approaches to preventing, diagnosing, and treating disease are impossible. Promising digital options such as social media have the potential to work alongside traditional methods to boost the promotion of clinical research. However, investigators and research institutions are challenged to leverage these innovations while saving time and resources. Objective To develop and test the efficiency of a Web-based tool that automates the generation and distribution of user-friendly social media messages about clinical trials. Methods Trial Promoter is developed in Ruby on Rails, HTML, cascading style sheet (CSS), and JavaScript. In order to test the tool and the correctness of the generated messages, clinical trials (n=46) were randomized into social media messages and distributed via the microblogging social media platform Twitter and the social network Facebook. The percent correct was calculated to determine the probability with which Trial Promoter generates accurate messages. Results During a 10-week testing phase, Trial Promoter automatically generated and published 525 user-friendly social media messages on Twitter and Facebook. On average, Trial Promoter correctly used the message templates and substituted the message parameters (text, URLs, and disease hashtags) 97.7% of the time (1563/1600). Conclusions Trial Promoter may serve as a promising tool to render clinical trial promotion more efficient while requiring limited resources. It supports the distribution of any research or other types of content. The Trial Promoter code and installation instructions are freely available online. PMID:27357424

Voltage-Load Sensitivity Matrix Based Demand Response for Voltage Control in High Solar Penetration Distribution Feeders

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

Zhu, Xiangqi; Wang, Jiyu; Mulcahy, David

This paper presents a voltage-load sensitivity matrix (VLSM) based voltage control method to deploy demand response resources for controlling voltage in high solar penetration distribution feeders. The IEEE 123-bus system in OpenDSS is used for testing the performance of the preliminary VLSM-based voltage control approach. A load disaggregation process is applied to disaggregate the total load profile at the feeder head to each load nodes along the feeder so that loads are modeled at residential house level. Measured solar generation profiles are used in the simulation to model the impact of solar power on distribution feeder voltage profiles. Different casemore » studies involving various PV penetration levels and installation locations have been performed. Simulation results show that the VLSM algorithm performance meets the voltage control requirements and is an effective voltage control strategy.« less

Modeling nurses' attitude toward using automated unit-based medication storage and distribution systems: an extension of the technology acceptance model.

PubMed

Escobar-Rodríguez, Tomás; Romero-Alonso, María Mercedes

2013-05-01

This article analyzes the attitude of nurses toward the use of automated unit-based medication storage and distribution systems and identifies influencing factors. Understanding these factors provides an opportunity to explore actions that might be taken to boost adoption by potential users. The theoretical grounding for this research is the Technology Acceptance Model. The Technology Acceptance Model specifies the causal relationships between perceived usefulness, perceived ease of use, attitude toward using, and actual usage behavior. The research model has six constructs, and nine hypotheses were generated from connections between these six constructs. These constructs include perceived risks, experience level, and training. The findings indicate that these three external variables are related to the perceived ease of use and perceived usefulness of automated unit-based medication storage and distribution systems, and therefore, they have a significant influence on attitude toward the use of these systems.

THE IRON CYCLE AND OXIDATIVE STRESS IN THE LUNG

EPA Science Inventory

While iron is essential for many aspects of cellular function, it can also generate oxygen-based free radicals that result in injury to biological molecules. For this reason, iron acquisition and distribution must be tightly regulated. Constant exposure to the atmosphere, howev...

Intertidal habitat utilization patterns of birds in a Northeast Pacific estuary

EPA Science Inventory

A habitat-based framework is a practical method for developing models (or, ecological production functions, EPFs) to describe the spatial distribution of ecosystem services. To generate EPFs for Yaquina estuary, Oregon, USA, we compared bird use patterns among intertidal habitats...

Assessing risk based on uncertain avalanche activity patterns

NASA Astrophysics Data System (ADS)

Zeidler, Antonia; Fromm, Reinhard

2015-04-01

Avalanches may affect critical infrastructure and may cause great economic losses. The planning horizon of infrastructures, e.g. hydropower generation facilities, reaches well into the future. Based on the results of previous studies on the effect of changing meteorological parameters (precipitation, temperature) and the effect on avalanche activity we assume that there will be a change of the risk pattern in future. The decision makers need to understand what the future might bring to best formulate their mitigation strategies. Therefore, we explore a commercial risk software to calculate risk for the coming years that might help in decision processes. The software @risk, is known to many larger companies, and therefore we explore its capabilities to include avalanche risk simulations in order to guarantee a comparability of different risks. In a first step, we develop a model for a hydropower generation facility that reflects the problem of changing avalanche activity patterns in future by selecting relevant input parameters and assigning likely probability distributions. The uncertain input variables include the probability of avalanches affecting an object, the vulnerability of an object, the expected costs for repairing the object and the expected cost due to interruption. The crux is to find the distribution that best represents the input variables under changing meteorological conditions. Our focus is on including the uncertain probability of avalanches based on the analysis of past avalanche data and expert knowledge. In order to explore different likely outcomes we base the analysis on three different climate scenarios (likely, worst case, baseline). For some variables, it is possible to fit a distribution to historical data, whereas in cases where the past dataset is insufficient or not available the software allows to select from over 30 different distribution types. The Monte Carlo simulation uses the probability distribution of uncertain variables using all valid combinations of the values of input variables to simulate all possible outcomes. In our case the output is the expected risk (Euro/year) for each object (e.g. water intake) considered and the entire hydropower generation system. The output is again a distribution that is interpreted by the decision makers as the final strategy depends on the needs and requirements of the end-user, which may be driven by personal preferences. In this presentation, we will show a way on how we used the uncertain information on avalanche activity in future to subsequently use it in a commercial risk software and therefore bringing the knowledge of natural hazard experts to decision makers.

Data Collection for Mobile Group Consumption: An Asynchronous Distributed Approach.

PubMed

Zhu, Weiping; Chen, Weiran; Hu, Zhejie; Li, Zuoyou; Liang, Yue; Chen, Jiaojiao

2016-04-06

Mobile group consumption refers to consumption by a group of people, such as a couple, a family, colleagues and friends, based on mobile communications. It differs from consumption only involving individuals, because of the complex relations among group members. Existing data collection systems for mobile group consumption are centralized, which has the disadvantages of being a performance bottleneck, having single-point failure and increasing business and security risks. Moreover, these data collection systems are based on a synchronized clock, which is often unrealistic because of hardware constraints, privacy concerns or synchronization cost. In this paper, we propose the first asynchronous distributed approach to collecting data generated by mobile group consumption. We formally built a system model thereof based on asynchronous distributed communication. We then designed a simulation system for the model for which we propose a three-layer solution framework. After that, we describe how to detect the causality relation of two/three gathering events that happened in the system based on the collected data. Various definitions of causality relations based on asynchronous distributed communication are supported. Extensive simulation results show that the proposed approach is effective for data collection relating to mobile group consumption.

Data Collection for Mobile Group Consumption: An Asynchronous Distributed Approach †

PubMed Central

Zhu, Weiping; Chen, Weiran; Hu, Zhejie; Li, Zuoyou; Liang, Yue; Chen, Jiaojiao

2016-01-01

Mobile group consumption refers to consumption by a group of people, such as a couple, a family, colleagues and friends, based on mobile communications. It differs from consumption only involving individuals, because of the complex relations among group members. Existing data collection systems for mobile group consumption are centralized, which has the disadvantages of being a performance bottleneck, having single-point failure and increasing business and security risks. Moreover, these data collection systems are based on a synchronized clock, which is often unrealistic because of hardware constraints, privacy concerns or synchronization cost. In this paper, we propose the first asynchronous distributed approach to collecting data generated by mobile group consumption. We formally built a system model thereof based on asynchronous distributed communication. We then designed a simulation system for the model for which we propose a three-layer solution framework. After that, we describe how to detect the causality relation of two/three gathering events that happened in the system based on the collected data. Various definitions of causality relations based on asynchronous distributed communication are supported. Extensive simulation results show that the proposed approach is effective for data collection relating to mobile group consumption. PMID:27058544

A better sequence-read simulator program for metagenomics.

PubMed

Johnson, Stephen; Trost, Brett; Long, Jeffrey R; Pittet, Vanessa; Kusalik, Anthony

2014-01-01

There are many programs available for generating simulated whole-genome shotgun sequence reads. The data generated by many of these programs follow predefined models, which limits their use to the authors' original intentions. For example, many models assume that read lengths follow a uniform or normal distribution. Other programs generate models from actual sequencing data, but are limited to reads from single-genome studies. To our knowledge, there are no programs that allow a user to generate simulated data following non-parametric read-length distributions and quality profiles based on empirically-derived information from metagenomics sequencing data. We present BEAR (Better Emulation for Artificial Reads), a program that uses a machine-learning approach to generate reads with lengths and quality values that closely match empirically-derived distributions. BEAR can emulate reads from various sequencing platforms, including Illumina, 454, and Ion Torrent. BEAR requires minimal user input, as it automatically determines appropriate parameter settings from user-supplied data. BEAR also uses a unique method for deriving run-specific error rates, and extracts useful statistics from the metagenomic data itself, such as quality-error models. Many existing simulators are specific to a particular sequencing technology; however, BEAR is not restricted in this way. Because of its flexibility, BEAR is particularly useful for emulating the behaviour of technologies like Ion Torrent, for which no dedicated sequencing simulators are currently available. BEAR is also the first metagenomic sequencing simulator program that automates the process of generating abundances, which can be an arduous task. BEAR is useful for evaluating data processing tools in genomics. It has many advantages over existing comparable software, such as generating more realistic reads and being independent of sequencing technology, and has features particularly useful for metagenomics work.

Deployment strategy for battery energy storage system in distribution network based on voltage violation regulation

NASA Astrophysics Data System (ADS)

Wu, H.; Zhou, L.; Xu, T.; Fang, W. L.; He, W. G.; Liu, H. M.

2017-11-01

In order to improve the situation of voltage violation caused by the grid-connection of photovoltaic (PV) system in a distribution network, a bi-level programming model is proposed for battery energy storage system (BESS) deployment. The objective function of inner level programming is to minimize voltage violation, with the power of PV and BESS as the variables. The objective function of outer level programming is to minimize the comprehensive function originated from inner layer programming and all the BESS operating parameters, with the capacity and rated power of BESS as the variables. The differential evolution (DE) algorithm is applied to solve the model. Based on distribution network operation scenarios with photovoltaic generation under multiple alternative output modes, the simulation results of IEEE 33-bus system prove that the deployment strategy of BESS proposed in this paper is well adapted to voltage violation regulation invariable distribution network operation scenarios. It contributes to regulating voltage violation in distribution network, as well as to improve the utilization of PV systems.

Mapping of Bird Distributions from Point Count Surveys

Treesearch

John R. Sauer; Grey W. Pendleton; Sandra Orsillo

1995-01-01

Maps generated from bird survey data are used for a variety of scientific purposes, but little is known about their bias and precision. We review methods for preparing maps from point count data and appropriate sampling methods for maps based on point counts. Maps based on point counts can be affected by bias associated with incomplete counts, primarily due to changes...

A PLM-based automated inspection planning system for coordinate measuring machine

NASA Astrophysics Data System (ADS)

Zhao, Haibin; Wang, Junying; Wang, Boxiong; Wang, Jianmei; Chen, Huacheng

2006-11-01

With rapid progress of Product Lifecycle Management (PLM) in manufacturing industry, automatic generation of inspection planning of product and the integration with other activities in product lifecycle play important roles in quality control. But the techniques for these purposes are laggard comparing with techniques of CAD/CAM. Therefore, an automatic inspection planning system for Coordinate Measuring Machine (CMM) was developed to improve the automatization of measuring based on the integration of inspection system in PLM. Feature information representation is achieved based on a PLM canter database; measuring strategy is optimized through the integration of multi-sensors; reasonable number and distribution of inspection points are calculated and designed with the guidance of statistic theory and a synthesis distribution algorithm; a collision avoidance method is proposed to generate non-collision inspection path with high efficiency. Information mapping is performed between Neutral Interchange Files (NIFs), such as STEP, DML, DMIS, XML, etc., to realize information integration with other activities in the product lifecycle like design, manufacturing and inspection execution, etc. Simulation was carried out to demonstrate the feasibility of the proposed system. As a result, the inspection process is becoming simpler and good result can be got based on the integration in PLM.

Derivation of hydrous pyrolysis kinetic parameters from open-system pyrolysis

NASA Astrophysics Data System (ADS)

Tseng, Yu-Hsin; Huang, Wuu-Liang

2010-05-01

Kinetic information is essential to predict the temperature, timing or depth of hydrocarbon generation within a hydrocarbon system. The most common experiments for deriving kinetic parameters are mainly by open-system pyrolysis. However, it has been shown that the conditions of open-system pyrolysis are deviant from nature by its low near-ambient pressure and high temperatures. Also, the extrapolation of heating rates in open-system pyrolysis to geological conditions may be questionable. Recent study of Lewan and Ruble shows hydrous-pyrolysis conditions can simulate the natural conditions better and its applications are supported by two case studies with natural thermal-burial histories. Nevertheless, performing hydrous pyrolysis experiment is really tedious and requires large amount of sample, while open-system pyrolysis is rather convenient and efficient. Therefore, the present study aims at the derivation of convincing distributed hydrous pyrolysis Ea with only routine open-system Rock-Eval data. Our results unveil that there is a good correlation between open-system Rock-Eval parameter Tmax and the activation energy (Ea) derived from hydrous pyrolysis. The hydrous pyrolysis single Ea can be predicted from Tmax based on the correlation, while the frequency factor (A0) is estimated based on the linear relationship between single Ea and log A0. Because the Ea distribution is more rational than single Ea, we modify the predicted single hydrous pyrolysis Ea into distributed Ea by shifting the pattern of Ea distribution from open-system pyrolysis until the weight mean Ea distribution equals to the single hydrous pyrolysis Ea. Moreover, it has been shown that the shape of the Ea distribution is very much alike the shape of Tmax curve. Thus, in case of the absence of open-system Ea distribution, we may use the shape of Tmax curve to get the distributed hydrous pyrolysis Ea. The study offers a new approach as a simple method for obtaining distributed hydrous pyrolysis Ea with only routine open-system Rock-Eval data, which will allow for better estimating hydrocarbon generation.

Distributions of topological observables in inclusive three- and four-jet events in pp collisions at [Formula: see text][Formula: see text].

PubMed

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This paper presents distributions of topological observables in inclusive three- and four-jet events produced in pp collisions at a centre-of-mass energy of 7[Formula: see text] with a data sample collected by the CMS experiment corresponding to a luminosity of 5.1[Formula: see text]. The distributions are corrected for detector effects, and compared with several event generators based on two- and multi-parton matrix elements at leading order. Among the considered calculations, MadGraph interfaced with pythia6 displays the overall best agreement with data.

Distributions of topological observables in inclusive three- and four-jet events in pp collisions at √s = 7 TeV

DOE PAGES

Khachatryan, Vardan

2015-07-01

This paper presents distributions of topological observables in inclusive three- and four-jet events produced in pp collisions at a centre-of-mass energy of 7TeV with a data sample collected by the CMS experiment corresponding to a luminosity of 5.1fb -1. We corrected the distributions for detector effects, and compared with several event generators based on two- and multi-parton matrix elements at leading order. Thus, among the considered calculations, MADGRAPH interfaced with PYTHIA6displays the overall best agreement with data.

Effect of process parameters on temperature distribution in twin-electrode TIG coupling arc

NASA Astrophysics Data System (ADS)

Zhang, Guangjun; Xiong, Jun; Gao, Hongming; Wu, Lin

2012-10-01

The twin-electrode TIG coupling arc is a new type of welding heat source, which is generated in a single welding torch that has two tungsten electrodes insulated from each other. This paper aims at determining the distribution of temperature for the coupling arc using the Fowler-Milne method under the assumption of local thermodynamic equilibrium. The influences of welding current, arc length, and distance between both electrode tips on temperature distribution of the coupling arc were analyzed. Based on the results, a better understanding of the twin-electrode TIG welding process was obtained.

TDIGG - TWO-DIMENSIONAL, INTERACTIVE GRID GENERATION CODE

NASA Technical Reports Server (NTRS)

Vu, B. T.

1994-01-01

TDIGG is a fast and versatile program for generating two-dimensional computational grids for use with finite-difference flow-solvers. Both algebraic and elliptic grid generation systems are included. The method for grid generation by algebraic transformation is based on an interpolation algorithm and the elliptic grid generation is established by solving the partial differential equation (PDE). Non-uniform grid distributions are carried out using a hyperbolic tangent stretching function. For algebraic grid systems, interpolations in one direction (univariate) and two directions (bivariate) are considered. These interpolations are associated with linear or cubic Lagrangian/Hermite/Bezier polynomial functions. The algebraic grids can subsequently be smoothed using an elliptic solver. For elliptic grid systems, the PDE can be in the form of Laplace (zero forcing function) or Poisson. The forcing functions in the Poisson equation come from the boundary or the entire domain of the initial algebraic grids. A graphics interface procedure using the Silicon Graphics (GL) Library is included to allow users to visualize the grid variations at each iteration. This will allow users to interactively modify the grid to match their applications. TDIGG is written in FORTRAN 77 for Silicon Graphics IRIS series computers running IRIX. This package requires either MIT's X Window System, Version 11 Revision 4 or SGI (Motif) Window System. A sample executable is provided on the distribution medium. It requires 148K of RAM for execution. The standard distribution medium is a .25 inch streaming magnetic IRIX tape cartridge in UNIX tar format. This program was developed in 1992.

Interpreting the Coulomb-field approximation for generalized-Born electrostatics using boundary-integral equation theory.

PubMed

Bardhan, Jaydeep P

2008-10-14

The importance of molecular electrostatic interactions in aqueous solution has motivated extensive research into physical models and numerical methods for their estimation. The computational costs associated with simulations that include many explicit water molecules have driven the development of implicit-solvent models, with generalized-Born (GB) models among the most popular of these. In this paper, we analyze a boundary-integral equation interpretation for the Coulomb-field approximation (CFA), which plays a central role in most GB models. This interpretation offers new insights into the nature of the CFA, which traditionally has been assessed using only a single point charge in the solute. The boundary-integral interpretation of the CFA allows the use of multiple point charges, or even continuous charge distributions, leading naturally to methods that eliminate the interpolation inaccuracies associated with the Still equation. This approach, which we call boundary-integral-based electrostatic estimation by the CFA (BIBEE/CFA), is most accurate when the molecular charge distribution generates a smooth normal displacement field at the solute-solvent boundary, and CFA-based GB methods perform similarly. Conversely, both methods are least accurate for charge distributions that give rise to rapidly varying or highly localized normal displacement fields. Supporting this analysis are comparisons of the reaction-potential matrices calculated using GB methods and boundary-element-method (BEM) simulations. An approximation similar to BIBEE/CFA exhibits complementary behavior, with superior accuracy for charge distributions that generate rapidly varying normal fields and poorer accuracy for distributions that produce smooth fields. This approximation, BIBEE by preconditioning (BIBEE/P), essentially generates initial guesses for preconditioned Krylov-subspace iterative BEMs. Thus, iterative refinement of the BIBEE/P results recovers the BEM solution; excellent agreement is obtained in only a few iterations. The boundary-integral-equation framework may also provide a means to derive rigorous results explaining how the empirical correction terms in many modern GB models significantly improve accuracy despite their simple analytical forms.

XUV ionization of aligned molecules

NASA Astrophysics Data System (ADS)

Kelkensberg, F.; Rouzée, A.; Siu, W.; Gademann, G.; Johnsson, P.; Lucchini, M.; Lucchese, R. R.; Vrakking, M. J. J.

2011-11-01

New extreme-ultraviolet (XUV) light sources such as high-order-harmonic generation (HHG) and free-electron lasers (FELs), combined with laser-induced alignment techniques, enable novel methods for making molecular movies based on measuring molecular frame photoelectron angular distributions. Experiments are presented where CO2 molecules were impulsively aligned using a near-infrared laser and ionized using femtosecond XUV pulses obtained by HHG. Measured electron angular distributions reveal contributions from four orbitals and the onset of the influence of the molecular structure.

Development of Load Duration Curve System in Data Scarce Watersheds Based on a Distributed Hydrological Model

NASA Astrophysics Data System (ADS)

WANG, J.

2017-12-01

In stream water quality control, the total maximum daily load (TMDL) program is very effective. However, the load duration curves (LDC) of TMDL are difficult to be established because no sufficient observed flow and pollutant data can be provided in data-scarce watersheds in which no hydrological stations or consecutively long-term hydrological data are available. Although the point sources or a non-point sources of pollutants can be clarified easily with the aid of LDC, where does the pollutant come from and to where it will be transported in the watershed cannot be traced by LDC. To seek out the best management practices (BMPs) of pollutants in a watershed, and to overcome the limitation of LDC, we proposed to develop LDC based on a distributed hydrological model of SWAT for the water quality management in data scarce river basins. In this study, firstly, the distributed hydrological model of SWAT was established with the scarce-hydrological data. Then, the long-term daily flows were generated with the established SWAT model and rainfall data from the adjacent weather station. Flow duration curves (FDC) was then developed with the aid of generated daily flows by SWAT model. Considering the goal of water quality management, LDC curves of different pollutants can be obtained based on the FDC. With the monitored water quality data and the LDC curves, the water quality problems caused by the point or non-point source pollutants in different seasons can be ascertained. Finally, the distributed hydrological model of SWAT was employed again to tracing the spatial distribution and the origination of the pollutants of coming from what kind of agricultural practices and/or other human activities. A case study was conducted in the Jian-jiang river, a tributary of Yangtze river, of Duyun city, Guizhou province. Results indicate that this kind of method can realize the water quality management based on TMDL and find out the suitable BMPs for reducing pollutant in a watershed.

Inversion method based on stochastic optimization for particle sizing.

PubMed

Sánchez-Escobar, Juan Jaime; Barbosa-Santillán, Liliana Ibeth; Vargas-Ubera, Javier; Aguilar-Valdés, Félix

2016-08-01

A stochastic inverse method is presented based on a hybrid evolutionary optimization algorithm (HEOA) to retrieve a monomodal particle-size distribution (PSD) from the angular distribution of scattered light. By solving an optimization problem, the HEOA (with the Fraunhofer approximation) retrieves the PSD from an intensity pattern generated by Mie theory. The analyzed light-scattering pattern can be attributed to unimodal normal, gamma, or lognormal distribution of spherical particles covering the interval of modal size parameters 46≤α≤150. The HEOA ensures convergence to the near-optimal solution during the optimization of a real-valued objective function by combining the advantages of a multimember evolution strategy and locally weighted linear regression. The numerical results show that our HEOA can be satisfactorily applied to solve the inverse light-scattering problem.

Small meteoroids' major contribution to Mercury's exosphere

NASA Astrophysics Data System (ADS)

Grotheer, E. B.; Livi, S. A.

2014-01-01

The contribution of the meteoroid population to the generation of Mercury's exosphere is analyzed to determine which segment contributes most greatly to exospheric refilling via the process of meteoritic impact vaporization. For the meteoroid data, a differential mass distribution based on work by Grün et al. (Grün, E., Zook, H.A., Fechtig, H., Giese, R.H. [1985]. Icarus 62(2), 244-272) and a differential velocity distribution based on the work of Zook (Zook, H.A. [1975]. In: 6th Lunar Science Conference, vol. 2. Pergamon Press, Inc., Houston, TX, pp. 1653-1672) is used. These distributions are then evaluated using the method employed by Cintala (Cintala, M.J. [1992]. J. Geophys. Res. 97(E1), 947-974) to determine impact rates for selected mass and velocity segments of the meteoroid population.

A Comprehensive Comparison of Multiparty Secure Additions with Differential Privacy

PubMed Central

Goryczka, Slawomir; Xiong, Li

2016-01-01

This paper considers the problem of secure data aggregation (mainly summation) in a distributed setting, while ensuring differential privacy of the result. We study secure multiparty addition protocols using well known security schemes: Shamir’s secret sharing, perturbation-based, and various encryptions. We supplement our study with our new enhanced encryption scheme EFT, which is efficient and fault tolerant. Differential privacy of the final result is achieved by either distributed Laplace or Geometric mechanism (respectively DLPA or DGPA), while approximated differential privacy is achieved by diluted mechanisms. Distributed random noise is generated collectively by all participants, which draw random variables from one of several distributions: Gamma, Gauss, Geometric, or their diluted versions. We introduce a new distributed privacy mechanism with noise drawn from the Laplace distribution, which achieves smaller redundant noise with efficiency. We compare complexity and security characteristics of the protocols with different differential privacy mechanisms and security schemes. More importantly, we implemented all protocols and present an experimental comparison on their performance and scalability in a real distributed environment. Based on the evaluations, we identify our security scheme and Laplace DLPA as the most efficient for secure distributed data aggregation with privacy. PMID:28919841

A Comprehensive Comparison of Multiparty Secure Additions with Differential Privacy.

PubMed

Goryczka, Slawomir; Xiong, Li

2017-01-01

This paper considers the problem of secure data aggregation (mainly summation) in a distributed setting, while ensuring differential privacy of the result. We study secure multiparty addition protocols using well known security schemes: Shamir's secret sharing, perturbation-based, and various encryptions. We supplement our study with our new enhanced encryption scheme EFT, which is efficient and fault tolerant. Differential privacy of the final result is achieved by either distributed Laplace or Geometric mechanism (respectively DLPA or DGPA), while approximated differential privacy is achieved by diluted mechanisms. Distributed random noise is generated collectively by all participants, which draw random variables from one of several distributions: Gamma, Gauss, Geometric, or their diluted versions. We introduce a new distributed privacy mechanism with noise drawn from the Laplace distribution, which achieves smaller redundant noise with efficiency. We compare complexity and security characteristics of the protocols with different differential privacy mechanisms and security schemes. More importantly, we implemented all protocols and present an experimental comparison on their performance and scalability in a real distributed environment. Based on the evaluations, we identify our security scheme and Laplace DLPA as the most efficient for secure distributed data aggregation with privacy.

Comparison of linear and nonlinear programming approaches for "worst case dose" and "minmax" robust optimization of intensity-modulated proton therapy dose distributions.

PubMed

Zaghian, Maryam; Cao, Wenhua; Liu, Wei; Kardar, Laleh; Randeniya, Sharmalee; Mohan, Radhe; Lim, Gino

2017-03-01

Robust optimization of intensity-modulated proton therapy (IMPT) takes uncertainties into account during spot weight optimization and leads to dose distributions that are resilient to uncertainties. Previous studies demonstrated benefits of linear programming (LP) for IMPT in terms of delivery efficiency by considerably reducing the number of spots required for the same quality of plans. However, a reduction in the number of spots may lead to loss of robustness. The purpose of this study was to evaluate and compare the performance in terms of plan quality and robustness of two robust optimization approaches using LP and nonlinear programming (NLP) models. The so-called "worst case dose" and "minmax" robust optimization approaches and conventional planning target volume (PTV)-based optimization approach were applied to designing IMPT plans for five patients: two with prostate cancer, one with skull-based cancer, and two with head and neck cancer. For each approach, both LP and NLP models were used. Thus, for each case, six sets of IMPT plans were generated and assessed: LP-PTV-based, NLP-PTV-based, LP-worst case dose, NLP-worst case dose, LP-minmax, and NLP-minmax. The four robust optimization methods behaved differently from patient to patient, and no method emerged as superior to the others in terms of nominal plan quality and robustness against uncertainties. The plans generated using LP-based robust optimization were more robust regarding patient setup and range uncertainties than were those generated using NLP-based robust optimization for the prostate cancer patients. However, the robustness of plans generated using NLP-based methods was superior for the skull-based and head and neck cancer patients. Overall, LP-based methods were suitable for the less challenging cancer cases in which all uncertainty scenarios were able to satisfy tight dose constraints, while NLP performed better in more difficult cases in which most uncertainty scenarios were hard to meet tight dose limits. For robust optimization, the worst case dose approach was less sensitive to uncertainties than was the minmax approach for the prostate and skull-based cancer patients, whereas the minmax approach was superior for the head and neck cancer patients. The robustness of the IMPT plans was remarkably better after robust optimization than after PTV-based optimization, and the NLP-PTV-based optimization outperformed the LP-PTV-based optimization regarding robustness of clinical target volume coverage. In addition, plans generated using LP-based methods had notably fewer scanning spots than did those generated using NLP-based methods. © 2017 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Generation of dark hollow femtosecond pulsed beam by phase-only liquid crystal spatial light modulator.

PubMed

Nie, Yongming; Ma, Haotong; Li, Xiujian; Hu, Wenhua; Yang, Jiankun

2011-07-20

Based on the refractive laser beam shaping system, the dark hollow femtosecond pulse beam shaping technique with a phase-only liquid crystal spatial light modulator (LC-SLM) is demonstrated. The phase distribution of the LC-SLM is derived by the energy conservation and constant optical path principle. The effects of the shaping system on the temporal properties, including spectral phase distribution and bandwidth of the femtosecond pulse, are analyzed in detail. Experimental results show that the hollow intensity distribution of the output pulsed beam can be maintained much at more than 1200 mm. The spectral phase of the pulse is changed, and the pulse width is expanded from 199 to 230 fs, which is caused by the spatial-temporal coupling effect. The coupling effect mainly depends on the phase-only LC-SLM itself, not on its loaded phase distribution. The experimental results indicate that the proposed shaping setup can generate a dark hollow femtosecond pulsed beam effectively, because the temporal Gaussian waveform is unchanged. © 2011 Optical Society of America

Experimental extraction of an entangled photon pair from two identically decohered pairs.

PubMed

Yamamoto, Takashi; Koashi, Masato; Ozdemir, Sahin Kaya; Imoto, Nobuyuki

2003-01-23

Entanglement is considered to be one of the most important resources in quantum information processing schemes, including teleportation, dense coding and entanglement-based quantum key distribution. Because entanglement cannot be generated by classical communication between distant parties, distribution of entangled particles between them is necessary. During the distribution process, entanglement between the particles is degraded by the decoherence and dissipation processes that result from unavoidable coupling with the environment. Entanglement distillation and concentration schemes are therefore needed to extract pairs with a higher degree of entanglement from these less-entangled pairs; this is accomplished using local operations and classical communication. Here we report an experimental demonstration of extraction of a polarization-entangled photon pair from two decohered photon pairs. Two polarization-entangled photon pairs are generated by spontaneous parametric down-conversion and then distributed through a channel that induces identical phase fluctuations to both pairs; this ensures that no entanglement is available as long as each pair is manipulated individually. Then, through collective local operations and classical communication we extract from the two decohered pairs a photon pair that is observed to be polarization-entangled.

Optimization based on benefit of regional energy suppliers of distributed generation in active distribution network

NASA Astrophysics Data System (ADS)

Huo, Xianxu; Li, Guodong; Jiang, Ling; Wang, Xudong

2017-08-01

With the development of electricity market, distributed generation (DG) technology and related policies, regional energy suppliers are encouraged to build DG. Under this background, the concept of active distribution network (ADN) is put forward. In this paper, a bi-level model of intermittent DG considering benefit of regional energy suppliers is proposed. The objective of the upper level is the maximization of benefit of regional energy suppliers. On this basis, the lower level is optimized for each scene. The uncertainties of DG output and load of users, as well as four active management measures, which include demand-side management, curtailing the output power of DG, regulating reactive power compensation capacity and regulating the on-load tap changer, are considered. Harmony search algorithm and particle swarm optimization are combined as a hybrid strategy to solve the model. This model and strategy are tested with IEEE-33 node system, and results of case study indicate that the model and strategy successfully increase the capacity of DG and benefit of regional energy suppliers.

The effect of the electric wind on the spatial distribution of chemical species in the positive corona discharge

NASA Astrophysics Data System (ADS)

Yanallah, K.; Pontiga, F.; Bouazza, M. R.; Chen, J. H.

2017-08-01

The electrohydrodynamic air flow generated by a positive corona discharge, and its effect on the spatial distribution of chemical species within a wire-plate corona reactor, have been numerically simulated. The computational model is based on the solutions of the Navier-Stokes equation and the continuity equation of each chemical species generated by the electrical discharge. A simplified analytical expression of the electric force density, which only requires the current density as the input parameter, has been used in the Navier-Stokes equation to obtain the velocity field. For the solution of the continuity equations, a plasma chemistry model that includes the most important reactions between electrons, atoms and molecules in air has been used. Similar to the electric force, the electron density distribution has been approximated by using a semi-analytical expression appropriate for the electrode geometry. The results of the study show that the spatial distribution of chemical species can be very different, and depends on the interplay between the electrohydrodynamic flow, the chemical kinetics of the species and its characteristic lifetime.

Correlation in photon pairs generated using four-wave mixing in a cold atomic ensemble

NASA Astrophysics Data System (ADS)

Ferdinand, Andrew Richard; Manjavacas, Alejandro; Becerra, Francisco Elohim

2017-04-01

Spontaneous four-wave mixing (FWM) in atomic ensembles can be used to generate narrowband entangled photon pairs at or near atomic resonances. While extensive research has been done to investigate the quantum correlations in the time and polarization of such photon pairs, the study and control of high dimensional quantum correlations contained in their spatial degrees of freedom has not been fully explored. In our work we experimentally investigate the generation of correlated light from FWM in a cold ensemble of cesium atoms as a function of the frequencies of the pump fields in the FWM process. In addition, we theoretically study the spatial correlations of the photon pairs generated in the FWM process, specifically the joint distribution of their orbital angular momentum (OAM). We investigate the width of the distribution of the OAM modes, known as the spiral bandwidth, and the purity of OAM correlations as a function of the properties of the pump fields, collected photons, and the atomic ensemble. These studies will guide experiments involving high dimensional entanglement of photons generated from this FWM process and OAM-based quantum communication with atomic ensembles. This work is supported by AFORS Grant FA9550-14-1-0300.

Solid Oxide Fuel Cell Hybrid System for Distributed Power Generation

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

David Deangelis; Rich Depuy; Debashis Dey

2004-09-30

This report summarizes the work performed by Hybrid Power Generation Systems, LLC (HPGS) during the April to October 2004 reporting period in Task 2.3 (SOFC Scaleup for Hybrid and Fuel Cell Systems) under Cooperative Agreement DE-FC26-01NT40779 for the U. S. Department of Energy, National Energy Technology Laboratory (DOE/NETL), entitled ''Solid Oxide Fuel Cell Hybrid System for Distributed Power Generation''. This study analyzes the performance and economics of power generation systems for central power generation application based on Solid Oxide Fuel Cell (SOFC) technology and fueled by natural gas. The main objective of this task is to develop credible scale upmore » strategies for large solid oxide fuel cell-gas turbine systems. System concepts that integrate a SOFC with a gas turbine were developed and analyzed for plant sizes in excess of 20 MW. A 25 MW plant configuration was selected with projected system efficiency of over 65% and a factory cost of under $400/kW. The plant design is modular and can be scaled to both higher and lower plant power ratings. Technology gaps and required engineering development efforts were identified and evaluated.« less

Design optimization of a fuzzy distributed generation (DG) system with multiple renewable energy sources

NASA Astrophysics Data System (ADS)

Ganesan, T.; Elamvazuthi, I.; Shaari, Ku Zilati Ku; Vasant, P.

2012-09-01

The global rise in energy demands brings major obstacles to many energy organizations in providing adequate energy supply. Hence, many techniques to generate cost effective, reliable and environmentally friendly alternative energy source are being explored. One such method is the integration of photovoltaic cells, wind turbine generators and fuel-based generators, included with storage batteries. This sort of power systems are known as distributed generation (DG) power system. However, the application of DG power systems raise certain issues such as cost effectiveness, environmental impact and reliability. The modelling as well as the optimization of this DG power system was successfully performed in the previous work using Particle Swarm Optimization (PSO). The central idea of that work was to minimize cost, minimize emissions and maximize reliability (multi-objective (MO) setting) with respect to the power balance and design requirements. In this work, we introduce a fuzzy model that takes into account the uncertain nature of certain variables in the DG system which are dependent on the weather conditions (such as; the insolation and wind speed profiles). The MO optimization in a fuzzy environment was performed by applying the Hopfield Recurrent Neural Network (HNN). Analysis on the optimized results was then carried out.

Reliability Overhaul Model

DTIC Science & Technology

1989-08-01

Random variables for the conditional exponential distribution are generated using the inverse transform method. C1) Generate U - UCO,i) (2) Set s - A ln...e - [(x+s - 7)/ n] 0 + [Cx-T)/n]0 c. Random variables from the conditional weibull distribution are generated using the inverse transform method. C1...using a standard normal transformation and the inverse transform method. B - 3 APPENDIX 3 DISTRIBUTIONS SUPPORTED BY THE MODEL (1) Generate Y - PCX S

Execution time supports for adaptive scientific algorithms on distributed memory machines

NASA Technical Reports Server (NTRS)

Berryman, Harry; Saltz, Joel; Scroggs, Jeffrey

1990-01-01

Optimizations are considered that are required for efficient execution of code segments that consists of loops over distributed data structures. The PARTI (Parallel Automated Runtime Toolkit at ICASE) execution time primitives are designed to carry out these optimizations and can be used to implement a wide range of scientific algorithms on distributed memory machines. These primitives allow the user to control array mappings in a way that gives an appearance of shared memory. Computations can be based on a global index set. Primitives are used to carry out gather and scatter operations on distributed arrays. Communications patterns are derived at runtime, and the appropriate send and receive messages are automatically generated.

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

Baker, Kyri; Dall'Anese, Emiliano; Summers, Tyler

This paper outlines a data-driven, distributionally robust approach to solve chance-constrained AC optimal power flow problems in distribution networks. Uncertain forecasts for loads and power generated by photovoltaic (PV) systems are considered, with the goal of minimizing PV curtailment while meeting power flow and voltage regulation constraints. A data- driven approach is utilized to develop a distributionally robust conservative convex approximation of the chance-constraints; particularly, the mean and covariance matrix of the forecast errors are updated online, and leveraged to enforce voltage regulation with predetermined probability via Chebyshev-based bounds. By combining an accurate linear approximation of the AC power flowmore » equations with the distributionally robust chance constraint reformulation, the resulting optimization problem becomes convex and computationally tractable.« less

Execution time support for scientific programs on distributed memory machines

NASA Technical Reports Server (NTRS)

Berryman, Harry; Saltz, Joel; Scroggs, Jeffrey

1990-01-01

Optimizations are considered that are required for efficient execution of code segments that consists of loops over distributed data structures. The PARTI (Parallel Automated Runtime Toolkit at ICASE) execution time primitives are designed to carry out these optimizations and can be used to implement a wide range of scientific algorithms on distributed memory machines. These primitives allow the user to control array mappings in a way that gives an appearance of shared memory. Computations can be based on a global index set. Primitives are used to carry out gather and scatter operations on distributed arrays. Communications patterns are derived at runtime, and the appropriate send and receive messages are automatically generated.

A Novel Wide-Area Backup Protection Based on Fault Component Current Distribution and Improved Evidence Theory

PubMed Central

Zhang, Zhe; Kong, Xiangping; Yin, Xianggen; Yang, Zengli; Wang, Lijun

2014-01-01

In order to solve the problems of the existing wide-area backup protection (WABP) algorithms, the paper proposes a novel WABP algorithm based on the distribution characteristics of fault component current and improved Dempster/Shafer (D-S) evidence theory. When a fault occurs, slave substations transmit to master station the amplitudes of fault component currents of transmission lines which are the closest to fault element. Then master substation identifies suspicious faulty lines according to the distribution characteristics of fault component current. After that, the master substation will identify the actual faulty line with improved D-S evidence theory based on the action states of traditional protections and direction components of these suspicious faulty lines. The simulation examples based on IEEE 10-generator-39-bus system show that the proposed WABP algorithm has an excellent performance. The algorithm has low requirement of sampling synchronization, small wide-area communication flow, and high fault tolerance. PMID:25050399

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

A two-step method for developing a control rod program for boiling water reactors

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

Taner, M.S.; Levine, S.H.; Hsiao, M.Y.

1992-01-01

This paper reports on a two-step method that is established for the generation of a long-term control rod program for boiling water reactors (BWRs). The new method assumes a time-variant target power distribution in core depletion. In the new method, the BWR control rod programming is divided into two steps. In step 1, a sequence of optimal, exposure-dependent Haling power distribution profiles is generated, utilizing the spectral shift concept. In step 2, a set of exposure-dependent control rod patterns is developed by using the Haling profiles generated at step 1 as a target. The new method is implemented in amore » computer program named OCTOPUS. The optimization procedure of OCTOPUS is based on the method of approximation programming, in which the SIMULATE-E code is used to determine the nucleonics characteristics of the reactor core state. In a test in cycle length over a time-invariant, target Haling power distribution case because of a moderate application of spectral shift. No thermal limits of the core were violated. The gain in cycle length could be increased further by broadening the extent of the spetral shift.« less

Mathematic simulation of mining company’s power demand forecast (by example of “Neryungri” coal strip mine)

NASA Astrophysics Data System (ADS)

Antonenkov, D. V.; Solovev, D. B.

2017-10-01

The article covers the aspects of forecasting and consideration of the wholesale market environment in generating the power demand forecast. Major mining companies that operate in conditions of the present day power market have to provide a reliable energy demand request for a certain time period ahead, thus ensuring sufficient reduction of financial losses associated with deviations of the actual power demand from the expected figures. Normally, under the power supply agreement, the consumer is bound to provide a per-month and per-hour request annually. It means that the consumer has to generate one-month-ahead short-term and medium-term hourly forecasts. The authors discovered that empiric distributions of “Yakutugol”, Holding Joint Stock Company, power demand belong to the sustainable rank parameter H-distribution type used for generating forecasts based on extrapolation of such distribution parameters. For this reason they justify the need to apply the mathematic rank analysis in short-term forecasting of the contracted power demand of “Neryungri” coil strip mine being a component of the technocenosis-type system of the mining company “Yakutugol”, Holding JSC.

Intergenerational effects of shifts in women's educational distribution in South Korea: Transmission, differential fertility, and assortative mating

PubMed Central

Kye, Bongoh; Mare, Robert D.

2014-01-01

This study examines the intergenerational effects of changes in women's education in South Korea. We define intergenerational effects as changes in the distribution of educational attainment in an offspring generation associated with the changes in a parental generation. Departing from the previous approach in research on social mobility that has focused on intergenerational association, we examine the changes in the distribution of educational attainment across generations. Using a simulation method based on Mare and Maralani's recursive population renewal model, we examine how intergenerational transmission, assortative mating, and differential fertility influence intergenerational effects. The results point to the following conclusions. First, we find a positive intergenerational effect: improvement in women's education leads to improvement in daughter's education. Second, we find that the magnitude of intergenerational effects substantially depends on assortative marriage and differential fertility: assortative mating amplifies and differential fertility dampens the intergenerational effects. Third, intergenerational effects become bigger for the less educated and smaller for the better educated over time, which is a consequence of educational expansion. We compare our results with Mare and Maralani's original Indonesian study to illustrate how the model of intergenerational effects works in different socioeconomic circumstances. PMID:23017970

Sparse Reconstruction for Temperature Distribution Using DTS Fiber Optic Sensors with Applications in Electrical Generator Stator Monitoring

PubMed Central

Bazzo, João Paulo; Pipa, Daniel Rodrigues; da Silva, Erlon Vagner; Martelli, Cicero; Cardozo da Silva, Jean Carlos

2016-01-01

This paper presents an image reconstruction method to monitor the temperature distribution of electric generator stators. The main objective is to identify insulation failures that may arise as hotspots in the structure. The method is based on temperature readings of fiber optic distributed sensors (DTS) and a sparse reconstruction algorithm. Thermal images of the structure are formed by appropriately combining atoms of a dictionary of hotspots, which was constructed by finite element simulation with a multi-physical model. Due to difficulties for reproducing insulation faults in real stator structure, experimental tests were performed using a prototype similar to the real structure. The results demonstrate the ability of the proposed method to reconstruct images of hotspots with dimensions down to 15 cm, representing a resolution gain of up to six times when compared to the DTS spatial resolution. In addition, satisfactory results were also obtained to detect hotspots with only 5 cm. The application of the proposed algorithm for thermal imaging of generator stators can contribute to the identification of insulation faults in early stages, thereby avoiding catastrophic damage to the structure. PMID:27618040

A Method for Estimating Noise from Full-Scale Distributed Exhaust Nozzles

NASA Technical Reports Server (NTRS)

Kinzie, Kevin W.; Schein, David B.

2004-01-01

A method to estimate the full-scale noise suppression from a scale model distributed exhaust nozzle (DEN) is presented. For a conventional scale model exhaust nozzle, Strouhal number scaling using a scale factor related to the nozzle exit area is typically applied that shifts model scale frequency in proportion to the geometric scale factor. However, model scale DEN designs have two inherent length scales. One is associated with the mini-nozzles, whose size do not change in going from model scale to full scale. The other is associated with the overall nozzle exit area which is much smaller than full size. Consequently, lower frequency energy that is generated by the coalesced jet plume should scale to lower frequency, but higher frequency energy generated by individual mini-jets does not shift frequency. In addition, jet-jet acoustic shielding by the array of mini-nozzles is a significant noise reduction effect that may change with DEN model size. A technique has been developed to scale laboratory model spectral data based on the premise that high and low frequency content must be treated differently during the scaling process. The model-scale distributed exhaust spectra are divided into low and high frequency regions that are then adjusted to full scale separately based on different physics-based scaling laws. The regions are then recombined to create an estimate of the full-scale acoustic spectra. These spectra can then be converted to perceived noise levels (PNL). The paper presents the details of this methodology and provides an example of the estimated noise suppression by a distributed exhaust nozzle compared to a round conic nozzle.

Efficient conceptual design for LED-based pixel light vehicle headlamps

NASA Astrophysics Data System (ADS)

Held, Marcel Philipp; Lachmayer, Roland

2017-12-01

High-resolution vehicle headlamps represent a future-oriented technology that can be used to increase traffic safety and driving comfort. As a further development to the current Matrix Beam headlamps, LED-based pixel light systems enable ideal lighting functions (e.g. projection of navigation information onto the road) to be activated in any given driving scenario. Moreover, compared to other light-modulating elements such as DMDs and LCDs, instantaneous LED on-off toggling provides a decisive advantage in efficiency. To generate highly individualized light distributions for automotive applications, a number of approaches using an LED array may be pursued. One approach is to vary the LED density in the array so as to output the desired light distribution. Another notable approach makes use of an equidistant arrangement of the individual LEDs together with distortion optics to formulate the desired light distribution. The optical system adjusts the light distribution in a manner that improves resolution and increases luminous intensity of the desired area. An efficient setup for pixel generation calls for one lens per LED. Taking into consideration the limited space requirements of the system, this implies that the luminous flux, efficiency and resolution image parameters are primarily controlled by the lens dimensions. In this paper a concept for an equidistant LED array arrangement utilizing distortion optics is presented. The paper is divided into two parts. The first part discusses the influence of lens geometry on the system efficiency whereas the second part investigates the correlation between resolution and luminous flux based on the lens dimensions.

Optimization and Validation of Rotating Current Excitation with GMR Array Sensors for Riveted

DTIC Science & Technology

2016-09-16

distribution. Simulation results, using both an optimized coil and a conventional coil, are generated using the finite element method (FEM) model...optimized coil and a conventional coil, are generated using the finite element method (FEM) model. The signal magnitude for an optimized coil is seen to be...optimized coil. 4. Model Based Performance Analysis A 3D finite element model (FEM) is used to analyze the performance of the optimized coil and

A TRMM/GPM retrieval of the total mean generator current for the global electric circuit

NASA Astrophysics Data System (ADS)

Peterson, Michael; Deierling, Wiebke; Liu, Chuntao; Mach, Douglas; Kalb, Christina

2017-09-01

A specialized satellite version of the passive microwave electric field retrieval algorithm (Peterson et al., 2015) is applied to observations from the Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Measurement (GPM) satellites to estimate the generator current for the Global Electric Circuit (GEC) and compute its temporal variability. By integrating retrieved Wilson currents from electrified clouds across the globe, we estimate a total mean current of between 1.4 kA (assuming the 7% fraction of electrified clouds producing downward currents measured by the ER-2 is representative) to 1.6 kA (assuming all electrified clouds contribute to the GEC). These current estimates come from all types of convective weather without preference, including Electrified Shower Clouds (ESCs). The diurnal distribution of the retrieved generator current is in excellent agreement with the Carnegie curve (RMS difference: 1.7%). The temporal variability of the total mean generator current ranges from 110% on semi-annual timescales (29% on an annual timescale) to 7.5% on decadal timescales with notable responses to the Madden-Julian Oscillation and El Nino Southern Oscillation. The geographical distribution of current includes significant contributions from oceanic regions in addition to the land-based tropical chimneys. The relative importance of the Americas and Asia chimneys compared to Africa is consistent with the best modern ground-based observations and further highlights the importance of ESCs for the GEC.

Polystyrene microspheres enable 10‐color compensation for immunophenotyping of primary human leukocytes

PubMed Central

Carr, Karen D.; Norman, John C.; Huye, Leslie; Hegde, Meenakshi

2015-01-01

Abstract Compensation is a critical process for the unbiased analysis of flow cytometry data. Numerous compensation strategies exist, including the use of bead‐based products. The purpose of this study was to determine whether beads, specifically polystyrene microspheres (PSMS) compare to the use of primary leukocytes for single color based compensation when conducting polychromatic flow cytometry. To do so, we stained individual tubes of both PSMS and leukocytes with panel specific antibodies conjugated to fluorochromes corresponding to fluorescent channels FL1‐FL10. We compared the matrix generated by PSMS to that generated using peripheral blood mononuclear cells (PBMC). Ideal for compensation is a sample with both a discrete negative population and a bright positive population. We demonstrate that PSMS display autofluorescence properties similar to PBMC. When comparing PSMS to PBMC for compensation PSMS yielded more evenly distributed and discrete negative and positive populations to use for compensation. We analyzed three donors' PBMC stained with our 10‐color T cell subpopulation panel using compensation generated by PSMS vs.PBMC and detected no significant differences in the population distribution. Panel specific antibodies bound to PSMS represent an invaluable valid tool to generate suitable compensation matrices especially when sample material is limited and/or the sample requires analysis of dynamically modulated or rare events. © 2015 The Authors. Cytometry Part A Published by Wiley Periodicals, Inc. PMID:26202733

Generation conditions of CW Diode Laser Sustained Plasma

NASA Astrophysics Data System (ADS)

Nishimoto, Koji; Matsui, Makoto; Ono, Takahiro

2016-09-01

Laser sustained plasma was generated using 1 kW class continuous wave diode laser. The laser beam was focused on the seed plasma generated by arc discharge in 1 MPa xenon lamp. The diode laser has advantages of high energy conversion efficiency of 80%, ease of maintenance, compact size and availability of conventional quartz based optics. Therefore, it has a prospect of further development compared with conventional CO2 laser. In this study, variation of the plasma shape caused by laser power is observed and also temperature distribution in the direction of plasma radius is measured by optical emission spectroscopy.

Stability metrics for multi-source biomedical data based on simplicial projections from probability distribution distances.

PubMed

Sáez, Carlos; Robles, Montserrat; García-Gómez, Juan M

2017-02-01

Biomedical data may be composed of individuals generated from distinct, meaningful sources. Due to possible contextual biases in the processes that generate data, there may exist an undesirable and unexpected variability among the probability distribution functions (PDFs) of the source subsamples, which, when uncontrolled, may lead to inaccurate or unreproducible research results. Classical statistical methods may have difficulties to undercover such variabilities when dealing with multi-modal, multi-type, multi-variate data. This work proposes two metrics for the analysis of stability among multiple data sources, robust to the aforementioned conditions, and defined in the context of data quality assessment. Specifically, a global probabilistic deviation and a source probabilistic outlyingness metrics are proposed. The first provides a bounded degree of the global multi-source variability, designed as an estimator equivalent to the notion of normalized standard deviation of PDFs. The second provides a bounded degree of the dissimilarity of each source to a latent central distribution. The metrics are based on the projection of a simplex geometrical structure constructed from the Jensen-Shannon distances among the sources PDFs. The metrics have been evaluated and demonstrated their correct behaviour on a simulated benchmark and with real multi-source biomedical data using the UCI Heart Disease data set. The biomedical data quality assessment based on the proposed stability metrics may improve the efficiency and effectiveness of biomedical data exploitation and research.

Algebraic grid generation for coolant passages of turbine blades with serpentine channels and pin fins

NASA Technical Reports Server (NTRS)

Shih, T. I.-P.; Roelke, R. J.; Steinthorsson, E.

1991-01-01

In order to study numerically details of the flow and heat transfer within coolant passages of turbine blades, a method must first be developed to generate grid systems within the very complicated geometries involved. In this study, a grid generation package was developed that is capable of generating the required grid systems. The package developed is based on an algebraic grid generation technique that permits the user considerable control over how grid points are to be distributed in a very explicit way. These controls include orthogonality of grid lines next to boundary surfaces and ability to cluster about arbitrary points, lines, and surfaces. This paper describes that grid generation package and shows how it can be used to generate grid systems within complicated-shaped coolant passages via an example.

The glycolipid GM1 reshapes asymmetric biomembranes and giant vesicles by curvature generation.

PubMed

Dasgupta, Raktim; Miettinen, Markus S; Fricke, Nico; Lipowsky, Reinhard; Dimova, Rumiana

2018-05-29

The ganglioside GM1 is present in neuronal membranes at elevated concentrations with an asymmetric spatial distribution. It is known to generate curvature and can be expected to strongly influence the neuron morphology. To elucidate these effects, we prepared giant vesicles with GM1 predominantly present in one leaflet of the membrane, mimicking the asymmetric GM1 distribution in neuronal membranes. Based on pulling inward and outward tubes, we developed a technique that allowed the direct measurement of the membrane spontaneous curvature. Using vesicle electroporation and fluorescence intensity analysis, we were able to quantify the GM1 asymmetry across the membrane and to subsequently estimate the local curvature generated by the molecule in the bilayer. Molecular-dynamics simulations confirm the experimentally determined dependence of the membrane spontaneous curvature as a function of GM1 asymmetry. GM1 plays a crucial role in connection with receptor proteins. Our results on curvature generation of GM1 point to an additional important role of this ganglioside, namely in shaping neuronal membranes. Copyright © 2018 the Author(s). Published by PNAS.

A novel approach to photonic generate microwave signals based on optical injection locking and four-wave mixing

NASA Astrophysics Data System (ADS)

Zhu, Huatao; Wang, Rong; Xiang, Peng; Pu, Tao; Fang, Tao; Zheng, Jilin; Li, Yuandong

2017-10-01

In this paper, a novel approach for photonic generation of microwave signals based on frequency multiplication using an injected distributed-feedback (DFB) semiconductor laser is proposed and demonstrated by a proof-of-concept experiment. The proposed system is mainly made up of a dual-parallel Mach-Zehnder modulator (DPMZM) and an injected DFB laser. By properly setting the bias voltage of the DPMZM, ±2-order sidebands with carrier suppression are generated, which are then injected into the slave laser. Due to the optical sideband locking and four-wave mixing (FWM) nonlinearity in the slave laser, new sidebands are generated. Then these sidebands are sent to an optical notch filter where all the undesired sidebands are removed. Finally, after photodetector detection, frequency multiplied microwave signals can be generated. Thanks to the flexibility of the optical sideband locking and FWM, frequency octupling, 12-tupling, 14-tupling and 16-tupling can be obtained.

Patch-Based Generative Shape Model and MDL Model Selection for Statistical Analysis of Archipelagos

NASA Astrophysics Data System (ADS)

Ganz, Melanie; Nielsen, Mads; Brandt, Sami

We propose a statistical generative shape model for archipelago-like structures. These kind of structures occur, for instance, in medical images, where our intention is to model the appearance and shapes of calcifications in x-ray radio graphs. The generative model is constructed by (1) learning a patch-based dictionary for possible shapes, (2) building up a time-homogeneous Markov model to model the neighbourhood correlations between the patches, and (3) automatic selection of the model complexity by the minimum description length principle. The generative shape model is proposed as a probability distribution of a binary image where the model is intended to facilitate sequential simulation. Our results show that a relatively simple model is able to generate structures visually similar to calcifications. Furthermore, we used the shape model as a shape prior in the statistical segmentation of calcifications, where the area overlap with the ground truth shapes improved significantly compared to the case where the prior was not used.

Digital Libraries: The Next Generation in File System Technology.

ERIC Educational Resources Information Center

Bowman, Mic; Camargo, Bill

1998-01-01

Examines file sharing within corporations that use wide-area, distributed file systems. Applications and user interactions strongly suggest that the addition of services typically associated with digital libraries (content-based file location, strongly typed objects, representation of complex relationships between documents, and extrinsic…

Boundary-Layer Receptivity and Integrated Transition Prediction

NASA Technical Reports Server (NTRS)

Chang, Chau-Lyan; Choudhari, Meelan

2005-01-01

The adjoint parabold stability equations (PSE) formulation is used to calculate the boundary layer receptivity to localized surface roughness and suction for compressible boundary layers. Receptivity efficiency functions predicted by the adjoint PSE approach agree well with results based on other nonparallel methods including linearized Navier-Stokes equations for both Tollmien-Schlichting waves and crossflow instability in swept wing boundary layers. The receptivity efficiency function can be regarded as the Green's function to the disturbance amplitude evolution in a nonparallel (growing) boundary layer. Given the Fourier transformed geometry factor distribution along the chordwise direction, the linear disturbance amplitude evolution for a finite size, distributed nonuniformity can be computed by evaluating the integral effects of both disturbance generation and linear amplification. The synergistic approach via the linear adjoint PSE for receptivity and nonlinear PSE for disturbance evolution downstream of the leading edge forms the basis for an integrated transition prediction tool. Eventually, such physics-based, high fidelity prediction methods could simulate the transition process from the disturbance generation through the nonlinear breakdown in a holistic manner.

Room temperature continuous wave, monolithic tunable THz sources based on highly efficient mid-infrared quantum cascade lasers

PubMed Central

Lu, Quanyong; Wu, Donghai; Sengupta, Saumya; Slivken, Steven; Razeghi, Manijeh

2016-01-01

A compact, high power, room temperature continuous wave terahertz source emitting in a wide frequency range (ν ~ 1–5 THz) is of great importance to terahertz system development for applications in spectroscopy, communication, sensing, and imaging. Here, we present a strong-coupled strain-balanced quantum cascade laser design for efficient THz generation based on intracavity difference frequency generation. Room temperature continuous wave emission at 3.41 THz with a side-mode suppression ratio of 30 dB and output power up to 14 μW is achieved with a wall-plug efficiency about one order of magnitude higher than previous demonstrations. With this highly efficient design, continuous wave, single mode THz emissions with a wide frequency tuning range of 2.06–4.35 THz and an output power up to 4.2 μW are demonstrated at room temperature from two monolithic three-section sampled grating distributed feedback-distributed Bragg reflector lasers. PMID:27009375

Room temperature continuous wave, monolithic tunable THz sources based on highly efficient mid-infrared quantum cascade lasers.

PubMed

Lu, Quanyong; Wu, Donghai; Sengupta, Saumya; Slivken, Steven; Razeghi, Manijeh

2016-03-24

A compact, high power, room temperature continuous wave terahertz source emitting in a wide frequency range (ν~1-5 THz) is of great importance to terahertz system development for applications in spectroscopy, communication, sensing, and imaging. Here, we present a strong-coupled strain-balanced quantum cascade laser design for efficient THz generation based on intracavity difference frequency generation. Room temperature continuous wave emission at 3.41 THz with a side-mode suppression ratio of 30 dB and output power up to 14 μW is achieved with a wall-plug efficiency about one order of magnitude higher than previous demonstrations. With this highly efficient design, continuous wave, single mode THz emissions with a wide frequency tuning range of 2.06-4.35 THz and an output power up to 4.2 μW are demonstrated at room temperature from two monolithic three-section sampled grating distributed feedback-distributed Bragg reflector lasers.

MAGI: many-component galaxy initializer

NASA Astrophysics Data System (ADS)

Miki, Yohei; Umemura, Masayuki

2018-04-01

Providing initial conditions is an essential procedure for numerical simulations of galaxies. The initial conditions for idealized individual galaxies in N-body simulations should resemble observed galaxies and be dynamically stable for time-scales much longer than their characteristic dynamical times. However, generating a galaxy model ab initio as a system in dynamical equilibrium is a difficult task, since a galaxy contains several components, including a bulge, disc, and halo. Moreover, it is desirable that the initial-condition generator be fast and easy to use. We have now developed an initial-condition generator for galactic N-body simulations that satisfies these requirements. The developed generator adopts a distribution-function-based method, and it supports various kinds of density models, including custom-tabulated inputs and the presence of more than one disc. We tested the dynamical stability of systems generated by our code, representing early- and late-type galaxies, with N = 2097 152 and 8388 608 particles, respectively, and we found that the model galaxies maintain their initial distributions for at least 1 Gyr. The execution times required to generate the two models were 8.5 and 221.7 seconds, respectively, which is negligible compared to typical execution times for N-body simulations. The code is provided as open-source software and is publicly and freely available at https://bitbucket.org/ymiki/magi.

Simultaneous Airy beam generation for both surface plasmon polaritons and transmitted wave based on metasurface.

PubMed

Wang, Sen; Wang, Xinke; Zhang, Yan

2017-10-02

Based on the amplitude and phase modulation of subwavelength slits, a metasurface which can simultaneously generate Airy beam for surface plasmon polaritons (SPPs) and transmitted wave is presented. Interestingly, by changing the handedness of circularly polarized light, the position of SPPs Airy beam can be switched to the left or right side of the metasurface, while the field distribution and the position of the Airy beam for transmitted wave are not affected. The nondiffracting, self-bending and self-healing properties of the generated Airy beams are analyzed as well. In addition, abruptly autofocusing of SPPs and transmitted wave are demonstrated by interfering two Airy beams. The dual functionality and chirality features of the metasurface can provide more freedoms in the potential applications of Airy beams.

Gluon tomography from deeply virtual Compton scattering at small x

DOE PAGES

Hatta, Yoshitaka; Xiao, Bo-Wen; Yuan, Feng

2017-06-29

We present a full evaluation of the deeply virtual Compton scattering cross section in the dipole framework in the small-x region. The result features the cosφ and cos2φ azimuthal angular correlations, which have been missing in previous studies based on the dipole model. In particular, the cos2φ term is generated by the elliptic gluon Wigner distribution of which the measurement at the planned electron-ion collider provides important information about the gluon tomography at small x. Here, we also show the consistency with the standard collinear factorization approach based on the quark and gluon generalized parton distributions.

An islanding detection methodology combining decision trees and Sandia frequency shift for inverter-based distributed generations

DOE PAGES

Azim, Riyasat; Li, Fangxing; Xue, Yaosuo; ...

2017-07-14

Distributed generations (DGs) for grid-connected applications require an accurate and reliable islanding detection methodology (IDM) for secure system operation. This paper presents an IDM for grid-connected inverter-based DGs. The proposed method is a combination of passive and active islanding detection techniques for aggregation of their advantages and elimination/minimisation of the drawbacks. In the proposed IDM, the passive method utilises critical system attributes extracted from local voltage measurements at target DG locations as well as employs decision tree-based classifiers for characterisation and detection of islanding events. The active method is based on Sandia frequency shift technique and is initiated only whenmore » the passive method is unable to differentiate islanding events from other system events. Thus, the power quality degradation introduced into the system by active islanding detection techniques can be minimised. Furthermore, a combination of active and passive techniques allows detection of islanding events under low power mismatch scenarios eliminating the disadvantage associated with the use of passive techniques alone. Finally, detailed case study results demonstrate the effectiveness of the proposed method in detection of islanding events under various power mismatch scenarios, load quality factors and in the presence of single or multiple grid-connected inverter-based DG units.« less

An islanding detection methodology combining decision trees and Sandia frequency shift for inverter-based distributed generations

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

Azim, Riyasat; Li, Fangxing; Xue, Yaosuo

Distributed generations (DGs) for grid-connected applications require an accurate and reliable islanding detection methodology (IDM) for secure system operation. This paper presents an IDM for grid-connected inverter-based DGs. The proposed method is a combination of passive and active islanding detection techniques for aggregation of their advantages and elimination/minimisation of the drawbacks. In the proposed IDM, the passive method utilises critical system attributes extracted from local voltage measurements at target DG locations as well as employs decision tree-based classifiers for characterisation and detection of islanding events. The active method is based on Sandia frequency shift technique and is initiated only whenmore » the passive method is unable to differentiate islanding events from other system events. Thus, the power quality degradation introduced into the system by active islanding detection techniques can be minimised. Furthermore, a combination of active and passive techniques allows detection of islanding events under low power mismatch scenarios eliminating the disadvantage associated with the use of passive techniques alone. Finally, detailed case study results demonstrate the effectiveness of the proposed method in detection of islanding events under various power mismatch scenarios, load quality factors and in the presence of single or multiple grid-connected inverter-based DG units.« less

SU-G-JeP2-01: A New Approach for MR-Only Treatment Planning: Tissue Segmentation-Based Pseudo-CT Generation Using T1-Weighted MRI

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

Yu, H; Leszczynski, K; Lee, Y

Purpose: To evaluate MR-only treatment planning for brain Stereotactic Ablative Radiotherapy (SABR) based on pseudo-CT (pCT) generation using one set of T1-weighted MRI. Methods: T1-weighted MR and CT images from 12 patients who were eligible for brain SABR were retrospectively acquired for this study. MR-based pCT was generated by using a newly in-house developed algorithm based on MR tissue segmentation and voxel-based electron density (ED) assignment (pCTv). pCTs using bulk density assignment (pCTb where bone and soft tissue were assigned 800HU and 0HU,respectively), and water density assignment (pCTw where all tissues were assigned 0HU) were generated for comparison of EDmore » assignment techniques. The pCTs were registered with CTs and contours of radiation targets and Organs-at-Risk (OARs) from clinical CT-based plans were copied to co-registered pCTs. Volumetric-Modulated-Arc-Therapy(VMAT) plans were independently created for pCTv and CT using the same optimization settings and a prescription (50Gy/10 fractions) to planning-target-volume (PTV) mean dose. pCTv-based plans and CT-based plans were compared with dosimetry parameters and monitor units (MUs). Beam fluence maps of CT-based plans were transferred to co-registered pCTs, and dose was recalculated on pCTs. Dose distribution agreement between pCTs and CT plans were quantified using Gamma analysis (2%/2mm, 1%/1mm with a 10% cut-off threshold) in axial, coronal and sagittal planes across PTV. Results: The average differences of PTV mean and maximum doses, and monitor units between independently created pCTv-based and CT-based plans were 0.5%, 1.5% and 1.1%, respectively. Gamma analysis of dose distributions of the pCTs and the CT calculated using the same fluence map resulted in average agreements of 92.6%/79.1%/52.6% with 1%/1mm criterion, and 98.7%/97.4%/71.5% with 2%/2mm criterion, for pCTv/CT, pCTb/CT and pCTw/CT, respectively. Conclusion: Plans produced on Voxel-based pCT is dosimetrically more similar to CT plans than bulk assignment-based pCTs. MR-only treatment planning using voxel-based pCT generated from T1-wieghted MRI may be feasible.« less

Evaluation of diffusion coefficients by means of an approximate steady-state condition in sedimentation velocity distributions.

PubMed

Scott, David J; Harding, Stephen E; Winzor, Donald J

2015-12-01

This investigation examined the feasibility of manipulating the rotor speed in sedimentation velocity experiments to spontaneously generate an approximate steady-state condition where the extent of diffusional spreading is matched exactly by the boundary sharpening arising from negative s-c dependence. Simulated sedimentation velocity distributions based on the sedimentation characteristics for a purified mucin preparation were used to illustrate a simple procedure for determining the diffusion coefficient from such steady-state distributions in situations where the concentration dependence of the sedimentation coefficient, s = s(0)/(1 + Kc), was quantified in terms of the limiting sedimentation coefficient as c → 0 (s(0)) and the concentration coefficient (K). Those simulations established that spontaneous generation of the approximate steady state could well be a feature of sedimentation velocity distributions for many unstructured polymer systems because the requirement that Kcoω(2)s(0)/D be between 46 and 183 cm(-2) is not unduly restrictive. Although spontaneous generation of the approximate steady state is also a theoretical prediction for structured macromolecular solutes exhibiting linear concentration dependence of the sedimentation coefficient, s = s(0)(1 - kc), the required value of k is far too large for any practical advantage to be taken of this approach with globular proteins. Copyright © 2015 Elsevier Inc. All rights reserved.

A Study on Grid-Square Statistics Based Estimation of Regional Electricity Demand and Regional Potential Capacity of Distributed Generators

NASA Astrophysics Data System (ADS)

Kato, Takeyoshi; Sugimoto, Hiroyuki; Suzuoki, Yasuo

We established a procedure for estimating regional electricity demand and regional potential capacity of distributed generators (DGs) by using a grid square statistics data set. A photovoltaic power system (PV system) for residential use and a co-generation system (CGS) for both residential and commercial use were taken into account. As an example, the result regarding Aichi prefecture was presented in this paper. The statistical data of the number of households by family-type and the number of employees by business category for about 4000 grid-square with 1km × 1km area was used to estimate the floor space or the electricity demand distribution. The rooftop area available for installing PV systems was also estimated with the grid-square statistics data set. Considering the relation between a capacity of existing CGS and a scale-index of building where CGS is installed, the potential capacity of CGS was estimated for three business categories, i.e. hotel, hospital, store. In some regions, the potential capacity of PV systems was estimated to be about 10,000kW/km2, which corresponds to the density of the existing area with intensive installation of PV systems. Finally, we discussed the ratio of regional potential capacity of DGs to regional maximum electricity demand for deducing the appropriate capacity of DGs in the model of future electricity distribution system.

Flow processes on the catchment scale - modeling of initial structural states and hydrological behavior in an artificial exemplary catchment

NASA Astrophysics Data System (ADS)

Maurer, Thomas; Caviedes-Voullième, Daniel; Hinz, Christoph; Gerke, Horst H.

2017-04-01

Landscapes that are heavily disturbed or newly formed by either natural processes or human activity are in a state of disequilibrium. Their initial development is thus characterized by highly dynamic processes under all climatic conditions. The primary distribution and structure of the solid phase (i.e. mineral particles forming the pore space) is one of the decisive factors for the development of hydrological behavior of the eco-hydrological system and therefore (co-) determining for its - more or less - stable final state. The artificially constructed ‚Hühnerwasser' catchment (a 6 ha area located in the open-cast lignite mine Welzow-Süd, southern Brandenburg, Germany) is a landscape laboratory where the initial eco-hydrological development is observed since 2005. The specific formation (or construction) processes generated characteristic sediment structures and distributions, resulting in a spatially heterogeneous initial state of the catchment. We developed a structure generator that simulates the characteristic distribution of the solid phase for such constructed landscapes. The program is able to generate quasi-realistic structures and sediment compositions on multiple spatial levels (1 cm up to 100 m scale). The generated structures can be i) conditioned to actual measurement values (e.g., soil texture and bulk distribution); ii) stochastically generated, and iii) calculated deterministically according to the geology and technical processes at the excavation site. Results are visualized using the GOCAD software package and the free software Paraview. Based on the 3D-spatial sediment distributions, effective hydraulic van-Genuchten parameters are calculated using pedotransfer functions. The hydraulic behavior of different sediment distribution (i.e. versions or variations of the catchment's porous body) is calculated using a numerical model developed by one of us (Caviedes-Voullième). Observation data are available from catchment monitoring are available for i) determining the boundary conditions (e.g., precipitation), and ii) the calibration / validation of the model (catchment discharge, ground water). The analysis of multiple sediment distribution scenarios should allow to approximately determine the influx of starting conditions on initial development of hydrological behavior. We present first flow modeling results for a reference (conditioned) catchment model and variations thereof. We will also give an outlook on further methodical development of our approach.

General Metropolis-Hastings jump diffusions for automatic target recognition in infrared scenes

NASA Astrophysics Data System (ADS)

Lanterman, Aaron D.; Miller, Michael I.; Snyder, Donald L.

1997-04-01

To locate and recognize ground-based targets in forward- looking IR (FLIR) images, 3D faceted models with associated pose parameters are formulated to accommodate the variability found in FLIR imagery. Taking a Bayesian approach, scenes are simulated from the emissive characteristics of the CAD models and compared with the collected data by a likelihood function based on sensor statistics. This likelihood is combined with a prior distribution defined over the set of possible scenes to form a posterior distribution. To accommodate scenes with variable numbers of targets, the posterior distribution is defined over parameter vectors of varying dimension. An inference algorithm based on Metropolis-Hastings jump- diffusion processes empirically samples from the posterior distribution, generating configurations of templates and transformations that match the collected sensor data with high probability. The jumps accommodate the addition and deletion of targets and the estimation of target identities; diffusions refine the hypotheses by drifting along the gradient of the posterior distribution with respect to the orientation and position parameters. Previous results on jumps strategies analogous to the Metropolis acceptance/rejection algorithm, with proposals drawn from the prior and accepted based on the likelihood, are extended to encompass general Metropolis-Hastings proposal densities. In particular, the algorithm proposes moves by drawing from the posterior distribution over computationally tractible subsets of the parameter space. The algorithm is illustrated by an implementation on a Silicon Graphics Onyx/Reality Engine.

Regional model-based computerized ionospheric tomography using GPS measurements: IONOLAB-CIT

NASA Astrophysics Data System (ADS)

Tuna, Hakan; Arikan, Orhan; Arikan, Feza

2015-10-01

Three-dimensional imaging of the electron density distribution in the ionosphere is a crucial task for investigating the ionospheric effects. Dual-frequency Global Positioning System (GPS) satellite signals can be used to estimate the slant total electron content (STEC) along the propagation path between a GPS satellite and ground-based receiver station. However, the estimated GPS-STEC is very sparse and highly nonuniformly distributed for obtaining reliable 3-D electron density distributions derived from the measurements alone. Standard tomographic reconstruction techniques are not accurate or reliable enough to represent the full complexity of variable ionosphere. On the other hand, model-based electron density distributions are produced according to the general trends of ionosphere, and these distributions do not agree with measurements, especially for geomagnetically active hours. In this study, a regional 3-D electron density distribution reconstruction method, namely, IONOLAB-CIT, is proposed to assimilate GPS-STEC into physical ionospheric models. The proposed method is based on an iterative optimization framework that tracks the deviations from the ionospheric model in terms of F2 layer critical frequency and maximum ionization height resulting from the comparison of International Reference Ionosphere extended to Plasmasphere (IRI-Plas) model-generated STEC and GPS-STEC. The suggested tomography algorithm is applied successfully for the reconstruction of electron density profiles over Turkey, during quiet and disturbed hours of ionosphere using Turkish National Permanent GPS Network.

Data Transparency | Distributed Generation Interconnection Collaborative |

Science.gov Websites

quality and availability are increasingly vital for reducing the costs of distributed generation completion in certain areas, increasing accountability for utility application processing. As distributed PV NREL, HECO, TSRG Improving Data Transparency for the Distributed PV Interconnection Process: Emergent

Concepts for design of an energy management system incorporating dispersed storage and generation

NASA Technical Reports Server (NTRS)

Kirkham, H.; Koerner, T.; Nightingale, D.

1981-01-01

New forms of generation based on renewable resources must be managed as part of existing power systems in order to be utilized with maximum effectiveness. Many of these generators are by their very nature dispersed or small, so that they will be connected to the distribution part of the power system. This situation poses new questions of control and protection, and the intermittent nature of some of the energy sources poses problems of scheduling and dispatch. Under the assumption that the general objectives of energy management will remain unchanged, the impact of dispersed storage and generation on some of the specific functions of power system control and its hardware are discussed.

Dual Cross-Linked Biofunctional and Self-Healing Networks to Generate User-Defined Modular Gradient Hydrogel Constructs.

PubMed

Wei, Zhao; Lewis, Daniel M; Xu, Yu; Gerecht, Sharon

2017-08-01

Gradient hydrogels have been developed to mimic the spatiotemporal differences of multiple gradient cues in tissues. Current approaches used to generate such hydrogels are restricted to a single gradient shape and distribution. Here, a hydrogel is designed that includes two chemical cross-linking networks, biofunctional, and self-healing networks, enabling the customizable formation of modular gradient hydrogel construct with various gradient distributions and flexible shapes. The biofunctional networks are formed via Michael addition between the acrylates of oxidized acrylated hyaluronic acid (OAHA) and the dithiol of matrix metalloproteinase (MMP)-sensitive cross-linker and RGD peptides. The self-healing networks are formed via dynamic Schiff base reaction between N-carboxyethyl chitosan (CEC) and OAHA, which drives the modular gradient units to self-heal into an integral modular gradient hydrogel. The CEC-OAHA-MMP hydrogel exhibits excellent flowability at 37 °C under shear stress, enabling its injection to generate gradient distributions and shapes. Furthermore, encapsulated sarcoma cells respond to the gradient cues of RGD peptides and MMP-sensitive cross-linkers in the hydrogel. With these superior properties, the dual cross-linked CEC-OAHA-MMP hydrogel holds significant potential for generating customizable gradient hydrogel constructs, to study and guide cellular responses to their microenvironment such as in tumor mimicking, tissue engineering, and stem cell differentiation and morphogenesis. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

On the use of an analytic source model for dose calculations in precision image-guided small animal radiotherapy.

PubMed

Granton, Patrick V; Verhaegen, Frank

2013-05-21

Precision image-guided small animal radiotherapy is rapidly advancing through the use of dedicated micro-irradiation devices. However, precise modeling of these devices in model-based dose-calculation algorithms such as Monte Carlo (MC) simulations continue to present challenges due to a combination of very small beams, low mechanical tolerances on beam collimation, positioning and long calculation times. The specific intent of this investigation is to introduce and demonstrate the viability of a fast analytical source model (AM) for use in either investigating improvements in collimator design or for use in faster dose calculations. MC models using BEAMnrc were developed for circular and square fields sizes from 1 to 25 mm in diameter (or side) that incorporated the intensity distribution of the focal spot modeled after an experimental pinhole image. These MC models were used to generate phase space files (PSFMC) at the exit of the collimators. An AM was developed that included the intensity distribution of the focal spot, a pre-calculated x-ray spectrum, and the collimator-specific entrance and exit apertures. The AM was used to generate photon fluence intensity distributions (ΦAM) and PSFAM containing photons radiating at angles according to the focal spot intensity distribution. MC dose calculations using DOSXYZnrc in a water and mouse phantom differing only by source used (PSFMC versus PSFAM) were found to agree within 7% and 4% for the smallest 1 and 2 mm collimator, respectively, and within 1% for all other field sizes based on depth dose profiles. PSF generation times were approximately 1200 times faster for the smallest beam and 19 times faster for the largest beam. The influence of the focal spot intensity distribution on output and on beam shape was quantified and found to play a significant role in calculated dose distributions. Beam profile differences due to collimator alignment were found in both small and large collimators sensitive to shifts of 1 mm with respect to the central axis.

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.

Subscribe to DGIC Updates | Distributed Generation Interconnection

Science.gov Websites

Distributed Generation Interconnection Collaborative. Subscribe Please provide and submit the following information to subscribe. The mailing list addresses are never sold, rented, distributed, or disclosed in any

GENERIC VERIFICATION PROTOCOL: DISTRIBUTED GENERATION AND COMBINED HEAT AND POWER FIELD TESTING PROTOCOL

EPA Science Inventory

This report is a generic verification protocol by which EPA’s Environmental Technology Verification program tests newly developed equipment for distributed generation of electric power, usually micro-turbine generators and internal combustion engine generators. The protocol will ...

Kaon quark distribution functions in the chiral constituent quark model

NASA Astrophysics Data System (ADS)

Watanabe, Akira; Sawada, Takahiro; Kao, Chung Wen

2018-04-01

We investigate the valence u and s ¯ quark distribution functions of the K+ meson, vK (u )(x ,Q2) and vK (s ¯)(x ,Q2), in the framework of the chiral constituent quark model. We judiciously choose the bare distributions at the initial scale to generate the dressed distributions at the higher scale, considering the meson cloud effects and the QCD evolution, which agree with the phenomenologically satisfactory valence quark distribution of the pion and the experimental data of the ratio vK (u )(x ,Q2)/vπ (u )(x ,Q2) . We show how the meson cloud effects affect the bare distribution functions in detail. We find that a smaller S U (3 ) flavor symmetry breaking effect is observed, compared with results of the preceding studies based on other approaches.

Foundational Report Series: Advanced Distribution Management Systems for Grid Modernization, DMS Integration of Distributed Energy Resources and Microgrids

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

Singh, Ravindra; Reilly, James T.; Wang, Jianhui

Deregulation of the electric utility industry, environmental concerns associated with traditional fossil fuel-based power plants, volatility of electric energy costs, Federal and State regulatory support of “green” energy, and rapid technological developments all support the growth of Distributed Energy Resources (DERs) in electric utility systems and ensure an important role for DERs in the smart grid and other aspects of modern utilities. DERs include distributed generation (DG) systems, such as renewables; controllable loads (also known as demand response); and energy storage systems. This report describes the role of aggregators of DERs in providing optimal services to distribution networks, through DERmore » monitoring and control systems—collectively referred to as a Distributed Energy Resource Management System (DERMS)—and microgrids in various configurations.« less

A distributed control approach for power and energy management in a notional shipboard power system

NASA Astrophysics Data System (ADS)

Shen, Qunying

The main goal of this thesis is to present a power control module (PCON) based approach for power and energy management and to examine its control capability in shipboard power system (SPS). The proposed control scheme is implemented in a notional medium voltage direct current (MVDC) integrated power system (IPS) for electric ship. To realize the control functions such as ship mode selection, generator launch schedule, blackout monitoring, and fault ride-through, a PCON based distributed power and energy management system (PEMS) is developed. The control scheme is proposed as two-layer hierarchical architecture with system level on the top as the supervisory control and zonal level on the bottom as the decentralized control, which is based on the zonal distribution characteristic of the notional MVDC IPS that was proposed as one of the approaches for Next Generation Integrated Power System (NGIPS) by Norbert Doerry. Several types of modules with different functionalities are used to derive the control scheme in detail for the notional MVDC IPS. Those modules include the power generation module (PGM) that controls the function of generators, the power conversion module (PCM) that controls the functions of DC/DC or DC/AC converters, etc. Among them, the power control module (PCON) plays a critical role in the PEMS. It is the core of the control process. PCONs in the PEMS interact with all the other modules, such as power propulsion module (PPM), energy storage module (ESM), load shedding module (LSHED), and human machine interface (HMI) to realize the control algorithm in PEMS. The proposed control scheme is implemented in real time using the real time digital simulator (RTDS) to verify its validity. To achieve this, a system level energy storage module (SESM) and a zonal level energy storage module (ZESM) are developed in RTDS to cooperate with PCONs to realize the control functionalities. In addition, a load shedding module which takes into account the reliability of power supply (in terms of quality of service) is developed. This module can supply uninterruptible power to the mission critical loads. In addition, a multi-agent system (MAS) based framework is proposed to implement the PCON based PEMS through a hardware setup that is composed of MAMBA boards and FPGA interface. Agents are implemented using Java Agent DEvelopment Framework (JADE). Various test scenarios were tested to validate the approach.