random energy model: Topics by WorldWideScience.org

Sample records for random energy model

A random energy model for size dependence : recurrence vs. transience

NARCIS (Netherlands)

Külske, Christof

1998-01-01

We investigate the size dependence of disordered spin models having an infinite number of Gibbs measures in the framework of a simplified 'random energy model for size dependence'. We introduce two versions (involving either independent random walks or branching processes), that can be seen as
Activated aging dynamics and effective trap model description in the random energy model

Science.gov (United States)

Baity-Jesi, M.; Biroli, G.; Cammarota, C.

2018-01-01

We study the out-of-equilibrium aging dynamics of the random energy model (REM) ruled by a single spin-flip Metropolis dynamics. We focus on the dynamical evolution taking place on time-scales diverging with the system size. Our aim is to show to what extent the activated dynamics displayed by the REM can be described in terms of an effective trap model. We identify two time regimes: the first one corresponds to the process of escaping from a basin in the energy landscape and to the subsequent exploration of high energy configurations, whereas the second one corresponds to the evolution from a deep basin to the other. By combining numerical simulations with analytical arguments we show why the trap model description does not hold in the former but becomes exact in the second.
Linearization effect in multifractal analysis: Insights from the Random Energy Model

Science.gov (United States)

Angeletti, Florian; Mézard, Marc; Bertin, Eric; Abry, Patrice

2011-08-01

The analysis of the linearization effect in multifractal analysis, and hence of the estimation of moments for multifractal processes, is revisited borrowing concepts from the statistical physics of disordered systems, notably from the analysis of the so-called Random Energy Model. Considering a standard multifractal process (compound Poisson motion), chosen as a simple representative example, we show the following: (i) the existence of a critical order q∗ beyond which moments, though finite, cannot be estimated through empirical averages, irrespective of the sample size of the observation; (ii) multifractal exponents necessarily behave linearly in q, for q>q∗. Tailoring the analysis conducted for the Random Energy Model to that of Compound Poisson motion, we provide explicative and quantitative predictions for the values of q∗ and for the slope controlling the linear behavior of the multifractal exponents. These quantities are shown to be related only to the definition of the multifractal process and not to depend on the sample size of the observation. Monte Carlo simulations, conducted over a large number of large sample size realizations of compound Poisson motion, comfort and extend these analyses.
Freezing and extreme-value statistics in a random energy model with logarithmically correlated potential

International Nuclear Information System (INIS)

Fyodorov, Yan V; Bouchaud, Jean-Philippe

2008-01-01

We investigate some implications of the freezing scenario proposed by Carpentier and Le Doussal (CLD) for a random energy model (REM) with logarithmically correlated random potential. We introduce a particular (circular) variant of the model, and show that the integer moments of the partition function in the high-temperature phase are given by the well-known Dyson Coulomb gas integrals. The CLD freezing scenario allows one to use those moments for extracting the distribution of the free energy in both high- and low-temperature phases. In particular, it yields the full distribution of the minimal value in the potential sequence. This provides an explicit new class of extreme-value statistics for strongly correlated variables, manifestly different from the standard Gumbel class. (fast track communication)
Freezing and extreme-value statistics in a random energy model with logarithmically correlated potential

Energy Technology Data Exchange (ETDEWEB)

Fyodorov, Yan V [School of Mathematical Sciences, University of Nottingham, Nottingham NG72RD (United Kingdom); Bouchaud, Jean-Philippe [Science and Finance, Capital Fund Management 6-8 Bd Haussmann, 75009 Paris (France)

2008-09-19

We investigate some implications of the freezing scenario proposed by Carpentier and Le Doussal (CLD) for a random energy model (REM) with logarithmically correlated random potential. We introduce a particular (circular) variant of the model, and show that the integer moments of the partition function in the high-temperature phase are given by the well-known Dyson Coulomb gas integrals. The CLD freezing scenario allows one to use those moments for extracting the distribution of the free energy in both high- and low-temperature phases. In particular, it yields the full distribution of the minimal value in the potential sequence. This provides an explicit new class of extreme-value statistics for strongly correlated variables, manifestly different from the standard Gumbel class. (fast track communication)
Derrida's Generalized Random Energy models; 4, Continuous state branching and coalescents

CERN Document Server

Bovier, A

2003-01-01

In this paper we conclude our analysis of Derrida's Generalized Random Energy Models (GREM) by identifying the thermodynamic limit with a one-parameter family of probability measures related to a continuous state branching process introduced by Neveu. Using a construction introduced by Bertoin and Le Gall in terms of a coherent family of subordinators related to Neveu's branching process, we show how the Gibbs geometry of the limiting Gibbs measure is given in terms of the genealogy of this process via a deterministic time-change. This construction is fully universal in that all different models (characterized by the covariance of the underlying Gaussian process) differ only through that time change, which in turn is expressed in terms of Parisi's overlap distribution. The proof uses strongly the Ghirlanda-Guerra identities that impose the structure of Neveu's process as the only possible asymptotic random mechanism.
Growth and renewable energy in Europe: A random effect model with evidence for neutrality hypothesis

International Nuclear Information System (INIS)

Menegaki, Angeliki N.

2011-01-01

This is an empirical study on the causal relationship between economic growth and renewable energy for 27 European countries in a multivariate panel framework over the period 1997-2007 using a random effect model and including final energy consumption, greenhouse gas emissions and employment as additional independent variables in the model. Empirical results do not confirm causality between renewable energy consumption and GDP, although panel causality tests unfold short-run relationships between renewable energy and greenhouse gas emissions and employment. The estimated cointegration factor refrains from unity, indicating only a weak, if any, relationship between economic growth and renewable energy consumption in Europe, suggesting evidence of the neutrality hypothesis, which can partly be explained by the uneven and insufficient exploitation of renewable energy sources across Europe.
A cluster expansion approach to exponential random graph models

International Nuclear Information System (INIS)

Yin, Mei

2012-01-01

The exponential family of random graphs are among the most widely studied network models. We show that any exponential random graph model may alternatively be viewed as a lattice gas model with a finite Banach space norm. The system may then be treated using cluster expansion methods from statistical mechanics. In particular, we derive a convergent power series expansion for the limiting free energy in the case of small parameters. Since the free energy is the generating function for the expectations of other random variables, this characterizes the structure and behavior of the limiting network in this parameter region
Log-correlated random-energy models with extensive free-energy fluctuations: Pathologies caused by rare events as signatures of phase transitions

Science.gov (United States)

Cao, Xiangyu; Fyodorov, Yan V.; Le Doussal, Pierre

2018-02-01

We address systematically an apparent nonphysical behavior of the free-energy moment generating function for several instances of the logarithmically correlated models: the fractional Brownian motion with Hurst index H =0 (fBm0) (and its bridge version), a one-dimensional model appearing in decaying Burgers turbulence with log-correlated initial conditions and, finally, the two-dimensional log-correlated random-energy model (logREM) introduced in Cao et al. [Phys. Rev. Lett. 118, 090601 (2017), 10.1103/PhysRevLett.118.090601] based on the two-dimensional Gaussian free field with background charges and directly related to the Liouville field theory. All these models share anomalously large fluctuations of the associated free energy, with a variance proportional to the log of the system size. We argue that a seemingly nonphysical vanishing of the moment generating function for some values of parameters is related to the termination point transition (i.e., prefreezing). We study the associated universal log corrections in the frozen phase, both for logREMs and for the standard REM, filling a gap in the literature. For the above mentioned integrable instances of logREMs, we predict the nontrivial free-energy cumulants describing non-Gaussian fluctuations on the top of the Gaussian with extensive variance. Some of the predictions are tested numerically.
Exponential vanishing of the ground-state gap of the quantum random energy model via adiabatic quantum computing

Science.gov (United States)

Adame, J.; Warzel, S.

2015-11-01

In this note, we use ideas of Farhi et al. [Int. J. Quantum. Inf. 6, 503 (2008) and Quantum Inf. Comput. 11, 840 (2011)] who link a lower bound on the run time of their quantum adiabatic search algorithm to an upper bound on the energy gap above the ground-state of the generators of this algorithm. We apply these ideas to the quantum random energy model (QREM). Our main result is a simple proof of the conjectured exponential vanishing of the energy gap of the QREM.
Exponential vanishing of the ground-state gap of the quantum random energy model via adiabatic quantum computing

International Nuclear Information System (INIS)

Adame, J.; Warzel, S.

2015-01-01

In this note, we use ideas of Farhi et al. [Int. J. Quantum. Inf. 6, 503 (2008) and Quantum Inf. Comput. 11, 840 (2011)] who link a lower bound on the run time of their quantum adiabatic search algorithm to an upper bound on the energy gap above the ground-state of the generators of this algorithm. We apply these ideas to the quantum random energy model (QREM). Our main result is a simple proof of the conjectured exponential vanishing of the energy gap of the QREM
Fault-tolerant topology in the wireless sensor networks for energy depletion and random failure

International Nuclear Information System (INIS)

Liu Bin; Dong Ming-Ru; Yin Rong-Rong; Yin Wen-Xiao

2014-01-01

Nodes in the wireless sensor networks (WSNs) are prone to failure due to energy depletion and poor environment, which could have a negative impact on the normal operation of the network. In order to solve this problem, in this paper, we build a fault-tolerant topology which can effectively tolerate energy depletion and random failure. Firstly, a comprehensive failure model about energy depletion and random failure is established. Then an improved evolution model is presented to generate a fault-tolerant topology, and the degree distribution of the topology can be adjusted. Finally, the relation between the degree distribution and the topological fault tolerance is analyzed, and the optimal value of evolution model parameter is obtained. Then the target fault-tolerant topology which can effectively tolerate energy depletion and random failure is obtained. The performances of the new fault tolerant topology are verified by simulation experiments. The results show that the new fault tolerant topology effectively prolongs the network lifetime and has strong fault tolerance. (general)
Continuous energy Monte Carlo calculations for randomly distributed spherical fuels based on statistical geometry model

Energy Technology Data Exchange (ETDEWEB)

Murata, Isao [Osaka Univ., Suita (Japan); Mori, Takamasa; Nakagawa, Masayuki; Itakura, Hirofumi

1996-03-01

The method to calculate neutronics parameters of a core composed of randomly distributed spherical fuels has been developed based on a statistical geometry model with a continuous energy Monte Carlo method. This method was implemented in a general purpose Monte Carlo code MCNP, and a new code MCNP-CFP had been developed. This paper describes the model and method how to use it and the validation results. In the Monte Carlo calculation, the location of a spherical fuel is sampled probabilistically along the particle flight path from the spatial probability distribution of spherical fuels, called nearest neighbor distribution (NND). This sampling method was validated through the following two comparisons: (1) Calculations of inventory of coated fuel particles (CFPs) in a fuel compact by both track length estimator and direct evaluation method, and (2) Criticality calculations for ordered packed geometries. This method was also confined by applying to an analysis of the critical assembly experiment at VHTRC. The method established in the present study is quite unique so as to a probabilistic model of the geometry with a great number of spherical fuels distributed randomly. Realizing the speed-up by vector or parallel computations in future, it is expected to be widely used in calculation of a nuclear reactor core, especially HTGR cores. (author).
Lamplighter model of a random copolymer adsorption on a line

Directory of Open Access Journals (Sweden)

L.I. Nazarov

2014-09-01

Full Text Available We present a model of an AB-diblock random copolymer sequential self-packaging with local quenched interactions on a one-dimensional infinite sticky substrate. It is assumed that the A-A and B-B contacts are favorable, while A-B are not. The position of a newly added monomer is selected in view of the local contact energy minimization. The model demonstrates a self-organization behavior with the nontrivial dependence of the total energy, E (the number of unfavorable contacts, on the number of chain monomers, N: E ~ N^3/4 for quenched random equally probable distribution of A- and B-monomers along the chain. The model is treated by mapping it onto the "lamplighter" random walk and the diffusion-controlled chemical reaction of X+X → 0 type with the subdiffusive motion of reagents.
A polymer, random walk model for the size-distribution of large DNA fragments after high linear energy transfer radiation

Science.gov (United States)

Ponomarev, A. L.; Brenner, D.; Hlatky, L. R.; Sachs, R. K.

2000-01-01

DNA double-strand breaks (DSBs) produced by densely ionizing radiation are not located randomly in the genome: recent data indicate DSB clustering along chromosomes. Stochastic DSB clustering at large scales, from > 100 Mbp down to simulations and analytic equations. A random-walk, coarse-grained polymer model for chromatin is combined with a simple track structure model in Monte Carlo software called DNAbreak and is applied to data on alpha-particle irradiation of V-79 cells. The chromatin model neglects molecular details but systematically incorporates an increase in average spatial separation between two DNA loci as the number of base-pairs between the loci increases. Fragment-size distributions obtained using DNAbreak match data on large fragments about as well as distributions previously obtained with a less mechanistic approach. Dose-response relations, linear at small doses of high linear energy transfer (LET) radiation, are obtained. They are found to be non-linear when the dose becomes so large that there is a significant probability of overlapping or close juxtaposition, along one chromosome, for different DSB clusters from different tracks. The non-linearity is more evident for large fragments than for small. The DNAbreak results furnish an example of the RLC (randomly located clusters) analytic formalism, which generalizes the broken-stick fragment-size distribution of the random-breakage model that is often applied to low-LET data.
Size-dependent piezoelectric energy-harvesting analysis of micro/nano bridges subjected to random ambient excitations

Science.gov (United States)

Radgolchin, Moeen; Moeenfard, Hamid

2018-02-01

The construction of self-powered micro-electro-mechanical units by converting the mechanical energy of the systems into electrical power has attracted much attention in recent years. While power harvesting from deterministic external excitations is state of the art, it has been much more difficult to derive mathematical models for scavenging electrical energy from ambient random vibrations, due to the stochastic nature of the excitations. The current research concerns analytical modeling of micro-bridge energy harvesters based on random vibration theory. Since classical elasticity fails to accurately predict the mechanical behavior of micro-structures, strain gradient theory is employed as a powerful tool to increase the accuracy of the random vibration modeling of the micro-harvester. Equations of motion of the system in the time domain are derived using the Lagrange approach. These are then utilized to determine the frequency and impulse responses of the structure. Assuming the energy harvester to be subjected to a combination of broadband and limited-band random support motion and transverse loading, closed-form expressions for mean, mean square, correlation and spectral density of the output power are derived. The suggested formulation is further exploited to investigate the effect of the different design parameters, including the geometric properties of the structure as well as the properties of the electrical circuit on the resulting power. Furthermore, the effect of length scale parameters on the harvested energy is investigated in detail. It is observed that the predictions of classical and even simple size-dependent theories (such as couple stress) appreciably differ from the findings of strain gradient theory on the basis of random vibration. This study presents a first-time modeling of micro-scale harvesters under stochastic excitations using a size-dependent approach and can be considered as a reliable foundation for future research in the field of
Piezoelectric energy harvesting from broadband random vibrations

International Nuclear Information System (INIS)

Adhikari, S; Friswell, M I; Inman, D J

2009-01-01

Energy harvesting for the purpose of powering low power electronic sensor systems has received explosive attention in the last few years. Most works using deterministic approaches focusing on using the piezoelectric effect to harvest ambient vibration energy have concentrated on cantilever beams at resonance using harmonic excitation. Here, using a stochastic approach, we focus on using a stack configuration and harvesting broadband vibration energy, a more practically available ambient source. It is assumed that the ambient base excitation is stationary Gaussian white noise, which has a constant power-spectral density across the frequency range considered. The mean power acquired from a piezoelectric vibration-based energy harvester subjected to random base excitation is derived using the theory of random vibrations. Two cases, namely the harvesting circuit with and without an inductor, have been considered. Exact closed-form expressions involving non-dimensional parameters of the electromechanical system have been given and illustrated using numerical examples
Piezoelectric energy harvesting from broadband random vibrations

Science.gov (United States)

Adhikari, S.; Friswell, M. I.; Inman, D. J.

2009-11-01

Energy harvesting for the purpose of powering low power electronic sensor systems has received explosive attention in the last few years. Most works using deterministic approaches focusing on using the piezoelectric effect to harvest ambient vibration energy have concentrated on cantilever beams at resonance using harmonic excitation. Here, using a stochastic approach, we focus on using a stack configuration and harvesting broadband vibration energy, a more practically available ambient source. It is assumed that the ambient base excitation is stationary Gaussian white noise, which has a constant power-spectral density across the frequency range considered. The mean power acquired from a piezoelectric vibration-based energy harvester subjected to random base excitation is derived using the theory of random vibrations. Two cases, namely the harvesting circuit with and without an inductor, have been considered. Exact closed-form expressions involving non-dimensional parameters of the electromechanical system have been given and illustrated using numerical examples.
Random Intercept and Random Slope 2-Level Multilevel Models

Directory of Open Access Journals (Sweden)

Rehan Ahmad Khan

2012-11-01

Full Text Available Random intercept model and random intercept & random slope model carrying two-levels of hierarchy in the population are presented and compared with the traditional regression approach. The impact of students’ satisfaction on their grade point average (GPA was explored with and without controlling teachers influence. The variation at level-1 can be controlled by introducing the higher levels of hierarchy in the model. The fanny movement of the fitted lines proves variation of student grades around teachers.
Pervasive randomness in physics: an introduction to its modelling and spectral characterisation

Science.gov (United States)

Howard, Roy

2017-10-01

An introduction to the modelling and spectral characterisation of random phenomena is detailed at a level consistent with a first exposure to the subject at an undergraduate level. A signal framework for defining a random process is provided and this underpins an introduction to common random processes including the Poisson point process, the random walk, the random telegraph signal, shot noise, information signalling random processes, jittered pulse trains, birth-death random processes and Markov chains. An introduction to the spectral characterisation of signals and random processes, via either an energy spectral density or a power spectral density, is detailed. The important case of defining a white noise random process concludes the paper.

Local lattice relaxations in random metallic alloys: Effective tetrahedron model and supercell approach

DEFF Research Database (Denmark)

Ruban, Andrei; Simak, S.I.; Shallcross, S.

2003-01-01

We present a simple effective tetrahedron model for local lattice relaxation effects in random metallic alloys on simple primitive lattices. A comparison with direct ab initio calculations for supercells representing random Ni0.50Pt0.50 and Cu0.25Au0.75 alloys as well as the dilute limit of Au-ri......-rich CuAu alloys shows that the model yields a quantitatively accurate description of the relaxtion energies in these systems. Finally, we discuss the bond length distribution in random alloys....
Operator product expansion in Liouville field theory and Seiberg-type transitions in log-correlated random energy models

Science.gov (United States)

Cao, Xiangyu; Le Doussal, Pierre; Rosso, Alberto; Santachiara, Raoul

2018-04-01

We study transitions in log-correlated random energy models (logREMs) that are related to the violation of a Seiberg bound in Liouville field theory (LFT): the binding transition and the termination point transition (a.k.a., pre-freezing). By means of LFT-logREM mapping, replica symmetry breaking and traveling-wave equation techniques, we unify both transitions in a two-parameter diagram, which describes the free-energy large deviations of logREMs with a deterministic background log potential, or equivalently, the joint moments of the free energy and Gibbs measure in logREMs without background potential. Under the LFT-logREM mapping, the transitions correspond to the competition of discrete and continuous terms in a four-point correlation function. Our results provide a statistical interpretation of a peculiar nonlocality of the operator product expansion in LFT. The results are rederived by a traveling-wave equation calculation, which shows that the features of LFT responsible for the transitions are reproduced in a simple model of diffusion with absorption. We examine also the problem by a replica symmetry breaking analysis. It complements the previous methods and reveals a rich large deviation structure of the free energy of logREMs with a deterministic background log potential. Many results are verified in the integrable circular logREM, by a replica-Coulomb gas integral approach. The related problem of common length (overlap) distribution is also considered. We provide a traveling-wave equation derivation of the LFT predictions announced in a precedent work.
Experimental Analysis of a Piezoelectric Energy Harvesting System for Harmonic, Random, and Sine on Random Vibration

Energy Technology Data Exchange (ETDEWEB)

Cryns, Jackson W.; Hatchell, Brian K.; Santiago-Rojas, Emiliano; Silvers, Kurt L.

2013-07-01

Formal journal article Experimental analysis of a piezoelectric energy harvesting system for harmonic, random, and sine on random vibration Abstract: Harvesting power with a piezoelectric vibration powered generator using a full-wave rectifier conditioning circuit is experimentally compared for varying sinusoidal, random and sine on random (SOR) input vibration scenarios. Additionally, the implications of source vibration characteristics on harvester design are discussed. Studies in vibration harvesting have yielded numerous alternatives for harvesting electrical energy from vibrations but piezoceramics arose as the most compact, energy dense means of energy transduction. The rise in popularity of harvesting energy from ambient vibrations has made piezoelectric generators commercially available. Much of the available literature focuses on maximizing harvested power through nonlinear processing circuits that require accurate knowledge of generator internal mechanical and electrical characteristics and idealization of the input vibration source, which cannot be assumed in general application. In this manuscript, variations in source vibration and load resistance are explored for a commercially available piezoelectric generator. We characterize the source vibration by its acceleration response for repeatability and transcription to general application. The results agree with numerical and theoretical predictions for in previous literature that load optimal resistance varies with transducer natural frequency and source type, and the findings demonstrate that significant gains are seen with lower tuned transducer natural frequencies for similar source amplitudes. Going beyond idealized steady state sinusoidal and simplified random vibration input, SOR testing allows for more accurate representation of real world ambient vibration. It is shown that characteristic interactions from more complex vibrational sources significantly alter power generation and power processing
Reliability Study of Energy Harvesting from Sea Waves by Piezoelectric Patches Consideraing Random JONSWAP Wave Theory

Directory of Open Access Journals (Sweden)

M. Ettefagh

2018-03-01

Full Text Available One of the new methods for powering low-power electronic devices employed in the sea, is using of mechanical energies of sea waves. In this method, piezoelectric material is employed to convert the mechanical energy of sea waves into electrical energy. The advantage of this method is based on not implementing the battery charging system. Although, many studies have been done about energy harvesting from sea waves, energy harvesting with considering random JONWSAP wave theory is not fully studied up to now. The random JONSWAP wave model is a more realistic approximation of sea waves in comparison of Airy wave model. Therefore, in this paper a vertical beam with the piezoelectric patches, which is fixed to the seabed, is considered as energy harvester system. The energy harvesting system is simulated by MATLAB software, and then the vibration response of the beam and consequently the generated power is obtained considering the JONWSAP wave theory. In addition, the reliability of the system and the effect of piezoelectric patches uncertainties on the generated power are studied by statistical method. Furthermore, the failure possibility of harvester based on violation criteria is investigated.
Modelling the impact of social network on energy savings

International Nuclear Information System (INIS)

Du, Feng; Zhang, Jiangfeng; Li, Hailong; Yan, Jinyue; Galloway, Stuart; Lo, Kwok L.

2016-01-01

Highlights: • Energy saving propagation along a social network is modelled. • This model consists of a time evolving weighted directed network. • Network weights and information decay are applied in savings calculation. - Abstract: It is noted that human behaviour changes can have a significant impact on energy consumption, however, qualitative study on such an impact is still very limited, and it is necessary to develop the corresponding mathematical models to describe how much energy savings can be achieved through human engagement. In this paper a mathematical model of human behavioural dynamic interactions on a social network is derived to calculate energy savings. This model consists of a weighted directed network with time evolving information on each node. Energy savings from the whole network is expressed as mathematical expectation from probability theory. This expected energy savings model includes both direct and indirect energy savings of individuals in the network. The savings model is obtained by network weights and modified by the decay of information. Expected energy savings are calculated for cases where individuals in the social network are treated as a single information source or multiple sources. This model is tested on a social network consisting of 40 people. The results show that the strength of relations between individuals is more important to information diffusion than the number of connections individuals have. The expected energy savings of optimally chosen node can be 25.32% more than randomly chosen nodes at the end of the second month for the case of single information source in the network, and 16.96% more than random nodes for the case of multiple information sources. This illustrates that the model presented in this paper can be used to determine which individuals will have the most influence on the social network, which in turn provides a useful guide to identify targeted customers in energy efficiency technology rollout
Quantum random bit generation using energy fluctuations in stimulated Raman scattering.

Science.gov (United States)

Bustard, Philip J; England, Duncan G; Nunn, Josh; Moffatt, Doug; Spanner, Michael; Lausten, Rune; Sussman, Benjamin J

2013-12-02

Random number sequences are a critical resource in modern information processing systems, with applications in cryptography, numerical simulation, and data sampling. We introduce a quantum random number generator based on the measurement of pulse energy quantum fluctuations in Stokes light generated by spontaneously-initiated stimulated Raman scattering. Bright Stokes pulse energy fluctuations up to five times the mean energy are measured with fast photodiodes and converted to unbiased random binary strings. Since the pulse energy is a continuous variable, multiple bits can be extracted from a single measurement. Our approach can be generalized to a wide range of Raman active materials; here we demonstrate a prototype using the optical phonon line in bulk diamond.
Free energy distribution function of a random Ising ferromagnet

International Nuclear Information System (INIS)

Dotsenko, Victor; Klumov, Boris

2012-01-01

We study the free energy distribution function of a weakly disordered Ising ferromagnet in terms of the D-dimensional random temperature Ginzburg–Landau Hamiltonian. It is shown that besides the usual Gaussian 'body' this distribution function exhibits non-Gaussian tails both in the paramagnetic and in the ferromagnetic phases. Explicit asymptotic expressions for these tails are derived. It is demonstrated that the tails are strongly asymmetric: the left tail (for large negative values of the free energy) is much slower than the right one (for large positive values of the free energy). It is argued that at the critical point the free energy of the random Ising ferromagnet in dimensions D < 4 is described by a non-trivial universal distribution function which is non-self-averaging
Randomly dispersed particle fuel model in the PSG Monte Carlo neutron transport code

International Nuclear Information System (INIS)

Leppaenen, J.

2007-01-01

High-temperature gas-cooled reactor fuels are composed of thousands of microscopic fuel particles, randomly dispersed in a graphite matrix. The modelling of such geometry is complicated, especially using continuous-energy Monte Carlo codes, which are unable to apply any deterministic corrections in the calculation. This paper presents the geometry routine developed for modelling randomly dispersed particle fuels using the PSG Monte Carlo reactor physics code. The model is based on the delta-tracking method, and it takes into account the spatial self-shielding effects and the random dispersion of the fuel particles. The calculation routine is validated by comparing the results to reference MCNP4C calculations using uranium and plutonium based fuels. (authors)
Complex networks-based energy-efficient evolution model for wireless sensor networks

Energy Technology Data Exchange (ETDEWEB)

Zhu Hailin [Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications, P.O. Box 106, Beijing 100876 (China)], E-mail: zhuhailin19@gmail.com; Luo Hong [Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications, P.O. Box 106, Beijing 100876 (China); Peng Haipeng; Li Lixiang; Luo Qun [Information Secure Center, State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, P.O. Box 145, Beijing 100876 (China)

2009-08-30

Based on complex networks theory, we present two self-organized energy-efficient models for wireless sensor networks in this paper. The first model constructs the wireless sensor networks according to the connectivity and remaining energy of each sensor node, thus it can produce scale-free networks which have a performance of random error tolerance. In the second model, we not only consider the remaining energy, but also introduce the constraint of links to each node. This model can make the energy consumption of the whole network more balanced. Finally, we present the numerical experiments of the two models.
Complex networks-based energy-efficient evolution model for wireless sensor networks

International Nuclear Information System (INIS)

Zhu Hailin; Luo Hong; Peng Haipeng; Li Lixiang; Luo Qun

2009-01-01

Based on complex networks theory, we present two self-organized energy-efficient models for wireless sensor networks in this paper. The first model constructs the wireless sensor networks according to the connectivity and remaining energy of each sensor node, thus it can produce scale-free networks which have a performance of random error tolerance. In the second model, we not only consider the remaining energy, but also introduce the constraint of links to each node. This model can make the energy consumption of the whole network more balanced. Finally, we present the numerical experiments of the two models.
Energy master equation

DEFF Research Database (Denmark)

Dyre, Jeppe

1995-01-01

energies chosen randomly according to a Gaussian. The random-walk model is here derived from Newton's laws by making a number of simplifying assumptions. In the second part of the paper an approximate low-temperature description of energy fluctuations in the random-walk modelthe energy master equation...... (EME)is arrived at. The EME is one dimensional and involves only energy; it is derived by arguing that percolation dominates the relaxational properties of the random-walk model at low temperatures. The approximate EME description of the random-walk model is expected to be valid at low temperatures...... of the random-walk model. The EME allows a calculation of the energy probability distribution at realistic laboratory time scales for an arbitrarily varying temperature as function of time. The EME is probably the only realistic equation available today with this property that is also explicitly consistent...
Generalization of Random Intercept Multilevel Models

Directory of Open Access Journals (Sweden)

Rehan Ahmad Khan

2013-10-01

Full Text Available The concept of random intercept models in a multilevel model developed by Goldstein (1986 has been extended for k-levels. The random variation in intercepts at individual level is marginally split into components by incorporating higher levels of hierarchy in the single level model. So, one can control the random variation in intercepts by incorporating the higher levels in the model.
A random matrix approach to the crossover of energy-level statistics from Wigner to Poisson

International Nuclear Information System (INIS)

Datta, Nilanjana; Kunz, Herve

2004-01-01

We analyze a class of parametrized random matrix models, introduced by Rosenzweig and Porter, which is expected to describe the energy level statistics of quantum systems whose classical dynamics varies from regular to chaotic as a function of a parameter. We compute the generating function for the correlations of energy levels, in the limit of infinite matrix size. The crossover between Poisson and Wigner statistics is measured by a renormalized coupling constant. The model is exactly solved in the sense that, in the limit of infinite matrix size, the energy-level correlation functions and their generating function are given in terms of a finite set of integrals
Communication strategies for two models of discrete energy harvesting

DEFF Research Database (Denmark)

Trillingsgaard, Kasper Fløe; Popovski, Petar

2014-01-01

Energy harvesting is becoming a viable option for powering small wireless devices. Energy for data transmission is supplied by the nature, such that when a transmission is about to take place in an arbitrary instant, the amount of available energy is a random quantity. The arrived energy is stored...... in a battery and transmissions are interrupted if the battery runs out of energy. We address communication in slot-based energy harvesting systems, where the transmitter communicates with ON-OFF signaling: in each slot it can either choose to transmit (ON) or stay silent (OFF). Two different models...... strategies and compare the slot- with the frame-based model in the case of an errorless transmission channel. Additionally, for the slot-based model and channel with errors, we provide a new proof of the capacity achieved by the save-and-transmit scheme....
High-temperature series expansions for random Potts models

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M.Hellmund

2005-01-01

Full Text Available We discuss recently generated high-temperature series expansions for the free energy and the susceptibility of random-bond q-state Potts models on hypercubic lattices. Using the star-graph expansion technique, quenched disorder averages can be calculated exactly for arbitrary uncorrelated coupling distributions while keeping the disorder strength p as well as the dimension d as symbolic parameters. We present analyses of the new series for the susceptibility of the Ising (q=2 and 4-state Potts model in three dimensions up to the order 19 and 18, respectively, and compare our findings with results from field-theoretical renormalization group studies and Monte Carlo simulations.
New constraints on modelling the random magnetic field of the MW

Energy Technology Data Exchange (ETDEWEB)

Beck, Marcus C.; Nielaba, Peter [Department of Physics, University of Konstanz, Universitätsstr. 10, D-78457 Konstanz (Germany); Beck, Alexander M.; Dolag, Klaus [University Observatory Munich, Scheinerstr. 1, D-81679 Munich (Germany); Beck, Rainer [Max Planck Institute for Radioastronomy, Auf dem Hügel 69, D-53121 Bonn (Germany); Strong, Andrew W., E-mail: marcus.beck@uni-konstanz.de, E-mail: abeck@usm.uni-muenchen.de, E-mail: rbeck@mpifr-bonn.mpg.de, E-mail: dolag@usm.uni-muenchen.de, E-mail: aws@mpe.mpg.de, E-mail: peter.nielaba@uni-konstanz.de [Max Planck Institute for Extraterrestrial Physics, Giessenbachstr. 1, D-85748 Garching (Germany)

2016-05-01

We extend the description of the isotropic and anisotropic random component of the small-scale magnetic field within the existing magnetic field model of the Milky Way from Jansson and Farrar, by including random realizations of the small-scale component. Using a magnetic-field power spectrum with Gaussian random fields, the NE2001 model for the thermal electrons and the Galactic cosmic-ray electron distribution from the current GALPROP model we derive full-sky maps for the total and polarized synchrotron intensity as well as the Faraday rotation-measure distribution. While previous work assumed that small-scale fluctuations average out along the line-of-sight or which only computed ensemble averages of random fields, we show that these fluctuations need to be carefully taken into account. Comparing with observational data we obtain not only good agreement with 408 MHz total and WMAP7 22 GHz polarized intensity emission maps, but also an improved agreement with Galactic foreground rotation-measure maps and power spectra, whose amplitude and shape strongly depend on the parameters of the random field. We demonstrate that a correlation length of 0≈22 pc (05 pc being a 5σ lower limit) is needed to match the slope of the observed power spectrum of Galactic foreground rotation-measure maps. Using multiple realizations allows us also to infer errors on individual observables. We find that previously-used amplitudes for random and anisotropic random magnetic field components need to be rescaled by factors of ≈0.3 and 0.6 to account for the new small-scale contributions. Our model predicts a rotation measure of −2.8±7.1 rad/m{sup 2} and 04.4±11. rad/m{sup 2} for the north and south Galactic poles respectively, in good agreement with observations. Applying our model to deflections of ultra-high-energy cosmic rays we infer a mean deflection of ≈3.5±1.1 degree for 60 EeV protons arriving from CenA.
Total-Factor Energy Efficiency in BRI Countries: An Estimation Based on Three-Stage DEA Model

Directory of Open Access Journals (Sweden)

Changhong Zhao

2018-01-01

Full Text Available The Belt and Road Initiative (BRI is showing its great influence and leadership on the international energy cooperation. Based on the three-stage DEA model, total-factor energy efficiency (TFEE in 35 BRI countries in 2015 was measured in this article. It shows that the three-stage DEA model could eliminate errors of environment variable and random, which made the result better than traditional DEA model. When environment variable errors and random errors were eliminated, the mean value of TFEE was declined. It demonstrated that TFEE of the whole sample group was overestimated because of external environment impacts and random errors. The TFEE indicators of high-income countries like South Korea, Singapore, Israel and Turkey are 1, which is in the efficiency frontier. The TFEE indicators of Russia, Saudi Arabia, Poland and China are over 0.8. And the indicators of Uzbekistan, Ukraine, South Africa and Bulgaria are in a low level. The potential of energy-saving and emissions reduction is great in countries with low TFEE indicators. Because of the gap in energy efficiency, it is necessary to distinguish different countries in the energy technology options, development planning and regulation in BRI countries.
Energy conservation law for randomly fluctuating electromagnetic fields

International Nuclear Information System (INIS)

Gbur, G.; Wolf, E.; James, D.

1999-01-01

An energy conservation law is derived for electromagnetic fields generated by any random, statistically stationary, source distribution. It is shown to provide insight into the phenomenon of correlation-induced spectral changes. The results are illustrated by an example. copyright 1999 The American Physical Society
Ground state energy fluctuations in the nuclear shell model

International Nuclear Information System (INIS)

Velazquez, Victor; Hirsch, Jorge G.; Frank, Alejandro; Barea, Jose; Zuker, Andres P.

2005-01-01

Statistical fluctuations of the nuclear ground state energies are estimated using shell model calculations in which particles in the valence shells interact through well-defined forces, and are coupled to an upper shell governed by random 2-body interactions. Induced ground-state energy fluctuations are found to be one order of magnitude smaller than those previously associated with chaotic components, in close agreement with independent perturbative estimates based on the spreading widths of excited states
Conditional Monte Carlo randomization tests for regression models.

Science.gov (United States)

Parhat, Parwen; Rosenberger, William F; Diao, Guoqing

2014-08-15

We discuss the computation of randomization tests for clinical trials of two treatments when the primary outcome is based on a regression model. We begin by revisiting the seminal paper of Gail, Tan, and Piantadosi (1988), and then describe a method based on Monte Carlo generation of randomization sequences. The tests based on this Monte Carlo procedure are design based, in that they incorporate the particular randomization procedure used. We discuss permuted block designs, complete randomization, and biased coin designs. We also use a new technique by Plamadeala and Rosenberger (2012) for simple computation of conditional randomization tests. Like Gail, Tan, and Piantadosi, we focus on residuals from generalized linear models and martingale residuals from survival models. Such techniques do not apply to longitudinal data analysis, and we introduce a method for computation of randomization tests based on the predicted rate of change from a generalized linear mixed model when outcomes are longitudinal. We show, by simulation, that these randomization tests preserve the size and power well under model misspecification. Copyright © 2014 John Wiley & Sons, Ltd.

Infinite Random Graphs as Statistical Mechanical Models

DEFF Research Database (Denmark)

Durhuus, Bergfinnur Jøgvan; Napolitano, George Maria

2011-01-01

We discuss two examples of infinite random graphs obtained as limits of finite statistical mechanical systems: a model of two-dimensional dis-cretized quantum gravity defined in terms of causal triangulated surfaces, and the Ising model on generic random trees. For the former model we describe a ...
RMBNToolbox: random models for biochemical networks

Directory of Open Access Journals (Sweden)

Niemi Jari

2007-05-01

Full Text Available Abstract Background There is an increasing interest to model biochemical and cell biological networks, as well as to the computational analysis of these models. The development of analysis methodologies and related software is rapid in the field. However, the number of available models is still relatively small and the model sizes remain limited. The lack of kinetic information is usually the limiting factor for the construction of detailed simulation models. Results We present a computational toolbox for generating random biochemical network models which mimic real biochemical networks. The toolbox is called Random Models for Biochemical Networks. The toolbox works in the Matlab environment, and it makes it possible to generate various network structures, stoichiometries, kinetic laws for reactions, and parameters therein. The generation can be based on statistical rules and distributions, and more detailed information of real biochemical networks can be used in situations where it is known. The toolbox can be easily extended. The resulting network models can be exported in the format of Systems Biology Markup Language. Conclusion While more information is accumulating on biochemical networks, random networks can be used as an intermediate step towards their better understanding. Random networks make it possible to study the effects of various network characteristics to the overall behavior of the network. Moreover, the construction of artificial network models provides the ground truth data needed in the validation of various computational methods in the fields of parameter estimation and data analysis.
A Structural Modeling Approach to a Multilevel Random Coefficients Model.

Science.gov (United States)

Rovine, Michael J.; Molenaar, Peter C. M.

2000-01-01

Presents a method for estimating the random coefficients model using covariance structure modeling and allowing one to estimate both fixed and random effects. The method is applied to real and simulated data, including marriage data from J. Belsky and M. Rovine (1990). (SLD)
Experimental Analysis of a Piezoelectric Energy Harvesting System for Harmonic, Random, and Sine on Random Vibration

Directory of Open Access Journals (Sweden)

Jackson W. Cryns

2013-01-01

Full Text Available Harvesting power with a piezoelectric vibration powered generator using a full-wave rectifier conditioning circuit is experimentally compared for varying sinusoidal, random, and sine on random (SOR input vibration scenarios; the implications of source vibration characteristics on harvester design are discussed. The rise in popularity of harvesting energy from ambient vibrations has made compact, energy dense piezoelectric generators commercially available. Much of the available literature focuses on maximizing harvested power through nonlinear processing circuits that require accurate knowledge of generator internal mechanical and electrical characteristics and idealization of the input vibration source, which cannot be assumed in general application. Variations in source vibration and load resistance are explored for a commercially available piezoelectric generator. The results agree with numerical and theoretical predictions in the previous literature for optimal power harvesting in sinusoidal and flat broadband vibration scenarios. Going beyond idealized steady-state sinusoidal and flat random vibration input, experimental SOR testing allows for more accurate representation of real world ambient vibration. It is shown that characteristic interactions from more complex vibration sources significantly alter power generation and processing requirements by varying harvested power, shifting optimal conditioning impedance, inducing voltage fluctuations, and ultimately rendering idealized sinusoidal and random analyses incorrect.
Random Dynamics

Science.gov (United States)

Bennett, D. L.; Brene, N.; Nielsen, H. B.

1987-01-01

The goal of random dynamics is the derivation of the laws of Nature as we know them (standard model) from inessential assumptions. The inessential assumptions made here are expressed as sets of general models at extremely high energies: gauge glass and spacetime foam. Both sets of models lead tentatively to the standard model.
Production of complex particles in low energy spallation and in fragmentation reactions by in-medium random clusterization

International Nuclear Information System (INIS)

Lacroix, D.; Durand, D.

2005-09-01

Rules for in-medium complex particle production in nuclear reactions are proposed. These rules have been implemented in two models to simulate nucleon-nucleus and nucleus-nucleus reactions around the Fermi energy. Our work emphasizes the effect of randomness in cluster formation, the importance of the nucleonic Fermi motion as well as the role of conservation laws. The concepts of total available phase-space and explored phase-space under constraint imposed by the reaction are clarified. The compatibility of experimental observations with a random clusterization is illustrated in a schematic scenario of a proton-nucleus collision. The role of randomness under constraint is also illustrated in the nucleus-nucleus case. (authors)
Applicability of special quasi-random structure models in thermodynamic calculations using semi-empirical Debye–Grüneisen theory

International Nuclear Information System (INIS)

Kim, Jiwoong

2015-01-01

In theoretical calculations, expressing the random distribution of atoms in a certain crystal structure is still challenging. The special quasi-random structure (SQS) model is effective for depicting such random distributions. The SQS model has not been applied to semi-empirical thermodynamic calculations; however, Debye–Grüneisen theory (DGT), a semi-empirical method, was used here for that purpose. The model reliability was obtained by comparing supercell models of various sizes. The results for chemical bonds, pair correlation, and elastic properties demonstrated the reliability of the SQS models. Thermodynamic calculations using density functional perturbation theory (DFPT) and DGT assessed the applicability of the SQS models. DGT and DFPT led to similar variations of the mixing and formation energies. This study provides guidelines for theoretical assessments to obtain the reliable SQS models and to calculate the thermodynamic properties of numerous materials with a random atomic distribution. - Highlights: • Various material properties are used to examine reliability of special quasi-random structures. • SQS models are applied to thermodynamic calculations by semi-empirical methods. • Basic calculation guidelines for materials with random atomic distribution are given.
First-principles modeling of electromagnetic scattering by discrete and discretely heterogeneous random media

Science.gov (United States)

Mishchenko, Michael I.; Dlugach, Janna M.; Yurkin, Maxim A.; Bi, Lei; Cairns, Brian; Liu, Li; Panetta, R. Lee; Travis, Larry D.; Yang, Ping; Zakharova, Nadezhda T.

2018-01-01

A discrete random medium is an object in the form of a finite volume of a vacuum or a homogeneous material medium filled with quasi-randomly and quasi-uniformly distributed discrete macroscopic impurities called small particles. Such objects are ubiquitous in natural and artificial environments. They are often characterized by analyzing theoretically the results of laboratory, in situ, or remote-sensing measurements of the scattering of light and other electromagnetic radiation. Electromagnetic scattering and absorption by particles can also affect the energy budget of a discrete random medium and hence various ambient physical and chemical processes. In either case electromagnetic scattering must be modeled in terms of appropriate optical observables, i.e., quadratic or bilinear forms in the field that quantify the reading of a relevant optical instrument or the electromagnetic energy budget. It is generally believed that time-harmonic Maxwell’s equations can accurately describe elastic electromagnetic scattering by macroscopic particulate media that change in time much more slowly than the incident electromagnetic field. However, direct solutions of these equations for discrete random media had been impracticable until quite recently. This has led to a widespread use of various phenomenological approaches in situations when their very applicability can be questioned. Recently, however, a new branch of physical optics has emerged wherein electromagnetic scattering by discrete and discretely heterogeneous random media is modeled directly by using analytical or numerically exact computer solutions of the Maxwell equations. Therefore, the main objective of this Report is to formulate the general theoretical framework of electromagnetic scattering by discrete random media rooted in the Maxwell–Lorentz electromagnetics and discuss its immediate analytical and numerical consequences. Starting from the microscopic Maxwell–Lorentz equations, we trace the development
First-principles modeling of electromagnetic scattering by discrete and discretely heterogeneous random media

International Nuclear Information System (INIS)

Mishchenko, Michael I.; Dlugach, Janna M.; Yurkin, Maxim A.; Bi, Lei; Cairns, Brian; Liu, Li; Panetta, R. Lee; Travis, Larry D.; Yang, Ping; Zakharova, Nadezhda T.

2016-01-01

A discrete random medium is an object in the form of a finite volume of a vacuum or a homogeneous material medium filled with quasi-randomly and quasi-uniformly distributed discrete macroscopic impurities called small particles. Such objects are ubiquitous in natural and artificial environments. They are often characterized by analyzing theoretically the results of laboratory, in situ, or remote-sensing measurements of the scattering of light and other electromagnetic radiation. Electromagnetic scattering and absorption by particles can also affect the energy budget of a discrete random medium and hence various ambient physical and chemical processes. In either case electromagnetic scattering must be modeled in terms of appropriate optical observables, i.e., quadratic or bilinear forms in the field that quantify the reading of a relevant optical instrument or the electromagnetic energy budget. It is generally believed that time-harmonic Maxwell’s equations can accurately describe elastic electromagnetic scattering by macroscopic particulate media that change in time much more slowly than the incident electromagnetic field. However, direct solutions of these equations for discrete random media had been impracticable until quite recently. This has led to a widespread use of various phenomenological approaches in situations when their very applicability can be questioned. Recently, however, a new branch of physical optics has emerged wherein electromagnetic scattering by discrete and discretely heterogeneous random media is modeled directly by using analytical or numerically exact computer solutions of the Maxwell equations. Therefore, the main objective of this Report is to formulate the general theoretical framework of electromagnetic scattering by discrete random media rooted in the Maxwell–Lorentz electromagnetics and discuss its immediate analytical and numerical consequences. Starting from the microscopic Maxwell–Lorentz equations, we trace the development
First-principles modeling of electromagnetic scattering by discrete and discretely heterogeneous random media

Energy Technology Data Exchange (ETDEWEB)

Mishchenko, Michael I., E-mail: michael.i.mishchenko@nasa.gov [NASA Goddard Institute for Space Studies, 2880 Broadway, New York, NY 10025 (United States); Dlugach, Janna M. [Main Astronomical Observatory of the National Academy of Sciences of Ukraine, 27 Zabolotny Str., 03680, Kyiv (Ukraine); Yurkin, Maxim A. [Voevodsky Institute of Chemical Kinetics and Combustion, SB RAS, Institutskaya str. 3, 630090 Novosibirsk (Russian Federation); Novosibirsk State University, Pirogova 2, 630090 Novosibirsk (Russian Federation); Bi, Lei [Department of Atmospheric Sciences, Texas A& M University, College Station, TX 77843 (United States); Cairns, Brian [NASA Goddard Institute for Space Studies, 2880 Broadway, New York, NY 10025 (United States); Liu, Li [NASA Goddard Institute for Space Studies, 2880 Broadway, New York, NY 10025 (United States); Columbia University, 2880 Broadway, New York, NY 10025 (United States); Panetta, R. Lee [Department of Atmospheric Sciences, Texas A& M University, College Station, TX 77843 (United States); Travis, Larry D. [NASA Goddard Institute for Space Studies, 2880 Broadway, New York, NY 10025 (United States); Yang, Ping [Department of Atmospheric Sciences, Texas A& M University, College Station, TX 77843 (United States); Zakharova, Nadezhda T. [Trinnovim LLC, 2880 Broadway, New York, NY 10025 (United States)

2016-05-16

A discrete random medium is an object in the form of a finite volume of a vacuum or a homogeneous material medium filled with quasi-randomly and quasi-uniformly distributed discrete macroscopic impurities called small particles. Such objects are ubiquitous in natural and artificial environments. They are often characterized by analyzing theoretically the results of laboratory, in situ, or remote-sensing measurements of the scattering of light and other electromagnetic radiation. Electromagnetic scattering and absorption by particles can also affect the energy budget of a discrete random medium and hence various ambient physical and chemical processes. In either case electromagnetic scattering must be modeled in terms of appropriate optical observables, i.e., quadratic or bilinear forms in the field that quantify the reading of a relevant optical instrument or the electromagnetic energy budget. It is generally believed that time-harmonic Maxwell’s equations can accurately describe elastic electromagnetic scattering by macroscopic particulate media that change in time much more slowly than the incident electromagnetic field. However, direct solutions of these equations for discrete random media had been impracticable until quite recently. This has led to a widespread use of various phenomenological approaches in situations when their very applicability can be questioned. Recently, however, a new branch of physical optics has emerged wherein electromagnetic scattering by discrete and discretely heterogeneous random media is modeled directly by using analytical or numerically exact computer solutions of the Maxwell equations. Therefore, the main objective of this Report is to formulate the general theoretical framework of electromagnetic scattering by discrete random media rooted in the Maxwell–Lorentz electromagnetics and discuss its immediate analytical and numerical consequences. Starting from the microscopic Maxwell–Lorentz equations, we trace the development
First-Principles Modeling Of Electromagnetic Scattering By Discrete and Discretely Heterogeneous Random Media

Science.gov (United States)

Mishchenko, Michael I.; Dlugach, Janna M.; Yurkin, Maxim A.; Bi, Lei; Cairns, Brian; Liu, Li; Panetta, R. Lee; Travis, Larry D.; Yang, Ping; Zakharova, Nadezhda T.

2016-01-01

A discrete random medium is an object in the form of a finite volume of a vacuum or a homogeneous material medium filled with quasi-randomly and quasi-uniformly distributed discrete macroscopic impurities called small particles. Such objects are ubiquitous in natural and artificial environments. They are often characterized by analyzing theoretically the results of laboratory, in situ, or remote-sensing measurements of the scattering of light and other electromagnetic radiation. Electromagnetic scattering and absorption by particles can also affect the energy budget of a discrete random medium and hence various ambient physical and chemical processes. In either case electromagnetic scattering must be modeled in terms of appropriate optical observables, i.e., quadratic or bilinear forms in the field that quantify the reading of a relevant optical instrument or the electromagnetic energy budget. It is generally believed that time-harmonic Maxwell's equations can accurately describe elastic electromagnetic scattering by macroscopic particulate media that change in time much more slowly than the incident electromagnetic field. However, direct solutions of these equations for discrete random media had been impracticable until quite recently. This has led to a widespread use of various phenomenological approaches in situations when their very applicability can be questioned. Recently, however, a new branch of physical optics has emerged wherein electromagnetic scattering by discrete and discretely heterogeneous random media is modeled directly by using analytical or numerically exact computer solutions of the Maxwell equations. Therefore, the main objective of this Report is to formulate the general theoretical framework of electromagnetic scattering by discrete random media rooted in the Maxwell- Lorentz electromagnetics and discuss its immediate analytical and numerical consequences. Starting from the microscopic Maxwell-Lorentz equations, we trace the development of
Random dynamics

International Nuclear Information System (INIS)

Bennett, D.L.

1987-01-01

The goal of random dynamics is the derivation of the laws of Nature as we know them (standard model) from inessential assumptions. The inessential assumptions made here are expressed as sets of general models at extremely high energies: Gauge glass and spacetime foam. Both sets of models lead tentatively to the standard model. (orig.)
Random dynamics

International Nuclear Information System (INIS)

Bennett, D.L.; Brene, N.; Nielsen, H.B.

1986-06-01

The goal of random dynamics is the derivation of the laws of Nature as we know them (standard model) from inessential assumptions. The inessential assumptions made here are expressed as sets of general models at extremely high energies: gauge glass and spacetime foam. Both sets of models lead tentatively to the standard model. (orig.)
Inflation in random landscapes with two energy scales

Science.gov (United States)

Blanco-Pillado, Jose J.; Vilenkin, Alexander; Yamada, Masaki

2018-02-01

We investigate inflation in a multi-dimensional landscape with a hierarchy of energy scales, motivated by the string theory, where the energy scale of Kahler moduli is usually assumed to be much lower than that of complex structure moduli and dilaton field. We argue that in such a landscape, the dynamics of slow-roll inflation is governed by the low-energy potential, while the initial condition for inflation are determined by tunneling through high-energy barriers. We then use the scale factor cutoff measure to calculate the probability distribution for the number of inflationary e-folds and the amplitude of density fluctuations Q, assuming that the low-energy landscape is described by a random Gaussian potential with a correlation length much smaller than M pl. We find that the distribution for Q has a unique shape and a preferred domain, which depends on the parameters of the low-energy landscape. We discuss some observational implications of this distribution and the constraints it imposes on the landscape parameters.
The influence of the directional energy distribution on the nonlinear dispersion relation in a random gravity wave field

Science.gov (United States)

Huang, N. E.; Tung, C.-C.

1977-01-01

The influence of the directional distribution of wave energy on the dispersion relation is calculated numerically using various directional wave spectrum models. The results indicate that the dispersion relation varies both as a function of the directional energy distribution and the direction of propagation of the wave component under consideration. Furthermore, both the mean deviation and the random scatter from the linear approximation increase as the energy spreading decreases. Limited observational data are compared with the theoretical results. The agreement is favorable.
Robustness of regularities for energy centroids in the presence of random interactions

International Nuclear Information System (INIS)

Zhao, Y.M.; Arima, A.; Yoshida, N.; Ogawa, K.; Yoshinaga, N.; Kota, V. K. B.

2005-01-01

In this paper we study energy centroids such as those with fixed spin and isospin and those with fixed irreducible representations for both bosons and fermions, in the presence of random two-body and/or three-body interactions. Our results show that regularities of energy centroids of fixed-spin states reported in earlier works are very robust in these more complicated cases. We suggest that these behaviors might be intrinsic features of quantum many-body systems interacting by random forces
Free Energy Self-Averaging in Protein-Sized Random Heteropolymers

International Nuclear Information System (INIS)

Chuang, Jeffrey; Grosberg, Alexander Yu.; Kardar, Mehran

2001-01-01

Current theories of heteropolymers are inherently macroscopic, but are applied to mesoscopic proteins. To compute the free energy over sequences, one assumes self-averaging -- a property established only in the macroscopic limit. By enumerating the states and energies of compact 18, 27, and 36mers on a lattice with an ensemble of random sequences, we test the self-averaging approximation. We find that fluctuations in the free energy between sequences are weak, and that self-averaging is valid at the scale of real proteins. The results validate sequence design methods which exponentially speed up computational design and simplify experimental realizations
Range walk error correction and modeling on Pseudo-random photon counting system

Science.gov (United States)

Shen, Shanshan; Chen, Qian; He, Weiji

2017-08-01

Signal to noise ratio and depth accuracy are modeled for the pseudo-random ranging system with two random processes. The theoretical results, developed herein, capture the effects of code length and signal energy fluctuation are shown to agree with Monte Carlo simulation measurements. First, the SNR is developed as a function of the code length. Using Geiger-mode avalanche photodiodes (GMAPDs), longer code length is proven to reduce the noise effect and improve SNR. Second, the Cramer-Rao lower bound on range accuracy is derived to justify that longer code length can bring better range accuracy. Combined with the SNR model and CRLB model, it is manifested that the range accuracy can be improved by increasing the code length to reduce the noise-induced error. Third, the Cramer-Rao lower bound on range accuracy is shown to converge to the previously published theories and introduce the Gauss range walk model to range accuracy. Experimental tests also converge to the presented boundary model in this paper. It has been proven that depth error caused by the fluctuation of the number of detected photon counts in the laser echo pulse leads to the depth drift of Time Point Spread Function (TPSF). Finally, numerical fitting function is used to determine the relationship between the depth error and the photon counting ratio. Depth error due to different echo energy is calibrated so that the corrected depth accuracy is improved to 1cm.
Entropy Characterization of Random Network Models

Directory of Open Access Journals (Sweden)

Pedro J. Zufiria

2017-06-01

Full Text Available This paper elaborates on the Random Network Model (RNM as a mathematical framework for modelling and analyzing the generation of complex networks. Such framework allows the analysis of the relationship between several network characterizing features (link density, clustering coefficient, degree distribution, connectivity, etc. and entropy-based complexity measures, providing new insight on the generation and characterization of random networks. Some theoretical and computational results illustrate the utility of the proposed framework.
Random detailed model for probabilistic neutronic calculation in pebble bed Very High Temperature Reactors

International Nuclear Information System (INIS)

Perez Curbelo, J.; Rosales, J.; Garcia, L.; Garcia, C.; Brayner, C.

2013-01-01

The pebble bed nuclear reactor is one of the main candidates for the next generation of nuclear power plants. In pebble bed type HTRs, the fuel is contained within graphite pebbles in the form of TRISO particles, which form a randomly packed bed inside a graphite-walled cylindrical cavity. Pebble bed reactors (PBR) offer the opportunity to meet the sustainability requirements, such as nuclear safety, economic competitiveness, proliferation resistance and a minimal production of radioactive waste. In order to simulate PBRs correctly, the double heterogeneity of the system must be considered. It consists on randomly located pebbles into the core and TRISO particles into the fuel pebbles. These features are often neglected due to the difficulty to model with MCPN code. The main reason is that there is a limited number of cells and surfaces to be defined. In this study, a computational tool which allows getting a new geometrical model of fuel pebbles for neutronic calculations with MCNPX code, was developed. The heterogeneity of system is considered, and also the randomly located TRISO particles inside the pebble. Four proposed fuel pebble models were compared regarding their effective multiplication factor and energy liberation profiles. Such models are: Homogeneous Pebble, Five Zone Homogeneous Pebble, Detailed Geometry, and Randomly Detailed Geometry. (Author)

Exact solution of the O(n) model on a random lattice

DEFF Research Database (Denmark)

Eynard, B.; Kristjansen, C.

1995-01-01

We present an exact solution of the O(n) model on a random lattice. The coupling constant space of our model is parametrized in terms of a set of moment variables and the same type of universality with respect to the potential as observed for the one-matrix model is found. In addition we find...... a large degree of universality with respect to n; namely for n gE ] - 2,2[ the solution can be presented in a form which is valid not only for any potential, but also for any n (not necessarily rational). The cases n = ±2 are treated separately. We give explicit expressions for the genus-zero contribution...... to the one- and two-loop correlators as well as for the genus-one contribution to the one-loop correlator and the free energy. It is shown how one can obtain from these results any multi-loop correlator and the free energy to any genus and the structure of the higher-genera contributions is described...
Energy modelling software

CSIR Research Space (South Africa)

Osburn, L

2010-01-01

Full Text Available The construction industry has turned to energy modelling in order to assist them in reducing the amount of energy consumed by buildings. However, while the energy loads of buildings can be accurately modelled, energy models often under...
The long-run forecasting of energy prices using the model of shifting trend

International Nuclear Information System (INIS)

Radchenko, Stanislav

2005-01-01

improve the long-term forecasts, I suggest to combine forecasts from the shifting trend model, random walk model, and an autoregressive model. The main results may be summarized as follows. The shifting trend model offers an alternative approach to construct long-run forecasts of energy prices which give additional insights about the competitive nature of energy markets. The constructed forecasts seem to be unaffected by the presence of large long-lived increases and decreases in energy prices. Also, these forecasts may be combined with the forecasts from random walk model and univariate autoregressive model to substantially decrease the mean squared forecast error (MSFE) of energy forecasts. (Author)
Cost efficiency of Japanese steam power generation companies: A Bayesian comparison of random and fixed frontier models

Energy Technology Data Exchange (ETDEWEB)

Assaf, A. George [Isenberg School of Management, University of Massachusetts-Amherst, 90 Campus Center Way, Amherst 01002 (United States); Barros, Carlos Pestana [Instituto Superior de Economia e Gestao, Technical University of Lisbon, Rua Miguel Lupi, 20, 1249-078 Lisbon (Portugal); Managi, Shunsuke [Graduate School of Environmental Studies, Tohoku University, 6-6-20 Aramaki-Aza Aoba, Aoba-Ku, Sendai 980-8579 (Japan)

2011-04-15

This study analyses and compares the cost efficiency of Japanese steam power generation companies using the fixed and random Bayesian frontier models. We show that it is essential to account for heterogeneity in modelling the performance of energy companies. Results from the model estimation also indicate that restricting CO{sub 2} emissions can lead to a decrease in total cost. The study finally discusses the efficiency variations between the energy companies under analysis, and elaborates on the managerial and policy implications of the results. (author)
Multiple regression models for energy use in air-conditioned office buildings in different climates

International Nuclear Information System (INIS)

Lam, Joseph C.; Wan, Kevin K.W.; Liu Dalong; Tsang, C.L.

2010-01-01

An attempt was made to develop multiple regression models for office buildings in the five major climates in China - severe cold, cold, hot summer and cold winter, mild, and hot summer and warm winter. A total of 12 key building design variables were identified through parametric and sensitivity analysis, and considered as inputs in the regression models. The coefficient of determination R 2 varies from 0.89 in Harbin to 0.97 in Kunming, indicating that 89-97% of the variations in annual building energy use can be explained by the changes in the 12 parameters. A pseudo-random number generator based on three simple multiplicative congruential generators was employed to generate random designs for evaluation of the regression models. The difference between regression-predicted and DOE-simulated annual building energy use are largely within 10%. It is envisaged that the regression models developed can be used to estimate the likely energy savings/penalty during the initial design stage when different building schemes and design concepts are being considered.
The random cluster model and a new integration identity

International Nuclear Information System (INIS)

Chen, L C; Wu, F Y

2005-01-01

We evaluate the free energy of the random cluster model at its critical point for 0 -1 (√q/2) is a rational number. As a by-product, our consideration leads to a closed-form evaluation of the integral 1/(4π 2 ) ∫ 0 2π dΘ ∫ 0 2π dΦ ln[A+B+C - AcosΘ - BcosΦ - Ccos(Θ+Φ)] = -ln(2S) + (2/π)[Ti 2 (AS) + Ti 2 (BS) + Ti 2 (CS)], which arises in lattice statistics, where A, B, C ≥ 0 and S=1/√(AB + BC + CA)
Modeling of battery energy storage in the National Energy Modeling System

Energy Technology Data Exchange (ETDEWEB)

Swaminathan, S.; Flynn, W.T.; Sen, R.K. [Sentech, Inc., Bethesda, MD (United States)

1997-12-01

The National Energy Modeling System (NEMS) developed by the U.S. Department of Energy`s Energy Information Administration is a well-recognized model that is used to project the potential impact of new electric generation technologies. The NEMS model does not presently have the capability to model energy storage on the national grid. The scope of this study was to assess the feasibility of, and make recommendations for, the modeling of battery energy storage systems in the Electricity Market of the NEMS. Incorporating storage within the NEMS will allow the national benefits of storage technologies to be evaluated.
Chaotic oscillation and random-number generation based on nanoscale optical-energy transfer.

Science.gov (United States)

Naruse, Makoto; Kim, Song-Ju; Aono, Masashi; Hori, Hirokazu; Ohtsu, Motoichi

2014-08-12

By using nanoscale energy-transfer dynamics and density matrix formalism, we demonstrate theoretically and numerically that chaotic oscillation and random-number generation occur in a nanoscale system. The physical system consists of a pair of quantum dots (QDs), with one QD smaller than the other, between which energy transfers via optical near-field interactions. When the system is pumped by continuous-wave radiation and incorporates a timing delay between two energy transfers within the system, it emits optical pulses. We refer to such QD pairs as nano-optical pulsers (NOPs). Irradiating an NOP with external periodic optical pulses causes the oscillating frequency of the NOP to synchronize with the external stimulus. We find that chaotic oscillation occurs in the NOP population when they are connected by an external time delay. Moreover, by evaluating the time-domain signals by statistical-test suites, we confirm that the signals are sufficiently random to qualify the system as a random-number generator (RNG). This study reveals that even relatively simple nanodevices that interact locally with each other through optical energy transfer at scales far below the wavelength of irradiating light can exhibit complex oscillatory dynamics. These findings are significant for applications such as ultrasmall RNGs.
The random walk model of intrafraction movement

International Nuclear Information System (INIS)

Ballhausen, H; Reiner, M; Kantz, S; Belka, C; Söhn, M

2013-01-01

The purpose of this paper is to understand intrafraction movement as a stochastic process driven by random external forces. The hypothetically proposed three-dimensional random walk model has significant impact on optimal PTV margins and offers a quantitatively correct explanation of experimental findings. Properties of the random walk are calculated from first principles, in particular fraction-average population density distributions for displacements along the principal axes. When substituted into the established optimal margin recipes these fraction-average distributions yield safety margins about 30% smaller as compared to the suggested values from end-of-fraction Gaussian fits. Stylized facts of a random walk are identified in clinical data, such as the increase of the standard deviation of displacements with the square root of time. Least squares errors in the comparison to experimental results are reduced by about 50% when accounting for non-Gaussian corrections from the random walk model. (paper)
The random walk model of intrafraction movement.

Science.gov (United States)

Ballhausen, H; Reiner, M; Kantz, S; Belka, C; Söhn, M

2013-04-07

The purpose of this paper is to understand intrafraction movement as a stochastic process driven by random external forces. The hypothetically proposed three-dimensional random walk model has significant impact on optimal PTV margins and offers a quantitatively correct explanation of experimental findings. Properties of the random walk are calculated from first principles, in particular fraction-average population density distributions for displacements along the principal axes. When substituted into the established optimal margin recipes these fraction-average distributions yield safety margins about 30% smaller as compared to the suggested values from end-of-fraction gaussian fits. Stylized facts of a random walk are identified in clinical data, such as the increase of the standard deviation of displacements with the square root of time. Least squares errors in the comparison to experimental results are reduced by about 50% when accounting for non-gaussian corrections from the random walk model.
On the equivalence of dilute antiferromagnets and ferromagnets in random external fields: Curie-Weiss models

International Nuclear Information System (INIS)

Perez, J.F.; Pontin, L.F.; Segundo, J.A.B.

1985-01-01

Using a method proposed by van Hemmen the free energy of the Curie-Weiss version of the site-dilute antiferromagnetic Ising model is computed, in the presence of an uniform magnetic field. The solution displays an exact correspondence between this model and the Curie-Weiss version of the Ising model in the presence of a random magnetic field. The phase diagrams are discussed and a tricritical point is shown to exist. (Author) [pt
Random matrix theory of the energy-level statistics of disordered systems at the Anderson transition

International Nuclear Information System (INIS)

Canali, C.M.

1995-09-01

We consider a family of random matrix ensembles (RME) invariant under similarity transformations and described by the probability density P(H) exp[-TrV(H)]. Dyson's mean field theory (MFT) of the corresponding plasma model of eigenvalues is generalized to the case of weak confining potential, V(is an element of) ∼ A/2 ln 2 (is an element of). The eigenvalue statistics derived from MFT are shown to deviate substantially from the classical Wigner-Dyson statistics when A c approx. 0.4 the distribution function of the level spacings (LSDF) coincides in a large energy window with the energy LSDF of the three dimensional Anderson model at the metal-insulator transition. For the same A = A c , the RME eigenvalue-number variance is linear and its slope is equal to 0.32 ± 0.02, which is consistent with the value found for the Anderson model at the critical point. (author). 51 refs, 10 figs
Dual resonant structure for energy harvesting from random vibration sources at low frequency

Directory of Open Access Journals (Sweden)

Shanshan Li

2016-01-01

Full Text Available We introduce a design with dual resonant structure which can harvest energy from random vibration sources at low frequency range. The dual resonant structure consists of two spring-mass subsystems with different frequency responses, which exhibit strong coupling and broad bandwidth when the two masses collide with each other. Experiments with piezoelectric elements show that the energy harvesting device with dual resonant structure can generate higher power output than the sum of the two separate devices from random vibration sources.
A random regret minimization model of travel choice

NARCIS (Netherlands)

Chorus, C.G.; Arentze, T.A.; Timmermans, H.J.P.

2008-01-01

Abstract This paper presents an alternative to Random Utility-Maximization models of travel choice. Our Random Regret-Minimization model is rooted in Regret Theory and provides several useful features for travel demand analysis. Firstly, it allows for the possibility that choices between travel
Random matrix models for phase diagrams

International Nuclear Information System (INIS)

Vanderheyden, B; Jackson, A D

2011-01-01

We describe a random matrix approach that can provide generic and readily soluble mean-field descriptions of the phase diagram for a variety of systems ranging from quantum chromodynamics to high-T c materials. Instead of working from specific models, phase diagrams are constructed by averaging over the ensemble of theories that possesses the relevant symmetries of the problem. Although approximate in nature, this approach has a number of advantages. First, it can be useful in distinguishing generic features from model-dependent details. Second, it can help in understanding the 'minimal' number of symmetry constraints required to reproduce specific phase structures. Third, the robustness of predictions can be checked with respect to variations in the detailed description of the interactions. Finally, near critical points, random matrix models bear strong similarities to Ginsburg-Landau theories with the advantage of additional constraints inherited from the symmetries of the underlying interaction. These constraints can be helpful in ruling out certain topologies in the phase diagram. In this Key Issues Review, we illustrate the basic structure of random matrix models, discuss their strengths and weaknesses, and consider the kinds of system to which they can be applied.
Modelling the multilevel structure and mixed effects of the factors influencing the energy consumption of electric vehicles

International Nuclear Information System (INIS)

Liu, Kai; Wang, Jiangbo; Yamamoto, Toshiyuki; Morikawa, Takayuki

2016-01-01

Highlights: • The impacts of driving heterogeneity on EVs’ energy efficiency are examined. • Several multilevel mixed-effects regression models are proposed and compared. • The most reasonable nested structure is extracted from the long term GPS data. • Proposed model improves the energy estimation accuracy by 7.5%. - Abstract: To improve the accuracy of estimation of the energy consumption of electric vehicles (EVs) and to enable the alleviation of range anxiety through the introduction of EV charging stations at suitable locations for the near future, multilevel mixed-effects linear regression models were used in this study to estimate the actual energy efficiency of EVs. The impacts of the heterogeneity in driving behaviour among various road environments and traffic conditions on EV energy efficiency were extracted from long-term daily trip-based energy consumption data, which were collected over 12 months from 68 in-use EVs in Aichi Prefecture in Japan. Considering the variations in energy efficiency associated with different types of EV ownership, different external environments, and different driving habits, a two-level random intercept model, three two-level mixed-effects models, and two three-level mixed-effects models were developed and compared. The most reasonable nesting structure was determined by comparing the models, which were designed with different nesting structures and different random variance component specifications, thereby revealing the potential correlations and non-constant variability of the energy consumption per kilometre (ECPK) and improving the estimation accuracy by 7.5%.
Creating, generating and comparing random network models with NetworkRandomizer.

Science.gov (United States)

Tosadori, Gabriele; Bestvina, Ivan; Spoto, Fausto; Laudanna, Carlo; Scardoni, Giovanni

2016-01-01

Biological networks are becoming a fundamental tool for the investigation of high-throughput data in several fields of biology and biotechnology. With the increasing amount of information, network-based models are gaining more and more interest and new techniques are required in order to mine the information and to validate the results. To fill the validation gap we present an app, for the Cytoscape platform, which aims at creating randomised networks and randomising existing, real networks. Since there is a lack of tools that allow performing such operations, our app aims at enabling researchers to exploit different, well known random network models that could be used as a benchmark for validating real, biological datasets. We also propose a novel methodology for creating random weighted networks, i.e. the multiplication algorithm, starting from real, quantitative data. Finally, the app provides a statistical tool that compares real versus randomly computed attributes, in order to validate the numerical findings. In summary, our app aims at creating a standardised methodology for the validation of the results in the context of the Cytoscape platform.
Monte Carlo simulation of the three-state vector Potts model on a three-dimensional random lattice

International Nuclear Information System (INIS)

Jianbo Zhang; Heping Ying

1991-09-01

We have performed a numerical simulation of the three-state vector Potts model on a three-dimensional random lattice. The averages of energy density, magnetization, specific heat and susceptibility of the system in the N 3 (N=8,10,12) lattices were calculated. The results show that a first order nature of the Z(3) symmetry breaking transition appears, as characterized by a thermal hysterisis in the energy density as well as an abrupt drop of magnetization being sharper and discontinuous with increasing of volume in the cross-over region. The results obtained on the random lattice were consistent with those obtained on the three-dimensional cubic lattice. (author). 12 refs, 4 figs
A random spatial network model based on elementary postulates

Science.gov (United States)

Karlinger, Michael R.; Troutman, Brent M.

1989-01-01

A model for generating random spatial networks that is based on elementary postulates comparable to those of the random topology model is proposed. In contrast to the random topology model, this model ascribes a unique spatial specification to generated drainage networks, a distinguishing property of some network growth models. The simplicity of the postulates creates an opportunity for potential analytic investigations of the probabilistic structure of the drainage networks, while the spatial specification enables analyses of spatially dependent network properties. In the random topology model all drainage networks, conditioned on magnitude (number of first-order streams), are equally likely, whereas in this model all spanning trees of a grid, conditioned on area and drainage density, are equally likely. As a result, link lengths in the generated networks are not independent, as usually assumed in the random topology model. For a preliminary model evaluation, scale-dependent network characteristics, such as geometric diameter and link length properties, and topologic characteristics, such as bifurcation ratio, are computed for sets of drainage networks generated on square and rectangular grids. Statistics of the bifurcation and length ratios fall within the range of values reported for natural drainage networks, but geometric diameters tend to be relatively longer than those for natural networks.
A note on crossing the phantom divide in hybrid dark energy model

International Nuclear Information System (INIS)

Wei Hao; Cai Ronggen

2006-01-01

Recently a lot of attention has been given to building dark energy models in which the equation-of-state parameter w can cross the phantom divide w=-1. However, to our knowledge, these models with crossing the phantom divide only provide the possibility that w can cross -1. They do not answer another question: why crossing phantom divide occurs recently? Since in many existing models whose equation-of-state parameter can cross the phantom divide, w undulates around -1 randomly, why are we living in an epochw<-1? This can be regarded as the second cosmological coincidence problem. In this Letter, we propose a possible approach to alleviate this problem within a hybrid dark energy model

Simulating WTP Values from Random-Coefficient Models

OpenAIRE

Maurus Rischatsch

2009-01-01

Discrete Choice Experiments (DCEs) designed to estimate willingness-to-pay (WTP) values are very popular in health economics. With increased computation power and advanced simulation techniques, random-coefficient models have gained an increasing importance in applied work as they allow for taste heterogeneity. This paper discusses the parametrical derivation of WTP values from estimated random-coefficient models and shows how these values can be simulated in cases where they do not have a kn...
Random effects coefficient of determination for mixed and meta-analysis models.

Science.gov (United States)

Demidenko, Eugene; Sargent, James; Onega, Tracy

2012-01-01

The key feature of a mixed model is the presence of random effects. We have developed a coefficient, called the random effects coefficient of determination, [Formula: see text], that estimates the proportion of the conditional variance of the dependent variable explained by random effects. This coefficient takes values from 0 to 1 and indicates how strong the random effects are. The difference from the earlier suggested fixed effects coefficient of determination is emphasized. If [Formula: see text] is close to 0, there is weak support for random effects in the model because the reduction of the variance of the dependent variable due to random effects is small; consequently, random effects may be ignored and the model simplifies to standard linear regression. The value of [Formula: see text] apart from 0 indicates the evidence of the variance reduction in support of the mixed model. If random effects coefficient of determination is close to 1 the variance of random effects is very large and random effects turn into free fixed effects-the model can be estimated using the dummy variable approach. We derive explicit formulas for [Formula: see text] in three special cases: the random intercept model, the growth curve model, and meta-analysis model. Theoretical results are illustrated with three mixed model examples: (1) travel time to the nearest cancer center for women with breast cancer in the U.S., (2) cumulative time watching alcohol related scenes in movies among young U.S. teens, as a risk factor for early drinking onset, and (3) the classic example of the meta-analysis model for combination of 13 studies on tuberculosis vaccine.
A Generalized Random Regret Minimization Model

NARCIS (Netherlands)

Chorus, C.G.

2013-01-01

This paper presents, discusses and tests a generalized Random Regret Minimization (G-RRM) model. The G-RRM model is created by replacing a fixed constant in the attribute-specific regret functions of the RRM model, by a regret-weight variable. Depending on the value of the regret-weights, the G-RRM
Simulation of a directed random-walk model: the effect of pseudo-random-number correlations

OpenAIRE

Shchur, L. N.; Heringa, J. R.; Blöte, H. W. J.

1996-01-01

We investigate the mechanism that leads to systematic deviations in cluster Monte Carlo simulations when correlated pseudo-random numbers are used. We present a simple model, which enables an analysis of the effects due to correlations in several types of pseudo-random-number sequences. This model provides qualitative understanding of the bias mechanism in a class of cluster Monte Carlo algorithms.
A Note on the Correlated Random Coefficient Model

DEFF Research Database (Denmark)

Kolodziejczyk, Christophe

In this note we derive the bias of the OLS estimator for a correlated random coefficient model with one random coefficient, but which is correlated with a binary variable. We provide set-identification to the parameters of interest of the model. We also show how to reduce the bias of the estimator...
Depletion benchmarks calculation of random media using explicit modeling approach of RMC

International Nuclear Information System (INIS)

Liu, Shichang; She, Ding; Liang, Jin-gang; Wang, Kan

2016-01-01

Highlights: • Explicit modeling of RMC is applied to depletion benchmark for HTGR fuel element. • Explicit modeling can provide detailed burnup distribution and burnup heterogeneity. • The results would serve as a supplement for the HTGR fuel depletion benchmark. • The method of adjacent burnup regions combination is proposed for full-core problems. • The combination method can reduce memory footprint, keeping the computing accuracy. - Abstract: Monte Carlo method plays an important role in accurate simulation of random media, owing to its advantages of the flexible geometry modeling and the use of continuous-energy nuclear cross sections. Three stochastic geometry modeling methods including Random Lattice Method, Chord Length Sampling and explicit modeling approach with mesh acceleration technique, have been implemented in RMC to simulate the particle transport in the dispersed fuels, in which the explicit modeling method is regarded as the best choice. In this paper, the explicit modeling method is applied to the depletion benchmark for HTGR fuel element, and the method of combination of adjacent burnup regions has been proposed and investigated. The results show that the explicit modeling can provide detailed burnup distribution of individual TRISO particles, and this work would serve as a supplement for the HTGR fuel depletion benchmark calculations. The combination of adjacent burnup regions can effectively reduce the memory footprint while keeping the computational accuracy.
Random fractal structures in North American energy markets

Energy Technology Data Exchange (ETDEWEB)

Serletis, Apostolos [Calgary Univ., Dept. of Economics, Calgary, AB (Canada); Andreadis, Ioannis [European Univ. of the Hague, Center of Management Studies, The Hague (Netherlands)

2004-05-01

This paper uses daily observations on West Texas Intermediate (WTI) crude oil prices at Chicago and Henry Hub natural gas prices at LA (over the deregulated period of the 1990s) and various tests from statistics and dynamical systems theory to support a random fractal structure for North American energy markets. In particular, this evidence is supported by the Vassilicos et al. (1993) multifractal structure test and the Ghashghaie et al. [Nature 381 (1996) 767] turbulent behavior test. (Author)
The random field Blume-Capel model revisited

Science.gov (United States)

Santos, P. V.; da Costa, F. A.; de Araújo, J. M.

2018-04-01

We have revisited the mean-field treatment for the Blume-Capel model under the presence of a discrete random magnetic field as introduced by Kaufman and Kanner (1990). The magnetic field (H) versus temperature (T) phase diagrams for given values of the crystal field D were recovered in accordance to Kaufman and Kanner original work. However, our main goal in the present work was to investigate the distinct structures of the crystal field versus temperature phase diagrams as the random magnetic field is varied because similar models have presented reentrant phenomenon due to randomness. Following previous works we have classified the distinct phase diagrams according to five different topologies. The topological structure of the phase diagrams is maintained for both H - T and D - T cases. Although the phase diagrams exhibit a richness of multicritical phenomena we did not found any reentrant effect as have been seen in similar models.
Random regression models for detection of gene by environment interaction

Directory of Open Access Journals (Sweden)

Meuwissen Theo HE

2007-02-01

Full Text Available Abstract Two random regression models, where the effect of a putative QTL was regressed on an environmental gradient, are described. The first model estimates the correlation between intercept and slope of the random regression, while the other model restricts this correlation to 1 or -1, which is expected under a bi-allelic QTL model. The random regression models were compared to a model assuming no gene by environment interactions. The comparison was done with regards to the models ability to detect QTL, to position them accurately and to detect possible QTL by environment interactions. A simulation study based on a granddaughter design was conducted, and QTL were assumed, either by assigning an effect independent of the environment or as a linear function of a simulated environmental gradient. It was concluded that the random regression models were suitable for detection of QTL effects, in the presence and absence of interactions with environmental gradients. Fixing the correlation between intercept and slope of the random regression had a positive effect on power when the QTL effects re-ranked between environments.
Random defect lines in conformal minimal models

International Nuclear Information System (INIS)

Jeng, M.; Ludwig, A.W.W.

2001-01-01

We analyze the effect of adding quenched disorder along a defect line in the 2D conformal minimal models using replicas. The disorder is realized by a random applied magnetic field in the Ising model, by fluctuations in the ferromagnetic bond coupling in the tricritical Ising model and tricritical three-state Potts model (the phi 12 operator), etc. We find that for the Ising model, the defect renormalizes to two decoupled half-planes without disorder, but that for all other models, the defect renormalizes to a disorder-dominated fixed point. Its critical properties are studied with an expansion in ε∝1/m for the mth Virasoro minimal model. The decay exponents X N =((N)/(2))1-((9(3N-4))/(4(m+1) 2 ))+O((3)/(m+1)) 3 of the Nth moment of the two-point function of phi 12 along the defect are obtained to 2-loop order, exhibiting multifractal behavior. This leads to a typical decay exponent X typ =((1)/(2))1+((9)/((m+1) 2 ))+O((3)/(m+1)) 3 . One-point functions are seen to have a non-self-averaging amplitude. The boundary entropy is larger than that of the pure system by order 1/m 3 . As a byproduct of our calculations, we also obtain to 2-loop order the exponent X-tilde N =N1-((2)/(9π 2 ))(3N-4)(q-2) 2 +O(q-2) 3 of the Nth moment of the energy operator in the q-state Potts model with bulk bond disorder
Emergent randomness in the Jaynes-Cummings model

International Nuclear Information System (INIS)

Garraway, B M; Stenholm, S

2008-01-01

We consider the well-known Jaynes-Cummings model and ask if it can display randomness. As a solvable Hamiltonian system, it does not display chaotic behaviour in the ordinary sense. Here, however, we look at the distribution of values taken up during the total time evolution. This evolution is determined by the eigenvalues distributed as the square roots of integers and leads to a seemingly erratic behaviour. That this may display a random Gaussian value distribution is suggested by an exactly provable result by Kac. In order to reach our conclusion we use the Kac model to develop tests for the emergence of a Gaussian. Even if the consequent double limits are difficult to evaluate numerically, we find definite indications that the Jaynes-Cummings case also produces a randomness in its value distributions. Numerical methods do not establish such a result beyond doubt, but our conclusions are definite enough to suggest strongly an unexpected randomness emerging in a dynamic time evolution
Critical Behavior of the Annealed Ising Model on Random Regular Graphs

Science.gov (United States)

Can, Van Hao

2017-11-01

In Giardinà et al. (ALEA Lat Am J Probab Math Stat 13(1):121-161, 2016), the authors have defined an annealed Ising model on random graphs and proved limit theorems for the magnetization of this model on some random graphs including random 2-regular graphs. Then in Can (Annealed limit theorems for the Ising model on random regular graphs, arXiv:1701.08639, 2017), we generalized their results to the class of all random regular graphs. In this paper, we study the critical behavior of this model. In particular, we determine the critical exponents and prove a non standard limit theorem stating that the magnetization scaled by n^{3/4} converges to a specific random variable, with n the number of vertices of random regular graphs.
Random matrix theory of the energy-level statistics of disordered systems at the Anderson transition

Energy Technology Data Exchange (ETDEWEB)

Canali, C M

1995-09-01

We consider a family of random matrix ensembles (RME) invariant under similarity transformations and described by the probability density P(H) exp[-TrV(H)]. Dyson`s mean field theory (MFT) of the corresponding plasma model of eigenvalues is generalized to the case of weak confining potential, V(is an element of) {approx} A/2 ln{sup 2}(is an element of). The eigenvalue statistics derived from MFT are shown to deviate substantially from the classical Wigner-Dyson statistics when A < 1. By performing systematic Monte Carlo simulations on the plasma model, we compute all the relevant statistical properties of the RME with weak confinement. For A{sub c} approx. 0.4 the distribution function of the level spacings (LSDF) coincides in a large energy window with the energy LSDF of the three dimensional Anderson model at the metal-insulator transition. For the same A = A{sub c}, the RME eigenvalue-number variance is linear and its slope is equal to 0.32 {+-} 0.02, which is consistent with the value found for the Anderson model at the critical point. (author). 51 refs, 10 figs.
Energy technologies and energy efficiency in economic modelling

DEFF Research Database (Denmark)

Klinge Jacobsen, Henrik

1998-01-01

This paper discusses different approaches to incorporating energy technologies and technological development in energy-economic models. Technological development is a very important issue in long-term energy demand projections and in environmental analyses. Different assumptions on technological ...... of renewable energy and especially wind power will increase the rate of efficiency improvement. A technologically based model in this case indirectly makes the energy efficiency endogenous in the aggregate energy-economy model....... technological development. This paper examines the effect on aggregate energy efficiency of using technological models to describe a number of specific technologies and of incorporating these models in an economic model. Different effects from the technology representation are illustrated. Vintage effects...... illustrates the dependence of average efficiencies and productivity on capacity utilisation rates. In the long run regulation induced by environmental policies are also very important for the improvement of aggregate energy efficiency in the energy supply sector. A Danish policy to increase the share...
Energy Models

Science.gov (United States)

Energy models characterize the energy system, its evolution, and its interactions with the broader economy. The energy system consists of primary resources, including both fossil fuels and renewables; power plants, refineries, and other technologies to process and convert these r...
Energy Contents of Frequently Ordered Restaurant Meals and Comparison with Human Energy Requirements and US Department of Agriculture Database Information: A Multisite Randomized Study

Science.gov (United States)

Urban, Lorien E.; Weber, Judith L.; Heyman, Melvin B.; Schichtl, Rachel L.; Verstraete, Sofia; Lowery, Nina S.; Das, Sai Krupa; Schleicher, Molly M.; Rogers, Gail; Economos, Christina; Masters, William A.; Roberts, Susan B.

2017-01-01

Background Excess energy intake from meals consumed away from home is implicated as a major contributor to obesity, and ~50% of US restaurants are individual or small-chain (non–chain) establishments that do not provide nutrition information. Objective To measure the energy content of frequently ordered meals in non–chain restaurants in three US locations, and compare with the energy content of meals from large-chain restaurants, energy requirements, and food database information. Design A multisite random-sampling protocol was used to measure the energy contents of the most frequently ordered meals from the most popular cuisines in non–chain restaurants, together with equivalent meals from large-chain restaurants. Setting Meals were obtained from restaurants in San Francisco, CA; Boston, MA; and Little Rock, AR, between 2011 and 2014. Main outcome measures Meal energy content determined by bomb calorimetry. Statistical analysis performed Regional and cuisine differences were assessed using a mixed model with restaurant nested within region×cuisine as the random factor. Paired t tests were used to evaluate differences between non–chain and chain meals, human energy requirements, and food database values. Results Meals from non–chain restaurants contained 1,205±465 kcal/meal, amounts that were not significantly different from equivalent meals from large-chain restaurants (+5.1%; P=0.41). There was a significant effect of cuisine on non–chain meal energy, and three of the four most popular cuisines (American, Italian, and Chinese) had the highest mean energy (1,495 kcal/meal). Ninety-two percent of meals exceeded typical energy requirements for a single eating occasion. Conclusions Non–chain restaurants lacking nutrition information serve amounts of energy that are typically far in excess of human energy requirements for single eating occasions, and are equivalent to amounts served by the large-chain restaurants that have previously been criticized
A random effects meta-analysis model with Box-Cox transformation.

Science.gov (United States)

Yamaguchi, Yusuke; Maruo, Kazushi; Partlett, Christopher; Riley, Richard D

2017-07-19

In a random effects meta-analysis model, true treatment effects for each study are routinely assumed to follow a normal distribution. However, normality is a restrictive assumption and the misspecification of the random effects distribution may result in a misleading estimate of overall mean for the treatment effect, an inappropriate quantification of heterogeneity across studies and a wrongly symmetric prediction interval. We focus on problems caused by an inappropriate normality assumption of the random effects distribution, and propose a novel random effects meta-analysis model where a Box-Cox transformation is applied to the observed treatment effect estimates. The proposed model aims to normalise an overall distribution of observed treatment effect estimates, which is sum of the within-study sampling distributions and the random effects distribution. When sampling distributions are approximately normal, non-normality in the overall distribution will be mainly due to the random effects distribution, especially when the between-study variation is large relative to the within-study variation. The Box-Cox transformation addresses this flexibly according to the observed departure from normality. We use a Bayesian approach for estimating parameters in the proposed model, and suggest summarising the meta-analysis results by an overall median, an interquartile range and a prediction interval. The model can be applied for any kind of variables once the treatment effect estimate is defined from the variable. A simulation study suggested that when the overall distribution of treatment effect estimates are skewed, the overall mean and conventional I 2 from the normal random effects model could be inappropriate summaries, and the proposed model helped reduce this issue. We illustrated the proposed model using two examples, which revealed some important differences on summary results, heterogeneity measures and prediction intervals from the normal random effects model. The
A random effects meta-analysis model with Box-Cox transformation

Directory of Open Access Journals (Sweden)

Yusuke Yamaguchi

2017-07-01

Full Text Available Abstract Background In a random effects meta-analysis model, true treatment effects for each study are routinely assumed to follow a normal distribution. However, normality is a restrictive assumption and the misspecification of the random effects distribution may result in a misleading estimate of overall mean for the treatment effect, an inappropriate quantification of heterogeneity across studies and a wrongly symmetric prediction interval. Methods We focus on problems caused by an inappropriate normality assumption of the random effects distribution, and propose a novel random effects meta-analysis model where a Box-Cox transformation is applied to the observed treatment effect estimates. The proposed model aims to normalise an overall distribution of observed treatment effect estimates, which is sum of the within-study sampling distributions and the random effects distribution. When sampling distributions are approximately normal, non-normality in the overall distribution will be mainly due to the random effects distribution, especially when the between-study variation is large relative to the within-study variation. The Box-Cox transformation addresses this flexibly according to the observed departure from normality. We use a Bayesian approach for estimating parameters in the proposed model, and suggest summarising the meta-analysis results by an overall median, an interquartile range and a prediction interval. The model can be applied for any kind of variables once the treatment effect estimate is defined from the variable. Results A simulation study suggested that when the overall distribution of treatment effect estimates are skewed, the overall mean and conventional I 2 from the normal random effects model could be inappropriate summaries, and the proposed model helped reduce this issue. We illustrated the proposed model using two examples, which revealed some important differences on summary results, heterogeneity measures and
Approximating prediction uncertainty for random forest regression models

Science.gov (United States)

John W. Coulston; Christine E. Blinn; Valerie A. Thomas; Randolph H. Wynne

2016-01-01

Machine learning approaches such as random forest haveÂ increased for the spatial modeling and mapping of continuousÂ variables. Random forest is a non-parametric ensembleÂ approach, and unlike traditional regression approaches thereÂ is no direct quantification of prediction error. UnderstandingÂ prediction uncertainty is important when using model-basedÂ continuous maps as...
Compensatory and non-compensatory multidimensional randomized item response models

NARCIS (Netherlands)

Fox, J.P.; Entink, R.K.; Avetisyan, M.

2014-01-01

Randomized response (RR) models are often used for analysing univariate randomized response data and measuring population prevalence of sensitive behaviours. There is much empirical support for the belief that RR methods improve the cooperation of the respondents. Recently, RR models have been

Energy models for commercial energy prediction and substitution of renewable energy sources

International Nuclear Information System (INIS)

Iniyan, S.; Suganthi, L.; Samuel, Anand A.

2006-01-01

In this paper, three models have been projected namely Modified Econometric Mathematical (MEM) model, Mathematical Programming Energy-Economy-Environment (MPEEE) model, and Optimal Renewable Energy Mathematical (OREM) model. The actual demand for coal, oil and electricity is predicted using the MEM model based on economic, technological and environmental factors. The results were used in the MPEEE model, which determines the optimum allocation of commercial energy sources based on environmental limitations. The gap between the actual energy demand from the MEM model and optimal energy use from the MPEEE model, has to be met by the renewable energy sources. The study develops an OREM model that would facilitate effective utilization of renewable energy sources in India, based on cost, efficiency, social acceptance, reliability, potential and demand. The economic variations in solar energy systems and inclusion of environmental constraint are also analyzed with OREM model. The OREM model will help policy makers in the formulation and implementation of strategies concerning renewable energy sources in India for the next two decades
SU-F-BRD-09: A Random Walk Model Algorithm for Proton Dose Calculation

International Nuclear Information System (INIS)

Yao, W; Farr, J

2015-01-01

Purpose: To develop a random walk model algorithm for calculating proton dose with balanced computation burden and accuracy. Methods: Random walk (RW) model is sometimes referred to as a density Monte Carlo (MC) simulation. In MC proton dose calculation, the use of Gaussian angular distribution of protons due to multiple Coulomb scatter (MCS) is convenient, but in RW the use of Gaussian angular distribution requires an extremely large computation and memory. Thus, our RW model adopts spatial distribution from the angular one to accelerate the computation and to decrease the memory usage. From the physics and comparison with the MC simulations, we have determined and analytically expressed those critical variables affecting the dose accuracy in our RW model. Results: Besides those variables such as MCS, stopping power, energy spectrum after energy absorption etc., which have been extensively discussed in literature, the following variables were found to be critical in our RW model: (1) inverse squared law that can significantly reduce the computation burden and memory, (2) non-Gaussian spatial distribution after MCS, and (3) the mean direction of scatters at each voxel. In comparison to MC results, taken as reference, for a water phantom irradiated by mono-energetic proton beams from 75 MeV to 221.28 MeV, the gamma test pass rate was 100% for the 2%/2mm/10% criterion. For a highly heterogeneous phantom consisting of water embedded by a 10 cm cortical bone and a 10 cm lung in the Bragg peak region of the proton beam, the gamma test pass rate was greater than 98% for the 3%/3mm/10% criterion. Conclusion: We have determined key variables in our RW model for proton dose calculation. Compared with commercial pencil beam algorithms, our RW model much improves the dose accuracy in heterogeneous regions, and is about 10 times faster than MC simulations
Energy-Water Modeling and Analysis | Energy Analysis | NREL

Science.gov (United States)

Generation (ReEDS Model Analysis) U.S. Energy Sector Vulnerabilities to Climate Change and Extreme Weather Modeling and Analysis Energy-Water Modeling and Analysis NREL's energy-water modeling and analysis vulnerabilities from various factors, including water. Example Projects Renewable Electricity Futures Study
Assessment of correlation energies based on the random-phase approximation

International Nuclear Information System (INIS)

Paier, Joachim; Ren, Xinguo; Rinke, Patrick; Scheffler, Matthias; Scuseria, Gustavo E; Grüneis, Andreas; Kresse, Georg

2012-01-01

The random-phase approximation to the ground state correlation energy (RPA) in combination with exact exchange (EX) has brought the Kohn-Sham (KS) density functional theory one step closer towards a universal, ‘general purpose first-principles method’. In an effort to systematically assess the influence of several correlation energy contributions beyond RPA, this paper presents dissociation energies of small molecules and solids, activation energies for hydrogen transfer and non-hydrogen transfer reactions, as well as reaction energies for a number of common test sets. We benchmark EX + RPA and several flavors of energy functionals going beyond it: second-order screened exchange (SOSEX), single-excitation (SE) corrections, renormalized single-excitation (rSE) corrections and their combinations. Both the SE correction and the SOSEX contribution to the correlation energy significantly improve on the notorious tendency of EX + RPA to underbind. Surprisingly, activation energies obtained using EX + RPA based on a KS reference alone are remarkably accurate. RPA + SOSEX + rSE provides an equal level of accuracy for reaction as well as activation energies and overall gives the most balanced performance, because of which it can be applied to a wide range of systems and chemical reactions. (paper)
Universality and Thouless energy in the supersymmetric Sachdev-Ye-Kitaev model

Science.gov (United States)

García-García, Antonio M.; Jia, Yiyang; Verbaarschot, Jacobus J. M.

2018-05-01

We investigate the supersymmetric Sachdev-Ye-Kitaev (SYK) model, N Majorana fermions with infinite range interactions in 0 +1 dimensions. We have found that, close to the ground state E ≈0 , discrete symmetries alter qualitatively the spectral properties with respect to the non-supersymmetric SYK model. The average spectral density at finite N , which we compute analytically and numerically, grows exponentially with N for E ≈0 . However the chiral condensate, which is normalized with respect the total number of eigenvalues, vanishes in the thermodynamic limit. Slightly above E ≈0 , the spectral density grows exponentially with the energy. Deep in the quantum regime, corresponding to the first O (N ) eigenvalues, the average spectral density is universal and well described by random matrix ensembles with chiral and superconducting discrete symmetries. The dynamics for E ≈0 is investigated by level fluctuations. Also in this case we find excellent agreement with the prediction of chiral and superconducting random matrix ensembles for eigenvalue separations smaller than the Thouless energy, which seems to scale linearly with N . Deviations beyond the Thouless energy, which describes how ergodicity is approached, are universally characterized by a quadratic growth of the number variance. In the time domain, we have found analytically that the spectral form factor g (t ), obtained from the connected two-level correlation function of the unfolded spectrum, decays as 1 /t2 for times shorter but comparable to the Thouless time with g (0 ) related to the coefficient of the quadratic growth of the number variance. Our results provide further support that quantum black holes are ergodic and therefore can be classified by random matrix theory.
Evaluating Energy Efficiency Policies with Energy-Economy Models

Energy Technology Data Exchange (ETDEWEB)

Mundaca, Luis; Neij, Lena; Worrell, Ernst; McNeil, Michael A.

2010-08-01

The growing complexities of energy systems, environmental problems and technology markets are driving and testing most energy-economy models to their limits. To further advance bottom-up models from a multidisciplinary energy efficiency policy evaluation perspective, we review and critically analyse bottom-up energy-economy models and corresponding evaluation studies on energy efficiency policies to induce technological change. We use the household sector as a case study. Our analysis focuses on decision frameworks for technology choice, type of evaluation being carried out, treatment of market and behavioural failures, evaluated policy instruments, and key determinants used to mimic policy instruments. Although the review confirms criticism related to energy-economy models (e.g. unrealistic representation of decision-making by consumers when choosing technologies), they provide valuable guidance for policy evaluation related to energy efficiency. Different areas to further advance models remain open, particularly related to modelling issues, techno-economic and environmental aspects, behavioural determinants, and policy considerations.
Computer simulations of the random barrier model

DEFF Research Database (Denmark)

Schrøder, Thomas; Dyre, Jeppe

2002-01-01

A brief review of experimental facts regarding ac electronic and ionic conduction in disordered solids is given followed by a discussion of what is perhaps the simplest realistic model, the random barrier model (symmetric hopping model). Results from large scale computer simulations are presented...
Introduction to conformal invariance in statistical mechanics and to random surface models

International Nuclear Information System (INIS)

David, F.

1995-01-01

In the first part of these lectures I give a brief and somewhat superficial introduction to the techniques of conformal invariance and to a few applications in statistical mechanics in two dimensions. My purpose is to introduce the basic ideas and some standard results for the students who are not familiar with the theory, and to introduce concepts and tools which will be useful for the other lecturers, rather than to give a complete and up to date review of the subject. In the second part I discuss several problems in the statistical mechanics of two dimensional random surfaces and membranes. As an introduction, I present some basic facts about the statistical mechanics of one-dimensional objects and polymers, which are classical examples of objects with critical properties. Then I emphasize the special role of curvature energy and of the elastic energy associated with the internal structure of membranes, and the corresponding models of random surfaces. Finally, I discuss the specific problem of self-avoiding tethered surfaces, whose critical properties are still poorly understood, and for which the applicability of some basic techniques of field theory, such as renormalization group calculations, has been understood only recently. (orig.)
Randomized Item Response Theory Models

NARCIS (Netherlands)

Fox, Gerardus J.A.

2005-01-01

The randomized response (RR) technique is often used to obtain answers on sensitive questions. A new method is developed to measure latent variables using the RR technique because direct questioning leads to biased results. Within the RR technique is the probability of the true response modeled by
Energy Contents of Frequently Ordered Restaurant Meals and Comparison with Human Energy Requirements and U.S. Department of Agriculture Database Information: A Multisite Randomized Study.

Science.gov (United States)

Urban, Lorien E; Weber, Judith L; Heyman, Melvin B; Schichtl, Rachel L; Verstraete, Sofia; Lowery, Nina S; Das, Sai Krupa; Schleicher, Molly M; Rogers, Gail; Economos, Christina; Masters, William A; Roberts, Susan B

2016-04-01

Excess energy intake from meals consumed away from home is implicated as a major contributor to obesity, and ∼50% of US restaurants are individual or small-chain (non-chain) establishments that do not provide nutrition information. To measure the energy content of frequently ordered meals in non-chain restaurants in three US locations, and compare with the energy content of meals from large-chain restaurants, energy requirements, and food database information. A multisite random-sampling protocol was used to measure the energy contents of the most frequently ordered meals from the most popular cuisines in non-chain restaurants, together with equivalent meals from large-chain restaurants. Meals were obtained from restaurants in San Francisco, CA; Boston, MA; and Little Rock, AR, between 2011 and 2014. Meal energy content determined by bomb calorimetry. Regional and cuisine differences were assessed using a mixed model with restaurant nested within region×cuisine as the random factor. Paired t tests were used to evaluate differences between non-chain and chain meals, human energy requirements, and food database values. Meals from non-chain restaurants contained 1,205±465 kcal/meal, amounts that were not significantly different from equivalent meals from large-chain restaurants (+5.1%; P=0.41). There was a significant effect of cuisine on non-chain meal energy, and three of the four most popular cuisines (American, Italian, and Chinese) had the highest mean energy (1,495 kcal/meal). Ninety-two percent of meals exceeded typical energy requirements for a single eating occasion. Non-chain restaurants lacking nutrition information serve amounts of energy that are typically far in excess of human energy requirements for single eating occasions, and are equivalent to amounts served by the large-chain restaurants that have previously been criticized for providing excess energy. Restaurants in general, rather than specific categories of restaurant, expose patrons to
Thermal behavior for a nanoscale two ferromagnetic phase system based on random anisotropy model

International Nuclear Information System (INIS)

Muraca, D.; Sanchez, F.H.; Pampillo, L.G.; Saccone, F.D.

2010-01-01

Advances in theory that explain the magnetic behavior as function of temperature for two phase nanocrystalline soft magnetic materials are presented. The theory developed is based on the well known random anisotropy model, which includes the crystalline exchange stiffness and anisotropy energies in both amorphous and crystalline phases. The phenomenological behavior of the coercivity was obtained in the temperature range between the amorphous phase Curie temperature and the crystalline phase one.
Dynamics of the Random Field Ising Model

Science.gov (United States)

Xu, Jian

The Random Field Ising Model (RFIM) is a general tool to study disordered systems. Crackling noise is generated when disordered systems are driven by external forces, spanning a broad range of sizes. Systems with different microscopic structures such as disordered mag- nets and Earth's crust have been studied under the RFIM. In this thesis, we investigated the domain dynamics and critical behavior in two dipole-coupled Ising ferromagnets Nd2Fe14B and LiHoxY 1-xF4. With Tc well above room temperature, Nd2Fe14B has shown reversible disorder when exposed to an external transverse field and crosses between two universality classes in the strong and weak disorder limits. Besides tunable disorder, LiHoxY1-xF4 has shown quantum tunneling effects arising from quantum fluctuations, providing another mechanism for domain reversal. Universality within and beyond power law dependence on avalanche size and energy were studied in LiHo0.65Y0.35 F4.
Prediction of interior noise due to random acoustic or turbulent boundary layer excitation using statistical energy analysis

Science.gov (United States)

Grosveld, Ferdinand W.

1990-01-01

The feasibility of predicting interior noise due to random acoustic or turbulent boundary layer excitation was investigated in experiments in which a statistical energy analysis model (VAPEPS) was used to analyze measurements of the acceleration response and sound transmission of flat aluminum, lucite, and graphite/epoxy plates exposed to random acoustic or turbulent boundary layer excitation. The noise reduction of the plate, when backed by a shallow cavity and excited by a turbulent boundary layer, was predicted using a simplified theory based on the assumption of adiabatic compression of the fluid in the cavity. The predicted plate acceleration response was used as input in the noise reduction prediction. Reasonable agreement was found between the predictions and the measured noise reduction in the frequency range 315-1000 Hz.
Fragmentation of polarized 23Na on 208Pb and the random-walk model

International Nuclear Information System (INIS)

Clarke, N.M.; Karban, O.; Blyth, C.O.; Choi, H.D.; Hall, S.J.; Roman, S.; Tungate, G.; Cole, A.J.; Davis, N.J.; Shotter, A.C.; Connell, K.A.

1993-01-01

Inclusive measurements are presented for the differential cross sections and tensor analyzing powers ( TT 20 and T 20 ) of ions produced by the fragmentation of a beam of polarized 23 Na incident on a 208 Pb target at an energy of 195.5 MeV (8.5 MeV/nucleon). The data are discussed in terms of a simple ''shape-effect'' model, and compared to the predictions of the nuclear random-walk model which has been extended to the calculation of aligned, deformed projectiles. This model reproduces the principal features of the differential cross sections and the trends as a function of mass loss, but gives poorer agreement for the analyzing powers
93-106, 2015 93 Multilevel random effect and marginal models

African Journals Online (AJOL)

Multilevel random effect and marginal models for longitudinal data ... and random effect models that take the correlation among measurements of the same subject ... comparing the level of redness, pain and irritability ... clinical trial evaluating the safety profile of a new .... likelihood-based methods to compare models and.
Ising model of a randomly triangulated random surface as a definition of fermionic string theory

International Nuclear Information System (INIS)

Bershadsky, M.A.; Migdal, A.A.

1986-01-01

Fermionic degrees of freedom are added to randomly triangulated planar random surfaces. It is shown that the Ising model on a fixed graph is equivalent to a certain Majorana fermion theory on the dual graph. (orig.)
Modeling and forecasting energy consumption for heterogeneous buildings using a physical–statistical approach

International Nuclear Information System (INIS)

Lü, Xiaoshu; Lu, Tao; Kibert, Charles J.; Viljanen, Martti

2015-01-01

Highlights: • This paper presents a new modeling method to forecast energy demands. • The model is based on physical–statistical approach to improving forecast accuracy. • A new method is proposed to address the heterogeneity challenge. • Comparison with measurements shows accurate forecasts of the model. • The first physical–statistical/heterogeneous building energy modeling approach is proposed and validated. - Abstract: Energy consumption forecasting is a critical and necessary input to planning and controlling energy usage in the building sector which accounts for 40% of the world’s energy use and the world’s greatest fraction of greenhouse gas emissions. However, due to the diversity and complexity of buildings as well as the random nature of weather conditions, energy consumption and loads are stochastic and difficult to predict. This paper presents a new methodology for energy demand forecasting that addresses the heterogeneity challenges in energy modeling of buildings. The new method is based on a physical–statistical approach designed to account for building heterogeneity to improve forecast accuracy. The physical model provides a theoretical input to characterize the underlying physical mechanism of energy flows. Then stochastic parameters are introduced into the physical model and the statistical time series model is formulated to reflect model uncertainties and individual heterogeneity in buildings. A new method of model generalization based on a convex hull technique is further derived to parameterize the individual-level model parameters for consistent model coefficients while maintaining satisfactory modeling accuracy for heterogeneous buildings. The proposed method and its validation are presented in detail for four different sports buildings with field measurements. The results show that the proposed methodology and model can provide a considerable improvement in forecasting accuracy
Random matrices and random difference equations

International Nuclear Information System (INIS)

Uppuluri, V.R.R.

1975-01-01

Mathematical models leading to products of random matrices and random difference equations are discussed. A one-compartment model with random behavior is introduced, and it is shown how the average concentration in the discrete time model converges to the exponential function. This is of relevance to understanding how radioactivity gets trapped in bone structure in blood--bone systems. The ideas are then generalized to two-compartment models and mammillary systems, where products of random matrices appear in a natural way. The appearance of products of random matrices in applications in demography and control theory is considered. Then random sequences motivated from the following problems are studied: constant pulsing and random decay models, random pulsing and constant decay models, and random pulsing and random decay models
LED Lighting System Reliability Modeling and Inference via Random Effects Gamma Process and Copula Function

Directory of Open Access Journals (Sweden)

Huibing Hao

2015-01-01

Full Text Available Light emitting diode (LED lamp has attracted increasing interest in the field of lighting systems due to its low energy and long lifetime. For different functions (i.e., illumination and color, it may have two or more performance characteristics. When the multiple performance characteristics are dependent, it creates a challenging problem to accurately analyze the system reliability. In this paper, we assume that the system has two performance characteristics, and each performance characteristic is governed by a random effects Gamma process where the random effects can capture the unit to unit differences. The dependency of performance characteristics is described by a Frank copula function. Via the copula function, the reliability assessment model is proposed. Considering the model is so complicated and analytically intractable, the Markov chain Monte Carlo (MCMC method is used to estimate the unknown parameters. A numerical example about actual LED lamps data is given to demonstrate the usefulness and validity of the proposed model and method.
Zero-inflated count models for longitudinal measurements with heterogeneous random effects.

Science.gov (United States)

Zhu, Huirong; Luo, Sheng; DeSantis, Stacia M

2017-08-01

Longitudinal zero-inflated count data arise frequently in substance use research when assessing the effects of behavioral and pharmacological interventions. Zero-inflated count models (e.g. zero-inflated Poisson or zero-inflated negative binomial) with random effects have been developed to analyze this type of data. In random effects zero-inflated count models, the random effects covariance matrix is typically assumed to be homogeneous (constant across subjects). However, in many situations this matrix may be heterogeneous (differ by measured covariates). In this paper, we extend zero-inflated count models to account for random effects heterogeneity by modeling their variance as a function of covariates. We show via simulation that ignoring intervention and covariate-specific heterogeneity can produce biased estimates of covariate and random effect estimates. Moreover, those biased estimates can be rectified by correctly modeling the random effects covariance structure. The methodological development is motivated by and applied to the Combined Pharmacotherapies and Behavioral Interventions for Alcohol Dependence (COMBINE) study, the largest clinical trial of alcohol dependence performed in United States with 1383 individuals.

The hard-core model on random graphs revisited

International Nuclear Information System (INIS)

Barbier, Jean; Krzakala, Florent; Zhang, Pan; Zdeborová, Lenka

2013-01-01

We revisit the classical hard-core model, also known as independent set and dual to vertex cover problem, where one puts particles with a first-neighbor hard-core repulsion on the vertices of a random graph. Although the case of random graphs with small and very large average degrees respectively are quite well understood, they yield qualitatively different results and our aim here is to reconciliate these two cases. We revisit results that can be obtained using the (heuristic) cavity method and show that it provides a closed-form conjecture for the exact density of the densest packing on random regular graphs with degree K ≥ 20, and that for K > 16 the nature of the phase transition is the same as for large K. This also shows that the hard-code model is the simplest mean-field lattice model for structural glasses and jamming
Application of Poisson random effect models for highway network screening.

Science.gov (United States)

Jiang, Ximiao; Abdel-Aty, Mohamed; Alamili, Samer

2014-02-01

In recent years, Bayesian random effect models that account for the temporal and spatial correlations of crash data became popular in traffic safety research. This study employs random effect Poisson Log-Normal models for crash risk hotspot identification. Both the temporal and spatial correlations of crash data were considered. Potential for Safety Improvement (PSI) were adopted as a measure of the crash risk. Using the fatal and injury crashes that occurred on urban 4-lane divided arterials from 2006 to 2009 in the Central Florida area, the random effect approaches were compared to the traditional Empirical Bayesian (EB) method and the conventional Bayesian Poisson Log-Normal model. A series of method examination tests were conducted to evaluate the performance of different approaches. These tests include the previously developed site consistence test, method consistence test, total rank difference test, and the modified total score test, as well as the newly proposed total safety performance measure difference test. Results show that the Bayesian Poisson model accounting for both temporal and spatial random effects (PTSRE) outperforms the model that with only temporal random effect, and both are superior to the conventional Poisson Log-Normal model (PLN) and the EB model in the fitting of crash data. Additionally, the method evaluation tests indicate that the PTSRE model is significantly superior to the PLN model and the EB model in consistently identifying hotspots during successive time periods. The results suggest that the PTSRE model is a superior alternative for road site crash risk hotspot identification. Copyright © 2013 Elsevier Ltd. All rights reserved.
Random matrix model for disordered conductors

Indian Academy of Sciences (India)

In the interpretation of transport properties of mesoscopic systems, the multichannel ... One defines the random matrix model with N eigenvalues 0. λТ ..... With heuristic arguments, using the ideas pertaining to Dyson Coulomb gas analogy,.
Analog model for quantum gravity effects: phonons in random fluids.

Science.gov (United States)

Krein, G; Menezes, G; Svaiter, N F

2010-09-24

We describe an analog model for quantum gravity effects in condensed matter physics. The situation discussed is that of phonons propagating in a fluid with a random velocity wave equation. We consider that there are random fluctuations in the reciprocal of the bulk modulus of the system and study free phonons in the presence of Gaussian colored noise with zero mean. We show that, in this model, after performing the random averages over the noise function a free conventional scalar quantum field theory describing free phonons becomes a self-interacting model.
Modeling random combustion of lycopodium particles and gas

Directory of Open Access Journals (Sweden)

M Bidabadi

2016-06-01

Full Text Available The random modeling combustion of lycopodium particles has been researched by many authors. In this paper, we extend this model and we also generate a different method by analyzing the effect of random distributed sources of combustible mixture. The flame structure is assumed to consist of a preheat-vaporization zone, a reaction zone and finally a post flame zone. We divide the preheat zone to different parts. We assumed that there is different distribution of particles in sections which are really random. Meanwhile, it is presumed that the fuel particles vaporize first to yield gaseous fuel. In other words, most of the fuel particles are vaporized at the end of the preheat zone. It is assumed that the Zel’dovich number is large; therefore, the reaction term in preheat zone is negligible. In this work, the effect of random distribution of particles in the preheat zone on combustion characteristics such as burning velocity, flame temperature for different particle radius is obtained.
Energy models for the FRG

International Nuclear Information System (INIS)

Voss, A.

1976-01-01

The development and application of energy models as helping factors in planning and decision making has gained more importance in all regions of energy economy and energy policy in recent times. This development not only covered models for the single branches and companies like, for example, for improving power plant systems, but also models showing the whole energy system. These models aim at analizing the possibilities of developing the energy supply with regard to aspects of the entire system, paying special attention to the integration of the energy system into economic and ecological side conditions. The following essay briefly explains the energy models developed for the Federal Republic of Germany after analizing the set of problems of energy and the demands on the energy planning methods arising from them. The energy model system developed by the programming team 'Systems research and technological development' of the nuclear research plant in Juelich is dealt with very intensively, explaining some model results as examples. Finally, the author gives his opinion on the problem of the integration and conversion of model studies in the process of decision making. (orig.) [de
Random versus Deterministic Descent in RNA Energy Landscape Analysis

Directory of Open Access Journals (Sweden)

Luke Day

2016-01-01

Full Text Available Identifying sets of metastable conformations is a major research topic in RNA energy landscape analysis, and recently several methods have been proposed for finding local minima in landscapes spawned by RNA secondary structures. An important and time-critical component of such methods is steepest, or gradient, descent in attraction basins of local minima. We analyse the speed-up achievable by randomised descent in attraction basins in the context of large sample sets where the size has an order of magnitude in the region of ~106. While the gain for each individual sample might be marginal, the overall run-time improvement can be significant. Moreover, for the two nongradient methods we analysed for partial energy landscapes induced by ten different RNA sequences, we obtained that the number of observed local minima is on average larger by 7.3% and 3.5%, respectively. The run-time improvement is approximately 16.6% and 6.8% on average over the ten partial energy landscapes. For the large sample size we selected for descent procedures, the coverage of local minima is very high up to energy values of the region where the samples were randomly selected from the partial energy landscapes; that is, the difference to the total set of local minima is mainly due to the upper area of the energy landscapes.
Accounting for unobserved management in renewable energy and growth

International Nuclear Information System (INIS)

Menegaki, Angeliki N.

2013-01-01

The paper employs a management random parameters frontier stochastic frontier and a simple frontier stochastic model to benchmark European countries according to their management efficiency in growth and renewable energy development. The results come from an empirical application of a panel with 31 European countries over a 14 year old period using a translog type stochastic frontier production function. In particular the paper focuses on results from a management random coefficients model and compares results with the conventional stochastic frontier model with inputs such as renewable energy, fossil fuel energy, employment and capital. The results suggest that the interaction of renewable energy with management affects growth in Europe and that the technical efficiency estimated by the management model is by 6.05% higher than the one produced by the simple stochastic frontier model. - Highlights: • Application of management random coefficients frontier model in growth-renewable energy nexus. • Comparison with the simple frontier efficiency model. • Technical efficiency is higher by 6.05% in the management model
A generalized model via random walks for information filtering

Energy Technology Data Exchange (ETDEWEB)

Ren, Zhuo-Ming, E-mail: zhuomingren@gmail.com [Department of Physics, University of Fribourg, Chemin du Musée 3, CH-1700, Fribourg (Switzerland); Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, ChongQing, 400714 (China); Kong, Yixiu [Department of Physics, University of Fribourg, Chemin du Musée 3, CH-1700, Fribourg (Switzerland); Shang, Ming-Sheng, E-mail: msshang@cigit.ac.cn [Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, ChongQing, 400714 (China); Zhang, Yi-Cheng [Department of Physics, University of Fribourg, Chemin du Musée 3, CH-1700, Fribourg (Switzerland)

2016-08-06

There could exist a simple general mechanism lurking beneath collaborative filtering and interdisciplinary physics approaches which have been successfully applied to online E-commerce platforms. Motivated by this idea, we propose a generalized model employing the dynamics of the random walk in the bipartite networks. Taking into account the degree information, the proposed generalized model could deduce the collaborative filtering, interdisciplinary physics approaches and even the enormous expansion of them. Furthermore, we analyze the generalized model with single and hybrid of degree information on the process of random walk in bipartite networks, and propose a possible strategy by using the hybrid degree information for different popular objects to toward promising precision of the recommendation. - Highlights: • We propose a generalized recommendation model employing the random walk dynamics. • The proposed model with single and hybrid of degree information is analyzed. • A strategy with the hybrid degree information improves precision of recommendation.
A generalized model via random walks for information filtering

International Nuclear Information System (INIS)

Ren, Zhuo-Ming; Kong, Yixiu; Shang, Ming-Sheng; Zhang, Yi-Cheng

2016-01-01

There could exist a simple general mechanism lurking beneath collaborative filtering and interdisciplinary physics approaches which have been successfully applied to online E-commerce platforms. Motivated by this idea, we propose a generalized model employing the dynamics of the random walk in the bipartite networks. Taking into account the degree information, the proposed generalized model could deduce the collaborative filtering, interdisciplinary physics approaches and even the enormous expansion of them. Furthermore, we analyze the generalized model with single and hybrid of degree information on the process of random walk in bipartite networks, and propose a possible strategy by using the hybrid degree information for different popular objects to toward promising precision of the recommendation. - Highlights: • We propose a generalized recommendation model employing the random walk dynamics. • The proposed model with single and hybrid of degree information is analyzed. • A strategy with the hybrid degree information improves precision of recommendation.
Active motions of Brownian particles in a generalized energy-depot model

International Nuclear Information System (INIS)

Zhang Yong; Koo Kim, Chul; Lee, Kong-Ju-Bock

2008-01-01

We present a generalized energy-depot model in which the rate of conversion of the internal energy into motion can be dependent on the position and velocity of a particle. When the conversion rate is a general function of the velocity, the active particle exhibits diverse patterns of motion, including a braking mechanism and a stepping motion. The phase trajectories of the motion are investigated in a systematic way. With a particular form of the conversion rate dependent on the position and velocity, the particle shows a spontaneous oscillation characterizing a negative stiffness. These types of active behaviors are compared with similar phenomena observed in biology, such as the stepping motion of molecular motors and amplification in the hearing mechanism. Hence, our model can provide a generic understanding of the active motion related to the energy conversion and also a new control mechanism for nano-robots. We also investigate the effect of noise, especially on the stepping motion, and observe random walk-like behavior as expected.
Evaluating energy efficiency policies with energy-economy models

NARCIS (Netherlands)

Mundaca, L.; Neij, L.; Worrell, E.; McNeil, M.

2010-01-01

The growing complexities of energy systems, environmental problems, and technology markets are driving and testing most energy-economy models to their limits. To further advance bottom-up models from a multidisciplinary energy efficiency policy evaluation perspective, we review and critically
Application of the resonating Hartree-Fock random phase approximation to the Lipkin model

International Nuclear Information System (INIS)

Nishiyama, S.; Ishida, K.; Ido, M.

1996-01-01

We have applied the resonating Hartree-Fock (Res-HF) approximation to the exactly solvable Lipkin model by utilizing a newly developed orbital-optimization algorithm. The Res-HF wave function was superposed by two Slater determinants (S-dets) which give two corresponding local energy minima of monopole ''deformations''. The self-consistent Res-HF calculation gives an excellent ground-state correlation energy. There exist excitations due to small vibrational fluctuations of the orbitals and mixing coefficients around their stationary values. They are described by a new approximation called the resonating Hartree-Fock random phase approximation (Res-HF RPA). Matrices of the second-order variation of the Res-HF energy have the same structures as those of the Res-HF RPA's matrices. The quadratic steepest descent of the Res-HF energy in the orbital optimization is considered to include certainly both effects of RPA-type fluctuations up to higher orders and their mode-mode couplings. It is a very important and interesting task to apply the Res-HF RPA to the Lipkin model with the use of the stationary values and to prove the above argument. It turns out that the Res-HF RPA works far better than the usual HF RPA and the renormalized one. We also show some important features of the Res-HF RPA. (orig.)
A random walk evolution model of wireless sensor networks and virus spreading

International Nuclear Information System (INIS)

Wang Ya-Qi; Yang Xiao-Yuan

2013-01-01

In this paper, considering both cluster heads and sensor nodes, we propose a novel evolving a network model based on a random walk to study the fault tolerance decrease of wireless sensor networks (WSNs) due to node failure, and discuss the spreading dynamic behavior of viruses in the evolution model. A theoretical analysis shows that the WSN generated by such an evolution model not only has a strong fault tolerance, but also can dynamically balance the energy loss of the entire network. It is also found that although the increase of the density of cluster heads in the network reduces the network efficiency, it can effectively inhibit the spread of viruses. In addition, the heterogeneity of the network improves the network efficiency and enhances the virus prevalence. We confirm all the theoretical results with sufficient numerical simulations. (general)
Effects of random noise in a dynamical model of love

Energy Technology Data Exchange (ETDEWEB)

Xu Yong, E-mail: hsux3@nwpu.edu.cn [Department of Applied Mathematics, Northwestern Polytechnical University, Xi' an 710072 (China); Gu Rencai; Zhang Huiqing [Department of Applied Mathematics, Northwestern Polytechnical University, Xi' an 710072 (China)

2011-07-15

Highlights: > We model the complexity and unpredictability of psychology as Gaussian white noise. > The stochastic system of love is considered including bifurcation and chaos. > We show that noise can both suppress and induce chaos in dynamical models of love. - Abstract: This paper aims to investigate the stochastic model of love and the effects of random noise. We first revisit the deterministic model of love and some basic properties are presented such as: symmetry, dissipation, fixed points (equilibrium), chaotic behaviors and chaotic attractors. Then we construct a stochastic love-triangle model with parametric random excitation due to the complexity and unpredictability of the psychological system, where the randomness is modeled as the standard Gaussian noise. Stochastic dynamics under different three cases of 'Romeo's romantic style', are examined and two kinds of bifurcations versus the noise intensity parameter are observed by the criteria of changes of top Lyapunov exponent and shape of stationary probability density function (PDF) respectively. The phase portraits and time history are carried out to verify the proposed results, and the good agreement can be found. And also the dual roles of the random noise, namely suppressing and inducing chaos are revealed.
Effects of random noise in a dynamical model of love

International Nuclear Information System (INIS)

Xu Yong; Gu Rencai; Zhang Huiqing

2011-01-01

Highlights: → We model the complexity and unpredictability of psychology as Gaussian white noise. → The stochastic system of love is considered including bifurcation and chaos. → We show that noise can both suppress and induce chaos in dynamical models of love. - Abstract: This paper aims to investigate the stochastic model of love and the effects of random noise. We first revisit the deterministic model of love and some basic properties are presented such as: symmetry, dissipation, fixed points (equilibrium), chaotic behaviors and chaotic attractors. Then we construct a stochastic love-triangle model with parametric random excitation due to the complexity and unpredictability of the psychological system, where the randomness is modeled as the standard Gaussian noise. Stochastic dynamics under different three cases of 'Romeo's romantic style', are examined and two kinds of bifurcations versus the noise intensity parameter are observed by the criteria of changes of top Lyapunov exponent and shape of stationary probability density function (PDF) respectively. The phase portraits and time history are carried out to verify the proposed results, and the good agreement can be found. And also the dual roles of the random noise, namely suppressing and inducing chaos are revealed.
Maternal Dietary Counseling Reduces Consumption of Energy-Dense Foods among Infants: A Randomized Controlled Trial

Science.gov (United States)

Vitolo, Marcia Regina; Bortolini, Gisele Ane; Campagnolo, Paula Dal Bo; Hoffman, Daniel J.

2012-01-01

Objective: To evaluate the impact of a dietary counseling in reducing the intake of energy-dense foods by infants. Design: A randomized controlled trial. Setting and Participants: Sao Leopoldo, Brazil. Mothers and infants of a low-income-group population were randomized into intervention (n = 163) and received dietary counseling during 10 home…
Using Random Forest Models to Predict Organizational Violence

Science.gov (United States)

Levine, Burton; Bobashev, Georgly

2012-01-01

We present a methodology to access the proclivity of an organization to commit violence against nongovernment personnel. We fitted a Random Forest model using the Minority at Risk Organizational Behavior (MAROS) dataset. The MAROS data is longitudinal; so, individual observations are not independent. We propose a modification to the standard Random Forest methodology to account for the violation of the independence assumption. We present the results of the model fit, an example of predicting violence for an organization; and finally, we present a summary of the forest in a "meta-tree,"
Alternative model of random surfaces

International Nuclear Information System (INIS)

Ambartzumian, R.V.; Sukiasian, G.S.; Savvidy, G.K.; Savvidy, K.G.

1992-01-01

We analyse models of triangulated random surfaces and demand that geometrically nearby configurations of these surfaces must have close actions. The inclusion of this principle drives us to suggest a new action, which is a modified Steiner functional. General arguments, based on the Minkowski inequality, shows that the maximal distribution to the partition function comes from surfaces close to the sphere. (orig.)
Energy models: methods and trends

Energy Technology Data Exchange (ETDEWEB)

Reuter, A [Division of Energy Management and Planning, Verbundplan, Klagenfurt (Austria); Kuehner, R [IER Institute for Energy Economics and the Rational Use of Energy, University of Stuttgart, Stuttgart (Germany); Wohlgemuth, N [Department of Economy, University of Klagenfurt, Klagenfurt (Austria)

1997-12-31

Energy environmental and economical systems do not allow for experimentation since this would be dangerous, too expensive or even impossible. Instead, mathematical models are applied for energy planning. Experimenting is replaced by varying the structure and some parameters of `energy models`, computing the values of depending parameters, comparing variations, and interpreting their outcomings. Energy models are as old as computers. In this article the major new developments in energy modeling will be pointed out. We distinguish between 3 reasons of new developments: progress in computer technology, methodological progress and novel tasks of energy system analysis and planning. 2 figs., 19 refs.

Energy models: methods and trends

International Nuclear Information System (INIS)

Reuter, A.; Kuehner, R.; Wohlgemuth, N.

1996-01-01

Energy environmental and economical systems do not allow for experimentation since this would be dangerous, too expensive or even impossible. Instead, mathematical models are applied for energy planning. Experimenting is replaced by varying the structure and some parameters of 'energy models', computing the values of depending parameters, comparing variations, and interpreting their outcomings. Energy models are as old as computers. In this article the major new developments in energy modeling will be pointed out. We distinguish between 3 reasons of new developments: progress in computer technology, methodological progress and novel tasks of energy system analysis and planning
Premium Pricing of Liability Insurance Using Random Sum Model

Directory of Open Access Journals (Sweden)

Mujiati Dwi Kartikasari

2017-03-01

Full Text Available Premium pricing is one of important activities in insurance. Nonlife insurance premium is calculated from expected value of historical data claims. The historical data claims are collected so that it forms a sum of independent random number which is called random sum. In premium pricing using random sum, claim frequency distribution and claim severity distribution are combined. The combination of these distributions is called compound distribution. By using liability claim insurance data, we analyze premium pricing using random sum model based on compound distribution
Random matrix approach to plasmon resonances in the random impedance network model of disordered nanocomposites

Science.gov (United States)

Olekhno, N. A.; Beltukov, Y. M.

2018-05-01

Random impedance networks are widely used as a model to describe plasmon resonances in disordered metal-dielectric and other two-component nanocomposites. In the present work, the spectral properties of resonances in random networks are studied within the framework of the random matrix theory. We have shown that the appropriate ensemble of random matrices for the considered problem is the Jacobi ensemble (the MANOVA ensemble). The obtained analytical expressions for the density of states in such resonant networks show a good agreement with the results of numerical simulations in a wide range of metal filling fractions 0
Modelling energy systems for developing countries

International Nuclear Information System (INIS)

Urban, F.; Benders, R.M.J.; Moll, H.C.

2007-01-01

Developing countries' energy use is rapidly increasing, which affects global climate change and global and regional energy settings. Energy models are helpful for exploring the future of developing and industrialised countries. However, energy systems of developing countries differ from those of industrialised countries, which has consequences for energy modelling. New requirements need to be met by present-day energy models to adequately explore the future of developing countries' energy systems. This paper aims to assess if the main characteristics of developing countries are adequately incorporated in present-day energy models. We first discuss these main characteristics, focusing particularly on developing Asia, and then present a model comparison of 12 selected energy models to test their suitability for developing countries. We conclude that many models are biased towards industrialised countries, neglecting main characteristics of developing countries, e.g. the informal economy, supply shortages, poor performance of the power sector, structural economic change, electrification, traditional bio-fuels, urban-rural divide. To more adequately address the energy systems of developing countries, energy models have to be adjusted and new models have to be built. We therefore indicate how to improve energy models for increasing their suitability for developing countries and give advice on modelling techniques and data requirements
Time-varying output performances of piezoelectric vibration energy harvesting under nonstationary random vibrations

Science.gov (United States)

Yoon, Heonjun; Kim, Miso; Park, Choon-Su; Youn, Byeng D.

2018-01-01

Piezoelectric vibration energy harvesting (PVEH) has received much attention as a potential solution that could ultimately realize self-powered wireless sensor networks. Since most ambient vibrations in nature are inherently random and nonstationary, the output performances of PVEH devices also randomly change with time. However, little attention has been paid to investigating the randomly time-varying electroelastic behaviors of PVEH systems both analytically and experimentally. The objective of this study is thus to make a step forward towards a deep understanding of the time-varying performances of PVEH devices under nonstationary random vibrations. Two typical cases of nonstationary random vibration signals are considered: (1) randomly-varying amplitude (amplitude modulation; AM) and (2) randomly-varying amplitude with randomly-varying instantaneous frequency (amplitude and frequency modulation; AM-FM). In both cases, this study pursues well-balanced correlations of analytical predictions and experimental observations to deduce the relationships between the time-varying output performances of the PVEH device and two primary input parameters, such as a central frequency and an external electrical resistance. We introduce three correlation metrics to quantitatively compare analytical prediction and experimental observation, including the normalized root mean square error, the correlation coefficient, and the weighted integrated factor. Analytical predictions are in an excellent agreement with experimental observations both mechanically and electrically. This study provides insightful guidelines for designing PVEH devices to reliably generate electric power under nonstationary random vibrations.
Development of random geometry capability in RMC code for stochastic media analysis

International Nuclear Information System (INIS)

Liu, Shichang; She, Ding; Liang, Jin-gang; Wang, Kan

2015-01-01

Highlights: • Monte Carlo method plays an important role in modeling of particle transport in random media. • Three stochastic geometry modeling methods have been developed in RMC. • The stochastic effects of the randomly dispersed fuel particles are analyzed. • Investigation of accuracy and efficiency of three methods has been carried out. • All the methods are effective, and explicit modeling is regarded as the best choice. - Abstract: Simulation of particle transport in random media poses a challenge for traditional deterministic transport methods, due to the significant effects of spatial and energy self-shielding. Monte Carlo method plays an important role in accurate simulation of random media, owing to its flexible geometry modeling and the use of continuous-energy nuclear cross sections. Three stochastic geometry modeling methods including Random Lattice Method, Chord Length Sampling and explicit modeling approach with mesh acceleration technique, have been developed in RMC to simulate the particle transport in the dispersed fuels. The verifications of the accuracy and the investigations of the calculation efficiency have been carried out. The stochastic effects of the randomly dispersed fuel particles are also analyzed. The results show that all three stochastic geometry modeling methods can account for the effects of the random dispersion of fuel particles, and the explicit modeling method can be regarded as the best choice
Energy exchange in thermal energy atom-surface scattering: impulsive models

International Nuclear Information System (INIS)

Barker, J.A.; Auerbach, D.J.

1979-01-01

Energy exchange in thermal energy atom surface collisions is studied using impulsive ('hard cube' and 'hard sphere') models. Both models reproduce the observed nearly linear relation between outgoing and incoming energies. In addition, the hard-sphere model accounts for the widths of the outcoming energy distributions. (Auth.)
Brazilian energy model

Science.gov (United States)

1981-05-01

A summary of the energy situation in Brazil is presented. Energy consumption rates, reserves of primary energy, and the basic needs and strategies for meeting energy self sufficiency are discussed. Conserving energy, increasing petroleum production, and utilizing other domestic energy products and petroleum by-products are discussed. Specific programs are described for the development and use of alcohol fuels, wood and charcoal, coal, schist, solar and geothermal energy, power from the sea, fresh biomass, special batteries, hydrogen, vegetable oil, and electric energy from water power, nuclear, and coal. Details of the energy model for 1985 are given. Attention is also given to the energy demands and the structure of global energy from 1975 to 1985.
Stochastic linear dynamical programming in order to apply it in energy modelling

Energy Technology Data Exchange (ETDEWEB)

El Hachem, S

1995-11-01

This thesis contributes to the development of new algorithms for the computation of stochastic dynamic problem and its mini-maxi variant for the case of imperfect knowledge on random data. The proposed algorithms are scenarios aggregation type. It also contributes to integrate these algorithms in a decision support approach and to discuss the stochastic modeling of two energy problems: the refining and the portfolio gas contracts. (author). 112 refs., 5 tabs.
Recent developments in exponential random graph (p*) models for social networks

NARCIS (Netherlands)

Robins, Garry; Snijders, Tom; Wang, Peng; Handcock, Mark; Pattison, Philippa

This article reviews new specifications for exponential random graph models proposed by Snijders et al. [Snijders, T.A.B., Pattison, P., Robins, G.L., Handcock, M., 2006. New specifications for exponential random graph models. Sociological Methodology] and demonstrates their improvement over
Evolution of the concentration PDF in random environments modeled by global random walk

Science.gov (United States)

Suciu, Nicolae; Vamos, Calin; Attinger, Sabine; Knabner, Peter

2013-04-01

The evolution of the probability density function (PDF) of concentrations of chemical species transported in random environments is often modeled by ensembles of notional particles. The particles move in physical space along stochastic-Lagrangian trajectories governed by Ito equations, with drift coefficients given by the local values of the resolved velocity field and diffusion coefficients obtained by stochastic or space-filtering upscaling procedures. A general model for the sub-grid mixing also can be formulated as a system of Ito equations solving for trajectories in the composition space. The PDF is finally estimated by the number of particles in space-concentration control volumes. In spite of their efficiency, Lagrangian approaches suffer from two severe limitations. Since the particle trajectories are constructed sequentially, the demanded computing resources increase linearly with the number of particles. Moreover, the need to gather particles at the center of computational cells to perform the mixing step and to estimate statistical parameters, as well as the interpolation of various terms to particle positions, inevitably produce numerical diffusion in either particle-mesh or grid-free particle methods. To overcome these limitations, we introduce a global random walk method to solve the system of Ito equations in physical and composition spaces, which models the evolution of the random concentration's PDF. The algorithm consists of a superposition on a regular lattice of many weak Euler schemes for the set of Ito equations. Since all particles starting from a site of the space-concentration lattice are spread in a single numerical procedure, one obtains PDF estimates at the lattice sites at computational costs comparable with those for solving the system of Ito equations associated to a single particle. The new method avoids the limitations concerning the number of particles in Lagrangian approaches, completely removes the numerical diffusion, and
National Energy Outlook Modelling System

Energy Technology Data Exchange (ETDEWEB)

Volkers, C.M. [ECN Policy Studies, Petten (Netherlands)

2013-12-15

For over 20 years, the Energy research Centre of the Netherlands (ECN) has been developing the National Energy Outlook Modelling System (NEOMS) for Energy projections and policy evaluations. NEOMS enables 12 energy models of ECN to exchange data and produce consistent and detailed results.
Disorder Identification in Hysteresis Data: Recognition Analysis of the Random-Bond-Random-Field Ising Model

International Nuclear Information System (INIS)

Ovchinnikov, O. S.; Jesse, S.; Kalinin, S. V.; Bintacchit, P.; Trolier-McKinstry, S.

2009-01-01

An approach for the direct identification of disorder type and strength in physical systems based on recognition analysis of hysteresis loop shape is developed. A large number of theoretical examples uniformly distributed in the parameter space of the system is generated and is decorrelated using principal component analysis (PCA). The PCA components are used to train a feed-forward neural network using the model parameters as targets. The trained network is used to analyze hysteresis loops for the investigated system. The approach is demonstrated using a 2D random-bond-random-field Ising model, and polarization switching in polycrystalline ferroelectric capacitors.
A random walk model for evaluating clinical trials involving serial observations.

Science.gov (United States)

Hopper, J L; Young, G P

1988-05-01

For clinical trials where the variable of interest is ordered and categorical (for example, disease severity, symptom scale), and where measurements are taken at intervals, it might be possible to achieve a greater discrimination between the efficacy of treatments by modelling each patient's progress as a stochastic process. The random walk is a simple, easily interpreted model that can be fitted by maximum likelihood using a maximization routine with inference based on standard likelihood theory. In general the model can allow for randomly censored data, incorporates measured prognostic factors, and inference is conditional on the (possibly non-random) allocation of patients. Tests of fit and of model assumptions are proposed, and application to two therapeutic trials of gastroenterological disorders are presented. The model gave measures of the rate of, and variability in, improvement for patients under different treatments. A small simulation study suggested that the model is more powerful than considering the difference between initial and final scores, even when applied to data generated by a mechanism other than the random walk model assumed in the analysis. It thus provides a useful additional statistical method for evaluating clinical trials.
Droplet localization in the random XXZ model and its manifestations

Science.gov (United States)

Elgart, A.; Klein, A.; Stolz, G.

2018-01-01

We examine many-body localization properties for the eigenstates that lie in the droplet sector of the random-field spin- \\frac 1 2 XXZ chain. These states satisfy a basic single cluster localization property (SCLP), derived in Elgart et al (2018 J. Funct. Anal. (in press)). This leads to many consequences, including dynamical exponential clustering, non-spreading of information under the time evolution, and a zero velocity Lieb-Robinson bound. Since SCLP is only applicable to the droplet sector, our definitions and proofs do not rely on knowledge of the spectral and dynamical characteristics of the model outside this regime. Rather, to allow for a possible mobility transition, we adapt the notion of restricting the Hamiltonian to an energy window from the single particle setting to the many body context.
Modeling energy-economy interactions using integrated models

International Nuclear Information System (INIS)

Uyterlinde, M.A.

1994-06-01

Integrated models are defined as economic energy models that consist of several submodels, either coupled by an interface module, or embedded in one large model. These models can be used for energy policy analysis. Using integrated models yields the following benefits. They provide a framework in which energy-economy interactions can be better analyzed than in stand-alone models. Integrated models can represent both energy sector technological details, as well as the behaviour of the market and the role of prices. Furthermore, the combination of modeling methodologies in one model can compensate weaknesses of one approach with strengths of another. These advantages motivated this survey of the class of integrated models. The purpose of this literature survey therefore was to collect and to present information on integrated models. To carry out this task, several goals were identified. The first goal was to give an overview of what is reported on these models in general. The second one was to find and describe examples of such models. Other goals were to find out what kinds of models were used as component models, and to examine the linkage methodology. Solution methods and their convergence properties were also a subject of interest. The report has the following structure. In chapter 2, a 'conceptual framework' is given. In chapter 3 a number of integrated models is described. In a table, a complete overview is presented of all described models. Finally, in chapter 4, the report is summarized, and conclusions are drawn regarding the advantages and drawbacks of integrated models. 8 figs., 29 refs
Random-growth urban model with geographical fitness

Science.gov (United States)

Kii, Masanobu; Akimoto, Keigo; Doi, Kenji

2012-12-01

This paper formulates a random-growth urban model with a notion of geographical fitness. Using techniques of complex-network theory, we study our system as a type of preferential-attachment model with fitness, and we analyze its macro behavior to clarify the properties of the city-size distributions it predicts. First, restricting the geographical fitness to take positive values and using a continuum approach, we show that the city-size distributions predicted by our model asymptotically approach Pareto distributions with coefficients greater than unity. Then, allowing the geographical fitness to take negative values, we perform local coefficient analysis to show that the predicted city-size distributions can deviate from Pareto distributions, as is often observed in actual city-size distributions. As a result, the model we propose can generate a generic class of city-size distributions, including but not limited to Pareto distributions. For applications to city-population projections, our simple model requires randomness only when new cities are created, not during their subsequent growth. This property leads to smooth trajectories of city population growth, in contrast to other models using Gibrat’s law. In addition, a discrete form of our dynamical equations can be used to estimate past city populations based on present-day data; this fact allows quantitative assessment of the performance of our model. Further study is needed to determine appropriate formulas for the geographical fitness.
Smooth random change point models.

Science.gov (United States)

van den Hout, Ardo; Muniz-Terrera, Graciela; Matthews, Fiona E

2011-03-15

Change point models are used to describe processes over time that show a change in direction. An example of such a process is cognitive ability, where a decline a few years before death is sometimes observed. A broken-stick model consists of two linear parts and a breakpoint where the two lines intersect. Alternatively, models can be formulated that imply a smooth change between the two linear parts. Change point models can be extended by adding random effects to account for variability between subjects. A new smooth change point model is introduced and examples are presented that show how change point models can be estimated using functions in R for mixed-effects models. The Bayesian inference using WinBUGS is also discussed. The methods are illustrated using data from a population-based longitudinal study of ageing, the Cambridge City over 75 Cohort Study. The aim is to identify how many years before death individuals experience a change in the rate of decline of their cognitive ability. Copyright © 2010 John Wiley & Sons, Ltd.
Performance Evaluation of User Selection Protocols in Random Networks with Energy Harvesting and Hardware Impairments

Directory of Open Access Journals (Sweden)

Tan Nhat Nguyen

2016-01-01

Full Text Available In this paper, we evaluate performances of various user selection protocols under impact of hardware impairments. In the considered protocols, a Base Station (BS selects one of available Users (US to serve, while the remaining USs harvest the energy from the Radio Frequency (RF transmitted by the BS. We assume that all of the US randomly appear around the BS. In the Random Selection Protocol (RAN, the BS randomly selects a US to transmit the data. In the second proposed protocol, named Minimum Distance Protocol (MIND, the US that is nearest to the BS will be chosen. In the Optimal Selection Protocol (OPT, the US providing the highest channel gain between itself and the BS will be served. For performance evaluation, we derive exact and asymptotic closed-form expressions of average Outage Probability (OP over Rayleigh fading channels. We also consider average harvested energy per a US. Finally, Monte-Carlo simulations are then performed to verify the theoretical results.
CONSISTENCY UNDER SAMPLING OF EXPONENTIAL RANDOM GRAPH MODELS.

Science.gov (United States)

Shalizi, Cosma Rohilla; Rinaldo, Alessandro

2013-04-01

The growing availability of network data and of scientific interest in distributed systems has led to the rapid development of statistical models of network structure. Typically, however, these are models for the entire network, while the data consists only of a sampled sub-network. Parameters for the whole network, which is what is of interest, are estimated by applying the model to the sub-network. This assumes that the model is consistent under sampling , or, in terms of the theory of stochastic processes, that it defines a projective family. Focusing on the popular class of exponential random graph models (ERGMs), we show that this apparently trivial condition is in fact violated by many popular and scientifically appealing models, and that satisfying it drastically limits ERGM's expressive power. These results are actually special cases of more general results about exponential families of dependent random variables, which we also prove. Using such results, we offer easily checked conditions for the consistency of maximum likelihood estimation in ERGMs, and discuss some possible constructive responses.

Simulating intrafraction prostate motion with a random walk model.

Science.gov (United States)

Pommer, Tobias; Oh, Jung Hun; Munck Af Rosenschöld, Per; Deasy, Joseph O

2017-01-01

Prostate motion during radiation therapy (ie, intrafraction motion) can cause unwanted loss of radiation dose to the prostate and increased dose to the surrounding organs at risk. A compact but general statistical description of this motion could be useful for simulation of radiation therapy delivery or margin calculations. We investigated whether prostate motion could be modeled with a random walk model. Prostate motion recorded during 548 radiation therapy fractions in 17 patients was analyzed and used for input in a random walk prostate motion model. The recorded motion was categorized on the basis of whether any transient excursions (ie, rapid prostate motion in the anterior and superior direction followed by a return) occurred in the trace and transient motion. This was separately modeled as a large step in the anterior/superior direction followed by a returning large step. Random walk simulations were conducted with and without added artificial transient motion using either motion data from all observed traces or only traces without transient excursions as model input, respectively. A general estimate of motion was derived with reasonable agreement between simulated and observed traces, especially during the first 5 minutes of the excursion-free simulations. Simulated and observed diffusion coefficients agreed within 0.03, 0.2 and 0.3 mm 2 /min in the left/right, superior/inferior, and anterior/posterior directions, respectively. A rapid increase in variance at the start of observed traces was difficult to reproduce and seemed to represent the patient's need to adjust before treatment. This could be estimated somewhat using artificial transient motion. Random walk modeling is feasible and recreated the characteristics of the observed prostate motion. Introducing artificial transient motion did not improve the overall agreement, although the first 30 seconds of the traces were better reproduced. The model provides a simple estimate of prostate motion during
Energy modelling in sensor networks

Science.gov (United States)

Schmidt, D.; Krämer, M.; Kuhn, T.; Wehn, N.

2007-06-01

Wireless sensor networks are one of the key enabling technologies for the vision of ambient intelligence. Energy resources for sensor nodes are very scarce. A key challenge is the design of energy efficient communication protocols. Models of the energy consumption are needed to accurately simulate the efficiency of a protocol or application design, and can also be used for automatic energy optimizations in a model driven design process. We propose a novel methodology to create models for sensor nodes based on few simple measurements. In a case study the methodology was used to create models for MICAz nodes. The models were integrated in a simulation environment as well as in a SDL runtime framework of a model driven design process. Measurements on a test application that was created automatically from an SDL specification showed an 80% reduction in energy consumption compared to an implementation without power saving strategies.
Stochastic Model Predictive Fault Tolerant Control Based on Conditional Value at Risk for Wind Energy Conversion System

Directory of Open Access Journals (Sweden)

Yun-Tao Shi

2018-01-01

Full Text Available Wind energy has been drawing considerable attention in recent years. However, due to the random nature of wind and high failure rate of wind energy conversion systems (WECSs, how to implement fault-tolerant WECS control is becoming a significant issue. This paper addresses the fault-tolerant control problem of a WECS with a probable actuator fault. A new stochastic model predictive control (SMPC fault-tolerant controller with the Conditional Value at Risk (CVaR objective function is proposed in this paper. First, the Markov jump linear model is used to describe the WECS dynamics, which are affected by many stochastic factors, like the wind. The Markov jump linear model can precisely model the random WECS properties. Second, the scenario-based SMPC is used as the controller to address the control problem of the WECS. With this controller, all the possible realizations of the disturbance in prediction horizon are enumerated by scenario trees so that an uncertain SMPC problem can be transformed into a deterministic model predictive control (MPC problem. Finally, the CVaR object function is adopted to improve the fault-tolerant control performance of the SMPC controller. CVaR can provide a balance between the performance and random failure risks of the system. The Min-Max performance index is introduced to compare the fault-tolerant control performance with the proposed controller. The comparison results show that the proposed method has better fault-tolerant control performance.
Money creation process in a random redistribution model

Science.gov (United States)

Chen, Siyan; Wang, Yougui; Li, Keqiang; Wu, Jinshan

2014-01-01

In this paper, the dynamical process of money creation in a random exchange model with debt is investigated. The money creation kinetics are analyzed by both the money-transfer matrix method and the diffusion method. From both approaches, we attain the same conclusion: the source of money creation in the case of random exchange is the agents with neither money nor debt. These analytical results are demonstrated by computer simulations.
UK energy policy ambition and UK energy modelling-fit for purpose?

International Nuclear Information System (INIS)

Strachan, Neil

2011-01-01

Aiming to lead amongst other G20 countries, the UK government has classified the twin energy policy priorities of decarbonisation and security of supply as a 'centennial challenge'. This viewpoint discusses the UK's capacity for energy modelling and scenario building as a critical underpinning of iterative decision making to meet these policy ambitions. From a nadir, over the last decade UK modelling expertise has been steadily built up. However extreme challenges remain in the level and consistency of funding of core model teams - critical to ensure a full scope of energy model types and hence insights, and in developing new state-of-the-art models to address evolving uncertainties. Meeting this challenge will facilitate a broad scope of types and geographical scale of UK's analytical tools to responsively deliver the evidence base for a range of public and private sector decision makers, and ensure that the UK contributes to global efforts to advance the field of energy-economic modelling. - Research highlights: → Energy modelling capacity is a critical underpinning for iterative energy policy making. → Full scope of energy models and analytical approaches is required. → Extreme challenges remain in consistent and sustainable funding of energy modelling teams. → National governments that lead in global energy policy also need to invest in modelling capacity.
The multi-factor energy input–output model

International Nuclear Information System (INIS)

Guevara, Zeus; Domingos, Tiago

2017-01-01

Energy input–output analysis (EIO analysis) is a noteworthy tool for the analysis of the role of energy in the economy. However, it has relied on models that provide a limited description of energy flows in the economic system and do not allow an adequate analysis of energy efficiency. This paper introduces a novel energy input–output model, the multi-factor energy input–output model (MF-EIO model), which is obtained from a partitioning of a hybrid-unit input–output system of the economy. This model improves on current models by describing the energy flows according to the processes of energy conversion and the levels of energy use in the economy. It characterizes the vector of total energy output as a function of seven factors: two energy efficiency indicators; two characteristics of end-use energy consumption; and three economic features of the rest of the economy. Moreover, it is consistent with the standard model for EIO analysis, i.e., the hybrid-unit model. This paper also introduces an approximate version of the MF-EIO model, which is equivalent to the former under equal energy prices for industries and final consumers, but requires less data processing. The latter is composed by two linked models: a model of the energy sector in physical units, and a model of the rest of the economy in monetary units. In conclusion, the proposed modelling framework improves EIO analysis and extends EIO applications to the accounting for energy efficiency of the economy. - Highlights: • A novel energy input–output model is introduced. • It allows a more adequate analysis of energy flows than current models. • It describes energy flows according to processes of energy conversion and use. • It can be used for other environmental applications (material use and emissions). • An approximate version of the model is introduced, simpler and less data intensive.
Stochastic equilibria of an asset pricing model with heterogeneous beliefs and random dividends

NARCIS (Netherlands)

Zhu, M.; Wang, D.; Guo, M.

2011-01-01

We investigate dynamical properties of a heterogeneous agent model with random dividends and further study the relationship between dynamical properties of the random model and those of the corresponding deterministic skeleton, which is obtained by setting the random dividends as their constant mean
Energy centre microgrid model

Energy Technology Data Exchange (ETDEWEB)

Pasonen, R.

2011-09-15

A simulation model of Energy centre microgrid made with PSCAD simulation software version 4.2.1 has been built in SGEM Smart Grids and Energy Markets (SGEM) work package 6.6. Microgrid is an autonomous electric power system which can operate separate from common distribution system. The idea of energy centre microgrid concept was considered in Master of Science thesis 'Community Microgrid - A Building block of Finnish Smart Grid'. The name of energy centre microgrid comes from a fact that production and storage units are concentrated into a single location, an energy centre. This centre feeds the loads which can be households or industrial loads. Power direction flow on the demand side remains same compared to the current distribution system and allows to the use of standard fuse protection in the system. The model consists of photovoltaic solar array, battery unit, variable frequency boost converter, inverter, isolation transformer and demand side (load) model. The model is capable to automatically switch to islanded mode when there is a fault in outside grid and back to parallel operation mode when fault is removed. The modelled system responses well to load changes and total harmonic distortion related to 50Hz base frequency is kept under 1.5% while operating and feeding passive load. (orig.)
Beyond the Random Phase Approximation for the Electron Correlation Energy: The Importance of Single Excitations

OpenAIRE

Ren, Xinguo; Rinke, Patrick; Tkatchenko, Alexandre; Scheffler, Matthias

2010-01-01

The random-phase approximation (RPA) for the electron correlation energy, combined with the exact-exchange (EX) energy, represents the state-of-the-art exchange-correlation functional within density-functional theory. However, the standard RPA practice-evaluating both the EX and the RPA correlation energies using Kohn-Sham (KS) orbitals from local or semilocal exchange-correlation functionals-leads to a systematic underbinding of molecules and solids. Here we demonstrate that this behavior ca...
A simple dynamic energy capacity model

International Nuclear Information System (INIS)

Gander, James P.

2012-01-01

I develop a simple dynamic model showing how total energy capacity is allocated to two different uses and how these uses and their corresponding energy flows are related and behave through time. The control variable of the model determines the allocation. All the variables of the model are in terms of a composite energy equivalent measured in BTU's. A key focus is on the shadow price of energy capacity and its behavior through time. Another key focus is on the behavior of the control variable that determines the allocation of overall energy capacity. The matching or linking of the model's variables to real world U.S. energy data is undertaken. In spite of some limitations of the data, the model and its behavior fit the data fairly well. Some energy policy implications are discussed. - Highlights: ► The model shows how energy capacity is allocated to current output production versus added energy capacity production. ► Two variables in the allocation are the shadow price of capacity and the control variable that determines the allocation. ► The model was linked to U.S. historical energy data and fit the data quite well. ► In particular, the policy control variable was cyclical and consistent with the model. ► Policy implications relevant to the allocation of energy capacity are discussed briefly.
Design of Energy Aware Adder Circuits Considering Random Intra-Die Process Variations

Directory of Open Access Journals (Sweden)

Marco Lanuzza

2011-04-01

Full Text Available Energy consumption is one of the main barriers to current high-performance designs. Moreover, the increased variability experienced in advanced process technologies implies further timing yield concerns and therefore intensifies this obstacle. Thus, proper techniques to achieve robust designs are a critical requirement for integrated circuit success. In this paper, the influence of intra-die random process variations is analyzed considering the particular case of the design of energy aware adder circuits. Five well known adder circuits were designed exploiting an industrial 45 nm static complementary metal-oxide semiconductor (CMOS standard cell library. The designed adders were comparatively evaluated under different energy constraints. As a main result, the performed analysis demonstrates that, for a given energy budget, simpler circuits (which are conventionally identified as low-energy slow architectures operating at higher power supply voltages can achieve a timing yield significantly better than more complex faster adders when used in low-power design with supply voltages lower than nominal.
Marginal and Random Intercepts Models for Longitudinal Binary Data with Examples from Criminology

Science.gov (United States)

Long, Jeffrey D.; Loeber, Rolf; Farrington, David P.

2009-01-01

Two models for the analysis of longitudinal binary data are discussed: the marginal model and the random intercepts model. In contrast to the linear mixed model (LMM), the two models for binary data are not subsumed under a single hierarchical model. The marginal model provides group-level information whereas the random intercepts model provides…
Exenatide has a Pronounced Effect on Energy Intake but not Energy Expenditure in Non-Diabetic Subjects with Obesity: A Randomized, Double-blind, Placebo-Controlled Trial.

Science.gov (United States)

Basolo, Alessio; Burkholder, Joshua; Osgood, Kristy; Graham, Alexis; Bundrick, Sarah; Frankl, Joseph; Piaggi, Paolo; Thearle, Marie S; Krakoff, Jonathan

2018-03-26

Exenatide is a glucagon-like peptide 1 (GLP-1) mimetic which induces weight loss predominantly, it is presumed, via decreased food intake. However, circulating GLP-1 is also a determinant of energy expenditure. We sought to quantify the effect of exenatide on energy expenditure (EE) and energy intake. In this single-center, randomized double-blind placebo controlled trial, we randomized 80 healthy, non-diabetic volunteers with obesity (46 women, age: 34.4±8.7 y, body fat by DXA: 44.2±7.8%) to subcutaneous exenatide 10 μg twice daily or placebo. Subjects were admitted to our clinical research unit for measurement of 24h-EE in a whole-room indirect calorimeter and ad libitum food intake using an automated vending machine paradigm before and after randomization. Furthermore, energy expenditure and ad libitum food intake measures were repeated at 24-week after readmission for 7-day inpatient stay. Body weight was obtained weekly for up to 5 weeks and was recorded at each monthly follow up visit up to 24 weeks. Prior to randomization, participants over ate during the 3-day vending machine period in the whole study group (114.6±35.2 %), expressed as percentage of weight maintaining energy needs (WMEN) with those who were eventually randomized to exenatide overeating more (121.6±37.7 %) compared to placebo group (107.6±31.5 %). In the exenatide group, ad libitum absolute energy intake decreased by 1016.1±724.5 kcal/day (95% CI: -1250.9 to -781.2) versus a 245.1±710.5 kcal/day (95% CI: -475.4 to -14.7) decrease in placebo (Δ= -624.8 Kcal/day, p energy intake between exenatide group and placebo group and the treatment group decreased 24-h EE more compared to placebo (β = -160.6 Kcal/day, 95% CI: -307.6 to 13.6, p = 0.03) compared to their pre-randomization measurement. However, this reduction was not present after adjustment for changes in FM and FFM (β = -87 kcal/day, p = 0.14). No difference was observed in body weight (Δ = -1.72 kg, 95% CI: -5.77 to 2.30, p
Quantum random oracle model for quantum digital signature

Science.gov (United States)

Shang, Tao; Lei, Qi; Liu, Jianwei

2016-10-01

The goal of this work is to provide a general security analysis tool, namely, the quantum random oracle (QRO), for facilitating the security analysis of quantum cryptographic protocols, especially protocols based on quantum one-way function. QRO is used to model quantum one-way function and different queries to QRO are used to model quantum attacks. A typical application of quantum one-way function is the quantum digital signature, whose progress has been hampered by the slow pace of the experimental realization. Alternatively, we use the QRO model to analyze the provable security of a quantum digital signature scheme and elaborate the analysis procedure. The QRO model differs from the prior quantum-accessible random oracle in that it can output quantum states as public keys and give responses to different queries. This tool can be a test bed for the cryptanalysis of more quantum cryptographic protocols based on the quantum one-way function.
Random-Effects Models for Meta-Analytic Structural Equation Modeling: Review, Issues, and Illustrations

Science.gov (United States)

Cheung, Mike W.-L.; Cheung, Shu Fai

2016-01-01

Meta-analytic structural equation modeling (MASEM) combines the techniques of meta-analysis and structural equation modeling for the purpose of synthesizing correlation or covariance matrices and fitting structural equation models on the pooled correlation or covariance matrix. Both fixed-effects and random-effects models can be defined in MASEM.…
Random isotropic one-dimensional XY-model

Science.gov (United States)

Gonçalves, L. L.; Vieira, A. P.

1998-01-01

The 1D isotropic s = ½XY-model ( N sites), with random exchange interaction in a transverse random field is considered. The random variables satisfy bimodal quenched distributions. The solution is obtained by using the Jordan-Wigner fermionization and a canonical transformation, reducing the problem to diagonalizing an N × N matrix, corresponding to a system of N noninteracting fermions. The calculations are performed numerically for N = 1000, and the field-induced magnetization at T = 0 is obtained by averaging the results for the different samples. For the dilute case, in the uniform field limit, the magnetization exhibits various discontinuities, which are the consequence of the existence of disconnected finite clusters distributed along the chain. Also in this limit, for finite exchange constants J A and J B, as the probability of J A varies from one to zero, the saturation field is seen to vary from Γ A to Γ B, where Γ A(Γ B) is the value of the saturation field for the pure case with exchange constant equal to J A(J B) .
Analysis of Random-Loading HTR-PROTEUS Cores with Continuous Energy Monte Carlo Code Based on A Statistical Geometry Model

International Nuclear Information System (INIS)

Murata, Isao; Miyamaru, Hiroyuki

2008-01-01

Spherical elements have remarkable features in various applications in the nuclear engineering field. In 1990's, by the project of HTR-PROTEUS at PSI various pebble bed reactor experiments were conducted including cores with a lot of spherical fuel elements loaded randomly. In this study, criticality experiments of the random-loading HTR-PROTEUS cores were analyzed by MCNP-BALL, which could deal with a random arrangement of spherical fuel elements exactly with a statistical geometry model. As a result of analysis, the calculated effective multiplication factors were in fairly good agreement with the measurements within about 0.5%Δk/k. In comparison with other numerical analysis, our effective multiplication factors were between the experimental values and the VSOP calculations. To investigate the discrepancy of the effective multiplication factors between the experiments and calculations, sensitivity analyses were performed. As the result, the sensitivity of impurity boron concentration was fairly large. The reason of the present slight overestimation was not made clear at present. However, the presently existing difference was thought to be related to the impurity boron concentration, not to the modelling of the reactor and the used nuclear data. From the present study, it was confirmed that MCNP-BALL would have an advantage to conventional transport codes by comparing with their numerical results and the experimental values. As for the criticality experiment of PROTEUS, we would conclude that the two cores of Core 4.2 and 4.3 could be regarded as an equivalent experiment of a reference critical core, which was packed in the packing fraction of RLP. (authors)
Analysis of Random-Loading HTR-PROTEUS Cores with Continuous Energy Monte Carlo Code Based on A Statistical Geometry Model

Energy Technology Data Exchange (ETDEWEB)

Murata, Isao; Miyamaru, Hiroyuki [Division of Electrical, Electronic and Information Engineering, Osaka University, Yamada-oka 2-1, Suita, Osaka, 565-0871 (Japan)

2008-07-01

Spherical elements have remarkable features in various applications in the nuclear engineering field. In 1990's, by the project of HTR-PROTEUS at PSI various pebble bed reactor experiments were conducted including cores with a lot of spherical fuel elements loaded randomly. In this study, criticality experiments of the random-loading HTR-PROTEUS cores were analyzed by MCNP-BALL, which could deal with a random arrangement of spherical fuel elements exactly with a statistical geometry model. As a result of analysis, the calculated effective multiplication factors were in fairly good agreement with the measurements within about 0.5%DELTAk/k. In comparison with other numerical analysis, our effective multiplication factors were between the experimental values and the VSOP calculations. To investigate the discrepancy of the effective multiplication factors between the experiments and calculations, sensitivity analyses were performed. As the result, the sensitivity of impurity boron concentration was fairly large. The reason of the present slight overestimation was not made clear at present. However, the presently existing difference was thought to be related to the impurity boron concentration, not to the modelling of the reactor and the used nuclear data. From the present study, it was confirmed that MCNP-BALL would have an advantage to conventional transport codes by comparing with their numerical results and the experimental values. As for the criticality experiment of PROTEUS, we would conclude that the two cores of Core 4.2 and 4.3 could be regarded as an equivalent experiment of a reference critical core, which was packed in the packing fraction of RLP. (authors)
A simple model for correcting the zero point energy problem in classical trajectory simulations of polyatomic molecules

International Nuclear Information System (INIS)

Miller, W.H.; Hase, W.L.; Darling, C.L.

1989-01-01

A simple model is proposed for correcting problems with zero point energy in classical trajectory simulations of dynamical processes in polyatomic molecules. The ''problems'' referred to are that classical mechanics allows the vibrational energy in a mode to decrease below its quantum zero point value, and since the total energy is conserved classically this can allow too much energy to pool in other modes. The proposed model introduces hard sphere-like terms in action--angle variables that prevent the vibrational energy in any mode from falling below its zero point value. The algorithm which results is quite simple in terms of the cartesian normal modes of the system: if the energy in a mode k, say, decreases below its zero point value at time t, then at this time the momentum P k for that mode has its sign changed, and the trajectory continues. This is essentially a time reversal for mode k (only exclamation point), and it conserves the total energy of the system. One can think of the model as supplying impulsive ''quantum kicks'' to a mode whose energy attempts to fall below its zero point value, a kind of ''Planck demon'' analogous to a Brownian-like random force. The model is illustrated by application to a model of CH overtone relaxation
Studies in astronomical time series analysis: Modeling random processes in the time domain

Science.gov (United States)

Scargle, J. D.

1979-01-01

Random process models phased in the time domain are used to analyze astrophysical time series data produced by random processes. A moving average (MA) model represents the data as a sequence of pulses occurring randomly in time, with random amplitudes. An autoregressive (AR) model represents the correlations in the process in terms of a linear function of past values. The best AR model is determined from sampled data and transformed to an MA for interpretation. The randomness of the pulse amplitudes is maximized by a FORTRAN algorithm which is relatively stable numerically. Results of test cases are given to study the effects of adding noise and of different distributions for the pulse amplitudes. A preliminary analysis of the optical light curve of the quasar 3C 273 is given.

Energy modelling and capacity building

International Nuclear Information System (INIS)

2005-01-01

The Planning and Economic Studies Section of the IAEA's Department of Nuclear Energy is focusing on building analytical capacity in MS for energy-environmental-economic assessments and for the elaboration of sustainable energy strategies. It offers a variety of analytical models specifically designed for use in developing countries for (i) evaluating alternative energy strategies; (ii) assessing environmental, economic and financial impacts of energy options; (iii) assessing infrastructure needs; (iv) evaluating regional development possibilities and energy trade; (v) assessing the role of nuclear power in addressing priority issues (climate change, energy security, etc.). These models can be used for analysing energy or electricity systems, and to assess possible implications of different energy, environmental or financial policies that affect the energy sector and energy systems. The models vary in complexity and data requirements, and so can be adapted to the available data, statistics and analytical needs of different countries. These models are constantly updated to reflect changes in the real world and in the concerns that drive energy system choices. They can provide thoughtfully informed choices for policy makers over a broader range of circumstances and interests. For example, they can readily reflect the workings of competitive energy and electricity markets, and cover such topics as external costs. The IAEA further offers training in the use of these models and -just as important- in the interpretation and critical evaluation of results. Training of national teams to develop national competence over the full spectrum of models, is a high priority. The IAEA maintains a broad spectrum of databanks relevant to energy, economic and environmental analysis in MS, and make these data available to analysts in MS for use in their own analytical work. The Reference Technology Data Base (RTDB) and the Reference Data Series (RDS-1) are the major vehicles by which we
New Energy Utility Business Models

International Nuclear Information System (INIS)

Potocnik, V.

2016-01-01

Recently a lot of big changes happened in the power sector: energy efficiency and renewable energy sources are quickly progressing, distributed or decentralised generation of electricity is expanding, climate change requires reduction of greenhouse gas emissions and price volatility and incertitude of fossil fuel supply is common. Those changes have led to obsolescence of vertically integrated business models which have dominated in energy utility organisations for a hundred years and new business models are being introduced. Those models take into account current changes in the power sector and enable a wider application of energy efficiency and renewable energy sources, especially for consumers, with the decentralisation of electricity generation and complying with the requirements of climate and environment preservation. New business models also solve the questions of financial compensations for utilities because of the reduction of centralised energy generation while contributing to local development and employment.(author).
A generalized model via random walks for information filtering

Science.gov (United States)

Ren, Zhuo-Ming; Kong, Yixiu; Shang, Ming-Sheng; Zhang, Yi-Cheng

2016-08-01

There could exist a simple general mechanism lurking beneath collaborative filtering and interdisciplinary physics approaches which have been successfully applied to online E-commerce platforms. Motivated by this idea, we propose a generalized model employing the dynamics of the random walk in the bipartite networks. Taking into account the degree information, the proposed generalized model could deduce the collaborative filtering, interdisciplinary physics approaches and even the enormous expansion of them. Furthermore, we analyze the generalized model with single and hybrid of degree information on the process of random walk in bipartite networks, and propose a possible strategy by using the hybrid degree information for different popular objects to toward promising precision of the recommendation.
Genetic Analysis of Daily Maximum Milking Speed by a Random Walk Model in Dairy Cows

DEFF Research Database (Denmark)

Karacaören, Burak; Janss, Luc; Kadarmideen, Haja

Data were obtained from dairy cows stationed at research farm ETH Zurich for maximum milking speed. The main aims of this paper are a) to evaluate if the Wood curve is suitable to model mean lactation curve b) to predict longitudinal breeding values by random regression and random walk models of ...... filter applications: random walk model could give online prediction of breeding values. Hence without waiting for whole lactation records, genetic evaluation could be made when the daily or monthly data is available......Data were obtained from dairy cows stationed at research farm ETH Zurich for maximum milking speed. The main aims of this paper are a) to evaluate if the Wood curve is suitable to model mean lactation curve b) to predict longitudinal breeding values by random regression and random walk models...... of maximum milking speed. Wood curve did not provide a good fit to the data set. Quadratic random regressions gave better predictions compared with the random walk model. However random walk model does not need to be evaluated for different orders of regression coefficients. In addition with the Kalman...
Total energy calculations from self-energy models

International Nuclear Information System (INIS)

Sanchez-Friera, P.

2001-06-01

Density-functional theory is a powerful method to calculate total energies of large systems of interacting electrons. The usefulness of this method, however, is limited by the fact that an approximation is required for the exchange-correlation energy. Currently used approximations (LDA and GGA) are not sufficiently accurate in many physical problems, as for instance the study of chemical reactions. It has been shown that exchange-correlation effects can be accurately described via the self-energy operator in the context of many-body perturbation theory. This is, however, a computationally very demanding approach. In this thesis a new scheme for calculating total energies is proposed, which combines elements from many-body perturbation theory and density-functional theory. The exchange-correlation energy functional is built from a simplified model of the self-energy, that nevertheless retains the main features of the exact operator. The model is built in such way that the computational effort is not significantly increased with respect to that required in a typical density-functional theory calculation. (author)
Random effect selection in generalised linear models

DEFF Research Database (Denmark)

Denwood, Matt; Houe, Hans; Forkman, Björn

We analysed abattoir recordings of meat inspection codes with possible relevance to onfarm animal welfare in cattle. Random effects logistic regression models were used to describe individual-level data obtained from 461,406 cattle slaughtered in Denmark. Our results demonstrate that the largest...
Towards low carbon business park energy systems: Classification of techno-economic energy models

International Nuclear Information System (INIS)

Timmerman, Jonas; Vandevelde, Lieven; Van Eetvelde, Greet

2014-01-01

To mitigate climate destabilisation, human-induced greenhouse gas emissions urgently need to be curbed. A major share of these emissions originates from the industry and energy sectors. Hence, a low carbon shift in industrial and business park energy systems is called for. Low carbon business parks minimise energy-related carbon dioxide emissions by maximal exploitation of local renewable energy production, enhanced energy efficiency, and inter-firm heat exchange, combined in a collective energy system. The holistic approach of techno-economic energy models facilitates the design of such systems, while yielding an optimal trade-off between energetic, economic and environmental performances. However, no models custom-tailored for industrial park energy systems are detected in literature. In this paper, existing energy model classifications are scanned for adequate model characteristics and accordingly, a confined number of models are selected and described. Subsequently, a practical typology is proposed, existing of energy system evolution, optimisation, simulation, accounting and integration models, and key model features are compared. Finally, important features for a business park energy model are identified. - Highlights: • A holistic perspective on (low carbon) business park energy systems is introduced. • A new categorisation of techno-economic energy models is proposed. • Model characteristics are described per model category. • Essential model features for business park energy system modelling are identified. • A strategy towards a techno-economic energy model for business parks is proposed
Annealed central limit theorems for the ising model on random graphs

NARCIS (Netherlands)

Giardinà, C.; Giberti, C.; van der Hofstad, R.W.; Prioriello, M.L.

2016-01-01

The aim of this paper is to prove central limit theorems with respect to the annealed measure for the magnetization rescaled by √N of Ising models on random graphs. More precisely, we consider the general rank-1 inhomogeneous random graph (or generalized random graph), the 2-regular configuration
Single-cluster dynamics for the random-cluster model

NARCIS (Netherlands)

Deng, Y.; Qian, X.; Blöte, H.W.J.

2009-01-01

We formulate a single-cluster Monte Carlo algorithm for the simulation of the random-cluster model. This algorithm is a generalization of the Wolff single-cluster method for the q-state Potts model to noninteger values q>1. Its results for static quantities are in a satisfactory agreement with those
A dynamic random effects multinomial logit model of household car ownership

DEFF Research Database (Denmark)

Bue Bjørner, Thomas; Leth-Petersen, Søren

2007-01-01

Using a large household panel we estimate demand for car ownership by means of a dynamic multinomial model with correlated random effects. Results suggest that the persistence in car ownership observed in the data should be attributed to both true state dependence and to unobserved heterogeneity...... (random effects). It also appears that random effects related to single and multiple car ownership are correlated, suggesting that the IIA assumption employed in simple multinomial models of car ownership is invalid. Relatively small elasticities with respect to income and car costs are estimated...
A single-level random-effects cross-lagged panel model for longitudinal mediation analysis.

Science.gov (United States)

Wu, Wei; Carroll, Ian A; Chen, Po-Yi

2017-12-06

Cross-lagged panel models (CLPMs) are widely used to test mediation with longitudinal panel data. One major limitation of the CLPMs is that the model effects are assumed to be fixed across individuals. This assumption is likely to be violated (i.e., the model effects are random across individuals) in practice. When this happens, the CLPMs can potentially yield biased parameter estimates and misleading statistical inferences. This article proposes a model named a random-effects cross-lagged panel model (RE-CLPM) to account for random effects in CLPMs. Simulation studies show that the RE-CLPM outperforms the CLPM in recovering the mean indirect and direct effects in a longitudinal mediation analysis when random effects exist in the population. The performance of the RE-CLPM is robust to a certain degree, even when the random effects are not normally distributed. In addition, the RE-CLPM does not produce harmful results when the model effects are in fact fixed in the population. Implications of the simulation studies and potential directions for future research are discussed.
The reverse effects of random perturbation on discrete systems for single and multiple population models

International Nuclear Information System (INIS)

Kang, Li; Tang, Sanyi

2016-01-01

Highlights: • The discrete single species and multiple species models with random perturbation are proposed. • The complex dynamics and interesting bifurcation behavior have been investigated. • The reverse effects of random perturbation on discrete systems have been discussed and revealed. • The main results can be applied for pest control and resources management. - Abstract: The natural species are likely to present several interesting and complex phenomena under random perturbations, which have been confirmed by simple mathematical models. The important questions are: how the random perturbations influence the dynamics of the discrete population models with multiple steady states or multiple species interactions? and is there any different effects for single species and multiple species models with random perturbation? To address those interesting questions, we have proposed the discrete single species model with two stable equilibria and the host-parasitoid model with Holling type functional response functions to address how the random perturbation affects the dynamics. The main results indicate that the random perturbation does not change the number of blurred orbits of the single species model with two stable steady states compared with results for the classical Ricker model with same random perturbation, but it can strength the stability. However, extensive numerical investigations depict that the random perturbation does not influence the complexities of the host-parasitoid models compared with the results for the models without perturbation, while it does increase the period of periodic orbits doubly. All those confirm that the random perturbation has a reverse effect on the dynamics of the discrete single and multiple population models, which could be applied in reality including pest control and resources management.
Energy-economic policy modeling

Science.gov (United States)

Sanstad, Alan H.

2018-01-01

Computational models based on economic principles and methods are powerful tools for understanding and analyzing problems in energy and the environment and for designing policies to address them. Among their other features, some current models of this type incorporate information on sustainable energy technologies and can be used to examine their potential role in addressing the problem of global climate change. The underlying principles and the characteristics of the models are summarized, and examples of this class of model and their applications are presented. Modeling epistemology and related issues are discussed, as well as critiques of the models. The paper concludes with remarks on the evolution of the models and possibilities for their continued development.
Effective dark energy equation of state in interacting dark energy models

International Nuclear Information System (INIS)

Avelino, P.P.; Silva, H.M.R. da

2012-01-01

In models where dark matter and dark energy interact non-minimally, the total amount of matter in a fixed comoving volume may vary from the time of recombination to the present time due to energy transfer between the two components. This implies that, in interacting dark energy models, the fractional matter density estimated using the cosmic microwave background assuming no interaction between dark matter and dark energy will in general be shifted with respect to its true value. This may result in an incorrect determination of the equation of state of dark energy if the interaction between dark matter and dark energy is not properly accounted for, even if the evolution of the Hubble parameter as a function of redshift is known with arbitrary precision. In this Letter we find an exact expression, as well as a simple analytical approximation, for the evolution of the effective equation of state of dark energy, assuming that the energy transfer rate between dark matter and dark energy is described by a simple two-parameter model. We also provide analytical examples where non-phantom interacting dark energy models mimic the background evolution and primary cosmic microwave background anisotropies of phantom dark energy models.
Effective dark energy equation of state in interacting dark energy models

Energy Technology Data Exchange (ETDEWEB)

Avelino, P.P., E-mail: ppavelin@fc.up.pt [Centro de Astrofisica da Universidade do Porto, Rua das Estrelas, 4150-762 Porto (Portugal); Departamento de Fisica e Astronomia da Faculdade de Ciencias da Universidade do Porto, Rua do Campo Alegre 687, 4169-007 Porto (Portugal); Silva, H.M.R. da, E-mail: hilberto.silva@gmail.com [Departamento de Fisica e Astronomia da Faculdade de Ciencias da Universidade do Porto, Rua do Campo Alegre 687, 4169-007 Porto (Portugal)

2012-07-24

In models where dark matter and dark energy interact non-minimally, the total amount of matter in a fixed comoving volume may vary from the time of recombination to the present time due to energy transfer between the two components. This implies that, in interacting dark energy models, the fractional matter density estimated using the cosmic microwave background assuming no interaction between dark matter and dark energy will in general be shifted with respect to its true value. This may result in an incorrect determination of the equation of state of dark energy if the interaction between dark matter and dark energy is not properly accounted for, even if the evolution of the Hubble parameter as a function of redshift is known with arbitrary precision. In this Letter we find an exact expression, as well as a simple analytical approximation, for the evolution of the effective equation of state of dark energy, assuming that the energy transfer rate between dark matter and dark energy is described by a simple two-parameter model. We also provide analytical examples where non-phantom interacting dark energy models mimic the background evolution and primary cosmic microwave background anisotropies of phantom dark energy models.
Business model innovation for sustainable energy: German utilities and renewable energy

International Nuclear Information System (INIS)

Richter, Mario

2013-01-01

The electric power sector stands at the beginning of a fundamental transformation process towards a more sustainable production based on renewable energies. Consequently, electric utilities as incumbent actors face a massive challenge to find new ways of creating, delivering, and capturing value from renewable energy technologies. This study investigates utilities' business models for renewable energies by analyzing two generic business models based on a series of in-depth interviews with German utility managers. It is found that utilities have developed viable business models for large-scale utility-side renewable energy generation. At the same time, utilities lack adequate business models to commercialize small-scale customer-side renewable energy technologies. By combining the business model concept with innovation and organization theory practical recommendations for utility mangers and policy makers are derived. - Highlights: • The energy transition creates a fundamental business model challenge for utilities. • German utilities succeed in large-scale and fail in small-scale renewable generation. • Experiences from other industries are available to inform utility managers. • Business model innovation capabilities will be crucial to master the energy transition
Modeling of chromosome intermingling by partially overlapping uniform random polygons.

Science.gov (United States)

Blackstone, T; Scharein, R; Borgo, B; Varela, R; Diao, Y; Arsuaga, J

2011-03-01

During the early phase of the cell cycle the eukaryotic genome is organized into chromosome territories. The geometry of the interface between any two chromosomes remains a matter of debate and may have important functional consequences. The Interchromosomal Network model (introduced by Branco and Pombo) proposes that territories intermingle along their periphery. In order to partially quantify this concept we here investigate the probability that two chromosomes form an unsplittable link. We use the uniform random polygon as a crude model for chromosome territories and we model the interchromosomal network as the common spatial region of two overlapping uniform random polygons. This simple model allows us to derive some rigorous mathematical results as well as to perform computer simulations easily. We find that the probability that one uniform random polygon of length n that partially overlaps a fixed polygon is bounded below by 1 − O(1/√n). We use numerical simulations to estimate the dependence of the linking probability of two uniform random polygons (of lengths n and m, respectively) on the amount of overlapping. The degree of overlapping is parametrized by a parameter [Formula: see text] such that [Formula: see text] indicates no overlapping and [Formula: see text] indicates total overlapping. We propose that this dependence relation may be modeled as f (ε, m, n) = [Formula: see text]. Numerical evidence shows that this model works well when [Formula: see text] is relatively large (ε ≥ 0.5). We then use these results to model the data published by Branco and Pombo and observe that for the amount of overlapping observed experimentally the URPs have a non-zero probability of forming an unsplittable link.
Economic modelling of energy services: Rectifying misspecified energy demand functions

International Nuclear Information System (INIS)

Hunt, Lester C.; Ryan, David L.

2015-01-01

Although it is well known that energy demand is derived, since energy is required not for its own sake but for the energy services it produces – such as heating, lighting, and motive power – energy demand models, both theoretical and empirical, often fail to take account of this feature. In this paper, we highlight the misspecification that results from ignoring this aspect, and its empirical implications – biased estimates of price elasticities and other measures – and provide a relatively simple and empirically practicable way to rectify it, which has a strong theoretical grounding. To do so, we develop an explicit model of consumer behaviour in which utility derives from consumption of energy services rather than from the energy sources that are used to produce them. As we discuss, this approach opens up the possibility of examining many aspects of energy demand in a theoretically sound way that have not previously been considered on a widespread basis, although some existing empirical work could be interpreted as being consistent with this type of specification. While this formulation yields demand equations for energy services rather than for energy or particular energy sources, these are shown to be readily converted, without added complexity, into the standard type of energy demand equation(s) that is (are) typically estimated. The additional terms that the resulting energy demand equations include, compared to those that are typically estimated, highlight the misspecification that is implicit when typical energy demand equations are estimated. A simple solution for dealing with an apparent drawback of this formulation for empirical purposes, namely that information is required on typically unobserved energy efficiency, indicates how energy efficiency can be captured in the model, such as by including exogenous trends and/or including its possible dependence on past energy prices. The approach is illustrated using an empirical example that involves
Some Limits Using Random Slope Models to Measure Academic Growth

Directory of Open Access Journals (Sweden)

Daniel B. Wright

2017-11-01

Full Text Available Academic growth is often estimated using a random slope multilevel model with several years of data. However, if there are few time points, the estimates can be unreliable. While using random slope multilevel models can lower the variance of the estimates, these procedures can produce more highly erroneous estimates—zero and negative correlations with the true underlying growth—than using ordinary least squares estimates calculated for each student or school individually. An example is provided where schools with increasing graduation rates are estimated to have negative growth and vice versa. The estimation is worse when the underlying data are skewed. It is recommended that there are at least six time points for estimating growth if using a random slope model. A combination of methods can be used to avoid some of the aberrant results if it is not possible to have six or more time points.
World energy projection system: Model documentation

Science.gov (United States)

1992-06-01

The World Energy Project System (WEPS) is an accounting framework that incorporates projects from independently documented models and assumptions about the future energy intensity of economic activity (ratios of total energy consumption divided by gross domestic product) and about the rate of incremental energy requirements met by hydropower, geothermal, coal, and natural gas to produce projections of world energy consumption published annually by the Energy Information Administration (EIA) in the International Energy Outlook (IEO). Two independently documented models presented in Figure 1, the Oil Market Simulation (OMS) model and the World Integrated Nuclear Evaluation System (WINES), provide projections of oil and nuclear power consumption published in the IEO. Output from a third independently documented model, and the International Coal Trade Model (ICTM), is not published in the IEO but is used in WEPS as a supply check on projections of world coal consumption produced by WEPS and published in the IEO. A WEPS model of natural gas production documented in this report provides the same type of implicit supply check on the WEPS projections of world natural gas consumption published in the IEO. Two additional models are included in Figure 1, the OPEC Capacity model and the Non-OPEC Oil Production model. These WEPS models provide inputs to the OMS model and are documented in this report.

World energy projection system: Model documentation

International Nuclear Information System (INIS)

1992-06-01

The World Energy Project System (WEPS) is an accounting framework that incorporates projects from independently documented models and assumptions about the future energy intensity of economic activity (ratios of total energy consumption divided by gross domestic product) and about the rate of incremental energy requirements met by hydropower, geothermal, coal, and natural gas to produce projections of world energy consumption published annually by the Energy Information Administration (EIA) in the International Energy Outlook (IEO) (Figure 1). Two independently documented models presented in Figure 1, the Oil Market Simulation (OMS) model and the World Integrated Nuclear Evaluation System (WINES) provide projections of oil and nuclear power consumption published in the IEO. Output from a third independently documented model, and the International Coal Trade Model (ICTM), is not published in the IEO but is used in WEPS as a supply check on projections of world coal consumption produced by WEPS and published in the IEO. A WEPS model of natural gas production documented in this report provides the same type of implicit supply check on the WEPS projections of world natural gas consumption published in the IEO. Two additional models are included in Figure 1, the OPEC Capacity model and the Non-OPEC Oil Production model. These WEPS models provide inputs to the OMS model and are documented in this report
Improved age-diffusion model for low-energy electron transport in solids. II. Application to secondary emission from aluminum

International Nuclear Information System (INIS)

Dubus, A.; Devooght, J.; Dehaes, J.C.

1987-01-01

The ''improved age-diffusion'' model for secondary-electron transport is applied to aluminum. Electron cross sections for inelastic collisions with the free-electron gas using the Lindhard dielectric function and for elastic collisions with the randomly distributed ionic cores are used in the calculations. The most important characteristics of backward secondary-electron emission induced by low-energy electrons on polycrystalline Al targets are calculated and compared to experimental results and to Monte Carlo calculations. The model appears to predict the electronic yield, the energy spectra, and the spatial dependence of secondary emission with reasonable accuracy
Utility based maintenance analysis using a Random Sign censoring model

International Nuclear Information System (INIS)

Andres Christen, J.; Ruggeri, Fabrizio; Villa, Enrique

2011-01-01

Industrial systems subject to failures are usually inspected when there are evident signs of an imminent failure. Maintenance is therefore performed at a random time, somehow dependent on the failure mechanism. A competing risk model, namely a Random Sign model, is considered to relate failure and maintenance times. We propose a novel Bayesian analysis of the model and apply it to actual data from a water pump in an oil refinery. The design of an optimal maintenance policy is then discussed under a formal decision theoretic approach, analyzing the goodness of the current maintenance policy and making decisions about the optimal maintenance time.
Global energy modeling - A biophysical approach

Energy Technology Data Exchange (ETDEWEB)

Dale, Michael

2010-09-15

This paper contrasts the standard economic approach to energy modelling with energy models using a biophysical approach. Neither of these approaches includes changing energy-returns-on-investment (EROI) due to declining resource quality or the capital intensive nature of renewable energy sources. Both of these factors will become increasingly important in the future. An extension to the biophysical approach is outlined which encompasses a dynamic EROI function that explicitly incorporates technological learning. The model is used to explore several scenarios of long-term future energy supply especially concerning the global transition to renewable energy sources in the quest for a sustainable energy system.
Models for the energy performance of low-energy houses

DEFF Research Database (Denmark)

Andersen, Philip Hvidthøft Delff

of buildings, the first topic analyzed is the variation of presence of occupants. As buildings get more energy-effcient, internal loads and user-behavior increasingly influence the energy consumption. Most simulation tools use deterministic occupancy profiles to simulate internal loads. However, such occupancy......The aim of this thesis is data-driven modeling of heat dynamics of buildings. Traditionally, thermal modeling of buildings is done using simulation tools which take information about the construction, weather data, occupancy etc. as inputs and generate deterministic energy profiles of the buildings....... The approach to modeling occupants’ presence provides a flexible method where no assumptions in the application. The rest of the thesis deals with statistical modeling of heat dynamics of buildings. First, discrete-time models are applied. Discrete-time models are computationally relatively simple and provide...
Application of random regression models to the genetic evaluation ...

African Journals Online (AJOL)

The model included fixed regression on AM (range from 30 to 138 mo) and the effect of herd-measurement date concatenation. Random parts of the model were RRM coefficients for additive and permanent environmental effects, while residual effects were modelled to account for heterogeneity of variance by AY. Estimates ...
Method of model reduction and multifidelity models for solute transport in random layered porous media

Energy Technology Data Exchange (ETDEWEB)

Xu, Zhijie; Tartakovsky, Alexandre M.

2017-09-01

This work presents a hierarchical model for solute transport in bounded layered porous media with random permeability. The model generalizes the Taylor-Aris dispersion theory to stochastic transport in random layered porous media with a known velocity covariance function. In the hierarchical model, we represent (random) concentration in terms of its cross-sectional average and a variation function. We derive a one-dimensional stochastic advection-dispersion-type equation for the average concentration and a stochastic Poisson equation for the variation function, as well as expressions for the effective velocity and dispersion coefficient. We observe that velocity fluctuations enhance dispersion in a non-monotonic fashion: the dispersion initially increases with correlation length λ, reaches a maximum, and decreases to zero at infinity. Maximum enhancement can be obtained at the correlation length about 0.25 the size of the porous media perpendicular to flow.
Origin of holographic dark energy models

International Nuclear Information System (INIS)

Myung, Yun Soo; Seo, Min-Gyun

2009-01-01

We investigate the origin of holographic dark energy models which were recently proposed to explain the dark energy-dominated universe. For this purpose, we introduce the spacetime foam uncertainty of δl≥l p α l α-1 . It was argued that the case of α=2/3 could describe the dark energy with infinite statistics, while the case of α=1/2 can describe the ordinary matter with Bose-Fermi statistics. However, two cases may lead to the holographic energy density if the latter recovers from the geometric mean of UV and IR scales. Hence the dark energy with infinite statistics based on the entropy bound is not an ingredient for deriving the holographic dark energy model. Furthermore, it is shown that the agegraphic dark energy models are the holographic dark energy model with different IR length scales
Italian energy scenarios: Markal model

International Nuclear Information System (INIS)

Gracceva, Francesco

2005-01-01

Energy scenarios carried out through formal models comply with scientific criteria such as internal coherence and transparency. Besides, Markal methodology allows a good understanding of the complex nature of the energy system. The business-as-usual scenario carried out through the Markal-Italy model shows that structural changes occurring in end-use sectors will continue to drive up energy consumption, in spite of the slow economic growth and the quite high energy prices [it
Towards an energy management maturity model

International Nuclear Information System (INIS)

Antunes, Pedro; Carreira, Paulo; Mira da Silva, Miguel

2014-01-01

Energy management is becoming a priority as organizations strive to reduce energy costs, conform to regulatory requirements, and improve their corporate image. Despite the upsurge of interest in energy management standards, a gap persists between energy management literature and current implementation practices. This gap can be traced to the lack of an incremental improvement roadmap. In this paper we propose an Energy Management Maturity Model that can be used to guide organizations in their energy management implementation efforts to incrementally achieve compliance with energy management standards such as ISO 50001. The proposed maturity model is inspired on the Plan-Do-Check-Act cycle approach for continual improvement, and covers well-understood fundamental energy management activities common across energy management texts. The completeness of our proposal is then evaluated by establishing an ontology mapping against ISO 50001. - Highlights: • Real-world energy management activities are not aligned with the literature. • An Energy Management Maturity Model is proposed to overcome this alignment gap. • The completeness and relevance of proposed model are validated
A random walk model to evaluate autism

Science.gov (United States)

Moura, T. R. S.; Fulco, U. L.; Albuquerque, E. L.

2018-02-01

A common test administered during neurological examination in children is the analysis of their social communication and interaction across multiple contexts, including repetitive patterns of behavior. Poor performance may be associated with neurological conditions characterized by impairments in executive function, such as the so-called pervasive developmental disorders (PDDs), a particular condition of the autism spectrum disorders (ASDs). Inspired in these diagnosis tools, mainly those related to repetitive movements and behaviors, we studied here how the diffusion regimes of two discrete-time random walkers, mimicking the lack of social interaction and restricted interests developed for children with PDDs, are affected. Our model, which is based on the so-called elephant random walk (ERW) approach, consider that one of the random walker can learn and imitate the microscopic behavior of the other with probability f (1 - f otherwise). The diffusion regimes, measured by the Hurst exponent (H), is then obtained, whose changes may indicate a different degree of autism.
Connectivity ranking of heterogeneous random conductivity models

Science.gov (United States)

Rizzo, C. B.; de Barros, F.

2017-12-01

To overcome the challenges associated with hydrogeological data scarcity, the hydraulic conductivity (K) field is often represented by a spatial random process. The state-of-the-art provides several methods to generate 2D or 3D random K-fields, such as the classic multi-Gaussian fields or non-Gaussian fields, training image-based fields and object-based fields. We provide a systematic comparison of these models based on their connectivity. We use the minimum hydraulic resistance as a connectivity measure, which it has been found to be strictly correlated with early time arrival of dissolved contaminants. A computationally efficient graph-based algorithm is employed, allowing a stochastic treatment of the minimum hydraulic resistance through a Monte-Carlo approach and therefore enabling the computation of its uncertainty. The results show the impact of geostatistical parameters on the connectivity for each group of random fields, being able to rank the fields according to their minimum hydraulic resistance.
No evidence that mRNAs have lower folding free energies than random sequences with the same dinucleotide distribution

DEFF Research Database (Denmark)

Workman, Christopher; Krogh, Anders Stærmose

1999-01-01

This work investigates whether mRNA has a lower estimated folding free energy than random sequences. The free energy estimates are calculated by the mfold program for prediction of RNA secondary structures. For a set of 46 mRNAs it is shown that the predicted free energy is not significantly diff...
Madelung energy for random metallic alloys in the coherent potential approximation

DEFF Research Database (Denmark)

Korzhavyi, P. A.; Ruban, Andrei; Abrikosov, I. A.

1995-01-01

Within the conventional single-site coherent potential approximation (CPA) used to calculate thermodynamic properties of random alloys, the effect of charge transfer is neglected. We discuss a number of recent models based on the same mathematical form but with a different prefactor β which allow...... random alloy, and in this case the screened-CPA method (β=1/2) gives more correct results. It is suggested that a comparison with the results obtained by the Connolly-Williams method may be used to determine an optimal value for β depending on the alloy under consideration....
Accumulator and random-walk models of psychophysical discrimination: a counter-evaluation.

Science.gov (United States)

Vickers, D; Smith, P

1985-01-01

In a recent assessment of models of psychophysical discrimination, Heath criticises the accumulator model for its reliance on computer simulation and qualitative evidence, and contrasts it unfavourably with a modified random-walk model, which yields exact predictions, is susceptible to critical test, and is provided with simple parameter-estimation techniques. A counter-evaluation is presented, in which the approximations employed in the modified random-walk analysis are demonstrated to be seriously inaccurate, the resulting parameter estimates to be artefactually determined, and the proposed test not critical. It is pointed out that Heath's specific application of the model is not legitimate, his data treatment inappropriate, and his hypothesis concerning confidence inconsistent with experimental results. Evidence from adaptive performance changes is presented which shows that the necessary assumptions for quantitative analysis in terms of the modified random-walk model are not satisfied, and that the model can be reconciled with data at the qualitative level only by making it virtually indistinguishable from an accumulator process. A procedure for deriving exact predictions for an accumulator process is outlined.
A cellular automata model of traffic flow with variable probability of randomization

International Nuclear Information System (INIS)

Zheng Wei-Fan; Zhang Ji-Ye

2015-01-01

Research on the stochastic behavior of traffic flow is important to understand the intrinsic evolution rules of a traffic system. By introducing an interactional potential of vehicles into the randomization step, an improved cellular automata traffic flow model with variable probability of randomization is proposed in this paper. In the proposed model, the driver is affected by the interactional potential of vehicles before him, and his decision-making process is related to the interactional potential. Compared with the traditional cellular automata model, the modeling is more suitable for the driver’s random decision-making process based on the vehicle and traffic situations in front of him in actual traffic. From the improved model, the fundamental diagram (flow–density relationship) is obtained, and the detailed high-density traffic phenomenon is reproduced through numerical simulation. (paper)
MODELING URBAN DYNAMICS USING RANDOM FOREST: IMPLEMENTING ROC AND TOC FOR MODEL EVALUATION

Directory of Open Access Journals (Sweden)

M. Ahmadlou

2016-06-01

Full Text Available The importance of spatial accuracy of land use/cover change maps necessitates the use of high performance models. To reach this goal, calibrating machine learning (ML approaches to model land use/cover conversions have received increasing interest among the scholars. This originates from the strength of these techniques as they powerfully account for the complex relationships underlying urban dynamics. Compared to other ML techniques, random forest has rarely been used for modeling urban growth. This paper, drawing on information from the multi-temporal Landsat satellite images of 1985, 2000 and 2015, calibrates a random forest regression (RFR model to quantify the variable importance and simulation of urban change spatial patterns. The results and performance of RFR model were evaluated using two complementary tools, relative operating characteristics (ROC and total operating characteristics (TOC, by overlaying the map of observed change and the modeled suitability map for land use change (error map. The suitability map produced by RFR model showed 82.48% area under curve for the ROC model which indicates a very good performance and highlights its appropriateness for simulating urban growth.
A Comparison of Three Random Number Generators for Aircraft Dynamic Modeling Applications

Science.gov (United States)

Grauer, Jared A.

2017-01-01

Three random number generators, which produce Gaussian white noise sequences, were compared to assess their suitability in aircraft dynamic modeling applications. The first generator considered was the MATLAB (registered) implementation of the Mersenne-Twister algorithm. The second generator was a website called Random.org, which processes atmospheric noise measured using radios to create the random numbers. The third generator was based on synthesis of the Fourier series, where the random number sequences are constructed from prescribed amplitude and phase spectra. A total of 200 sequences, each having 601 random numbers, for each generator were collected and analyzed in terms of the mean, variance, normality, autocorrelation, and power spectral density. These sequences were then applied to two problems in aircraft dynamic modeling, namely estimating stability and control derivatives from simulated onboard sensor data, and simulating flight in atmospheric turbulence. In general, each random number generator had good performance and is well-suited for aircraft dynamic modeling applications. Specific strengths and weaknesses of each generator are discussed. For Monte Carlo simulation, the Fourier synthesis method is recommended because it most accurately and consistently approximated Gaussian white noise and can be implemented with reasonable computational effort.
Power-based electric vehicle energy consumption model: Model development and validation

International Nuclear Information System (INIS)

Fiori, Chiara; Ahn, Kyoungho; Rakha, Hesham A.

2016-01-01

Highlights: • The study developed an instantaneous energy consumption model (VT-CPEM) for EVs. • The model captures instantaneous braking energy regeneration. • The model can be used for transportation modeling and vehicle applications (e.g. eco-routing). • The proposed model can be easily calibrated using publically available EV data. • Usages of air conditioning and heating systems reduce EV energy consumption by up to 10% and 24%, respectively. - Abstract: The limited drive range (The maximum distance that an EV can travel.) of Electric Vehicles (EVs) is one of the major challenges that EV manufacturers are attempting to overcome. To this end, a simple, accurate, and efficient energy consumption model is needed to develop real-time eco-driving and eco-routing systems that can enhance the energy efficiency of EVs and thus extend their travel range. Although numerous publications have focused on the modeling of EV energy consumption levels, these studies are limited to measuring energy consumption of an EV’s control algorithm, macro-project evaluations, or simplified well-to-wheels analyses. Consequently, this paper addresses this need by developing a simple EV energy model that computes an EV’s instantaneous energy consumption using second-by-second vehicle speed, acceleration and roadway grade data as input variables. In doing so, the model estimates the instantaneous braking energy regeneration. The proposed model can be easily implemented in the following applications: in-vehicle, Smartphone eco-driving, eco-routing and transportation simulation software to quantify the network-wide energy consumption levels for a fleet of EVs. One of the main advantages of EVs is their ability to recover energy while braking using a regenerative braking system. State-of-the-art vehicle energy consumption models consider an average constant regenerative braking energy efficiency or regenerative braking factors that are mainly dependent on the vehicle’s average
Joint modeling of ChIP-seq data via a Markov random field model

NARCIS (Netherlands)

Bao, Yanchun; Vinciotti, Veronica; Wit, Ernst; 't Hoen, Peter A C

Chromatin ImmunoPrecipitation-sequencing (ChIP-seq) experiments have now become routine in biology for the detection of protein-binding sites. In this paper, we present a Markov random field model for the joint analysis of multiple ChIP-seq experiments. The proposed model naturally accounts for

Macroeconomic models and energy transition

International Nuclear Information System (INIS)

Douillard, Pierre; Le Hir, Boris; Epaulard, Anne

2016-02-01

As a new policy for energy transition has just been adopted, several questions emerge about the best way to reduce CO 2 emissions, about policies which enable this reduction, and about their costs and opportunities. This note discusses the contribution macro-economic models may have in this respect, notably in the definition of policies which trigger behaviour changes, and those which support energy transition. The authors first discuss the stakes of the assessment of energy transition, and then describe macro-economic models which can be used for such an assessment, give and comment some results of simulations performed for France by using four of these models (Mesange, Numesis, ThreeME, and Imaclim-R France). The authors finally draw lessons about the way to use these models and to interpret their results within the frame of energy transition
Accurate Quasiparticle Spectra from the T-Matrix Self-Energy and the Particle-Particle Random Phase Approximation.

Science.gov (United States)

Zhang, Du; Su, Neil Qiang; Yang, Weitao

2017-07-20

The GW self-energy, especially G 0 W 0 based on the particle-hole random phase approximation (phRPA), is widely used to study quasiparticle (QP) energies. Motivated by the desirable features of the particle-particle (pp) RPA compared to the conventional phRPA, we explore the pp counterpart of GW, that is, the T-matrix self-energy, formulated with the eigenvectors and eigenvalues of the ppRPA matrix. We demonstrate the accuracy of the T-matrix method for molecular QP energies, highlighting the importance of the pp channel for calculating QP spectra.
Agent based modeling of energy networks

International Nuclear Information System (INIS)

Gonzalez de Durana, José María; Barambones, Oscar; Kremers, Enrique; Varga, Liz

2014-01-01

Highlights: • A new approach for energy network modeling is designed and tested. • The agent-based approach is general and no technology dependent. • The models can be easily extended. • The range of applications encompasses from small to large energy infrastructures. - Abstract: Attempts to model any present or future power grid face a huge challenge because a power grid is a complex system, with feedback and multi-agent behaviors, integrated by generation, distribution, storage and consumption systems, using various control and automation computing systems to manage electricity flows. Our approach to modeling is to build upon an established model of the low voltage electricity network which is tested and proven, by extending it to a generalized energy model. But, in order to address the crucial issues of energy efficiency, additional processes like energy conversion and storage, and further energy carriers, such as gas, heat, etc., besides the traditional electrical one, must be considered. Therefore a more powerful model, provided with enhanced nodes or conversion points, able to deal with multidimensional flows, is being required. This article addresses the issue of modeling a local multi-carrier energy network. This problem can be considered as an extension of modeling a low voltage distribution network located at some urban or rural geographic area. But instead of using an external power flow analysis package to do the power flow calculations, as used in electric networks, in this work we integrate a multiagent algorithm to perform the task, in a concurrent way to the other simulation tasks, and not only for the electric fluid but also for a number of additional energy carriers. As the model is mainly focused in system operation, generation and load models are not developed
Generalized Whittle-Matern random field as a model of correlated fluctuations

International Nuclear Information System (INIS)

Lim, S C; Teo, L P

2009-01-01

This paper considers a generalization of the Gaussian random field with covariance function of the Whittle-Matern family. Such a random field can be obtained as the solution to the fractional stochastic differential equation with two fractional orders. Asymptotic properties of the covariance functions belonging to this generalized Whittle-Matern family are studied, which are used to deduce the sample path properties of the random field. The Whittle-Matern field has been widely used in modeling geostatistical data such as sea beam data, wind speed, field temperature and soil data. In this paper we show that the generalized Whittle-Matern field provides a more flexible model for wind speed data
Theoretical modeling, simulation and experimental study of hybrid piezoelectric and electromagnetic energy harvester

Directory of Open Access Journals (Sweden)

Ping Li

2018-03-01

Full Text Available In this paper, performances of vibration energy harvester combined piezoelectric (PE and electromagnetic (EM mechanism are studied by theoretical analysis, simulation and experimental test. For the designed harvester, electromechanical coupling modeling is established, and expressions of vibration response, output voltage, current and power are derived. Then, performances of the harvester are simulated and tested; moreover, the power charging rechargeable battery is realized through designed energy storage circuit. By the results, it’s found that compared with piezoelectric-only and electromagnetic-only energy harvester, the hybrid energy harvester can enhance the output power and harvesting efficiency; furthermore, at the harmonic excitation, output power of harvester linearly increases with acceleration amplitude increasing; while it enhances with acceleration spectral density increasing at the random excitation. In addition, the bigger coupling strength, the bigger output power is, and there is the optimal load resistance to make the harvester output the maximal power.
A simulation-based goodness-of-fit test for random effects in generalized linear mixed models

DEFF Research Database (Denmark)

Waagepetersen, Rasmus

2006-01-01

The goodness-of-fit of the distribution of random effects in a generalized linear mixed model is assessed using a conditional simulation of the random effects conditional on the observations. Provided that the specified joint model for random effects and observations is correct, the marginal...... distribution of the simulated random effects coincides with the assumed random effects distribution. In practice, the specified model depends on some unknown parameter which is replaced by an estimate. We obtain a correction for this by deriving the asymptotic distribution of the empirical distribution...
A simulation-based goodness-of-fit test for random effects in generalized linear mixed models

DEFF Research Database (Denmark)

Waagepetersen, Rasmus Plenge

The goodness-of-fit of the distribution of random effects in a generalized linear mixed model is assessed using a conditional simulation of the random effects conditional on the observations. Provided that the specified joint model for random effects and observations is correct, the marginal...... distribution of the simulated random effects coincides with the assumed random effects distribution. In practice the specified model depends on some unknown parameter which is replaced by an estimate. We obtain a correction for this by deriving the asymptotic distribution of the empirical distribution function...
The ESRI Energy Model

OpenAIRE

Di Cosmo, Valeri; Hyland, Marie

2012-01-01

PUBLISHED In Ireland, the energy sector has undergone significant change in the last forty years. In this period, there has been a significant increase in the demand for energy. This increase has been driven by economic and demographic factors. Although the current deep recession has quelled the upward trend in the demand for energy, a future economic recovery will bring these issues back into focus. This paper documents a model of the Irish energy sector which relates energy demand to re...
Evolving and energy dependent optical model description of heavy-ion elastic scattering

International Nuclear Information System (INIS)

Michaelian, K.

1996-01-01

We present the application of a genetic algorithm to the problem of determining an energy dependent optical model description of heavy-ion elastic scattering. The problem requires a search for the global best optical model potential and its energy dependence in a very rugged 12 dimensional parameter space of complex topographical features with many local minima. Random solutions are created in the first generation. The fitness of a solution is related to the χ 2 fit of the calculated differential cross sections with the experimental data. Best fit solutions are evolved through cross over and mutation following the biological example. This genetic algorithm approach combined with local gradient minimization is shown to provide a global, complete and extremely efficient search method, well adapted to complex fitness landscapes. These characteristics, combined with the facility of application, should make it the search method of choice for a wide variety of problems from nuclear physics. (Author)
Uncertainty analysis of geothermal energy economics

Science.gov (United States)

Sener, Adil Caner

This dissertation research endeavors to explore geothermal energy economics by assessing and quantifying the uncertainties associated with the nature of geothermal energy and energy investments overall. The study introduces a stochastic geothermal cost model and a valuation approach for different geothermal power plant development scenarios. The Monte Carlo simulation technique is employed to obtain probability distributions of geothermal energy development costs and project net present values. In the study a stochastic cost model with incorporated dependence structure is defined and compared with the model where random variables are modeled as independent inputs. One of the goals of the study is to attempt to shed light on the long-standing modeling problem of dependence modeling between random input variables. The dependence between random input variables will be modeled by employing the method of copulas. The study focuses on four main types of geothermal power generation technologies and introduces a stochastic levelized cost model for each technology. Moreover, we also compare the levelized costs of natural gas combined cycle and coal-fired power plants with geothermal power plants. The input data used in the model relies on the cost data recently reported by government agencies and non-profit organizations, such as the Department of Energy, National Laboratories, California Energy Commission and Geothermal Energy Association. The second part of the study introduces the stochastic discounted cash flow valuation model for the geothermal technologies analyzed in the first phase. In this phase of the study, the Integrated Planning Model (IPM) software was used to forecast the revenue streams of geothermal assets under different price and regulation scenarios. These results are then combined to create a stochastic revenue forecast of the power plants. The uncertainties in gas prices and environmental regulations will be modeled and their potential impacts will be
Self-consistent Random Phase Approximation applied to a schematic model of the field theory

International Nuclear Information System (INIS)

Bertrand, Thierry

1998-01-01

The self-consistent Random Phase Approximation (SCRPA) is a method allowing in the mean-field theory inclusion of the correlations in the ground and excited states. It has the advantage of not violating the Pauli principle in contrast to RPA, that is based on the quasi-bosonic approximation; in addition, numerous applications in different domains of physics, show a possible variational character. However, the latter should be formally demonstrated. The first model studied with SCRPA is the anharmonic oscillator in the region where one of its symmetries is spontaneously broken. The ground state energy is reproduced by SCRPA more accurately than RPA, with no violation of the Ritz variational principle, what is not the case for the latter approximation. The success of SCRPA is the the same in case of ground state energy for a model mixing bosons and fermions. At the transition point the SCRPA is correcting RPA drastically, but far from this region the correction becomes negligible, both methods being of similar precision. In the deformed region in the case of RPA a spurious mode occurred due to the microscopical character of the model.. The SCRPA may also reproduce this mode very accurately and actually it coincides with an excitation in the exact spectrum
Numerical Simulation of Entropy Growth for a Nonlinear Evolutionary Model of Random Markets

Directory of Open Access Journals (Sweden)

Mahdi Keshtkar

2016-01-01

Full Text Available In this communication, the generalized continuous economic model for random markets is revisited. In this model for random markets, agents trade by pairs and exchange their money in a random and conservative way. They display the exponential wealth distribution as asymptotic equilibrium, independently of the effectiveness of the transactions and of the limitation of the total wealth. In the current work, entropy of mentioned model is defined and then some theorems on entropy growth of this evolutionary problem are given. Furthermore, the entropy increasing by simulation on some numerical examples is verified.
Energy flow modeling and optimal operation analysis of the micro energy grid based on energy hub

International Nuclear Information System (INIS)

Ma, Tengfei; Wu, Junyong; Hao, Liangliang

2017-01-01

Highlights: • Design a novel architecture for energy hub integrating power hub, cooling hub and heating hub. • The micro energy grid based on energy hub is introduced and its advantages are discussed. • Propose a generic modeling method for the energy flow of micro energy grid. • Propose an optimal operation model for micro energy grid with considering demand response. • The roles of renewable energy, energy storage devices and demand response are discussed separately. - Abstract: The energy security and environmental problems impel people to explore a more efficient, environment friendly and economical energy utilization pattern. In this paper, the coordinated operation and optimal dispatch strategies for multiple energy system are studied at the whole Micro Energy Grid level. To augment the operation flexibility of energy hub, the innovation sub-energy hub structure including power hub, heating hub and cooling hub is put forward. Basing on it, a generic energy hub architecture integrating renewable energy, combined cooling heating and power, and energy storage devices is developed. Moreover, a generic modeling method for the energy flow of micro energy grid is proposed. To minimize the daily operation cost, a day-ahead dynamic optimal operation model is formulated as a mixed integer linear programming optimization problem with considering the demand response. Case studies are undertaken on a community Micro Energy Grid in four different scenarios on a typical summer day and the roles of renewable energy, energy storage devices and demand response are discussed separately. Numerical simulation results indicate that the proposed energy flow modeling and optimal operation method are universal and effective over the entire energy dispatching horizon.
Scaling of coercivity in a 3d random anisotropy model

Energy Technology Data Exchange (ETDEWEB)

Proctor, T.C., E-mail: proctortc@gmail.com; Chudnovsky, E.M., E-mail: EUGENE.CHUDNOVSKY@lehman.cuny.edu; Garanin, D.A.

2015-06-15

The random-anisotropy Heisenberg model is numerically studied on lattices containing over ten million spins. The study is focused on hysteresis and metastability due to topological defects, and is relevant to magnetic properties of amorphous and sintered magnets. We are interested in the limit when ferromagnetic correlations extend beyond the size of the grain inside which the magnetic anisotropy axes are correlated. In that limit the coercive field computed numerically roughly scales as the fourth power of the random anisotropy strength and as the sixth power of the grain size. Theoretical arguments are presented that provide an explanation of numerical results. Our findings should be helpful for designing amorphous and nanosintered materials with desired magnetic properties. - Highlights: • We study the random-anisotropy model on lattices containing up to ten million spins. • Irreversible behavior due to topological defects (hedgehogs) is elucidated. • Hysteresis loop area scales as the fourth power of the random anisotropy strength. • In nanosintered magnets the coercivity scales as the six power of the grain size.
Comparing holographic dark energy models with statefinder

International Nuclear Information System (INIS)

Cui, Jing-Lei; Zhang, Jing-Fei

2014-01-01

We apply the statefinder diagnostic to the holographic dark energy models, including the original holographic dark energy (HDE) model, the new holographic dark energy model, the new agegraphic dark energy (NADE) model, and the Ricci dark energy model. In the low-redshift region the holographic dark energy models are degenerate with each other and with the ΛCDM model in the H(z) and q(z) evolutions. In particular, the HDE model is highly degenerate with the ΛCDM model, and in the HDE model the cases with different parameter values are also in strong degeneracy. Since the observational data are mainly within the low-redshift region, it is very important to break this lowredshift degeneracy in the H(z) and q(z) diagnostics by using some quantities with higher order derivatives of the scale factor. It is shown that the statefinder diagnostic r(z) is very useful in breaking the low-redshift degeneracies. By employing the statefinder diagnostic the holographic dark energy models can be differentiated efficiently in the low-redshift region. The degeneracy between the holographic dark energy models and the ΛCDM model can also be broken by this method. Especially for the HDE model, all the previous strong degeneracies appearing in the H(z) and q(z) diagnostics are broken effectively. But for the NADE model, the degeneracy between the cases with different parameter values cannot be broken, even though the statefinder diagnostic is used. A direct comparison of the holographic dark energy models in the r-s plane is also made, in which the separations between the models (including the ΛCDM model) can be directly measured in the light of the current values {r 0 , s 0 } of the models. (orig.)
Balmorel open source energy system model

DEFF Research Database (Denmark)

Wiese, Frauke; Bramstoft, Rasmus; Koduvere, Hardi

2018-01-01

As the world progresses towards a cleaner energy future with more variable renewable energy sources, energy system models are required to deal with new challenges. This article describes design, development and applications of the open source energy system model Balmorel, which is a result...... of a long and fruitful cooperation between public and private institutions within energy system research and analysis. The purpose of the article is to explain the modelling approach, to highlight strengths and challenges of the chosen approach, to create awareness about the possible applications...... of Balmorel as well as to inspire to new model developments and encourage new users to join the community. Some of the key strengths of the model are the flexible handling of the time and space dimensions and the combination of operation and investment optimisation. Its open source character enables diverse...
Particle filters for random set models

CERN Document Server

Ristic, Branko

2013-01-01

“Particle Filters for Random Set Models” presents coverage of state estimation of stochastic dynamic systems from noisy measurements, specifically sequential Bayesian estimation and nonlinear or stochastic filtering. The class of solutions presented in this book is based on the Monte Carlo statistical method. The resulting algorithms, known as particle filters, in the last decade have become one of the essential tools for stochastic filtering, with applications ranging from navigation and autonomous vehicles to bio-informatics and finance. While particle filters have been around for more than a decade, the recent theoretical developments of sequential Bayesian estimation in the framework of random set theory have provided new opportunities which are not widely known and are covered in this book. These recent developments have dramatically widened the scope of applications, from single to multiple appearing/disappearing objects, from precise to imprecise measurements and measurement models. This book...
Modeling international trends in energy efficiency

International Nuclear Information System (INIS)

Stern, David I.

2012-01-01

I use a stochastic production frontier to model energy efficiency trends in 85 countries over a 37-year period. Differences in energy efficiency across countries are modeled as a stochastic function of explanatory variables and I estimate the model using the cross-section of time-averaged data, so that no structure is imposed on technological change over time. Energy efficiency is measured using a new energy distance function approach. The country using the least energy per unit output, given its mix of outputs and inputs, defines the global production frontier. A country's relative energy efficiency is given by its distance from the frontier—the ratio of its actual energy use to the minimum required energy use, ceteris paribus. Energy efficiency is higher in countries with, inter alia, higher total factor productivity, undervalued currencies, and smaller fossil fuel reserves and it converges over time across countries. Globally, technological change was the most important factor counteracting the energy-use and carbon-emissions increasing effects of economic growth.
Asthma Self-Management Model: Randomized Controlled Trial

Science.gov (United States)

Olivera, Carolina M. X.; Vianna, Elcio Oliveira; Bonizio, Roni C.; de Menezes, Marcelo B.; Ferraz, Erica; Cetlin, Andrea A.; Valdevite, Laura M.; Almeida, Gustavo A.; Araujo, Ana S.; Simoneti, Christian S.; de Freitas, Amanda; Lizzi, Elisangela A.; Borges, Marcos C.; de Freitas, Osvaldo

2016-01-01

Information for patients provided by the pharmacist is reflected in adhesion to treatment, clinical results and patient quality of life. The objective of this study was to assess an asthma self-management model for rational medicine use. This was a randomized controlled trial with 60 asthmatic patients assigned to attend five modules presented by…
Hybrid Energy System Modeling in Modelica

Energy Technology Data Exchange (ETDEWEB)

William R. Binder; Christiaan J. J. Paredis; Humberto E. Garcia

2014-03-01

In this paper, a Hybrid Energy System (HES) configuration is modeled in Modelica. Hybrid Energy Systems (HES) have as their defining characteristic the use of one or more energy inputs, combined with the potential for multiple energy outputs. Compared to traditional energy systems, HES provide additional operational flexibility so that high variability in both energy production and consumption levels can be absorbed more effectively. This is particularly important when including renewable energy sources, whose output levels are inherently variable, determined by nature. The specific HES configuration modeled in this paper include two energy inputs: a nuclear plant, and a series of wind turbines. In addition, the system produces two energy outputs: electricity and synthetic fuel. The models are verified through simulations of the individual components, and the system as a whole. The simulations are performed for a range of component sizes, operating conditions, and control schemes.

World Energy Projection System model documentation

International Nuclear Information System (INIS)

Hutzler, M.J.; Anderson, A.T.

1997-09-01

The World Energy Projection System (WEPS) was developed by the Office of Integrated Analysis and Forecasting within the Energy Information Administration (EIA), the independent statistical and analytical agency of the US Department of Energy. WEPS is an integrated set of personal computer based spreadsheets containing data compilations, assumption specifications, descriptive analysis procedures, and projection models. The WEPS accounting framework incorporates projections from independently documented models and assumptions about the future energy intensity of economic activity (ratios of total energy consumption divided by gross domestic product GDP), and about the rate of incremental energy requirements met by natural gas, coal, and renewable energy sources (hydroelectricity, geothermal, solar, wind, biomass, and other renewable resources). Projections produced by WEPS are published in the annual report, International Energy Outlook. This report documents the structure and procedures incorporated in the 1998 version of the WEPS model. It has been written to provide an overview of the structure of the system and technical details about the operation of each component of the model for persons who wish to know how WEPS projections are produced by EIA
World Energy Projection System model documentation

Energy Technology Data Exchange (ETDEWEB)

Hutzler, M.J.; Anderson, A.T.

1997-09-01

The World Energy Projection System (WEPS) was developed by the Office of Integrated Analysis and Forecasting within the Energy Information Administration (EIA), the independent statistical and analytical agency of the US Department of Energy. WEPS is an integrated set of personal computer based spreadsheets containing data compilations, assumption specifications, descriptive analysis procedures, and projection models. The WEPS accounting framework incorporates projections from independently documented models and assumptions about the future energy intensity of economic activity (ratios of total energy consumption divided by gross domestic product GDP), and about the rate of incremental energy requirements met by natural gas, coal, and renewable energy sources (hydroelectricity, geothermal, solar, wind, biomass, and other renewable resources). Projections produced by WEPS are published in the annual report, International Energy Outlook. This report documents the structure and procedures incorporated in the 1998 version of the WEPS model. It has been written to provide an overview of the structure of the system and technical details about the operation of each component of the model for persons who wish to know how WEPS projections are produced by EIA.
Genomic-Enabled Prediction Kernel Models with Random Intercepts for Multi-environment Trials

Science.gov (United States)

Cuevas, Jaime; Granato, Italo; Fritsche-Neto, Roberto; Montesinos-Lopez, Osval A.; Burgueño, Juan; Bandeira e Sousa, Massaine; Crossa, José

2018-01-01

In this study, we compared the prediction accuracy of the main genotypic effect model (MM) without G×E interactions, the multi-environment single variance G×E deviation model (MDs), and the multi-environment environment-specific variance G×E deviation model (MDe) where the random genetic effects of the lines are modeled with the markers (or pedigree). With the objective of further modeling the genetic residual of the lines, we incorporated the random intercepts of the lines (l) and generated another three models. Each of these 6 models were fitted with a linear kernel method (Genomic Best Linear Unbiased Predictor, GB) and a Gaussian Kernel (GK) method. We compared these 12 model-method combinations with another two multi-environment G×E interactions models with unstructured variance-covariances (MUC) using GB and GK kernels (4 model-method). Thus, we compared the genomic-enabled prediction accuracy of a total of 16 model-method combinations on two maize data sets with positive phenotypic correlations among environments, and on two wheat data sets with complex G×E that includes some negative and close to zero phenotypic correlations among environments. The two models (MDs and MDE with the random intercept of the lines and the GK method) were computationally efficient and gave high prediction accuracy in the two maize data sets. Regarding the more complex G×E wheat data sets, the prediction accuracy of the model-method combination with G×E, MDs and MDe, including the random intercepts of the lines with GK method had important savings in computing time as compared with the G×E interaction multi-environment models with unstructured variance-covariances but with lower genomic prediction accuracy. PMID:29476023
Energy and Development. A Modelling Approach

International Nuclear Information System (INIS)

Van Ruijven, B.J.

2008-01-01

Rapid economic growth of developing countries like India and China implies that these countries become important actors in the global energy system. Examples of this impact are the present day oil shortages and rapidly increasing emissions of greenhouse gases. Global energy models are used to explore possible future developments of the global energy system and identify policies to prevent potential problems. Such estimations of future energy use in developing countries are very uncertain. Crucial factors in the future energy use of these regions are electrification, urbanisation and income distribution, issues that are generally not included in present day global energy models. Model simulations in this thesis show that current insight in developments in low-income regions lead to a wide range of expected energy use in 2030 of the residential and transport sectors. This is mainly caused by many different model calibration options that result from the limited data availability for model development and calibration. We developed a method to identify the impact of model calibration uncertainty on future projections. We developed a new model for residential energy use in India, in collaboration with the Indian Institute of Science. Experiments with this model show that the impact of electrification and income distribution is less univocal than often assumed. The use of fuelwood, with related health risks, can decrease rapidly if the income of poor groups increases. However, there is a trade off in terms of CO2 emissions because these groups gain access to electricity and the ownership of appliances increases. Another issue is the potential role of new technologies in developing countries: will they use the opportunities of leapfrogging? We explored the potential role of hydrogen, an energy carrier that might play a central role in a sustainable energy system. We found that hydrogen only plays a role before 2050 under very optimistic assumptions. Regional energy
Restoration of dimensional reduction in the random-field Ising model at five dimensions

Science.gov (United States)

Fytas, Nikolaos G.; Martín-Mayor, Víctor; Picco, Marco; Sourlas, Nicolas

2017-04-01

The random-field Ising model is one of the few disordered systems where the perturbative renormalization group can be carried out to all orders of perturbation theory. This analysis predicts dimensional reduction, i.e., that the critical properties of the random-field Ising model in D dimensions are identical to those of the pure Ising ferromagnet in D -2 dimensions. It is well known that dimensional reduction is not true in three dimensions, thus invalidating the perturbative renormalization group prediction. Here, we report high-precision numerical simulations of the 5D random-field Ising model at zero temperature. We illustrate universality by comparing different probability distributions for the random fields. We compute all the relevant critical exponents (including the critical slowing down exponent for the ground-state finding algorithm), as well as several other renormalization-group invariants. The estimated values of the critical exponents of the 5D random-field Ising model are statistically compatible to those of the pure 3D Ising ferromagnet. These results support the restoration of dimensional reduction at D =5 . We thus conclude that the failure of the perturbative renormalization group is a low-dimensional phenomenon. We close our contribution by comparing universal quantities for the random-field problem at dimensions 3 ≤D equality at all studied dimensions.
Modeling of renewable hybrid energy sources

Directory of Open Access Journals (Sweden)

Dumitru Cristian Dragos

2009-12-01

Full Text Available Recent developments and trends in the electric power consumption indicate an increasing use of renewable energy. Renewable energy technologies offer the promise of clean, abundant energy gathered from self-renewing resources such as the sun, wind, earth and plants. Virtually all regions of the world have renewable resources of one type or another. By this point of view studies on renewable energies focuses more and more attention. The present paper intends to present different mathematical models related to different types of renewable energy sources such as: solar energy and wind energy. It is also presented the validation and adaptation of such models to hybrid systems working in geographical and meteorological conditions specific to central part of Transylvania region. The conclusions based on validation of such models are also shown.
Magnetically coupled flextensional transducer for wideband vibration energy harvesting: Design, modeling and experiments

Science.gov (United States)

Zou, Hong-Xiang; Zhang, Wen-Ming; Li, Wen-Bo; Wei, Ke-Xiang; Hu, Kai-Ming; Peng, Zhi-Ke; Meng, Guang

2018-03-01

The combination of nonlinear bistable and flextensional mechanisms has the advantages of wide operating frequency and high equivalent piezoelectric constant. In this paper, three magnetically coupled flextensional vibration energy harvesters (MF-VEHs) are designed from three magnetically coupled vibration systems which utilize a magnetic repulsion, two symmetrical magnetic attractions and multi-magnetic repulsions, respectively. The coupled dynamic models are developed to describe the electromechanical transitions. Simulations under harmonic excitation and random excitation are carried out to investigate the performance of the MF-VEHs with different parameters. Experimental validations of the MF-VEHs are performed under different excitation levels. The experimental results verify that the developed mathematical models can be used to accurately characterize the MF-VEHs for various magnetic coupling modes. A comparison of three MF-VEHs is provided and the results illustrate that a reasonable arrangement of multiple magnets can reduce the threshold excitation intensity and increase the harvested energy.
Impacts of Model Building Energy Codes

Energy Technology Data Exchange (ETDEWEB)

Athalye, Rahul A. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Sivaraman, Deepak [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Elliott, Douglas B. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Liu, Bing [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Bartlett, Rosemarie [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

2016-10-31

The U.S. Department of Energy (DOE) Building Energy Codes Program (BECP) periodically evaluates national and state-level impacts associated with energy codes in residential and commercial buildings. Pacific Northwest National Laboratory (PNNL), funded by DOE, conducted an assessment of the prospective impacts of national model building energy codes from 2010 through 2040. A previous PNNL study evaluated the impact of the Building Energy Codes Program; this study looked more broadly at overall code impacts. This report describes the methodology used for the assessment and presents the impacts in terms of energy savings, consumer cost savings, and reduced CO₂ emissions at the state level and at aggregated levels. This analysis does not represent all potential savings from energy codes in the U.S. because it excludes several states which have codes which are fundamentally different from the national model energy codes or which do not have state-wide codes. Energy codes follow a three-phase cycle that starts with the development of a new model code, proceeds with the adoption of the new code by states and local jurisdictions, and finishes when buildings comply with the code. The development of new model code editions creates the potential for increased energy savings. After a new model code is adopted, potential savings are realized in the field when new buildings (or additions and alterations) are constructed to comply with the new code. Delayed adoption of a model code and incomplete compliance with the code’s requirements erode potential savings. The contributions of all three phases are crucial to the overall impact of codes, and are considered in this assessment.
Simulating intrafraction prostate motion with a random walk model

Directory of Open Access Journals (Sweden)

Tobias Pommer, PhD

2017-07-01

Conclusions: Random walk modeling is feasible and recreated the characteristics of the observed prostate motion. Introducing artificial transient motion did not improve the overall agreement, although the first 30 seconds of the traces were better reproduced. The model provides a simple estimate of prostate motion during delivery of radiation therapy.
Random matrices and the six-vertex model

CERN Document Server

Bleher, Pavel

2013-01-01

This book provides a detailed description of the Riemann-Hilbert approach (RH approach) to the asymptotic analysis of both continuous and discrete orthogonal polynomials, and applications to random matrix models as well as to the six-vertex model. The RH approach was an important ingredient in the proofs of universality in unitary matrix models. This book gives an introduction to the unitary matrix models and discusses bulk and edge universality. The six-vertex model is an exactly solvable two-dimensional model in statistical physics, and thanks to the Izergin-Korepin formula for the model with domain wall boundary conditions, its partition function matches that of a unitary matrix model with nonpolynomial interaction. The authors introduce in this book the six-vertex model and include a proof of the Izergin-Korepin formula. Using the RH approach, they explicitly calculate the leading and subleading terms in the thermodynamic asymptotic behavior of the partition function of the six-vertex model with domain wa...
Renewable Energy and Efficiency Modeling Analysis Partnership: An Analysis of How Different Energy Models Addressed a Common High Renewable Energy Penetration Scenario in 2025

Energy Technology Data Exchange (ETDEWEB)

Blair, N.; Jenkin, T.; Milford, J.; Short, W.; Sullivan, P.; Evans, D.; Lieberman, E.; Goldstein, G.; Wright, E.; Jayaraman, K.; Venkatech, B.; Kleiman, G.; Namovicz, C.; Smith, B.; Palmer, K.; Wiser, R.; Wood, F.

2009-09-30

The Renewable Energy and Efficiency Modeling and Analysis Partnership (REMAP) sponsors ongoing workshops to discuss individual 'renewable' technologies, energy/economic modeling, and - to some extent - policy issues related to renewable energy. Since 2002, the group has organized seven workshops, each focusing on a different renewable technology (geothermal, solar, wind, etc.). These workshops originated and continue to be run under an informal partnership of the Environmental Protection Agency (EPA), the Department of Energy's (DOE) Office of Energy Efficiency and Renewable Energy (EERE), the National Renewable Energy Laboratory (NREL), and the American Council on Renewable Energy (ACORE). EPA originally funded the activities, but support is now shared between EPA and EERE. REMAP has a wide range of participating analysts and models/modelers that come from government, the private sector, and academia. Modelers include staff from the Energy Information Administration (EIA), the American Council for an Energy-Efficient Economy (ACEEE), NREL, EPA, Resources for the Future (RFF), Argonne National Laboratory (ANL), Northeast States for Coordinated Air Use Management (NESCAUM), Regional Economic Models Inc. (REMI), ICF International, OnLocation Inc., and Boston University. The working group has more than 40 members, which also includes representatives from DOE, Lawrence Berkeley National Laboratory (LBNL), Union of Concerned Scientists (UCS), Massachusetts Renewable Energy Trust, Federal Energy Regulatory Commission (FERC), and ACORE. This report summarizes the activities and findings of the REMAP activity that started in late 2006 with a kickoff meeting, and concluded in mid-2008 with presentations of final results. As the project evolved, the group compared results across models and across technologies rather than just examining a specific technology or activity. The overall goal was to better understand how and why different energy models give similar
Modelling distributed energy resources in energy service networks

CERN Document Server

Acha, Salvador

2013-01-01

Focuses on modelling two key infrastructures (natural gas and electrical) in urban energy systems with embedded technologies (cogeneration and electric vehicles) to optimise the operation of natural gas and electrical infrastructures under the presence of distributed energy resources
Modeling and optimizing of the random atomic spin gyroscope drift based on the atomic spin gyroscope

Energy Technology Data Exchange (ETDEWEB)

Quan, Wei; Lv, Lin, E-mail: lvlinlch1990@163.com; Liu, Baiqi [School of Instrument Science and Opto-Electronics Engineering, Beihang University, Beijing 100191 (China)

2014-11-15

In order to improve the atom spin gyroscope's operational accuracy and compensate the random error caused by the nonlinear and weak-stability characteristic of the random atomic spin gyroscope (ASG) drift, the hybrid random drift error model based on autoregressive (AR) and genetic programming (GP) + genetic algorithm (GA) technique is established. The time series of random ASG drift is taken as the study object. The time series of random ASG drift is acquired by analyzing and preprocessing the measured data of ASG. The linear section model is established based on AR technique. After that, the nonlinear section model is built based on GP technique and GA is used to optimize the coefficients of the mathematic expression acquired by GP in order to obtain a more accurate model. The simulation result indicates that this hybrid model can effectively reflect the characteristics of the ASG's random drift. The square error of the ASG's random drift is reduced by 92.40%. Comparing with the AR technique and the GP + GA technique, the random drift is reduced by 9.34% and 5.06%, respectively. The hybrid modeling method can effectively compensate the ASG's random drift and improve the stability of the system.
Finite-range Coulomb gas models of banded random matrices and quantum kicked rotors.

Science.gov (United States)

Pandey, Akhilesh; Kumar, Avanish; Puri, Sanjay

2017-11-01

Dyson demonstrated an equivalence between infinite-range Coulomb gas models and classical random matrix ensembles for the study of eigenvalue statistics. We introduce finite-range Coulomb gas (FRCG) models via a Brownian matrix process, and study them analytically and by Monte Carlo simulations. These models yield new universality classes, and provide a theoretical framework for the study of banded random matrices (BRMs) and quantum kicked rotors (QKRs). We demonstrate that, for a BRM of bandwidth b and a QKR of chaos parameter α, the appropriate FRCG model has the effective range d=b^{2}/N=α^{2}/N, for large N matrix dimensionality. As d increases, there is a transition from Poisson to classical random matrix statistics.
Low-energy neutron-induced single-event upsets in static random access memory

International Nuclear Information System (INIS)

Guo Xiaoqiang; Guo Hongxia; Wang Guizhen; Ling Dongsheng; Chen Wei; Bai Xiaoyan; Yang Shanchao; Liu Yan

2009-01-01

The visual analysis method of data process was provided for neutron-induced single-event upset(SEU) in static random access memory(SRAM). The SEU effects of six CMOS SRAMs with different feature size(from 0.13 μm to 1.50 μm) were studied. The SEU experiments were performed using the neutron radiation environment at Xi'an pulsed reactor. And the dependence of low-energy neutron-induced SEU cross section on SRAM's feature size was given. The results indicate that the decreased critical charge is the dominant factor for the increase of single event effect sensitivity of SRAM devices with decreased feature size. Small-sized SRAM devices are more sensitive than large-sized ones to single event effect induced by low-energy neutrons. (authors)
Energies of the ground state and first excited 0 sup + state in an exactly solvable pairing model

CERN Document Server

Dinh Dang, N

2003-01-01

Several approximations are tested by calculating the ground-state energy and the energy of the first excited 0 sup + state using an exactly solvable model with two symmetric levels interacting via a pairing force. They are the BCS approximation (BCS), Lipkin-Nogami (LN) method, random-phase approximation (RPA), quasiparticle RPA (QRPA), the renormalized RPA (RRPA), and renormalized QRPA (RQRPA). It is shown that, in the strong-coupling regime, the QRPA which neglects the scattering term of the model Hamiltonian offers the best fit to the exact solutions. A recipe is proposed using the RRPA and RQRPA in combination with the pairing gap given by the LN method. Applying this recipe, it is shown that the superfluid-normal phase transition is avoided, and a reasonably good description for both of the ground-state energy and the energy of the first excited 0 sup + state is achieved. (orig.)
Technology Learning Ratios in Global Energy Models

International Nuclear Information System (INIS)

Varela, M.

2001-01-01

The process of introduction of a new technology supposes that while its production and utilisation increases, also its operation improves and its investment costs and production decreases. The accumulation of experience and learning of a new technology increase in parallel with the increase of its market share. This process is represented by the technological learning curves and the energy sector is not detached from this process of substitution of old technologies by new ones. The present paper carries out a brief revision of the main energy models that include the technology dynamics (learning). The energy scenarios, developed by global energy models, assume that the characteristics of the technologies are variables with time. But this trend is incorporated in a exogenous way in these energy models, that is to say, it is only a time function. This practice is applied to the cost indicators of the technology such as the specific investment costs or to the efficiency of the energy technologies. In the last years, the new concept of endogenous technological learning has been integrated within these global energy models. This paper examines the concept of technological learning in global energy models. It also analyses the technological dynamics of the energy system including the endogenous modelling of the process of technological progress. Finally, it makes a comparison of several of the most used global energy models (MARKAL, MESSAGE and ERIS) and, more concretely, about the use these models make of the concept of technological learning. (Author) 17 refs
Mechanism and models for collisional energy transfer in highly excited large polyatomic molecules

International Nuclear Information System (INIS)

Gilbert, R. G.

1995-01-01

Collisional energy transfer in highly excited molecules (say, 200-500 kJ mol -1 above the zero-point energy of reactant, or of product, for a recombination reaction) is reviewed. An understanding of this energy transfer is important in predicting and interpreting the pressure dependence of gas-phase rate coefficients for unimolecular and recombination reactions. For many years it was thought that this pressure dependence could be calculated from a single energy-transfer quantity, such as the average energy transferred per collision. However, the discovery of 'super collisions' (a small but significant fraction of collisions which transfer abnormally large amounts of energy) means that this simplistic approach needs some revision. The 'ordinary' (non-super) component of the distribution function for collisional energy transfer can be quantified either by empirical models (e.g., an exponential-down functional form) or by models with a physical basis, such as biased random walk (applicable to monatomic or diatomic collision partners) or ergodic (for polyatomic collision partners) treatments. The latter two models enable approximate expressions for the average energy transfer to be estimated from readily available molecular parameters. Rotational energy transfer, important for finding the pressure dependence for recombination reactions, can for these purposes usually be taken as transferring sufficient energy so that the explicit functional form is not required to predict the pressure dependence. The mechanism of 'ordinary' energy transfer seems to be dominated by low-frequency modes of the substrate, whereby there is sufficient time during a vibrational period for significant energy flow between the collision partners. Super collisions may involve sudden energy flow as an outer atom of the substrate is squashed between the substrate and the bath gas, and then is moved away from the interaction by large-amplitude motion such as a ring vibration or a rotation; improved
Model documentation report: Transportation sector model of the National Energy Modeling System

Energy Technology Data Exchange (ETDEWEB)

1994-03-01

This report documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Transportation Model (TRAN). The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated by the model. This document serves three purposes. First, it is a reference document providing a detailed description of TRAN for model analysts, users, and the public. Second, this report meets the legal requirements of the Energy Information Administration (EIA) to provide adequate documentation in support of its statistical and forecast reports (Public Law 93-275, 57(b)(1)). Third, it permits continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements.
A comparison of observation-level random effect and Beta-Binomial models for modelling overdispersion in Binomial data in ecology & evolution.

Science.gov (United States)

Harrison, Xavier A

2015-01-01

Overdispersion is a common feature of models of biological data, but researchers often fail to model the excess variation driving the overdispersion, resulting in biased parameter estimates and standard errors. Quantifying and modeling overdispersion when it is present is therefore critical for robust biological inference. One means to account for overdispersion is to add an observation-level random effect (OLRE) to a model, where each data point receives a unique level of a random effect that can absorb the extra-parametric variation in the data. Although some studies have investigated the utility of OLRE to model overdispersion in Poisson count data, studies doing so for Binomial proportion data are scarce. Here I use a simulation approach to investigate the ability of both OLRE models and Beta-Binomial models to recover unbiased parameter estimates in mixed effects models of Binomial data under various degrees of overdispersion. In addition, as ecologists often fit random intercept terms to models when the random effect sample size is low (model types under a range of random effect sample sizes when overdispersion is present. Simulation results revealed that the efficacy of OLRE depends on the process that generated the overdispersion; OLRE failed to cope with overdispersion generated from a Beta-Binomial mixture model, leading to biased slope and intercept estimates, but performed well for overdispersion generated by adding random noise to the linear predictor. Comparison of parameter estimates from an OLRE model with those from its corresponding Beta-Binomial model readily identified when OLRE were performing poorly due to disagreement between effect sizes, and this strategy should be employed whenever OLRE are used for Binomial data to assess their reliability. Beta-Binomial models performed well across all contexts, but showed a tendency to underestimate effect sizes when modelling non-Beta-Binomial data. Finally, both OLRE and Beta-Binomial models performed

Beyond the random-phase approximation for the electron correlation energy: the importance of single excitations.

Science.gov (United States)

Ren, Xinguo; Tkatchenko, Alexandre; Rinke, Patrick; Scheffler, Matthias

2011-04-15

The random-phase approximation (RPA) for the electron correlation energy, combined with the exact-exchange (EX) energy, represents the state-of-the-art exchange-correlation functional within density-functional theory. However, the standard RPA practice--evaluating both the EX and the RPA correlation energies using Kohn-Sham (KS) orbitals from local or semilocal exchange-correlation functionals--leads to a systematic underbinding of molecules and solids. Here we demonstrate that this behavior can be corrected by adding a "single excitation" contribution, so far not included in the standard RPA scheme. A similar improvement can also be achieved by replacing the non-self-consistent EX total energy by the corresponding self-consistent Hartree-Fock total energy, while retaining the RPA correlation energy evaluated using KS orbitals. Both schemes achieve chemical accuracy for a standard benchmark set of noncovalent intermolecular interactions.
Universality for 1d Random Band Matrices: Sigma-Model Approximation

Science.gov (United States)

Shcherbina, Mariya; Shcherbina, Tatyana

2018-02-01

The paper continues the development of the rigorous supersymmetric transfer matrix approach to the random band matrices started in (J Stat Phys 164:1233-1260, 2016; Commun Math Phys 351:1009-1044, 2017). We consider random Hermitian block band matrices consisting of W× W random Gaussian blocks (parametrized by j,k \\in Λ =[1,n]^d\\cap Z^d ) with a fixed entry's variance J_{jk}=δ _{j,k}W^{-1}+β Δ _{j,k}W^{-2} , β >0 in each block. Taking the limit W→ ∞ with fixed n and β , we derive the sigma-model approximation of the second correlation function similar to Efetov's one. Then, considering the limit β , n→ ∞, we prove that in the dimension d=1 the behaviour of the sigma-model approximation in the bulk of the spectrum, as β ≫ n , is determined by the classical Wigner-Dyson statistics.
Exploring the Influence of Neighborhood Characteristics on Burglary Risks: A Bayesian Random Effects Modeling Approach

Directory of Open Access Journals (Sweden)

Hongqiang Liu

2016-06-01

Full Text Available A Bayesian random effects modeling approach was used to examine the influence of neighborhood characteristics on burglary risks in Jianghan District, Wuhan, China. This random effects model is essentially spatial; a spatially structured random effects term and an unstructured random effects term are added to the traditional non-spatial Poisson regression model. Based on social disorganization and routine activity theories, five covariates extracted from the available data at the neighborhood level were used in the modeling. Three regression models were fitted and compared by the deviance information criterion to identify which model best fit our data. A comparison of the results from the three models indicates that the Bayesian random effects model is superior to the non-spatial models in fitting the data and estimating regression coefficients. Our results also show that neighborhoods with above average bar density and department store density have higher burglary risks. Neighborhood-specific burglary risks and posterior probabilities of neighborhoods having a burglary risk greater than 1.0 were mapped, indicating the neighborhoods that should warrant more attention and be prioritized for crime intervention and reduction. Implications and limitations of the study are discussed in our concluding section.
Rapid Energy Modeling Workflow Demonstration Project

Science.gov (United States)

2014-01-01

app FormIt for conceptual modeling with further refinement available in Revit or Vasari. Modeling can also be done in Revit (detailed and conceptual...referenced building model while in the field. • Autodesk® Revit is a BIM software application with integrated energy and carbon analyses driven by Green...FormIt, Revit and Vasari, and (3) comparative analysis. The energy results of these building analyses are represented as annual energy use for natural
Policy modeling for industrial energy use

Energy Technology Data Exchange (ETDEWEB)

Worrell, Ernst; Park, Hi-Chun; Lee, Sang-Gon; Jung, Yonghun; Kato, Hiroyuki; Ramesohl, Stephan; Boyd, Gale; Eichhammer, Wolfgang; Nyboer, John; Jaccard, Mark; Nordqvist, Joakim; Boyd, Christopher; Klee, Howard; Anglani, Norma; Biermans, Gijs

2003-03-01

The international workshop on Policy Modeling for Industrial Energy Use was jointly organized by EETA (Professional Network for Engineering Economic Technology Analysis) and INEDIS (International Network for Energy Demand Analysis in the Industrial Sector). The workshop has helped to layout the needs and challenges to include policy more explicitly in energy-efficiency modeling. The current state-of-the-art models have a proven track record in forecasting future trends under conditions similar to those faced in the recent past. However, the future of energy policy in a climate-restrained world is likely to demand different and additional services to be provided by energy modelers. In this workshop some of the international models used to make energy consumption forecasts have been discussed as well as innovations to enable the modeling of policy scenarios. This was followed by the discussion of future challenges, new insights in the data needed to determine the inputs into energy model s, and methods to incorporate decision making and policy in the models. Based on the discussion the workshop participants came to the following conclusions and recommendations: Current energy models are already complex, and it is already difficult to collect the model inputs. Hence, new approaches should be transparent and not lead to extremely complex models that try to ''do everything''. The model structure will be determined by the questions that need to be answered. A good understanding of the decision making framework of policy makers and clear communication on the needs are essential to make any future energy modeling effort successful. There is a need to better understand the effects of policy on future energy use, emissions and the economy. To allow the inclusion of policy instruments in models, evaluation of programs and instruments is essential, and need to be included in the policy instrument design. Increased efforts are needed to better understand the
Model based energy benchmarking for glass furnace

International Nuclear Information System (INIS)

Sardeshpande, Vishal; Gaitonde, U.N.; Banerjee, Rangan

2007-01-01

Energy benchmarking of processes is important for setting energy efficiency targets and planning energy management strategies. Most approaches used for energy benchmarking are based on statistical methods by comparing with a sample of existing plants. This paper presents a model based approach for benchmarking of energy intensive industrial processes and illustrates this approach for industrial glass furnaces. A simulation model for a glass furnace is developed using mass and energy balances, and heat loss equations for the different zones and empirical equations based on operating practices. The model is checked with field data from end fired industrial glass furnaces in India. The simulation model enables calculation of the energy performance of a given furnace design. The model results show the potential for improvement and the impact of different operating and design preferences on specific energy consumption. A case study for a 100 TPD end fired furnace is presented. An achievable minimum energy consumption of about 3830 kJ/kg is estimated for this furnace. The useful heat carried by glass is about 53% of the heat supplied by the fuel. Actual furnaces operating at these production scales have a potential for reduction in energy consumption of about 20-25%
Applicability of the condensed-random-walk Monte Carlo method at low energies in high-Z materials

International Nuclear Information System (INIS)

Berger, Martin J.

1998-01-01

The predictions of several Monte Carlo codes were compared with each other and with experimental results pertaining to the penetration of through gold foils of electrons incident with energies from 128 to 8 keV. The main purpose was to demonstrate that reflection and transmission coefficients, for number and energy, can be estimated reliably with a simple Monte Carlo code based on the condensed-random-walk and continuous-slowing-down approximations
Modeling Energy and Development : An Evaluation of Models and Concepts

NARCIS (Netherlands)

Ruijven, Bas van; Urban, Frauke; Benders, René M.J.; Moll, Henri C.; Sluijs, Jeroen P. van der; Vries, Bert de; Vuuren, Detlef P. van

2008-01-01

Most global energy models are developed by institutes from developed countries focusing primarily oil issues that are important in industrialized countries. Evaluation of the results for Asia of the IPCC/SRES models shows that broad concepts of energy and development. the energy ladder and the
A comparison of observation-level random effect and Beta-Binomial models for modelling overdispersion in Binomial data in ecology & evolution

Directory of Open Access Journals (Sweden)

Xavier A. Harrison

2015-07-01

Full Text Available Overdispersion is a common feature of models of biological data, but researchers often fail to model the excess variation driving the overdispersion, resulting in biased parameter estimates and standard errors. Quantifying and modeling overdispersion when it is present is therefore critical for robust biological inference. One means to account for overdispersion is to add an observation-level random effect (OLRE to a model, where each data point receives a unique level of a random effect that can absorb the extra-parametric variation in the data. Although some studies have investigated the utility of OLRE to model overdispersion in Poisson count data, studies doing so for Binomial proportion data are scarce. Here I use a simulation approach to investigate the ability of both OLRE models and Beta-Binomial models to recover unbiased parameter estimates in mixed effects models of Binomial data under various degrees of overdispersion. In addition, as ecologists often fit random intercept terms to models when the random effect sample size is low (<5 levels, I investigate the performance of both model types under a range of random effect sample sizes when overdispersion is present. Simulation results revealed that the efficacy of OLRE depends on the process that generated the overdispersion; OLRE failed to cope with overdispersion generated from a Beta-Binomial mixture model, leading to biased slope and intercept estimates, but performed well for overdispersion generated by adding random noise to the linear predictor. Comparison of parameter estimates from an OLRE model with those from its corresponding Beta-Binomial model readily identified when OLRE were performing poorly due to disagreement between effect sizes, and this strategy should be employed whenever OLRE are used for Binomial data to assess their reliability. Beta-Binomial models performed well across all contexts, but showed a tendency to underestimate effect sizes when modelling non
Temperature-Controlled Delivery of Radiofrequency Energy in Fecal Incontinence: A Randomized Sham-Controlled Clinical Trial.

Science.gov (United States)

Visscher, Arjan P; Lam, Tze J; Meurs-Szojda, Maria M; Felt-Bersma, Richelle J F

2017-08-01

Controlled delivery of radiofrequency energy has been suggested as treatment for fecal incontinence. The aim of this study was to determine whether the clinical response to the radiofrequency energy procedure is superior to sham in patients with fecal incontinence. This was a randomized sham-controlled clinical trial from 2008 to 2015. This study was conducted in an outpatient clinic. Forty patients with fecal incontinence in whom maximal conservative management had failed were randomly assigned to receiving either radiofrequency energy or sham procedure. Fecal incontinence was measured using the Vaizey incontinence score (range, 0-24). The impact of fecal incontinence on quality of life was measured by using the fecal incontinence quality-of-life score (range, 1-4). Measurements were performed at baseline and at 6 months. Anorectal function was evaluated using anal manometry and anorectal endosonography at baseline and at 3 months. At baseline, Vaizey incontinence score was 16.8 (SD 2.9). At t = 6 months, the radiofrequency energy group improved by 2.5 points on the Vaizey incontinence score compared with the sham group (13.2 (SD 3.1), 15.6 (SD 3.3), p = 0.02). The fecal incontinence quality-of-life score at t = 6 months was not statistically different. Anorectal function did not show any alteration. Patients with severe fecal incontinence were included in the study, thus making it difficult to generalize the results. Both radiofrequency energy and sham procedure improved the fecal incontinence score, the radiofrequency energy procedure more than sham. Although statistically significant, the clinical impact for most of the patients was negligible. Therefore, the radiofrequency energy procedure should not be recommended for patients with fecal incontinence until patient-related factors associated with treatment success are known. See Video Abstract at http://links.lww.com/DCR/A373.
An Empirical Model for Energy Storage Systems

Energy Technology Data Exchange (ETDEWEB)

Rosewater, David Martin [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Scott, Paul [TransPower, Poway, CA (United States)

2016-03-17

Improved models of energy storage systems are needed to enable the electric grid’s adaptation to increasing penetration of renewables. This paper develops a generic empirical model of energy storage system performance agnostic of type, chemistry, design or scale. Parameters for this model are calculated using test procedures adapted from the US DOE Protocol for Uniformly Measuring and Expressing the Performance of Energy Storage. We then assess the accuracy of this model for predicting the performance of the TransPower GridSaver – a 1 MW rated lithium-ion battery system that underwent laboratory experimentation and analysis. The developed model predicts a range of energy storage system performance based on the uncertainty of estimated model parameters. Finally, this model can be used to better understand the integration and coordination of energy storage on the electric grid.
Delocalization in polymer models

CERN Document Server

Jitomirskaya, S Yu; Stolz, G

2003-01-01

A polymer model is a one-dimensional Schroedinger operator composed of two finite building blocks. If the two associated transfer matrices commute, the corresponding energy is called critical. Such critical energies appear in physical models, an example being the widely studied random dimer model. Although the random models are known to have pure-point spectrum with exponentially localized eigenstates for almost every configuration of the polymers, the spreading of an initially localized wave packet is here proven to be at least diffusive for every configuration.
A lattice-model representation of continuous-time random walks

International Nuclear Information System (INIS)

Campos, Daniel; Mendez, Vicenc

2008-01-01

We report some ideas for constructing lattice models (LMs) as a discrete approach to the reaction-dispersal (RD) or reaction-random walks (RRW) models. The analysis of a rather general class of Markovian and non-Markovian processes, from the point of view of their wavefront solutions, let us show that in some regimes their macroscopic dynamics (front speed) turns out to be different from that by classical reaction-diffusion equations, which are often used as a mean-field approximation to the problem. So, the convenience of a more general framework as that given by the continuous-time random walks (CTRW) is claimed. Here we use LMs as a numerical approach in order to support that idea, while in previous works our discussion was restricted to analytical models. For the two specific cases studied here, we derive and analyze the mean-field expressions for our LMs. As a result, we are able to provide some links between the numerical and analytical approaches studied
A lattice-model representation of continuous-time random walks

Energy Technology Data Exchange (ETDEWEB)

Campos, Daniel [School of Mathematics, Department of Applied Mathematics, University of Manchester, Manchester M60 1QD (United Kingdom); Mendez, Vicenc [Grup de Fisica Estadistica, Departament de Fisica, Universitat Autonoma de Barcelona, 08193 Bellaterra (Barcelona) (Spain)], E-mail: daniel.campos@uab.es, E-mail: vicenc.mendez@uab.es

2008-02-29

We report some ideas for constructing lattice models (LMs) as a discrete approach to the reaction-dispersal (RD) or reaction-random walks (RRW) models. The analysis of a rather general class of Markovian and non-Markovian processes, from the point of view of their wavefront solutions, let us show that in some regimes their macroscopic dynamics (front speed) turns out to be different from that by classical reaction-diffusion equations, which are often used as a mean-field approximation to the problem. So, the convenience of a more general framework as that given by the continuous-time random walks (CTRW) is claimed. Here we use LMs as a numerical approach in order to support that idea, while in previous works our discussion was restricted to analytical models. For the two specific cases studied here, we derive and analyze the mean-field expressions for our LMs. As a result, we are able to provide some links between the numerical and analytical approaches studied.
Modelling the energy transition in cities

Energy Technology Data Exchange (ETDEWEB)

Huber, Felix [Wuppertal Univ. (Germany). Dept. of Civil Engineering; Schwarze, Bjoern; Spiekermann, Klaus; Wegener, Michael [Spiekermann und Wegener Urban and Regional Research, Dortmund (Germany)

2013-09-01

The history of cities is a history of energy transitions. In the medieval city heating and cooking occurred with wood and peat. The growth of the industrial city in the 19th century was built on coal and electricity. The sprawling metropolis of the 20th century was made possible by oil and gas. How will the city of the 21st century look after the next energy transition from fossil to renewable energy? This paper reports on the extension of an urban land-use transport interaction model to a model of the energy transition in the Ruhr Area, a five-million agglomeration in Germany. The paper presents the planned model extensions and how they are to be integrated into the model and shows first preliminary results.
Self-dual random-plaquette gauge model and the quantum toric code

Science.gov (United States)

Takeda, Koujin; Nishimori, Hidetoshi

2004-05-01

We study the four-dimensional Z2 random-plaquette lattice gauge theory as a model of topological quantum memory, the toric code in particular. In this model, the procedure of quantum error correction works properly in the ordered (Higgs) phase, and phase boundary between the ordered (Higgs) and disordered (confinement) phases gives the accuracy threshold of error correction. Using self-duality of the model in conjunction with the replica method, we show that this model has exactly the same mathematical structure as that of the two-dimensional random-bond Ising model, which has been studied very extensively. This observation enables us to derive a conjecture on the exact location of the multicritical point (accuracy threshold) of the model, pc=0.889972…, and leads to several nontrivial results including bounds on the accuracy threshold in three dimensions.
Self-dual random-plaquette gauge model and the quantum toric code

International Nuclear Information System (INIS)

Takeda, Koujin; Nishimori, Hidetoshi

2004-01-01

We study the four-dimensional Z 2 random-plaquette lattice gauge theory as a model of topological quantum memory, the toric code in particular. In this model, the procedure of quantum error correction works properly in the ordered (Higgs) phase, and phase boundary between the ordered (Higgs) and disordered (confinement) phases gives the accuracy threshold of error correction. Using self-duality of the model in conjunction with the replica method, we show that this model has exactly the same mathematical structure as that of the two-dimensional random-bond Ising model, which has been studied very extensively. This observation enables us to derive a conjecture on the exact location of the multicritical point (accuracy threshold) of the model, p c =0.889972..., and leads to several nontrivial results including bounds on the accuracy threshold in three dimensions
Model of Nordic energy market

International Nuclear Information System (INIS)

Gjelsvik, E.; Johnsen, T.; Mysen, H.T.

1992-01-01

Simulation results are given of the consumption of electricity and oil in Denmark, Norway and Sweden based on the demand section of a Nordic energy market model which is in the process of being developed in Oslo under the auspices of the Nordic Council of Ministers. The model incorporates supply, and trade between countries so that it can be analyzed how trading can contribute to goals within energy and environmental policies and to cost effective activities aimed at reducing pollution. The article deals in some detail with the subject of how taxation on carbon dioxide emission can influence pollution abatement and with energy consumption development within individual sectors in individual Northern countries. The model of energy demand is described with emphasis on the individual sectors of industry, transport, service and private households. Simulation results giving the effects of energy consumption and increased taxation on fossil fuels are given. On this background the consequences of the adaption of power plants is discussed and a sketch is given of a Nordic electric power market incorporating trading. (AB) (15 refs.)
Model documentation: Renewable Fuels Module of the National Energy Modeling System

Energy Technology Data Exchange (ETDEWEB)

1994-04-01

This report documents the objectives, analytical approach, and design of the National Energy Modeling System (NEMS) Renewable Fuels Module (RFM) as it related to the production of the 1994 Annual Energy Outlook (AEO94) forecasts. The report catalogues and describes modeling assumptions, computational methodologies, data inputs, and parameter estimation techniques. A number of offline analyses used in lieu of RFM modeling components are also described. This documentation report serves two purposes. First, it is a reference document for model analysts, model users, and the public interested in the construction and application of the RFM. Second, it meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its models. The RFM consists of six analytical submodules that represent each of the major renewable energy resources -- wood, municipal solid waste (MSW), solar energy, wind energy, geothermal energy, and alcohol fuels. Of these six, four are documented in the following chapters: municipal solid waste, wind, solar and biofuels. Geothermal and wood are not currently working components of NEMS. The purpose of the RFM is to define the technological and cost characteristics of renewable energy technologies, and to pass these characteristics to other NEMS modules for the determination of mid-term forecasted renewable energy demand.
A model for dark energy decay

Energy Technology Data Exchange (ETDEWEB)

Abdalla, Elcio, E-mail: eabdalla@usp.br [Instituto de Física, Universidade de São Paulo, CP 66318, 05315-970, São Paulo (Brazil); Graef, L.L., E-mail: leilagraef@usp.br [Instituto de Física, Universidade de São Paulo, CP 66318, 05315-970, São Paulo (Brazil); Wang, Bin, E-mail: wang_b@sjtu.edu.cn [INPAC and Department of Physics, Shanghai Jiao Tong University, 200240 Shanghai (China)

2013-11-04

We discuss a model of nonperturbative decay of dark energy. We suggest the possibility that this model can provide a mechanism from the field theory to realize the energy transfer from dark energy into dark matter, which is the requirement to alleviate the coincidence problem. The advantage of the model is the fact that it accommodates a mean life compatible with the age of the universe. We also argue that supersymmetry is a natural set up, though not essential.

Economics, modeling, planning and management of energy

International Nuclear Information System (INIS)

Rogner, H.H.; Khan, A.M.; Furlan, G.

1989-01-01

The Workshop attended by 89 participants from 40 countries aimed to provide participants with an overview of global and regional issues and to familiarize them with analytical tools and modeling techniques appropriate for the analysis and planning of national energy systems. Emphasis was placed on energy-economy-interaction, modelling for balancing energy demand and supply, technical-economic evaluation of energy supply alternatives and energy demand management. This volume presents some of the lectures delivered at the Workshop. The material has been organized in five parts under the headings General Review of Current Energy Trends, Energy and Technology Menu, Basic Analytical Approaches, Energy Modeling and Planning, and Energy Management and Policy. A separate abstract was prepared for each of the lectures presented. Refs, figs and tabs
The difference between energy consumption and energy cost: Modelling energy tariff structures for water resource recovery facilities.

Science.gov (United States)

Aymerich, I; Rieger, L; Sobhani, R; Rosso, D; Corominas, Ll

2015-09-15

The objective of this paper is to demonstrate the importance of incorporating more realistic energy cost models (based on current energy tariff structures) into existing water resource recovery facilities (WRRFs) process models when evaluating technologies and cost-saving control strategies. In this paper, we first introduce a systematic framework to model energy usage at WRRFs and a generalized structure to describe energy tariffs including the most common billing terms. Secondly, this paper introduces a detailed energy cost model based on a Spanish energy tariff structure coupled with a WRRF process model to evaluate several control strategies and provide insights into the selection of the contracted power structure. The results for a 1-year evaluation on a 115,000 population-equivalent WRRF showed monthly cost differences ranging from 7 to 30% when comparing the detailed energy cost model to an average energy price. The evaluation of different aeration control strategies also showed that using average energy prices and neglecting energy tariff structures may lead to biased conclusions when selecting operating strategies or comparing technologies or equipment. The proposed framework demonstrated that for cost minimization, control strategies should be paired with a specific optimal contracted power. Hence, the design of operational and control strategies must take into account the local energy tariff. Copyright © 2015 Elsevier Ltd. All rights reserved.
Modeling superhydrophobic surfaces comprised of random roughness

Science.gov (United States)

Samaha, M. A.; Tafreshi, H. Vahedi; Gad-El-Hak, M.

2011-11-01

We model the performance of superhydrophobic surfaces comprised of randomly distributed roughness that resembles natural surfaces, or those produced via random deposition of hydrophobic particles. Such a fabrication method is far less expensive than ordered-microstructured fabrication. The present numerical simulations are aimed at improving our understanding of the drag reduction effect and the stability of the air-water interface in terms of the microstructure parameters. For comparison and validation, we have also simulated the flow over superhydrophobic surfaces made up of aligned or staggered microposts for channel flows as well as streamwise or spanwise ridge configurations for pipe flows. The present results are compared with other theoretical and experimental studies. The numerical simulations indicate that the random distribution of surface roughness has a favorable effect on drag reduction, as long as the gas fraction is kept the same. The stability of the meniscus, however, is strongly influenced by the average spacing between the roughness peaks, which needs to be carefully examined before a surface can be recommended for fabrication. Financial support from DARPA, contract number W91CRB-10-1-0003, is acknowledged.
The transverse spin-1 Ising model with random interactions

Energy Technology Data Exchange (ETDEWEB)

Bouziane, Touria [Department of Physics, Faculty of Sciences, University of Moulay Ismail, B.P. 11201 Meknes (Morocco)], E-mail: touria582004@yahoo.fr; Saber, Mohammed [Department of Physics, Faculty of Sciences, University of Moulay Ismail, B.P. 11201 Meknes (Morocco); Dpto. Fisica Aplicada I, EUPDS (EUPDS), Plaza Europa, 1, San Sebastian 20018 (Spain)

2009-01-15

The phase diagrams of the transverse spin-1 Ising model with random interactions are investigated using a new technique in the effective field theory that employs a probability distribution within the framework of the single-site cluster theory based on the use of exact Ising spin identities. A model is adopted in which the nearest-neighbor exchange couplings are independent random variables distributed according to the law P(J{sub ij})=p{delta}(J{sub ij}-J)+(1-p){delta}(J{sub ij}-{alpha}J). General formulae, applicable to lattices with coordination number N, are given. Numerical results are presented for a simple cubic lattice. The possible reentrant phenomenon displayed by the system due to the competitive effects between exchange interactions occurs for the appropriate range of the parameter {alpha}.
Role of Statistical Random-Effects Linear Models in Personalized Medicine.

Science.gov (United States)

Diaz, Francisco J; Yeh, Hung-Wen; de Leon, Jose

2012-03-01

Some empirical studies and recent developments in pharmacokinetic theory suggest that statistical random-effects linear models are valuable tools that allow describing simultaneously patient populations as a whole and patients as individuals. This remarkable characteristic indicates that these models may be useful in the development of personalized medicine, which aims at finding treatment regimes that are appropriate for particular patients, not just appropriate for the average patient. In fact, published developments show that random-effects linear models may provide a solid theoretical framework for drug dosage individualization in chronic diseases. In particular, individualized dosages computed with these models by means of an empirical Bayesian approach may produce better results than dosages computed with some methods routinely used in therapeutic drug monitoring. This is further supported by published empirical and theoretical findings that show that random effects linear models may provide accurate representations of phase III and IV steady-state pharmacokinetic data, and may be useful for dosage computations. These models have applications in the design of clinical algorithms for drug dosage individualization in chronic diseases; in the computation of dose correction factors; computation of the minimum number of blood samples from a patient that are necessary for calculating an optimal individualized drug dosage in therapeutic drug monitoring; measure of the clinical importance of clinical, demographic, environmental or genetic covariates; study of drug-drug interactions in clinical settings; the implementation of computational tools for web-site-based evidence farming; design of pharmacogenomic studies; and in the development of a pharmacological theory of dosage individualization.
Rogeaulito: A World Energy Scenario Modeling Tool for Transparent Energy System Thinking

International Nuclear Information System (INIS)

Benichou, Léo; Mayr, Sebastian

2014-01-01

Rogeaulito is a world energy model for scenario building developed by the European think tank The Shift Project. It’s a tool to explore world energy choices from a very long-term and systematic perspective. As a key feature and novelty it computes energy supply and demand independently from each other revealing potentially missing energy supply by 2100. It is further simple to use, didactic, and open source. As such, it targets a broad user group and advocates for reproducibility and transparency in scenario modeling as well as model-based learning. Rogeaulito applies an engineering approach using disaggregated data in a spreadsheet model.
Rogeaulito: A World Energy Scenario Modeling Tool for Transparent Energy System Thinking

Energy Technology Data Exchange (ETDEWEB)

Benichou, Léo, E-mail: leo.benichou@theshiftproject.org [The Shift Project, Paris (France); Mayr, Sebastian, E-mail: communication@theshiftproject.org [Paris School of International Affairs, Sciences Po., Paris (France)

2014-01-13

Rogeaulito is a world energy model for scenario building developed by the European think tank The Shift Project. It’s a tool to explore world energy choices from a very long-term and systematic perspective. As a key feature and novelty it computes energy supply and demand independently from each other revealing potentially missing energy supply by 2100. It is further simple to use, didactic, and open source. As such, it targets a broad user group and advocates for reproducibility and transparency in scenario modeling as well as model-based learning. Rogeaulito applies an engineering approach using disaggregated data in a spreadsheet model.
Discrete random walk models for space-time fractional diffusion

International Nuclear Information System (INIS)

Gorenflo, Rudolf; Mainardi, Francesco; Moretti, Daniele; Pagnini, Gianni; Paradisi, Paolo

2002-01-01

A physical-mathematical approach to anomalous diffusion may be based on generalized diffusion equations (containing derivatives of fractional order in space or/and time) and related random walk models. By space-time fractional diffusion equation we mean an evolution equation obtained from the standard linear diffusion equation by replacing the second-order space derivative with a Riesz-Feller derivative of order α is part of (0,2] and skewness θ (moduleθ≤{α,2-α}), and the first-order time derivative with a Caputo derivative of order β is part of (0,1]. Such evolution equation implies for the flux a fractional Fick's law which accounts for spatial and temporal non-locality. The fundamental solution (for the Cauchy problem) of the fractional diffusion equation can be interpreted as a probability density evolving in time of a peculiar self-similar stochastic process that we view as a generalized diffusion process. By adopting appropriate finite-difference schemes of solution, we generate models of random walk discrete in space and time suitable for simulating random variables whose spatial probability density evolves in time according to this fractional diffusion equation
Energy Systems Modelling Research and Analysis

DEFF Research Database (Denmark)

Møller Andersen, Frits; Alberg Østergaard, Poul

2015-01-01

This editorial introduces the seventh volume of the International Journal of Sustainable Energy Planning and Management. The volume presents part of the outcome of the project Energy Systems Modelling Research and Analysis (ENSYMORA) funded by the Danish Innovation Fund. The project carried out b...... by 11 university and industry partners has improved the basis for decision-making within energy planning and energy scenario making by providing new and improved tools and methods for energy systems analyses.......This editorial introduces the seventh volume of the International Journal of Sustainable Energy Planning and Management. The volume presents part of the outcome of the project Energy Systems Modelling Research and Analysis (ENSYMORA) funded by the Danish Innovation Fund. The project carried out...
Quantification of uncertainties in turbulence modeling: A comparison of physics-based and random matrix theoretic approaches

International Nuclear Information System (INIS)

Wang, Jian-Xun; Sun, Rui; Xiao, Heng

2016-01-01

Highlights: • Compared physics-based and random matrix methods to quantify RANS model uncertainty. • Demonstrated applications of both methods in channel ow over periodic hills. • Examined the amount of information introduced in the physics-based approach. • Discussed implications to modeling turbulence in both near-wall and separated regions. - Abstract: Numerical models based on Reynolds-Averaged Navier-Stokes (RANS) equations are widely used in engineering turbulence modeling. However, the RANS predictions have large model-form uncertainties for many complex flows, e.g., those with non-parallel shear layers or strong mean flow curvature. Quantification of these large uncertainties originating from the modeled Reynolds stresses has attracted attention in the turbulence modeling community. Recently, a physics-based Bayesian framework for quantifying model-form uncertainties has been proposed with successful applications to several flows. Nonetheless, how to specify proper priors without introducing unwarranted, artificial information remains challenging to the current form of the physics-based approach. Another recently proposed method based on random matrix theory provides the prior distributions with maximum entropy, which is an alternative for model-form uncertainty quantification in RANS simulations. This method has better mathematical rigorousness and provides the most non-committal prior distributions without introducing artificial constraints. On the other hand, the physics-based approach has the advantages of being more flexible to incorporate available physical insights. In this work, we compare and discuss the advantages and disadvantages of the two approaches on model-form uncertainty quantification. In addition, we utilize the random matrix theoretic approach to assess and possibly improve the specification of priors used in the physics-based approach. The comparison is conducted through a test case using a canonical flow, the flow past
Directory of Energy Information Administration models 1996

Energy Technology Data Exchange (ETDEWEB)

NONE

1996-07-01

This directory revises and updates the Directory of Energy Information Administration Models 1995, DOE/EIA-0293(95), Energy Information Administration (EIA), U.S. Department of Energy, July 1995. Four models have been deleted in this directory as they are no longer being used: (1) Market Penetration Model for Ground-Water Heat Pump Systems (MPGWHP); (2) Market Penetration Model for Residential Rooftop PV Systems (MPRESPV-PC); (3) Market Penetration Model for Active and Passive Solar Technologies (MPSOLARPC); and (4) Revenue Requirements Modeling System (RRMS).
Shape Modelling Using Markov Random Field Restoration of Point Correspondences

DEFF Research Database (Denmark)

Paulsen, Rasmus Reinhold; Hilger, Klaus Baggesen

2003-01-01

A method for building statistical point distribution models is proposed. The novelty in this paper is the adaption of Markov random field regularization of the correspondence field over the set of shapes. The new approach leads to a generative model that produces highly homogeneous polygonized sh...
A spatial error model with continuous random effects and an application to growth convergence

Science.gov (United States)

Laurini, Márcio Poletti

2017-10-01

We propose a spatial error model with continuous random effects based on Matérn covariance functions and apply this model for the analysis of income convergence processes (β -convergence). The use of a model with continuous random effects permits a clearer visualization and interpretation of the spatial dependency patterns, avoids the problems of defining neighborhoods in spatial econometrics models, and allows projecting the spatial effects for every possible location in the continuous space, circumventing the existing aggregations in discrete lattice representations. We apply this model approach to analyze the economic growth of Brazilian municipalities between 1991 and 2010 using unconditional and conditional formulations and a spatiotemporal model of convergence. The results indicate that the estimated spatial random effects are consistent with the existence of income convergence clubs for Brazilian municipalities in this period.
Rogeaulito: a world energy scenario modeling tool for transparent energy system thinking

Directory of Open Access Journals (Sweden)

Léo eBenichou

2014-01-01

Full Text Available Rogeaulito is a world energy model for scenario building developed by the European think tank The Shift Project. It’s a tool to explore world energy choices from a very long-term and systematic perspective. As a key feature and novelty it computes energy supply and demand independently from each other revealing potentially missing energy supply by 2100. It is further simple to use, didactic and open source. As such, it targets a broad user group and advocates for reproducibility and transparency in scenario modeling as well as model-based learning. Rogeaulito applies an engineering approach using disaggregated data in a spreadsheet model.
Estimating overall exposure effects for the clustered and censored outcome using random effect Tobit regression models.

Science.gov (United States)

Wang, Wei; Griswold, Michael E

2016-11-30

The random effect Tobit model is a regression model that accommodates both left- and/or right-censoring and within-cluster dependence of the outcome variable. Regression coefficients of random effect Tobit models have conditional interpretations on a constructed latent dependent variable and do not provide inference of overall exposure effects on the original outcome scale. Marginalized random effects model (MREM) permits likelihood-based estimation of marginal mean parameters for the clustered data. For random effect Tobit models, we extend the MREM to marginalize over both the random effects and the normal space and boundary components of the censored response to estimate overall exposure effects at population level. We also extend the 'Average Predicted Value' method to estimate the model-predicted marginal means for each person under different exposure status in a designated reference group by integrating over the random effects and then use the calculated difference to assess the overall exposure effect. The maximum likelihood estimation is proposed utilizing a quasi-Newton optimization algorithm with Gauss-Hermite quadrature to approximate the integration of the random effects. We use these methods to carefully analyze two real datasets. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
Calibration of Discrete Random Walk (DRW) Model via G.I Taylor's Dispersion Theory

Science.gov (United States)

Javaherchi, Teymour; Aliseda, Alberto

2012-11-01

Prediction of particle dispersion in turbulent flows is still an important challenge with many applications to environmental, as well as industrial, fluid mechanics. Several models of dispersion have been developed to predict particle trajectories and their relative velocities, in combination with a RANS-based simulation of the background flow. The interaction of the particles with the velocity fluctuations at different turbulent scales represents a significant difficulty in generalizing the models to the wide range of flows where they are used. We focus our attention on the Discrete Random Walk (DRW) model applied to flow in a channel, particularly to the selection of eddies lifetimes as realizations of a Poisson distribution with a mean value proportional to κ / ɛ . We present a general method to determine the constant of this proportionality by matching the DRW model dispersion predictions for fluid element and particle dispersion to G.I Taylor's classical dispersion theory. This model parameter is critical to the magnitude of predicted dispersion. A case study of its influence on sedimentation of suspended particles in a tidal channel with an array of Marine Hydrokinetic (MHK) turbines highlights the dependency of results on this time scale parameter. Support from US DOE through the Northwest National Marine Renewable Energy Center, a UW-OSU partnership.
Effect of wind energy system performance on optimal renewable energy model - an analysis

International Nuclear Information System (INIS)

Iniyan, S.; Jagadeesan, T.R.

1998-01-01

The Optimal Renewable Energy Model (OREM) has been developed to determine the optimum level of renewable energy sources utilisation in India for the year 2020-21. The model aims at minimising cost/efficiency ratio and determines the optimum allocation of different renewable energy sources for various end-uses. The extent of social acceptance level, potential limit, demand and reliability will decide the renewable energy distribution pattern and are hence used as constraints in the model. In this paper, the performance and reliability of wind energy system and its effects on OREM model has been analysed. The demonstration windfarm (4 MW) which is situated in Muppandal, a village in the southern part of India, has been selected for the study. The windfarm has 20 wind turbine machines of 200 KW capacity . The average technical availability, real availability and capacity factor have been analysed from 1991 to 1995 and they are found to be 94.1%, 76.4% and 25.5% respectively. The reliability factor of wind energy systems is found to be 0.5 at 10,000 hours. The OREM model is analysed considering the above said factors for wind energy system, solar energy system and biomass energy systems. The model selects wind energy for pumping end-use to an extent of 0.3153 x10 15 KJ. (Author)
Investigating Facebook Groups through a Random Graph Model

OpenAIRE

Dinithi Pallegedara; Lei Pan

2014-01-01

Facebook disseminates messages for billions of users everyday. Though there are log files stored on central servers, law enforcement agencies outside of the U.S. cannot easily acquire server log files from Facebook. This work models Facebook user groups by using a random graph model. Our aim is to facilitate detectives quickly estimating the size of a Facebook group with which a suspect is involved. We estimate this group size according to the number of immediate friends and the number of ext...
Least squares estimation in a simple random coefficient autoregressive model

DEFF Research Database (Denmark)

Johansen, S; Lange, T

2013-01-01

The question we discuss is whether a simple random coefficient autoregressive model with infinite variance can create the long swings, or persistence, which are observed in many macroeconomic variables. The model is defined by yt=stρyt−1+εt,t=1,…,n, where st is an i.i.d. binary variable with p...... we prove the curious result that View the MathML source. The proof applies the notion of a tail index of sums of positive random variables with infinite variance to find the order of magnitude of View the MathML source and View the MathML source and hence the limit of View the MathML source...
The causal role of breakfast in energy balance and health: a randomized controlled trial in obese adults.

Science.gov (United States)

Chowdhury, Enhad A; Richardson, Judith D; Holman, Geoffrey D; Tsintzas, Kostas; Thompson, Dylan; Betts, James A

2016-03-01

The causal nature of associations between breakfast and health remain unclear in obese individuals. We sought to conduct a randomized controlled trial to examine causal links between breakfast habits and components of energy balance in free-living obese humans. The Bath Breakfast Project is a randomized controlled trial with repeated measures at baseline and follow-up among a cohort in South West England aged 21-60 y with dual-energy X-ray absorptiometry-derived fat mass indexes of ≥13 kg/m(2) for women (n = 15) and ≥9 kg/m(2) for men (n = 8). Components of energy balance (resting metabolic rate, physical activity thermogenesis, diet-induced thermogenesis, and energy intake) were measured under free-living conditions with random allocation to daily breakfast (≥700 kcal before 1100) or extended fasting (0 kcal until 1200) for 6 wk, with baseline and follow-up measures of health markers (e.g., hematology/adipose biopsies). Breakfast resulted in greater physical activity thermogenesis during the morning than when fasting during that period (difference: 188 kcal/d; 95% CI: 40, 335) but without any consistent effect on 24-h physical activity thermogenesis (difference: 272 kcal/d; 95% CI: -254, 798). Energy intake was not significantly greater with breakfast than fasting (difference: 338 kcal/d; 95% CI: -313, 988). Body mass increased across both groups over time but with no treatment effects on body composition or any change in resting metabolic rate (stable within 8 kcal/d). Metabolic/cardiovascular health also did not respond to treatments, except for a reduced insulinemic response to an oral-glucose-tolerance test over time with daily breakfast relative to an increase with daily fasting (P = 0.05). In obese adults, daily breakfast leads to greater physical activity during the morning, whereas morning fasting results in partial dietary compensation (i.e., greater energy intake) later in the day. There were no differences between groups in weight change and most

Extending the random-phase approximation for electronic correlation energies: the renormalized adiabatic local density approximation

DEFF Research Database (Denmark)

Olsen, Thomas; Thygesen, Kristian S.

2012-01-01

The adiabatic connection fluctuation-dissipation theorem with the random phase approximation (RPA) has recently been applied with success to obtain correlation energies of a variety of chemical and solid state systems. The main merit of this approach is the improved description of dispersive forces...... while chemical bond strengths and absolute correlation energies are systematically underestimated. In this work we extend the RPA by including a parameter-free renormalized version of the adiabatic local-density (ALDA) exchange-correlation kernel. The renormalization consists of a (local) truncation...... of the ALDA kernel for wave vectors q > 2kF, which is found to yield excellent results for the homogeneous electron gas. In addition, the kernel significantly improves both the absolute correlation energies and atomization energies of small molecules over RPA and ALDA. The renormalization can...
A cultural model of household energy consumption

International Nuclear Information System (INIS)

Lutzenhiser, Loren

1992-01-01

In this paper, we consider the development of demand-side research, from an early interest in conservation behavior to a later focus on physical, economic, psychological and social models of energy consumption. Unfortunately, none of these models account satisfactorily for measured energy consumption in the residential sector. Growing interest in the end-uses of energy (e.g. in support of load forecasting, demand-side management and least-cost utility planning), increasing international studies of energy use, and continuing work in the energy and lifestyles research tradition now support an emerging cultural perspective on household energy use. The ecological foundations of the cultural model and its applications in energy research are discussed, along with some of the analytic consequences of this approach. (author)
Bridging Weighted Rules and Graph Random Walks for Statistical Relational Models

Directory of Open Access Journals (Sweden)

Seyed Mehran Kazemi

2018-02-01

Full Text Available The aim of statistical relational learning is to learn statistical models from relational or graph-structured data. Three main statistical relational learning paradigms include weighted rule learning, random walks on graphs, and tensor factorization. These paradigms have been mostly developed and studied in isolation for many years, with few works attempting at understanding the relationship among them or combining them. In this article, we study the relationship between the path ranking algorithm (PRA, one of the most well-known relational learning methods in the graph random walk paradigm, and relational logistic regression (RLR, one of the recent developments in weighted rule learning. We provide a simple way to normalize relations and prove that relational logistic regression using normalized relations generalizes the path ranking algorithm. This result provides a better understanding of relational learning, especially for the weighted rule learning and graph random walk paradigms. It opens up the possibility of using the more flexible RLR rules within PRA models and even generalizing both by including normalized and unnormalized relations in the same model.
The ising model on the dynamical triangulated random surface

International Nuclear Information System (INIS)

Aleinov, I.D.; Migelal, A.A.; Zmushkow, U.V.

1990-01-01

The critical properties of Ising model on the dynamical triangulated random surface embedded in D-dimensional Euclidean space are investigated. The strong coupling expansion method is used. The transition to thermodynamical limit is performed by means of continuous fractions
Energy modeling: nuclear energy as China's main energy after 2040

International Nuclear Information System (INIS)

Guo Xingqu

1987-01-01

According to the energy modeling and the strategic forecast of China's economic development and population, the energy demand in China in the coming century has been calculated yearly by computer simulation. It is shown by the calculation results that the primary energy consumption in 2050 will be 3.37-4.25 times as that of 2000. The fossil energy will still be the main energy during the early stage of 21st century, but it will be cut down rapidly since 2020s as its annual consumption is increased to 1.656-2.044 x 10 9 tce/a. Because the fossil fuel ressources in China are limited, more and more fossil fuel will be mainly turned to chemical products, and the environmental pollution will be serious if we still use the fossil as a main fuel widely. The amount of renewable energy will be increasing, but its share in the primary energy consumption will be cut down from 36% to about 20% during the first half of next century and then will maintain this portion. In this case, the nuclear energy will be developed rapidly during the early stage of next century and will become the main energy since 2040. The methodology of energy forecast has also been reviewed
Metamaterial Model of Tachyonic Dark Energy

Directory of Open Access Journals (Sweden)

Igor I. Smolyaninov

2014-02-01

Full Text Available Dark energy with negative pressure and positive energy density is believed to be responsible for the accelerated expansion of the universe. Quite a few theoretical models of dark energy are based on tachyonic fields interacting with itself and normal (bradyonic matter. Here, we propose an experimental model of tachyonic dark energy based on hyperbolic metamaterials. Wave equation describing propagation of extraordinary light inside hyperbolic metamaterials exhibits 2 + 1 dimensional Lorentz symmetry. The role of time in the corresponding effective 3D Minkowski spacetime is played by the spatial coordinate aligned with the optical axis of the metamaterial. Nonlinear optical Kerr effect bends this spacetime resulting in effective gravitational force between extraordinary photons. We demonstrate that this model has a self-interacting tachyonic sector having negative effective pressure and positive effective energy density. Moreover, a composite multilayer SiC-Si hyperbolic metamaterial exhibits closely separated tachyonic and bradyonic sectors in the long wavelength infrared range. This system may be used as a laboratory model of inflation and late time acceleration of the universe.
A Statistical Model for Energy Intensity

Directory of Open Access Journals (Sweden)

Marjaneh Issapour

2012-12-01

Full Text Available A promising approach to improve scientific literacy in regards to global warming and climate change is using a simulation as part of a science education course. The simulation needs to employ scientific analysis of actual data from internationally accepted and reputable databases to demonstrate the reality of the current climate change situation. One of the most important criteria for using a simulation in a science education course is the fidelity of the model. The realism of the events and consequences modeled in the simulation is significant as well. Therefore, all underlying equations and algorithms used in the simulation must have real-world scientific basis. The "Energy Choices" simulation is one such simulation. The focus of this paper is the development of a mathematical model for "Energy Intensity" as a part of the overall system dynamics in "Energy Choices" simulation. This model will define the "Energy Intensity" as a function of other independent variables that can be manipulated by users of the simulation. The relationship discovered by this research will be applied to an algorithm in the "Energy Choices" simulation.
Expand the Modeling Capabilities of DOE's EnergyPlus Building Energy Simulation Program

Energy Technology Data Exchange (ETDEWEB)

Don Shirey

2008-02-28

EnergyPlus{trademark} is a new generation computer software analysis tool that has been developed, tested, and commercialized to support DOE's Building Technologies (BT) Program in terms of whole-building, component, and systems R&D (http://www.energyplus.gov). It is also being used to support evaluation and decision making of zero energy building (ZEB) energy efficiency and supply technologies during new building design and existing building retrofits. Version 1.0 of EnergyPlus was released in April 2001, followed by semiannual updated versions over the ensuing seven-year period. This report summarizes work performed by the University of Central Florida's Florida Solar Energy Center (UCF/FSEC) to expand the modeling capabilities of EnergyPlus. The project tasks involved implementing, testing, and documenting the following new features or enhancement of existing features: (1) A model for packaged terminal heat pumps; (2) A model for gas engine-driven heat pumps with waste heat recovery; (3) Proper modeling of window screens; (4) Integrating and streamlining EnergyPlus air flow modeling capabilities; (5) Comfort-based controls for cooling and heating systems; and (6) An improved model for microturbine power generation with heat recovery. UCF/FSEC located existing mathematical models or generated new model for these features and incorporated them into EnergyPlus. The existing or new models were (re)written using Fortran 90/95 programming language and were integrated within EnergyPlus in accordance with the EnergyPlus Programming Standard and Module Developer's Guide. Each model/feature was thoroughly tested and identified errors were repaired. Upon completion of each model implementation, the existing EnergyPlus documentation (e.g., Input Output Reference and Engineering Document) was updated with information describing the new or enhanced feature. Reference data sets were generated for several of the features to aid program users in selecting proper
The Effects of the SUN Project on Teacher Knowledge and Self-Efficacy Regarding Biological Energy Transfer Are Significant and Long-Lasting: Results of a Randomized Controlled Trial

Science.gov (United States)

Batiza, Ann Finney; Gruhl, Mary; Zhang, Bo; Harrington, Tom; Roberts, Marisa; LaFlamme, Donna; Haasch, Mary Anne; Knopp, Jonathan; Vogt, Gina; Goodsell, David; Hagedorn, Eric; Marcey, David; Hoelzer, Mark; Nelson, Dave

2013-01-01

Biological energy flow has been notoriously difficult to teach. Our approach to this topic relies on abiotic and biotic examples of the energy released by moving electrons in thermodynamically spontaneous reactions. A series of analogical model-building experiences was supported with common language and representations including manipulatives. These materials were designed to help learners understand why electrons move in a hydrogen explosion and hydrogen fuel cell, so they could ultimately understand the rationale for energy transfer in the mitochondrion and the chloroplast. High school biology teachers attended a 2-wk Students Understanding eNergy (SUN) workshop during a randomized controlled trial. These treatment group teachers then took hydrogen fuel cells, manipulatives, and other materials into their regular biology classrooms. In this paper, we report significant gains in teacher knowledge and self-efficacy regarding biological energy transfer in the treatment group versus randomized controls. Significant effects on treatment group teacher knowledge and self-efficacy were found not only post–SUN workshop but even 1 yr later. Teacher knowledge was measured with both a multiple-choice exam and a drawing with a written explanation. Teacher confidence in their ability to teach biological energy transfer was measured by a modified form of the Science Teaching Efficacy Belief Instrument, In-Service A. Professional development implications regarding this topic are discussed. PMID:23737635
Social aggregation in pea aphids: experiment and random walk modeling.

Directory of Open Access Journals (Sweden)

Christa Nilsen

Full Text Available From bird flocks to fish schools and ungulate herds to insect swarms, social biological aggregations are found across the natural world. An ongoing challenge in the mathematical modeling of aggregations is to strengthen the connection between models and biological data by quantifying the rules that individuals follow. We model aggregation of the pea aphid, Acyrthosiphon pisum. Specifically, we conduct experiments to track the motion of aphids walking in a featureless circular arena in order to deduce individual-level rules. We observe that each aphid transitions stochastically between a moving and a stationary state. Moving aphids follow a correlated random walk. The probabilities of motion state transitions, as well as the random walk parameters, depend strongly on distance to an aphid's nearest neighbor. For large nearest neighbor distances, when an aphid is essentially isolated, its motion is ballistic with aphids moving faster, turning less, and being less likely to stop. In contrast, for short nearest neighbor distances, aphids move more slowly, turn more, and are more likely to become stationary; this behavior constitutes an aggregation mechanism. From the experimental data, we estimate the state transition probabilities and correlated random walk parameters as a function of nearest neighbor distance. With the individual-level model established, we assess whether it reproduces the macroscopic patterns of movement at the group level. To do so, we consider three distributions, namely distance to nearest neighbor, angle to nearest neighbor, and percentage of population moving at any given time. For each of these three distributions, we compare our experimental data to the output of numerical simulations of our nearest neighbor model, and of a control model in which aphids do not interact socially. Our stochastic, social nearest neighbor model reproduces salient features of the experimental data that are not captured by the control.
The role of nuclear energy for Korean long-term energy supply strategy : application of energy demand-supply model

International Nuclear Information System (INIS)

Chae, Kyu Nam

1995-02-01

An energy demand and supply analysis is carried out to establish the future nuclear energy system of Korea in the situation of environmental restriction and resource depletion. Based on the useful energy intensity concept, a long-term energy demand forecasting model FIN2USE is developed to integrate with a supply model. The energy supply optimization model MESSAGE is improved to evaluate the role of nuclear energy system in Korean long-term energy supply strategy. Long-term demand for useful energy used as an exogeneous input of the energy supply model is derived from the trend of useful energy intensity by sectors and energy carriers. Supply-side optimization is performed for the overall energy system linked with the reactor and nuclear fuel cycle strategy. The limitation of fossil fuel resources and the CO 2 emission constraints are reflected as determinants of the future energy system. As a result of optimization of energy system using linear programming with the objective of total discounted system cost, the optimal energy system is obtained with detailed results on the nuclear sector for various scenarios. It is shown that the relative importance of nuclear energy would increase especially in the cases of CO 2 emission constraint. It is concluded that nuclear reactor strategy and fuel cycle strategy should be incorporated with national energy strategy and be changed according to environmental restriction and energy demand scenarios. It is shown that this modelling approach is suitable for a decision support system of nuclear energy policy
Energy based prediction models for building acoustics

DEFF Research Database (Denmark)

Brunskog, Jonas

2012-01-01

In order to reach robust and simplified yet accurate prediction models, energy based principle are commonly used in many fields of acoustics, especially in building acoustics. This includes simple energy flow models, the framework of statistical energy analysis (SEA) as well as more elaborated...... principles as, e.g., wave intensity analysis (WIA). The European standards for building acoustic predictions, the EN 12354 series, are based on energy flow and SEA principles. In the present paper, different energy based prediction models are discussed and critically reviewed. Special attention is placed...... on underlying basic assumptions, such as diffuse fields, high modal overlap, resonant field being dominant, etc., and the consequences of these in terms of limitations in the theory and in the practical use of the models....
Dark energy observational evidence and theoretical models

CERN Document Server

Novosyadlyj, B; Shtanov, Yu; Zhuk, A

2013-01-01

The book elucidates the current state of the dark energy problem and presents the results of the authors, who work in this area. It describes the observational evidence for the existence of dark energy, the methods and results of constraining of its parameters, modeling of dark energy by scalar fields, the space-times with extra spatial dimensions, especially Kaluza---Klein models, the braneworld models with a single extra dimension as well as the problems of positive definition of gravitational energy in General Relativity, energy conditions and consequences of their violation in the presence of dark energy. This monograph is intended for science professionals, educators and graduate students, specializing in general relativity, cosmology, field theory and particle physics.
Renewable Energy and Efficiency Modeling Analysis Partnership (REMAP): An Analysis of How Different Energy Models Addressed a Common High Renewable Energy Penetration Scenario in 2025

Energy Technology Data Exchange (ETDEWEB)

Blair, N.; Jenkin, T.; Milford, J.; Short, W.; Sullivan, P.; Evans, D.; Lieberman, E.; Goldstein, G.; Wright, E.; Jayaraman, K. R.; Venkatesh, B.; Kleiman, G.; Namovicz, C.; Smith, B.; Palmer, K.; Wiser, R.; Wood, F.

2009-09-01

Energy system modeling can be intentionally or unintentionally misused by decision-makers. This report describes how both can be minimized through careful use of models and thorough understanding of their underlying approaches and assumptions. The analysis summarized here assesses the impact that model and data choices have on forecasting energy systems by comparing seven different electric-sector models. This analysis was coordinated by the Renewable Energy and Efficiency Modeling Analysis Partnership (REMAP), a collaboration among governmental, academic, and nongovernmental participants.
Dynamic energy models and carbon mitigation policies

Science.gov (United States)

Tilley, Luke A.

In this dissertation I examine a specific class of energy models and their implications for carbon mitigation policies. The class of models includes a production function capable of reproducing the empirically observed phenomenon of short run rigidity of energy use in response to energy price changes and long run exibility of energy use in response to energy price changes. I use a theoretical model, parameterized using empirical data, to simulate economic performance under several tax regimes where taxes are levied on capital income, investment, and energy. I also investigate transitions from one tax regime to another. I find that energy taxes intended to reduce energy use can successfully achieve those goals with minimal or even positive impacts on macroeconomic performance. But the transition paths to new steady states are lengthy, making political commitment to such policies very challenging.
Visual prosthesis wireless energy transfer system optimal modeling.

Science.gov (United States)

Li, Xueping; Yang, Yuan; Gao, Yong

2014-01-16

Wireless energy transfer system is an effective way to solve the visual prosthesis energy supply problems, theoretical modeling of the system is the prerequisite to do optimal energy transfer system design. On the basis of the ideal model of the wireless energy transfer system, according to visual prosthesis application condition, the system modeling is optimized. During the optimal modeling, taking planar spiral coils as the coupling devices between energy transmitter and receiver, the effect of the parasitic capacitance of the transfer coil is considered, and especially the concept of biological capacitance is proposed to consider the influence of biological tissue on the energy transfer efficiency, resulting in the optimal modeling's more accuracy for the actual application. The simulation data of the optimal model in this paper is compared with that of the previous ideal model, the results show that under high frequency condition, the parasitic capacitance of inductance and biological capacitance considered in the optimal model could have great impact on the wireless energy transfer system. The further comparison with the experimental data verifies the validity and accuracy of the optimal model proposed in this paper. The optimal model proposed in this paper has a higher theoretical guiding significance for the wireless energy transfer system's further research, and provide a more precise model reference for solving the power supply problem in visual prosthesis clinical application.
Estimating required information size by quantifying diversity in random-effects model meta-analyses

DEFF Research Database (Denmark)

Wetterslev, Jørn; Thorlund, Kristian; Brok, Jesper

2009-01-01

an intervention effect suggested by trials with low-risk of bias. METHODS: Information size calculations need to consider the total model variance in a meta-analysis to control type I and type II errors. Here, we derive an adjusting factor for the required information size under any random-effects model meta......-analysis. RESULTS: We devise a measure of diversity (D2) in a meta-analysis, which is the relative variance reduction when the meta-analysis model is changed from a random-effects into a fixed-effect model. D2 is the percentage that the between-trial variability constitutes of the sum of the between...... and interpreted using several simulations and clinical examples. In addition we show mathematically that diversity is equal to or greater than inconsistency, that is D2 >or= I2, for all meta-analyses. CONCLUSION: We conclude that D2 seems a better alternative than I2 to consider model variation in any random...
Holography and holographic dark energy model

International Nuclear Information System (INIS)

Gong Yungui; Zhang Yuanzhong

2005-01-01

The holographic principle is used to discuss the holographic dark energy model. We find that the Bekenstein-Hawking entropy bound is far from saturation under certain conditions. A more general constraint on the parameter of the holographic dark energy model is also derived
Generalized linear models with random effects unified analysis via H-likelihood

CERN Document Server

Lee, Youngjo; Pawitan, Yudi

2006-01-01

Since their introduction in 1972, generalized linear models (GLMs) have proven useful in the generalization of classical normal models. Presenting methods for fitting GLMs with random effects to data, Generalized Linear Models with Random Effects: Unified Analysis via H-likelihood explores a wide range of applications, including combining information over trials (meta-analysis), analysis of frailty models for survival data, genetic epidemiology, and analysis of spatial and temporal models with correlated errors.Written by pioneering authorities in the field, this reference provides an introduction to various theories and examines likelihood inference and GLMs. The authors show how to extend the class of GLMs while retaining as much simplicity as possible. By maximizing and deriving other quantities from h-likelihood, they also demonstrate how to use a single algorithm for all members of the class, resulting in a faster algorithm as compared to existing alternatives. Complementing theory with examples, many of...
A Parametric Energy Model for Energy Management of Long Belt Conveyors

Directory of Open Access Journals (Sweden)

Tebello Mathaba

2015-12-01

Full Text Available As electricity prices continue to rise, the increasing need for energy management requires better understanding of models for energy-consuming applications, such as conveyor belts. Conveyor belts are used in a wide range of industries, including power generation, mining and mineral processing. Conveyor technological advances are leading to increasingly long conveyor belts being commissioned. Thus, the energy consumption of each individual belt conveyor unit is becoming increasingly significant. This paper proposes a generic energy model for belt conveyors with long troughed belts. The model has a two-parameter power equation, and it uses a partial differential equation to capture the variable amount of material mass per unit length throughout the belt length. Verification results show that the power consumption calculations of the newly proposed simpler model are consistent with those of a known non-linear model with an error of less than 4%. The online parameter identification set-up of the model is proposed. Simulations indicate that the parameters can be identified successfully from data with up to 15% measurement noise. Results show that the proposed model gives better predictions of the power consumed and material delivered by a long conveyor belt than the steady-state models in the current literature.

A new neural network model for solving random interval linear programming problems.

Science.gov (United States)

Arjmandzadeh, Ziba; Safi, Mohammadreza; Nazemi, Alireza

2017-05-01

This paper presents a neural network model for solving random interval linear programming problems. The original problem involving random interval variable coefficients is first transformed into an equivalent convex second order cone programming problem. A neural network model is then constructed for solving the obtained convex second order cone problem. Employing Lyapunov function approach, it is also shown that the proposed neural network model is stable in the sense of Lyapunov and it is globally convergent to an exact satisfactory solution of the original problem. Several illustrative examples are solved in support of this technique. Copyright © 2017 Elsevier Ltd. All rights reserved.
A Fay-Herriot Model with Different Random Effect Variances

Czech Academy of Sciences Publication Activity Database

Hobza, Tomáš; Morales, D.; Herrador, M.; Esteban, M.D.

2011-01-01

Roč. 40, č. 5 (2011), s. 785-797 ISSN 0361-0926 R&D Projects: GA MŠk 1M0572 Institutional research plan: CEZ:AV0Z10750506 Keywords : small area estimation * Fay-Herriot model * Linear mixed model * Labor Force Survey Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.274, year: 2011 http://library.utia.cas.cz/separaty/2011/SI/hobza-a%20fay-herriot%20model%20with%20different%20random%20effect%20variances.pdf
Structure model of energy efficiency indicators and applications

International Nuclear Information System (INIS)

Wu, Li-Ming; Chen, Bai-Sheng; Bor, Yun-Chang; Wu, Yin-Chin

2007-01-01

For the purposes of energy conservation and environmental protection, the government of Taiwan has instigated long-term policies to continuously encourage and assist industry in improving the efficiency of energy utilization. While multiple actions have led to practical energy saving to a limited extent, no strong evidence of improvement in energy efficiency was observed from the energy efficiency indicators (EEI) system, according to the annual national energy statistics and survey. A structural analysis of EEI is needed in order to understand the role that energy efficiency plays in the EEI system. This work uses the Taylor series expansion to develop a structure model for EEI at the level of the process sector of industry. The model is developed on the premise that the design parameters of the process are used in comparison with the operational parameters for energy differences. The utilization index of production capability and the variation index of energy utilization are formulated in the model to describe the differences between EEIs. Both qualitative and quantitative methods for the analysis of energy efficiency and energy savings are derived from the model. Through structural analysis, the model showed that, while the performance of EEI is proportional to the process utilization index of production capability, it is possible that energy may develop in a direction opposite to that of EEI. This helps to explain, at least in part, the inconsistency between EEI and energy savings. An energy-intensive steel plant in Taiwan was selected to show the application of the model. The energy utilization efficiency of the plant was evaluated and the amount of energy that had been saved or over-used in the production process was estimated. Some insights gained from the model outcomes are helpful to further enhance energy efficiency in the plant
Modeling technical change in energy system analysis: analyzing the introduction of learning-by-doing in bottom-up energy models

International Nuclear Information System (INIS)

Berglund, Christer; Soederholm, Patrik

2006-01-01

The main objective of this paper is to provide an overview and a critical analysis of the recent literature on incorporating induced technical change in energy systems models. Special emphasis is put on surveying recent studies aimed at integrating learning-by-doing into bottom-up energy systems models through so-called learning curves, and on analyzing the relevance of learning curve analysis for understanding the process of innovation and technology diffusion in the energy sector. The survey indicates that this model work represents a major advance in energy research, and embeds important policy implications, not the least concerning the cost and the timing of environmental policies (including carbon emission constraints). However, bottom-up energy models with endogenous learning are also limited in their characterization of technology diffusion and innovation. While they provide a detailed account of technical options-which is absent in many top-down models-they also lack important aspects of diffusion behavior that are captured in top-down representations. For instance, they often fail in capturing strategic technology diffusion behavior in the energy sector as well as the energy sector's endogenous responses to policy, and they neglect important general equilibrium impacts (such as the opportunity cost of redirecting R and D support to the energy sector). Some suggestions on how innovation and diffusion modeling in bottom-up analysis can be improved are put forward
On a Stochastic Failure Model under Random Shocks

Science.gov (United States)

Cha, Ji Hwan

2013-02-01

In most conventional settings, the events caused by an external shock are initiated at the moments of its occurrence. In this paper, we study a new classes of shock model, where each shock from a nonhomogeneous Poisson processes can trigger a failure of a system not immediately, as in classical extreme shock models, but with delay of some random time. We derive the corresponding survival and failure rate functions. Furthermore, we study the limiting behaviour of the failure rate function where it is applicable.
Random Walk Model for Cell-To-Cell Misalignments in Accelerator Structures

International Nuclear Information System (INIS)

Stupakov, Gennady

2000-01-01

Due to manufacturing and construction errors, cells in accelerator structures can be misaligned relative to each other. As a consequence, the beam generates a transverse wakefield even when it passes through the structure on axis. The most important effect is the long-range transverse wakefield that deflects the bunches and causes growth of the bunch train projected emittance. In this paper, the effect of the cell-to-cell misalignments is evaluated using a random walk model that assumes that each cell is shifted by a random step relative to the previous one. The model is compared with measurements of a few accelerator structures
Capabilities and accuracy of energy modelling software

CSIR Research Space (South Africa)

Osburn, L

2010-11-01

Full Text Available Energy modelling can be used in a number of different ways to fulfill different needs, including certification within building regulations or green building rating tools. Energy modelling can also be used in order to try and predict what the energy...
Energy Model of Neuron Activation.

Science.gov (United States)

Romanyshyn, Yuriy; Smerdov, Andriy; Petrytska, Svitlana

2017-02-01

On the basis of the neurophysiological strength-duration (amplitude-duration) curve of neuron activation (which relates the threshold amplitude of a rectangular current pulse of neuron activation to the pulse duration), as well as with the use of activation energy constraint (the threshold curve corresponds to the energy threshold of neuron activation by a rectangular current pulse), an energy model of neuron activation by a single current pulse has been constructed. The constructed model of activation, which determines its spectral properties, is a bandpass filter. Under the condition of minimum-phase feature of the neuron activation model, on the basis of Hilbert transform, the possibilities of phase-frequency response calculation from its amplitude-frequency response have been considered. Approximation to the amplitude-frequency response by the response of the Butterworth filter of the first order, as well as obtaining the pulse response corresponding to this approximation, give us the possibility of analyzing the efficiency of activating current pulses of various shapes, including analysis in accordance with the energy constraint.
High energy X-ray phase and dark-field imaging using a random absorption mask.

Science.gov (United States)

Wang, Hongchang; Kashyap, Yogesh; Cai, Biao; Sawhney, Kawal

2016-07-28

High energy X-ray imaging has unique advantage over conventional X-ray imaging, since it enables higher penetration into materials with significantly reduced radiation damage. However, the absorption contrast in high energy region is considerably low due to the reduced X-ray absorption cross section for most materials. Even though the X-ray phase and dark-field imaging techniques can provide substantially increased contrast and complementary information, fabricating dedicated optics for high energies still remain a challenge. To address this issue, we present an alternative X-ray imaging approach to produce transmission, phase and scattering signals at high X-ray energies by using a random absorption mask. Importantly, in addition to the synchrotron radiation source, this approach has been demonstrated for practical imaging application with a laboratory-based microfocus X-ray source. This new imaging method could be potentially useful for studying thick samples or heavy materials for advanced research in materials science.
Developing a Model of the Irish Energy-System

DEFF Research Database (Denmark)

Connolly, David; Lund, Henrik; Mathiesen, Brian Vad

2009-01-01

to create the model as it accounts for all sectors that need to be considered for integrating large penetrations of renewable energy: the electricity, heat and transport sectors. Before various alternative energy-systems could be investigated for Ireland, a reference model of the existing system needed...... is a vital step due to the scale of the change required for large-scale renewable penetrations. In this paper, a model of the Irish energy system is created to identify how Ireland can transform from a fossil-fuel to a renewable energy-system. The energy-systems-analysis tool, EnergyPLAN, was chosen...... to be created. This paper focuses on the construction of this reference model, in terms of the data gathered, the assumptions made and the accuracy achieved. In future work, this model will be used to investigate alternative energy-systems for Ireland, with the aim to determine the most effective energy system...
Natural gas transmission and distribution model of the National Energy Modeling System

International Nuclear Information System (INIS)

1997-02-01

The Natural Gas Transmission and Distribution Model (NGTDM) is the component of the National Energy Modeling System (NEMS) that is used to represent the domestic natural gas transmission and distribution system. NEMS was developed in the Office of Integrated Analysis and Forecasting of the Energy Information Administration (EIA). NEMS is the third in a series of computer-based, midterm energy modeling systems used since 1974 by the EIA and its predecessor, the Federal Energy Administration, to analyze domestic energy-economy markets and develop projections. From 1982 through 1993, the Intermediate Future Forecasting System (IFFS) was used by the EIA for its analyses, and the Gas Analysis Modeling System (GAMS) was used within IFFS to represent natural gas markets. Prior to 1982, the Midterm Energy Forecasting System (MEFS), also referred to as the Project Independence Evaluation System (PIES), was employed. NEMS was developed to enhance and update EIA's modeling capability by internally incorporating models of energy markets that had previously been analyzed off-line. In addition, greater structural detail in NEMS permits the analysis of a broader range of energy issues. The time horizon of NEMS is the midterm period (i.e., through 2015). In order to represent the regional differences in energy markets, the component models of NEMS function at regional levels appropriate for the markets represented, with subsequent aggregation/disaggregation to the Census Division level for reporting purposes
Natural gas transmission and distribution model of the National Energy Modeling System

Energy Technology Data Exchange (ETDEWEB)

NONE

1997-02-01

The Natural Gas Transmission and Distribution Model (NGTDM) is the component of the National Energy Modeling System (NEMS) that is used to represent the domestic natural gas transmission and distribution system. NEMS was developed in the Office of Integrated Analysis and Forecasting of the Energy Information Administration (EIA). NEMS is the third in a series of computer-based, midterm energy modeling systems used since 1974 by the EIA and its predecessor, the Federal Energy Administration, to analyze domestic energy-economy markets and develop projections. From 1982 through 1993, the Intermediate Future Forecasting System (IFFS) was used by the EIA for its analyses, and the Gas Analysis Modeling System (GAMS) was used within IFFS to represent natural gas markets. Prior to 1982, the Midterm Energy Forecasting System (MEFS), also referred to as the Project Independence Evaluation System (PIES), was employed. NEMS was developed to enhance and update EIA`s modeling capability by internally incorporating models of energy markets that had previously been analyzed off-line. In addition, greater structural detail in NEMS permits the analysis of a broader range of energy issues. The time horizon of NEMS is the midterm period (i.e., through 2015). In order to represent the regional differences in energy markets, the component models of NEMS function at regional levels appropriate for the markets represented, with subsequent aggregation/disaggregation to the Census Division level for reporting purposes.
An Optimization Scheduling Model for Wind Power and Thermal Power with Energy Storage System considering Carbon Emission Trading

Directory of Open Access Journals (Sweden)

Huan-huan Li

2015-01-01

Full Text Available Wind power has the characteristics of randomness and intermittence, which influences power system safety and stable operation. To alleviate the effect of wind power grid connection and improve power system’s wind power consumptive capability, this paper took emission trading and energy storage system into consideration and built an optimization model for thermal-wind power system and energy storage systems collaborative scheduling. A simulation based on 10 thermal units and wind farms with 2800 MW installed capacity verified the correctness of the models put forward by this paper. According to the simulation results, the introduction of carbon emission trading can improve wind power consumptive capability and cut down the average coal consumption per unit of power. The introduction of energy storage system can smooth wind power output curve and suppress power fluctuations. The optimization effects achieve the best when both of carbon emission trading and energy storage system work at the same time.
Nonparametric Estimation of Distributions in Random Effects Models

KAUST Repository

Hart, Jeffrey D.

2011-01-01

We propose using minimum distance to obtain nonparametric estimates of the distributions of components in random effects models. A main setting considered is equivalent to having a large number of small datasets whose locations, and perhaps scales, vary randomly, but which otherwise have a common distribution. Interest focuses on estimating the distribution that is common to all datasets, knowledge of which is crucial in multiple testing problems where a location/scale invariant test is applied to every small dataset. A detailed algorithm for computing minimum distance estimates is proposed, and the usefulness of our methodology is illustrated by a simulation study and an analysis of microarray data. Supplemental materials for the article, including R-code and a dataset, are available online. © 2011 American Statistical Association.
Model for Analysis of Energy Demand (MAED-2)

International Nuclear Information System (INIS)

2007-01-01

The IAEA has been supporting its Member States in the area of energy planning for sustainable development. Development and dissemination of appropriate methodologies and their computer codes are important parts of this support. This manual has been produced to facilitate the use of the MAED model: Model for Analysis of Energy Demand. The methodology of the MAED model was originally developed by. B. Chateau and B. Lapillonne of the Institute Economique et Juridique de l'Energie (IEJE) of the University of Grenoble, France, and was presented as the MEDEE model. Since then the MEDEE model has been developed and adopted to be appropriate for modelling of various energy demand system. The IAEA adopted MEDEE-2 model and incorporated important modifications to make it more suitable for application in the developing countries, and it was named as the MAED model. The first version of the MAED model was designed for the DOS based system, which was later on converted for the Windows system. This manual presents the latest version of the MAED model. The most prominent feature of this version is its flexibility for representing structure of energy consumption. The model now allows country-specific representations of energy consumption patterns using the MAED methodology. The user can now disaggregate energy consumption according to the needs and/or data availability in her/his country. As such, MAED has now become a powerful tool for modelling widely diverse energy consumption patterns. This manual presents the model in details and provides guidelines for its application
Vacuum energy from noncommutative models

Science.gov (United States)

Mignemi, S.; Samsarov, A.

2018-04-01

The vacuum energy is computed for a scalar field in a noncommutative background in several models of noncommutative geometry. One may expect that the noncommutativity introduces a natural cutoff on the ultraviolet divergences of field theory. Our calculations show however that this depends on the particular model considered: in some cases the divergences are suppressed and the vacuum energy is only logarithmically divergent, in other cases they are stronger than in the commutative theory.
Incoherent neutron scattering functions for random jump diffusion in bounded and infinite media

International Nuclear Information System (INIS)

Hall, P.L.; Ross, D.K.

1981-01-01

The incoherent neutron scattering function for unbounded jump diffusion is calculated from random walk theory assuming a gaussian distribution of jump lengths. The method is then applied to calculate the scattering function for spatially bounded random jumps in one dimension. The dependence on momentum transfer of the quasi-elastic energy broadenings predicted by this model and a previous model for bounded one-dimensional continuous diffusion are calculated and compared with the predictions of models for diffusion in unbounded media. The one-dimensional solutions can readily be generalized to three dimensions to provide a description of quasi-elastic scattering of neutrons by molecules undergoing localized random motions. (author)
Compensatory mechanisms activated with intermittent energy restriction: A randomized control trial.

Science.gov (United States)

Coutinho, Sílvia Ribeiro; Halset, Eline Holli; Gåsbakk, Sigrid; Rehfeld, Jens F; Kulseng, Bård; Truby, Helen; Martins, Cátia

2018-06-01

Strong compensatory responses, with reduced resting metabolic rate (RMR), increased exercise efficiency (ExEff) and appetite, are activated when weight loss (WL) is achieved with continuous energy restriction (CER), which try to restore energy balance. Intermittent energy restriction (IER), where short spells of energy restriction are interspaced by periods of habitual energy intake, may offer some protection in minimizing those responses. We aimed to compare the effect of IER versus CER on body composition and the compensatory responses induced by WL. 35 adults (age: 39 ± 9 y) with obesity (BMI: 36 ± 4 kg/m 2 ) were randomized to lose a similar weight with an IER (N = 18) or a CER (N = 17) diet over a 12 week period. Macronutrient composition and overall energy restriction (33% reduction) were similar between groups. Body weight/composition, RMR, fasting respiratory quotient (RQ), ExEff (10, 25, and 50 W), subjective appetite ratings (hunger, fullness, desire to eat, and prospective food consumption (PFC)), and appetite-regulating hormones (active ghrelin (AG), cholecystokinin (CCK), total peptide YY (PYY), active glucagon-like peptide-1 (GLP-1), and insulin) were measured before and after WL. Changes in body weight (≈12.5% WL) and composition were similar in both groups. Fasting RQ and ExEff at 10 W increased in both groups. Losing weight, either by IER or CER dieting, did not induce significant changes in subjective appetite ratings. RMR decreased and ExEff at 25 and 50 W increased (P intermittent, does not appear to modulate the compensatory mechanisms activated by weight loss. NCT02169778 (the study was registered in clinicaltrial.gov). Copyright © 2017 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.
Modeling and optimization of HVAC energy consumption

Energy Technology Data Exchange (ETDEWEB)

Kusiak, Andrew; Li, Mingyang; Tang, Fan [Department of Mechanical and Industrial Engineering, University of Iowa, Iowa City, IA 52242 - 1527 (United States)

2010-10-15

A data-driven approach for minimization of the energy to air condition a typical office-type facility is presented. Eight data-mining algorithms are applied to model the nonlinear relationship among energy consumption, control settings (supply air temperature and supply air static pressure), and a set of uncontrollable parameters. The multiple-linear perceptron (MLP) ensemble outperforms other models tested in this research, and therefore it is selected to model a chiller, a pump, a fan, and a reheat device. These four models are integrated into an energy optimization model with two decision variables, the setpoint of the supply air temperature and the static pressure in the air handling unit. The model is solved with a particle swarm optimization algorithm. The optimization results have demonstrated the total energy consumed by the heating, ventilation, and air-conditioning system is reduced by over 7%. (author)
Modelling energy demand of Croatian industry sector

DEFF Research Database (Denmark)

Medić, Zlatko Bačelić; Pukšec, Tomislav; Mathiesen, Brian Vad

2014-01-01

Industry represents one of the most interesting sectors when analysing Croatian final energy demand. Croatian industry represents 20% of nation's GDP and employs 25% of total labour force making it a significant subject for the economy. Today, with around 60 PJ of final energy demand...... it is the third most energy intensive sector in Croatia after transport and households. Implementing mechanisms that would lead to improvements in energy efficiency in this sector seems relevant. Through this paper, long-term energy demand projections for Croatian industry will be shown. The central point...... for development of the model will be parameters influencing the industry in Croatia. Energy demand predictions in this paper are based upon bottom-up approach model. IED model produces results which can be compared to Croatian National Energy Strategy. One of the conclusions shown in this paper is significant...

Zero temperature renormalisation group study of the random systems: The Ising model in a transverse field in two dimensions

International Nuclear Information System (INIS)

Kamieniarz, G.

1984-12-01

A zero temperature real space renormalization group block method is applied to the random quantum Ising model with a transverse field on the planar honeycomb and square lattices. For the bond diluted system the magnetisation and the separation of the ground state energy level (in the paramagnetic phase) are presented for several bond concentrations p. The critical exponents extracted both from the fixed-points and from direct numerical computations preserve some scaling relations, and the critical curve displays a characteristic discontinuity at the percolation concentration. For the McCoy and Wu distribution the random fields and bonds are found to introduce a strong relevant disorder. The order parameter still falls off continuously to zero for well-defined values of the parameters, but a new fixed point yields a slight change in the critical exponents. (author)
Introducing technology learning for energy technologies in a national CGE model through soft links to global and national energy models

International Nuclear Information System (INIS)

Martinsen, Thomas

2011-01-01

This paper describes a method to model the influence by global policy scenarios, particularly spillover of technology learning, on the energy service demand of the non-energy sectors of the national economy. It is exemplified by Norway. Spillover is obtained from the technology-rich global Energy Technology Perspective model operated by the International Energy Agency. It is provided to a national hybrid model where a national bottom-up Markal model carries forward spillover into a national top-down CGE model at a disaggregated demand category level. Spillover of technology learning from the global energy technology market will reduce national generation costs of energy carriers. This may in turn increase demand in the non-energy sectors of the economy because of the rebound effect. The influence of spillover on the Norwegian economy is most pronounced for the production level of industrial chemicals and for the demand for electricity for residential energy services. The influence is modest, however, because all existing electricity generating capacity is hydroelectric and thus compatible with the low emission policy scenario. In countries where most of the existing generating capacity must be replaced by nascent energy technologies or carbon captured and storage the influence on demand is expected to be more significant. - Highlights: → Spillover of global technology learning may be forwarded into a macroeconomic model. → The national electricity price differs significantly between the different global scenarios. → Soft-linking global and national models facilitate transparency in the technology learning effect chain.
Random cyclic constitutive models of 0Cr18Ni10Ti pipe steel

International Nuclear Information System (INIS)

Zhao Yongxiang; Yang Bing

2004-01-01

Experimental study is performed on the random cyclic constitutive relations of a new pipe stainless steel, 0Cr18Ni10Ti, by an incremental strain-controlled fatigue test. In the test, it is verified that the random cyclic constitutive relations, like the wide recognized random cyclic strain-life relations, is an intrinsic fatigue phenomenon of engineering materials. Extrapolating the previous work by Zhao et al, probability-based constitutive models are constructed, respectively, on the bases of Ramberg-Osgood equation and its modified form. Scattering regularity and amount of the test data are taken into account. The models consist of the survival probability-strain-life curves, the confidence strain-life curves, and the survival probability-confidence-strain-life curves. Availability and feasibility of the models have been indicated by analysis of the present test data
Ultraviolet complete dark energy model

Science.gov (United States)

Narain, Gaurav; Li, Tianjun

2018-04-01

We consider a local phenomenological model to explain a nonlocal gravity scenario which has been proposed to address dark energy issues. This nonlocal gravity action has been seen to fit the data as well as Λ -CDM and therefore demands a more fundamental local treatment. The induced gravity model coupled with higher-derivative gravity is exploited for this proposal, as this perturbatively renormalizable model has a well-defined ultraviolet (UV) description where ghosts are evaded. We consider a generalized version of this model where we consider two coupled scalar fields and their nonminimal coupling with gravity. In this simple model, one of the scalar field acquires a vacuum expectation value (VEV), thereby inducing a mass for one of the scalar fields and generating Newton's constant. The induced mass however is seen to be always above the running energy scale thereby leading to its decoupling. The residual theory after decoupling becomes a platform for driving the accelerated expansion under certain conditions. Integrating out the residual scalar generates a nonlocal gravity action. The leading term of which is the nonlocal gravity action used to fit the data of dark energy.
Simultaneous escaping of explicit and hidden free energy barriers: application of the orthogonal space random walk strategy in generalized ensemble based conformational sampling.

Science.gov (United States)

Zheng, Lianqing; Chen, Mengen; Yang, Wei

2009-06-21

To overcome the pseudoergodicity problem, conformational sampling can be accelerated via generalized ensemble methods, e.g., through the realization of random walks along prechosen collective variables, such as spatial order parameters, energy scaling parameters, or even system temperatures or pressures, etc. As usually observed, in generalized ensemble simulations, hidden barriers are likely to exist in the space perpendicular to the collective variable direction and these residual free energy barriers could greatly abolish the sampling efficiency. This sampling issue is particularly severe when the collective variable is defined in a low-dimension subset of the target system; then the "Hamiltonian lagging" problem, which reveals the fact that necessary structural relaxation falls behind the move of the collective variable, may be likely to occur. To overcome this problem in equilibrium conformational sampling, we adopted the orthogonal space random walk (OSRW) strategy, which was originally developed in the context of free energy simulation [L. Zheng, M. Chen, and W. Yang, Proc. Natl. Acad. Sci. U.S.A. 105, 20227 (2008)]. Thereby, generalized ensemble simulations can simultaneously escape both the explicit barriers along the collective variable direction and the hidden barriers that are strongly coupled with the collective variable move. As demonstrated in our model studies, the present OSRW based generalized ensemble treatments show improved sampling capability over the corresponding classical generalized ensemble treatments.
A universal self-charging system driven by random biomechanical energy for sustainable operation of mobile electronics

Science.gov (United States)

Niu, Simiao; Wang, Xiaofeng; Yi, Fang; Zhou, Yu Sheng; Wang, Zhong Lin

2015-12-01

Human biomechanical energy is characterized by fluctuating amplitudes and variable low frequency, and an effective utilization of such energy cannot be achieved by classical energy-harvesting technologies. Here we report a high-efficient self-charging power system for sustainable operation of mobile electronics exploiting exclusively human biomechanical energy, which consists of a high-output triboelectric nanogenerator, a power management circuit to convert the random a.c. energy to d.c. electricity at 60% efficiency, and an energy storage device. With palm tapping as the only energy source, this power unit provides a continuous d.c. electricity of 1.044 mW (7.34 W m-3) in a regulated and managed manner. This self-charging unit can be universally applied as a standard `infinite-lifetime' power source for continuously driving numerous conventional electronics, such as thermometers, electrocardiograph system, pedometers, wearable watches, scientific calculators and wireless radio-frequency communication system, which indicates the immediate and broad applications in personal sensor systems and internet of things.
A random matrix model of relaxation

International Nuclear Information System (INIS)

Lebowitz, J L; Pastur, L

2004-01-01

We consider a two-level system, S 2 , coupled to a general n level system, S n , via a random matrix. We derive an integral representation for the mean reduced density matrix ρ(t) of S 2 in the limit n → ∞, and we identify a model of S n which possesses some of the properties expected for macroscopic thermal reservoirs. In particular, it yields the Gibbs form for ρ(∞). We also consider an analog of the van Hove limit and obtain a master equation (Markov dynamics) for the evolution of ρ(t) on an appropriate time scale
Factorisations for partition functions of random Hermitian matrix models

International Nuclear Information System (INIS)

Jackson, D.M.; Visentin, T.I.

1996-01-01

The partition function Z N , for Hermitian-complex matrix models can be expressed as an explicit integral over R N , where N is a positive integer. Such an integral also occurs in connection with random surfaces and models of two dimensional quantum gravity. We show that Z N can be expressed as the product of two partition functions, evaluated at translated arguments, for another model, giving an explicit connection between the two models. We also give an alternative computation of the partition function for the φ 4 -model.The approach is an algebraic one and holds for the functions regarded as formal power series in the appropriate ring. (orig.)
Enumeration of RNA complexes via random matrix theory

DEFF Research Database (Denmark)

Andersen, Jørgen E; Chekhov, Leonid O.; Penner, Robert C

2013-01-01

molecules and hydrogen bonds in a given complex. The free energies of this matrix model are computed using the so-called topological recursion, which is a powerful new formalism arising from random matrix theory. These numbers of RNA complexes also have profound meaning in mathematics: they provide......In the present article, we review a derivation of the numbers of RNA complexes of an arbitrary topology. These numbers are encoded in the free energy of the Hermitian matrix model with potential V(x)=x(2)/2 - stx/(1 - tx), where s and t are respective generating parameters for the number of RNA...
Randomizing growing networks with a time-respecting null model

Science.gov (United States)

Ren, Zhuo-Ming; Mariani, Manuel Sebastian; Zhang, Yi-Cheng; Medo, Matúš

2018-05-01

Complex networks are often used to represent systems that are not static but grow with time: People make new friendships, new papers are published and refer to the existing ones, and so forth. To assess the statistical significance of measurements made on such networks, we propose a randomization methodology—a time-respecting null model—that preserves both the network's degree sequence and the time evolution of individual nodes' degree values. By preserving the temporal linking patterns of the analyzed system, the proposed model is able to factor out the effect of the system's temporal patterns on its structure. We apply the model to the citation network of Physical Review scholarly papers and the citation network of US movies. The model reveals that the two data sets are strikingly different with respect to their degree-degree correlations, and we discuss the important implications of this finding on the information provided by paradigmatic node centrality metrics such as indegree and Google's PageRank. The randomization methodology proposed here can be used to assess the significance of any structural property in growing networks, which could bring new insights into the problems where null models play a critical role, such as the detection of communities and network motifs.
Effect of disorder correlation in random mers

International Nuclear Information System (INIS)

Brezini, A.; Sebbani, M.; Depollier, C.; Belbachir, M.

1995-12-01

A widely held view in solid-state physics is that disorder precludes the presence of long-range transport in one-dimension. Recently a series of models has been proposed that do not conform to this view such as the well known Random Dimer Model (RDM). In the following paper, we must present a generalization of the RDM. In particular, the nature of the eigenstates of a non-interacting electron is investigated by means of a popular one-dimensional Kronig-Penney Hamiltonian in which n-mers have been placed at random on a regular lattice. Mainly in each allowed energy band of the spectrum, it is found that n-mers exhibits n - 1 resonances associated to extended states. Moreover these resonances appear to be narrower if the potential is attractive against repulsive, i.e. constituted of wells instead barriers, which discriminates the ability in localizing the eigenstates. Attention has been paid to the energy transition as one approaches the two resonances of the random trimer within the first allowed band. The transition exhibits a smooth behaviour for the lower energy when compared to the higher one with respect to the first resonance and shows quite a similar behaviour for both sides close to the second resonance. The discrepancy is attributed to the typical nature of the eigenstates for each resonance. Correspondingly, the wave functions associated to the first resonance are not like Bloch-waves while for the second one they look like the crystal wave functions displaying only minor distortions. (author). 44 refs, 6 figs
One-dimensional energy flow model for poroelastic material

International Nuclear Information System (INIS)

Kim, Jung Soo; Kang, Yeon June

2009-01-01

This paper presents a one-dimensional energy flow model to investigate the energy behavior for poroelastic media coupled with acoustical media. The proposed energy flow model is expressed by an independent energy governing equation that is classified into each wave component propagating in poroelastic media. The energy governing equation is derived using the General Energetic Method (GEM). To facilitate a comparison with the classical solution based on the conventional displacement-base formulation, approximate solutions of energy density and intensity are obtained. Furthermore, the limitations and usability of the proposed energy flow model for poroelastic media are described.
Modeling Technical Change in Energy System Analysis: Analyzing the Introduction of Learning-by-Doing in Bottom-up Energy Models

Energy Technology Data Exchange (ETDEWEB)

Berglund, Christer; Soederholm, Patrik [Luleaa Univ. of Technology (Sweden). Div. of Economics

2005-02-01

The main objective of this paper is to provide an overview and a critical analysis of the recent literature on incorporating induced technical change in energy systems models. Special emphasis is put on surveying recent studies aiming at integrating learning-by-doing into bottom-up energy systems models through so-called learning curves, and on analyzing the relevance of learning curve analysis for understanding the process of innovation and technology diffusion in the energy sector. The survey indicates that this model work represents a major advance in energy research, and embeds important policy implications, not the least concerning the cost and the timing of environmental policies (including carbon emission constraints). However, bottom-up energy models with endogenous learning are also limited in their characterization of technology diffusion and innovation. While they provide a detailed account of technical options - which is absent in many top-down models - they also lack important aspects of diffusion behavior that are captured in top-down representations. For instance, they fail in capturing strategic technology diffusion behavior in the energy sector, and they neglect important general equilibrium impacts (such as the opportunity cost of redirecting R and D support to the energy sector). For these reasons bottom-up and top-down models with induced technical change should not be viewed as substitutes but rather as complements.
Structure formation in inhomogeneous Early Dark Energy models

International Nuclear Information System (INIS)

Batista, R.C.; Pace, F.

2013-01-01

We study the impact of Early Dark Energy fluctuations in the linear and non-linear regimes of structure formation. In these models the energy density of dark energy is non-negligible at high redshifts and the fluctuations in the dark energy component can have the same order of magnitude of dark matter fluctuations. Since two basic approximations usually taken in the standard scenario of quintessence models, that both dark energy density during the matter dominated period and dark energy fluctuations on small scales are negligible, are not valid in such models, we first study approximate analytical solutions for dark matter and dark energy perturbations in the linear regime. This study is helpful to find consistent initial conditions for the system of equations and to analytically understand the effects of Early Dark Energy and its fluctuations, which are also verified numerically. In the linear regime we compute the matter growth and variation of the gravitational potential associated with the Integrated Sachs-Wolf effect, showing that these observables present important modifications due to Early Dark Energy fluctuations, though making them more similar to the ΛCDM model. We also make use of the Spherical Collapse model to study the influence of Early Dark Energy fluctuations in the nonlinear regime of structure formation, especially on δ c parameter, and their contribution to the halo mass, which we show can be of the order of 10%. We finally compute how the number density of halos is modified in comparison to the ΛCDM model and address the problem of how to correct the mass function in order to take into account the contribution of clustered dark energy. We conclude that the inhomogeneous Early Dark Energy models are more similar to the ΛCDM model than its homogeneous counterparts
Integration of motion energy from overlapping random background noise increases perceived speed of coherently moving stimuli.

Science.gov (United States)

Chuang, Jason; Ausloos, Emily C; Schwebach, Courtney A; Huang, Xin

2016-12-01

The perception of visual motion can be profoundly influenced by visual context. To gain insight into how the visual system represents motion speed, we investigated how a background stimulus that did not move in a net direction influenced the perceived speed of a center stimulus. Visual stimuli were two overlapping random-dot patterns. The center stimulus moved coherently in a fixed direction, whereas the background stimulus moved randomly. We found that human subjects perceived the speed of the center stimulus to be significantly faster than its veridical speed when the background contained motion noise. Interestingly, the perceived speed was tuned to the noise level of the background. When the speed of the center stimulus was low, the highest perceived speed was reached when the background had a low level of motion noise. As the center speed increased, the peak perceived speed was reached at a progressively higher background noise level. The effect of speed overestimation required the center stimulus to overlap with the background. Increasing the background size within a certain range enhanced the effect, suggesting spatial integration. The speed overestimation was significantly reduced or abolished when the center stimulus and the background stimulus had different colors, or when they were placed at different depths. When the center- and background-stimuli were perceptually separable, speed overestimation was correlated with perceptual similarity between the center- and background-stimuli. These results suggest that integration of motion energy from random motion noise has a significant impact on speed perception. Our findings put new constraints on models regarding the neural basis of speed perception. Copyright © 2016 the American Physiological Society.
Aquifer thermal-energy-storage modeling

Science.gov (United States)

Schaetzle, W. J.; Lecroy, J. E.

1982-09-01

A model aquifer was constructed to simulate the operation of a full size aquifer. Instrumentation to evaluate the water flow and thermal energy storage was installed in the system. Numerous runs injecting warm water into a preconditioned uniform aquifer were made. Energy recoveries were evaluated and agree with comparisons of other limited available data. The model aquifer is simulated in a swimming pool, 18 ft by 4 ft, which was filled with sand. Temperature probes were installed in the system. A 2 ft thick aquifer is confined by two layers of polyethylene. Both the aquifer and overburden are sand. Four well configurations are available. The system description and original tests, including energy recovery, are described.
Random regression models for daily feed intake in Danish Duroc pigs

DEFF Research Database (Denmark)

Strathe, Anders Bjerring; Mark, Thomas; Jensen, Just

The objective of this study was to develop random regression models and estimate covariance functions for daily feed intake (DFI) in Danish Duroc pigs. A total of 476201 DFI records were available on 6542 Duroc boars between 70 to 160 days of age. The data originated from the National test station......-year-season, permanent, and animal genetic effects. The functional form was based on Legendre polynomials. A total of 64 models for random regressions were initially ranked by BIC to identify the approximate order for the Legendre polynomials using AI-REML. The parsimonious model included Legendre polynomials of 2nd...... order for genetic and permanent environmental curves and a heterogeneous residual variance, allowing the daily residual variance to change along the age trajectory due to scale effects. The parameters of the model were estimated in a Bayesian framework, using the RJMC module of the DMU package, where...
International Energy Agency Ocean Energy Systems Task 10 Wave Energy Converter Modeling Verification and Validation

DEFF Research Database (Denmark)

Wendt, Fabian F.; Yu, Yi-Hsiang; Nielsen, Kim

2017-01-01

This is the first joint reference paper for the Ocean Energy Systems (OES) Task 10 Wave Energy Converter modeling verification and validation group. The group is established under the OES Energy Technology Network program under the International Energy Agency. OES was founded in 2001 and Task 10 ...
Comparison between the SIMPLE and ENERGY mixing models

International Nuclear Information System (INIS)

Burns, K.J.; Todreas, N.E.

1980-07-01

The SIMPLE and ENERGY mixing models were compared in order to investigate the limitations of SIMPLE's analytically formulated mixing parameter, relative to the experimentally calibrated ENERGY mixing parameters. For interior subchannels, it was shown that when the SIMPLE and ENERGY parameters are reduced to a common form, there is good agreement between the two models for a typical fuel geometry. However, large discrepancies exist for typical blanket (lower P/D) geometries. Furthermore, the discrepancies between the mixing parameters result in significant differences in terms of the temperature profiles generated by the ENERGY code utilizing these mixing parameters as input. For edge subchannels, the assumptions made in the development of the SIMPLE model were extended to the rectangular edge subchannel geometry used in ENERGY. The resulting effective eddy diffusivities (used by the ENERGY code) associated with the SIMPLE model are again closest to those of the ENERGY model for the fuel assembly geometry. Finally, the SIMPLE model's neglect of a net swirl effect in the edge region is most limiting for assemblies exhibiting relatively large radial power skews
Random Modeling of Daily Rainfall and Runoff Using a Seasonal Model and Wavelet Denoising

Directory of Open Access Journals (Sweden)

Chien-ming Chou

2014-01-01

Full Text Available Instead of Fourier smoothing, this study applied wavelet denoising to acquire the smooth seasonal mean and corresponding perturbation term from daily rainfall and runoff data in traditional seasonal models, which use seasonal means for hydrological time series forecasting. The denoised rainfall and runoff time series data were regarded as the smooth seasonal mean. The probability distribution of the percentage coefficients can be obtained from calibrated daily rainfall and runoff data. For validated daily rainfall and runoff data, percentage coefficients were randomly generated according to the probability distribution and the law of linear proportion. Multiplying the generated percentage coefficient by the smooth seasonal mean resulted in the corresponding perturbation term. Random modeling of daily rainfall and runoff can be obtained by adding the perturbation term to the smooth seasonal mean. To verify the accuracy of the proposed method, daily rainfall and runoff data for the Wu-Tu watershed were analyzed. The analytical results demonstrate that wavelet denoising enhances the precision of daily rainfall and runoff modeling of the seasonal model. In addition, the wavelet denoising technique proposed in this study can obtain the smooth seasonal mean of rainfall and runoff processes and is suitable for modeling actual daily rainfall and runoff processes.

Energy Auditor and Quality Control Inspector Competency Model

Energy Technology Data Exchange (ETDEWEB)

Head, Heather R [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Kurnik, Charles W [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Schroeder, Derek [U.S. Department of Energy; Cutchin, Kelly [Simonson Management Services

2018-05-02

The Energy Auditor (EA) and Quality Control Inspector (QCI) Competency model was developed to identify the soft skills, foundational competencies and define the levels of Knowledge, Skills, and Abilities (KSAs) required to successfully perform the tasks defined in the EA and QCI Job Task Analysis (JTAs), the U.S. Department of Energy (DOE) used the U.S. Department of Labor's (DOL) Competency Model Clearinghouse resources to develop a QCI and EA Competency Model. To keep the QCI and EA competency model consistent with other construction and energy management competency models, DOE and the National Renewable Energy Laboratory used the existing 'Residential Construction Competency Model' and the 'Advanced Commercial Building Competency Model' where appropriate.
A note on moving average models for Gaussian random fields

DEFF Research Database (Denmark)

Hansen, Linda Vadgård; Thorarinsdottir, Thordis L.

The class of moving average models offers a flexible modeling framework for Gaussian random fields with many well known models such as the Matérn covariance family and the Gaussian covariance falling under this framework. Moving average models may also be viewed as a kernel smoothing of a Lévy...... basis, a general modeling framework which includes several types of non-Gaussian models. We propose a new one-parameter spatial correlation model which arises from a power kernel and show that the associated Hausdorff dimension of the sample paths can take any value between 2 and 3. As a result...
Random unitary evolution model of quantum Darwinism with pure decoherence

Science.gov (United States)

Balanesković, Nenad

2015-10-01

We study the behavior of Quantum Darwinism [W.H. Zurek, Nat. Phys. 5, 181 (2009)] within the iterative, random unitary operations qubit-model of pure decoherence [J. Novotný, G. Alber, I. Jex, New J. Phys. 13, 053052 (2011)]. We conclude that Quantum Darwinism, which describes the quantum mechanical evolution of an open system S from the point of view of its environment E, is not a generic phenomenon, but depends on the specific form of input states and on the type of S-E-interactions. Furthermore, we show that within the random unitary model the concept of Quantum Darwinism enables one to explicitly construct and specify artificial input states of environment E that allow to store information about an open system S of interest with maximal efficiency.
Modelling energy utilisation in broiler breeder hens.

Science.gov (United States)

Rabello, C B V; Sakomura, N K; Longo, F A; Couto, H P; Pacheco, C R; Fernandes, J B K

2006-10-01

1. The objective of this study was to determine a metabolisable energy (ME) requirement model for broiler breeder hens. The influence of temperature on ME requirements for maintenance was determined in experiments conducted in three environmental rooms with temperatures kept constant at 13, 21 and 30 degrees C using a comparative slaughter technique. The energy requirements for weight gain were determined based upon body energy content and efficiency of energy utilisation for weight gain. The energy requirements for egg production were determined on the basis of egg energy content and efficiency of energy deposition in the eggs. 2. The following model was developed using these results: ME = kgW0.75(806.53-26.45T + 0.50T2) + 31.90G + 10.04EM, where kgW0.75 is body weight (kg) raised to the power 0.75, T is temperature ( degrees C), G is weight gain (g) and EM is egg mass (g). 3. A feeding trial was conducted using 400 Hubbard Hi-Yield broiler breeder hens and 40 Peterson males from 31 to 46 weeks of age in order to compare use of the model with a recommended feeding programme for this strain of bird. The application of the model in breeder hens provided good productive and reproductive performance and better results in feed and energy conversion than in hens fed according to strain recommendation. In conclusion, the model evaluated predicted an ME intake which matched breeder hens' requirements.
Modeling urban building energy use: A review of modeling approaches and procedures

Energy Technology Data Exchange (ETDEWEB)

Li, Wenliang; Zhou, Yuyu; Cetin, Kristen; Eom, Jiyong; Wang, Yu; Chen, Gang; Zhang, Xuesong

2017-12-01

With rapid urbanization and economic development, the world has been experiencing an unprecedented increase in energy consumption and greenhouse gas (GHG) emissions. While reducing energy consumption and GHG emissions is a common interest shared by major developed and developing countries, actions to enable these global reductions are generally implemented at the city scale. This is because baseline information from individual cities plays an important role in identifying economical options for improving building energy efficiency and reducing GHG emissions. Numerous approaches have been proposed for modeling urban building energy use in the past decades. This paper aims to provide an up-to-date review of the broad categories of energy models for urban buildings and describes the basic workflow of physics-based, bottom-up models and their applications in simulating urban-scale building energy use. Because there are significant differences across models with varied potential for application, strengths and weaknesses of the reviewed models are also presented. This is followed by a discussion of challenging issues associated with model preparation and calibration.
Model projections for household energy use in India

NARCIS (Netherlands)

van Ruijven, B.J.; van Vuuren, D.P.; de Vries, B.J.M.; Isaac, M.; van der Sluijs, J.P.; Lucas, P.L.; Balachandra, P.

2011-01-01

Energy use in developing countries is heterogeneous across households. Present day global energy models are mostly too aggregate to account for this heterogeneity. Here, a bottom-up model for residential energy use that starts from key dynamic concepts on energy use in developing countries is
Modeling Innovations Advance Wind Energy Industry

Science.gov (United States)

2009-01-01

In 1981, Glenn Research Center scientist Dr. Larry Viterna developed a model that predicted certain elements of wind turbine performance with far greater accuracy than previous methods. The model was met with derision from others in the wind energy industry, but years later, Viterna discovered it had become the most widely used method of its kind, enabling significant wind energy technologies-like the fixed pitch turbines produced by manufacturers like Aerostar Inc. of Westport, Massachusetts-that are providing sustainable, climate friendly energy sources today.
The importance of regret minimization in the choice for renewable energy programmes: Evidence from a discrete choice experiment

International Nuclear Information System (INIS)

Boeri, Marco; Longo, Alberto

2017-01-01

This study provides a methodologically rigorous attempt to disentangle the impact of various factors – unobserved heterogeneity, information and environmental attitudes – on the inclination of individuals to exhibit either a utility maximization or a regret minimization behaviour in a discrete choice experiment for renewable energy programmes described by four attributes: greenhouse gas emissions, power outages, employment in the energy sector, and electricity bill. We explore the ability of different models – multinomial logit, random parameters logit, and hybrid latent class – and of different choice paradigms – utility maximization and regret minimization – in explaining people's choices for renewable energy programmes. The “pure” random regret random parameters logit model explains the choices of our respondents better than other models, indicating that regret is an important choice paradigm, and that choices for renewable energy programmes are mostly driven by regret, rather than by rejoice. In particular, we find that our respondents' choices are driven more by changes in greenhouse gas emissions than by reductions in power outages. Finally, we find that changing the level of information to one attribute has no effect on choices, and that being a member of an environmental organization makes a respondent more likely to be associated with the utility maximization choice framework. - Highlights: • The first paper to use the Random Regret Minimization choice paradigm in energy economics • With a hybrid latent class model, choices conform to either utility or pure random regret. • The pure random regret random parameters logit model outperforms other models. • Reducing greenhouse gas emissions is more important than reducing power outages.
Model documentation renewable fuels module of the National Energy Modeling System

Science.gov (United States)

1995-06-01

This report documents the objectives, analytical approach, and design of the National Energy Modeling System (NEMS) Renewable Fuels Module (RFM) as it relates to the production of the 1995 Annual Energy Outlook (AEO95) forecasts. The report catalogs and describes modeling assumptions, computational methodologies, data inputs, and parameter estimation techniques. A number of offline analyses used in lieu of RFM modeling components are also described. The RFM consists of six analytical submodules that represent each of the major renewable energy resources -- wood, municipal solid waste (MSW), solar energy, wind energy, geothermal energy, and alcohol fuels. The RFM also reads in hydroelectric facility capacities and capacity factors from a data file for use by the NEMS Electricity Market Module (EMM). The purpose of the RFM is to define the technological, cost, and resource size characteristics of renewable energy technologies. These characteristics are used to compute a levelized cost to be competed against other similarly derived costs from other energy sources and technologies. The competition of these energy sources over the NEMS time horizon determines the market penetration of these renewable energy technologies. The characteristics include available energy capacity, capital costs, fixed operating costs, variable operating costs, capacity factor, heat rate, construction lead time, and fuel product price.
Model documentation renewable fuels module of the National Energy Modeling System

Energy Technology Data Exchange (ETDEWEB)

NONE

1995-06-01

This report documents the objectives, analytical approach, and design of the National Energy Modeling System (NEMS) Renewable Fuels Module (RFM) as it relates to the production of the 1995 Annual Energy Outlook (AEO95) forecasts. The report catalogues and describes modeling assumptions, computational methodologies, data inputs, and parameter estimation techniques. A number of offline analyses used in lieu of RFM modeling components are also described. The RFM consists of six analytical submodules that represent each of the major renewable energy resources--wood, municipal solid waste (MSW), solar energy, wind energy, geothermal energy, and alcohol fuels. The RFM also reads in hydroelectric facility capacities and capacity factors from a data file for use by the NEMS Electricity Market Module (EMM). The purpose of the RFM is to define the technological, cost and resource size characteristics of renewable energy technologies. These characteristics are used to compute a levelized cost to be competed against other similarly derived costs from other energy sources and technologies. The competition of these energy sources over the NEMS time horizon determines the market penetration of these renewable energy technologies. The characteristics include available energy capacity, capital costs, fixed operating costs, variable operating costs, capacity factor, heat rate, construction lead time, and fuel product price.
Parallel random number generator for inexpensive configurable hardware cells

Science.gov (United States)

Ackermann, J.; Tangen, U.; Bödekker, B.; Breyer, J.; Stoll, E.; McCaskill, J. S.

2001-11-01

A new random number generator ( RNG) adapted to parallel processors has been created. This RNG can be implemented with inexpensive hardware cells. The correlation between neighboring cells is suppressed with smart connections. With such connection structures, sequences of pseudo-random numbers are produced. Numerical tests including a self-avoiding random walk test and the simulation of the order parameter and energy of the 2D Ising model give no evidence for correlation in the pseudo-random sequences. Because the new random number generator has suppressed the correlation between neighboring cells which is usually observed in cellular automaton implementations, it is applicable for extended time simulations. It gives an immense speed-up factor if implemented directly in configurable hardware, and has recently been used for long time simulations of spatially resolved molecular evolution.
Demonstrating sustainable energy: A review-based model of sustainable energy demonstration projects

NARCIS (Netherlands)

Bossink, Bart

2017-01-01

This article develops a model of sustainable energy demonstration projects, based on a review of 229 scientific publications on demonstrations in renewable and sustainable energy. The model addresses the basic organizational characteristics (aim, cooperative form, and physical location) and learning
(Non-) Gibbsianness and Phase Transitions in Random Lattice Spin Models

NARCIS (Netherlands)

Külske, C.

1999-01-01

We consider disordered lattice spin models with finite-volume Gibbs measures µΛ[η](dσ). Here σ denotes a lattice spin variable and η a lattice random variable with product distribution P describing the quenched disorder of the model. We ask: when will the joint measures limΛ↑Zd P(dη)µΛ[η](dσ) be
Energy modeling issues in quick service restaurants

Energy Technology Data Exchange (ETDEWEB)

Smith, V.A.; Johnson, K.F.

1997-03-01

The complexity of monitoring and modeling the energy performance of food-service facilities was discussed. Usually, less than one third of the energy consumed in a commercial food-service facility is used by equipment and systems typically modeled in building simulation software such as DOE-2. Algorithms have not yet been developed to handle independent makeup air units and the kitchen and dining room HVAC systems. The energy used by food process equipment and water heating is based on customer-volume and operation-hours. Monitoring projects have been undertaken to provide detailed energy use profiles of individual appliances and whole restaurants. Some technical issues that are unique to food-service modeling in current versions of DOE-2.1E software in the context of quick service restaurants, such as difficulties in modelling internal heat gains of hooded cooking appliances and walk-in refrigeration, and system and zone limitations on tracking energy consumption, were discussed. 1 fig.
Random regret-based discrete-choice modelling: an application to healthcare.

Science.gov (United States)

de Bekker-Grob, Esther W; Chorus, Caspar G

2013-07-01

A new modelling approach for analysing data from discrete-choice experiments (DCEs) has been recently developed in transport economics based on the notion of regret minimization-driven choice behaviour. This so-called Random Regret Minimization (RRM) approach forms an alternative to the dominant Random Utility Maximization (RUM) approach. The RRM approach is able to model semi-compensatory choice behaviour and compromise effects, while being as parsimonious and formally tractable as the RUM approach. Our objectives were to introduce the RRM modelling approach to healthcare-related decisions, and to investigate its usefulness in this domain. Using data from DCEs aimed at determining valuations of attributes of osteoporosis drug treatments and human papillomavirus (HPV) vaccinations, we empirically compared RRM models, RUM models and Hybrid RUM-RRM models in terms of goodness of fit, parameter ratios and predicted choice probabilities. In terms of model fit, the RRM model did not outperform the RUM model significantly in the case of the osteoporosis DCE data (p = 0.21), whereas in the case of the HPV DCE data, the Hybrid RUM-RRM model outperformed the RUM model (p implied by the two models can vary substantially. Differences in model fit between RUM, RRM and Hybrid RUM-RRM were found to be small. Although our study did not show significant differences in parameter ratios, the RRM and Hybrid RUM-RRM models did feature considerable differences in terms of the trade-offs implied by these ratios. In combination, our results suggest that RRM and Hybrid RUM-RRM modelling approach hold the potential of offering new and policy-relevant insights for health researchers and policy makers.
Rapid Energy Modeling Workflow Demonstration

Science.gov (United States)

2013-10-31

trail at AutodeskVasari.com Considered a lightweight version of Revit for energy modeling and analysis Many capabilities are in process of...Journal of Hospitality & Tourism Research 32(1):3-21. DOD (2005) Energy Managers Handbook. Retrieved from www.wbdg.org/ccb/DOD/DOD4/dodemhb.pdf
Dynamic modeling, simulation and control of energy generation

CERN Document Server

Vepa, Ranjan

2013-01-01

This book addresses the core issues involved in the dynamic modeling, simulation and control of a selection of energy systems such as gas turbines, wind turbines, fuel cells and batteries. The principles of modeling and control could be applied to other non-convention methods of energy generation such as solar energy and wave energy.A central feature of Dynamic Modeling, Simulation and Control of Energy Generation is that it brings together diverse topics in thermodynamics, fluid mechanics, heat transfer, electro-chemistry, electrical networks and electrical machines and focuses on their appli
General Business Model Patterns for Local Energy Management Concepts

International Nuclear Information System (INIS)

Facchinetti, Emanuele; Sulzer, Sabine

2016-01-01

The transition toward a more sustainable global energy system, significantly relying on renewable energies and decentralized energy systems, requires a deep reorganization of the energy sector. The way how energy services are generated, delivered, and traded is expected to be very different in the coming years. Business model innovation is recognized as a key driver for the successful implementation of the energy turnaround. This work contributes to this topic by introducing a heuristic methodology easing the identification of general business model patterns best suited for Local Energy Management concepts such as Energy Hubs. A conceptual framework characterizing the Local Energy Management business model solution space is developed. Three reference business model patterns providing orientation across the defined solution space are identified, analyzed, and compared. Through a market review, a number of successfully implemented innovative business models have been analyzed and allocated within the defined solution space. The outcomes of this work offer to potential stakeholders a starting point and guidelines for the business model innovation process, as well as insights for policy makers on challenges and opportunities related to Local Energy Management concepts.
General Business Model Patterns for Local Energy Management Concepts

Energy Technology Data Exchange (ETDEWEB)

Facchinetti, Emanuele, E-mail: emanuele.facchinetti@hslu.ch; Sulzer, Sabine [Lucerne Competence Center for Energy Research, Lucerne University of Applied Science and Arts, Horw (Switzerland)

2016-03-03

The transition toward a more sustainable global energy system, significantly relying on renewable energies and decentralized energy systems, requires a deep reorganization of the energy sector. The way how energy services are generated, delivered, and traded is expected to be very different in the coming years. Business model innovation is recognized as a key driver for the successful implementation of the energy turnaround. This work contributes to this topic by introducing a heuristic methodology easing the identification of general business model patterns best suited for Local Energy Management concepts such as Energy Hubs. A conceptual framework characterizing the Local Energy Management business model solution space is developed. Three reference business model patterns providing orientation across the defined solution space are identified, analyzed, and compared. Through a market review, a number of successfully implemented innovative business models have been analyzed and allocated within the defined solution space. The outcomes of this work offer to potential stakeholders a starting point and guidelines for the business model innovation process, as well as insights for policy makers on challenges and opportunities related to Local Energy Management concepts.
Model of Random Polygon Particles for Concrete and Mesh Automatic Subdivision

Institute of Scientific and Technical Information of China (English)

无

2001-01-01

In order to study the constitutive behavior of concrete in mesoscopic level, a new method is proposed in this paper. This method uses random polygon particles to simulate full grading broken aggregates of concrete. Based on computational geometry, we carry out the automatic generation of the triangle finite element mesh for the model of random polygon particles of concrete. The finite element mesh generated in this paper is also applicable to many other numerical methods.

Covariance of random stock prices in the Stochastic Dividend Discount Model

OpenAIRE

Agosto, Arianna; Mainini, Alessandra; Moretto, Enrico

2016-01-01

Dividend discount models have been developed in a deterministic setting. Some authors (Hurley and Johnson, 1994 and 1998; Yao, 1997) have introduced randomness in terms of stochastic growth rates, delivering closed-form expressions for the expected value of stock prices. This paper extends such previous results by determining a formula for the covariance between random stock prices when the dividends' rates of growth are correlated. The formula is eventually applied to real market data.
Evaluation of Automated Model Calibration Techniques for Residential Building Energy Simulation

Energy Technology Data Exchange (ETDEWEB)

and Ben Polly, Joseph Robertson [National Renewable Energy Lab. (NREL), Golden, CO (United States); Polly, Ben [National Renewable Energy Lab. (NREL), Golden, CO (United States); Collis, Jon [Colorado School of Mines, Golden, CO (United States)

2013-09-01

This simulation study adapts and applies the general framework described in BESTEST-EX (Judkoff et al 2010) for self-testing residential building energy model calibration methods. BEopt/DOE-2.2 is used to evaluate four mathematical calibration methods in the context of monthly, daily, and hourly synthetic utility data for a 1960's-era existing home in a cooling-dominated climate. The home's model inputs are assigned probability distributions representing uncertainty ranges, random selections are made from the uncertainty ranges to define "explicit" input values, and synthetic utility billing data are generated using the explicit input values. The four calibration methods evaluated in this study are: an ASHRAE 1051-RP-based approach (Reddy and Maor 2006), a simplified simulated annealing optimization approach, a regression metamodeling optimization approach, and a simple output ratio calibration approach. The calibration methods are evaluated for monthly, daily, and hourly cases; various retrofit measures are applied to the calibrated models and the methods are evaluated based on the accuracy of predicted savings, computational cost, repeatability, automation, and ease of implementation.
Evaluation of Automated Model Calibration Techniques for Residential Building Energy Simulation

Energy Technology Data Exchange (ETDEWEB)

Robertson, J.; Polly, B.; Collis, J.

2013-09-01

This simulation study adapts and applies the general framework described in BESTEST-EX (Judkoff et al 2010) for self-testing residential building energy model calibration methods. BEopt/DOE-2.2 is used to evaluate four mathematical calibration methods in the context of monthly, daily, and hourly synthetic utility data for a 1960's-era existing home in a cooling-dominated climate. The home's model inputs are assigned probability distributions representing uncertainty ranges, random selections are made from the uncertainty ranges to define 'explicit' input values, and synthetic utility billing data are generated using the explicit input values. The four calibration methods evaluated in this study are: an ASHRAE 1051-RP-based approach (Reddy and Maor 2006), a simplified simulated annealing optimization approach, a regression metamodeling optimization approach, and a simple output ratio calibration approach. The calibration methods are evaluated for monthly, daily, and hourly cases; various retrofit measures are applied to the calibrated models and the methods are evaluated based on the accuracy of predicted savings, computational cost, repeatability, automation, and ease of implementation.
A model for Long-term Industrial Energy Forecasting (LIEF)

Energy Technology Data Exchange (ETDEWEB)

Ross, M. [Lawrence Berkeley Lab., CA (United States)]|[Michigan Univ., Ann Arbor, MI (United States). Dept. of Physics]|[Argonne National Lab., IL (United States). Environmental Assessment and Information Sciences Div.; Hwang, R. [Lawrence Berkeley Lab., CA (United States)

1992-02-01

The purpose of this report is to establish the content and structural validity of the Long-term Industrial Energy Forecasting (LIEF) model, and to provide estimates for the model`s parameters. The model is intended to provide decision makers with a relatively simple, yet credible tool to forecast the impacts of policies which affect long-term energy demand in the manufacturing sector. Particular strengths of this model are its relative simplicity which facilitates both ease of use and understanding of results, and the inclusion of relevant causal relationships which provide useful policy handles. The modeling approach of LIEF is intermediate between top-down econometric modeling and bottom-up technology models. It relies on the following simple concept, that trends in aggregate energy demand are dependent upon the factors: (1) trends in total production; (2) sectoral or structural shift, that is, changes in the mix of industrial output from energy-intensive to energy non-intensive sectors; and (3) changes in real energy intensity due to technical change and energy-price effects as measured by the amount of energy used per unit of manufacturing output (KBtu per constant $ of output). The manufacturing sector is first disaggregated according to their historic output growth rates, energy intensities and recycling opportunities. Exogenous, macroeconomic forecasts of individual subsector growth rates and energy prices can then be combined with endogenous forecasts of real energy intensity trends to yield forecasts of overall energy demand. 75 refs.
Assessing robustness of designs for random effects parameters for nonlinear mixed-effects models.

Science.gov (United States)

Duffull, Stephen B; Hooker, Andrew C

2017-12-01

Optimal designs for nonlinear models are dependent on the choice of parameter values. Various methods have been proposed to provide designs that are robust to uncertainty in the prior choice of parameter values. These methods are generally based on estimating the expectation of the determinant (or a transformation of the determinant) of the information matrix over the prior distribution of the parameter values. For high dimensional models this can be computationally challenging. For nonlinear mixed-effects models the question arises as to the importance of accounting for uncertainty in the prior value of the variances of the random effects parameters. In this work we explore the influence of the variance of the random effects parameters on the optimal design. We find that the method for approximating the expectation and variance of the likelihood is of potential importance for considering the influence of random effects. The most common approximation to the likelihood, based on a first-order Taylor series approximation, yields designs that are relatively insensitive to the prior value of the variance of the random effects parameters and under these conditions it appears to be sufficient to consider uncertainty on the fixed-effects parameters only.
Directory of Energy Information Administration Models 1994

International Nuclear Information System (INIS)

1994-07-01

This directory revises and updates the 1993 directory and includes 15 models of the National Energy Modeling System (NEMS). Three other new models in use by the Energy Information Administration (EIA) have also been included: the Motor Gasoline Market Model (MGMM), Distillate Market Model (DMM), and the Propane Market Model (PPMM). This directory contains descriptions about each model, including title, acronym, purpose, followed by more detailed information on characteristics, uses and requirements. Sources for additional information are identified. Included in this directory are 37 EIA models active as of February 1, 1994
Directory of Energy Information Administration Models 1994

Energy Technology Data Exchange (ETDEWEB)

1994-07-01

This directory revises and updates the 1993 directory and includes 15 models of the National Energy Modeling System (NEMS). Three other new models in use by the Energy Information Administration (EIA) have also been included: the Motor Gasoline Market Model (MGMM), Distillate Market Model (DMM), and the Propane Market Model (PPMM). This directory contains descriptions about each model, including title, acronym, purpose, followed by more detailed information on characteristics, uses and requirements. Sources for additional information are identified. Included in this directory are 37 EIA models active as of February 1, 1994.
P2 : A random effects model with covariates for directed graphs

NARCIS (Netherlands)

van Duijn, M.A.J.; Snijders, T.A.B.; Zijlstra, B.J.H.

A random effects model is proposed for the analysis of binary dyadic data that represent a social network or directed graph, using nodal and/or dyadic attributes as covariates. The network structure is reflected by modeling the dependence between the relations to and from the same actor or node.
A binomial random sum of present value models in investment analysis

OpenAIRE

Βουδούρη, Αγγελική; Ντζιαχρήστος, Ευάγγελος

1997-01-01

Stochastic present value models have been widely adopted in financial theory and practice and play a very important role in capital budgeting and profit planning. The purpose of this paper is to introduce a binomial random sum of stochastic present value models and offer an application in investment analysis.
Local and regional energy companies offering energy services: Key activities and implications for the business model

International Nuclear Information System (INIS)

Kindström, Daniel; Ottosson, Mikael

2016-01-01

Highlights: • Many companies providing energy services are experiencing difficulties. • This research identifies key activities for the provision of energy services. • Findings are aggregated to the business-model level providing managerial insights. • This research identifies two different business model innovation paths. • Energy companies may need to renew parts of, or the entire, business model. - Abstract: Energy services play a key role in increasing energy efficiency in the industry. The key actors in these services are the local and regional energy companies that are increasingly implementing energy services as part of their market offering and developing service portfolios. Although expectations for energy services have been high, progress has so far been limited, and many companies offering energy services, including energy companies, are experiencing difficulties in implementing energy services and providing them to the market. Overall, this research examines what is needed for local and regional energy companies to successfully implement energy services (and consequently provide them to the market). In doing this, a two-stage process is used: first, we identify key activities for the successful implementation of energy services, and second, we aggregate the findings to the business model level. This research demonstrates that to succeed in implementing energy services, an energy company may need to renew parts or all of its existing product-based business model, formulate a new business model, or develop coexisting multiple business models. By discussing two distinct business model innovation processes, this research demonstrates that there can be different paths to success.
PROBABILISTIC MODEL OF BEAM–PLASMA INTERACTION IN RANDOMLY INHOMOGENEOUS PLASMA

International Nuclear Information System (INIS)

Voshchepynets, A.; Krasnoselskikh, V.; Artemyev, A.; Volokitin, A.

2015-01-01

We propose a new model that describes beam–plasma interaction in the presence of random density fluctuations with a known probability distribution. We use the property that, for the given frequency, the probability distribution of the density fluctuations uniquely determines the probability distribution of the phase velocity of waves. We present the system as discrete and consisting of small, equal spatial intervals with a linear density profile. This approach allows one to estimate variations in wave energy density and particle velocity, depending on the density gradient on any small spatial interval. Because the characteristic time for the evolution of the electron distribution function and the wave energy is much longer than the time required for a single wave–particle resonant interaction over a small interval, we determine the description for the relaxation process in terms of averaged quantities. We derive a system of equations, similar to the quasi-linear approximation, with the conventional velocity diffusion coefficient D and the wave growth rate γ replaced by the average in phase space, by making use of the probability distribution for phase velocities and by assuming that the interaction in each interval is independent of previous interactions. Functions D and γ are completely determined by the distribution function for the amplitudes of the fluctuations. For the Gaussian distribution of the density fluctuations, we show that the relaxation process is determined by the ratio of beam velocity to plasma thermal velocity, the dispersion of the fluctuations, and the width of the beam in the velocity space
Towards a 3d Spatial Urban Energy Modelling Approach

Science.gov (United States)

Bahu, J.-M.; Koch, A.; Kremers, E.; Murshed, S. M.

2013-09-01

Today's needs to reduce the environmental impact of energy use impose dramatic changes for energy infrastructure and existing demand patterns (e.g. buildings) corresponding to their specific context. In addition, future energy systems are expected to integrate a considerable share of fluctuating power sources and equally a high share of distributed generation of electricity. Energy system models capable of describing such future systems and allowing the simulation of the impact of these developments thus require a spatial representation in order to reflect the local context and the boundary conditions. This paper describes two recent research approaches developed at EIFER in the fields of (a) geo-localised simulation of heat energy demand in cities based on 3D morphological data and (b) spatially explicit Agent-Based Models (ABM) for the simulation of smart grids. 3D city models were used to assess solar potential and heat energy demand of residential buildings which enable cities to target the building refurbishment potentials. Distributed energy systems require innovative modelling techniques where individual components are represented and can interact. With this approach, several smart grid demonstrators were simulated, where heterogeneous models are spatially represented. Coupling 3D geodata with energy system ABMs holds different advantages for both approaches. On one hand, energy system models can be enhanced with high resolution data from 3D city models and their semantic relations. Furthermore, they allow for spatial analysis and visualisation of the results, with emphasis on spatially and structurally correlations among the different layers (e.g. infrastructure, buildings, administrative zones) to provide an integrated approach. On the other hand, 3D models can benefit from more detailed system description of energy infrastructure, representing dynamic phenomena and high resolution models for energy use at component level. The proposed modelling strategies
Energy and externality environmental regional model

International Nuclear Information System (INIS)

Baldi, L.; Bianchi, A.; Peri, M.

2000-01-01

The use of environmental externalities in both territorial management and the direction of energy and environment, faces the difficulties arising from their calculation. The so-called MACBET regional model, which has been constructed for Lombardy, is a first brand new attempt to overcome them. MACBET is a calculation model to assess environmental and employment externalities connected to energy use [it
Bayesian analysis for exponential random graph models using the adaptive exchange sampler

KAUST Repository

Jin, Ick Hoon; Liang, Faming; Yuan, Ying

2013-01-01

Exponential random graph models have been widely used in social network analysis. However, these models are extremely difficult to handle from a statistical viewpoint, because of the existence of intractable normalizing constants. In this paper, we
Model documentation renewable fuels module of the National Energy Modeling System

Energy Technology Data Exchange (ETDEWEB)

NONE

1997-04-01

This report documents the objectives, analytical approach, and design of the National Energy Modeling System (NEMS) Renewable Fuels Module (RFM) as it relates to the production of the 1997 Annual Energy Outlook forecasts. The report catalogues and describes modeling assumptions, computational methodologies, data inputs. and parameter estimation techniques. A number of offline analyses used in lieu of RFM modeling components are also described. This documentation report serves three purposes. First, it is a reference document for model analysts, model users, and the public interested in the construction and application of the RFM. Second, it meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its models. Finally, such documentation facilitates continuity in EIA model development by providing information sufficient to perform model enhancements and data updates as part of EIA`s ongoing mission to provide analytical and forecasting information systems.
Model documentation renewable fuels module of the National Energy Modeling System

International Nuclear Information System (INIS)

1997-04-01

This report documents the objectives, analytical approach, and design of the National Energy Modeling System (NEMS) Renewable Fuels Module (RFM) as it relates to the production of the 1997 Annual Energy Outlook forecasts. The report catalogues and describes modeling assumptions, computational methodologies, data inputs. and parameter estimation techniques. A number of offline analyses used in lieu of RFM modeling components are also described. This documentation report serves three purposes. First, it is a reference document for model analysts, model users, and the public interested in the construction and application of the RFM. Second, it meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its models. Finally, such documentation facilitates continuity in EIA model development by providing information sufficient to perform model enhancements and data updates as part of EIA's ongoing mission to provide analytical and forecasting information systems
Towards increased policy relevance in energy modeling

Energy Technology Data Exchange (ETDEWEB)

Worrell, Ernst; Ramesohl, Stephan; Boyd, Gale

2003-07-29

Historically, most energy models were reasonably equipped to assess the impact of a subsidy or change in taxation, but are often insufficient to assess the impact of more innovative policy instruments. We evaluate the models used to assess future energy use, focusing on industrial energy use. We explore approaches to engineering-economic analysis that could help improve the realism and policy relevance of engineering-economic modeling frameworks. We also explore solutions to strengthen the policy usefulness of engineering-economic analysis that can be built from a framework of multi-disciplinary cooperation. We focus on the so-called ''engineering-economic'' (or ''bottom-up'') models, as they include the amount of detail that is commonly needed to model policy scenarios. We identify research priorities for the modeling framework, technology representation in models, policy evaluation and modeling of decision-making behavior.
A CAD model for energy efficient offshore structures for desalination and energy generation

Directory of Open Access Journals (Sweden)

R. Rahul Dev,

2016-09-01

Full Text Available This paper presents a ‘Computer Aided Design (CAD’ model for energy efficient design of offshore structures. In the CAD model preliminary dimensions and geometric details of an offshore structure (i.e. semi-submersible are optimized to achieve a favorable range of motion to reduce the energy consumed by the ‘Dynamic Position System (DPS’. The presented model allows the designer to select the configuration satisfying the user requirements and integration of Computer Aided Design (CAD and Computational Fluid Dynamics (CFD. The integration of CAD with CFD computes a hydrodynamically and energy efficient hull form. Our results show that the implementation of the present model results into an design that can serve the user specified requirements with less cost and energy consumption.
A Meta Model for Domestic Energy Consumption

Directory of Open Access Journals (Sweden)

K.,J SREEKANTH

2011-01-01

Full Text Available Prediction of energy consumption particularly in micro level is of vital importance in terms of energy planning and also implementation of any Clean Development Mechanism (CDM activities that has become the order of the world today. It may be difficult to model household energy consumption using conventional methods such as time series forecasting due to many influencing factors. This paper presents a step wise regression model for forecasting domestic energy consumption based on micro level household survey data collected from Kerala, a state in southern part of India. The analysis of the data reveals significant influence of socio-economic, demographic, geographic, and family attributes upon total household energy requirements. While a wide variation in the pattern of energy requirements across the domestic sector belonging to different expenditure classes, per capita income level can be identified as the most important explanatory variable influencing variation in energy requirements. The models developed also demonstrates the influence of per capita land area, residential area among the higher income group while average age and literacy forms significant variables among the lower income group.
Analysis of a Residential Building Energy Consumption Demand Model

Directory of Open Access Journals (Sweden)

Meng Liu

2011-03-01

Full Text Available In order to estimate the energy consumption demand of residential buildings, this paper first discusses the status and shortcomings of current domestic energy consumption models. Then it proposes and develops a residential building energy consumption demand model based on a back propagation (BP neural network model. After that, taking residential buildings in Chongqing (P.R. China as an example, 16 energy consumption indicators are introduced as characteristics of the residential buildings in Chongqing. The index system of the BP neutral network prediction model is established and the multi-factorial BP neural network prediction model of Chongqing residential building energy consumption is developed using the Cshap language, based on the SQL server 2005 platform. The results obtained by applying the model in Chongqing are in good agreement with actual ones. In addition, the model provides corresponding approximate data by taking into account the potential energy structure adjustments and relevant energy policy regulations.

Two sustainable energy system analysis models

DEFF Research Database (Denmark)

Lund, Henrik; Goran Krajacic, Neven Duic; da Graca Carvalho, Maria

2005-01-01

This paper presents a comparative study of two energy system analysis models both designed with the purpose of analysing electricity systems with a substantial share of fluctuating renewable energy....
Model Diagnostics for the Department of Energy's Accelerated Climate Modeling for Energy (ACME) Project

Science.gov (United States)

Smith, B.

2015-12-01

In 2014, eight Department of Energy (DOE) national laboratories, four academic institutions, one company, and the National Centre for Atmospheric Research combined forces in a project called Accelerated Climate Modeling for Energy (ACME) with the goal to speed Earth system model development for climate and energy. Over the planned 10-year span, the project will conduct simulations and modeling on DOE's most powerful high-performance computing systems at Oak Ridge, Argonne, and Lawrence Berkeley Leadership Compute Facilities. A key component of the ACME project is the development of an interactive test bed for the advanced Earth system model. Its execution infrastructure will accelerate model development and testing cycles. The ACME Workflow Group is leading the efforts to automate labor-intensive tasks, provide intelligent support for complex tasks and reduce duplication of effort through collaboration support. As part of this new workflow environment, we have created a diagnostic, metric, and intercomparison Python framework, called UVCMetrics, to aid in the testing-to-production execution of the ACME model. The framework exploits similarities among different diagnostics to compactly support diagnosis of new models. It presently focuses on atmosphere and land but is designed to support ocean and sea ice model components as well. This framework is built on top of the existing open-source software framework known as the Ultrascale Visualization Climate Data Analysis Tools (UV-CDAT). Because of its flexible framework design, scientists and modelers now can generate thousands of possible diagnostic outputs. These diagnostics can compare model runs, compare model vs. observation, or simply verify a model is physically realistic. Additional diagnostics are easily integrated into the framework, and our users have already added several. Diagnostics can be generated, viewed, and manipulated from the UV-CDAT graphical user interface, Python command line scripts and programs
Generic Energy Matching Model and Figure of Matching Algorithm for Combined Renewable Energy Systems

Directory of Open Access Journals (Sweden)

J.C. Brezet

2009-08-01

Full Text Available In this paper the Energy Matching Model and Figure of Matching Algorithm which originally was dedicated only to photovoltaic (PV systems [1] are extended towards a Model and Algorithm suitable for combined systems which are a result of integration of two or more renewable energy sources into one. The systems under investigation will range from mobile portable devices up to the large renewable energy system conceivably to be applied at the Afsluitdijk (Closure- dike in the north of the Netherlands. This Afsluitdijk is the major dam in the Netherlands, damming off the Zuiderzee, a salt water inlet of the North Sea and turning it into the fresh water lake of the IJsselmeer. The energy chain of power supplies based on a combination of renewable energy sources can be modeled by using one generic Energy Matching Model as starting point.
Dielectric Matrix Formulation of Correlation Energies in the Random Phase Approximation: Inclusion of Exchange Effects.

Science.gov (United States)

Mussard, Bastien; Rocca, Dario; Jansen, Georg; Ángyán, János G

2016-05-10

Starting from the general expression for the ground state correlation energy in the adiabatic-connection fluctuation-dissipation theorem (ACFDT) framework, it is shown that the dielectric matrix formulation, which is usually applied to calculate the direct random phase approximation (dRPA) correlation energy, can be used for alternative RPA expressions including exchange effects. Within this famework, the ACFDT analog of the second order screened exchange (SOSEX) approximation leads to a logarithmic formula for the correlation energy similar to the direct RPA expression. Alternatively, the contribution of the exchange can be included in the kernel used to evaluate the response functions. In this case, the use of an approximate kernel is crucial to simplify the formalism and to obtain a correlation energy in logarithmic form. Technical details of the implementation of these methods are discussed, and it is shown that one can take advantage of density fitting or Cholesky decomposition techniques to improve the computational efficiency; a discussion on the numerical quadrature made on the frequency variable is also provided. A series of test calculations on atomic correlation energies and molecular reaction energies shows that exchange effects are instrumental for improvement over direct RPA results.
Modelization of three-dimensional bone micro-architecture using Markov random fields with a multi-level clique system

International Nuclear Information System (INIS)

Lamotte, T.; Dinten, J.M.; Peyrin, F.

2004-01-01

Imaging trabecular bone micro-architecture in vivo non-invasively is still a challenging issue due to the complexity and small size of the structure. Thus, having a realistic 3D model of bone micro-architecture could be useful in image segmentation or image reconstruction. The goal of this work was to develop a 3D model of trabecular bone micro-architecture which can be seen as a problem of texture synthesis. We investigated a statistical model based on 3D Markov Random Fields (MRF's). Due to the Hammersley-Clifford theorem MRF's may equivalently be defined by an energy function on some set of cliques. In order to model 3D binary bone texture images (bone / background), we first used a particular well-known subclass of MRFs: the Ising model. The local energy function at some voxel depends on the closest neighbors of the voxels and on some parameters which control the shape and the proportion of bone. However, simulations yielded textures organized as connected clusters which even when varying the parameters did not approach the complexity of bone micro-architecture. Then, we introduced a second level of cliques taking into account neighbors located at some distance d from the site s and a new set of cliques allowing to control the plate thickness and spacing. The 3D bone texture images generated using the proposed model were analyzed using the usual bone-architecture quantification tools in order to relate the parameters of the MRF model to the characteristic parameters of bone micro-architecture (trabecular spacing, trabecular thickness, number of trabeculae...). (authors)
Interacting holographic dark energy models: a general approach

Science.gov (United States)

Som, S.; Sil, A.

2014-08-01

Dark energy models inspired by the cosmological holographic principle are studied in homogeneous isotropic spacetime with a general choice for the dark energy density . Special choices of the parameters enable us to obtain three different holographic models, including the holographic Ricci dark energy (RDE) model. Effect of interaction between dark matter and dark energy on the dynamics of those models are investigated for different popular forms of interaction. It is found that crossing of phantom divide can be avoided in RDE models for β>0.5 irrespective of the presence of interaction. A choice of α=1 and β=2/3 leads to a varying Λ-like model introducing an IR cutoff length Λ -1/2. It is concluded that among the popular choices an interaction of the form Q∝ Hρ m suits the best in avoiding the coincidence problem in this model.
A model for Long-term Industrial Energy Forecasting (LIEF)

Energy Technology Data Exchange (ETDEWEB)

Ross, M. (Lawrence Berkeley Lab., CA (United States) Michigan Univ., Ann Arbor, MI (United States). Dept. of Physics Argonne National Lab., IL (United States). Environmental Assessment and Information Sciences Div.); Hwang, R. (Lawrence Berkeley Lab., CA (United States))

1992-02-01

The purpose of this report is to establish the content and structural validity of the Long-term Industrial Energy Forecasting (LIEF) model, and to provide estimates for the model's parameters. The model is intended to provide decision makers with a relatively simple, yet credible tool to forecast the impacts of policies which affect long-term energy demand in the manufacturing sector. Particular strengths of this model are its relative simplicity which facilitates both ease of use and understanding of results, and the inclusion of relevant causal relationships which provide useful policy handles. The modeling approach of LIEF is intermediate between top-down econometric modeling and bottom-up technology models. It relies on the following simple concept, that trends in aggregate energy demand are dependent upon the factors: (1) trends in total production; (2) sectoral or structural shift, that is, changes in the mix of industrial output from energy-intensive to energy non-intensive sectors; and (3) changes in real energy intensity due to technical change and energy-price effects as measured by the amount of energy used per unit of manufacturing output (KBtu per constant $ of output). The manufacturing sector is first disaggregated according to their historic output growth rates, energy intensities and recycling opportunities. Exogenous, macroeconomic forecasts of individual subsector growth rates and energy prices can then be combined with endogenous forecasts of real energy intensity trends to yield forecasts of overall energy demand. 75 refs.
Net energy analysis in a Ramsey–Hotelling growth model

International Nuclear Information System (INIS)

Macías, Arturo; Matilla-García, Mariano

2015-01-01

This article presents a dynamic growth model with energy as an input in the production function. The available stock of energy resources is ordered by a quality parameter based on energy accounting: the “Energy Return on Energy Invested” (EROI). In our knowledge this is the first paper where EROI fits in a neoclassical growth model (with individual utility maximization and market equilibrium), establishing the economic use of “net energy analysis” on a firmer theoretical ground. All necessary concepts to link neoclassical economics and EROI are discussed before their use in the model, and a comparative static analysis of the steady states of a simplified version of the model is presented. - Highlights: • A neoclassical growth model with EROI (“Energy Return on Energy Invested”) is shown • All concepts linking neoclassical economics and net energy analysis are discussed • Any EROI decline can be compensated increasing gross activity in the energy sector. • The economic impact of EROI depends on some non-energy cost in the energy sector. • Comparative steady-state statics for different EROI levels is performed and discussed. • Policy implications are suggested.
Deterministic models for energy-loss straggling

International Nuclear Information System (INIS)

Prinja, A.K.; Gleicher, F.; Dunham, G.; Morel, J.E.

1999-01-01

Inelastic ion interactions with target electrons are dominated by extremely small energy transfers that are difficult to resolve numerically. The continuous-slowing-down (CSD) approximation is then commonly employed, which, however, only preserves the mean energy loss per collision through the stopping power, S(E) = ∫ 0 ∞ dEprime (E minus Eprime) σ s (E → Eprime). To accommodate energy loss straggling, a Gaussian distribution with the correct mean-squared energy loss (akin to a Fokker-Planck approximation in energy) is commonly used in continuous-energy Monte Carlo codes. Although this model has the unphysical feature that ions can be upscattered, it nevertheless yields accurate results. A multigroup model for energy loss straggling was recently presented for use in multigroup Monte Carlo codes or in deterministic codes that use multigroup data. The method has the advantage that the mean and mean-squared energy loss are preserved without unphysical upscatter and hence is computationally efficient. Results for energy spectra compared extremely well with Gaussian distributions under the idealized conditions for which the Gaussian may be considered to be exact. Here, the authors present more consistent comparisons by extending the method to accommodate upscatter and, further, compare both methods with exact solutions obtained from an analog Monte Carlo simulation, for a straight-ahead transport problem
Calculating radiotherapy margins based on Bayesian modelling of patient specific random errors

International Nuclear Information System (INIS)

Herschtal, A; Te Marvelde, L; Mengersen, K; Foroudi, F; Ball, D; Devereux, T; Pham, D; Greer, P B; Pichler, P; Eade, T; Kneebone, A; Bell, L; Caine, H; Hindson, B; Kron, T; Hosseinifard, Z

2015-01-01

Collected real-life clinical target volume (CTV) displacement data show that some patients undergoing external beam radiotherapy (EBRT) demonstrate significantly more fraction-to-fraction variability in their displacement (‘random error’) than others. This contrasts with the common assumption made by historical recipes for margin estimation for EBRT, that the random error is constant across patients. In this work we present statistical models of CTV displacements in which random errors are characterised by an inverse gamma (IG) distribution in order to assess the impact of random error variability on CTV-to-PTV margin widths, for eight real world patient cohorts from four institutions, and for different sites of malignancy. We considered a variety of clinical treatment requirements and penumbral widths. The eight cohorts consisted of a total of 874 patients and 27 391 treatment sessions. Compared to a traditional margin recipe that assumes constant random errors across patients, for a typical 4 mm penumbral width, the IG based margin model mandates that in order to satisfy the common clinical requirement that 90% of patients receive at least 95% of prescribed RT dose to the entire CTV, margins be increased by a median of 10% (range over the eight cohorts −19% to +35%). This substantially reduces the proportion of patients for whom margins are too small to satisfy clinical requirements. (paper)
Electrostatic energy harvesting device with dual resonant structure for wideband random vibration sources at low frequency.

Science.gov (United States)

Zhang, Yulong; Wang, Tianyang; Zhang, Ai; Peng, Zhuoteng; Luo, Dan; Chen, Rui; Wang, Fei

2016-12-01

In this paper, we present design and test of a broadband electrostatic energy harvester with a dual resonant structure, which consists of two cantilever-mass subsystems each with a mass attached at the free edge of a cantilever. Comparing to traditional devices with single resonant frequency, the proposed device with dual resonant structure can resonate at two frequencies. Furthermore, when one of the cantilever-masses is oscillating at resonance, the vibration amplitude is large enough to make it collide with the other mass, which provides strong mechanical coupling between the two subsystems. Therefore, this device can harvest a decent power output from vibration sources at a broad frequency range. During the measurement, continuous power output up to 6.2-9.8 μW can be achieved under external vibration amplitude of 9.3 m/s 2 at a frequency range from 36.3 Hz to 48.3 Hz, which means the bandwidth of the device is about 30% of the central frequency. The broad bandwidth of the device provides a promising application for energy harvesting from the scenarios with random vibration sources. The experimental results indicate that with the dual resonant structure, the vibration-to-electricity energy conversion efficiency can be improved by 97% when an external random vibration with a low frequency filter is applied.
Stochastic geometry, spatial statistics and random fields models and algorithms

CERN Document Server

2015-01-01

Providing a graduate level introduction to various aspects of stochastic geometry, spatial statistics and random fields, this volume places a special emphasis on fundamental classes of models and algorithms as well as on their applications, for example in materials science, biology and genetics. This book has a strong focus on simulations and includes extensive codes in Matlab and R, which are widely used in the mathematical community. It can be regarded as a continuation of the recent volume 2068 of Lecture Notes in Mathematics, where other issues of stochastic geometry, spatial statistics and random fields were considered, with a focus on asymptotic methods.
Variable Renewable Energy in Long-Term Planning Models: A Multi-Model Perspective

Energy Technology Data Exchange (ETDEWEB)

Cole, Wesley [National Renewable Energy Lab. (NREL), Golden, CO (United States); Frew, Bethany [National Renewable Energy Lab. (NREL), Golden, CO (United States); Mai, Trieu [National Renewable Energy Lab. (NREL), Golden, CO (United States); Sun, Yinong [National Renewable Energy Lab. (NREL), Golden, CO (United States); Bistline, John [Electric Power Research Inst. (EPRI), Knoxville, TN (United States); Blanford, Geoffrey [Electric Power Research Inst. (EPRI), Knoxville, TN (United States); Young, David [Electric Power Research Inst. (EPRI), Knoxville, TN (United States); Marcy, Cara [U.S. Energy Information Administration, Washington, DC (United States); Namovicz, Chris [U.S. Energy Information Administration, Washington, DC (United States); Edelman, Risa [US Environmental Protection Agency (EPA), Washington, DC (United States); Meroney, Bill [US Environmental Protection Agency (EPA), Washington, DC (United States); Sims, Ryan [US Environmental Protection Agency (EPA), Washington, DC (United States); Stenhouse, Jeb [US Environmental Protection Agency (EPA), Washington, DC (United States); Donohoo-Vallett, Paul [Dept. of Energy (DOE), Washington DC (United States)

2017-11-01

Long-term capacity expansion models of the U.S. electricity sector have long been used to inform electric sector stakeholders and decision-makers. With the recent surge in variable renewable energy (VRE) generators — primarily wind and solar photovoltaics — the need to appropriately represent VRE generators in these long-term models has increased. VRE generators are especially difficult to represent for a variety of reasons, including their variability, uncertainty, and spatial diversity. This report summarizes the analyses and model experiments that were conducted as part of two workshops on modeling VRE for national-scale capacity expansion models. It discusses the various methods for treating VRE among four modeling teams from the Electric Power Research Institute (EPRI), the U.S. Energy Information Administration (EIA), the U.S. Environmental Protection Agency (EPA), and the National Renewable Energy Laboratory (NREL). The report reviews the findings from the two workshops and emphasizes the areas where there is still need for additional research and development on analysis tools to incorporate VRE into long-term planning and decision-making. This research is intended to inform the energy modeling community on the modeling of variable renewable resources, and is not intended to advocate for or against any particular energy technologies, resources, or policies.
Model documentation Renewable Fuels Module of the National Energy Modeling System

Energy Technology Data Exchange (ETDEWEB)

NONE

1996-01-01

This report documents the objectives, analaytical approach and design of the National Energy Modeling System (NEMS) Renewable Fuels Module (RFM) as it relates to the production of the 1996 Annual Energy Outlook forecasts. The report catalogues and describes modeling assumptions, computational methodologies, data inputs, and parameter estimation techniques. A number of offline analyses used in lieu of RFM modeling components are also described.
Comparison of the Predictive Performance and Interpretability of Random Forest and Linear Models on Benchmark Data Sets.

Science.gov (United States)

Marchese Robinson, Richard L; Palczewska, Anna; Palczewski, Jan; Kidley, Nathan

2017-08-28

The ability to interpret the predictions made by quantitative structure-activity relationships (QSARs) offers a number of advantages. While QSARs built using nonlinear modeling approaches, such as the popular Random Forest algorithm, might sometimes be more predictive than those built using linear modeling approaches, their predictions have been perceived as difficult to interpret. However, a growing number of approaches have been proposed for interpreting nonlinear QSAR models in general and Random Forest in particular. In the current work, we compare the performance of Random Forest to those of two widely used linear modeling approaches: linear Support Vector Machines (SVMs) (or Support Vector Regression (SVR)) and partial least-squares (PLS). We compare their performance in terms of their predictivity as well as the chemical interpretability of the predictions using novel scoring schemes for assessing heat map images of substructural contributions. We critically assess different approaches for interpreting Random Forest models as well as for obtaining predictions from the forest. We assess the models on a large number of widely employed public-domain benchmark data sets corresponding to regression and binary classification problems of relevance to hit identification and toxicology. We conclude that Random Forest typically yields comparable or possibly better predictive performance than the linear modeling approaches and that its predictions may also be interpreted in a chemically and biologically meaningful way. In contrast to earlier work looking at interpretation of nonlinear QSAR models, we directly compare two methodologically distinct approaches for interpreting Random Forest models. The approaches for interpreting Random Forest assessed in our article were implemented using open-source programs that we have made available to the community. These programs are the rfFC package ( https://r-forge.r-project.org/R/?group_id=1725 ) for the R statistical
Model documentation report: Industrial sector demand module of the National Energy Modeling System

International Nuclear Information System (INIS)

1997-01-01

This report documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Industrial Demand Model. The report catalogues and describes model assumptions, computational methodology, parameter estimation techniques, and model source code. This document serves three purposes. First, it is a reference document providing a detailed description of the NEMS Industrial Model for model analysts, users, and the public. Second, this report meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its models. Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements as future projects. The NEMS Industrial Demand Model is a dynamic accounting model, bringing together the disparate industries and uses of energy in those industries, and putting them together in an understandable and cohesive framework. The Industrial Model generates mid-term (up to the year 2015) forecasts of industrial sector energy demand as a component of the NEMS integrated forecasting system. From the NEMS system, the Industrial Model receives fuel prices, employment data, and the value of industrial output. Based on the values of these variables, the Industrial Model passes back to the NEMS system estimates of consumption by fuel types
A Novel Algorithm of Quantum Random Walk in Server Traffic Control and Task Scheduling

Directory of Open Access Journals (Sweden)

Dong Yumin

2014-01-01

Full Text Available A quantum random walk optimization model and algorithm in network cluster server traffic control and task scheduling is proposed. In order to solve the problem of server load balancing, we research and discuss the distribution theory of energy field in quantum mechanics and apply it to data clustering. We introduce the method of random walk and illuminate what the quantum random walk is. Here, we mainly research the standard model of one-dimensional quantum random walk. For the data clustering problem of high dimensional space, we can decompose one m-dimensional quantum random walk into m one-dimensional quantum random walk. In the end of the paper, we compare the quantum random walk optimization method with GA (genetic algorithm, ACO (ant colony optimization, and SAA (simulated annealing algorithm. In the same time, we prove its validity and rationality by the experiment of analog and simulation.
The methodology of energy policy-making in economical models

Energy Technology Data Exchange (ETDEWEB)

Poursina, B.

1998-08-01

Scrutiny and careful study in energy is a subject that in human science has been investigated from different point of view. The expansion of this research, because of its importance and effect in different dimensions of human life, has also arrived in the field of political and economic sciences. Economics evaluates the energy phenomenon at the side of elements such as labor, capital and technology in the production functions of firms. The nature of these discussions is mainly from the viewpoint of micro analyses. Nevertheless, the variation and challenges concerning energy and environment during the recent decades and the economists` detailed investigations in its analysis and evaluation have led to the arrival of energy discussions in a special shape in macro planning and large economic models. The paper compares various energy models - EFDM, MEDEE, MIDAS and HERMES. This extent of planning and consequently modelling which lacks a background in the processes of economic researches, deals with analysis of energy and economics reacting effects. Modelling of energy-economy interaction and energy policy in modeling macroeconomics large models are new ideas in energy studies and economics. 7 refs., 6 figs., 1 tab.
Possibility/Necessity-Based Probabilistic Expectation Models for Linear Programming Problems with Discrete Fuzzy Random Variables

Directory of Open Access Journals (Sweden)

Hideki Katagiri

2017-10-01

Full Text Available This paper considers linear programming problems (LPPs where the objective functions involve discrete fuzzy random variables (fuzzy set-valued discrete random variables. New decision making models, which are useful in fuzzy stochastic environments, are proposed based on both possibility theory and probability theory. In multi-objective cases, Pareto optimal solutions of the proposed models are newly defined. Computational algorithms for obtaining the Pareto optimal solutions of the proposed models are provided. It is shown that problems involving discrete fuzzy random variables can be transformed into deterministic nonlinear mathematical programming problems which can be solved through a conventional mathematical programming solver under practically reasonable assumptions. A numerical example of agriculture production problems is given to demonstrate the applicability of the proposed models to real-world problems in fuzzy stochastic environments.
Energy-transfer properties and mechanisms:

International Nuclear Information System (INIS)

Barker, J.R.

1988-02-01

This project continues the research on vibrational energy transfer involving large molecules. The motivation of the research is to advance knowledge concerning molecular energy in the electronic ground state so that meaningful predictions can be made. The experimental program will use several techniques on several different molecules with the aim of eliminating experimental artifacts and gaining more insight into energy transfer processes. The theoretical effort will be directed toward assessing the validity of the Biased Random Walk theory and toward developing simpler models that adequately describe the energy transfer process. 6 figs

Reactive Power Pricing Model Considering the Randomness of Wind Power Output

Science.gov (United States)

Dai, Zhong; Wu, Zhou

2018-01-01

With the increase of wind power capacity integrated into grid, the influence of the randomness of wind power output on the reactive power distribution of grid is gradually highlighted. Meanwhile, the power market reform puts forward higher requirements for reasonable pricing of reactive power service. Based on it, the article combined the optimal power flow model considering wind power randomness with integrated cost allocation method to price reactive power. Meanwhile, considering the advantages and disadvantages of the present cost allocation method and marginal cost pricing, an integrated cost allocation method based on optimal power flow tracing is proposed. The model realized the optimal power flow distribution of reactive power with the minimal integrated cost and wind power integration, under the premise of guaranteeing the balance of reactive power pricing. Finally, through the analysis of multi-scenario calculation examples and the stochastic simulation of wind power outputs, the article compared the results of the model pricing and the marginal cost pricing, which proved that the model is accurate and effective.
Protein homology model refinement by large-scale energy optimization.

Science.gov (United States)

Park, Hahnbeom; Ovchinnikov, Sergey; Kim, David E; DiMaio, Frank; Baker, David

2018-03-20

Proteins fold to their lowest free-energy structures, and hence the most straightforward way to increase the accuracy of a partially incorrect protein structure model is to search for the lowest-energy nearby structure. This direct approach has met with little success for two reasons: first, energy function inaccuracies can lead to false energy minima, resulting in model degradation rather than improvement; and second, even with an accurate energy function, the search problem is formidable because the energy only drops considerably in the immediate vicinity of the global minimum, and there are a very large number of degrees of freedom. Here we describe a large-scale energy optimization-based refinement method that incorporates advances in both search and energy function accuracy that can substantially improve the accuracy of low-resolution homology models. The method refined low-resolution homology models into correct folds for 50 of 84 diverse protein families and generated improved models in recent blind structure prediction experiments. Analyses of the basis for these improvements reveal contributions from both the improvements in conformational sampling techniques and the energy function.
Modeling primary energy substitution in the Asia Pacific

International Nuclear Information System (INIS)

Aguilera, Roberto F.; Ripple, Ronald D.

2013-01-01

Highlights: • We model the market shares (i.e. energy mix) of gases, liquids and solids in the Asia Pacific. • The model matches the historical energy mix and projects three scenarios of the future mix to 2030. • We then model the past and future hydrogen to carbon ratio (a proxy for environmental quality). • Importance of natural gas in the region could increase significantly, depending on policy and tech progress. - Abstract: A Global Energy Market model (GEM) is used to analyze the market shares (i.e. the primary energy mix) of gases, liquids and solids in the Asia Pacific. The model is successful in matching the historical energy mix from 1850 to 2009. The model also provides a good match of the hydrogen to carbon ratio, which is a proxy for environmental quality. Given these validations, the GEM is then used to present scenarios of the Asia Pacific energy mix and hydrogen to carbon ratio until the year 2030. Three energy mix scenarios are presented – reference case; alternative case 1; alternative case 2. The reference case assumes limited divergence from current policies and technologies. It indicates that Asia Pacific energy needs will be met by approximately 46% solids, 34% liquids, and 20% gases by 2030. Alternative cases 1 and 2 represent policies and technologies that either encourage or discourage the use of gases. The good matches observed for historical data suggest the GEM can be used cautiously for evaluating outcomes and opportunities in the region. Although the model can be used for projecting far into the future, it is currently calibrated to what we consider a reasonable time horizon – until the year 2030. Given appropriate energy policies and sufficient technological advancement, the importance of natural gas in the region could increase significantly
Genetic evaluation of European quails by random regression models

Directory of Open Access Journals (Sweden)

Flaviana Miranda Gonçalves

2012-09-01

Full Text Available The objective of this study was to compare different random regression models, defined from different classes of heterogeneity of variance combined with different Legendre polynomial orders for the estimate of (covariance of quails. The data came from 28,076 observations of 4,507 female meat quails of the LF1 lineage. Quail body weights were determined at birth and 1, 14, 21, 28, 35 and 42 days of age. Six different classes of residual variance were fitted to Legendre polynomial functions (orders ranging from 2 to 6 to determine which model had the best fit to describe the (covariance structures as a function of time. According to the evaluated criteria (AIC, BIC and LRT, the model with six classes of residual variances and of sixth-order Legendre polynomial was the best fit. The estimated additive genetic variance increased from birth to 28 days of age, and dropped slightly from 35 to 42 days. The heritability estimates decreased along the growth curve and changed from 0.51 (1 day to 0.16 (42 days. Animal genetic and permanent environmental correlation estimates between weights and age classes were always high and positive, except for birth weight. The sixth order Legendre polynomial, along with the residual variance divided into six classes was the best fit for the growth rate curve of meat quails; therefore, they should be considered for breeding evaluation processes by random regression models.
Modelling the hydrokinetic energy resource for in-stream energy converters

International Nuclear Information System (INIS)

Lalander, Emilia

2010-01-01

Hydrokinetic energy, referring to the energy contained in moving water, is a renewable energy source that has gained much attention the past years. The energy is found in all moving water masses, but is only economical to convert for water masses moving with high velocity, i.e. likely around 1 m/s and above. This energy can for example be found in tidal, ocean and river currents which flow through narrow straits and channels. Along the west coast of Norway, there are many sites where kinetic energy conversion would be possible due to the strong current present. The driving force behind the currents is the tidal wave that progresses northward along the coast and increases in strength. The models that so far have been used for estimating the resource in Norway have been shown to be uncertain since they do not account for the fact that the velocities and the water levels are altered when energy is extracted. These effects can be simulated with numerical models. A channel in the Dal river, the Soederfors channel, is situated downstream a hydropower plant and was simulated with the numerical model MIKE. The water level alteration due to turbines was simulated. It was shown to be a lot less than the water level alteration caused by the level change in the downstream lake. Velocity profiles measured at several different locations were used to estimate how the power coefficient was changed. Four turbine configurations were studied and it was shown that changes in the power coefficient were prominent only for a vertical shear profile with a strong gradient. At the Div. of Electricity, studies have been conducted on how to convert hydrokinetic energy to electricity since 2003. The main idea has been to use a system that limits the need for maintenance. The concept studied is a vertical axis turbine directly coupled to a permanent magnet generator. The Soederfors channel has, due to aspects such as the flow properties and velocity, been chosen as a site for an experimental
Modeling and understanding of effects of randomness in arrays of resonant meta-atoms

DEFF Research Database (Denmark)

Tretyakov, Sergei A.; Albooyeh, Mohammad; Alitalo, Pekka

2013-01-01

In this review presentation we will discuss approaches to modeling and understanding electromagnetic properties of 2D and 3D lattices of small resonant particles (meta-atoms) in transition from regular (periodic) to random (amorphous) states. Nanostructured metasurfaces (2D) and metamaterials (3D......) are arrangements of optically small but resonant particles (meta-atoms). We will present our results on analytical modeling of metasurfaces with periodical and random arrangements of electrically and magnetically resonant meta-atoms with identical or random sizes, both for the normal and oblique-angle excitations....... We show how the electromagnetic response of metasurfaces is related to the statistical parameters of the structure. Furthermore, we will discuss the phenomenon of anti-resonance in extracted effective parameters of metamaterials and clarify its relation to the periodicity (or amorphous nature...
Analytical connection between thresholds and immunization strategies of SIS model in random networks

Science.gov (United States)

Zhou, Ming-Yang; Xiong, Wen-Man; Liao, Hao; Wang, Tong; Wei, Zong-Wen; Fu, Zhong-Qian

2018-05-01

Devising effective strategies for hindering the propagation of viruses and protecting the population against epidemics is critical for public security and health. Despite a number of studies based on the susceptible-infected-susceptible (SIS) model devoted to this topic, we still lack a general framework to compare different immunization strategies in completely random networks. Here, we address this problem by suggesting a novel method based on heterogeneous mean-field theory for the SIS model. Our method builds the relationship between the thresholds and different immunization strategies in completely random networks. Besides, we provide an analytical argument that the targeted large-degree strategy achieves the best performance in random networks with arbitrary degree distribution. Moreover, the experimental results demonstrate the effectiveness of the proposed method in both artificial and real-world networks.
Randomized Lagrangian Relaxation and their contribution to the development of automated electricity markets for distributed energy resources

International Nuclear Information System (INIS)

Ruthe, Sebastian

2015-01-01

The ongoing shift towards decentralized power systems and the related rapidly growing number of decentralized energy resources (DER) like wind- and PV-units, CHP-units, storage devices and shiftable loads requires new information systems and control algorithms in order to pland and optimize the commitment of DER in line with the conventional generation system. In this context the paradigm of market based control derived from the Lagrangian relaxation of the unit commitment problem represents a promising solution approach to build highly scalable distributed systems able to perform this task within the required time limits. Market based control approaches typically achieve high quality solutions and protect the private data of the controlled units. However in case of DER with discontinuous utility functions market based control approaches suffer under the problem of ''joint commitment'', which may lead to a divergence of the iterative solution algorithm resulting in highly cost inefficient solutions. This thesis introduces a new concept of randomizing the Lagrangian multipliers to spread the individual commitment thresholds of DER thereby mitigating th negative effects of ''joint commitments''. Based on the randomized solution approach different boundaries for the solution quality regarding the overall energy production costs and the equilibrium constraints are established. Furthermore it is shown how the developed approach can be utilized to build new scalable information systems for future energy markets and their interfaces to the existing energy markets.
The dilute random field Ising model by finite cluster approximation

International Nuclear Information System (INIS)

Benyoussef, A.; Saber, M.

1987-09-01

Using the finite cluster approximation, phase diagrams of bond and site diluted three-dimensional simple cubic Ising models with a random field have been determined. The resulting phase diagrams have the same general features for both bond and site dilution. (author). 7 refs, 4 figs
Energy expenditure in people with transtibial amputation walking with crossover and energy storing prosthetic feet: A randomized within-subject study.

Science.gov (United States)

McDonald, Cody L; Kramer, Patricia A; Morgan, Sara J; Halsne, Elizabeth G; Cheever, Sarah M; Hafner, Brian J

2018-05-01

Energy storing feet are unable to reduce the energy required for normal locomotion among people with transtibial amputation. Crossover feet, which incorporate aspects of energy storing and running specific feet, are designed to maximize energy return while providing stability for everyday activities. Do crossover prosthetic feet reduce the energy expenditure of walking across a range of speeds, when compared with energy storing feet among people with transtibial amputation due to non-dysvascular causes? A randomized within-subject study was conducted with a volunteer sample of twenty-seven adults with unilateral transtibial amputation due to non-dysvascular causes. Participants were fit with two prostheses. One had an energy storing foot (Össur Variflex) and the other a crossover foot (Össur Cheetah Xplore). Other components, including sockets, suspension, and interface were standardized. Energy expenditure was measured with a portable respirometer (Cosmed K4b2) while participants walked on a treadmill at self-selected slow, comfortable, and fast speeds with each prosthesis. Gross oxygen consumption rates (VO 2  ml/min) were compared between foot conditions. Energy storing feet were used as the baseline condition because they are used by most people with a lower limb prosthesis. Analyses were performed to identify people who may benefit from transition to crossover feet. On average, participants had lower oxygen consumption in the crossover foot condition compared to the energy storing foot condition at each self-selected walking speed, but this difference was not statistically significant. Participants with farther six-minute walk test distances, higher daily step counts, and higher Medicare Functional Classification Levels at baseline were more likely to use less energy in the crossover foot. Crossover feet may be most beneficial for people with higher activity levels and physical fitness. Further research is needed to examine the effect of crossover feet on
Quantum phase transitions in random XY spin chains

International Nuclear Information System (INIS)

Bunder, J.E.; McKenzie, R.H.

2000-01-01

Full text: The XY spin chain in a transverse field is one of the simplest quantum spin models. It is a reasonable model for heavy fermion materials such as CeCu 6-x Au x . It has two quantum phase transitions: the Ising transition and the anisotropic transition. Quantum phase transitions occur at zero temperature. We are investigating what effect the introduction of randomness has on these quantum phase transitions. Disordered systems which undergo quantum phase transitions can exhibit new universality classes. The universality class of a phase transition is defined by the set of critical exponents. In a random system with quantum phase transitions we can observe Griffiths-McCoy singularities. Such singularities are observed in regions which have no long range order, so they are not classified as critical regions, yet they display phenomena normally associated with critical points, such as a diverging susceptibility. Griffiths-McCoy phases are due to rare regions with stronger than! average interactions and may be present far from the quantum critical point. We show how the random XY spin chain may be mapped onto a random Dirac equation. This allows us to calculate the density of states without making any approximations. From the density of states we can describe the conditions which should allow a Griffiths-McCoy phase. We find that for the Ising transition the dynamic critical exponent, z, is not universal. It is proportional to the disorder strength and inversely proportional to the energy gap, hence z becomes infinite at the critical point where the energy gap vanishes
Application of the load flow and random flow models for the analysis of power transmission networks

International Nuclear Information System (INIS)

Zio, Enrico; Piccinelli, Roberta; Delfanti, Maurizio; Olivieri, Valeria; Pozzi, Mauro

2012-01-01

In this paper, the classical load flow model and the random flow model are considered for analyzing the performance of power transmission networks. The analysis concerns both the system performance and the importance of the different system elements; this latter is computed by power flow and random walk betweenness centrality measures. A network system from the literature is analyzed, representing a simple electrical power transmission network. The results obtained highlight the differences between the LF “global approach” to flow dispatch and the RF local approach of randomized node-to-node load transfer. Furthermore, computationally the LF model is less consuming than the RF model but problems of convergence may arise in the LF calculation.
Modeling of long-term energy system of Japan

International Nuclear Information System (INIS)

Gotoh, Yoshitaka; Sato, Osamu; Tadokoro, Yoshihiro

1999-07-01

In order to analyze the future potential of reducing carbon dioxide emissions, the long-term energy system of Japan was modeled following the framework of the MARKAL model, and the database of energy technology characteristics was developed. First, a reference energy system was built by incorporating all important energy sources and technologies that will be available until the year 2050. This system consists of 25 primary energy sources, 33 technologies for electric power generation and/or low temperature heat production, 97 technologies for energy transformation, storage, and distribution, and 170 end-use technologies. Second, the database was developed for the characteristics of individual technologies in the system. The characteristic data consists of input and output of energy carriers, efficiency, availability, lifetime, investment cost, operation and maintenance cost, CO 2 emission coefficient, and others. Since a large number of technologies are included in the system, this report focuses modeling of a supply side, and involves the database of energy technologies other than for end-use purposes. (author)
Direct regional energy/economic modeling (DREEM) design

Energy Technology Data Exchange (ETDEWEB)

Hall, P.D.; Pleatsikas, C.J.

1979-10-01

This report summarizes an investigation into the use of regional and multiregional economic models for estimating the indirect and induced impacts of Federally-mandated energy policies. It includes an examination of alternative types of energy policies that can impact regional economies and the available analytical frameworks for measuring the magnitudes and spatial extents of these impacts. One such analytical system, the National Regional Impact Evaluation System (NRIES), currently operational in the Bureau of Economic Analysis (BEA), is chosen for more detailed investigation. The report summarizes the models capabilities for addressing various energy policy issues and then demonstrates the applicability of the model in specified contexts by developing appropriate input data for three scenarios. These scenarios concern the multi-state impacts of alternative coal-mining-development decisions, multi-regional impacts of macroeconomic change, and the comprehensive effects of an alternative national energy supply trajectory. On the basis of this experience, the capabilities of NRIES for analyzing energy-policy issues are summarized in a concluding chapter.
Topics in random walks in random environment

International Nuclear Information System (INIS)

Sznitman, A.-S.

2004-01-01

Over the last twenty-five years random motions in random media have been intensively investigated and some new general methods and paradigms have by now emerged. Random walks in random environment constitute one of the canonical models of the field. However in dimension bigger than one they are still poorly understood and many of the basic issues remain to this day unresolved. The present series of lectures attempt to give an account of the progresses which have been made over the last few years, especially in the study of multi-dimensional random walks in random environment with ballistic behavior. (author)
Does quasi-long-range order in the two-dimensional XY model really survive weak random phase fluctuations?

International Nuclear Information System (INIS)

Mudry, Christopher; Wen Xiaogang

1999-01-01

Effective theories for random critical points are usually non-unitary, and thus may contain relevant operators with negative scaling dimensions. To study the consequences of the existence of negative-dimensional operators, we consider the random-bond XY model. It has been argued that the XY model on a square lattice, when weakly perturbed by random phases, has a quasi-long-range ordered phase (the random spin wave phase) at sufficiently low temperatures. We show that infinitely many relevant perturbations to the proposed critical action for the random spin wave phase were omitted in all previous treatments. The physical origin of these perturbations is intimately related to the existence of broadly distributed correlation functions. We find that those relevant perturbations do enter the Renormalization Group equations, and affect critical behavior. This raises the possibility that the random XY model has no quasi-long-range ordered phase and no Kosterlitz-Thouless (KT) phase transition
Modelling energy consumption in a manufacturing plant using productivity KPIs

Energy Technology Data Exchange (ETDEWEB)

Gallachoir, Brian O.; Cahill, Caiman (Sustainable Energy Research Group, Dept. of Civil and Environmental Engineering, Univ. College Cork (Ireland))

2009-07-01

Energy efficiency initiatives in industrial plants are often focused on getting energy-consuming utilities and devices to operate more efficiently, or on conserving energy. While such device-oriented energy efficiency measures can achieve considerable savings, greater energy efficiency improvement may be achieved by improving the overall productivity and quality of manufacturing processes. The paper highlights the observed relationship between productivity and energy efficiency using aggregated data on unit consumption and production index data for Irish industry. Past studies have developed simple top-down models of final energy consumption in manufacturing plants using energy consumption and production output figures, but these models do not help identify opportunities for energy savings that could achieved through increased productivity. This paper proposes an improved and innovative method of modelling plant final energy demand that introduces standard productivity Key Performance Indicators (KPIs) into the model. The model demonstrates the relationship between energy consumption and productivity, and uses standard productivity metrics to identify the areas of manufacturing activity that offer the most potential for improved energy efficiency. The model provides a means of comparing the effect of device-oriented energy efficiency measures with the potential for improved energy efficiency through increased productivity.
Highly efficient hybrid energy generator: coupled organic photovoltaic device and randomly oriented electrospun poly(vinylidene fluoride) nanofiber.

Science.gov (United States)

Park, Boongik; Lee, Kihwan; Park, Jongjin; Kim, Jongmin; Kim, Ohyun

2013-03-01

A hybrid architecture consisting of an inverted organic photovoltaic device and a randomly-oriented electrospun PVDF piezoelectric device was fabricated as a highly-efficient energy generator. It uses the inverted photovoltaic device with coupled electrospun PVDF nanofibers as tandem structure to convert solar and mechanical vibrations energy to electricity simultaneously or individually. The power conversion efficiency of the photovoltaic device was also significantly improved up to 4.72% by optimized processes such as intrinsic ZnO, MoO3 and active layer. A simple electrospinning method with the two electrode technique was adopted to achieve a high voltage of - 300 mV in PVDF piezoelectric fibers. Highly-efficient HEG using voltage adder circuit provides the conceptual possibility of realizing multi-functional energy generator whenever and wherever various energy sources are available.
A Correction of Random Incidence Absorption Coefficients for the Angular Distribution of Acoustic Energy under Measurement Conditions

DEFF Research Database (Denmark)

Jeong, Cheol-Ho

2009-01-01

Most acoustic measurements are based on an assumption of ideal conditions. One such ideal condition is a diffuse and reverberant field. In practice, a perfectly diffuse sound field cannot be achieved in a reverberation chamber. Uneven incident energy density under measurement conditions can cause...... discrepancies between the measured value and the theoretical random incidence absorption coefficient. Therefore the angular distribution of the incident acoustic energy onto an absorber sample should be taken into account. The angular distribution of the incident energy density was simulated using the beam...... tracing method for various room shapes and source positions. The averaged angular distribution is found to be similar to a Gaussian distribution. As a result, an angle-weighted absorption coefficient was proposed by considering the angular energy distribution to improve the agreement between...
Inference of a random potential from random walk realizations: Formalism and application to the one-dimensional Sinai model with a drift

International Nuclear Information System (INIS)

Cocco, S; Monasson, R

2009-01-01

We consider the Sinai model, in which a random walker moves in a random quenched potential V, and ask the following questions: 1. how can the quenched potential V be inferred from the observations of one or more realizations of the random motion? 2. how many observations (walks) are required to make a reliable inference, that is, to be able to distinguish between two similar but distinct potentials, V 1 and V 2 ? We show how question 1 can be easily solved within the Bayesian framework. In addition, we show that the answer to question 2 is, in general, intimately connected to the calculation of the survival probability of a fictitious walker in a potential W defined from V 1 and V 2 , with partial absorption at sites where V 1 and V 2 do not coincide. For the one-dimensional Sinai model, this survival probability can be analytically calculated, in excellent agreement with numerical simulations.

A model of optimization for local energy infrastructure development

International Nuclear Information System (INIS)

Juroszek, Zbigniew; Kudelko, Mariusz

2016-01-01

The authors present a non-linear, optimization model supporting the planning of local energy systems development. The model considers two forms of final energy – heat and electricity. The model reflects both private and external costs and is designed to show the social perspective. It considers the variability of the marginal costs attributed to local renewable resources. In order to demonstrate the capacity of the model, the authors present a case study by modelling the development of the energy infrastructure in a municipality located in the south of Poland. The ensuing results show that a swift and significant shift in the local energy policy of typical central European municipalities is needed. The modelling is done in two scenarios – with and without the internalization of external environmental costs. The results confirm that the internalization of the external costs of energy production on a local scale leads to a significant improvement in the allocation of resources. - Highlights: • A model for municipal energy system development in Central European environment has been developed. • The variability of marginal costs of local, renewable fuels is considered. • External, environmental costs are considered. • The model reflects both network and individual energy infrastructure (e.g. individual housing boilers). • A swift change in Central European municipal energy infrastructure is necessary.
Technology assessment in energy landscapes. Agent-based modeling of energy conflicts

International Nuclear Information System (INIS)

Scheffran, Juergen; Link, P. Michael; Shaaban, Mostafa; Suesser, Diana

2017-01-01

The risks and conflicts of the fossil-nuclear age are in contrast to the effects of renewable energies which appear in a largely positive light. However, the transformation towards a low-carbon energy supply creates new energy landscapes with a high demand for suitable land areas - which may also provoke energy conflicts. Technology assessment can contribute to reducing such energy conflicts and increasing public acceptance by using spatial agent-based models that represent dynamic decisions and interactions of stakeholders regarding energy alternatives and land-use options. Northern Germany serves as a case study region where farmers and communities are local actors of the energy transition.
Bi-resonant structure with piezoelectric PVDF films for energy harvesting from random vibration sources at low frequency

DEFF Research Database (Denmark)

Liang, Shanshan; Crovetto, Andrea; Peng, Zhuoteng

2016-01-01

and experiments with piezoelectric elements show that the energy harvesting device with the bi-resonant structure can generate higher power output than that of the sum of the two separate devices from random vibration sources at low frequency, and hence significantly improves the vibration-to- electricity......This paper reports on a bi-resonant structure of piezoelectric PVDF films energy harvester (PPEH), which consists of two cantilevers with resonant frequencies of 15 Hz and 22 Hz. With increased acceleration, the vibration amplitudes of the two cantilever-mass structures are increased and collision...
Criticality of the random-site Ising model: Metropolis, Swendsen-Wang and Wolff Monte Carlo algorithms

Directory of Open Access Journals (Sweden)

D.Ivaneyko

2005-01-01

Full Text Available We apply numerical simulations to study of the criticality of the 3D Ising model with random site quenched dilution. The emphasis is given to the issues not being discussed in detail before. In particular, we attempt a comparison of different Monte Carlo techniques, discussing regions of their applicability and advantages/disadvantages depending on the aim of a particular simulation set. Moreover, besides evaluation of the critical indices we estimate the universal ratio Γ+/Γ- for the magnetic susceptibility critical amplitudes. Our estimate Γ+/Γ- = 1.67 ± 0.15 is in a good agreement with the recent MC analysis of the random-bond Ising model giving further support that both random-site and random-bond dilutions lead to the same universality class.
Evaluating predictive models for solar energy growth in the US states and identifying the key drivers

Science.gov (United States)

Chakraborty, Joheen; Banerji, Sugata

2018-03-01

Driven by a desire to control climate change and reduce the dependence on fossil fuels, governments around the world are increasing the adoption of renewable energy sources. However, among the US states, we observe a wide disparity in renewable penetration. In this study, we have identified and cleaned over a dozen datasets representing solar energy penetration in each US state, and the potentially relevant socioeconomic and other factors that may be driving the growth in solar. We have applied a number of predictive modeling approaches - including machine learning and regression - on these datasets over a 17-year period and evaluated the relative performance of the models. Our goals were: (1) identify the most important factors that are driving the growth in solar, (2) choose the most effective predictive modeling technique for solar growth, and (3) develop a model for predicting next year’s solar growth using this year’s data. We obtained very promising results with random forests (about 90% efficacy) and varying degrees of success with support vector machines and regression techniques (linear, polynomial, ridge). We also identified states with solar growth slower than expected and representing a potential for stronger growth in future.
Economic analysis model for total energy and economic systems

International Nuclear Information System (INIS)

Shoji, Katsuhiko; Yasukawa, Shigeru; Sato, Osamu

1980-09-01

This report describes framing an economic analysis model developed as a tool of total energy systems. To prospect and analyze future energy systems, it is important to analyze the relation between energy system and economic structure. We prepared an economic analysis model which was suited for this purpose. Our model marks that we can analyze in more detail energy related matters than other economic ones, and can forecast long-term economic progress rather than short-term economic fluctuation. From view point of economics, our model is longterm multi-sectoral economic analysis model of open Leontief type. Our model gave us appropriate results for fitting test and forecasting estimation. (author)
Energy laboratory data and model directory

Science.gov (United States)

Lahiri, S.; Carson, J.

1981-07-01

Over the past several years M.I.T. faculty, staff, and students have produced a substantial body of research and analysis relating to the production, conversion,, and use of energy in domestic and international markets. Much of this research takes the form of models and associated data bases that have enduring value in policy studies (models) and in supporting related research and modeling efforts (date). For such models and data it is important to ensure that the useful life cycle does not end with the conclusion of the research project. This directory is an important step in extending the usefulness of models and data bases available at the M.I.T. Energy Laboratory. It will be updated from time to time to include new models and data bases that have been developed, or significant changes that have occurred.
Transportation Sector Model of the National Energy Modeling System. Volume 1

Energy Technology Data Exchange (ETDEWEB)

NONE

1998-01-01

This report documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Transportation Model (TRAN). The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated by the model. The NEMS Transportation Model comprises a series of semi-independent models which address different aspects of the transportation sector. The primary purpose of this model is to provide mid-term forecasts of transportation energy demand by fuel type including, but not limited to, motor gasoline, distillate, jet fuel, and alternative fuels (such as CNG) not commonly associated with transportation. The current NEMS forecast horizon extends to the year 2010 and uses 1990 as the base year. Forecasts are generated through the separate consideration of energy consumption within the various modes of transport, including: private and fleet light-duty vehicles; aircraft; marine, rail, and truck freight; and various modes with minor overall impacts, such as mass transit and recreational boating. This approach is useful in assessing the impacts of policy initiatives, legislative mandates which affect individual modes of travel, and technological developments. The model also provides forecasts of selected intermediate values which are generated in order to determine energy consumption. These elements include estimates of passenger travel demand by automobile, air, or mass transit; estimates of the efficiency with which that demand is met; projections of vehicle stocks and the penetration of new technologies; and estimates of the demand for freight transport which are linked to forecasts of industrial output. Following the estimation of energy demand, TRAN produces forecasts of vehicular emissions of the following pollutants by source: oxides of sulfur, oxides of nitrogen, total carbon, carbon dioxide, carbon monoxide, and volatile organic compounds.
Random vibration sensitivity studies of modeling uncertainties in the NIF structures

International Nuclear Information System (INIS)

Swensen, E.A.; Farrar, C.R.; Barron, A.A.; Cornwell, P.

1996-01-01

The National Ignition Facility is a laser fusion project that will provide an above-ground experimental capability for nuclear weapons effects simulation. This facility will achieve fusion ignition utilizing solid-state lasers as the energy driver. The facility will cover an estimated 33,400 m 2 at an average height of 5--6 stories. Within this complex, a number of beam transport structures will be houses that will deliver the laser beams to the target area within a 50 microm ms radius of the target center. The beam transport structures are approximately 23 m long and reach approximately heights of 2--3 stories. Low-level ambient random vibrations are one of the primary concerns currently controlling the design of these structures. Low level ambient vibrations, 10 -10 g 2 /Hz over a frequency range of 1 to 200 Hz, are assumed to be present during all facility operations. Each structure described in this paper will be required to achieve and maintain 0.6 microrad ms laser beam pointing stability for a minimum of 2 hours under these vibration levels. To date, finite element (FE) analysis has been performed on a number of the beam transport structures. Certain assumptions have to be made regarding structural uncertainties in the FE models. These uncertainties consist of damping values for concrete and steel, compliance within bolted and welded joints, and assumptions regarding the phase coherence of ground motion components. In this paper, the influence of these structural uncertainties on the predicted pointing stability of the beam line transport structures as determined by random vibration analysis will be discussed
Energy-economy interactions revisited within a comprehensive sectoral model

Energy Technology Data Exchange (ETDEWEB)

Hanson, D. A.; Laitner, J. A.

2000-07-24

This paper describes a computable general equilibrium (CGE) model with considerable sector and technology detail, the ``All Modular Industry Growth Assessment'' Model (AMIGA). It is argued that a detailed model is important to capture and understand the several rolls that energy plays within the economy. Fundamental consumer and industrial demands are for the services from energy; hence, energy demand is a derived demand based on the need for heating, cooling mechanical, electrical, and transportation services. Technologies that provide energy-services more efficiently (on a life cycle basis), when adopted, result in increased future output of the economy and higher paths of household consumption. The AMIGA model can examine the effects on energy use and economic output of increases in energy prices (e.g., a carbon charge) and other incentive-based policies or energy-efficiency programs. Energy sectors and sub-sector activities included in the model involve energy extraction conversion and transportation. There are business opportunities to produce energy-efficient goods (i.e., appliances, control systems, buildings, automobiles, clean electricity). These activities are represented in the model by characterizing their likely production processes (e.g., lighter weight motor vehicles). Also, multiple industrial processes can produce the same output but with different technologies and inputs. Secondary recovery, i.e., recycling processes, are examples of these multiple processes. Combined heat and power (CHP) is also represented for energy-intensive industries. Other modules represent residential and commercial building technologies to supply energy services. All sectors of the economy command real resources (capital services and labor).
Quantitative model of New Zealand's energy supply industry

Energy Technology Data Exchange (ETDEWEB)

Smith, B. R. [Victoria Univ., Wellington, (New Zealand); Lucas, P. D. [Ministry of Energy Resources (New Zealand)

1977-10-15

A mathematical model is presented to assist in an analysis of energy policy options available. The model is based on an engineering orientated description of New Zealand's energy supply and distribution system. The system is cast as a linear program, in which energy demand is satisfied at least cost. The capacities and operating modes of process plant (such as power stations, oil refinery units, and LP-gas extraction plants) are determined by the model, as well as the optimal mix of fuels supplied to the final consumers. Policy analysis with the model enables a wide ranging assessment of the alternatives and uncertainties within a consistent quantitative framework. It is intended that the model be used as a tool to investigate the relative effects of various policy options, rather than to present a definitive plan for satisfying the nation's energy requirements.
Statistical models describing the energy signature of buildings

DEFF Research Database (Denmark)

Bacher, Peder; Madsen, Henrik; Thavlov, Anders

2010-01-01

Approximately one third of the primary energy production in Denmark is used for heating in buildings. Therefore efforts to accurately describe and improve energy performance of the building mass are very important. For this purpose statistical models describing the energy signature of a building, i...... or varying energy prices. The paper will give an overview of statistical methods and applied models based on experiments carried out in FlexHouse, which is an experimental building in SYSLAB, Risø DTU. The models are of different complexity and can provide estimates of physical quantities such as UA......-values, time constants of the building, and other parameters related to the heat dynamics. A method for selecting the most appropriate model for a given building is outlined and finally a perspective of the applications is given. Aknowledgements to the Danish Energy Saving Trust and the Interreg IV ``Vind i...
Offshore Wind Energy Cost Modeling Installation and Decommissioning

CERN Document Server

Kaiser, Mark J

2012-01-01

Offshore wind energy is one of the most promising and fastest growing alternative energy sources in the world. Offshore Wind Energy Cost Modeling provides a methodological framework to assess installation and decommissioning costs, and using examples from the European experience, provides a broad review of existing processes and systems used in the offshore wind industry. Offshore Wind Energy Cost Modeling provides a step-by-step guide to modeling costs over four sections. These sections cover: ·Background and introductory material, ·Installation processes and vessel requirements, ·Installation cost estimation, and ·Decommissioning methods and cost estimation. This self-contained and detailed treatment of the key principles in offshore wind development is supported throughout by visual aids and data tables. Offshore Wind Energy Cost Modeling is a key resource for anyone interested in the offshore wind industry, particularly those interested in the technical and economic aspects of installation and decom...
Holographic dark energy in the DGP model

International Nuclear Information System (INIS)

Cruz, Norman; Lepe, Samuel; Pena, Francisco; Avelino, Arturo

2012-01-01

The braneworld model proposed by Dvali, Gabadadze, and Porrati leads to an accelerated universe without cosmological constant or any other form of dark energy. Nevertheless, we have investigated the consequences of this model when an holographic dark energy is included, taking the Hubble scale as IR cutoff. We have found that the holographic dark energy leads to an accelerated flat universe (de Sitter-like expansion) for the two branches: ε=±1, of the DGP model. Nevertheless, in universes with no null curvature the dark energy presents an EoS corresponding to a phantom fluid during the present era and evolving to a de Sitter-like phase for future cosmic time. In the special case in which the holographic parameter c is equal to one we have found a sudden singularity in closed universes. In this case the expansion is decelerating. (orig.)
Holographic dark energy in the DGP model

Energy Technology Data Exchange (ETDEWEB)

Cruz, Norman [Universidad de Santiago, Departamento de Fisica, Facultad de Ciencia, Santiago (Chile); Lepe, Samuel [Pontificia Universidad Catolica de Valparaiso, Instituto de Fisica, Facultad de Ciencias, Valparaiso (Chile); Pena, Francisco [Universidad de La Frontera, Departamento de Ciencias Fisicas, Facultad de Ingenieria, Ciencias y Administracion, Avda. Francisco Salazar 01145, Casilla 54-D, Temuco (Chile); Avelino, Arturo [Universidad de Guanajuato, Departamento de Fisica, DCI, Codigo Postal 37150, Leon, Guanajuato (Mexico)

2012-09-15

The braneworld model proposed by Dvali, Gabadadze, and Porrati leads to an accelerated universe without cosmological constant or any other form of dark energy. Nevertheless, we have investigated the consequences of this model when an holographic dark energy is included, taking the Hubble scale as IR cutoff. We have found that the holographic dark energy leads to an accelerated flat universe (de Sitter-like expansion) for the two branches: {epsilon}={+-}1, of the DGP model. Nevertheless, in universes with no null curvature the dark energy presents an EoS corresponding to a phantom fluid during the present era and evolving to a de Sitter-like phase for future cosmic time. In the special case in which the holographic parameter c is equal to one we have found a sudden singularity in closed universes. In this case the expansion is decelerating. (orig.)
Business-as-Unusual: Existing policies in energy model baselines

International Nuclear Information System (INIS)

Strachan, Neil

2011-01-01

Baselines are generally accepted as a key input assumption in long-term energy modelling, but energy models have traditionally been poor on identifying baselines assumptions. Notably, transparency on the current policy content of model baselines is now especially critical as long-term climate mitigation policies have been underway for a number of years. This paper argues that the range of existing energy and emissions policies are an integral part of any long-term baseline, and hence already represent a 'with-policy' baseline, termed here a Business-as-Unusual (BAuU). Crucially, existing energy policies are not a sunk effort; as impacts of existing policy initiatives are targeted at future years, they may be revised through iterative policy making, and their quantitative effectiveness requires ex-post verification. To assess the long-term role of existing policies in energy modelling, currently identified UK policies are explicitly stripped out of the UK MARKAL Elastic Demand (MED) optimisation energy system model, to generate a BAuU (with-policy) and a REF (without policy) baseline. In terms of long-term mitigation costs, policy-baseline assumptions are comparable to another key exogenous modelling assumption - that of global fossil fuel prices. Therefore, best practice in energy modelling would be to have both a no-policy reference baseline, and a current policy reference baseline (BAuU). At a minimum, energy modelling studies should have a transparent assessment of the current policy contained within the baseline. Clearly identifying and comparing policy-baseline assumptions are required for cost effective and objective policy making, otherwise energy models will underestimate the true cost of long-term emissions reductions.
GENERATION OF MULTI-LOD 3D CITY MODELS IN CITYGML WITH THE PROCEDURAL MODELLING ENGINE RANDOM3DCITY

Directory of Open Access Journals (Sweden)

F. Biljecki

2016-09-01

Full Text Available The production and dissemination of semantic 3D city models is rapidly increasing benefiting a growing number of use cases. However, their availability in multiple LODs and in the CityGML format is still problematic in practice. This hinders applications and experiments where multi-LOD datasets are required as input, for instance, to determine the performance of different LODs in a spatial analysis. An alternative approach to obtain 3D city models is to generate them with procedural modelling, which is – as we discuss in this paper – well suited as a method to source multi-LOD datasets useful for a number of applications. However, procedural modelling has not yet been employed for this purpose. Therefore, we have developed RANDOM3DCITY, an experimental procedural modelling engine for generating synthetic datasets of buildings and other urban features. The engine is designed to produce models in CityGML and does so in multiple LODs. Besides the generation of multiple geometric LODs, we implement the realisation of multiple levels of spatiosemantic coherence, geometric reference variants, and indoor representations. As a result of their permutations, each building can be generated in 392 different CityGML representations, an unprecedented number of modelling variants of the same feature. The datasets produced by RANDOM3DCITY are suited for several applications, as we show in this paper with documented uses. The developed engine is available under an open-source licence at Github at http://github.com/tudelft3d/Random3Dcity.
Kinetic k-essence ghost dark energy model

International Nuclear Information System (INIS)

Rozas-Fernández, Alberto

2012-01-01

A ghost dark energy model has been recently put forward to explain the current accelerated expansion of the Universe. In this model, the energy density of ghost dark energy, which comes from the Veneziano ghost of QCD, is proportional to the Hubble parameter, ρ D =αH. Here α is a constant of order Λ QCD 3 where Λ QCD ∼100 MeV is the QCD mass scale. We consider a connection between ghost dark energy with/without interaction between the components of the dark sector and the kinetic k-essence field. It is shown that the cosmological evolution of the ghost dark energy dominated Universe can be completely described a kinetic k-essence scalar field. We reconstruct the kinetic k-essence function F(X) in a flat Friedmann-Robertson-Walker Universe according to the evolution of ghost dark energy density.
Random effects model for the reliability management of modules of a fighter aircraft

Energy Technology Data Exchange (ETDEWEB)

Sohn, So Young [Department of Computer Science and Industrial Systems Engineering, Yonsei University, Shinchondong 134, Seoul 120-749 (Korea, Republic of)]. E-mail: sohns@yonsei.ac.kr; Yoon, Kyung Bok [Department of Computer Science and Industrial Systems Engineering, Yonsei University, Shinchondong 134, Seoul 120-749 (Korea, Republic of)]. E-mail: ykb@yonsei.ac.kr; Chang, In Sang [Department of Computer Science and Industrial Systems Engineering, Yonsei University, Shinchondong 134, Seoul 120-749 (Korea, Republic of)]. E-mail: isjang@yonsei.ac.kr

2006-04-15

The operational availability of fighter aircrafts plays an important role in the national defense. Low operational availability of fighter aircrafts can cause many problems and ROKA (Republic of Korea Airforce) needs proper strategies to improve the current practice of reliability management by accurately forecasting both MTBF (mean time between failure) and MTTR (mean time to repair). In this paper, we develop a random effects model to forecast both MTBF and MTTR of installed modules of fighter aircrafts based on their characteristics and operational conditions. Advantage of using such a random effects model is the ability of accommodating not only the individual characteristics of each module and operational conditions but also the uncertainty caused by random error that cannot be explained by them. Our study is expected to contribute to ROKA in improving operational availability of fighter aircrafts and establishing effective logistics management.
Modeling renewable energy company risk

International Nuclear Information System (INIS)

Sadorsky, Perry

2012-01-01

The renewable energy sector is one of the fastest growing components of the energy industry and along with this increased demand for renewable energy there has been an increase in investing and financing activities. The tradeoff between risk and return in the renewable energy sector is, however, precarious. Renewable energy companies are often among the riskiest types of companies to invest in and for this reason it is necessary to have a good understanding of the risk factors. This paper uses a variable beta model to investigate the determinants of renewable energy company risk. The empirical results show that company sales growth has a negative impact on company risk while oil price increases have a positive impact on company risk. When oil price returns are positive and moderate, increases in sales growth can offset the impact of oil price returns and this leads to lower systematic risk.

Modelling future private car energy demand in Ireland

International Nuclear Information System (INIS)

Daly, Hannah E.; Ó Gallachóir, Brian P.

2011-01-01

Targeted measures influencing vehicle technology are increasingly a tool of energy policy makers within the EU as a means of meeting energy efficiency, renewable energy, climate change and energy security goals. This paper develops the modelling capacity for analysing and evaluating such legislation, with a focus on private car energy demand. We populate a baseline car stock and car activity model for Ireland to 2025 using historical car stock data. The model takes account of the lifetime survival profile of different car types, the trends in vehicle activity over the fleet and the fuel price and income elasticities of new car sales and total fleet activity. The impacts of many policy alternatives may only be simulated by such a bottom-up approach, which can aid policy development and evaluation. The level of detail achieved provides specific insights into the technological drivers of energy consumption, thus aiding planning for meeting climate targets. This paper focuses on the methodology and baseline scenario. Baseline results for Ireland forecast a decline in private car energy demand growth (0.2%, compared with 4% in the period 2000–2008), caused by the relative growth in fleet efficiency compared with activity. - Highlights: ► Bottom-up private car energy forecasting model developed. ► The demographic and technological distribution of vehicle activity is a key veriable. ► Irish car energy demand growth predicted to slow steadily. ► Change in vehicle taxation forecast to save 10% energy.
Simulating Urban Growth Using a Random Forest-Cellular Automata (RF-CA Model

Directory of Open Access Journals (Sweden)

Courage Kamusoko

2015-04-01

Full Text Available Sustainable urban planning and management require reliable land change models, which can be used to improve decision making. The objective of this study was to test a random forest-cellular automata (RF-CA model, which combines random forest (RF and cellular automata (CA models. The Kappa simulation (KSimulation, figure of merit, and components of agreement and disagreement statistics were used to validate the RF-CA model. Furthermore, the RF-CA model was compared with support vector machine cellular automata (SVM-CA and logistic regression cellular automata (LR-CA models. Results show that the RF-CA model outperformed the SVM-CA and LR-CA models. The RF-CA model had a Kappa simulation (KSimulation accuracy of 0.51 (with a figure of merit statistic of 47%, while SVM-CA and LR-CA models had a KSimulation accuracy of 0.39 and −0.22 (with figure of merit statistics of 39% and 6%, respectively. Generally, the RF-CA model was relatively accurate at allocating “non-built-up to built-up” changes as reflected by the correct “non-built-up to built-up” components of agreement of 15%. The performance of the RF-CA model was attributed to the relatively accurate RF transition potential maps. Therefore, this study highlights the potential of the RF-CA model for simulating urban growth.
International energy market dynamics: a modelling approach. Tome 1

International Nuclear Information System (INIS)

Nachet, S.

1996-01-01

This work is an attempt to model international energy market and reproduce the behaviour of both energy demand and supply. Energy demand was represented using sector versus source approach. For developing countries, existing link between economic and energy sectors were analysed. Energy supply is exogenous for energy sources other than oil and natural gas. For hydrocarbons, exploration-production process was modelled and produced figures as production yield, exploration effort index, etc. The model built is econometric and is solved using a software that was constructed for this purpose. We explore the energy market future using three scenarios and obtain projections by 2010 for energy demand per source and oil natural gas supply per region. Economic variables are used to produce different indicators as energy intensity, energy per capita, etc. (author). 378 refs., 26 figs., 35 tabs., 11 appends
International energy market dynamics: a modelling approach. Tome 2

International Nuclear Information System (INIS)

Nachet, S.

1996-01-01

This work is an attempt to model international energy market and reproduce the behaviour of both energy demand and supply. Energy demand was represented using sector versus source approach. For developing countries, existing link between economic and energy sectors were analysed. Energy supply is exogenous for energy sources other than oil and natural gas. For hydrocarbons, exploration-production process was modelled and produced figures as production yield, exploration effort index, ect. The model build is econometric and is solved using a software that was constructed for this purpose. We explore the energy market future using three scenarios and obtain projections by 2010 for energy demand per source and oil and natural gas supply per region. Economic variables are used to produce different indicators as energy intensity, energy per capita, etc. (author). 378 refs., 26 figs., 35 tabs., 11 appends
Energy demand modelling: pointing out alternative energy sources. The example of industry in OECD countries

International Nuclear Information System (INIS)

Renou, P.

1992-01-01

This thesis studies energy demand and alternative energy sources in OECD countries. In the first part, the principle models usually used for energy demand modelling. In the second part, the author studies the flexible functional forms (translog, generalized Leontief, generalized quadratic, Fourier) to obtain an estimation of the production function. In the third part, several examples are given, chosen in seven countries (Usa, Japan, Federal Republic of Germany, France, United Kingdom, Italy, Canada). Energy systems analysis in these countries, can help to choose models and gives informations on alternative energies. 246 refs., 24 figs., 27 tabs
Statistical shape model with random walks for inner ear segmentation

DEFF Research Database (Denmark)

Pujadas, Esmeralda Ruiz; Kjer, Hans Martin; Piella, Gemma

2016-01-01

is required. We propose a new framework for segmentation of micro-CT cochlear images using random walks combined with a statistical shape model (SSM). The SSM allows us to constrain the less contrasted areas and ensures valid inner ear shape outputs. Additionally, a topology preservation method is proposed...
The macroeconomic effects of ambitious energy efficiency policy in Germany – Combining bottom-up energy modelling with a non-equilibrium macroeconomic model

International Nuclear Information System (INIS)

Hartwig, Johannes; Kockat, Judit; Schade, Wolfgang; Braungardt, Sibylle

2017-01-01

Energy efficiency is one of the fastest and most cost-effective contributions to a sustainable, secure and affordable energy system. Furthermore, the so-called “non-energy benefits”, “co-benefits” or “multiple benefits” of energy efficiency are receiving increased interest from policy makers and the scientific community. Among the various non-energy benefits of energy efficiency initiatives, the macroeconomic benefits play an important role. Our study presents a detailed analysis of the long-term macroeconomic effects of German energy efficiency policy including the industry and service sectors as well as residential energy demand. We quantify the macroeconomic effects of an ambitious energy efficiency scenario by combining bottom-up models with an extended dynamic input-output model. We study sectoral shifts within the economy regarding value added and employment compared to the baseline scenario. We provide an in-depth analysis of the effects of energy efficiency policy on consumers, individual industry sectors, and the economy as a whole. We find significant positive macroeconomic effects resulting from energy efficiency initiatives, with growth effects for both GDP and employment ranging between 0.88% and 3.38%. Differences in sectoral gains lead to a shift in the economy. Our methodological approach provides a comprehensive framework for analyzing the macroeconomic benefits of energy efficiency. - Highlights: • Integration of detailed sectoral models for energy demand with macroeconomic model. • Detailed assessment of effects of ambitious energy efficiency targets for Germany. • Positive macroeconomic effects can support policymaking and reduce uncertainty.
Conditional Random Fields versus Hidden Markov Models for activity recognition in temporal sensor data

NARCIS (Netherlands)

van Kasteren, T.L.M.; Noulas, A.K.; Kröse, B.J.A.; Smit, G.J.M.; Epema, D.H.J.; Lew, M.S.

2008-01-01

Conditional Random Fields are a discriminative probabilistic model which recently gained popularity in applications that require modeling nonindependent observation sequences. In this work, we present the basic advantages of this model over generative models and argue about its suitability in the
Clustering properties of dynamical dark energy models

International Nuclear Information System (INIS)

Avelino, P. P.; Beca, L. M. G.; Martins, C. J. A. P.

2008-01-01

We provide a generic but physically clear discussion of the clustering properties of dark energy models. We explicitly show that in quintessence-type models the dark energy fluctuations, on scales smaller than the Hubble radius, are of the order of the perturbations to the Newtonian gravitational potential, hence necessarily small on cosmological scales. Moreover, comparable fluctuations are associated with different gauge choices. We also demonstrate that the often used homogeneous approximation is unrealistic, and that the so-called dark energy mutation is a trivial artifact of an effective, single fluid description. Finally, we discuss the particular case where the dark energy fluid is nonminimally coupled to dark matter
A simulation-based robust biofuel facility location model for an integrated bio-energy logistics network

Directory of Open Access Journals (Sweden)

Jae-Dong Hong

2014-10-01

Full Text Available Purpose: The purpose of this paper is to propose a simulation-based robust biofuel facility location model for solving an integrated bio-energy logistics network (IBLN problem, where biomass yield is often uncertain or difficult to determine.Design/methodology/approach: The IBLN considered in this paper consists of four different facilities: farm or harvest site (HS, collection facility (CF, biorefinery (BR, and blending station (BS. Authors propose a mixed integer quadratic modeling approach to simultaneously determine the optimal CF and BR locations and corresponding biomass and bio-energy transportation plans. The authors randomly generate biomass yield of each HS and find the optimal locations of CFs and BRs for each generated biomass yield, and select the robust locations of CFs and BRs to show the effects of biomass yield uncertainty on the optimality of CF and BR locations. Case studies using data from the State of South Carolina in the United State are conducted to demonstrate the developed model’s capability to better handle the impact of uncertainty of biomass yield.Findings: The results illustrate that the robust location model for BRs and CFs works very well in terms of the total logistics costs. The proposed model would help decision-makers find the most robust locations for biorefineries and collection facilities, which usually require huge investments, and would assist potential investors in identifying the least cost or important facilities to invest in the biomass and bio-energy industry.Originality/value: An optimal biofuel facility location model is formulated for the case of deterministic biomass yield. To improve the robustness of the model for cases with probabilistic biomass yield, the model is evaluated by a simulation approach using case studies. The proposed model and robustness concept would be a very useful tool that helps potential biofuel investors minimize their investment risk.
Analysis of the energy and environmental effects of green car deployment by an integrating energy system model with a forecasting model

International Nuclear Information System (INIS)

Lee, Duk Hee; Park, Sang Yong; Hong, Jong Chul; Choi, Sang Jin; Kim, Jong Wook

2013-01-01

Highlights: ► A new methodology for improving energy system analysis models was proposed. ► The MARKAL model was integrated with the diffusion model. ► The new methodology was applied to green car technology. ► The ripple effect of green car technology on the energy system can be analyzed. -- Abstract: By 2020, Korea has set itself the challenging target of reducing nationwide greenhouse gas emissions by 30%, more than the BAU (Business as Usual) scenario, as the implementation goal required to achieve the new national development paradigm of green growth. To achieve such a target, it is necessary to diffuse innovative technologies with the capacity to drastically reduce greenhouse gas emissions. To that end, the ripple effect of diffusing innovative technologies on the energy and environment must be quantitatively analyzed using an energy system analysis model such as the MARKAL (Market Allocation) model. However, energy system analysis models based on an optimization methodology have certain limitations in that a technology with superior cost competitiveness dominates the whole market and non-cost factors cannot be considered. Therefore, this study proposes a new methodology for overcoming problems associated with the use of MARKAL models, by interfacing with a forecasting model based on the discrete-choice model. The new methodology was applied to green car technology to verify its usefulness and to study the ripple effects of green car technology on greenhouse gas reduction. The results of this study can be used as a reference when establishing a strategy for effectively reducing greenhouse gas emissions in the transportation sector, and could be of assistance to future studies using the energy system analysis model.
Rényi Entropies from Random Quenches in Atomic Hubbard and Spin Models

Science.gov (United States)

Elben, A.; Vermersch, B.; Dalmonte, M.; Cirac, J. I.; Zoller, P.

2018-02-01

We present a scheme for measuring Rényi entropies in generic atomic Hubbard and spin models using single copies of a quantum state and for partitions in arbitrary spatial dimensions. Our approach is based on the generation of random unitaries from random quenches, implemented using engineered time-dependent disorder potentials, and standard projective measurements, as realized by quantum gas microscopes. By analyzing the properties of the generated unitaries and the role of statistical errors, with respect to the size of the partition, we show that the protocol can be realized in existing quantum simulators and used to measure, for instance, area law scaling of entanglement in two-dimensional spin models or the entanglement growth in many-body localized systems.
Statistical model for expected un supplied energy; Statistisk modell for forventet ILE

Energy Technology Data Exchange (ETDEWEB)

NONE

2005-07-01

Results from a statistical analysis of expected un supplied energy for Norwegian network companies are presented. The data are from the years 1996-2004. The estimation model includes several explanatory variables that together reflect the characteristics of the network, climatic aspects and other geographical conditions. The model has a high degree of accuracy when compared to the historical number of un supplied energy for about 90 percent of the network companies. But for 12 companies there are substantial, negative deviances that are not compatible with the available data. There is reason to believe that improved data for some types of variables can improve the accuracy of the model. In addition to establishing a norm for expected un supplied energy in the revenue estimations, the model can be used to reflect geographical constraints in NVEs (Norwegian Water and Energy directorate) efficiency analyses (ml)
Use of Danish Heat Atlas and energy system models for exploring renewable energy scenarios

DEFF Research Database (Denmark)

Petrovic, Stefan; Karlsson, Kenneth Bernard

2013-01-01

networks in relation with significant heat saving measures that are capital intensive infrastructure investments require highly detailed decision - support tools. The Heat Atlas for Denmark provides a highly detailed database and includes heat demand and possible heat savings for about 2.5 million...... buildings with associated costs included. Energy systems modelling tools that incorporate economic, environmental, energy and engineering analysis of future energy systems are considered crucial for quantitative assessment of transitional scenarios towards future milestones, such as (i) EU 2020 goals...... of reducing greenhouse gas emissions, increasing share of renewable energy and improving energy efficiency and (ii) Denmark’s 2050 goals of covering entire energy supply by renewable energy. Optimization and simulation energy system models are currently used in Denmark. The present paper tends to provide...
Potts Model with Invisible Colors : Random-Cluster Representation and Pirogov–Sinai Analysis

NARCIS (Netherlands)

Enter, Aernout C.D. van; Iacobelli, Giulio; Taati, Siamak

We study a recently introduced variant of the ferromagnetic Potts model consisting of a ferromagnetic interaction among q “visible” colors along with the presence of r non-interacting “invisible” colors. We introduce a random-cluster representation for the model, for which we prove the existence of
Global economics/energy/environmental (E3) modeling of long-term nuclear energy futures

International Nuclear Information System (INIS)

Krakowski, R.A.; Davidson, J.W.; Bathke, C.G.; Arthur, E.D.; Wagner, R.L. Jr.

1997-01-01

A global energy, economics, environment (E 3 ) model has been adopted and modified with a simplified, but comprehensive and multi-regional, nuclear energy module. Using this model, consistent nuclear energy scenarios are constructed. A spectrum of future is examined at two levels in a hierarchy of scenario attributes in which drivers are either external or internal to nuclear energy. Impacts of a range of nuclear fuel-cycle scenarios are reflected back to the higher-level scenario attributes. An emphasis is placed on nuclear materials inventories (in magnitude, location, and form) and their contribution to the long-term sustainability of nuclear energy and the future competitiveness of both conventional and advanced nuclear reactors
Energy modelling with SOPKA-E for the energy paths of the Commission of Inquiry on ''Future nuclear energy policy''

International Nuclear Information System (INIS)

Faude, D.

1983-03-01

The Commission of Inquiry on ''Future nuclear energy policy'' of the 8th Deutscher Bundestag has examined the question of the longterm exploitation of nuclear energy in the Federal Republic of Germany within a more general framework of energy policy and, for this purpose, created the concept of energy paths. To calculate these energy paths, the SOPKA-E simulation model has been developed and applied at the Karlsruhe Nuclear Research Center. In Chapter 2, the central part of this report, the form and contents of path modeling are described in detail. To help readers understand the energy paths concept, the general background of energy policy in the seventies, which gave rise to the contents of the energy paths, is outlined in a survey article in Chapter 1. Chapter 3 is a description of the energy projections contained in the joint expert opinion on the third updated version of the Energy Program in the light of the energy paths. In Chapter 4 some approaches - albeit fragmentary - are outlined which have been adopted by the Commission of Inquiry of the 9th Deutscher Bundestag in adapting energy paths to the present situation. The presentation in this report of the model computations with SOPKA-E is meant to be a documentation. (orig./UA) [de
Changes in Energy Intake and Diet Quality during an 18-Month Weight-Management Randomized Controlled Trial in Adults with Intellectual and Developmental Disabilities.

Science.gov (United States)

Ptomey, Lauren T; Steger, Felicia L; Lee, Jaehoon; Sullivan, Debra K; Goetz, Jeannine R; Honas, Jeffery J; Washburn, Richard A; Gibson, Cheryl A; Donnelly, Joseph E

2018-06-01

Previous research indicates that individuals with intellectual and developmental disabilities (IDDs) are at risk for poor diet quality. The purpose of this secondary analysis was to determine whether two different weight-loss diets affect energy intake, macronutrient intake, and diet quality as measured by the Healthy Eating Index-2010 (HEI-2010) during a 6-month weight-loss period and 12-month weight-management period, and to examine differences in energy intake, macronutrient intake, and HEI-2010 between groups. Overweight/obese adults with IDDs took part in an 18-month randomized controlled trial and were assigned to either an enhanced Stop Light Diet utilizing portion-controlled meals or a conventional diet consisting of reducing energy intake and following the 2010 Dietary Guidelines for Americans. Proxy-assisted 3-day food records were collected at baseline, 6 months, and 18 months, and were analyzed using Nutrition Data System for Research software. HEI-2010 was calculated using the data from Nutrition Data System for Research. The study took place from June 2011 through May 2014 in the greater Kansas City metropolitan area. This was a secondary analysis of a weight-management intervention for adults with IDDs randomized to an enhanced Stop Light Diet or conventional diet, to examine differences in energy intake, macronutrient intake, and HEI-2010 across time and between groups. Independent- and paired-samples t tests and general mixed modeling for repeated measures were performed to examine group differences and changes at baseline, 6 months, and 18 months between the enhanced Stop Light Diet and conventional diet groups. One hundred and forty six participants (57% female, mean±standard deviation age=36.2±12.0 years) were randomized to either the enhanced Stop Light Diet or conventional diet group (77 enhanced Stop Light Diet, 69 conventional diet) and provided data for analysis at baseline, 124 completed the 6-month weight-loss period, and 101 completed
Model documentation: Natural Gas Transmission and Distribution Model of the National Energy Modeling System; Volume 1

Energy Technology Data Exchange (ETDEWEB)

NONE

1994-02-24

The Natural Gas Transmission and Distribution Model (NGTDM) is a component of the National Energy Modeling System (NEMS) used to represent the domestic natural gas transmission and distribution system. NEMS is the third in a series of computer-based, midterm energy modeling systems used since 1974 by the Energy Information Administration (EIA) and its predecessor, the Federal Energy Administration, to analyze domestic energy-economy markets and develop projections. This report documents the archived version of NGTDM that was used to produce the natural gas forecasts used in support of the Annual Energy Outlook 1994, DOE/EIA-0383(94). The purpose of this report is to provide a reference document for model analysts, users, and the public that defines the objectives of the model, describes its basic design, provides detail on the methodology employed, and describes the model inputs, outputs, and key assumptions. It is intended to fulfill the legal obligation of the EIA to provide adequate documentation in support of its models (Public Law 94-385, Section 57.b.2). This report represents Volume 1 of a two-volume set. (Volume 2 will report on model performance, detailing convergence criteria and properties, results of sensitivity testing, comparison of model outputs with the literature and/or other model results, and major unresolved issues.) Subsequent chapters of this report provide: (1) an overview of the NGTDM (Chapter 2); (2) a description of the interface between the National Energy Modeling System (NEMS) and the NGTDM (Chapter 3); (3) an overview of the solution methodology of the NGTDM (Chapter 4); (4) the solution methodology for the Annual Flow Module (Chapter 5); (5) the solution methodology for the Distributor Tariff Module (Chapter 6); (6) the solution methodology for the Capacity Expansion Module (Chapter 7); (7) the solution methodology for the Pipeline Tariff Module (Chapter 8); and (8) a description of model assumptions, inputs, and outputs (Chapter 9).
Randomized random walk on a random walk

International Nuclear Information System (INIS)

Lee, P.A.

1983-06-01

This paper discusses generalizations of the model introduced by Kehr and Kunter of the random walk of a particle on a one-dimensional chain which in turn has been constructed by a random walk procedure. The superimposed random walk is randomised in time according to the occurrences of a stochastic point process. The probability of finding the particle in a particular position at a certain instant is obtained explicitly in the transform domain. It is found that the asymptotic behaviour for large time of the mean-square displacement of the particle depends critically on the assumed structure of the basic random walk, giving a diffusion-like term for an asymmetric walk or a square root law if the walk is symmetric. Many results are obtained in closed form for the Poisson process case, and these agree with those given previously by Kehr and Kunter. (author)

Assessing the predictive capability of randomized tree-based ensembles in streamflow modelling

Science.gov (United States)

Galelli, S.; Castelletti, A.

2013-07-01

Combining randomization methods with ensemble prediction is emerging as an effective option to balance accuracy and computational efficiency in data-driven modelling. In this paper, we investigate the prediction capability of extremely randomized trees (Extra-Trees), in terms of accuracy, explanation ability and computational efficiency, in a streamflow modelling exercise. Extra-Trees are a totally randomized tree-based ensemble method that (i) alleviates the poor generalisation property and tendency to overfitting of traditional standalone decision trees (e.g. CART); (ii) is computationally efficient; and, (iii) allows to infer the relative importance of the input variables, which might help in the ex-post physical interpretation of the model. The Extra-Trees potential is analysed on two real-world case studies - Marina catchment (Singapore) and Canning River (Western Australia) - representing two different morphoclimatic contexts. The evaluation is performed against other tree-based methods (CART and M5) and parametric data-driven approaches (ANNs and multiple linear regression). Results show that Extra-Trees perform comparatively well to the best of the benchmarks (i.e. M5) in both the watersheds, while outperforming the other approaches in terms of computational requirement when adopted on large datasets. In addition, the ranking of the input variable provided can be given a physically meaningful interpretation.
Scenario Analysis With Economic-Energy Systems Models Coupled to Simple Climate Models

Science.gov (United States)

Hanson, D. A.; Kotamarthi, V. R.; Foster, I. T.; Franklin, M.; Zhu, E.; Patel, D. M.

2008-12-01

Here, we compare two scenarios based on Stanford University's Energy Modeling Forum Study 22 on global cooperative and non-cooperative climate policies. In the former, efficient transition paths are implemented including technology Research and Development effort, energy conservation programs, and price signals for greenhouse gas (GHG) emissions. In the non-cooperative case, some countries try to relax their regulations and be free riders. Total emissions and costs are higher in the non-cooperative scenario. The simulations, including climate impacts, run to the year 2100. We use the Argonne AMIGA-MARS economic-energy systems model, the Texas AM University's Forest and Agricultural Sector Optimization Model (FASOM), and the University of Illinois's Integrated Science Assessment Model (ISAM), with offline coupling between the FASOM and AMIGA-MARS and an online coupling between AMIGA-MARS and ISAM. This set of models captures the interaction of terrestrial systems, land use, crops and forests, climate change, human activity, and energy systems. Our scenario simulations represent dynamic paths over which all the climate, terrestrial, economic, and energy technology equations are solved simultaneously Special attention is paid to biofuels and how they interact with conventional gasoline/diesel fuel markets. Possible low-carbon penetration paths are based on estimated costs for new technologies, including cellulosic biomass, coal-to-liquids, plug-in electric vehicles, solar and nuclear energy. We explicitly explore key uncertainties that affect mitigation and adaptation scenarios.
Kinetics of transformations nucleated on random parallel planes: analytical modelling and computer simulation

International Nuclear Information System (INIS)

Rios, Paulo R; Assis, Weslley L S; Ribeiro, Tatiana C S; Villa, Elena

2012-01-01

In a classical paper, Cahn derived expressions for the kinetics of transformations nucleated on random planes and lines. He used those as a model for nucleation on the boundaries, edges and vertices of a polycrystal consisting of equiaxed grains. In this paper it is demonstrated that Cahn's expression for random planes may be used in situations beyond the scope envisaged in Cahn's original paper. For instance, we derived an expression for the kinetics of transformations nucleated on random parallel planes that is identical to that formerly obtained by Cahn considering random planes. Computer simulation of transformations nucleated on random parallel planes is carried out. It is shown that there is excellent agreement between simulated results and analytical solutions. Such an agreement is to be expected if both the simulation and the analytical solution are correct. (paper)
Nonlinear spherical perturbations in quintessence models of dark energy

Science.gov (United States)

Pratap Rajvanshi, Manvendra; Bagla, J. S.

2018-06-01

Observations have confirmed the accelerated expansion of the universe. The accelerated expansion can be modelled by invoking a cosmological constant or a dynamical model of dark energy. A key difference between these models is that the equation of state parameter w for dark energy differs from ‑1 in dynamical dark energy (DDE) models. Further, the equation of state parameter is not constant for a general DDE model. Such differences can be probed using the variation of scale factor with time by measuring distances. Another significant difference between the cosmological constant and DDE models is that the latter must cluster. Linear perturbation analysis indicates that perturbations in quintessence models of dark energy do not grow to have a significant amplitude at small length scales. In this paper we study the response of quintessence dark energy to non-linear perturbations in dark matter. We use a fully relativistic model for spherically symmetric perturbations. In this study we focus on thawing models. We find that in response to non-linear perturbations in dark matter, dark energy perturbations grow at a faster rate than expected in linear perturbation theory. We find that dark energy perturbation remains localised and does not diffuse out to larger scales. The dominant drivers of the evolution of dark energy perturbations are the local Hubble flow and a supression of gradients of the scalar field. We also find that the equation of state parameter w changes in response to perturbations in dark matter such that it also becomes a function of position. The variation of w in space is correlated with density contrast for matter. Variation of w and perturbations in dark energy are more pronounced in response to large scale perturbations in matter while the dependence on the amplitude of matter perturbations is much weaker.
Modelling smart energy systems in tropical regions

DEFF Research Database (Denmark)

Dominkovic, D. F.; Dobravec, V.; Jiang, Y.

2018-01-01

and water desalination sectors. Five different large scale storages were modelled, too. The developed linear optimization model further included endogenous decisions about the share of district versus individual cooling, implementation of energy efficiency solutions and implementation of demand response...... emissions, 15% higher particulate matter emissions and 2% larger primary energy consumption compared to a business-as-usual case....
Concepts for dynamic modelling of energy-related flows in manufacturing

International Nuclear Information System (INIS)

Wright, A.J.; Oates, M.R.; Greenough, R.

2013-01-01

Highlights: ► Modelling of the thermal flows in factories and processes is usually separate. ► We propose a set of key features for an integrated thermal model. ► Such models can be used to improve the efficiency of manufacturing processes. - Abstract: Industry uses around one third of the world’s energy, and accounts for about 40% of global carbon dioxide emissions. There is increasing economic and social pressure to improve efficiency and create closed-loop industrial systems, in which energy efficiency plays a key role. This paper describes some of the key concepts involved in modelling the energy flows in manufacturing, both for the building services and the industrial processes. Detailed dynamic energy simulation of buildings is well established and routinely used, working on a time series basis – but current tools are inadequate to model the energy flows of many industrial processes. There are also well-established models of manufacturing flows, used to optimise production efficiency, but typically not modelling energy, and usually representing production and material flows as event-driven processes. The THERM project has developed new software tools to model energy-related and other utility flows in manufacturing, incorporating these into existing thermal models of factory buildings. This makes it possible to map out the whole energy system, and hence to test efficiency measures, to understand the effect of processes on building energy use, to investigate recycling of heat or cooling into other processes or building conditioning, and so on. The paper describes some of the key concepts and modelling approaches involved in developing these models, and gives examples of some real processes modelled in factories. It concludes that such models are entirely feasible and potentially very useful, although to develop a tool which comprehensively models both energy and manufacturing flows would be a major undertaking
93-106, 2015 93 Multilevel random effect and marginal models

African Journals Online (AJOL)

injected by the candidate vaccine have a lower or higher risk for the occurrence of ... outcome relationship and test whether subjects inject- ... contains an agent that resembles a disease-causing ... to have different random effect variability at each cat- ... In the marginal models settings, the responses are ... Behavior as usual.
Gravitational lensing by eigenvalue distributions of random matrix models

Science.gov (United States)

Martínez Alonso, Luis; Medina, Elena

2018-05-01

We propose to use eigenvalue densities of unitary random matrix ensembles as mass distributions in gravitational lensing. The corresponding lens equations reduce to algebraic equations in the complex plane which can be treated analytically. We prove that these models can be applied to describe lensing by systems of edge-on galaxies. We illustrate our analysis with the Gaussian and the quartic unitary matrix ensembles.
Random resistor network model of minimal conductivity in graphene.

Science.gov (United States)

Cheianov, Vadim V; Fal'ko, Vladimir I; Altshuler, Boris L; Aleiner, Igor L

2007-10-26

Transport in undoped graphene is related to percolating current patterns in the networks of n- and p-type regions reflecting the strong bipolar charge density fluctuations. Finite transparency of the p-n junctions is vital in establishing the macroscopic conductivity. We propose a random resistor network model to analyze scaling dependencies of the conductance on the doping and disorder, the quantum magnetoresistance and the corresponding dephasing rate.
Model documentation report: Macroeconomic Activity Module (MAM) of the National Energy Modeling System

Energy Technology Data Exchange (ETDEWEB)

NONE

1997-02-01

This report documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Macroeconomic Activity Module (MAM) used to develop the Annual Energy Outlook for 1997 (AEO 97). The report catalogues and describes the module assumptions, computations, methodology, parameter estimation techniques, and mainframe source code. This document serves three purposes. First it is a reference document providing a detailed description of the NEMS MAM used for the AEO 1997 production runs for model analysts, users, and the public. Second, this report meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its models. Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements as future projects.
Designing a Model for the Glogbal Energy System—GENeSYS-MOD: An Application of the Open-Source Energy Modeling System (OSeMOSYS

Directory of Open Access Journals (Sweden)

Konstantin Löffler

2017-09-01

Full Text Available This paper develops a path for the global energy system up to 2050, presenting a new application of the open-source energy modeling system (OSeMOSYS to the community. It allows quite disaggregate energy and emission analysis: Global Energy System Model (GENeSYS-MOD uses a system of linear equations of the energy system to search for lowest-cost solutions for a secure energy supply, given externally defined constraints, mainly in terms of CO2-emissions. The general algebraic modeling system (GAMS version of OSeMOSYS is updated to the newest version and, in addition, extended and enhanced to include e.g., a modal split for transport, an improved trading system, and changes to storages. The model can be scaled from small-scale applications, e.g., a company, to cover the global energy system. The paper also includes an application of GENeSYS-MOD to analyze decarbonization scenarios at the global level, broken down into 10 regions. Its main focus is on interdependencies between traditionally segregated sectors: electricity, transportation, and heating; which are all included in the model. Model calculations suggests that in order to achieve the 1.5–2 °C target, a combination of renewable energy sources provides the lowest-cost solution, solar photovoltaic being the dominant source. Average costs of electricity generation in 2050 are about 4 €cents/kWh (excluding infrastructure and transportation costs.
QCD parton model at collider energies

International Nuclear Information System (INIS)

Ellis, R.K.

1984-09-01

Using the example of vector boson production, the application of the QCD improved parton model at collider energies is reviewed. The reliability of the extrapolation to SSC energies is assessed. Predictions at √S = 0.54 TeV are compared with data. 21 references
Energy and development : A modelling approach

NARCIS (Netherlands)

van Ruijven, B.J.|info:eu-repo/dai/nl/304834521

2008-01-01

Rapid economic growth of developing countries like India and China implies that these countries become important actors in the global energy system. Examples of this impact are the present day oil shortages and rapidly increasing emissions of greenhouse gases. Global energy models are used explore
OSeMOSYS Energy Modeling Using an Extended UTOPIA Model

Science.gov (United States)

Lavigne, Denis

2017-01-01

The OSeMOSYS project offers open-access energy modeling to a wide audience. Its relative simplicity makes it appealing for academic research and governmental organizations to study the impacts of policy decisions on an energy system in the context of possibly severe greenhouse gases emissions limitations. OSeMOSYS is a tool that enhances the…
Random broadcast on random geometric graphs

Energy Technology Data Exchange (ETDEWEB)

Bradonjic, Milan [Los Alamos National Laboratory; Elsasser, Robert [UNIV OF PADERBORN; Friedrich, Tobias [ICSI/BERKELEY; Sauerwald, Tomas [ICSI/BERKELEY

2009-01-01

In this work, we consider the random broadcast time on random geometric graphs (RGGs). The classic random broadcast model, also known as push algorithm, is defined as: starting with one informed node, in each succeeding round every informed node chooses one of its neighbors uniformly at random and informs it. We consider the random broadcast time on RGGs, when with high probability: (i) RGG is connected, (ii) when there exists the giant component in RGG. We show that the random broadcast time is bounded by {Omicron}({radical} n + diam(component)), where diam(component) is a diameter of the entire graph, or the giant component, for the regimes (i), or (ii), respectively. In other words, for both regimes, we derive the broadcast time to be {Theta}(diam(G)), which is asymptotically optimal.
Using observation-level random effects to model overdispersion in count data in ecology and evolution

Directory of Open Access Journals (Sweden)

Xavier A. Harrison

2014-10-01

Full Text Available Overdispersion is common in models of count data in ecology and evolutionary biology, and can occur due to missing covariates, non-independent (aggregated data, or an excess frequency of zeroes (zero-inflation. Accounting for overdispersion in such models is vital, as failing to do so can lead to biased parameter estimates, and false conclusions regarding hypotheses of interest. Observation-level random effects (OLRE, where each data point receives a unique level of a random effect that models the extra-Poisson variation present in the data, are commonly employed to cope with overdispersion in count data. However studies investigating the efficacy of observation-level random effects as a means to deal with overdispersion are scarce. Here I use simulations to show that in cases where overdispersion is caused by random extra-Poisson noise, or aggregation in the count data, observation-level random effects yield more accurate parameter estimates compared to when overdispersion is simply ignored. Conversely, OLRE fail to reduce bias in zero-inflated data, and in some cases increase bias at high levels of overdispersion. There was a positive relationship between the magnitude of overdispersion and the degree of bias in parameter estimates. Critically, the simulations reveal that failing to account for overdispersion in mixed models can erroneously inflate measures of explained variance (r2, which may lead to researchers overestimating the predictive power of variables of interest. This work suggests use of observation-level random effects provides a simple and robust means to account for overdispersion in count data, but also that their ability to minimise bias is not uniform across all types of overdispersion and must be applied judiciously.
A decision model for energy resource selection in China

International Nuclear Information System (INIS)

Wang Bing; Kocaoglu, Dundar F.; Daim, Tugrul U.; Yang Jiting

2010-01-01

This paper evaluates coal, petroleum, natural gas, nuclear energy and renewable energy resources as energy alternatives for China through use of a hierarchical decision model. The results indicate that although coal is still the major preferred energy alternative, it is followed closely by renewable energy. The sensitivity analysis indicates that the most critical criterion for energy selection is the current energy infrastructure. A hierarchical decision model is used, and expert judgments are quantified, to evaluate the alternatives. Criteria used for the evaluations are availability, current energy infrastructure, price, safety, environmental impacts and social impacts.
Directory of energy information administration models 1995

Energy Technology Data Exchange (ETDEWEB)

NONE

1995-07-13

This updated directory has been published annually; after this issue, it will be published only biennially. The Disruption Impact Simulator Model in use by EIA is included. Model descriptions have been updated according to revised documentation approved during the past year. This directory contains descriptions about each model, including title, acronym, purpose, followed by more detailed information on characteristics, uses, and requirements. Sources for additional information are identified. Included are 37 EIA models active as of February 1, 1995. The first group is the National Energy Modeling System (NEMS) models. The second group is all other EIA models that are not part of NEMS. Appendix A identifies major EIA modeling systems and the models within these systems. Appendix B is a summary of the `Annual Energy Outlook` Forecasting System.
Characterizing emerging industrial technologies in energy models

Energy Technology Data Exchange (ETDEWEB)

Laitner, John A. (Skip); Worrell, Ernst; Galitsky, Christina; Hanson, Donald A.

2003-07-29

Conservation supply curves are a common tool in economic analysis. As such, they provide an important opportunity to include a non-linear representation of technology and technological change in economy-wide models. Because supply curves are closely related to production isoquants, we explore the possibility of using bottom-up technology assessments to inform top-down representations of energy models of the U.S. economy. Based on a recent report by LBNL and ACEEE on emerging industrial technologies within the United States, we have constructed a supply curve for 54 such technologies for the year 2015. Each of the selected technologies has been assessed with respect to energy efficiency characteristics, likely energy savings by 2015, economics, and environmental performance, as well as needs for further development or implementation of the technology. The technical potential for primary energy savings of the 54 identified technologies is equal to 3.54 Quads, or 8.4 percent of the assume d2015 industrial energy consumption. Based on the supply curve, assuming a discount rate of 15 percent and 2015 prices as forecasted in the Annual Energy Outlook2002, we estimate the economic potential to be 2.66 Quads - or 6.3 percent of the assumed forecast consumption for 2015. In addition, we further estimate how much these industrial technologies might contribute to standard reference case projections, and how much additional energy savings might be available assuming a different mix of policies and incentives. Finally, we review the prospects for integrating the findings of this and similar studies into standard economic models. Although further work needs to be completed to provide the necessary link between supply curves and production isoquants, it is hoped that this link will be a useful starting point for discussion with developers of energy-economic models.
Modeling and Simulation of Energy Recovery from a Photovoltaic ...

African Journals Online (AJOL)

Modeling and Simulation of Energy Recovery from a Photovoltaic Solar cell. ... Photovoltaic (PV) solar cell which converts solar energy directly into electrical energy is one of ... model of the solar panel which could represent the real systems.

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