A random energy model for size dependence : recurrence vs. transience
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 gener
Sample to sample fluctuations in the random energy model
Derrida, B. (Service de Physique Theorique, CEN Saclay, 91 - Gif-sur-Yvette (France)); Toulouse, G. (E.S.P.C.I., 75 - Paris (France))
1985-03-15
In the spin glass phase, mean field theory says that the weights of the valleys vary from sample to sample. Exact expressions for the probability laws of these fluctuations are derived, from the random energy model, without recourse to the replica method.
Liouville field theory and log-correlated Random Energy Models
Cao, Xiangyu; Rosso, Alberto; Santachiara, Raoul
2016-01-01
An exact mapping is established between the $c\\geq25$ Liouville field theory (LFT) and the Gibbs measure statistics of a thermal particle in a 2D Gaussian Free Field plus a logarithmic confining potential. The probability distribution of the position of the minimum of the energy landscape is obtained exactly by combining the conformal bootstrap and one-step replica symmetry breaking methods. Operator product expansions in LFT allow to unveil novel universal behaviours of the log-correlated Random Energy class. High precision numerical tests are given.
Condition for Energy Efficient Watermarking with Random Vector Model without WSS Assumption
Yan, Bin; Guo, Yinjing
2009-01-01
Energy efficient watermarking preserves the watermark energy after linear attack as much as possible. We consider in this letter non-stationary signal models and derive conditions for energy efficient watermarking under random vector model without WSS assumption. We find that the covariance matrix of the energy efficient watermark should be proportional to host covariance matrix to best resist the optimal linear removal attacks. In WSS process our result reduces to the well known power spectrum condition. Intuitive geometric interpretation of the results are also discussed which in turn also provide more simpler proof of the main results.
Universality of AC conductivity: Random site-energy model with Fermi statistics
Pasveer, W. F.; Bobbert, P. A.; Michels, M. A. J.
2006-10-01
The universality of the frequency-dependent (AC) conduction of many disordered solids in the extreme-disorder limit has been demonstrated experimentally. Theoretically, this universality has been established with different techniques and for various models. A popular model that has been extensively investigated and for which AC universality was established is the symmetric random-barrier model without Fermi statistics. However, for the more realistic model of random site-energies and Fermi statistics AC universality has never been rigorously established. In the present work we perform a numerical study of the latter model for a regular lattice in two dimensions. In addition, we allow for variable-range hopping. Our main conclusion is that AC universality appears to hold for this realistic model. The obtained master curve for the conductivity and the one obtained for the random-barrier model in two dimensions appear to be the same.
Derrida's Generalized Random Energy models; 4, Continuous state branching and coalescents
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.
Manavalan, Balachandran; Lee, Juyong; Lee, Jooyoung
2014-01-01
Recently, predicting proteins three-dimensional (3D) structure from its sequence information has made a significant progress due to the advances in computational techniques and the growth of experimental structures. However, selecting good models from a structural model pool is an important and challenging task in protein structure prediction. In this study, we present the first application of random forest based model quality assessment (RFMQA) to rank protein models using its structural features and knowledge-based potential energy terms. The method predicts a relative score of a model by using its secondary structure, solvent accessibility and knowledge-based potential energy terms. We trained and tested the RFMQA method on CASP8 and CASP9 targets using 5-fold cross-validation. The correlation coefficient between the TM-score of the model selected by RFMQA (TMRF) and the best server model (TMbest) is 0.945. We benchmarked our method on recent CASP10 targets by using CASP8 and 9 server models as a training set. The correlation coefficient and average difference between TMRF and TMbest over 95 CASP10 targets are 0.984 and 0.0385, respectively. The test results show that our method works better in selecting top models when compared with other top performing methods. RFMQA is available for download from http://lee.kias.re.kr/RFMQA/RFMQA_eval.tar.gz.
Finite size corrections in the random energy model and the replica approach
Derrida, Bernard; Mottishaw, Peter
2015-01-01
We present a systematic and exact way of computing finite size corrections for the random energy model, in its low temperature phase. We obtain explicit (though complicated) expressions for the finite size corrections of the overlap functions. In its low temperature phase, the random energy model is known to exhibit Parisi's broken symmetry of replicas. The finite size corrections given by our exact calculation can be reproduced using replicas if we make specific assumptions about the fluctuations (with negative variances!) of the number and sizes of the blocks when replica symmetry is broken. As an alternative we show that the exact expression for the non-integer moments of the partition function can be written in terms of coupled contour integrals over what can be thought of as ‘complex replica numbers’. Parisi's one step replica symmetry breaking arises naturally from the saddle point of these integrals without making any ansatz or using the replica method. The fluctuations of the ‘complex replica numbers’ near the saddle point in the imaginary direction correspond to the negative variances we observed in the replica calculation. Finally our approach allows one to see why some apparently diverging series or integrals are harmless.
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).
Transverse momentum spectra of the produced hadrons at SPS energy and a random walk model
Bedangadas Mohanty
2014-05-01
The transverse momentum spectra of the produced hadrons have been compared to a model, which is based on the assumption that a nucleus–nucleus collision is a superposition of isotropically decaying thermal sources at a given freeze-out temperature. The freeze-out temperature in nucleus–nucleus collisions is fixed from the inverse slope of the transverse momentum spectra of hadrons in nucleon–nucleon collision. The successive collisions in the nuclear reaction lead to gain in transverse momentum, as the nucleons propagate in the nucleus following a random walk pattern. The average transverse rapidity shift per collision is determined from the nucleon–nucleus collision data. Using this information, we obtain parameter-free result for the transverse momentum distribution of produced hadrons in nucleus–nucleus collisions. It is observed that such a model is able to explain the transverse mass spectra of the produced pions at SPS energies. However, it fails to satisfactorily explain the transverse mass spectra of kaons and protons. This indicates the presence of collective effect which cannot be accounted for, by the initial state collision broadening of transverse momentum of produced hadrons, the basis of random walk model.
Random free energy barrier hopping model for ac conduction in chalcogenide glasses
Murti, Ram; Tripathi, S. K.; Goyal, Navdeep; Prakash, Satya
2016-03-01
The random free energy barrier hopping model is proposed to explain the ac conductivity (σac) of chalcogenide glasses. The Coulomb correlation is consistently accounted for in the polarizability and defect distribution functions and the relaxation time is augmented to include the overlapping of hopping particle wave functions. It is observed that ac and dc conduction in chalcogenides are due to same mechanism and Meyer-Neldel (MN) rule is the consequence of temperature dependence of hopping barriers. The exponential parameter s is calculated and it is found that s is subjected to sample preparation and measurement conditions and its value can be less than or greater than one. The calculated results for a - Se, As2S3, As2Se3 and As2Te3 are found in close agreement with the experimental data. The bipolaron and single polaron hopping contributions dominates at lower and higher temperatures respectively and in addition to high energy optical phonons, low energy optical and high energy acoustic phonons also contribute to the hopping process. The variations of hopping distance with temperature is also studied. The estimated defect number density and static barrier heights are compared with other existing calculations.
Adame, J.; Warzel, S., E-mail: warzel@ma.tum.de [Zentrum Mathematik, TU München, Boltzmannstr. 3, 85747 Garching (Germany)
2015-11-15
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.
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 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.
Energy and criticality in random Boolean networks
Andrecut, M. [Institute for Biocomplexity and Informatics, University of Calgary, 2500 University Drive NW, Calgary, Alberta, T2N 1N4 (Canada)], E-mail: mandrecu@ucalgary.ca; Kauffman, S.A. [Institute for Biocomplexity and Informatics, University of Calgary, 2500 University Drive NW, Calgary, Alberta, T2N 1N4 (Canada)
2008-06-30
The central issue of the research on the Random Boolean Networks (RBNs) model is the characterization of the critical transition between ordered and chaotic phases. Here, we discuss an approach based on the 'energy' associated with the unsatisfiability of the Boolean functions in the RBNs model, which provides an upper bound estimation for the energy used in computation. We show that in the ordered phase the RBNs are in a 'dissipative' regime, performing mostly 'downhill' moves on the 'energy' landscape. Also, we show that in the disordered phase the RBNs have to 'hillclimb' on the 'energy' landscape in order to perform computation. The analytical results, obtained using Derrida's approximation method, are in complete agreement with numerical simulations.
Exponential random graph models
Fronczak, Agata
2012-01-01
Nowadays, exponential random graphs (ERGs) are among the most widely-studied network models. Different analytical and numerical techniques for ERG have been developed that resulted in the well-established theory with true predictive power. An excellent basic discussion of exponential random graphs addressed to social science students and researchers is given in [Anderson et al., 1999][Robins et al., 2007]. This essay is intentionally designed to be more theoretical in comparison with the well-known primers just mentioned. Given the interdisciplinary character of the new emerging science of complex networks, the essay aims to give a contribution upon which network scientists and practitioners, who represent different research areas, could build a common area of understanding.
Random Phases and Energy Dispersion
刘全慧; 刘天贵; 班卫全
2003-01-01
Using 2N + 1 successive stationary states centred at nth, we construct a rectangular wavepacket in which the stationary states are superimposed with the equal weight √2N + 1. With the requirement of the wavepacket to be a quasi-classical state, the number N is determined by minimizing the uncertainty △x△p. Since the stationary state can only be determined to within an arbitrary multiplicative complex phase factor of unit magnitude, a number of N is obtained as a set of the phases are given. For a harmonic oscillator, when all of the phase factors are essentially the same, we have N ≈ [61/3n2/3] with [x] signifying the integral part of positive number x. When every phase in the phase factors is given by a random number generated in a closed interval [0, 2π] and when n ≥ 10, the probability of appearance of N is roughly 1/2N when N = 1 to 7, and does not exceed 0.01 whenN ≥ 8.
Curcó, David; Alemán, Carlos
2004-04-30
The performance of a recently developed method to generate representative atomistic models of amorphous polymers has been investigated. This method, which is denoted SuSi, can be defined as a random generator of energy minima. The effects produced by different parameters used to define the size of the system and the characteristics of the generation algorithm have been examined. Calculations have been performed on poly(L,D-lactic) acid (rho = 1.25 g/cm3) and nylon 6 (rho = 1.084 g/cm(3)), which are important commercial polymers.
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...
Vibration energy harvesting from random force and motion excitations
Tang, Xiudong; Zuo, Lei
2012-07-01
A vibration energy harvester is typically composed of a spring-mass system with an electromagnetic or piezoelectric transducer connected in parallel with a spring. This configuration has been well studied and optimized for harmonic vibration sources. Recently, a dual-mass harvester, where two masses are connected in series by the energy transducer and a spring, has been proposed. The dual-mass vibration energy harvester is proved to be able to harvest more power and has a broader bandwidth than the single-mass configuration, when the parameters are optimized and the excitation is harmonic. In fact, some dual-mass vibration energy harvesters, such as regenerative vehicle suspensions and buildings with regenerative tuned mass dampers (TMDs), are subjected to random excitations. This paper is to investigate the dual-mass and single-mass vibration harvesters under random excitations using spectrum integration and the residue theorem. The output powers for these two types of vibration energy harvesters, when subjected to different random excitations, namely force, displacement, velocity and acceleration, are obtained analytically with closed-form expressions. It is also very interesting to find that the output power of the vibration energy harvesters under random excitations depends on only a few parameters in very simple and elegant forms. This paper also draws some important conclusions on regenerative vehicle suspensions and buildings with regenerative TMDs, which can be modeled as dual-mass vibration energy harvesters. It is found that, under white-noise random velocity excitation from road irregularity, the harvesting power from vehicle suspensions is proportional to the tire stiffness and road vertical excitation spectrum only. It is independent of the chassis mass, tire-wheel mass, suspension stiffness and damping coefficient. Under random wind force excitation, the power harvested from buildings with regenerative TMD will depends on the building mass only, not
Random Intercept and Random Slope 2-Level Multilevel Models
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.
The XXZ Heisenberg model on random surfaces
Ambjørn, J., E-mail: ambjorn@nbi.dk [The Niels Bohr Institute, Copenhagen University, Blegdamsvej 17, DK-2100 Copenhagen (Denmark); Institute for Mathematics, Astrophysics and Particle Physics (IMAPP), Radbaud University Nijmegen, Heyendaalseweg 135, 6525 AJ, Nijmegen (Netherlands); Sedrakyan, A., E-mail: sedrak@nbi.dk [The Niels Bohr Institute, Copenhagen University, Blegdamsvej 17, DK-2100 Copenhagen (Denmark); Yerevan Physics Institute, Br. Alikhanyan str. 2, Yerevan-36 (Armenia)
2013-09-21
We consider integrable models, or in general any model defined by an R-matrix, on random surfaces, which are discretized using random Manhattan lattices. The set of random Manhattan lattices is defined as the set dual to the lattice random surfaces embedded on a regular d-dimensional lattice. They can also be associated with the random graphs of multiparticle scattering nodes. As an example we formulate a random matrix model where the partition function reproduces the annealed average of the XXZ Heisenberg model over all random Manhattan lattices. A technique is presented which reduces the random matrix integration in partition function to an integration over their eigenvalues.
The XXZ Heisenberg model on random surfaces
Ambjorn, J
2013-01-01
We consider integrable models, or in general any model defined by an $R$-matrix, on random surfaces, which are discretized using random Manhattan lattices. The set of random Manhattan lattices is defined as the set dual to the lattice random surfaces embedded on a regular d-dimensional lattice. They can also be associated with the random graphs of multiparticle scattering nodes. As an example we formulate a random matrix model where the partition function reproduces the annealed average of the XXZ Heisenberg model over all random Manhattan lattices. A technique is presented which reduces the random matrix integration in partition function to an integration over their eigenvalues.
Precise Asymptotics for Random Matrices and Random Growth Models
Zhong Gen SU
2008-01-01
The author considers the largest eigenvalues of random matrices from Gaussian unitary ensemble and Laguerre unitary ensemble, and the rightmost charge in certain random growth models.We obtain some precise asymptotics results, which are in a sense similar to the precise asymptotics for sums of independent random variables in the context of the law of large numbers and complete convergence. Our proofs depend heavily upon the upper and lower tail estimates for random matrices and random growth models. The Tracy-Widom distribution plays a central role as well.
Reiter, E.R.
1980-01-01
A highly sophisticated and accurate approach is described to compute on an hourly or daily basis the energy consumption for space heating by individual buildings, urban sectors, and whole cities. The need for models and specifically weather-sensitive models, composite models, and space-heating models are discussed. Development of the Colorado State University Model, based on heat-transfer equations and on a heuristic, adaptive, self-organizing computation learning approach, is described. Results of modeling energy consumption by the city of Minneapolis and Cheyenne are given. Some data on energy consumption in individual buildings are included.
A Mixed Effects Randomized Item Response Model
Fox, J.-P.; Wyrick, Cheryl
2008-01-01
The randomized response technique ensures that individual item responses, denoted as true item responses, are randomized before observing them and so-called randomized item responses are observed. A relationship is specified between randomized item response data and true item response data. True item response data are modeled with a (non)linear…
Generalization of Random Intercept Multilevel Models
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.
The parabolic Anderson model random walk in random potential
König, Wolfgang
2016-01-01
This is a comprehensive survey on the research on the parabolic Anderson model – the heat equation with random potential or the random walk in random potential – of the years 1990 – 2015. The investigation of this model requires a combination of tools from probability (large deviations, extreme-value theory, e.g.) and analysis (spectral theory for the Laplace operator with potential, variational analysis, e.g.). We explain the background, the applications, the questions and the connections with other models and formulate the most relevant results on the long-time behavior of the solution, like quenched and annealed asymptotics for the total mass, intermittency, confinement and concentration properties and mass flow. Furthermore, we explain the most successful proof methods and give a list of open research problems. Proofs are not detailed, but concisely outlined and commented; the formulations of some theorems are slightly simplified for better comprehension.
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)
Random Effect and Latent Variable Model Selection
Dunson, David B
2008-01-01
Presents various methods for accommodating model uncertainty in random effects and latent variable models. This book focuses on frequentist likelihood ratio and score tests for zero variance components. It also focuses on Bayesian methods for random effects selection in linear mixed effects and generalized linear mixed models
Infinite Random Graphs as Statistical Mechanical Models
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...
Analysis theory of random energy of train derailment in wind
无
2010-01-01
Based on the analysis theory of random energy of train derailment, an analysis theory of random energy of train derailment in wind is suggested. Two methods are proposed -the time domain method and the frequency domain method of analysis theory of random energy of train derailment in wind. The curves of σ pw -v under various wind speeds are obtained through the computation. The original curve of σ p -v is expanded, which turns the analysis theory of random energy of train derailment into the all-weather theory. Train derailment condition has been established under wind action. The first and second criterions of train derailment have been proposed in light of wind action. The analysis of train derailment cases at home or abroad is made, in- cluding the first analysis of Xinjiang train derailment case encountered 13-level of gale, which explained the inevitability of train derailment. The analysis theory of random energy of train derailment in wind shows its validity and accuracy. The input energy σ pw of the transverse vibration of train-track(bridge)-wind system is linked to train speed. With the establishment of the analysis theory of random energy of train derailment in wind, It is likely to initiate an all-weather speed limit map for a train or any high-speed train.
DUAL RANDOM MODEL OF INCREASING ANNUITY
HeWenjiong; ZhangYi
2001-01-01
The dual random models about the life insurance and social pension insurance have received considerable attention in the recent articles on actuarial theory and applications. This paper discusses a general kind of increasing annuity based on its force of interest accumulationfunction as a general random process. The dual random model of the present value of the benefits of the increasing annuity has been set, and their moments have been calculated under certainconditions.
National Energy Modeling System
Skinner, C.W. (Energy Information Administration, Washington, DC (United States))
1993-01-01
The Energy Information Administration is developing a new National Energy Modeling System to provide annual forecasts of energy supply, demand, and prices on a regional basis in the United States and, to a limited extent, in the rest of the world. The design for the system was based on a requirements analysis, a comparison of requirements with existing modeling capabilities, and a series of widely circulated issue papers defining the choices and tradeoffs for 13 key design decisions. An initial prototpye of the new NEMS was implemented in late 1992, with a more complete, operational version in 1993. NEMS is expected to provide EIA and other users with a greatly enhanced ability to illustrate quickly and effectively the effects of a wide range of energy policy proposals.
Energy Centroids in the presence of random interactions
Zhao, Y M; 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, those with fixed irreducible representations for bosons, 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 more robust than expected.
Random Riesz energies on compact K\\"{a}hler manifolds
Feng, Renjie
2011-01-01
This article determines the asymptotics of the expected Riesz s-energy of the zero set of a Gaussian random systems of polynomials of degree N as the degree N tends to infinity in all dimensions and codimensions. The asymptotics are proved more generally for sections of any positive line bundle over any compact Kaehler manifold. In comparison with the results on energies of zero sets in one complex dimension due to Qi Zhong (arXiv:0705.2000) (see also [arXiv:0705.2000]), the zero sets have higher energies than randomly chosen points in dimensions > 2 due to clumping of zeros.
Random Walk Smooth Transition Autoregressive Models
2004-01-01
This paper extends the family of smooth transition autoregressive (STAR) models by proposing a specification in which the autoregressive parameters follow random walks. The random walks in the parameters can capture structural change within a regime switching framework, but in contrast to the time varying STAR (TV-STAR) speciifcation recently introduced by Lundbergh et al (2003), structural change in our random walk STAR (RW-STAR) setting follows a stochastic process rather than a determinist...
Quenched Point-to-Point Free Energy for Random Walks in Random Potentials
Rassoul-Agha, Firas
2012-01-01
We consider a random walk in a random potential on a square lattice of arbitrary dimension. The potential is a function of an ergodic environment and some steps of the walk. The potential can be unbounded, but it is subject to a moment assumption whose strictness is tied to the mixing of the environment, the best case being the i.i.d. environment. We prove that the infinite volume quenched point-to-point free energy exists and has a variational formula in terms of an entropy. We establish regularity properties of the point-to-point free energy, as a function of the potential and as a function on the convex hull of the admissible steps of the walk, and link it to the infinite volume free energy and quenched large deviations of the endpoint of the walk. One corollary is a quenched large deviation principle for random walk in an ergodic random environment, with a continuous rate function.
Quenched Free Energy and Large Deviations for Random Walks in Random Potentials
Rassoul-Agha, Firas; Yilmaz, Atilla
2011-01-01
We study quenched distributions on random walks in a random potential on integer lattices of arbitrary dimension and with an arbitrary finite set of admissible steps. The potential can be unbounded and can depend on a few steps of the walk. Directed, undirected and stretched polymers, as well as random walk in random environment, are covered. The restriction needed is on the moment of the potential, in relation to the degree of mixing of the ergodic environment. We derive two variational formulas for the limiting quenched free energy and prove a process-level quenched large deviation principle for the empirical measure. As a corollary we obtain LDPs for types of random walk in random environment not covered by earlier results.
Thermal vacancy formation energies of random solid solutions
Luo, H. B.; Hu, Q. M.; Du, J.; Yan, A. R.; Liu, J. P.
2017-01-01
Vacancy mechanism plays a dominant role in the atomic migration when a close-packed disordered alloy undergoes ordering transition. However, the calculation of thermal vacancy formation energies (VFEs) of random solid solutions is usually cumbersome due to the difficulty in considering various local atomic environments. Here, we propose a transparent way that combines coherent potential approximation and supercell-local cluster expansion to investigate VFEs of random solid solutions. This met...
Carrozza, Sylvain; Tanasa, Adrian
2016-11-01
We define in this paper a class of three-index tensor models, endowed with {O(N)^{⊗ 3}} invariance ( N being the size of the tensor). This allows to generate, via the usual QFT perturbative expansion, a class of Feynman tensor graphs which is strictly larger than the class of Feynman graphs of both the multi-orientable model (and hence of the colored model) and the U( N) invariant models. We first exhibit the existence of a large N expansion for such a model with general interactions. We then focus on the quartic model and we identify the leading and next-to-leading order (NLO) graphs of the large N expansion. Finally, we prove the existence of a critical regime and we compute the critical exponents, both at leading order and at NLO. This is achieved through the use of various analytic combinatorics techniques.
Recent progress on the Random Conductance Model
Biskup, Marek
2011-01-01
Recent progress on the understanding of the Random Conductance Model is reviewed and commented. A particular emphasis is on the results on the scaling limit of the random walk among random conductances for almost every realization of the environment, observations on the behavior of the effective resistance as well as the scaling limit of certain models of gradient fields with non-convex interactions. The text is an expanded version of the lecture notes for a course delivered at the 2011 Cornell Summer School on Probability.
Estimating the Energy Consumption of Emerging Random Access Memory Technologies
Moreau, Magnus
2013-01-01
In this work, a model for estimating the energy consumption of different types ofrandom access memory(RAM) technologies, likely to be commercially available by2017, has been developed. The goal for this model has been to evaluate whichof the memory technologies that will be the most energy efficient in 2017. Thiswas done by building the model on the required energies to read or write a bit forthe different technologies. The memory technologies that have been modelled are:Dynamic RAM (DRAM), S...
Modelling population processes with random initial conditions.
Pollett, P K; Dooley, A H; Ross, J V
2010-02-01
Population dynamics are almost inevitably associated with two predominant sources of variation: the first, demographic variability, a consequence of chance in progenitive and deleterious events; the second, initial state uncertainty, a consequence of partial observability and reporting delays and errors. Here we outline a general method for incorporating random initial conditions in population models where a deterministic model is sufficient to describe the dynamics of the population. Additionally, we show that for a large class of stochastic models the overall variation is the sum of variation due to random initial conditions and variation due to random dynamics, and thus we are able to quantify the variation not accounted for when random dynamics are ignored. Our results are illustrated with reference to both simulated and real data.
2017-04-27
Energy Operation Model (EOM) simulates the operation of the electric grid at the zonal scale, including inter-zonal transmission constraints. It generates the production cost, power generation by plant and category, fuel usage, and locational marginal price (LMP) with a flexible way to constrain the power production by environmental constraints, e.g. heat waves, drought conditions). Different from commercial software such as PROMOD IV where generator capacity and heat rate efficiency can only be adjusted on a monthly basis, EOM calculates capacity impacts and plant efficiencies based on hourly ambient conditions (air temperature and humidity) and cooling water availability for thermal plants. What is missing is a hydro power dispatch.
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
Free energy fluctuations for directed polymers in random media in 1+1 dimension
Borodin, Alexei; Ferrari, Patrik
2012-01-01
We consider two models for directed polymers in space-time independent random media (the O'Connell-Yor semi-discrete directed polymer and the continuum directed random polymer) at positive temperature and prove their KPZ universality via asymptotic analysis of exact Fredholm determinant formulas for the Laplace transform of their partition functions. In particular, we show that for large time tau, the probability distributions for the free energy fluctuations, when rescaled by tau^{1/3}, converges to the GUE Tracy-Widom distribution. We also consider the effect of boundary perturbations to the quenched random media on the limiting free energy statistics. For the semi-discrete directed polymer, when the drifts of a finite number of the Brownian motions forming the quenched random media are critically tuned, the statistics are instead governed by the limiting Baik-Ben Arous-Peche distributions from spiked random matrix theory. For the continuum polymer, the boundary perturbations correspond to choosing the init...
Random matrix model approach to chiral symmetry
Verbaarschot, J J M
1996-01-01
We review the application of random matrix theory (RMT) to chiral symmetry in QCD. Starting from the general philosophy of RMT we introduce a chiral random matrix model with the global symmetries of QCD. Exact results are obtained for universal properties of the Dirac spectrum: i) finite volume corrections to valence quark mass dependence of the chiral condensate, and ii) microscopic fluctuations of Dirac spectra. Comparisons with lattice QCD simulations are made. Most notably, the variance of the number of levels in an interval containing $n$ levels on average is suppressed by a factor $(\\log n)/\\pi^2 n$. An extension of the random matrix model model to nonzero temperatures and chemical potential provides us with a schematic model of the chiral phase transition. In particular, this elucidates the nature of the quenched approximation at nonzero chemical potential.
Computer simulations of the random barrier model
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......, focusing on universality of the ac response in the extreme disorder limit. Finally, some important unsolved problems relating to hopping models for ac conduction are listed....
A Dexterous Optional Randomized Response Model
Tarray, Tanveer A.; Singh, Housila P.; Yan, Zaizai
2017-01-01
This article addresses the problem of estimating the proportion Pi[subscript S] of the population belonging to a sensitive group using optional randomized response technique in stratified sampling based on Mangat model that has proportional and Neyman allocation and larger gain in efficiency. Numerically, it is found that the suggested model is…
Theory of random energy analysis for train derailment
向俊; 曾庆元; 娄平
2003-01-01
Three fundamental problems in the calculation of train derailment abroad and at home were pointed out and the solutions to these problems were presented. The theory of random energy analysis for train derailment was suggested. The main contents of this theory are as follows: geometric criterion of derailment; method of random energy analysis of transverse vibration of train track system; mechanism of derailment and energy increment criterion for derailment evaluation; calculation of the entire derailment course of train. This theory is used to calculate a case of freight train derailment, which corresponds to an actually occurring accident. Another derailment test, in which the train is judged not to be derailed, is calculated and the maximum vibration response is well correspond to the test results. And the effectiveness and practicability of the theory are proved by the two calculated cases.
National Energy Outlook Modelling System
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.
Energy System Modeling with REopt
Simpkins, Travis; Anderson, Kate; Cutler, Dylan; Olis, Dan; Elgqvist, Emma; DiOrio, Nick; Walker, Andy
2016-07-15
This poster details how REopt - NREL's software modeling platform for energy systems integration and optimization - can help to model energy systems. Some benefits of modeling with REopt include optimizing behind the meter storage for cost and resiliency, optimizing lab testing, optimizing dispatch of utility scale storage, and quantifying renewable energy impact on outage survivability.
Randomly Stopped Sums: Models and Psychological Applications
Michael eSmithson
2014-11-01
Full Text Available This paper describes an approach to modeling the sums of a continuous random variable over a number of measurement occasions when the number of occasions also is a random variable. A typical example is summing the amounts of time spent attending to pieces of information in an information search task leading to a decision to obtain the total time taken to decide. Although there is a large literature on randomly stopped sums in financial statistics, it is largely absent from psychology. The paper begins with the standard modeling approaches used in financial statistics, and then extends them in two ways. First, the randomly stopped sums are modeled as ``life distributions'' such as the gamma or log-normal distribution. A simulation study investigates Type I error rate accuracy and power for gamma and log-normal versions of this model. Second, a Bayesian hierarchical approach is used for constructing an appropriate general linear model of the sums. Model diagnostics are discussed, and three illustrations are presented from real datasets.
Critical properties of random Potts models
Kinzel, Wolfgang; Domany, Eytan
1981-04-01
The critical properties of Potts models with random bonds are considered in two dimensions. A position-space renormalization-group procedure, based on the Migdal-Kadanoff method, is developed. While all previous position-space calculations satisfied the Harris criterion and the resulting scaling relation only approximately, we found conditions under which these relations are exactly satisfied, and constructed our renormalization-group procedure accordingly. Numerical results for phase diagrams and thermodynamic functions for various random-bond Potts models are presented. In addition, some exact results obtained using a duality transformation, as well as an heuristic derivation of scaling properties that correspond to the percolation problem are given.
Duality between random trap and barrier models
Jack, Robert L [Department of Chemistry, University of California at Berkeley, Berkeley, CA 94720 (United States); Sollich, Peter [Department of Mathematics, King' s College London, London WC2R 2LS (United Kingdom)
2008-08-15
We discuss the physical consequences of a duality between two models with quenched disorder, in which particles propagate in one dimension among random traps or across random barriers. We derive an exact relation between their diffusion fronts at fixed disorder and deduce from this that their disorder-averaged diffusion fronts are exactly equal. We use effective dynamics schemes to isolate the different physical processes by which particles propagate in the models and discuss how the duality arises from a correspondence between the rates for these different processes.
Parabolic Anderson Model in a Dynamic Random Environment: Random Conductances
Erhard, D.; den Hollander, F.; Maillard, G.
2016-06-01
The parabolic Anderson model is defined as the partial differential equation ∂ u( x, t)/ ∂ t = κ Δ u( x, t) + ξ( x, t) u( x, t), x ∈ ℤ d , t ≥ 0, where κ ∈ [0, ∞) is the diffusion constant, Δ is the discrete Laplacian, and ξ is a dynamic random environment that drives the equation. The initial condition u( x, 0) = u 0( x), x ∈ ℤ d , is typically taken to be non-negative and bounded. The solution of the parabolic Anderson equation describes the evolution of a field of particles performing independent simple random walks with binary branching: particles jump at rate 2 d κ, split into two at rate ξ ∨ 0, and die at rate (- ξ) ∨ 0. In earlier work we looked at the Lyapunov exponents λ p(κ ) = limlimits _{tto ∞} 1/t log {E} ([u(0,t)]p)^{1/p}, quad p in {N} , qquad λ 0(κ ) = limlimits _{tto ∞} 1/2 log u(0,t). For the former we derived quantitative results on the κ-dependence for four choices of ξ : space-time white noise, independent simple random walks, the exclusion process and the voter model. For the latter we obtained qualitative results under certain space-time mixing conditions on ξ. In the present paper we investigate what happens when κΔ is replaced by Δ𝓚, where 𝓚 = {𝓚( x, y) : x, y ∈ ℤ d , x ˜ y} is a collection of random conductances between neighbouring sites replacing the constant conductances κ in the homogeneous model. We show that the associated annealed Lyapunov exponents λ p (𝓚), p ∈ ℕ, are given by the formula λ p({K} ) = {sup} {λ p(κ ) : κ in {Supp} ({K} )}, where, for a fixed realisation of 𝓚, Supp(𝓚) is the set of values taken by the 𝓚-field. We also show that for the associated quenched Lyapunov exponent λ 0(𝓚) this formula only provides a lower bound, and we conjecture that an upper bound holds when Supp(𝓚) is replaced by its convex hull. Our proof is valid for three classes of reversible ξ, and for all 𝓚
Two-Stage Modelling Of Random Phenomena
Barańska, Anna
2015-12-01
The main objective of this publication was to present a two-stage algorithm of modelling random phenomena, based on multidimensional function modelling, on the example of modelling the real estate market for the purpose of real estate valuation and estimation of model parameters of foundations vertical displacements. The first stage of the presented algorithm includes a selection of a suitable form of the function model. In the classical algorithms, based on function modelling, prediction of the dependent variable is its value obtained directly from the model. The better the model reflects a relationship between the independent variables and their effect on the dependent variable, the more reliable is the model value. In this paper, an algorithm has been proposed which comprises adjustment of the value obtained from the model with a random correction determined from the residuals of the model for these cases which, in a separate analysis, were considered to be the most similar to the object for which we want to model the dependent variable. The effect of applying the developed quantitative procedures for calculating the corrections and qualitative methods to assess the similarity on the final outcome of the prediction and its accuracy, was examined by statistical methods, mainly using appropriate parametric tests of significance. The idea of the presented algorithm has been designed so as to approximate the value of the dependent variable of the studied phenomenon to its value in reality and, at the same time, to have it "smoothed out" by a well fitted modelling function.
Improving randomness characterization through Bayesian model selection
R., Rafael Díaz-H; Martínez, Alí M Angulo; U'Ren, Alfred B; Hirsch, Jorge G; Marsili, Matteo; Castillo, Isaac Pérez
2016-01-01
Nowadays random number generation plays an essential role in technology with important applications in areas ranging from cryptography, which lies at the core of current communication protocols, to Monte Carlo methods, and other probabilistic algorithms. In this context, a crucial scientific endeavour is to develop effective methods that allow the characterization of random number generators. However, commonly employed methods either lack formality (e.g. the NIST test suite), or are inapplicable in principle (e.g. the characterization derived from the Algorithmic Theory of Information (ATI)). In this letter we present a novel method based on Bayesian model selection, which is both rigorous and effective, for characterizing randomness in a bit sequence. We derive analytic expressions for a model's likelihood which is then used to compute its posterior probability distribution. Our method proves to be more rigorous than NIST's suite and the Borel-Normality criterion and its implementation is straightforward. We...
Random effect selection in generalised linear models
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...
Infinite Random Graphs as Statistical Mechanical Models
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 relation to the so-called uniform infinite tree and results on the Hausdorff and spectral dimension of two-dimensional space-time obtained in B. Durhuus, T. Jonsson, J.F. Wheater, J. Stat. Phys. 139, 859 (2010) are briefly outlined. For the latter we discuss results on the absence of spontaneous...... magnetization and argue that, in the generic case, the values of the Hausdorff and spectral dimension of the underlying infinite trees are not influenced by the coupling to an Ising model in a constant magnetic field (B. Durhuus, G.M. Napolitano, in preparation)...
Tests of Hypotheses Arising In the Correlated Random Coefficient Model.
Heckman, James J; Schmierer, Daniel
2010-11-01
This paper examines the correlated random coefficient model. It extends the analysis of Swamy (1971), who pioneered the uncorrelated random coefficient model in economics. We develop the properties of the correlated random coefficient model and derive a new representation of the variance of the instrumental variable estimator for that model. We develop tests of the validity of the correlated random coefficient model against the null hypothesis of the uncorrelated random coefficient model.
Regularities with random interactions in energy centroids defined by group symmetries
Kota, V K B
2005-01-01
Regular structures generated by random interactions in energy centroids defined over irreducible representations (irreps) of some of the group symmetries of the interacting boson models $sd$IBM, $sdg$IBM, $sd$IBM-$T$ and $sd$IBM-$ST$ are studied by deriving trace propagations equations for the centroids. It is found that, with random interactions, the lowest and highest group irreps in general carry most of the probability for the corresponding centroids to be lowest in energy. This generalizes the result known earlier, via numerical diagonalization, for the more complicated fixed spin ($J$) centroids where simple trace propagation is not possible.
Testing the Correlated Random Coefficient Model*
Heckman, James J.; Schmierer, Daniel; Urzua, Sergio
2010-01-01
The recent literature on instrumental variables (IV) features models in which agents sort into treatment status on the basis of gains from treatment as well as on baseline-pretreatment levels. Components of the gains known to the agents and acted on by them may not be known by the observing economist. Such models are called correlated random coe cient models. Sorting on unobserved components of gains complicates the interpretation of what IV estimates. This paper examines testable implications of the hypothesis that agents do not sort into treatment based on gains. In it, we develop new tests to gauge the empirical relevance of the correlated random coe cient model to examine whether the additional complications associated with it are required. We examine the power of the proposed tests. We derive a new representation of the variance of the instrumental variable estimator for the correlated random coefficient model. We apply the methods in this paper to the prototypical empirical problem of estimating the return to schooling and nd evidence of sorting into schooling based on unobserved components of gains. PMID:21057649
Delayed Random Walks: Modeling Human Posture Control
Ohira, Toru
1998-03-01
We consider a phenomenological description of a noisy trajectory which appears on a stabiliogram platform during human postural sway. We hypothesize that this trajectory arises due to a mixture of uncontrollable noise and a corrective delayed feedback to an upright position. Based on this hypothesis, we model the process with a biased random walk whose transition probability depends on its position at a fixed time delay in the past, which we call a delayed random walk. We first introduce a very simple model (T. Ohira and J. G. Milton, Phys.Rev.E. 52), 3277, (1995), which can nevertheless capture the rough qualitative features of the two--point mean square displacement of experimental data with reasonable estimation of delay time. Then, we discuss two approaches toward better capturing and understanding of the experimental data. The first approach is an extension of the model to include a spatial displacement threshold from the upright position below which no or only weak corrective feedback motion takes place. This can be incorporated into an extended delayed random walk model. Numerical simulations show that this extended model can better capture the three scaling region which appears in the two--point mean square displacement. The other approach studied the autocorrelation function of the experimental data, which shows oscillatory behavior. We recently investigated a delayed random walk model whose autocorrelation function has analytically tractable oscillatory behavior (T. Ohira, Phys.Rev.E. 55), R1255, (1997). We discuss how this analytical understanding and its application to delay estimation (T. Ohira and R. Sawatari, Phys.Rev.E. 55), R2077, (1997) could possibly be used to further understand the postural sway data.
Random matrix model for disordered conductors
Zafar Ahmed; Sudhir R Jain
2000-03-01
We present a random matrix ensemble where real, positive semi-deﬁnite matrix elements, , are log-normal distributed, $\\exp[-\\log^{2}(x)]$. We show that the level density varies with energy, , as 2/(1 + ) for large , in the unitary family, consistent with the expectation for disordered conductors. The two-level correlation function is studied for the unitary family and found to be largely of the universal form despite the fact that the level density has a non-compact support. The results are based on the method of orthogonal polynomials (the Stieltjes-Wigert polynomials here). An interesting random walk problem associated with the joint probability distribution of the ensuing ensemble is discussed and its connection with level dynamics is brought out. It is further proved that Dyson's Coulomb gas analogy breaks down whenever the conﬁning potential is given by a transcendental function for which there exist orthogonal polynomials.
Random versus Deterministic Descent in RNA Energy Landscape Analysis
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.
Inventory of state energy models
Melcher, A.G.; Gist, R.L.; Underwood, R.G.; Weber, J.C.
1980-03-31
These models address a variety of purposes, such as supply or demand of energy or of certain types of energy, emergency management of energy, conservation in end uses of energy, and economic factors. Fifty-one models are briefly described as to: purpose; energy system; applications;status; validation; outputs by sector, energy type, economic and physical units, geographic area, and time frame; structure and modeling techniques; submodels; working assumptions; inputs; data sources; related models; costs; references; and contacts. Discussions in the report include: project purposes and methods of research, state energy modeling in general, model types and terminology, and Federal legislation to which state modeling is relevant. Also, a state-by-state listing of modeling efforts is provided and other model inventories are identified. The report includes a brief encylopedia of terms used in energy models. It is assumed that many readers of the report will not be experienced in the technical aspects of modeling. The project was accomplished by telephone conversations and document review by a team from the Colorado School of Mines Research Institute and the faculty of the Colorado School of Mines. A Technical Committee (listed in the report) provided advice during the course of the project.
Objective information about energy models
Hale, D.R. (Energy Information Administration, Washington, DC (United States))
1993-01-01
This article describes the Energy Information Administration's program to develop objective information about its modeling systems without hindering model development and applications, and within budget and human resource constraints. 16 refs., 1 fig., 2 tabs.
Kinetic models with randomly perturbed binary collisions
Bassetti, Federico; Toscani, Giuseppe
2010-01-01
We introduce a class of Kac-like kinetic equations on the real line, with general random collisional rules, which include as particular cases models for wealth redistribution in an agent-based market or models for granular gases with a background heat bath. Conditions on these collisional rules which guarantee both the existence and uniqueness of equilibrium profiles and their main properties are found. We show that the characterization of these stationary solutions is of independent interest, since the same profiles are shown to be solutions of different evolution problems, both in the econophysics context and in the kinetic theory of rarefied gases.
A discrete impulsive model for random heating and Brownian motion
Ramshaw, John D.
2010-01-01
The energy of a mechanical system subjected to a random force with zero mean increases irreversibly and diverges with time in the absence of friction or dissipation. This random heating effect is usually encountered in phenomenological theories formulated in terms of stochastic differential equations, the epitome of which is the Langevin equation of Brownian motion. We discuss a simple discrete impulsive model that captures the essence of random heating and Brownian motion. The model may be regarded as a discrete analog of the Langevin equation, although it is developed ab initio. Its analysis requires only simple algebraic manipulations and elementary averaging concepts, but no stochastic differential equations (or even calculus). The irreversibility in the model is shown to be a consequence of a natural causal stochastic condition that is closely analogous to Boltzmann's molecular chaos hypothesis in the kinetic theory of gases. The model provides a simple introduction to several ostensibly more advanced topics, including random heating, molecular chaos, irreversibility, Brownian motion, the Langevin equation, and fluctuation-dissipation theorems.
Particle filters for random set models
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...
Random graph models for dynamic networks
Zhang, Xiao; Newman, M E J
2016-01-01
We propose generalizations of a number of standard network models, including the classic random graph, the configuration model, and the stochastic block model, to the case of time-varying networks. We assume that the presence and absence of edges are governed by continuous-time Markov processes with rate parameters that can depend on properties of the nodes. In addition to computing equilibrium properties of these models, we demonstrate their use in data analysis and statistical inference, giving efficient algorithms for fitting them to observed network data. This allows us, for instance, to estimate the time constants of network evolution or infer community structure from temporal network data using cues embedded both in the probabilities over time that node pairs are connected by edges and in the characteristic dynamics of edge appearance and disappearance. We illustrate our methods with a selection of applications, both to computer-generated test networks and real-world examples.
Energy Balance for Random Vibrations of Piecewise-Conservative Systems
IOURTCHENKO, D. V.; DIMENTBERG, M. F.
2001-12-01
Vibrations of systems with instantaneous or stepwise energy losses, e.g., due to impacts with imperfect rebounds, dry friction forces(s) (in which case the losses may be treated as instantaneous ones by appropriate introduction of the response energy) and/or active feedback “bang-bang” control of the systems' response are considered. Response of such (non-linear) systems to a white-noise random excitation is considered for the case where there are no other response energy losses. Thus, a simple linear energy growth with time between “jumps” is observed. Explicit expressions for the expected response energy are derived by direct application of the stochastic differential equations calculus, which contains the expected time interval between two consecutive jumps. The latter may be predicted as a solution to the relevant first-passage problem. Perturbational analysis of the relevant PDE for this problem for a certain vibroimpact system demonstrated the possibility for using the solution to the corresponding free vibration problem as a zero order approximation. The method is applied to an s.d.o.f. system with a feedback inertia control, designed according to a certain previously introduced “generalized reversed swings law”. Extensive Monte-Carlo simulation results are presented for this system as well as for several previously analyzed ones: system with impacts; system with dry friction; system with stiffness control; pendulum with controlled length. The results are compared with those due to the asymptotic stochastic averaging approach. Both methods are shown to provide adequate accuracy far beyond the expected applicability range of the asymptotic approach (which requires both excitation intensity and losses to be small), with direct energy balance being generally superior.
Energy demand modeling for Uzbekistan
Bobur Khodjaev
2012-05-01
Full Text Available The paper is devoted to energy demand forecasting in Uzbekistan. Studies show that in spite of the abundant reserves of hydrocarbons, low energy efficiency can have an adverse impact on energy security in Uzbekistan in the future. Oil and gas are the main primary energy source and they ensure energy security of Uzbekistan. Energy demand forecasting is essential in order to develop an effective energy policy. Such forecast can be useful to plan oil and gas production volumes, to identify priorities for the industrial modernization and to create favorable conditions for sustainable economic development in the future. Author proposes model based on translog function for developing medium-and long-term development programs in energy sector and the modernization and technological re-equipment of industry.
Estimation in Dirichlet random effects models
Kyung, Minjung; Casella, George; 10.1214/09-AOS731
2010-01-01
We develop a new Gibbs sampler for a linear mixed model with a Dirichlet process random effect term, which is easily extended to a generalized linear mixed model with a probit link function. Our Gibbs sampler exploits the properties of the multinomial and Dirichlet distributions, and is shown to be an improvement, in terms of operator norm and efficiency, over other commonly used MCMC algorithms. We also investigate methods for the estimation of the precision parameter of the Dirichlet process, finding that maximum likelihood may not be desirable, but a posterior mode is a reasonable approach. Examples are given to show how these models perform on real data. Our results complement both the theoretical basis of the Dirichlet process nonparametric prior and the computational work that has been done to date.
Reducing RANS Model Error Using Random Forest
Wang, Jian-Xun; Wu, Jin-Long; Xiao, Heng; Ling, Julia
2016-11-01
Reynolds-Averaged Navier-Stokes (RANS) models are still the work-horse tools in the turbulence modeling of industrial flows. However, the model discrepancy due to the inadequacy of modeled Reynolds stresses largely diminishes the reliability of simulation results. In this work we use a physics-informed machine learning approach to improve the RANS modeled Reynolds stresses and propagate them to obtain the mean velocity field. Specifically, the functional forms of Reynolds stress discrepancies with respect to mean flow features are trained based on an offline database of flows with similar characteristics. The random forest model is used to predict Reynolds stress discrepancies in new flows. Then the improved Reynolds stresses are propagated to the velocity field via RANS equations. The effects of expanding the feature space through the use of a complete basis of Galilean tensor invariants are also studied. The flow in a square duct, which is challenging for standard RANS models, is investigated to demonstrate the merit of the proposed approach. The results show that both the Reynolds stresses and the propagated velocity field are improved over the baseline RANS predictions. SAND Number: SAND2016-7437 A
Regions in Energy Market Models
Short, W.
2007-02-01
This report explores the different options for spatial resolution of an energy market model--and the advantages and disadvantages of models with fine spatial resolution. It examines different options for capturing spatial variations, considers the tradeoffs between them, and presents a few examples from one particular model that has been run at different levels of spatial resolution.
Regions in Energy Market Models
None
2009-01-18
This report explores the different options for spatial resolution of an energy market model and the advantages and disadvantages of models with fine spatial resolution. It examines different options for capturing spatial variations, considers the tradeoffs between them, and presents a few examples from one particular model that has been run at different levels of spatial resolution.
Rapid Energy Modeling Workflow Demonstration
2013-10-31
sustainable building . Models produced through the REM process can be updated and accessed continually, thus allowing energy managers to continuously explore...time and cost of audits 4. Review the energy analysis findings under the High Performance and Sustainable Building Guiding Principles Compliance
A random effects epidemic-type aftershock sequence model.
Lin, Feng-Chang
2011-04-01
We consider an extension of the temporal epidemic-type aftershock sequence (ETAS) model with random effects as a special case of a well-known doubly stochastic self-exciting point process. The new model arises from a deterministic function that is randomly scaled by a nonnegative random variable, which is unobservable but assumed to follow either positive stable or one-parameter gamma distribution with unit mean. Both random effects models are of interest although the one-parameter gamma random effects model is more popular when modeling associated survival times. Our estimation is based on the maximum likelihood approach with marginalized intensity. The methods are shown to perform well in simulation experiments. When applied to an earthquake sequence on the east coast of Taiwan, the extended model with positive stable random effects provides a better model fit, compared to the original ETAS model and the extended model with one-parameter gamma random effects.
Bridges in the random-cluster model
Eren Metin Elçi
2016-02-01
Full Text Available The random-cluster model, a correlated bond percolation model, unifies a range of important models of statistical mechanics in one description, including independent bond percolation, the Potts model and uniform spanning trees. By introducing a classification of edges based on their relevance to the connectivity we study the stability of clusters in this model. We prove several exact relations for general graphs that allow us to derive unambiguously the finite-size scaling behavior of the density of bridges and non-bridges. For percolation, we are also able to characterize the point for which clusters become maximally fragile and show that it is connected to the concept of the bridge load. Combining our exact treatment with further results from conformal field theory, we uncover a surprising behavior of the (normalized variance of the number of (non-bridges, showing that it diverges in two dimensions below the value 4cos2(π/3=0.2315891⋯ of the cluster coupling q. Finally, we show that a partial or complete pruning of bridges from clusters enables estimates of the backbone fractal dimension that are much less encumbered by finite-size corrections than more conventional approaches.
None, None
2011-06-30
The Miami Science Museum energy model has been used during DD to test the building's potential for energy savings as measured by ASHRAE 90.1-2007 Appendix G. This standard compares the designed building's yearly energy cost with that of a code-compliant building. The building is currently on track show 20% or better improvement over the ASHRAE 90.1-2007 Appendix G baseline; this performance would ensure minimum compliance with both LEED 2.2 and current Florida Energy Code, which both reference a less strict version of ASHRAE 90.1. In addition to being an exercise in energy code compliance, the energy model has been used as a design tool to show the relative performance benefit of individual energy conservation measures (ECMs). These ECMs are areas where the design team has improved upon code-minimum design paths to improve the energy performance of the building. By adding ECMs one a time to a code-compliant baseline building, the current analysis identifies which ECMs are most effective in helping the building meet its energy performance goals.
Communication strategies for two models of discrete energy harvesting
Trillingsgaard, Kasper Fløe; Popovski, Petar
2014-01-01
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...... of harvesting and communication are addressed. In the first model an energy quantum can arrive, with a certain probability, in each slot. The second model is based on a frame of size F: energy arrives periodically over F slots, in batches containing a random number of energy quanta. We devise achievable...
Characteristic Polynomials of Complex Random Matrix Models
Akemann, G
2003-01-01
We calculate the expectation value of an arbitrary product of characteristic polynomials of complex random matrices and their hermitian conjugates. Using the technique of orthogonal polynomials in the complex plane our result can be written in terms of a determinant containing these polynomials and their kernel. It generalizes the known expression for hermitian matrices and it also provides a generalization of the Christoffel formula to the complex plane. The derivation we present holds for complex matrix models with a general weight function at finite-N, where N is the size of the matrix. We give some explicit examples at finite-N for specific weight functions. The characteristic polynomials in the large-N limit at weak and strong non-hermiticity follow easily and they are universal in the weak limit. We also comment on the issue of the BMN large-N limit.
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.
Holographic dark-energy models
Del Campo, Sergio; Fabris, Júlio. C.; Herrera, Ramón; Zimdahl, Winfried
2011-06-01
Different holographic dark-energy models are studied from a unifying point of view. We compare models for which the Hubble scale, the future event horizon or a quantity proportional to the Ricci scale are taken as the infrared cutoff length. We demonstrate that the mere definition of the holographic dark-energy density generally implies an interaction with the dark-matter component. We discuss the relation between the equation-of-state parameter and the energy density ratio of both components for each of the choices, as well as the possibility of noninteracting and scaling solutions. Parameter estimations for all three cutoff options are performed with the help of a Bayesian statistical analysis, using data from supernovae type Ia and the history of the Hubble parameter. The ΛCDM model is the clear winner of the analysis. According to the Bayesian information criterion (BIC), all holographic models should be considered as ruled out, since the difference ΔBIC to the corresponding ΛCDM value is >10. According to the Akaike information criterion (AIC), however, we find ΔAIC<2 for models with Hubble-scale and Ricci-scale cutoffs, indicating, that they may still be competitive. As we show for the example of the Ricci-scale case, also the use of certain priors, reducing the number of free parameters to that of the ΛCDM model, may result in a competitive holographic model.
Energy technologies and energy efficiency in economic modelling
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.......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...... development are one of the main causes for the very diverging results which have been obtained using bottom-up and top-down models for analysing the costs of greenhouse gas mitigation. One of the objectives for studies comparing model results have been to create comparable model assumptions regarding...
Self-Organized Criticality in a Random Network Model
Nirei, Makoto
1998-01-01
A new model of self-organized criticality is defined by incorporating a random network model in order to explain endogenous complex fluctuations of economic aggregates. The model can feature many globally interactive systems such as economies or societies.
Sharp critical behavior for pinning model in random correlated environment
Berger, Quentin
2011-01-01
This article investigates the effect for random pinning models of long range power-law decaying correlations in the environment. For a particular type of environment based on a renewal construction, we are able to sharply describe the phase transition from the delocalized phase to the localized one, giving the critical exponent for the (quenched) free-energy, and proving that at the critical point the trajectories are fully delocalized. These results contrast with what happens both for the pure model (i.e. without disorder) and for the widely studied case of i.i.d. disorder, where the relevance or irrelevance of disorder on the critical properties is decided via the so-called Harris Criterion.
Competitive growth model involving random deposition and random deposition with surface relaxation
Horowitz, Claudio M.; Monetti, Roberto A.; Albano, Ezequiel V.
2001-06-01
A deposition model that considers a mixture of random deposition with surface relaxation and a pure random deposition is proposed and studied. As the system evolves, random deposition with surface relaxation (pure random deposition) take place with probability p and (1{minus}p), respectively. The discrete (microscopic) approach to the model is studied by means of extensive numerical simulations, while continuous equations are used in order to investigate the mesoscopic properties of the model. A dynamic scaling ansatz for the interface width W(L,t,p) as a function of the lattice side L, the time t and p is formulated and tested. Three exponents, which can be linked to the standard growth exponent of random deposition with surface relaxation by means of a scaling relation, are identified. In the continuous limit, the model can be well described by means of a phenomenological stochastic growth equation with a p-dependent effective surface tension.
Modeling of Random Delays in Networked Control Systems
Yuan Ge
2013-01-01
Full Text Available In networked control systems (NCSs, the presence of communication networks in control loops causes many imperfections such as random delays, packet losses, multipacket transmission, and packet disordering. In fact, random delays are usually the most important problems and challenges in NCSs because, to some extent, other problems are often caused by random delays. In order to compensate for random delays which may lead to performance degradation and instability of NCSs, it is necessary to establish the mathematical model of random delays before compensation. In this paper, four major delay models are surveyed including constant delay model, mutually independent stochastic delay model, Markov chain model, and hidden Markov model. In each delay model, some promising compensation methods of delays are also addressed.
Estimation of the Nonlinear Random Coefficient Model when Some Random Effects Are Separable
du Toit, Stephen H. C.; Cudeck, Robert
2009-01-01
A method is presented for marginal maximum likelihood estimation of the nonlinear random coefficient model when the response function has some linear parameters. This is done by writing the marginal distribution of the repeated measures as a conditional distribution of the response given the nonlinear random effects. The resulting distribution…
A Note on the Correlated Random Coefficient Model
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...
Compact Sets without Converging Sequences in the Random Real Model
D. Fremlin
2007-10-01
Full Text Available It is shown that in the model obtained by adding any number of random reals to a model of CH, there is a compact Hausdorff space of weight w1 which contains no non-trivial converging sequences. It is shown that for certain spaces with noconverging sequences, the addition of random reals will not add any converging sequences.
Random non-Hermitian tight-binding models
Marinello, G.; Pato, M. P.
2016-08-01
For a one dimensional system tight binding models are described by sparse tridiagonal matrices which describe interactions between nearest neighbors. In this report, we construct open and closed random tight-binding models based in the tridiagonal matrices of the so-called,β-ensembles of random matrix theory.
Trapping in the random conductance model
Biskup, M; Rozinov, A; Vandenberg-Rodes, A
2012-01-01
We consider random walks on $\\Z^d$ among nearest-neighbor random conductances which are i.i.d., positive, bounded uniformly from above but whose support extends all the way to zero. Our focus is on the detailed properties of the paths of the random walk conditioned to return back to the starting point at time $2n$. We show that in the situations when the heat kernel exhibits subdiffusive decay --- which is known to occur in dimensions $d\\ge4$ --- the walk gets trapped for a time of order $n$ in a small spatial region. This shows that the strategy used earlier to infer subdiffusive lower bounds on the heat kernel in specific examples is in fact dominant. In addition, we settle a conjecture concerning the worst possible subdiffusive decay in four dimensions.
Trapping in the Random Conductance Model
Biskup, M.; Louidor, O.; Rozinov, A.; Vandenberg-Rodes, A.
2013-01-01
We consider random walks on ℤ d among nearest-neighbor random conductances which are i.i.d., positive, bounded uniformly from above but whose support extends all the way to zero. Our focus is on the detailed properties of the paths of the random walk conditioned to return back to the starting point at time 2 n. We show that in the situations when the heat kernel exhibits subdiffusive decay—which is known to occur in dimensions d≥4—the walk gets trapped for a time of order n in a small spatial region. This shows that the strategy used earlier to infer subdiffusive lower bounds on the heat kernel in specific examples is in fact dominant. In addition, we settle a conjecture concerning the worst possible subdiffusive decay in four dimensions.
Evaluating energy efficiency policies with energy-economy models
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 analyz
On competitive Lotka–Volterra model in random environments
Zhu, C; Yin, G
2009-01-01
Focusing on competitive Lotka-Volterra model in random environments, this paper uses regime-switching diffusions to model the dynamics of the population sizes of n different species in an ecosystem...
Modeling Malaysia's Energy System: Some Preliminary Results
Ahmad M. Yusof
2011-01-01
Problem statement: The current dynamic and fragile world energy environment necessitates the development of new energy model that solely caters to analyze Malaysias energy scenarios. Approach: The model is a network flow model that traces the flow of energy carriers from its sources (import and mining) through some conversion and transformation processes for the production of energy products to final destinations (energy demand sectors). The integration to the economic sectors is done exogene...
Evaluating Energy Efficiency Policies with Energy-Economy Models
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.
A simplified analytical random walk model for proton dose calculation
Yao, Weiguang; Merchant, Thomas E.; Farr, Jonathan B.
2016-10-01
We propose an analytical random walk model for proton dose calculation in a laterally homogeneous medium. A formula for the spatial fluence distribution of primary protons is derived. The variance of the spatial distribution is in the form of a distance-squared law of the angular distribution. To improve the accuracy of dose calculation in the Bragg peak region, the energy spectrum of the protons is used. The accuracy is validated against Monte Carlo simulation in water phantoms with either air gaps or a slab of bone inserted. The algorithm accurately reflects the dose dependence on the depth of the bone and can deal with small-field dosimetry. We further applied the algorithm to patients’ cases in the highly heterogeneous head and pelvis sites and used a gamma test to show the reasonable accuracy of the algorithm in these sites. Our algorithm is fast for clinical use.
Aslam, Muhammad Zaheer
2011-01-01
Mobile Adhoc Network is a kind of wireless ad hoc network where nodes are connected wirelessly and the network is self configuring. MANET may work in a standalone manner or may be a part of another network. In this paper we have compared Random Walk Mobility Model and Random Waypoint Mobility Model over two reactive routing protocols Dynamic Source Routing (DSR) and Adhoc On-Demand Distance Vector Routing (AODV) protocol and one Proactive routing protocol Distance Sequenced Distance Vector Routing (DSDV) Our analysis showed that DSR, AODV & DSDV under Random Walk and Random Way Point Mobility models have similar results for similar inputs however as the pause time increases so does the difference in performance rises. They show that their motion, direction, angle of direction, speed is same under both mobility models. We have made their analysis on packet delivery ratio, throughput and routing overhead. We have tested them with different criteria like different number of nodes, speed and different maximum...
Some random models in traffic science
Hjorth, U.
1996-06-01
We give an overview of stochastic models for the following traffic phenomena. Models for traffic flow including gaps and capacities for lanes, crossings and roundabouts. Models for wanted and achieved speed distributions. Mode selection models including dispersed equilibrium models and traffic accident models. Also some statistical questions are discussed. 60 refs, 1 tab
A Model for Random Student Drug Testing
Nelson, Judith A.; Rose, Nancy L.; Lutz, Danielle
2011-01-01
The purpose of this case study was to examine random student drug testing in one school district relevant to: (a) the perceptions of students participating in competitive extracurricular activities regarding drug use and abuse; (b) the attitudes and perceptions of parents, school staff, and community members regarding student drug involvement; (c)…
Consistent estimators in random censorship semiparametric models
王启华
1996-01-01
For the fixed design regression modelwhen Y, are randomly censored on the right, the estimators of unknown parameter and regression function g from censored observations are defined in the two cases .where the censored distribution is known and unknown, respectively. Moreover, the sufficient conditions under which these estimators are strongly consistent and pth (p>2) mean consistent are also established.
Versatility and robustness of Gaussian random fields for modelling random media
Quintanilla, John A.; Chen, Jordan T.; Reidy, Richard F.; Allen, Andrew J.
2007-06-01
One of the authors (JAQ) has recently introduced a method of modelling random materials using excursion sets of Gaussian random fields. This method uses convex quadratic programming to find the optimal admissible field autocorrelation function, providing both theoretical and computational advantages over other techniques such as simulated annealing. In this paper, we discuss the application of this algorithm to model various aerogel systems given small-angle neutron scattering data. We also present new results concerning the robustness of this method.
Modelling distributed energy resources in energy service networks
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
The Variance of Energy Estimates for the Product Model
David Smallwood
2003-01-01
, is the product of a slowly varying random window, {w(t}, and a stationary random process, {g(t}, is defined. A single realization of the process will be defined as x(t. This is slightly different from the usual definition of the product model where the window is typically defined as deterministic. An estimate of the energy (the zero order temporal moment, only in special cases is this physical energy of the random process, {x(t}, is defined as m0=∫∞∞|x(t|2dt=∫−∞∞|w(tg(t|2dt Relationships for the mean and variance of the energy estimates, m0, are then developed. It is shown that for many cases the uncertainty (4π times the product of rms duration, Dt, and rms bandwidth, Df is approximately the inverse of the normalized variance of the energy. The uncertainty is a quantitative measure of the expected error in the energy estimate. If a transient has a significant random component, a small uncertainty parameter implies large error in the energy estimate. Attempts to resolve a time/frequency spectrum near the uncertainty limits of a transient with a significant random component will result in large errors in the spectral estimates.
Modeling energy transport in nanostructures
Pattamatta, Arvind
Heat transfer in nanostructures differ significantly from that in the bulk materials since the characteristic length scales associated with heat carriers, i.e., the mean free path and the wavelength, are comparable to the characteristic length of the nanostructures. Nanostructure materials hold the promise of novel phenomena, properties, and functions in the areas of thermal management and energy conversion. Example of thermal management in micro/nano electronic devices is the use of efficient nanostructured materials to alleviate 'hot spots' in integrated circuits. Examples in the manipulation of heat flow and energy conversion include nanostructures for thermoelectric energy conversion, thermophotovoltaic power generation, and data storage. One of the major challenges in Metal-Oxide Field Effect Transistor (MOSFET) devices is to study the 'hot spot' generation by accurately modeling the carrier-optical phonon-acoustic phonon interactions. Prediction of hotspot temperature and position in MOSFET devices is necessary for improving thermal design and reliability of micro/nano electronic devices. Thermoelectric properties are among the properties that may drastically change at nanoscale. The efficiency of thermoelectric energy conversion in a material is measured by a non-dimensional figure of merit (ZT) defined as, ZT = sigmaS2T/k where sigma is the electrical conductivity, S is the Seebeck coefficient, T is the temperature, and k is the thermal conductivity. During the last decade, advances have been made in increasing ZT using nanostructures. Three important topics are studied with respect to energy transport in nanostructure materials for micro/nano electronic and thermoelectric applications; (1) the role of nanocomposites in improving the thermal efficiency of thermoelectric devices, (2) the interfacial thermal resistance for the semiconductor/metal contacts in thermoelectric devices and for metallic interconnects in micro/nano electronic devices, (3) the
Random Matrix Theory Approach to Indonesia Energy Portfolio Analysis
Mahardhika, Alifian; Purqon, Acep
2017-07-01
In a few years, Indonesia experienced difficulties in maintaining energy security, the problem is the decline in oil production from 1.6 million barrels per day to 861 thousand barrels per day in 2012. However, there is a difference condition in 2015 until the third week in 2016, world oil prices actually fell at the lowest price level since last 12 years. The decline in oil prices due to oversupply of oil by oil-producing countries of the world due to the instability of the world economy. Wave of layoffs in Indonesia is a response to the decline in oil prices, this led to the energy and mines portfolios Indonesia feared would not be more advantageous than the portfolio in other countries. In this research, portfolio analysis will be done on energy and mining in Indonesia by using stock price data of energy and mines in the period 26 November 2010 until April 1, 2016. It was found that the results have a wide effect of the market potential is high in the determination of the return on the portfolio energy and mines. Later, it was found that there are eight of the thirty stocks in the energy and mining portfolio of Indonesia which have a high probability of return relative to the average return of stocks in a portfolio of energy and mines.
Energy Blocks — A Physical Model for Teaching Energy Concepts
Hertting, Scott
2016-01-01
Most physics educators would agree that energy is a very useful, albeit abstract topic. It is therefore important to use various methods to help the student internalize the concept of energy itself and its related ideas. These methods include using representations such as energy bar graphs, energy pie charts, or energy tracking diagrams. Activities and analogies like Energy Theater and Richard Feynman's blocks, as well as the popular money (or wealth) analogy, can also be very effective. The goal of this paper is to describe a physical model of Feynman's blocks that can be employed by instructors to help students learn the following energy-related concepts: 1. The factors affecting each individual mechanical energy storage mode (this refers to what has been traditionally called a form of energy, and while the Modeling Method of instruction is not the focus of this paper, much of the energy related language used is specific to the Modeling Method). For example, how mass or height affects gravitational energy; 2. Energy conservation; and 3. The graphical relationships between the energy storage mode and a factor affecting it. For example, the graphical relationship between elastic energy and the change in length of a spring.
Self-organized Criticality in an Earthquake Model on Random Network
无
2006-01-01
A simplified Olami-Feder-Christensen model on a random network has been studied. We propose a new toppling rule - when there is an unstable site toppling, the energy of the site is redistributed to its nearest neighbors randomly not averagely. The simulation results indicate that the model displays self-organized criticality when the system is conservative, and the avalanche size probability distribution of the system obeys finite size scaling. When the system is nonconservative, the model does not display scaling behavior. Simulation results of our model with different nearest neighbors q is also compared, which indicates that the spatialtopology does not alter the critical behavior of the system.
Two sustainable energy system analysis models
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.......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....
Complex Evaluation Model of Corporate Energy Management
Ágnes Kádár Horváth
2014-01-01
With the ever increasing energy problems at the doorstep alongside with political, economic, social and environmental challenges, conscious energy management has become of increasing importance in corporate resource management. Rising energy costs, stricter environmental and climate regulations as well as considerable changes in the energy market require companies to rationalise their energy consumption and cut energy costs. This study presents a complex evaluation model of corporate energy m...
Energy: modelization and econometrics. Proceedings of colloquium
Fericelli, J.; Lesourd, J.B.
1985-01-01
The document presents the communications of the ''applied econometric association'' symposium and introduces the description of various French and foreigner models: analysis of the energy demand and production functions with energy input. A detailed evaluation of the Translog function applied to energy is described. Other energy economic aspects are approched: energy prices and costs, energetic balances, energy management in enterprises, impact evaluation of alternative energy policies.
Bi-Spectrum Scattering Model for Conducting Randomly Rough Surface
刘宁; 李宗谦
2002-01-01
A scattering model is developed to predict the scattering coefficient of a conducting randomly rough surface by analyzing the randomly rough surface in the spectral domain using the bi-spectrum method. For common randomly rough surfaces without obvious two-scale characteristics, a scale-compression filter can divide the auto-correlation spectrum into two parts with different correlation lengths. The Kirchhoff approximation and the small perturbation method are used to obtain the surface field, then a bistatic scattering model, the bi-spectrum model (BSM), is used to derive an explicit expression from the surface field. Examples using the integral equation model (IEM), finite difference of the time domain (FDTD) method, and BSM show that the BSM accuracy is acceptable and its range of validity is similar to IEM. BSM can also be extended to a scattering model for dielectric randomly rough surfaces.
Parameter estimation of hidden periodic model in random fields
何书元
1999-01-01
Two-dimensional hidden periodic model is an important model in random fields. The model is used in the field of two-dimensional signal processing, prediction and spectral analysis. A method of estimating the parameters for the model is designed. The strong consistency of the estimators is proved.
A note on moving average models for Gaussian random fields
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...
Sums of random matrices and the Potts model on random planar maps
Atkin, Max R.; Niedner, Benjamin; Wheater, John F.
2016-05-01
We compute the partition function of the q-states Potts model on a random planar lattice with p≤slant q allowed, equally weighted colours on a connected boundary. To this end, we employ its matrix model representation in the planar limit, generalising a result by Voiculescu for the addition of random matrices to a situation beyond free probability theory. We show that the partition functions with p and q - p colours on the boundary are related algebraically. Finally, we investigate the phase diagram of the model when 0≤slant q≤slant 4 and comment on the conformal field theory description of the critical points.
Random walk models for top-N recommendation task
Yin ZHANG; Jiang-qin WU; Yue-ting ZHUANG
2009-01-01
Recently there has been an increasing interest in applying random walk based methods to recommender systems.We employ a Gaussian random field to model the top-N recommendation task as a semi-supervised learning problem.taking into account the degree of each node on the user-item bipartite graph,and induce an effective absorbing random walk (ARW) algorithm for the top-N recommendation task.Our random walk approach directly generates the top-N recommendations for individuals,rather than predicting the ratings of the recommendations.Experimental results on the two real data sets show that our random walk algorithm significantly outperforms the state-of-the-art random walk based personalized ranking algorithm as well as the popular item-based collaborative filtering method.
Global energy modeling - A biophysical approach
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.
Weighted Hybrid Decision Tree Model for Random Forest Classifier
Kulkarni, Vrushali Y.; Sinha, Pradeep K.; Petare, Manisha C.
2016-06-01
Random Forest is an ensemble, supervised machine learning algorithm. An ensemble generates many classifiers and combines their results by majority voting. Random forest uses decision tree as base classifier. In decision tree induction, an attribute split/evaluation measure is used to decide the best split at each node of the decision tree. The generalization error of a forest of tree classifiers depends on the strength of the individual trees in the forest and the correlation among them. The work presented in this paper is related to attribute split measures and is a two step process: first theoretical study of the five selected split measures is done and a comparison matrix is generated to understand pros and cons of each measure. These theoretical results are verified by performing empirical analysis. For empirical analysis, random forest is generated using each of the five selected split measures, chosen one at a time. i.e. random forest using information gain, random forest using gain ratio, etc. The next step is, based on this theoretical and empirical analysis, a new approach of hybrid decision tree model for random forest classifier is proposed. In this model, individual decision tree in Random Forest is generated using different split measures. This model is augmented by weighted voting based on the strength of individual tree. The new approach has shown notable increase in the accuracy of random forest.
Carrozza, Sylvain
2015-01-01
We define in this paper a class of three indices tensor models, endowed with $O(N)^{\\otimes 3}$ invariance ($N$ being the size of the tensor). This allows to generate, via the usual QFT perturbative expansion, a class of Feynman tensor graphs which is strictly larger than the class of Feynman graphs of both the multi-orientable model (and hence of the colored model) and the $U(N)$ invariant models. We first exhibit the existence of a large $N$ expansion for such a model with general interactions. We then focus on the quartic model and we identify the leading and next-to-leading order (NLO) graphs of the large $N$ expansion. Finally, we prove the existence of a critical regime and we compute the critical exponents, both at leading order and at NLO. This is achieved through the use of various analytic combinatorics techniques.
Carrozza, Sylvain; Tanasa, Adrian
2016-08-01
We define in this paper a class of three-index tensor models, endowed with {O(N)^{⊗ 3}} invariance (N being the size of the tensor). This allows to generate, via the usual QFT perturbative expansion, a class of Feynman tensor graphs which is strictly larger than the class of Feynman graphs of both the multi-orientable model (and hence of the colored model) and the U(N) invariant models. We first exhibit the existence of a large N expansion for such a model with general interactions. We then focus on the quartic model and we identify the leading and next-to-leading order (NLO) graphs of the large N expansion. Finally, we prove the existence of a critical regime and we compute the critical exponents, both at leading order and at NLO. This is achieved through the use of various analytic combinatorics techniques.
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…
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…
Multilevel random effect and marginal models for longitudinal data ...
Multilevel random effect and marginal models for longitudinal data. ... Ethiopian Journal of Science and Technology ... the occurrence of specific adverse events than children injected with licensed vaccine, and if so, to quantify the difference.
A Gompertzian model with random effects to cervical cancer growth
Mazlan, Mazma Syahidatul Ayuni; Rosli, Norhayati [Faculty of Industrial Sciences and Technology, Universiti Malaysia Pahang, Lebuhraya Tun Razak, 26300 Gambang, Pahang (Malaysia)
2015-05-15
In this paper, a Gompertzian model with random effects is introduced to describe the cervical cancer growth. The parameters values of the mathematical model are estimated via maximum likehood estimation. We apply 4-stage Runge-Kutta (SRK4) for solving the stochastic model numerically. The efficiency of mathematical model is measured by comparing the simulated result and the clinical data of the cervical cancer growth. Low values of root mean-square error (RMSE) of Gompertzian model with random effect indicate good fits.
Multicritical tensor models and hard dimers on spherical random lattices
Bonzom, Valentin
2012-01-01
Random tensor models which display multicritical behaviors in a remarkably simple fashion are presented. They come with entropy exponents \\gamma = (m-1)/m, similarly to multicritical random branched polymers. Moreover, they are interpreted as models of hard dimers on a set of random lattices for the sphere in dimension three and higher. Dimers with their exclusion rules are generated by the different interactions between tensors, whose coupling constants are dimer activities. As an illustration, we describe one multicritical point, which is interpreted as a transition between the dilute phase and a crystallized phase, though with negative activities.
Bayesian nonparametric centered random effects models with variable selection.
Yang, Mingan
2013-03-01
In a linear mixed effects model, it is common practice to assume that the random effects follow a parametric distribution such as a normal distribution with mean zero. However, in the case of variable selection, substantial violation of the normality assumption can potentially impact the subset selection and result in poor interpretation and even incorrect results. In nonparametric random effects models, the random effects generally have a nonzero mean, which causes an identifiability problem for the fixed effects that are paired with the random effects. In this article, we focus on a Bayesian method for variable selection. We characterize the subject-specific random effects nonparametrically with a Dirichlet process and resolve the bias simultaneously. In particular, we propose flexible modeling of the conditional distribution of the random effects with changes across the predictor space. The approach is implemented using a stochastic search Gibbs sampler to identify subsets of fixed effects and random effects to be included in the model. Simulations are provided to evaluate and compare the performance of our approach to the existing ones. We then apply the new approach to a real data example, cross-country and interlaboratory rodent uterotrophic bioassay.
Models of Energy Saving Systems
Nørgård, Jørgen Stig
1999-01-01
The paper first describes the concepts and methods around energy saving, such as energy chain, energy services, end-use technologies, secondary energy, etc. Next are discussed the problems of defining and adding energy services and hence end-use energy efficiency or intensity. A section is devote...... service level and technology are demonstrated as the main determinants of future energy consumption. In the concluding remarks, the main flaws of present energy policy and some visions of the future are discussed.......The paper first describes the concepts and methods around energy saving, such as energy chain, energy services, end-use technologies, secondary energy, etc. Next are discussed the problems of defining and adding energy services and hence end-use energy efficiency or intensity. A section is devoted...... to what is termed lifestyle efficiency, including the cultural values and the ability of the economy to provide the services wanted. As explained, integrated resource planning with its optimizing the whole energy chain cannot be combined with sub-optimizing part of it, for instance the supply technology...
Models of Energy Saving Systems
Nørgård, Jørgen Stig
1999-01-01
The paper first describes the concepts and methods around energy saving, such as energy chain, energy services, end-use technologies, secondary energy, etc. Next are discussed the problems of defining and adding energy services and hence end-use energy efficiency or intensity. A section is devote...... service level and technology are demonstrated as the main determinants of future energy consumption. In the concluding remarks, the main flaws of present energy policy and some visions of the future are discussed.......The paper first describes the concepts and methods around energy saving, such as energy chain, energy services, end-use technologies, secondary energy, etc. Next are discussed the problems of defining and adding energy services and hence end-use energy efficiency or intensity. A section is devoted...... to what is termed lifestyle efficiency, including the cultural values and the ability of the economy to provide the services wanted. As explained, integrated resource planning with its optimizing the whole energy chain cannot be combined with sub-optimizing part of it, for instance the supply technology...
Rumor spreading models with random denials
Giorno, Virginia; Spina, Serena
2016-11-01
The concept of denial is introduced on rumor spreading processes. The denials occur with a certain rate and they reset to start the initial situation. A population of N individuals is subdivided into ignorants, spreaders and stiflers; at the initial time there is only one spreader and the rest of the population is ignorant. The denials are introduced in the classic DK model and in its generalization, in which a spreader can transmit the rumor at most to k ignorants. The steady state densities are analyzed for these models. Finally, a numerical analysis is performed to study the rule of the involved parameters and to compare the proposed models.
Configuring Random Graph Models with Fixed Degree Sequences
Fosdick, Bailey K; Nishimura, Joel; Ugander, Johan
2016-01-01
Random graph null models have found widespread application in diverse research communities analyzing network datasets. The most popular family of random graph null models, called configuration models, are defined as uniform distributions over a space of graphs with a fixed degree sequence. Commonly, properties of an empirical network are compared to properties of an ensemble of graphs from a configuration model in order to quantify whether empirical network properties are meaningful or whether they are instead a common consequence of the particular degree sequence. In this work we study the subtle but important decisions underlying the specification of a configuration model, and investigate the role these choices play in graph sampling procedures and a suite of applications. We place particular emphasis on the importance of specifying the appropriate graph labeling---stub-labeled or vertex-labeled---under which to consider a null model, a choice that closely connects the study of random graphs to the study of...
Modelling Of Random Vertical Irregularities Of Railway Tracks
Podwórna M.
2015-08-01
Full Text Available The study presents state-of-the-art in analytical and numerical modelling of random vertical irregularities of continuously welded ballasted railway tracks. The common model of railway track irregularity vertical profiles is applied, in the form of a stationary and ergodic Gaussian process in space. Random samples of track irregularity vertical profiles are generated with the Monte-Carlo method. Based on the numerical method developed in the study, the minimum and recommended sampling number required in the random analysis of railway bridges and number of frequency increments (harmonic components in track irregularity vertical profiles simulation are determined. The lower and upper limits of wavelengths are determined based on the literature studies. The approach yields track irregularity random samples close to reality. The track irregularity model developed in the study can be used in the dynamic analysis of railway bridge / track structure / highspeed train systems.
Neuhauser, Daniel; Rabani, Eran; Baer, Roi
2013-04-04
A fast method is developed for calculating the random phase approximation (RPA) correlation energy for density functional theory. The correlation energy is given by a trace over a projected RPA response matrix, and the trace is taken by a stochastic approach using random perturbation vectors. For a fixed statistical error in the total energy per electron, the method scales, at most, quadratically with the system size; however, in practice, due to self-averaging, it requires less statistical sampling as the system grows, and the performance is close to linear scaling. We demonstrate the method by calculating the RPA correlation energy for cadmium selenide and silicon nanocrystals with over 1500 electrons. We find that the RPA correlation energies per electron are largely independent of the nanocrystal size. In addition, we show that a correlated sampling technique enables calculation of the energy difference between two slightly distorted configurations with scaling and a statistical error similar to that of the total energy per electron.
Money creation in a random matching model
Alexei Deviatov
2004-01-01
I study money creation in versions of the Trejos-Wright (1995) and Shi (1995) models with indivisible money and individual holdings bounded at two units. I work with the same class of policies as in Deviatov and Wallace (2001), who study money creation in that model. However, I consider an alternative notion of implementability–the ex ante pairwise core. I compute a set of numerical examples to determine whether money creation is beneficial. I find beneficial e?ects of money creation if indiv...
伍细如
2015-01-01
proton emits energy wave, electron could sits any position away from nucleus, but be the most stable just when it sits at the trough of energy wave, and this position accords with Bohr radius and Schr?dinger equation.
Modelling energy systems for developing countries
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 ind
ENOR - An Energy-Model for Norway
A. Ek
1981-01-01
Full Text Available The Energy model for Norway, ENOR, is a dynamic, multisectoral economic stimulation model to be used for long term energy analyses. Energy sectors and energy carriers are in principle treated in the same way as other sectors and economic commodities and integrated in the same general framework. The model has a two-level structure - a central coordination module ensures economic consistency, while the behaviour of each production and consumption sector is modelled in separate sector models. The model framework is thus capable of handling both engineering and economic knowledge.
A generalized model via random walks for information filtering
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.
Energy modeling. Volume 2: Inventory and details of state energy models
Melcher, A. G.; Underwood, R. G.; Weber, J. C.; Gist, R. L.; Holman, R. P.; Donald, D. W.
1981-05-01
An inventory of energy models developed by or for state governments is presented, and certain models are discussed in depth. These models address a variety of purposes such as: supply or demand of energy or of certain types of energy; emergency management of energy; and energy economics. Ten models are described. The purpose, use, and history of the model is discussed, and information is given on the outputs, inputs, and mathematical structure of the model. The models include five models dealing with energy demand, one of which is econometric and four of which are econometric-engineering end-use models.
Capabilities and accuracy of energy modelling software
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...
Tseng, Yuan Heng; Shen, Wen Chao; Lin, Chrong Jung
2012-04-01
The intense development and study of resistive random access memory (RRAM) devices has opened a new era in semiconductor memory manufacturing. Resistive switching and carrier conduction inside RRAM films have become critical issues in recent years. Electron trapping/detrapping behavior is observed and investigated in the proposed contact resistive random access memory (CR-RAM) cell. Through the fitting of the space charge limiting current (SCLC) model, and analysis in terms of the random telegraph noise (RTN) model, the temperature-dependence of resistance levels and the high-temperature data retention behavior of the contact RRAM film are successfully and completely explained. Detail analyses of the electron capture and emission from the traps by forward and reverse read measurements provide further verifications for hopping conduction mechanism and current fluctuation discrepancies.
A hybrid random field model for scalable statistical learning.
Freno, A; Trentin, E; Gori, M
2009-01-01
This paper introduces hybrid random fields, which are a class of probabilistic graphical models aimed at allowing for efficient structure learning in high-dimensional domains. Hybrid random fields, along with the learning algorithm we develop for them, are especially useful as a pseudo-likelihood estimation technique (rather than a technique for estimating strict joint probability distributions). In order to assess the generality of the proposed model, we prove that the class of pseudo-likelihood distributions representable by hybrid random fields strictly includes the class of joint probability distributions representable by Bayesian networks. Once we establish this result, we develop a scalable algorithm for learning the structure of hybrid random fields, which we call 'Markov Blanket Merging'. On the one hand, we characterize some complexity properties of Markov Blanket Merging both from a theoretical and from the experimental point of view, using a series of synthetic benchmarks. On the other hand, we evaluate the accuracy of hybrid random fields (as learned via Markov Blanket Merging) by comparing them to various alternative statistical models in a number of pattern classification and link-prediction applications. As the results show, learning hybrid random fields by the Markov Blanket Merging algorithm not only reduces significantly the computational cost of structure learning with respect to several considered alternatives, but it also leads to models that are highly accurate as compared to the alternative ones.
Hybrid Energy System Modeling in Modelica
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.
Positive random fields for modeling material stiffness and compliance
Hasofer, Abraham Michael; Ditlevsen, Ove Dalager; Tarp-Johansen, Niels Jacob
1998-01-01
with material properties modeled in terms of the considered random fields.The paper addsthe gamma field, the Fisher field, the beta field, and their reciprocal fields to the catalogue. These fields are all defined on the basis of sums of squares of independent standard Gaussian random variables.All the existing...... marginal moments and the correlation functions are obtained explicitly. Also an inverse Gaussian fieldis added to the catalogue. It is defined in terms of first passage times in correlated joint Brownian motions. Finally an n-dimensional random vector of positive components is defined such that it can...
Effects of introducing nonlinear components for a random excited hybrid energy harvester
Zhou, Xiaoya; Gao, Shiqiao; Liu, Haipeng; Guan, Yanwei
2017-01-01
This work is mainly devoted to discussing the effects of introducing nonlinear components for a hybrid energy harvester under random excitation. For two different types of nonlinear hybrid energy harvesters subjected to random excitation, the analytical solutions of the mean output power, voltage and current are derived from Fokker-Planck (FP) equations. Monte Carlo simulation exhibits qualitative agreement with FP theory, showing that load values and excitation’s spectral density have an effect on the total mean output power, piezoelectric (PE) power and electromagnetic power. Nonlinear components affect output characteristics only when the PE capacitance of the hybrid energy harvester is non-negligible. Besides, it is also demonstrated that for this type of nonlinear hybrid energy harvesters under random excitation, introducing nonlinear components can improve output performances effectively.
Using convex quadratic programming to model random media with Gaussian random fields
Quintanilla, John A.; Jones, W. Max
2007-04-01
Excursion sets of Gaussian random fields (GRFs) have been frequently used in the literature to model two-phase random media with measurable phase autocorrelation functions. The goal of successful modeling is finding the optimal field autocorrelation function that best approximates the prescribed phase autocorrelation function. In this paper, we present a technique which uses convex quadratic programming to find the best admissible field autocorrelation function under a prescribed discretization. Unlike previous methods, this technique efficiently optimizes over all admissible field autocorrelation functions, instead of optimizing only over a predetermined parametrized family. The results from using this technique indicate that the GRF model is significantly more versatile than observed in previous studies. An application to modeling a base-catalyzed tetraethoxysilane aerogel system given small-angle neutron scattering data is also presented
Money creation process in a random redistribution model
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.
Energy Systems Modelling Research and Analysis
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...... 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....
A random effects generalized linear model for reliability compositive evaluation
无
2009-01-01
This paper first proposes a random effects generalized linear model to evaluate the storage life of one kind of high reliable and small sample-sized products by combining multi-sources information of products coming from the same population but stored at different environments. The relevant algorithms are also provided. Simulation results manifest the soundness and effectiveness of the proposed model.
Single-cluster dynamics for the random-cluster model
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
Shape Modelling Using Markov Random Field Restoration of Point Correspondences
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...
Least squares estimation in a simple random coefficient autoregressive model
Johansen, Søren; Lange, Theis
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=P(...
Least squares estimation in a simple random coefficient autoregressive model
Johansen, Søren; Lange, Theis
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=P(...
Simulating intrafraction prostate motion with a random walk model
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.
Single-cluster dynamics for the random-cluster model
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 random effects generalized linear model for reliability compositive evaluation
ZHAO Hui; YU Dan
2009-01-01
This paper first proposes a random effects generalized linear model to evaluate the storage life of one kind of high reliable and small sample-sized products by combining multi-sources information of products coming from the same population but stored at different environments.The relevant algorithms are also provided.Simulation results manifest the soundness and effectiveness of the proposed model.
Zhe-Qi Lin; Hae Chang Gea; Shu-Tian Liu
2011-01-01
Converting ambient vibration energy into electrical energy by using piezoelectric energy harvester has attracted a lot of interest in the past few years.In this paper,a topology optimization based method is applied to simultaneously determine the optimal layout of the piezoelectric energy harvesting devices and the optimal position of the mass loading.The objective function is to maximize the energy harvesting performance over a range of vibration frequencies.Pseudo excitation method (PEM) is adopted to analyze structural stationary random responses,and sensitivity analysis is then performed by using the adjoint method.Numerical examples are presented to demonstrate the validity of the proposed approach.
Munira, Kamaram; Visscher, P. B.
2015-05-01
To make a useful spin-transfer torque magnetoresistive random-access memory (STT-MRAM) device, it is necessary to be able to calculate switching rates, which determine the error rates of the device. In a single-macrospin model, one can use a Fokker-Planck equation to obtain a low-current thermally activated rate ∝exp(-Ee f f/kBT ) . Here, the effective energy barrier Eeff scales with the single-macrospin energy barrier KV, where K is the effective anisotropy energy density and V the volume. A long-standing paradox in this field is that the actual energy barrier appears to be much smaller than this. It has been suggested that incoherent motions may lower the barrier, but this has proved difficult to quantify. In the present paper, we show that the coherent precession has a magnetostatic instability, which allows quantitative estimation of the energy barrier and may resolve the paradox.
Energy based prediction models for building acoustics
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...
Fujino, J.; Yamaji, K. [The University of Tokyo, Tokyo (Japan); Yamamoto, H. [Central Research Institute of Electric Power Industry, Tokyo (Japan)
1997-01-30
Bio-energy potential is evaluated using world energy models. The world energy model is a dynamic model by which the total cost of energy systems between 1995 and 2055 can be minimized on the basis of the optimization type world energy demand and supply model. For the given utilization costs of transportation, recovery and planting, the utilization of bio-energy is promoted even under the cost minimization condition. However, the utilization amount varies in a wide range by changing the utilization costs. Among conversion technologies of bio-energy, it is biomass liquefaction that provides the largest utilization amount. Thermal demand, direct combustion for power generation, and biomass gasification follow to the above. Biomass-integrated gasifier/gas turbine (BIG/GT) is to be used up to 2020. It is not to be used after 2030, due to the complete shift to the biomass liquefaction. For a model including the utilization of fast breeder after 2030, the utilization amount of bio-energy is not to change. Competition with food and land utilization is to be investigated. 11 refs., 19 figs., 4 tabs.
Fujino, J.; Yamaji, K. [The University of Tokyo, Tokyo (Japan); Yamamoto, H. [Central Research Institute of Electric Power Industry, Tokyo (Japan)
1997-01-30
Bio-energy potential is evaluated using world energy models. The world energy model is a dynamic model by which the total cost of energy systems between 1995 and 2055 can be minimized on the basis of the optimization type world energy demand and supply model. For the given utilization costs of transportation, recovery and planting, the utilization of bio-energy is promoted even under the cost minimization condition. However, the utilization amount varies in a wide range by changing the utilization costs. Among conversion technologies of bio-energy, it is biomass liquefaction that provides the largest utilization amount. Thermal demand, direct combustion for power generation, and biomass gasification follow to the above. Biomass-integrated gasifier/gas turbine (BIG/GT) is to be used up to 2020. It is not to be used after 2030, due to the complete shift to the biomass liquefaction. For a model including the utilization of fast breeder after 2030, the utilization amount of bio-energy is not to change. Competition with food and land utilization is to be investigated. 11 refs., 19 figs., 4 tabs.
Eigenvalue Separation in Some Random Matrix Models
Bassler, Kevin E; Frankel, Norman E
2008-01-01
The eigenvalue density for members of the Gaussian orthogonal and unitary ensembles follows the Wigner semi-circle law. If the Gaussian entries are all shifted by a constant amount c/Sqrt(2N), where N is the size of the matrix, in the large N limit a single eigenvalue will separate from the support of the Wigner semi-circle provided c > 1. In this study, using an asymptotic analysis of the secular equation for the eigenvalue condition, we compare this effect to analogous effects occurring in general variance Wishart matrices and matrices from the shifted mean chiral ensemble. We undertake an analogous comparative study of eigenvalue separation properties when the size of the matrices are fixed and c goes to infinity, and higher rank analogues of this setting. This is done using exact expressions for eigenvalue probability densities in terms of generalized hypergeometric functions, and using the interpretation of the latter as a Green function in the Dyson Brownian motion model. For the shifted mean Gaussian u...
A Dynamic Model for Energy Structure Analysis
无
2006-01-01
Energy structure is a complicated system concerning economic development, natural resources, technological innovation, ecological balance, social progress and many other elements. It is not easy to explain clearly the developmental mechanism of an energy system and the mutual relations between the energy system and its related environments by the traditional methods. It is necessary to develop a suitable dynamic model, which can reflect the dynamic characteristics and the mutual relations of the energy system and its related environments. In this paper, the historical development of China's energy structure was analyzed. A new quantitative analysis model was developed based on system dynamics principles through analysis of energy resources, and the production and consumption of energy in China and comparison with the world. Finally, this model was used to predict China's future energy structures under different conditions.
The Effect of Random Voids in the Modified Gurson Model
Fei, Huiyang; Yazzie, Kyle; Chawla, Nikhilesh; Jiang, Hanqing
2012-02-01
The porous plasticity model (usually referred to as the Gurson-Tvergaard-Needleman model or modified Gurson model) has been widely used in the study of microvoid-induced ductile fracture. In this paper, we studied the effects of random voids on the porous plasticity model. Finite-element simulations were conducted to study a copper/tin/copper joint bar under uniaxial tension using the commercial finite-element package ABAQUS. A randomly distributed initial void volume fraction with different types of distribution was introduced, and the effects of this randomness on the crack path and macroscopic stress-strain behavior were studied. It was found that consideration of the random voids is able to capture more detailed and localized deformation features, such as different crack paths and different ultimate tensile strengths, and meanwhile does not change the macroscopic stress-strain behavior. It seems that the random voids are able to qualitatively explain the scattered observations in experiments while keeping the macroscopic measurements consistent.
Directory of Energy Information Administration models 1996
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).
Modeling Malaysia's Energy System: Some Preliminary Results
Ahmad M. Yusof
2011-01-01
Full Text Available Problem statement: The current dynamic and fragile world energy environment necessitates the development of new energy model that solely caters to analyze Malaysias energy scenarios. Approach: The model is a network flow model that traces the flow of energy carriers from its sources (import and mining through some conversion and transformation processes for the production of energy products to final destinations (energy demand sectors. The integration to the economic sectors is done exogeneously by specifying the annual sectoral energy demand levels. The model in turn optimizes the energy variables for a specified objective function to meet those demands. Results: By minimizing the inter temporal petroleum product imports for the crude oil system the annual extraction level of Tapis blend is projected at 579600 barrels per day. The aggregate demand for petroleum products is projected to grow at 2.1% year-1 while motor gasoline and diesel constitute 42 and 38% of the petroleum products demands mix respectively over the 5 year planning period. Petroleum products import is expected to grow at 6.0% year-1. Conclusion: The preliminary results indicate that the model performs as expected. Thus other types of energy carriers such as natural gas, coal and biomass will be added to the energy system for the overall development of Malaysia energy model.
Random field distributed Heisenberg model on a thin film geometry
Akıncı, Ümit, E-mail: umit.akinci@deu.edu.tr
2014-11-15
The effects of the bimodal random field distribution on the thermal and magnetic properties of the Heisenberg thin film have been investigated by making use of a two spin cluster with the decoupling approximation. Particular attention has been devoted to the obtaining of phase diagrams and magnetization behaviors. The physical behaviors of special as well as tricritical points are discussed for a wide range of selected Hamiltonian parameters. For example, it is found that when the strength of a magnetic field increases, the locations of the special point (which is the ratio of the surface exchange interaction and the exchange interaction of the inner layers that makes the critical temperature of the film independent of the thickness) in the related plane decrease. Moreover, tricritical behavior has been obtained for higher values of the magnetic field, and influences of the varying Hamiltonian parameters on its behavior have been elucidated in detail in order to have a better understanding of the mechanism underlying the considered system. - Highlights: • Effect of bimodal random field distribution within the Heisenberg model is investigated. • Phase diagrams of the random field Heisenberg model in a thin film geometry are obtained. • Effect of the random field on the magnetic properties is obtained. • Variation of the special point with random field is determined. • Variation of the tricritical point with random field is determined.
Effects of random noise in a dynamical model of love
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.
Low Energy Properties of the Random Spin-1/2 Ferromagnetic-Antiferromagnetic Heisenberg Chain
Hida, Kazuo
1996-01-01
The low energy properties of the spin-1/2 random Heisenberg chain with ferromagnetic and antiferromagnetic interactions are studied by means of the density matrix renormalization group (DMRG) and real space renormalization group (RSRG) method for finite chains. The results of the two methods are consistent with each other. The deviation of the gap distribution from that of the random singlet phase and the formation of the large-spin state is observed even for relatively small systems. For a s...
INFLUENCE ANALYSIS ON EXPONENTIAL NONLINEAR MODELS WITH RANDOM EFFECTS
宗序平; 赵俊; 王海斌; 韦博成
2003-01-01
This paper presents a unified diagnostic method for exponential nonlinear models with random effects based upon the joint likelihood given by Robinson in 1991.The authors show that the case deletion model is equivalent to mean shift outlier model.From this point of view,several diagnostic measures,such as Cook distance,score statistics are derived.The local influence measure of Cook is also presented.Numerical example illustrates that our method is available.
INFLUENCE ANALYSIS IN NONLINEAR MODELS WITH RANDOM EFFECTS
WeiBocheng; ZhongXuping
2001-01-01
Abstract. In this paper,a unified diagnostic method for the nonlinear models with random ef-fects based upon the joint likelihood given by Robinson in 1991 is presented. It is shown that thecase deletion model is equivalent to the mean shift outlier model. From this point of view ,sever-al diagnostic measures, such as Cook distance, score statistics are derived. The local influencemeasure of Cook is also presented. A numerical example illustrates that the method is avail-able
Discrete Modeling of the Worm Spread with Random Scanning
Uchida, Masato
In this paper, we derive a set of discrete time difference equations that models the spreading process of computer worms such as Code-Red and Slammer, which uses a common strategy called “random scanning” to spread through the Internet. We show that the derived set of discrete time difference equations has an exact relationship with the Kermack and McKendrick susceptible-infectious-removed (SIR) model, which is known as a standard continuous time model for worm spreading.
Spectra of Anderson Type Models with Decaying Randomness
M Krishna; K B Sinha
2001-05-01
In this paper we consider some Anderson type models, with free parts having long range tails with the random perturbations decaying at different rates in different directions and prove that there is a.c. spectrum in the model which is pure. In addition, we show that there is pure point spectrum outside some interval. Our models include potentials decaying in all directions in which case absence of singular continuous spectrum is also shown.
Using Random Forest Models to Predict Organizational Violence
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,"
Confining Bond Rearrangement in the Random Center Vortex Model
Altarawneh, Derar; Engelhardt, Michael
2015-01-01
We present static meson-meson and baryon--anti-baryon potentials in Z(2) and Z(3) random center vortex models for the infrared sector of Yang-Mills theory, i.e., hypercubic lattice models of random vortex world-surfaces. In particular, we calculate Polyakov loop correlators of two static mesons resp. (anti-)baryons in a center vortex background and observe that their expectation values follow the minimal area law and show bond rearrangement behavior. The static meson-meson and baryon--anti-baryon potentials are compared with theoretical predictions and lattice QCD simulations.
Random-anisotropy Blume-Emery-Griffiths model
Maritan, Amos; Cieplak, Marek; Swift, Michael R.; Toigo, Flavio; Banavar, Jayanth R.
1992-01-01
The results are described of studies of a random-anisotropy Blume-Emery-Griffiths spin-1 Ising model using mean-field theory, transfer-matrix calculations, and position-space renormalization-group calculations. The interplay between the quenched randomness of the anisotropy and the annealed disorder introduced by the spin-1 model leads to a rich phase diagram with a variety of phase transitions and reentrant behavior. The results may be relevant to the study of the phase separation of He-3 - He-4 mixtures in porous media in the vicinity of the superfluid transition.
Random-anisotropy Blume-Emery-Griffiths model
Maritan, Amos; Cieplak, Marek; Swift, Michael R.; Toigo, Flavio; Banavar, Jayanth R.
1992-01-01
The results are described of studies of a random-anisotropy Blume-Emery-Griffiths spin-1 Ising model using mean-field theory, transfer-matrix calculations, and position-space renormalization-group calculations. The interplay between the quenched randomness of the anisotropy and the annealed disorder introduced by the spin-1 model leads to a rich phase diagram with a variety of phase transitions and reentrant behavior. The results may be relevant to the study of the phase separation of He-3 - He-4 mixtures in porous media in the vicinity of the superfluid transition.
Random-anisotropy Blume-Emery-Griffiths model
Maritan, Amos; Cieplak, Marek; Swift, Michael R.; Toigo, Flavio; Banavar, Jayanth R.
1992-10-01
We describe the results of studies of a random-anisotropy Blume-Emery-Griffiths spin-1 Ising model using mean-field theory, transfer-matrix calculations, and position-space renormalization-group calculations. The interplay between the quenched randomness of the anisotropy and the annealed disorder introduced by the spin-1 model leads to a rich phase diagram with a variety of phase transitions and reentrant behavior. Our results may be relevant to the study of the phase separation of 3He-4He mixtures in porous media in the vicinity of the superfluid transition.
Directory of Energy Information Administration Models 1994
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.
Power Systems and Energy Storage Modeling for Directed Energy Weapons
2014-06-01
electron laser kW Kilo-watt LCS Littoral Combat Ship LAWS Laser Weapon System MLD Maritime Laser Demonstration MW Mega -watt NiMH Nickel metal...and various littoral combat ships. Also, an accurate, working model of the capacitor energy bank is being developed and the flywheel model is being
World energy projection system: Model documentation
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.
G-corrected holographic dark energy model
Malekjani, M
2013-01-01
Here we investigate the holographic dark energy model in the framework of FRW cosmology where the Newtonian gravitational constant,$G$, is varying with cosmic time. Using the complementary astronomical data which support the time dependency of $G$, the evolutionary treatment of EoS parameter and energy density of dark energy model are calculated in the presence of time variation of $G$. It has been shown that in this case, the phantom regime can be achieved at the present time. We also calculate the evolution of $G$- corrected deceleration parameter for holographic dark energy model and show that the dependency of $G$ on the comic time can influence on the transition epoch from decelerated expansion to the accelerated phase. Finally we perform the statefinder analysis for $G$- corrected holographic model and show that this model has a shorter distance from the observational point in $s-r$ plane compare with original holographic dark energy model.
Buffalos milk yield analysis using random regression models
A.S. Schierholt
2010-02-01
Full Text Available Data comprising 1,719 milk yield records from 357 females (predominantly Murrah breed, daughters of 110 sires, with births from 1974 to 2004, obtained from the Programa de Melhoramento Genético de Bubalinos (PROMEBUL and from records of EMBRAPA Amazônia Oriental - EAO herd, located in Belém, Pará, Brazil, were used to compare random regression models for estimating variance components and predicting breeding values of the sires. The data were analyzed by different models using the Legendre’s polynomial functions from second to fourth orders. The random regression models included the effects of herd-year, month of parity date of the control; regression coefficients for age of females (in order to describe the fixed part of the lactation curve and random regression coefficients related to the direct genetic and permanent environment effects. The comparisons among the models were based on the Akaike Infromation Criterion. The random effects regression model using third order Legendre’s polynomials with four classes of the environmental effect were the one that best described the additive genetic variation in milk yield. The heritability estimates varied from 0.08 to 0.40. The genetic correlation between milk yields in younger ages was close to the unit, but in older ages it was low.
Are Discrepancies in RANS Modeled Reynolds Stresses Random?
Xiao, Heng; Wang, Jian-xun; Paterson, Eric G
2016-01-01
In the turbulence modeling community, significant efforts have been made to quantify the uncertainties in the Reynolds-Averaged Navier--Stokes (RANS) models and to improve their predictive capabilities. Of crucial importance in these efforts is the understanding of the discrepancies in the RANS modeled Reynolds stresses. However, to what extent these discrepancies can be predicted or whether they are completely random remains a fundamental open question. In this work we used a machine learning algorithm based on random forest regression to predict the discrepancies. The success of the regression--prediction procedure indicates that, to a large extent, the discrepancies in the modeled Reynolds stresses can be explained by the mean flow feature, and thus they are universal quantities that can be extrapolated from one flow to another, at least among different flows sharing the same characteristics such as separation. This finding has profound implications to the future development of RANS models, opening up new ...
Bi-Spectrum Scattering Model for Dielectric Randomly Rough Surface
刘宁; 李宗谦
2003-01-01
The bistatic scattering model is offen used for remote microwave sensing. The bi-spectrum model (BSM) for conducting surfaces was used to develop a scattering model for dielectric randomly rough surfaces to estimate their bistatic scattering coefficients. The model for dielectric rough surfaces differs from the BSM for a conducting surface by including Fresnell reflection and transmission from dielectric rough surfaces. The bistatic scattering coefficients were defined to satisfy the reciprocal theorem. Values calculated using the BSM for dielectric randomly rough surfaces compare well with those of the integral equation model (IEM) and with experimental data, showing that the BSM accuracy is acceptable and its range of validity is similar to that of IEM while the BSM expression is simpler than that of IEM.
Modeling of renewable hybrid energy sources
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.
Statefinder parameters in two dark energy models
Panotopoulos, Grigoris
2007-01-01
The statefinder parameters ($r,s$) in two dark energy models are studied. In the first, we discuss in four-dimensional General Relativity a two fluid model, in which dark energy and dark matter are allowed to interact with each other. In the second model, we consider the DGP brane model generalized by taking a possible energy exchange between the brane and the bulk into account. We determine the values of the statefinder parameters that correspond to the unique attractor of the system at hand. Furthermore, we produce plots in which we show $s,r$ as functions of red-shift, and the ($s-r$) plane for each model.
Modeling of random wave transformation with strong wave-induced coastal currents
Zheng Jinhai; H. Mase; Li Tongfei
2008-01-01
The propagation and transformation of multi-directional and uni-directional random waves over a coast with complicated bathymetric and geometric features are studied experimentally and numerically. Laboratory investigation indicates that wave energy convergence and divergence cause strong coastal currents to develop and inversely modify the wave fields. A coastal spectral wave model, based on the wave action balance equation with diffraction effect (WABED), is used to simulate the transformation of random waves over the complicated bathymetry. The diffraction effect in the wave model is derived from a parabolic approximation of wave theory, and the mean energy dissipation rate per unit horizontal area due to wave breaking is parameterized by the bore-based formulation with a breaker index of 0.73. The numerically simulated wave field without considering coastal currents is different from that of experiments, whereas model results considering currents clearly reproduce the intensification of wave height in front of concave shorelines.
A new gravitational model for dark energy
HUANG Chao-Guang; ZHANG Hai-Qing; GUO Han-Ying
2008-01-01
A new gravitational model for dark energy is presented based on the model of de Sitter gauge theory of gravity.In the model,in addition to the cosmological constant,the homogeneous and isotropic torsion and its coupling with curvature play an important role for dark energy.The model may supply the universe with a natural transit from decelerating expansion to accelerating expansion.
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 ...
Modeling of battery energy storage in the National Energy Modeling System
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.
Modeling of battery energy storage in the National Energy Modeling System
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.
Energy and Uncertainty: Models and Algorithms for Complex Energy Systems
2014-01-01
The problem of controlling energy systems (generation, transmission, storage, investment) introduces a number of optimization problems which need to be solved in the presence of different types of uncertainty. We highlight several of these applications, using a simple energy storage problem as a case application. Using this setting, we describe a modeling framework based around five fundamental dimensions which is more natural than the standard canonical form widely used in the reinforcement ...
First principles modeling of magnetic random access memory devices (invited)
Butler, W.H.; Zhang, X.; Schulthess, T.C.; Nicholson, D.M.; Oparin, A.B. [Metals and Ceramics Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831 (United States); MacLaren, J.M. [Department of Physics, Tulane University, New Orleans, Louisiana 70018 (United States)
1999-04-01
Giant magnetoresistance (GMR) and spin-dependent tunneling may be used to make magnetic random access memory devices. We have applied first-principles based electronic structure techniques to understand these effects and in the case of GMR to model the transport properties of the devices. {copyright} {ital 1999 American Institute of Physics.}
Performance of Random Effects Model Estimators under Complex Sampling Designs
Jia, Yue; Stokes, Lynne; Harris, Ian; Wang, Yan
2011-01-01
In this article, we consider estimation of parameters of random effects models from samples collected via complex multistage designs. Incorporation of sampling weights is one way to reduce estimation bias due to unequal probabilities of selection. Several weighting methods have been proposed in the literature for estimating the parameters of…
Statistical properties of several models of fractional random point processes
Bendjaballah, C.
2011-08-01
Statistical properties of several models of fractional random point processes have been analyzed from the counting and time interval statistics points of view. Based on the criterion of the reduced variance, it is seen that such processes exhibit nonclassical properties. The conditions for these processes to be treated as conditional Poisson processes are examined. Numerical simulations illustrate part of the theoretical calculations.
Asthma Self-Management Model: Randomized Controlled Trial
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…
Modeling Energy and Development : An Evaluation of Models and Concepts
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 envir
Quantum random oracle model for quantum digital signature
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.
On exact superpotentials, free energies and matrix models
Hailu, Girma; Georgi, Howard [Jefferson Laboratory of Physics, Harvard University, Cambridge, MA (United States)]. E-mail addresses: hailu@feynman.harvard.edu; georgi@physics.harvard.edu
2004-02-01
We discuss exact results for the full nonperturbative effective superpotentials of four dimensional N=1 supersymmetric U(N) gauge theories with additional chiral superfield in the adjoint representation and the free energies of the related zero dimensional bosonic matrix models with polynomial potentials in the planar limit using the Dijkgraaf-Vafa matrix model prescription and integrating in and out. The exact effective superpotentials are produced including the leading Veneziano-Yankielowicz term directly from the matrix models. We also discuss how to use integrating in and out as a tool to do random matrix integrals in the large-N limit. (author)
Extended Quark Potential Model From Random Phase Approximation
DENGWei－Zhen; CHENXiao－Lin; 等
2002-01-01
The quark potential model is extended to include the sea quark excitation using the random phase approximation.The effective quark interaction preserves the important QCD properties-chiral symmetry and confinement simultaneously.A primary qualitative analysis shows that the π meson as a well-known typical Goldstone boson and the other mesons made up of valence qq quark pair such as the ρ meson can also be described in this extended quark potential model.
Extended Quark Potential Model from Random Phase Approximation
DENG Wei-Zhen; CHEN Xiao-Lin; LU Da-Hai; YANG Li-Ming
2002-01-01
The quark potential model is extended to include the sea quark excitation using the random phase approx-imation. The effective quark interaction preserves the important QCD properties - chiral symmetry and confinementsimultaneously. A primary qualitative analysis shows that the π meson as a well-known typical Goldstone boson andthe other mesons made up of valence qq quark pair such as the ρ meson can also be described in this extended quarkpotential model.
Investigating Facebook Groups through a Random Graph Model
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...
Analysis of Two-Layered Random Interfaces for Two Dimensional Widom-Rowlinson's Model
Jun Wang
2011-01-01
Full Text Available The statistical behaviors of two-layered random-phase interfaces in two-dimensional Widom-Rowlinson's model are investigated. The phase interfaces separate two coexisting phases of the lattice Widom-Rowlinson model; when the chemical potential μ of the model is large enough, the convergence of the probability distributions which describe the fluctuations of the phase interfaces is studied. In this paper, the backbones of interfaces are introduced in the model, and the corresponding polymer chains and cluster expansions are developed and analyzed for the polymer weights. And the existence of the free energy for two-layered random-phase interfaces of the two-dimensional Widom-Rowlinson model is given.
Magnetic properties of a transverse spin- Ising model with random longitudinal field
Liang, Ya-Qiu; Wei, Guo-Zhu; Song, Guo-Li
2004-12-01
Within the framework of the effective-field theory with correlations, a spin- transverse Ising model in the longitudinal random-field on a honeycomb lattice is studied. The phase diagrams and the behavior of the tricritical point are examined. The possible re-entrance phenomena displayed by the system due to the competition effects that occur for the appropriate ranges of the random and transverse field are investigated. The longitudinal and transverse magnetizations, the longitudinal quadrupolar moments and internal energy are given numerically for a honeycomb lattice (z = 3).
Dark energy observational evidence and theoretical models
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.
Modeling global and regional energy futures
Rethinaraj, T. S. Gopi
A rigorous econometric calibration of a model of energy consumption is presented using a comprehensive time series database on energy consumption and other socioeconomic indicators. The future of nuclear power in the evolving distribution of various energy sources is also examined. An important consideration for the long-term future of nuclear power concerns the rate of decline of the fraction of energy that comes from coal, which has historically declined on a global basis about linearly as a function of the cumulative use of coal. The use of fluid fossil fuels is also expected to eventually decline as the more readily extractable deposits are depleted. The investigation here is restricted to examining a comparatively simple model of the dynamics of competition between nuclear and other competing energy sources. Using a defined tropical/temperate disaggregation of the world, region-specific modeling results are presented for population growth, GDP growth, energy use, and carbon use compatible with a gradual transition to energy sustainability. Results for the fractions of energy use from various sources by grouping nine commercial primary energy sources into pairs of competing fuel categories are presented in combination with the idea of experiential learning and resource depletion. Analysis based on this division provides estimates for future evolution of the fractional shares, annual use rates, cumulative use of individual energy sources, and the economic attractiveness of spent nuclear fuel reprocessing. This unified approach helps to conceptualize and understand the dynamics of evolution of importance of various energy resources over time.
Random matrices as models for the statistics of quantum mechanics
Casati, Giulio; Guarneri, Italo; Mantica, Giorgio
1986-05-01
Random matrices from the Gaussian unitary ensemble generate in a natural way unitary groups of evolution in finite-dimensional spaces. The statistical properties of this time evolution can be investigated by studying the time autocorrelation functions of dynamical variables. We prove general results on the decay properties of such autocorrelation functions in the limit of infinite-dimensional matrices. We discuss the relevance of random matrices as models for the dynamics of quantum systems that are chaotic in the classical limit. Permanent address: Dipartimento di Fisica, Via Celoria 16, 20133 Milano, Italy.
Stochastic geometry, spatial statistics and random fields models and algorithms
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.
New 1/N expansions in random tensor models
Bonzom, Valentin
2012-01-01
Although random tensor models were introduced twenty years ago, it is only in 2011 that Gurau proved the existence of a 1/N expansion. Here we show that there actually is more than a single 1/N expansion, depending on the dimension. In the large N limit, these new expansions retain more than the melonic graphs. Still, in most cases, the large N limit is found to be Gaussian, and therefore extends the scope of the universality theorem for large random tensors. Nevertheless, a scaling which leads to non-Gaussian large N limits, in even dimensions, is identified for the first time.
Boundary States of the Potts Model on Random Planar Maps
Atkin, Max; Wheater, John
2015-01-01
We revisit the 3-states Potts model on random planar triangulations as a Hermitian matrix model. As a novelty, we obtain an algebraic curve which encodes the partition function on the disc with both fixed and mixed spin boundary conditions. We investigate the critical behaviour of this model and find scaling exponents consistent with previous literature. We argue that the conformal field theory that describes the double scaling limit is Liouville quantum gravity coupled to the $(A_4,D_4)$ minimal model with extended $\\mathcal{W}_3$-symmetry.
A Bi-directional Energy Splitable Model for Energy Optimization in Wireless Sensor Networks
A. Rajeswari
2011-01-01
Full Text Available Wireless Sensor Networks is a budding prototype of networking and computing, where a node may be self powered and individual node have the capability to sense and compute and communicate. Wireless Sensor Networks have been proposed for variety of applications such as Industrial control and monitoring and home automation and consumer electronics and security andMilitary sensing, Asset tracking and supply chain management, Intelligent Agriculture, Missile directing, Fire alarming, Landslide Warning, Environmental monitoring and health monitoring and commercial applications. In Wireless Sensor Network large number of nodes are deployed randomly. Depends on the network architecture the application may be personalized such as Energy Efficiency, Routing and Power Management and data dissemination. Energy Optimization involves in minimizing an energy expenditure and maximizing the lifetime of the complete network. In the proposed work, the placement of nodes are directly involved with residual energy. Energy Optimization in sensor network is very difficult task to achieve it. The optimization of energy is performed through Bidirectional Energy Splitable Model. The data flow in both forward and backward directions are considered, In order to achieve the best QOS in transmission, some parameters such as load, delay and direction of individual nodes are considered. A mathematical model is developed to determine the data flow of individual node based on the residual energy.
Stochastic Modelling of Energy Systems
Andersen, Klaus Kaae
2001-01-01
equations are expressed in terms of stochastic differential equations. From a theoretical viewpoint the techniques for experimental design, parameter estimation and model validation are considered. From the practical viewpoint emphasis is put on how this methods can be used to construct models adequate...
Modeling and Optimization for Piercing Energy Consumption
XIAO Dong; PAN Xiao-li; YUAN Yong; MAO Zhi-zhong; WANG Fu-li
2009-01-01
Energy consumption is an important quality index in the production of seamless tubes. The complex factors affecting energy consumption make it difficult to build its mechanism model, and optimization is also very difficult, if not impossible. The piercing process was divided into three parts based on the production process, and an energy consumption prediction model was proposed based on the step mean value staged multiway partial least square meth-od. On the basis of the batch process prediction model, a genetic algorithm was adopted to calculate the optimum mean value of each process parameter and the minimum piercing energy consumption. Simulation proves that the op-timization method based on the energy consumption prediction model can obtain the optimum process parameters ef-fectively and also provide reliable evidences for practical production.
Modeling approach suitable for energy system
Goetschel, D. V.
1979-01-01
Recently increased attention has been placed on optimization problems related to the determination and analysis of operating strategies for energy systems. Presented in this paper is a nonlinear model that can be used in the formulation of certain energy-conversion systems-modeling problems. The model lends itself nicely to solution approaches based on nonlinear-programming algorithms and, in particular, to those methods falling into the class of variable metric algorithms for nonlinearly constrained optimization.
Exact solution of phantom dark energy model
Wang Wen-Fu; Shui Zheng-Wei; Tang Bin
2010-01-01
We investigate the phantom dark energy model derived from the scalar field with a negative kinetic term. By assuming a particular relation between the time derivative of the phantom field and the Hubble function, an exact solution of the model is constructed. Absence of the 'big rip' singularity is shown explicitly. We then derive special features of phantom dark energy model and show that its predictions are consistent with all astrophysical observations.
On Kinetics Modeling of Vibrational Energy Transfer
Gilmore, John O.; Sharma, Surendra P.; Cavolowsky, John A. (Technical Monitor)
1996-01-01
Two models of vibrational energy exchange are compared at equilibrium to the elementary vibrational exchange reaction for a binary mixture. The first model, non-linear in the species vibrational energies, was derived by Schwartz, Slawsky, and Herzfeld (SSH) by considering the detailed kinetics of vibrational energy levels. This model recovers the result demanded at equilibrium by the elementary reaction. The second model is more recent, and is gaining use in certain areas of computational fluid dynamics. This model, linear in the species vibrational energies, is shown not to recover the required equilibrium result. Further, this more recent model is inconsistent with its suggested rate constants in that those rate constants were inferred from measurements by using the SSH model to reduce the data. The non-linear versus linear nature of these two models can lead to significant differences in vibrational energy coupling. Use of the contemporary model may lead to significant misconceptions, especially when integrated in computer codes considering multiple energy coupling mechanisms.
A generalized model via random walks for information filtering
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.
Jackknifed random weighting for Cox proportional hazards model
LI Xiao; WU YaoHua; TU DongSheng
2012-01-01
The Cox proportional hazards model is the most used statistical model in the analysis of survival time data.Recently,a random weighting method was proposed to approximate the distribution of the maximum partial likelihood estimate for the regression coefficient in the Cox model.This method was shown not as sensitive to heavy censoring as the bootstrap method in simulation studies but it may not be second-order accurate as was shown for the bootstrap approximation.In this paper,we propose an alternative random weighting method based on one-step linear jackknife pseudo values and prove the second accuracy of the proposed method.Monte Carlo simulations are also performed to evaluate the proposed method for fixed sample sizes.
Random curds as mathematical models of fractal rhythm in architecture
Ćirović Ivana
2014-01-01
Full Text Available The author Carl Bovill has suggested and described a method for generating rhythm in architecture with the help of random curds, as they are the mathematical models of unpredictable and uneven groupings which he recognizes in natural shapes and in natural processes. He specified the rhythm generated in this way as the fractal rhythm. Random curds can be generated by a simple process of curdling, as suggested by B. Mandelbrot. This paper examines the way in which the choice of probability for every stage or level of the curdling process, and the number of stages in the procedure of curdling, affect the characteristics of the obtained fractal object as a potential mathematical model of rhythm in the design process. At the same time, this paper examines the characteristics of rhythm in architecture which determine whether the obtained fractal object will be accepted as an appropriate mathematical model of the observed rhythm.
Thermal behavior for a nanoscale two ferromagnetic phase system based on random anisotropy model
Muraca, D., E-mail: diego.muraca@gmail.co [INTECIN - Instituto de Tecnologia y Ciencias de la Ingenieria ' Hilario Fernandez Long' (UBA-CONICET), Facultad de Ingenieria, Paseo Colon 850, (1063), Buenos Aires (Argentina); Sanchez, F.H. [Departamento de Fisica-Instituto de Fisica de La Plata, Facultad de Ciencias Exactas, Universidad Nacional de La Plata, C. C. 69, (1900), La Plata (Argentina); Pampillo, L.G.; Saccone, F.D. [INTECIN - Instituto de Tecnologia y Ciencias de la Ingenieria ' Hilario Fernandez Long' (UBA-CONICET), Facultad de Ingenieria, Paseo Colon 850, (1063), Buenos Aires (Argentina)
2010-03-15
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.
Modelling total energy costs of sports centres
Boussabaine, A.H.; Kirkham, R.J.; Grew, R.J. [Liverpool Univ., School of Architecture and Building Engineering, Liverpool (United Kingdom)
1999-12-07
Providing and maintaining safe and comfortable conditions in sport centres raises many issues, particularly cost. The paper gives an overview of the factors associated with sport centre servicing and attempts to highlight the governing factors associated with this, particularly energy costs. A total of 19 sport centres in the City of Liverpool in the UK are investigated, using data elicited from the Liverpool Leisure Services Directorate. The energy operating costs were analysed using statistical methods. Six models were developed to predict total energy costs. Testing and validation results showed a high level of model accuracy. The models would be of use to professionals involved in feasibility studies at the design stage. (Author)
The van Hemmen model and effect of random crystalline anisotropy field
Morais, Denes M. de [Instituto de Física, Universidade Federal de Mato Grosso, 78060-900 Cuiabá, Mato Grosso (Brazil); Godoy, Mauricio, E-mail: mgodoy@fisica.ufmt.br [Instituto de Física, Universidade Federal de Mato Grosso, 78060-900 Cuiabá, Mato Grosso (Brazil); Arruda, Alberto S. de, E-mail: aarruda@fisica.ufmt.br [Instituto de Física, Universidade Federal de Mato Grosso, 78060-900 Cuiabá, Mato Grosso (Brazil); Silva, Jonathas N. da [Universidade Estadual Paulista, 14800-901, Araraquara, São Paulo (Brazil); Ricardo de Sousa, J. [Instituto Nacional de Sistemas Complexos, Departamento de Fisica, Universidade Federal do Amazona, 69077-000, Manaus, Amazonas (Brazil)
2016-01-15
In this work, we have presented the generalized phase diagrams of the van Hemmen model for spin S=1 in the presence of an anisotropic term of random crystalline field. In order to study the critical behavior of the phase transitions, we employed a mean-field Curie–Weiss approach, which allows calculation of the free energy and the equations of state of the model. The phase diagrams obtained here displayed tricritical behavior, with second-order phase transition lines separated from the first-order phase transition lines by a tricritical point. - Highlights: • Several phase diagrams are obtained for the model. • The influence of the random crystalline anisotropy field on the model is investigated. • Three ordered (spin-glass, ferromagnetic and mixed) phases are found. • The tricritical behavior is examined.
Scaling of coercivity in a 3d random anisotropy model
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.
Approximation by randomly weighting method in censored regression model
无
2009-01-01
Censored regression ("Tobit") models have been in common use, and their linear hypothesis testings have been widely studied. However, the critical values of these tests are usually related to quantities of an unknown error distribution and estimators of nuisance parameters. In this paper, we propose a randomly weighting test statistic and take its conditional distribution as an approximation to null distribution of the test statistic. It is shown that, under both the null and local alternative hypotheses, conditionally asymptotic distribution of the randomly weighting test statistic is the same as the null distribution of the test statistic. Therefore, the critical values of the test statistic can be obtained by randomly weighting method without estimating the nuisance parameters. At the same time, we also achieve the weak consistency and asymptotic normality of the randomly weighting least absolute deviation estimate in censored regression model. Simulation studies illustrate that the per-formance of our proposed resampling test method is better than that of central chi-square distribution under the null hypothesis.
Approximation by randomly weighting method in censored regression model
WANG ZhanFeng; WU YaoHua; ZHAO LinCheng
2009-01-01
Censored regression ("Tobit") models have been in common use,and their linear hypothesis testings have been widely studied.However,the critical values of these tests are usually related to quantities of an unknown error distribution and estimators of nuisance parameters.In this paper,we propose a randomly weighting test statistic and take its conditional distribution as an approximation to null distribution of the test statistic.It is shown that,under both the null and local alternative hypotheses,conditionally asymptotic distribution of the randomly weighting test statistic is the same as the null distribution of the test statistic.Therefore,the critical values of the test statistic can be obtained by randomly weighting method without estimating the nuisance parameters.At the same time,we also achieve the weak consistency and asymptotic normality of the randomly weighting least absolute deviation estimate in censored regression model.Simulation studies illustrate that the performance of our proposed resampling test method is better than that of central chi-square distribution under the null hypothesis.
On a Random Matrix Models of Quantum Relaxation
Lebowitz, J L; Pastur, L
2007-01-01
Earlier two of us (J.L. and L.P.) considered a matrix model for a two-level system interacting with a $n\\times n$ reservoir and assuming that the interaction is modelled by a random matrix. We presented there a formula for the reduced density matrix in the limit $n\\to \\infty $ as well as several its properties and asymptotic forms in various regimes. In this paper we give the proofs of the assertions, and present also a new fact about the model.
Statistical shape model with random walks for inner ear segmentation
Pujadas, Esmeralda Ruiz; Kjer, Hans Martin; Piella, Gemma
2016-01-01
Cochlear implants can restore hearing to completely or partially deaf patients. The intervention planning can be aided by providing a patient-specific model of the inner ear. Such a model has to be built from high resolution images with accurate segmentations. Thus, a precise segmentation...... 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...
Antiferromagnetic Potts model on the Erdos-Renyi random graph
Contucci, Pierluig; Giardina', Cristian; Starr, Shannon
2011-01-01
We study the antiferromagnetic Potts model on the Erdos-Renyi random graph. By identifying a suitable interpolation structure and proving an extended variational principle we show that the replica symmetric solution is an upper bound for the limiting pressure which can be recovered in the framework of Derrida-Ruelle probability cascades. A comparison theorem with a mixed model made of a mean field Potts-antiferromagnet plus a Potts-Sherrington-Kirkpatrick model allows to show that the replica symmetric solution is exact at high temperatures.
A Random Dot Product Model for Weighted Networks
DeFord, Daryl R
2016-01-01
This paper presents a generalization of the random dot product model for networks whose edge weights are drawn from a parametrized probability distribution. We focus on the case of integer weight edges and show that many previously studied models can be recovered as special cases of this generalization. Our model also determines a dimension--reducing embedding process that gives geometric interpretations of community structure and centrality. The dimension of the embedding has consequences for the derived community structure and we exhibit a stress function for determining appropriate dimensions. We use this approach to analyze a coauthorship network and voting data from the U.S. Senate.
Minimum-energy broadcast in random-grid ad-hoc networks: approximation and distributed algorithms
Calamoneri, Tiziana; Monti, Angelo; Rossi, Gianluca; Silvestri, Riccardo
2008-01-01
The Min Energy broadcast problem consists in assigning transmission ranges to the nodes of an ad-hoc network in order to guarantee a directed spanning tree from a given source node and, at the same time, to minimize the energy consumption (i.e. the energy cost) yielded by the range assignment. Min energy broadcast is known to be NP-hard. We consider random-grid networks where nodes are chosen independently at random from the $n$ points of a $\\sqrt n \\times \\sqrt n$ square grid in the plane. The probability of the existence of a node at a given point of the grid does depend on that point, that is, the probability distribution can be non-uniform. By using information-theoretic arguments, we prove a lower bound $(1-\\epsilon) \\frac n{\\pi}$ on the energy cost of any feasible solution for this problem. Then, we provide an efficient solution of energy cost not larger than $1.1204 \\frac n{\\pi}$. Finally, we present a fully-distributed protocol that constructs a broadcast range assignment of energy cost not larger tha...
RANDOM SYSTEMS OF HARD PARTICLES:MODELS AND STATISTICS
Dietrich Stoyan
2002-01-01
This paper surveys models and statistical properties of random systems of hard particles. Such systems appear frequently in materials science, biology and elsewhere. In mathematical - statistical investigations, simulations of such structures play an important role. In these simulations various methods and models are applied, namely the RSA model, sedimentation and collective rearrangement algorithms, molecular dynamics, and Monte Carlo methods such as the Metropolis - Hastings algorithm. The statistical description of real and simulated particle systems uses ideas of the mathematical theories of random sets and point processes. This leads to characteristics such as volume fraction or porosity, covariance,contact distribution functions, specific connectivity number from the random set approach and intensity, pair correlation function and mark correlation functions from the point process approach. Some of them can be determined stereologically using planar sections, while others can only be obtained using three - dimensional data and 3D image analysis. They are valuable tools for fitting models to empirical data and, consequently, for understanding various materials, biological structures, porous media and other practically important spatial structures.
Modelling in nuclear energy environments
M. Samaras
2008-12-01
Full Text Available Producing energy to supply the demands of our societies is reaching a critical limit. To tackle this issue, there is a slow renaissance of fission reactors and the push to realise fusion reactors. The safe, reliable and optimal performance of fusion and fission plants is dependent on the choice of suitable materials used as components and fuels. As these materials are degraded by their exposure to high temperatures, irradiation and a corrosive environment, it is necessary to address the issue of long term degradation of materials under service exposure in advanced plants. A higher confidence in life-time assessments of these materials requires an understanding of the related physical phenomena on a range of scales from the atomic level of single defect energetics all the way up to macroscopic effects.
Impacts of Model Building Energy Codes
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 CO_{2} 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.
Energy Systems Modelling Research and Analysis
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...
A global energy model with fusion
Lechon, Yolanda [CIEMAT, Avda Complutense 22, 28040 Madrid (Spain)]. E-mail: yolanda.lechon@ciemat.es; Cabal, H. [CIEMAT, Avda Complutense 22, 28040 Madrid (Spain); Varela, M. [CIEMAT, Avda Complutense 22, 28040 Madrid (Spain); Saez, R. [CIEMAT, Avda Complutense 22, 28040 Madrid (Spain); Eherer, C. [TUG/ITP, Petersgasse 16, 8010 Graz (Austria); Baumann, M. [TUG/ITP, Petersgasse 16, 8010 Graz (Austria); Dueweke, J. [IPP, Boltzmannstr. 2, D-85748 Garching (Germany); Hamacher, T. [IPP, Boltzmannstr. 2, D-85748 Garching (Germany); Tosato, G.C. [EFDA Close Support Unit, Boltzmannstr. 2, D-85748 Garching (Germany)
2005-11-15
Some analysts expect a complete shift of the global energy system in the 21st century, away from fossil fuels to either renewable sources or new nuclear technologies [L. Schrattenholzer, A roadmap to a sustainable global energy system, in: Proceedings of the International Energy Workshop, Paris, June, 2004]. Fusion might become a corner stone of the future energy system. The construction and successful operation of ITER is a necessary condition to reach this goal. Within the Socio Economic Research on Fusion (SERF) programme guided by EFDA, a consortium between CIEMAT, TU Graz (TUG), ENEA and IPP open to other European energy and fusion research laboratories has been formed to analyse the possible role of fusion in the future energy system. Using TIMES, a single region global model has been constructed including fusion as an energy option. Background of the model is a detailed bottom-up description of the complete energy system starting from mining process up to the various demand sectors. The model dynamics is determined by an optimisation process, in which total surplus is maximized. The paper will present the first attempts to set-up a single region global model and the first results.
World Energy Projection System model documentation
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.
Directory of Energy Information Administration Models 1993
1993-07-06
This directory contains descriptions about each model, including the title, acronym, purpose, followed by more detailed information on characteristics, uses, and requirements. Sources for additional information are identified. Included in this directory are 35 EIA models active as of May 1, 1993. Models that run on personal computers are identified by ``PC`` as part of the acronym. EIA is developing new models, a National Energy Modeling System (NEMS), and is making changes to existing models to include new technologies, environmental issues, conservation, and renewables, as well as extend forecast horizon. Other parts of the Department are involved in this modeling effort. A fully operational model is planned which will integrate completed segments of NEMS for its first official application--preparation of EIA`s Annual Energy Outlook 1994. Abstracts for the new models will be included in next year`s version of this directory.
Directory of energy information administration models 1995
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.
Spatially random models, estimation theory, and robot arm dynamics
Rodriguez, G.
1987-01-01
Spatially random models provide an alternative to the more traditional deterministic models used to describe robot arm dynamics. These alternative models can be used to establish a relationship between the methodologies of estimation theory and robot dynamics. A new class of algorithms for many of the fundamental robotics problems of inverse and forward dynamics, inverse kinematics, etc. can be developed that use computations typical in estimation theory. The algorithms make extensive use of the difference equations of Kalman filtering and Bryson-Frazier smoothing to conduct spatial recursions. The spatially random models are very easy to describe and are based on the assumption that all of the inertial (D'Alembert) forces in the system are represented by a spatially distributed white-noise model. The models can also be used to generate numerically the composite multibody system inertia matrix. This is done without resorting to the more common methods of deterministic modeling involving Lagrangian dynamics, Newton-Euler equations, etc. These methods make substantial use of human knowledge in derivation and minipulation of equations of motion for complex mechanical systems.
Modelling the energy transition in cities
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.
Random weighting method for Cox’s proportional hazards model
2008-01-01
Variance of parameter estimate in Cox’s proportional hazards model is based on asymptotic variance. When sample size is small, variance can be estimated by bootstrap method. However, if censoring rate in a survival data set is high, bootstrap method may fail to work properly. This is because bootstrap samples may be even more heavily censored due to repeated sampling of the censored observations. This paper proposes a random weighting method for variance estimation and confidence interval estimation for proportional hazards model. This method, unlike the bootstrap method, does not lead to more severe censoring than the original sample does. Its large sample properties are studied and the consistency and asymptotic normality are proved under mild conditions. Simulation studies show that the random weighting method is not as sensitive to heavy censoring as bootstrap method is and can produce good variance estimates or confidence intervals.
Random weighting method for Cox's proportional hazards model
CUI WenQuan; LI Kai; YANG YaNing; WU YueHua
2008-01-01
Variance of parameter estimate in Cox's proportional hazards model is based on asymptotic variance.When sample size is small,variance can be estimated by bootstrap method.However,if censoring rate in a survival data set is high,bootstrap method may fail to work properly.This is because bootstrap samples may be even more heavily censored due to repeated sampling of the censored observations.This paper proposes a random weighting method for variance estimation and confidence interval estimation for proportional hazards model.This method,unlike the bootstrap method,does not lead to more severe censoring than the original sample does.Its large sample properties are studied and the consistency and asymptotic normality are proved under mild conditions.Simulation studies show that the random weighting method is not as sensitive to heavy censoring as bootstrap method is and can produce good variance estimates or confidence intervals.
Random unitary evolution model of quantum Darwinism with pure decoherence
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.
Statistical Modeling of Robotic Random Walks on Different Terrain
Naylor, Austin; Kinnaman, Laura
Issues of public safety, especially with crowd dynamics and pedestrian movement, have been modeled by physicists using methods from statistical mechanics over the last few years. Complex decision making of humans moving on different terrains can be modeled using random walks (RW) and correlated random walks (CRW). The effect of different terrains, such as a constant increasing slope, on RW and CRW was explored. LEGO robots were programmed to make RW and CRW with uniform step sizes. Level ground tests demonstrated that the robots had the expected step size distribution and correlation angles (for CRW). The mean square displacement was calculated for each RW and CRW on different terrains and matched expected trends. The step size distribution was determined to change based on the terrain; theoretical predictions for the step size distribution were made for various simple terrains. It's Dr. Laura Kinnaman, not sure where to put the Prefix.
Zahra Etesami
2017-05-01
Full Text Available We investigate harvesting electrical energy from Gaussian white, Gaussian colored, telegraph and random phase-random amplitude (RARP noises, using linear and nonlinear electromechanical systems. We show that the output power of the linear system with one or two degrees of freedom, is maximum for the Gaussian white noise. The response of the system with two degrees of freedom is widened in a larger frequency domain compared to that of a single degree of freedom system. A nonlinear system generates more power than a linear one.
Roth, Christine-Andrea; Dreyfus, Tom; Robert, Charles H; Cazals, Frédéric
2016-03-30
The number of local minima of the potential energy landscape (PEL) of molecular systems generally grows exponentially with the number of degrees of freedom, so that a crucial property of PEL exploration algorithms is their ability to identify local minima, which are low lying and diverse. In this work, we present a new exploration algorithm, retaining the ability of basin hopping (BH) to identify local minima, and that of transition based rapidly exploring random trees (T-RRT) to foster the exploration of yet unexplored regions. This ability is obtained by interleaving calls to the extension procedures of BH and T-RRT, and we show tuning the balance between these two types of calls allows the algorithm to focus on low lying regions. Computational efficiency is obtained using state-of-the art data structures, in particular for searching approximate nearest neighbors in metric spaces. We present results for the BLN69, a protein model whose conformational space has dimension 207 and whose PEL has been studied exhaustively. On this system, we show that the propensity of our algorithm to explore low lying regions of the landscape significantly outperforms those of BH and T-RRT.
Bose-Einstein Correlations from Random Walk Models
Tomasik, Boris; Pisút, J; Tomasik, Boris; Heinz, Ulrich; Pisut, Jan
1998-01-01
We argue that the recently suggested ``random walk models'' for the extrapolation of hadronic transverse mass spectra from pp or pA to AB collisions fail to describe existing data on Bose-Einstein correlations. In particular they are unable to reproduce the measured magnitude and K_\\perp-dependence of R_s in Pb+Pb collisions and the increase of R_l with increasing size of the collision system.
Toy Model for Large Non-Symmetric Random Matrices
Snarska, Małgorzata
2010-01-01
Non-symmetric rectangular correlation matrices occur in many problems in economics. We test the method of extracting statistically meaningful correlations between input and output variables of large dimensionality and build a toy model for artificially included correlations in large random time series.The results are then applied to analysis of polish macroeconomic data and can be used as an alternative to classical cointegration approach.
Random resistor network model of minimal conductivity in graphene.
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.
Information inefficiency in a random linear economy model
Jerico, Joao Pedro
2016-01-01
We study the effects of introducing information inefficiency in a model for a random linear economy with a representative consumer. This is done by considering statistical, instead of classical, economic general equilibria. Employing two different approaches we show that inefficiency increases the consumption set of a consumer but decreases her expected utility. In this scenario economic activity grows while welfare shrinks, that is the opposite of the behavior obtained by considering a rational consumer.
Theory of Distribution Estimation of Hyperparameters in Markov Random Field Models
Sakamoto, Hirotaka; Nakanishi-Ohno, Yoshinori; Okada, Masato
2016-06-01
We investigated the performance of distribution estimation of hyperparameters in Markov random field models proposed by Nakanishi-Ohno et al., http://doi.org/10.1088/1751-8113/47/4/045001, J. Phys. A 47, 045001 (2014) when used to evaluate the confidence of data. We analytically calculated the configurational average, with respect to data, of the negative logarithm of the posterior distribution, which is called free energy based on an analogy with statistical mechanics. This configurational average of free energy shrinks as the amount of data increases. Our results theoretically confirm the numerical results from that previous study.
Single-cluster dynamics for the random-cluster model
Deng, Youjin; Qian, Xiaofeng; Blöte, Henk W. J.
2009-09-01
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 of the existing Swendsen-Wang-Chayes-Machta (SWCM) algorithm, which involves a full-cluster decomposition of random-cluster configurations. We explore the critical dynamics of this algorithm for several two-dimensional Potts and random-cluster models. For integer q , the single-cluster algorithm can be reduced to the Wolff algorithm, for which case we find that the autocorrelation functions decay almost purely exponentially, with dynamic exponents zexp=0.07 (1), 0.521 (7), and 1.007 (9) for q=2 , 3, and 4, respectively. For noninteger q , the dynamical behavior of the single-cluster algorithm appears to be very dissimilar to that of the SWCM algorithm. For large critical systems, the autocorrelation function displays a range of power-law behavior as a function of time. The dynamic exponents are relatively large. We provide an explanation for this peculiar dynamic behavior.
Energy-Latency Tradeoff for In-Network Function Computation in Random Networks
Balister, Paul; Anandkumar, Animashree; Willsky, Alan
2011-01-01
The problem of designing policies for in-network function computation with minimum energy consumption subject to a latency constraint is considered. The scaling behavior of the energy consumption under the latency constraint is analyzed for random networks, where the nodes are uniformly placed in growing regions and the number of nodes goes to infinity. The special case of sum function computation and its delivery to a designated root node is considered first. A policy which achieves order-optimal average energy consumption in random networks subject to the given latency constraint is proposed. The scaling behavior of the optimal energy consumption depends on the path-loss exponent of wireless transmissions and the dimension of the Euclidean region where the nodes are placed. The policy is then extended to computation of a general class of functions which decompose according to maximal cliques of a proximity graph such as the $k$-nearest neighbor graph or the geometric random graph. The modified policy achiev...
Lan, Chunbo; Qin, Weiyang
2017-02-01
When a bistable energy harvester (BEH) is driven by weak random excitation, its harvesting efficiency will decrease due to the seldom occurrence of interwell motion. To overcome this defect, we developed an improved bistable energy harvester (IBEH) from BEH by adding a small magnet at the middle of two fixed magnets. It is proved that the attractive force originated from the additional magnet can pull down the potential barrier and shallow the potential well, but still keep the middle position of beam unstable. This can make jumping between potential wells easier. Thus IBEH can realize snap-through even at fairly weak excitation. The magnetic potential energy is given and the electromechanical equations are derived. Then the harvesting performance of IBEH under random excitation is studied. Validation experiments are designed and carried out. Comparisons prove that IBEH is preferable to BEH in harvesting random energy and can give out a high output voltage even at weak excitation. The size of additional magnet can be optimized to reach the best performance of IBEH.
Chaotic oscillation and random-number generation based on nanoscale optical-energy transfer
Naruse, Makoto; Kim, Song-Ju; Aono, Masashi; Hori, Hirokazu; Ohtsu, Motoichi
2014-08-01
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.
Energy-based models for environmental biotechnology.
Rodríguez, Jorge; Lema, Juan M; Kleerebezem, Robbert
2008-07-01
Environmental biotechnology is evolving. Current process objectives include the production of chemicals and/or energy carriers (biofuels) in addition to the traditional objective of removing pollutants from waste. To maximise product yields and minimise biomass production, future processes will rely on anaerobic microbial communities. Anaerobic processes are characterised by small Gibbs energy changes in the reactions catalysed, and this provides clear thermodynamic process boundaries. Here, a Gibbs-energy-based methodology is proposed for mathematical modelling of energy-limited anaerobic ecosystems. This methodology provides a basis for the description of microbial activities as a function of environmental factors, which will allow enhanced catalysis of specific reactions of interest for process development.
Models for the energy performance of low-energy houses
Andersen, Philip Hvidthøft Delff
such as mechanical ventilation, floor heating, and control of the lighting effect, the heat dynamics must be taken into account. Hence, this thesis provides methods for data-driven modeling of heat dynamics of modern buildings. While most of the work in this thesis is related to characterization of heat dynamics...... - referred to as "grey-box” modeling - one-step predictions can be generated and used for model validation by testing statistically whether the model describes all variation and dynamics observed in the data. The possibility of validating the model dynamics is a great advantage from the use of stochastic......-building. The building is well-insulated and features large modern energy-effcient windows and oor heating. These features lead to increased non-linear responses to solar radiation and longer time constants. The building is equipped with advanced control and measuring equipment. Experiments are designed and performed...
Nonlinear system modeling with random matrices: echo state networks revisited.
Zhang, Bai; Miller, David J; Wang, Yue
2012-01-01
Echo state networks (ESNs) are a novel form of recurrent neural networks (RNNs) that provide an efficient and powerful computational model approximating nonlinear dynamical systems. A unique feature of an ESN is that a large number of neurons (the "reservoir") are used, whose synaptic connections are generated randomly, with only the connections from the reservoir to the output modified by learning. Why a large randomly generated fixed RNN gives such excellent performance in approximating nonlinear systems is still not well understood. In this brief, we apply random matrix theory to examine the properties of random reservoirs in ESNs under different topologies (sparse or fully connected) and connection weights (Bernoulli or Gaussian). We quantify the asymptotic gap between the scaling factor bounds for the necessary and sufficient conditions previously proposed for the echo state property. We then show that the state transition mapping is contractive with high probability when only the necessary condition is satisfied, which corroborates and thus analytically explains the observation that in practice one obtains echo states when the spectral radius of the reservoir weight matrix is smaller than 1.
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.
2016-05-01
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
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
Modeling Innovations Advance Wind Energy Industry
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.
Stochastic Characteristics and Simulation of the Random Waypoint Mobility Model
Ahuja, A; Krishna, P Venkata
2012-01-01
Simulation results for Mobile Ad-Hoc Networks (MANETs) are fundamentally governed by the underlying Mobility Model. Thus it is imperative to find whether events functionally dependent on the mobility model 'converge' to well defined functions or constants. This shall ensure the long-run consistency among simulation performed by disparate parties. This paper reviews a work on the discrete Random Waypoint Mobility Model (RWMM), addressing its long run stochastic stability. It is proved that each model in the targeted discrete class of the RWMM satisfies Birkhoff's pointwise ergodic theorem [13], and hence time averaged functions on the mobility model surely converge. We also simulate the most common and general version of the RWMM to give insight into its working.
Simple model of stacking-fault energies
Stokbro, Kurt; Jacobsen, Lærke Wedel
1993-01-01
-density calculations of stacking-fault energies, and gives a simple way of understanding the calculated energy contributions from the different atomic layers in the stacking-fault region. The two parameters in the model describe the relative energy contributions of the s and d electrons in the noble and transition......A simple model for the energetics of stacking faults in fcc metals is constructed. The model contains third-nearest-neighbor pairwise interactions and a term involving the fourth moment of the electronic density of states. The model is in excellent agreement with recently published local...... metals, and thereby explain the pronounced differences in energetics in these two classes of metals. The model is discussed in the framework of the effective-medium theory where it is possible to find a functional form for the pair potential and relate the contribution associated with the fourth moment...
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.
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...... different from random sequences with the same dinucleotide distribution. For random sequences with the same mononucleotide distribution it has previously been shown that the native mRNA sequences have a lower predicted free energy, which indicates a more stable structure than random sequences. However......, dinucleotide content is important when assessing the significance of predicted free energy as the physical stability of RNA secondary structure is known to depend on dinucleotide base stacking energies. Even known RNA secondary structures, like tRNAs, can be shown to have predicted free energies...
Random Boolean network models and the yeast transcriptional network
Kauffman, Stuart; Peterson, Carsten; Samuelsson, Björn; Troein, Carl
2003-12-01
The recently measured yeast transcriptional network is analyzed in terms of simplified Boolean network models, with the aim of determining feasible rule structures, given the requirement of stable solutions of the generated Boolean networks. We find that for ensembles of generated models, those with canalyzing Boolean rules are remarkably stable, whereas those with random Boolean rules are only marginally stable. Furthermore, substantial parts of the generated networks are frozen, in the sense that they reach the same state regardless of initial state. Thus, our ensemble approach suggests that the yeast network shows highly ordered dynamics.
On a Stochastic Failure Model under Random Shocks
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.
Ensemble renormalization group for the random-field hierarchical model.
Decelle, Aurélien; Parisi, Giorgio; Rocchi, Jacopo
2014-03-01
The renormalization group (RG) methods are still far from being completely understood in quenched disordered systems. In order to gain insight into the nature of the phase transition of these systems, it is common to investigate simple models. In this work we study a real-space RG transformation on the Dyson hierarchical lattice with a random field, which leads to a reconstruction of the RG flow and to an evaluation of the critical exponents of the model at T=0. We show that this method gives very accurate estimations of the critical exponents by comparing our results with those obtained by some of us using an independent method.
Randomized shortest-path problems: two related models.
Saerens, Marco; Achbany, Youssef; Fouss, François; Yen, Luh
2009-08-01
This letter addresses the problem of designing the transition probabilities of a finite Markov chain (the policy) in order to minimize the expected cost for reaching a destination node from a source node while maintaining a fixed level of entropy spread throughout the network (the exploration). It is motivated by the following scenario. Suppose you have to route agents through a network in some optimal way, for instance, by minimizing the total travel cost-nothing particular up to now-you could use a standard shortest-path algorithm. Suppose, however, that you want to avoid pure deterministic routing policies in order, for instance, to allow some continual exploration of the network, avoid congestion, or avoid complete predictability of your routing strategy. In other words, you want to introduce some randomness or unpredictability in the routing policy (i.e., the routing policy is randomized). This problem, which will be called the randomized shortest-path problem (RSP), is investigated in this work. The global level of randomness of the routing policy is quantified by the expected Shannon entropy spread throughout the network and is provided a priori by the designer. Then, necessary conditions to compute the optimal randomized policy-minimizing the expected routing cost-are derived. Iterating these necessary conditions, reminiscent of Bellman's value iteration equations, allows computing an optimal policy, that is, a set of transition probabilities in each node. Interestingly and surprisingly enough, this first model, while formulated in a totally different framework, is equivalent to Akamatsu's model ( 1996 ), appearing in transportation science, for a special choice of the entropy constraint. We therefore revisit Akamatsu's model by recasting it into a sum-over-paths statistical physics formalism allowing easy derivation of all the quantities of interest in an elegant, unified way. For instance, it is shown that the unique optimal policy can be obtained by
Policy modeling for industrial energy use
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
Holographic dark energy in the DGP model
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.)
A stochastic model of randomly accelerated walkers for human mobility
Gallotti, Riccardo; Bazzani, Armando; Rambaldi, Sandro; Barthelemy, Marc
2016-08-01
Recent studies of human mobility largely focus on displacements patterns and power law fits of empirical long-tailed distributions of distances are usually associated to scale-free superdiffusive random walks called Lévy flights. However, drawing conclusions about a complex system from a fit, without any further knowledge of the underlying dynamics, might lead to erroneous interpretations. Here we show, on the basis of a data set describing the trajectories of 780,000 private vehicles in Italy, that the Lévy flight model cannot explain the behaviour of travel times and speeds. We therefore introduce a class of accelerated random walks, validated by empirical observations, where the velocity changes due to acceleration kicks at random times. Combining this mechanism with an exponentially decaying distribution of travel times leads to a short-tailed distribution of distances which could indeed be mistaken with a truncated power law. These results illustrate the limits of purely descriptive models and provide a mechanistic view of mobility.
Discrete random walk models for space-time fractional diffusion
Gorenflo, Rudolf; Mainardi, Francesco; Moretti, Daniele; Pagnini, Gianni; Paradisi, Paolo
2002-11-01
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 {alpha} is part of (0,2] and skewness {theta} (module{theta}{<=}{l_brace}{alpha},2-{alpha}{r_brace}), and the first-order time derivative with a Caputo derivative of order {beta} 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.
Random matrices and the six-vertex model
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...
High energy X-ray phase and dark-field imaging using a random absorption mask
Wang, Hongchang; Kashyap, Yogesh; Cai, Biao; Sawhney, Kawal
2016-07-01
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.
Mussard, Bastien; Jansen, Georg; Angyan, Janos
2016-01-01
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 co...
Revolutions in energy through modeling and simulation
Tatro, M.; Woodard, J.
1998-08-01
The development and application of energy technologies for all aspects from generation to storage have improved dramatically with the advent of advanced computational tools, particularly modeling and simulation. Modeling and simulation are not new to energy technology development, and have been used extensively ever since the first commercial computers were available. However, recent advances in computing power and access have broadened the extent and use, and, through increased fidelity (i.e., accuracy) of the models due to greatly enhanced computing power, the increased reliance on modeling and simulation has shifted the balance point between modeling and experimentation. The complex nature of energy technologies has motivated researchers to use these tools to understand better performance, reliability and cost issues related to energy. The tools originated in sciences such as the strength of materials (nuclear reactor containment vessels); physics, heat transfer and fluid flow (oil production); chemistry, physics, and electronics (photovoltaics); and geosciences and fluid flow (oil exploration and reservoir storage). Other tools include mathematics, such as statistics, for assessing project risks. This paper describes a few advancements made possible by these tools and explores the benefits and costs of their use, particularly as they relate to the acceleration of energy technology development. The computational complexity ranges from basic spreadsheets to complex numerical simulations using hardware ranging from personal computers (PCs) to Cray computers. In all cases, the benefits of using modeling and simulation relate to lower risks, accelerated technology development, or lower cost projects.
Nonparametric Estimation of Distributions in Random Effects Models
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.
Universality of Correlation Functions in Random Matrix Models of QCD
Jackson, A D; Verbaarschot, J J M
1997-01-01
We demonstrate the universality of the spectral correlation functions of a QCD inspired random matrix model that consists of a random part having the chiral structure of the QCD Dirac operator and a deterministic part which describes a schematic temperature dependence. We calculate the correlation functions analytically using the technique of Itzykson-Zuber integrals for arbitrary complex super-matrices. An alternative exact calculation for arbitrary matrix size is given for the special case of zero temperature, and we reproduce the well-known Laguerre kernel. At finite temperature, the microscopic limit of the correlation functions are calculated in the saddle point approximation. The main result of this paper is that the microscopic universality of correlation functions is maintained even though unitary invariance is broken by the addition of a deterministic matrix to the ensemble.
Random Matrix Model for Nakagami-Hoyt Fading
Kumar, Santosh; 10.1109/TIT.2010.2044060
2011-01-01
Random matrix model for the Nakagami-q (Hoyt) fading in multiple-input multiple-output (MIMO) communication channels with arbitrary number of transmitting and receiving antennas is considered. The joint probability density for the eigenvalues of H{\\dag}H (or HH{\\dag}), where H is the channel matrix, is shown to correspond to the Laguerre crossover ensemble of random matrices and is given in terms of a Pfaffian. Exact expression for the marginal density of eigenvalues is obtained as a series consisting of associated Laguerre polynomials. This is used to study the effect of fading on the Shannon channel capacity. Exact expressions for higher order density correlation functions are also given which can be used to study the distribution of channel capacity.
Prediction of Geological Subsurfaces Based on Gaussian Random Field Models
Abrahamsen, Petter
1997-12-31
During the sixties, random functions became practical tools for predicting ore reserves with associated precision measures in the mining industry. This was the start of the geostatistical methods called kriging. These methods are used, for example, in petroleum exploration. This thesis reviews the possibilities for using Gaussian random functions in modelling of geological subsurfaces. It develops methods for including many sources of information and observations for precise prediction of the depth of geological subsurfaces. The simple properties of Gaussian distributions make it possible to calculate optimal predictors in the mean square sense. This is done in a discussion of kriging predictors. These predictors are then extended to deal with several subsurfaces simultaneously. It is shown how additional velocity observations can be used to improve predictions. The use of gradient data and even higher order derivatives are also considered and gradient data are used in an example. 130 refs., 44 figs., 12 tabs.
A Meta Model for Domestic Energy Consumption
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.
Interacting Dark Energy Models and Observations
Shojaei, Hamed; Urioste, Jazmin
2017-01-01
Dark energy is one of the mysteries of the twenty first century. Although there are candidates resembling some features of dark energy, there is no single model describing all the properties of dark energy. Dark energy is believed to be the most dominant component of the cosmic inventory, but a lot of models do not consider any interaction between dark energy and other constituents of the cosmic inventory. Introducing an interaction will change the equation governing the behavior of dark energy and matter and creates new ways to explain cosmic coincidence problem. In this work we studied how the Hubble parameter and density parameters evolve with time in the presence of certain types of interaction. The interaction serves as a way to convert dark energy into matter to avoid a dark energy-dominated universe by creating new equilibrium points for the differential equations. Then we will use numerical analysis to predict the values of distance moduli at different redshifts and compare them to the values for the distance moduli obtained by WMAP (Wilkinson Microwave Anisotropy Probe). Undergraduate Student
Brookhaven buildings energy conservation optimization model
Carhart, S C; Mulherkar, S S; Sanborn, Y
1978-01-01
The Brookhaven Buildings Energy Conservation Optimization Model is a linear programming representation of energy use in buildings. Starting with engineering and economic data on cost and performance of energy technologies used in buildings, including both conversion devices (such as heat pumps) and structural improvements, the model constructs alternative flows for energy through the technologies to meet demands for space heating, air conditioning, thermal applications, and electric lighting and appliances. Alternative paths have different costs and efficiencies. Within constraints such as total demand for energy services, retirement of existing buildings, seasonal operation of certain devices, and others, the model calculates an optimal configuration of energy technologies in buildings. The penetration of the various basic technologies within this configuration is specified in considerable detail, covering new and retrofit markets for nine building types in four regions. Each market may choose from several appropriate conversion devices and four levels each of new and retrofit structural improvement. The principal applications for which the model was designed described briefly.
Chaotic oscillation and random-number generation based on nanoscale optical-energy transfer
Naruse, Makoto; Aono, Masashi; Hori, Hirokazu; Ohtsu, Motoichi
2014-01-01
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 (R...
Marginal and Random Intercepts Models for Longitudinal Binary Data with Examples from Criminology
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…
Marginal and Random Intercepts Models for Longitudinal Binary Data with Examples from Criminology
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…
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.…
Web software reliability modeling with random impulsive shocks
Jianfeng Yang; Ming Zhao; Wensheng Hu
2014-01-01
As the web-server based business is rapidly developed and popularized, how to evaluate and improve the reliability of web-servers has been extremely important. Although a large num-ber of software reliability growth models (SRGMs), including those combined with multiple change-points (CPs), have been available, these conventional SRGMs cannot be directly applied to web soft-ware reliability analysis because of the complex web operational profile. To characterize the web operational profile precisely, it should be realized that the workload of a web server is normal y non-homogeneous and often observed with the pattern of random impulsive shocks. A web software reliability model with random im-pulsive shocks and its statistical analysis method are developed. In the proposed model, the web server workload is characterized by a geometric Brownian motion process. Based on a real data set from IIS server logs of ICRMS website (www.icrms.cn), the proposed model is demonstrated to be powerful for estimating impulsive shocks and web software reliability.
Reconciling diversification: random pulse models of speciation and extinction.
Ricklefs, Robert E
2014-08-01
Inferring the underlying speciation-extinction dynamics of a clade from the phylogenetic relationships of contemporary species has proven difficult, primarily because the record of extinction is absent. Moreover, models of diversification tend to emphasize either time homogeneity or gradual trends in speciation and extinction rates. In contrast, the fossil records of many groups exhibit repeated increase and decrease of species richness within clades. Modeling this dynamic in the structure of phylogenetic trees has had limited application. Here, I consider the idea that pulses of diversification followed by declines in clade size-such pulses having short life spans in evolutionary time-occur frequently and more or less randomly among lineages. I suggest that this model might characterize diversification quite generally. Analyses of a recent phylogeny of the ovenbirds and treecreepers (Aves: Furnariidae) supports the random pulse model in that ancestral lineages at 15, 10, and 5 Ma exhibit diversification rate heterogeneity, but the sizes of ancestral and descendant lineages are uncorrelated. Simulations of such a process and its manifestations in reconstructed phylogenies would help to characterize diversification pulses in an abstract sense and draw attention to the underlying biological processes that produce them.
Genetic evaluation of European quails by random regression models
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.
Richly parameterized linear models additive, time series, and spatial models using random effects
Hodges, James S
2013-01-01
A First Step toward a Unified Theory of Richly Parameterized Linear ModelsUsing mixed linear models to analyze data often leads to results that are mysterious, inconvenient, or wrong. Further compounding the problem, statisticians lack a cohesive resource to acquire a systematic, theory-based understanding of models with random effects.Richly Parameterized Linear Models: Additive, Time Series, and Spatial Models Using Random Effects takes a first step in developing a full theory of richly parameterized models, which would allow statisticians to better understand their analysis results. The aut
Building Energy Model Development for Retrofit Homes
Chasar, David; McIlvaine, Janet; Blanchard, Jeremy; Widder, Sarah H.; Baechler, Michael C.
2012-09-30
Based on previous research conducted by Pacific Northwest National Laboratory and Florida Solar Energy Center providing technical assistance to implement 22 deep energy retrofits across the nation, 6 homes were selected in Florida and Texas for detailed post-retrofit energy modeling to assess realized energy savings (Chandra et al, 2012). However, assessing realized savings can be difficult for some homes where pre-retrofit occupancy and energy performance are unknown. Initially, savings had been estimated using a HERS Index comparison for these homes. However, this does not account for confounding factors such as occupancy and weather. This research addresses a method to more reliably assess energy savings achieved in deep energy retrofits for which pre-retrofit utility bills or occupancy information in not available. A metered home, Riverdale, was selected as a test case for development of a modeling procedure to account occupancy and weather factors, potentially creating more accurate estimates of energy savings. This “true up” procedure was developed using Energy Gauge USA software and post-retrofit homeowner information and utility bills. The 12 step process adjusts the post-retrofit modeling results to correlate with post-retrofit utility bills and known occupancy information. The “trued” post retrofit model is then used to estimate pre-retrofit energy consumption by changing the building efficiency characteristics to reflect the pre-retrofit condition, but keeping all weather and occupancy-related factors the same. This creates a pre-retrofit model that is more comparable to the post-retrofit energy use profile and can improve energy savings estimates. For this test case, a home for which pre- and post- retrofit utility bills were available was selected for comparison and assessment of the accuracy of the “true up” procedure. Based on the current method, this procedure is quite time intensive. However, streamlined processing spreadsheets or
Cosmological constraints on superconducting dark energy models
Keresztes, Zoltán; Harko, Tiberiu; Liang, Shi-Dong
2015-01-01
We consider cosmological tests of a scalar-vector-tensor gravitational model, in which the dark energy is included in the total action through a gauge invariant, electromagnetic type contribution. The ground state of dark energy, corresponding to a constant potential $V$ is a Bose-Einstein type condensate with spontaneously broken U(1) symmetry. In another words dark energy appears as a massive vector field emerging from a superposition of a massless vector and a scalar field, the latter corresponding to the Goldstone boson. Two particular cosmological models, corresponding to pure electric and pure magnetic type potentials, respectively are confronted with Type IA Supernovae and Hubble parameter data. In the electric case good fit is obtained along a narrow inclined stripe in the $\\Omega _{m}-\\Omega _{V}$ parameter plane, which includes the $\\Lambda $CDM limit. The other points on this admissible region represent superconducting dark energy as a sum of a cosmological constant and a time-evolving contribution...
a Bidirectional Reflectance Model for Non-Random Canopies.
Welles, Jonathan Mark
The general array model (GAR) is extended to calculate bidirectional reflectance (reflectance as a function of angle of view and angle of illumination) of a plant stand. The new model (BIGAR) defines the plant canopy as one or more foliage-containing ellipsoids arranged in any desired pattern. Foliage is assumed randomly distributed within each ellipsoid, with a specified distribution of inclination angles and random azimuthal orientation distribution. A method of specifying sub-ellipsoids that contain foliage of varying properties is discussed. Foliage is assumed to scatter radiation in a Lambertian fashion. The soil bidirectional reflectance is modelled separately as a boundary condition. The reflectance of any given grid point within the plant stand is calculated from the incident radiation (direct beam, diffuse sky, and diffuse scattered from the soil and foliage) and a view weighting factor that is based upon how much of the view is occupied by that particular grid point. Integrating this over a large number of grid locations provides a prediction of the bidirectional reflectance. Model predictions are compared with measurements in corn and soybean canopies at three stages of growth. The model does quite well in predicting the general shape and dynamics of the measured bidirectional reflectance factors, and rms errors are typically 10% to 15% (relative) of the integrated reflectance value. The effect of rows is evident in both the measurements and the model in the early part of the growing season. The presence of tassles in the corn may be the cause of unpredicted row effects later in the season. Predicted nadir reflectances are accurate for soybean, but are low for full cover corn. The presence of specular reflection causes the model to slightly underpredict reflectances looking toward the sun at large solar zenith angles.
A nuclear fragmentation energy deposition model
Ngo, D. M.; Wilson, J. W.; Fogarty, T. N.; Buck, W. W.; Townsend, L. W. (Principal Investigator)
1991-01-01
A formalism for target fragment transport is presented with application to energy loss spectra in thin silicon devices. A nuclear data base is recommended that agrees well with the measurements of McNulty et al. using surface barrier detectors. High-energy events observed by McNulty et al., which are not predicted by intranuclear cascade models, are well represented by the present work.
Extra Dimensions and Vacuum Dark Energy Models
CHEN Chi-Yi; SHEN You-Gen
2004-01-01
@@ The role of vacuum energy or cosmological constant in cosmology is discussed in a kind of nontrivial higherdimensional model. Under the framework of Einstein's gravity, we obtain the corresponding equations of motion and find that the cosmological constant and vacuum energy in the full regime does not drive its acceleration, but decelerates the expansion of the universe. The dimension of space is required to be n = 3 if we regard vacuum energy or cosmological constant as the candidate to drive the accelerated expansion of the universe.
Solar energy estimation using REST2 model
M. Rizwan, Majid Jamil, D. P. Kothari
2010-03-01
Full Text Available The network of solar energy measuring stations is relatively rare through out the world. In India, only IMD (India Meteorological Department Pune provides data for quite few stations, which is considered as the base data for research purposes. However, hourly data of measured energy is not available, even for those stations where measurement has already been done. Due to lack of hourly measured data, the estimation of solar energy at the earth’s surface is required. In the proposed study, hourly solar energy is estimated at four important Indian stations namely New Delhi, Mumbai, Pune and Jaipur keeping in mind their different climatic conditions. For this study, REST2 (Reference Evaluation of Solar Transmittance, 2 bands, a high performance parametric model for the estimation of solar energy is used. REST2 derivation uses the two-band scheme as used in the CPCR2 (Code for Physical Computation of Radiation, 2 bands but CPCR2 does not include NO2 absorption, which is an important parameter for estimating solar energy. In this study, using ground measurements during 1986-2000 as reference, a MATLAB program is written to evaluate the performance of REST2 model at four proposed stations. The solar energy at four stations throughout the year is estimated and compared with CPCR2. The results obtained from REST2 model show the good agreement against the measured data on horizontal surface. The study reveals that REST2 models performs better and evaluate the best results as compared to the other existing models under cloudless sky for Indian climatic conditions.
Comprehensive analytical model to characterize randomness in optical waveguides.
Zhou, Junhe; Gallion, Philippe
2016-04-01
In this paper, the coupled mode theory (CMT) is used to derive the corresponding stochastic differential equations (SDEs) for the modal amplitude evolution inside optical waveguides with random refractive index variations. Based on the SDEs, the ordinary differential equations (ODEs) are derived to analyze the statistics of the modal amplitudes, such as the optical power and power variations as well as the power correlation coefficients between the different modal powers. These ODEs can be solved analytically and therefore, it greatly simplifies the analysis. It is demonstrated that the ODEs for the power evolution of the modes are in excellent agreement with the Marcuse' coupled power model. The higher order statistics, such as the power variations and power correlation coefficients, which are not exactly analyzed in the Marcuse' model, are discussed afterwards. Monte-Carlo simulations are performed to demonstrate the validity of the analytical model.
Multivariate parametric random effect regression models for fecundability studies.
Ecochard, R; Clayton, D G
2000-12-01
Delay until conception is generally described by a mixture of geometric distributions. Weinberg and Gladen (1986, Biometrics 42, 547-560) proposed a regression generalization of the beta-geometric mixture model where covariates effects were expressed in terms of contrasts of marginal hazards. Scheike and Jensen (1997, Biometrics 53, 318-329) developed a frailty model for discrete event times data based on discrete-time analogues of Hougaard's results (1984, Biometrika 71, 75-83). This paper is on a generalization to a three-parameter family distribution and an extension to multivariate cases. The model allows the introduction of explanatory variables, including time-dependent variables at the subject-specific level, together with a choice from a flexible family of random effect distributions. This makes it possible, in the context of medically assisted conception, to include data sources with multiple pregnancies (or attempts at pregnancy) per couple.
SIRS Dynamics on Random Networks: Simulations and Analytical Models
Rozhnova, Ganna; Nunes, Ana
The standard pair approximation equations (PA) for the Susceptible-Infective-Recovered-Susceptible (SIRS) model of infection spread on a network of homogeneous degree k predict a thin phase of sustained oscillations for parameter values that correspond to diseases that confer long lasting immunity. Here we present a study of the dependence of this oscillatory phase on the parameter k and of its relevance to understand the behaviour of simulations on networks. For k = 4, we compare the phase diagram of the PA model with the results of simulations on regular random graphs (RRG) of the same degree. We show that for parameter values in the oscillatory phase, and even for large system sizes, the simulations either die out or exhibit damped oscillations, depending on the initial conditions. This failure of the standard PA model to capture the qualitative behaviour of the simulations on large RRGs is currently being investigated.
A PRACTICAL MODEL FOR THE DECAY OF RANDOM WAVES ON MUDDY BEACHES
NIU Xiao-jing; YU Xi-ping
2008-01-01
A practical model has been developed for the propagation and decay of random waves on muddy beaches. In the model, an irregular wave train is characterized by its root-mean-squared wave height, mean wave frequency and mean wave direction. It is also assumed that the wave spectrum is narrow-banded in terms of both frequency and direction. Transformation of root-mean-squared wave height is derived from the conservation of energy flux for individual wave components. Energy dissipation is considered due to both wave breaking and the dynamics response of muddy seabed. The model is applied to waves on the muddy beach at Hangzhou Bay, and the numerical results obtained are shown to be acceptably accurate as comparing with available field data.
Coupling dark energy with Standard Model states
Bento, M C; Bertolami, O
2009-01-01
In this contribution one examines the coupling of dark energy to the gauge fields, to neutrinos, and to the Higgs field. In the first case, one shows how a putative evolution of the fundamental couplings of strong and weak interactions via coupling to dark energy through a generalized Bekenstein-type model may cause deviations on the statistical nuclear decay Rutherford-Soddy law. Existing bounds for the weak interaction exclude any significant deviation. For neutrinos, a perturbative approach is developed which allows for considering viable varying mass neutrino models coupled to any quintessence-type field. The generalized Chaplygin model is considered as an example. For the coupling with the Higgs field one obtains an interesting cosmological solution which includes the unification of dark energy and dark matter.
Random field model reveals structure of the protein recombinational landscape.
Philip A Romero
Full Text Available We are interested in how intragenic recombination contributes to the evolution of proteins and how this mechanism complements and enhances the diversity generated by random mutation. Experiments have revealed that proteins are highly tolerant to recombination with homologous sequences (mutation by recombination is conservative; more surprisingly, they have also shown that homologous sequence fragments make largely additive contributions to biophysical properties such as stability. Here, we develop a random field model to describe the statistical features of the subset of protein space accessible by recombination, which we refer to as the recombinational landscape. This model shows quantitative agreement with experimental results compiled from eight libraries of proteins that were generated by recombining gene fragments from homologous proteins. The model reveals a recombinational landscape that is highly enriched in functional sequences, with properties dominated by a large-scale additive structure. It also quantifies the relative contributions of parent sequence identity, crossover locations, and protein fold to the tolerance of proteins to recombination. Intragenic recombination explores a unique subset of sequence space that promotes rapid molecular diversification and functional adaptation.
Interpreting parameters in the logistic regression model with random effects
Larsen, Klaus; Petersen, Jørgen Holm; Budtz-Jørgensen, Esben
2000-01-01
interpretation, interval odds ratio, logistic regression, median odds ratio, normally distributed random effects......interpretation, interval odds ratio, logistic regression, median odds ratio, normally distributed random effects...
A General Random Walk Model of Molecular Motor
WANG Xian-Ju; AI Bao-Quan; LIU Guo-Tao; LIU Liang-Gang
2003-01-01
A general random walk model framework is presented which can be used to statistically describe the internaldynamics and external mechanical movement of molecular motors along filament track. The motion of molecular motorin a periodic potential and a constant force is considered. We show that the molecular motor's movement becomesslower with the potential barrier increasing, but if the forceis increased, the molecular motor's movement becomesfaster. The relation between the effective rate constant and the potential barrier's height, and that between the effectiverate constant and the value of the force are discussed. Our results are consistent with the experiments and relevanttheoretical consideration, and can be used to explain some physiological phenomena.
Critical Interfaces in the Random-Bond Potts Model
Jacobsen, Jesper L.; Le Doussal, Pierre; Picco, Marco; Santachiara, Raoul; Wiese, Kay Jörg
2009-02-01
We study geometrical properties of interfaces in the random-temperature q-states Potts model as an example of a conformal field theory weakly perturbed by quenched disorder. Using conformal perturbation theory in q-2 we compute the fractal dimension of Fortuin-Kasteleyn (FK) domain walls. We also compute it numerically both via the Wolff cluster algorithm for q=3 and via transfer-matrix evaluations. We also obtain numerical results for the fractal dimension of spin clusters interfaces for q=3. These are found numerically consistent with the duality κspinκFK=16 as expressed in putative SLE parameters.
Creep motion in a random-field Ising model.
Roters, L; Lübeck, S; Usadel, K D
2001-02-01
We analyze numerically a moving interface in the random-field Ising model which is driven by a magnetic field. Without thermal fluctuations the system displays a depinning phase transition, i.e., the interface is pinned below a certain critical value of the driving field. For finite temperatures the interface moves even for driving fields below the critical value. In this so-called creep regime the dependence of the interface velocity on the temperature is expected to obey an Arrhenius law. We investigate the details of this Arrhenius behavior in two and three dimensions and compare our results with predictions obtained from renormalization group approaches.
On estimation of survival function under random censoring model
JIANG; Jiancheng(蒋建成); CHENG; Bo(程博); WU; Xizhi(吴喜之)
2002-01-01
We study an estimator of the survival function under the random censoring model. Bahadur-type representation of the estimator is obtained and asymptotic expression for its mean squared errors is given, which leads to the consistency and asymptotic normality of the estimator. A data-driven local bandwidth selection rule for the estimator is proposed. It is worth noting that the estimator is consistent at left boundary points, which contrasts with the cases of density and hazard rate estimation. A Monte Carlo comparison of different estimators is made and it appears that the proposed data-driven estimators have certain advantages over the common Kaplan-Meier estmator.
A random resistor network model of voltage trimming
Grimaldi, C [Laboratoire de Production Microtechnique, Ecole Polytechnique Federale de Lausanne, CH-1015 Lausanne (Switzerland); Maeder, T [Laboratoire de Production Microtechnique, Ecole Polytechnique Federale de Lausanne, CH-1015 Lausanne (Switzerland); Ryser, P [Laboratoire de Production Microtechnique, Ecole Polytechnique Federale de Lausanne, CH-1015 Lausanne (Switzerland); Straessler, S [Laboratoire de Production Microtechnique, Ecole Polytechnique Federale de Lausanne, CH-1015 Lausanne (Switzerland)
2004-08-07
In industrial applications, the controlled adjustment (trimming) of resistive elements via the application of high voltage pulses is a promising technique, with several advantages with respect to more classical approaches such as the laser cutting method. The microscopic processes governing the response to high voltage pulses depend on the nature of the resistor and on the interaction with the local environment. Here we provide a theoretical statistical description of voltage discharge effects on disordered composites by considering random resistor network models with different properties and processes due to the voltage discharge. We compare standard percolation results with biased percolation effects and provide a tentative explanation of the different scenarios observed during trimming processes.
Metamaterial Model of Tachyonic Dark Energy
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.
Interacting Dark Energy Models -- Scalar Linear Perturbations
Perico, E L D
2016-01-01
We extend the dark sector interacting models assuming the dark energy as the sum of independent contributions $\\rho_{\\Lambda} =\\sum_i\\rho_{\\Lambda i}$, associated with (and interacting with) each of the $i$ material species. We derive the linear scalar perturbations for two interacting dark energy scenarios, modeling its cosmic evolution and identifying their different imprints in the CMB and matter power spectrum. Our treatment was carried out for two phenomenological motivated expressions of the dark energy density, $\\rho_\\Lambda(H^2)$ and $\\rho_\\Lambda(R)$. The $\\rho_\\Lambda(H^2)$ description turned out to be a full interacting model, i.e., the dark energy interacts with everyone material species in the universe, whereas the $\\rho_\\Lambda(R)$ description only leads to interactions between dark energy and the non-relativistic matter components; which produces different imprints of the two models on the matter power spectrum. A comparison with the Planck 2015 data was made in order to constrain the free para...
Raytracing simulations of coupled dark energy models
Pace, Francesco; Moscardini, Lauro; Bacon, David; Crittenden, Robert
2014-01-01
Dark matter and dark energy are usually assumed to be independent, coupling only gravitationally. An extension to this simple picture is to model dark energy as a scalar field which is directly coupled to the cold dark matter fluid. Such a non-trivial coupling in the dark sector leads to a fifth force and a time-dependent dark matter particle mass. In this work we examine the impact that dark energy-dark matter couplings have on weak lensing statistics by constructing realistic simulated weak-lensing maps using raytracing techniques through a suite of N-body cosmological simulations. We construct maps for an array of different lensing quantities, covering a range of scales from a few arcminutes to several degrees. The concordance $\\Lambda$CDM model is compared to different coupled dark energy models, described either by an exponential scalar field potential (standard coupled dark energy scenario) or by a SUGRA potential (bouncing model). We analyse several statistical quantities, in particular the power spect...
Geometric Models for Isotropic Random Porous Media: A Review
Helmut Hermann
2014-01-01
Full Text Available Models for random porous media are considered. The models are isotropic both from the local and the macroscopic point of view; that is, the pores have spherical shape or their surface shows piecewise spherical curvature, and there is no macroscopic gradient of any geometrical feature. Both closed-pore and open-pore systems are discussed. The Poisson grain model, the model of hard spheres packing, and the penetrable sphere model are used; variable size distribution of the pores is included. A parameter is introduced which controls the degree of open-porosity. Besides systems built up by a single solid phase, models for porous media with the internal surface coated by a second phase are treated. Volume fraction, surface area, and correlation functions are given explicitly where applicable; otherwise numerical methods for determination are described. Effective medium theory is applied to calculate physical properties for the models such as isotropic elastic moduli, thermal and electrical conductivity, and static dielectric constant. The methods presented are exemplified by applications: small-angle scattering of systems showing fractal-like behavior in limited ranges of linear dimension, optimization of nanoporous insulating materials, and improvement of properties of open-pore systems by atomic layer deposition of a second phase on the internal surface.
Rigorously testing multialternative decision field theory against random utility models.
Berkowitsch, Nicolas A J; Scheibehenne, Benjamin; Rieskamp, Jörg
2014-06-01
Cognitive models of decision making aim to explain the process underlying observed choices. Here, we test a sequential sampling model of decision making, multialternative decision field theory (MDFT; Roe, Busemeyer, & Townsend, 2001), on empirical grounds and compare it against 2 established random utility models of choice: the probit and the logit model. Using a within-subject experimental design, participants in 2 studies repeatedly choose among sets of options (consumer products) described on several attributes. The results of Study 1 showed that all models predicted participants' choices equally well. In Study 2, in which the choice sets were explicitly designed to distinguish the models, MDFT had an advantage in predicting the observed choices. Study 2 further revealed the occurrence of multiple context effects within single participants, indicating an interdependent evaluation of choice options and correlations between different context effects. In sum, the results indicate that sequential sampling models can provide relevant insights into the cognitive process underlying preferential choices and thus can lead to better choice predictions.
Energy harvesting in a quad-stable harvester subjected to random excitation
Zhi-yong Zhou
2016-02-01
Full Text Available In response to the defects of bi-stable energy harvester (BEH, we develop a novel quad-stable energy harvester (QEH to improve harvesting efficiency. The device is made up of a bimorph cantilever beam having a tip magnet and three external fixed magnets. By adjusting the positions of the fixed magnets and the distances between the tip magnet and the fixed ones, the quad-stable equilibrium positions can emerge. The potential energy shows that the barriers of the QEH are lower than those of the BEH for the same separation distance. Experiment results reveal that the QEH can realize snap-through easier and make a dense snap-through in response under random excitation. Moreover, its strain and voltage both become large for snap-through between the nonadjacent stable positions. There exists an optimal separation distance for different excitation intensities.
Probability distribution of the free energy of a directed polymer in a random medium
Brunet, Éric; Derrida, Bernard
2000-06-01
We calculate exactly the first cumulants of the free energy of a directed polymer in a random medium for the geometry of a cylinder. By using the fact that the nth moment of the partition function is given by the ground-state energy of a quantum problem of n interacting particles on a ring of length L, we write an integral equation allowing to expand these moments in powers of the strength of the disorder γ or in powers of n. For n small and n~(Lγ)-1/2, the moments take a scaling form which allows us to describe all the fluctuations of order 1/L of the free energy per unit length of the directed polymer. The distribution of these fluctuations is the same as the one found recently in the asymmetric exclusion process, indicating that it is characteristic of all the systems described by the Kardar-Parisi-Zhang equation in 1+1 dimensions.
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.
The multilevel p2 model : A random effects model for the analysis of multiple social networks
Zijlstra, B.J.H.; van Duijn, M.A.J.; Snijders, T.A.B.
2006-01-01
The p2 model is a random effects model with covariates for the analysis of binary directed social network data coming from a single observation of a social network. Here, a multilevel variant of the p2 model is proposed for the case of multiple observations of social networks, for example, in a samp
OSeMOSYS Energy Modeling Using an Extended UTOPIA Model
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…
Hartley, Madeline K; Vine, Seanna; Walsh, Elizabeth; Avrantinis, Sara; Daub, G William; Cave, Robert J
2016-03-03
We investigate several representative density functional theory approaches for the calculation of relative activation energies and free energies of a set of model pericyclic reactions, some of which have been studied experimentally. In particular, we use a standard hybrid functional (B3LYP), the same hybrid functional augmented with a basis set superposition error and dispersion correction, a meta-hybrid functional developed to treat transition states and weak interactions (M06-2X), and the recently implemented random phase approximation (RPA) based on Kohn-Sham orbitals from conventional density functional theory by Furche and co-workers. We apply these methods to calculate relative activation energies and estimated free energies for the amide acetal Claisen rearrangement. We focus on relative activation energies to assess the effects of steric and weak interactions in the various methods and compare with experiment where possible. We also discuss the advantages of using this set of reactions as a test bed for the comparison of treatments of weak interactions. We conclude that all methods yield similar trends in relative reactivity, but the RPA yields results in best agreement with the experimental values.
Munira, Kamaram [Center for Materials for Information Technology, University of Alabama, Tuscaloosa, Alabama 35401 (United States); Visscher, P. B., E-mail: visscher@ua.edu [Center for Materials for Information Technology, University of Alabama, Tuscaloosa, Alabama 35401 (United States); Department of Physics and Astronomy, University of Alabama, Tuscaloosa, Alabama 35401 (United States)
2015-05-07
To make a useful spin-transfer torque magnetoresistive random-access memory (STT-MRAM) device, it is necessary to be able to calculate switching rates, which determine the error rates of the device. In a single-macrospin model, one can use a Fokker-Planck equation to obtain a low-current thermally activated rate ∝exp(−E{sub eff}/k{sub B}T). Here, the effective energy barrier E{sub eff} scales with the single-macrospin energy barrier KV, where K is the effective anisotropy energy density and V the volume. A long-standing paradox in this field is that the actual energy barrier appears to be much smaller than this. It has been suggested that incoherent motions may lower the barrier, but this has proved difficult to quantify. In the present paper, we show that the coherent precession has a magnetostatic instability, which allows quantitative estimation of the energy barrier and may resolve the paradox.
Energy modelling for economies in transition
Van Leeuwen, M.L.; Velthuijsen, J.W. [Foundation for Economic Research SEO, University of Amsterdam UvA, Amsterdam (Netherlands); Van Oostvoorn, F.; Voogt, M. [ECN Policy Study, Petten (Netherlands)
1998-12-31
The model system composed of a Computable General Equilibrium (CGE) E3 model and the least-cost energy sector model Energy Flow Optimization Model - Environment (EFOM-ENV) proved to be a useful support in developing long-term scenarios for several Central European and Eastern European (CEE) countries. Calculation results obtained from using the model.system could be used to support energy policy decisions in the framework of different possible future developments in energy demand and supply and related emissions, which is also consistent with macro-economic developments in the national economies. Also, and most important, the developments within the national (transition) economy could be made consistent with external developments (on a world and European Union (EU) level) that are envisioned in EC-scenarios. This facilitates the analysis of an increasing convergence process of different CEE countries towards the EU and could be useful in the policy dialogue on convergence. Empirical studies with the model system have shown that the interrelations between macro-economic indicators and important factors determining energy supply and demand could be dealt with in a transparent way. An assessment could be made of the impact of changes in economic structure, employment rate, trade balance, social security and public spending on the structure of energy demand, fuel mix, capacity requirements and related energy costs, and vice versa. Specific policy issues such as a restructuring of the Polish coal industry or determining the scope for CO2 reduction in Romania could be addressed and instruments could be identified to encounter these issues. Especially for policy makers in transition economies who are faced with many interactive changes, it is important to have a realistic insight in the scope and restrictions of future policy. Ambitions are often very high, but reaching certain objectives could be conflicting with others. Results obtained from calculations with the model
Szeliski, Richard; Zabih, Ramin; Scharstein, Daniel; Veksler, Olga; Kolmogorov, Vladimir; Agarwala, Aseem; Tappen, Marshall; Rother, Carsten
2008-06-01
Among the most exciting advances in early vision has been the development of efficient energy minimization algorithms for pixel-labeling tasks such as depth or texture computation. It has been known for decades that such problems can be elegantly expressed as Markov random fields, yet the resulting energy minimization problems have been widely viewed as intractable. Recently, algorithms such as graph cuts and loopy belief propagation (LBP) have proven to be very powerful: for example, such methods form the basis for almost all the top-performing stereo methods. However, the tradeoffs among different energy minimization algorithms are still not well understood. In this paper we describe a set of energy minimization benchmarks and use them to compare the solution quality and running time of several common energy minimization algorithms. We investigate three promising recent methods graph cuts, LBP, and tree-reweighted message passing in addition to the well-known older iterated conditional modes (ICM) algorithm. Our benchmark problems are drawn from published energy functions used for stereo, image stitching, interactive segmentation, and denoising. We also provide a general-purpose software interface that allows vision researchers to easily switch between optimization methods. Benchmarks, code, images, and results are available at http://vision.middlebury.edu/MRF/.
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.
Economic Modeling of Compressed Air Energy Storage
Rui Bo
2013-04-01
Full Text Available Due to the variable nature of wind resources, the increasing penetration level of wind power will have a significant impact on the operation and planning of the electric power system. Energy storage systems are considered an effective way to compensate for the variability of wind generation. This paper presents a detailed production cost simulation model to evaluate the economic value of compressed air energy storage (CAES in systems with large-scale wind power generation. The co-optimization of energy and ancillary services markets is implemented in order to analyze the impacts of CAES, not only on energy supply, but also on system operating reserves. Both hourly and 5-minute simulations are considered to capture the economic performance of CAES in the day-ahead (DA and real-time (RT markets. The generalized network flow formulation is used to model the characteristics of CAES in detail. The proposed model is applied on a modified IEEE 24-bus reliability test system. The numerical example shows that besides the economic benefits gained through energy arbitrage in the DA market, CAES can also generate significant profits by providing reserves, compensating for wind forecast errors and intra-hour fluctuation, and participating in the RT market.
Random spatial processes and geostatistical models for soil variables
Lark, R. M.
2009-04-01
Geostatistical models of soil variation have been used to considerable effect to facilitate efficient and powerful prediction of soil properties at unsampled sites or over partially sampled regions. Geostatistical models can also be used to investigate the scaling behaviour of soil process models, to design sampling strategies and to account for spatial dependence in the random effects of linear mixed models for spatial variables. However, most geostatistical models (variograms) are selected for reasons of mathematical convenience (in particular, to ensure positive definiteness of the corresponding variables). They assume some underlying spatial mathematical operator which may give a good description of observed variation of the soil, but which may not relate in any clear way to the processes that we know give rise to that observed variation in the real world. In this paper I shall argue that soil scientists should pay closer attention to the underlying operators in geostatistical models, with a view to identifying, where ever possible, operators that reflect our knowledge of processes in the soil. I shall illustrate how this can be done in the case of two problems. The first exemplar problem is the definition of operators to represent statistically processes in which the soil landscape is divided into discrete domains. This may occur at disparate scales from the landscape (outcrops, catchments, fields with different landuse) to the soil core (aggregates, rhizospheres). The operators that underly standard geostatistical models of soil variation typically describe continuous variation, and so do not offer any way to incorporate information on processes which occur in discrete domains. I shall present the Poisson Voronoi Tessellation as an alternative spatial operator, examine its corresponding variogram, and apply these to some real data. The second exemplar problem arises from different operators that are equifinal with respect to the variograms of the
Genetic parameters for various random regression models to describe the weight data of pigs
Huisman, A.E.; Veerkamp, R.F.; Arendonk, van J.A.M.
2002-01-01
Various random regression models have been advocated for the fitting of covariance structures. It was suggested that a spline model would fit better to weight data than a random regression model that utilizes orthogonal polynomials. The objective of this study was to investigate which kind of random
Genetic parameters for different random regression models to describe weight data of pigs
Huisman, A.E.; Veerkamp, R.F.; Arendonk, van J.A.M.
2001-01-01
Various random regression models have been advocated for the fitting of covariance structures. It was suggested that a spline model would fit better to weight data than a random regression model that utilizes orthogonal polynomials. The objective of this study was to investigate which kind of random
Large Representation Recurrences in Large N Random Unitary Matrix Models
Karczmarek, Joanna L
2011-01-01
In a random unitary matrix model at large N, we study the properties of the expectation value of the character of the unitary matrix in the rank k symmetric tensor representation. We address the problem of whether the standard semiclassical technique for solving the model in the large N limit can be applied when the representation is very large, with k of order N. We find that the eigenvalues do indeed localize on an extremum of the effective potential; however, for finite but sufficiently large k/N, it is not possible to replace the discrete eigenvalue density with a continuous one. Nonetheless, the expectation value of the character has a well-defined large N limit, and when the discreteness of the eigenvalues is properly accounted for, it shows an intriguing approximate periodicity as a function of k/N.
Auxiliary Parameter MCMC for Exponential Random Graph Models
Byshkin, Maksym; Stivala, Alex; Mira, Antonietta; Krause, Rolf; Robins, Garry; Lomi, Alessandro
2016-11-01
Exponential random graph models (ERGMs) are a well-established family of statistical models for analyzing social networks. Computational complexity has so far limited the appeal of ERGMs for the analysis of large social networks. Efficient computational methods are highly desirable in order to extend the empirical scope of ERGMs. In this paper we report results of a research project on the development of snowball sampling methods for ERGMs. We propose an auxiliary parameter Markov chain Monte Carlo (MCMC) algorithm for sampling from the relevant probability distributions. The method is designed to decrease the number of allowed network states without worsening the mixing of the Markov chains, and suggests a new approach for the developments of MCMC samplers for ERGMs. We demonstrate the method on both simulated and actual (empirical) network data and show that it reduces CPU time for parameter estimation by an order of magnitude compared to current MCMC methods.
Development of an energy storage tank model
Buckley, Robert Christopher
A linearized, one-dimensional finite difference model employing an implicit finite difference method for energy storage tanks is developed, programmed with MATLAB, and demonstrated for different applications. A set of nodal energy equations is developed by considering the energy interactions on a small control volume. The general method of solving these equations is described as are other features of the simulation program. Two modeling applications are presented: the first using a hot water storage tank with a solar collector and an absorption chiller to cool a building in the summer, the second using a molten salt storage system with a solar collector and steam power plant to generate electricity. Recommendations for further study as well as all of the source code generated in the project are also provided.
Modeling elements of energy systems for thermal energy transportation
Shurygin A. M.
2016-12-01
Full Text Available Heating industrial facilities and the residential sector in recent years is the economic and technical challenge. It has been noted that the efficiency of the heat generating equipment depends not only on its sophistication, fuel type, but also on work of the distributing network taking into account the thermal, hydraulic losses, characteristics and modes of use of heating objects – buildings and technological processes. Possibility of supplying maximum heat flow from the heating system considering mismatch of highs and types of resources consumed from individual consumers should be provided by the right choice of energy equipment set, as well as bandwidth of transport systems and possibility of its regulation. It is important not just to configure the system to work effectively in the current mode (usually at the maximum load, but in the entire load range, as the calculated mode often takes a relatively small portion of the operating time. Thus, the efficiency of heating systems is largely determined by the method used for its control, including the possibility of regulating the main units and elements of the system. The paper considers the factors affecting the system efficiency. Mathematical models of the system elements allowing adjust the amount of released heat energy for consumers have been presented. Separately the mathematical model of the control system of electric drive vehicles used in the system has been considered and implemented.
Energy Centroids of Spin $I$ States by Random Two-body Interactions
Zhao, Y M; Ogawa, K
2005-01-01
In this paper we study the behavior of energy centroids (denoted as $\\bar{E_I}$) of spin $I$ states in the presence of random two-body interactions, for systems ranging from very simple systems (e.g. single-$j$ shell for very small $j$) to very complicated systems (e.g., many-$j$ shells with different parities and with isospin degree of freedom). Regularities of $\\bar{E_I}$'s discussed in terms of the so-called geometric chaoticity (or quasi-randomness of two-body coefficients of fractional parentage) in earlier works are found to hold even for very simple systems in which one cannot assume the geometric chaoticity. It is shown that the inclusion of isospin and parity does not "break" the regularities of $\\bar{E_I}$'s.
The Sustainable Energy Utility (SEU) Model for Energy Service Delivery
Houck, Jason; Rickerson, Wilson
2009-01-01
Climate change, energy price spikes, and concerns about energy security have reignited interest in state and local efforts to promote end-use energy efficiency, customer-sited renewable energy, and energy conservation. Government agencies and utilities have historically designed and administered such demand-side measures, but innovative…
Energy Blocks--A Physical Model for Teaching Energy Concepts
Hertting, Scott
2016-01-01
Most physics educators would agree that energy is a very useful, albeit abstract topic. It is therefore important to use various methods to help the student internalize the concept of energy itself and its related ideas. These methods include using representations such as energy bar graphs, energy pie charts, or energy tracking diagrams.…
Learning curves in energy planning models
Barreto, L.; Kypreos, S. [Paul Scherrer Inst. (PSI), Villigen (Switzerland)
1999-08-01
This study describes the endogenous representation of investment cost learning curves into the MARKAL energy planning model. A piece-wise representation of the learning curves is implemented using Mixed Integer Programming. The approach is briefly described and some results are presented. (author) 3 figs., 5 refs.
Numerical modelling in wave energy conversion systems
El Marjani, A. [Labo. de Turbomachines, Ecole Mohammadia d' Ingenieurs (EMI), Universite Mohammed V Agdal, Av Ibn Sina, B.P. 765 Agdal, Rabat (Morocco); Castro Ruiz, F.; Rodriguez, M.A.; Parra Santos, M.T. [Depto. de Ingenieria Energetica y Fluidomecanica, Escuela Tecnica Superior de Ingenieros Industriales, Universidad de Valladolid, Paseo del Cauce s/n, E-47011 Valladolid (Spain)
2008-08-15
This paper deals with a numerical modelling devoted to predict the flow characteristics in the components of an oscillating water column (OWC) system used for the wave energy capture. In the present paper, the flow behaviour is modelled by using the FLUENT code. Two numerical flow models have been elaborated and tested independently in the geometries of an air chamber and a turbine, which is chosen of a radial impulse type. The flow is assumed to be three-dimensional (3D), viscous, turbulent and unsteady. The FLUENT code is used with a solver of the coupled conservation equations of mass, momentum and energy, with an implicit time scheme and with the adoption of the dynamic mesh and the sliding mesh techniques in areas of moving surfaces. Turbulence is modelled with the k-{epsilon} model. The obtained results indicate that the developed models are well suitable to analyse the air flows both in the air chamber and in the turbine. The performances associated with the energy transfer processes have been well predicted. For the turbine, the numerical results of pressure and torque were compared to the experimental ones. Good agreements between these results have been observed. (author)
Kinza, Michael; Honerkamp, Carsten
2015-07-01
In the derivation of low-energy effective models for solids targeting the bands near the Fermi level, the constrained random-phase approximation (cRPA) has become an appreciated tool to compute the effective interactions. The Wick-ordered constrained functional renormalization group (cfRG) generalizes the cRPA approach by including all interaction channels in an unbiased way. Here we present applications of the cfRG to two simple multiband systems and compare the resulting effective interactions to the cRPA. First, we consider a multiband model for monolayer graphene, where we integrate out the σ bands to get an effective theory for π bands. It turns out that terms beyond cRPA are strongly suppressed by the different x y -plane reflection symmetry of the bands. In our model the cfRG corrections to cRPA become visible when one disturbs this symmetry difference slightly, however, without qualitative changes. This study shows that the embedding or layering of two-dimensional electronic systems can alter the effective interaction parameters beyond what is expected from screening considerations. The second example is a one-dimensional model for a diatomic system reminiscent of a CuO chain, where we consider an effective theory for Cu 3 d -like orbitals. Here the fRG data shows relevant and qualitative corrections compared to the cRPA results. We argue that the new interaction terms affect the magnetic properties of the low-energy model.
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/s2 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.
A generic statistical model of hydride formation in a random alloy
Zhdanov, Vladimir P.
2016-09-01
Hydride formation in metals (e.g. in Pd), accompanied by a hysteresis loop in the absorption isotherms, is one of the generic examples of first-order phase transitions (FOPTs). During the last decade, the corresponding experimental studies, driven by applications related to hydrogen storage, have shifted towards metal particles sized from a few nanometers to micrometers in general and to alloyed particles of these sizes in particular. The understanding of hydride formation in alloys is, however, still far from complete. Herein, a statistical model of hydride formation in a random alloy is presented. The model is focused on the situation when this process is favorable in metal 1 (e.g. Pd) and shows what may happen when atoms of metal 2 make it less favorable due to decrease of the hydrogen binding energy and/or attractive hydrogen-hydrogen (H-H) interaction. Random distribution of metal atoms is taken explicitly into account. The attractive H-H interaction, including its dependence on fraction of metal 2 in the alloy, is described at the mean-field level. With increasing fraction of the latter metal, the critical temperature is found to decrease linearly or nonlinearly depending on the values of the model parameters. If the decrease of the hydrogen binding energy with increasing number of nearest-neighbor (nn) atoms of metal 2 is appreciable, the model predicts up to three hysteresis loops.
Design of Energy Aware Adder Circuits Considering Random Intra-Die Process Variations
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.
Sørensen, L B; Astrup, A.
2011-01-01
Objective: To compare the effect of dark and milk chocolate on appetite sensations and energy intake at an ad libitum test meal in healthy, normal-weight men. Subjects/methods: A total of 16 young, healthy, normal-weight men participated in a randomized, crossover study. Test meals were 100 g of either milk (2285 kJ) or dark chocolate (2502 kJ). Visual-analogue scales were used to record appetite sensations before and after the test meal was consumed and subsequently every 30 min for 5 h. An ...
Wave packet dynamics in energy space, random matrix theory, and the quantum-classical correspondence
Cohen; Izrailev; Kottos
2000-03-06
We apply random-matrix-theory (RMT) to the analysis of evolution of wave packets in energy space. We study the crossover from ballistic behavior to saturation, the possibility of having an intermediate diffusive behavior, and the feasibility of strong localization effect. Both theoretical considerations and numerical results are presented. Using quantal-classical correspondence considerations we question the validity of the emerging dynamical picture. In particular, we claim that the appearance of the intermediate diffusive behavior is possibly an artifact of the RMT strategy.
Development of an Integrated Global Energy Model
Krakowski, R.A.
1999-07-08
The primary objective of this research was to develop a forefront analysis tool for application to enhance understanding of long-term, global, nuclear-energy and nuclear-material futures. To this end, an existing economics-energy-environmental (E{sup 3}) model was adopted, modified, and elaborated to examine this problem in a multi-regional (13), long-term ({approximately}2,100) context. The E{sup 3} model so developed was applied to create a Los Alamos presence in this E{sup 3} area through ''niche analyses'' that provide input to the formulation of policies dealing with and shaping of nuclear-energy and nuclear-materials futures. Results from analyses using the E{sup 3} model have been presented at a variety of national and international conferences and workshops. Through use of the E{sup 3} model Los Alamos was afforded the opportunity to participate in a multi-national E{sup 3} study team that is examining a range of global, long-term nuclear issues under the auspices of the IAEA during the 1998-99 period . Finally, the E{sup 3} model developed under this LDRD project is being used as an important component in more recent Nuclear Material Management Systems (NMMS) project.
Constraining Logotropic Unified Dark Energy Models
Ferreira, V M C
2016-01-01
A unification of dark matter and dark energy in terms of a logotropic perfect dark fluid has recently been proposed, where deviations with respect to the standard $\\Lambda {\\rm CDM}$ model are dependent on a single parameter $B$. In this paper we show that the requirement that the linear growth of cosmic structures on comoving scales larger than $8 h^{-1} \\, {\\rm Mpc}$ is not significantly affected with respect to the standard $\\Lambda {\\rm CDM}$ result provides the strongest constraint to date on the model ($B <6 \\times 10^{-7}$), an improvement of more than three orders of magnitude over previous constraints on the value of $B$. We further show that this constraint rules out the logotropic Unified Dark Energy model as a possible solution to the small scale problems of the $\\Lambda$CDM model, including the cusp problem of Dark Matter halos or the missing satellite problem, as well as the original version of the model where the Planck energy density was taken as one of the two parameters characterizing the...
Cosmological Perturbations in Phantom Dark Energy Models
Imanol Albarran
2017-03-01
Full Text Available The ΛCDM paradigm, characterised by a constant equation of state w = − 1 for dark energy, is the model that better fits observations. However, the same observations strongly support the possibility of a dark energy content where the corresponding equation of state is close to but slightly smaller than − 1 . In this regard, we focus on three different models where the dark energy content is described by a perfect fluid with an equation of state w ≲ − 1 which can evolve or not. The three proposals show very similar behaviour at present, while the asymptotic evolution of each model drives the Universe to different abrupt events known as (i Big Rip; (ii Little Rip (LR; and (iii Little Sibling of the Big Rip. With the aim of comparing these models and finding possible imprints in their predicted matter distribution, we compute the matter power spectrum and the growth rate f σ 8 . We conclude that the model which induces a LR seems to be favoured by observations.
Madelung energy for random metallic alloys in the coherent potential approximation
Korzhavyi, P. A.; Ruban, Andrei; Abrikosov, I. A.;
1995-01-01
one to include charge-transfer effects in the framework of the CPA. We show how the models work in actual calculations for selected metallic alloy systems, Al-Li, Li-Mg, and Ni-Pt, which exhibit charge transfer. We find that the so-called screened impurity model (β=1), which is derived completely...... within the mean-field single-site approximation, leads to the best agreement with experimental lattice parameter and mixing energy data for Al-Li and Li-Mg alloys. However, for the Ni-Pt system exhibiting strong ordering tendency this model seems to overestimate the Madelung energy of the completely...
Singularity Problem in Teleparallel Dark Energy Models
Geng, Chao-Qiang; Lee, Chung-Chi
2013-01-01
We study the singularity problem in teleparallel dark energy models. A future singularity may occur due to the non-minimal coupling of the dark energy scalar field to teleparallel gravity that effectively changes the gravitational coupling strength and can even make it diverge. This singularity may be avoided by a binding-type self-potential that keeps the scalar field away from the singularity point. For demonstration we analyze the model with a quadratic potential and show how the (non)occurrence of the singularity depends on the initial conditions and the steepness of the potential, both of which affect the competition between the self-interaction and the non-minimal coupling. To examine the capability of the binding-type potential to fit observational data and meanwhile to avoid the singularity, we perform the data fitting for this model and show that the observationally viable region up to the $3\\sigma$ confidence level is free of the future singularity.
Simple implementation of general dark energy models
Bloomfield, Jolyon K. [MIT Kavli Institute for Astrophysics and Space Research, Massachusetts Institute of Technology, 77 Massachusetts Ave #37241, Cambridge, MA, 02139 (United States); Pearson, Jonathan A., E-mail: jolyon@mit.edu, E-mail: jonathan.pearson@durham.ac.uk [Centre for Particle Theory, Department of Mathematical Sciences, Durham University, South Road, Durham, DH1 3LE (United Kingdom)
2014-03-01
We present a formalism for the numerical implementation of general theories of dark energy, combining the computational simplicity of the equation of state for perturbations approach with the generality of the effective field theory approach. An effective fluid description is employed, based on a general action describing single-scalar field models. The formalism is developed from first principles, and constructed keeping the goal of a simple implementation into CAMB in mind. Benefits of this approach include its straightforward implementation, the generality of the underlying theory, the fact that the evolved variables are physical quantities, and that model-independent phenomenological descriptions may be straightforwardly investigated. We hope this formulation will provide a powerful tool for the comparison of theoretical models of dark energy with observational data.
PECULIARITIES OF THE RENEWABLE ENERGY BUSINESS MODELS
BĂLOI Ionut-Cosmin
2014-07-01
Full Text Available By exploring the competitiveness of industries and companies, we could identify the factors whose importance is likely to generate competitive advantage. An inventory of content elements of the business model summarizes the clearest opportunities and prospects. The objectives developed throughout the paper want to identify the pillars of a renewable business model and to describe the strategic dimensions of their capitalisation in regional and national energy entrepreneurship. The trend of increasing the renewable energy business volume is driven by the entrepreneurs and company’s availability to try new markets, with many unpredictable implications and the willingness of these players or their creditors to spend their savings, in various forms, for the concerned projects. There is no alternative to intensive investment strategies, given that the small projects are not able to create high value and competitiveness for interested entrepreneurs. For this reason, the international practice shows that the business models in energy production are supported by partnerships and networks of entrepreneurs who are involved in the development of large projects. The most important feature of renewable business initiatives is on attracting the latest clean emerging technologies, and obviously the investors who can assume the risk of such great projects. The benefits of a well developed business model recommend a prudent approach in the launching in the investment strategies, because the competitive contexts hide always some dissatisfaction of the partners that endanger the business concept’s success. The small firms can develop a profitable business model by exploring the opportunity of the alliances, namely the particular joint ventures (association between Romanian and foreign firms. The advantages of joint venture's partners are considerable; they include access to expertise, resources and other assets that the partners could not achieve on their own
Equivalence of the Random Oracle Model and the Ideal Cipher Model, Revisited
Holenstein, Thomas; Tessaro, Stefano
2010-01-01
We consider the cryptographic problem of constructing an invertible random permutation from a public random function (i.e., which can be accessed by the adversary). This goal is formalized by the notion of indifferentiability of Maurer et al. (TCC 2004). This is the natural extension to the public setting of the well-studied problem of building random permutations from random functions, which was first solved by Luby and Rackoff (Siam J. Comput., '88) using the so-called Feistel construction. The most important implication of such a construction is the equivalence of the random oracle model (Bellare and Rogaway, CCS '93) and the ideal cipher model, which is typically used in the analysis of several constructions in symmetric cryptography. Coron et al. (CRYPTO 2008) gave a rather involved proof that the six-round Feistel construction with independent random round functions is indifferentiable from an invertible random permutation. Also, it is known that fewer than six rounds do not suffice for indifferentiabil...
Observing and Modeling Earth's Energy Flows
Stevens, Bjorn; Schwartz, Stephen E.
2012-07-01
This article reviews, from the authors' perspective, progress in observing and modeling energy flows in Earth's climate system. Emphasis is placed on the state of understanding of Earth's energy flows and their susceptibility to perturbations, with particular emphasis on the roles of clouds and aerosols. More accurate measurements of the total solar irradiance and the rate of change of ocean enthalpy help constrain individual components of the energy budget at the top of the atmosphere to within ±2 W m-2. The measurements demonstrate that Earth reflects substantially less solar radiation and emits more terrestrial radiation than was believed even a decade ago. Active remote sensing is helping to constrain the surface energy budget, but new estimates of downwelling surface irradiance that benefit from such methods are proving difficult to reconcile with existing precipitation climatologies. Overall, the energy budget at the surface is much more uncertain than at the top of the atmosphere. A decade of high-precision measurements of the energy budget at the top of the atmosphere is providing new opportunities to track Earth's energy flows on timescales ranging from days to years, and at very high spatial resolution. The measurements show that the principal limitation in the estimate of secular trends now lies in the natural variability of the Earth system itself. The forcing-feedback-response framework, which has developed to understand how changes in Earth's energy flows affect surface temperature, is reviewed in light of recent work that shows fast responses (adjustments) of the system are central to the definition of the effective forcing that results from a change in atmospheric composition. In many cases, the adjustment, rather than the characterization of the compositional perturbation (associated, for instance, with changing greenhouse gas concentrations, or aerosol burdens), limits accurate determination of the radiative forcing. Changes in clouds contribute
van Aggelen, Helen; Yang, Yang; Yang, Weitao
2014-05-14
Despite their unmatched success for many applications, commonly used local, semi-local, and hybrid density functionals still face challenges when it comes to describing long-range interactions, static correlation, and electron delocalization. Density functionals of both the occupied and virtual orbitals are able to address these problems. The particle-hole (ph-) Random Phase Approximation (RPA), a functional of occupied and virtual orbitals, has recently known a revival within the density functional theory community. Following up on an idea introduced in our recent communication [H. van Aggelen, Y. Yang, and W. Yang, Phys. Rev. A 88, 030501 (2013)], we formulate more general adiabatic connections for the correlation energy in terms of pairing matrix fluctuations described by the particle-particle (pp-) propagator. With numerical examples of the pp-RPA, the lowest-order approximation to the pp-propagator, we illustrate the potential of density functional approximations based on pairing matrix fluctuations. The pp-RPA is size-extensive, self-interaction free, fully anti-symmetric, describes the strong static correlation limit in H2, and eliminates delocalization errors in H2(+) and other single-bond systems. It gives surprisingly good non-bonded interaction energies--competitive with the ph-RPA--with the correct R(-6) asymptotic decay as a function of the separation R, which we argue is mainly attributable to its correct second-order energy term. While the pp-RPA tends to underestimate absolute correlation energies, it gives good relative energies: much better atomization energies than the ph-RPA, as it has no tendency to underbind, and reaction energies of similar quality. The adiabatic connection in terms of pairing matrix fluctuation paves the way for promising new density functional approximations.
Many-body Systems Interacting via a Two-body Random Ensemble average energy of each angular momentum
Zhao, Y M; Yoshinaga, N
2002-01-01
In this paper, we discuss the regularities of energy of each angular momentum $I$ averaged over all the states for a fixed angular momentum (denoted as $\\bar{E}_I$'s) in many-body systems interacting via a two-body random ensemble. It is found that $\\bar{E}_I$'s with $I \\sim I_{min}$ (minimum of $I$) or $I_{max}$ have large probabilities (denoted as ${\\cal P}(I)$) to be the lowest, and that ${\\cal P}(I)$ is close to zero elsewhere. A simple argument based on the randomness of the two-particle cfp's is given. A compact trajectory of the energy $\\bar{E}_I$ vs. $I(I+1)$ is found to be robust. Regular fluctuations of the $P(I)$ (the probability of finding $I$ to be the ground state) and ${\\cal P}(I)$ of even fermions in a single-$j$ shell and boson systems are found to be reverse, and argued by the dimension fluctuation of the model space. Other regularities, such as why there are 2 or 3 sizable ${\\cal P}(I)$'s with $I\\sim I_{min}$ and ${\\cal P}(I) \\ll {\\cal P}(I_{max})$'s with $I\\sim I_{max}$, why the coefficien...
Joint modeling of ChIP-seq data via a Markov random field model
Bao, Yanchun; Vinciotti, Veronica; Wit, Ernst; 't Hoen, Peter A C
2014-01-01
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 spat
Local random potentials of high differentiability to model the Landscape
Battefeld, Thorsten
2015-01-01
We generate random functions locally via a novel generalization of Dyson Brownian motion, such that the functions are in a desired differentiability class, while ensuring that the Hessian is a member of the Gaussian orthogonal ensemble (other ensembles might be chosen if desired). Potentials in such higher differentiability classes are required/desirable to model string theoretical landscapes, for instance to compute cosmological perturbations (e.g., smooth first and second derivatives for the power-spectrum) or to search for minima (e.g., suitable de Sitter vacua for our universe). Since potentials are created locally, numerical studies become feasible even if the dimension of field space is large (D ~ 100). In addition to the theoretical prescription, we provide some numerical examples to highlight properties of such potentials; concrete cosmological applications will be discussed in companion publications.
Random field Ising model and community structure in complex networks
Son, S.-W.; Jeong, H.; Noh, J. D.
2006-04-01
We propose a method to determine the community structure of a complex network. In this method the ground state problem of a ferromagnetic random field Ising model is considered on the network with the magnetic field Bs = +∞, Bt = -∞, and Bi≠s,t=0 for a node pair s and t. The ground state problem is equivalent to the so-called maximum flow problem, which can be solved exactly numerically with the help of a combinatorial optimization algorithm. The community structure is then identified from the ground state Ising spin domains for all pairs of s and t. Our method provides a criterion for the existence of the community structure, and is applicable equally well to unweighted and weighted networks. We demonstrate the performance of the method by applying it to the Barabási-Albert network, Zachary karate club network, the scientific collaboration network, and the stock price correlation network. (Ising, Potts, etc.)
A General Random Walk Model of Molecular Motor
WANGXian-Ju; AIBao-Quan; LIUGuo-Tao; LIULiang-Gang
2003-01-01
A general random walk model framework is presented which can be used to statistically describe the internal dynamics and external mechanical movement of molecular motors along filament track. The motion of molecular motor in a periodic potential and a constant force is considered. We show that the molecular motor's movement becomes slower with the potential barrier increasing, but if the force is increased, the molecular motor''s movement becomes faster. The relation between the effective rate constant and the potential battler's height, and that between the effective rate constant and the value of the force are discussed. Our results are consistent with the experiments and relevant theoretical consideration, and can be used to explain some physiological phenomena.
[Critical of the additive model of the randomized controlled trial].
Boussageon, Rémy; Gueyffier, François; Bejan-Angoulvant, Theodora; Felden-Dominiak, Géraldine
2008-01-01
Randomized, double-blind, placebo-controlled clinical trials are currently the best way to demonstrate the clinical effectiveness of drugs. Its methodology relies on the method of difference (John Stuart Mill), through which the observed difference between two groups (drug vs placebo) can be attributed to the pharmacological effect of the drug being tested. However, this additive model can be questioned in the event of statistical interactions between the pharmacological and the placebo effects. Evidence in different domains has shown that the placebo effect can influence the effect of the active principle. This article evaluates the methodological, clinical and epistemological consequences of this phenomenon. Topics treated include extrapolating results, accounting for heterogeneous results, demonstrating the existence of several factors in the placebo effect, the necessity to take these factors into account for given symptoms or pathologies, as well as the problem of the "specific" effect.
Outlier Edge Detection Using Random Graph Generation Models and Applications
Zhang, Honglei; Gabbouj, Moncef
2016-01-01
Outliers are samples that are generated by different mechanisms from other normal data samples. Graphs, in particular social network graphs, may contain nodes and edges that are made by scammers, malicious programs or mistakenly by normal users. Detecting outlier nodes and edges is important for data mining and graph analytics. However, previous research in the field has merely focused on detecting outlier nodes. In this article, we study the properties of edges and propose outlier edge detection algorithms using two random graph generation models. We found that the edge-ego-network, which can be defined as the induced graph that contains two end nodes of an edge, their neighboring nodes and the edges that link these nodes, contains critical information to detect outlier edges. We evaluated the proposed algorithms by injecting outlier edges into some real-world graph data. Experiment results show that the proposed algorithms can effectively detect outlier edges. In particular, the algorithm based on the Prefe...
Nonlinear modeling of thermoacoustically driven energy cascade
Gupta, Prateek; Scalo, Carlo; Lodato, Guido
2016-11-01
We present an investigation of nonlinear energy cascade in thermoacoustically driven high-amplitude oscillations, from the initial weakly nonlinear regime to the shock wave dominated limit cycle. We develop a first principle based quasi-1D model for nonlinear wave propagation in a canonical minimal unit thermoacoustic device inspired by the experimental setup of Biwa et al.. Retaining up to quadratic nonlinear terms in the governing equations, we develop model equations for nonlinear wave propagation in the proximity of differentially heated no-slip boundaries. Furthermore, we discard the effects of acoustic streaming in the present study and focus on nonlinear energy cascade due to high amplitude wave propagation. Our model correctly predicts the observed exponential growth of the thermoacoustically amplified second harmonic, as well as the energy transfer rate to higher harmonics causing wave steepening. Moreover, we note that nonlinear coupling of local pressure with heat transfer reduces thermoacoustic amplification gradually thus causing the system to reach limit cycle exhibiting shock waves. Throughout, we verify the results from the quasi-1D model with fully compressible Navier-Stokes simulations.
Dynamic energy-demand models. A comparison
Yi, Feng [Department of Economics, Goeteborg University, Gothenburg (Sweden)
2000-04-01
This paper compares two second-generation dynamic energy demand models, a translog (TL) and a general Leontief (GL), in the study of price elasticities and factor substitutions of nine Swedish manufacturing industries: food, textiles, wood, paper, printing, chemicals, non-metallic minerals, base metals and machinery. Several model specifications are tested with likelihood ratio test. There is a disagreement on short-run adjustments; the TL model accepts putty-putty production technology of immediate adjustments, implying equal short- and long-run price elasticities of factors, while the GL model rejects immediate adjustments, giving out short-run elasticities quite different from the long-run. The two models also disagree in substitutability in many cases. 21 refs.
Alternative Dark Energy Models: An Overview
Lima, J A S
2004-01-01
A large number of recent observational data strongly suggest that we live in a flat, accelerating Universe composed of $\\sim$ 1/3 of matter (baryonic + dark) and $\\sim$ 2/3 of an exotic component with large negative pressure, usually named {\\bf Dark Energy} or {\\bf Quintessence}. The basic set of experiments includes: observations from SNe Ia, CMB anisotropies, large scale structure, X-ray data from galaxy clusters, age estimates of globular clusters and old high redshift galaxies (OHRG's). Such results seem to provide the remaining piece of information connecting the inflationary flatness prediction ($\\Omega_{\\rm{T}} = 1$) with astronomical observations. Theoretically, they have also stimulated the current interest for more general models containing an extra component describing this unknown dark energy, and simultaneously accounting for the present accelerating stage of the Universe. An overlook in the literature shows that at least five dark energy candidates have been proposed in the context of general re...
Hilpert, Simon; Günther, Stephan; Kaldemeyer, Cord
2017-01-01
The process of modelling energy systems is accompanied by challenges inherently connected with mathematical modelling. However, due to modern realities in the 21st century, existing challenges are gaining in magnitude and are supplemented with new ones. Modellers are confronted with a rising comp...
Random walk models of worker sorting in ant colonies.
Sendova-Franks, Ana B; Van Lent, Jan
2002-07-21
Sorting can be an important mechanism for the transfer of information from one level of biological organization to another. Here we study the algorithm underlying worker sorting in Leptothorax ant colonies. Worker sorting is related to task allocation and therefore to the adaptive advantages associated with an efficient system for the division of labour in ant colonies. We considered four spatially explicit individual-based models founded on two-dimensional correlated random walk. Our aim was to establish whether sorting at the level of the worker population could occur with minimal assumptions about the behavioural algorithm of individual workers. The behaviour of an individual worker in the models could be summarized by the rule "move if you can, turn always". We assume that the turning angle of a worker is individually specific and negatively dependent on the magnitude of an internal parameter micro which could be regarded as a measure of individual experience or task specialization. All four models attained a level of worker sortedness that was compatible with results from experiments onLeptothorax ant colonies. We found that the presence of a sorting pivot, such as the nest wall or an attraction force towards the centre of the worker population, was crucial for sorting. We make a distinction between such pivots and templates and discuss the biological implications of their difference.
Gould, Tim
2012-01-01
The inhomogeneous Singwi, Tosi, Land and Sjolander (ISTLS) correlation energy functional of Dobson, Wang and Gould [PRB {\\bf 66} 081108(R) (2008)] has proved to be excellent at predicting correlation energies in semi-homogeneous systems, showing promise as a robust `next step' fifth-rung functional by using dynamic correlation to go beyond the limitations of the direct random-phase approximation (dRPA), but with similar numerical scaling with system size. In this work we test the functional on fourteen spherically symmetric, neutral and charged atomic systems and find it gives excellent results (within 2mHa/$e^-$ except Be) for the absolute correlation energies of the neutral atoms tested, and good results for the ions (within 4mHa/$e^-$). In all cases it performs better than the dRPA. When combined with the previous successes, these new results point to the ISTLS functional being a prime contender for high-accuracy, benchmark DFT correlation energy calculations.
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)
Sørensen, L B; Astrup, A
2011-01-01
Objective: To compare the effect of dark and milk chocolate on appetite sensations and energy intake at an ad libitum test meal in healthy, normal-weight men. Subjects/methods: A total of 16 young, healthy, normal-weight men participated in a randomized, crossover study. Test meals were 100 g of either milk (2285 kJ) or dark chocolate (2502 kJ). Visual-analogue scales were used to record appetite sensations before and after the test meal was consumed and subsequently every 30 min for 5 h. An ad libitum meal was served 2 h after the test meal had been consumed. Results: The participants felt more satiated, less hungry, and had lower ratings of prospective food consumption after consumption of the dark chocolate than after the milk chocolate. Ratings of the desire to eat something sweet, fatty or savoury were all lower after consumption of the dark chocolate. Energy intake at the ad libitum meal was 17% lower after consumption of the dark chocolate than after the milk chocolate (P=0.002). If the energy provided by the chocolate is included in the calculation, the energy intake after consumption of the dark chocolate was still 8% lower than after the milk chocolate (P=0.01). The dark chocolate load resulted in an overall energy difference of −584 kJ (95% confidence interval (−1027;−141)) during the test period. Conclusion: In the present study, dark chocolate promotes satiety, lowers the desire to eat something sweet, and suppresses energy intake compared with milk chocolate. PMID:23455041
Sørensen, L B; Astrup, A
2011-12-05
To compare the effect of dark and milk chocolate on appetite sensations and energy intake at an ad libitum test meal in healthy, normal-weight men. A total of 16 young, healthy, normal-weight men participated in a randomized, crossover study. Test meals were 100 g of either milk (2285 kJ) or dark chocolate (2502 kJ). Visual-analogue scales were used to record appetite sensations before and after the test meal was consumed and subsequently every 30 min for 5 h. An ad libitum meal was served 2 h after the test meal had been consumed. The participants felt more satiated, less hungry, and had lower ratings of prospective food consumption after consumption of the dark chocolate than after the milk chocolate. Ratings of the desire to eat something sweet, fatty or savoury were all lower after consumption of the dark chocolate. Energy intake at the ad libitum meal was 17% lower after consumption of the dark chocolate than after the milk chocolate (P=0.002). If the energy provided by the chocolate is included in the calculation, the energy intake after consumption of the dark chocolate was still 8% lower than after the milk chocolate (P=0.01). The dark chocolate load resulted in an overall energy difference of -584 kJ (95% confidence interval (-1027;-141)) during the test period. In the present study, dark chocolate promotes satiety, lowers the desire to eat something sweet, and suppresses energy intake compared with milk chocolate.
Cardiovascular Effects of Energy Drinks in Familial Long QT Syndrome: A Randomized Cross-Over Study.
Gray, Belinda; Ingles, Jodie; Medi, Caroline; Driscoll, Timothy; Semsarian, Christopher
2017-03-15
Caffeinated energy drinks may trigger serious cardiac effects. The aim of this study was to determine the cardiovascular effects of caffeinated energy drink consumption in patients with familial long QT syndrome (LQTS). From 2014-2016, 24 LQTS patients aged 16-50 years were recruited to a randomized, double-blind, cross-over study of energy drink (ED) versus control (CD) with participants acting as their own controls (one week washout). The primary study outcome was an increase in corrected QT interval (QTc) by >20ms. Secondary outcomes were changes in systolic and diastolic blood pressure. In 24 patients with LQTS (no dropout), mean age was 29±9 years, 13/24 (54%) were female, and 8/24 (33%) were probands. Intention to treat analysis revealed no significant change in QTc with ED compared with CD (12±28ms vs 16±27ms, 3% vs 4%, p=0.71). The systolic and diastolic blood pressure significantly increased with ED compared to CD (peak change 7±16mmHg vs 1±16mmHg, 6% vs 0.8%, p=0.046 and 8±10 vs 2±9mmHg, 11% vs 3% p=0.01 respectively). These changes correlated with significant increases in serum caffeine (14.6±11.3 vs 0.5±0.1μmol/L, p<0.001) and serum taurine (737±199 vs -59±22μmol/L, p<0.001). There were three patients with dangerous QTc prolongation of ≥50ms following energy drink consumption. Caffeinated energy drinks have significant haemodynamic effects in patients with LQTS, especifically an acute increase in blood pressure. Since dangerous QTc prolongation was seen in some LQTS patients, we recommend caution in young patients with LQTS consuming energy drinks. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Scripted Building Energy Modeling and Analysis: Preprint
Hale, E.; Macumber, D.; Benne, K.; Goldwasser, D.
2012-08-01
Building energy modeling and analysis is currently a time-intensive, error-prone, and nonreproducible process. This paper describes the scripting platform of the OpenStudio tool suite (http://openstudio.nrel.gov) and demonstrates its use in several contexts. Two classes of scripts are described and demonstrated: measures and free-form scripts. Measures are small, single-purpose scripts that conform to a predefined interface. Because measures are fairly simple, they can be written or modified by inexperienced programmers.
Low energy behaviour of standard model extensions
Boggia, Michele; Passarino, Giampiero
2016-01-01
The integration of heavy scalar fields is discussed in a class of BSM models, containing more that one representation for scalars and with mixing. The interplay between integrating out heavy scalars and the Standard Model decoupling limit is examined. In general, the latter cannot be obtained in terms of only one large scale and can only be achieved by imposing further assumptions on the couplings. Systematic low-energy expansions are derived in the more general, non-decoupling scenario, including mixed tree-loop and mixed heavy-light generated operators. The number of local operators is larger than the one usually reported in the literature.
Systems Engineering Model for ART Energy Conversion
Mendez Cruz, Carmen Margarita [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Rochau, Gary E. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Wilson, Mollye C. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2017-02-01
The near-term objective of the EC team is to establish an operating, commercially scalable Recompression Closed Brayton Cycle (RCBC) to be constructed for the NE - STEP demonstration system (demo) with the lowest risk possible. A systems engineering approach is recommended to ensure adequate requirements gathering, documentation, and mode ling that supports technology development relevant to advanced reactors while supporting crosscut interests in potential applications. A holistic systems engineering model was designed for the ART Energy Conversion program by leveraging Concurrent Engineering, Balance Model, Simplified V Model, and Project Management principles. The resulting model supports the identification and validation of lifecycle Brayton systems requirements, and allows designers to detail system-specific components relevant to the current stage in the lifecycle, while maintaining a holistic view of all system elements.
Valuation Model for Adding Energy Resource into Autonomous Energy Cluster
De Kok, E.; Negeri, E.O.; Van Wijk, A.; Baken, N.
2013-01-01
With the availability of distributed generation (DG), clusters that can autonomously manage their energy profile are emerging in the power grid. These autonomous clusters manage their load profiles by orchestrating their energy resources, such as DG, storage, flexible energy consuming appliances, et
Valuation Model for Adding Energy Resource into Autonomous Energy Cluster
De Kok, E.; Negeri, E.O.; Van Wijk, A.; Baken, N.
2013-01-01
With the availability of distributed generation (DG), clusters that can autonomously manage their energy profile are emerging in the power grid. These autonomous clusters manage their load profiles by orchestrating their energy resources, such as DG, storage, flexible energy consuming appliances,
A random walk evolution model of wireless sensor networks and virus spreading
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.
Nesting statistics in the $O(n)$ loop model on random maps of arbitrary topologies
Borot, Gaëtan
2016-01-01
We pursue the analysis of nesting statistics in the $O(n)$ loop model on random maps, initiated for maps with the topology of disks and cylinders in math-ph/1605.02239, here for arbitrary topologies. For this purpose we rely on the topological recursion results of math-ph/0910.5896 and math-ph/1303.5808 for the enumeration of maps in the $O(n)$ model. We characterize the generating series of maps of genus $g$ with $k'$ marked points and $k$ boundaries and realizing a fixed nesting graph. These generating series are amenable to explicit computations in the loop model with bending energy on triangulations, and we characterize their behavior at criticality in the dense and in the dilute phase.
Applications of GARCH models to energy commodities
Humphreys, H. Brett
This thesis uses GARCH methods to examine different aspects of the energy markets. The first part of the thesis examines seasonality in the variance. This study modifies the standard univariate GARCH models to test for seasonal components in both the constant and the persistence in natural gas, heating oil and soybeans. These commodities exhibit seasonal price movements and, therefore, may exhibit seasonal variances. In addition, the heating oil model is tested for a structural change in variance during the Gulf War. The results indicate the presence of an annual seasonal component in the persistence for all commodities. Out-of-sample volatility forecasting for natural gas outperforms standard forecasts. The second part of this thesis uses a multivariate GARCH model to examine volatility spillovers within the crude oil forward curve and between the London and New York crude oil futures markets. Using these results the effect of spillovers on dynamic hedging is examined. In addition, this research examines cointegration within the oil markets using investable returns rather than fixed prices. The results indicate the presence of strong volatility spillovers between both markets, weak spillovers from the front of the forward curve to the rest of the curve, and cointegration between the long term oil price on the two markets. The spillover dynamic hedge models lead to a marginal benefit in terms of variance reduction, but a substantial decrease in the variability of the dynamic hedge; thereby decreasing the transactions costs associated with the hedge. The final portion of the thesis uses portfolio theory to demonstrate how the energy mix consumed in the United States could be chosen given a national goal to reduce the risks to the domestic macroeconomy of unanticipated energy price shocks. An efficient portfolio frontier of U.S. energy consumption is constructed using a covariance matrix estimated with GARCH models. The results indicate that while the electric
Critical behavior of the random-bond clock model
Wu, Raymond P. H.; Lo, Veng-cheong; Huang, Haitao
2012-09-01
The critical behavior of the clock model in two-dimensional square lattice is studied numerically using Monte Carlo method with Wolff algorithm. The Kosterlitz-Thouless (KT) transition is observed in the 8-state clock model, where an intermediate phase exists between the low-temperature ordered phase and the high-temperature disordered phase. The bond randomness is introduced to the system by assuming a Gaussian distribution for the coupling coefficients with the mean μ = 1 and different values of variance: from σ2 = 0.1 to σ2 = 3.0. An abrupt jump in the helicity modulus at the transition, which is the key characteristic of the KT transition, is verified with a stability argument. Our results show that, a small amount of disorder (small σ) reduces the critical temperature of the system, without altering the nature of transition. However, a larger amount of disorder changes the transition from the KT-type into that of non-KT-type.
Goldstein, Harvey; Leckie, George; Charlton, Christopher; Tilling, Kate; Browne, William J
2017-01-01
Aim To present a flexible model for repeated measures longitudinal growth data within individuals that allows trends over time to incorporate individual-specific random effects. These may reflect the timing of growth events and characterise within-individual variability which can be modelled as a function of age. Subjects and methods A Bayesian model is developed that includes random effects for the mean growth function, an individual age-alignment random effect and random effects for the within-individual variance function. This model is applied to data on boys' heights from the Edinburgh longitudinal growth study and to repeated weight measurements of a sample of pregnant women in the Avon Longitudinal Study of Parents and Children cohort. Results The mean age at which the growth curves for individual boys are aligned is 11.4 years, corresponding to the mean 'take off' age for pubertal growth. The within-individual variance (standard deviation) is found to decrease from 0.24 cm(2) (0.50 cm) at 9 years for the 'average' boy to 0.07 cm(2) (0.25 cm) at 16 years. Change in weight during pregnancy can be characterised by regression splines with random effects that include a large woman-specific random effect for the within-individual variation, which is also correlated with overall weight and weight gain. Conclusions The proposed model provides a useful extension to existing approaches, allowing considerable flexibility in describing within- and between-individual differences in growth patterns.
Time series, correlation matrices and random matrix models
Vinayak [Instituto de Ciencias Físicas, Universidad Nacional Autónoma de México, C.P. 62210 Cuernavaca (Mexico); Seligman, Thomas H. [Instituto de Ciencias Físicas, Universidad Nacional Autónoma de México, C.P. 62210 Cuernavaca, México and Centro Internacional de Ciencias, C.P. 62210 Cuernavaca (Mexico)
2014-01-08
In this set of five lectures the authors have presented techniques to analyze open classical and quantum systems using correlation matrices. For diverse reasons we shall see that random matrices play an important role to describe a null hypothesis or a minimum information hypothesis for the description of a quantum system or subsystem. In the former case various forms of correlation matrices of time series associated with the classical observables of some system. The fact that such series are necessarily finite, inevitably introduces noise and this finite time influence lead to a random or stochastic component in these time series. By consequence random correlation matrices have a random component, and corresponding ensembles are used. In the latter we use random matrices to describe high temperature environment or uncontrolled perturbations, ensembles of differing chaotic systems etc. The common theme of the lectures is thus the importance of random matrix theory in a wide range of fields in and around physics.
Underwater Noise Modelling of Wave Energy Devices
NONE
2009-07-01
Future large-scale implementation of wave energy converts (WECs) will introduce an anthropogenic activity in the ocean which may contribute to underwater noise. The Ocean houses several marine species with acoustic sensibility; consequently the potential impact of the underwater noise needs to be addressed. At present, there are no acoustic impact studies based on acquired data. The WEAM project (Wave Energy Acoustic Monitoring) aims at developing an underwater noise monitoring plan for WECs. The development of an acoustic monitoring plan must consider the sound propagation in the ocean, identify noise sources, understand the operational characteristics and select adequate instrumentation. Any monitoring strategy must involve in-situ measurements. However, the vast distances which sound travels within the ocean, can make in-situ measurements covering the entire area of interest, impracticable. This difficulty can be partially overcome through acoustic numerical modelling. This paper presents a synthetic study, on the application of acoustic forward modelling and the evaluation of the impact of noise produced by wave energy devices on marine mammals using criteria based on audiograms of dolphins, or other species. The idea is to illustrate the application of that methodology, and to show to what extent it allows for estimating distances of impacts due to acoustic noise.
Bewerunge, J
2016-01-01
The concept of potential energy landscapes is applied in many areas of science. We experimentally realize a random potential energy landscape (rPEL) to which colloids are exposed. This is achieved exploiting the interaction of matter with light. The optical set-up is based on a special diffuser, which creates a top-hat beam containing a speckle pattern. This is imposed on colloids. The effect of the speckle pattern on the colloids can be described by a rPEL. The speckle pattern as well as the rPEL are quantitatively characterized. The distributions of both, intensity and potential energy values, can be approximated by Gamma distributions. They can be tuned from exponential to approximately Gaussian with variable standard deviation, which determines the contrast of the speckles and the roughness of the rPEL. Moreover, the characteristic length scales, e.g. the speckle size, can be controlled. By rotating the diffuser, furthermore, a flat potential can be created and hence only radiation pressure exerted on the...
Cheng, Xiaojun; Lowell, Zachary; Zhao, Liyi; Genack, Azriel Z
2016-01-01
The impact of surface reflection upon transmission through and energy distributions within random media has generally been described in terms of the boundary extrapolation lengths $z_b, z_b'$ at the input and output end of an open sample, which are the distance beyond the sample surfaces at which the energy density within the sample extrapolates to zeroThe importance of reflection at the sample boundaries plays a key role in the scaling of transmission. Here we consider the impact of surface reflection on the propagation of diffusive waves in terms of the modification of the distribution of transmission eigenvalues (DTE). We review our finding of a transition in the analytical form of the DTE at the point that the sample length equals $|z_b-z_b'|$. The highest transmission eigenvalue for stronger asymmetry in boundary reflection is strictly smaller than unity. The average transmission and profiles of energy density inside the sample can still be described in terms of the sample length, $L$, and the boundary e...
Bishop, Michael
2011-01-01
In this paper, we show the that the ground state energy of the one-dimensional Discrete Random Schr\\"{o}dinger Operator with Bernoulli Potential is controlled asymptotically as the system size N goes to infinity by the random variable, $\\ell_N$ the length the longest consecutive sequence of sites on the lattice with potential equal to zero. Specifically, we will show that with probability one the limit as the system size goes to infinity the ratio of the ground state energy with the energy of a half-sine wave converges to one.
Ageing first passage time density in continuous time random walks and quenched energy landscapes
Krüsemann, Henning; Godec, Aljaž; Metzler, Ralf
2015-07-01
We study the first passage dynamics of an ageing stochastic process in the continuous time random walk (CTRW) framework. In such CTRW processes the test particle performs a random walk, in which successive steps are separated by random waiting times distributed in terms of the waiting time probability density function \\psi (t)≃ {t}-1-α (0≤slant α ≤slant 2). An ageing stochastic process is defined by the explicit dependence of its dynamic quantities on the ageing time ta, the time elapsed between its preparation and the start of the observation. Subdiffusive ageing CTRWs with 0\\lt α \\lt 1 describe systems such as charge carriers in amorphous semiconducters, tracer dispersion in geological and biological systems, or the dynamics of blinking quantum dots. We derive the exact forms of the first passage time density for an ageing subdiffusive CTRW in the semi-infinite, confined, and biased case, finding different scaling regimes for weakly, intermediately, and strongly aged systems: these regimes, with different scaling laws, are also found when the scaling exponent is in the range 1\\lt α \\lt 2, for sufficiently long ta. We compare our results with the ageing motion of a test particle in a quenched energy landscape. We test our theoretical results in the quenched landscape against simulations: only when the bias is strong enough, the correlations from returning to previously visited sites become insignificant and the results approach the ageing CTRW results. With small bias or without bias, the ageing effects disappear and a change in the exponent compared to the case of a completely annealed landscape can be found, reflecting the build-up of correlations in the quenched landscape.
Förster energy transfer induced random lasing at unconventional excitation wavelengths
Shadak Alee, K.; Barik, Sabyasachi; Mujumdar, Sushil
2013-11-01
We experimentally demonstrate efficient lasing from a Rhodamine-nanoscatterer random laser when pumped with unconventional wavelengths, at which the absorption of Rhodamine is negligible. Förster-type energy transfer was realized by using Coumarin molecules as donors. Explicit time-resolved spectroscopy provided direct evidence for the nonradiative transfer with ˜48% efficiency. We obtained lasing at reduced thresholds by a factor of over 3 and increased amplification rates by a factor of ˜4 in the Förster regime, even in samples with sub-diffusive disorder strength. We characterize the efficacy of the Förster transfer induced lasing over a range of unconventional wavelengths for the Rh-based system.
Tsung-Yung Chiu
2012-12-01
Full Text Available Global energy sources are gradually becoming scarce and prices are continually rising. Governments and businesses in various countries are actively developing technologies for energy management and developing new sources of energy. On 15 June 2011, the International Organization for Standardization (ISO announced the ISO 50001 standard for energy management systems. Organizations and enterprises are confronted with challenges associated with enhancing energy performance indicators, continuing to improve energy consumption efficiency, and managing third-party international certifications. This study conducted cases studies of businesses that have introduced an ISO 50001 energy management system by using an integration-energy-practice model to improve energy performance indicators and to complete the international auditing and certification procedures for ISO 50001 energy management systems. Based on case study results, the achievement rates for annual energy performance indicators increased, thereby enhancing the energy intensity efficiency. Establishing an integration-energy-practice model for introducing an ISO 50001 energy management system can efficiently meet demands for energy performance indicators and pass the international certification for ISO 50001 energy management systems. The proposed model efficiently provides enterprises with methods for developing sustainable energy management. It integrates internal and external technical resources to establish energy technology think tanks, for promoting successful technology and experiences to various sectors, thereby allowing enterprises to integrate energy management, increase energy efficiency, and meet the ISO 50001 international standard for energy management systems.
Random matrix models of stochastic integral type for free infinitely divisible distributions
Molina, J Armando Domínguez
2010-01-01
The Bercovici-Pata bijection maps the set of classical infinitely divisible distributions to the set of free infinitely divisible distributions. The purpose of this work is to study random matrix models for free infinitely divisible distributions under this bijection. First, we find a specific form of the polar decomposition for the L\\'{e}vy measures of the random matrix models considered in Benaych-Georges who introduced the models through their measures. Second, random matrix models for free infinitely divisible distributions are built consisting of infinitely divisible matrix stochastic integrals whenever their corresponding classical infinitely divisible distributions admit stochastic integral representations. These random matrix models are realizations of random matrices given by stochastic integrals with respect to matrix-valued L\\'{e}vy processes. Examples of these random matrix models for several classes of free infinitely divisible distributions are given. In particular, it is shown that any free sel...
Rational choice theory and Becker's model of random behavior
Krstić Miloš
2015-01-01
Full Text Available According to rational choice theory, rational consumers tend to maximize utility under a given budget constraints. This will be achieved if they choose a combination of goods that can satisfy their needs and provide the maximum level of utility. Gary Becker, on the other hand, imagines irrational consumers who choose bundle on the budget line. As irrational consumers have an equal probability of choosing any bundle on the budget line, on average, we expect that they will pick the bundle lying at the midpoint of the line. The results of research in which artificial Becker's agents choose among more than two commodities, rational choice theory is small and more than two budget/price situations show that the percentage of agents whose behavior violate. Adding some factors to Becker's model of random behavior, experimenters can minimize these minor violations. Therefore, rational choice theory is unfalsifiable. The results of our research have confirmed this theory. In addition, in the paper we discussed about explanatory value of rational choice theory in specific circumstances (positive substitution effect and we concluded that the explanatory value of rational choice theory was significantly reduced in specific cases.
Force Limited Random Vibration Test of TESS Camera Mass Model
Karlicek, Alexandra; Hwang, James Ho-Jin; Rey, Justin J.
2015-01-01
The Transiting Exoplanet Survey Satellite (TESS) is a spaceborne instrument consisting of four wide field-of-view-CCD cameras dedicated to the discovery of exoplanets around the brightest stars. As part of the environmental testing campaign, force limiting was used to simulate a realistic random vibration launch environment. While the force limit vibration test method is a standard approach used at multiple institutions including Jet Propulsion Laboratory (JPL), NASA Goddard Space Flight Center (GSFC), European Space Research and Technology Center (ESTEC), and Japan Aerospace Exploration Agency (JAXA), it is still difficult to find an actual implementation process in the literature. This paper describes the step-by-step process on how the force limit method was developed and applied on the TESS camera mass model. The process description includes the design of special fixtures to mount the test article for properly installing force transducers, development of the force spectral density using the semi-empirical method, estimation of the fuzzy factor (C2) based on the mass ratio between the supporting structure and the test article, subsequent validating of the C2 factor during the vibration test, and calculation of the C.G. accelerations using the Root Mean Square (RMS) reaction force in the spectral domain and the peak reaction force in the time domain.
Scale-free random graphs and Potts model
D-S Lee; K-I Goh; B Kahng; D Kim
2005-06-01
We introduce a simple algorithm that constructs scale-free random graphs efficiently: each vertex has a prescribed weight − (0 < < 1) and an edge can connect vertices and with rate . Corresponding equilibrium ensemble is identified and the problem is solved by the → 1 limit of the -state Potts model with inhomogeneous interactions for all pairs of spins. The number of loops as well as the giant cluster size and the mean cluster size are obtained in the thermodynamic limit as a function of the edge density. Various critical exponents associated with the percolation transition are also obtained together with finite-size scaling forms. The process of forming the giant cluster is qualitatively different between the cases of > 3 and 2 < < 3, where = 1 + -1 is the degree distribution exponent. While for the former, the giant cluster forms abruptly at the percolation transition, for the latter, however, the formation of the giant cluster is gradual and the mean cluster size for finite shows double peaks.
Heatstroke Pathophysiology: The Energy Depletion Model
1989-06-12
Pathophysiology: The Energy Depletion Model Roger W. Hubbard, Ph.D., Director Heat Research Division U. S. Army Research Institute of Environmental...Medicine Natick, MA 01760-5007 USA Send correspondence to: Roger W. Hubbard, Ph.D. Director Heat Research Division USARIEM Kansas St Natick, MA 01760...The NaK-Pump. Part B: Celular Asoects J.C. Skou, J.G. Normy, A.B. Maunsback, and M. Esmann (Eds) New York: Alan R. Uss, 1988, pp. 171-194. 54: Lewis
Symbolic modeling of high energy beam optics
Autin, Bruno
1999-01-01
A classical problem of computational physics consists of finding the minimum of a chi /sup 2/ like function of many variables. Powerful optimization algorithms have been developed but do not guarantee convergence towards an absolute minimum. Analytical methods can improve the insight into a physical problem but calculations quickly exceed the power of a human brain. There comes the interest of optical design of high energy particle accelerators. The physics background is sketched and emphasis is put on the methodology. In practice, algebraic models may not be precise enough but they usually provide excellent initial conditions for a final numerical optimization. (4 refs).
Elastic Model for Dinucleosome Structure and Energy
Fatemi, Hashem; Mohammad-Rafiee, Farshid
2016-01-01
The equilibrium structure of a Dinucleosome is studied using an elastic model that takes into account the force and torque balance conditions. Using the proper boundary conditions, it is found that the conformational energy of the problem does not depend on the length of the linker DNA. In addition it is shown that the two histone octamers are almost perpendicular to each other and the linker DNA in short lengths is almost straight. These findings could shed some light on the role of DNA elasticity in the chromatin structure.
Energy modelling towards low carbon development of Beijing in 2030
Zhao, Guangling; Guerrero, Josep M.; Jiang, Kejun
2017-01-01
Beijing, as the capital of China, is under the high pressure of climate change and pollution. The consumption of non-renewable energy is one of the most important sources of the CO2 emissions, which cause climate changes. This paper presents a study on the energy system modelling towards renewable...... energy and low carbon development for the city of Beijing. The analysis of energy system modelling is organized in two steps to explore the alternative renewable energy system in Beijing. Firstly, a reference energy system of Beijing is created based on the available data in 2014. The Energy......PLAN, an energy system analysis tool, is chosen to develop the reference energy model. Secondly, this reference model is used to investigate the alternative energy system for integrating renewable energies. Three scenarios are developed towards the energy system of Beijing in 2030, which are: (i) reference...
Kinetic study of CO2 reaction with CaO by a modified random pore model
Nouri S.M.M.
2016-03-01
Full Text Available In this work, a modified random pore model was developed to study the kinetics of the carbonation reaction of CaO. Pore size distributions of the CaO pellets were measured by nitrogen adsorption and mercury porosimetry methods. The experiments were carried out in a thermogravimeter at different isothermal temperatures and CO2 partial pressures. A fractional concentration dependency function showed the best accuracy for predicting the intrinsic rate of reaction. The activation energy was determined as 11 kcal/mole between 550–700°C. The effect of product layer formation was also taken into account by using the variable product layer diffusivity. Also, the model was successfully predicted the natural lime carbonation reaction data extracted from the literature.
Mendelian Randomization versus Path Models: Making Causal Inferences in Genetic Epidemiology.
Ziegler, Andreas; Mwambi, Henry; König, Inke R
2015-01-01
The term Mendelian randomization is popular in the current literature. The first aim of this work is to describe the idea of Mendelian randomization studies and the assumptions required for drawing valid conclusions. The second aim is to contrast Mendelian randomization and path modeling when different 'omics' levels are considered jointly. We define Mendelian randomization as introduced by Katan in 1986, and review its crucial assumptions. We introduce path models as the relevant additional component to the current use of Mendelian randomization studies in 'omics'. Real data examples for the association between lipid levels and coronary artery disease illustrate the use of path models. Numerous assumptions underlie Mendelian randomization, and they are difficult to be fulfilled in applications. Path models are suitable for investigating causality, and they should not be mixed up with the term Mendelian randomization. In many applications, path modeling would be the appropriate analysis in addition to a simple Mendelian randomization analysis. Mendelian randomization and path models use different concepts for causal inference. Path modeling but not simple Mendelian randomization analysis is well suited to study causality with different levels of 'omics' data. 2015 S. Karger AG, Basel.
Repulsive gravity model for dark energy
Hohmann, Manuel
2010-01-01
We construct a multimetric gravity theory containing N >= 3 copies of standard model matter and a corresponding number of metrics. In the Newtonian limit, this theory generates attractive gravitational forces within each matter sector, and repulsive forces of the same strength between matter from different sectors. This result demonstrates that the recently proven no-go theorem that forbids gravity theories of this type in N = 2 cannot be extended beyond the bimetric case. We apply our theory to cosmology and show that the repulsion between different types of matter may induce the observed accelerating expansion of the universe. In this way dark energy can be explained simply by dark copies of the well-understood standard model.
Repulsive gravity model for dark energy
Hohmann, Manuel; Wohlfarth, Mattias N. R.
2010-05-01
We construct a multimetric gravity theory containing N≥3 copies of standard model matter and a corresponding number of metrics. In the Newtonian limit, this theory generates attractive gravitational forces within each matter sector and repulsive forces of the same strength between matter from different sectors. This result demonstrates that the recently proven no-go theorem that forbids gravity theories of this type in N=2 cannot be extended beyond the bimetric case. We apply our theory to cosmology and show that the repulsion between different types of matter may induce the observed accelerating expansion of the universe. In this way dark energy can be explained simply by dark copies of the well-understood standard model.
Observational Test for a Random Sweeping Model in Solar Wind Turbulence.
Perschke, C; Narita, Y; Motschmann, U; Glassmeier, K H
2016-03-25
Evidence of frequency broadening at ion kinetic scales due to large-scale eddies and waves is found in solar wind turbulence by a test for a random sweeping model using the magnetic energy spectrum in the frequency vs wave number domain in the comoving frame of the flow obtained from multispacecraft observations. The statistical analysis of the frequency vs wave number spectra without using Taylor's hypothesis shows Gaussian frequency broadening around nearly zero frequencies that increases for larger wave numbers and non-Gaussian tails at higher frequencies. Comparison of the observed frequency broadening with a random sweeping model derived from hydrodynamic turbulence reveals similarities with respect to the Gaussian shape. The standard deviation of the broadening scales with ∼k^{1.6±0.2} and differs from the hydrodynamic turbulence model that predicts ∼k^{2/3}. We interpret this stronger increasing broadening as a consequence of the more diverse large scale structures (eddies and waves) in plasma turbulence and the accompanied more complex sweeping. Consequently, an identification and association of waves with normal modes based on their dispersion relation only, in particular at ion kinetic scales and below, is not possible in solar wind turbulence.
Ellis, Katherine; Kerr, Jacqueline; Godbole, Suneeta; Lanckriet, Gert; Wing, David; Marshall, Simon
2014-11-01
Wrist accelerometers are being used in population level surveillance of physical activity (PA) but more research is needed to evaluate their validity for correctly classifying types of PA behavior and predicting energy expenditure (EE). In this study we compare accelerometers worn on the wrist and hip, and the added value of heart rate (HR) data, for predicting PA type and EE using machine learning. Forty adults performed locomotion and household activities in a lab setting while wearing three ActiGraph GT3X+ accelerometers (left hip, right hip, non-dominant wrist) and a HR monitor (Polar RS400). Participants also wore a portable indirect calorimeter (COSMED K4b2), from which EE and metabolic equivalents (METs) were computed for each minute. We developed two predictive models: a random forest classifier to predict activity type and a random forest of regression trees to estimate METs. Predictions were evaluated using leave-one-user-out cross-validation. The hip accelerometer obtained an average accuracy of 92.3% in predicting four activity types (household, stairs, walking, running), while the wrist accelerometer obtained an average accuracy of 87.5%. Across all 8 activities combined (laundry, window washing, dusting, dishes, sweeping, stairs, walking, running), the hip and wrist accelerometers obtained average accuracies of 70.2% and 80.2% respectively. Predicting METs using the hip or wrist devices alone obtained root mean square errors (rMSE) of 1.09 and 1.00 METs per 6 min bout, respectively. Including HR data improved MET estimation, but did not significantly improve activity type classification. These results demonstrate the validity of random forest classification and regression forests for PA type and MET prediction using accelerometers. The wrist accelerometer proved more useful in predicting activities with significant arm movement, while the hip accelerometer was superior for predicting locomotion and estimating EE.
Data mining, mining data : energy consumption modelling
Dessureault, S. [Arizona Univ., Tucson, AZ (United States)
2007-09-15
Most modern mining operations are accumulating large amounts of data on production and business processes. Data, however, provides value only if it can be translated into information that appropriate users can utilize. This paper emphasized that a new technological focus should emerge, notably how to concentrate data into information; analyze information sufficiently to become knowledge; and, act on that knowledge. Researchers at the Mining Information Systems and Operations Management (MISOM) laboratory at the University of Arizona have created a method to transform data into action. The data-to-action approach was exercised in the development of an energy consumption model (ECM), in partnership with a major US-based copper mining company, 2 software companies, and the MISOM laboratory. The approach begins by integrating several key data sources using data warehousing techniques, and increasing the existing level of integration and data cleaning. An online analytical processing (OLAP) cube was also created to investigate the data and identify a subset of several million records. Data mining algorithms were applied using the information that was isolated by the OLAP cube. The data mining results showed that traditional cost drivers of energy consumption are poor predictors. A comparison was made between traditional methods of predicting energy consumption and the prediction formed using data mining. Traditionally, in the mines for which data were available, monthly averages of tons and distance are used to predict diesel fuel consumption. However, this article showed that new information technology can be used to incorporate many more variables into the budgeting process, resulting in more accurate predictions. The ECM helped mine planners improve the prediction of energy use through more data integration, measure development, and workflow analysis. 5 refs., 11 figs.
Thermodynamical Properties of Spin-3／2 Ising Model in a Longitudinal Random Field with Crystal Field
LIANGYa-Qiu; WEIGuo-Zhu; ZHANGHong; SONGGuo-Li
2004-01-01
A theoretical study of a spin-3/2 Ising model in a longitudinal random field with crystal field is studied by using of the effective-field theory with correlations. The phase diagrams and the behavior of the tricritical point are investigated numerically for the honeycomb lattice when the random field is bimodal. In particular, the specific heat and the internal energy are examined in detail for the system with a crystal-field constant in the critical region where the ground-state configuration may change from the spin-3/2 state to the spin-1/2 state. We find many interesting phenomena in the system.
Peng, Degao; Yang, Yang; Zhang, Peng [Department of Chemistry, Duke University, Durham, North Carolina 27708 (United States); Yang, Weitao, E-mail: weitao.yang@duke.edu [Department of Chemistry and Department of Physics, Duke University, Durham, North Carolina 27708 (United States)
2014-12-07
In this article, we develop systematically second random phase approximations (RPA) and Tamm-Dancoff approximations (TDA) of particle-hole and particle-particle channels for calculating molecular excitation energies. The second particle-hole RPA/TDA can capture double excitations missed by the particle-hole RPA/TDA and time-dependent density-functional theory (TDDFT), while the second particle-particle RPA/TDA recovers non-highest-occupied-molecular-orbital excitations missed by the particle-particle RPA/TDA. With proper orbital restrictions, these restricted second RPAs and TDAs have a formal scaling of only O(N{sup 4}). The restricted versions of second RPAs and TDAs are tested with various small molecules to show some positive results. Data suggest that the restricted second particle-hole TDA (r2ph-TDA) has the best overall performance with a correlation coefficient similar to TDDFT, but with a larger negative bias. The negative bias of the r2ph-TDA may be induced by the unaccounted ground state correlation energy to be investigated further. Overall, the r2ph-TDA is recommended to study systems with both single and some low-lying double excitations with a moderate accuracy. Some expressions on excited state property evaluations, such as 〈S{sup ^2}〉 are also developed and tested.
Peng, Degao; Yang, Yang; Zhang, Peng; Yang, Weitao
2014-12-01
In this article, we develop systematically second random phase approximations (RPA) and Tamm-Dancoff approximations (TDA) of particle-hole and particle-particle channels for calculating molecular excitation energies. The second particle-hole RPA/TDA can capture double excitations missed by the particle-hole RPA/TDA and time-dependent density-functional theory (TDDFT), while the second particle-particle RPA/TDA recovers non-highest-occupied-molecular-orbital excitations missed by the particle-particle RPA/TDA. With proper orbital restrictions, these restricted second RPAs and TDAs have a formal scaling of only O(N4). The restricted versions of second RPAs and TDAs are tested with various small molecules to show some positive results. Data suggest that the restricted second particle-hole TDA (r2ph-TDA) has the best overall performance with a correlation coefficient similar to TDDFT, but with a larger negative bias. The negative bias of the r2ph-TDA may be induced by the unaccounted ground state correlation energy to be investigated further. Overall, the r2ph-TDA is recommended to study systems with both single and some low-lying double excitations with a moderate accuracy. Some expressions on excited state property evaluations, such as < hat{S}2rangle are also developed and tested.
Modeling energy flexibility of low energy buildings utilizing thermal mass
Foteinaki, Kyriaki; Heller, Alfred; Rode, Carsten
2016-01-01
the load shifting potential of an apartment of a low energy building in Copenhagen is assessed, utilizing the heat storage capacity of the thermal mass when the heating system is switched off for relieving the energy system. It is shown that when using a 4-hour preheating period before switching off...... of the external envelope and the thermal capacity of the internal walls as the main parameters that affect the load shifting potential of the apartment....... to match the production patterns, shifting demand from on-peak hours to off-peak hours. Buildings could act as flexibility suppliers to the energy system, through load shifting potential, provided that the large thermal mass of the building stock could be utilized for energy storage. In the present study...
A discrete model of energy-conserved wavefunction collapse
Gao, Shan
2013-01-01
Energy nonconservation is a serious problem of dynamical collapse theories. In this paper, we propose a discrete model of energy-conserved wavefunction collapse. It is shown that the model is consistent with existing experiments and our macroscopic experience.
A stochastic model of randomly accelerated walkers for human mobility
Gallotti, Riccardo; Bazzani, Armando; Rambaldi, Sandro; Barthelemy, Marc
2016-01-01
Recent studies of human mobility largely focus on displacements patterns and power law fits of empirical long-tailed distributions of distances are usually associated to scale-free superdiffusive random walks called Lévy flights...
Gravastar model in a dark energy universe
Brandt, Carlos Frederico Charret; Silva, Maria de Fatima Alves da [Universidade do Estado do Rio de Janeiro (UERJ), RJ (Brazil). Inst. de Fisica. Dept. de Fisica Teorica; Chan, Roberto [Observatorio Nacional, Rio de Janeiro, RJ (Brazil); Rocha, Pedro [Associacao Comunitaria Escola de Radio Progresso (ACERP), Rio de Janeiro, RJ (Brazil)
2011-07-01
Full text: The study of gravastars, in general, has considered these objects embedded in a Schwarzschild spacetime. However, taking the point of view that the universe must be fulfilled by a considerable amount of dark energy, it is very important to investigate its influence in the gravastar stability and in the possible dynamical evolution. In a first step, we have considered the de Sitter-Schwarzschild exterior spacetime, in order to introduce a positive cosmological constant, which has been suggested as a dark energy candidate. Then, with this purpose, we constructed three-layer dynamical models, which consists of an internal anisotropic dark energy fluid, a dynamical infinitely thin shell of perfect fluid with the equation of state p = (1 - γ)σ, and an external de Sitter- Schwarzschild spacetime. The present work allows to confirm one of the conclusion of one of the our previous work, that is, the sign of the difference between the pressures (radial and tangential) affects the conditions of the formation of the gravastar and black hole when the interior fluid of prototype gravastars are anisotropic, even when combined with an external cosmological constant. We have shown explicitly that the final output can be a black hole, a 'bounded excursion' stable gravastar depending on the total mass m of the system, the cosmological constant L{sub e}, the parameter ω, the constant a, the parameter γ and the initial position R{sub 0} of the dynamical shell. Another interesting result is that we can have black hole and stable gravastar formation even with an interior and a shell constituted of dark and repulsive dark energy. We also would like to point out the significant influence of the presence of the exterior cosmological constant to formation of this kind of structure, since there are some cases where we have a stable gravastar (for Λ 0) or none structure (for Λ > 0). Still more interesting is a case, where for small radius of the shell, we have
Low and High Energy Modeling in Geant4
Wright, Dennis H; Folger, Günter; Ivanchenko, Vladimir; Kossov, Mikhail; Starkov, Nikolai; Heikkinen, Aatos; Wellisch, Hans-Peter
2007-01-01
Four of the most-used Geant4 hadronic models, the Quark-gluon string, Bertini-style cascade, Binary cascade and Chiral Invariant Phase Space, are discussed. These models cover high, medium and low energies, respectively, and represent a more theoretical approach to simulating hadronic interactions than do the Low Energy and High Energy Parameterized models. The four models together do not yet cover all particles for all energies, so the Low Energy and High Energy Parameterized models, among others, are used to fill the gaps.The validity range in energy and particle type of each model is presented, as is a discussion of the models' distinguishing features. The main modeling stages are also described qualitatively and areas for improvement are pointed out for each model.
Low And High Energy Modeling in GEANT4
Wright, Dennis H.; Koi, Tatsumi; /SLAC; Folger, Gunter; Ivanchenko, Vladimir; Kossov, Mikhail; Starkov, Nikolai; /CERN; Heikkinen, Aatos; /Helsinki Inst. of Phys.; Wellisch,
2007-10-05
Four of the most-used Geant4 hadronic models, the Quark-gluon string, Bertini-style cascade, Binary cascade and Chiral Invariant Phase Space, are discussed. These models cover high, medium and low energies, respectively, and represent a more theoretical approach to simulating hadronic interactions than do the Low Energy and High Energy Parameterized models. The four models together do not yet cover all particles for all energies, so the Low Energy and High Energy Parameterized models, among others, are used to fill the gaps. The validity range in energy and particle type of each model is presented, as is a discussion of the models' distinguishing features. The main modeling stages are also described qualitatively and areas for improvement are pointed out for each model.
Statefinder Diagnostic for Born-Infeld Type Dark Energy Model
HUANG Zeng-Guang; LU Hui-Qing
2008-01-01
Using a new method called the statefinder diagnostics which can make one dark energy model differ from the others, we investigate the dynamics of Born-Infeld (B-I) type dark energy model. The evolution trajectory of B-I type dark energy with Mexican hat potential model with respect to e-folding time N is shown in the r (s) diagram, When the parameter of noncanonical kinetic energy term η→0 or kinetic energy ψ2→0, the B-I type dark energy (K-essence) model reduces to the quintessence model or the ACDM model corresponding to the statefinder pair {r, s}={1, 0} respectively. As a result, the evolution trajectory of our model in the r (s) diagram in Mexican hat potential is quite different from those of other dark energy models. The current values of parameters Ω,ψ and ω,ψ in this model meet the latest observations WMAP5 well.
Modeling Urban Dynamics Using Random Forest: Implementing Roc and Toc for Model Evaluation
Ahmadlou, M.; Delavar, M. R.; Shafizadeh-Moghadam, H.; Tayyebi, A.
2016-06-01
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.
Modeling and Simulation of Smart Energy Systems
Connolly, David; Lund, Henrik; Mathiesen, Brian Vad
2015-01-01
At a global level, it is essential that the world transfers from fossil fuels to renewable energy resources to minimize the implications of climate change, which has been clearly demonstrated by the Intergovernmental Panel on Climate Change (IPCC, 2007a). At a national level, for most countries......, the transition to renewable energy will improve energy security of supply, create new jobs, enhance trade, and consequently grow the national economy. However, even with such promising consequences, renewable energy only provided approximately 13% of the world's energy in 2007 (International Energy Agency, 2009a......). Therefore, identifying how to utilize more renewable energy is one of the most pressing challenges facing many countries at present. Owing to the ever-growing complexity of modern energy systems, energy-system-analysis tools are often used to analyze the potential of renewable energy in future energy...
Random regression models using different functions to model milk flow in dairy cows.
Laureano, M M M; Bignardi, A B; El Faro, L; Cardoso, V L; Tonhati, H; Albuquerque, L G
2014-09-12
We analyzed 75,555 test-day milk flow records from 2175 primiparous Holstein cows that calved between 1997 and 2005. Milk flow was obtained by dividing the mean milk yield (kg) of the 3 daily milking by the total milking time (min) and was expressed as kg/min. Milk flow was grouped into 43 weekly classes. The analyses were performed using a single-trait Random Regression Models that included direct additive genetic, permanent environmental, and residual random effects. In addition, the contemporary group and linear and quadratic effects of cow age at calving were included as fixed effects. Fourth-order orthogonal Legendre polynomial of days in milk was used to model the mean trend in milk flow. The additive genetic and permanent environmental covariance functions were estimated using random regression Legendre polynomials and B-spline functions of days in milk. The model using a third-order Legendre polynomial for additive genetic effects and a sixth-order polynomial for permanent environmental effects, which contained 7 residual classes, proved to be the most adequate to describe variations in milk flow, and was also the most parsimonious. The heritability in milk flow estimated by the most parsimonious model was of moderate to high magnitude.
Probabilistic Models for Estimation of Random and Pseudo—Random Test Length
向东; 魏道政; 等
1992-01-01
A new probabilistic testability measure is presented to ease test length analyses of random testing and pseudorandom testing.The testability measure given in this paper is oriented to signal conflict of reconvergent fanouts.Test length analyses in this paper are based on a hard fault set,calculations of which are practicable and simple.Experimental results have been obtained to show the accuracy of this test length analyser in comparison with that of Savir[6],Chin and McClusker[8],and Wunderlich[4] by using a pseudorandom est generator combined with exhaustive fault simulation.
Influence of Random Potentials on the Current of the Molecular Motor Model
贾亚; 李家荣
2001-01-01
The current of the molecular motor model disturbed by random potentials, which involve the dichotomous and Ornstein-Uhlenbeck potentials, is studied using a finite-space correlation function. It is found that: (i) the amplitude and the correlation length of random potentials play opposing roles in the transport of the molecular motor model; (ii) a random potential with small amplitude and large correlation length is very useful in the molecular motor system.
Modeling Reserve Ancillary Service as Virtual Energy Carrier in Multi-Energy Systems
Damavandi, M; Moghaddam, Mohsen,; Haghifam, M.-R.; Shafie-khah, M.; Catalão, João,
2015-01-01
Part 14: Energy: Simulation; International audience; Multi-energy systems (MES) are considered various energy carriers and energy players in an integrated energy model. Vast amount of decision making data is gathered in these systems that cannot be processed by conventional methods. Cloud-based computing is an opportunity to develop these kinds of integrated and efficient approaches. Developing mathematical models that can be compatible with cloud-based engineering systems will help decision ...
Modelling QTL effect on BTA06 using random regression test day models.
Suchocki, T; Szyda, J; Zhang, Q
2013-02-01
In statistical models, a quantitative trait locus (QTL) effect has been incorporated either as a fixed or as a random term, but, up to now, it has been mainly considered as a time-independent variable. However, for traits recorded repeatedly, it is very interesting to investigate the variation of QTL over time. The major goal of this study was to estimate the position and effect of QTL for milk, fat, protein yields and for somatic cell score based on test day records, while testing whether the effects are constant or variable throughout lactation. The analysed data consisted of 23 paternal half-sib families (716 daughters of 23 sires) of Chinese Holstein-Friesian cattle genotyped at 14 microsatellites located in the area of the casein loci on BTA6. A sequence of three models was used: (i) a lactation model, (ii) a random regression model with a QTL constant in time and (iii) a random regression model with a QTL variable in time. The results showed that, for each production trait, at least one significant QTL exists. For milk and protein yields, the QTL effect was variable in time, while for fat yield, each of the three models resulted in a significant QTL effect. When a QTL is incorporated into a model as a constant over time, its effect is averaged over lactation stages and may, thereby, be difficult or even impossible to be detected. Our results showed that, in such a situation, only a longitudinal model is able to identify loci significantly influencing trait variation.
Random effects coefficient of determination for mixed and meta-analysis models.
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.
Exact solution of the O(n) model on a random lattice
Eynard, B
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\\in ]-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=\\pm 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. Furthermore we describe how the calculation of the higher genera contributions can be pursued in the scaling limit.
Human fixation detection model in video compressed domain based on Markov random field
Li, Yongjun; Li, Yunsong; Liu, Weijia; Hu, Jing; Ge, Chiru
2017-01-01
Recently, research on and applications of human fixation detection in video compressed domain have gained increasing attention. However, prediction accuracy and computational complexity still remain a challenge. This paper addresses the problem of compressed domain fixations detection in the videos based on residual discrete cosine transform coefficients norm (RDCN) and Markov random field (MRF). RDCN feature is directly extracted from the compressed video with partial decoding and is normalized. After spatial-temporal filtering, the normalized map [Smoothed RDCN (SRDCN) map] is taken to the MRF model, and the optimal binary label map is obtained. Based on the label map and the center saliency map, saliency enhancement and nonsaliency inhibition are done for the SRDCN map, and the final SRDCN-MRF salient map is obtained. Compared with the similar models, we enhance the available energy functions and introduce an energy function that indicates the positional information of the saliency. The procedure is advantageous for improving prediction accuracy and reducing computational complexity. The validation and comparison are made by several accuracy metrics on two ground truth datasets. Experimental results show that the proposed saliency detection model achieves superior performances over several state-of-the-art compressed-domain and pixel-domain algorithms on evaluation metrics. Computationally, our algorithm reduces 26% more computational complexity with comparison to similar algorithms.
Adaptive Multi-GPU Exchange Monte Carlo for the 3D Random Field Ising Model
Navarro, C A; Deng, Youjin
2015-01-01
The study of disordered spin systems through Monte Carlo simulations has proven to be a hard task due to the adverse energy landscape present at the low temperature regime, making it difficult for the simulation to escape from a local minimum. Replica based algorithms such as the Exchange Monte Carlo (also known as parallel tempering) are effective at overcoming this problem, reaching equilibrium on disordered spin systems such as the Spin Glass or Random Field models, by exchanging information between replicas of neighbor temperatures. In this work we present a multi-GPU Exchange Monte Carlo method designed for the simulation of the 3D Random Field Model. The implementation is based on a two-level parallelization scheme that allows the method to scale its performance in the presence of faster and GPUs as well as multiple GPUs. In addition, we modified the original algorithm by adapting the set of temperatures according to the exchange rate observed from short trial runs, leading to an increased exchange rate...
Developing an Energy Performance Modeling Startup Kit
none,
2012-10-01
In 2011, the NAHB Research Center began assessing the needs and motivations of residential remodelers regarding energy performance remodeling. This report outlines: the current remodeling industry and the role of energy efficiency; gaps and barriers to adding energy efficiency into remodeling; and support needs of professional remodelers to increase sales and projects involving improving home energy efficiency.
Energy modeling towards low carbon development of Beijing in 2030
Zhao, Guangling; Chen, Sha; Guerrero, Josep M.
2017-01-01
renewable energy and low carbon development for the city of Beijing. The analysis of energy system modeling is organized in two steps to explore the potential renewable energy alternative in Beijing. Firstly, a reference energy system of Beijing is created based on the available data in 2014. The Energy......PLAN, an energy system analysis tool, is chosen to develop the reference energy model. Secondly, this reference model is used to investigate the alternative energy system for integrating renewable energies. Three scenarios are developed towards the energy system of Beijing in 2030, which are: (i) reference...... scenario 2030, (ii) BAU (business as usual) scenario 2030 and (iii) RES (renewable energies) scenario 2030. The results shows that the share of renewables can increase to 100% of electricity and heat production in the RE scenario. The primary fuel consumption is reduced to 155.9 TWh, which is 72 % of fuel...
Soft-systems model of energy management and checklists for energy managers
Fawkes, S.
1987-01-01
This paper presents a model of the energy management process developed using a soft systems methodology. The model divides energy management into 4 levels; good housekeeping, retro-fit projects, plant replacement projects and new process design. The purpose of the model is to assist energy managers and other agents of change implement technical changes resulting in energy conservation. However, as with all soft systems models, it should not be taken as a final development, but rather a starting point for structured debate. From the model a number of checklists for energy managers are developed and presented.
Modeling and optimizing of the random atomic spin gyroscope drift based on the atomic spin gyroscope
Quan, Wei; Lv, Lin; Liu, Baiqi
2014-11-01
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.
Modeling and optimizing of the random atomic spin gyroscope drift based on the atomic spin gyroscope
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.
Quan, Wei; Lv, Lin; Liu, Baiqi
2014-11-01
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.
Modeling of the magnetic free energy of self-diffusion in bcc Fe
Sandberg, N.; Chang, Z.; Messina, L.; Olsson, P.; Korzhavyi, P.
2015-11-01
A first-principles based approach to calculating self-diffusion rates in bcc Fe is discussed with particular focus on the magnetic free energy associated with diffusion activation. First, the enthalpies and entropies of vacancy formation and migration in ferromagnetic bcc Fe are calculated from standard density functional theory methods in combination with transition state theory. Next, the shift in diffusion activation energy when going from the ferromagnetic to the paramagnetic state is estimated by averaging over random spin states. Classical and quantum mechanical Monte Carlo simulations within the Heisenberg model are used to study the effect of spin disordering on the vacancy formation and migration free energy. Finally, a quasiempirical model of the magnetic contribution to the diffusion activation free energy is applied in order to connect the current first-principles results to experimental data. The importance of the zero-point magnon energy in modeling of diffusion in bcc Fe is stressed.
Genetic Analysis of Daily Maximum Milking Speed by a Random Walk Model in Dairy Cows
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...
Random regression models in the evaluation of the growth curve of Simbrasil beef cattle
Mota, M.; Marques, F.A.; Lopes, P.S.; Hidalgo, A.M.
2013-01-01
Random regression models were used to estimate the types and orders of random effects of (co)variance functions in the description of the growth trajectory of the Simbrasil cattle breed. Records for 7049 animals totaling 18,677 individual weighings were submitted to 15 models from the third to the
Random regression models in the evaluation of the growth curve of Simbrasil beef cattle
Mota, M.; Marques, F.A.; Lopes, P.S.; Hidalgo, A.M.
2013-01-01
Random regression models were used to estimate the types and orders of random effects of (co)variance functions in the description of the growth trajectory of the Simbrasil cattle breed. Records for 7049 animals totaling 18,677 individual weighings were submitted to 15 models from the third to the f
Recent developments in exponential random graph (p*) models for social networks
Robins, Garry; Snijders, Tom; Wang, Peng; Handcock, Mark; Pattison, Philippa
2007-01-01
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 homogen
DYNAMIC FREE ENERGY HYSTERESIS MODEL IN MAGNETOSTRICTIVE ACTUATORS
无
2006-01-01
A dynamic free energy hysteresis model in magnetostrictive actuators is presented. It is the free energy hysteresis model coupled to an ordinary different equation in an unusual way. According to its special structure, numerical implementation method of the dynamic model is provided. The resistor parameter in the dynamic model changes according to different frequency ranges. This makes numerical implementation results reasonable in the discussed operating frequency range. The validity of the dynamic free energy model is illustrated by comparison with experimental data.
Random-field Ising model: Insight from zero-temperature simulations
P.E. Theodorakis
2014-12-01
Full Text Available We enlighten some critical aspects of the three-dimensional (d=3 random-field Ising model (RFIM from simulations performed at zero temperature. We consider two different, in terms of the field distribution, versions of model, namely a Gaussian RFIM and an equal-weight trimodal RFIM. By implementing a computational approach that maps the ground-state of the system to the maximum-flow optimization problem of a network, we employ the most up-to-date version of the push-relabel algorithm and simulate large ensembles of disorder realizations of both models for a broad range of random-field values and systems sizes V=LxLxL, where L denotes linear lattice size and Lmax=156. Using as finite-size measures the sample-to-sample fluctuations of various quantities of physical and technical origin, and the primitive operations of the push-relabel algorithm, we propose, for both types of distributions, estimates of the critical field hmax and the critical exponent ν of the correlation length, the latter clearly suggesting that both models share the same universality class. Additional simulations of the Gaussian RFIM at the best-known value of the critical field provide the magnetic exponent ratio β/ν with high accuracy and clear out the controversial issue of the critical exponent α of the specific heat. Finally, we discuss the infinite-limit size extrapolation of energy- and order-parameter-based noise to signal ratios related to the self-averaging properties of the model, as well as the critical slowing down aspects of the algorithm.
Improvement of energy model based on cubic interpolation curve
Li Peipei; Li Xuemei; and Wei Yu
2012-01-01
In CAGD and CG, energy model is often used to control the curves and surfaces shape. In curve/surface modeling, we can get fair curve/surface by minimizing the energy of curve/surface. However, our research indicates that in some cases we can＇t get fair curves/surface using the current energy model. So an improved energy model is presented in this paper. Examples are also included to show that fair curves can be obtained using the improved energy model.
Random forest (RF) modeling has emerged as an important statistical learning method in ecology due to its exceptional predictive performance. However, for large and complex ecological datasets there is limited guidance on variable selection methods for RF modeling. Typically, e...
Random surfaces, solvable lattice models and discrete quantum gravity in two dimensions
Kostov, I.K. (CEA Centre d' Etudes Nucleaires de Saclay, 91 - Gif-sur-Yvette (France). Service de Physique Theorique)
1989-07-01
We give a review of the analytical results concerning dynamically triangulated surfaces and statistical models on a planar random lattice. The critical behaviour of these models is described by conformal field theories coupled to 2d quantum gravity. (orig.).
Realistic cosmological model with dynamical cancellation of vacuum energy
Dolgov, A D
2003-01-01
We propose a model with a compensating scalar field whose back reaction to the cosmological curvature cancels possible vacuum energy density down to the terms of the order of the time dependent critical energy density. Thus the model simultaneously solves the mystery of the compensation of vacuum energy with the accuracy of 120 orders of magnitude and explains existence of the observed dark energy. At an early stage the suggested cosmological model might experience exponential expansion without an additional inflaton field.
The terms of turbulent kinetic energy budget within random arrays of emergent cylinders
Ricardo, Ana M.; Koll, Katinka; Franca, Mário J.; Schleiss, Anton J.; Ferreira, Rui M. L.
2014-05-01
This article is aimed at quantifying and discussing the relative magnitude of key terms of the equation of conservation of turbulent kinetic energy (TKE) in the inter-stem space of a flow within arrays of vertical cylinders simulating plant stems of emergent and rigid vegetation. The spatial distribution of turbulent quantities and mean flow variables are influenced by two fundamental space scales, the diameter of the stems and the local stem areal number-density. Both may vary considerably since the areal distribution of plant stems in natural systems is generally not homogeneous; they are often arranged in alternating sparse and dense patches. The magnitude of the terms of the budget of TKE in the inter-stem space has seldom been quantified experimentally and is currently not well known. This work addresses this research need. New databases, consisting of three-component LDA velocity series and two-component PIV velocity maps, obtained in carefully controlled laboratory conditions, were used to calculate the terms of the TKE budget. The physical system comprises random arrays of rigid and emergent cylinders with longitudinally varying areal number-density. It is verified that the main source of TKE is vortex shedding from individual cylinders. The rates of production and dissipation are not in equilibrium. Regions with negative production, a previously unreported feature, are identified. Turbulent transport is particularly important along the von Kármán vortex street. Convective rate of change of TKE and pressure diffusion are most relevant in the vicinity of the cylinders.
WANG Wen-Ge
2001-01-01
The Wigner band random matrix model is studied by making use of a generalization of Brillouin-Wigner perturbation theory. Energy eigenfunctions are shown to be divided into perturbative and nonperturbative parts. A relation between the average shape of eigenstates and that of the so-called local spectral density of states (LDOS) is derived by making use of some properties of energy eigenfunctions drawn from numerical results. Several perturbation strengths predicted by the perturbation theory are found to play important roles in the variation of the shape of the LDOS with perturbation strength.
Chen, Duan; Wei, Guo-Wei
2010-01-01
The miniaturization of nano-scale electronic devices, such as metal oxide semiconductor field effect transistors (MOSFETs), has given rise to a pressing demand in the new theoretical understanding and practical tactic for dealing with quantum mechanical effects in integrated circuits. Modeling and simulation of this class of problems have emerged as an important topic in applied and computational mathematics. This work presents mathematical models and computational algorithms for the simulation of nano-scale MOSFETs. We introduce a unified two-scale energy functional to describe the electrons and the continuum electrostatic potential of the nano-electronic device. This framework enables us to put microscopic and macroscopic descriptions in an equal footing at nano scale. By optimization of the energy functional, we derive consistently-coupled Poisson-Kohn-Sham equations. Additionally, layered structures are crucial to the electrostatic and transport properties of nano transistors. A material interface model is proposed for more accurate description of the electrostatics governed by the Poisson equation. Finally, a new individual dopant model that utilizes the Dirac delta function is proposed to understand the random doping effect in nano electronic devices. Two mathematical algorithms, the matched interface and boundary (MIB) method and the Dirichlet-to-Neumann mapping (DNM) technique, are introduced to improve the computational efficiency of nano-device simulations. Electronic structures are computed via subband decomposition and the transport properties, such as the I-V curves and electron density, are evaluated via the non-equilibrium Green's functions (NEGF) formalism. Two distinct device configurations, a double-gate MOSFET and a four-gate MOSFET, are considered in our three-dimensional numerical simulations. For these devices, the current fluctuation and voltage threshold lowering effect induced by the discrete dopant model are explored. Numerical convergence
Chen, Duan; Wei, Guo-Wei
2010-06-01
The miniaturization of nano-scale electronic devices, such as metal oxide semiconductor field effect transistors (MOSFETs), has given rise to a pressing demand in the new theoretical understanding and practical tactic for dealing with quantum mechanical effects in integrated circuits. Modeling and simulation of this class of problems have emerged as an important topic in applied and computational mathematics. This work presents mathematical models and computational algorithms for the simulation of nano-scale MOSFETs. We introduce a unified two-scale energy functional to describe the electrons and the continuum electrostatic potential of the nano-electronic device. This framework enables us to put microscopic and macroscopic descriptions in an equal footing at nano-scale. By optimization of the energy functional, we derive consistently coupled Poisson-Kohn-Sham equations. Additionally, layered structures are crucial to the electrostatic and transport properties of nano-transistors. A material interface model is proposed for more accurate description of the electrostatics governed by the Poisson equation. Finally, a new individual dopant model that utilizes the Dirac delta function is proposed to understand the random doping effect in nano-electronic devices. Two mathematical algorithms, the matched interface and boundary (MIB) method and the Dirichlet-to-Neumann mapping (DNM) technique, are introduced to improve the computational efficiency of nano-device simulations. Electronic structures are computed via subband decomposition and the transport properties, such as the I- V curves and electron density, are evaluated via the non-equilibrium Green's functions (NEGF) formalism. Two distinct device configurations, a double-gate MOSFET and a four-gate MOSFET, are considered in our three-dimensional numerical simulations. For these devices, the current fluctuation and voltage threshold lowering effect induced by the discrete dopant model are explored. Numerical
Single-cluster-update Monte Carlo method for the random anisotropy model
Rößler, U. K.
1999-06-01
A Wolff-type cluster Monte Carlo algorithm for random magnetic models is presented. The algorithm is demonstrated to reduce significantly the critical slowing down for planar random anisotropy models with weak anisotropy strength. Dynamic exponents zcluster algorithms are estimated for models with ratio of anisotropy to exchange constant D/J=1.0 on cubic lattices in three dimensions. For these models, critical exponents are derived from a finite-size scaling analysis.
A Random Matrix Approach for Quantifying Model-Form Uncertainties in Turbulence Modeling
Xiao, Heng; Ghanem, Roger G
2016-01-01
With the ever-increasing use of Reynolds-Averaged Navier--Stokes (RANS) simulations in mission-critical applications, the quantification of model-form uncertainty in RANS models has attracted attention in the turbulence modeling community. Recently, a physics-based, nonparametric approach for quantifying model-form uncertainty in RANS simulations has been proposed, where Reynolds stresses are projected to physically meaningful dimensions and perturbations are introduced only in the physically realizable limits. However, a challenge associated with this approach is to assess the amount of information introduced in the prior distribution and to avoid imposing unwarranted constraints. In this work we propose a random matrix approach for quantifying model-form uncertainties in RANS simulations with the realizability of the Reynolds stress guaranteed. Furthermore, the maximum entropy principle is used to identify the probability distribution that satisfies the constraints from available information but without int...
Positive random fields for modeling material stiffness and compliance
Hasofer, Abraham Michael; Ditlevsen, Ove Dalager; Tarp-Johansen, Niels Jacob
1998-01-01
Positive random fields with known marginal properties and known correlation function are not numerous in the literature. The most prominent example is the log\\-normal field for which the complete distribution is known and for which the reciprocal field is also lognormal. It is of interest to supp...
Missing Not at Random Models for Latent Growth Curve Analyses
Enders, Craig K.
2011-01-01
The past decade has seen a noticeable shift in missing data handling techniques that assume a missing at random (MAR) mechanism, where the propensity for missing data on an outcome is related to other analysis variables. Although MAR is often reasonable, there are situations where this assumption is unlikely to hold, leading to biased parameter…
Regressor and random-effects dependencies in multilevel models
Ebbes, P.; Bockenholt, U; Wedel, M.
The objectives of this paper are (1) to review methods that can be used to test for different types of random effects and regressor dependencies, (2) to present results from Monte Carlo studies designed to investigate the performance of these methods, and (3) to discuss estimation methods that can
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
Modelling of biomass utilization for energy purpose
Grzybek, Anna (ed.)
2010-07-01
the overall farms structure, farms land distribution on several separate subfields for one farm, villages' overpopulation and very high employment in agriculture (about 27% of all employees in national economy works in agriculture). Farmers have low education level. In towns 34% of population has secondary education and in rural areas - only 15-16%. Less than 2% inhabitants of rural areas have higher education. The structure of land use is as follows: arable land 11.5%, meadows and pastures 25.4%, forests 30.1%. Poland requires implementation of technical and technological progress for intensification of agricultural production. The reason of competition for agricultural land is maintenance of the current consumption level and allocation of part of agricultural production for energy purposes. Agricultural land is going to be key factor for biofuels production. In this publication research results for the Project PL0073 'Modelling of energetical biomass utilization for energy purposes' have been presented. The Project was financed from the Norwegian Financial Mechanism and European Economic Area Financial Mechanism. The publication is aimed at moving closer and explaining to the reader problems connected with cultivations of energy plants and dispelling myths concerning these problems. Exchange of fossil fuels by biomass for heat and electric energy production could be significant input in carbon dioxide emission reduction. Moreover, biomass crop and biomass utilization for energetical purposes play important role in agricultural production diversification in rural areas transformation. Agricultural production widening enables new jobs creation. Sustainable development is going to be fundamental rule for Polish agriculture evolution in long term perspective. Energetical biomass utilization perfectly integrates in the evolution frameworks, especially on local level. There are two facts. The fist one is that increase of interest in energy crops in Poland
Modelling of biomass utilization for energy purpose
Grzybek, Anna (ed.)
2010-07-01
the overall farms structure, farms land distribution on several separate subfields for one farm, villages' overpopulation and very high employment in agriculture (about 27% of all employees in national economy works in agriculture). Farmers have low education level. In towns 34% of population has secondary education and in rural areas - only 15-16%. Less than 2% inhabitants of rural areas have higher education. The structure of land use is as follows: arable land 11.5%, meadows and pastures 25.4%, forests 30.1%. Poland requires implementation of technical and technological progress for intensification of agricultural production. The reason of competition for agricultural land is maintenance of the current consumption level and allocation of part of agricultural production for energy purposes. Agricultural land is going to be key factor for biofuels production. In this publication research results for the Project PL0073 'Modelling of energetical biomass utilization for energy purposes' have been presented. The Project was financed from the Norwegian Financial Mechanism and European Economic Area Financial Mechanism. The publication is aimed at moving closer and explaining to the reader problems connected with cultivations of energy plants and dispelling myths concerning these problems. Exchange of fossil fuels by biomass for heat and electric energy production could be significant input in carbon dioxide emission reduction. Moreover, biomass crop and biomass utilization for energetical purposes play important role in agricultural production diversification in rural areas transformation. Agricultural production widening enables new jobs creation. Sustainable development is going to be fundamental rule for Polish agriculture evolution in long term perspective. Energetical biomass utilization perfectly integrates in the evolution frameworks, especially on local level. There are two facts. The fist one is that increase of interest in energy crops in Poland
Holographic tachyon model of dark energy
Setare, M.R.
2007-01-01
In this paper we consider a correspondence between the holographic dark energy density and tachyon energy density in FRW universe. Then we reconstruct the potential and the dynamics of the tachyon field which describe tachyon cosmology.
McNeil, J; Brenner, D R; Courneya, K S; Friedenreich, C M
2017-08-01
Despite the clear health benefits of exercise, exercised-induced weight loss is often less than expected. The term 'exercise energy compensation' is used to define the amount of weight loss below what is expected for the amount of exercise energy expenditure. We examined the dose-response effects of exercise volume on energy compensation in postmenopausal women. Data from Alberta Physical Activity and Breast Cancer Prevention (ALPHA) and Breast Cancer and Exercise Trial in Alberta (BETA) were combined for the present analysis. The ALPHA and BETA trials were two-centred, two-armed, 12-month randomized controlled trials. The ALPHA trial included 160 participants randomized to 225 min per week of aerobic exercise, and the BETA trial randomized 200 participants to each 150 and 300 min per week of aerobic exercise. All participants were aged 50-74 years, moderately inactive (compensation was based on changes in body composition (dual-energy X-ray absorptiometry scan) and estimated exercise energy expenditure from completed exercise volume. Associations between Δenergy intake, ΔVO2peak and Δphysical activity time with energy compensation were assessed. No differences in energy compensation were noted between interventions. However, there were large inter-individual differences in energy compensation between participants; 9.4% experienced body composition changes that were greater than expected based on exercise energy expenditure, 64% experienced some degree of energy compensation and 26.6% experienced weight gain based on exercise energy expenditure. Increases in VO2peak were associated with reductions in energy compensation (β=-3.44 ml kg(-1) min(-1), 95% confidence interval for β=-4.71 to -2.17 ml kg(-1) min(-1); P=0.0001). Large inter-individual differences in energy compensation were noted, despite no differences between activity doses. In addition, increases in VO2peak were associated with lower energy compensation. Future studies are needed to
Targets IMage Energy Regional (TIMER) Model, Technical Documentation
Vries B de; Vuuren D van; Elzen M den; Janssen M; MNV
2002-01-01
The Targets IMage Energy Regional simulation model, TIMER, is described in detail. This model was developed and used in close connection with the Integrated Model to Assess the Global Environment (IMAGE) 2.2. The system-dynamics TIMER model simulates the global energy system at an intermediate level
Modelling energy consumption in a manufacturing plant using productivity KPIs
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.
Programming models for energy-aware systems
Zhu, Haitao
Energy efficiency is an important goal of modern computing, with direct impact on system operational cost, reliability, usability and environmental sustainability. This dissertation describes the design and implementation of two innovative programming languages for constructing energy-aware systems. First, it introduces ET, a strongly typed programming language to promote and facilitate energy-aware programming, with a novel type system design called Energy Types. Energy Types is built upon a key insight into today's energy-efficient systems and applications: despite the popular perception that energy and power can only be described in joules and watts, real-world energy management is often based on discrete phases and modes, which in turn can be reasoned about by type systems very effectively. A phase characterizes a distinct pattern of program workload, and a mode represents an energy state the program is expected to execute in. Energy Types is designed to reason about energy phases and energy modes, bringing programmers into the optimization of energy management. Second, the dissertation develops Eco, an energy-aware programming language centering around sustainability. A sustainable program built from Eco is able to adaptively adjusts its own behaviors to stay on a given energy budget, avoiding both deficit that would lead to battery drain or CPU overheating, and surplus that could have been used to improve the quality of the program output. Sustainability is viewed as a form of supply and demand matching, and a sustainable program consistently maintains the equilibrium between supply and demand. ET is implemented as a prototyped compiler for smartphone programming on Android, and Eco is implemented as a minimal extension to Java. Programming practices and benchmarking experiments in these two new languages showed that ET can lead to significant energy savings for Android Apps and Eco can efficiently promote battery awareness and temperature awareness in real
Random Modeling of Daily Rainfall and Runoff Using a Seasonal Model and Wavelet Denoising
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.
Bello, Nora M; Steibel, Juan P; Tempelman, Robert J
2010-06-01
Bivariate mixed effects models are often used to jointly infer upon covariance matrices for both random effects (u) and residuals (e) between two different phenotypes in order to investigate the architecture of their relationship. However, these (co)variances themselves may additionally depend upon covariates as well as additional sets of exchangeable random effects that facilitate borrowing of strength across a large number of clusters. We propose a hierarchical Bayesian extension of the classical bivariate mixed effects model by embedding additional levels of mixed effects modeling of reparameterizations of u-level and e-level (co)variances between two traits. These parameters are based upon a recently popularized square-root-free Cholesky decomposition and are readily interpretable, each conveniently facilitating a generalized linear model characterization. Using Markov Chain Monte Carlo methods, we validate our model based on a simulation study and apply it to a joint analysis of milk yield and calving interval phenotypes in Michigan dairy cows. This analysis indicates that the e-level relationship between the two traits is highly heterogeneous across herds and depends upon systematic herd management factors.
Development of a Random Field Model for Gas Plume Detection in Multiple LWIR Images.
Heasler, Patrick G.
2008-09-30
This report develops a random field model that describes gas plumes in LWIR remote sensing images. The random field model serves as a prior distribution that can be combined with LWIR data to produce a posterior that determines the probability that a gas plume exists in the scene and also maps the most probable location of any plume. The random field model is intended to work with a single pixel regression estimator--a regression model that estimates gas concentration on an individual pixel basis.
Renormalization procedure for random tensor networks and the canonical tensor model
Sasakura, Naoki
2015-01-01
We discuss a renormalization procedure for random tensor networks, and show that the corresponding renormalization-group flow is given by the Hamiltonian vector flow of the canonical tensor model, which is a discretized model of quantum gravity. The result is the generalization of the previous one concerning the relation between the Ising model on random networks and the canonical tensor model with N=2. We also prove a general theorem which relates discontinuity of the renormalization-group flow and the phase transitions of random tensor networks.
A model for Long-term Industrial Energy Forecasting (LIEF)
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.
Methodology for Modeling Building Energy Performance across the Commercial Sector
Griffith, B.; Long, N.; Torcellini, P.; Judkoff, R.; Crawley, D.; Ryan, J.
2008-03-01
This report uses EnergyPlus simulations of each building in the 2003 Commercial Buildings Energy Consumption Survey (CBECS) to document and demonstrate bottom-up methods of modeling the entire U.S. commercial buildings sector (EIA 2006). The ability to use a whole-building simulation tool to model the entire sector is of interest because the energy models enable us to answer subsequent 'what-if' questions that involve technologies and practices related to energy. This report documents how the whole-building models were generated from the building characteristics in 2003 CBECS and compares the simulation results to the survey data for energy use.
Quantification model for energy consumption in edification
Mercader, Mª P.
2012-12-01
Full Text Available The research conducted in this paper focuses on the generation of a model for the quantification of energy consumption in building. This is to be done through one of the most relevant environmental impact indicators associated with weight per m^{2} of construction, as well as the energy consumption resulting from the manufacturing process of materials used in building construction.
The practical application of the proposed model on different buildings typologies in Seville, will provide information regarding the building materials, the subsystems and the most relevant construction elements. Hence, we will be able to observe the impact the built surface has on the environment.
The results obtained aim to reference the scientific community, providing quantitative data comparable to other types of buildings and geographical areas. Furthermore, it may also allow the analysis and the characterization of feasible solutions to reduce the environmental impact generated by the different materials, subsystems and construction elements commonly used in the different building types defined in this study.
La investigación realizada en el presente trabajo plantea la generación de un modelo de cuantificación del consumo energético en edificación, a través de uno de los indicadores de impacto ambiental más relevantes asociados al peso por m^{2} de construcción, el consumo energético derivado del proceso de fabricación de los materiales de construcción empleados en edificación.
La aplicación práctica del modelo propuesto sobre diferentes tipologías edificatorias en Sevilla aportará información respecto a los materiales de construcción, subsistemas y elementos constructivos más impactantes, permitiendo visualizar la influencia que presenta la superficie construida en cuanto al impacto ambiental generado.
Los resultados obtenidos pretenden servir de referencia a la comunidad científica, aportando datos num
A matrix model for strings beyond the c=1 barrier: the spin-s Heisenberg model on random surfaces
Ambjorn, J; Sedrakyan, A
2014-01-01
We consider a spin-s Heisenberg model coupled to two-dimensional quantum gravity. We quantize the model using the Feynman path integral, summing over all possible two-dimensional geometries and spin configurations. We regularize this path integral by starting with the R-matrices defining the spin-s Heisenberg model on a regular 2d Manhattan lattice. 2d quantum gravity is included by defining the R-matrices on random Manhattan lattices and summing over these, in the same way as one sums over 2d geometries using random triangulations in non-critical string theory. We formulate a random matrix model where the partition function reproduces the annealed average of the spin-s Heisenberg model over all random Manhattan lattices. A technique is presented which reduces the random matrix integration in partition function to an integration over their eigenvalues.
MATHEMATICAL MODEL OF OPTIMAL PROJECT PORTFOLIO FORMING BASED ON RANDOM FACTORS
I. A. Korkhina
2014-03-01
Full Text Available Purpose. To identify the ways of perspective development for railway transport one should solve the problem of forming the investment project portfolio. Thus, it is necessary to deal with uncertainty in the input data (prices of services, materials, energy products. To take into account this uncertainty it is proposed to use the developed model of stochastic programming. Methodology. For accounting of uncertain data the probabilistic limits on the quantities of resources, which are used in the project portfolio are imposed. As the objective function it is proposed to maximize the threshold, which with a given probability may exceed the planning interval of the net income. Findings. Stochastic programming model with line-by-line probabilistic constraints was obtained. Coefficients of this model are normally distributed random variables. Ratios, which allow calculating mathematical expectations and covariance matrices of these coefficients, were concluded. Originality. Known methods of forming the optimal project portfolio are based on the fact that all inputs are known exactly. On the basis of this consideration, the authors of works on the creating an optimal project portfolio have come to a scheme of deterministic mathematical programming. In this article we propose to take into account the uncertainty in the input data, which will increase the reliability of the portfolio effectiveness estimation through the use of stochastic mathematical programming scheme. Practical value. The developed model can be used in order to solve the planning problems of railway transport development.
Wang, Zhiyong; Xu, Jinbo
2011-07-01
Accurate tertiary structures are very important for the functional study of non-coding RNA molecules. However, predicting RNA tertiary structures is extremely challenging, because of a large conformation space to be explored and lack of an accurate scoring function differentiating the native structure from decoys. The fragment-based conformation sampling method (e.g. FARNA) bears shortcomings that the limited size of a fragment library makes it infeasible to represent all possible conformations well. A recent dynamic Bayesian network method, BARNACLE, overcomes the issue of fragment assembly. In addition, neither of these methods makes use of sequence information in sampling conformations. Here, we present a new probabilistic graphical model, conditional random fields (CRFs), to model RNA sequence-structure relationship, which enables us to accurately estimate the probability of an RNA conformation from sequence. Coupled with a novel tree-guided sampling scheme, our CRF model is then applied to RNA conformation sampling. Experimental results show that our CRF method can model RNA sequence-structure relationship well and sequence information is important for conformation sampling. Our method, named as TreeFolder, generates a much higher percentage of native-like decoys than FARNA and BARNACLE, although we use the same simple energy function as BARNACLE. zywang@ttic.edu; j3xu@ttic.edu Supplementary data are available at Bioinformatics online.
Local dependence in random graph models: characterization, properties and statistical inference.
Schweinberger, Michael; Handcock, Mark S
2015-06-01
Dependent phenomena, such as relational, spatial and temporal phenomena, tend to be characterized by local dependence in the sense that units which are close in a well-defined sense are dependent. In contrast with spatial and temporal phenomena, though, relational phenomena tend to lack a natural neighbourhood structure in the sense that it is unknown which units are close and thus dependent. Owing to the challenge of characterizing local dependence and constructing random graph models with local dependence, many conventional exponential family random graph models induce strong dependence and are not amenable to statistical inference. We take first steps to characterize local dependence in random graph models, inspired by the notion of finite neighbourhoods in spatial statistics and M-dependence in time series, and we show that local dependence endows random graph models with desirable properties which make them amenable to statistical inference. We show that random graph models with local dependence satisfy a natural domain consistency condition which every model should satisfy, but conventional exponential family random graph models do not satisfy. In addition, we establish a central limit theorem for random graph models with local dependence, which suggests that random graph models with local dependence are amenable to statistical inference. We discuss how random graph models with local dependence can be constructed by exploiting either observed or unobserved neighbourhood structure. In the absence of observed neighbourhood structure, we take a Bayesian view and express the uncertainty about the neighbourhood structure by specifying a prior on a set of suitable neighbourhood structures. We present simulation results and applications to two real world networks with 'ground truth'.
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.
Algorithm for Tree Growth Modeling Based on Random Parameters and ARMA
Lichun Jiang
2013-08-01
Full Text Available Chapman-Richards function is used to model growth data of dahurian larch (Larix gmelinii Rupr. from longitudinal measurements using nonlinear mixed-effects modeling approach. The parameter variation in the model was divided into random effects, fixed effects and variance-covariance structure. The values for fixed effects parameters and the variance-covariance matrix of random effects were estimated using NLME function in S-plus software. Autocorrelation structure was considered for explaining the dependency among multiple measurements within the individuals. Information criterion statistics (AIC, BIC and Likelihood ratio test are used for comparing different structures of the random effects components. These methods are illustrated using the nonlinear mixed-effects methods in S-Plus software. Results showed that the Chapman-Richards model with three random parameters could typically depict the dahurian larch tree growth in northeastern China. The mixed-effects model provided better performance and more precise estimations than the fixed-effects model.
RESRO: A spatio-temporal model to optimise regional energy systems emphasising renewable energies
2012-01-01
RESRO (Reference Energy System Regional Optimization) optimises the simultaneous fulfilment of the heat and power demand in regional energy systems. It is a mixed-integer program realised in the modelling language GAMS. The model handles information on geographically disaggregated data describing heat demand and renewable energy potentials (e.g. biomass, solar energy, ambient heat). Power demand is handled spatially aggregated in an hourly time resolution within 8 type days. The major idea is...
Analysis of resonance energy transfer in model membranes: role of orientational effects.
Domanov, Yegor A; Gorbenko, Galina P
2002-10-16
The model of resonance energy transfer (RET) in membrane systems containing donors randomly distributed over two parallel planes separated by fixed distance and acceptors confined to a single plane is presented. Factors determining energy transfer rate are considered with special attention being given to the contribution from orientational heterogeneity of the donor emission and acceptor absorption transition dipoles. Analysis of simulated data suggests that RET in membranes, as compared to intramolecular energy transfer, is substantially less sensitive to the degree of reorientational freedom of chromophores due to averaging over multiple donor-acceptor pairs. The uncertainties in the distance estimation resulting from the unknown mutual orientation of the donor and acceptor are analyzed.
A model for Long-term Industrial Energy Forecasting (LIEF)
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.
Gregg, Jay Sterling; Balyk, Olexandr; Pérez, Cristian Hernán Cabrera
The objectives of the Sustainable Energy for All (SE4ALL), a United Nations (UN) global initiative, are to achieve, by 2030: 1) universal access to modern energy services; 2) a doubling of the global rate of improvement in energy efficiency; and 3) a doubling of the share of renewable energy in t...... including updating data, setting constraints, and reporting on output. The presentation also addresses the addition of new model components such as traditional biomass and building energy efficiency....
Approximating the XY model on a random graph with a q -state clock model
Lupo, Cosimo; Ricci-Tersenghi, Federico
2017-02-01
Numerical simulations of spin glass models with continuous variables set the problem of a reliable but efficient discretization of such variables. In particular, the main question is how fast physical observables computed in the discretized model converge toward the ones of the continuous model when the number of states of the discretized model increases. We answer this question for the XY model and its discretization, the q -state clock model, in the mean-field setting provided by random graphs. It is found that the convergence of physical observables is exponentially fast in the number q of states of the clock model, so allowing a very reliable approximation of the XY model by using a rather small number of states. Furthermore, such an exponential convergence is found to be independent from the disorder distribution used. Only at T =0 , the convergence is slightly slower (stretched exponential). Thanks to the analytical solution to the q -state clock model, we compute accurate phase diagrams in the temperature versus disorder strength plane. We find that, at zero temperature, spontaneous replica symmetry breaking takes place for any amount of disorder, even an infinitesimal one. We also study the one step of replica symmetry breaking (1RSB) solution in the low-temperature spin glass phase.
Quantifying and Disaggregating Consumer Purchasing Behavior for Energy Systems Modeling
Consumer behaviors such as energy conservation, adoption of more efficient technologies, and fuel switching represent significant potential for greenhouse gas mitigation. Current efforts to model future energy outcomes have tended to use simplified economic assumptions ...
Quantifying and Disaggregating Consumer Purchasing Behavior for Energy Systems Modeling
Consumer behaviors such as energy conservation, adoption of more efficient technologies, and fuel switching represent significant potential for greenhouse gas mitigation. Current efforts to model future energy outcomes have tended to use simplified economic assumptions ...
Bionic models for new sustainable energy technology
Tributsch, H. [Hahn-Meitner Inst., Dept. Solare Energetik, Berlin (Germany)
2004-07-01
Within the boundary conditions of an abundant, but diluted solar energy supply nature has successfully evolved sophisticated regenerative energy technologies, which are not yet familiar to human engineering tradition. Since until the middle of this century a substantial contribution of renewable energy to global energy consumption is required in order to limit environmental deterioration, bionic technologies may contribute to the development of commercially affordable technical options. Four biological energy technologies have been selected as examples to discuss the challenges, both in scientific and technological terms, as well as the material research aspects involved: photovoltaics based on irreversible kinetics, tensile water technology, solar powered protonic energy circuits, fuel cell catalysis based on abundant transition metals. (orig.)
Carroll, T.O.; Kydes, A.S.; Sanborn, J.
1977-06-01
There is no doubt that major conservation of future regional energy expenditures can be achieved through the propitious allocation and configuring of land-use activities. The task of searching for and selecting strategies and measures which will bring about energy conservation vis-a-vis land use becomes that of understanding and defining relationships between sets of possible land use activities in a given region and the resultant energy end use demand. The outcome of the search is the determination of the relative impact of the strategies and measures upon both the regional and national energy system. The Land Use-Energy Simulation Model with integrated capability for generating energy demand is an extension of the classic Lowry model. Such a model framework captures two essential features of the land use-energy utilization interaction; first, the spatial location of land use activity is implicit, and second, transportation energy demand is determined as an integral part of the spatial configuration. The model is divided both conceptually and computationally into three parts; the land use model, a submodel for transportation which provides the work and shop trip distributions for spatial allocation of activities within the land use submodel, and an energy submodel which determines the energy demand from the land use configuration. Two specific types of applications of thecomputer model are described. The model was utilized to assess the energy demand of the Long Island region in New York. Second, the model was applied to study the generic relationships between energy utilization and urban form.
The National Energy Modeling System: An overview 1998
NONE
1998-02-01
The National Energy Modeling System (NEMS) is a computer-based, energy-economy modeling system of US energy markets for the midterm period through 2020. NEMS projects the production, imports, conversion, consumption, and prices of energy, subject to assumptions on macroeconomic and financial factors world energy markets, resource availability and costs, behavior and technological choice criteria, cost and performance characteristics of energy technologies, and demographics. This report presents an overview of the structure and methodology of NEMS and each of its components. The first chapter provides a description of the design and objectives of the system, followed by a chapter on the overall modeling structure and solution algorithm. The remainder of the report summarizes the methodology and scope of the component modules of NEMS. The model descriptions are intended for readers familiar with terminology from economics, operations research, and energy modeling. 21 figs.
A Romanian energy system model and a nuclear reduction strategy
Gota, Dan-Ioan; Lund, Henrik; Miclea, Liviu
2011-01-01
This paper presents a model of the Romanian energy system with the purpose of providing a tool for the analysis of future sustainable energy strategies. The model represents the total national energy system and is detailed to the level of hourly demand and production in order to be able to analyse...... the consequences of adding fluctuating renewable energy sources to the system. The model has been implemented into the EnergyPLAN tool and has been validated in order to determine if it can be used as a reference model for other simulations. In EnergyPLAN, two different future strategy scenarios for the Romanian...... energy system are compared to the actual data of Romania of year 2008. First, a comparison is made between the 2008 model and the 2013 strategy scenario corresponding to the grid of the Romanian transmission system operator (TSO) Transelectrica. Then, a comparison is made to a second strategy scenario...
Comparison of dark energy models after Planck 2015
Xu, Yue-Yao
2016-01-01
We make a comparison for ten typical, popular dark energy models according to theirs capabilities of fitting the current observational data. The observational data we use in this work include the JLA sample of type Ia supernovae observation, the Planck 2015 distance priors of cosmic microwave background observation, the baryon acoustic oscillations measurements, and the direct measurement of the Hubble constant. Since the models have different numbers of parameters, in order to make a fair comparison, we employ the Akaike and Bayesian information criteria to assess the worth of the models. The analysis results show that, according to the capability of explaining observations, the cosmological constant model is still the best one among all the dark energy models. The generalized Chaplygin gas model, the constant $w$ model, and the $\\alpha$ dark energy model are worse than the cosmological constant model, but still are good models compared to others. The holographic dark energy model, the new generalized Chaply...
A liquid drop model for embedded atom method cluster energies
Finley, C. W.; Abel, P. B.; Ferrante, J.
1996-01-01
Minimum energy configurations for homonuclear clusters containing from two to twenty-two atoms of six metals, Ag, Au, Cu, Ni, Pd, and Pt have been calculated using the Embedded Atom Method (EAM). The average energy per atom as a function of cluster size has been fit to a liquid drop model, giving estimates of the surface and curvature energies. The liquid drop model gives a good representation of the relationship between average energy and cluster size. As a test the resulting surface energies are compared to EAM surface energy calculations for various low-index crystal faces with reasonable agreement.
Markov random field modelling for fluid distributions from the seismic velocity structures
Kuwatani, T.; Nagata, K.; Okada, M.; Toriumi, M.
2011-12-01
Recent development of geophysical observations, such as seismic tomography, seismic reflection method and geomagnetic method, provide us detailed images of the earth's interior. However, it has still been difficult to interpret these data geologically, including predicting lithology and fluid distributions, mainly because (1) available data usually have large noise and uncertainty, and (2) the number of observable parameters is usually smaller than the number of target parameters. Therefore, the statistical analyses of geophysical data sets are essential for the objective and quantitative geological interpretation. We propose the use of Markov random field (MRF) model to geophysical image data as an alternative to classical deterministic approaches. The MRF model is a Bayesian stochastic model using a generalized form of Markov Chains, and is often applied to the analysis of images, particularly in the detection of visual patterns or textures. The MRF model assumes that the spatial gradients of physical properties are relatively small compared to the observational noises. By hyperparameter estimation, the variances of noises can be appropriately estimated only from available data sets without prior information about observational noises. In this study, we try to image the fluid distributions based on the seismic velocity structure by using the Markov random field model. According to Nakajima et al. (2005), seismic velocities (Vp and Vs) are expressed as functions of porosity and pore geometry using the unified formulation proposed by Takei (2002). Additionally, the spatial continuity of porosity and pore geometry is incorporated by Gaussian Markov Chains as prior probabilities. The most probable estimation can be obtained by maximizing the posterior probability of the fluid distribution given the observed velocity structures. In the present study, the steepest descent method was implemented in order to minimize the free energy (i.e. maximize the posterior
Barangi, Mahmood; Erementchouk, Mikhail; Mazumder, Pinaki
2016-08-01
Strain-mediated magnetization switching in a magnetic tunneling junction (MTJ) by exploiting a combination of piezoelectricity and magnetostriction has been proposed as an energy efficient alternative to spin transfer torque (STT) and field induced magnetization switching methods in MTJ-based magnetic random access memories (MRAM). Theoretical studies have shown the inherent advantages of strain-assisted switching, and the dynamic response of the magnetization has been modeled using the Landau-Lifshitz-Gilbert (LLG) equation. However, an attempt to use LLG for simulating dynamics of individual elements in large-scale simulations of multi-megabyte straintronics MRAM leads to extremely time-consuming calculations. Hence, a compact analytical solution, predicting the flipping delay of the magnetization vector in the nanomagnet under stress, combined with a liberal approximation of the LLG dynamics in the straintronics MTJ, can lead to a simplified model of the device suited for fast large-scale simulations of multi-megabyte straintronics MRAMs. In this work, a tensor-based approach is developed to study the dynamic behavior of the stressed nanomagnet. First, using the developed method, the effect of stress on the switching behavior of the magnetization is investigated to realize the margins between the underdamped and overdamped regimes. The latter helps the designer realize the oscillatory behavior of the magnetization when settling along the minor axis, and the dependency of oscillations on the stress level and the damping factor. Next, a theoretical model to predict the flipping delay of the magnetization vector is developed and tested against LLG-based numerical simulations to confirm the accuracy of findings. Lastly, the obtained delay is incorporated into the approximate solutions of the LLG dynamics, in order to create a compact model to liberally and quickly simulate the magnetization dynamics of the MTJ under stress. Using the developed delay equation, the
Barangi, Mahmood, E-mail: barangi@umich.edu; Erementchouk, Mikhail; Mazumder, Pinaki [Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, Michigan 48109-2121 (United States)
2016-08-21
Strain-mediated magnetization switching in a magnetic tunneling junction (MTJ) by exploiting a combination of piezoelectricity and magnetostriction has been proposed as an energy efficient alternative to spin transfer torque (STT) and field induced magnetization switching methods in MTJ-based magnetic random access memories (MRAM). Theoretical studies have shown the inherent advantages of strain-assisted switching, and the dynamic response of the magnetization has been modeled using the Landau-Lifshitz-Gilbert (LLG) equation. However, an attempt to use LLG for simulating dynamics of individual elements in large-scale simulations of multi-megabyte straintronics MRAM leads to extremely time-consuming calculations. Hence, a compact analytical solution, predicting the flipping delay of the magnetization vector in the nanomagnet under stress, combined with a liberal approximation of the LLG dynamics in the straintronics MTJ, can lead to a simplified model of the device suited for fast large-scale simulations of multi-megabyte straintronics MRAMs. In this work, a tensor-based approach is developed to study the dynamic behavior of the stressed nanomagnet. First, using the developed method, the effect of stress on the switching behavior of the magnetization is investigated to realize the margins between the underdamped and overdamped regimes. The latter helps the designer realize the oscillatory behavior of the magnetization when settling along the minor axis, and the dependency of oscillations on the stress level and the damping factor. Next, a theoretical model to predict the flipping delay of the magnetization vector is developed and tested against LLG-based numerical simulations to confirm the accuracy of findings. Lastly, the obtained delay is incorporated into the approximate solutions of the LLG dynamics, in order to create a compact model to liberally and quickly simulate the magnetization dynamics of the MTJ under stress. Using the developed delay equation, the
One- and two-matrix models and random cylindre with two-coloured boundaries
Orantin, Nicolas
2004-01-01
In this training course report, I briefly present the one- and two-matrix models as tools for the study of conformal field theories with boundaries. In a first part, after a short historical presentation of random matrices, I present the matrix models' formalism, their diagramatic interpretation, their link with random surfaces and conformal field theories and the "loop equations" method for the 2-matrix model. In a second part, I use this method for the calculation of the generating function of random cylindres whose boundaries are two-coloured, which was not know before.
Numerical Simulation of Entropy Growth for a Nonlinear Evolutionary Model of Random Markets
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.
A novel configuration model for random graphs with given degree sequence
Xu Xin-Ping; Liu Feng
2007-01-01
Recently, random graphs in which vertices are characterized by hidden variables controlling the establishment of edges between pairs of vertices have attracted much attention. This paper presents a specific realization of a class of random network models in which the connection probability between two vertices (i, j) is a specific function of degrees ki and kj. In the framework of the configuration model of random graphs, we find the analytical expressions for the degree correlation and clustering as a function of the variance of the desired degree distribution. The obtained expressions are checked by means of numerical simulations. Possible applications of our model are discussed.
Large dimension forecasting models and random singular value spectra
Bouchaud, J P; Miceli, M A; Potters, M; Bouchaud, Jean-Philippe; Laloux, Laurent; Potters, Marc
2005-01-01
We present a general method to detect and extract from a finite time sample statistically meaningful correlations between input and output variables of large dimensionality. Our central result is derived from the theory of free random matrices, and gives an explicit expression for the interval where singular values are expected in the absence of any true correlations between the variables under study. Our result can be seen as the natural generalization of the Marcenko-Pastur distribution for the case of rectangular correlation matrices. We illustrate the interest of our method on a set of macroeconomic time series.
Meric de Bellefon, G.; van Duysen, J. C.; Sridharan, K.
2017-08-01
The stacking fault energy (SFE) plays an important role in deformation behavior and radiation damage of FCC metals and alloys such as austenitic stainless steels. In the present communication, existing expressions to calculate SFE in those steels from chemical composition are reviewed and an improved multivariate linear regression with random intercepts is used to analyze a new database of 144 SFE measurements collected from 30 literature references. It is shown that the use of random intercepts can account for experimental biases in these literature references. A new expression to predict SFE from austenitic stainless steel compositions is proposed.
Dynamic modeling, simulation and control of energy generation
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
Energy transfers in shell models for magnetohydrodynamics turbulence.
Lessinnes, Thomas; Carati, Daniele; Verma, Mahendra K
2009-06-01
A systematic procedure to derive shell models for magnetohydrodynamic turbulence is proposed. It takes into account the conservation of ideal quadratic invariants such as the total energy, the cross helicity, and the magnetic helicity, as well as the conservation of the magnetic energy by the advection term in the induction equation. This approach also leads to simple expressions for the energy exchanges as well as to unambiguous definitions for the energy fluxes. When applied to the existing shell models with nonlinear interactions limited to the nearest-neighbor shells, this procedure reproduces well-known models but suggests a reinterpretation of the energy fluxes.